Evidence map›Paper›PMID 26531810›Full record

ArticleScientific reports2015

Systems biology-guided identification of synthetic lethal gene pairs and its potential use to discover antibiotic combinations.

Ramy K Aziz, Jonathan M Monk, Robert M Lewis, Suh In Loh, Arti Mishra, Amrita Abhay Nagle, Chitkala Satyanarayana, Saravanakumar Dhakshinamoorthy, Michele Luche, Douglas B Kitchen and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Antibiotic resistance: Time of synthesis in a post-genomic age.Computational and structural biotechnology journal · 2021
    Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Antibiotic efficacy-context matters.Current opinion in microbiology · 2017
    Review
  12. Article
  13. Big Data: Challenges and opportunities for clinical pharmacology.British journal of clinical pharmacology · 2016
    Article
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

15 authors.

Ramy K AzizDepartment of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, 11562, Egypt.
Jonathan M MonkDepartment of Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA.
Robert M LewisComputer-Aided Drug Discovery, Albany Molecular Research, Inc., Albany, New York, 12203, USA.
Suh In LohAlbany Molecular Research Singapore Research Centre, Pte Ltd, Singapore, 117525.
Arti MishraAlbany Molecular Research Singapore Research Centre, Pte Ltd, Singapore, 117525.
Amrita Abhay NagleAlbany Molecular Research Singapore Research Centre, Pte Ltd, Singapore, 117525.
Chitkala SatyanarayanaAlbany Molecular Research Singapore Research Centre, Pte Ltd, Singapore, 117525.
Saravanakumar DhakshinamoorthyAlbany Molecular Research Singapore Research Centre, Pte Ltd, Singapore, 117525.
Michele LucheComputer-Aided Drug Discovery, Albany Molecular Research, Inc., Albany, New York, 12203, USA.
Douglas B KitchenComputer-Aided Drug Discovery, Albany Molecular Research, Inc., Albany, New York, 12203, USA.
Kathleen A AndrewsDepartment of Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA.
Nicole L FongDepartment of Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA.
Howard J LiDepartment of Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA.
Bernhard O PalssonDepartment of Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA.
Pep CharusantiDepartment of Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA.

Funding

GENOMICALLY BASED MODELS FOR ANTIBIOTIC DEVELOPMENTR01GM057089 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 1998 to 2021
$6.9M
Model-guided Identification of Synthetic Lethal Genes for Drug Target DevelopmentR01GM098105 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PALSSON, BERNHARD O · 2011 to 2013
$1.8M
NIGMS NIH HHS GM057089NIGMS NIH HHS R01 GM057089NIGMS NIH HHS R01 GM098105
6 · The paper itself

Abstract

Mathematical models of metabolism from bacterial systems biology have proven their utility across multiple fields, for example metabolic engineering, growth phenotype simulation, and biological discovery. The usefulness of the models stems from their ability to compute a link between genotype and phenotype, but their ability to accurately simulate gene-gene interactions has not been investigated extensively. Here we assess how accurately a metabolic model for Escherichia coli computes one particular type of gene-gene interaction, synthetic lethality, and find that the accuracy rate is between 25% and 43%. The most common failure modes were incorrect computation of single gene essentiality and biological information that was missing from the model. Moreover, we performed virtual and biological screening against several synthetic lethal pairs to explore whether two-compound formulations could be found that inhibit the growth of Gram-negative bacteria. One set of molecules was identified that, depending on the concentrations, inhibits E. coli and S. enterica serovar Typhimurium in an additive or antagonistic manner. These findings pinpoint specific ways in which to improve the predictive ability of metabolic models, and highlight one potential application of systems biology to drug discovery and translational medicine.

Indexed as

Anti-Bacterial AgentsDrug CombinationsDrug DiscoveryEscherichia coli O157Foodborne DiseasesGenes, LethalKlebsiella pneumoniaeMicrobial Sensitivity TestsModels, BiologicalModels, TheoreticalSalmonella typhimuriumSystems BiologyYersinia pestisAnti-Bacterial AgentsDrug Combinations

Identifiers

PMID26531810
PMCPMC4631998

What OpenQuestion holds

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LicenceCC BY
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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.