Raman microspectroscopy as an identification tool within the phylogenetically homogeneous ‘Bacillus subtilis’-group

Biochemical characterization of pathogenic bacterial species using Raman spectroscopy and discrimination model based on selected spectral features

This study aimed to evaluate the differences in the Raman spectra of nine clinical species of bacteria isolated from infections (three Gram-positive and six Gram-negative species), correlating the spectra with the chemical composition of each species and to develop a classification model through discriminant analysis to categorize each bacterial strain using the peaks with the most significant differences. Bacteria were cultured in Mueller Hinton agar and a sample of biomass was harvested and placed in an aluminum sample holder. A total of 475 spectra from 115 different strains were obtained through a dispersive Raman spectrometer (830 nm) with exposure time of 50 s. The intensities of the peaks were evaluated by one-way analysis of variance (ANOVA) and the peaks with significant differences were related to the differences in the biochemical composition of the strains. Discriminant analysis based on quadratic distance applied to the peaks with the most significant differences and partial least squares applied to the whole spectrum showed 89.5% and 90.1% of global accuracy, respectively, for classification of the spectra in all the groups. Raman spectroscopy could be a promising technique to identify spectral differences related to the biochemical content of pathogenic microorganisms and to provide a faster diagnosis of infectious diseases.

Feasibility of using RFLP of PCR-amplified 16S rRNA gene(s) for rapid differentiation of isolates of aerobic spore-forming bacteria from honey

This study aimed to assess the feasibility of using RFLP of PCR-amplified 16S rRNA gene (s) by using universal primers 27f/1492r and a combination of three restriction enzymes, AluI, CfoI, and TaqI, for a low-cost, rapid screen for a primarily differentiation of isolates of the complex of aerobic spore-forming bacteria commonly found in honey samples. The described method produced unique and distinguishable patterns to differentiate among 80 isolates belonging to 26 different species of Bacillus, Brevibacillus, Lysinibacillus, Rummeliibacillus, and Paenibacillus reported in honey and other apiarian sources.

Detectability of biosignatures in a low-biomass simulation of martian sediments

Discovery of a remnant habitable environment by the Mars Science Laboratory in the sedimentary record of Gale Crater has reinvigorated the search for evidence of martian life. In this study, we used a simulated martian mudstone material, based on data from Gale Crater, that was inoculated and cultured over several months and then dried and pressed. The simulated mudstone was analysed with a range of techniques to investigate the detectability of biosignatures. Cell counting and DNA extraction showed a diverse but low biomass microbial community that was highly dispersed. Pellets were analysed with bulk Elemental Analysis – Isotope Ratio Mass Spectrometry (EA-IRMS), high-resolution Laser-ablation Ionisation Mass Spectrometry (LIMS), Raman spectroscopy and Fourier Transform InfraRed (FTIR) spectroscopy, which are all techniques of relevance to current and future space missions. Bulk analytical techniques were unable to differentiate between inoculated samples and abiotic controls, despite total levels of organic carbon comparable with that of the martian surface. Raman spectroscopy, FTIR spectroscopy and LIMS, which are high sensitivity techniques that provide chemical information at high spatial resolution, retrieved presumptive biosignatures but these remained ambiguous and the sedimentary matrix presented challenges for all techniques. This suggests challenges for detecting definitive evidence for life, both in the simulated lacustrine environment via standard microbiological techniques and in the simulated mudstone via analytical techniques with relevance to robotic missions. Our study suggests that multiple co-incident high-sensitivity techniques that can scan the same micrometre-scale spots are required to unambiguously detect biosignatures, but the spatial coverage of these techniques needs to be high enough not to miss individual cellular-scale structures in the matrix.

Translational utility of a hierarchical classification strategy in biomolecular data analytics

Hierarchical classification (HC) stratifies and classifies data from broad classes into more specific classes. Unlike commonly used data classification strategies, this enables the probabilistic prediction of unknown classes at different levels, minimizing the burden of incomplete databases. Despite these advantages, its translational application in biomedical sciences has been limited. We describe and demonstrate the implementation of a HC approach for "omics-driven" classification of 15 bacterial species at various taxonomic levels achieving 90-100% accuracy, and 9 cancer types into morphological types and 35 subtypes with 99% and 76% accuracy, respectively. Unknown bacterial species were probabilistically assigned with 100% accuracy to their respective genus or family using mass spectra (n = 284). Cancer types were predicted by mRNA data (n = 1960) for most subtypes with 95-100% accuracy. This has high relevance in clinical practice where complete datasets are difficult to compile with the continuous evolution of diseases and emergence of new strains, yet prediction of unknown classes, such as bacterial species, at upper hierarchy levels may be sufficient to initiate antimicrobial therapy. The algorithms presented here can be directly translated into clinical-use with any quantitative data, and have broad application potential, from unlabeled sample identification, to hierarchical feature selection, and discovery of new taxonomic variants.

Laboratory Investigations on the Survival of Bacillus subtilis Spores in Deliquescent Salt Mars Analog Environments

Observed features such as recurring slope lineae suggest that liquid water may exist on the surface and near-subsurface of Mars today. The presence of this liquid water, likely in the form of a brine, has important implications for the present-day water cycle, habitability, and planetary protection policies. It is possible that this water is formed, at least partially, by deliquescence of salts, a process during which hygroscopic salts absorb water vapor from the atmosphere and form a saturated liquid brine. We performed laboratory experiments to examine the ability of Bacillus subtilis (B-168) spores, alone or mixed with calcium perchlorate salt (Ca(ClO₄)₂), to form liquid water via deliquescence under Mars-relevant conditions. Spore survival after exposure to these conditions was examined. An environmental chamber was used to expose the samples to temperature and relative humidity (RH) values similar to those found on Mars, and Raman microscopy was used to identify the phases of water and salt that were present and to confirm the presence of spores. We found that B-168 spores did not condense any detectable water vapor on their own during the diurnal cycle, even at 100% RH. However, when spores were mixed with perchlorate salt, the entire sample deliquesced at low RH values, immersing the spores in a brine solution during the majority of the simulated martian temperature and humidity cycle. After exposure to the simulated diurnal cycles and, in some cases, perchlorate brine, the impact of each environmental scenario on spore survival was estimated by standard plate assay. We found that, if there are deliquescent salts in contact with spores, there is a mechanism for the spores to acquire liquid water starting with only atmospheric water vapor as the H₂O source. Also, neither crystalline nor liquid Ca(ClO₄)₂ is sporicidal despite the low water activity. Key Words: Raman microscopy-Mars-Planetary protection-Salts-Water activity. Astrobiology 17, 997-1008.

Antifungal Activity of Isolated Bacillus amyloliquefaciens SYBC H47 for the Biocontrol of Peach Gummosis

The gummosis disease is caused by Botryosphaeria dothidea (Moug. ex. Fr) Ces. et de Not., and it is one of the most important diseases of stone fruits worldwide. The use of biocontrol as an alternative approach to synthetic chemical fungicides has aroused general concern about how to control plant diseases that are caused by phytopathogens. The aim of this study is to isolate Bacillus strains from raw honeys with the capacity to inhibit B. dothidea and to explore the mechanisms by which they could be used in the biocontrol of peach gummosis. Bacillus amyloliquefaciens SYBC H47 was isolated and identified on the basis of its physiological and biochemical characteristics and its 16S rRNA and gyrB gene sequences. The cell suspension and the cell-free supernatant of its culture showed significant antifungal activity against Aspergillus niger, Mucor racemosus, Fusarium oxysporum, Penicillium citrinum, and Candida albicans by agar-diffusion assays. The primary antifungal substances were bacillomycin L, fengycin, and surfactin, which were analyzed by HPLC LC/ESI-MS/MS. Bacillomycin L showed the best inhibitory effect against conidial germination of B. dothidea, followed by fengycin and surfactin. Surfactin had limited effects on mycelial growth, contrary to those of bacillomycin L and fengycin. However, a mixture of the three lipopeptides had a synergistic effect that disrupted the structure of the conidia and mycelia. In order to reduce the production cost, the use of waste frying peanut oil and soy oil as the sole carbon source increased the lipopeptide yield levels by approximately 17% (2.42 g/L) and 110% (4.35 g/L), respectively. In a field trial, the decreases in the infected gummosis rate (IGR) and the disease severity index (DSI) through cell suspension treatments were 20% and 57.5% (in 2014), respectively, and 40% and 57.5% (in 2015), respectively, in comparison with the control. In conclusion, B. amyloliquefaciens SYBC H47 could inhibit the germination of conidia and the growth of mycelia from B. dothidea; therefore, this strain behaves as a potential biocontrol agent against the gummosis disease.

In-vitro antibacterial, antifungal, antioxidant and functional properties of Bacillus amyloliquefaciens

BACKGROUND

Food born pathogenic bacteria and filamentous fungi are able to grow on most foods, including natural foods, processed foods, and fermented foods and create considerable economic loss. The aim of this study was to determine the antibacterial, antifungal, antioxidant and functional properties of Bacillus amyloliquefaciens recovered from silage.

METHODS

Minimum Inhibitory Concentration (MIC) of the compounds was assessed by using broth micro dilution method. The 1,1-diphenyl-2-picrylhydrazyl (DPPH)-radical scavenging and hydroxyl radical-scavenging abilities were measured to evaluate antioxidant activity of the strain.

RESULTS

Primary antimicrobial compound production screening revealed that B. amyloliquefaciens exhibited significant activity against all the tested bacteria and fungi compared to other strains. The 16S rRNA and gyrase A gene sequence analysis determined using molecular biological tools confirmed that the strain was 99% similarity towards B. amyloliquefaciens. The Minimum Inhibitory Concentration (MIC) of ethyl acetate extract against Bacillus subtilis, Enterococcus cloacae and Staphylococcus aureus were 25.0 μg ml-1, and S, epidermidis were 12.5 μg ml-1, respectively. Filamentous fungi Aspergillus clavatus, A. fumigates, A. niger and Gibberella moniliformis showed 25 μg ml-1. VJ-1 was able to survive the gastrointestinal conditions simulating the stomach and duodenum passage with the highest percentage of hydrophobicity. In addition, its resistance to hydrogen peroxide and highest hydroxyl radical and 2, 2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activities, with inhibition rates of 56.84% and 67.12% respectively, were its advantage. An antimicrobial susceptibility pattern was an intrinsic feature of this strain, and thus, consumption does not represent a health risk to humans.

CONCLUSION

Bacillus amyloliquefaciens might be a promising candidate for new pharmaceutical agents and probiotics.

Control efficacy of an endophytic Bacillus amyloliquefaciens strain BZ6-1 against peanut bacterial Wilt, Ralstonia solanacearum

We aimed to isolate and identify endophytic bacteria that might have efficacy against peanut bacterial wilt (BW) caused by Ralstonia solanacearum. Thirty-seven endophytic strains were isolated from healthy peanut plants in R. solanacearum-infested fields and eight showed antagonistic effects against R. solanacearum. Strain BZ6-1 with the highest antimicrobial activity was identified as Bacillus amyloliquefaciens based on morphology, biochemistry, and 16S rRNA analysis. Culture conditions of BZ6-1 were optimized using orthogonal test method and inhibitory zone diameter in dual culture plate assay reached 34.2 mm. Furthermore, main antimicrobial substances of surfactin and fengycin A homologues produced by BZ6-1 were analyzed by high performance liquid chromatography electrospray ionization tandem mass spectrometry. Finally, pot experiments were adopted to test the control efficiency of BZ6-1 against peanut BW. Disease incidence decreased significantly from 84.5% in the control to 12.1% with addition of 15 mL (10(8) cfu mL(-1)) culture broth for each seedling, suggesting the feasibility of strain BZ6-1 in the biological control of peanut plants BW.

Sensitive and specific discrimination of pathogenic and nonpathogenic Escherichia coli using Raman spectroscopy-a comparison of two multivariate analysis techniques

The determination of bacterial identity at the strain level is still a complex and time-consuming endeavor. In this study, visible wavelength spontaneous Raman spectroscopy has been used for the discrimination of four closely related Escherichia coli strains: pathogenic enterohemorrhagic E. coli O157:H7 and non-pathogenic E. coli C, E. coli Hfr K-12, and E. coli HF4714. Raman spectra from 600 to 2000 cm(-1) were analyzed with two multivariate chemometric techniques, principal component-discriminant function analysis and partial least squares-discriminant analysis, to determine optimal parameters for the discrimination of pathogenic E. coli from the non-pathogenic strains. Spectral preprocessing techniques such as smoothing with windows of various sizes and differentiation were investigated. The sensitivity and specificity of both techniques was in excess of 95%, determined by external testing of the chemometric models. This study suggests that spontaneous Raman spectroscopy with visible wavelength excitation is potentially useful for the rapid identification and classification of clinically-relevant bacteria at the strain level.

Surface enhanced Raman spectroscopy (SERS) for the discrimination of Arthrobacter strains based on variations in cell surface composition

Surface enhanced Raman spectroscopy (SERS) is a rapid and highly sensitive spectroscopic technique that has the potential to measure chemical changes in bacterial cell surface in response to environmental changes. The objective of this study was to determine whether SERS had sufficient resolution to differentiate closely related bacteria within a genus grown on solid and liquid medium, and a single Arthrobacter strain grown in multiple chromate concentrations. Fourteen closely related Arthrobacter strains, based on their 16S rRNA gene sequences, were used in this study. After performing principal component analysis in conjunction with Linear Discriminant Analysis, we used a novel, adapted cross-validation method, which more faithfully models the classification of spectra. All fourteen strains could be classified with up to 97% accuracy. The hierarchical trees comparing SERS spectra from the liquid and solid media datasets were different. Additionally, hierarchical trees created from the Raman data were different from those obtained using 16S rRNA gene sequences (a phylogenetic measure). A single bacterial strain grown on solid media culture with three different chromate levels also showed significant spectral distinction at discrete points identified by the new Elastic Net regularized regression method demonstrating the ability of SERS to detect environmentally induced changes in cell surface composition. This study demonstrates that SERS is effective in distinguishing between a large number of very closely related Arthrobacter strains and could be a valuable tool for rapid monitoring and characterization of phenotypic variations in a single population in response to environmental conditions.

Isolation, identification and characterization of Bacillus amyloliquefaciens BZ-6, a bacterial isolate for enhancing oil recovery from oily sludge

Over 100 biosurfactant-producing microorganisms were isolated from oily sludge and petroleum-contaminated soil from Shengli oil field in north China. Sixteen of the bacterial isolates produced biosurfactants and reduced the surface tension of the growth medium from 71 to <30 mN m(-1) after 72 h of growth. These bacteria were used to treat oily sludge and the recovery efficiencies of oil from oily sludge were determined. The oil recovery efficiencies of different isolates ranged from 39% to 88%. Bacterial isolate BZ-6 was found to be the most efficient strain and the three phases (oil, water and sediment) were separated automatically after the sludge was treated with the culture medium of BZ-6. Based on morphological, physiological characteristics and molecular identification, isolate BZ-6 was identified as Bacillus amyloliquefaciens. The biosurfactant produced by isolate BZ-6 was purified and analyzed by high performance liquid chromatography-electrospray ionization tandem mass spectrometry. There were four ion peaks representing four different fengycin A homologues.

Distinct differentiation of closely related species of Bacillus subtilis group with industrial importance

PCR amplification of 16S rRNA gene by universal primers followed by restriction fragment length polymorphism analysis using RsaI, CfoI and HinfI endonucleases, distinctly differentiated closely related Bacillus amyloliquefaciens, Bacillus licheniformis and Bacillus pumilus from Bacillus subtilis sensu stricto. This simple, economical, rapid and reliable protocol could be an alternative to misleading phenotype-based grouping of these closely related species.

A simple method of surface functionalisation for immuno-specific immobilisation of proteins

We present a new and advanced methodology, developed for surface functionalisation of gold and to study immobilisation of an immuno-specific system of proteins. A combination of electrochemical quartz crystal microbalance and Raman spectroscopy techniques allowed a complete understanding of the system starting from surface functionalisation and progressing to the functional structure analysis of immobilised proteins. A simple electrochemical procedure was formulated to prepare sulphonyl chloride terminated gold surfaces that form a strong sulphonamide bond with the receptor protein staphylococcal protein A (SpA). On the SpA grafted surfaces, the immobilisation of a human IgG and consecutive binding of an immuno-specific anti-human IgG was observed. The surface functional groups form a strong interaction with SpA without disturbing its functional properties. The native functional structure of SpA and also the IgGs was found to be retained in their immobilised state.

From learning taxonomies to phylogenetic learning: integration of 16S rRNA gene data into FAME-based bacterial classification

Background

Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification.

Results

In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model.

Conclusions

FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial species. Summarized, by phylogenetic learning we are able to situate and evaluate FAME-based bacterial species classification in a more informative context.

Monitoring poly(3-hydroxybutyrate) production in cupriavidus necator DSM 428 (H16) with raman spectroscopy

This study explored the potential of Raman spectroscopy for the analysis of poly(3-hydroxybutyrate) (PHB) in bacteria. PHB can be formed in large amounts by certain bacteria as a storage material and is of high importance for industrial biodegradable plastic production. Raman spectra were collected from Cupriavidus necator DSM 428 (H16), from its non-PHB-producing mutant strain C. necator DSM 541, and from pure PHB, in order to determine at which Raman shifts a contribution of PHB in bacterial spectra can be expected. The Raman band intensity at ca. 1734 cm(-1) appeared to be suitable for the monitoring of PHB production and consumption. These intensities were linearly related to the PHB concentration (mg L(-1) culture) determined by parallel HPLC analysis. Therefore, Raman spectroscopy is considered as a fast and noninvasive technique for the determination and monitoring of the PHB content in bacteria.

Methods for extracting biochemical information from bacterial Raman spectra: focus on a group of structurally similar biomolecules--fatty acids

In this paper we explore the possibilities of Raman spectroscopy in order to deduce information on the fatty acid composition of bacterial cells. Therefore, representative strains of two bacterial taxa were each cultured in different conditions and in parallel analyzed by Raman spectroscopy and gaschromatographic FAME analysis. Raman spectra of pure fatty acids were recorded and used as reference spectra. The culturing conditions for each strain could be easily distinguished by the fatty acid information retrieved from bacterial Raman spectra. Chemometric techniques such as EMSC and PCA allowed to extract information about groups of fatty acids, that was consistent with the results from FAME analysis. Although the information retrieved from Raman spectroscopy is not as refined as that from FAME analysis, the presented methods could be useful to obtain basic information on the fatty acid present in bacteria when performing Raman spectroscopic analysis for fast whole cell profiling, which provides information for different types of cell components (fatty acids, amino acids, primary metabolites, etc.).

Chemotaxonomical identification of spores of macrofungi: possibilities of Raman spectroscopy

Confocal Raman spectroscopy is a non-destructive analytical method which is useful to obtain detailed information about the molecular composition of biological samples. Its high spatial resolution was used to collect spectra of single basidiospores of macrofungi of the genera Collybia, Gymnopus, Laccaria, Lactarius, Mycena and Russula. These spectra can be divided into three major taxon-related groups, with general compositional differences, such as the relative amount of lipids compared to proteins. In this study, collapsing of thin-walled spores during storage was often observed, a phenomenon which has been given little attention in the literature. The Raman spectra are treated with different chemometric preprocessing techniques, including Savitsky-Golay, standard normal variate (SNV) preprocessing and extended multiplicative scatter correction (EMSC). By using linear discriminant analysis, approximately 90% of the spectra can be assigned to the correct genus, but identification on the species level was not possible.

Methods for extracting biochemical information from bacterial Raman spectra: an explorative study on Cupriavidus metallidurans

In this study, we explore Raman spectra of bacteria for their biochemical information. Therefore, a database of biomolecules was used and several approaches were applied such as the study of difference spectra, the calculation dot products, the usage of coefficients obtained from an EMSC procedure and the application of 2D correlation spectroscopy. These methods were applied on a dataset containing Raman spectra of Cupriavidus metallidurans LMG 1195 in five stages of its growth, aiming to extract information about the evolution of cell components during growth. EMSC coefficients seemed to be most promising for tracking metabolic products and the results were often confirmed by difference spectra or by 2D correlation spectroscopy.