MétaCan
Menu
← Back to cohort
Record W4311298283 · doi:10.1101/2022.12.02.518811

Identification of a forkhead box protein transcriptional network induced in human neutrophils in response to inflammatory stimuli

2022· preprint· en· W4311298283 on OpenAlexafffund
Aiten Ismailova, Reyhaneh Salehi-Tabar, V. Dimitrov, Babak Memari, Camille Barbier, John H. White

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldImmunology and Microbiology
TopicNeutrophil, Myeloperoxidase and Oxidative Mechanisms
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsChromatin immunoprecipitationTranscription factorInflammationBiologyTransactivationImmunologyProinflammatory cytokineLipopolysaccharideChromatinTranscription (linguistics)GenePromoterCell biologyGene expressionGenetics

Abstract

fetched live from OpenAlex

Abstract Neutrophils represent the largest proportion of circulating leukocytes and, in response to inflammatory stimuli, are rapidly recruited to sites of infection where they neutralize pathogens. We have identified a novel neutrophil transcription network induced in response to inflammatory stimuli. We performed the first RNAseq analysis of human neutrophils exposed to lipopolysaccharide (LPS), followed by a meta-analysis of our dataset and previously published studies of LPS-challenged neutrophils. This revealed a robustly enhanced transcriptional network driven by forkhead box (FOX) transcription factors. The network is enriched in genes encoding proinflammatory cytokines and transcription factors, including MAFF and ATF3 , which are implicated in responses to stress, survival and inflammation. Expression of transcription factors FOXP1 and FOXP4 is induced in neutrophils exposed to inflammatory stimuli, and potential FOXP1/FOXP4 binding sites were identified in several genes in the network, all located in chromatin regions consistent with neutrophil enhancer function. Chromatin immunoprecipitation (ChIP) assays in neutrophils confirmed enhanced binding of FOXP4, but not FOXP1, to multiple sites in response to LPS. Binding to numerous motifs and transactivation of network genes were also observed when FOXP proteins were transiently expressed in HEK293 cells. In addition to LPS, the transcriptional network is induced by other inflammatory stimuli, indicating it represents a general neutrophil response to inflammation. Collectively, these findings reveal a role for the FOXP4 transcription network as a regulator of responses to inflammatory stimuli in neutrophils. Author Summary In response to pathogens, neutrophils, the most abundant white blood cells in the body, are the first to be recruited to sites of infection. However, defects in neutrophil responses lead to common chronic inflammatory conditions such as atherosclerosis, chronic obstructive lung disease and autoimmune disorders. As such, it is critical to uncover the molecular players implicated in neutrophil responses to signals that induce inflammation. Here we profile how bacterial lipopolysaccharide (LPS), which is derived from the cell walls of bacteria and is a commonly used agent to mimic inflammation, alters gene transcription in isolated human neutrophils. We also combined our data with those of other published studies to identify conserved molecular pathways stimulated in LPS-exposed neutrophils. This analysis revealed a network of genes whose transcription is regulated by members of the so-called forkhead box (FOX) transcription factors. We provide evidence that FOXP4 regulates transcription of genes within the network in neutrophils. We also find that the same network of genes is induced by other inflammatory stimuli, suggesting it plays a role in neutrophil responses to inflammation.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.248
Teacher spread0.227 · 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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicNeutrophil, Myeloperoxidase and Oxidative Mechanisms→French-language works237,207→