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Record W6962019304 · doi:10.15454/5npyx6

Temporal transcriptome analysis of Bacillus subtilis NDmed in the submerged biofilm model

2021· dataset· en· W6962019304 on OpenAlexaff

Bibliographic record

VenueRecherche Data Gouv France · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsBacillus subtilisRNABiofilmGene expressionBacillaceaeStrain (injury)BacteriaTranscriptome

Abstract

fetched live from OpenAlex

Investigation of the kinetics of whole genome gene expression level changes in Bacillus subtilis NDmed strain during formation of submerged biofilm and pellicle. The Bacillus subtilis NDmed strain analyzed in this study is able to form thick and highly structurated submerged biofilms as described in Bridier et al., (2011) The Spatial Architecture of Bacillus subtilis Biofilms Deciphered Using a Surface-Associated Model and In Situ Imaging. PLoS ONE 6(1):e16177. A seven chip study using total RNA recovered from static cultures of Bacillus subtilis NDmed growing in TSB medium in 96-well microplates for different times after adhesion to the bottom of the wells. Each chip measures the expression level of 5,737 transcripts from Bacillus subtilis 168. 200 µL of an overnight culture of Bacillus subtilis NDmed in TSB (adjusted to an OD 600nm of 0.02) were added in each well of 96-well microtiter plates, incubated at 30°C for 90 min to allow the bacteria to adhere to the bottom of the wells. Wells were then rinsed with TSB to eliminate non-adherent bacteria and refilled with 200 µL of sterile TSB. For each time point (1h, 3h, 4h, 5h, 7h, 24h and 48h) 96-well plates were prepared. Total RNA was extracted as described by Nicolas et al., (2012) Science 335, 1103–1106 (PMID:22383849). RNA concentration was measured using a NanoDrop spectrophotometer; RNA quality was checked by analysis with an Agilent 2100 Bioanalyzer (Agilent Technologies). For cDNA synthesis, 10 µg of total RNA were mixed with random primers (FairPlay III Microarray Labeling Kit) and spike-ins (One-Color RNA Spike-In Kit, Agilent Technologies) and incubated at 70°C for 10 min followed by 5 min incubation on ice. Then, first-strand Master Mix, Actinomycin D (final conc. 40 µg/ml) and AffinityScript HC Reverse Transcriptase were added. The reaction was incubated for 60 min at room temperature and for 60 min at 42°C. After hydrolyzing the RNA, cDNA was precipitated overnight at -20°C. NHS-ester dye coupling (CyDye Mono-Reactive Dye, GE Healthcare) and purification of labeled cDNA were performed according to the FairPlay III instructions. cDNA and Cy-dye concentrations were quantified by means of a NanoDrop spectrophotometer. 1200 ng of Cy3-labeled cDNA were hybridized to the tiling array following Agilent’s hybridization, washing and scanning protocol (One-Color Microarray-based Gene Expression Analysis, version 5.5). The microarray (BaSysBio Bacillus subtilis T3 array, 2x400K [Agilent-044473]) was scanned with Agilent Technologies Scanner, model G2505C. Grid: 044473_D_F_20121025. Protocol: GE1_107_Sep09. An aggregated expression value was computed for each Genbank annotated CDS and newly defined transcribed region as the median log2 expression signal intensity of probes lying entirely within the corresponding region as described in (Nicolas et al., 2012 PMID: 22383849). The expression intensity was computed from the raw intensity data using a model of signal shift and drift and correcting for probe affinity variations as described in (Nicolas et al., 2009, Bioinformatics 25, 2341-2347). Data were quantile normalized using LIMMA package.To control for possible cross-hybridization artefacts the sequence of each probe was BLAST-aligned against the whole chromosome sequence and probes with a SeqS value above the 1.5 cut-off were discarded (Wei et al., 2008 Nucl. Acids Res. 36, 2926-2938).

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.323
GPT teacher head0.402
Teacher spread0.079 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueRecherche Data Gouv FranceFrench-language works237,207