Literature DB >> 31152870

Ramanome technology platform for label-free screening and sorting of microbial cell factories at single-cell resolution.

Yuehui He1, Xixian Wang1, Bo Ma2, Jian Xu3.   

Abstract

Phenotypic profiling of natural, engineered or synthetic cells has increasingly become a bottleneck in the mining and engineering of cell factories. Single-cell phenotyping technologies are highly promising for tackling this hurdle, yet ideally they should allow non-invasive live-cell probing, be label-free, provide landscape-like phenotyping capability, distinguish complex functions, operate with high speed, sufficient throughput and low cost, and finally, couple with cell sorting so as to enable downstream omics analysis. This review focuses on recent progress in Ramanome Technology Platform (RTP), which consists of Raman spectroscopy based phenotyping, sorting and sequencing of single cells, and discuss the key challenges and emerging trends. In addition, we propose ramanome, a collection of single-cell Raman spectra (SCRS) acquired from individual cells within a cellular population or consortium, as a new type of biological phenome datatype at the single-cell resolution. By establishing the phenome-genome links in a label-free, single-cell manner, RTP should find wide applications in functional screening and strain development of live microbial, plant and animal cell factories.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cell sorting; Microbial cell factory; Molecular spectroscopy; Phenotyping; Single-cell phenome; Single-cell sequencing; Synthetic biology

Mesh:

Year:  2019        PMID: 31152870     DOI: 10.1016/j.biotechadv.2019.04.010

Source DB:  PubMed          Journal:  Biotechnol Adv        ISSN: 0734-9750            Impact factor:   14.227


  9 in total

Review 1.  Development overview of Raman-activated cell sorting devoted to bacterial detection at single-cell level.

Authors:  Shuaishuai Yan; Jingxuan Qiu; Liang Guo; Dezhi Li; Dongpo Xu; Qing Liu
Journal:  Appl Microbiol Biotechnol       Date:  2021-01-22       Impact factor: 4.813

Review 2.  Next-generation physiology approaches to study microbiome function at single cell level.

Authors:  Roland Hatzenpichler; Viola Krukenberg; Rachel L Spietz; Zackary J Jay
Journal:  Nat Rev Microbiol       Date:  2020-02-13       Impact factor: 60.633

3.  Positive dielectrophoresis-based Raman-activated droplet sorting for culture-free and label-free screening of enzyme function in vivo.

Authors:  Xixian Wang; Yi Xin; Lihui Ren; Zheng Sun; Pengfei Zhu; Yuetong Ji; Chunyu Li; Jian Xu; Bo Ma
Journal:  Sci Adv       Date:  2020-08-07       Impact factor: 14.136

4.  Exploring a blue-light-sensing transcription factor to double the peak productivity of oil in Nannochloropsis oceanica.

Authors:  Peng Zhang; Yi Xin; Yuehui He; Xianfeng Tang; Chen Shen; Qintao Wang; Nana Lv; Yun Li; Qiang Hu; Jian Xu
Journal:  Nat Commun       Date:  2022-03-29       Impact factor: 17.694

5.  Intra-Ramanome Correlation Analysis Unveils Metabolite Conversion Network from an Isogenic Population of Cells.

Authors:  Yuehui He; Shi Huang; Peng Zhang; Yuetong Ji; Jian Xu
Journal:  mBio       Date:  2021-08-31       Impact factor: 7.867

6.  Rapid, Label-Free Prediction of Antibiotic Resistance in Salmonella typhimurium by Surface-Enhanced Raman Spectroscopy.

Authors:  Ping Zhang; Xi-Hao Wu; Lan Su; Hui-Qin Wang; Tai-Feng Lin; Ya-Ping Fang; Hui-Min Zhao; Wen-Jing Lu; Meng-Jia Liu; Wen-Bo Liu; Da-Wei Zheng
Journal:  Int J Mol Sci       Date:  2022-01-25       Impact factor: 5.923

7.  Assessing Efficacy of Clinical Disinfectants for Pathogenic Fungi by Single-Cell Raman Microspectroscopy.

Authors:  Fan Li; Lihui Ren; Rongze Chen; Xi Sun; Jian Xu; Pengfei Zhu; Fang Yang
Journal:  Front Cell Infect Microbiol       Date:  2022-02-23       Impact factor: 5.293

8.  Single-cell Raman spectroscopy identifies Escherichia coli persisters and reveals their enhanced metabolic activities.

Authors:  Chuan Wang; Rongze Chen; Jian Xu; Lijian Jin
Journal:  Front Microbiol       Date:  2022-08-04       Impact factor: 6.064

9.  Microbial Single-Cell Analysis: What Can We Learn From Mammalian?

Authors:  Zixi Chen; Beixin Mo; Anping Lei; Jiangxin Wang
Journal:  Front Cell Dev Biol       Date:  2022-01-17
  9 in total

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