Progress has been made in the study of single cell Raman tracing the evolution track of bacterial resistance in urban environment institute

　　The frequent emergence of antibiotic resistance challenges modern medicine. It is very important to discuss the evolution of resistance to curb its global spread. The evolution of resistance involves a highly complex phenotypic heterogeneous response. Under the treatment of antibiotics, a small number of antibiotic-tolerant cell subsets will appear in the microbial flora with identical genes. The surviving subgroup can’t grow in the presence of antibiotics, but it can grow again after removing antibiotics, resulting in long-term recurrent infection, which is also the key reservoir for subsequent mutation of resistance genes. However, due to the complex heterogeneous response and stagnant growth of tolerance subgroups, it is still a challenge to identify tolerance subgroups from a large number of bacterial populations and track their physiological evolution trajectory.　
　　Recently, the team of Academician Zhu Yongguan from the Institute of Urban Environment, Chinese Academy of Sciences and Cui Li’s research group published in German Applied Chemistry. A research paper entitled an isotope-labeled single-cell Raman spectroscopy approach for tracking the physiological evolution of bacteria towards biological resistance was published. In this study, the heterogeneity of bacterial response was analyzed in situ at a high-precision level by developing a combination of single-cell Raman-deuterium isotope-multivariate statistical analysis, and the differentiation and dynamic changes of phenotypic subsets were sensitively identified from a large number of bacterial populations, which realized the rapid in-situ tracking of bacterial phenotypic physiological trajectory before resistance mutation, providing important guidance for curbing resistance evolution.　
　　In this study, bacteria were repeatedly exposed to clinical therapeutic doses of antibiotics, and antibiotic resistance evolved. In this paper, the in-situ activity of bacteria during evolution was detected by Raman spectroscopy of single cells labeled with heavy water in a culture-independent way. The results showed that the activity of bacteria under antibiotic pressure gradually increased with the treatment cycle without resistance mutation, indicating that its phenotypic tolerance gradually improved. Furthermore, the study uses UMAP multivariate statistical algorithm to analyze the single cell Raman fingerprint interval of thousands of bacteria in all evolutionary stages. According to the physiological response of bacterial phenotype indicated by Raman fingerprint, four phenotypic subgroups differentiated with the evolution of resistance were identified from bacterial populations with identical initial genotypes, namely sensitive flora, primary tolerant bacteria, evolution tolerant bacteria and evolution resistant bacteria, and the dynamic changes of the four subgroups with the evolution process were sensitively captured. So far, based on the heterogeneous response of bacteria in situ phenotype revealed by single cell Raman, researchers have drawn a physiological trajectory map of resistance evolution. Genome-wide sequencing of bacteria verified the revealed phenotype interactively, and analyzed the genetic basis of phenotype. Phenotypic differentiation is very important to maintain the survival and evolution of the whole flora. Because phenotypic differentiation is much earlier than resistance mutation, identifying phenotypic differentiation is of great significance for guiding clinical medication and reducing the occurrence of antibiotic tolerance and resistance mutation. In this study, the Raman spectra of four distinct subgroups were used to dig out the Raman marker peaks of tolerance and resistance mutation, which promoted the rapid and accurate identification of different stages of resistance evolution, especially phenotypic tolerance.　
　　The single cell analysis platform can be extended to a wider range of research on the evolution of resistance induced by antibiotics or non-antibiotic chemicals. In the future, the single-cell Raman can be combined with targeted single-cell sorting and multi-omics technology to realize the accurate correlation between tolerance and resistance phenotype and genotype, and promote the further explanation of evolutionary mechanism. The research work is supported by the "0 to 1" original innovation project of Chinese Academy of Sciences, the innovative research group project of National Natural Science Foundation of China and Fujian Natural Science Foundation.　
　　Paper link　
　　Tracking the evolution of bacterial antibiotic resistance by single cell Raman-isotope labeling-multivariate statistical analysis