Droplet-based high-throughput single microbe RNA sequencing by smRandom-seq Article Swipe
Ziye Xu
,
Yuting Wang
,
Kuanwei Sheng
,
Raoul G Rosenthal
,
Nan Liu
,
Xiaoting Hua
,
Tianyu Zhang
,
Jiaye Chen
,
Mengdi Song
,
Yuexiao Lv
,
Shunji Zhang
,
Yingjuan Huang
,
Zhaolun Wang
,
Ting Cao
,
Yifei Shen
,
Yan Jiang
,
Yunsong Yu
,
Yu Chen
,
Guoji Guo
,
Peng Yin
,
David A. Weitz
,
Yongcheng Wang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1038/s41467-023-40137-9
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1038/s41467-023-40137-9
Bacteria colonize almost all parts of the human body and can differ significantly. However, the population level transcriptomics measurements can only describe the average bacteria population behaviors, ignoring the heterogeneity among bacteria. Here, we report a droplet-based high-throughput single-microbe RNA-seq assay (smRandom-seq), using random primers for in situ cDNA generation, droplets for single-microbe barcoding, and CRISPR-based rRNA depletion for mRNA enrichment. smRandom-seq showed a high species specificity (99%), a minor doublet rate (1.6%), a reduced rRNA percentage (32%), and a sensitive gene detection (a median of ~1000 genes per single E. coli ). Furthermore, smRandom-seq successfully captured transcriptome changes of thousands of individual E. coli and discovered a few antibiotic resistant subpopulations displaying distinct gene expression patterns of SOS response and metabolic pathways in E. coli population upon antibiotic stress. smRandom-seq provides a high-throughput single-microbe transcriptome profiling tool that will facilitate future discoveries in microbial resistance, persistence, microbe-host interaction, and microbiome research.
Related Topics
Concepts
Transcriptome
Biology
Microbiome
RNA-Seq
Population
Gene
Computational biology
Ribosomal RNA
Gene expression profiling
Bacteria
Genetics
RNA
Metagenomics
Gene expression
Demography
Sociology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41467-023-40137-9
- https://www.nature.com/articles/s41467-023-40137-9.pdf
- OA Status
- gold
- Cited By
- 83
- References
- 64
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386116682
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386116682Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1038/s41467-023-40137-9Digital Object Identifier
- Title
-
Droplet-based high-throughput single microbe RNA sequencing by smRandom-seqWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-23Full publication date if available
- Authors
-
Ziye Xu, Yuting Wang, Kuanwei Sheng, Raoul G Rosenthal, Nan Liu, Xiaoting Hua, Tianyu Zhang, Jiaye Chen, Mengdi Song, Yuexiao Lv, Shunji Zhang, Yingjuan Huang, Zhaolun Wang, Ting Cao, Yifei Shen, Yan Jiang, Yunsong Yu, Yu Chen, Guoji Guo, Peng Yin, David A. Weitz, Yongcheng WangList of authors in order
- Landing page
-
https://doi.org/10.1038/s41467-023-40137-9Publisher landing page
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-
https://www.nature.com/articles/s41467-023-40137-9.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://www.nature.com/articles/s41467-023-40137-9.pdfDirect OA link when available
- Concepts
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Transcriptome, Biology, Microbiome, RNA-Seq, Population, Gene, Computational biology, Ribosomal RNA, Gene expression profiling, Bacteria, Genetics, RNA, Metagenomics, Gene expression, Demography, SociologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
83Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 38, 2024: 43, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
64Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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