The search for the "Holy Grail" in clinical diagnostic microbiology-a reliable, accurate, low-cost, real-time, easy-to-use method-has brought up several methods with the potential to meet these criteria. One is Raman spectroscopy, an optical, nondestructive method based on the inelastic scattering of monochromatic light. The current study focuses on the possible use of Raman spectroscopy for identifying microbes causing severe, often life-threatening bloodstream infections. We included 305 microbial strains of 28 species acting as causative agents of bloodstream infections. Raman spectroscopy identified the strains from grown colonies, with 2.8% and 7% incorrectly identified strains using the support vector machine algorithm based on centered and uncentred principal-component analyses, respectively. We combined Raman spectroscopy with optical tweezers to speed up the process and captured and analyzed microbes directly from spiked human serum. The pilot study suggests that it is possible to capture individual microbial cells from human serum and characterize them by Raman spectroscopy with notable differences among different species. IMPORTANCE Bloodstream infections are among the most common causes of hospitalizations and are often life-threatening. To establish an effective therapy for a patient, the timely identification of the causative agent and characterization of its antimicrobial susceptibility and resistance profiles are essential. Therefore, our multidisciplinary team of microbiologists and physicists presents a method that reliably, rapidly, and inexpensively identifies pathogens causing bloodstream infections-Raman spectroscopy. We believe that it might become a valuable diagnostic tool in the future. Combined with optical trapping, it offers a new approach where the microorganisms are individually trapped in a noncontact way by optical tweezers and investigated by Raman spectroscopy directly in a liquid sample. Together with the automatic processing of measured Raman spectra and comparison with a database of microorganisms, it makes the whole identification process almost real time.

• Keywords
• Candida, Raman spectroscopy, Raman tweezers, bacteria, bloodstream infections, diagnostics, sepsis,
• MeSH
• Algorithms MeSH
• Humans MeSH
• Optical Tweezers MeSH
• Pilot Projects MeSH
• Spectrum Analysis, Raman * methods   MeSH
• Sepsis * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Rapid and accurate identification of pathogens causing infections is one of the biggest challenges in medicine. Timely identification of causative agents and their antimicrobial resistance profile can significantly improve the management of infection, lower costs for healthcare, mitigate ever-growing antimicrobial resistance and in many cases, save lives. Raman spectroscopy was shown to be a useful-quick, non-invasive, and non-destructive -tool for identifying microbes from solid and liquid media. Modifications of Raman spectroscopy and/or pretreatment of samples allow single-cell analyses and identification of microbes from various samples. It was shown that those non-culture-based approaches could also detect antimicrobial resistance. Moreover, recent studies suggest that a combination of Raman spectroscopy with optical tweezers has the potential to identify microbes directly from human body fluids. This review aims to summarize recent advances in non-culture-based approaches of identification of microbes and their virulence factors, including antimicrobial resistance, using methods based on Raman spectroscopy in the context of possible use in the future point-of-care diagnostic process.

• Keywords
• Raman spectroscopy, Raman tweezers, antimicrobial resistance, diagnostics, identification of microorganisms, magnetic beads, microfluidic devices,
• MeSH
• Single-Cell Analysis MeSH
• Anti-Infective Agents * MeSH
• Virulence Factors MeSH
• Humans MeSH
• Spectrum Analysis, Raman * methods   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• Anti-Infective Agents * MeSH
• Virulence Factors MeSH

Oleaginous filamentous fungi can accumulate large amount of cellular lipids and biopolymers and pigments and potentially serve as a major source of biochemicals for food, feed, chemical, pharmaceutical, and transport industries. We assessed suitability of Fourier transform (FT) Raman spectroscopy for screening and process monitoring of filamentous fungi in biotechnology. Six Mucoromycota strains were cultivated in microbioreactors under six growth conditions (three phosphate concentrations in the presence and absence of calcium). FT-Raman and FT-infrared (FTIR) spectroscopic data was assessed in respect to reference analyses of lipids, phosphorus, and carotenoids by using principal component analysis (PCA), multiblock or consensus PCA, partial least square regression (PLSR), and analysis of spectral variation due to different design factors by an ANOVA model. All main chemical biomass constituents were detected by FT-Raman spectroscopy, including lipids, proteins, cell wall carbohydrates, and polyphosphates, and carotenoids. FT-Raman spectra clearly show the effect of growth conditions on fungal biomass. PLSR models with high coefficients of determination (0.83-0.94) and low error (approximately 8%) for quantitative determination of total lipids, phosphates, and carotenoids were established. FT-Raman spectroscopy showed great potential for chemical analysis of biomass of oleaginous filamentous fungi. The study demonstrates that FT-Raman and FTIR spectroscopies provide complementary information on main fungal biomass constituents.

• Keywords
• biodiesel, biopolymers, carotenoids, chitin, chitosan, fatty acids, fermentation, fungi, oleaginous microorganisms, pigments,
• MeSH
• Principal Component Analysis MeSH
• Pigments, Biological analysis   MeSH
• Biomass MeSH
• Biotechnology MeSH
• Chromatography, Gas MeSH
• Phosphorus analysis   metabolism   MeSH
• Fourier Analysis MeSH
• Fungi chemistry   growth & development   MeSH
• Carotenoids analysis   MeSH
• Lipids analysis   MeSH
• Magnetic Resonance Spectroscopy MeSH
• Spectrum Analysis, Raman methods   MeSH
• Spectrophotometry, Ultraviolet MeSH
• Spectroscopy, Fourier Transform Infrared MeSH
• Calcium metabolism   MeSH
• Chromatography, High Pressure Liquid MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Pigments, Biological MeSH
• Phosphorus MeSH
• Carotenoids MeSH
• Lipids MeSH
• Calcium MeSH

The biofilm-forming microbial species Candida parapsilosis and Staphylococcus epidermidis have been recently linked to serious infections associated with implanted medical devices. We studied microbial biofilms by high resolution scanning electron microscopy (SEM), which allowed us to visualize the biofilm structure, including the distribution of cells inside the extracellular matrix and the areas of surface adhesion. We compared classical SEM (chemically fixed samples) with cryogenic SEM, which employs physical sample preparation based on plunging the sample into various liquid cryogens, as well as high-pressure freezing (HPF). For imaging the biofilm interior, we applied the freeze-fracture technique. In this study, we show that the different means of sample preparation have a fundamental influence on the observed biofilm structure. We complemented the SEM observations with Raman spectroscopic analysis, which allowed us to assess the time-dependent chemical composition changes of the biofilm in vivo. We identified the individual spectral peaks of the biomolecules present in the biofilm and we employed principal component analysis (PCA) to follow the temporal development of the chemical composition.

• Keywords
• Raman spectroscopy, biofilm, cryo-SEM, sample preparation, scanning electron microscopy,
• MeSH
• Bacterial Infections diagnosis   microbiology   MeSH
• Biofilms growth & development   MeSH
• Candida parapsilosis isolation & purification   pathogenicity   ultrastructure   MeSH
• Humans MeSH
• Microscopy, Electron, Scanning MeSH
• Spectrum Analysis, Raman MeSH
• Staphylococcus epidermidis isolation & purification   pathogenicity   ultrastructure   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH