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MINIREVIEW Molecular ecology of microbial mats Henk Bolhuis, Mariana Silvia Cretoiu & Lucas J. Stal Department of Marine Microbiology, Royal Netherlands Institute for Sea Research, NIOZ, Yerseke, The Netherlands Correspondence: Henk Bolhuis, Department of Marine Microbiology, Royal Netherlands Institute for Sea Research, NIOZ, Korringaweg 7, NL 4401 NT Yerseke, The Netherlands. Tel.: +31-113-577478; fax: +31-113-573616; e-mail: [email protected] Received 21 May 2014; revised 27 July 2014; accepted 5 August 2014. Final version published online 28 August 2014. DOI: 10.1111/1574-6941.12408 Editor: Gerard Muyzer MICROBIOLOGY ECOLOGY Keywords Cyanobacteria; microbial mat; metagenomics; hyperthermal; hypersaline; coastal. Abstract Phototrophic microbial mats are ideal model systems for ecological and evolutionary analysis of highly diverse microbial communities. Microbial mats are small-scale, nearly closed, and self-sustaining benthic ecosystems that comprise the major element cycles, trophic levels, and food webs. The steep and fluctuating physicochemical microgradients, that are the result of the ever changing environmental conditions and of the microorganisms’ own activities, give rise to a plethora of potential niches resulting in the formation of one of the most diverse microbial ecosystems known to date. For several decades, microbial mats have been studied extensively and more recently molecular biological techniques have been introduced that allowed assessing and investigating the diversity and functioning of these systems. These investigations also involved metagenomics analyses using high-throughput DNA and RNA sequencing. Here, we summarize some of the latest developments in metagenomic analysis of three representative phototrophic microbial mat types (coastal, hot spring, and hypersaline). We also present a comparison of the available metagenomic data sets from mats emphasizing the major differences between them as well as elucidating the overlap in overall community composition. Introduction Microbial mats are vertically stratified communities of functional groups of microorganisms embedded in an organic matrix that can also contain various amounts of minerals such as silicates and carbonates (Stal, 2012). Microbial mats are benthic communities that grow on a solid substrate (e.g. sand, rock, and other sediments) and the vast majority is autotrophic, that is utilize inorganic carbon as carbon source. This review focuses on phototrophic microbial mats that develop in illuminated environments, which are in majority build by the oxygenic phototrophic Cyanobacteria, sometimes aided by phototrophic microbial Eukarya (e.g. diatoms). Microbial mats are often considered as analogs of stromatolites, the fossil remains of which date back to almost 3.5 billion years and, hence, represent the oldest ecosystem we know (Margulis et al., 1980). Precambrian stromatolites, that is laminated rock, were formed by microbial mats in shallow marine environments and lithified through calcification or silicification. The laminated structure reflects the successive development of microbial mats and in certain cases may have followed sea level rise. FEMS Microbiol Ecol 90 (2014) 335–350 Microbial mats are also important for terraforming by stabilizing the sediment surface and increasing the sediment erosion threshold. For instance, coastal microbial mats affect coastal morphodynamics and may serve as a natural barrier against rising sea levels (Yallop et al., 1994). The typical multilayered structure of microbial mats (‘vertical stratification’) originates from the physicochemical gradients that are generated and maintained by the activities of the component microorganisms. These physicochemical gradients provide microenvironments for different functional groups of microorganisms, that is groups that exhibit a certain physiology with which they fulfill a specific function (van Gemerden, 1993). For example, in phototrophic microbial mats Cyanobacteria and phototrophic Eukarya fulfill largely the same function of harvesting light as the source of energy, splitting water as the source of electrons and using these to fix CO2. These are used to synthesize organic matter (‘primary production’) for growth and for the production of nonstructural components such as extracellular polymers (EPS) (De Philippis & Vincenzini, 1998). EPS form the matrix in which the organisms are embedded and serve ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved H. Bolhuis et al. 336 as glue with which a cohesive structure is formed that renders stability to the mat and the sediment surface (Grant & Gust, 1987). The organic matter formed through primary production is the basis of the microbial food web. This organic matter becomes available to other microorganisms by a variety of processes (microbial loop) (Pomeroy et al., 2007). In the dark, Cyanobacteria and algae respire their endogenous carbon reserves thereby depleting the mat of oxygen. These organisms continue to degrade their carbon reserves under anoxic conditions by fermentation resulting in the production of low-molecular organic acids and alcohols (Stal & Moezelaar, 1997). These fermentation products are further oxidized by methanogenic bacteria and sulfate-reducing bacteria, often in a syntrophic mode with other microorganisms. Sulfate-reducing bacteria outcompete methanogens in marine and hypersaline microbial mats because of the high concentration of sulfate in the seawater, but are important in lowsulfate microbial mats. Sulfate-reducing bacteria produce sulfide, which is oxidized back to sulfate by sulfur-oxidizing bacteria. Chemoautotrophic bacteria oxidize sulfide aerobically while anoxygenic photoautotrophic bacteria oxidize sulfide anaerobically in the light (van Gemerden, 1993). The latter forms a purple layer underneath the Cyanobacteria. Colorless sulfur bacteria do not form such a distinct layer and are found throughout the mat and probably take advantage of the vertical migrations of the oxygenated layer (Visscher et al., 1992). Also sulfatereducing bacteria do not form a distinct layer, although different species may be found along the vertical gradient, depending on their oxygen tolerance (Canfield & Des Marais, 1991; Risatti et al., 1994). Grazing has not been extensively studied in microbial mats per se. It does probably not play an important role in microbial mats and therefore does not contribute substantially to carbon and nutrient cycling. When grazing meioand macrofauna would be present they would destroy the mat (Fenchel, 1998). It is therefore generally thought that microbial mats only develop in environments that largely exclude grazing organisms (i.e. extreme environments). When inundated, coastal microbial mats may periodically experience grazing by nematodes (Feazel et al., 2008), snails, or even fish. Eukarya, including metazoa, are present in such microbial mats, but their role as grazers remains to be seen (Bolhuis et al., 2013; Edgcomb et al., 2014). Although not much is known about viruses (bacteriophages) in microbial mats, they are present and most likely they are important factors for the recycling of carbon and nutrients and probably also contribute to genetic exchange and bacterial evolution within the mat (Br€ ussow et al., 2004). In a comparison between different ecosystems, a submerged marine cyanobacterial mat was ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved found to have the highest phage density of all tested ecosystems (Hennes & Suttle, 1995). Investigations of Clustered Regularly Interspaced Palindromic Repeats (CRISPRs) and cas genes in hot spring microbial mat Cyanobacteria (Synechococcus) hinted to a fast coevolution of the host and viral genome (Heidelberg et al., 2009). Microbiologists and geologists have studied microbial mats intensively for several decades (e.g. Stal, 2012). However, the initial studies were hampered by the lack of appropriate methods and tools that would allow the investigation of microbial processes in the often less than a millimeter thick layers of these systems. The first breakthrough was the application of microelectrodes and microlight sensors in the study of microbial mats (Jørgensen et al., 1983; Lassen & Jørgensen, 1994). These sensors allowed measurements at the tens-of-micrometer scale and revealed detailed high-resolution spatial and temporal information on light (including its spectral distribution in the mat), oxygen, sulfide, pH, redox, photosynthesis, and sulfate reduction. However, much remained unknown about the organisms and their activities that were behind these biogeochemical processes. Until the application of molecular genetic techniques, information about the microorganisms in microbial mats was limited to isolation and cultivation and microscopy. Molecular biology revealed the enormous diversity of the microbial community and their metabolic pathways and opened whole new avenues for the study of microbial mats, which is witnessed by a wealth of scientific reports that have appeared in recent years. The rRNA clone libraries and DGGE techniques, that were initially used, have now been replaced by meta-omics and high-throughput sequencing (HTS) and with the availability of new bioinformatics tools their analysis will lead to a revolutionary different understanding of the diversity, ecology, and evolution of microbial mats. In this minireview, we show how molecular genetics has revolutionized the study of microbial mats, discuss some problematic issues with the application of molecular biology, review the progress achieved, and provide an outlook on what we can expect in the near future. As an example, we selected three extreme environments where modern microbial mats develop and examined what is known about microbial diversity in intertidal, hypersaline, and hyperthermal microbial mats and compare these three systems with respect to the environments they thrive in. Sampling and molecular analysis of microbial mats Nucleic acid extraction Microbial mats require their own approach and strategies with respect to sampling and molecular analysis. Nucleic FEMS Microbiol Ecol 90 (2014) 335–350 337 Molecular ecology of microbial mats acid extraction is particularly problematic because of the presence of a dense EPS/sediment matrix and precipitates of calcite and halite (Dupraz & Visscher, 2005). Whether to use commercially available nucleic acid extraction kits or classical phenol/chloroform-based methods depends on the geochemical nature and physical properties of the samples and requires optimization for each mat type. An additional problem with nucleic acid extraction is that the efficiency of cell lysis strongly varies among different microorganisms. In particular, filamentous Cyanobacteria that are heavily encapsulated by EPS are known to be difficult to lyse and may require a combination of mechanical (bead beating) enzymatic (proteases, lysozyme, or polysaccharide degrading enzymes) and chemical lysis (guanidine isothiocyanate, sodium dodecyl sulfate, NaOH). Moreover, even when lysis is successful, nucleic acids may become trapped in EPS and inaccessible for, for example PCR and sequencing. Therefore, with any chosen method of nucleic acid extraction one should realize that several groups of microorganisms might be missed in the final molecular data set. Extracellular DNA The EPS matrix of biofilms including microbial mats may contain high amounts of extracellular DNA (Vlassov et al., 2007). This extracellular DNA appears to be stable in sediments and protected from nucleases (Lorenz & Wackernagel, 1994). Some authors estimated that of the DNA recovered from marine sediments up to 90% might represent extracellular nucleic acid (Dell’Anno & Danovaro, 2005). In that case, RNA would give a better idea of the actual active microbial species composition and their metabolic diversity assuming that extracellular RNA is unstable. Covering the spatial and temporal heterogeneity An additional challenge is the spatial heterogeneity of microbial mats (Armitage et al., 2012; Bolhuis et al., 2013). Microbial mats are heterogeneous at the microand macroscale. Heterogeneity is typical for almost any ecosystem and is generated by alternating stable states (van de Koppel et al., 2001). In microbial mats physicochemical gradients of light, temperature, salinity, oxygen, carbon, sulfur, and nitrogenous compounds will affect the microbial community composition at the microscale. In particular, in coastal microbial mats, larger scale heterogeneity is generated by the tides, precipitation, vegetation, bioturbation, and other factors. This makes it basically impossible to analyze the full extent of microbial diversity of coastal mats that may stretch over several square kiloFEMS Microbiol Ecol 90 (2014) 335–350 meters (Villanueva et al., 2004, 2007; Bolhuis et al., 2013). The problem of the heterogeneity of microbial mats must also be taken into consideration when analyzing the metatranscriptome. Moreover, in the higher and lower latitudes seasonality is also important for the composition and activity of the mat community. These mats may experience a yearly cycle of growth, climax, and destruction in addition to erratic events. Sampling at one time point and at one position will therefore only provide a ‘snapshot’ of the mat’s actual community composition and function and cannot be reproduced and any extrapolation of such data can be questioned. Currently, the best approach appears to be to collect several randomly chosen samples (the number depends on the structure and heterogeneity of the mat) in a chosen plot and to resample the same site at different time points during a 24-h day and during different seasons. However, this may easily result in the analysis of hundreds of samples (e.g. three mat types with 10 spatial points per mat type, sampled over six time points in a 24-h period, repeated over four seasons result in 720 samples for only DNA analysis and the double amount if the RNA fraction is also targeted). Although separate analysis of samples is preferred as it allows thorough statistical analysis and insight in the heterogeneity of the system this may quickly become unaffordable for most laboratories. Depending on the goal, available tools, and (financial) resources, subsamples can either be pooled to cover spatial or temporal heterogeneity or analyzed separately. It should also be noted that mats in intertidal areas often develop in one direction and that it is unlikely that a previous state will return. Molecular analysis in the omics era Molecular techniques have greatly advanced the analysis of microbial diversity in divergent ecosystems. Although a number of different genes have been used for phylogenetic studies, the analysis of the 16S and 18S ribosomal RNA (rRNA) genes of, respectively, Bacteria/Archaea and microbial Eukarya have revolutionized microbial ecology and enhanced our knowledge of the abundance, diversity, and function of these microorganisms. With the exception of direct sequencing techniques and analysis of single isolates, most phylogenetic studies in microbial communities relied on PCR based amplification of the genes of interest followed by direct sequencing or by a combination of cloning and sequencing. The sequences are compared with databases to identify their closest match with those of cultivated or uncultivated microorganisms. The current standard in the study of microbial diversity involves next generation HTS techniques. These methods generate between 1 million (454 pyrosequencing) and 600 million (Illumina) independent small DNA ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved 338 fragments (reads). Each of these techniques has its specific advantages and disadvantages with respect to read length versus error rates (Harris et al., 2013). For reproducible and comparable results, special care has to be given to library construction conditions (Ross et al., 2013) and to obtaining high-base quality data (especially for high GC regions) and increasing read lengths. For amplicon sequencing the choice of primers is crucial and the scientific community would benefit from focusing on one fixed region of the 16S or 18S rRNA gene so that databases consist of comparable data sets (Chakravorty et al., 2007; Ghyselinck et al., 2013). Several PCR steps can be omitted when whole environmental genome sequencing becomes available for affordable prices, yielding sufficient phylogenetic information on 16S or 18S rRNA genes and protein coding sequences to uncover the dominant and rare biodiversity (Fierer et al., 2012). HTS has revolutionized microbial ecology allowing access to the full extent of microbial diversity including rare species that were missed in traditional clone libraries. Moreover, gene diversity can be assessed and used to reconstruct metabolic networks using metatranscriptomics. Intertidal microbial mats Globally, intertidal microbial mats are formed on beaches with low slopes and fine sandy sediments (Stal, 2012). Intertidal areas are extreme environments in several ways. Because intertidal areas are irregularly flooded, they experience strong salinity fluctuations (from almost freshwater after rain to moderate hypersaline conditions upon prolonged desiccation) and large changes in temperature. These environmental changes and fluctuations follow in short time frames and could have generated the (micro-) diversity that characterizes intertidal microbial mats (Bolhuis & Stal, 2011). Unlike hypersaline and hot spring mats that exclude most Eukarya, intertidal microbial mats are rich in microeukaryotic organisms (Bolhuis et al., 2013). Intertidal microbial mats alter their environment and provide the conditions for higher organisms to colonize the sediment and eventually form salt marshes or initiate the formation of dunes (Grant & Gust, 1987; Blanchard et al., 2000; Dupraz & Visscher, 2005; Bolhuis & Stal, 2011; Armitage et al., 2012). Intertidal mats cover large coastal surfaces worldwide including the well-studied beaches of the North Sea barrier islands in the Netherlands, Germany and Denmark (Stal et al., 1984; Villbrandt et al., 1990; Severin & Stal, 2008; ). Microscopy of intertidal mats revealed the dominance of Cyanobacteria such as Coleofasciculus (Microcoleus) chthonoplastes and Lyngbya aestuarii. Cyanobacteria are the initial builders of coastal mats by producing biomass, EPS and other organic matter, which form the basis of the ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved H. Bolhuis et al. microbial food web and support a plethora of different functional groups of microorganisms (Stal et al., 1984; van Gemerden, 1993; Bebout & Garcia-Pichel, 1995; Guerrero et al., 2002; Abed et al., 2008; Dijkman et al., 2010; Severin et al., 2010; Bauersachs et al., 2011; Gobet et al., 2012). A millimeter dissection of a tidal microbial mat using 16S amplicon HTS and metagenomic analysis was performed on samples extracted from the Great Sippewisset salt marsh in the USA (Armitage et al., 2012). The amplified rRNA gene reads were dominated by Cyanobacteria and purple sulfur bacteria (Chromatiales – Gammaproteobacteria). Cyanobacteria were most abundant in the top 2 mm and still detectable at 20 mm depth. Proteobacteria other than Chromatiales dominated the 2–20 mm range. Overall, the Sippewisset mats were taxonomically highly diverse, and the community compositions differed depending on the developmental stage of the mat, the year of sampling, and the mat layer. Phylogenetic richness and evenness positively covaried with depth while trait richness tended to decrease with depth. The lower diversity in the top layer may be caused by unfavorable conditions such as UV irradiation, temperature, desiccation, and erosion by wind and flooding that occur on a daily base. During the day, the top layer of the mat is likely composed of stress-tolerant aerobes such as the Cyanobacteria, while at night microaerophiles and UV-sensitive taxa may temporarily migrate to the surface (Villanueva et al., 2007). In an attempt to assess part of the predicted heterogeneity of an intertidal mat, Gobet et al. (2012) compared the microbial community of the sediment pore water, the sand grains, and the overlaying seawater. Samples from a shallow subtidal sand flat at the German island of Sylt in the North Sea were analyzed using bacterial 16S amplicon HTS of the c. 60 bp long variable V6 region of the 16S rRNA gene. This study revealed that pore water contained < 0.2% of the species that were associated with the sand grains and the authors concluded that most of the microbial mat community was tightly bound to the sediment and embedded in EPS. The abundant phyla associated with the sediment belong to the Proteobacteria, Cyanobacteria, Bacteroidetes, and Acidobacteria. The number of Cyanobacteria decreased with depth, but this was also the case with the nonphotosynthetic Bacteroidetes. The number of Betaproteobacteria increased with depth. Gobet et al. (2012) showed that there was no change at the level of phyla and class of the predominant groups with time. However, when observed at a higher taxonomic resolution (e.g. family, genus, and species), drastic changes in the bacterial community composition were found. Only 0.55% of the total number of > 27 000 unique OTU’s were present in all samples at all times. However, it has FEMS Microbiol Ecol 90 (2014) 335–350 339 Molecular ecology of microbial mats to be taken into account that at a higher taxonomic resolution the outcome is more sensitive to point mutations introduced by the PCR steps during pyrosequencing. Richness estimates for the different samples varied between 496 and 2993 OTU’s at the 97% cutoff level underlining the overall high richness measured in coastal microbial mats (Gobet et al., 2012). Metagenomic study of an Arctic photosynthetic microbial mat revealed a similar bacterial community composition dominated by Proteobacteria, Cyanobacteria, Bacteroidetes, and Actinobacteria despite harsher conditions such as temperatures ranging far below zero in wintertime and around 1 °C during summer (Varin et al., 2010). In our own study (Bolhuis & Stal, 2011), we investigated microbial diversity (both Archaea and Bacteria) of coastal mats using the 60 bp, V6 variable 16S rRNA gene amplicon HTS at various levels of spatial and temporal resolution. Three different mat types were identified (fresh/brackish water, intermediate and marine) that were situated along a tidal salinity gradient that were sampled during three different seasons. The most important outcome of that study was that the coastal mats of the Dutch barrier island of Schiermonnikoog are among the most diverse and species rich marine microbial ecosystems studied so far, which was in agreement with other HTS studies of similar microbial mats (Ley et al., 2006; Baumgartner et al., 2009; Armitage et al., 2012; Gobet et al., 2012). Mats from the fresh/brackish water and intermediate zones contained a large proportion of Cyanobacteria, but this group was not the most abundant as expected from their visual dominance. Proteobacteria (especially Alphaproteobacteria) and Bacteroidetes appeared as the most dominant group in all coastal mat types studied on the island of Schiermonnikoog. The Cyanobacteria were present at much lower numbers in the marine zone that is continuously affected by the tide. Bacteroidetes were found in higher numbers in the marine tidal zone. The diversity between the different mat types was far more pronounced than the changes between the different seasons at one location. Several novel taxonomic levels were identified ranging from classes to species especially among the rare types. A subsequent study used DGGE and confirmed the presence of three different mat types by the conserved clustering of the different community fingerprints in three major clusters (including Eukarya) but also exposed a considerable (micro-) heterogeneity between the communities (Bolhuis et al., 2013). Carbon flux in the active population of intertidal microbial mats in the Elkhorn Slough estuary in Central California, USA was studied using metatranscriptomics (Burow et al., 2013). The active community was strongly dominated by Cyanobacteria (80–90% of the active population) independent of the time (morning or evening) of FEMS Microbiol Ecol 90 (2014) 335–350 extraction. However, the contribution of Cyanobacteria to the DNA fraction was c. 20% of the total community, which is in agreement with the findings by Bolhuis & Stal (2011). The Elkhorn Slough mats revealed a surprisingly low number of Proteobacteria among the active community which was unexpected given the known contribution of this group of Bacteria to essential processes such as the sulfur cycle and is in contrast with studies on similar mats in which Proteobacteria were often found to be the dominant group. These mats also evolved net H2 under anoxic conditions in the dark through cyanobacterial (Microcoleus) fermentation (Burow et al., 2012). Sulfatereducing bacteria (Desulfobacteriales) oxidized part of this H2 but insufficiently so to leave a net efflux (Burow et al., 2014). Only Chloroflexi contributed importantly to the cyanobacterial dominated mRNA pool, which was also observed in hypersaline mats suggesting an intimate relationship between Cyanobacteria and Chloroflexi (Ley et al., 2006). Metabolic reconstruction of highly expressed genes in the metatranscriptome suggests that Cyanobacteria contribute in this relationship by fermenting photosynthate (stored as glycogen) to organic acids and ethanol, which are taken up as carbon source by Chloroflexi that store it as polyhydroxyalkanoates (Burow et al., 2013). The importance of sulfur cycling by sulfide-oxidizing and sulfate-reducing prokaryotes is well established in coastal microbial mats (Canfield & Des Marais, 1991; van Gemerden, 1993; Overmann & van Gemerden, 2000). The metagenomic data presented above confirm their importance and numerical dominance as most mats are dominated by Proteobacteria important in sulfur cycling, especially the purple sulfur bacteria belonging to the Gamma-clade and sulfate-reducing bacteria belonging to the Delta-clade (Bolhuis & Stal, 2011; Armitage et al., 2012; Burow et al., 2012; Gobet et al., 2012). Hypersaline microbial mats Hypersaline mats are among the best-studied microbial mat systems. These microbial mats are found worldwide in natural occurring salt lakes and man-made salterns used for salt industries. Hypersaline microbial mats are exposed to salinities up to the crystallization point of halite (Jørgensen, 1994; Des Marais, 1995) as well as to high temperatures and to high solar radiation. These factors affect the community composition and metabolic performance of the mat organisms but apparently do not prevent the formation of a highly diverse and complex microbial ecosystem. Hypersaline mats are less affected by seasonal disruptions as found in coastal mats and continue to grow for several years resulting in multilayered structures. Whereas Archaea such as the enigmatic Haloª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved H. Bolhuis et al. 340 quadratum walsbyi often dominate the hypersaline water column (Bolhuis et al., 2004; Legault et al., 2006), hypersaline mats have a distinct bacterial signature (Ley et al., 2006; Robertson et al., 2009; Armitage et al., 2012; Harris et al., 2013). Ratios of bacterial/archaeal/eukaryal rRNA genes of 90%/9%/1% have been found in the Guerrero Negro mats confirming the bacterial dominance although with a significant archaeal contribution to the metabolic activities (Robertson et al., 2009). Also in hypersaline mats, Cyanobacteria are the dominant primary producers and are responsible for the production of a thick EPS matrix that serves among others as protection against desiccation. Sulfate-reducing bacteria, sulfur-oxidizing and anoxygenic phototrophic bacteria are vertically stratified according to microgradients of oxygen, sulfide, and light, as is the case in other types of microbial mats. Sanger sequencing already provided insight in a diverse cyanobacterial community in hypersaline mats consisting of unicellular species (e.g. Pleurocapsa, Synechococcus, and Gloeothece), filamentous nonheterocystous species such as Coleofasciculus, Oscillatoria, Leptolyngbya, Schizothrix and Phormidium, and heterocystous species such as Scytonema and Calothrix (Paerl et al., 2000; Fourcßans et al., 2004; Abed et al., 2011). The diversity of the hypersaline microbial mats of Guerrero Negro in Baja California Sur, Mexico, was investigated using Sanger sequencing of a stunning number of 119.000 nearly full-length sequences and 454 pyrosequencing of 28 000 reads of c. 200 bp (Harris et al., 2013). The taxonomic information obtained with both technologies gave congruent results. The reads were obtained from a depth profile consisting of 10 layers and revealed a phylogenetic stratification corresponding to light and geochemical gradients. Similar to coastal mats, hypersaline mats also turned out to be among the most diverse environments known. Dominant groups in these hypersaline mats were Cyanobacteria, Bacteroidetes, Proteobacteria, Spirochetes, Chloroflexi, and Planctomycetes. Among the Proteobacteria especially the Deltaproteobacteria were abundant and at lower level Alpha- and Gammaproteobacteria. Several new phylumlevel groups and many previously undetected lower level taxa were found in the bacterial domain. The hypersaline mats of Guerrero Negro contained members of more than 40 of the estimated 100 different bacterial phyla known, far more than, for example the approximately eight phyla found in the human gut microbiome (Harris et al., 2013). Dissection of a Guerrero Negro mat into 10 successive 1-mm layers revealed a correlation between the genetic gradient and the physicochemical profile of the mat (Kunin et al., 2008). Analysis of the metagenome revealed that proteins had a slight acid-shifted average isoelectric point when compared with nonhalophilic genomes revealª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved ing an adaptation to increased salinity by enriching proteins with acidic amino acids. Heterotrophy below 3 mm is important given the twofold increased proteins involved in the sugar degradation pathways (glycolysis and oxidative pentose phosphate pathway and uronic acid degradation). Cyanobacteria were found up to 50 mm depth but dominated the top 5 mm. A wide vertical distribution of the Cyanobacteria has been reported previously (Armitage et al., 2012) and may be inherent to the ability of matforming Cyanobacteria to migrate along light and chemical gradients (e.g. Richardson & Castenholz, 1987; Bebout & Garcia-Pichel, 1995; Kruschel & Castenholz, 1998; Nadeau et al., 1999). Very little is known about vertical migration of anoxygenic phototrophic bacteria and sulfate-reducing bacteria in hypersaline microbial mats. Fourcßans et al. (2006) showed that anoxygenic phototrophic bacteria positioned themselves actively by migration in the oxygen and light gradient in a hypersaline microbial mat. The same group observed also migration of certain sulfate-reducing bacteria following the daily shifting oxygen gradients in the same mats, although other groups appeared to be uniformly distributed (Fourßcans et al., 2008). These authors based their conclusions on temporal and spatial T-RFLP profiles of anoxygenic phototrophic bacteria and sulfate-reducing bacteria in the mat during a day–night cycle, but did not actually observe migratory behavior of these organisms as they did for the Cyanobacteria in that mat. HTS has not yet been applied to investigate the question of migratory behavior in microbial mats. HTS based phylogenetic analysis of bacterial species in a hypersaline microbial mat from the Cuatro Cienegas Basin, Mexico revealed the abundance of Pseudomonads, Sphingomonadales, and Sphingobacteria (Bonilla-Rosso et al., 2012). This hypersaline mat from a red colored desiccation pond was less diverse than a nearby lower salinity green mat and had a low evenness in which a few species already made up for more than 50% of the diversity. Genomic recruitment analysis showed that the cosmopolitan C. chthonoplastes is the most dominant Cyanobacterium in this hypersaline microbial mat and likely is the primary producer, which in relative low numbers maintains high numbers of metabolically versatile heterotrophs. For instance, the dominant Pseudomonas sp. has broad catabolic and transport capabilities and is also capable of forming biofilms (Davies et al., 1993). Hot spring microbial mats Hot springs and their geological and physicochemical features have been investigated since the 19th century. The interest on their microbial inhabitants started in the FEMS Microbiol Ecol 90 (2014) 335–350 Molecular ecology of microbial mats 1950s with the isolation of thermophilic bacteria (Marsh & Larsen, 1953). Currently, there is much interest in hot spring environments because enzymes of their inhabitants may possess potential value for biotechnological applications. The hot spring microbial mats are natural model systems for the study of life under extreme conditions and for the presumed conditions under which life developed on early earth (Ward et al., 1998). Hot spring environments often combine high temperature (between 50 and 91 °C) with an acidic pH and a high sulfide concentration, which restrict the diversity of life and limit it to Bacteria and Archaea. When compared to other types of microbial mats, hot spring environments often lack seasonality and only undergo irregular changes in light intensities (except those related to the diurnal cycle), temperature, pH, and sulfide concentrations. The composition of microbial mats seems to be largely determined by temperature (Miller et al., 2009). The complexity of the community decreases with temperature and vice versa. At higher temperature primary production is largely covered by sulfide oxidation while oxygenic and anoxygenic photosynthesis contribute considerably more to primary production, which allows for the diversification of the mat community (Everroad et al., 2012). Photosynthetic hot spring microbial mats can be produced by thermophilic Cyanobacteria (oxygenic mats), by anoxygenic photosynthetic bacteria (Chloroflexus mats) or acidophilic anoxygenic phototrophic bacteria (Chlorobium mats) and by combinations thereof (Bateson et al., 1989; Ward et al., 1998). Miller et al. (2009) found that either Cyanobacteria or Chloroflexi dominated hot spring mats, and these authors conceived that the two groups of microorganisms compete for a limiting resource. Hot springs are geographically isolated and therefore represent dispersal barriers that resulted in the genetic isolation of the microorganisms that form the microbial mats in these environments (Miller et al., 2007; Takacs-Vesbach et al., 2008; Lau et al., 2009). Microbial mats in the Mushroom and Octopus Springs in Yellowstone National Park (WY) have been used as model system for more than three decades to decipher the structure and function of microbial communities living in these high temperature habitats (Brock, 1978; Ward et al., 1998, 2006; Ward & Castenholz, 2002; Klatt et al., 2011, 2013a, b). These alkaline, low-sulfide mats are dominated by two major bacterial phyla – Cyanobacteria and Chloroflexi – and additional abundant species of the phyla Acidobacteria and Chlorobi (Klatt et al., 2013b). The community composition, including the different ecotypes, changes while following the gradients of light and chemical conditions without changing the functional organization of the mat (Ramsing et al., 2000; Ward et al., 2006). Notably, these authors did not observe FEMS Microbiol Ecol 90 (2014) 335–350 341 migration of the (unicellular) organisms along the physicochemical gradients in the mat. Sulfur-turf hot spring mats in Japan are dominated by colorless sulfur bacteria of the Aquifex-Hydrogenobacter group (Yamamoto et al., 1998). The rates of CO2 fixation by these bacteria were more than one order of magnitude higher than in Synechococcus sp. dominated hot spring mats (Kimura et al., 2010). This may be related to the fact that these organisms use the reductive tricarboxylic acid cycle for carbon fixation (Hall et al., 2008). In another type of hot spring microbial mat (alkaline, sulfidic, 65 °C), Kubo et al. (2011) identified three functional groups of bacteria. Aerobic chemolithotrophic sulfide-oxidizing bacteria (Sulfurihydrogenibium) were situated at the mat surface where they scavenged O2 allowing activity of the anaerobic anoxygenic phototroph Chloroflexus and the sulfate-reducing bacteria of the Thermodesulfobacterium/Thermodesulfatator group. These anaerobic bacteria used H2 as the electron donor, produced by fermentation of organic matter (Otaki et al., 2012). The sulfate-reducing bacteria provided sulfide for Sulfurihydrogenibium. No results of HTS have been published and therefore the microbial diversity of these hot spring mats is unknown. Extensive microbial diversity analysis of the Mushroom and Octopus Springs was performed using Sanger based metagenomic shotgun sequencing and amplicon sequencing of the 16S rRNA gene V3/V5 region using pyrosequencing (Klatt et al., 2011). The unicellular Cyanobacterium Synechococcus sp. dominates the surface and deep-green layers of mats located in the effluent channels of the spring with temperatures between 71 and 75 °C (the upper temperature) and 50 °C. Recruitment analysis revealed the presence of two distinct populations of Synechococcus sp. strains A and B’ that were previously identified by DGGE analysis of the 16S RNA gene (Ward et al., 2006). Analysis of different mat layers suggested that different Synechococcus populations adapted to different light conditions, temperature, and pH, which have steep vertical gradients in the mats. Overall, the assembled metagenomic sequences indicated the presence of six dominant chlorophototrophic populations and several novel community members belonging to the Chlorobiales (Klatt et al., 2011). Also a novel lineage of Chloroflexi was found that include the previously described chlorophototroph Candidatus Chloracidobacterium thermophilum (Bryant et al., 2007). The distribution of microorganisms other than Cyanobacteria also followed the vertical gradients in the mats. The abundance of the anoxygenic phototroph Roseiflexus increased with mat depth, while variations in the number of Candidatus Chloracidobacterium appear to be related to the temperature gradient (62–66 °C). Liu et al. (2011) studied metatranscriptomic sequences of Mushroom Spring from four samples taken at different ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved 342 time points during a day–night cycle. Analysis of the 16S rRNA gene fraction confirmed the dominance of four bacterial taxa: Cyanobacteria, Chloroflexi, Chlorobi and Acidobacteria. Large changes in relative mRNA percentages among different time points were observed for Cyanobacteria and Acidobacteria. The mRNAs assigned to Cyanobacteria were significantly less abundant than their average rRNA content at sunset, and increased significantly in the morning when the mat was fully illuminated. The mRNAs affiliated to Acidobacteria were highly abundant at sunset and in high-intensity light in the morning and significantly lower at sunrise and low-intensity light. Earlier reports on the expression of Synechococcus spp. genes involved in photosynthesis and nitrogen fixation (Steunou et al., 2008) during a day–night cycle were confirmed. Transcriptome analysis of Mushroom hot spring mat samples taken at an hourly interval during a 24-h period revealed that chlorophototrophic members of the Chloroflexi transcribe several photosynthesis related genes during the night (Klatt et al., 2013a). These include genes encoding the type 2 photosynthetic reaction centers (pufLM), genes encoding the chlorosome envelope and genes involved in bacteriochlorophyll biosynthesis. Klatt et al. (2013a) proposed that the Chloroflexi grew by fermenting the cyanobacterial produced glycogen and synthesize bacteriochlorophyll and components of the photosynthetic apparatus as well as polyhydroxyalkanoates and wax esters that are used as carbon source during daytime. Whether protein synthesis for the expressed genes is also initiated in the dark or that the mRNA remains stable until transcription is still unknown. Bird’s eye view on mat diversity The recent studies using next generation sequencing techniques confirm the major building blocks of microbial mats. Distinct functional groups find their optimal niche in a narrow region along the geochemical gradients of a mat leaving a colorful visible layering in the sand. These groups and their function were already identified some decades ago using for that time conventional methods (Stal et al., 1985; van Gemerden, 1993). Today, HTS has become the method of choice and in this fast moving field of research the new techniques and technologies continue to produce more DNA and RNA sequence data with higher precision, longer read lengths, and greater ease of producing long contigs or even full genomes can be assembled from metagenomic data. The high taxonomic resolution with which the present day techniques can assess microbial diversity warranted a reappraisal of descriptive studies, but now provides a near complete insight in the full diversity of microbial ecosystems. ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved H. Bolhuis et al. Studying microbial mats with HTS techniques led to a number of interesting discoveries. One of the major findings was the enormous species richness and diversity especially in coastal and moderate saline microbial mats, which are now considered to be among the most diverse microbial ecosystems on earth. Mats in hot springs and in hypersaline crystallizer ponds are characterized by a much lower diversity, apparently because each of these systems approach the environmental limits of which life is possible. Microbial mats are dominated by bacterial species, even in the most extreme environments, that are otherwise dominated by Archaea (Casamayor et al., 2002). Finally, the visually abundant Cyanobacteria are often not numerically the most dominant species but they remain the major group of primary producers that fuel the ecosystem. One of the recurring questions in microbial ecology is how an ecosystem is capable of maintaining such high species diversity, especially with respect to the rare biosphere tail of species distribution (Pedr os-Ali o, 2006, 2007). As niche theory predicts, areas of high resource heterogeneity will support a large diversity of taxa (Macarthur & Levins, 1967). Microbial mats harbor an enormous geomorphological and biogeochemical heterogeneity with steep biogeochemical gradients along a water-sediment-air interface that result in a large number of potential ecological niches for microorganisms. Moreover, coastal microbial mats are, in contrast to the more constant conditions in hypersaline and hot spring mats, also exposed to strong fluctuations in environmental factors that generate ecological niches in a temporal manner. It comes therefore as no surprise that coastal microbial mats appear to be among the most diverse marine microbial ecosystem. Equal high diversities are found in hypersaline mats but only at salinities well below saturation. The plethora in potential niches can be occupied by different functional groups of microorganisms from various phylogenetic lineages (Bonilla-Rosso et al., 2012). Indeed, microbial mats contain various unrelated species that share the same trophic level or metabolic function (e.g. the different types of sulfate-reducing and sulfide-oxidizing bacteria) but are able to colonize the mats and coexist due to the large number of potential niches (Burke et al., 2011). However, Armitage et al. (2012) argue that the layering of different phyla in microbial mats is indicative for phylogenetic clustering in these layers. These authors propose as explanation ‘habitat filtering’, which predicts that dominant species exhibit similar traits (Maire et al., 2012). Habitat filtering and niche differentiation are not necessarily exclusive and may both contribute to the observed diversity. General ecological principles also predict that more extreme environments are less diverse (Frontier, 1985). This certainly applies most prominently FEMS Microbiol Ecol 90 (2014) 335–350 Molecular ecology of microbial mats for Eukarya in aquatic hypersaline and thermal ecosystems but also for Bacteria and Archaea with only a few dominant species remaining at extreme salinities (Benlloch et al., 2002; Casamayor et al., 2002). This trend is also observed in thermal mats and hypersaline mats from crystallizer ponds that have a much lower diversity and species richness than moderate halophilic and intertidal mats (Fig. 1). However, while the diversity at the higher taxonomic levels (phyla, class, order) is low in extreme environments, there appears to be a hidden higher ‘microdiversity’ of coexisting, closely related clones of microorganisms as was shown for coexisting unicellular Cyanobacteria Synechococcus ecotypes (Melendrez et al., 2011). High microdiversity reflects the large number of available niches in a microbial mat that are occupied by a limited number of species but at a large number of varieties (ecotypes). Bacteria dominate the microbial mats that we discussed here, while Archaea and Eukarya represent only a small fraction of these mats. Archaea make up between 1% and 20% of microbial mat communities (Sievert et al., 2000; L opez-L opez et al., 2013). This number reflects more or less the abundance of Archaea in most ecosystems. For example, the global ocean survey metagenomic analysis of surface water yielded < 3% archaeal sequences, in soils the estimates vary between 1% and 5%, whereas 20% has been estimated for deeper marine waters DeLong & Pace, 2001; Yooseph et al., 2007). In hypersaline waters, the archaeal fraction can make up to 80% of the total biomass (Benlloch et al., 2002). Remarkably, these large numbers of Archaea are not found in hypersaline microbial mats in the same ponds (Ley et al., 2006; Armitage et al., 2012; Harris et al., 2013). Archaea that are present in microbial mats are predominantly halophilic Archaea (haloarchaea) and methanogens. Haloarchaea are well adapted to desiccation stress and are mainly involved in decomposition of organic matter and are found in hypersaline mats and in coastal mats after an extended period of high temperatures and draught (Bolhuis & Stal, 2011). Methanogenesis may be important in microbial mats although net methane production is not likely because of the presence of aerobic (Bacteria) and anaerobic (Archaea) methanotrophs (Ward, 1978; Potter et al., 2009). Due to the dominance of the sulfur cycle in many microbial mats, methanogenic Archaea may occupy only the niche of using noncompetitive substrates such as methylamines, which cannot be used by sulfate-reducing bacteria (Kelley et al., 2012). Comparison of metagenome sequencing data confirms that hypersaline and coastal microbial mats reveal a common phylogenetic pattern with respect to the different phyla (Fig. 1). Cluster analysis of the phyla distribution in the different mat samples shows high similarity FEMS Microbiol Ecol 90 (2014) 335–350 343 between the freshwater hot spring mats and hypersaline mats (Fig. 1a). Within the saline cluster, the hypersaline red mat sample stands out from the rest as the result of a lower diversity and domination (75%) by Proteobacteria. While it has been previously assumed that microbial (Cyanobacteria) mats are numerically dominated by Cyanobacteria, molecular analysis consistently showed that in fact Proteobacteria (especially the Alpha-, Gamma-, and Delta-lineages) and Bacteroidetes are the dominant microorganisms (Fig. 1b). Proteobacteria are important for sulfur cycling, comprising the purple sulfur bacteria (Gamma-clade: e.g. Chromatiales) and sulfate-reducing bacteria (Delta-clade: e.g. Desulfobacterales and Desulfovibrionales). Alphaproteobacteria comprising the purple nonsulfur bacteria of the order Rhodobacterales are abundantly present in coastal microbial mats, particularly Rhodobacter spp. They are versatile photoheterotrophic organisms that can adopt different trophic strategies and therefore occupy various niches in the mats (Garrity et al., 2005). Bacteroidetes are also mainly heterotrophic organisms that are active in multiple layers in the mat where they are important for carbon cycling (Harris et al., 2013). Bacteroidetes are specialized in the decomposition of high-molecular-mass dissolved organic matter in marine ecosystems (O’Sullivan et al., 2006). With an average contribution to the microbial population density of 10–20%, the Cyanobacteria may not be the most abundant group but they are undoubtedly the most prominent primary producers. Filamentous Cyanobacteria are very large when compared to most other Bacteria. Hence, in terms of biomass Cyanobacteria are the dominant component of cyanobacterial mats (Dijkman et al., 2010). Cyanobacteria are the pioneering organisms that colonize, build and establish the microbial mat and are primarily responsible for the flow of energy and elements. The requirement of Cyanobacteria for light, N2 and CO2 positions them at the mat surface. As this position comes with the toll of dehydration and exposure to UV, potential predators, and viral attack, Cyanobacteria protect themselves by excreting excess fixed carbon as EPS. In hypersaline and coastal mats, Firmicutes occur in similar numbers as Cyanobacteria (Bolhuis & Stal, 2011; Harris et al., 2013; L opez-L opez et al., 2013). Firmicutes comprise among others Bacilli and Clostridiales and are known as decomposers of organic matter and form heatand desiccation-resistant endospores that allow them to survive conditions that prevent growth. Chloroflexi, Chlorobi, Acidobacteria, and Actinobacteria are present in lower numbers in coastal and hypersaline mats, but may fulfill an important role in carbon and sulfur cycling. Hot spring mats are different and less diverse compared with hypersaline and tidal mats (Fig. 1). Terrestrial hot springs are mostly low salinity systems. Salinity is one ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved H. Bolhuis et al. 344 (a) (b) (c) Fig. 1. Comparison of the microbial diversity in hyperthermal, saline, and coastal microbial mats. (a) Chao index of the estimated richness calculated at the genus level. (b) Stacked column graph representing the relative distribution of the dominant phyla in the different mats. For visibility, this graph consists of the 12 most abundant phyla that together make up 95% of the total diversity. (c) Cluster analysis of the microbial diversity at the genus level. The data were retrieved from MG-RAST (http://metagenomics.anl.gov) and consisted of metagenomic data sets. Data sets used were Hot_mus: combined data from 4443745.3, 4443746.3 and 4443747.3 and 4443762.3 (Mushroom Springs, Yellowstone, Core A, B, D and F), Hot_octo: 4443749.3 and 4443750.3 (Octopus Springs, Yellowstone, Core F and R), Salt_red: 4442467.3 (Red Mat Cuatro Cienegas Coahuila, Mexico), Salt_green: 4441363.3 (Green Mat Pozas Azules Cuatro Cienegas Coahuila, Mexico), Salt_Guer: combined samples 4440964.3 (Guerrero Negro 0–1 mm) – 4440963.3 (Guerrero Negro 1–2 mm) – 4440965.3 (Guerrero Negro 2–3 mm) – 4440966.3 (Guerrero Negro 3–4 mm) – 4440967.3 (Guerrero Negro 4–5 mm) – 4440969.3 (Guerrero Negro 5–6 mm) – 4440970.3 (Guerrero Negro 6–10 mm), Coast_Tidal: 4548349.3 (Schiermonnikoog, the Netherlands, Tidal mat), and Coast_int: 4548350.3 (Schiermonnikoog, the Netherlands, Intermediate mat). The data sets from Guerrero Negro were combined to cover the average depth of a microbial mat. The data sets from Mushroom springs and Octopus Springs consist of the combined data from different cores. of the major drivers of microbial diversity in coastal mats (Bolhuis et al., 2013) and, hence, may also explain the difference between hot spring mats and those thriving in saline environments. The microbial community in various hot spring mats forms a cluster separated from saline mats (Fig. 1a). In addition to salinity, the low concentraª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved tions of sulfate in these hot springs are unfavorable for sulfate-reducing bacteria and may explain the low number of Deltaproteobacteria. Dillon et al. (2007) looked at the dsrAB genes encoding for dissimilatory sulfite reductase, a protein essential in the sulfate reduction pathway and showed that a highly active sulfate-reducing FEMS Microbiol Ecol 90 (2014) 335–350 Molecular ecology of microbial mats community in the Yellowstone hot springs was composed of only a few dsrAB genotypes that were especially active near the surface during the switch from net photosynthetic to net respiratory conditions at the end of the day. Hot spring mats maintain a similar functional layering of photosynthetic Cyanobacteria combined with sulfur-oxidizing Chlorobi (green sulfur bacteria) and filamentous anoxygenic phototrophic Chloroflexi. In particular, in the sulfidic hot springs, sulfide-oxidizing Chloroflexi are present (Bryant et al., 2007, 2012; Klatt et al., 2013b). Whereas in tidal and hypersaline mats, the sulfide production by sulfate-reducing bacteria is a consequence of the high concentration of sulfate in natural seawater, the sulfur cycle in the low-sulfide alkaline hot spring mats is in most cases driven by sulfide from geothermal origin or sulfide formed by sulfate-reducing bacteria in deeper layers in the sediment (Dillon et al., 2007; Smith et al., 2010). Sulfide-oxidizing bacteria produce sulfate, which drives the sulfate-reducing bacteria. Although Proteobacteria and Bacteroidetes are not among the dominant groups in hot spring microbial mats, the gammaproteobacterial genus Chromatium (Thermochromatium) is reported in the top 10 in these systems (Klatt et al., 2013b). The high number of sequences obtained per sample gives insight in the rare biosphere, comprising species that are represented in very low numbers. However, due to the short read lengths and PCR error rates that still haunt proper analysis of DNA sequences, it is difficult to position rare genotypes and to attribute functions to them. It has been postulated that the rare biosphere consists of microorganisms that have escaped predation or viral lysis and may serve as a genetic pool that supplies the community when conditions change. The importance of the rare biosphere should not be underestimated because it comprises a large proportion of the microbial community as indicated by the long distribution tails in rank-abundance curves (Pedr os-Ali o, 2007). Gobet et al. (2012) studied the potential impact of the rare biodiversity by applying multivariate cutoff level analysis of HTS data combined with geochemical data. Their analysis predicted that removing 50% of the rare biodiversity had a major effect on the community structure but experimental proof is required to validate this prediction. Future perspectives Due to the tremendous HTS efforts during the past decade, the phylogenetic diversity of microbial communities can be described to the near full extent. However, a large fraction of the obtained sequences belong to uncultivated species and the ecosystem function of these populations can only be inferred from cultivated relatives. It is clear that such inferences are highly uncertain. As a rule, FEMS Microbiol Ecol 90 (2014) 335–350 345 microorganisms possess a versatile physiology and exhibit remarkably different lifestyles. For example, the aerobic, oxygenic phototrophic Cyanobacteria can adopt an anaerobic heterotrophic lifestyle by fermenting intracellular organic carbon storage to small molecular weight organic compounds that serve as substrate for other microorganisms in the microbial mat. Hence, in the closely packed matrix of the mat these fermentation products realize a flow of substrates to a range of terminal oxidizers such as sulfate-reducing bacteria and Chloroflexi (Lee et al., 2014). Metagenomic analysis forms an important tool to understand the true genetic and potential metabolic diversity, which should be applied to microbial ecology. To overcome the problems of assembly of short reads it is advisable to produce and sequence large insert libraries (e.g. fosmids/cosmids/BAC’s) or to use novel HTS techniques that generate long sequence read lengths (PacBio or Nanopore technology). This would improve the assembly, annotation and identification of the metagenome and facilitate a more detailed analysis. Once a genetic backbone has been established, experiments can be designed that will give answers to ecological relevant questions such as how the single components interact and communicate to form a microbial mat as a single entity and how it evolves. Systems biology aims to fulfill the long coined promise to translate genetic diversity into function. This is accomplished by analyzing the individual components as well as the combined processes and interactions of an ecosystem in a holistic approach (Karsenti et al., 2011). Combining chemical, biogeochemical, ecological, and genetic data using various techniques will provide a broad picture of how individual organisms operate, how they affect their ecosystem and how other biological and abiotic processes respond to their activities. A more accurate prediction can then be made about ecosystem response to fluctuating environmental conditions and potential consequences of, for example, global change. It also requires a multidisciplinary approach and the integration of data from different techniques and experimentation to understand each shackle in the chain of events that occurs in a microbial mat. The full complexity of microbial mats is probably too large to comprehend with the current techniques and available bioinformatics tools. One approach is to carry out experiments with simplified microbial mat communities. There are two possible approaches. Synthetic microbial mat communities can be created from a select number of well-characterized and fully sequenced key species representing different functional groups. The degree of complexity of such synthetic microbial mats can be increased depending on the research question. Another approach to decrease the complexity is to generate minimal microbial ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved H. Bolhuis et al. 346 mats by diluting the natural community to a level that still contains the basic characteristics of a microbial mat (e.g. primary production by photoautotrophs, and intact carbon, sulfur and nitrogen cycles). Obviously, these minimal microbial mat communities lack the rare biodiversity but therefore might provide insight in its role, which is still debated (Pedr os-Ali o, 2007; Chen-Harris et al., 2013; Morgan et al., 2013). Artificial microbial mats that are maintained and monitored for several years offer an ideal model system to study the influence of environmental factors on community composition and metabolic pathways. Under laboratory conditions, the mats can be exposed to different levels of community complexity, different temperatures, light intensities, tidal cycles, or desiccation stress. Systems biology requires mathematical modeling of the (metagenomics) data to help understanding the function of the microbial mat and the interactions between its individual components and to predict the effect of forcing on the system (Decker et al., 2005; Marx, 2012, 2013). An additional challenge lies in the putative discrepancy between present and active populations, which becomes clear when analyzing RNA transcripts rather than DNA. Microorganisms that appear to be dominant from 16S rRNA gene analysis may be negligible when analyzing the 16S rRNA gene molecules. Transcriptomics provides insight in the actual transcribed genes but also in a yet unknown number of small RNA transcripts involved in regulation (Gierga et al., 2012). Understanding the role and action of these small regulatory RNAs is currently restricted to single isolates but would greatly benefit from synthetic microbial communities in which the total amount of data can still be understood. Another factor that complicates the picture is that RNA transcripts do not necessarily translate into the respective of protein, nor does it say anything about the actual activity of this protein. A cascade of post-translational modifications and the need for additional protein subunits and cofactors makes it nearly impossible to predict the actual activity and function and warrants the need of additional analyses at the protein production and activity level such as proteomics and metabolomics. Eventually, there is still much to learn about microbial ecosystems. The microbial systems ecology approach encompassing the enormous amount of data through HTS and simultaneously evolving bioinformatics will be the way forward understanding microbial mat communities as living entities. Acknowledgements The authors acknowledge support of the European Commission 7th Framework Programme project MaCuMBA (Marine Microorganisms: Cultivation Methods for Improvª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved ing their Biotechnological Applications) contract no. 311957. 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