Evidence map›Paper›PMID 41410773›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

Emergent eukaryotic directional sensing via receptor degradation and diffusion.

Andrew Goetz, Purushottam Dixit

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 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.

Andrew GoetzDepartment of Biomedical Engineering, Yale University, New Haven, CT 06511.
Purushottam DixitDepartment of Biomedical Engineering, Yale University, New Haven, CT 06511.ORCID 0000-0003-3282-0866

Funding

MANET: Maximum Entropy Neural Networks for Mechanistic Modeling of Single Cell BehaviorR35GM142547 · NIGMS · YALE UNIVERSITY · PI DIXIT, PURUSHOTTAM · 2021 to 2025
$1.9M
HHS | NIH | National Institute of General Medical Sciences (NIGMS) R35GM142547NIGMS NIH HHS R35 GM142547
6 · The paper itself

Abstract

Directional sensing enables eukaryotic cells to detect spatial gradients of extracellular ligands, allowing them to orient and migrate within complex environments. Prevalent models explain this computation through a circuit where signaling species with distinct diffusion constants act incoherently on a downstream readout. Here, we propose a fundamentally different mechanism of directional sensing based on simple receptor-level processes. Our model integrates three ubiquitous receptor processes-lateral diffusion, basal ligand-independent activation, and active receptor degradation, THAT together synergize to generate robust directional sensing. In the absence of diffusion, active receptor degradation and basal activity implement an integral feedback that adapts active receptor levels to a ligand-independent set point while depleting receptors in relatively ligand-rich regions. Diffusion then redistributes receptors from regions of relatively low ligand exposure to regions with higher ligand exposure. This creates a spatial mismatch between activity and feedback that drives asymmetric receptor activity relative to the set point. The model predicts an optimal diffusion constant that maximizes polarization, reveals that receptors can encode relative rather than absolute ligand concentrations, and identifies the optimal basal activity that maximizes the signal-to-noise ratio in stochastic regimes. A survey of kinetic parameters across receptor families suggests that this diffusion-degradation synergy constitutes a broadly applicable, receptor-level mechanism for directional sensing.

Indexed as

Eukaryotic CellsModels, BiologicalReceptors, Cell SurfaceDiffusionLigandsProteolysisSignal TransductionLigandsReceptors, Cell Surfacedirectional sensingintegral feedbackreaction diffusion

Identifiers

PMID41410773
PMCPMC12745794

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.