Mohsen Hooshyar

Short Co-occurring Polypeptide Regions Can Predict Global Protein Interaction Maps

A goal of the post-genomics era has been to elucidate a detailed global map of protein-protein interactions (PPIs) within a cell. Here, we show that the presence of co-occurring short polypeptide sequences between interacting protein partners appears to be conserved across different organisms. We present an algorithm to automatically generate PPI prediction method parameters for various organisms and illustrate that global PPIs can be predicted from previously reported PPIs within the same or a different organism using protein primary sequences. The PPI prediction code is further accelerated through the use of parallel multi-core programming, which improves its usability for large scale or proteome-wide PPI prediction. We predict and analyze hundreds of novel human PPIs, experimentally confirm protein functions and importantly predict the first genome-wide PPI maps for S. pombe (∼9,000 PPIs) and C. elegans (∼37,500 PPIs).

Recent advances in protein-protein interaction prediction: experimental and computational methods.

Introduction: Proteins within the cell act as part of complex networks, which allow pathways and processes to function. Therefore, understanding how proteins interact is a significant area of current research. Areas covered: This review aims to present an overview of key experimental techniques (yeast two-hybrid, tandem affinity purification and protein microarrays) used to discover protein–protein interactions (PPIs), as well as to briefly discuss certain computational methods for predicting protein interactions based on gene localization, phylogenetic information, 3D structural modeling or primary protein sequence data. Due to the large-scale applicability of primary sequence-based methods, the authors have chosen to focus on this strategy for our review. There is an emphasis on a recent algorithm called Protein Interaction Prediction Engine (PIPE) that can predict global PPIs. The readers will discover recent advances both in the practical determination of protein interaction and the strategies that are available to attempt to anticipate interactions without the time and costs of experimental work. Expert opinion: Global PPI maps can help understand the biology of complex diseases and facilitate the identification of novel drug target sites. This study describes different techniques used for PPI prediction that we believe will significantly impact the development of the field in a new future. We expect to see a growing number of similar techniques capable of large-scale PPI predictions.

Conditional Epistatic Interaction Maps Reveal Global Functional Rewiring of Genome Integrity Pathways in Escherichia coli

As antibiotic resistance is increasingly becoming a public health concern, an improved understanding of the bacterial DNA damage response (DDR), which is commonly targeted by antibiotics, could be of tremendous therapeutic value. Although the genetic components of the bacterial DDR have been studied extensively in isolation, how the underlying biological pathways interact functionally remains unclear. Here, we address this by performing systematic, unbiased, quantitative synthetic genetic interaction (GI) screens and uncover widespread changes in the GI network of the entire genomic integrity apparatus of Escherichia coli under standard and DNA-damaging growth conditions. The GI patterns of untreated cultures implicated two previously uncharacterized proteins (YhbQ and YqgF) as nucleases, whereas reorganization of the GI network after DNA damage revealed DDR roles for both annotated and uncharacterized genes. Analyses of pan-bacterial conservation patterns suggest that DDR mechanisms and functional relationships are near universal, highlighting a modular and highly adaptive genomic stress response.

Phosphatase complex Pph3/Psy2 is involved in regulation of efficient non-homologous end-joining pathway in the yeast Saccharomyces cerevisiae.

One of the main mechanisms for double stranded DNA break (DSB) repair is through the non-homologous end-joining (NHEJ) pathway. Using plasmid and chromosomal repair assays, we showed that deletion mutant strains for interacting proteins Pph3p and Psy2p had reduced efficiencies in NHEJ. We further observed that this activity of Pph3p and Psy2p appeared linked to cell cycle Rad53p and Chk1p checkpoint proteins. Pph3/Psy2 is a phosphatase complex, which regulates recovery from the Rad53p DNA damage checkpoint. Overexpression of Chk1p checkpoint protein in a parallel pathway to Rad53p compensated for the deletion of PPH3 or PSY2 in a chromosomal repair assay. Double mutant strains Δpph3/Δchk1 and Δpsy2/Δchk1 showed additional reductions in the efficiency of plasmid repair, compared to both single deletions which is in agreement with the activity of Pph3p and Psy2p in a parallel pathway to Chk1p. Genetic interaction analyses also supported a role for Pph3p and Psy2p in DNA damage repair, the NHEJ pathway, as well as cell cycle progression. Collectively, we report that the activity of Pph3p and Psy2p further connects NHEJ repair to cell cycle progression.

Spindle Checkpoint Factors Bub1 and Bub2 Promote DNA Double-Strand Break Repair by Nonhomologous End Joining.

ABSTRACT The nonhomologous end-joining (NHEJ) pathway is essential for the preservation of genome integrity, as it efficiently repairs DNA double-strand breaks (DSBs). Previous biochemical and genetic investigations have indicated that, despite the importance of this pathway, the entire complement of genes regulating NHEJ remains unknown. To address this, we employed a plasmid-based NHEJ DNA repair screen in budding yeast (Saccharomyces cerevisiae) using 369 putative nonessential DNA repair-related components as queries. Among the newly identified genes associated with NHEJ deficiency upon disruption are two spindle assembly checkpoint kinases, Bub1 and Bub2. Both observation of resulting phenotypes and chromatin immunoprecipitation demonstrated that Bub1 and -2, either alone or in combination with cell cycle regulators, are recruited near the DSB, where phosphorylated Rad53 or H2A accumulates. Large-scale proteomic analysis of Bub kinases phosphorylated in response to DNA damage identified previously unknown kinase substrates on Tel1 S/T-Q sites. Moreover, Bub1 NHEJ function appears to be conserved in mammalian cells. 53BP1, which influences DSB repair by NHEJ, colocalizes with human BUB1 and is recruited to the break sites. Thus, while Bub is not a core component of NHEJ machinery, our data support its dual role in mitotic exit and promotion of NHEJ repair in yeast and mammals.

In vivo investigation of protein-protein interactions for helicases using tandem affinity purification.

A key component in determining the functional role of any protein is the elucidation of its binding partners using protein-protein interaction (PPI) data. Here we examine the use of tandem affinity purification (TAP) tagging to study RNA/DNA helicase PPIs in Escherichia coli. The tag, which consists of a calmodulin-binding region, a TEV protease recognition sequence, and an IgG-binding domain, is introduced into E. coli using a lambdared recombination system. This method prevents the overproduction of the target protein, which could generate false interactions. The interacting proteins are then affinity purified using double affinity purification steps and are separated by SDS-PAGE followed by mass spectrometry identification. Each protein identified would represent a physical interaction in the cell. These interactions may potentially be mediated by an RNA/DNA template, for which the helicase would likely be needed to disrupt the secondary structures.

The sensitivity of the yeast, Saccharomyces cerevisiae, to acetic acid is influenced by DOM34 and RPL36A

The presence of acetic acid during industrial alcohol fermentation reduces the yield of fermentation by imposing additional stress on the yeast cells. The biology of cellular responses to stress has been a subject of vigorous investigations. Although much has been learned, details of some of these responses remain poorly understood. Members of heat shock chaperone HSP proteins have been linked to acetic acid and heat shock stress responses in yeast. Both acetic acid and heat shock have been identified to trigger different cellular responses including reduction of global protein synthesis and induction of programmed cell death. Yeast HSC82 and HSP82 code for two important heat shock proteins that together account for 1–2% of total cellular proteins. Both proteins have been linked to responses to acetic acid and heat shock. In contrast to the overall rate of protein synthesis which is reduced, the expression of HSC82 and HSP82 is induced in response to acetic acid stress. In the current study we identified two yeast genes DOM34 and RPL36A that are linked to acetic acid and heat shock sensitivity. We investigated the influence of these genes on the expression of HSP proteins. Our observations suggest that Dom34 and RPL36A influence translation in a CAP-independent manner.

Designing anti-Zika virus peptides derived from predicted human-Zika virus protein-protein interactions

The production of anti-Zika virus (ZIKV) therapeutics has become increasingly important as the propagation of the devastating virus continues largely unchecked. Notably, a causal relationship between ZIKV infection and neurodevelopmental abnormalities has been widely reported, yet a specific mechanism underlying impaired neurological development has not been identified. Here, we report on the design of several synthetic competitive inhibitory peptides against key pathogenic ZIKV proteins through the prediction of protein-protein interactions (PPIs). Often, PPIs between host and viral proteins are crucial for infection and pathogenesis, making them attractive targets for therapeutics. Using two complementary sequence-based PPI prediction tools, we first produced a comprehensive map of predicted human-ZIKV PPIs (involving 209 human protein candidates). We then designed several peptides intended to disrupt the corresponding host-pathogen interactions thereby acting as anti-ZIKV therapeutics. The data generated in this study constitute a foundational resource to aid in the multi-disciplinary effort to combat ZIKV infection, including the design of additional synthetic proteins.

Uncharacterized ORF HUR1 influences the efficiency of non-homologous end-joining repair in Saccharomyces cerevisiae

Non-Homologous End Joining (NHEJ) is a highly conserved pathway that repairs Double-Strand Breaks (DSBs) within DNA. Here we show that the deletion of yeast uncharacterized ORF HUR1, Hydroxyurea Resistance1 affects the efficiency of NHEJ. Our findings are supported by Protein-Protein Interaction (PPI), genetic interaction and drug sensitivity analyses. To assess the activity of HUR1 in DSB repair, we deleted its non-overlapping region with PMR1, referred to as HUR1-A. We observed that similar to deletion of TPK1 and NEJ1, and unlike YKU70 (important for NHEJ of DNA with overhang and not blunt end), deletion of HUR1-A reduced the efficiency of NHEJ in both overhang and blunt end plasmid repair assays. Similarly, a chromosomal repair assay showed a reduction for repair efficiency when HUR1-A was deleted. In agreement with a functional connection for Hur1p with Tpk1p and NEJ1p, double mutant strains Δhur1-A/Δtpk1, and Δhur1-A/Δnej1 showed the same reduction in the efficiency of plasmid repair, compared to both single deletion strains. Also, using a Homologous Recombination (HR) specific plasmid-based DSB repair assay we observed that deletion of HUR1-A influenced the efficiency of HR repair, suggesting that HUR1 might also play additional roles in other DNA repair pathways.

Evolution of protein-protein interaction networks in yeast

Interest in the evolution of protein-protein and genetic interaction networks has been rising in recent years, but the lack of large-scale high quality comparative datasets has acted as a barrier. Here, we carried out a comparative analysis of computationally predicted protein-protein interaction (PPI) networks from five closely related yeast species. We used the Protein-protein Interaction Prediction Engine (PIPE), which uses a database of known interactions to make sequence-based PPI predictions, to generate high quality predicted interactomes. Simulated proteomes and corresponding PPI networks were used to provide null expectations for the extent and nature of PPI network evolution. We found strong evidence for conservation of PPIs, with lower than expected levels of change in PPIs for about a quarter of the proteome. Furthermore, we found that changes in predicted PPI networks are poorly predicted by sequence divergence. Our analyses identified a number of functional classes experiencing fewer PPI changes than expected, suggestive of purifying selection on PPIs. Our results demonstrate the added benefit of considering predicted PPI networks when studying the evolution of closely related organisms.