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Record W2408121873 · doi:10.3389/fmicb.2016.00767

In Situ Microbial Community Succession on Mild Steel in Estuarine and Marine Environments: Exploring the Role of Iron-Oxidizing Bacteria

2016· article· en· W2408121873 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Microbiology · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of Saskatchewan
FundersDivision of Materials ResearchOffice of Naval ResearchState of Maine Department of Marine Resources
KeywordsArchaeaMicrobial population biologyBacteriaBiologyBiogeochemical cycleBrackish waterBayBiofilmIron bacteriaSedimentEstuaryEcologyEnvironmental chemistryChemistryOceanographySalinityGeology

Abstract

fetched live from OpenAlex

Microbiologically influenced corrosion (MIC) is a complex biogeochemical process involving interactions between microbes, metals, minerals, and their environment. We hypothesized that sediment-derived iron-oxidizing bacteria (FeOB) would colonize and become numerically abundant on steel surfaces incubated in coastal marine environments. To test this, steel coupons were incubated on sediments over 40 days, and samples were taken at regular intervals to examine microbial community succession. The experiments were conducted at two locations: (1) a brackish salt marsh stream and (2) a coastal marine bay. We analyzed DNA extracted from the MIC biofilms for bacterial diversity using high-throughput amplicon sequencing of the SSU rRNA gene, and two coupons from the coastal site were single cell sorted and screened for the SSU rRNA gene. We quantified communities of Zetaproteobacteria, sulfate-reducing bacteria (SRB), and total bacteria and archaea using qPCR analyses. Zetaproteobacteria and SRB were identified in the sequencing data and qPCR analyses for samples collected throughout the incubations and were also present in adjacent sediments. At the brackish site, the diversity of Zetaproteobacteria was lower on the steel compared to sediments, consistent with the expected enrichment of FeOB on steel. Their numbers increased rapidly over the first 10 days. At the marine site, Zetaproteobacteria and other known FeOB were not detected in sediments; however, the numbers of Zetaproteobacteria increased dramatically within 10 days on the steel surface, although their diversity was nearly clonal. Iron oxyhydroxide stalk biosignatures were observed on the steel and in earlier enrichment culture studies; this is evidence that the Zetaproteobacteria identified in the qPCR, pyrosequencing, and single cell data were likely FeOB. In the brackish environment, members of freshwater FeOB were also present, but were absent in the fully marine site. This work indicates there is a successional pattern in the colonization of steel surfaces with FeOB being early colonizers; over time the MIC community matures to include other members that may help accelerate corrosion. This work also shows there is a reservoir for Zetaproteobacteria in coastal sediment habitats, where they may influence the coastal iron cycle, and can rapidly colonize steel surfaces or other sources of Fe(II) when available.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.222
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it