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CANDIDA YEASTS AND CARCINOGENIC ACETALDEHYDE IN UPPER DIGESTIVE TRACT CARCINOGENESIS Mikko Nieminen ACADEMIC DISSERTATION Research Unit on Acetaldehyde and Cancer, Biomedicum Department of Bacteriology and Immunology, Haartman Institute Department of Oral and Maxillofacial Diseases, Helsinki University Central Hospital Department of Periodontology, Institute of Dentistry University of Helsinki, Finland Respiratory Research Group, Institute of Inflammation and Repair Education and Research Centre, University Hospital of Southern Manchester University of Manchester, United Kingdom Finnish Doctoral Programme in Oral Sciences (FINDOS) To be presented, with the permission of the Faculty of Medicine of the University of Helsinki, for public examination in lecture hall 2, Biomedicum 1, th Haartmaninkatu 8, Helsinki, on 24 October 2014, at 12 o’clock noon. © 2014 by Mikko Nieminen Cover image by Dr Ranjith Rajendran, University of Glasgow (SEM of Candida albicans SC5314 biofilm) ISBN 978-951-51-0131-0 (pbk.) ISBN 978-951-51-0132-7 (PDF) ISSN 2342-3161 (print) ISSN 2342-317X (online) http://ethesis.helsinki.fi Hansaprint Oy Helsinki 2014 2 SUPERVISED BY: Riina Rautemaa-Richardson D.D.S., PhD, FRCPath, Docent Department of Bacteriology and Immunology, Haartman Institute Department of Oral Medicine, Institute of Dentistry University of Helsinki, Helsinki, Finland Faculty of Human and Medical Sciences, Institute of Inflammation and Repair University Hospital of South, Wythenshawe Hospital The University of Manchester, Manchester, United Kingdom Timo Sorsa Professor, D.D.S., PhD, Dipl. Perio Department of Periodontology, Institute of Dentistry University of Helsinki, Helsinki, Finland Division of Periodontology, Department of Dental Medicine Karolinska Institutet, Huddinge, Sweden Mikko Salaspuro Professor (emeritus), M.D., PhD Research Unit on Acetaldehyde and Cancer, Biomedicum Faculty of Medicine, University of Helsinki, Helsinki, Finland REVIEWED BY: Markus Haapasalo Professor, D.D.S., PhD Department of Oral Biological & Medical Sciences University of British Columbia, Vancouver, Canada Bernhard Hube Professor, PhD Department of Microbial Pathogenicity Mechanisms Leibniz Institute for Natural Product Research and Infection Biology Hans Knöll Institute Friedrich Schiller University, Jena, Germany OPPOSED BY: Neil A.R. Gow Professor, PhD, FRSE, FSB, FAAM School of Medical Sciences, Institute of Medical Sciences University of Aberdeen, Aberdeen, United Kingdom 3 “Don’t play what’s there, play what’s not there.” Miles Davis 4 LIST OF CONTENTS 1 LIST OF ORIGINAL PUBLICATIONS ......................................................................... 8 2 ABBREVIATIONS ................................................................................................... 9 3 ABSTRACT ........................................................................................................... 11 4 INTRODUCTION .................................................................................................. 13 5 REVIEW OF THE LITERATURE ............................................................................... 16 5.1 CANDIDA YEASTS AND THE HUMAN MYCOBIOME ........................................ 16 5.2 PATHOGENESIS OF CANDIDA YEASTS ............................................................. 18 5.2.1 Virulence factors..................................................................................... 18 5.2.1.1 Polymorphism and phenotypic switching ................................... 18 5.2.1.2 Biofilm lifestyle ............................................................................ 19 5.2.1.3 Adhesion, invasion and hydrolysis .............................................. 21 5.2.2 Infection and disease .............................................................................. 22 5.2.2.1 Oral candidosis ............................................................................ 23 5.2.2.2 Oesophageal candidosis .............................................................. 24 5.2.2.3 Invasive candidosis ...................................................................... 24 5.2.3 Interaction with bacteria ........................................................................ 25 5.2.4 Mucosal immunity .................................................................................. 25 5.2.4.1 Innate immunity .......................................................................... 26 5.2.4.2 Adaptive immunity ...................................................................... 27 5.3 TREATMENT STRATEGIES ............................................................................... 28 5.3.1 Treatment of infection ........................................................................... 29 5.3.1.1 Topical treatment ........................................................................ 29 5.3.1.1.1 Polyenes ........................................................................... 29 5.3.1.1.2 Azoles ............................................................................... 30 5.3.1.1.3 Chlorhexidine ................................................................... 30 5.3.1.2 Systemic treatment ..................................................................... 30 5.3.1.2.1 Triazoles ........................................................................... 31 5.3.1.2.2 Echinocandins .................................................................. 31 5.3.1.2.3 Polyenes ........................................................................... 32 5.3.1.2.4 Antifungal vaccines .......................................................... 32 5.3.2 Suppressive therapy ............................................................................... 32 5.3.3 Probiotics as an alternative approach .................................................... 33 5.3.4 Alternative anti-biofilm agents ............................................................... 34 5.4 ETHANOL AND ACETALDEHYDE METABOLISM IN THE HUMAN BODY ........... 34 5.4.1 Ethanol oxidation in humans .................................................................. 36 5.4.1.1 Alcohol dehydrogenase (ADH) .................................................... 36 5.4.1.2 Microsomal ethanol oxidising system (MEOS) ............................ 36 5.4.1.3 Aldehyde dehydrogenase (ALDH) ............................................... 37 5.4.2 Hepatic metabolism ............................................................................... 37 5.4.3 Extra-hepatic metabolism ...................................................................... 38 5.4.3.1 Metabolism in the upper digestive tract ..................................... 38 5.4.3.2 Microbial metabolism ................................................................. 39 5 5.4.3.2.1 Bacterial metabolism ....................................................... 39 5.4.3.2.2 Candida metabolism ........................................................ 40 5.5 ACETALDEHYDE IN CARCINOGENESIS OF THE UPPER DIGESTIVE TRACT ....... 44 5.5.1 Ethanol-related toxicity .......................................................................... 44 5.5.2 Acetaldehyde-related toxicity and carcinogenicity ................................ 44 5.5.3 Aetiology and epidemiology of upper digestive tract cancers ............... 46 5.5.3.1 Main risk factors .......................................................................... 47 5.5.3.2 Candida and cancer ..................................................................... 48 6 AIMS OF THE STUDY ........................................................................................... 49 7 MATERIALS AND METHODS ................................................................................ 50 7.1 STUDY DESIGN ................................................................................................ 50 7.2 MATERIALS ..................................................................................................... 51 7.2.1 Candida strains and isolates ................................................................... 51 7.2.2 Reagents ................................................................................................. 52 7.2.2.1 Starter cultures............................................................................ 53 7.2.2.2 Primers ........................................................................................ 53 7.2.2.3 Antibodies ................................................................................... 54 7.3 METHODS ....................................................................................................... 55 7.3.1 Candida growth conditions .................................................................... 55 7.3.1.1 Planktonic cells ............................................................................ 55 7.3.1.2 Biofilm formation ........................................................................ 55 7.3.1.2.1 In vitro biofilm .................................................................. 55 7.3.1.2.2 Biofilm susceptibility to D,L-2-hydroxyisocaproic acid (HICA) ......................................................................................... 56 7.3.1.2.3 In vivo biofilm ................................................................... 56 7.3.2 Fermentation using starter cultures ....................................................... 56 7.3.3 Isolation and identification of the microbiota in starter cultures .......... 57 7.3.3.1 Assessment of microbial growth and isolation of microorganisms ..................................................................................................... 57 7.3.3.2 DNA extraction ............................................................................ 57 7.3.3.3 16S and 18S sequencing and data analysis ................................. 58 7.3.4 Gas chromatography .............................................................................. 58 7.3.4.1 Planktonic cells and biofilms ....................................................... 58 7.3.4.2 Starter cultures and fermentation .............................................. 59 7.3.5 Analysis of Adh activity ........................................................................... 60 7.3.6 Evaluation of Candida albicans biofilm formation ................................. 60 7.3.6.1 XTT reduction assay .................................................................... 60 7.3.6.2 PicoGreen assay .......................................................................... 61 7.3.6.3 Scanning electron microscopy (SEM) .......................................... 61 7.3.7 Gene expression analysis........................................................................ 61 7.3.7.1 RNA extraction ............................................................................ 61 7.3.7.2 cDNA synthesis ............................................................................ 62 7.3.7.3 RT-qPCR analysis ......................................................................... 62 7.3.8 In vivo biofilm murine model .................................................................. 62 7.3.8.1 Ethics statement ......................................................................... 62 6 7.3.8.2 Diffusion chamber model ............................................................ 62 7.3.9 Immunohistochemistry .......................................................................... 63 7.3.10 Statistical analysis ................................................................................... 64 8 RESULTS .............................................................................................................. 65 8.1 PRODUCTION OF ACETALDEHYDE AND ETHANOL BY CANDIDA YEASTS IN VITRO ..................................................................................................................... 65 8.1.1 Planktonic Candida albicans and non-albicans Candida cultures .......... 65 8.1.1.1 Acetaldehyde production in ethanol incubation ........................ 65 8.1.1.2 Acetaldehyde production in glucose, fructose or xylitol incubation or in co-incubation with ethanol................................................ 66 8.1.1.3 Adh activity.................................................................................. 67 8.1.2 Mixed bacteria/yeast starter culture during fermentation .................... 67 8.1.2.1 Pilot experiments ........................................................................ 67 8.1.2.2 Distribution of yeast and bacterial species in starter cultures .... 68 8.1.2.3 Changes in microbial counts and pH during fermentation ......... 69 8.1.2.4 Acetaldehyde and ethanol production during fermentation and correlation with microbiota .................................................................. 69 8.1.3 Candida albicans biofilms ....................................................................... 69 8.1.3.1 Pilot experiments ........................................................................ 69 8.1.3.2 Acetaldehyde production from ethanol and glucose at an acidic and a neutral pH ................................................................................ 70 8.2 INHIBITORY EFFECT OF D,L-2-HYDROXYISOCAPROIC ACID (HICA) ON CANDIDA ALBICANS BIOFILM FORMATION AND ACETALDEHYDE METABOLISM IN VITRO .................................................................................................................. 71 8.2.1 Pilot experiment - HICA susceptibility .................................................... 71 8.2.2 Effect of HICA on metabolic activity, biomass and ultrastructure of biofilms .............................................................................................................. 72 8.2.3 Acetaldehyde production during challenge with HICA and caspofungin ....................................................................................................... 73 8.2.4 Transcriptional changes (CaADH1, CaADH2, CaALD4, CaALD5, CaALD6, CaACS1 and CaACS2) in biofilms ......................................................... 74 8.2.4.1 Basal and relative gene expression ............................................. 74 8.2.4.2 Correlation with acetaldehyde levels .......................................... 75 8.3 ANTI-BIOFILM AND ANTI-INFLAMMATORY PROPERTIES OF HICA IN VIVO .... 75 9 DISCUSSION ........................................................................................................ 77 9.1 PRINCIPLE FINDINGS....................................................................................... 77 9.2 LIMITATIONS OF THE STUDY .......................................................................... 81 9.3 STRENGTHS OF THE STUDY ............................................................................ 83 9.4 RELEVANCE OF THE STUDY ............................................................................. 84 10 CONCLUSIONS .................................................................................................... 85 11 ACKNOWLEDGEMENTS ....................................................................................... 87 12 REFERENCES........................................................................................................ 90 7 1 LIST OF ORIGINAL PUBLICATIONS This thesis is based on the following original articles, which are referred to in the text by Roman numerals as indicated below: I Nieminen MT, Uittamo J, Salaspuro M, Rautemaa R. Acetaldehyde production from ethanol and glucose by non-Candida albicans yeasts in vitro. Oral Oncology 2009; 45(12): e245-8. II Uittamo J, Nieminen MT, Kaihovaara P, Bowyer P, Salaspuro M, Rautemaa R. Xylitol inhibits carcinogenic acetaldehyde production by Candida species. International Journal of Cancer 2011; 129(8): 2038-41. III Nieminen MT, Novak-Frazer L, Collins R, Dawsey SP, Dawsey SM, Abnet CC, White RE, Freedman ND, Mwachiro M, Bowyer P, Salaspuro M, Rautemaa R. Alcohol and acetaldehyde in African fermented milk mursik – A possible etiological factor for high incidence of esophageal cancer in western Kenya. Cancer Epidemiology, Biomarkers & Prevention 2013; 22(1): 69-75. IV Nieminen MT, Novak-Frazer L, Richardson V, Rajendran R, Sorsa T, Ramage G, Bowyer P, Rautemaa R. A novel antifungal is active against Candida albicans biofilms and inhibits mutagenic acetaldehyde production in vitro. PLoS one 2014; 9(5): e97864. V Nieminen MT, Hernandez M, Novak-Frazer L, Kuula H, Ramage G, Bowyer P, Warn P, Sorsa T, Rautemaa R. D,L-2-hydroxyisocaproic acid (HICA) attenuates inflammatory responses in a murine Candida albicans biofilm model. Clinical and Vaccine Immunology 2014; 21(9): 1240-1245. Publication II has been used as part of the thesis of author J.U. The original publications have been reprinted with the permission of their copyright holders. 8 2 ACH Acs ADH Adh adh AIDS ALDH Ald ald Als AmB ATP BA CaACS CaADH CaALD CaPDC CaPDH cDNA CO2 CLED CMC CVC CYP DC Del-1 dH2O DNA dsDNA ESCC F-6-P FAA G-6-P GI HIV IC ICU ABBREVIATIONS acetaldehyde acetyl-CoA synthetase (yeast) alcohol dehydrogenase (human) alcohol dehydrogenase (yeast) alcohol dehydrogenase (bacteria) acquired immune deficiency syndrome aldehyde dehydrogenase (human) aldehyde dehydrogenase (yeast) aldehyde dehydrogenase (bacteria) agglutinin-like sequences (yeast) amphotericin B adenosine triphosphate lysed blood agar acetyl-Coa synthetase gene (C. albicans) alcohol dehydrogenase gene (C. albicans) aldehyde dehydrogenase gene (C. albicans) pyruvate decarboxylase gene (C. albicans) pyruvate dehydrogenase enzyme complex (C. albicans) complementary deoxyribonucleic acid carbon dioxide cysteine-, lactose- and electrolyte-deficient agar chronic mucocutaneous candidosis central venous catheter cytochrome P450 (human) dendritic cell developmental endothelial locus 1 distilled water deoxyribonucleic acid double-stranded DNA oesophageal squamous cell carcinoma fructose-6-phosphate fastidious anaerobe agar glucose-6-phosphate gastrointestinal human immunodeficiency virus invasive candidosis intensive care unit 9 IL1 MEOS MMP MPO NAC NAD NE NLR NV OSCC PAMP PBS PCA PMN PRR ROS RPMI Xdh XTT SAB Sap ScADH ScALD SCC SEM TCA TLR TNFα 10 interleukin 1 microsomal ethanol oxidising system matrix metalloproteinase myeloperoxidase non-albicans Candida nicotinamide adenine dinucleotide neutrophil elastase nod-like receptor neomycin-vancomycin blood agar oral squamous cell carcinoma pathogen associated molecular pattern phosphate buffered saline perchloric acid polymorphonuclear neutrophil pattern recognition receptor reactive oxygen species Roswell Park Memorial Institute -1640 media xylitol dehydrogenase (yeast) 2,3-Bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5carboxanilide inner salt Sabouraud agar secreted aspartic protease (yeast) alcohol dehydrogenase gene (S. cerevisiae) aldehyde dehydrogenase gene (S. cerevisiae) squamous cell carcinoma scanning electron microscopy tricarboxylic acid cycle Toll-like receptor tumour necrosis factor alpha 3 ABSTRACT Cancers of the upper digestive tract (oral, pharyngeal, laryngeal, oesophageal and stomach) are among the ten most common cancers worldwide and are associated with high mortality and morbidity. Despite improved treatment strategies, the prognosis of these cancers remains poor. The main aetiological factors for the upper digestive tract cancers are alcohol consumption and smoking. Dietary and genetic factors can also contribute to an increased risk. Alcohol consumption, smoking and poor oral hygiene all lead to exposure of the upper digestive tract mucosa to salivary acetaldehyde. Ethanol is not carcinogenic, but acetaldehyde, its first metabolite, is. The International Agency for Research on Cancer has classified acetaldehyde associated with alcoholic consumption as a group I carcinogen. Cigarette smoke contains acetaldehyde, as does saliva after alcohol intake. Microbially fermented food products can also contain high levels of acetaldehyde. Therefore, salivary acetaldehyde levels are a result of its direct intake as well as systemic, local and microbial ethanol metabolism. The ability of the mucosa and microbes to remove acetaldehyde has been shown to be limited. Chronic Candida mucositis is associated with oro-oesophageal carcinogenesis. Candida yeasts are common colonisers of the upper digestive tract, with an extraordinary ability to form biofilms. Candida albicans is the dominant species in health and disease. The biofilm structure protects fungal cells against hostile actions, and infections are mainly biofilm-related. This is highlighted by high resistance to antifungals by yeast biofilms. Fungal cells can become dispersed from a biofilm, making it a constant source of infection. In immunocompromised patients, this process can lead to fatal systemic infections. The similarity of fungal and human cells makes the development of antifungals difficult, and treatment is often compromised. The primary aim of the research presented in this thesis was to investigate the ability of clinically important Candida yeasts to produce carcinogenic acetaldehyde in planktonic and biofilm modes of growth in vitro. Fermented milk mursik constitutes a major part of the diet in western Kenya, an area with a high local incidence of oesophageal cancer and a low prevalence of common risk factors. The second aim was to identify the microbiota of the starter cultures used for the production of mursik. The ability of these mixed cultures of bacteria and yeast to produce acetaldehyde and ethanol was assessed in a fermentation experiment. Finally, the potential anti-biofilm and anti-inflammatory effect of a Lactobacillus metabolite, 2-hydroxyisocaproic acid (HICA), was explored in vitro and in vivo. HICA has previously shown efficacy against various planktonically grown microbes. 11 The results of the research presented in this thesis demonstrate that C. albicans biofilms can produce mutagenic levels of acetaldehyde when incubated with ethanol and glucose at clinically relevant concentrations. In addition, planktonic C. albicans and non-albicans Candida (NAC) species produce significant levels of acetaldehyde in the presence of ethanol. C. glabrata shows a unique ability among NAC species to produce mutagenic acetaldehyde in the presence of sugars. Interestingly, the production of acetaldehyde by Candida species can be significantly reduced by the sugar alcohol xylitol. Highly mutagenic levels of acetaldehyde and ethanol can be measured during the production of mursik. Candida yeasts are associated with high acetaldehyde and ethanol production during fermentation. C. albicans biofilm formation is significantly reduced in response to HICA treatment in vitro. Interestingly, certain genes belonging to the fermentative pathway and acetaldehyde metabolism are highly up-regulated under stress and during biofilm formation. An attenuated inflammatory response was observed when a C. albicans biofilm was treated with HICA in vivo. Overall, these results underline the significant potential of clinically relevant Candida yeasts to produce carcinogenic acetaldehyde. Colonisation of the upper digestive tract with Candida spp. could expose the mucosa to mutagenic levels of acetaldehyde in the presence of alcohol and dietary sugars. This could play a role in the carcinogenesis associated with Candida infection. In addition, the consumption of fermented food products such as mursik, with a high acetaldehyde and ethanol content, could elevate the risk of cancer. HICA could provide a safe and efficient approach to treat biofilmrelated Candida infections and reduce the inflammation and mutagenicity associated with C. albicans biofilms. 12 4 INTRODUCTION The human microbiome, a complex community comprising all the bacterial, archaeal, viral and fungal members, has a major impact on health and disease, and vice versa. To fully understand the biological function of the human body, we also need to understand the function and composition of our microbiome. Interestingly, the total number of microbial genes is estimated to be 150 times larger than the number of human genes, thus showing the genetic potential of the microbiome (Qin et al. 2010). In health, the microbiome functions as a barrier against invaders and has a major role in the development of vital innate and adaptive immune responses in early life. In disease, the microbiome acts as a platform for the pathogenic growth of microorganisms and pathological immune responses that can lead to chronic inflammatory disease in the long term and eventually to malignancy. In the past ten years, the enormous diversity of the human microbiome has started to be revealed (Human Microbiome Project 2012). These members interact with each other, and this interplay has a specific role in maintaining the balance between the microbiome and the host. Major steps have been taken towards understanding of the microbiome due to major advances in detection techniques, particularly culture-independent technologies and bioinformatics. Large projects, including the Human Microbiome Project and Metagenomics of the Human Intestinal Tract (MetaHIT), have greatly enhanced progress in the field (Human Microbiome Project 2012, Le Chatelier et al. 2013). Although there has been major progress, work has mainly focused on the bacterial part of the microbiome, and little is still known about the fungal part of the human microbiome, recently defined as the mycobiome (Cui et al. 2013, Ghannoum et al. 2010). The oral cavity is a major gateway for micro-organisms to enter the human body. As an entry point to the gastrointestinal tract, the oral cavities of healthy individuals harbour a diverse and fluctuating collection of micro-organisms (Aas et al. 2005, Bik et al. 2010, Nasidze et al. 2009). Altogether, 1,179 taxa of bacteria have been identified in the oral microbiome, also including uncultivable and unnamed taxa (Dewhirst et al. 2010). The most prevalent bacterial genera found are Streptococcus, Haemophilus, Prevotella, Veillonella and Corynebacterium (Human Microbiome Project 2012). The relative abundance of genera differs between the diverse environmental niches of the oral cavity (Human Microbiome Project 2012). Anatomically, the oral cavity is conjoined with the oesophagus, which further leads to the stomach. These three sites comprise the upper digestive tract. However, the main focus of this thesis is on the former two sites, as they share similar characteristics regarding mucosal fungal infections. Although both the oral cavity and oesophagus have unique microbiomes, 13 they are connected by saliva and similar dominant genera are present (Bik et al. 2010, Pei et al. 2004, Segata et al. 2012). Co-existing alongside the oral bacterial microbiome is a fungal community that is dominated by the genus Candida, particularly Candida albicans. Candida yeasts are opportunistic pathogens. Compromised immunity and the loss of homeostasis within the microbiome predispose the human host to increased colonisation by Candida spp. and induce the transition of Candida yeast from commensal to pathogenic traits. A biofilm lifestyle is preferred in the microbial communities along the GI tract (Jenkinson and Lamont 2005, Macfarlane et al. 2011). This is particularly evident in the oral cavity, where polymicrobial communities exist in multiple forms, such as dental plaque (Marsh 2004). The majority of human microbial infections, including Candida spp., are biofilm-related (Costerton et al. 1999, Donlan and Costerton 2002). Good oral hygiene is required for the maintenance of a healthy balance at the orooesophageal host–microbiome interface. Long-term negligence of hygiene leads to the aberrant growth of pathogenic bacteria and fungi (Marsh 2006, Sbordone and Bortolaia 2004). The biofilm structure provides a well-protected environment for microbes to grow, which is highlighted in Candida yeasts by an increase in resistance against commonly used antifungals such as azoles. The frequent use of antifungals and antibacterial compounds can lead to the selective growth of more resistant strains and the loss of vital homeostasis as the spectrum of species narrows down within the local microbiome (Jakobsson et al. 2010, Rautemaa et al. 2007b, Robinson and Young 2010). This can aggravate the initial infection and related disease. As the number of immune-compromised patients is increasing due to advances in medical treatment, such as cancer therapies and organ transplantation surgery, the incidence of opportunistic fungal infections is rising (Brown et al. 2012). Yeasts are eukaryotic organisms and their similarity to human cells makes the development of antifungals difficult. Current antifungals have poor efficacy against biofilms. Overall, more advanced and effective treatment strategies are required. Prior the use of antifungal medication, the traditional anti-infective actions to maintain oral hygiene, such as the daily disruption of biofilms using a toothbrush and regular check-ups by dental professionals should be highlighted in the prevention of oro-oesophageal biofilm infections. Members of the oral microbiome can be the primary cause of oral mucosal lesions or a source for secondary intruders in non-infectious inflammatory mucosal conditions. The most common mucosal infection caused by fungi in humans is oral candidosis. In the long term, local inflammation induced by candidosis may lead to mucosal dysplasia and other pre-malignant changes. Studies have shown that chronic candida mucositis (CMC) can be carcinogenic in the upper digestive tract in vivo (Delsing et al. 14 2012, Rautemaa et al. 2007a). In addition, oral and oesophageal cancer lesions have been associated with Candida, thus further raising a question about the link between Candida yeasts and upper digestive tract carcinogenesis (Nagy et al. 1998, Scott and Jenkins 1982). Alcohol abuse and smoking are major and synergistic risk factors for upper digestive tract cancers. In the human body, ethanol is mainly metabolised by the liver, but ethanol metabolism at the mucosa–biofilm interface of the GI tract has been shown to play an important role regarding its carcinogenicity. Acetaldehyde (ACH) is the first metabolite of ethanol oxidation, and ACH exposure linked to chronic alcohol consumption has been ranked as a group I carcinogen by the International Agency for Research on Cancer (Secretan et al. 2009). ACH is one of the major carcinogens of tobacco smoke. Both of these risk factors result in an increase in salivary ACH. Previous studies have shown that the microbiome is the main determinant of local ACH production in the upper digestive tract. The primary aim of the research presented in this thesis was to investigate the capacity of Candida spp. or a mixed bacteria/yeast cultures to produce mutagenic ACH and to provide new insights into the carcinogenicity of Candida infections. Secondly, the goal was to find more effective ways to inhibit the mutagenicity and pathogenicity of C. albicans biofilms than currently available. 15 5 REVIEW OF THE LITERATURE 5.1 CANDIDA YEASTS AND THE HUMAN MYCOBIOME In recent years, the extent and characteristics of fungal ecosystems in the human body have begun to become apparent in conjunction with the progression of studies on the human microbiome (Ghannoum et al. 2010, Huffnagle and Noverr 2013). The spectrum and frequency of fungal species in the human body is strongly affected by health and disease. The interplay between fungal and bacterial microbiomes affects the balance, and both synergistic and competitive behaviour between the two have been noted (Cui et al. 2013). The distribution and diversity of fungal species can vary considerably between distant body sites, but similarities have been found between neighbouring sites, such as the oral and nasal cavities (Ghannoum et al. 2010, SellartAltisent et al. 2007). The most common commensal fungi in humans in both health and disease are Candida yeasts, which are mostly isolated from the mucosal surfaces of the GI tract and vagina (Calderone and Clancy 2011, Drell et al. 2013, Ghannoum et al. 2010). Candida can also be found on the skin, but colonization is site-specific and not as frequent as in the aforementioned niches (Findley et al. 2013). The genus Candida falls into the ascomycetes in the fungal phylum, and more specifically into a subphylum called Saccharomycotina. Approximately 160 species of Candida exist (Calderone and Clancy 2011). However, only a small proportion of these species are pathogenic and important in terms of human infections. Candida albicans is the most common Candida species found in humans in both health and disease. Other medically important Candida species include C. dubliniensis, C. famata, C. glabrata, C. guilliermondii, C. inconspicua, C. kefyr, C. krusei, C. lusitaniae, C. norvegensis, C. parapsilosis, C. rugosa and C. tropicalis, which are often referred to as non-albicans Candida species (NAC; Table 1, Calderone and Clancy 2011, Pfaller et al. 2010). NAC species are predominantly isolated from immunocompromised patients with advanced medical conditions such as haematological malignancy or bone marrow transplant (Krcmery and Barnes 2002). 16 Table 1. Major characteristics of C. albicans and non-albicans Candida yeasts, including their frequency in health and disease (infection). The infection frequencies in patients with infections are derived from a study that compiled statistics from 100 medical centres internationally. Frequencies in health are based on data from a medical centre in the USA (aPfaller et al. 2011, b Ghannoum et al. 2010, cThompson et al. 2011, dButler et al. 2009, eSilva et al. 2009; nd. = not described). There are marked differences in the characteristics and behaviour of Candida species due to their independent evolution and survival in unique habitats (Table 1). The ability to adapt and endure stress considerably differs between species (Papon et al. 2013). Some of these differences can be explained by the large genetic distances between species in the phylogenetic tree, some of which are larger than the distance between humans and certain genera of fish (Figure 1; Dujon 2010). The subphylum Saccharomycotina has two main branches or clades. Clinically important Candida yeasts are primarily located in the Candida CTG clade, which was named due to the alternative translation of the CTG codon as serine instead of leucine. C. glabrata alongside S. cerevisiae belongs to a whole genome duplication (WGD) clade under the Saccharomycetaceae, which also includes species such as C. krusei. The mycobiome of the upper digestive tract is dominated by Candida spp. The mean carriage rate of Candida spp. in the oral cavity of healthy humans varies (18% to 75%; Cannon and Chaffin 1999, Ghannoum et al. 2010). C. albicans is the dominant species in healthy subjects, but C. parapsilosis and C. tropicalis have also been found (Drell et al. 2013, Ghannoum et al. 2010, Scanlan and Marchesi 2008). Other frequently present fungi in the oral cavity include Malassezia, Cladosporium, Aureobasidium, Saccharomyces, Aspergillus, Fusarium and Cryptococcus species (Dupuy et al. 2014, Ghannoum et al. 2010). Previous studies have pointed out the similarities between oesophageal and oral microbiomes (Gagliardi et al. 1998, Norder Grusell et al. 2013). C. albicans has been isolated from samples taken along the upper and lower parts of 17 the oesophagus and is the dominant fungus and member of Candida spp. in the oesophageal microbiome (Norder Grusell et al. 2013). Figure 1. Phylogenetic tree illustrating genetic distances and clade distribution between the clinically important Candida species in the subphylum Saccharomycotina. The distances shown are arbitrary (reproduced from Papon et al. 2013). 5.2 PATHOGENESIS OF CANDIDA YEASTS 5.2.1 Virulence factors The pathogenic properties of Candida yeasts are dominated by six major virulence factors: polymorphism, phenotypic switching, biofilm formation, adhesion, invasion and hydrolysis. These properties greatly differ between and within species, and the pathogenicity of an isolate can consequently be drastically different from one to another. 5.2.1.1 Polymorphism and phenotypic switching Candida yeasts are polymorphic organisms. They can exist in a unicellular budding form (yeast) or in two filamentous forms: as elongated ellipsoidal structures with constrictions in septae (pseudohyphae) or as parallel lined filaments without constrictions (hyphae). However, only C. albicans, C. dubliniensis and C. tropicalis can form true hyphae (Table 1; Thompson et al. 2011). Hyphal formation has a major role 18 in tissue invasion, while the yeast form is more important for dissemination (Saville et al. 2003). Candida can also transit between two phenotypes: i) white cells are round and dome-shaped with a shiny cover, and ii) opaque cells form flatter and darker colonies that can be elongated. The major transcriptional regulator for phenotypic switching is the gene WOR1 (Huang et al. 2006). White-to-opaque switching has been shown to occur during mating and biofilm formation. It has been suggested to play a role in antifungal resistance and colonisation (Alby and Bennett 2009, Soll 2014). Most Candida yeasts are diploid organisms, but some exceptions exist among NAC species (Table 1; Butler et al. 2009). C. albicans was long considered as a strict diploid, but a very recent study reported that C. albicans is able to transform its ploidy in response to environmental challenges, and haploid or even polyploid forms also exist (Hickman et al. 2013). This can be advantageous when the yeast is confronted by various stress factors, such as antifungals (Harrison et al. 2014). The transition in phenotype and ploidy highlights the genomic plasticity of C. albicans and its advanced ability to adapt to different environmental niches. 5.2.1.2 Biofilm lifestyle The main virulence factor underlined in the context of mucosal colonisation and pathogenesis is the ability of Candida to grow as a biofilm. The earliest descriptions of th the biofilm lifestyle date back to the late 17 century, when Antonie van Leeuwenhoek described dental plaque from his own teeth (van Leeuwenhoek 1684). However, the general concept of a biofilm was first described by Bill Costerton in 1978 (Costerton et al. 1978). Approximately 80% of micro-organisms live in biofilm communities and 65–80% of human infections are biofilm-related (Costerton et al. 1999, Donlan and Costerton 2002). Candida biofilms are structurally advanced populations of fungal cells in yeast and/or hyphal forms adhered to either an abiotic or biotic surface. These populations are embedded in a self-produced extracellular carbohydrate polymeric matrix. Common abiotic surfaces in the human body colonised with Candida include central venous catheters (CVC) and various prosthetic structures such as dentures or tooth implants (Andes et al. 2004, Nett et al. 2010). Candida frequently forms biofilms on biotic surfaces in the human body, particularly on the mucosa of the GI tract and the vaginal epithelium (Dongari-Bagtzoglou et al. 2009, Harriott et al. 2010). Cell populations within biofilms phenotypically differ from their planktonic counterparts due to transcriptional reprogramming, and this highlights the unique nature of biofilm communities (Nett et al. 2009, Yeater et al. 2007). 19 The development of a biofilm is a multistep process (Finkel and Mitchell 2011). In the early phase, Candida cells adhere to the surface and form micro-colonies. These cells go through morphological switching and form hyphae, if able to do so. These hyphal structures act as a rigid and solid mesh that supports the growth of a cell population and resists mechanical stress (Figure 2). In the phase of maturation, fungal cells multiply and the matrix structure starts to form to support and protect the cells against environmental stress. In older biofilms, a dense and thick extracellular matrix covers the cells and hyphae. β-Glucans, particularly β-1,3-glucan, and mannans are the principle carbohydrates in the matrix structure (Nett et al. 2007). Fungal cells begin to disperse in the final stages of biofilm development as the population starts to regulate its growth by secreting quorum-sensing molecules, such as farnesol (Ramage et al. 2002b). These dispersed cells have been shown to be more virulent in a mouse model for disseminated candidosis (Uppuluri et al. 2010b). Therefore, biofilms can be considered as a constant source of infection. Hyphal and biofilm formation are both highly governed by various environmental cues, including pH, temperature, osmolarity and the presence of endogenous or exogenous antimicrobial agents (Chandra et al. 2001, Ene et al. 2012, Fiori et al. 2012, Kucharikova et al. 2011). Figure 2. Significant steps in biofilm formation: i) cellular adherence, ii) initial micro-colony formation and hyphal growth, iii) cellular multiplication and matrix formation and iv) dispersal of the cells from the biofilm due to quorum sensing. The SEM image above shows the ultrastructure of a mature (24h) C. albicans biofilm characterised by budding ovoid yeast cells and a hyphal network. Due to the advances in genomics, major progress has been made in understanding the plethora of genes that regulate C. albicans biofilm formation. A recent study revealed 20 six major transcription factors (TFs) that govern C. albicans biofilm formation: Bcr1p, Brg1p, Efg1p, Ndt80p, Rob1p and Tec1p (Nobile et al. 2012). This transcriptional circuitry includes over 1,000 genes, which represents 15% of all Candida genes. Candida species have a varied ability to form biofilms (Table 1; Kuhn et al. 2002, Silva et al. 2009). C. albicans, C. tropicalis, C. parapsilosis and C. glabrata can all form fully mature biofilms. However, C. albicans and C. tropicalis biofilms show a more complex and robust biofilm ultrastructure compared to the more uniform and thinner biofilms produced by C. glabrata and C. parapsilosis. Biofilm formation and the different properties are not only dependent on the species but also on the strain and environmental conditions (Silva et al. 2009). Mature biofilms are highly resistant against antimicrobial compounds, host immune factors and antimicrobial peptides (Ramage et al. 2014). Biofilms are also highly tolerant and adaptive to environmental cues, such as hypoxia, and oxidative and mechanical stress (Bonhomme et al. 2011, Paramonova et al. 2009, Seneviratne et al. 2008, Stichternoth and Ernst 2009). The factors behind increased resistance include the advanced matrix structure, the hyphal-cell ratio, cell density, transcriptional rewiring, extracellular DNA, the occurrence of persister cells and increased expression of efflux pumps (Martins et al. 2010, Nett et al. 2007, Perumal et al. 2007, Ramage et al. 2002a, Sellam et al. 2009, Vediyappan et al. 2010). 5.2.1.3 Adhesion, invasion and hydrolysis Overall, effective adherence to a biomaterial or the host surface is of major importance to biofilm formation and survival. The agglutinin-like sequence (ALS) is a major family of adhesion proteins or adhesins, and a total of eight ALS adhesins have been identified in C. albicans (Hoyer et al. 2008). Als3p has been shown to be the most vital adhesin, which mediates attachment to host cells and artificial surfaces (Almeida et al. 2008). In addition to Als3p, Hwp1p has been recognised as an important adhesin and virulence factor (Staab et al. 1999). Both Als3p and Hwp1p contribute strongly to biofilm formation (Nobile et al. 2008). Invasion of the host tissue is important for the establishment of infection and nutrient acquisition. Candida expresses specific proteins called invasins that can link the cell to host ligands and induce endocytosis (Phan et al. 2005, Phan et al. 2007). Hyphaassociated Als3p and Ssa1p have been recognized as the major invasins of C. albicans (Phan et al. 2007, Sun et al. 2010). Hyphal formation is essential for both active penetration of tissue and induced endocytosis (Wachtler et al. 2012, Gow and Hube 2012). Mechanical stress, nutrient sources, contact sensing and surface topology have 21 been shown to activate and regulate both hyphal and biofilm formation (Brand and Gow 2009, Brand et al. 2008, Watts et al. 1998). These factors are important for virulence in vivo (Brand et al. 2008). Hydrolytic enzymes secreted by Candida spp., including proteases, lipases and phospholipases, are major virulence factors and important for effective invasion. Secreted aspartic proteases (SAPs) have been shown to be the main family of proteases and have a dominant role in invasion and virulence. Their expression differs depending on environmental factors such as the pH and nutrient concentrations. The number of SAPs varies between Candida species. C. albicans expresses a total of ten SAPs (Naglik et al. 2003). 5.2.2 Infection and disease The incidence of fungal infections has been rising due to an increase in the number of immunocompromised patients (Garcia-Vidal et al. 2013, Pfaller and Diekema 2007). Candida is the most common cause of human fungal infection (Pfaller and Diekema 2007). In general, the infections caused by Candida yeasts vary from superficial mucosal infections, such as vaginal or oral candidosis, to life-threatening invasive infections. In healthy subjects, the colonisation and growth of Candida yeasts is controlled by specific and non-specific defence mechanisms, such as salivary and mucosal antimicrobial compounds, as well as by competitive inhibition by the surrounding microbiome. There are multiple pre-disposing factors that solely or in combination allow Candida to transform from a commensal organism into a pathogen in the upper digestive tract (Table 2). Table 2. Local, systemic and treatment-related predisposing factors for candidosis of the oral cavity and oesophagus. In general, an opportunity for infection arises when local or systemic defence mechanisms are weakened, the homeostasis within the microbiome is altered, or oral hygiene is poorly managed (Table 2; Laudenbach and Epstein 2009, Rautemaa and Ramage 2011, Samaranayake et al. 2009). In addition, uncleaned and cracked dentures, salivary hypofunction and smoking have adverse effects on mucosal health 22 and increase the risk of Candida overgrowth (Baboni et al. 2009, Fanello et al. 2006, Grimoud et al. 2005, Närhi et al. 1993). Systemic factors should be well assessed, as immunosuppressed patients are at major risk of developing candidosis. The use of corticosteroids, high glucose levels due to imbalanced diabetes, long-term treatment with broad-spectrum antibiotics, a low pH due to reflux disease and various immune deficiencies all increase the risk of development of candidosis (Arendorf and Walker 1980, Buhl 2006, Darwazeh et al. 1990, Kiehne et al. 2005). Oral candidosis is the most common oral complication in patients with human immunodeficiency virus (HIV) (Patton et al. 2002, Thanyasrisung et al. 2014). Up to 90% of HIV and acquired immune deficiency syndrome (AIDS) patients are colonised by Candida, and 27% of HIV patients and one-third of patients with AIDS have been reported with symptomatic oral candidosis (Calderone and Clancy 2011, Patel et al. 2012, Thompson et al. 2010). 5.2.2.1 Oral candidosis Oral candidosis is a superficial infection with either acute (thrush) or chronic characteristics. The clinical manifestations include pseudomembranous and erythematous forms, which are both typically described as acute infections and often a result from a general cause such as antibiotic or corticosteroid treatment (Samaranayake et al. 2009). The clinical picture of the pseudomembranous form often includes inflamed mucosa with white patches on top. In erythematous candidosis, the mucosa appears as red, dry and glazed. Erythematous candidosis is the most common form diagnosed in HIV patients (Bodhade et al. 2011). Typical symptoms for both of these forms include pain and/or a burning sensation. Chronic infections include atrophic erythematous and hyperplastic variants. Hyperplastic candidosis can be further divided into subtypes, including nodular, plaque-like or candida leukoplakia, depending on the clinical picture (Samaranayake et al. 2009). Chronic infections are characterised by both persistence and recurrence. In addition to these major variants of candidosis, lesions with a multifactorial background are often associated with Candida growth. These include median rhomboid glossitis, denture stomatitis, angular cheilitis and linear gingival erythema (Samaranayake et al. 2009). In comparison to various primary infections listed above, secondary candidosis is a result of underlying immune deficiency or autoimmune disease. Diseases most commonly found in the aetiology of the infections are HIV and haematological malignancies combined with the use of cytotoxic agents (Pagano et al. 2006, Samaranayake 1992). Chronic mucocutaneous candidosis (CMC) is a rare and 23 heterogeneous group of clinical syndromes, in which chronic Candida infections occur in the skin and mucosal surfaces throughout the body (Liu and Hua 2007). 5.2.2.2 Oesophageal candidosis Oesophageal candidosis, or Candida oesophagitis, is the most common infectious disease of the oesophagus and highly prevalent in patients with HIV (8–53%; Bonacini et al. 1991, Nishimura et al. 2013, Nkuize et al. 2010, Rolston and Rodriguez 1992). The high variance in the reported prevalence is mainly due to the advances in antiviral treatment in the past two decades. Candida oesophagitis is often classified into mild and severe forms according to endoscopial findings. Severe forms are associated with haemorrhage, oesophagotracheal fistulas and stenosis (Gaissert et al. 1999, Kanzaki et al. 2009). The main symptom is pain during swallowing. Oral candidosis is often used as a marker for the diagnosis of oesophageal candidosis (Samonis et al. 1998, Wilcox et al. 1995). The majority of the predisposing factors for oral candidosis therefore apply for oesophageal candidosis (Table 2; Baehr and McDonald 1994). 5.2.2.3 Invasive candidosis If superficial candidosis does not respond to treatment, is left untreated or has refractory features in immunocompromised patients, the infection can transform into invasive candidosis (IC; Laudenbach and Epstein 2009). The term IC encompasses various candida-related disorders with an invasive and more severe clinical picture: candidaemia, disseminated candidosis, endocarditis, meningitis, endophthalmitis, or deep organ involvement. In immunocompromised patients, candidal leakage into the bloodstream is a result of high local Candida colonisation and mucosal damage in the GI tract (Nucci and Anaissie 2001, Rosen et al. 2005, Pasqualotto et al. 2006). Patients are commonly treated for bacteraemia prior to the onset of candidaemia. The use of broad-spectrum antibiotics is a well-known predisposing factor for candidosis and involves increased colonisation (Pasqualotto et al. 2006). Biofilm infections related to medical devices, such as CVC, predispose patients to candidaemia (Kojic and Darouiche 2004). Dispersing cells from the gut or CVC-related biofilm travel in the bloodstream, and the highly adherent cells can disseminate into extra-intestinal organs such as the liver or spleen. IC has been reported as the fourth leading cause of nosocomial infections, with a yearly incidence globally varying from 2.4 to 29 per 100,000 (Pfaller and Diekema 2007). The crude mortality rates of these infections have remained high globally (26–46%; Morgan 2005, Tortorano et al. 2006). C. albicans is the dominant cause of infection, but the incidence of infections caused by 24 NAC species, particularly C. glabrata and C. parapsilosis, has been rising in the past two decades (Krcmery and Barnes 2002). 5.2.3 Interaction with bacteria As commensal organisms, Candida yeasts are in constant interaction with bacterial counterparts in the upper digestive tract, and they can together form complex polymicrobial biofilms on soft and hard tissues (Dongari-Bagtzoglou et al. 2009, Zijnge et al. 2010). The outcome of this interaction may be positive or negative in terms of human health. Denture stomatitis is an oral inflammatory disease highly associated with Candida biofilms (Ramage et al. 2004). Mixed species biofilms of bacteria and fungi have been shown to affect the inflammatory process in denture stomatitis and periodontitis (Avon et al. 2007, Järvensivu et al. 2004). Streptococcus gordonii, a common coloniser of the upper digestive tract mucosa, can induce C. albicans filamentation and biofilm formation in a synergistic fashion (Bamford et al. 2009, Silverman et al. 2010). Inter-species signalling affects the behaviour of bacteria and fungi. The quorum-sensing molecule farnesol secreted by C. albicans can alter the behaviour and virulence of Pseudomonas aeruginosa by reducing the production of phenazine, a potent toxin (Cugini et al. 2007). In contrast, P. aeruginosa -secreted phenazines inhibit yeast–hyphal transition and reduce biofilm formation (Morales et al. 2013). The formation of polymicrobial biofilms can result in increased virulence of both bacteria and yeast, and reduced susceptibility to antimicrobials as has been shown in co-infection studies with Staphylococcus aureus or Streptococcus spp. and C. albicans (Carlson 1983, Harriott and Noverr 2009, Shirtliff et al. 2009). In addition, it has been recently suggested that Candida yeasts can play a role in the onset of dental caries (Falsetta et al. 2014). Bacterial/fungal co-communities can create conditions that can either promote or control the growth of one or the other. Lactobacillus spp. can reduce the fungal load, and multiple studies have identified Lactobacillus metabolites that inhibit the metabolism and growth of Candida (Atanassova et al. 2003, Kohler et al. 2012, Okkers et al. 1999, Villena et al. 2011, Wagner et al. 2000). High vaginal colonisation by Lactobacilli inversely correlates with the incidence of vaginitis in women (Boris and Barbes 2000). 5.2.4 Mucosal immunity Local defence mechanisms are the primary line of immunity against mucosal candidosis and include the epithelial barrier function, salivary and mucosal soluble antimicrobial agents and the innate immune system. Mucosal trauma impairs the barrier function and increases the risk of candidosis, as highlighted in denture stomatitis (Samaranayake et al. 2009). Saliva plays an important role in antimicrobial 25 defence, and low salivary flow rates correlate with Candida colonisation (KamagataKiyoura et al. 2004, Radfar et al. 2003, Sreebny 2000). Various compounds in saliva and mucus inhibit microbial growth, including histatins, secretory IgA, lysozyme, mucins, defensins and lactoferrin (Li et al. 2006). 5.2.4.1 Innate immunity The major players of the innate immune system are the epithelial cells and phagocytotic cells, including polymorphonuclear neutrophils (PMNs), monocytes, macrophages and dendritic cells. PMNs play a dominant role in anti-Candida immunity. Their action in the targeted area is primed by the chemotaxis induced by epithelial cell recognition, which leads to extravasation through the endothelial cell layer in the capillaries. Neutropenia is a major risk factor for Candida infections, thus highlighting the role of PMNs (Warnock 1998). Phagocytosis and the intercellular signalling circuitry determine the outcome of the response and also initiate the adaptive immune response to provide “memory”. Interestingly, recent studies have shown that innate effector cells can also have “memory” when re-infection occurs (Ifrim et al. 2014, Quintin et al. 2012). The activation of innate immunity is primed by the recognition of Candida with specific pattern recognition receptors (PRRs) located in epithelial or immune cells (Cheng et al. 2012, Lionakis and Netea 2013, Naglik et al. 2011). This recognition can lead to either suppression of the protective response (tolerance) or induction of an immune response. An effective immune response includes complement, cytokine and chemokine signalling, phagocytosis and antimicrobial peptide production. Human βdefensins and LL-37 have been recognised as important antimicrobial peptides in mucosal immunity against candidosis (Li et al. 2011, Vylkova et al. 2007). In addition, extracellular proteases, including matrix metalloproteinases (MMPs), are produced by epithelial and immune effector cells to regulate the mucosal barrier function, and have been shown to modulate the epithelium during infection (Claveau et al. 2004). These factors are involved in the inflammatory response, which can eventually lead to host damage. PRRs bind to specific pathogen-associated molecular patterns (PAMPs) on the surface of yeast cells or hyphae. The hyphal cell surface is structurally different from yeast cells and involves different downstream signalling and pathway activation (Moyes et al. 2010). PRRs can be divided into three major classes: Toll-like receptors (TLRs), lectins and intracellular Nod-like receptors (NLRs). The main targets for these receptors are various cell wall components (differently linked mannans, glucans, lipoproteins, lipopolysaccharides) and fungal RNA or DNA. Synergistic interactions have been demonstrated between PRRs, such as Dectin-1, TLR-2 and TLR-4 (Ferwerda 26 et al. 2008, Gantner et al. 2003). PRR-PAMP binding leads to the stimulation of signalling cascades and eventually to the activation of more or less two major pathways: NF-κβ and Type I IFN (Lionakis and Netea 2013). In addition, candidal immunity involves the inflammasome pathways: NLRP3-Caspase-1 and CARD9Caspase-8, which have been implicated to play a role in IL1β production (Gringhuis et al. 2012, Kumar et al. 2009). The cytokine- or chemokine profile can either be pro- or anti-inflammatory and is determined by the sum of the pathways above. Pro-inflammatory cytokines IL-6, IL-8 and TNFα have a major role in PMN recruitment and activation (Balish et al. 1999, Netea et al. 1999, Romani et al. 1996, van Enckevort et al. 1999). In addition to the pro-inflammatory cytokines, hematopoietic growth factors granulocyte colonystimulation factor (G-CSF) and granulocyte-macrophage colony stimulation factor (GM-CSF) are important for PMN recruitment and activation (Kullberg et al. 1999, Lieschke and Burgess 1992). IL1α and ILβ are crucial cytokines in candidal immunity (Vonk et al. 2006). PMNs and mononuclear cells, monocytes and macrophages, can kill both intra- and extracellularly. Hydrolytic enzymes, antimicrobial peptides and reactive oxygen radical are produced by PMNs. Myeloperoxidase (MPO) and neutrophil elastase (NE) are the major hydrolytic enzymes produced by PMNs and are important in the activation of monocytes/macrophages and extracellular proteases, such as matrix metalloproteinase. In addition, neutrophils also produce extracellular fibre structures named neutrophil extracellular traps (NETs) that can capture and kill Candida (Urban et al. 2006). Considering the importance of the biofilm lifestyle in pathogenesis, few reports have shown that a biofilm induces an attenuated immune response with a very distinct cytokine profile in contrast to planktonic cells in vitro (Chandra et al. 2007, Xie et al. 2012). Biofilms have been proposed as a possible immune evasion mechanism (Dwivedi et al. 2011). A similar response has been noted in a study with S. aureus biofilms in vivo (Thurlow et al. 2011). 5.2.4.2 Adaptive immunity Dendritic cells (DCs) function as a major link between innate and adaptive immunity. DCs phagocytose and process Candida for antigen presentation and activate T-cells in lymph nodes (Newman and Holly 2001). Adaptive immunity against mucosal candidosis is coordinated by Th1, Th2 and Th17 T-cell responses, which are mainly regulated by CD4+ T-cells. However, a compensatory role has been described for CD8+ T-cells in HIV patients (Fidel 2011). Th1 T-cells activate phagocytotic cells by specific signals against Candida, while in contrast, Th2 T-cells attenuate the candidicidal measures by inhibiting effector cell actions. Th17 T-cells act in synergy with Th1 T-cells 27 and are the main source of IL-17. The Th17 response contributes to multiple facets of both innate and adaptive immunity: PMN chemotaxis and the regulation of antimicrobial peptide, cytokine and MMP production (Huppler et al. 2014). Deficiency of IL-17 results in increased susceptibility to mucosal and systemic candidosis (Conti et al. 2009, Ho et al. 2010, Huppler et al. 2014, Puel et al. 2011). Generally, no strict line can be drawn between innate and adaptive responses. Effective candidal immunity is underlined by the advanced integration of factors from both innate and adaptive sides. 5.3 TREATMENT STRATEGIES Considering the nature of oro-oesophageal candidosis as a biofilm infection, the outcome of treatment depends on the ability to disrupt and remove the biofilm. Antifungal resistance is an increasing problem and highlighted in biofilm infections. The maintenance of good oral hygiene is the backbone for the successful treatment of oral candidosis, particularly in patients with impaired immunity. The successful treatment of candidosis involves the identification of impaired local and systemic defence mechanisms. The treatment strategy should be chosen based on the extent and nature of Candida infection, for example whether the infection is local/superficial or systemic, acute or chronic, or whether it is a recurrent infection. Currently, three major classes of antifungals are used in the treatment of candidosis: polyenes, azoles (imidazoles and triazoles) and echinocandins. They all target the function or structure of the cell membrane or wall (Figure 3). All three classes can be administered intravenously, and topical formulations are available for certain polyenes and azoles. In general, immunocompetent patients with oral candidosis should be treated with topical antifungals, while a combination of topical and systemic antifungals should be targeted at immunocompromised patients. Oesophageal candidosis requires systemic antifungal therapy (Denning and Hope 2010). If candidosis is refractory, the risk for the development and selection of resistant strains should be considered and minimised when choosing the appropriate antifungal. The potential presence of NAC species should also be kept in mind in recurrent and refractory infections. NAC species often require different medications for successful treatment, as they exhibit decreased susceptibility, particularly towards azoles. This underlines the importance of accurate microbial diagnostics in the treatment of candidosis, especially in immunocompromised patients with recurrent infections. Increasing attention has recently been drawn to the mechanisms by which antifungals modulate host immune responses, which might be of importance when 28 constructing a rational treatment strategy against deep-seated infections in patients with impaired immunity (Ben-Ami et al. 2008). Figure 3. Cellular targets of major antifungals used for the topical and systemic treatment of candidosis. 5.3.1 5.3.1.1 Treatment of infection Topical treatment Topical antifungals are used for the local treatment of oral candidosis, and high drug levels can be obtained in the targeted area. Their absorption from the GI tract is mainly poor, and the systemic levels will therefore remain low. Thus, side effects and drug–drug interactions will not be as strong a compromising factor as with intravenously administered antifungals, although local irritation, GI symptoms, poor taste and inconvenience have been noted (Epstein et al. 2004). 5.3.1.1.1 Polyenes Nystatin and amphotericin B (AmB) are polyene antifungals that bind to ergosterol in the fungal cell membrane and increase membrane permeability (Figure 3). Both nystatin and amphotericin B have been widely used topically, as they are poorly absorbed from the GI tract and have various adverse effects in systemic therapy. They have been considered as the primary choice for the local treatment of oral candidosis and have broad-spectrum antimicrobial activity (Rautemaa and Ramage 2011). 29 5.3.1.1.2 Azoles Clotrimazole and miconazole inhibit fungal ergosterol synthesis, which is vital for the fungal cell plasma membrane. This results in an increase in cell membrane permeability (Figure 3). Both compounds are readily absorbed from the GI tract, and drug–drug interactions will thus occur. Clotrimazole is a moderate inhibitor of CYP3A4 on the GI cell wall and can increase the bioavailability of certain drugs, such as tacrolimus, cyclosporine, bentzodiazepines and HMG-CoA reductase inhibitors (Laudenbach and Epstein 2009, Vasquez et al. 2005). Miconazole treatment leads to fungal cell death due to the accumulation of reactive oxygen species (ROS) and oxidative stress (Barasch and Griffin 2008). Both drugs have long been used for the treatment of superficial candidosis, as they have both antifungal, mainly fungistatic, and antibacterial activity. Miconazole is active against various Candida spp., including fluconazole resistance isolates (Isham and Ghannoum 2010). 5.3.1.1.3 Chlorhexidine Chlorhexidine is a cationic polybisguanide compound that has broad-spectrum antimicrobial activity. It impairs the function of the cell membrane by increasing its fluidity (Figure 3). Chlorhexidine gluconate solution (0.2%) as an oral rinse has shown efficacy in the treatment of oral candidosis when used in combination with tooth brushing (Barasch and Griffin 2008, Grimoud et al. 2005). It has shown broadspectrum activity against various Candida spp., including fluconazole-resistant strains (Salim et al. 2013a). Chlorhexidine and nystatin should not be applied simultaneously, because interaction and loss of the anti-Candida effect will occur (Barkvoll and Attramadal 1989). A 4% suspension of chlorhexidine has been successfully used as a denture disinfectant (Mantri et al. 2013). 5.3.1.2 Systemic treatment Systemic antifungal therapy should be considered in complicated refractory superficial infections or in patients who are at risk of systemic Candida infection. First-generation triazoles (fluconazole and itraconazole) are considered as a first line of antifungal therapy if oral systemic treatment is required (Laudenbach and Epstein 2009, Rautemaa and Ramage 2011). The use of second-generation triazoles (voriconazole and posaconazole) should be restricted to immunocompromised patients with a severe infection and resistance profile. In cases where triazole cross-resistance has been diagnosed or infection is device- and biofilm-related, echinocandins are the best option, followed by amB (Cornely et al. 2012). 30 5.3.1.2.1 Triazoles Triazoles interrupt ergosterol biosynthesis by inhibiting the cytochrome P450 enzyme 14α-demethylase in the fungal cell wall, and toxic C-14α methylsterols start to accumulate within the cell (Figure 3). Fluconazole is a well-tolerated antifungal and widely used as a first line of systemic treatment, especially in HIV and AIDS patients (Cha and Sobel 2004, Hamza et al. 2008). However, prolonged and repeated therapy with a low dosage of fluconazole should be avoided, as the development of resistant isolates and selection pressure towards NAC species have been reported (Rautemaa et al. 2007b, Siikala et al. 2010). Itraconazole has a better susceptibility profile than fluconazole (Denning and Hope 2010). It is absorbed well, particularly as an oral solution, but sub-therapeutic drug concentrations are seen in patients with an elevated gastric pH. It is secreted into mucous membranes, and a topical effect will thus also be achieved. Multiple toxicities are associated with the use of itraconazole, and this should be assessed before the therapy (Denning and Hope 2010). The second-generation triazole antifungals voriconazole and posaconazole have a broad spectrum of activity against a plethora of Candida spp. and moulds, including fluconazole-resistant species and isolates (Pfaller et al. 2004). Voriconazole is structurally related to fluconazole and posaconazole to itraconazole. Posaconazole is a well-tolerated drug and oral bioavailability is especially enhanced by fatty food. Voriconazole has various drug interactions and side effects that should be taken into consideration. Immunomodulatory properties have been detected for triazoles: fluconazole and voriconazole have shown synergistic activity with phagocytes against C. albicans (Brummer and Stevens 1996, Garcha et al. 1995, Vora et al. 1998) and fluconazole can drive protective T-cell responses in vivo (Cenci et al. 1997). 5.3.1.2.2 Echinocandins Echinocandin class antifungals (caspofungin, micafungin, anidulafungin) can only be administered intravenously. They act via non-competitive inhibition of β-1,3-D-glucan synthetase in the fungal cell wall, which results in osmotic instability and cell lysis (Figure 3). All three echinocandins are well tolerated, have broad-spectrum fungicidal activity against Candida spp. and have few drug–drug interactions, which is a major advantage over other antifungals (Cornely et al. 2012). However, resistance against caspofungin has been reported, especially among C. glabrata isolates (Alexander et al. 2013). Caspofungin has shown promising efficacy against Candida biofilms, and has thus been suggested as a therapeutic option in CVC-related infections (Andes et al. 2012). Caspofungin modulates immune responses. Exposure of C. albicans to 31 caspofungin results in β-glucan unmasking in the fungal cell wall, and this induces proinflammatory responses by macrophages (Lamaris et al. 2008, Wheeler et al. 2008). 5.3.1.2.3 Polyenes There are currently three lipid formulations of conventional amphotericin B (AmB lipid complex, ABLC, AmB colloidal dispersion, ABCD, and liposomal amphotericin B, LAmB), which were developed to enable systemic therapy and reduce toxicity. Lipid AmBs have shown decreased renal toxicity compared to conventional AmB (AmB deoxycholate) (Ashley et al. 2006). AmB antifungals have a very broad spectrum of activity, with efficacy against Candida spp. and moulds. Conventional Amb and lipid AmBs are suggested treatment options for device-related infections (Cornely et al. 2012). AmB and ABCD induce pro-inflammatory responses, but in contrast, ABLC and L-AmB either attenuate or have no effect on inflammatory responses by immune effector cells (Arning et al. 1995, Simitsopoulou et al. 2005). 5.3.1.2.4 Antifungal vaccines One optional route for systemic therapy in infectious diseases is vaccination. The first vaccines against bacterial and viral infections were developed over a few centuries ago, and multiple vaccines currently exist against various bacterial and viral species. No vaccines are currently on the market against fungal infections. Experimental models have produced some promising results in this field. A Candida vaginitis model using anti-β-glucan has shown success in mice (Pietrella et al. 2010). In addition, Als3p adhesin and Sap2p invasin have been identified as important targets. Als3 antiCandida (rAls3-N) vaccine protected against oropharyngeal and systemic candidosis in mice (Spellberg et al. 2006), while rSap2-N induced protection against vaginal infection in rats (De Bernardis et al. 2012). 5.3.2 Suppressive therapy In clinical scenarios where patients are at risk of developing a fungal infection, primary or secondary antifungal prophylaxis may be an appropriate strategy to suppress Candida overgrowth, transient colonisation and the risk of systemic disease (Laudenbach and Epstein 2009, Rautemaa and Ramage 2011). The topical polyene antifungals nystatin or AmB are recommended as the primary choice for prophylactic treatment of oral candidosis in the prevention of recurrent infection. In HIV patients with frequent and severe recurrent infections, prophylaxis can be considered (Kaplan et al. 2009, Lodi et al. 2007). Fluconazole and itraconazole have been reported as 32 effective prophylactic antifungals for the prevention of systemic infection in intensive care unit (ICU) patients with haematological or upper digestive tract malignancies or AIDS (Cornely et al. 2003, Corvo et al. 2008, Playford et al. 2006, Vardakas et al. 2005). Antifungal prophylaxis can be recommended for patients who have undergone abdominal surgery and have perforations in the gut and anostomotic leakage (Cornely et al. 2012). Posaconazole has been used as antifungal prophylaxis in autoimmune polyendocrinopathy-candidosis-ectodermal dystrophy (APECED) patients with CMC. Posaconazole was found to be more effective than fluconazole and itraconazole as a prophylactic agent in neutropenic patients with leukaemia or in bone marrow transplant recipients (Cornely et al. 2012, Ullmann et al. 2007). Although promising outcomes have been observed with prophylactic treatment, overall evidence for treatment efficacy remains limited and no drug has shown superior potential. Controversial results have also been reported. Nystatin was not effective in the prophylactic treatment of cancer patients (Clarkson et al. 2007, Epstein et al. 2003). The choice of prophylactic agent is complicated by the multiple adverse effects associated with the use of antifungal agents. If antifungal prophylaxis is considered, the agent should be carefully chosen and the risk for the development and selection of resistant strains should be kept in mind, especially when using fluconazole. In addition, the predisposing factors for candidosis and oral hygiene should be well addressed and managed beforehand. 5.3.3 Probiotics as an alternative approach Candida colonisation in health is suppressed by competitive inhibition with surrounding bacteria. The idea behind probiotic therapy is based on this model and th was first presented in the early 20 century by Elie Metchnikoff (Metchnikoff 1908). Probiotics are defined as health-promoting live microbial supplements that are nonpathogenic and normally belong to the human microbiome. Probiotics can stabilise the balance within the microbiome by reducing the overgrowth of pathogenic microbes. Probiotic bacteria have been industrially applied to enhance processes such as fermentation and to protect food products as preservatives. Micro-organisms used as probiotics mainly belong to the group of lactic acid bacteria, such as Lactobacillus spp. and Bifidobacterium spp., but other bacteria and also yeasts, such as Saccharomyces boulardii, have additionally been used. Many beneficial effects have been reported, particularly in the treatment of vulvovaginal candidosis and in the suppressive therapy in the gut (Manzoni et al. 2006, Reid et al. 2003, Wagner et al. 1997). Probiotics can reduce Candida overgrowth and suppress candidal colonisation of the oral cavity in vivo (Elahi et al. 2005, Hatakka et al. 2007). However, evidence regarding the benefits of long-term use of probiotics in humans is still limited, and this 33 therapy can have adverse outcomes. The use of probiotic micro-organisms can lead to bacteraemia and sepsis in immunocompromised patients, and caution is thus warranted (Salminen et al. 2004). 5.3.4 Alternative anti-biofilm agents The treatment of oro-oesophageal candidosis with current antifungals is often challenged by the biofilm lifestyle and poor patient compliance due to multiple side effects and/or toxicity. In addition to the mucosal surface structures, abiotic surfaces in various medical devices provide an excellent surface for biofilm formation, as highlighted in CVC-related infections. In the oral cavity, various biomaterial surfaces exist in the form of dentures, fillings and implants. Multiple approaches are currently under investigation to find more effective ways to eradicate biofilm infections. Xylitol, a sugar alcohol, has shown beneficial effects on oral health and has been widely used in oral health products and other consumables. It reduces dental plaque formation and acid production by oral streptococci, particularly the cariogenic pathogen Streptococcus mutans, and this inhibits the development of dental caries (Iwata et al. 2003, Lee et al. 2009, Söderling and Hietala-Lenkkeri 2010). S. mutans and C. albicans function synergistically in dental plaque formation, and increased pathogenesis in the form of dental caries has been shown in vivo (Falsetta et al. 2014). Xylitol could potentially act against this synergism. Chlorhexidine showed better in vitro effect than fluconazole against C. albicans biofilms when the two compounds were impregnated into denture acrylic in vitro (Salim et al. 2013b). Farnesol is a quorum-sensing molecule produced by C. albicans that inhibits yeast–hyphal transition (Hornby et al. 2001). It has shown efficacy against biofilms in vitro, but contradictory outcomes have been observed in in vivo models (Hisajima et al. 2008, Navarathna et al. 2007, Ramage et al. 2002b). Plants have effective strategies to fight against fungi, and numerous plant compounds have been investigated for their potential anti-Candida activity. Some of them, including tea tree oil, terpenoids and eugenol, have shown promising efficacy against Candida biofilms in vitro (Khan and Ahmad 2012, Ramage et al. 2012, Sudjana et al. 2012). However, the in vivo efficacy remains unknown. 5.4 ETHANOL AND ACETALDEHYDE METABOLISM IN THE HUMAN BODY In general, the liver is the main organ responsible for ethanol metabolism. Approximately 75–90% of ethanol oxidation is carried out by the liver in health, but 34 the level of oxidation can be substantially lower in liver disease, such as hepatic cirrhosis (Agarwal and Goedde 1990). When alcohol is ingested, the bolus travels through the upper digestive tract and stomach into the small intestine, where the majority of ethanol (70–80%) is absorbed via simple diffusion without specific transport mechanisms. It rapidly passes through the membranes because of its small molecular size and high water solubility and enters the bloodstream, mainly the portal vein carrying blood to the liver. Ethanol is evenly distributed via the circulation and diffusion into the water content of human body, including saliva. Ethanol metabolism also occurs in the digestive tract (extra-hepatic). Part of the ingested ethanol is directly absorbed and metabolised by the mucosal and microbial cells in the oral cavity, oesophagus and stomach. Studies comparing intravenous and oral administration of ethanol have demonstrated that the blood alcohol level is significantly lower after oral ingestion, thus proving the existence of first-pass metabolism (Julkunen et al. 1985). Severe liver injury can induce first-pass metabolism and account for as much as 40–50% of total ethanol metabolism (Dam et al. 2009, Utne and Winkler 1980). Extra-hepatic metabolism is of considerable interest, as ethanol is known to contribute to various pathological conditions in the upper digestive tract. Ethanol is oxidised in mucosal, microbial and hepatic cells, yielding acetaldehyde (ACH) as the first and major metabolite. The majority of ACH is formed by various alcohol dehydrogenase (ADH) enzymes in both human and microbial cells. In addition, the cytochrome P450 2E1 (CYP2E1)-dependent microsomal ethanol oxidizing system (MEOS) plays a role in ethanol oxidation in humans. Peroxisomal catalase can oxidise ethanol, but the reaction is limited by the bioavailability of hydrogen peroxide, thus contributing only minimally to ethanol oxidation in the liver (Oshino et al. 1973). Toxic ACH is further metabolised by aldehyde dehydrogenase (ALDH) enzymes into a less harmful compound, acetate. Finally, acetate is eliminated by the human body through oxidation to CO2 in the heart, skeletal muscle and brain cells. Acetate can also be further metabolised in human or microbial cells into acetyl coenzyme A (Acetyl-CoA) and used as an energy source or utilised for the biosynthesis of cell components such as lipids and cholesterol. In addition to the exogenous sources of ethanol, the human body and mainly the GI mucosa can be exposed to endogenously produced ethanol via microbial metabolism. At a low oxygen tension, microbes produce energy through fermentation and ethanol is formed via ACH. Patients suffering from achlorhydric atrophic gastritis have shown microbial overgrowth and endogenous ethanol and ACH production (Väkeväinen et al. 2002). However, not all fermentative processes yield ethanol as an end product. Some human cells produce lactate in anaerobiosis. Certain 35 bacterial species produce a spectrum of short-chain fatty acids, including butyrate, acetate and succinate, in their fermentative metabolism. 5.4.1 5.4.1.1 Ethanol oxidation in humans Alcohol dehydrogenase (ADH) Human ADH enzymes are located in the cytosolic compartment of the cell. The oxidative process catalysed by ADH involves intermediate carriers of electrons, + + nicotine adenine dinucleotide or its phosphate analogue (NAD or NADP ), which are reduced by two electrons to NADH or NADPH in the reaction. Human ADH enzymes can be divided into five classes based on their main characteristics (Holmes 1994). Class I ADH enzymes (ADH 1) have a low Km value for ethanol (<4 mM). Classes II (ADH 2), IV (ADH 4) and V (ADH 5) have moderate Km values for ethanol (<40 mM), and class III (ADH 3) is hardly saturated at all (Km > 3 M). A total of seven genes (ADH1A, ADH1B, ADH1C, ADH2-5) have been identified to encode various ADH enzymes (Osier et al. 2002). The three major isoenzymes of class I encoded by ADH1A, ADH1B and ADH1C play a substantial role in ethanol oxidation in humans, and their polymorphisms have been linked to disease (Bosron and Li 1986). In addition, ADH enzymes have a significant role in the oxidation of other excess alcohol compounds such as retinol, which is needed for retinoic acid biosynthesis (Duester et al. 1999). 5.4.1.2 Microsomal ethanol oxidising system (MEOS) The MEOS is located in the endoplasmic reticulum and characterised by the presence of cytochrome P450 (CYP) enzymes. In humans, multiple CYP enzymes oxidise ethanol, including CYP2E1, -1A2 and -3A4 (Koop 1992, Niemelä et al. 1999). However, CYP2E1 has the highest affinity for ethanol of all CYP enzyme family members (Koop 1992). CYP2E1 can also oxidise other low molecular weight molecules, such as carcinogenic nitrosamines, aflatoxins and polycyclic hydrocarbons, and ethanol-induced CYP2E1 metabolism has therefore been linked to other toxic effects (Koop 1992). Normally, CYP2E1-dependent MEOS accounts only for a small percentage of ethanol metabolism due to its high Km (7–10 mM), but the activity can be induced by up to 10–20 fold in chronic alcohol use (Oneta et al. 2002). However, individual variation exists in the level of induction. During CYP2E1-mediated ethanol metabolism, ROS are generated (Lieber 1997). This leads to the formation of lipid peroxidation products, which can be genotoxic due to protein adduct formation and cause damage comparable to that of ACH (Aleynik et al. 1998, Niemelä et al. 1999). 36 5.4.1.3 Aldehyde dehydrogenase (ALDH) Ten different genes (ALDH1-10) encode ALDH enzymes in humans (Yoshida et al. + 1998). ALDH requires NAD in the oxidation of ACH into acetate, thus further decreasing the redox state of the cell. The cellular localisation of ALDH enzymes is more varied compared to ADH enzymes. Mitochondrial, cytosolic and microsomal isoforms have been identified. Different ALDH enzymes can be divided into groups according to their Km values: ALDH1 and ALDH2 isoenzymes have low Km values (0.2– 180 µM) and ALDH3 and ALDH4 are isoenzymes with a high Km value (5–83 mM) (Jelski and Szmitkowski 2008, Klyosov et al. 1996). Cytosolic ALDH1 and particularly mitochondrial ALDH2 have a high affinity to ACH and play a major role in ACH metabolism. The rest of the ALDH enzymes do not contribute substantially to ACH elimination due to their high Km values and low affinity for ACH, and their role in ACHrelated pathogenesis is thus minimal (Crabb et al. 2004). They are mainly responsible for the elimination of other toxic aldehydes. 5.4.2 Hepatic metabolism ADH 1 and its isoenzymes play a substantial (95% of total activity) role in ethanol oxidation in the liver. Their low Km values underline this property. The redox state, i.e. + NADH/NAD ratio, regulates metabolism in the liver. A reduction in the redox status due to ethanol oxidation can impair other metabolic functions of the liver, such as gluconeogenesis, fatty acid oxidation and the activity of the tricarboxylic acid (TCA) cycle. Ethanol turnover into ACH, i.e. the rate of ethanol elimination, is mainly regulated by the rate of NADH re-oxidation. Blood ACH levels and ethanol oxidation in the liver can be significantly affected by polymorphisms. Major mutations appear in two ADH genes: ADH1B and ADH1C (Crabb et al. 2004). The ADH1B*2 allele encodes a 40 times more active isoenzyme than ADH1B1*1, which leads to ACH accumulation in the blood. A similar intolerance of alcohol has been described as in individuals heterozygous for ALDH2*2 (Thomasson et al. 1991). Caucasians rarely have ADH1B*2, but it is more frequent in Asians. ADH1C*1 increases ethanol metabolism by 2.5 fold compared with the other allele, ADH1C*2 (Bosron and Li 1986). The major role of ALDH2 in ACH metabolism has been supported by studies on ALDH2-deficient individuals. Two allelic forms exist for the ALDH2 isoenzyme: the active ALDH2*1 and highly inactive ALDH2*2. Individuals homozygous for ALDH2*2 have no activity and persons heterozygous for ALDH2*2 retain approximately 6% of the activity (Crabb et al. 1989). Between 40–50% of Asians have the deficient form of ALDH2. Homozygotes cannot tolerate alcohol due to adverse effects (nausea, facial flushing and headache) associated with high ACH concentrations in blood. Heterozygotes can tolerate alcohol better, and they are consequently at greater risk of ACH-related pathogenesis. 37 5.4.3 5.4.3.1 Extra-hepatic metabolism Metabolism in the upper digestive tract Mucosal cells in the oral cavity and oesophagus are challenged with ethanol and ACH via saliva and blood. A study by Dong et al. demonstrated the presence of high Km ADH 4, but a lack of low Km ALDH2 and ALDH1 enzymes in gingival and tongue biopsies (Table 3; Dong et al. 1996). Thus, it was suggested that cytotoxic ACH may be involved in the aetiology of alcohol-related oral injury. Yin et al. compared the expression and activity of ADH and ALDH enzymes of the oesophageal and gastric mucosa and detected 4-fold higher activity of high Km ADH enzymes and 4-fold lower activity of the low Km ALDH2 enzyme in the oesophageal mucosa compared to the stomach (Yin et al. 1993, Yin et al. 1997). Both oral and oesophageal tissue samples lacked highly active ALDH2 (Table 3; Chiang et al. 2012). CYP2E1 is highly present in the oral and oesophageal mucosa (Godoy et al. 2002, Lechevrel et al. 1999, Liu et al. 2001b). Interestingly, CYP2E1 was shown to be expressed in pre-cancerous and cancer lesions of the oral cavity (Warnakulasuriya et al. 2008a). Overall, these findings indicate that oral, oesophageal and gastric mucosal cells are capable of oxidizing ethanol, but their ability to eliminate ACH is either lacking or limited, especially among subjects with a genetically deficient ALDH2 enzyme. Table 3. Mean ADH and ALDH activity (mU) relative to the amount of tissue and protein present in the oral cavity and oesophagus compared to the liver (modified from Chiang et al. 2012; nd. = non-detectable). 38 5.4.3.2 Microbial metabolism In subjects with the normal ALDH2 enzyme, ACH levels in the peripheral blood remain under the detection limit, even after high doses of ethanol (Stowell 1979). Significantly elevated salivary ACH levels after alcohol intake can, however, be detected in ALDH2-deficient individuals. After alcohol consumption, ethanol levels in the saliva are equal to those in the blood (Jones 1979). Significant ACH levels are detected in saliva after moderate alcohol intake, and these correlate with salivary ethanol levels (Homann et al. 1997, Jokelainen et al. 1996). In ALDH2-deficient subjects, a dose of alcohol results in 2–3 times higher ACH levels in saliva compared to individuals with the normal ALDH2 enzyme (Väkeväinen et al. 2000, Yokoyama et al. 2008). This is partly caused by oxidation of ethanol to ACH in the parotid glands (Väkeväinen et al. 2000). Main determinant for salivary ACH is microbial metabolism (Homann et al. 1997, Väkeväinen et al. 2001). Microbial ACH production has been shown to occur in the oropharynx in vivo (Pikkarainen et al. 1981). ACH levels detected in saliva were significantly lower after a chlorhexidine mouthwash rinse, thus providing strong support for the microbial origin of ACH. No correlation was found between microbial counts and salivary ACH levels, thus indicating that a qualitative change in microbial composition has an effect on salivary ACH levels (Homann et al. 1997). The highest salivary ACH levels are seen immediately after alcohol intake at very high local ethanol concentrations (Linderborg et al. 2011). Poor oral hygiene correlates with high salivary ACH levels, and a link between facultative bacteria and yeasts, particularly C. albicans, with high salivary ACH levels has been shown (Homann et al. 2001, Yokoyama et al. 2007). Altogether, these findings suggest that the microbiome plays a substantial role in local ACH exposure in the upper digestive tract. 5.4.3.2.1 Bacterial metabolism Under a low oxygen tension, bacterial cells produce energy through fermentation and ethanol is formed. Endogenous ethanol production by the local microbiome has been measured in vivo (Cope et al. 2000). Bacterial alcohol dehydrogenase (adh) can function in a reversible fashion, and in aerobic conditions bacterial cells oxidise ethanol to ACH (Maconi et al. 1988). Aerobic oral Streptococcus, Corynebacterium and Stomatococcus species have previously been linked to high ACH levels detected in saliva (Homann et al. 2001, Yokoyama et al. 2007). Oral Streptococci spp. and Neisseria spp. can produce high amounts of ACH from ethanol in vitro and possess a highly functional adh with a low Km for ethanol (Kurkivuori et al. 2007, Muto et al. 39 2000, Pavlova et al. 2013, Väkeväinen et al. 2001). Pavlova et al. investigated ADH expression in S. gordonii and demonstrated that three functional ethanol oxidising enzymes exist and one, namely adhE, with a high activity (Pavlova et al. 2013). Other enzymes were also identified that showed substrate specificity for other alcohols. Interestingly, no functioning aldehyde dehydrogenase (ald) enzyme was identified for any of the Streptococcal or Neisseria species investigated (Muto et al. 2000, Pavlova et al. 2013). Fully functional alds have been identified in bacteria of the gut, but the elimination of ACH by these enzymes was lower than alcohol dehydrogenasedependent ACH formation, which could contribute to ACH accumulation (Nosova et al. 1998, Nosova et al. 1996). Interestingly, probiotic Lactobacillus spp. and Bifidobacterium spp. possess an active enzyme that efficiently removes ACH (Nosova et al. 2000). This indicates that probiotics could have protective effects in addition to the ones already observed. Catalase is found in aerobic and facultatively anaerobic bacteria, and inhibition of catalase decreased the ACH level produced in vitro. Thus, alternative pathways for oxidation exist in bacteria (Tillonen et al. 1998). The way of life of various commensal and pathogenic bacteria in the oral and oesophageal microbiome is highlighted by the community-oriented biofilm lifestyle. When a metatranscriptomic approach was applied to investigate the metabolic patterns in the oral microbiome, disease-associated communities showed similar metabolic profiles, and genes encoding enzymes in pyruvate and ethanol metabolism were highly expressed (Jorth et al. 2014). Both oesophageal and oral microbiomes, including the salivary microbiome, are highly dominated by Streptococcus spp. (Segata et al. 2012, Yang et al. 2009). Neisseria spp. are also among the highly prevalent species in these microbiomes in healthy subjects. Therefore, the upper digestive tract is colonised by bacteria that can efficiently oxidise ethanol, but their ability to remove ACH appears limited. Thus, local ACH accumulation can occur. However, environmental factors have to be taken into account. Nutrients and oxygen levels, together with the composition of the bacterial community, vary considerably within each niche and have a major effect on the metabolome and the potential ACH exposure locally. 5.4.3.2.2 Candida metabolism Candidal metabolism is largely driven by carbohydrate metabolism. In general, yeasts favour sugars as their primary and preferred energy source (Askew et al. 2009). Our knowledge of the carbohydrate metabolism of eukaryotic cells mostly derives from studies on Saccharomyces cerevisiae, referred to as conventional yeast. S. cerevisiae has been widely used for industrial purposes due to its high tendency for fermentation. A universal theme in yeast carbohydrate metabolism is the conversion of 5- or 6-carbon sugars to either glucose-6-phosphate (G-6-P) or fructose-6- 40 phosphate (F-6-P), which are then converted to pyruvate in glycolysis (Figure 4; Barnett 2003, Flores et al. 2000). The fate of pyruvate varies depending on the availability of oxygen and the type of yeast. Figure 4. A schematic diagram of central carbon metabolism and fermentative pathway in Candida albicans (abbreviations as follows: F6P = fructose-6-phosphate, G6P = glucose-6phosphate). The solid line denotes the central carbon metabolism in aerobiosis and the dashed line indicates the pathway of fermentative metabolism in anaerobiosis. The major genes regarding ethanol metabolism are shown. Eukaryotic cells typically prefer respiration to produce energy when oxygen is present (normoxia). In respiration, acetyl-CoA derived from pyruvate is utilised by the TCA cycle, where it is oxidised to carbon dioxide (CO2). NADH and FADH2 are formed in the reductive process. Energy is produced in the form of adenosine triphosphate (ATP) through oxidative phosphorylation, where the two electron carriers NADH and FADH2 are re-oxidised. At a low oxygen tension (hypoxia), eukaryotic cells produce energy through fermentation. In yeasts, pyruvate is transformed into ethanol in the reductive + process along the fermentative pathway. Respiration is preferred, as more NAD and ATP per glucose can be produced in oxidative phosphorylation than in fermentation. S. cerevisiae is a Crabtree-positive yeast that prefers fermentation for energy production and represses respiration even when carbohydrates and oxygen are available. In contrast, C. albicans and other non-conventional yeasts are defined as Crabtree-negative yeasts that oxidise pyruvate to CO2 to produce energy under aerobic conditions via the TCA cycle, and fermentation is only used under hypoxic conditions. To further underline these differences, highly distinct post-transcriptional mechanisms regarding carbon assimilation exist in C. albicans and S. cerevisiae (Sandai et al. 2013). Importantly, this section mainly focuses on the metabolism of C. albicans. Multiple transcriptomic studies have highlighted the effect of oxygen levels on metabolism. In C. albicans, genes belonging to the glycolytic pathway, ergosterol 41 synthesis and fermentation are up-regulated under hypoxic conditions, while the expression of genes involved in oxidative metabolism is down-regulated (Ernst and Tielker 2009, Setiadi et al. 2006, Synnott et al. 2010). Before entering the TCA cycle, pyruvate is decarboxylated to acetyl-CoA in the mitochondrial pyruvate dehydrogenase complex (CaPDH) (Figure 4; Flores et al. 2000, Pronk et al. 1996). The equilibrium between respiration and fermentation is transcriptionally regulated by CaGal4p and CaTye7p in C. albicans, depending on the nutrient source (Askew et al. 2009). These master regulators are vital for normal growth and virulence, and they both activate genes linked to fermentation. However, the CaPDH-dependent decarboxylation step is only controlled by Gal4p. In the fermentative pathway, pyruvate is first converted to ACH by pyruvate decarboxylase, which is encoded in C. albicans by CaPDC11. In yeasts, as well as in humans, ACH is a metabolite that is located at the point where the fermentative pathway and pyruvate bypass pathway cross (Figure 4; Flores et al. 2000). In fermentation, ACH is metabolised to ethanol by ADH, and in the process NADH is + oxidised to NAD to maintain glycolysis. Glycerol production supports the redox + balance by the formation of NAD in anaerobiosis. Importantly, glycerol metabolism is also associated with osmotic stress resistance and biofilm formation (Desai et al. 2013, Flores et al. 2000). CaAdh1p is a bi-directional enzyme in C. albicans. Thus, ethanol can be used as both a carbon and an energy source (Bertram et al. 1996). In pyruvate bypass, ACH is metabolised to acetate by the enzyme Ald, followed by the metabolism of acetate to acetyl-CoA by the enzyme acetyl CoA synthetase (Acs). Acetyl-CoA is transported into mitochondria by a carnitine-dependent mechanism, + and NADH is re-oxidised to NAD during the process. This route bypasses mitochondrial acetyl-CoA formation by the PDH complex. Fermentation is upregulated in hyphal and biofilm formation and during colonisation (Hernaez et al. 2010, Martinez-Gomariz et al. 2009, Monteoliva et al. 2011, Pierce et al. 2013). In various niches of the human host, fungal cells are often faced with hypoxic conditions. Therefore, fermentative metabolism is vital for adaptation and survival. A total of five alcohol dehydrogenase genes (CaADH1-5) exist in the C. albicans genome (Inglis et al. 2012). CaADH1 and CaADH2 show significant homology to corresponding genes in S. cerevisiae (75–77%; Inglis et al. 2012). CaAdh1p is the only isoenzyme that has been studied in depth. The protein functions either in the cytosol or cell wall (Crowe et al. 2003, Mukherjee et al. 2006). CaAdh1p mainly converts ACH to ethanol and is expressed in the exponential and stationary growth phases of planktonic growth (Bertram et al. 1996, Kusch et al. 2008, Swoboda et al. 1994). mRNA levels of CaADH1 do not correlate with the protein levels, thus suggesting the existence of post-transcriptional regulation (Bertram et al. 1996). Previous 42 transcriptomic and proteomic studies have indicated that CaADH1 or CaAdh1p has a regulatory role in biofilm formation and growth (Martinez-Gomariz et al. 2009, Mukherjee et al. 2006, Thomas et al. 2006). A limited amount of information is available on the functions and role of other CaAdhs in C. albicans. S. cerevisiae ScAdh2p functions under glucose-repressed conditions and preferably converts ethanol to ACH (Maestre et al. 2008). In a transcriptomic study by Setiadi et al. (2006) CaADH1, CaADH2 and CaADH5 were up-regulated in hypoxia. CaADH5 regulates matrix formation during biofilm development (Nobile et al. 2009). The number and functional role of CaAld enzymes in C. albicans is not well known. There are five genes in the S. cerevisiae genome (Cherry et al. 2012). ScALD4 and ScALD6 encode the major mitochondrial and cytosolic isoforms, respectively. ScALD5 encodes the minor mitochondrial isoform in S. cerevisiae and is homologous to CaALD5 (61%; Inglis et al. 2012). ScALD2 and ScALD3 in S. cerevisiae encode cytosolic isoenzymes that do not participate in acetate formation (Saint-Prix et al. 2004). ScAld5p and ScAld6p have a major role in acetate formation in S. cerevisiae (Saint-Prix et al. 2004). CaAld5p is expressed in C. albicans biofilms during oxidative stress and hypoxia (Martinez-Gomariz et al. 2009, Seneviratne et al. 2008, Strijbis et al. 2009). ACH accumulation has been reported to be regulated in planktonic cultures during hypoxia by the downstream enzymes CaAld6p and CaAcs1p in C. albicans (Marttila et al. 2013a). CaAld4p has a role in carnitine biosynthesis (Strijbis et al. 2008). Carnitinedependent transport of acetyl-CoA is required for growth on non-fermentable carbon sources (ethanol, acetate) and for biofilm development (Strijbis et al. 2008). The role of acetyl-CoA synthetases in C. albicans has been extensively studied, and two genes have been identified: CaACS2 encodes the major isoform, which is vital for growth on most carbon sources, and CaACS1 is required for the full utilisation of alternative carbon sources (Carman et al. 2008). Although carbohydrates are the preferred source, metabolic flexibility is needed for survival and virulence. When carbohydrates are not available, utilisation of alternative carbon sources, such as ethanol and acetate, is required for the biosynthesis of critical cellular components. The glyoxylate cycle, a metabolic pathway partly overlapping with the TCA cycle, enables the use of two-carbon sources in gluconeogenesis and is critical for virulence in C. albicans (Figure 4; Ramirez and Lorenz 2007). During the early steps of phagocytosis, glycolysis is repressed and the glyoxylate shunt and gluconeogenesis are up-regulated. However, later survival is dependent on glycolysis (Barelle et al. 2006). It has also been shown that the availability of glucose regulates the stress responses in C. albicans, thus underlining the importance of central carbon metabolism in fungal pathogenesis (Rodaki et al. 2009). 43 5.5 5.5.1 ACETALDEHYDE IN CARCINOGENESIS OF THE UPPER DIGESTIVE TRACT Ethanol-related toxicity Ethanol (ethyl alcohol, CH3CH2OH) is a highly toxic compound when used in large amounts. Alcohol abuse has been linked to various disorders and conditions, including liver disease, pancreatic disorders, gastritis, cardiovascular diseases, mental disorders, depression and impairment of metabolism and malnutrition (Room et al. 2005). Ethanol can increase the permeability of the gut by modulating tight junctions (Basuroy et al. 2005, Bjarnason et al. 1984, Robinson et al. 1981). In addition, it can induce adverse changes in the gut microbiome, and these two factors combined can lead to the translocation of pathogenic microbes into the circulation (Parlesak et al. 2000, Rao 2009). This can also result in extra-intestinal organ involvement and an increase in inflammation. Although a clear association has been found between chronic alcohol consumption and carcinogenesis of the upper digestive tract, liver, colorectum and female breast, a debate exists concerning the mechanisms behind the carcinogenicity of ethanol. Multiple potential mechanisms have been described, including direct damage to mucosal cells (Bode et al. 1982), increased oxidative stress and lipid peroxidation (Niemelä et al. 1999), enhanced solubility of carcinogens (Wight and Ogden 1998), increased cell membrane permeability due to lipid dissolution (Squier et al. 2003), induction of detoxifying enzymes and activation of procarcinogens (Stickel et al. 2002), immunomodulation (Szabo 1999), an increase in oestrogen levels in women (Coutelle et al. 2004) and interference with folate and retinoic acid metabolism and synthesis (Giovannucci et al. 1995, Halsted et al. 2002, Liu et al. 2001a). Although these various harmful direct or indirect effects of ethanol exist, ethanol itself is not genotoxic (Ellahuene et al. 2012, Phillips and Jenkinson 2001). However, its first metabolite, ACH, is. 5.5.2 Acetaldehyde-related toxicity and carcinogenicity ACH (ethanal, CH3CHO) is a highly volatile, cytotoxic and mutagenic compound (Dellarco 1988). A carcinogenic effect has been shown in animals (Feron et al. 1982, Woutersen et al. 1986). Multiple epidemiological and biochemical studies have supported its carcinogenicity in humans (Boccia et al. 2009, Homann et al. 1997). Recently, ACH linked to alcohol abuse was ranked as a group I carcinogen by IARC (Secretan et al. 2009). This was largely due to evidence derived from animal experiments and particularly from epidemiologic studies, which have shown the strong association between the GI tract cancer risk and ALDH2 deficiency in humans. A small amount of ACH may be formed during threonine metabolism in the human 44 body, but the majority is derived from ethanol metabolism in the liver and gut (Lin and Greenberg 1954). However, the highest levels of ACH can be found in saliva due to microbial metabolism, and this might explain why ethanol-induced cancers are located in the upper digestive tract (Väkeväinen et al. 2000, Yokoyama et al. 2008). The mutagenic effect of ACH has been shown to occur at concentrations as low as 40– 100 µM, which can be found in saliva after moderate alcohol drinking (Brooks and Theruvathu 2005, Homann et al. 1997, Lachenmeier and Monakhova 2011, Linderborg et al. 2011, Seitz and Stickel 2007). In addition to its presence in the human body, it is widely present in foodstuffs, beverages, industrial processes and the environment (Feron et al. 1991, Salaspuro 2009). When consumed, the oral cavity and oesophagus are the first sites in direct contact with exogenous ACH. ACH is the most abundant carcinogen in tobacco smoke and it dissolves in saliva during smoking (Salaspuro and Salaspuro 2004, Hoffmann et al. 2001). The ACH content of alcoholic and nonalcoholic beverages is dependent on the manufacturing process: fermentation, distillation and preservation. The highest ACH content has been detected in calvados, sherry and fruit spirits (Boffetta et al. 2011, Lachenmeier et al. 2009, Linderborg et al. 2008). Multiple direct or indirect genotoxic effects related to ACH have been described (Figure 5). ACH interferes with DNA synthesis and repair (Espina et al. 1988, Garro et al. 1986). Cytogenetic changes observed in vitro include sister chromatid changes and gross chromosomal aberrations (Maffei et al. 2000, Maffei et al. 2002, Obe et al. 1986). ACH forms stable DNA adducts, and significant levels have been measured in multiple organs and conditions including oral pre-malignant and malignant lesions due to chronic alcohol abuse (Fang and Vaca 1995, 1997, Warnakulasuriya et al. 2008a). 2 The most abundant and best-studied stable ACH adduct is N -ethyl-2’-deoxyguanosine (N-EdG), which is found at damaging levels in the oral cavity within 4 to 6 hours of alcohol exposure in humans (Balbo et al. 2012). ACH adducts can further generate DNA-strand cross-links and cause DNA-strand breaks when repaired (Matsuda et al. 1998). ACH-related adduct formation has been shown to occur with lipid peroxidation products, such as malondialdehyde, as a result of oxidative stress due to ROS (Niemelä et al. 1999, Niemelä et al. 1995). 45 Figure 5. Schematic diagram of the major mechanisms of acetaldehyde-related mutagenesis. The main enzymes related to acetaldehyde metabolism are shown: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH) and cytochrome P450 2E1 (CYP 2E1) within the microsomal ethanol oxidising system (MEOS). 5.5.3 Aetiology and epidemiology of upper digestive tract cancers Oral (lip, oral cavity, oro- and hypopharynx) and oesophageal carcinomas are among the ten most common cancers globally (Ferlay et al. 2013). There is large geographic and demographic variation in the incidence worldwide. In Finland, approximately 300 new cases of oral and pharyngeal cancers with an annual incidence of ~7/100,000 and 200 new cases of oesophageal cancer with an annual incidence of ~3/100,000 are diagnosed every year among men (Finnish Cancer Registry). Among women, the numbers are lower: 200 new cases of oral and pharyngeal cancers and 40 new cases of oesophageal cancer are diagnosed in Finland every year (annual incidence of ~4 and ~1/100,000, respectively). In contrast, among the European Union countries, Hungary has the highest incidence of oral cancer (40/100,000) and the United Kingdom of oesophageal cancer (15/100,000) among men (Ferlay et al. 2013). Squamous cell carcinoma (SCC) is the most common histological subtype of oesophageal and oral cancer worldwide and the type mainly associated with ethanolrelated carcinogenesis (Scully and Bagan 2009, Steevens et al. 2010). However, the incidence of oesophageal adenocarcinoma has rapidly increased and now exceeds the incidence of oesophageal SCC (ESCC) in some Western countries, including Finland (Pohl and Welch 2005). Despite advances in surgical techniques, radiation and chemotherapy, mortality and morbidity rates remain high, with 5-year survival rates of only 40–50% and 15–25% for oral and oesophageal cancer, respectively (Enzinger and Mayer 2003, Warnakulasuriya 2009). This is mainly due to delayed diagnosis and 46 treatment. The incidence of oral and oesophageal cancer increases as a function of age. However, an increased incidence of oral cancer has been lately been noted among youths (van Monsjou et al. 2013). 5.5.3.1 Main risk factors Squamous cell carcinomas of the oral cavity and oesophagus have very similar risk factor profiles. Tobacco smoking and alcohol abuse are the major risk factors. Approximately 30% of oral cancers and 25% of oesophageal cancers may be attributed to the consumption of alcohol (Boffetta et al. 2006). Alcohol drinking and smoking have a synergistic effect on upper digestive tract carcinogenesis (Lee et al. 2007, Pelucchi et al. 2008). They both result in increased salivary ACH levels in vitro and in vivo (Homann et al. 1997, Salaspuro and Salaspuro 2004, Tillonen et al. 1999). The risk of carcinogenesis in the upper digestive tract is increased by poor oral health (Abnet et al. 2008, Guha et al. 2007, Sepehr et al. 2005, Velly et al. 1998, Wei et al. 2005). As stated above, additional support for the major role of alcohol abuse and ACH in cancer aetiology is provided by mutations in the genes responsible for ethanol metabolism (ADH1B, ADH1C, ADH2, ADH4, ALDH2, CYP2E1). These polymorphisms have been associated with a high incidence of cancers of the oesophagus, oral cavity, pharynx and larynx (Guo et al. 2008, Hashibe et al. 2006, Hashibe et al. 2008, McKay et al. 2011, Oze et al. 2009, Tanaka et al. 2010). Other important risk factors for oral cancer are a low socioeconomic status, nutritional deficiencies, ultraviolet and ionizing radiation, sexual behaviour and HPV infection (Scully and Bagan 2009). Chewing of betel quid increases the risk of both oral and oesophageal cancer, and a synergistic effect exists with tobacco smoking (Petti 2009, Wen et al. 2010). In addition, regular consumption of microbially fermented food products and beverages with a high ACH and ethanol content has been linked to the aetiology of upper digestive tract cancers (Lachenmeier and Sohnius 2008, Linderborg et al. 2008) A dysbiotic microbiome has been linked to inflammation and malignant transformation in the upper digestive tract (Hooper et al. 2009). Lower microbial richness was found in lesions showing dysplasia in the oesophagus (Yu et al. 2014). Specific Streptococcal and periodontopathogenic species have been frequently identified in oesophageal cancer lesions (Narikiyo et al. 2004). Bacteria produce metabolites that can modulate and damage the host genome (Schwabe and Jobin 2013). Oral carcinoma specimens showed similarities in their microbiome with certain combinations of aerobic and anaerobic bacteria and C. albicans (Nagy et al. 1998). Besides being a significant risk factor for cancer, smoking can alter the microbiome. The microbiome of the oral cavity has been found to significantly differ between 47 smokers and non-smokers (Morris et al. 2013). Adherence, growth and biofilm formation by S. aureus and C. albicans was enhanced after exposure to tobacco smoke (Kulkarni et al. 2012, Semlali et al. 2014). In addition to their role in the production of carcinogenic ACH, bacteria can activate carcinogenic nitrosamines of tobacco smoke (Ahn et al. 2012, Shapiro et al. 1991). 5.5.3.2 Candida and cancer The association of Candida with pre-malignant lesions and the potential cancerinducing role was already reported in the 1960s (Cawson 1969). More recently, multiple studies have reported an association between Candida and mucosal dysplasia (Barrett et al. 1998, McCullough et al. 2002, Nagy et al. 1998, O'Grady and Reade 1992, Rindum et al. 1994). Oesophageal carcinoma has been shown to be associated with candidosis (Scott and Jenkins 1982). Several case reports have demonstrated the association between CMC and oral and oesophageal carcinomas (Delsing et al. 2012, Rautemaa et al. 2007a, Rosa et al. 2008). In a Finnish patient population, the majority of the patients with autoimmune polyendocrinopathy-candidosis-ectodermal dystrophy (APECED) syndrome had CMC, and 10% of the patients above the age of 25 developed oral or oesophageal carcinoma (Rautemaa et al. 2007a). Multiple studies have shown that C. albicans isolated from oral cancer and APECED patients can produce substantial levels of ACH (Marttila et al. 2013a, Marttila et al. 2013b, Uittamo et al. 2009). High salivary ACH levels are associated with a high prevalence of Candida yeasts, mainly C. albicans (Tillonen et al. 1999). Carcinogenic nitrosamine production by Candida has been proposed as one possible mechanism underlying the malignant transformation, and to support this, Hsia et al. reported an increased nitrosation potential in strains isolated from pre-cancer lesions with more advanced dysplasia (Hsia et al. 1981, Krogh 1990). 48 6 AIMS OF THE STUDY The general aim of this study was to explore the ability of Candida yeasts to produce carcinogenic acetaldehyde (ACH) during the planktonic and biofilm modes of growth, and the effect of bacterial co-culture and metabolites on candidal growth, metabolism and the host response. The specific aims for this study were: I To determine the ability of Candida spp. to produce ACH from ethanol in the planktonic mode of growth in vitro and examine the effect of glucose, fructose and xylitol on ACH production solely or in combination with ethanol. II To examine the synergistic potential of bacteria and yeast to produce ACH and ethanol during the production of fermented milk mursik. To study this interplay, a simulated fermentation process was performed and the microbiota of the mursik starter cultures used in the fermentation process was identified. Starter cultures were collected from local families in western Kenya, an area with an unusually high incidence of oesophageal cancer and regular consumption of fermented food products. III To analyse the ability of C. albicans biofilms to produce ACH from ethanol and glucose in vitro. IV To explore the potential of D,L-2-hydroxyisocaproic acid (HICA), a Lactobacillus metabolite, to inhibit the growth and metabolism of C. albicans biofilms in vitro as well as its impact on the degree of inflammation and biofilm growth in vivo. 49 7 MATERIALS AND METHODS 7.1 STUDY DESIGN The experiments performed in this study can be divided into two main parts, as shown in Figures 6 and 7. In brief, the ability of planktonic Candida spp. to produce acetaldehyde (ACH) was first investigated (I,II). Secondly, planktonic starter cultures with a mixed bacteria-yeast flora were used to produce fermented milk. ACH and ethanol levels were measured during the fermentation process and members of the microbiota were identified (III). Thirdly, the effect of the Lactobacillus metabolite HICA and its various comparators on the metabolic activity, biomass and ultrastructure of C. albicans biofilms was explored using XTT and PicoGreen assays and scanning electron microscopy (SEM), respectively, in vitro (IV). The production of ACH by biofilms was measured using gas chromatography, and RT-qPCR was performed in order to analyse the transcriptional changes in genes contributing to ethanol and ACH metabolism during biofilm formation and HICA challenge (IV). Finally, the anti-biofilm and antiinflammatory activity of HICA was assessed in a C. albicans biofilm murine model in vivo (V). Figure 6. I, II, III). 50 Study design for the experiments with planktonic microbes (RT = room temperature; Figure 7. 7.2 7.2.1 Study design for the experiments with biofilms (IV,V). MATERIALS Candida strains and isolates A total of three reference strains and one clinical isolate of C. albicans and total of seven reference strains and 23 clinical isolates of non-albicans Candida (NAC) were used for this study (Table 4). Reference strains were obtained from the American Type Culture Collection (ATCC), the Culture Collection of the University of Gothenburg (CCUG) and the United Kingdom National External Quality Assessment Service (UKNEQAS), except for C. albicans SC5314 and 3153A reference strains, which were provided by Prof Gordon Ramage (University of Glasgow). Clinical isolates were obtained from isolate depositories of the Clinical Microbiology Laboratory of Helsinki University Central Hospital HUSLAB (T and HI- isolates) and the Institute of Dentistry, University of Helsinki (D and G isolates). Candida spp. were identified based on colony morphology on CHROMagar medium (CHROMagar, France) or API32C (Bio-merieux, France) assimilation tests. All isolates and strains were stored in milk-glycerine at -70 o C and plated at least twice on Sabouraud dextrose agar (SAB; Melford, UK or Lab M, o UK) and incubated under aerobic conditions at 37 C for 48 h before use to check purity and viability. 51 Species C. albicans Isolate no. ATCC 90029 SC5314 3153A HI2580 C. dubliniensis UK NEQAS 2/07 G29 G130 G161 G174 C. glabrata CCUG 32725 UK NEQAS 5/08 G212 G52 T1609 C. guilliermondii UK NEQAS 9/06 G66 G68 T1475 T1043 C. krusei ATCC 6258 D206B G65 T1336 T880 C. parapsilosis ATCC 22019 G95 G170 T1282 T1432 C. tropicalis ATCC 750 D213 G9 G22 T1011 Table 4. 7.2.2 I x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x II x Study III IV x x x V x x x x x x x x x x x x x x Summary of all Candida strains and clinical isolates used (n = 34). Reagents The different growth media, carbon substrates and antimicrobials used in the study are listed in Table 5. 52 Table 5. 7.2.2.1 Different growth media, substrates and antimicrobials used in the experiments. Starter cultures A total of eight starter cultures were used to study ACH and ethanol production during a simulated mursik milk fermentation process (III). Each starter culture was obtained from separate families belonging to the Kalenjin tribe in the Bomet area, Rift Valley Province, western Kenya by investigators from Tenwek Hospital (Bomet, Kenya). 7.2.2.2 Primers All primers used in the study are listed in Table 6. Primers used for RT-qPCR experiments were designed using Primer 3.0 Plus and were manufactured and produced by Eurofins MWG Operon (Eurofins MWG Operon, Germany; Untergasser et al. 2007). CaRIP1 was used as a reference gene for RT-qPCR experiments (Nailis et al. 2006). The PCR amplification efficiencies for all primers were optimised prior to the analysis. ITS1 and NL4 primers spanning the ITS1-5.8S, rRNA-ITS2 and 26S rRNA regions were used for the identification of yeast isolates and PA and PH primers 53 spanning the 16S rRNA were used for the identification of bacterial isolates (III; Hutson et al. 1993, Kurtzman and Robnett 1997, White 1990). Table 6. 7.2.2.3 Primers used in the experiments. Antibodies The antibodies used are listed in Table 7 (V). Table 7. 54 Primary polyclonal antibodies used for immunohistochemistry (V). 7.3 METHODS 7.3.1 7.3.1.1 Candida growth conditions Planktonic cells o Candida yeasts were incubated on SAB plates under aerobic conditions at 37 C for 48 h (I,II). One to two colonies were suspended in phosphate buffered saline (PBS, 6 M) 7 and the inoculum was adjusted spectrophotometrically to correspond to 1.0 x 10 colony forming units per millilitre (CFU/ml). The counts were checked by dilution plating. 7.3.1.2 Biofilm formation C. albicans reference strains 3153A, ATCC 90029 and SC5314 were used to study the biofilm mode of growth. The ability of each strain to produce ACH and their susceptibility to HICA and caspofungin were evaluated in the pilot experiment, and the most representative strain was selected for the final experiments (Figure 7; IV,V). One colony was suspended into 20 ml of yeast peptone dextrose (YPD) broth and o grown overnight at 37 C with continuous shaking. Cells were harvested and washed twice with PBS, and were then re-suspended in RPMI-1640 medium (#6504) and buffered to pH 7.4 with morpholinepropanesulfonic acid (MOPS) (Oxoid Ltd., UK). The 6 cell density was measured using a haemocytometer and adjusted to 1.0 x 10 CFU/ml 7 (study IV) or 1.0 x 10 CFU/ml (V) to produce the standardised biofilm inoculum. Cell counts were verified by dilution plating. 7.3.1.2.1 In vitro biofilm C. albicans biofilms were grown in vitro on Thermanox® coverslips (Thermoscientific, USA) in RPMI #6504 medium at pH 7.4 in static 24-well plates (Corning Costar, USA) o under aerobic conditions at 37 C. After 4, 24 and 48 h of growth, the biofilms were exposed to 5% (w/v) D,L-2-hydroxyisocaproic acid (HICA) and the comparators 10 mg/l caspofungin, 5% (w/v) leucine, 0.05% (v/v; 11 mM) ethanol, PBS or RPMI-1640 #6504 for 24 h at pH 5.2 or pH 7.4. Substrates were dissolved in RPMI 1640 #6504, except for the ethanol treatment, which was dissolved in RPMI #1383 without D-glucose or sodium bicarbonate and then adjusted to pH 5.2 or pH 7.4. 55 7.3.1.2.2 Biofilm susceptibility to D,L-2-hydroxyisocaproic acid (HICA) To test the susceptibility of C. albicans biofilm to HICA in vitro, a previously described and standardised method was used (Pierce et al. 2008). Biofilms of three different strains were pre-grown on 96-well plates in RPMI-1640 (#6504) at pH 7.4 under o aerobic conditions at 37 C. After 24 h of growth, biofilms were exposed to HICA by injecting 100 µl of the two-fold dilution series (0.039–5%; v/v) into the well. Caspofungin (10 mg/l) and RPMI were used as controls. The measurements were performed in sextuplicate for each concentration. After treatment, the reduction in metabolic activity was measured using the XTT assay, as described below. 7.3.1.2.3 In vivo biofilm 7 A volume of 100 µL of 10 CFU/ml C. albicans inoculum was injected percutaneously 6 into a diffusion chamber underneath the dorsal skin of a mouse (10 CFU/mouse; V). The inoculum was well mixed by vortexing before injection. The counts were rechecked after injection by dilution plating on SAB. The viability of the biofilms formed in vivo was checked by culture at the end of the experiment after treatment with HICA, caspofungin or PBS. 7.3.2 Fermentation using starter cultures The fermentation experiments simulated the protocol used by local population in western Kenya to produce mursik milk (III). Finnish whole milk (Arla-Ingman, Finland) was used in the experiments. Pilot fermentation was performed with non-boiled milk and 0.1 ml of starter culture was mixed with 9.9 ml of the milk in a glass vial, sealed o and left to ferment for 0,1, 4, and 6 days at RT (22–25 C). For the final experiment, the milk was first briefly boiled as suggested in the protocol and then allowed to cool before mixing with the starter culture in similar proportions to those used in the pilot experiment. The vials were sealed airtight and left to ferment for 0, 24, 48 hours and 4, 7 and 14 days at RT. The pilot fermentation was carried out once with three parallel samples. The final fermentation experiment was carried out twice and the pH of the milk was measured at each time point. 56 7.3.3 7.3.3.1 Isolation and identification of the microbiota in starter cultures Assessment of microbial growth and isolation of microorganisms Microbial growth (CFU/ml) was measured during fermentation at the time points 0, 24, 48 hours and 4, 7, 14 days by dilution plating on lysed blood agar (BA). Selective and non-selective media under aerobic and anaerobic conditions were used to determine the microbial flora in starter cultures. Fastidious anaerobe agar (FAA) supplemented with 5% v/v horse blood was used to determine the total number of cultivable bacteria. BA was used to enumerate the total number of aerobic bacteria. Neomycin-vancomycin blood agar (NV; blood agar and neomycin sulphate) supplemented with 7.5 µg/ml vancomycin, 0.5 µg/ml menadione and 5% v/v sheep blood was used to determine the number of anaerobic Gram-negative bacteria. Aerobic Gram-negative fermentative rods were isolated using cysteine-, lactose- and electrolyte-deficient agar (CLED; C.L.E.D. medium). The growth of yeasts was determined using SAB. The BA, CLED and SAB plates were incubated under aerobic o conditions and the FAA and NV plates under anaerobic conditions at 37 C for 48 h or 5 days, respectively. After incubation, multiple subcultures of bacteria and yeast colonies were prepared. 16S or 18S PCR gene sequencing was used to detect bacterial and fungal isolates from these pure cultures. Yeast isolates were also identified by API 32C auxanographic strips (bioMerieux, France) following the manufacturer’s protocol. 7.3.3.2 DNA extraction Before gene sequencing, DNA was extracted from the bacterial and fungal pure cultures (III). The MycXtra DNA extraction kit was used following the manufacturer’s instructions to extract fungal DNA (Myconostica, UK). Bacterial DNA was initially extracted using Chelex-100 beads (Walsh et al. 1991). If these two protocols were unsuccessful, a modified cetyl trimethyl ammonium bromide (CTAB) method was performed (Wilson 1987). Briefly, HCl-washed beads (diameter 425-600 µm, Sigma G8772, Sigma-Aldrich, USA) were mixed in a bead tube together with pre-heated extraction buffer containing 2% CTAB and a few colonies from the pure culture. Suspensions were homogenized using a Fastrep-24 instrument (MP Biomedical, USA). The vortex and heating steps were repeated twice. Supernatants were collected into new tubes after centrifugation at o 13 400 rpm for 2 min and followed by RNase treatment at 37 C for 30 min. 57 Chloroform-isoamyl alcohol was added, mixed well and centrifuged at 13 400 rpm for 2 min. The RNase and chloroform-isoamyl treatments were repeated once. The aqueous phase was collected and mixed with isopropanol, followed by centrifugation at 13 400 rpm for 2 min. The pellets were washed with ethanol and air-dried. Before storage, the pellets were re-suspended in 50 µl of dH2O. 7.3.3.3 16S and 18S sequencing and data analysis ITS1 and NL4 primers were used to identify yeast isolates from fungal DNA (Table 6; III). PA and PH primers were used to identify bacterial isolates from bacterial DNA (Table 6; III). Sequencing was conducted using a 16 capillary ABI Prism 3100 Genetic Analyzer (Thermo Fisher Scientific, USA) and performed either at the University of Manchester DNA Sequencing Facility or Beckman Coulter Genomics sequencing service (Essex, UK). The sequences were aligned and matched to sequences stored in GenBank using the NCBI-BLASTn matching tool (Altschul et al. 1990, Nilsson et al. 2006). 7.3.4 Gas chromatography A Perkin Elmer Autosystem Gas Chromatograph and Headspace Sampler HS 40XL (Perkin Elmer, USA) (I,II,III) or a Varian CP-3800 and CombiPal autosampler (Varian Medical Systems, USA) (IV) were used to measure ACH and ethanol concentrations. Chromatographs were equipped with Zebron WaxPlus or Supelco columns (CTC Analytics GmbH, Germany or Sigma-Aldrich, USA). Peaks were detected by flame ionisation. 7.3.4.1 Planktonic cells and biofilms 7 In studies using planktonic cultures of Candida spp., 350 µl (II) or 400 µl (I) of 1.0 x 10 CFU/ml yeast suspension was transferred into a gas chromatography vial. Thereafter, 50 µl of PBS buffer containing ethanol (I,II) and 50 µl of PBS containing D-glucose, Dfructose or xylitol (II) was added and the vial was immediately sealed airtight. The ability of Candida to produce ACH solely from D-glucose, D-fructose or xylitol was measured by adding 50 µl of one of these substrates and 50 µl of PBS into the vial o with yeast suspension (II). Vials were incubated at 37 C under aerobic conditions for 30 min. Metabolism was stopped by injecting 50 µl of 6 M PCA through the rubber septum of the vial. To measure the baseline and artefactual ACH, 50 µl of PCA was added to the vials immediately after adding the substrates and before incubation at o 37 C. 58 The ability of three different C. albicans strains to produce ACH as biofilms was tested and compared with planktonic cells in a pilot experiment. Biofilm was grown in RPMIo 1640 medium (#6504) for 24 h at 37 C, pH 7.4. The production of ACH by each strain as planktonic cells was tested in parallel and the inoculum size was adjusted to correspond the initial biofilm inoculum. In the pilot experiment, the biofilms and planktonic cells were incubated with similar substrates to those used with planktonic cultures above, except that fructose was not used. In the final biofilm experiment, ACH production by pre-grown (4, 24, 48 h) biofilms exposed to 5% HICA, 11 mM ethanol, 10 mg/l caspofungin or RPMI for 24 h was measured (IV). In both pilot and final experiments with C. albicans biofilms, the biofilms were washed with PBS before ACH analysis and transferred to 20 ml glass vials containing 1 ml of ethanol, D-glucose or PBS. In the pilot experiment, the effect of xylitol on ACH production from ethanol was tested by adding xylitol (1 ml) or ethanol (1 ml) to the vial separately or in combination (500 µl + 500 µl). The vials were sealed with silicon o caps airtight and incubated under aerobic conditions at 37 C for 30 min. The reaction was stopped by 100 µl of 6 M PCA. To measure the artefactual ACH production, 100 µl of PCA was injected immediately after transferring the biofilm to the vials and prior to adding the substrates. The final concentrations in incubations were 11 mM (I,IV) or 12 mM (II) for ethanol and 100 mM (I,IV) or 110 mM (II) for sugars. 7.3.4.2 Starter cultures and fermentation Gas chromatography was performed at each time point of the pilot fermentation (0, 1, 4 or 6 days). In the final fermentation experiment, ethanol and ACH levels were measured at the first three time points (0, 24 and 48 hours), which were selected based on the microbial growth curves. For the ACH and ethanol measurements, 500 µl aliquots of the suspension, including the milk and starter culture, were pipetted into 20 ml gas chromatography vials, closed airtight and left to ferment at RT. To measure artefactual ACH and ethanol production, vials including the milk alone were fermented and analysed in parallel to actual samples at each time point. The fermentation process was stopped by injecting 50 µl of 6 M PCA through the rubber septum of the vial. Artefactual concentrations of ACH and ethanol were subtracted as background. In the final and pilot experiments, three independent and parallel samples were used. The final experiments were performed twice. To determine the microbial source for major ACH production during fermentation, a second pilot experiment was performed in parallel to isolation of the microbial flora. 59 The starter culture with the highest ACH content measured in the pilot fermentation was selected for the experiment. A volume of 0.1 ml of starter culture was added onto non-selective (FAA or BA) or selective (SAB) growth media and incubated as described above. After culturing, 3 ml of PBS was injected onto each growth media, colonies were gently scrubbed into the liquid, and this was then transferred into a sterile tube. The tube was homogenised by vortexing and 400 µl of this suspension was used for ACH analysis. The suspension was incubated with 50 µl of 100 mM o glucose or 11 mM ethanol for 30 min at 37 C and the reaction stopped with 50 µl of PCA. The baseline and artefactual ACH production was measured as earlier described in the ACH experiments with planktonic cultures. 7.3.5 Analysis of Adh activity A fluorometric approach was applied to study the Adh enzyme activity in Candida yeasts as previously described (Kurkivuori et al. 2007). Planktonic cells were grown as described earlier and then lysed with glass beads (diameter 1.0 mm) by vortexing in 5 x 1 min cycles in the presence of a protease inhibitor mixture (#P8340; SigmaAldrich, USA). Before each cycle, samples were cooled on ice. Cell lysates were centrifuged for 5 min at 2,900 g (Hettich EBA 20, Hettich, UK). The supernatants were o collected and further centrifuged at 139,700 g for 65 min at 4 C (Beckman Optima Le80k Ultracentrifuge, Beckman Coulter, USA). The final supernatant was used for the enzyme analysis. Cytosolic Adh activity was determined by measuring fluorescence (excitation 340 nm, emission 440 nm) after the addition of ethanol or ethanol and o xylitol (final concentration 100 mM) and NAD (final concentration 2.5 mM) at 37 C in 0.1 M glycine buffer (pH 9.6). Ethanol was used at concentrations ranging from 0.68 to 2174 mM. Adh activity was detected using a Tecan Safire microplate detection system and Magellan software ver. 6.05 (Tecan Trading AG, Switzerland). Lineweaver Burk plots and GraphPad Prism software ver. 5.0 (GraphPad, USA) were used to determine Vmax and Km values for the Adh enzyme. 7.3.6 7.3.6.1 Evaluation of Candida albicans biofilm formation XTT reduction assay The 2,3-bis-(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) reduction assay was performed to measure the metabolic activity of C. albicans biofilms (IV). Before analysis, biofilms were washed thoroughly with sterile PBS. Biofilms grown on coverslips were transferred to fresh 24-well plates after the wash (Corning Costar, UK). Then, 100 or 200 µl of saturated XTT/1 µM menadione solution was added to the 96- or 24-well plate. The plates were covered with aluminium foil 60 o and incubated for 2 h at 37 C. After incubation, 100 µl of XTT supernatant was pipetted into a fresh 96-well plate (Corning Costar, UK) and the colorimetric changes were recorded spectrophotometrically (BMG Labtech, UK) at 492 nm. 7.3.6.2 PicoGreen assay Fluorescent nucleic acid Quant-iT PicoGreen® reagent (Molecular Probes, USA) was used to quantify double stranded DNA (dsDNA) in C. albicans biofilms (IV). The amount of dsDNA has been shown to correlate with the number of viable cells, thus describing the biomass of a biofilm (Marstorp and Witter 1999). DNA was extracted from the biofilms using a modified CTAB method as described above. Extracted DNA and PicoGreen® reagent were thoroughly mixed in the well and analysed fluorometrically at 492 nm (BMG Labtech, UK). The lambda DNA within the Quant-iT kit was used for the construction of the standard curve (concentration range 40–500 ng/ml) according to the manufacturer’s instructions and pipetted alongside samples (100 µl per well; Corning Costar, UK). 7.3.6.3 Scanning electron microscopy (SEM) Biofilms were pre-grown in RPMI as previously described for 24 h and then exposed to 5% HICA or RPMI (control) for 24h at pH 5.2 and pH 7.4 (IV). The biofilms were washed once with PBS and then placed in a fixative overnight as previously described (Erlandsen et al. 2004). After fixation, biofilms were rinsed in 0.1 M phosphate buffer and air-dried. The samples were coated with gold/palladium (40/60% ratio) and observed under a scanning electron microscope (Leo 435 VP) in high vacuum mode at 10 kV. 7.3.7 7.3.7.1 Gene expression analysis RNA extraction In vitro biofilms used for the gene expression analysis were flash-frozen in liquid o nitrogen post-exposure to HICA and comparators and stored at -80 C until RNA extraction (IV). Biofilms were first detached by vortexing and then homogenized using glass beads (425–600 µm in diameter; Sigma-Aldrich, USA) and a FastPrep-24 Instrument (MP Biomedical, USA). The samples were centrifuged at RT for 1 min at 12,000 g after the homogenization step. RNA was extracted using the Isolate I RNA Mini kit according to the manufacturer’s instructions and genomic DNA was removed using Ambion DNA-free DNase (Life Technologies, UK). The amount and quality of RNA 61 was assessed spectrophotometrically (A260). The purity was further assessed by RTo qPCR and gel electrophoresis. RNA was stored at -80 C for further use. 7.3.7.2 cDNA synthesis cDNA synthesis by reverse transcription was performed using an AffinityScript qPCR cDNA synthesis kit (Agilent, UK) according to the manufacturer’s protocol (IV). Six microlitres of RNA (10 ng/µl) was used as a template. In no-RT controls, reverse transcriptase was replaced by dH2O. 7.3.7.3 RT-qPCR analysis RT-qPCR reactions were conducted using a Brilliant II SYBR Green 2-step kit (Agilent, UK) and as described in the manual (IV). The reaction mastermix was composed of 6.25 µl of SYBR Green fluorescent probe, 1 µl of forward (F) primer, 1 µl of reverse primer, 2 µl of cDNA and 2.25 µl DNA/RNA-free molecular grade water (primers listed in Table 6). RT-qPCR was performed with a Stratagene MX3005P instrument (Agilent, UK). 7.3.8 7.3.8.1 In vivo biofilm murine model Ethics statement All mice in the study were handled in strict accordance with good animal practice and conducted under an ethically reviewed license authorised by the Secretary of the State at the University of Manchester, UK (license no. PPL 40/3101) (V). 7.3.8.2 Diffusion chamber model A previously published chamber model was modified for the in vivo biofilm experiment (Rajendran et al. 2011) (V). The biofilm diffusion chamber was structurally based on a chamber kit (Millipore, Watford, UK). The chamber was made of a semipermeable Durapore® membrane with a pore size of 0.45 µm fixed to a Plexiglas® ring. A non-permeable silicon sheet was fixed onto the opposite side to close the chamber. A total of 24 male CD1 mice weighing 21–24 g were included. Mice were allowed to acclimatise before surgery for seven days. The surgical implantation of the chambers was performed under isoflurane and xylocaine anaesthesia. The dorsal flank of each mouse was shaved and a 2-cm incision was made. The diffusion chamber was implanted subcutaneously, so that the semipermeable membrane faced the dorsal 62 flank of each mouse shaved and the non-permeable silicon sheet faced the skin. The wound was closed with non-absorbable braided silk sutures (Ethicon, USA) and meloxicam (3 mg/kg) was administered intraperitoneally daily for 3 days post-surgery. One mouse was lost in surgery (n = 23). Mice were divided into two main groups: biofilm (n = 15) and no-biofilm (n = 8). The chambers in the biofilm group were 6 injected percutaneously with C. albicans inoculum under isoflurane anaesthesia (10 CFU/mouse). The mice were allowed to recover for 5 days. A robust C. albicans biofilm formed inside the chamber during the infection period. After five days of infection, biofilms were treated for 12 h with 5% HICA (n = 8), and 10 mg/l caspofungin (n = 3) or PBS (n = 4) were used as control treatments. No-biofilm chambers were similarly treated with HICA (n = 2), caspofungin (n = 3) or PBS (n = 3). The mice were euthanised post-treatment with an overdose of isoflurane. Chambers were collected and biofilms detached and weighed. Tissues around the chambers were dissected and embedded into 10% formaldehyde for storage and further analysis. 7.3.9 Immunohistochemistry A previously described method was adapted for the immunohistochemistry and semiquantitative analyses (Kuula et al. 2009) (V). Tissue sections from mice were embedded in paraffin. Paraffin-embedded specimens were cut, deparaffinised, pretreated with 0.4% pepsin, and the endogenous peroxidase activity was blocked in H2O2/methanol solution. Staining was performed with polyclonal Vectastain Elite rabbit or goat ABC kits (Vector Laboratories, Burlingame, CA, USA). Samples were blocked with goat or rabbit normal serum in 2% bovine serum albumin and incubated with the following polyclonal primary antibodies: MMP-8, MMP-9, MPO, NE, IL1β, TNFα and Del-1 (Table 7). The control sections were incubated with non-immune rabbit or goat serum. The studied inflammatory markers were visualized with a biotinylated anti-rabbit or anti-goat secondary antibody and avidin-biotin enzyme complex. 3-Amino-9-ethyl-carbazole was used as a chromogen and Mayer’s hematoxylin (Histolab Products AB, Sweden) as a counterstain. All sections were also stained with hematoxylin and eosin (H&E) for routine histopathology. Slides were mounted with Dako glycergel (Dako corp., USA). The immunohistochemical staining was evaluated under an Olympus BX61 light microscope and representative images were taken using an Olympus DP50 camera attached to the microscope and AnalySIS software (AnalySIS ver. 3.2, Soft Imaging System GmbH, Germany). The intensity of staining was semiquantified and graded as no staining, mild, moderate or strong staining. The semiquantitative analyses were reconfirmed blindly by a second evaluator and a trained pathologist examined the basic histopathology without information on the groupings. Distributions of staining 63 intensities within groups were visualised using GraphPad Prism ver. 5.0 software (GraphPad Software Inc., USA). 7.3.10 Statistical analysis PASW statistics ver. 15.0 - 21.0 (IBM, USA) and Graphpad Prism software ver. 5.0 (GraphPad Software Inc., USA) were used for statistical analyses in all studies. Univariate analysis of variance (ANOVA) or a generalised estimating equations (GEE) model was used for statistical comparisons (I, II, IV and V). Relative gene expressions were statistically compared with a pair-wise fixed re-allocation test within REST 2009 ver. 1.0 software (Qiagen, USA) (Pfaffl et al. 2002) and basal transcriptions of each -ΔCt gene relative to the reference gene RIP1 were evaluated using equation 2 (ΔCt=Cttreatment-Ctreference), and these levels were used to calculate correlations (IV). Spearman’s rho (rs) with a 95% confidence interval was used to calculate correlations (I, II, III and IV). A p-value less than 0.05 was considered statistically significant. 64 8 RESULTS 8.1 PRODUCTION OF ACETALDEHYDE AND ETHANOL BY CANDIDA YEASTS IN VITRO This section summarises the results from all in vitro experiments, in which the ability of Candida yeasts to produce acetaldehyde (ACH) as planktonic mono- or mixed cultures or as biofilms was investigated (I, II, III, IV). ACH production is described as high (>100 µM), moderate (40–100 µM) or low (<40 µM). All measurements with planktonic monocultures and biofilms were performed after 30 min incubation with o substrate at 37 C. The ability of starter culture with a mixed planktonic bacteria-yeast flora to produce ACH and ethanol was studied in a simulated fermentation experiment that was carried out at room temperature (RT). 8.1.1 8.1.1.1 Planktonic Candida albicans and non-albicans Candida cultures Acetaldehyde production in ethanol incubation All Candida isolates produced moderate or high levels of ACH from ethanol in vitro. Marked variation was observed between and within species (Figure 8; I, II). C. albicans and three NAC species, including C. parapsilosis, C. tropicalis and C. glabrata, produced over 200 µM of ACH from ethanol. C. parapsilosis was the highest producer (258.9 ± 48.6 µM). ACH production by C. guilliermondii and C. dubliniensis was lower, but high levels were still detected (177.2 ± 62.9 µM and 165.0 ± 53.1 µM, respectively). Moderate levels were only measured for C. krusei (56.0 ± 12.0 µM). 65 Figure 8. Acetaldehyde production by planktonic Candida spp. when incubated for 30 min at 37 C with ethanol, ethanol + xylitol, ethanol + glucose or glucose only, and ethanol + fructose or fructose only. The strains and isolates used are presented in the Material and Methods section (Table 4). Means (± SD) are shown. o 8.1.1.2 Acetaldehyde production in glucose, fructose or xylitol incubation or in co-incubation with ethanol Major differences were observed in the ability of C. albicans and NAC species to produce ACH when incubated with glucose or fructose (Figure 8; I,II). None of the isolates were able to produce high levels. Moderate levels (40–100 µM) were mostly produced by C. glabrata: 89.9 ± 18.8 µM in glucose and 94.2 ± 8.9 µM in fructose incubation. One of the two C. albicans isolates produced moderate levels from glucose. Almost no ACH was detected when Candida isolates were incubated with xylitol alone (<1.8 µM). When glucose or fructose was co-incubated with ethanol, C. glabrata was the only species that showed increased ACH production compared to incubation with ethanol only (375.4 ± 60.7 µM vs. 220.5 ± 79.7 µM, p < 0.001). For other species, glucose-ethanol or fructose-ethanol co-incubation resulted in a decrease in ACH production when compared to incubation with ethanol alone (mean 23% and 29%, respectively). This change was not significant (p = ns). However, coincubation of ethanol and xylitol significantly reduced ACH production by a mean of 84% compared to incubation with ethanol alone in all species (p < 0.001). 66 8.1.1.3 Adh activity Enzyme kinetics were investigated for Adh enzymes of three different Candida species, which were chosen to represent the highest (C. glabrata CCUG 32725), moderate (C. albicans ATCC 90029) and lowest (C. krusei ATCC 6258) ACH producers -1 (II). C. glabrata Adh showed the highest activity (Vmax = 4.5 s , Km = 2.8 mM). This was -1 followed by C. albicans Adh (Vmax = 3.4 s , Km = 0.2 mM). Adh with low activity was -1 recorded for C. krusei (Vmax = 1.7 s , Km = 0.1 mM). Xylitol (100 mM) reduced the enzyme activity in C. glabrata by 61–66% when co-incubated with 11 or 110 mM ethanol. In C. albicans, the reduction in activity was 100%. No reduction was observed in C. krusei. 8.1.2 Mixed bacteria/yeast starter culture during fermentation The potential of a mixed bacteria/yeast culture to produce ACH was examined in a simulated fermentation using mursik starter cultures. The first two pilot experiments were carried out to test the potential ability of each starter culture (n = 8) and the selected members of the starter culture microbiota to produce ACH and ethanol. Starter cultures were mixed with whole milk and left to ferment at room temperature. The microbiota of the starter cultures was identified. The changes in pH, microbial counts, ACH and ethanol content were recorded during the final fermentation process. 8.1.2.1 Pilot experiments Figure 9. Results from two pilot experiments. (A) Each milk starter culture (n = 8) was mixed with whole milk and left to ferment at room temperature for 6 d. The acetaldehyde and ethanol content was measured at four time points during the fermentation. (B) Acetaldehyde production by an anaerobic and aerobic bacterial flora and yeast. Selective and non-selective media were used for isolation, as described in the Materials and Methods section. The colonies were scraped off the media into the liquid and incubated with ethanol or glucose for 30 min at 37 oC. Means (± SD) are shown. 67 The pilot fermentation demonstrated that significant ACH and ethanol production occurs during fermentation at RT (Figure 9A). However, variation was observed in the ability of each mursik starter culture to produce ethanol or ACH. The highest mean ACH and ethanol levels were reached at 6 d (324.6 ± 295.3 µM and 47.5 ± 12.6 mM, respectively). A second pilot was carried out in parallel to the identification of the microbial flora of each starter culture. Microbial colonies on the selective and nonselective media belonging to the starter culture with highest ACH and ethanol levels in the previous experiment were tested for their ability to produce ACH. Moderate or high production of ACH was only detected when plates selective for yeasts or bacterial aerobic flora were incubated with ethanol or glucose (Figure 9B). Yeasts produced the highest levels of ACH in both ethanol and glucose incubations (130.4 ± 47.8 µM and 115.8 ± 15.6 µM, respectively). 8.1.2.2 Distribution of yeast and bacterial species in starter cultures Figure 10. Microbial distribution and number of species in each starter culture (n = 8). Yeasts were isolated from each starter culture. Their proportion of the total microbial count (CFU/ml) varied considerably (Figure 10). Candida yeasts were isolated from seven of the total of eight starter cultures, C. krusei being the most common (5/8 starter cultures). Other Candida species included C. kefyr and C. sphaerica. Saccharomyces yeast was identified in one of the eight starter cultures. The bacterial 68 flora was dominated by Lactobacillus species. L. kefiri was the most frequently isolated species (6/8 starter cultures). Furthermore, L. kefiri was commonly (5/8 milks) found in combination with C. krusei. Other bacterial species were identified, but their prevalence was lower. 8.1.2.3 Changes in microbial counts and pH during fermentation An exponential increase was detected in microbial counts during the fermentation. The counts first increased from the initial mean of 6.6 log10 CFU/ml to the peak value of 10.4 log10 CFU/ml at 48 h, and then decreased slightly to 9.5 log10 CFU/ml at 14 d. During the 14 d fermentation, the pH declined in a linear fashion from 6.6 to 3.5. No significant variation in pH or microbial counts was detected between starter cultures. 8.1.2.4 Acetaldehyde and ethanol production during fermentation and correlation with microbiota ACH levels ranging from zero to 1809 µM were measured during fermentation. In general, ACH and ethanol levels were higher and increased quicker compared to pilots, and this may be due to the use of boiled whole milk as specified in the protocol. Seven of the eight starter cultures produced high levels during first 24 h of fermentation. At the 48 h time point, four milks reached an ACH content of over 1000 µM, with a range of 1150–1809 µM. High ethanol levels (>20 mM) were mostly detected at 48 h. The highest ethanol levels were produced by the same four starter cultures that also showed high ACH production (mean 79 mM, range 62–106 mM at 48 h). There was a significant correlation between ACH and ethanol production (rs = 0.88, p < 0.001). The microbial composition correlated with high ACH production. The four milks that produced high ACH levels also had similar combinations of yeast and lactobacilli, mainly C. krusei and L. kefiri (milk no. 1–4; Figure 10). The prevalence of other bacterial species correlated with low production of ACH. 8.1.3 8.1.3.1 Candida albicans biofilms Pilot experiments All three strains produced significantly higher levels of ACH from ethanol as a biofilm (mean range 113.4–261.4 µM) compared to planktonic cultures (mean range 50.5– 71.3 µM), as demonstrated in Figure 11. ACH production by biofilms in ethanol incubation was strain-dependent. Strain 3153A produced the highest levels of ACH 69 (261.4 ± 10.5 µM) and ATCC 90029 the lowest (113.4 ± 4.9 µM). However, SC5314 was the only strain to produce moderate or high levels of ACH in both ethanol and glucose incubations as a biofilm (164.1 ± 4.0 µM and 61.7 ± 2.8 µM, respectively). Xylitol coincubation with ethanol decreased the levels of ACH compared to incubation with ethanol alone, and the reduction was significant for biofilms (p = 0.022; Figure 11). Based on these results, strain SC5314 was chosen for further analysis (IV,V). Figure 11. The ability of three different C. albicans strains to produce acetaldehyde from 11 mM ethanol and 100 mM glucose was investigated in a pilot experiment. Cells were pre-grown in YPD and counts were standardised (106 CFU/ml). Biofilms were allowed to form for 24 h in RPMI. The effect of xylitol on ethanol oxidation was measured in co-incubation with ethanol, and statistically significant differences are presented compared to incubation in ethanol alone (* p < 0.05). Means (± SD) are shown. 8.1.3.2 Acetaldehyde production from ethanol and glucose at an acidic and a neutral pH All C. albicans SC5314 biofilms produced moderate or high levels of ACH in ethanol incubation at both test pH values (Figure 12; mean range 49–135 µM at pH 5.2 and 40–130 µM at pH 7.4). The highest levels of ACH in ethanol incubation were produced by biofilms grown in RPMI at both pH values: at pH 5.2 the peak ACH values were detected for biofilms pre-grown for 24 h and at pH 7.4 for biofilms pre-grown for 48 h (mean ± SEM: 135.2 ± 5.7 µM and 130.3 ± 12.3 µM). Biofilms that were pre-grown for 24 h and exposed to ethanol showed similarly high levels at the acidic pH (120.0 ± 12.7 µM). When biofilms were incubated with glucose, ACH levels were markedly lower compared to ethanol incubation (Figure 12). Biofilms produced more ACH at the neutral pH compared to the acidic pH (range: mean 0–54 µM at pH 7.4 and mean 0– 41 µM at pH 5.2). Moderate levels were only produced by control biofilms pre-grown for 48 h at neutral pH (53.8 ± 1.9 µM); otherwise, levels remained low. 70 Figure 12. Acetaldehyde production from (A) ethanol or (B) glucose by C. albicans SC5314 biofilms pre-grown for 4, 24 or 48 h in RPMI and then exposed for 24 h to HICA, ethanol and caspofungin or RPMI (control) at pH 5.2 or 7.4. Means (± SEM) are shown. 8.2 8.2.1 INHIBITORY EFFECT OF D,L-2-HYDROXYISOCAPROIC ACID (HICA) ON CANDIDA ALBICANS BIOFILM FORMATION AND ACETALDEHYDE METABOLISM IN VITRO Pilot experiment - HICA susceptibility The susceptibility of C. albicans biofilms to HICA was tested using a concentration range of 0.039–5% (w/v) and an antifungal control (caspofungin 10 mg/l). Three reference strains were tested and HICA showed efficacy against all three strains (Figure 13). No metabolic activity was detected for any of the three strains after exposure to 5% (w/v) HICA. A major decrease in metabolic activity occurred when the concentration was increased from 0.625% to 1.25%, and only 6–23% of the metabolic activity remained compared to the control at the concentration of 1.25%. There was considerable variation between strains in susceptibility to HICA and the caspofungin control. Caspofungin showed no efficacy against the strain SC5314; moreover, paradoxical growth was observed. In contrast, only 34% of metabolic activity remained for 3153A strain after exposure to caspofungin. In addition, no reduction in metabolic activity was shown for SC5314 in the concentration range of 0.039– 0.3125%, but 3153A retained only 56–65% of its metabolic activity in a similar range. 71 Figure 13. Percentage metabolic activity of mature (24 h) C. albicans biofilms formed by three different strains (3153A, ATCC 90029 and SC5314) after 24 h HICA challenge relative to a control biofilm in RPMI. To test the susceptibility, a concentration range of 0.039–5% (w/v) was used (HICA diluted to RPMI medium at pH 5.2). Caspofungin, RPMI only and biofilm+RPMI controls were included. Means (± SEM) are shown. 8.2.2 Effect of HICA on metabolic activity, biomass and ultrastructure of biofilms A major decrease in both metabolic activity and biomass was measured in all pregrown (4, 24, 48 h) biofilms after 24 h exposure to 5% HICA compared to RPMI at an acidic pH (Figure 14A; mean -71% and -62%, respectively). At a neutral pH, the efficacy of HICA was less significant: metabolic activity dropped by 22% and biomass by 17% on average in all pre-grown biofilms. Caspofungin exposure only led to significant changes in metabolic activity, and at a neutral pH the highest average reduction of 29% of all conditions was measured. Interestingly, a reduction of 73% by caspofungin was measured in 4 h pre-grown biofilms. The greatest reductions in biomass at a neutral and acidic pH were observed post-exposure to cysteine (63% and 33%, respectively). Leucine, a metabolic comparator for HICA, increased the metabolic activity by a mean of 3% and biomass by a mean of 14% at a neutral pH. 72 Figure 14. (A) Mean (± SEM) % metabolic activity and % biomass of all C. albicans pre-grown (4, 24 or 48 h) biofilms after 24 h exposure to 5% HICA and comparators relative to the control (RPMI). (B) Scanning electron microscopy (SEM) images taken of 24 h pre-grown biofilms, the upper biofilm treated with HICA and the lower one a control biofilm (RPMI) at pH 5.2. Scanning electron microscopy (SEM) further supported the results concerning the anti-biofilm activity of HICA. An SEM image revealed a collapsed network of hyphae and aberrant cell wall structures in a 24 h pre-grown biofilm after HICA exposure at an acidic pH (Figure 14B). At a neutral pH, an HICA-exposed biofilm showed no collapsing hyphae, but a less dense mesh of hyphae and similar cell wall defects were observed. A strong and intact mesh of hyphae was seen in images of RPMI controls at both pH values. 8.2.3 Acetaldehyde production during challenge with HICA and caspofungin No ACH was detected in glucose incubation when biofilms were exposed to HICA at an acidic pH (Figure 12). In addition, no production of ACH in glucose incubation was seen with 4 h pre-grown biofilms exposed to caspofungin at a neutral pH. ACH production by 24 and 48 h pre-grown biofilms exposed to HICA or caspofungin was significantly lower compared to RPMI in glucose and ethanol incubation at a neutral pH (p < 0.05). HICA exposure also resulted in lower ACH production in 4 and 24 h pregrown biofilms at an acidic pH. A similar significant reduction was observed in caspofungin-treated biofilms at an acidic pH (p < 0.05). Interestingly, at an acidic pH, moderate and the highest levels (>40 µM) were measured for 48 h pre-grown biofilms exposed to caspofungin (41.4 ± 7.5 µM). 73 8.2.4 8.2.4.1 Transcriptional changes (CaADH1, CaADH2, CaALD4, CaALD5, CaALD6, CaACS1 and CaACS2) in biofilms Basal and relative gene expression Transcriptional changes in pre-grown biofilms challenged with HICA or comparators were first evaluated by analysing the basal expression levels at an acidic and a neutral pH. Significant differences were detected in the expression of CaADH1, CaADH2 and CaALD5 relative to the reference gene CaRIP1 (>1.0; Figure 15). ADH1 was most highly expressed in 4 h and 48 h pre-grown biofilms at an acidic pH (range 2–18 fold). The highest transcription rates for CaADH1 were detected after exposure to HICA, cysteine or PBS. High CaADH1 expression was accompanied by CaADH2 expression and a significant correlation was found (rs = 0.703, p < 0.001). However, CaADH2 expression always remained lower than CaADH1 expression (range 2–5 fold). No similar up-regulation of CaADH1 or CaADH2 was recorded at a neutral pH. CaALD5 was the most highly up-regulated of all genes of interest in all conditions at both an acidic and a neutral pH (range 2–24 fold). Interestingly, similar expression of CaADH1, CaADH2 and CaALD5 was detected at an acidic pH in 48 h pre-grown biofilms after exposure to HICA or cysteine. CaALD5 was the only gene up-regulated after exposure to caspofungin (range 2–6 fold). This was mainly seen in 24 h pre-grown biofilms. Figure 15. Basal gene expression of CaADH1, CaADH2 and CaALD5 in pre-grown (4, 24 or 48 h) biofilms at pH 5.2 or 7.4 after 24 h exposure to HICA and comparators: caspofungin (CAS), leucine (LEU), cysteine (CYS), ethanol (ETOH), and PBS and RPMI controls. The mean transcription rate of each gene was calculated relative to the reference gene CaRIP1 under each condition. The dotted line represents the transcription rate of 1.0 of the reference gene. 74 The expression levels were further standardised against the control condition (RPMI) to examine the relative gene expression. Similar expression or significant upregulation of genes was observed after exposure to HICA at both pH levels relative to RPMI, whereas caspofungin exposure mainly resulted in down-regulation of ethanol metabolism. Interestingly, cysteine and leucine expression profiles showed similarities with HICA. Ethanol exposure led to a similar expression profile to HICA at a neutral pH. 8.2.4.2 Correlation with acetaldehyde levels In general, significant correlations were found between gene expression and ACH levels. However, this was dependent on pH. At a neutral pH, CaALD5 expression correlated negatively with ACH levels in ethanol incubation in all conditions tested (0.769 < rs < -0.661, 0.001< p < 0.003), but in glucose incubation this correlation was only significant in the control condition (RPMI; rs = -0.763, p < 0.001). In contrast to a neutral pH, no similar correlations were found at an acidic pH. The only significant correlations were calculated under the control condition. ACH values correlated negatively with CaADH1 and CaADH2 in ethanol incubation (rs = -0.558, p = 0.016 and rs = -0.636, p = 0.005 respectively), but a positive correlation was found between CaALD5 expression and ACH values (rs = 0.746, p < 0.001). 8.3 ANTI-BIOFILM AND ANTI-INFLAMMATORY PROPERTIES OF HICA IN VIVO HICA showed immunomodulatory properties when its efficacy was investigated in a murine C. albicans biofilm infection model. No significant decrease in biofilm weight was measured in vivo after 12 h treatment with HICA or the controls, caspofungin and PBS (p = ns). A suppression of inflammation was observed in tissues surrounding biofilm chambers treated with HICA compared to caspofungin or PBS controls. A dense inflammatory infiltrate, including macrophages and PMNs, and a thick band of granulation tissue were observed in the caspofungin and PBS biofilm groups. In contrast, tissues in the HICA biofilm group showed characteristics more similar to noninfected, non-biofilm controls, as the infiltrate was predominantly of a mononuclear cell type. However, in the HICA biofilm group, some PMN cells were also present. Staining of MPO, MMP-8 and MMP-9 predominantly localised in inflammatory cells, and the HICA biofilm group showed less intense staining compared to caspofungin and PBS controls. When treatments were compared within biofilm groups, the most prominent differences were observed in MPO and MMP-9 staining. In contrast, no major differences were seen in the staining of MMP-8, MMP-9 or MPO in the nonbiofilm group. More intense staining for NE and IL1β was seen in inflammatory cells in 75 the biofilm group than in the non-biofilm group, with no differences between treatments. Staining for TNFα was weak in all groups and treatments. Similar strong staining for Del-1, produced by endothelial cells, was detected in both HICA biofilm and all non-biofilm groups, whereas caspofungin and particularly PBS showed a milder intensity. 76 9 DISCUSSION When opportunity prevails, Candida yeasts can colonise the upper digestive tract in high numbers and cause infection. Pathogenic Candida species prefer a biofilm lifestyle in mucosal pathogenesis, which has been associated with oro-oesophageal malignancies. The major risk factors for oral and oesophageal cancer are alcohol abuse and smoking, and their effect on the risk is synergistic. When consumed, they both result in an increased salivary acetaldehyde (ACH) content. The oral and oesophageal microbiome has been shown as the main determinant for the local production of ACH, the carcinogenic metabolite of ethanol (Homann et al. 1997). Mucosal cells also possess the capacity to oxidise ethanol. However, their ability to eliminate ACH is limited (Chiang et al. 2012). ACH-related mutagenesis has been shown to occur at concentrations as low as 40 µM. Previous studies have demonstrated that prevalence of yeast, particularly Candida yeasts, is associated with high salivary ACH levels (Homann et al. 1997, Tillonen et al. 1999, Yokoyama et al. 2007). 9.1 PRINCIPLE FINDINGS The results of this study provide strong evidence for the significant capacity and role of Candida yeasts in the formation of carcinogenic ACH. This is the first study to show that C. albicans biofilms are able to produce mutagenic amounts of ACH, as levels well above 40 µM were measured after incubation with clinically relevant concentrations of ethanol and glucose in vitro. The highest ACH concentrations were produced by 24 and 48 h pre-grown biofilms, which can be considered mature according to the literature (Andes et al. 2004, Kaneko et al. 2013, Ricicová et al. 2010). This is important, as mucosal biofilms are predominantly in a mature state. However, it is relevant to note that mucosal biofilms are dynamic structures, and different stages from initiation to dispersal can be observed in these biofilms (Uppuluri et al. 2010a, Uppuluri et al. 2010b). Mutagenic levels of ACH were produced by biofilms at both a neutral and an acidic pH. This is clinically relevant, as in the oral cavity and oesophagus the pH can fluctuate daily in healthy subjects, and a more permanent decrease in pH can occur in conditions such as reflux disease. Furthermore, planktonic C. albicans cells were also able to produce mutagenic levels of ACH from ethanol and glucose in vitro. In ethanol incubation, levels of up to 240 µM were measured. The mutagenic production of ACH by planktonic C. albicans cultures has additionally been reported by other researchers (Tillonen et al. 1999, Uittamo et al. 2009). When initial growth conditions and cell counts were 77 standardised in the pilot experiment of this study, biofilms produced significantly higher levels of ACH compared to planktonic cells, again highlighting the impact of the biofilm mode of growth on the production of ACH and providing insights into the metabolic traits common for biofilms. All NAC species investigated were also able to produce mutagenic amounts of ACH from ethanol in planktonic mode of growth in vitro. When the ability to produce ACH was compared, large variation existed between and within different Candida species. This can be explained by metabolic rewiring due to their unique development through micro- and macroevolution in various environmental niches (Butler et al. 2009, Ihmels et al. 2005). Interestingly, only C. glabrata and C. albicans showed mutagenic production of ACH in glucose incubation when grown planktonically. Furthermore, C. glabrata was the only yeast that also produced ACH from fructose, and co-incubation of ethanol with either of the two carbohydrates resulted in even higher ACH production compared to incubation in ethanol alone. This suggests that there is a high metabolic flux towards pyruvate bypass and ACH, although cells were grown in aerobic conditions. Adh enzyme activity was also highest in C. glabrata, which supports its high fermentative trait. These findings are supported by the characteristics of C. glabrata, which is a Crabtree -positive yeast and more closely located in the phylogenetic tree to another Crabtree -positive yeast, S. cerevisiae, than other NAC species (Van Urk et al. 1990). High homology between the Adh1p enzyme of C. glabrata and S. cerevisiae further strengthens the metabolic similarity (87%; Inglis et al. 2012). For all Candida species, a significant reduction in ACH production was detected when ethanol was co-incubated with sugar alcohol xylitol in vitro. Xylitol is famous for its anti-cariogenic effect and inhibitory role in bacterial metabolism (Persson et al. 1993). Adh and xylitol dehydrogenase (Xdh) enzymes show a close resemblance in their structure, and both enzymes negatively affect to the redox balance in the cell (Kotter et al. 1990, Persson et al. 1993). These factors could contribute to the inhibitory action seen. Carcinogenic exposure in the upper digestive tract may also occur by direct exposure to ACH. Microbially fermented foodstuffs and beverages have been linked to the aetiology of squamous cell carcinoma in the upper digestive tract (Lachenmeier and Sohnius 2008, Linderborg et al. 2008). In this study, ACH and ethanol production during fermentation was studied using original mursik milk starter cultures collected from local families belonging to Kalenjin tribe in western Kenya. ESCC is the most common malignancy among men and women, especially in members of Kalenjin tribe. The common risk factors, smoking and alcohol consumption, are not highly prevalent in the area (Duron et al. 2013, Parker et al. 2010, Wakhisi et al. 2005). A major portion 78 of the daily diet in Africans is comprised of fermented food products, and fermented milk mursik is used daily by locals in western Kenya (Sanni 1993). High levels of ACH (up to 1800 µM) and ethanol (up to 110 mM) were produced during a simulated mursik fermentation process using original local starter cultures and boiled whole milk. ACH is an important flavour compound in milk products, and equally high levels of ACH and ethanol have been measured in previous studies (Guzel-Seydim et al. 2000, Kok-Tas et al. 2013). The ACH and ethanol concentrations correlated with the microbiota of the starter cultures. Candida yeasts and Lactobacillus bacteria were the most prevalent microbial members isolated. These microbial findings are in line with reports documenting the microbiota of industrial and other indigenous fermentation processes (Narvhus and Gadaga 2003). When the starter culture was grown on different selective media in a pilot experiment, colonies from yeast-specific media were mainly responsible for the ACH production, again highlighting the role of yeast as a source of significant ACH production. The highest levels of ACH (1150–1809 µM) were produced by milks containing a C. krusei–L.kefiri combination. When C. krusei was studied in planktonic mono-species cultures, it was the lowest producer of ACH of all Candida species. The reduction in pH from mild to highly acidic suggested robust lactate production by Lactobacillus. This is a wellknown property of Lactobacillus fermentations and beneficial for both yeasts and Lactobacillus, as the majority of the competing or contaminating bacteria cannot tolerate a low pH (Gadaga et al. 2001a, b, Mugula et al. 2003, Narvhus and Gadaga 2003). Thus, these findings imply that a metabolic synergy and symbiotic growth exist between the bacteria and yeast. This can also be considered interesting in the context of the human microbiome, where both species exist in combination and interact. Competitive inhibition has been shown within the human microbiome in health and disease. Probiotic lactobacilli and Lactobacillus metabolites can inhibit fungal growth (Crowley et al. 2012, 2013b, Guo et al. 2012, Hatakka et al. 2007, Hietala et al. 1979, Wagner et al. 2000). This study demonstrated that the Lactobacillus metabolite HICA, a leucine derivative, can effectively reduce the growth and biofilm formation of C. albicans in vitro. HICA has previously demonstrated broad-spectrum antimicrobial activity against various planktonically grown bacterial and fungal species in vitro (Sakko et al. 2013, Sakko et al. 2012). Both the metabolic activity and biomass of C. albicans biofilms were significantly reduced by HICA in different phases of biofilm growth, and defects in biofilm ultrastructure were confirmed by SEM. Major inhibitory activity of HICA was measured at an acidic pH. This is common for Lactobacillus metabolites. HICA also showed markedly improved efficacy over caspofungin, a commonly used antifungal against Candida biofilms (Cornely et al. 2012, Pfaller et al. 2011). 79 Gene expression analysis revealed highly significant basal and relative expression of CaADH1 and CaALD5 genes in biofilms due to challenge with particularly HICA and cysteine, among others, in vitro. Considering the well-known toxicity of cysteine to fungal cells at high concentrations, these results underline the importance of CaADH1 and CaALD5 in stress resistance and further support their broader role in biofilm growth. CaALD5 encodes the mitochondrial isoenzyme in S. cerevisiae. Interestingly, the C. albicans CaAld5p shows homology to mouse ALDH2, which is highly homologous to human ALDH2 (Chang and Yoshida 1994). Human and mouse mitochondrial ALDH2 has been associated with stress resistance. In addition, ACH levels in biofilms significantly correlated with CaALD5 expression. These findings imply that aldehyde dehydrogenases have similar roles in different eukaryotic organisms (Baek et al. 2004, Ohsawa et al. 2003, Szocs et al. 2007). No ACH was produced by any of the HICA-treated biofilms at an acidic pH, which may suggest an impairment of central carbon metabolism and more specifically glycolysis. This has earlier been shown as the potential mode of action for Lactobacillus metabolites (Crowley et al. 2013a, Kohler et al. 2012). No anti-biofilm activity for HICA or caspofungin was measured in a murine infection model. A longer treatment regimen may be required for an anti-biofilm effect, as reported in other animal models (Walraven and Lee 2013). However, an attenuated inflammatory response was observed in subcutaneous tissue sections surrounding an HICA-treated biofilm chamber. Lower expression was described, particularly for MMP9 and MPO, a tissue destructive protease and its activator highly expressed in cascade in various inflammatory conditions (Hajishengallis 2014, Sorsa et al. 2006). The present study did not establish whether the anti-inflammatory effect observed was direct or indirect, or a combination of these. In the case of an indirect effect, attenuation of the inflammatory response could be secondary to the efficient eradication of C. albicans biofilms. The potential direct anti-inflammatory effect of HICA is supported by a few previous studies that have demonstrated attenuated inflammation in response to treatment with Lactobacillus metabolites (Jones et al. 2009, Ramos et al. 2010). In addition, antifungals can possess direct anti-inflammatory activity, as shown for clotrimazole during the treatment of vaginal candidosis (Wilson et al. 2013). The direct effect is supported by the findings of a previous in vitro study in which an anti-proteolytic effect was described for HICA (Westermarck et al. 1997). Del-1 was strongly expressed in the non-infected, non-biofilm group, as expected for an inhibitor of neutrophil extravasation. Interestingly, Del-1 was also strongly expressed in the HICA biofilm group. Although Del-1 has been shown to play an important role in the regulation of immune responses in various inflammatory diseases, this study reports for the first time its expression in fungal infection (Baban 80 et al. 2013, Eskan et al. 2012, Shin et al. 2013, Zhao et al. 2014). Del-1 can also regulate the expression of IL-17, which plays an important role in mucosal immunity against candidosis (Conti et al. 2009, Eskan et al. 2012, Ho et al. 2010, Huppler et al. 2014, Puel et al. 2011). Thus, Del-1 could play a role in various Candida-related inflammatory conditions. 9.2 LIMITATIONS OF THE STUDY ACH production by Candida species was only investigated in vitro and mainly with single-species cultures. These settings are drastically different from the in vivo conditions faced by Candida in the upper digestive tract. The number of Candida cells can be much lower at a single locus in vivo than used here in vitro. Multiple environmental and inhibitory factors affect candidal metabolism and biofilm formation. Competitive inhibition and synergy with bacteria also exist, further shaping the metabolism and development of the fungal cell and biofilm in vivo. The level of oxygen is a major factor affecting local ACH production. Oxygen levels regulate the balance between respiration and fermentation in Candida spp. and other members of the microbiome. The availability of oxygen can widely largely between various niches of the oral cavity and oesophagus, and oxygen concentrations ranging from 0.5% to 14% have been observed (Marcotte and Lavoie 1998, Theilade 1990). High levels of oxygen can be measured in saliva (5–14% O2), and hypoxic levels in deep gingival pockets or in the deeper layers of oral polymicrobial biofilms (<1% O2). In comparison, the normal oxygen concentration in the air is around 21% . The low level of oxygen at the core of the biofilm is a result of reduced oxygen diffusion and the consumption of a major proportion of the available oxygen by facultative anaerobic microbes. In the upper digestive microbiome, metabolically distinct microbial members are present in terms of oxygen sensitivity, and members ranging from obligate anaerobes to aerobes exist. Under anaerobic conditions, fermentative metabolism is up-regulated and ethanol is produced from sugars via the reduction of ACH. When oxygen is present, ethanol derived from endogenous or exogenous sources is oxidised to ACH. Oxygen levels in saliva support this oxidative metabolism of ethanol. An additional parameter driving microbial metabolism in hypoxia is the higher level of CO2. In addition to microbial ethanol metabolism, mucosal cells also have the enzymatic capacity to oxidise ethanol into ACH. Thus, multiple factors affect the overall ACH exposure in vivo. Although the microbiota dominantly contributes to local ACH exposure, no study has described the relative contribution of microbial and host cells to the total ACH exposure. Overall, enhanced models simulating the in vivo conditions are required. 81 Although cells were cultured under aerobic growth conditions, the levels of oxygen faced by the planktonic cells or biofilms at the bottom of the plastic wells or glass vials filled with media or buffer were more likely to be moderately hypoxic. This is particularly the case when cultures are grown statically, as in this study (Odds et al. 1995). Moderately hypoxic conditions have been shown to stimulate high ACH production by C. albicans (Marttila et al. 2013a). The strain and various growth parameters, such as nutrient availability, time of biofilm development, pH and the type of in vivo model, can have a major impact on the metabolic outcome of the fungal cell and biofilm development in vitro and in vivo, as shown in the literature (Kucharikova et al. 2011, Maccallum 2012, Martinez-Gomariz et al. 2009). Variation in these growth parameters would have potentially resulted in more variation in the results and in better understanding of the effects of various compounds tested in this study. The number of isolates per species under investigation was low, although both clinical and reference strains were selected for the experiments with planktonic cultures. Biofilm experiments were mainly carried out using one reference strain. Including more Candida isolates from clinical samples would provide vital information and produce a broader picture of how biofilm formation and central metabolic pathways, including ACH metabolism, are affected by the microevolution of each isolate. Biofilm biomass was calculated based on the concentration of double stranded DNA (dsDNA), which has been shown to correlate with number of viable cells (Marstorp and Witter 1999). The biofilm matrix can contain extracellular DNA (eDNA), which facilitates the formation, resistance and inflammatory properties of fungal and bacterial biofilms (Martins et al. 2010, Rajendran et al. 2013, Whitchurch et al. 2002). Therefore, eDNA of the matrix could affect our results, although we tried to limit this by including multiple washing steps. Reliable quantitation of Candida biofilms can be problematic, as previously documented (Taff et al. 2012). Furthermore, it is important to acknowledge the recent data presented by Harrison et al. (2014), which showed that pathogenic Candida yeasts can shift the ploidy of the cell in response to certain stress factors, such as antifungals, in vitro and in vivo. This shift increases the dsDNA content of the cell. Thus, one can question how this phenomenon possibly affects the results described in this study. When gene expression levels were measured, only the main genes linked to ethanol metabolism were analysed. Although both basal and relative expression was calculated against a standard reference gene, these results remain restricted in terms of the total transcriptomic and metabolic outcome of the biofilm. Therefore, more 82 extensive genomic and proteomic studies are warranted in the future. It should also be taken into account that the availability of oxygen and nutrients can differ within the different layers of a biofilm. Thus, the cellular metabolic and transcriptomic responses can considerably differ between the core and surface of the biofilm. It is common that the RNA is extracted from the whole biofilm. Therefore, the transcriptional changes shown describe the average expression of the specific gene in the biofilm and not the expression in a certain layer or niche. Inflammatory responses were investigated in a murine infection model. The inflammatory responses can greatly differ between humans and mice (Seok et al. 2013). Thus, the results cannot be fully extrapolated to the human host. Furthermore, the number of mice, particularly in the control groups, was low. Therefore, in vivo studies with larger groups are warranted to strengthen these findings. 9.3 STRENGTHS OF THE STUDY Overall, the results of this study demonstrate the considerable capacity of various Candida species to oxidise ethanol to mutagenic ACH. High production of ACH by NAC species is clinically important, as NAC species have become increasingly frequent concurrently with the rise in the number of immunocompromised patients (Pfaller et al. 2011). The concentrations of ethanol (11-12 mM) used in the experiments can be considered clinically relevant, as they are normally found in saliva in an average male (80 kg) after consuming 0.5–0.6 g of ethanol per kilogram of body weight. Concentrations of glucose and fructose were adjusted to 18–20 g/l (100–110 mM), commonly found in the Western diet. It was important to identify a compound with high efficacy against C. albicans biofilms. New approaches to treat fungal infections are required, as the current antifungals act poorly, especially against biofilms, and harmful side effects often accompany their use. HICA is a safe compound, as it is found in the human body and has been used as an animal food and by professional athletes (Boebel and Baker 1982, Hietala et al. 1979, Mero et al. 2010). The antiinflammatory properties of HICA could provide additional benefits when combating inflammatory disease associated with irreversible tissue damage (Westermarck et al. 1997). HICA could also be used in combination with other antifungals, such as echinocandins or azoles, to strengthen the inhibitory effect. Future studies are required to elucidate the potential effect of combined therapy. The properties of the inflammatory response that a C. albicans biofilm induces in vivo are not well known. Thus, this study contributed to the limited information currently existing and demonstrated distinct cytokine expression, similar to what has been described in vitro (Chandra et al. 2007, Xie et al. 2012). 83 9.4 RELEVANCE OF THE STUDY Candida yeasts have been shown to be associated with pre-malignant lesions and carcinomas in the oral cavity and oesophagus (McCullough et al. 2002, Nagy et al. 1998, Rautemaa et al. 2006, Warnakulasuriya et al. 2008b). Interestingly, carcinoma often develops next to the site of biofilm-related Candida mucositis. Local infection causes inflammation in neighbouring tissues, and in the long-term this process can lead to dysplasia. Carcinogenesis is initiated when the threshold of DNA damage is exceeded in a normal cell, although strong defence involving cellular repair mechanisms exists. Increased production of mutagenic ACH in the presence of suitable carbon sources due to colonisation with C. albicans or NAC species could induce mutagenic changes and add to other stress factors, such as inflammation, in mucosal cells, and eventually contribute to the initiation of cancer. Mutagenic ACH could also affect the neighbouring flora and cause mutations leading to enhanced virulence and particularly to the development of resistance, which is a major clinical problem worldwide. Candida yeasts were also associated with the formation of mutagenic levels of ACH during mursik fermentation. Regular consumption of fermented products, such as mursik, with a high ACH content could further increase the stress faced by mucosal cells. A high ethanol content present as a congener could be oxidised to ACH by microbes, especially yeasts, thus further increasing the exposure. HICA could provide a safe approach to inhibit biofilm growth by C. albicans in mucosal infections and reduce the mutagenicity and inflammation associated with the pathogenic biofilm lifestyle. 84 10 CONCLUSIONS This study led to the following conclusions: I C. albicans can produce mutagenic levels of acetaldehyde from ethanol and glucose in both planktonic and biofilm modes of growth in vitro. C. albicans is the most common fungus in the upper digestive tract and its biofilm lifestyle is associated with pathogenicity. Carcinoma often develops next to the site of biofilm-related Candida mucositis. Thus, carcinogenic acetaldehyde produced by C. albicans biofilm could have a major role in oral and oesophageal carcinogenesis. II Experiments with planktonic cells demonstrated the significant ability of clinically relevant non-albicans Candida species to produce acetaldehyde in the presence of ethanol in vitro. However, significant differences were detected between and within species. Interestingly, co-incubation with xylitol significantly reduced acetaldehyde production from ethanol by all Candida spp. C. glabrata shows a specific potential for acetaldehyde production, as mutagenic levels could be measured in the presence of glucose and also fructose. Acetaldehyde production by C. glabrata was increased in glucoseethanol and glucose-fructose co-incubations. These findings and also the high Adh activity detected in C. glabrata demonstrate its high tendency for fermentative metabolism. As the prevalence of non-albicans Candida species in health and disease is increasing, colonisation with species such as C. glabrata could significantly increase the production of carcinogenic acetaldehyde locally when ethanol or sugars are present and add to the risk of cancer in the upper digestive tract. Xylitol could be potentially used to reduce local acetaldehyde exposure by Candida spp. III Regular consumption of fermented food products and beverages containing acetaldehyde and ethanol has been associated with upper digestive tract carcinogenesis. Consumption can lead to direct exposure of the mucosa to carcinogenic acetaldehyde or indirect exposure through microbial ethanol metabolism and salivary acetaldehyde. Highly mutagenic levels of acetaldehyde and ethanol are produced during mursik milk fermentation, as simulated in this study. Specific Candida–Lactobacillus combinations are associated with the highest acetaldehyde and ethanol production, thus showing the role of microbial synergy in the process. Yeasts have a major role in the production of acetaldehyde. As mursik constitutes a major part of the 85 diet in western Kenya, an area with a high incidence of oesophageal cancer and a low prevalence of common risk factors, the regular consumption of mursik could contribute to the unusually high cancer incidence. IV 86 Yeasts are eukaryotic organisms. Their similarity to human cells makes the development of antifungals difficult, and patient compliance is often compromised because of various side effects. Treating Candida infections is a challenging task, and more effective antifungal agents are required. This study demonstrated the major efficacy of Lactobacillus and the leucine metabolite HICA against C. albicans biofilms in vitro. During challenge with HICA and comparators, certain genes related to ethanol metabolism were upregulated, thus showing their important role in stress resistance and biofilm formation in general. Furthermore, HICA attenuated the inflammatory response in a murine C. albicans biofilm infection model. This combination of anti-biofilm and anti-inflammatory activity can be highly beneficial when treating biofilm-related chronic inflammatory disease. Effective eradication of Candida biofilms with HICA could reduce the exposure of the neighbouring mucosa and surrounding microbiome to mutagenic acetaldehyde and reduce the biofilm-induced inflammatory burden on mucosal cells. 11 ACKNOWLEDGEMENTS This PhD thesis was a collaborative project between the University of Helsinki, Finland and the University of Manchester, United Kingdom during the years 2009-2014. The experiments were performed at the Research Unit on Acetaldehyde and Cancer, Biomedicum, University of Helsinki (I,II), at the Department of Bacteriology and Immunology, Haartman Institute, University of Helsinki (III) and at Research lab of Dental Institute, Biomedicum, University of Helsinki (I,II,V) and at University Hospital of Southern Manchester, Wythenshawe Hospital, University of Manchester (III,IV,V). In addition, Candida biofilm model was studied at the University of Glasgow under supervision of Prof Gordon Ramage prior to construction of our own biofilm model at Wythenshawe hospital. Study III was performed in collaboration with National Cancer Institute of National Institutes of Health (NIH), USA and the samples were collected by their field researchers in Western Kenya. I sincerely thank Dr Neal Freedman and his co-workers at NIH for their contribution and effort. First and foremost I am deeply grateful for my supervisors Riina Richardson, Mikko Salaspuro and Timo Sorsa for their excellent guidance during this project. Riina, I sincerely thank you for your endless enthusiasm, optimism and care. Your determination and passion towards science has pushed me forward. The wisdom and vast knowledge you possess has been something to admire. I also thank you for the introduction to English culture together with your family, the accommodation during my visits to Manchester and the spare time shared. Mikko, I kindly thank you for all the support given especially in the beginning of my PhD studies. Your expertise, innovative thinking and contribution to the field of GI tract carcinogenesis and acetaldehyde-related toxicity has been of world-class and provided the framework for this project. Timo, I greatly appreciate your knowledge and wide experience in science, especially in the area of inflammation and tissue proteases. I also deeply honour your integrity and open-mindedness. In addition, the discussions with you inside and outside the field of science have been a great joy. I wish to express my deep appreciation to my reviewers Prof Bernhard Hube and Prof Markus Haapasalo for their valuable critique and in-depth commentary. I kindly thank Roy Siddall for the excellent language revision. I most sincerely thank Dr Paul Bowyer (Univ. of Manchester) for sharing his resources and the world-class expertise in molecular microbiology. Dr Peter Warn (Univ. of 87 Manchester) is highly appreciated for the collaboration and work regarding animal and infection models. I am deeply indebted for Dr Lily Novak-Frazer (Univ. of Manchester) for all her hard work and superior guidance during these years in the research lab of Wythenshawe hospital. Your determination and precision were vital for the successful establishment of the biofilm model and the progress made during the past three years. I deeply honour your endless support and effort given. I also want to express my gratitude towards other co-researchers in the lab, particularly Vilma Rautemaa, Rebecca Collins, Mike Bromley and Marcin Fraczek. Dr Julie Morris (Univ. of Manchester) is acknowledged for her expert guidance on statistical analysis. I highly honour the role of Prof Malcolm Richardson in sharing his expertise in mycology. Your contribution to the manuscripts, particularly regarding their language, cannot be thanked enough. The discussions around the diverse aspects of science and technology have been highly amusing. I kindly thank Prof Gordon Ramage and Dr Ranjith Rajendran from University of Glasgow for teaching me the fundamentals of Candida biofilms in the beginning of my research projects in UK. I am also deeply grateful for the resources and the excellent collaboration and support shared. Among the team members of Mikko Salaspuro, I especially want to acknowledge the work of Maarit Raukola. Your conribution for the lab has been irreplaceable and the discussions shared a great joy. The contribution and help of Pertti Kaihovaara in the field of gas chromatography is highly acknowledged. I owe also special thanks to other co-workers, particularly Johanna Uittamo, Satu Väkeväinen, Klas Linderborg and Andreas Helminen for their support. In addition, I want to thank the Finnish colleagues belonging to Riina’s team: Lotta Grönholm, Peter Rusanen, Esa Färkkilä, Marjus Sakko and Emilia Siikala, it has been wonderful to work with you and share the experiences around PhD studies. Among the staff of the Research lab of Dental Institute of the University of Helsinki, I want to acknowledge the work of Marjatta Kivekäs and Dr Taina Tervahartiala. I most sincerely thank you for the contribution and knowledge shared regarding immunohistochemistry. I kindly thank Dr Kirsti Kari for providing me excellent working facilities. I also thank the other co-workers, particularly Dr Pirkko Pussinen and her team members Elisa Kallio, Kati Hyvärinen, and Aino Salminen for the support and 88 joyful discussions. Collaborator of Timo Sorsa, Prof Marcela Hernandez from the University of Chile is highly acknowledged for her advice and contribution regarding immunohistochemistry and pathology. This work is dedicated to my parents, Anna-Liisa and Markku, who have given their endless support throughout my life and encouraged me to pursuit the dreams I have. I am more than grateful for the rest of the family as well, especially my little sister and brother Riitta and Martti. I also owe the deepest gratitude to my dearest, Fanny, for all her love and friendship. Your humour and endless support has given me tons of energy during this challenging, but highly rewarding and enjoyable step of my career. I am more than grateful to all my friends in Finland and abroad for pulling me out of the hectic academic and work life once in a while, for putting things in life into perspective and for all the amazing moments experienced. 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