Transient intracellular acidification regulates the core transcriptional heat shock response, bioRxiv, 2018-09-12
AbstractCellular stress induces rapid expression of genes encoding molecular chaperones. In many eukaryotes, stress also triggers transient intracellular acidification which, by unknown mechanisms, is associated with increased survival. Here, using budding yeast as a model, we discover that preventing cells from transiently acidifying during heat shock compromises induction of molecular chaperones and fitness. Prevention of acidification during stress and recovery silences induction of a canonical heat-shock protein altogether. The association between acidification, induction, and growth holds at the population and single-cell levels. Hinting at the molecular basis of these effects, the failure to acidify specifically suppresses induction of genes regulated by the conserved heat shock transcription factor Hsf1. Our results establish a central role for intracellular pH in the eukaryotic transcriptional stress response, and implicate pH-sensitive stress-sensing proteins, rather than misfolded proteins, in the activation of Hsf1 under physiological heat shock conditions.
biorxiv cell-biology 0-100-users 2018The genomic view of diversification, bioRxiv, 2018-09-11
ABSTRACTEvolutionary relationships between species are traditionally represented in the form of a tree, called the species tree. The reconstruction of the species tree from molecular data is hindered by frequent conflicts between gene genealogies. A standard way of dealing with this issue is to postulate the existence of a unique species tree where disagreements between gene trees are explained by incomplete lineage sorting (ILS) due to random coalescences of gene lineages inside the edges of the species tree. This paradigm, known as the multi-species coalescent (MSC), is constantly violated by the ubiquitous presence of gene flow revealed by empirical studies, leading to topological incongruences of gene trees that cannot be explained by ILS alone. Here we argue that this paradigm should be revised in favor of a vision acknowledging the importance of gene flow and where gene histories shape the species tree rather than the opposite. We propose a new, plastic framework for modeling the joint evolution of gene and species lineages relaxing the hierarchy between the species tree and gene trees. We implement this framework in two mathematical models called the gene-based diversification models (GBD) 1) GBD-forward, following all evolving genomes and thus very intensive computationally and 2) GBD-backward, based on coalescent theory and thus more efficient. Each model features four parameters tuning colonization, mutation, gene flow and reproductive isolation. We propose a quick inference method based on the differences between gene trees and use it to evaluate the amount of gene flow in two empirical data-sets. We find that in these data-sets, gene tree distributions are better explained by the best fitting GBD model than by the best fitting MSC model. This work should pave the way for approaches of diversification using the richer signal contained in genomic evolutionary histories rather than in the mere species tree.
biorxiv evolutionary-biology 100-200-users 2018A data-driven approach to the automated mapping of functional brain topographies across species, bioRxiv, 2018-09-09
AbstractBehavioral neuroscience has made great strides in developing animal models of human behavior and psychiatric disorders. Animal models allow for the formulation of hypotheses regarding the mechanisms underlying psychiatric disorders, and the opportunity to test these hypotheses using procedures that are too invasive for human participants. However, recent scientific reviews have highlighted the low success rate of translating results from animal models into clinical interventions in humans. A potential roadblock is that bidirectional functional mappings between the human and rodent brain are incomplete. To narrow this gap, we created a framework, Neurobabel, for performing large-scale automated synthesis of human neuroimaging data and behavioral neuroscience data. By leveraging the semantics of how researchers within each field describe their studies, this framework enables region to region mapping of brain regions across species, as well as cross-species mapping of psychological functions. As a proof of concept, we utilize the framework to create a functional cross-species mapping between the amygdala and hippocampus for fear-related and spatial memories, respectively. We then proceed to address two open questions in the field (1) Do rodents have a dorsolateral prefrontal cortex? (2) Which human brain region corresponds to the rodent prelimbic cortex?
biorxiv neuroscience 0-100-users 2018A data-driven approach to the automated study of cross-species homologies, bioRxiv, 2018-09-09
AbstractBehavioral neuroscience has made great strides in developing animal models of human behavior and psychiatric disorders. Animal models allow for the formulation of hypotheses regarding the mechanisms underlying psychiatric disorders, and the opportunity to test these hypotheses using procedures that are too invasive for human participants. However, recent scientific reviews have highlighted the low success rate of translating results from animal models into clinical interventions in humans. A potential roadblock is that bidirectional functional mappings between the human and rodent brain are incomplete. To narrow this gap, we created a framework, Neurobabel, for performing large-scale automated synthesis of human neuroimaging data and behavioral neuroscience data. By leveraging the semantics of how researchers within each field describe their studies, this framework enables region to region mapping of brain regions across species, as well as cross-species mapping of psychological functions. As a proof of concept, we utilize the framework to create a functional cross-species mapping between the amygdala and hippocampus for fear-related and spatial memories, respectively. We then proceed to address two open questions in the field (1) Do rodents have a dorsolateral prefrontal cortex? (2) Which human brain region corresponds to the rodent prelimbic cortex?
biorxiv neuroscience 0-100-users 2018Resource Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires, bioRxiv, 2018-09-07
SummaryEssential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.
biorxiv genomics 100-200-users 2018The geometry of abstraction in hippocampus and pre-frontal cortex, bioRxiv, 2018-09-07
The curse of dimensionality plagues models of reinforcement learning and decision-making. The process of abstraction solves this by constructing abstract variables describing features shared by different specific instances, reducing dimensionality and enabling generalization in novel situations. Here we characterized neural representations in monkeys performing a task where a hidden variable described the temporal statistics of stimulus-response-outcome mappings. Abstraction was defined operationally using the generalization performance of neural decoders across task conditions not used for training. This type of generalization requires a particular geometric format of neural representations. Neural ensembles in dorsolateral pre-frontal cortex, anterior cingulate cortex and hippocampus, and in simulated neural networks, simultaneously represented multiple hidden and explicit variables in a format reflecting abstraction. Task events engaging cognitive operations modulated this format. These findings elucidate how the brain and artificial systems represent abstract variables, variables critical for generalization that in turn confers cognitive flexibility.
biorxiv neuroscience 100-200-users 2018