Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.10.24.684462

Scaling laws in biological thermal performances

Arroyo, J. I.·Lopez, A.·Maass, A.·Gershenson, C.·Marquet, P.·West, G.·Kempes, C. P.
View original source ↗Export metadata ↓

Abstract

Understanding the extent to which genetic correlations change in response to environmental factors, such as temperature, is a poorly explored question, despite the importance of understanding how different processes will change with climate warming. Despite correlations between thermal performance traits having been reported in the literature for a few taxa and performance tasks, such as population growth rate, a comprehensive global analysis of the entire tree of life and multiple performance tasks remains an open challenge. To advance in this open question, we compile a database of 1,300 thermal response curves, encompassing 38 variable types related to individuals performance (including per capita population growth rate, photosynthetic rate, among others) and 1,125 different species, ranging from viruses to mammals, encompassing all major lineages of the tree of life. Our analysis reveals that among all possible relationships between traits and optimal performance, four traits form a line with a high goodness-of-fit, while the remaining traits exhibit a polygonal pattern, either a triangle or a tetrahedron. We derive a thermodynamic framework that explains the relationships described by a curve or line (as opposed to a surface or polygon), highlighting the linear relationship between maximum and minimum temperatures, as well as between maximum and optimum temperatures. We also discuss other generic trait evolution models, which could account for the other significant sublinear relationships, as well as the more general model, Pareto optimality theory, which could account for relationships in the form of lines or polygons. Our theoretical framework and empirical evidence suggest that, based on a single data point (e.g., minimum temperature), all critical temperature limits and maximum performance boundaries can be predicted using the estimated parameter from this study. Our results reveal universal scaling relationships in thermal performance, which could be useful for predicting changes in performance under scenarios of climate warming.

Explore related subjects

biophysicsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Arroyo, J. I., Lopez, A., Maass, A., Gershenson, C., Marquet, P., West, G., Kempes, C. P.. 2025-10-25. Scaling laws in biological thermal performances. https://doi.org/10.1101/2025.10.24.684462

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Cancers relax selection on charge at the mitochondrial complex I quinone cavity

Mitochondrial complex I translocates protons through hydrated channels whose connectivity and electrostatics are both defined by structure, but whether they are distinctly constrained is unknown. From a 2.39 cryo-EM structure modelling 2,945 ordered waters, we built the proton wire of the seven mtDNA-encoded ND subunits and scored all 40,166 missense substitutions on two near-orthogonal axes (r = 0.17): electrostatic shift at proton-loading sites, and topological disruption of the wire. Across 858 germline variant sites, loading sites (0.51) and cut vertices (0.67) are both depleted. In tumours only loading sites are enriched (1.42 TCGA, 1.67 PCAWG, 1.29 MSK-IMPACT), a 3.06-fold difference tested as a wire class tissue-type interaction (P = 3.6 10-). It survives adjustment for conservation, burial and coverage, and is concentrated in ND1 within 15 of the quinone cavity, not spread along the proton path. Selection separates charge from connectivity, without establishing a fitness benefit.

biophysics↗
bioRxiv2026

Rugnux: from diffraction images to structure at synchrotrons and XFELs in one program

Rising data rates in macromolecular crystallography outpace multi-program pipelines on computing clusters. Rugnux, a single GPU-accelerated program, turns rotation or serial still diffraction images into merged data and an initial structure. At synchrotrons, results arrive seconds after the last image; on one workstation, 207 public datasets from 36 sources took a median of 15 s each, with deposition-quality. Serial XFEL data were processed faster than the collection rate, enabling real-time structure determination.

biophysics↗
bioRxiv2026

Phase Separation of Intracellular Proteins Influences Synaptic Bistability

Synaptic bistability at the post synaptic density has been proposed to be the result of the nucleation and evaporation of receptor clusters. The exact biophysical mechanism underlying these inter-receptor attractions that can trigger nucleation remains to be elucidated. Emerging evidence demonstrates that numerous postsynaptic density submembrane proteins, that interact with various membrane receptors, can undergo phase separation, necessitating a revised conceptual model. By employing Langevin dynamics simulations of coarse-grained scaffold proteins and interacting membrane receptors, we study how phase transitions of scaffold proteins alter receptor clustering at the membrane. In our model, scaffold macromolecules can undergo phase separation and interact with receptor molecules at the model membranes. We observed that the presence of scaffold polymers across the membrane creates an attractive interaction between otherwise purely repulsive receptors. By systematically varying the number of receptors at the membrane, we dissected the coupling between receptor clustering and the phase behavior of scaffold macromolecules. We show that the propensity for receptor clustering is enhanced by the condensation of scaffold proteins. We then used two different scaffolds and systematically varied the interaction between them, to change the spatial organization of two condensed phases w.r.t. one another. Interestingly, we observed that receptor clustering can be reduced by co-phase separation of scaffold macromolecules, indicating the role of competing interactions in receptor clustering. Our work advances understanding of receptor-mediated signaling and phase separation, providing insights into cellular compartmentalization and biochemical regulation at the synapse.

biophysics↗