Michael A. Calderwood

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype–phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or ‘passenger’, cancer mutations from causal, or ‘driver’, mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Viral perturbations of host networks reflect disease etiology.

Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases), are also associated with viral infections (virally implicated diseases), either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV) and human papillomavirus (HPV), we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.

Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism.

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.

Genome-Wide Analysis of Epstein-Barr Virus Rta DNA Binding

ABSTRACT The Epstein-Barr virus (EBV) lytic transactivator Rta activates promoters through direct binding to cognate DNA sites termed Rta response elements (RREs). Rta also activates promoters that apparently lack Rta binding sites, notably Zp and Rp. Chromatin immunoprecipitation (ChIP) of endogenous Rta expressed during early replication in B95-8 cells was performed to identify Rta binding sites in the EBV genome. Quantitative PCR (qPCR) analysis showed strong enrichment for known RREs but little or no enrichment for Rp or Zp, suggesting that the Rta ChIP approach enriches for direct Rta binding sites. Rta ChIP combined with deep sequencing (ChIP-seq) identified most known RREs and several novel Rta binding sites. Rta ChIP-seq peaks were frequently upstream of Rta-responsive genes, indicating that these Rta binding sites are likely functioning as RREs. Unexpectedly, the BALF5 promoter contained an Rta binding peak. To assess whether BALF5 might be activated by an RRE-dependent mechanism, an Rta mutant (Rta K156A), deficient for DNA binding and RRE activation but competent for Zp/Rp activation, was used. Rta K156A failed to activate BALF5p, suggesting this promoter can be activated by an RRE-dependent mechanism. Rta binding to late gene promoters was not seen at early time points but was specifically detected at later times within the Rta-responsive BLRF2 and BFRF3 promoters, even when DNA replication was inhibited. Our results represent the first characterization of Rta binding to the EBV genome during replication, identify previously unknown RREs, such as one in BALF5p, and highlight the complexity of EBV late gene promoter activation by Rta.

Pooled-matrix protein interaction screens using Barcode Fusion Genetics

High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Two‐Hybrid (BFG‐Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG‐Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein‐pair barcodes that can be quantified via next‐generation sequencing. We applied BFG‐Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG‐Y2H increases the efficiency of protein matrix screening, with quality that is on par with state‐of‐the‐art Y2H methods.

The EBNA3 Family of Epstein-Barr Virus Nuclear Proteins Associates with the USP46/USP12 Deubiquitination Complexes to Regulate Lymphoblastoid Cell Line Growth

The Epstein-Barr virus (EBV) nuclear proteins EBNA3A, EBNA3B, and EBNA3C interact with the cell DNA binding protein RBPJ and regulate cell and viral genes. Repression of the CDKN2A tumor suppressor gene products p16INK4A and p14ARF by EBNA3A and EBNA3C is critical for EBV mediated transformation of resting B lymphocytes into immortalized lymphoblastoid cell lines (LCLs). To define the composition of endogenous EBNA3 protein complexes, we generated lymphoblastoid cell lines (LCLs) expressing flag-HA tagged EBNA3A, EBNA3B, or EBNA3C and used tandem affinity purification to isolate each EBNA3 complex. Our results demonstrated that each EBNA3 protein forms a distinct complex with RBPJ. Mass-spectrometry revealed that the EBNA3A and EBNA3B complexes also contained the deubquitylation complex consisting of WDR48, WDR20, and USP46 (or its paralog USP12) and that EBNA3C complexes contained WDR48. Immunoprecipitation confirmed that EBNA3A, EBNA3B, and EBNA3C association with the USP46 complex. Using chromatin immunoprecipitation, we demonstrate that WDR48 and USP46 are recruited to the p14ARF promoter in an EBNA3C dependent manner. Mapping studies were consistent with WDR48 being the primary mediator of EBNA3 association with the DUB complex. By ChIP assay, WDR48 was recruited to the p14ARF promoter in an EBNA3C dependent manner. Importantly, WDR48 associated with EBNA3A and EBNA3C domains that are critical for LCL growth, suggesting a role for USP46/USP12 in EBV induced growth transformation.

An inter-species protein-protein interaction network across vast evolutionary distance.

In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical‐versus‐functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an “inter‐interactome” approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter‐interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra‐species networks. Although substantially reduced relative to intra‐species networks, the levels of functional overlap in the yeast–human inter‐interactome network uncover significant remnants of co‐functionality widely preserved in the two proteomes beyond human–yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co‐functionality. Such non‐functional interactions, however, represent a reservoir from which nascent functional interactions may arise.

An RS Motif within the Epstein-Barr Virus BLRF2 Tegument Protein Is Phosphorylated by SRPK2 and Is Important for Viral Replication

Epstein-Barr virus (EBV) is a gammaherpesvirus that causes infectious mononucleosis, B cell lymphomas, and nasopharyngeal carcinoma. Many of the genes required for EBV virion morphogenesis are found in all herpesviruses, but some are specific to gammaherpesviruses. One of these gamma-specific genes, BLRF2, encodes a tegument protein that has been shown to be essential for replication in other gammaherpesviruses. In this study, we identify BLRF2 interacting proteins using binary and co-complex protein assays. Serine/Arginine-rich Protein Kinase 2 (SRPK2) was identified by both assays and was further shown to phosphorylate an RS motif in the BLRF2 C-terminus. Mutation of this RS motif (S148A+S150A) abrogated the ability of BLRF2 to support replication of a murine gammaherpesvirus 68 genome lacking the BLRF2 homolog (ORF52). We conclude that the BLRF2 RS motif is phosphorylated by SRPK2 and is important for viral replication.

Chapter 3 – Interactome Networks

Anne-Ruxandra Carvunis, Frederick P. Roth, Michael A. Calderwood, Michael E. Cusick, Giulio Superti-Furga and Marc Vidal Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA, Department of Genetics, Harvard Medical School, Boston, MA 02115, USA, Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario M5S-3E1, Canada, & Samuel Lunenfeld Research Institute, Mt. Sinai Hospital, Toronto, Ontario M5G-1X5, Canada, Research Center for

Network-based prediction of protein interactions

As biological function emerges through interactions between a cell’s molecular constituents, understanding cellular mechanisms requires us to catalogue all physical interactions between proteins [1–4]. Despite spectacular advances in high-throughput mapping, the number of missing human protein-protein interactions (PPIs) continues to exceed the experimentally documented interactions [5, 6]. Computational tools that exploit structural, sequence or network topology information are increasingly used to fill in the gap, using the patterns of the already known interactome to predict undetected, yet biologically relevant interactions [7–9]. Such network-based link prediction tools rely on the Triadic Closure Principle (TCP) [10–12], stating that two proteins likely interact if they share multiple interaction partners. TCP is rooted in social network analysis, namely the observation that the more common friends two individuals have, the more likely that they know each other [13, 14]. Here, we offer direct empirical evidence across multiple datasets and organisms that, despite its dominant use in biological link prediction, TCP is not valid for most protein pairs. We show that this failure is fundamental - TCP violates both structural constraints and evolutionary processes. This understanding allows us to propose a link prediction principle, consistent with both structural and evo-lutionary arguments, that predicts yet uncovered protein interactions based on paths of length three (L3). A systematic computational cross-validation shows that the L3 principle significantly outperforms existing link prediction methods. To experimentally test the L3 predictions, we perform both large-scale high-throughput and pairwise tests, finding that the predicted links test positively at the same rate as previously known interactions, suggesting that most (if not all) predicted interactions are real. Combining L3 predictions with experimen-tal tests provided new interaction partners of FAM161A, a protein linked to retinitis pigmentosa, offering novel insights into the molecular mechanisms that lead to the disease. Because L3 is rooted in a fundamental biological principle, we expect it to have a broad applicability, enabling us to better understand the emergence of biological function under both healthy and pathological conditions. Summary We unveil a fundamental organizing principle of biological networks and demonstrate its predictive power for uncovering novel protein interactions.