Evidence map›Paper›PMID 33481066›Full record

ReviewApplied microbiology and biotechnology2021

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

Shuaishuai Yan, Jingxuan Qiu, Liang Guo, Dezhi Li, Dongpo Xu, Qing Liu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Applied microbiology and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.5field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
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  7. Review
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  9. Article
  10. Review
  11. Raman cell sorting for single-cell research.Frontiers in bioengineering and biotechnology · 2024
    Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Environmental science and ecotechnology · 2022
    Review
  18. Article
  19. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Shuaishuai YanSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Jingxuan QiuSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Liang GuoSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Dezhi LiSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Dongpo XuSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.
Qing LiuSchool of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China. liuq@usst.edu.cn.ORCID http://orcid.org/0000-0002-5152-2736
University of Shanghai for Science and Technology · CN

Funding

National Key R&D Program of China 2018YFC1602900Science and Technology innovation Plan of Shanghai 19391902000the Fundamental Research Funds for National Key R&D Program of China 2018YFC1602500
6 · The paper itself

Abstract

Understanding the metabolic interactions between bacteria in natural habitat at the single-cell level and the contribution of individual cell to their functions is essential for exploring the dark matter of uncultured bacteria. The combination of Raman-activated cell sorting (RACS) and single-cell Raman spectra (SCRS) with unique fingerprint characteristics makes it possible for research in the field of microbiology to enter the single cell era. This review presents an overview of current knowledge about the research progress of recognition and assessment of single bacterium cell based on RACS and further research perspectives. We first systematically summarize the label-free and non-destructive RACS strategies based on microfluidics, microdroplets, optical tweezers, and specially made substrates. The importance of RACS platforms in linking target cell genotype and phenotype is highlighted and the approaches mentioned in this paper for distinguishing single-cell phenotype include surface-enhanced Raman scattering (SERS), biomarkers, stable isotope probing (SIP), and machine learning. Finally, the prospects and challenges of RACS in exploring the world of unknown microorganisms are discussed. KEY POINTS: • Analysis of single bacteria is essential for further understanding of the microbiological world. • Raman-activated cell sorting (RACS) systems are significant protocol for characterizing phenotypes and genotypes of individual bacteria.

Indexed as

Single-Cell AnalysisSpectrum Analysis, RamanBacteriaBiomarkersBiomarkersBiomarkersMachine learningRaman-activated cell sortingSingle cellStable isotope probingSurface-enhanced Raman scattering

Identifiers

PMID33481066
OpenAlexW3123917559

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.