epiTCR: a highly sensitive predictor for TCR-peptide binding.

MOTIVATION: Predicting the binding between T-cell receptor (TCR) and peptide presented by human leucocyte antigen molecule is a highly challenging task and a key bottleneck in the development of immunotherapy. Existing prediction tools, despite exhibiting good performance on the datasets they were built with, suffer from low true positive rates when used to predict epitopes capable of eliciting T-cell responses in patients. Therefore, an improved tool for TCR-peptide prediction built upon a large dataset combining existing publicly available data is still needed. RESULTS: We collected data from five public databases (IEDB, TBAdb, VDJdb, McPAS-TCR, and 10X) to form a dataset of >3 million TCR-peptide pairs, 3.27% of which were binding interactions. We proposed epiTCR, a Random Forest-based method dedicated to predicting the TCR-peptide interactions. epiTCR used simple input of TCR CDR3ß sequences and antigen sequences, which are encoded by flattened BLOSUM62. epiTCR performed with area under the curve (0.98) and higher sensitivity (0.94) than other existing tools (NetTCR, Imrex, ATM-TCR, and pMTnet), while maintaining comparable prediction specificity (0.9). We identified seven epitopes that contributed to 98.67% of false positives predicted by epiTCR and exerted similar effects on other tools. We also demonstrated a considerable influence of peptide sequences on prediction, highlighting the need for more diverse peptides in a more balanced dataset. In conclusion, epiTCR is among the most well-performing tools, thanks to the use of combined data from public sources and its use will contribute to the quest in identifying neoantigens for precision cancer immunotherapy. AVAILABILITY AND IMPLEMENTATION: epiTCR is available on GitHub (https://github.com/ddiem-ri-4D/epiTCR).

The emergence of plasmid-borne cfr-mediated linezolid resistant-staphylococci in Vietnam.

OBJECTIVES: Linezolid is one of the last resort antibiotics effectively used in the treatment of infections caused by multidrug-resistant Gram-positive bacteria. Recent outbreaks of Linezolid resistance have been the great concern worldwide, while many countries have not experienced it. In this work, we aimed to evaluate the existence of linezolid resistance and further clarify potential resistance mechanism(s) in staphylococcal isolates obtained from the hospital in Vietnam, a country in which linezolid resistance had not been previously detected. METHODS: Seventy staphylococcal clinical isolates including MRSA (n=63) and methicillin-resistant coagulase-negative staphylococci (MRCNS, n=7) were collected and analyzed for linezolid resistance. Linezolid-resistant isolates were submitted for whole genome sequencing to search for the resistance determinants. RESULTS: We identified two coagulase-negative staphylococcal isolates that were resistant to linezolid. Whole genome sequencing revealed several alterations in the 23S rRNA and L3, L17, L22, L24, L30 ribosomal proteins. Importantly, both isolates harbour the chloramphenicol/florfenicol resistance (cfr) gene on a plasmid. The plasmid was closely identical to the pLRSA417 plasmid that was originally reported in China. CONCLUSIONS: To the best of our knowledge, this is the first report of cfr-mediated linezolid resistance in clinically isolated staphylococci in Vietnam. We suggest that adequate surveillance is necessary to monitor the dissemination of linezolid resistance among staphylococcal species and other important pathogens.