rapid discrimination of newly isolated bacillales with industrial

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Laser Phys. Lett., 1–7 (2012) / DOI 10.7452/lapl.201210052Laser Physics

Letters 1

Abstract: Members of the bacterial order Bacillales have beenof great interest for agricultural, horticultural, industrial andmedical applications because of their capacity to produce var-ious extracellular enzymes. One of the challenges for Bacil-lales study is to rapidly and effectively identify and character-ize newly isolated strains. In the present study, Raman spec-troscopy was performed to identify 14 Bacillales strains iso-lated from Tibet, China. The biochemical properties of eachisolate were characterized, and several Raman bands corre-sponding to nucleic acids, proteins or saccharides were differ-ent between isolates. Multivariate analysis of 112 Raman spec-tra clearly revealed that all 14 isolates were clustered into 3groups, which was in accordance with the phylogenetic analy-sis of their 16S rRNA genes. Our results suggest that Ramanspectroscopy is an effective and promising approach that couldquickly discriminate different phylogenetic groups of Bacil-lales.

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Rapid discrimination of newly isolated Bacillales withindustrial applications using Raman spectroscopy

A.H. Deng, 1 Z.P. Sun, 1,2 G.Q. Zhang, 1,2 J. Wu, 1,2 and T.Y. Wen 1,∗

1 Department of Industrial Microbiology and Biotechnology, Institute of Microbiology, Chinese Academy of Sciences, 1 West BeichenRoad, Chaoyang District, 100101 Beijing, China

2 Graduate University of Chinese Academy of Sciences, 100049 Beijing, China

Received: 27 March 2012, Accepted: 8 May 2012Published online: 16 June 2012

Key words: Raman spectroscopy; Bacillales; 16S rRNA genes; multivariate analyses; phylogenetic analysis

1. Introduction

Bacillales is a group of gram-positive bacteria that areglobally distributed [1,2]. One important application ofmany members of Bacillales is their capacity to secretevarious enzymes (e.g. proteases, amylases, xylanases, cel-lulases, lipases, etc.) that have been widely applied in agri-culture, horticulture, industry and medicine [1,3]. Com-mercial interest in these bacteria has prompted the iso-lation of novel Bacillales strains from a variety of envi-ronments, including the deep sea, plateaus, polar regionsand other extreme environments [4,5]. A variety of meth-ods, such as physiological characterization, cellular fatty

acid profiling, G-C content, DNA-DNA hybridization, andribosomal gene-based phylogenetic analysis, have beenused for identification of newly isolated bacteria in Bacil-lales [6]. Although very powerful, these traditional meth-ods for characterization of biochemical, biophysical andphylogenetic properties of isolates are somewhat labori-ous. Efficient approaches that can rapidly and simultane-ously identify different groups of Bacillales are still re-quired [6].

Raman spectroscopy is a fast and nondestructive op-tical technique that is able to provide detailed informa-tion about the chemical composition of samples [7]. Ra-man spectroscopy is based on inelastic scattering of pho-

∗ Corresponding author: e-mail: [email protected]

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Letters A.H. Deng, Z.P. Sun, et al.: Rapid discrimination of newly isolated Bacillales

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Figure 1 The zone of protein (a), xylan (b), and starch (c) hydrolysis by newly isolated strains on agar plates containing casein, xylanand starch, respectively. C+ and C− refer to positive and negative controls, respectively

tons with molecular vibrations of the chemical bonds inthe sample [8]. This spectroscopic approach can generate“whole-organism fingerprints” of microorganisms and is,therefore, widely applied to biochemical and functionalanalysis of microbes as well as microbial ecology stud-ies [8,9]. Recently, a growing amount of research has re-vealed that Raman spectroscopy is also an effective ap-proach for the rapid discrimination of different bacterialpopulations [10-13], including those from distinct Bacil-lus groups [14,15]. For example, Hutsebaut et al. indicatedthat Raman spectroscopy could be used to robustly dis-criminate B. cereus, B. licheniformis, and B. pumilus [15].Although the authors found that culture conditions couldinfluence identification accuracy, the differences caused byculture conditions did not obscure the inter-species dis-crimination of these Bacillus bacteria [15]. In addition, athorough analysis of 68 Bacillus strains revealed that Ra-man spectroscopy could effectively identify closely relatedBacillus in the phylogenetically homogeneous B. subtilisgroup. Therefore, Raman spectroscopy is thought to be apotential approach for fast identification of Bacillus bacte-ria.

In the present study, 14 strains affiliated with the gen-era Bacillus and Paenibacillus were isolated from Ti-bet, China, and were identified to produce extracellu-lar proteases, amylases or xylanases. Their phylogeneticpositions were identified by comparing 16S rRNA genesequences. Raman spectroscopy was then performed tocharacterize and compare the biochemical compositionof these bacteria. The aim of this study is to determinewhether Raman spectroscopy can be used to rapidly dif-ferentiate different newly isolated groups belonging to theorder Bacillales.

2. Materials and methods

2.1. Strain isolation and culture conditions

Soil samples were collected from alpine meadow soil atan altitude of ∼ 4077 m (33◦34.586′N, 99◦53.899′E) inTibet, China. One gram of soil sample was suspended insterile 0.9% NaCl solution and incubated for 48 h at roomtemperature. Then, 0.05 to 0.10 ml of soil suspension was

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Laser Phys. Lett. (2012)Laser Physics

Letters 3

Strain Length, Category Nearest GenBank relative Identity, Accession no.bp (RDP tax string) (accession no. of relative) %

WYT010 1445 Bacillales; Paenibacillus pabuli 99 JQ807857Paenibacillaceae strain Gt-1 (GU201854)

WYT011 1431 Bacillales; Paenibacillus 99 JQ807858Paenibacillaceae sp. 6M01 (AM162345)

WYT002 1438 Bacillales; Bacillus 99 JQ807852Bacillaceae sp. Sd-16 (JF508419)


WYT003 1428 Bacillales; Bacillus simplex 99 JQ807853Bacillaceae strain A1-6 (JF496323)

WYT036 1440 Bacillales; Bacillus simplex 99 JQ807861Bacillaceae strain A1-6 (JF496323)


WYT039 1437 Bacillales; Bacillus 99 JQ807864Bacillaceae sp. K8SC-2 (JF799969)

WYT008 1440 Bacillales; Bacillus 99 JQ807856Bacillaceae sp. K8SC-2 (JF799969)

WYT004 1440 Bacillales; Bacillus simplex 99 JQ807854Bacillaceae strain EQH11 (FJ999940)

WYT037 1439 Bacillales; Bacillus simplex 99 JQ807862Bacillaceae strain EQH11 (FJ999940)

WYT001 1439 Bacillales; Bacillus mycoides 99 JQ807851Bacillaceae strain NBRC 3015 (AB679984)



Table 1 Strains isolated in this study, their affiliations, nearest relatives, percent similarities, and accession numbers

plated onto agar plates containing 0.05 g of yeast extract,0.10 g of tryptone, 0.15 g of NaCl and 20.00 g of agarin 1 liter of medium. After incubation for 24 – 48 h at 20 –30◦C, colonies with different phenotypes were selected forfurther analysis. The protease, amylase and xylanase activ-ities of each strain were detected on agar plates containingwith 0.5% casein, 1.0% starch, and 0.5% xylan, respec-tively.

2.2. PCR amplification of 16S rRNA genes,cloning, and DNA sequencing

Genomic DNA of isolated strains was extracted us-ing the bacteria genomic DNA extraction kit (Tian-gen, Beijing, China) according to the manufacturer’s in-structions. Nearly complete 16S rRNA genes were am-plified by using the universal bacterial primers 27F

(5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-GGTTACCTTGTTACGACTT-3′) [16]. PCR was con-ducted in a final volume of 50 µl using 0.2 mM of eachof the four dNTPs, 1.25 U Taq DNA polymerase (Ex Taq,TaKaRa, Dalian, China) with 1× Taq buffer (MgCl2 plus),8 pmol of each primer, and 0.5 µl of template DNA. ThePCR conditions were 94◦C for 10 min, 30 cycles of 94◦Cfor 0.5 min, 54◦C for 0.5 min, and 72◦C for 1.5 min, fol-lowed by a final 5-min extension at 72◦C. The PCR prod-uct was purified by 1% (wt/vol) agarose gel electrophore-sis.

The purified PCR product was cloned into the pMD19-T vector and chemically competent DH5α cells (TaKaRa,Dalian, China) by following the manufacturer’s instruc-tions. The transformed cells were incubated overnight onLuria-Bertani agar plates with ampicillin. Clones wererandomly selected and were sequenced using an ABI3730genetic analyzer (Beijing Genomics Institute, Beijing,China).

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Figure 2 (online color at www.lasphys.com) Maximum-likelihood phylogenetic tree of 16S rRNA gene sequences and the averageRaman spectra of newly isolated strains. Numbers at the nodes are ML bootstrap proportions. Note that three well-supported groupsare present in the tree

2.3. Phylogenetic analysis

The resulting 16S rRNA gene sequences were checked forchimera formation with the Bellerophon server [17] be-fore being compared with the GenBank database usingthe BLAST program to search for related sequences withhigh similarities [18]. The sequences were then alignedusing MUSCLE [19], and the phylogenetic trees wereconstructed utilizing a maximum-likelihood (ML) methodbased on the data-specific model [20]. The tree with thehighest log likelihood (–4214.4730) was selected. A dis-crete Gamma distribution was used to model evolutionaryrate differences among sites (5 categories (+G, parame-ter = 0.4325)). The rate variation model allowed for somesites to be evolutionarily invariable ([+I], 34.2778% sites).Evolutionary analyses were conducted using MEGA5[21].

2.4. Raman spectroscopy

Samples for Raman analysis were prepared by transferringa single colony onto a slide as described by Maquelin et al.[22]. Raman spectroscopy was performed using an InVia-Reflex confocal Raman microscope (Renishaw, England).A 532-nm laser was employed with a power of ∼ 8 mW

at the sampling point. Each sample was focused under a100× objective, and a single spectrum was collected fromthe 100 to 2000 cm−1 Raman shift range. The spatial reso-lution of the setup was ∼ 1 µm in the lateral direction and∼ 2 µm along the vertical direction.

2.5. Spectral and multivariate analyses

For each strain, 8 spectra were randomly collected to com-pensate for potential biological variance, resulting in a to-tal of 112 spectra. The WiRE 3.0 software package wasused for spectral analysis, including baseline correction,smoothing, and normalization (Min-Max) with default pa-rameters. The acquired spectral ranges were reduced to400 – 1800 cm−1 to highlight the fingerprint region for fur-ther multivariate analyses.

Multivariate analyses, including principal componentanalysis (PCA), discriminant function analysis (DFA), andhierarchical cluster analysis (HCA), were performed us-ing the multivariate analysis package PyChem 3.0.5 [23].First, PCA analysis (with the following parameters: corre-lation matrix; non-iterative partial least squares; 10 PCs)was used to reduce the dimensionality of the spectral data.Principal components 1 – 10 were subsequently used for



Letters 5

Peak no. Peak position, cm−1 Suggested assignment Reference1 600.48 Triolein [25]2 747.90 O-P-O symmetric stretching, or L-Phenylalanine [8,25]3 780.52 Cytosine, uracil [8]4 1002.42 Phenylalanine, or β-D-glucose, or N-Acetyl-D-glucosamine [8,25]5 1127.44 Protein C-N, C-C stretching [12]6 1171.82 12-Methyltetradecanoic acid, or 15-Methylpalmitic acid, or Acetoacetate [25]7 1311.96 D-(-)-Arabinose [25]8 1337.86 Adenine, guanine, tyrosine, tryptophan [8]9 1447.62 Protein, or δ(C-H2) deformation, or CaDPA [8,25]

10 1585.24 L-Phenylalanine [25]11 1662.52 Amide I [8]

Table 2 Tentative assignment of biochemical bands identified using Raman spectra. For peak numbers, please see Fig. 2

DFA analysis. DFA was conducted to discriminate be-tween groups using the Fisher ratio with a priori knowl-edge of the class structure. HCA was also performed basedon the DFA scores using the Euclidean distance.

3. Results and discussion

Fourteen microbial colonies exhibiting different pheno-types, all of which were aerobic and rod-shaped, wereisolated from Tibetan soils. These isolates were then pu-rified, reserved and tested for extracellular enzymes onagar plates containing different substrates. As shown inFig. 1a, large proteolytic zones were detected aroundthe colonies of strains WYT001, WYT034, WYT007,WYT039, and WYT008, which indicated that these iso-lates exhibited a better ability to secrete proteases. Iso-lates WYT035, WYT037, WYT038, WYT004, WYT010,WYT011, WYT002, and WYT003 exhibited moderateproteolytic abilities. As shown in Fig. 1b and Fig. 1c,strains WYT010 and WYT011 showed high amylase ac-tivities and moderate xylanase activities. These newly iso-lated strains, taken together, can produce extracellular pro-teases, amylases or xylanases and could be used as enzymeresources for future industrial and biotechnological appli-cations.

Nearly complete 16S rRNA gene sequences of allnewly cultivated strains were amplified and phylogeneti-cally analyzed. The similarities among these 14 sequencesranged from 88 to 99%. The values for sequence similar-ities to the nearest published sequences and the phyloge-netic affiliations of these sequences are summarized in Ta-ble 1. All sequences were highly similar (99%) to the pub-lished sequences belonging to the order Bacillales. Most ofthe isolates were affiliated with the genus Bacillus, whilestrains WYT010 and WYT011 fall into the genus Paeni-bacillus (Table 1).

Phylogenetic analysis revealed that all new sequencescould be divided into three major evolutionary groups

(Fig. 2). Two strains (WYT010 and WYT011) werefound to constitute Group 1. Group 2 included iso-lates WYT008, WYT035, WYT036, WYT037, WYT038,WYT039, WYT002, WYT003, and WYT004, with in-group similarities ranging from 98 to 99%. StrainsWYT034, WYT007, and WYT001 were affiliated withGroup 3 and the in-group similarities were larger than99%. The phylogenetic divergence between these threegroups ranged from 6 to 12%, greater than the cut-off point(3%) for species definition [24], suggesting that these iso-lates likely represent three different species.

Raman spectroscopy has been proved to be a fast andnondestructive analysis tool to identify microbes, the spec-tra of which contain information about biomolecules inwhole cells [25]. The averaged Raman spectra of the 14isolated Bacillales strains are shown in Fig. 2. Tentativeassignments of typical Raman bands are summarized inTable 2. As shown in Fig. 2, several bands, including bands2, 5, and 10 (potential amino acids bands), band 6 (poten-tial fatty acids and fats), band 7 (potential saccharides),and band 8 (potential nucleic acids), are observed in allRaman profiles, indicating that the “chemical fingerprints”of these strains were somewhat similar. However, certaindiscrepancies in band heights could be visually detected.For example, the nucleic acid band (band 3 in Fig. 2) inGroup 3 is much more prominent than that in the other twogroups, while the protein and saccharide bands (bands 4, 9,and 11) in Group 1 and Group 3 are more prominent thanthose in Group 2. These differences in Raman spectral sig-natures might reflect that the cellular constituents of strainsare different among these three groups; therefore, Ramanspectra are potentially useful to identify and discriminatethe three Bacillales groups isolated in the present study.

To determine whether Raman spectra could effec-tively and reproducibly discriminate between these iso-lates, spectral data were analyzed using multivariate anal-yses. PCA was conducted to reduce the dimensionality ofthe spectra data to 10 principal components (PCs). ThesePCs scores were used as the input into the DFA algo-


6Laser Physics


rithm. Fig. 3a has shown the DFA scatter plots of the Ra-man spectra for all 14 isolates in this study. Eight Ra-man spectra were used for each strain in this study. Itis clearly shown that these 112 spectra clustered into 3groups, which was in accordance with the evolutionarygroups based on the phylogenetic analysis in Fig. 2. Toprovide an additional perspective on the relationships be-tween the individual isolates, a HCA dendrogram was gen-erated based on the DFA scores, which confirmed the sep-aration of all isolates into three clusters (Fig. 3b).

Previous results have revealed that Raman spectralanalysis is a powerful approach to characterize the macro-molecular composition of a single cell [26]. Analysiswith Raman spectra is reported to even distinguish dif-ferent physiological statuses (e.g. logarithmic and sta-tionary phase) within a single bacterial strain, althoughthese differences are not greater than the differences be-tween species [9]. The results presented in this studyclearly show that Raman spectra can effectively discrim-inate different phylogenetic populations of Bacillales bac-teria, which are consistent with previous studies [14,15]and suggests that Raman analysis is a potentially usefultool for quickly characterizing and identifying newly iso-lated bacterial strains. It is widely accepted that bacterialRaman spectra reflect phenotypes of microorganisms, andthe reasons behind successful species differentiation usingRaman spectra are so far unknown. One possible expla-nation is that taxonomic different bacteria may representdistinct cellular architectures, that is, each species exhibitsdifferences in their cellular macromolecular compositions[26]. Nevertheless, the true causes for successful differ-entiation of different Bacillales groups by Raman spectraare to be further studied. Our results indicate that Ramanspectra, together with traditional physiological character-istics and sequence-based phylogenetic analysis, consti-tute a powerful tool for better characterizing novel isolatedBacillales strains. Furthermore, complementary to othersingle-cell analysis methods, such as fluorescence in situhybridization [27], Raman spectra is also a promising ap-proach for characterizing uncultivated microorganisms innature.

4. Conclusion

In the present study, 14 strains belonging to the orderBacillales were isolated from Tibet, China. These iso-lates could be divided into three evolutionary groupsbased on the phylogenetic analysis of 16S rRNA genes.Raman spectroscopy was then applied to identify thesestrains. The biochemical differences of isolates belong-ing to different evolutionary groups were reflected in theRaman profiles. Several bands corresponding to nucleicacids, proteins and saccharides were apparently differ-ent between each group. DFA and HCA analyses clearlyrevealed that the 14 isolates were clustered into threegroups, which was consistent with phylogenetic analy-sis. Our study has demonstrated that Raman spectroscopy

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Figure 3 (online color at www.lasphys.com) (a) PC-DFA plotsfor Raman spectra of all isolated strains and (b) a dendrogramgenerated by HCA. Both analyses clearly revealed that threegroups were formed based on Raman spectroscopy results

is a rapid and effective approach for discriminating phy-logenetically different Bacillales populations. Therefore,taking our findings together with those of other stud-ies [14,15], it is reasonable to suggest that Raman spec-troscopy is potentially useful for fast characterization anddiscrimination of bacteria in the Bacillales.

Acknowledgements We thank Dr. Wei Lin at the Institute of Ge-ology and Geophysics, CAS, for his technical assistance and dataanalysis. This work was supported by the State Key Labora-tory of Microbial Resources, the Institute of Microbiology, theChinese Academy of Sciences (Grant SKLMR-20110604), theNational Hi-Tech Research and Development of China (Grant2007AA02Z212), and the Key Project of Chinese Academy ofSciences (Grant KSCX2-YW-G-075-22).



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rapid discrimination of newly isolated bacillales with industrial

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