Efficient prediction of human protein-protein interactions at a global scale.

BACKGROUND: Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods. RESULTS: On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments. CONCLUSIONS: The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.

Genetic interaction maps in Escherichia coli reveal functional crosstalk among cell envelope biogenesis pathways.

As the interface between a microbe and its environment, the bacterial cell envelope has broad biological and clinical significance. While numerous biosynthesis genes and pathways have been identified and studied in isolation, how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear. To this end, we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic (rich medium) and prototrophic (minimal medium) culture conditions. The differential patterns of genetic interactions detected among > 235,000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance. These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria (including pathogens) and an important target.

Chemical-genetic profile analysis in yeast suggests that a previously uncharacterized open reading frame, YBR261C, affects protein synthesis.

BACKGROUND: Functional genomics has received considerable attention in the post-genomic era, as it aims to identify function(s) for different genes. One way to study gene function is to investigate the alterations in the responses of deletion mutants to different stimuli. Here we investigate the genetic profile of yeast non-essential gene deletion array (yGDA, approximately 4700 strains) for increased sensitivity to paromomycin, which targets the process of protein synthesis. RESULTS: As expected, our analysis indicated that the majority of deletion strains (134) with increased sensitivity to paromomycin, are involved in protein biosynthesis. The remaining strains can be divided into smaller functional categories: metabolism (45), cellular component biogenesis and organization (28), DNA maintenance (21), transport (20), others (38) and unknown (39). These may represent minor cellular target sites (side-effects) for paromomycin. They may also represent novel links to protein synthesis. One of these strains carries a deletion for a previously uncharacterized ORF, YBR261C, that we term TAE1 for Translation Associated Element 1. Our focused follow-up experiments indicated that deletion of TAE1 alters the ribosomal profile of the mutant cells. Also, gene deletion strain for TAE1 has defects in both translation efficiency and fidelity. Miniaturized synthetic genetic array analysis further indicates that TAE1 genetically interacts with 16 ribosomal protein genes. Phenotypic suppression analysis using TAE1 overexpression also links TAE1 to protein synthesis. CONCLUSION: We show that a previously uncharacterized ORF, YBR261C, affects the process of protein synthesis and reaffirm that large-scale genetic profile analysis can be a useful tool to study novel gene function(s).

Interacting proteins Rtt109 and Vps75 affect the efficiency of non-homologous end-joining in Saccharomyces cerevisiae.

One of the key pathways for DNA double-stranded break (DSB) repair is the non-homologous end-joining (NHEJ) pathway, which directly re-ligates two broken ends of DNA. Using a plasmid repair assay screen, we identified that the deletion strain for RTT109 had a reduced efficiency for NHEJ in yeast. This deletion strain also had a reduced efficiency to repair induced chromosomal DSBs in vivo. Tandem-affinity purification of Rtt109 recovered Vps75 as a physical interacting protein. Deletion of VPS75 was also shown to have an effect on the efficiency of NHEJ in both the plasmid repair and the chromosomal repair assays. In addition, deletion mutants for both RTT109 and VPS75 showed hypersensitivity to different DNA damaging agents. Our genetic interaction analysis supports a role for RTT109 in DNA damage repair. We propose that one function of the Rtt109-Vps75 interacting protein pair is to affect the efficiency of NHEJ in yeast. Vps75 but not Rtt109 also seem to have an effect on the efficiency of DSB repair using homologous recombination.

Computational methods for predicting protein-protein interactions.

Protein-protein interactions (PPIs) play a critical role in many cellular functions. A number of experimental techniques have been applied to discover PPIs; however, these techniques are expensive in terms of time, money, and expertise. There are also large discrepancies between the PPI data collected by the same or different techniques in the same organism. We therefore turn to computational techniques for the prediction of PPIs. Computational techniques have been applied to the collection, indexing, validation, analysis, and extrapolation of PPI data. This chapter will focus on computational prediction of PPI, reviewing a number of techniques including PIPE, developed in our own laboratory. For comparison, the conventional large-scale approaches to predict PPIs are also briefly discussed. The chapter concludes with a discussion of the limitations of both experimental and computational methods of determining PPIs.

A global investigation of gene deletion strains that affect premature stop codon bypass in yeast, Saccharomyces cerevisiae.

Protein biosynthesis is an orderly process that requires a balance between rate and accuracy. To produce a functional product, the fidelity of this process has to be maintained from start to finish. In order to systematically identify genes that affect stop codon bypass, three expression plasmids, pUKC817, pUKC818 and pUKC819, were integrated into the yeast non-essential loss-of-function gene array (5000 strains). These plasmids contain three different premature stop codons (UAA, UGA and UAG, respectively) within the LacZ expression cassette. A fourth plasmid, pUKC815 that carries the native LacZ gene was used as a control. Transformed strains were subjected to large-scale ß-galactosidase lift assay analysis to evaluate production of ß-galactosidase for each gene deletion strain. In this way 84 potential candidate genes that affect stop codon bypass were identified. Three candidate genes, OLA1, BSC2, and YNL040W, were further investigated, and were found to be important for cytoplasmic protein biosynthesis.

Large-scale investigation of oxygen response mutants in Saccharomyces cerevisiae.

A genome-wide screen of a yeast non-essential gene-deletion library was used to identify sick phenotypes due to oxygen deprivation. The screen provided a manageable list of 384 potentially novel as well as known oxygen responding (anoxia-survival) genes. The gene-deletion mutants were further assayed for sensitivity to ferrozine and cobalt to obtain a subset of 34 oxygen-responsive candidate genes including the known hypoxic gene activator, MGA2. With each mutant in this subset a plasmid based ß-galactosidase assay was performed using the anoxic-inducible promoter from OLE1 gene, and 17 gene deletions were identified that inhibit induction under anaerobic conditions. Genetic interaction analysis for one of these mutants, the RNase-encoding POP2 gene, revealed synthetic sick interactions with a number of genes involved in oxygen sensing and response. Knockdown experiments for CNOT8, human homolog of POP2, reduced cell survival under low oxygen condition suggesting a similar function in human cells.

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.

Chemical-genetic profile analysis of five inhibitory compounds in yeast.

BACKGROUND: Chemical-genetic profiling of inhibitory compounds can lead to identification of their modes of action. These profiles can help elucidate the complex interactions between small bioactive compounds and the cell machinery, and explain putative gene function(s). RESULTS: Colony size reduction was used to investigate the chemical-genetic profile of cycloheximide, 3-amino-1,2,4-triazole, paromomycin, streptomycin and neomycin in the yeast Saccharomyces cerevisiae. These compounds target the process of protein biosynthesis. More than 70,000 strains were analyzed from the array of gene deletion mutant yeast strains. As expected, the overall profiles of the tested compounds were similar, with deletions for genes involved in protein biosynthesis being the major category followed by metabolism. This implies that novel genes involved in protein biosynthesis could be identified from these profiles. Further investigations were carried out to assess the activity of three profiled genes in the process of protein biosynthesis using relative fitness of double mutants and other genetic assays. CONCLUSION: Chemical-genetic profiles provide insight into the molecular mechanism(s) of the examined compounds by elucidating their potential primary and secondary cellular target sites. Our follow-up investigations into the activity of three profiled genes in the process of protein biosynthesis provided further evidence concerning the usefulness of chemical-genetic analyses for annotating gene functions. We termed these genes TAE2, TAE3 and TAE4 for translation associated elements 2-4.

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.