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Discrimination between Bacillus and
Alicyclobacillus Isolates in Apple Juice by Fourier
Transform Infrared Spectroscopy and
Multivariate Analysis
Murad A. Al-Holy, Mengshi Lin, Omar A. Alhaj, and Mahmoud H. Abu-Goush
Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared
spectroscopy (FT-IR) was used to identify and discriminate between 4 Alicyclobacillus strains and 4 Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm−1 reflected the most distinctive
biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (for example, principal component
analysis and soft independent modeling of class analogy) were used to analyze the spectral data. Distinctive separation
of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate
analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus
and to distinguish between species belonging to these 2 genera.
Abstract:
This research provides further evidence that Fourier transform infrared spectroscopy spectroscopy
can be used rapidly and effectively to detect the spoilage of apple juice caused by Alicyclobacillus strains and to discriminate
between Bacillus and Alicyclobacillus strains in apple juice.
Practical Application:
Introduction
Alicyclobacillus is a spore-forming acidophilic and thermophilic
bacterium that can potentially cause spoilage in acidic beverages
(Silva and others 1999; Lee and others 2002). This bacterium was
previously considered as a part of the Bacillus genus but was then
reclassified as a new genus (Alicyclobacillus) using the 16S rRNA
comparative sequence analysis (Wisotzkey and others 1992; Chang
and Kang 2004). Alicyclobacillus spp. are nonpathogenic Gram positive, rod-shape, and spore-forming bacteria. Alicyclobacillus spp.
have been linked to spoilage of acidic beverages with a characteristic medicinal off-odor in commercially pasteurized apple juice
(Chang and Kang 2004). This microorganism is considered as one
of the most important target spoilage organisms in acidic foods
because Alicyclobacillus spores are able to germinate and proliferate in high acid environments and produce guaiacol that causes
medicinal off-flavor in apple juice (Yamazaki and others 1997).
Similarly, Some Bacillus spp. including Bacillus coagulans can cause
flat-sour type spoilage in heat processed acidic beverages, tomato
juice, and acidified vegetable products because they form heatresistant spores that can grow at low pH (Vercammen and others
2012). Spores of B. coagulans are able to germinate and grow at
MS 20141707 Submitted 10/14/2014, Accepted 12/4/2014. Authors Al-Holy
and Abu-Goush are with Dept. of Clinical Nutrition and Dietetics, Faculty of Allied
Health Sciences, Hashemite Univ., Zarqa-Jordan 13115, Zarqa Governorate. Authors
Lin is with Food Science Program, 256 William Stringer Wing, Univ. of Missouri,
Columbia, MO 65211, U.S.A. Authors Alhaj is with Dept. of Food Science and
Nutrition, College of Food and Agricultural Sciences, King Saud Univ., P.O. Box
2460, Riyadh 11451, Saudi Arabia. Direct inquiries to Author Al-Holy (E-mail:
[email protected]).
R
C 2015 Institute of Food Technologists
doi: 10.1111/1750-3841.12768
Further reproduction without permission is prohibited
pH values between 3.7 and 4.5 pH and are naturally present in
fruit juices such as apple and orange juices (Mallidis and others
1990; Daryaei and Balasubramaniam 2013). Furthermore, it was
reported that Bacillus licheniformis and Bacillus subtilis can grow in
acidic and acidified foods such as tomato juice and acidified carrot
juice (Rodriguez and others 1993; Tola and Ramaswamy 2014).
Therefore, it is important to discriminate between Bacillus and
Alicyclobacillus in acidic beverages such as apple juice. In addition,
it is important to discriminate between different Alicyclobacillus
spp. because not all Alicyclobacillus spp. are capable of producing
guaiacol, the substance that gives rise to an objectionable off-odor
in acidic beverages.
Currently, detection of Alicyclobacillus is achieved by several
methods, including molecular methods such as PCR or 16S
rRNA gene sequence analysis (Yamazaki and others 1997;
Murakami and others 1998; Cerny and others 2000), and the
combination of membrane filtration with optimized recovery
media (Chang and Kang 2004). However, these methods are
generally labor intensive, time-consuming, and require skilled
personnel to conduct product testing. Furthermore, detection
results are always contingent upon different isolation protocols.
Chang and Kang (2004) reported that many products containing
Alicyclobacillus remained undetected and resulted in spoilage
reported by consumers. Therefore, it will be prudent to develop
a rapid and sensitive method to detect Alicyclobacillus spp. in apple
juice and to differentiate it from its closely related genus, Bacillus;
because some Bacillus spp. such as B. megaterium and B. sutilis are
also guaiacol producers as Alicyclobacillus (Smit and others 2011).
Fourier transform infrared spectroscopy (FT-IR) has shown
capacity to provide a rapid, nondestructive analysis to generate
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Keywords: Alicyclobacillus, Bacillus, FT-IR, PCA, spectroscopy
Discrimination between Bacillus and Alicyclobacillus . . .
relevant information on microbial classification and identification
(Alvares-Ordonez and others 2011). FT-IR needs minimum sample preparation and only takes a few seconds to collect a full spectrum. Alongside, FT-IR can provide insight regarding different
components in cell wall and cytoplasm, such as proteins and peptides, polysaccharides, peptidoglycan (murein), and phospholipids.
The capability of the FT-IR technique to differentiate between
microorganisms involves revealing differences in the molecular vibrations of the examined chemical species in the infrared (IR)
region. Hence, subtle differences in the chemical composition of
microbial cell contribute to a typical and unique IR spectral fingerprint (Al-Holy and others 2006). Based on its capacity, the
FT-IR technique has been extensively studied to identify and differentiate between many microbes of a particular significance to
food. It has been elucidated that FT-IR spectroscopy in combination with multivariate statistical analysis techniques was successfully used to discriminate between several spp. of Bacillus such
as Bacillus cereus, Bacillus mycoides, and Bacillus thuringiensis (Beattie
and others 1998). In addition, FT-IR technique was successfully
used to differentiate between the probiotic B. cereus strains and
other wild types such as B. cereus, B. thuringiensis, and B. mycoides
(Mietke and others 2010). Nonetheless, the Bacillus strains used in
the aforementioned study were tested in a pure culture but not in
a real food system.
In addition, FT-IR technique has been used to identify and classify many microorganisms including yeast, cyanobacterial strains,
lactic acid bacteria, Bradyrhizobium japonicum, Listeria spp., Staphylococcus spp., Clostridium spp., and Escherichia coli O157:H7 (Zeroual
and others 1994; Holt and others 1995; Lefier and others 1997;
Goodacre and others 1998; Kümmerle and others 1998; Kansiz
and others 1999; Oberreuter and others 2000; Al-Holy and others
2006). FT-IR analysis was also capable of discriminating and identifying pathogenic strains of Listeria monocytogenes (Rebuffo-Scheer
and others 2007). Schawe and others (2011) also demonstrated that
FT-IR spectroscopy can be used to quantify bacterial species individually even when bacterial cells are present in a mixed culture
and at different growth phases. In this study, FT-IR spectroscopy
was investigated, since it is a rapid and easy-to-use technique that
requires minimal sample preparation. Therefore, the aim of this
study was to evaluate the potential of using FT-IR spectroscopy
to discriminate between Bacillus spp. and Alicyclobacillus spp. inoculated into apple juice. A 2nd objective was to investigate the
capability of this technique to differentiate between species that
belong to each of Bacillus and Alicyclobacillus, respectively.
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Figure 1–Representative FT-IR spectra of
Bacillus spp. (A) and Alicyclobacillus spp.
(B) recovered from inoculated apple juice.
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Discrimination between Bacillus and Alicyclobacillus . . .
Preparation of bacterial cultures
The bacterial strains used in this study were obtained from the
culture collection of the Food Microbiology Lab at Washington
State University. Four Bacillus strains (B. cereus ATCC 10876 and
ATCC 13061, B. coagulans, and B. subtilis isolate). The latter 2
Bacillus strains were isolated from apple juice. Four Alicyclobacillus
isolates were used, A-Gala 2-1, 18-1, 14-2, and C-Fuji 6. All
of the Alicyclobacillus isolates are apple juice isolates. The Bacillus
isolates were kept on tryptic soy agar (TSA; Difco Laboratories,
Detroit, Mich., U.S.A.) slants and were resuscitated aerobically
prior to experiment on TSA for 24 h at 37 °C and then transferred
to 10 mL of brain heart infusion (BHI; Difco Laboratories) broth.
Although, the Alicyclobacillus strains from refrigerated slants were
activated by streaking onto potato dextrose agar (PDA, pH 5.6,
Beckton, Dickenson, Cockeysville, Md., U.S.A.) at 43 °C for
48 h. A representative colony was then inoculated into 10 mL
of BHI and incubated at 37 °C for 48 h. At this point, the cells
(approximately 106 to 107 CFU/mL) were ready for further use.
Apple juice inoculation
Apple juice (pH 3.7; Treetop Inc., Selah, Wash., U.S.A.) was
purchased from a local grocery store in the day the experiments
conducted. Samples of 50 mL of apple juice were inoculated individually with 1 mL of BHI containing either Bacillus or Alicyclobacillus isolates. Each of Bacillus and Alicyclobacillus was grown in
apple juice for 1 wk at 43 °C, then harvested by centrifugation of
50 mL of apple juice at 4000 rpm for 15 min. The obtained pellet
was resuspended again into 9 mL of 0.9% saline and centrifuged
again as mentioned earlier. The process was repeated twice to
remove residual apple juice and bacterial metabolites. The resulting pellet was suspended into 3 mL of 0.9% saline solution and
vortexed vigorously to obtain a homogeneous cell distribution.
Thereafter, an aliquot of 500 μL of the bacterial suspension was
dispensed onto an aluminum oxide membrane filter (0.2 μm pore
size, 25 mm OD; Anodisc, Whatman Inc., Clifton, N.J., U.S.A.).
Similarly, 500 μL of apple juice was applied onto an Anodisc
membrane as a control. The Anodisc filters were subsequently
air dried under laminar flow at room temperature for 1 h to allow the formation of a homogeneous dried film of bacterial cells.
The experiment was repeated in duplicate. Bacillus counts were
determined using a standard spread plating method on TSA. The
plates were incubated at 37 °C for 24 h. Alicyclobacillus counts were
determined on PDA and the plates were incubated at 43 °C for
48 h.
FT-IR spectroscopy
Thermo Nicolet Avatar 360 FT-IR spectrometer (Thermo
Electron Inc., San Jose, Calif., U.S.A.) was used for the FT-IR
spectra collections. To collect spectra, the Anodisc membrane filters coated with homogeneous bacterial cells were placed in direct
contact with an attenuated total reflection (ATR) zinc selenide
(ZnSe) crystal as described by Schmitt and Flemming (1998).
Sixty spectra of each sample were acquired at room temperature
for each bacterial isolates. FT-IR spectra were recorded in the
range of 500–4000 cm−1 and the resolution of measurements was
set as 4 cm−1 with average of 36 scans for each spectral collection.
Multivariate analysis
Data analysis were carried out using OMNIC (Thermo
Electron Inc.) and Delight version 3.2.1 (Textron Systems,
Wilmington, Mass., U.S.A.) softwares. FT-IR spectral features
often look similar and differences between bacterial strains are
very subtle. Therefore, some data preprocessing algorithms were
employed to analyze the data, such as binning, smoothing, and
2nd derivative transformation (Lin and others 2003). The spectra
were smoothed using Gaussian function over 4 cm−1 followed
by 2nd derivative transformation with a gap value of 12 cm−1 .
The principal component analysis (PCA) was used to analyze the
spectral data. PCA, one of the most commonly used multivariate
statistical analysis technique, has been widely employed in the
interpretation and extraction of infrared spectral data variance. It
reduces a multidimensional data set to its most dominant features,
removes the random variation (noise), and retains the principal
components (PCs) that capture the related variation (Goodacre
and others 1998). PCA analysis shows whether there are natural
clusters in the data and describes similarities or differences from
Figure 2–Principal components analysis (PCA)
of Bacillus (BC ATCC 10876, BC ATCC 10361,
B. subtilis, and B. coagulans) and
Alicyclobacillus (A-Gala 2-1, 18-1, 14-2, and
C-Fuji 6) isolated from inoculated apple juice.
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Materials and Methods
Discrimination between Bacillus and Alicyclobacillus . . .
multivariate data sets (Martens and Naes 1989). Soft independent
modeling of class analogy (SIMCA) was used to assign test samples
to a category based upon the analogy of the spectra for the test
sample to those in a training set (Lin and others 2005).
Results and Discussion
FT-IR spectroscopy was used in this study to discriminate
between isolates of Bacillus and Alicyclobacillus inoculated into
apple juice. Bacillus spp. and Alicyclobacilluss pp. counts ranged
between 1.1 × 105 and 7.8 × 106 CFU/mL of apple juice.
The ability of the FT-IR spectroscopy to differentiate between
microorganisms relies on detecting discrepancies in molecular
vibrations of the tested chemical species (Al-Holy and others
2006). These differences originate mainly from slight differences
present in the bacterial cell wall and cell membrane as well
as in the composition of bacterial cytoplasm (Al-Qadiri and others
2006).
Figure 1 shows representative spectra of 4 different isolates of
Bacillus and other 4 isolates of Alicyclobacillus. The FT-IR absorbance spectra exhibited by each bacterial strain are related to
the interaction between FT-IR spectra and the generic functional
groups found in bacterial cellular constituents. Each bacterial strain
elicited a unique absorbance pattern between 500 and 4000 cm−1 .
One of the main compositional differences that distinguishes Alicycclobacillus from other Bacillus spp. is the presence of ω-alicyclic
fatty acids predominantly in their cell membrane (Smit and others
2011). The absorption peaks noticed around 2850 to 3000 cm−1
emanate mainly from the CH2 and CH3 stretching vibrations of
fatty acid in bacterial cell wall. In the case of Alicyclobacillus spp.,
these vibrations possibly come from the presence of ω-alicyclic
fatty acids as a unique and major cell membrane constituent (Lin
and others 2005). Although ω-alicyclic fatty acids are characteristic components of Alicycclobacillus spp., some Bacillus spp. were
found to contain ω-alicyclic fatty acids too, albeit in small quantities (Smit and others 2011). Therefore, the presence of ω-alicyclic
fatty acids in relatively higher concentrations compared to Bacillus
spp. may impart certain differences in the FT-IR spectra of the 2
genera.
Additional prominent peaks were noticed at around 1600 and
1700 cm−1 , most likely originate from protein amide and from
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Figure 3–Loading plots of 1st 3 principal
components (PCs) obtained from PCA of FT-IR
spectra.
Figure 4–SIMCA classification of 4 Bacillus ()
and Alicyclobacillus (•) strains.
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Discrimination between Bacillus and Alicyclobacillus . . .
of the correctly classified spectra increases, the characteristics of
the tested samples show more similarity to the training set. Using
SIMCA analysis, it was possible to correctly classify around 78% of
the spectra of Bacillus strains and approximately 79% of the spectra
of Alicyclobacillus strains. Therefore, this technique could be used
to discriminate between Bacillus and Alicyclobacillus isolates. In a
study by Rodriguez-Saona and others (2001), SIMCA exhibited
a good cluster separation between closely related isolates of Escherichia coli and Bacillus spp. (B. cereus and B. thuringiensis) spiked
into apple juice. Lin and others (2005) successfully used SIMCA to
correctly classify and differentiate between guaiacol producing and
non-guaiacol producing strains of Alicyclobacillus. SIMCA was also
employed to compare spectral features of 3 foodborne pathogens
(E. coli O157:H7, Campylobacter jejini, and Pseudoomonas aeruginosa)
exposed to cold stress injury. SIMCA successfully segregated intact and injured cells of each particular pathogen and differentiated
between the 3 pathogens present in low nutrient media (Lu and
others 2011).
Conclusions
This study demonstrated the capability of the FT-IR spectroscopy in combination with multivariate analysis techniques to
discriminate between phenotypically and compositionally related
genera (Bacillus and Alicyclobacillus) in apple juice. In addition,
the technique showed a potential to discriminate between closely
related species that belong to the Bacillus and Alicyclobacillus genera. This method may serve as a helpful tool to rapidly identify
Bacillus and Alicyclobacillus contamination in apple juice industry
and therefore may help in detecting and preventing apple juice
spoilage.
Acknowledgments
The authors thank Dr. Barbara Rasco from Washington State
University for providing the bacterial strains used in the study.
The authors also thank the Fulbright program in Jordan and the
Hashemite University for partially funding this work.
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Discrimination between Bacillus and Alicyclobacillus . . .
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