Metabolic activity affects response of single cells to a nutrient switch in structured populations, bioRxiv, 2019-03-18
AbstractMicrobes live in ever-changing environments where they need to adapt their metabolism to different nutrient conditions. Many studies have characterized the response of genetically identical cells to nutrient switches in homogenous cultures, however in nature microbes often live in spatially structured groups such as biofilms where cells can create metabolic gradients by consuming and releasing nutrients. Consequently, cells experience different local microenvironments and vary in their phenotype. How does this phenotypic variation affect the ability of cells to cope with nutrient switches? Here we address this question by growing dense populations of Escherichia coli in microfluidic chambers and studying a switch from glucose to acetate at the single cell level. Before the switch, cells vary in their metabolic activity some grow on glucose while others cross-feed on acetate. After the switch, only few cells can resume growth after a period of lag. The probability to resume growth depends on a cells’ phenotype prior to the switch it is highest for cells crossfeeding on acetate, while it depends in a non-monotonic way on growth rate for cells growing on glucose. Our results suggest that the strong phenotypic variation in spatially structured populations might enhance their ability to cope with fluctuating environments.
biorxiv systems-biology 100-200-users 2019Dosing Time Matters, bioRxiv, 2019-03-16
AbstractTrainees in medicine are taught to diagnose and administer treatment as needed; time-of-day is rarely considered. Yet accumulating evidence shows that ∼half of human genes and physiologic functions follow daily rhythms. Circadian medicine aims to incorporate knowledge of these rhythms to enhance diagnosis and treatment. Interest in this approach goes back at least six decades, but the path to the clinic has been marked by starts, stops, and ambiguity. How do we move the field forward to impact clinical practice? To gain insight into successful strategies, we studied the results of more than 100 human trials that evaluated time-of-administration of drugs.
biorxiv epidemiology 100-200-users 2019Evolutionary dynamics in structured populations under strong population genetic forces, bioRxiv, 2019-03-16
High rates of migration between subpopulations result in little population differentiation in the long-term neutral equilibrium. However, in the short-term, even very abundant migration may not be enough for subpopulations to equilibrate immediately. In this study, we investigate dynamical patterns of short-term population differentiation in adapting populations via stochastic and analytical modeling through time. We characterize a regime in which selection and migration interact to create non-monotonic patterns of the population differentiation statistic FST when migration is weaker than selection, but stronger than drift. We demonstrate how these patterns can be leveraged to estimate high migration rates that would lead to panmixia in the long term equilibrium using an approximate Bayesian computation approach. We apply this approach to estimate fast migration in a rapidly adapting intra-host Simian-HIV population sampled from different anatomical locations. Notably, we find differences in estimated migration rates between different compartments, all above Nem = 1. This work demonstrates how studying demographic processes on the timescale of selective sweeps illuminates processes too fast to leave signatures on neutral timescales.
biorxiv evolutionary-biology 100-200-users 2019Population histories of the United States revealed through fine-scale migration and haplotype analysis, bioRxiv, 2019-03-14
AbstractThe population of the United States is shaped by centuries of migration, isolation, growth, and admixture between ancestors of global origins. Here, we assemble a comprehensive view of recent population history by studying the ancestry and population structure of over 32,000 individuals in the US using genetic, ancestral birth origin, and geographic data from the National Geographic Genographic Project. We identify migration routes and barriers that reflect historical demographic events. We also uncover the spatial patterns of relatedness in subpopulations through the combination of haplotype clustering, ancestral birth origin analysis, and local ancestry inference. These patterns include substantial substructure and heterogeneity in HispanicsLatinos, isolation-by-distance in African Americans, elevated levels of relatedness and homozygosity in Asian immigrants, and fine-scale structure in European descents. Taken together, our results provide detailed insights into the genetic structure and demographic history of the diverse US population.
biorxiv genetics 100-200-users 2019ARMOR an Automated Reproducible MOdular workflow for preprocessing and differential analysis of RNA-seq data, bioRxiv, 2019-03-13
AbstractThe extensive generation of RNA sequencing (RNA-seq) data in the last decade has resulted in a myriad of specialized software for its analysis. Each software module typically targets a specific step within the analysis pipeline, making it necessary to join several of them to get a single cohesive workflow. Multiple software programs automating this procedure have been proposed, but often lack modularity, transparency or flexibility. We present ARMOR, which performs an end-to-end RNA-seq data analysis, from raw read files, via quality checks, alignment and quantification, to differential expression testing, geneset analysis and browser-based exploration of the data. ARMOR is implemented using the Snakemake workflow management system and leverages conda environments; Bioconductor objects are generated to facilitate downstream analysis, ensuring seamless integration with many R packages. The workflow is easily implemented by cloning the GitHub repository, replacing the supplied input and reference files and editing a configuration file. Although we have selected the tools currently included in ARMOR, the setup is modular and alternative tools can be easily integrated.
biorxiv bioinformatics 100-200-users 2019A comprehensive atlas of immunological differences between humans, mice and non-human primates, bioRxiv, 2019-03-12
Animal models are an integral part of the drug development and evaluation process. However, they are unsurprisingly imperfect reflections of humans, and the extent and nature of many immunological differences are unknown. With the rise of targeted and biological therapeutics, it is increasingly important that we understand the molecular differences in immunological behavior of humans and model organisms. Thus, we profiled a large number of healthy humans, along with three of the model organisms most similar to humans rhesus and cynomolgus macaques and African green monkeys; and the most widely used mammalian model mice. Using cross-species, universal phenotyping and signaling panels, we measured immune cell signaling responses to an array of 15 stimuli using CyTOF mass cytometry. We found numerous instances of different cellular phenotypes and immune signaling events occurring within and between species with likely effects on evaluation of therapeutics, and detail three examples (double-positive T cell frequency and signaling; granulocyte response to Bacillus anthracis antigen; and B cell subsets). We also explore the correlation of herpes simian B virus serostatus on the immune profile. The full dataset is available online at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsflowrepository.org>httpsflowrepository.org<jatsext-link> (accession FR-FCM-Z2ZY) and <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsimmuneatlas.org>httpsimmuneatlas.org<jatsext-link>.
biorxiv immunology 100-200-users 2019