cytochrome-c-t and Bacterial-Infections

The ability of bacterial pathogens to inhibit apoptosis in eukaryotic cells during infection is an emerging theme in the study of bacterial pathogenesis. Prevention of apoptosis provides a survival advantage because it enables the bacteria to replicate inside host cells. Bacterial pathogens have evolved several ways to prevent apoptosis by protecting the mitochondria and preventing cytochrome c release, by activating cell survival pathways, or by preventing caspase activation. This review summarizes the most recent work on bacterial anti-apoptotic strategies and suggests new research that is necessary to advance the field.

Topics: Animals; Apoptosis; Bacteria; Bacterial Infections; Caspase Inhibitors; Caspases; Cell Line; Cytochromes c; Eukaryotic Cells; Host-Pathogen Interactions; Humans; Mitochondria; Rats

Invasive fungal infection serves as a great threat to human health. Discrimination between fungal and bacterial infections at the earliest stage is vital for effective clinic practice; however, traditional culture-dependent microscopic diagnosis of fungal infection usually requires several days, meanwhile, culture-independent immunological and molecular methods are limited by the detectable type of pathogens and the issues with high false-positive rates. In this study, we proposed a novel culture-independent phenotyping method based on single-cell Raman spectroscopy for the rapid discrimination between fungal and bacterial infections. Three Raman biomarkers, including cytochrome c, peptidoglycan, and nucleic acid, were identified through hierarchical clustering analysis of Raman spectra across 12 types of most common yeast and bacterial pathogens. Compared to those of bacterial pathogens, the single cells of yeast pathogens demonstrated significantly stronger Raman peaks for cytochrome c, but weaker signals for peptidoglycan and nucleic acid. A two-step protocol combining the three biomarkers was established and able to differentiate fungal infections from bacterial infections with an overall accuracy of 94.9%. Our approach was also used to detect ten raw urinary tract infection samples. Successful identification of fungi was achieved within half an hour after sample obtainment. We further demonstrated the accurate fungal species taxonomy achieved with Raman-assisted cell ejection. Our findings demonstrate that Raman-based fungal identification is a novel, facile, reliable, and with a breadth of coverage approach, that has a great potential to be adopted in routine clinical practice to reduce the turn-around time of invasive fungal disease (IFD) diagnostics.

Topics: Bacteria; Bacterial Infections; Cytochromes c; Humans; Peptidoglycan; Saccharomyces cerevisiae; Spectrum Analysis, Raman