Raman Stable Isotope Probing of Bacteria in Visible and Deep UV-Ranges

Raman stable isotope probing (Raman-SIP) is an excellent technique that can be used to access the overall metabolism of microorganisms. Recent studies have mainly used an excitation wavelength in the visible range to characterize isotopically labeled bacteria. In this work, we used UV resonance Raman spectroscopy (UVRR) to evaluate the spectral red-shifts caused by the uptake of isotopes (13C, 15N, 2H(D) and 18O) in E. coli cells. Moreover, we present a new approach based on the extraction of labeled DNA in combination with UVRR to identify metabolically active cells. The proof-of-principle study on E. coli revealed heterogeneities in the Raman features of both the bacterial cells and the extracted DNA after labeling with 13C, 15N, and D. The wavelength of choice for studying 18O- and deuterium-labeled cells is 532 nm is, while 13C-labeled cells can be investigated with visible and deep UV wavelengths. However, 15N-labeled cells are best studied at the excitation wavelength of 244 nm since nucleic acids are in resonance at this wavelength. These results highlight the potential of the presented approach to identify active bacterial cells. This work can serve as a basis for the development of new techniques for the rapid and efficient detection of active bacteria cells without the need for a cultivation step

Application of Raman spectroscopy in the hospital environment

The hospital environment is a field with unique microbiological characteristics. Pathogens evolve and spread in different areas of the hospital affecting patients and staff. In addition, a constant circulation of pathogens between the hospital and the outer environment is ongoing. In this context, an extensive management is required in order to minimize the harmful effect of hospital flora on humans as well as the natural environment. Raman spectroscopy has been shown to be an effective tool for this purpose since it is applicable in a variety of biological samples ranging from the patient samples to the hospital's wastewater. It enables the detection of infection, bacterial species identification, antimicrobial resistance determination, epidemiological typing as well as infection control, mandatory for hospital management. The biggest advantages of this analytical method are the limited time and minimal resources required in its workflow. In the current review the Raman‐based analytical methods that have been developed over years in the field of microbiology are presented and their applicability in the different areas of the hospital environment is discussed

Use of polymers as wavenumber calibration standards in deep-UVRR

Deep-UV resonance Raman spectroscopy (UVRR) allows the classification of bacterial species with high accuracy and is a promising tool to be developed for clinical application. For this attempt, the optimization of the wavenumber calibration is required to correct the overtime changes of the Raman setup. In the present study, different polymers were investigated as potential calibration agents. The ones with many sharp bands within the spectral range 400–1900 cm−1 were selected and used for wavenumber calibration of bacterial spectra. Classification models were built using a training cross-validation dataset that was then evaluated with an independent test dataset obtained after 4 months. Without calibration, the training cross-validation dataset provided an accuracy for differentiation above 99 % that dropped to 51.2 % after test evaluation. Applying the test evaluation with PET and Teflon calibration allowed correct assignment of all spectra of Gram-positive isolates. Calibration with PS and PEI leads to misclassifications that could be overcome with majority voting. Concerning the very closely related and similar in genome and cell biochemistry Enterobacteriaceae species, all spectra of the training cross-validation dataset were correctly classified but were misclassified in test evaluation. These results show the importance of selecting the most suitable calibration agent in the classification of bacterial species and help in the optimization of the deep-UVRR technique

Label‐free differentiation of clinical E. coli and Klebsiella isolates with Raman spectroscopy

Raman spectroscopy is a promising spectroscopic technique for microbiological diagnostics. In routine diagnostic, the differentiation of pathogens of the Enterobacteriaceae family remain challenging. In this study, Raman spectroscopy was applied for the differentiation of 24 clinical E. coli , Klebsiella pneumoniae and Klebsiella oxytoca isolates. Spectra were collected with two spectroscopic approaches: UV‐Resonance Raman spectroscopy (UVRR) and single‐cell Raman microspectroscopy with 532 nm excitation. A description of the different biochemical profiles provided by the different excitation wavelengths was performed followed by machine‐learning models for the classification at the genus and species levels. UVRR was shown to outperform 532 nm excitation, enabling correct classification at the genus level of 23/24 isolates. Furthermore, for the first time, Klebsiella species were correctly classified at the species level with 92% accuracy, classifying all three K. oxytoca isolates correctly. These findings should guide future applicative studies, increasing the scope of Raman spectroscopy's suitability for clinical applications

Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy

Abstract In recent years, we have seen a steady rise in the prevalence of antibiotic-resistant bacteria. This creates many challenges in treating patients who carry these infections, as well as stopping and preventing outbreaks. Identifying these resistant bacteria is critical for treatment decisions and epidemiological studies. However, current methods for identification of resistance either require long cultivation steps or expensive reagents. Raman spectroscopy has been shown in the past to enable the rapid identification of bacterial strains from single cells and cultures. In this study, Raman spectroscopy was applied for the differentiation of resistant and sensitive strains of Escherichia coli . Our focus was on clinical multi-resistant (extended-spectrum β-lactam and carbapenem-resistant) bacteria from hospital patients. The spectra were collected using both UV resonance Raman spectroscopy in bulk and single-cell Raman microspectroscopy, without exposure to antibiotics. We found resistant strains have a higher nucleic acid/protein ratio, and used the spectra to train a machine learning model that differentiates resistant and sensitive strains. In addition, we applied a majority of voting system to both improve the accuracy of our models and make them more applicable for a clinical setting. This method could allow rapid and accurate identification of antibiotic resistant bacteria, and thus improve public health. Graphical abstrac

Comparison of Different Label-Free Raman Spectroscopy Approaches for the Discrimination of Clinical MRSA and MSSA Isolates

Methicillin-resistant Staphylococcus aureus (MRSA) is classified as one of the priority pathogens that threaten human health. Resistance detection with conventional microbiological methods takes several days, forcing physicians to administer empirical antimicrobial treatment that is not always appropriate. A need exists for a rapid, accurate, and cost-effective method that allows targeted antimicrobial therapy in limited time. In this pilot study, we investigate the efficacy of three different label-free Raman spectroscopic approaches to differentiate methicillin-resistant and -susceptible clinical isolates of S. aureus (MSSA). Single-cell analysis using 532 nm excitation was shown to be the most suitable approach since it captures information on the overall biochemical composition of the bacteria, predicting 87.5% of the strains correctly. UV resonance Raman microspectroscopy provided a balanced accuracy of 62.5% and was not sensitive enough in discriminating MRSA from MSSA. Excitation of 785 nm directly on the petri dish provided a balanced accuracy of 87.5%. However, the difference between the strains was derived from the dominant staphyloxanthin bands in the MRSA, a cell component not associated with the presence of methicillin resistance. This is the first step toward the development of label-free Raman spectroscopy for the discrimination of MRSA and MSSA using single-cell analysis with 532 nm excitation. IMPORTANCE Label-free Raman spectra capture the high chemical complexity of bacterial cells. Many different Raman approaches have been developed using different excitation wavelength and cell analysis methods. This study highlights the major importance of selecting the most suitable Raman approach, capable of providing spectral features that can be associated with the cell mechanism under investigation. It is shown that the approach of choice for differentiating MRSA from MSSA should be single-cell analysis with 532 nm excitation since it captures the difference in the overall biochemical composition. These results should be taken into consideration in future studies aiming for the development of label-free Raman spectroscopy as a clinical analytical tool for antimicrobial resistance determination

Effect of the Novel Influenza A (H1N1) Virus in the Human Immune System

BACKGROUND: The pandemic by the novel H1N1 virus has created the need to study any probable effects of that infection in the immune system of the host. METHODOLOGY/PRINCIPAL FINDINGS: Blood was sampled within the first two days of the presentation of signs of infection from 10 healthy volunteers; from 18 cases of flu-like syndrome; and from 31 cases of infection by H1N1 confirmed by reverse RT-PCR. Absolute counts of subtypes of monocytes and of lymphocytes were determined after staining with monoclonal antibodies and analysis by flow cytometry. Peripheral blood mononuclear cells (PBMCs) were isolated from patients and stimulated with various bacterial stimuli. Concentrations of tumour necrosis factor-alpha, interleukin (IL)-1beta, IL-6, IL-18, interferon (FN)-alpha and of IFN-gamma were estimated in supernatants by an enzyme immunoassay. Infection by H1N1 was accompanied by an increase of monocytes. PBMCs of patients evoked strong cytokine production after stimulation with most of bacterial stimuli. Defective cytokine responses were shown in response to stimulation with phytohemagglutin and with heat-killed Streptococcus pneumoniae. Adaptive immune responses of H1N1-infected patients were characterized by decreases of CD4-lymphocytes and of B-lymphocytes and by increase of T-regulatory lymphocytes (Tregs). CONCLUSIONS/SIGNIFICANCE: Infection by the H1N1 virus is accompanied by a characteristic impairment of the innate immune responses characterized by defective cytokine responses to S.pneumoniae. Alterations of the adaptive immune responses are predominated by increase of Tregs. These findings signify a predisposition for pneumococcal infections after infection by H1N1 influenza

TREM-1 expression on neutrophils and monocytes of septic patients: relation to the underlying infection and the implicated pathogen

<p>Abstract</p> <p>Background</p> <p>Current knowledge on the exact ligand causing expression of TREM-1 on neutrophils and monocytes is limited. The present study aimed at the role of underlying infection and of the causative pathogen in the expression of TREM-1 in sepsis.</p> <p>Methods</p> <p>Peripheral venous blood was sampled from 125 patients with sepsis and 88 with severe sepsis/septic shock. The causative pathogen was isolated in 91 patients. Patients were suffering from acute pyelonephritis, community-acquired pneumonia (CAP), intra-abdominal infections (IAIs), primary bacteremia and ventilator-associated pneumonia or hospital-acquired pneumonia (VAP/HAP). Blood monocytes and neutrophils were isolated. Flow cytometry was used to estimate the TREM-1 expression from septic patients.</p> <p>Results</p> <p>Within patients bearing intrabdominal infections, expression of TREM-1 was significantly lower on neutrophils and on monocytes at severe sepsis/shock than at sepsis. That was also the case for severe sepsis/shock developed in the field of VAP/HAP. Among patients who suffered infections by Gram-negative community-acquired pathogens or among patients who suffered polymicrobial infections, expression of TREM-1 on monocytes was significantly lower at the stage of severe sepsis/shock than at the stage of sepsis.</p> <p>Conclusions</p> <p>Decrease of the expression of TREM-1 on the membrane of monocytes and neutrophils upon transition from sepsis to severe sepsis/septic shock depends on the underlying type of infection and the causative pathogen.</p