Bio.Phylo: A Unified Toolkit for Processing, Analyzing and Visualizing Phylogenetic Trees in Biopython

Background: Ongoing innovation in phylogenetics and evolutionary biology has been accompanied by a proliferation of software tools, data formats, analytical techniques and web servers. This brings with it the challenge of integrating phylogenetic and other related biological data found in a wide variety of formats, and underlines the need for reusable software that can read, manipulate and transform this information into the various forms required to build computational pipelines. Results: We built a Python software library for working with phylogenetic data that is tightly integrated with Biopython, a broad-ranging toolkit for computational biology. Our library, Bio.Phylo, is highly interoperable with existing libraries, tools and standards, and is capable of parsing common file formats for phylogenetic trees, performing basic transformations and manipulations, attaching rich annotations, and visualizing trees. We unified the modules for working with the standard file formats Newick, NEXUS and phyloXML behind a consistent and simple API, providing a common set of functionality independent of the data source. Conclusions: Bio.Phylo meets a growing need in bioinformatics for working with heterogeneous types of phylogenetic data. By supporting interoperability with multiple file formats and leveraging existing Biopython features, this library simplifies the construction of phylogenetic workflows. We also provide examples of the benefits of building a community around a shared open-source project. Bio.Phylo is included with Biopython, available through the Biopython website, http://biopython.org

Ten Simple Rules for Getting Help from Online Scientific Communities

The increasing complexity of research requires scientists to work at the intersection of multiple fields and to face problems for which their formal education has not prepared them. For example, biologists with no or little background in programming are now often using complex scripts to handle the results from their experiments; vice versa, programmers wishing to enter the world of bioinformatics must know about biochemistry, genetics, and other fields. In this context, communication tools such as mailing lists, web forums, and online communities acquire increasing importance. These tools permit scientists to quickly contact people skilled in a specialized field. A question posed properly to the right online scientific community can help in solving difficult problems, often faster than screening literature or writing to publication authors. The growth of active online scientific communities, such as those listed in Table S1, demonstrates how these tools are becoming an important source of support for an increasing number of researchers. Nevertheless, making proper use of these resources is not easy. Adhering to the social norms of World Wide Web communication—loosely termed “netiquette”—is both important and non-trivial. In this article, we take inspiration from our experience on Internet-shared scientific knowledge, and from similar documents such as “Asking the Questions the Smart Way” and “Getting Answers”, to provide guidelines and suggestions on how to use online communities to solve scientific problems

A system-level, molecular evolutionary analysis of mammalian phototransduction

Phototransduction is the biochemical process by which a light stimulus is converted to a neuronal signal. The process functions through complex interactions between many proteins, which work in concert to tightly control the dynamics of the photoresponse. The primary aim of this thesis is to describe how the topology and kinetics of these interactions have given rise to detectable patterns of molecular evolution. To this end, a secondary aim is to develop a comprehensive mathematical model of mammalian phototransduction, first through the improvement of an existing model of the amphibian system and then through the re-tuning of that model to fit mammalian data. The results show a striking importance of the signal recovery-related proteins in shaping the photoresponse. This is reflected in relaxed evolutionary constraint on those proteins that exert the greatest dynamic influence. Meanwhile, the proteins most central to the process, while less important dynamically, are strongly constrained due to their essentiality in proper signal transduction.La fototransducció és el procés bioquímic pel qual un estímul de llum es converteix en un senyal neuronal. El procés funciona a través d'interaccions complexes entre moltes proteïnes, que funcionen en conjunt per controlar estretament la dinàmica de la fotoresposta. L'objectiu principal d'aquesta tesi és descriure com la topologia i la cinètica d'aquestes interaccions han donat lloc a patrons detectables d'evolució molecular. Amb aquesta finalitat, un objectiu secundari és el desenvolupament d'un model matemàtic integral de la fototransducció en mamífers, primer a través de la millora d'un model existent del sistema d'amfibis i després a través de la refinament d'aquest model per ajustar-lo a les dades de mamífers. Els resultats mostren una importància notable de les proteïnes relacionades amb la recuperació del senyal en la fotoresposta. Això es reflecteix en una relaxació de les constriccions evolutives en les proteïnes que exerceixen la major influència dinàmica. Alhora, les proteïnes més centrals per al procés, tot i essent menys importants dinàmicament, es troben fortament limitades degut a la seva essencialitat en la correcta transducció de senyal

Reconstructing phosphorylation signalling networks from quantitative phosphoproteomic data

Cascades of phosphorylation between protein kinases comprise a core mechanism in the integration and propagation of intracellular signals. Although we have accumulated a wealth of knowledge around some such pathways, this is subject to study biases and much remains to be uncovered. Phosphoproteomics, the identification and quantification of phosphorylated proteins on a proteomic scale, provides a high-throughput means of interrogating the state of intracellular phosphorylation, both at the pathway level and at the whole-cell level. In this review, we discuss methods for using human quantitative phosphoproteomic data to reconstruct the underlying signalling networks that generated it. We address several challenges imposed by the data on such analyses and we consider promising advances towards reconstructing unbiased, kinome-scale signalling networks.ISSN:0071-1365ISSN:1744-135

Dynamic sensitivity and nonlinear interactions influence the system-level evolutionary patterns of phototransduction proteins

Determining the influence of complex, molecular-system dynamics on the evolution of proteins is hindered by the significant challenge of quantifying the control exerted by the proteins on system output. We have employed a combination of systems biology and molecular evolution analyses in a first attempt to unravel this relationship. We employed a comprehensive mathematical model of mammalian phototransduction to predict the degree of influence that each protein in the system exerts on the high-level dynamic behaviour. We found that the genes encoding the most dynamically sensitive proteins exhibit relatively relaxed evolutionary constraint. We also investigated the evolutionary and epistatic influences of the many nonlinear interactions between proteins in the system and found several pairs to have coevolved, including those whose interactions are purely dynamical with respect to system output. This evidence points to a key role played by nonlinear system dynamics in influencing patterns of molecular evolution.This work was supported by the Ministerio de Economia y Competitividad, Spain (grant no. BFU2013-43726-P, subprogram BMC) and the María de Maez to Program for Units of Excellence in R&D (MDM-2014-0370); the Departament d'Economia i Coneixement de la Generalitat de Catalunya (Grup de Recerca Consolidat GRC 2014 SGR 866); AGAUR, Generalitat de Catalunya (2011 FI BI 00275 to B.M.I.); and the Spanish Ministry of Science and Innovation (MICINN) (Juan de la Cierva Program to L.M.

Dynamic sensitivity and nonlinear interactions influence the system-level evolutionary patterns of phototransduction proteins

Determining the influence of complex, molecular-system dynamics on the evolution of proteins is hindered by the significant challenge of quantifying the control exerted by the proteins on system output. We have employed a combination of systems biology and molecular evolution analyses in a first attempt to unravel this relationship. We employed a comprehensive mathematical model of mammalian phototransduction to predict the degree of influence that each protein in the system exerts on the high-level dynamic behaviour. We found that the genes encoding the most dynamically sensitive proteins exhibit relatively relaxed evolutionary constraint. We also investigated the evolutionary and epistatic influences of the many nonlinear interactions between proteins in the system and found several pairs to have coevolved, including those whose interactions are purely dynamical with respect to system output. This evidence points to a key role played by nonlinear system dynamics in influencing patterns of molecular evolution.This work was supported by the Ministerio de Economia y Competitividad, Spain (grant no. BFU2013-43726-P, subprogram BMC) and the María de Maez to Program for Units of Excellence in R&D (MDM-2014-0370); the Departament d'Economia i Coneixement de la Generalitat de Catalunya (Grup de Recerca Consolidat GRC 2014 SGR 866); AGAUR, Generalitat de Catalunya (2011 FI BI 00275 to B.M.I.); and the Spanish Ministry of Science and Innovation (MICINN) (Juan de la Cierva Program to L.M.

Bio.Phylo: A unified toolkit for processing, analyzing and visualizing phylogenetic trees in Biopython

Abstract Background Ongoing innovation in phylogenetics and evolutionary biology has been accompanied by a proliferation of software tools, data formats, analytical techniques and web servers. This brings with it the challenge of integrating phylogenetic and other related biological data found in a wide variety of formats, and underlines the need for reusable software that can read, manipulate and transform this information into the various forms required to build computational pipelines. Results We built a Python software library for working with phylogenetic data that is tightly integrated with Biopython, a broad-ranging toolkit for computational biology. Our library, Bio.Phylo, is highly interoperable with existing libraries, tools and standards, and is capable of parsing common file formats for phylogenetic trees, performing basic transformations and manipulations, attaching rich annotations, and visualizing trees. We unified the modules for working with the standard file formats Newick, NEXUS and phyloXML behind a consistent and simple API, providing a common set of functionality independent of the data source. Conclusions Bio.Phylo meets a growing need in bioinformatics for working with heterogeneous types of phylogenetic data. By supporting interoperability with multiple file formats and leveraging existing Biopython features, this library simplifies the construction of phylogenetic workflows. We also provide examples of the benefits of building a community around a shared open-source project. Bio.Phylo is included with Biopython, available through the Biopython website, http://biopython.org.</p

A system-level, molecular evolutionary analysis of mammalian phototransduction

Visual perception is initiated in the photoreceptor cells of the retina via the phototransduction system./nThis system has shown marked evolution during mammalian divergence in such complex attributes as activation time and recovery time. We have performed a molecular evolutionary analysis of proteins involved in mammalian/nphototransduction in order to unravel how the action of natural selection has been distributed throughout the/nsystem to evolve such traits. We found selective pressures to be non-randomly distributed according to both a simple protein classification scheme and a protein-interaction network representation of the signaling pathway. Proteins which are topologically central in the signaling pathway, such as the G proteins, as well as retinoid cycle chaperones and proteins involved in photoreceptor cell-type determination, were found to be more constrained in their evolution. Proteins peripheral to the pathway, such as ion channels and exchangers, as well as the retinoid cycle enzymes, have experienced a relaxation of selective pressures. Furthermore, signals of positive selection were detected in two genes: the short-wave (blue) opsin (OPN1SW) in hominids and the rod-specific Na+/Ca2+,K+ ion exchanger (SLC24A1) in rodents. The functions of the proteins involved in phototransduction and the topology of the interactions between them have imposed non-random constraints on their evolution. Thus, in shaping or conserving system-level phototransduction traits, natural selection has targeted the underlying proteins in a concerted manner.This research was funded by grant BFU2010-19443 (subprogram BMC) awarded by Ministerio de Ciencia y Tecnología (Spain) and by the Direcció General de/nRecerca, Generalitat de Catalunya (Grup de Recerca Consolidat 2009SGR 1101). BI is supported by a FI-DGR from AGAUR, Generalitat de Catalunya (2011F1 B100275). LM acknowledges funding from the Juan de la Cierva Program of the Spanish Ministry of Science and Innovation (MICINN)

Sub-minute Phosphoregulation of Cell Cycle Systems during Plasmodium Gamete Formation

The transmission of malaria parasites to mosquitoes relies on the rapid induction of sexual reproduction upon their ingestion into a blood meal. Haploid female and male gametocytes become activated and emerge from their host cells, and the males enter the cell cycle to produce eight microgametes. The synchronized nature of gametogenesis allowed us to investigate phosphorylation signaling during its first minute in Plasmodium berghei via a high-resolution time course of the phosphoproteome. This revealed an unexpectedly broad response, with proteins related to distinct cell cycle events undergoing simultaneous phosphoregulation. We implicate several protein kinases in the process, and we validate our analyses on the plant-like calcium-dependent protein kinase 4 (CDPK4) and a homolog of serine/arginine-rich protein kinases (SRPK1). Mutants in these kinases displayed distinct phosphoproteomic disruptions, consistent with differences in their phenotypes. The results reveal the central role of protein phosphorylation in the atypical cell cycle regulation of a divergent eukaryote

A system-level, molecular evolutionary analysis of mammalian phototransduction

Visual perception is initiated in the photoreceptor cells of the retina via the phototransduction system./nThis system has shown marked evolution during mammalian divergence in such complex attributes as activation time and recovery time. We have performed a molecular evolutionary analysis of proteins involved in mammalian/nphototransduction in order to unravel how the action of natural selection has been distributed throughout the/nsystem to evolve such traits. We found selective pressures to be non-randomly distributed according to both a simple protein classification scheme and a protein-interaction network representation of the signaling pathway. Proteins which are topologically central in the signaling pathway, such as the G proteins, as well as retinoid cycle chaperones and proteins involved in photoreceptor cell-type determination, were found to be more constrained in their evolution. Proteins peripheral to the pathway, such as ion channels and exchangers, as well as the retinoid cycle enzymes, have experienced a relaxation of selective pressures. Furthermore, signals of positive selection were detected in two genes: the short-wave (blue) opsin (OPN1SW) in hominids and the rod-specific Na+/Ca2+,K+ ion exchanger (SLC24A1) in rodents. The functions of the proteins involved in phototransduction and the topology of the interactions between them have imposed non-random constraints on their evolution. Thus, in shaping or conserving system-level phototransduction traits, natural selection has targeted the underlying proteins in a concerted manner.This research was funded by grant BFU2010-19443 (subprogram BMC) awarded by Ministerio de Ciencia y Tecnología (Spain) and by the Direcció General de/nRecerca, Generalitat de Catalunya (Grup de Recerca Consolidat 2009SGR 1101). BI is supported by a FI-DGR from AGAUR, Generalitat de Catalunya (2011F1 B100275). LM acknowledges funding from the Juan de la Cierva Program of the Spanish Ministry of Science and Innovation (MICINN)