Evidence map›Paper›PMID 32132208›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2020

Metabolic and genetic basis for auxotrophies in Gram-negative species.

Yara Seif, Kumari Sonal Choudhary, Ying Hefner, Amitesh Anand, Laurence Yang, Bernhard O Palsson

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
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

42 citing papers in PubMed, 61 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Predicting Strain-Specific Metabolic Capabilities in the GenusComputational and structural biotechnology journal · 2026
    Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Infection and immunity · 2024
    Article
  16. Article
  17. Article
  18. From microbiome composition to functional engineering, one step at a time.Microbiology and molecular biology reviews : MMBR · 2023
    Review
  19. Article
  20. 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

6 authors at 3 institutions in 3 countries.

Yara SeifSystems Biology Research Group, Department of Bioengineering, University of California San Diego, CA 92122.ORCID 0000-0001-8813-5679
Kumari Sonal ChoudharySystems Biology Research Group, Department of Bioengineering, University of California San Diego, CA 92122.ORCID 0000-0001-9527-7958
Ying HefnerSystems Biology Research Group, Department of Bioengineering, University of California San Diego, CA 92122.
Amitesh AnandSystems Biology Research Group, Department of Bioengineering, University of California San Diego, CA 92122.ORCID 0000-0002-3720-4301
Laurence YangSystems Biology Research Group, Department of Bioengineering, University of California San Diego, CA 92122.ORCID 0000-0001-6663-7643
Bernhard O PalssonSystems Biology Research Group, Department of Bioengineering, University of California San Diego, CA 92122; palsson@ucsd.edu.ORCID 0000-0003-2357-6785
University of California San Diego · USNovo Nordisk Foundation · DKQueen's University · CA

Funding

Systems Biology Approach to Redefine Susceptibility Testing and Treatment of MDR Pathogens in the Context of Host ImmunityU01AI124316 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 2016 to 2020
$10.2M
GENOMICALLY BASED MODELS FOR ANTIBIOTIC DEVELOPMENTR01GM057089 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 1998 to 2021
$6.9M
NIAID NIH HHS U01 AI124316NIGMS NIH HHS R01 GM057089
6 · The paper itself

Abstract

Auxotrophies constrain the interactions of bacteria with their environment, but are often difficult to identify. Here, we develop an algorithm (AuxoFind) using genome-scale metabolic reconstruction to predict auxotrophies and apply it to a series of available genome sequences of over 1,300 Gram-negative strains. We identify 54 auxotrophs, along with the corresponding metabolic and genetic basis, using a pangenome approach, and highlight auxotrophies conferring a fitness advantage in vivo. We show that the metabolic basis of auxotrophy is species-dependent and varies with 1) pathway structure, 2) enzyme promiscuity, and 3) network redundancy. Various levels of complexity constitute the genetic basis, including 1) deleterious single-nucleotide polymorphisms (SNPs), in-frame indels, and deletions; 2) single/multigene deletion; and 3) movement of mobile genetic elements (including prophages) combined with genomic rearrangements. Fourteen out of 19 predictions agree with experimental evidence, with the remaining cases highlighting shortcomings of sequencing, assembly, annotation, and reconstruction that prevent predictions of auxotrophies. We thus develop a framework to identify the metabolic and genetic basis for auxotrophies in Gram-negatives.

Indexed as

Models, BiologicalAlgorithmsComputer SimulationEnergy MetabolismGenome, BacterialGenomicsGram-Negative BacteriaHost Microbial InteractionsInterspersed Repetitive SequencesMetabolic Networks and PathwaysMetabolomicsNutrientsNutrientsauxotrophycomparative genomicsmathematical modelingpangenomesystems biology

Identifiers

PMID32132208
PMCPMC7084086
OpenAlexW3010074221

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.