Evidence map›Paper›PMID 40501803›Full record

ArticlebioRxiv : the preprint server for biology2025

Positioning of negative feedback loops within immune signaling pathways influences gene expression noise.

Danial Asgari, Ann T Tate

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Danial AsgariDepartment of Biological Sciences, Vanderbilt University, Nashville, Tennessee.ORCID 0000-0002-2987-0291
Ann T TateDepartment of Biological Sciences, Vanderbilt University, Nashville, Tennessee.ORCID 0000-0001-6601-0234

Funding

The influence of coevolutionary feedbacks on the origins and maintenance of genetic pleiotropyR35GM138007 · NIGMS · VANDERBILT UNIVERSITY · PI Ann Thomas Tate · 2020 to 2026
$2.8M
NIGMS NIH HHS R35 GM138007
6 · The paper itself

Abstract

Signaling pathways depend on negative and positive feedback loops (NFLs and PFLs) to regulate internal noise. Across diverse organisms, signaling is regulated by NFLs that function at different cellular locations. These range from NFLs functioning upstream near signal-receiving receptors to those downstream within the nucleus. While previous studies have examined the relationship between NFLs, internal noise in signaling pathways, and network topology, none have directly addressed how the cellular location of NFLs impacts noise regulation. This is significant given the almost ubiquitous presence of multi-level regulation systems within signaling pathways. Here, we use stochastic models inspired by Imd and Toll signaling to address this gap within the context of immune signaling. We use both mechanistic and evolutionary models to demonstrate how noise is regulated by NFLs and how this, in turn, affects the host's ability to fight off infection while minimizing immunopathologic effects of excessive immune gene expression. We found that downstream NFLs reduce noise in antimicrobial peptides (AMP) expression for some parameter values. On the other hand, upstream NFLs amplify the noise, but the presence of a strong PFL can reduce this noise. Our evolutionary simulations suggest that the mechanisms through which the downstream NFL operates within the cell can affect the evolution of the upstream NFLs. The results of our study provide insight into why distinct signaling pathways are regulated by varying numbers of NFLs, which operate in different cellular locations and employ diverse mechanisms to control gene expression.

Identifiers

PMID40501803
PMCPMC12157479

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.