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Record W3002702197 · doi:10.3389/fmicb.2019.03132

Initial Transcriptomic Response and Adaption of Listeria monocytogenes to Desiccation on Food Grade Stainless Steel

2020· article· en· W3002702197 on OpenAlexfundno aff
Martin Laage Kragh, Lisbeth Truelstrup Hansen

Bibliographic record

VenueFrontiers in Microbiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsnot available
FundersUniversity of British ColumbiaDanmarks Tekniske Universitet
KeywordsDesiccationBiologyTranscriptomeListeria monocytogenesSuperoxide dismutaseGeneOxidative stressMicrobiologyFood scienceCatalaseStrain (injury)BiochemistryGene expressionBacteriaGeneticsBotany

Abstract

fetched live from OpenAlex

The foodborne pathogen Listeria monocytogenes survives exposure to a variety of stresses including desiccation in the food industry. Strand-specific RNA sequencing was applied to analyze changes in the transcriptomes of two strains of L. monocytogenes (Lm 568 and Lm 08-5578) during desiccation (15°C, 43% relative humidity) on food grade stainless steel surfaces over 48 h to simulate a weekend with no food production. Both strains showed similar survival during desiccation with a 1.8-2 Log CFU/cm2 reduction after 48 h. Analysis of differentially expressed (DE) genes (>2-fold, adjusted p-value < 0.05) revealed that the initial response to desiccation was established after 6 h and remained constant with few new genes being DE after 12, 24 and 48 h. A core of 81 up- and 73 down-regulated DE genes were identified as a shared, strain independent response to desiccation. Among common upregulated genes were energy and oxidative stress related genes e.g., qoxABCD (cytochrome aa3) pdhABC (pyruvate dehydrogenase complex) and mntABCH (manganese transporter). Common downregulated genes related to anaerobic growth, proteolysis and the two component systems lmo1172/lmo1173 and cheA/cheY, which are involved in cold growth and flagellin production, respectively. Both strains upregulated additional genes involved in combatting oxidative stress and reactive oxygen species (ROS), including sod (superoxide dismutase), kat (catalase), tpx (thiol peroxidase) and several thioredoxins including trxAB, lmo2390 and lmo2830. Osmotic stress related genes were also upregulated in both strains, including gbuABC (glycine betaine transporter) and several chaperones clpC, cspA and groE. Significant strain differences were also detected with the food outbreak strain Lm 08-5578 differentially expressing 1.9× more genes (726) compared to Lm 568 (410). Unique to Lm 08-5578 was a significant upregulation of the expression of the alternative transcription factor σB and its regulon. A number of long antisense transcripts (lasRNA) were upregulated during desiccation including anti0605, anti0936, anti1846 and anti0777, with the latter controlling flagellum biosynthesis and possibly the downregulation of motility genes observed in both strains. This exploration of the transcriptomes of desiccated L. monocytogenes provides further understanding of how this bacterium encounters and survives the stress faced when exposed to dry conditions in the food industry.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.071
GPT teacher head0.303
Teacher spread0.232 · 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".

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Citations34
Published2020
Admission routes1
Has abstractyes

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