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Record W4391886483 · doi:10.1093/jcag/gwad061.040

A40 THE ROLE OF HYPOXIA-INDUCIBLE FACTOR IN CELLULAR METABOLIC ADAPTATION UPON <i>GIARDIA</i> INFECTION

2024· article· en· W4391886483 on OpenAlexafffundabout
Emily DeMichele, Olivia Sosnowski, Thibault Allain, André G. Buret

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHypoxia (environmental)Adaptation (eye)GiardiaHypoxia-inducible factorsMicrobiologyBiologyImmunologyChemistryBiochemistryGeneNeuroscienceOxygen

Abstract

fetched live from OpenAlex

Abstract Background Recent findings have highlighted the integral role of oxygen tension in gastrointestinal (GI) homeostasis. During hypoxia when oxygen supply is limited, mammalian cells utilize the Hypoxia-Inducible Factor (HIF) complex to activate genes that promote cell survival and alter glucose metabolism. The GI system exists in a state of physiologic hypoxia, subject to further alterations by pathogens. Although tissue and blood parasites are known to influence tissue oxygen tension, little is known regarding the modulation of hypoxia and HIF by enteric parasites. Aims This project aims to characterize the effect of Giardia duodenalis, a common enteric protozoan that perturbs gastrointestinal function leading to diarrheal disease, on the cellular hypoxic response. We hypothesize that hypoxia-associated genes are activated upon Giardia infection, leading to an adaptive metabolic response with increased glycolytic flux to maintain cellular bioenergetic homeostasis. Methods Caco-2 colonic epithelial cells were infected with Giardia isolate GS/M (MOI 10) for 1.5 or 4.5 hours to capture early and peak HIF activation, under normoxic (21% O2) or hypoxic (1%O2, STEMCELL hypoxia incubator) conditions. RNA was extracted for RT-qPCR to assess transcriptional changes of known HIF-target genes. Intracellular metabolite analysis via liquid-chromatography mass-spectrometry (hydrophilic-interaction chromatography method) was performed to assess HIF-mediated metabolic changes in uninfected and Giardia-infected cells (MOI 10) exposed to the hypoxia mimetic DMOG or the HIF inhibitor PX-478. Results Under normoxic conditions, genes associated with compensatory cellular stress responses such as VEGFA, ANKRD37, GADD45A, and glycolysis-associated genes HK2, and LDHA are upregulated in Giardia-infected cells in a time-dependent manner (pampersand:003C0.05). Under hypoxic conditions, fewer HIF-target genes are upregulated (e.g., VEGFA, GADD45A, PGK1; pampersand:003C0.05), suggesting Giardia-infected cells behave similarly to uninfected cells with constant HIF activation. Analysis of the Caco-2 intracellular metabolome indicates HIF-dependent changes in amino acid (e.g., glycine, threonine) and nucleic acid (e.g., guanosine, inosine, uracil) metabolism. DMOG treatment altered the production of glycolytic intermediates (e.g., DHAP, PEP), confirming the promotion of glycolytic flux by HIF. Conclusions Both cell-stress-related and glucose-metabolism HIF target genes are activated upon Giardia infection. As well, some metabolic changes are dependent on HIF activation. These novel findings indicate Giardia promotes a hypoxic state in human intestinal cells, highlighting a metabolic cell rescue mechanism in response to enteropathogens. Furthermore, understanding the role of hypoxia in enteric parasitic infections will shed light on the potential of HIF as a therapeutic target. Funding Agencies Natural Sciences and Engineering Research Council of Canada (NSERC)

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 score0.001
Threshold uncertainty score0.005

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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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Same venueJournal of the Canadian Association of GastroenterologySame topicParasitic Infections and DiagnosticsFrench-language works237,207