RESUMEN
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.
Asunto(s)
Bacterias/aislamiento & purificación , Estructuras Celulares/química , Espectrofotometría Infrarroja/métodos , Espectrometría Raman/métodos , Bacterias/química , Bacterias/ultraestructura , VibraciónRESUMEN
The identification of avian gender is important for prosperous breeding of birds. Since birds do not possess external genital organs, endoscopic investigations, blood analysis, and molecular biological methods are applied to determine the gender in monomorphic species. However, anesthesia and blood sampling impose stress on the examined bird and should be avoided in terms of animal protection. Here we report on the application of UV-resonance Raman spectroscopy as a minimal invasive method for gender determination of birds via an evaluation of feather pulp samples. Sample preparation for this investigation method is simple and facilitates a quick and easy analysis. The UV-resonance Raman spectra of the feather pulp sample extracts are dominated by DNA and protein signals. The different DNA content in male and female chicken allows for gender differentiation via its characteristic Raman fingerprint. The classification either to male or female chicken is ideally accomplished by support vector machines due to the fact that no unknown classes are involved. Recognition rates of about 95% were compared to less effective results of the unsupervised hierarchical cluster analysis. Within the scope of our investigations, principal component analysis was also applied to determine the important spectral regions for the classification of chicken's feather pulp samples.
Asunto(s)
Plumas/fisiología , Análisis para Determinación del Sexo/métodos , Diferenciación Sexual/fisiología , Animales , Pollos , Proteínas de Unión al ADN/metabolismo , Femenino , Masculino , Análisis de Componente Principal , Sensibilidad y Especificidad , Espectrofotometría Ultravioleta/métodos , Espectrometría Raman/métodosRESUMEN
Various diseases shift the composition of human plasma; hence, the relative quantification of plasma constituents offers the opportunity to use the dynamic and complex composition of plasma to gain information on novel diagnostic and prognostic factors. Since plasma contains, besides water, mostly proteins, UV-resonance Raman spectroscopy (UVRR) seems to be a suitable method for investigating plasma. With this method the signals of aromatic amino acids and proteins are selectively enhanced. In this study an UV-resonance Raman approach was used for the investigation of human plasma of healthy volunteers and patients with thrombotic microangiopathy. For comparison, selected plasma components were analyzed for a more detailed characterization of cryoprecipitates from human plasma.
Asunto(s)
Plasma/química , Púrpura Trombocitopénica Trombótica/sangre , Espectrometría Raman/métodos , Donantes de Tejidos , Humanos , Espectrofotometría Ultravioleta/métodos , VibraciónRESUMEN
For a fast identification of eukaryotic cells such as yeast species without a cultivation step it should be possible to perform the investigation on only one single cell. Since yeasts as eukaryotes are heterogeneous and their Raman spectra are therefore dependent on the measuring position, one Raman spectra is not representative of the whole cell. In this contribution we demonstrate the application of average Raman spectra of a line scan over single yeast cells. These average spectra are used for classification with the help of a support vector machine.
Asunto(s)
Células Eucariotas/clasificación , Espectrometría Raman/métodos , Candida/química , Candida/clasificación , Candida/citología , Células Eucariotas/química , Células Eucariotas/citología , Saccharomyces cerevisiae/química , Saccharomyces cerevisiae/clasificación , Saccharomyces cerevisiae/citología , Levaduras/química , Levaduras/clasificación , Levaduras/citologíaRESUMEN
Microbial contamination is not only a medical problem, but also plays a large role in pharmaceutical clean room production and food processing technology. Therefore many techniques were developed to achieve differentiation and identification of microorganisms. Among these methods vibrational spectroscopic techniques (IR, Raman and SERS) are useful tools because of their rapidity and sensitivity. Recently we have shown that micro-Raman spectroscopy in combination with a support vector machine is an extremely capable approach for a fast and reliable, non-destructive online identification of single bacteria belonging to different genera. In order to simulate different environmental conditions we analyzed in this contribution different Staphylococcus strains with varying cultivation conditions in order to evaluate our method with a reliable dataset. First, micro-Raman spectra of the bulk material and single bacterial cells that were grown under the same conditions were recorded and used separately for a distinct chemotaxonomic classification of the strains. Furthermore Raman spectra were recorded from single bacterial cells that were cultured under various conditions to study the influence of cultivation on the discrimination ability. This dataset was analyzed both with a hierarchical cluster analysis (HCA) and a support vector machine (SVM).