Affiliation:
1. Single‐Cell Center Qingdao Institute of Bioenergy and Bioprocess Technology Chinese Academy of Sciences Qingdao Shandong China
2. State Key Laboratory of Infectious Disease Prevention and Control Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases National Institute for Communicable Disease Control and Prevention Chinese Center for Disease Control and Prevention Beijing China
3. Department of Clinical Laboratory Peking Union Medical College Hospital Peking Union Medical College Chinese Academy of Medical Sciences Beijing China
4. Medical Affairs Danaher Corporation/Cepheid Shanghai China
5. Qingdao Single‐Cell Biotech. Co., Ltd. Qingdao Shandong China
6. Chongqing International Institute of Immunology Chongqing Sichuan China
Abstract
AbstractDue 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.
Cited by
3 articles.
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