Identification of single eukaryotic cells with micro-Raman spectroscopy

The Ground-Based BIOMEX Experiment Verification Tests for Life Detection on Mars

The success of an astrobiological search for life campaign on Mars, or other planetary bodies in the Solar System, relies on the detectability of past or present microbial life traces, namely, biosignatures. Spectroscopic methods require little or no sample preparation, can be repeated almost endlessly, and can be performed in contact or even remotely. Such methods are therefore ideally suited to use for the detection of biosignatures, which can be confirmed with supporting instrumentation. Here, we discuss the use of Raman and Fourier Transform Infrared (FT-IR) spectroscopies for the detection and characterization of biosignatures from colonies of the fungus Cryomyces antarcticus, grown on Martian analogues and exposed to increasing doses of UV irradiation under dried conditions. The results report significant UV-induced DNA damage, but the non-exceeding of thresholds for allowing DNA amplification and detection, while the spectral properties of the fungal melanin remained unaltered, and pigment detection and identification was achieved via complementary analytical techniques. Finally, this work found that fungal cell wall compounds, likely chitin, were not degraded, and were still detectable even after high UV irradiation doses. The implications for the preservation and detection of biosignatures in extraterrestrial environments are discussed.

Resonance Raman Spectra for the In Situ Identification of Bacteria Strains and Their Inactivation Mechanism

The resonance Raman spectra of bacterial carotenoids have been employed to identify bacterial strains and their intensity changes as a function of ultraviolet (UV) radiation dose have been used to differentiate between live and dead bacteria. In addition, the resonance-enhanced Raman spectra enabled us to detect bacteria in water at much lower concentrations (∼10⁸ cells/mL) than normally detected spectroscopically. A handheld spectrometer capable of recording resonance Raman spectra in situ was designed, constructed, and was used to record the spectra. In addition to bacteria, the method presented in this paper may also be used to identify fungi, viruses, and plants, in situ, and detect infections within a very short period of time.

Decoding Optical Data with Machine Learning

Optical spectroscopy and imaging techniques play important roles in many fields such as disease diagnosis, biological study, information technology, optical science, and materials science. Over the past decade, machine learning (ML) has proved promising in decoding complex data, enabling rapid and accurate analysis of optical spectra and images. This review aims to shed light on various ML algorithms for optical data analysis with a focus on their applications in a wide range of fields. The goal of this work is to sketch the validity of ML-based optical data decoding. The review concludes with an outlook on unaddressed problems and opportunities in this emerging subject that interfaces optics, data science and ML.

Raman fingerprints as promising markers of cellular senescence and aging

Due to our aging population, understanding of the underlying molecular mechanisms constantly gains more and more importance. Senescent cells, defined by being irreversibly growth arrested and associated with a specific gene expression and secretory pattern, accumulate with age and thus contribute to several age-related diseases. However, their specific detection, especially in vivo, is still a major challenge. Raman microspectroscopy is able to record biochemical fingerprints of cells and tissues, allowing a distinction between different cellular states, or between healthy and cancer tissue. Similarly, Raman microspectroscopy was already successfully used to distinguish senescent from non-senescent cells, as well as to investigate other molecular changes that occur at cell and tissue level during aging. This review is intended to give an overview about various applications of Raman microspectroscopy to study aging, especially in the context of detecting senescent cells.

Zinc oxide nanorod based immunosensing platform for the determination of human leukemic cells

Zinc oxide (ZnO) based nanostructures owing unique physical properties - high photoluminescence, biocompatibility and other characteristics, therefore, they attract attention as building blocks suitable for biosensor development. In this research as a target we have used human leukemic cell line IM9 (IM9). IM9 was derived from the patient with a multiple myeloma and expressed cluster of differentiation proteins СD19 on the surface of 85-95% here investigated cancer cells. As a control sample healthy human's peripheral blood mononuclear cells (PBMC) were used and the expression of CD19 protein was found only in 5-9% of these cells. Two types of antibodies labeled by fluorescein isothiocyanate (FITC) were used for the labeling of human leukemic cells: FITC-conjugated mouse antibodies against Human CD19 protein (anti-CD19-FITC*) and FITC-conjugated mouse antibodies against Human IgG1 protein (anti-IgG1-FITC*). In order to demonstrate the applicability of zinc oxide nanorods (ZnO-NRs) based platforms three types of ZnO-NRs-based structures were investigated: (i) ZnO-NRs modified by anti-CD19-FITC*; (ii) ZnO-NRs modified by IM9 cells, which were pre-incubated with anti-CD19-FITC*; (iii) ZnO-NRs modified by PBMC cells, which were pre-incubated with anti-CD19-FITC*. It was demonstrated that IM9 cells after specific interaction with anti-CD19-FITC* bind to ZnO-NRs (ZnO-NRs/IM9 +anti-CD19-FITC*) and photoluminescence based signal significantly increase in comparison with that observed in control samples, which contained PBMC cells incubated with anti-CD19-FITC* (ZnO-NRs/PBMC+anti-CD19-FITC*). The photoluminescence results are in good correlation with the data obtained by flow cytometry. This study illustrate that ZnO-NRs exhibit a photoluminescence signal suitable for the determination of anti-CD19-FITC* labeled IM9 cell line at concentrations - from 10 till 500 cells adsorbed per 1 mm² of ZnO-NRs platform.

Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using Raman spectroscopic mapping

Tumour heterogeneity plays a large role in the response of tumour tissues to radiation therapy. Inherent biological, physical, and even dose deposition heterogeneity all play a role in the resultant observed response. We here implement the use of Haralick textural analysis to quantify the observed glycogen production response, as observed via Raman spectroscopic mapping, of tumours irradiated within a murine model. While an array of over 20 Haralick features have been proposed, we here concentrate on five of the most prominent features: homogeneity, local homogeneity, contrast, entropy, and correlation. We show that these Haralick features can be used to quantify the inherent heterogeneity of the Raman spectroscopic maps of tumour response to radiation. Furthermore, our results indicate that Haralick-calculated textural features show a statistically significant dose dependent variation in response heterogeneity, specifically, in glycogen production in tumours irradiated with clinically relevant doses of ionizing radiation. These results indicate that Haralick textural analysis provides a quantitative methodology for understanding the response of murine tumours to radiation therapy. Future work in this area can, for example, utilize the Haralick textural features for understanding the heterogeneity of radiation response as measured by biopsied patient tumour samples, which remains the standard of patient tumour investigation.

High-contrast Brillouin and Raman micro-spectroscopy for simultaneous mechanical and chemical investigation of microbial biofilms

Mechanical mapping with chemical specificity of biological samples is now made possible by joint micro-Brillouin and micro-Raman measurements. In this work, thanks to the unprecedented contrast of a new tandem Fabry-Perot interferometer, we demonstrate simultaneous detection of Brillouin and Raman spectra from different Candida biofilms. Our proof-of-concept study reveals the potential of this label-free joint micro-spectroscopy technique in challenging microbiological issues. In particular, heterogeneous chemo-mechanical maps of Candida biofilms are obtained, without the need for staining or touching the sample. The correlative Raman and Brillouin investigation evidences the role of both extracellular polymeric substances and of hydration water in inducing a marked local softening of the biofilm.

Pioneering particle-based strategy for isolating viable bacteria from multipart soil samples compatible with Raman spectroscopy

The study of edaphic bacteria is of great interest, particularly for evaluating soil remediation and recultivation methods. Therefore, a fast and simple strategy to isolate various bacteria from complex soil samples using poly(ethyleneimine) (PEI)-modified polyethylene particles is introduced. The research focuses on the binding behavior under different conditions, such as the composition, pH value, and ionic strength, of the binding buffer, and is supported by the characterization of the surface properties of particles and bacteria. The results demonstrate that electrostatic forces and hydrophobicity are responsible for the adhesion of target bacteria to the particles. Distinct advantages of the particle-based isolation strategy include simple handling, enrichment efficiency, and the preservation of viable bacteria. The presented isolation method allows a subsequent identification of the bacteria using Raman microspectroscopy in combination with chemometrical methods. This is demonstrated with a dataset of five different bacteria (Escherichia coli, Bacillus subtilis, Pseudomonas fluorescens, Streptomyces tendae, and Streptomyces acidiscabies) which were isolated from spiked soil samples. In total 92% of the Raman spectra could be identified correctly.

Evanescent-field-induced Raman scattering for bio-friendly fingerprinting at sub-cellular dimension

Evanescent field induced chemical imaging concept has been realized in analytical platform based on the µ-tip-enhanced Raman scattering spectroscopy (µ-TERS). The technique aimed to minimize thermal decomposition of dried biological sample as the result of huge concentration of optical field near the tip by increasing the size of an aperture-less "excitation source". µ-TERS technique is similar to classical biosensor systems based on propagating surface plasmon resonance phenomenon but with sensitive elements a few micrometers in size that can be targeted to the area of interest. The utility of the concept is exemplified by the analysis of dried single cell envelope of genetically modified Saccharomyces cerevisiae yeast cells, which do not have any heat-removing pathways, by water as in the case of the living cell. Practical excitation conditions effective for µ-TERS Raman observation of single layer dried biological samples without photodamage-related spectral distortion have been determined - the allowable limit is above 30s at 13 µW/µm(2). Finally, potential of µ-TERS spectroscopy as new bio-friendly instrumental platform for chemical fingerprinting and analytical characterization of buried nanoscale features is discussed.

Methods and applications of Raman microspectroscopy to single-cell analysis

Raman spectroscopy is a powerful biochemical analysis technique that allows for the dynamic characterization and imaging of living biological cells in the absence of fluorescent stains. In this review, we summarize some of the most recent developments in the noninvasive biochemical characterization of single cells by spontaneous Raman scattering. Different instrumentation strategies utilizing confocal detection optics, multispot, and line illumination have been developed to improve the speed and sensitivity of the analysis of single cells by Raman spectroscopy. To analyze and visualize the large data sets obtained during such experiments, sophisticated multivariate statistical analysis tools are necessary to reduce the data and extract components of interest. We highlight the most recent applications of single cell analysis by Raman spectroscopy and their biomedical implications that have enabled the noninvasive characterization of specific metabolic states of eukaryotic cells, the identification and characterization of stem cells, and the rapid identification of bacterial cells. We conclude the article with a brief look into the future of this rapidly evolving research area.

Spatially resolved investigation of the oil composition in single intact hyphae of Mortierella spp. with micro-Raman spectroscopy

Zygomycetes are well known for their ability to produce various secondary metabolites. Fungi of the genus Mortierella can accumulate highly unsaturated lipids in large amounts as lipid droplets. However, no information about the spatial distribution or homogeneity of the oil inside the fungi is obtainable to date due to the invasive and destructive analytical techniques applied so far. Raman spectroscopy has been demonstrated to be well suited to investigate biological samples on a micrometre scale. It also has been shown that the degree of unsaturation of lipids can be determined from Raman spectra. We applied micro-Raman spectroscopy to investigate the spatial distribution and composition of lipid vesicles inside intact hyphae. For Mortierella alpina and Mortierella elongata distinct differences in the degree of unsaturation and even the impact of growth conditions are determined from the Raman spectra. In both species we found that the fatty acid saturation in the vesicles is highly variable in the first 600 μm of the growing hyphal tip and fluctuates towards a constant composition and saturation ratio in all of the remaining mycelium. Our approach facilitates in vivo monitoring of the lipid production and allows us to investigate the impact of cultivation parameters on the oil composition directly in the growing hyphae without the need for extensive extraction procedures.

Raman spectroscopy as a potential tool for detection of Brucella spp. in milk

Detection of Brucella, causing brucellosis, is very challenging, since the applied techniques are mostly time-demanding and not standardized. While the common detection system relies on the cultivation of the bacteria, further classical typing up to the biotype level is mostly based on phenotypic or genotypic characteristics. The results of genotyping do not always fit the existing taxonomy, and misidentifications between genetically closely related genera cannot be avoided. This situation gets even worse, when detection from complex matrices, such as milk, is necessary. For these reasons, the availability of a method that allows early and reliable identification of possible Brucella isolates for both clinical and epidemiological reasons would be extremely useful. We evaluated micro-Raman spectroscopy in combination with chemometric analysis to identify Brucella from agar plates and directly from milk: prior to these studies, the samples were inactivated via formaldehyde treatment to ensure a higher working safety. The single-cell Raman spectra of different Brucella, Escherichia, Ochrobactrum, Pseudomonas, and Yersinia spp. were measured to create two independent databases for detection in media and milk. Identification accuracies of 92% for Brucella from medium and 94% for Brucella from milk were obtained while analyzing the single-cell Raman spectra via support vector machine. Even the identification of the other genera yielded sufficient results, with accuracies of >90%. In summary, micro-Raman spectroscopy is a promising alternative for detecting Brucella. The measurements we performed at the single-cell level thus allow fast identification within a few hours without a demanding process for sample preparation.

Label-free in situ SERS imaging of biofilms

Surface-enhanced Raman scattering (SERS) is a promising technique for the chemical characterization of biological systems. It yields highly informative spectra, can be applied directly in aqueous environment, and has high sensitivity in comparison with normal Raman spectroscopy. Moreover, SERS imaging can provide chemical information with spatial resolution in the micrometer range (chemical imaging). In this paper, we report for the first time on the application of SERS for in situ, label-free imaging of biofilms and demonstrate the suitability of this technique for the characterization of the complex biomatrix. Biofilms, being communities of microorganisms embedded in a matrix of extracellular polymeric substances (EPS), represent the predominant mode of microbial life. Knowledge of the chemical composition and the structure of the biofilm matrix is important in different fields, e.g., medicine, biology, and industrial processes. We used colloidal silver nanoparticles for the in situ SERS analysis. Good SERS measurement reproducibility, along with a significant enhancement of Raman signals by SERS (>10(4)) and highly informative SERS signature, enables rapid SERS imaging (1 s for a single spectrum) of the biofilm matrix. Altogether, this work illustrates the potential of SERS for biofilm analysis, including the detection of different constituents and the determination of their distribution in a biofilm even at low biomass concentration.

Identification and differentiation of single cells from peripheral blood by Raman spectroscopic imaging

Medical diagnosis can be improved significantly by fast, highly sensitive and quantitative cell identification from easily accessible body fluids. Prominent examples are disseminated tumor cells circulating in the peripheral blood of cancer patients. These cells are extremely rare and therefore difficult to detect. In this contribution we present the Raman spectroscopic characterization of different cells that can be found in peripheral blood such as leukocytes, leukemic cells and solid tumor cells. Leukocytes were isolated from the peripheral blood from healthy donors. Breast carcinoma derived tumor cells (MCF-7, BT-20) and myeloid leukaemia cells (OCI-AML3) were prepared from cell cultures. Raman images were collected from dried cells on calcium fluoride slides using 785 nm laser excitation. Unsupervised statistical methods (hierarchical cluster analysis and principal component analysis) were used to visualize spectral differences and cluster formation according to the cell type. With the help of supervised statistical methods (support vector machines) a classification model with 99.7% accuracy rates for the differentiation of the cells was built. The model was successfully applied to identify single cells from an independent mixture of cells based on their vibrational spectra. The classification was confirmed by fluorescence staining of the cells after the Raman measurement.

Biochemical imaging below the diffraction limit--probing cellular membrane related structures by tip-enhanced Raman spectroscopy (TERS)

A first vibrational mapping on the nanometer scale was performed on a protein (streptavidin) labelled supported phospholipid film by means of tip-enhanced Raman spectroscopy (TERS). For this purpose a TERS spectral map was measured on the biomembrane model, using a step size far below the diffraction limit. Considering the model composition, spectra were classified as either typical for lipids, proteins or both simultaneously, in a qualitative manner. Subsequently, the spectroscopic information was assigned with respect to the topographic features. Since a spatial differentiation between different compositional domains is difficult to achieve by topographic features only, the combination of morphology and spectral data enables a much more detailed characterization of biomembranes.

Raman spectroscopy-compatible inactivation method for pathogenic endospores

Micro-Raman spectroscopy is a fast and sensitive tool for the detection, classification, and identification of biological organisms. The vibrational spectrum inherently serves as a fingerprint of the biochemical composition of each bacterium and thus makes identification at the species level, or even the subspecies level, possible. Therefore, microorganisms in areas susceptible to bacterial contamination, e.g., clinical environments or food-processing technology, can be sensed. Within the scope of point-of-care-testing also, detection of intentionally released biosafety level 3 (BSL-3) agents, such as Bacillus anthracis endospores, or their products is attainable. However, no Raman spectroscopy-compatible inactivation method for the notoriously resistant Bacillus endospores has been elaborated so far. In this work we present an inactivation protocol for endospores that permits, on the one hand, sufficient microbial inactivation and, on the other hand, the recording of Raman spectroscopic signatures of single endospores, making species-specific identification by means of highly sophisticated chemometrical methods possible. Several physical and chemical inactivation methods were assessed, and eventually treatment with 20% formaldehyde proved to be superior to the other methods in terms of sporicidal capacity and information conservation in the Raman spectra. The latter fact has been verified by successfully using self-learning machines (such as support vector machines or artificial neural networks) to identify inactivated B. anthracis-related endospores with adequate accuracies within the range of the limited model database employed.

Characterization of yeast species using surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) is used for the characterization of six yeast species and six isolates. The sample for SERS analysis is prepared by mixing the yeast cells with a four times concentrated silver colloidal suspension. The scanning electron microscopy (SEM) images show that the strength of the interaction between silver nanoparticles and the yeast cells depends on the biochemical structure of the cell wall. The SERS spectra are used to identify the biochemical structures on the yeast cell wall. It is found that the density of -SH and -NH2 groups might be higher on certain yeast cell walls. Finally, the obtained SERS spectra from yeast is used for the classification of the yeast.

Vibrational spectroscopy--a powerful tool for the rapid identification of microbial cells at the single-cell level

Rapid microbial detection and identification with a high grade of sensitivity and selectivity is a great and challenging issue in many fields, primarily in clinical diagnosis, pharmaceutical, or food processing technology. The tedious and time-consuming processes of current microbiological approaches call for faster ideally on-line identification techniques. The vibrational spectroscopic techniques IR absorption and Raman spectroscopy are noninvasive methods yielding molecular fingerprint information; thus, allowing for a fast and reliable analysis of complex biological systems such as bacterial or yeast cells. In this short review, we discuss recent vibrational spectroscopic advances in microbial identification of yeast and bacterial cells for bulk environment and single-cell analysis. IR absorption spectroscopy enables a bulk analysis whereas micro-Raman-spectroscopy with excitation in the near infrared or visible range has the potential for the analysis of single bacterial and yeast cells. The inherently weak Raman signal can be increased up to several orders of magnitude by applying Raman signal enhancement methods such as UV-resonance Raman spectroscopy with excitation in the deep UV region, surface enhanced Raman scattering, or tip-enhanced Raman scattering.

Direct analysis of clinical relevant single bacterial cells from cerebrospinal fluid during bacterial meningitis by means of micro-Raman spectroscopy

Bacterial meningitis is a relevant public health concern. Despite the availability of modern treatment strategies it is still a life-threatening disease that causes significant morbidity and mortality. Therefore, an initial treatment approach plays an important role. For in-time identification of specific bacterial pathogens of the cerebrospinal fluid (CSF) and emerged antimicrobial and adjunctive treatment, microbiological examination is of major importance. This contribution spotlights the potential of micro-Raman spectroscopy as a biomedical assay for direct analysis of bacteria in cerebrospinal fluid of patients with bacterial meningitis. The influence of miscellaneous artificial environments on several bacterial species present during bacterial meningitis was studied by means of Raman spectroscopy. The application of chemometric data interpretation via hierarchical cluster analysis (HCA) allows for the differentiation of in vitro cultured bacterial cells and can also be achieved on a single cell level. Moreover as proof of principle the investigation of a CSF sample obtained from a patient with meningococcal meningitis showed that the cerebrospinal fluid matrix does not mask the Raman spectrum of a bacterial cell notably since via chemometric analysis with HCA an identification of N. meningitidis cells from patients with bacterial meningitis could be achieved.

UV Raman spectroscopy--a technique for biological and mineralogical in situ planetary studies

We report on the great advantages of using deep UV Raman system for in situ planetary applications. Among them are to be mentioned: (I) higher scattering efficiency compared to VIS-IR Raman excitation wavelengths, (II) electronic resonance effects which increase the intrinsically weak Raman signal thus improving the S/N ratio of the detected Raman signals and (III) spectral separation of Raman and fluorescence signals. All these advantages are making UV Raman a valuable technique for in situ planetary applications. Mineral as well as biological samples were analyzed using Raman deep UV excitation and the results are presented. For the mineral samples a comparison with excitation in the NIR-VIS spectral regions is made. The impact of fluorescence on Raman data acquisition at different laser excitation wavelengths is assessed. Making use of the resonance effects, spectra of microorganisms were recorded with a high S/N ratio, allowing afterwards a very precise identification and classification (to the strain level) of the measured samples.

The Influence of Fluoroquinolone Drugs on the Bacterial Growth of S. epidermidis Utilizing the Unique Potential of Vibrational Spectroscopy

Increasing resistance of many antibiotics has made the design of new drugs necessary. To assist a target-oriented search for new structures and for the elucidation of the mode of action of existing drugs, powerful analytical techniques are required. In this work, vibrational spectroscopy is used to shed more light on the as-yet elusive interaction of gyrase inhibitors of the fluoroquinolone type with their biological target inside the Gram-positive bacterium Staphylococcus epidermidis by investigating whole-cell changes that occur as a result of the presence of the drug moxifloxacin. IR absorption and Raman spectra with excitation off resonance (lambda exc = 532 nm) and in resonance with the biological targets DNA and the aromatic amino acids of gyrase (lambda exc = 244 nm) were recorded for unperturbed bacteria and bacteria in varying drug concentrations (0.08, 0.16, 0.27, and 0.62 microg moxifloxacin/mL bacterial culture). The spectral changes caused by the action of the drug were analyzed with the help of statistical methods, such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and Fisher's linear discriminant analysis (LDA) combined with variable selection. The wavenumbers mostly affected by the action of the drug could be assigned to protein and DNA moieties, supporting the proposed mechanisms of a tertiary complex of the fluoroquinolone, the enzyme gyrase, and DNA.

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.

Towards a Detailed Understanding of Bacterial Metabolism—Spectroscopic Characterization ofStaphylococcus Epidermidis

Bacteria are a major cause of infection. To fight disease and growing resistance, research interest is focused on understanding bacterial metabolism. For a detailed evaluation of the involved mechanisms, a precise knowledge of the molecular composition of the bacteria is required. In this article, various vibrational spectroscopic techniques are applied to comprehensively characterize, on a molecular level, bacteria of the strain Staphylococcus epidermidis, an opportunistic pathogen which has evolved to become a major cause of nosocomial infections. IR absorption spectroscopy reflects the overall chemical composition of the cells, with major focus on the protein vibrations. Smaller sample volumes-down to a single cell-are sufficient to probe the overall chemical composition by means of micro-Raman spectroscopy. The nucleic-acid and aromatic amino-acid moieties are almost exclusively explored by UV resonance Raman spectroscopy. In combination with statistical evaluation methods [hierarchical cluster analysis (HCA), principal component analysis (PCA), linear discriminant analysis (LDA)], the protein and nucleic-acid components that change during the different bacterial growth phases can be identified from the in vivo vibrational spectra. Furthermore, tip-enhanced Raman spectroscopy (TERS) provides insight into the surface structures and follows the dynamics of the polysaccharide and peptide components on the bacterial cells with a spatial resolution below the diffraction limit. This might open new ways for the elucidation of host-bacteria and drug-bacteria interactions.

Fourier transform infrared (FT-IR) spectroscopy in bacteriology: towards a reference method for bacteria discrimination

Rapid and reliable discrimination among clinically relevant pathogenic organisms is a crucial task in microbiology. Microorganism resistance to antimicrobial agents increases prevalence of infections. The possibility of Fourier transform infrared (FT-IR) spectroscopy to assess the overall molecular composition of microbial cells in a non-destructive manner is reflected in the specific spectral fingerprints highly typical for different microorganisms. With the objective of using FT-IR spectroscopy for discrimination between diverse microbial species and strains on a routine basis, a wide range of chemometrics techniques need to be applied. Still a major issue in using FT-IR for successful bacteria characterization is the method for spectra pre-processing. We analyzed different spectra pre-processing methods and their impact on the reduction of spectral variability and on the increase of robustness of chemometrics models. Different types of the Enterococcus faecium bacterial strain were classified according to chromosomal DNA restriction patterns produced by pulsed-field gel electrophoresis (PFGE). Samples were collected from human patients. Collected FT-IR spectra were used to verify if the same classification was obtained. In order to further optimize bacteria classification we investigated whether a selected combination of the most discriminative spectral regions could improve results. Two different variable selection methods (genetic algorithms (GAs) and bootstrapping) were investigated and their relative merit for bacteria classification is reported by comparing with results obtained using the entire spectra. Discriminant partial least-squares (Di-PLS) models based on corrected spectra showed improved predictive ability up to 40% when compared to equivalent models using the entire spectral range. The uncertainty in estimating scores was reduced by about 50% when compared to models with all wavelengths. Spectral ranges with relevant chemical information for Enterococcus faecium bacteria discrimination were outlined.