{"title":"Single cell metabolic phenome and genome via the ramanome technology platform: Precision medicine of infectious diseases at the ultimate precision?","authors":"Jian Xu, Jianzhong Zhang, Yingchun Xu, Yi-Wei Tang, Bo Ma, Yuzhang Wu","doi":"10.1002/ila2.12","DOIUrl":null,"url":null,"abstract":"<p>Due to the limitations of existing approaches, a rapid, sensitive, accurate, comprehensive, and generally applicable strategy to diagnose and treat bacterial and fungal infections remains a major challenge. Here, based on the ramanome technology platform, we propose a culture-free, one cell resolution, phenome-genome-combined strategy called <span>s</span>ingle-<span>c</span>ell <span>i</span>dentification, <span>v</span>iability and <span>v</span>itality tests and <span>s</span>ource tracking (SCIVVS). For each cell directly extracted from a clinical specimen, the fingerprint region of the D<sub>2</sub>O-probed single cell Raman spectrum (SCRS) enables species-level identification based on a reference SCRS database of pathogen species, whereas the C-D band accurately quantifies viability, metabolic vitality, phenotypic susceptibility to antimicrobials, and their intercellular heterogeneity. Moreover, to source track a cell, Raman-activated cell sorting followed by sequencing or cultivation proceeds, producinging an indexed, high coverage genome assembly or a pure culture from precisely one pathogenic cell. Finally, an integrated SCIVVS workflow that features automated profiling and sorting of metabolic and morphological phenomes can complete the entire process in only a few hours. Because it resolves heterogeneity for both the metabolic phenome and genome, targets functions, can be automated, and is orders-of-magnitude faster while cost-effective, SCIVVS is a new technological and data framework to diagnose and treat bacterial and fungal infections in various clinical and disease control settings.</p>","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"1 1","pages":"5-14"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.12","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"iLABMED","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ila2.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Due to the limitations of existing approaches, a rapid, sensitive, accurate, comprehensive, and generally applicable strategy to diagnose and treat bacterial and fungal infections remains a major challenge. Here, based on the ramanome technology platform, we propose a culture-free, one cell resolution, phenome-genome-combined strategy called single-cell identification, viability and vitality tests and source tracking (SCIVVS). For each cell directly extracted from a clinical specimen, the fingerprint region of the D2O-probed single cell Raman spectrum (SCRS) enables species-level identification based on a reference SCRS database of pathogen species, whereas the C-D band accurately quantifies viability, metabolic vitality, phenotypic susceptibility to antimicrobials, and their intercellular heterogeneity. Moreover, to source track a cell, Raman-activated cell sorting followed by sequencing or cultivation proceeds, producinging an indexed, high coverage genome assembly or a pure culture from precisely one pathogenic cell. Finally, an integrated SCIVVS workflow that features automated profiling and sorting of metabolic and morphological phenomes can complete the entire process in only a few hours. Because it resolves heterogeneity for both the metabolic phenome and genome, targets functions, can be automated, and is orders-of-magnitude faster while cost-effective, SCIVVS is a new technological and data framework to diagnose and treat bacterial and fungal infections in various clinical and disease control settings.