Evidence map›Paper›PMID 36702958›Full record

ArticleNature chemical biology2023

Photo-ANA enables profiling of host-bacteria protein interactions during infection.

Xiao-Meng Li, Siyue Huang, Xiang David Li

Abstract read
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In one paragraph

Article in Nature chemical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Experimental Approaches to Visualize Effector Protein Translocation During Host-Pathogen Interactions.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. MACSPI enables tissue-selective proteomic and interactomic analyses in multicellular organisms.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  10. Article
  11. Article
  12. 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.

Xiao-Meng LiDepartment of Chemistry, The University of Hong Kong, Hong Kong, China.ORCID http://orcid.org/0000-0002-8486-6826
Siyue HuangDepartment of Chemistry, The University of Hong Kong, Hong Kong, China.
Xiang David LiDepartment of Chemistry, The University of Hong Kong, Hong Kong, China. xiangli@hku.hk.ORCID http://orcid.org/0000-0002-2797-4134

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial pathogens rapidly change and adapt their proteome to cope with the environment in host cells and secrete effector proteins to hijack host targets and ensure their survival and proliferation during infection. Excessive host proteins make it difficult to profile pathogens' proteome dynamics by conventional proteomics. It is even more challenging to map pathogen-host protein-protein interactions in real time, given the low abundance of bacterial effectors and weak and transient interactions in which they may be involved. Here we report a method for selectively labeling bacterial proteomes using a bifunctional amino acid, photo-ANA, equipped with a bio-orthogonal handle and a photoreactive warhead, which enables simultaneous analysis of bacterial proteome reprogramming and pathogen-host protein interactions of Salmonella enterica serovar Typhimurium (S. Typhimurium) during infection. Using photo-ANA, we identified FLOT1/2 as host interactors of S. Typhimurium effector PipB2 in late-stage infection and globally profiled the extensive interactions between host proteins and pathogens during infection.

Indexed as

Bacterial ProteinsProteomeHost-Pathogen InteractionsSalmonella typhimuriumBacterial ProteinsProteome

Identifiers

What OpenQuestion holds

Textmetadata
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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.