Evidence map›Paper›PMID 42674639›Full record

ArticleEnvironmental science & technology2026

DURABLE: A Workflow for Determining Corrosion-Driving and Protective Microbial Mechanisms.

Aifen Zhou, Yuwen Li, Han Zhang, Evelyn Callaway, Song-I Han, Jason S Lee, Kyongbum Lee, Arul Jayaraman, Paul de Figueiredo, Arum Han

Abstract read
In one paragraph

Article in Environmental science & technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Aifen ZhouDepartment of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States.ORCID 0000-0003-3019-5649
Yuwen LiDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, Texas77843, United States.
Han ZhangDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, Texas77843, United States.
Evelyn CallawayDepartment of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States.
Song-I HanDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, Texas77843, United States.
Jason S LeeU.S. Naval Research Laboratory, Stennis Space Center, Stennis Space Center, MississippiMS39529, United States.
Kyongbum LeeDepartment of Chemical and Biological Engineering, Tufts University, Medford, Massachusetts02155, United States.
Arul JayaramanDepartment of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States.
Paul de FigueiredoChristopher S Bond Life Sciences Center, University of Missouri, Columbia, Missouri65211, United States.
Arum HanDepartment of Chemical Engineering, Texas A&M University, College Station, Texas77843, United States.ORCID 0000-0002-9223-8301

Funding

Defense Advanced Research Projects Agency HR00112320006
6 · The paper itself

Abstract

Microbiologically influenced corrosion (MIC) threatens global infrastructure, causing billions of dollars in annual losses. Its persistence stems from unresolved mechanisms─particularly the metabolites produced by microorganisms that drive or inhibit corrosion─and the microbial community structures. Progress has been hindered by the absence of systematic workflows to rapidly and accurately identify MIC-relevant microorganisms and their functions. Here, we present DURABLE (Detection of Unique Corrosion Resistant or Accelerating Biologics in a Laboratory Environment), a pipeline that couples high-throughput microbial screening with genomic and metabolic workflows. We applied the DURABLE workflow to six diesel tank samples and revealed fuel-dependent microbial community structures, which showed greater diversity and evenness in bacterial communities than their fungal counterparts. The workflow used carbon steel beads to rapidly screen over 80 bacterial isolates for corrosive activity, reducing assay time to approximately 2 days compared with the conventional 30-day metal coupon test. More than 40 isolates were identified as corrosive. Further testing using mass spectrometry analysis revealed corrosion-associated metabolites, which were further validated using electrochemical assays. Thus, DURABLE achieved a ∼15-fold increase in screening speed and provided a scalable and mechanistic framework for dissecting MIC dynamics. We expect this advance will enable the development of precision mitigation strategies in hydrocarbon fuel infrastructure.

Indexed as

CorrosionEnvironmental MicrobiologyBacteriaFungiSteelWorkflowSteelbacterial strain isolationcorrosion metabolites profilingfuel storage tankmicrobial community compositionmicrobiologically influenced corrosion (MIC)rapid carbon steel bead-based corrosion phenotype screening

Identifiers

PMID42674639
PMCPMC13523691

What Socratic holds

Textmetadata
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.