ArticlebioRxiv : the preprint server for biology2024
Comprehensive double-mutant analysis of the
Byoung-Mo Koo, Horia Todor, Jiawei Sun, Jordi van Gestel, John S Hawkins, Cameron C Hearne, Amy B Banta, Kerwyn Casey Huang, Jason M Peters, Carol A Gross
Abstract readPreprint
In one paragraphArticle in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
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4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
10 authors.
Byoung-Mo KooDepartment of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0003-1001-6367 Horia TodorDepartment of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
Jiawei SunDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Jordi van GestelDepartment of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
John S HawkinsDepartment of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
Cameron C HearneDepartment of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
Amy B BantaPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0002-1843-5059 Kerwyn Casey HuangDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Jason M PetersPharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0003-2722-8382 Carol A GrossDepartment of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0002-5595-9732 Funding
Cellular homeostasis pathways in bacteriaR35GM118061 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GROSS, CAROL ANNE · 2016 to 2025
$9.0MA universal pipeline for functional characterization of the human microbiota at a massive scaleRM1GM135102 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BUIE, CULLEN RICHARD, DEUTSCHBAUER, ADAM M · 2020 to 2024
$7.6MAntimicrobial Resistance and Horizontal Gene Transfer in the Human Gut Microbiome in Response to an AntibioticR01AI147023 · NIAID · PALO ALTO VETERANS INSTIT FOR RESEARCH · PI RELMAN, DAVID A. · 2020 to 2024
$3.5MMolecular Biophysics Training GrantT32GM149436 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Aashish Manglik · 2023 to 2026
$1.6MCross-species Analysis of Bacterial Gene NetworksR35GM150487 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Jason M. Peters · 2023 to 2026
$1.5MNIAID NIH HHS R01 AI147023NIGMS NIH HHS R35 GM118061NIGMS NIH HHS R35 GM150487NIGMS NIH HHS RM1 GM135102NIGMS NIH HHS T32 GM149436
6 · The paper itselfAbstract
Understanding bacterial gene function remains a major biological challenge. Double-mutant genetic interaction (GI) analysis addresses this challenge by uncovering the functional partners of targeted genes, allowing us to associate genes of unknown function with novel pathways and unravel connections between well-studied pathways, but is difficult to implement at the genome-scale. Here, we develop and use double-CRISPRi to systematically quantify genetic interactions at scale in the
Indexed as
Cell divisionCell envelopeDouble-CRISPRiGenetic interactionmblmreB
Identifiers
PMID39185233
PMCPMC11343205
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