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Record W4400457721 · doi:10.1128/msphere.00476-24

Autoclaving is at least as effective as gamma irradiation for biotic clearing and intentional microbial recolonization of soil

2024· article· en· W4400457721 on OpenAlexaff
William L. King, Emily Grandinette, Olivia Trase, M. Laura Rolon, Howard M. Salis, Terrence H. Bell

Bibliographic record

VenuemSphere · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersU.S. Department of AgricultureAdvanced Research Projects AgencyDefense Advanced Research Projects AgencyU.S. Department of Defense
KeywordsSterilization (economics)MicrocosmSoil waterGamma irradiationEnvironmental scienceBiologyAgronomyIrradiationEcologySoil science

Abstract

fetched live from OpenAlex

ABSTRACT Sterilization is commonly used to remove or reduce the biotic constraints of a soil to allow recolonization by soil-dwelling organisms, with autoclaving and gamma irradiation being the most frequently used approaches. Many studies have characterized sterilization impacts on soil physicochemical properties, with gamma irradiation often described as the preferred approach, despite the lower cost and higher scalability of autoclaving. However, few studies have compared how sterilization techniques impact soil recolonization by microorganisms. Here, we compared how two sterilization approaches (autoclaving; gamma irradiation) and soil washing impacted microbial recolonization of soil from a diverse soil inoculum. Sterilization method had little impact on microbial alpha diversity across recolonized soils. For sterile soil regrowth microcosms, species richness and diversity were significantly reduced by autoclaving relative to gamma irradiation, particularly for fungi. There was no impact of sterilization method on bacterial composition in recolonized soils and minimal impact on fungal composition ( P = 0.05). Washing soils had a greater impact on microbial composition than sterilization method, and sterile soil regrowth had negligible impacts on microbial recolonization. These data suggest that sterilization method has no clear impact on microbial recolonization, at least across the soils tested, indicating that soil autoclaving is an appropriate and economical approach for biotically clearing soils. IMPORTANCE Sterilized soils represent soil-like environments that act as a medium to study microbial colonization dynamics in more “natural” settings relative to artificial culturing environments. Soil sterilization is often carried out by gamma irradiation or autoclaving, which both alter soil properties, but gamma irradiation is thought to be the gentler technique. Gamma irradiation can be cost prohibitive and does not scale well for larger experiments. We sought to examine how soil sterilization technique can impact microbial colonization, and additionally looked at the impact of soil washing which is believed to remove soil toxins that inhibit soil recolonization. We found that both gamma-irradiated and autoclaved soils showed similar colonization patterns when reintroducing microorganisms. Soil washing, relative to sterilization technique, had a greater impact on which microorganisms were able to recolonize the soil. When allowing sterilized soils to regrow (i.e., persisting microorganisms), gamma irradiation performed worse, suggesting that gamma irradiation does not biotically clear soils as well as autoclaving. These data suggest that both sterilization techniques are comparable, and that autoclaving may be more effective at biotically clearing soil.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.300
Teacher spread0.281 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2024
Admission routes1
Has abstractyes

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