通过ramanome技术平台的单细胞代谢现象和基因组:传染病精准医学的终极精度?

iLABMED Pub Date : 2023-05-09 DOI:10.1002/ila2.12
Jian Xu, Jianzhong Zhang, Yingchun Xu, Yi-Wei Tang, Bo Ma, Yuzhang Wu
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摘要

由于现有方法的局限性,诊断和治疗细菌和真菌感染的快速、敏感、准确、全面和普遍适用的策略仍然是一个重大挑战。在这里,基于ramanome技术平台,我们提出了一种无培养、单细胞分辨率、现象基因组组合策略,称为单细胞鉴定、活力和活力测试以及来源跟踪(SCIVVS)。对于直接从临床标本中提取的每个细胞,D2O探测的单细胞拉曼光谱(SCRS)的指纹区能够基于病原体物种的参考SCRS数据库进行物种水平的鉴定,而C-D带准确地量化了生存能力、代谢活力、对抗菌剂的表型易感性及其细胞间异质性。此外,为了来源追踪细胞,进行拉曼激活的细胞分选,然后测序或培养,从一个致病细胞中产生索引的、高覆盖率的基因组组装或纯培养物。最后,一个集成的SCIVVS工作流程,以代谢和形态现象的自动分析和排序为特色,可以在几个小时内完成整个过程。由于它解决了代谢现象和基因组的异质性,靶向功能,可以自动化,速度快几个数量级,同时具有成本效益,SCIVVS是一种新的技术和数据框架,用于在各种临床和疾病控制环境中诊断和治疗细菌和真菌感染。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Single cell metabolic phenome and genome via the ramanome technology platform: Precision medicine of infectious diseases at the ultimate precision?

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.

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