From Mollusks to Medicine: A Venomics Approach for the Discovery and Characterization of Therapeutics from Terebridae Peptide Toxins

Animal venoms comprise a diversity of peptide toxins that manipulate molecular targets such as ion channels and receptors, making venom peptides attractive candidates for the development of therapeutics to benefit human health. However, identifying bioactive venom peptides remains a significant challenge. In this review we describe our particular venomics strategy for the discovery, characterization, and optimization of Terebridae venom peptides, teretoxins. Our strategy reflects the scientific path from mollusks to medicine in an integrative sequential approach with the following steps: (1) delimitation of venomous Terebridae lineages through taxonomic and phylogenetic analyses; (2) identification and classification of putative teretoxins through omics methodologies, including genomics, transcriptomics, and proteomics; (3) chemical and recombinant synthesis of promising peptide toxins; (4) structural characterization through experimental and computational methods; (5) determination of teretoxin bioactivity and molecular function through biological assays and computational modeling; (6) optimization of peptide toxin affinity and selectivity to molecular target; and (7) development of strategies for effective delivery of venom peptide therapeutics. While our research focuses on terebrids, the venomics approach outlined here can be applied to the discovery and characterization of peptide toxins from any venomous taxa

Genetic variation in insulin‐induced kinase signaling

Individual differences in sensitivity to insulin contribute to disease susceptibility including diabetes and metabolic syndrome. Cellular responses to insulin are well studied. However, which steps in these response pathways differ across individuals remains largely unknown. Such knowledge is needed to guide more precise therapeutic interventions. Here, we studied insulin response and found extensive individual variation in the activation of key signaling factors, including ERK whose induction differs by more than 20‐fold among our subjects. This variation in kinase activity is propagated to differences in downstream gene expression response to insulin. By genetic analysis, we identified cis‐acting DNA variants that influence signaling response, which in turn affects downstream changes in gene expression and cellular phenotypes, such as protein translation and cell proliferation. These findings show that polymorphic differences in signal transduction contribute to individual variation in insulin response, and suggest kinase modulators as promising therapeutics for diseases characterized by insulin resistance.SynopsisGenetic variants contribute to individual variation in insulin response, including kinase activation, changes in gene expression and cell growth, suggesting kinase modulators as promising therapeutics for diseases characterized by insulin resistance.Extensive individual variation is observed in insulin‐induced activation of signal transduction.The variation in signaling response is propagated downstream to influence gene expression and cell growth.There is a genetic component to the individual differences in signaling and gene expression response to insulin.Genetic variants contribute to individual variation in insulin response, including kinase activation, changes in gene expression and cell growth, suggesting kinase modulators as promising therapeutics for diseases characterized by insulin resistance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/112224/1/msb156250-sup-0001-EVFigs.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/112224/2/msb156250.reviewer_comments.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/112224/3/msb156250.pd

Molecular Diversity and Gene Evolution of the Venom Arsenal of Terebridae Predatory Marine Snails

Venom peptides from predatory organisms are a resource for investigating evolutionary processes such as adaptive radiation or diversification, and exemplify promising targets for biomedical drug development. Terebridae are an understudied lineage of conoidean snails,which also includes cone snails and turrids. Characterization of cone snail venompeptides, conotoxins, has revealed a cocktail of bioactive compounds used to investigate physiological cellular function, predator-prey interactions, and to develop novel therapeutics. However, venom diversity of other conoidean snails remains poorly understood. The present research applies a venomics approach to characterize novel terebrid venom peptides, teretoxins, from the venom gland transcriptomes of Triplostephanus anilis and Terebra subulata. Next-generation sequencing and de novo assembly identified 139 putative teretoxins that were analyzed for the presence of canonical peptide features as identified in conotoxins. To meet the challenges of de novo assembly, multiple approaches for cross validation of findings were performed to achieve reliable assemblies of venom duct transcriptomes and to obtain a robust portrait of Terebridae venom. Phylogenetic methodology was used to identify 14 teretoxin gene superfamilies for the first time, 13 of which are unique to the Terebridae. Additionally, basic local algorithm search tool homologybased searches to venom-related genes and posttranslational modification enzymes identified a convergence of certain venom proteins, suchas actinoporin, commonly foundinvenoms. This research provides novel insights intovenomevolutionandrecruitment in Conoidean predatory marine snails and identifies a plethora of terebrid venom peptides that can be used to investigate fundamental questions pertaining to gene evolution

Phylogenomic Identification of Regulatory Sequences in Bacteria: an Analysis of Statistical Power and an Application to Borrelia burgdorferi Sensu Lato

Phylogenomic footprinting is an approach for ab initio identification of genome-wide regulatory elements in bacterial species based on sequence conservation. The statistical power of the phylogenomic approach depends on the degree of sequence conservation, the length of regulatory elements, and the level of phylogenetic divergence among genomes. Building on an earlier model, we propose a binomial model that uses synonymous tree lengths as neutral expectations for determining the statistical significance of conserved intergenic spacer (IGS) sequences. Simulations show that the binomial model is robust to variations in the value of evolutionary parameters, including base frequencies and the transition-to-transversion ratio. We used the model to search for regulatory sequences in the Lyme disease species group (Borrelia burgdorferi sensu lato) using 23 genomes. The model indicates that the currently available set of Borrelia genomes would not yield regulatory sequences shorter than five bases, suggesting that genome sequences of additional B. burgdorferi sensu lato species are needed. Nevertheless, we show that previously known regulatory elements are indeed strongly conserved in sequence or structure across these Borrelia species. Further, we predict with sufficient confidence two new RpoS binding sites, 39 promoters, 19 transcription terminators, 28 noncoding RNAs, and four sets of coregulated genes. These putative cis- and trans-regulatory elements suggest novel, Borrelia-specific mechanisms regulating the transition between the tick and host environments, a key adaptation and virulence mechanism of B. burgdorferi. Alignments of IGS sequences are available on BorreliaBase.org, an online database of orthologous open reading frame (ORF) and IGS sequences in Borrelia

BorreliaBase: a phylogeny-centered browser of Borrelia genomes

Background The bacterial genus Borrelia (phylum Spirochaetes) consists of two groups of pathogens represented respectively by B. burgdorferi, the agent of Lyme borreliosis, and B. hermsii, the agent of tick-borne relapsing fever. The number of publicly available Borrelia genomic sequences is growing rapidly with the discovery and sequencing of Borrelia strains worldwide. There is however a lack of dedicated online databases to facilitate comparative analyses of Borrelia genomes. Description We have developed BorreliaBase, an online database for comparative browsing of Borrelia genomes. The database is currently populated with sequences from 35 genomes of eight Lyme-borreliosis (LB) group Borrelia species and 7 Relapsing-fever (RF) group Borrelia species. Distinct from genome repositories and aggregator databases, BorreliaBase serves manually curated comparative-genomic data including genome-based phylogeny, genome synteny, and sequence alignments of orthologous genes and intergenic spacers. Conclusions With a genome phylogeny at its center, BorreliaBase allows online identification of hypervariable lipoprotein genes, potential regulatory elements, and recombination footprints by providing evolution-based expectations of sequence variability at each genomic locus. The phylo-centric design of BorreliaBase (http://borreliabase.org) is a novel model for interactive browsing and comparative analysis of bacterial genomes online

From Mollusks to Medicine: A Venomics Approach for the Discovery and Characterization of Therapeutics from Terebridae Peptide Toxins

Animal venoms comprise a diversity of peptide toxins that manipulate molecular targets such as ion channels and receptors, making venom peptides attractive candidates for the development of therapeutics to benefit human health. However, identifying bioactive venom peptides remains a significant challenge. In this review we describe our particular venomics strategy for the discovery, characterization, and optimization of Terebridae venom peptides, teretoxins. Our strategy reflects the scientific path from mollusks to medicine in an integrative sequential approach with the following steps: (1) delimitation of venomous Terebridae lineages through taxonomic and phylogenetic analyses; (2) identification and classification of putative teretoxins through omics methodologies, including genomics, transcriptomics, and proteomics; (3) chemical and recombinant synthesis of promising peptide toxins; (4) structural characterization through experimental and computational methods; (5) determination of teretoxin bioactivity and molecular function through biological assays and computational modeling; (6) optimization of peptide toxin affinity and selectivity to molecular target; and (7) development of strategies for effective delivery of venom peptide therapeutics. While our research focuses on terebrids, the venomics approach outlined here can be applied to the discovery and characterization of peptide toxins from any venomous taxa

BpWrapper: BioPerl-based sequence and tree utilities for rapid prototyping of bioinformatics pipelines

Abstract Background Automated bioinformatics workflows are more robust, easier to maintain, and results more reproducible when built with command-line utilities than with custom-coded scripts. Command-line utilities further benefit by relieving bioinformatics developers to learn the use of, or to interact directly with, biological software libraries. There is however a lack of command-line utilities that leverage popular Open Source biological software toolkits such as BioPerl (http://bioperl.org) to make many of the well-designed, robust, and routinely used biological classes available for a wider base of end users. Results Designed as standard utilities for UNIX-family operating systems, BpWrapper makes functionality of some of the most popular BioPerl modules readily accessible on the command line to novice as well as to experienced bioinformatics practitioners. The initial release of BpWrapper includes four utilities with concise command-line user interfaces, bioseq, bioaln, biotree, and biopop, specialized for manipulation of molecular sequences, sequence alignments, phylogenetic trees, and DNA polymorphisms, respectively. Over a hundred methods are currently available as command-line options and new methods are easily incorporated. Performance of BpWrapper utilities lags that of precompiled utilities while equivalent to that of other utilities based on BioPerl. BpWrapper has been tested on BioPerl Release 1.6, Perl versions 5.10.1 to 5.25.10, and operating systems including Apple macOS, Microsoft Windows, and GNU/Linux. Release code is available from the Comprehensive Perl Archive Network (CPAN) at https://metacpan.org/pod/Bio::BPWrapper. Source code is available on GitHub at https://github.com/bioperl/p5-bpwrapper. Conclusions BpWrapper improves on existing sequence utilities by following the design principles of Unix text utilities such including a concise user interface, extensive command-line options, and standard input/output for serialized operations. Further, dozens of novel methods for manipulation of sequences, alignments, and phylogenetic trees, unavailable in existing utilities (e.g., EMBOSS, Newick Utilities, and FAST), are provided. Bioinformaticians should find BpWrapper useful for rapid prototyping of workflows on the command-line without creating custom scripts for comparative genomics and other bioinformatics applications

Additional file 1: of BpWrapper: BioPerl-based sequence and tree utilities for rapid prototyping of bioinformatics pipelines

A reference card for the four BpWrapper utilities (PDF 758 kb