Machine Learning of Stem Cell Identities From Single-Cell Expression Data via Regulatory Network Archetypes

The molecular regulatory network underlying stem cell pluripotency has been intensively studied, and we now have a reliable ensemble model for the “average” pluripotent cell. However, evidence of significant cell-to-cell variability suggests that the activity of this network varies within individual stem cells, leading to differential processing of environmental signals and variability in cell fates. Here, we adapt a method originally designed for face recognition to infer regulatory network patterns within individual cells from single-cell expression data. Using this method we identify three distinct network configurations in cultured mouse embryonic stem cells—corresponding to naïve and formative pluripotent states and an early primitive endoderm state—and associate these configurations with particular combinations of regulatory network activity archetypes that govern different aspects of the cell's response to environmental stimuli, cell cycle status and core information processing circuitry. These results show how variability in cell identities arise naturally from alterations in underlying regulatory network dynamics and demonstrate how methods from machine learning may be used to better understand single cell biology, and the collective dynamics of cell communities

Entropy, Ergodicity and Stem Cell Multipotency

Populations of mammalian stem cells commonly exhibit considerable cell-cell variability. However, the functional role of this diversity is unclear. Here, we analyze expression fluctuations of the stem cell surface marker Sca1 in mouse hematopoietic progenitor cells using a simple stochastic model and find that the observed dynamics naturally lie close to a critical state, thereby producing a diverse population that is able to respond rapidly to environmental changes. We propose an information-theoretic interpretation of these results that views cellular multipotency as an instance of maximum entropy statistical inference.Comment: 6 pages, 3 figure

An Esrrb and nanog cell fate regulatory module controlled by feed forward loop interactions

Cell fate decisions during development are governed by multi-factorial regulatory mechanisms including chromatin remodeling, DNA methylation, binding of transcription factors to specific loci, RNA transcription and protein synthesis. However, the mechanisms by which such regulatory 'dimensions' coordinate cell fate decisions are currently poorly understood. Here we quantified the multi-dimensional molecular changes that occur in mouse embryonic stem cells (mESCs) upon depletion of Estrogen related receptor beta (Esrrb), a key pluripotency regulator. Comparative analyses of expression changes subsequent to depletion of Esrrb or Nanog, indicated that a system of interlocked feed-forward loops involving both factors, plays a central part in regulating the timing of mESC fate decisions. Taken together, our meta-analyses support a hierarchical model in which pluripotency is maintained by an Oct4-Sox2 regulatory module, while the timing of differentiation is regulated by a Nanog-Esrrb module

Noise-Driven Phenotypic Heterogeneity with Finite Correlation Time in Clonal Populations

There has been increasing awareness in the wider biological community of the role of clonal phenotypic heterogeneity in playing key roles in phenomena such as cellular bet-hedging and decision making, as in the case of the phage-λ lysis/lysogeny and B. Subtilis competence/vegetative pathways. Here, we report on the effect of stochasticity in growth rate, cellular memory/intermittency, and its relation to phenotypic heterogeneity. We first present a linear stochastic differential model with finite auto-correlation time, where a randomly fluctuating growth rate with a negative average is shown to result in exponential growth for sufficiently large fluctuations in growth rate. We then present a non-linear stochastic self-regulation model where the loss of coherent self-regulation and an increase in noise can induce a shift from bounded to unbounded growth. An important consequence of these models is that while the average change in phenotype may not differ for various parameter sets, the variance of the resulting distributions may considerably change. This demonstrates the necessity of understanding the influence of variance and heterogeneity within seemingly identical clonal populations, while providing a mechanism for varying functional consequences of such heterogeneity. Our results highlight the importance of a paradigm shift from a deterministic to a probabilistic view of clonality in understanding selection as an optimization problem on noise-driven processes, resulting in a wide range of biological implications, from robustness to environmental stress to the development of drug resistance

Amino Acid Restriction Triggers Angiogenesis via GCN2/ATF4 Regulation of VEGF and H2S Production

Angiogenesis, the formation of new blood vessels by endothelial cells (ECs), is an adaptive response to oxygen/nutrient deprivation orchestrated by vascular endothelial growth factor (VEGF) upon ischemia or exercise. Hypoxia is the best-understood trigger of VEGF expression via the transcription factor HIF1 alpha. Nutrient deprivation is inseparable from hypoxia during ischemia, yet its role in angiogenesis is poorly characterized. Here, we identified sulfur amino acid restriction as a proangiogenic trigger, promoting increased VEGF expression, migration and sprouting in ECs in vitro, and increased capillary density in mouse skeletal muscle in vivo via the GCN2/ATF4 amino acid starvation response pathway independent of hypoxia or HIF1 alpha. We also identified a requirement for cystathionine-gamma-lyase in VEGF-dependent angiogenesis via increased hydrogen sulfide (H2S) production. H2S mediated its proangiogenic effects in part by inhibiting mitochondrial electron transport and oxidative phosphorylation, resulting in increased glucose uptake and glycolytic ATP production.11Ysciescopu

Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle

<p>Abstract</p> <p>Background</p> <p>'Selection signatures' delimit regions of the genome that are, or have been, functionally important and have therefore been under either natural or artificial selection. In this study, two different and complementary methods--integrated Haplotype Homozygosity Score (|iHS|) and population differentiation index (F_ST)--were applied to identify traces of decades of intensive artificial selection for traits of economic importance in modern cattle.</p> <p>Results</p> <p>We scanned the genome of a diverse set of dairy and beef breeds from Germany, Canada and Australia genotyped with a 50 K SNP panel. Across breeds, a total of 109 extreme |iHS| values exceeded the empirical threshold level of 5% with 19, 27, 9, 10 and 17 outliers in Holstein, Brown Swiss, Australian Angus, Hereford and Simmental, respectively. Annotating the regions harboring clustered |iHS| signals revealed a panel of interesting candidate genes like SPATA17, MGAT1, PGRMC2 and ACTC1, COL23A1, MATN2, respectively, in the context of reproduction and muscle formation. In a further step, a new Bayesian F_ST-based approach was applied with a set of geographically separated populations including Holstein, Brown Swiss, Simmental, North American Angus and Piedmontese for detecting differentiated loci. In total, 127 regions exceeding the 2.5 per cent threshold of the empirical posterior distribution were identified as extremely differentiated. In a substantial number (56 out of 127 cases) the extreme F_STvalues were found to be positioned in poor gene content regions which deviated significantly (p < 0.05) from the expectation assuming a random distribution. However, significant F_STvalues were found in regions of some relevant genes such as SMCP and FGF1.</p> <p>Conclusions</p> <p>Overall, 236 regions putatively subject to recent positive selection in the cattle genome were detected. Both |iHS| and F_STsuggested selection in the vicinity of the Sialic acid binding Ig-like lectin 5 gene on BTA18. This region was recently reported to be a major QTL with strong effects on productive life and fertility traits in Holstein cattle. We conclude that high-resolution genome scans of selection signatures can be used to identify genomic regions contributing to within- and inter-breed phenotypic variation.</p

Predicting where a radiation will occur: Acoustic and molecular surveys reveal overlooked diversity in Indian Ocean Island crickets (Mogoplistinae: Ornebius)

Recent theory suggests that the geographic location of island radiations (local accumulation of species diversity due to cladogenesis) can be predicted based on island area and isolation. Crickets are a suitable group for testing these predictions, as they show both the ability to reach some of the most isolated islands in the world, and to speciate at small spatial scales. Despite substantial song variation between closely related species in many island cricket lineages worldwide, to date this characteristic has not received attention in the western Indian Ocean islands; existing species descriptions are based on morphology alone. Here we use a combination of acoustics and DNA sequencing to survey these islands for Ornebius crickets. We uncover a small but previously unknown radiation in the Mascarenes, constituting a three-fold increase in the Ornebius species diversity of this archipelago (from two to six species). A further new species is detected in the Comoros. Although double archipelago colonisation is the best explanation for species diversity in the Seychelles, in situ cladogenesis is the best explanation for the six species in the Mascarenes and two species of the Comoros. Whether the radiation of Mascarene Ornebius results from intra- or purely inter- island speciation cannot be determined on the basis of the phylogenetic data alone. However, the existence of genetic, song and ecological divergence at the intra-island scale is suggestive of an intra-island speciation scenario in which ecological and mating traits diverge hand-in-hand. Our results suggest that the geographic location of Ornebius radiations is partially but not fully explained by island area and isolation. A notable anomaly is Madagascar, where our surveys are consistent with existing accounts in finding no Ornebius species present. Possible explanations are discussed, invoking ecological differences between species and differences in environmental history between islands. (Résumé d'auteur

Integrated Genome-Scale Prediction of Detrimental Mutations in Transcription Networks

A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or “edge”) rather than a gene (or “node”) in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy) associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism

Salmonella Strains Isolated from Galápagos Iguanas Show Spatial Structuring of Serovar and Genomic Diversity

It is thought that dispersal limitation primarily structures host-associated bacterial populations because host distributions inherently limit transmission opportunities. However, enteric bacteria may disperse great distances during food-borne outbreaks. It is unclear if such rapid long-distance dispersal events happen regularly in natural systems or if these events represent an anthropogenic exception. We characterized Salmonella enterica isolates from the feces of free-living Galápagos land and marine iguanas from five sites on four islands using serotyping and genomic fingerprinting. Each site hosted unique and nearly exclusive serovar assemblages. Genomic fingerprint analysis offered a more complex model of S. enterica biogeography, with evidence of both unique strain pools and of spatial population structuring along a geographic gradient. These findings suggest that even relatively generalist enteric bacteria may be strongly dispersal limited in a natural system with strong barriers, such as oceanic divides. Yet, these differing results seen on two typing methods also suggests that genomic variation is less dispersal limited, allowing for different ecological processes to shape biogeographical patterns of the core and flexible portions of this bacterial species' genome