Single-cell transcriptomics and data analyses for prokaryotes-Past, present and future concepts
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Single-cell transcriptomics and data analyses for prokaryotes-Past, present and future concepts. / Münch, Julia M; Sobol, Morgan S; Brors, Benedikt; Kaster, Anne-Kristin.
In: ADV APPL MICROBIOL, Vol. 123, 2023, p. 1-39.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Single-cell transcriptomics and data analyses for prokaryotes-Past, present and future concepts
AU - Münch, Julia M
AU - Sobol, Morgan S
AU - Brors, Benedikt
AU - Kaster, Anne-Kristin
N1 - Copyright © 2023. Published by Elsevier Inc.
PY - 2023
Y1 - 2023
N2 - Transcriptomics, or more specifically mRNA sequencing, is a powerful tool to study gene expression at the single-cell level (scRNA-seq) which enables new insights into a plethora of biological processes. While methods for single-cell RNA-seq in eukaryotes are well established, application to prokaryotes is still challenging. Reasons for that are rigid and diverse cell wall structures hampering lysis, the lack of polyadenylated transcripts impeding mRNA enrichment, and minute amounts of RNA requiring amplification steps before sequencing. Despite those obstacles, several promising scRNA-seq approaches for bacteria have been published recently, albeit difficulties in the experimental workflow and data processing and analysis remain. In particular, bias is often introduced by amplification which makes it difficult to distinguish between technical noise and biological variation. Future optimization of experimental procedures and data analysis algorithms are needed for the improvement of scRNA-seq but also to aid in the emergence of prokaryotic single-cell multi-omics. to help address 21st century challenges in the biotechnology and health sector.
AB - Transcriptomics, or more specifically mRNA sequencing, is a powerful tool to study gene expression at the single-cell level (scRNA-seq) which enables new insights into a plethora of biological processes. While methods for single-cell RNA-seq in eukaryotes are well established, application to prokaryotes is still challenging. Reasons for that are rigid and diverse cell wall structures hampering lysis, the lack of polyadenylated transcripts impeding mRNA enrichment, and minute amounts of RNA requiring amplification steps before sequencing. Despite those obstacles, several promising scRNA-seq approaches for bacteria have been published recently, albeit difficulties in the experimental workflow and data processing and analysis remain. In particular, bias is often introduced by amplification which makes it difficult to distinguish between technical noise and biological variation. Future optimization of experimental procedures and data analysis algorithms are needed for the improvement of scRNA-seq but also to aid in the emergence of prokaryotic single-cell multi-omics. to help address 21st century challenges in the biotechnology and health sector.
KW - Transcriptome
KW - Sequence Analysis, RNA/methods
KW - Single-Cell Analysis/methods
KW - Data Analysis
KW - RNA, Messenger
U2 - 10.1016/bs.aambs.2023.04.002
DO - 10.1016/bs.aambs.2023.04.002
M3 - SCORING: Journal article
C2 - 37400172
VL - 123
SP - 1
EP - 39
JO - ADV APPL MICROBIOL
JF - ADV APPL MICROBIOL
SN - 0065-2164
ER -