Identification of bacteria in mixed infection from urinary tract of patient's samples using Raman analysis of dried droplets.

Urinary tract infections (UTI) are among the most frequent nosocomial infections. A fast identification of the pathogen and assignment of Gram type could help to prescribe most suitable treatments. Raman spectroscopy holds high potential for fast and reliable bacterial pathogens identification. While most studies so far have focused on individual pathogens or artificial mixtures, this contribution aims to translate the analysis to primary urine samples from patients with suspected UTIs. For this, we have included 59 primary urine samples out of which 29 were diagnosed as mixed infections. For Raman analysis, we first trained two classification models based on principal component analysis - linear discriminant analysis (PCA-LDA) with more than 3500 Raman spectra of 85 clinical isolates from 23 species in order to (1) identify the Gram type of the bacteria and (2) assign family membership to one of the six most abundant bacterial families in urinary tract infections (Enterobacteriaceae, Morganellaceae, Pseudomonadaceae, Enterococcaceae, Staphylococcaceae and Streptococcaceae). The classification models were applied to artificial mixtures of Gram positive and Gram negative bacteria to correctly predict mixed infections with an accuracy of 75%. Raman scans of dried droplets did not yet yield optimal classification results on family level. When translating the method to primary urine samples, we observed a strong bias towards Gram negative bacteria, on family level towards Morganellaceae, which reduced prediction accuracy. Spectral differences were observed between isolates grown on standard growth medium and bacteria of the same strain when characterized directly from the patient. Thus, improvement of the classification accuracy is expected with a larger data base containing also bacteria measured directly from the urine sample.

Development of a rapid diagnostic test based on loop-mediated isothermal amplification to identify the most frequent non-typhoidal Salmonella serovars from culture.

Identification of Salmonella serovars is performed by conventional seroagglutination or sequencing. These methods are labor-intensive and require technical experience. An easy-to-perform assay allowing the timely identification of the most common non-typhoidal serovars (NTS) is needed. In this study, a molecular assay based on loop-mediated isothermal amplification (LAMP) targeting specific gene sequences of Salmonella Enteritidis, S. Typhimurium, S. Infantis, S. Derby, and S. Choleraesuis has been developed for rapid serovar identification from cultured colonies. A total of 318 Salmonella strains and 25 isolates of other Enterobacterales species that served as negative controls were analyzed. All S. Enteritidis (n = 40), S. Infantis (n = 27), and S. Choleraesuis (n = 11) strains were correctly identified. Seven out of 104 S. Typhimurium and 10 out of 38 S. Derby strains missed a positive signal. Cross-reactions of the gene targets were only rarely observed and restricted to the S. Typhimurium primer set (5 false-positives). Sensitivity and specificity of the assay compared to seroagglutination were as follows: 100% and 100% for S. Enteritidis, 93.3% and 97.7% for S. Typhimurium, 100% and 100% for S. Infantis, 73.7% and 100% for S. Derby, and 100% and 100% for S. Choleraesuis, respectively. With results available in just a few minutes of hands-on time and a test run time of 20 min, the LAMP assay developed here may be a useful tool for the rapid identification of common Salmonella NTS in daily routine diagnostics.

The sirtuin 1/2 inhibitor tenovin-1 induces a nonlinear apoptosis-inducing factor-dependent cell death in a p53 null Ewing's sarcoma cell line.

The sirtuin 1/2 inhibitor tenovin-1 activates p53 and may have potential in the management of cancer. Here, we investigated the responsiveness of Ewing's sarcoma cells to tenovin-1. We examined its effects in two Ewing's sarcoma cell lines with different p53 status, i.e. in p53 wild-type and p53 null cells. Effects were assessed by flow cytometric analyses of cell death, mitochondrial membrane depolarization and reactive oxygen species (ROS) generation, by caspase 3/7 activity measurement, by mRNA expression profiling and by immunoblotting. Tenovin-1 elicited caspase-mediated cell death in p53 wild-type cells, but caspase-independent cell death in p53 null cells. Remarkably, it induced a nonlinear concentration response in the latter: low concentrations of tenovin-1 were much more effective than were higher concentrations. Tenovin-1's effects in p53 null cells involved gene expression changes of Bcl-2 family members, mitochondrial membrane depolarization, nuclear translocation of apoptosis-inducing factor, ROS formation and DNA damage; all these effects followed a bell-shaped pattern. In conclusion, our results provide new insights into tenovin-1's mode of action by demonstrating that it can induce different pathways of cell death.