A computational model of stereoscopic prey capture in praying mantises
We present a simple model which can account for the stereoscopic sensitivity of praying mantis predatory strikes. The model consists of a single “disparity sensor”: a binocular neuron sensitive to stereoscopic disparity and thus to distance from the animal. The model is based closely on the kn own behavioural and neurophysiological properties of mantis stereopsis. The monocular inputs to the neuron reflect temporal change and are insensitive to contrast sign, making the sensor insensitive to interocular correlation. The monocular receptive fields have a excitatory centre and inhibitory su rround, making them tuned to s...
Source: PLoS Computational Biology - May 19, 2022 Category: Biology Authors: James O ’Keeffe Source Type: research

LncRNAs of < i > Saccharomyces cerevisiae < /i > bypass the cell cycle arrest imposed by ethanol stress
by Lucas Cardoso L ázari, Ivan Rodrigo Wolf, Amanda Piveta Schnepper, Guilherme Targino Valente Ethanol alters many subsystems ofSaccharomyces cerevisiae, including the cell cycle. Two ethanol-responsive lncRNAs in yeast interact with cell cycle proteins, and here, we investigated the role of these RNAs in cell cycle. Our network dynamic modeling showed that higher and lower ethanol-tolerant strains undergo cell cycle arrest in mitosis and G1 phases, respectively, during ethanol stress. The higher population rebound of the lower ethanol-tolerant phenotype after stress relief responds to the late phase arrest. We found th...
Source: PLoS Computational Biology - May 19, 2022 Category: Biology Authors: Lucas Cardoso L ázari Source Type: research

Scalable and flexible inference framework for stochastic dynamic single-cell models
by Sebastian Persson, Niek Welkenhuysen, Sviatlana Shashkova, Samuel Wiqvist, Patrick Reith, Gregor W. Schmidt, Umberto Picchini, Marija Cvijovic Understanding the inherited nature of how biological processes dynamically change over time and exhibit intra- and inter-individual variability, due to the different responses to environmental stimuli and when interacting with other processes, has been a major focus of systems biology. The rise of single-cell fluorescent microscopy has enabled the study of those phenomena. The analysis of single-cell data with mechanistic models offers an invaluable tool to describe dynamic cell...
Source: PLoS Computational Biology - May 19, 2022 Category: Biology Authors: Sebastian Persson Source Type: research

Enhancing long-term forecasting: Learning from COVID-19 models
by Hazhir Rahmandad, Ran Xu, Navid Ghaffarzadegan While much effort has gone into building predictive models of the COVID-19 pandemic, some have argued that early exponential growth combined with the stochastic nature of epidemics make the long-term prediction of contagion trajectories impossible. We conduct two complementary studies to assess mo del features supporting better long-term predictions. First, we leverage the diverse models contributing to the CDC repository of COVID-19 USA death projections to identify factors associated with prediction accuracy across different projection horizons. We find that better long-...
Source: PLoS Computational Biology - May 19, 2022 Category: Biology Authors: Hazhir Rahmandad Source Type: research

CystiHuman: A model of human neurocysticercosis
by Gabrielle Bonnet, Francesco Pizzitutti, Eloy A. Gonzales-Gustavson, Sarah Gabri ël, William K. Pan, Hector H. Garcia, Javier A. Bustos, Percy Vilchez, Seth E. O’Neal, for the Cysticercosis Working Group in Peru IntroductionTheTaenia solium tapeworm is responsible for cysticercosis, a neglected tropical disease presenting as larvae in the body of a host following taenia egg ingestion. Neurocysticercosis (NCC), the name of the disease when it affects the human central nervous system, is a major cause of epilepsy in developing countries, and can also cause intracranial hypertension, hydrocephalus and death. Simulation m...
Source: PLoS Computational Biology - May 19, 2022 Category: Biology Authors: Gabrielle Bonnet Source Type: research

Linear viscoelastic properties of the vertex model for epithelial tissues
by Sijie Tong, Navreeta K. Singh, Rastko Sknepnek, Andrej Ko šmrlj Epithelial tissues act as barriers and, therefore, must repair themselves, respond to environmental changes and grow without compromising their integrity. Consequently, they exhibit complex viscoelastic rheological behavior where constituent cells actively tune their mechanical properties to chang e the overall response of the tissue, e.g., from solid-like to fluid-like. Mesoscopic mechanical properties of epithelia are commonly modeled with the vertex model. While previous studies have predominantly focused on the rheological properties of the vertex mod...
Source: PLoS Computational Biology - May 19, 2022 Category: Biology Authors: Sijie Tong Source Type: research

Phase-locking patterns underlying effective communication in exact firing rate models of neural networks
by David Reyner-Parra, Gemma Huguet Macroscopic oscillations in the brain have been observed to be involved in many cognitive tasks but their role is not completely understood. One of the suggested functions of the oscillations is to dynamically modulate communication between neural circuits. The Communication Through Coherence (CTC ) theory proposes that oscillations reflect rhythmic changes in excitability of the neuronal populations. Thus, populations need to be properly phase-locked so that input volleys arrive at the peaks of excitability of the receiving population to communicate effectively. Here, we present a mode...
Source: PLoS Computational Biology - May 18, 2022 Category: Biology Authors: David Reyner-Parra Source Type: research

Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
by Thomas E. Valles, Hannah Shoenhard, Joseph Zinski, Sarah Trick, Mason A. Porter, Michael R. Lindstrom A major strategy to prevent the spread of COVID-19 is the limiting of in-person contacts. However, limiting contacts is impractical or impossible for the many disabled people who do not live in care facilities but still require caregivers to assist them with activities of daily living. We seek to determine which interventions can best prevent infections of disabled people and their caregivers. To accomplish this, we simulate COVID-19 transmission with a compartmental model that includes susceptible, exposed, asymptomat...
Source: PLoS Computational Biology - May 18, 2022 Category: Biology Authors: Thomas E. Valles Source Type: research

Anomalous diffusion and asymmetric tempering memory in neutrophil chemotaxis
by Peter Dieterich, Otto Lindemann, Mats Leif Moskopp, Sebastien Tauzin, Anna Huttenlocher, Rainer Klages, Aleksei Chechkin, Albrecht Schwab The motility of neutrophils and their ability to sense and to react to chemoattractants in their environment are of central importance for the innate immunity. Neutrophils are guided towards sites of inflammation following the activation of G-protein coupled chemoattractant receptors such as CXCR2 whose signaling strongly depends on the activity of Ca2+ permeable TRPC6 channels. It is the aim of this study to analyze data sets obtained in vitro (murine neutrophils) and in vivo (zebra...
Source: PLoS Computational Biology - May 18, 2022 Category: Biology Authors: Peter Dieterich Source Type: research

Negative feedback may suppress variation to improve collective foraging performance
by Andreagiovanni Reina, James A. R. Marshall Social insect colonies use negative as well as positive feedback signals to regulate foraging behaviour. In ants and bees individual foragers have been observed to use negative pheromones or mechano-auditory signals to indicate that forage sources are not ideal, for example being unrewarded, crowd ed, or dangerous. Here we propose an additional function for negative feedback signals during foraging, variance reduction. We show that while on average populations will converge to desired distributions over forage patches both with and without negative feedback signals, in small p...
Source: PLoS Computational Biology - May 18, 2022 Category: Biology Authors: Andreagiovanni Reina Source Type: research

CBEA: Competitive balances for taxonomic enrichment analysis
by Quang P. Nguyen, Anne G. Hoen, H. Robert Frost Research in human-associated microbiomes often involves the analysis of taxonomic count tables generated via high-throughput sequencing. It is difficult to apply statistical tools as the data is high-dimensional, sparse, and compositional. An approachable way to alleviate high-dimensionality and s parsity is to aggregate variables into pre-defined sets. Set-based analysis is ubiquitous in the genomics literature and has demonstrable impact on improving interpretability and power of downstream analysis. Unfortunately, there is a lack of sophisticated set-based analysis meth...
Source: PLoS Computational Biology - May 18, 2022 Category: Biology Authors: Quang P. Nguyen Source Type: research

Spatially resolved in silico modeling of NKG2D signaling kinetics suggests a key role of NKG2D and Vav1 Co-clustering in generating natural killer cell activation
by Rajdeep Kaur Grewal, Jayajit Das Natural Killer (NK) cells provide key resistance against viral infections and tumors. A diverse set of activating and inhibitory NK cell receptors (NKRs) interact with cognate ligands presented by target host cells, where integration of dueling signals initiated by the ligand-NKR interactions dete rmines NK cell activation or tolerance. Imaging experiments over decades have shown micron and sub-micron scale spatial clustering of activating and inhibitory NKRs. The mechanistic roles of these clusters in affecting downstream signaling and activation are often unclear. To this end, we deve...
Source: PLoS Computational Biology - May 18, 2022 Category: Biology Authors: Rajdeep Kaur Grewal Source Type: research

Evolution of tunnels in α/β-hydrolase fold proteins—What can we learn from studying epoxide hydrolases?
by Maria Bz ówka, Karolina Mitusińska, Agata Raczyńska, Tomasz Skalski, Aleksandra Samol, Weronika Bagrowska, Tomasz Magdziarz, Artur Góra The evolutionary variability of a protein’s residues is highly dependent on protein region and function. Solvent-exposed residues, excluding those at interaction interfaces, are more variable than buried residues whereas active site residues are considered to be conserved. The abovementioned rul es apply also to α/β-hydrolase fold proteins—one of the oldest and the biggest superfamily of enzymes with buried active sites equipped with tunnels linking the reaction site with the...
Source: PLoS Computational Biology - May 17, 2022 Category: Biology Authors: Maria Bz ówka Source Type: research

Predicting knee adduction moment response to gait retraining with minimal clinical data
We present a regression model that uses minimal clinical data—a set of six features easily obtain ed in the clinic—to predict the extent of first peak KAM reduction after toe-in gait retraining. For such a model to generalize, the training data must be large and variable. Given the lack of large public datasets that contain different gaits for the same patient, we generated this dataset synthe tically. Insights learned from a ground-truth dataset with both baseline and toe-in gait trials (N = 12) enabled the creation of a large (N = 138) synthetic dataset for training the predictive model. On a test set of data collect...
Source: PLoS Computational Biology - May 16, 2022 Category: Biology Authors: Nataliya Rokhmanova Source Type: research

Annotating functional effects of non-coding variants in neuropsychiatric cell types by deep transfer learning
by Boqiao Lai, Sheng Qian, Hanwei Zhang, Siwei Zhang, Alena Kozlova, Junbao Duan, Jinbo Xu, Xin He Genomewide association studies (GWAS) have identified a large number of loci associated with neuropsychiatric traits, however, understanding the molecular mechanisms underlying these loci remains difficult. To help prioritize causal variants and interpret their functions, computational methods hav e been developed to predict regulatory effects of non-coding variants. An emerging approach to variant annotation is deep learning models that predict regulatory functions from DNA sequences alone. While such models have been train...
Source: PLoS Computational Biology - May 16, 2022 Category: Biology Authors: Boqiao Lai Source Type: research