Back

Temporal Structure of Environmental Noise Controls the Localization and Tracking of Populations of Chemotactic Microorganisms

Arencibia, G.; Gutierrez, M. E.; Panetsos, F.

2026-05-12 bioengineering
10.64898/2026.05.07.723364 bioRxiv
Show abstract

The ability of chemotactic populations to localize and track targets in fluctuating environments depends critically on the temporal structure of environmental signals. Using a minimal agent-based framework of non-interacting run-and-tumble cells implementing an E. coli-inspired temporal sensing strategy, populations are exposed to static and moving chemoattractant fields perturbed by noise with controlled temporal structure, spanning white, pink (1/f), and correlated Ornstein-Uhlenbeck processes. Chemotactic populations are found to act as temporal filters, robustly suppressing fast fluctuations while remaining highly sensitive to slowly varying perturbations. As a consequence, chemotactic performance is governed not by noise amplitude, but by its temporal correlations. By continuously varying the noise correlation time, a critical regime emerges at{tau} c [~]{tau} run, where aggregates lose stability, tracking errors increase sharply, and spatial dispersion rises. Power spectral analysis further shows that the low-frequency power fraction of the signal provides a strong predictor of failure, outperforming total signal variance and establishing a direct link between environmental noise spectra and collective behavior. Introducing external flow reveals that advective transport amplifies noise-induced destabilization when it overlaps the chemotactic capture region, defining a combined spatiotemporal constraint on robustness. Together, these results identify temporal correlations and spectral structure as fundamental control parameters for chemotactic organization and provide a quantitative framework for predicting and designing collective behavior in fluctuating environments.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Journal of The Royal Society Interface
189 papers in training set
Top 0.1%
28.0%
2
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 4%
12.5%
3
Nature Communications
4913 papers in training set
Top 22%
8.5%
4
Cell Systems
167 papers in training set
Top 2%
6.4%
50% of probability mass above
5
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 0.5%
6.4%
6
Advanced Science
249 papers in training set
Top 5%
3.6%
7
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 2%
3.6%
8
PLOS Computational Biology
1633 papers in training set
Top 9%
3.6%
9
Scientific Reports
3102 papers in training set
Top 47%
2.4%
10
Cell Reports
1338 papers in training set
Top 20%
2.1%
11
Science Advances
1098 papers in training set
Top 12%
2.1%
12
eLife
5422 papers in training set
Top 38%
1.9%
13
Royal Society Open Science
193 papers in training set
Top 4%
0.9%
14
Nano Letters
63 papers in training set
Top 2%
0.9%
15
Science
429 papers in training set
Top 19%
0.8%
16
Physical Review X
23 papers in training set
Top 0.6%
0.8%
17
Frontiers in Computational Neuroscience
53 papers in training set
Top 2%
0.7%
18
Physical Review Research
46 papers in training set
Top 1.0%
0.7%
19
iScience
1063 papers in training set
Top 36%
0.7%
20
ACS Synthetic Biology
256 papers in training set
Top 4%
0.5%
21
Evolutionary Applications
91 papers in training set
Top 2%
0.5%
22
PRX Life
34 papers in training set
Top 1%
0.5%
23
Bulletin of Mathematical Biology
84 papers in training set
Top 2%
0.5%