Evidence map›Paper›PMID 36180320›Full record

ReviewTrends in biochemical sciences2023

High-throughput approaches to understand and engineer bacteriophages.

Phil Huss, Jackie Chen, Srivatsan Raman

Abstract readReview
In one paragraph

Review in Trends in biochemical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Optimizing phage therapy with artificial intelligence: a perspective.Frontiers in cellular and infection microbiology · 2025
    Review
  9. Article
  10. 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

3 authors.

Phil HussDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA; Microbiology Doctoral Training Program, University of Wisconsin-Madison, Madison, WI 53706, USA.
Jackie ChenDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Srivatsan RamanDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA. Electronic address: sraman4@wisc.edu.

Funding

Biotechnology Training ProgramT32GM135066 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI SCOTT M. COYLE, BRIAN G FOX · 2020 to 2026
$7.0M
Understanding molecular rules governing bacteriophage specificity and virulence by high-throughput mutational and metagenomic scanningR21AI156785 · NIAID · UNIVERSITY OF WISCONSIN-MADISON · PI RAMAN, SRIVATSAN · 2021 to 2022
$427k
NIAID NIH HHS R21 AI156785NIGMS NIH HHS T32 GM135066
6 · The paper itself

Abstract

Bacteriophage research has been vital to fundamental aspects of modern biology. Advances in metagenomics have revealed treasure troves of new and uncharacterized bacteriophages ('phages') that are not yet understood. However, our ability to find new phages has outpaced our understanding of how sequence encodes function in phages. Traditional approaches for characterizing phages are limited in scale and face hurdles in determining how changes in sequence drive function. We describe powerful emerging technologies that can be used to clarify sequence-function relationships in phages through high-throughput genome engineering. Using these approaches, up to 10

Indexed as

BacteriophagesGenome, Viraldeep sequencingengineered bacteriophagesgenome engineeringphage–host interactionsphage libraryphage mutagenesis

Identifiers

PMID36180320
PMCPMC9868059

What OpenQuestion holds

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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.