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Peris-Yague, V.

Publications and source records attributed to Peris-Yague, V..

3 recordsLinked to original sources

Least Component Analysis reveals ecological constraints in microbial communities

How microbial communities maintain robust and reproducible ecological functions despite their extraordinary taxonomic diversity remains an open question. Here we show that functional organization in microbial communities can be uncovered by repurposing Principal Component Analysis to focus on directions of lowest variance in taxon abundance data, rather than maximal variance. These least-variance components are statistically significant and correspond to ecological constraints on taxon abundances that are consistently fulfilled across samples. Using consumer-resource models, we show that these constraints arise from resource-mediated interactions and express biomass conservation, effectively grouping taxa into producer and consumer guilds. We validate this interpretation in simulated communities and experimental systems under competition and cross-feeding. Finally, we show that low-variance structure is ubiquitous in natural microbial communities and reveals a sparse network of taxa with disproportionate influence on community structure. Together, our results establish low-variance components as indicators of ecological constraints linking taxonomic diversity to functional organization.

ecology↗

Barrier-Free Microhabitats: Self-Organized Seclusion in Microbial Communities

Bacteria frequently colonize natural microcavities such as gut crypts, plant apoplasts, and soil pores. Recent studies have shown that the physical structure of these spaces plays a crucial role in shaping the stability and resilience of microbial populations (1, 2). Here, we demonstrate that protected microhabitats can emerge dynamically, even in the absence of physical barriers. Interactions with surface features--such as roughness or friction--lead microbial populations to self-organize into effectively segregated subpopulations. Our numerical and analytical models reveal that this self-organization persists even when strains have different growth rates, allowing slower-growing strains to avoid competitive exclusion. These findings suggest that emergent spatial structuring can serve as a fundamental mechanism for maintaining microbial diversity, despite selection pressures, competition, and genetic drift.

biophysics↗

A mathematical model for electrical activity in pig atrial tissue

Atrial fibrillation (AF) is the most common sustained form of cardiac arrhythmia occurring in humans. Its effective treatment requires a detailed understanding of the underlying mechanisms at the genetic, molecular, cellular, tissue and organ levels. To study the complex mechanisms underlying the development, maintenance and termination of cardiac arrhythmias, we need preclinical research models. These models range from in vitro cell cultures to in vivo small and large animal hearts. However, translational research requires that the results of these animal experiments are understood in the context of human subjects. Currently, this is achieved through simulations with state-of-the-art mathematical models for human and animal heart tissue. In the context of AF, a model that is extensively used by experimentalists, is that of the pig atria. However, until now, an ionically detailed mathematical model for pig atrial tissue has been lacking, and researchers have been forced to rely on mathematical models from other animal species to understand their experimental observations. In this paper, we present the first ionically detailed mathematical model of porcine atrial electrophysiology. To build the model, we first fitted experimental patch-clamp data from literature to describe the individual currents flowing across the cell membrane. Later, we fine-tuned the model by fitting action potential duration restitution (APDR) curves for different repolarisation levels. The experimental data for the APDR studies was produced in N. Voigts lab. We extended our model to the tissue level and demonstrated the ability to maintain stable spiral waves. In agreement with previous experimental results, our model shows that early repolarisation is primarily driven by a calcium-mediated chloride current, IClCa, which is completely inactivated at high pacing frequencies. This is a condition found only in porcine atria. The model shows spatiotemporal chaos with reduced repolarisation. Author summaryState-of-the-art mathematical models of cardiac electrophysiology play an important role in bridging the gap between animal research conducted in the laboratory and preclinical research being considered for translation into the clinic. Using computer simulations, these models enable detailed studies of the behaviour of ion channels and ion transfer at the cellular level, the propagation of electrical waves at the tissue level and the visualisation of the excitation pattern within the heart wall at the organ level. Thus, they contribute to a better understanding of the mechanisms underlying cardiac arrhythmias. Here, we present the first ionically detailed mathematical model for porcine atrial electrophysiology. The individual membrane currents were modelled by fitting experimental data obtained from literature. The overall electrical response of the tissue was adjusted by fitting action potential duration restitution (APDR) curves obtained from in-house patch-clamp measurements. Our model accounts for an early repolarisation phase of the AP that is primarily Ca2+-dependent, a feature that is consistent with experiments and is identified to be unique to pigs. In extended media, our model is capable of sustaining stable spiral waves, and spatiotemporal chaos, when the repolarisation reserve is reduced.

biophysics↗