Integrating mixed microbial population dynamics into modeling energy transport during the initial stages of the aerobic composting of a switchgrass mixture

A mathematical model which integrates empirically derived microbial growth kinetics with heat and mass transfer phenomena and substrate degradation kinetics has been developed to capture the dynamics of the aerobic composting of a switchgrass and dog food mixture over a period of 64 h. The model incorporated three microbial populations of yeasts, bacteria and fungi that metabolized composting material consisting of sugars and starches, cellulose and hemicelluloses to produce heat and utilize oxygen in a static, cylindrical reactor employing forced aeration. Model predictions captured well the dynamics obtained experimentally between physical and microbial variables and the model has the potential to become a predictive tool for substrate degradation during aerobic composting processes.     

OpenABM-Covid19—An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing

SARS-CoV-2 has spread across the world, causing high mortality and unprecedented restrictions on social and economic activity. Policymakers are assessing how best to navigate through the ongoing epidemic, with computational models being used to predict the spread of infection and assess the impact of public health measures. Here, we present OpenABM-Covid19: an agent-based simulation of the epidemic including detailed age-stratification and realistic social networks. By default the model is parameterised to UK demographics and calibrated to the UK epidemic, however, it can easily be re-parameterised for other countries. OpenABM-Covid19 can evaluate non-pharmaceutical interventions, including both manual and digital contact tracing, and vaccination programmes. It can simulate a population of 1 million people in seconds per day, allowing parameter sweeps and formal statistical model-based inference. The code is open-source and has been developed by teams both inside and outside academia, with an emphasis on formal testing, documentation, modularity and transparency. A key feature of OpenABM-Covid19 are its Python and R interfaces, which has allowed scientists and policymakers to simulate dynamic packages of interventions and help compare options to suppress the COVID-19 epidemic.     

Exome sequencing of deer mice on two California Channel Islands identifies potential adaptation to strongly contrasting ecological conditions

Understanding the forces that drive genotypic and phenotypic change in wild populations is a central goal of evolutionary biology. We examined exome variation in populations of deer mice from two of the California Channel Islands: Peromyscus maniculatus elusus from Santa Barbara Island and P. m. santacruzae from Santa Cruz Island exhibit significant differences in olfactory predator recognition, activity timing, aggressive behavior, morphology, prevalence of Sin Nombre virus, and population densities. We characterized variation in protein‐coding regions using exome capture and sequencing of 25 mice from Santa Barbara Island and 22 mice from Santa Cruz Island. We identified and examined 386,256 SNPs using three complementary methods (BayeScan, pcadapt, and LFMM). We found strong differences in molecular variation between the two populations and 710 outlier SNPs in protein‐coding genes that were detected by all three methods. We identified 35 candidate genes from this outlier set that were related to differences in phenotypes between island populations. Enrichment analyses demonstrated that patterns of molecular variation were associated with biological processes related to response to chemical stimuli and regulation of immune processes. Candidate genes associated with olfaction (Gfy, Tlr2, Vmn13r2, numerous olfactory receptor genes), circadian activity (Cry1), anxiety (Brca1), immunity (Cd28, Eif2ak4, Il12a, Syne1), aggression (Cyp19a, Lama2), and body size (Bc16, Syne1) exhibited non‐synonymous mutations predicted to have moderate to large effects. Variation in olfaction‐related genes, including a stop codon in the Santa Barbara Island population, suggests loss of predator‐recognition traits at the molecular level, consistent with a lack of behavioral aversion to fox feces. These findings also suggest that divergent pathogen prevalence and population density may have influenced adaptive immunity and behavioral phenotypes, such as reduced aggression. Overall, our study indicates that ecological differences between islands are associated with signatures of selection in protein‐coding genes underlying phenotypes that promote success in those environments.