Evidence map›Paper›PMID 39014020›Full record

ArticleScientific reports2024

Systematic analysis of microorganisms' metabolism for selective targeting.

Mehdi Dehghan Manshadi, Payam Setoodeh, Habil Zare

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Anti-infective compounds forSustainable microbiology · 2026
    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.

Mehdi Dehghan ManshadiDepartment of Chemical Engineering, School of Chemical, Petroleum and Gas Engineering, Shiraz University, Shiraz, Iran.
Payam Setoodeh *Department of Chemical Engineering, School of Chemical, Petroleum and Gas Engineering, Shiraz University, Shiraz, Iran. payamst@shirazu.ac.ir.
Habil Zare *Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA. zare@uthscsa.edu.

Funding

DISCOVERY - Statistics and Analysis CoreU19NS115388 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Steven M Greenberg, Natalia S Rost · 2019 to 2026
$75.4M
South Texas Alzheimer's Disease Research CenterP30AG066546 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Mohamad Habes · 2021 to 2026
$24.0M
Plasma Proteome and Risk of Alzheimer Dementia and Related Endophenotypes in the Framingham StudyRF1AG063507 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GERSZTEN, ROBERT E, RAMACHANDRAN, VASAN S · 2019 to 2019
$4.2M
Mechanisms of tau- and aging-induced neurological dysfunction: Focus on the nucleusR01AG057896 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FROST, BESS · 2019 to 2023
$2.8M
Proteasome dysfunction as a driver of age-associated risk for Alzheimer's disease onset and progressionRF1AG065301 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI PICKERING, ANDREW MICHAEL · 2020 to 2020
$2.1M
High Resolution Profiling of Senescent Neurons and Their Microenvironments in Postmortem Human Brain Tissue Spanning Eight Decades of LifeR01AG068293 · NIA · WASHINGTON UNIVERSITY · PI ORR, MIRANDA ETHEL · 2020 to 2025
$2.0M
Investigating the role of transposable element dysregulation as a driver of neurotoxicity in tauopathyRF1NS112391 · NINDS · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FROST, BESS · 2019 to 2019
$1.9M
NIA NIH HHS P30 AG066546NIA NIH HHS R01 AG057896NIA NIH HHS R01 AG068293NIA NIH HHS RF1 AG063507NIA NIH HHS RF1 AG065301NIH-NIA R01AG057896, 1RF1AG063507, R01AG068293, 1R01AG0665241A,1R01AG065301, P30 AG066546NIH-NINDS RF1NS112391, U19NS115388NINDS NIH HHS RF1 NS112391NINDS NIH HHS U19 NS115388
6 · The paper itself

Abstract

Selective drugs with a relatively narrow spectrum can reduce the side effects of treatments compared to broad-spectrum antibiotics by specifically targeting the pathogens responsible for infection. Furthermore, combating an infectious pathogen, especially a drug-resistant microorganism, is more efficient by attacking multiple targets. Here, we combined synthetic lethality with selective drug targeting to identify multi-target and organism-specific potential drug candidates by systematically analyzing the genome-scale metabolic models of six different microorganisms. By considering microorganisms as targeted or conserved in groups ranging from one to six members, we designed 665 individual case studies. For each case, we identified single essential reactions as well as double, triple, and quadruple synthetic lethal reaction sets that are lethal for targeted microorganisms and neutral for conserved ones. As expected, the number of obtained solutions for each case depends on the genomic similarity between the studied microorganisms. Mapping the identified potential drug targets to their corresponding pathways highlighted the importance of key subsystems such as cell envelope biosynthesis, glycerophospholipid metabolism, membrane lipid metabolism, and the nucleotide salvage pathway. To assist in the validation and further investigation of our proposed potential drug targets, we introduced two sets of targets that can theoretically address a substantial portion of the 665 cases. We expect that the obtained solutions provide valuable insights into designing narrow-spectrum drugs that selectively cause system-wide damage only to the target microorganisms.

Indexed as

Anti-Bacterial AgentsBacteriaMetabolic Networks and PathwaysAnti-Bacterial AgentsGenome-scale metabolic modelNarrow-spectrum antibioticOrganism-specific drugSelective drug targetSynthetic lethalitySystems biology

Identifiers

PMID39014020
PMCPMC11252421

What Socratic holds

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LicenceCC BY
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 Socratic graph.