Integrated computational and experimental analysis of host-virus interaction systems

Host-virus systems biology seeks to elucidate the complex interactions between a virus and its host, and to determine the downstream consequences of these interactions for the host. Traditional studies of host-virus interactions, conducted one-at-a-time, yield high-quality results, but these have limited scope. By contrast, systems biology uses a holistic approach to examine many interactions simultaneously, thereby increasing the breadth of interactions revealed. However, these studies have largely focused on common human pathogens (e.g., influenza or HIV), and their results may not apply to unrelated viruses, such as those that cause hemorrhagic fevers. Combining experimental and computational techniques can yield novel information about host-virus interactions that traditional virological or purely computational systems-biology methods cannot uncover. In this thesis, I demonstrate the utility of combined experimental and computational approaches by: (1) revealing general principles of host-virus interactions, broadly applicable to a wide range of viruses; and (2) probing a specific host-virus interaction system to identify transcriptional signatures which elucidate host response to Ebola virus. I identify general mechanisms governing host-virus protein-protein interactions (PPIs) using domain-resolved PPI networks. This method identifies mechanistic differences between virus-human and within-human interactions, such as the preference viral proteins exhibit for binding human proteins containing linear motif-binding domains. Using domain-resolved PPIs reveals novel signatures of pleiotropy, economy, and convergent evolution in the viral-host interactome not previously identified in other PPI networks. I further identify transcriptional signatures of host response to Ebola virus (EBOV) infection by pairing high-throughput microarray data with advanced pathway analyses. I compare EBOV-infected, non-human primates with and without anticoagulant treatment, to identify transcriptional signatures associated with survival following infection. Having found that CCAAT-enhancer binding proteins (CEBPs) are associated with survival, I determine the role CEBPs have in EBOV infection by using comparative microarray analysis of multiple viral infections of hemorrhagic and non-hemorrhagic origin. I also identify unique transcriptional changes in the host that distinguish EBOV infection from other viral infections, such as Influenza. Integrating these two areas of research provides information about universally applicable patterns of viral infection, while simultaneously examining the consequences of specific host-pathogen interactions

Signatures of Pleiotropy, Economy and Convergent Evolution in a Domain-Resolved Map of Human–Virus Protein–Protein Interaction Networks

A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1) domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2) domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral-host interactions that are otherwise hidden in the traditional binary network, highlighting the power and necessity of high-resolution approaches in host-pathogen systems biology

Production of a reference transcriptome and transcriptomic database (PocilloporaBase) for the cauliflower coral, Pocillopora damicornis

<p>Abstract</p> <p>Background</p> <p>Motivated by the precarious state of the world's coral reefs, there is currently a keen interest in coral transcriptomics. By identifying changes in coral gene expression that are triggered by particular environmental stressors, we can begin to characterize coral stress responses at the molecular level, which should lead to the development of more powerful diagnostic tools for evaluating the health of corals in the field. Furthermore, the identification of genetic variants that are more or less resilient in the face of particular stressors will help us to develop more reliable prognoses for particular coral populations. Toward this end, we performed deep mRNA sequencing of the cauliflower coral, <it>Pocillopora damicornis</it>, a geographically widespread Indo-Pacific species that exhibits a great diversity of colony forms and is able to thrive in habitats subject to a wide range of human impacts. Importantly, <it>P. damicornis </it>is particularly amenable to laboratory culture. We collected specimens from three geographically isolated Hawaiian populations subjected to qualitatively different levels of human impact. We isolated RNA from colony fragments ("nubbins") exposed to four environmental stressors (heat, desiccation, peroxide, and hypo-saline conditions) or control conditions. The RNA was pooled and sequenced using the 454 platform.</p> <p>Description</p> <p>Both the raw reads (n = 1, 116, 551) and the assembled contigs (n = 70, 786; mean length = 836 nucleotides) were deposited in a new publicly available relational database called PocilloporaBase <url>http://www.PocilloporaBase.org</url>. Using BLASTX, 47.2% of the contigs were found to match a sequence in the NCBI database at an E-value threshold of ≤.001; 93.6% of those contigs with matches in the NCBI database appear to be of metazoan origin and 2.3% bacterial origin, while most of the remaining 4.1% match to other eukaryotes, including algae and amoebae.</p> <p>Conclusions</p> <p><it>P. damicornis </it>now joins the handful of coral species for which extensive transcriptomic data are publicly available. Through PocilloporaBase <url>http://www.PocilloporaBase.org</url>, one can obtain assembled contigs and raw reads and query the data according to a wide assortment of attributes including taxonomic origin, PFAM motif, KEGG pathway, and GO annotation.</p

Postcopulatory Sexual Selection Is Associated with Reduced Variation in Sperm Morphology

The evolutionary role of postcopulatory sexual selection in shaping male reproductive traits, including sperm morphology, is well documented in several taxa. However, previous studies have focused almost exclusively on the influence of sperm competition on variation among species. In this study we tested the hypothesis that intraspecific variation in sperm morphology is driven by the level of postcopulatory sexual selection in passerine birds.Using two proxy measures of sperm competition level, (i) relative testes size and (ii) extrapair paternity level, we found strong evidence that intermale variation in sperm morphology is negatively associated with the degree of postcopulatory sexual selection, independently of phylogeny.Our results show that the role of postcopulatory sexual selection in the evolution of sperm morphology extends to an intraspecific level, reducing the variation towards what might be a species-specific 'optimum' sperm phenotype. This finding suggests that while postcopulatory selection is generally directional (e.g., favouring longer sperm) across avian species, it also acts as a stabilising evolutionary force within species under intense selection, resulting in reduced variation in sperm morphology traits. We discuss some potential evolutionary mechanisms for this pattern

Integrative genomic analysis by interoperation of bioinformatics tools in GenomeSpace

Integrative analysis of multiple data types to address complex biomedical questions requires the use of multiple software tools in concert and remains an enormous challenge for most of the biomedical research community. Here we introduce GenomeSpace (http://www.genomespace.org), a cloud-based, cooperative community resource. Seeded as a collaboration of six of the most popular genomics analysis tools, GenomeSpace now supports the streamlined interaction of 20 bioinformatics tools and data resources. To facilitate the ability of non-programming users’ to leverage GenomeSpace in integrative analysis, it offers a growing set of ‘recipes’, short workflows involving a few tools and steps to guide investigators through high utility analysis tasks

Viral proteins have a higher fraction of domain-motif interactions (DMIs) than human proteins.

<p>Fraction of DMIs out of the total number of interactions per protein tend to be higher in viral proteins (red) than human proteins (blue) in (<b>A</b>) all interactions in the network (permutation test, two-tailed <i>P</i> = 0.047), and (<b>B</b>) confirmed interactions (<i>P</i> = 0.018). Error bars reflect the standard error.</p

Domain-centric mechanisms of host-virus protein-protein interaction.

<p>(<b>A</b>) A domain-domain interaction (DDI) example <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003778#ppat.1003778-SchulzeGahmen1" target="_blank">[43]</a>: a cyclin domain-containing protein from Saimiriine herpesvirus 2 (red) targets a human CDK6 kinase domain (white). (<b>B</b>) A domain-motif interaction (DMI) example <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003778#ppat.1003778-Lee1" target="_blank">[44]</a>: human retinoblastoma-associated protein (white) contains a linear motif-binding (LMB) domain which recognizes the peptide motif LxCxE (red) in the human papillomavirus E7 protein.</p

Coverage of human-virus protein-protein interaction network by domain-centric interaction mechanisms.

<p>Fractions of endogenous and exogenous PPIs that can be assigned to different domain-centric interaction mechanisms (DDIs and DMIs). Each mechanism is illustrated using the symbols at the left, with the percentage of interactions described by that mechanism given below. An interaction may be described by more than one interaction mechanism.</p