A computational exploration of resilience and evolvability of protein–protein interaction networks

Protein-protein interaction (PPI) networks represent complex intra-cellular protein interactions , and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype's PPI network's resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks' resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms-random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits

A computational exploration of resilience and evolvability of protein–protein interaction networks

Protein–protein interaction (PPI) networks represent complex intra-cellular protein interactions, and the presence or absence of such interactions can lead to biological changes in an organism. Recent network-based approaches have shown that a phenotype’s PPI network’s resilience to environmental perturbations is related to its placement in the tree of life; though we still do not know how or why certain intra-cellular factors can bring about this resilience. Here, we explore the influence of gene expression and network properties on PPI networks’ resilience. We use publicly available data of PPIs for E. coli, S. cerevisiae, and H. sapiens, where we compute changes in network resilience as new nodes (proteins) are added to the networks under three node addition mechanisms—random, degree-based, and gene-expression-based attachments. By calculating the resilience of the resulting networks, we estimate the effectiveness of these node addition mechanisms. We demonstrate that adding nodes with gene-expression-based preferential attachment (as opposed to random or degree-based) preserves and can increase the original resilience of PPI network in all three species, regardless of gene expression distribution or network structure. These findings introduce a general notion of prospective resilience, which highlights the key role of network structures in understanding the evolvability of phenotypic traits

Interneuron Development Is Disrupted in Preterm Brains With Diffuse White Matter Injury: Observations in Mouse and Human

Preterm brain injury, occurring in approximately 30% of infants born <32 weeks gestational age, is associated with an increased risk of neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). The mechanism of gray matter injury in preterm born children is unclear and likely to be multifactorial; however, inflammation, a high predictor of poor outcome in preterm infants, has been associated with disrupted interneuron maturation in a number of animal models. Interneurons are important for regulating normal brain development, and disruption in interneuron development, and the downstream effects of this, has been implicated in the etiology of neurodevelopmental disorders. Here, we utilize postmortem tissue from human preterm cases with or without diffuse white matter injury (WMI; PMA range: 23+2 to 28+1 for non-WMI group, 26+6 to 30+0 for WMI group, p = 0.002) and a model of inflammation-induced preterm diffuse white matter injury (i.p. IL-1β, b.d., 10 μg/kg/injection in male CD1 mice from P1–5). Data from human preterm infants show deficits in interneuron numbers in the cortex and delayed growth of neuronal arbors at this early stage of development. In the mouse, significant reduction in the number of parvalbumin-positive interneurons was observed from postnatal day (P) 10. This decrease in parvalbumin neuron number was largely rectified by P40, though there was a significantly smaller number of parvalbumin positive cells associated with perineuronal nets in the upper cortical layers. Together, these data suggest that inflammation in the preterm brain may be a contributor to injury of specific interneuron in the cortical gray matter. This may represent a potential target for postnatal therapy to reduce the incidence and/or severity of neurodevelopmental disorders in preterm infants

Rolling Deck to Repository: Supporting the marine science community with data management services from academic research expeditions

Direct observations of the oceans acquired on oceanographic research ships operated across the international community support fundamental research into the many disciplines of ocean science and provide essential information for monitoring the health of the oceans. A comprehensive knowledge base is needed to support the responsible stewardship of the oceans with easy access to all data acquired globally. In the United States, the multidisciplinary shipboard sensor data routinely acquired each year on the fleet of coastal, regional and global ranging vessels supporting academic marine research are managed by the Rolling Deck to Repository (R2R, rvdata.us) program. With over a decade of operations, the R2R program has developed a robust routinized system to transform diverse data contributions from different marine data providers into a standardized and comprehensive collection of global-ranging observations of marine atmosphere, ocean, seafloor and subseafloor properties that is openly available to the international research community. In this article we describe the elements and framework of the R2R program and the services provided. To manage all expeditions conducted annually, a fleet-wide approach has been developed using data distributions submitted from marine operators with a data management workflow designed to maximize automation of data curation. Other design goals are to improve the completeness and consistency of the data and metadata archived, to support data citability, provenance tracking and interoperable data access aligned with FAIR (findable, accessible, interoperable, reusable) recommendations, and to facilitate delivery of data from the fleet for global data syntheses. Findings from a collection-level review of changes in data acquisition practices and quality over the past decade are presented. Lessons learned from R2R operations are also discussed including the benefits of designing data curation around the routine practices of data providers, approaches for ensuring preservation of a more complete data collection with a high level of FAIRness, and the opportunities for homogenization of datasets from the fleet so that they can support the broadest re-use of data across a diverse user community

Search for top squark pair production in pp collisions at root s=13 TeV using single lepton events

Peer reviewe

Search for supersymmetry in proton-proton collisions at 13 TeV using identified top quarks

A search for supersymmetry is presented based on proton-proton collision events containing identified hadronically decaying top quarks, no leptons, and an imbalance p(T)(miss) in transverse momentum. The data were collected with the CMS detector at the CERN LHC at a center-of-mass energy of 13 TeV, and correspond to an integrated luminosity of 35.9 fb(-1). Search regions are defined in terms of the multiplicity of bottom quark jet and top quark candidates, the p(T)(miss) , the scalar sum of jet transverse momenta, and themT2 mass variable. No statistically significant excess of events is observed relative to the expectation from the standard model. Lower limits on the masses of supersymmetric particles are determined at 95% confidence level in the context of simplified models with top quark production. For a model with direct top squark pair production followed by the decay of each top squark to a top quark and a neutralino, top squark masses up to 1020 GeVand neutralino masses up to 430 GeVare excluded. For amodel with pair production of gluinos followed by the decay of each gluino to a top quark-antiquark pair and a neutralino, gluino masses up to 2040 GeVand neutralino masses up to 1150 GeVare excluded. These limits extend previous results.Peer reviewe