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Record W7062732622

Using Whole Genome Sequencing to Track Colibacillosis on Saskatchewan Broiler Flocks

2022· dissertation· en· W7062732622 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPlasmidEscherichia coliFlockVirulenceWhole genome sequencingPathogenic Escherichia coliNanopore sequencingOutbreak
DOInot available

Abstract

fetched live from OpenAlex

Colibacillosis is a systemic infection caused by Escherichia coli resulting in significant morbidity and mortality in broiler flocks worldwide. Little is known about the group of E. coli that cause colibacillosis, collectively termed avian pathogenic E. coli (APEC). My MSc research focused on determining how APEC differ from resident E. coli that live in the chicken gut but do not cause disease. I hypothesized that systemic and cecal E. coli are genetically distinct, and E. coli that cause colibacillosis are virulent outbreak strains. My objectives were to isolate E. coli from Saskatchewan broilers, sequence their genomes using Nanopore and Illumina technology, and screen them for virulence, antimicrobial resistance, and disinfectant resistance. I developed a pipeline to isolate and sequence E. coli from Saskatchewan colibacillosis outbreaks, selecting isolates based on outbreak, disease status, and biofilm profiles. I sequenced 96 E. coli isolates, consisting of 58 from diseased broilers with confirmed colibacillosis (systemic E. coli), and 38 from the cecal contents of healthy broilers in the same flocks (cecal E. coli). Our initial experiments were optimized for whole genome assembly and excluded DNA fragments under 500bp; therefore, we likely missed plasmids present in E. coli isolates. I tested six plasmid kits and two sequencing protocols to develop a methodology to capture missed plasmids in avian E. coli isolates and successfully identified new plasmids in both types of isolates. Systemic E. coli were more drug-resistant than cecal E. coli against a panel of 27 antimicrobial agents and possessed significantly more plasmids than cecal E. coli. plasmids contained multiple virulence and antimicrobial resistance genes that may contribute to disease. Since biofilms can provide protection from antibiotics and disinfectants, I quantified biofilm formation in three different medias. Systemic isolates were significantly more likely to form biofilms in rich media, but there was no correlation between biofilm formation and antimicrobial resistance. My characterization led us to conclude that systemic and cecal E. coli represent two different populations of strains. This will need to be confirmed with the analysis of more isolates. Characterization of avian pathogenic E. coli will help us understand how these isolates cause disease.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.189
Teacher spread0.177 · 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