A Bioinformatics Approach to the Structure, Function, and Evolution of the Nucleoprotein of the Order Mononegavirales

The goal of this Bioinformatic study is to investigate sequence conservation in relation to evolutionary function/structure of the nucleoprotein of the order Mononegavirales. In the combined analysis of 63 representative nucleoprotein (N) sequences from four viral families (Bornaviridae, Filoviridae, Rhabdoviridae, and Paramyxoviridae) we predict the regions of protein disorder, intra-residue contact and co-evolving residues. Correlations between location and conservation of predicted regions illustrate a strong division between families while high- lighting conservation within individual families. These results suggest the conserved regions among the nucleoproteins, specifically within Rhabdoviridae and Paramyxoviradae, but also generally among all members of the order, reflect an evolutionary advantage in maintaining these sites for the viral nucleoprotein as part of the transcription/replication machinery. Results indicate conservation for disorder in the C-terminus region of the representative proteins that is important for interacting with the phosphoprotein and the large subunit polymerase during transcription and replication. Additionally, the C-terminus region of the protein preceding the disordered region, is predicted to be important for interacting with the encapsidated genome. Portions of the N-terminus are responsible for N∶N stability and interactions identified by the presence or lack of co-evolving intra-protein contact predictions. The validation of these prediction results by current structural information illustrates the benefits of the Disorder, Intra-residue contact and Compensatory mutation Correlator (DisICC) pipeline as a method for quickly characterizing proteins and providing the most likely residues and regions necessary to target for disruption in viruses that have little structural information available

A Vision for Science Gateways: Bridging the Gap and Broadening the Outreach

The future for science gateways warrants exploration as we consider the possibilities that extend well beyond science and high performance computing into new interfaces, applications and user communities. In this paper, we look retrospectively at the successes of representative gateways thus far. This serves to highlight existing gaps gateways need to overcome in areas such as accessibility, usability and interoperability, and in the need for broader outreach by drawing insights from technology adoption research. We explore two particularly promising opportunities for gateways - computational social sciences and virtual reality – and make the case for the gateway community to be more intentional in engaging with users to encourage adoption and implementation, especially in the area of educational usage. We conclude with a call for focused attention on legal hurdles in order to realize the full future potential of science gateways. This paper serves as a roadmap for a vision of science gateways in the next ten years

Science Gateways and AI/ML: How Can Gateway Concepts and Solutions Meet the Needs in Data Science?

Science gateways are a crucial component of critical infrastructure as they provide the means for users to focus on their topics and methods instead of the technical details of the infrastructure. They are defined as end-to-end solutions for accessing data, software, computing services, sensors, and equipment specific to the needs of a science or engineering discipline and their goal is to hide the complexity of the underlying infrastructure. Science gateways are often called Virtual Research Environments in Europe and Virtual Labs in Australasia; we consider these two terms to be synonymous with science gateways. Over the past decade, artificial intelligence (AI) and machine learning (ML) have found applications in many different fields in private industry, and private industry has reaped the benefits. Likewise, in the academic realm, large-scale data science applications have also learned to apply public high-performance computing resources to make use of this technology. However, academic and research science gateways have yet to fully adopt the tools of AI. There is an opportunity in the gateways space, both to increase the visibility and accessibility to AI/ML applications and to enable researchers and developers to advance the field of science gateway cyberinfrastructure itself. Harnessing AI/ML is recognized as a high priority by the science gateway community. It is, therefore, critical for the next generation of science gateways to adapt to support the AI/ML that is already transforming many scientific fields. The goal is to increase collaborations between the two fields and to ensure that gateway services are used and are valuable to the AI/ML community. This chapter presents state-of-the-art examples and areas of opportunity for the science gateways community to pursue in relation to AI/ML and some vision of where these new capabilities might impact science gateways and support scientific research

Genetic variation in insulin-like growth factor signaling genes and breast cancer risk among BRCA1 and BRCA2 carriers

Abstract Introduction Women who carry mutations in BRCA1 and BRCA2 have a substantially increased risk of developing breast cancer as compared with the general population. However, risk estimates range from 20 to 80%, suggesting the presence of genetic and/or environmental risk modifiers. Based on extensive in vivo and in vitro studies, one important pathway for breast cancer pathogenesis may be the insulin-like growth factor (IGF) signaling pathway, which regulates both cellular proliferation and apoptosis. BRCA1 has been shown to directly interact with IGF signaling such that variants in this pathway may modify risk of cancer in women carrying BRCA mutations. In this study, we investigate the association of variants in genes involved in IGF signaling and risk of breast cancer in women who carry deleterious BRCA1 and BRCA2 mutations. Methods A cohort of 1,665 adult, female mutation carriers, including 1,122 BRCA1 carriers (433 cases) and 543 BRCA2 carriers (238 cases) were genotyped for SNPs in IGF1, IGF1 receptor (IGF1R), IGF1 binding protein (IGFBP1, IGFBP2, IGFBP5), and IGF receptor substrate 1 (IRS1). Cox proportional hazards regression was used to model time from birth to diagnosis of breast cancer for BRCA1 and BRCA2 carriers separately. For linkage disequilibrium (LD) blocks with multiple SNPs, an additive genetic model was assumed; and for single SNP analyses, no additivity assumptions were made. Results Among BRCA1 carriers, significant associations were found between risk of breast cancer and LD blocks in IGF1R (global P = 0.011 for LD block 2 and global P = 0.012 for LD block 11). Among BRCA2 carriers, an LD block in IGFBP2 (global P = 0.0145) was found to be associated with the time to breast cancer diagnosis. No significant LD block associations were found for the other investigated genes among BRCA1 and BRCA2 carriers. Conclusions This is the first study to investigate the role of genetic variation in IGF signaling and breast cancer risk in women carrying deleterious mutations in BRCA1 and BRCA2. We identified significant associations in variants in IGF1R and IRS1 in BRCA1 carriers and in IGFBP2 in BRCA2 carriers. Although there is known to be interaction of BRCA1 and IGF signaling, further replication and identification of causal mechanisms are needed to better understand these associations

Loss of Metal Ions, Disulfide Reduction and Mutations Related to Familial ALS Promote Formation of Amyloid-Like Aggregates from Superoxide Dismutase

Mutations in the gene encoding Cu-Zn superoxide dismutase (SOD1) are one of the causes of familial amyotrophic lateral sclerosis (FALS). Fibrillar inclusions containing SOD1 and SOD1 inclusions that bind the amyloid-specific dye thioflavin S have been found in neurons of transgenic mice expressing mutant SOD1. Therefore, the formation of amyloid fibrils from human SOD1 was investigated. When agitated at acidic pH in the presence of low concentrations of guanidine or acetonitrile, metalated SOD1 formed fibrillar material which bound both thioflavin T and Congo red and had circular dichroism and infrared spectra characteristic of amyloid. While metalated SOD1 did not form amyloid-like aggregates at neutral pH, either removing metals from SOD1 with its intramolecular disulfide bond intact or reducing the intramolecular disulfide bond of metalated SOD1 was sufficient to promote formation of these aggregates. SOD1 formed amyloid-like aggregates both with and without intermolecular disulfide bonds, depending on the incubation conditions, and a mutant SOD1 lacking free sulfhydryl groups (AS-SOD1) formed amyloid-like aggregates at neutral pH under reducing conditions. ALS mutations enhanced the ability of disulfide-reduced SOD1 to form amyloid-like aggregates, and apo-AS-SOD1 formed amyloid-like aggregates at pH 7 only when an ALS mutation was also present. These results indicate that some mutations related to ALS promote formation of amyloid-like aggregates by facilitating the loss of metals and/or by making the intramolecular disulfide bond more susceptible to reduction, thus allowing the conversion of SOD1 to a form that aggregates to form resembling amyloid. Furthermore, the occurrence of amyloid-like aggregates per se does not depend on forming intermolecular disulfide bonds, and multiple forms of such aggregates can be produced from SOD1

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Genomic analysis of SARS-CoV-2 variants of concern circulating in Hawai'i to facilitate public-health policies.

Using genomics, bioinformatics and statistics, herein we demonstrate the effect of statewide and nationwide quarantine on the introduction of SARS-CoV-2 variants of concern (VOC) in Hawai'i. To define the origins of introduced VOC, we analyzed 260 VOC sequences from Hawai'i, and 301,646 VOC sequences worldwide, deposited in the GenBank and global initiative on sharing all influenza data (GISAID), and constructed phylogenetic trees. The trees define the most recent common ancestor as the origin. Further, the multiple sequence alignment used to generate the phylogenetic trees identified the consensus single nucleotide polymorphisms in the VOC genomes. These consensus sequences allow for VOC comparison and identification of mutations of interest in relation to viral immune evasion and host immune activation. Of note is the P71L substitution within the E protein, the protein sensed by TLR2 to produce cytokines, found in the B.1.351 VOC may diminish the efficacy of some vaccines. Based on the phylogenetic trees, the B.1.1.7, B.1.351, B.1.427, and B.1.429 VOC have been introduced in Hawai'i multiple times since December 2020 from several definable geographic regions. From the first worldwide report of VOC in GenBank and GISAID, to the first arrival of VOC in Hawai'i, averages 320 days with quarantine, and 132 days without quarantine. As such, the effect of quarantine is shown to significantly affect the time to arrival of VOC in Hawai'i. Further, the collective 2020 quarantine of 43-states in the United States demonstrates a profound impact in delaying the arrival of VOC in states that did not practice quarantine, such as Utah. Our data demonstrates that at least 76% of all definable SARS-CoV-2 VOC have entered Hawai'i from California, with the B.1.351 variant in Hawai'i originating exclusively from the United Kingdom. These data provide a foundation for policy-makers and public-health officials to apply precision public health genomics to real-world policies such as mandatory screening and quarantine

Tapis-CHORDS Integration: Time-Series DataSupport in Science Gateway Infrastructure

The explosion of IoT devices and sensors in recent years has led to a demand for efficiently storing, processing and analyzing time-series data. Geoscience researchers use time-series data stores such as Hydroserver, VOEIS and CHORDS. Many of these tools require a great deal of infrastructure to deploy and expertise to manage and scale. Tapis's (formerly known as Agave) platform as a service provides a way to support researchers in a way that they are not responsible for the infrastructure and can focus on the science. The University of Hawai‘i (UH) and Texas Advanced Computing Center (TACC) have collaborated to develop a new API integration that combines Tapis with the CHORDS time series data service to support projects at both institutions for storing, annotating and querying time-series data. This new Streams API leverages the strengths of both the Tapis platform and CHORDS service to enable capabilities for supporting time-series data streams not available in either tool alone. These new capabilities may be leveraged by Tapis powered science gateways with needs for handling spatially indexed time-series data-sets for their researchers as they have been at UH and TACC.Office of the VP for Researc

Evolution of Teleost Fish Retroviruses: Characterization of New Retroviruses with Cellular Genes

The interactions between retroviruses and their hosts can be of a beneficial or detrimental nature. Some endogenous retroviruses are involved in development, while others cause disease. The Genome Parsing Suite (GPS) is a software tool to track and trace all Retroid agents in any sequenced genome (M. A. McClure et al., Genomics 85:512-523, 2005). Using the GPS, the retroviral content was assessed in four model teleost fish. Eleven new species of fish retroviruses are identified and characterized. The reverse transcriptase protein sequences were used to reconstruct a fish retrovirus phylogeny, thereby, significantly expanding the epsilonretrovirus family. Most of these novel retroviruses encode additional genes, some of which are homologous to cellular genes that would confer viral advantage. Although the fish divergence is much more ancient, retroviruses began infecting fish genomes approximately 4 million years ago