-
[show abstract]
[hide abstract]
ABSTRACT: 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).
Scientific Reports 01/2012; 2:239.
-
Matthew Jessulat,
Sylvain Pitre,
Yuan Gui,
Mohsen Hooshyar,
Katayoun Omidi,
Bahram Samanfar,
Le Hoa Tan,
Md Alamgir,
James Green,
Frank Dehne,
Ashkan Golshani
[show abstract]
[hide abstract]
ABSTRACT: 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.
Expert Opinion on Drug Discovery 09/2011; 6(9):921-35. · 2.12 Impact Factor
-
Mohan Babu,
Hiroyuki Aoki,
Wasimul Q Chowdhury,
Alla Gagarinova,
Chris Graham,
Sadhna Phanse,
Ben Laliberte,
Noor Sunba, Matthew Jessulat,
Ashkan Golshani,
Andrew Emili,
Jack F Greenblatt,
M Clelia Ganoza
[show abstract]
[hide abstract]
ABSTRACT: Elongation factor RbbA is required for ATP-dependent deacyl-tRNA release presumably after each peptide bond formation; however, there is no information about the cellular role. Proteomic analysis in Escherichia coli revealed that RbbA reciprocally co-purified with a conserved inner membrane protein of unknown function, YhjD. Both proteins are also physically associated with the 30S ribosome and with members of the lipopolysaccharide transport machinery. Genome-wide genetic screens of rbbA and yhjD deletion mutants revealed aggravating genetic interactions with mutants deficient in the electron transport chain. Cells lacking both rbbA and yhjD exhibited reduced cell division, respiration and global protein synthesis as well as increased sensitivity to antibiotics targeting the ETC and the accuracy of protein synthesis. Our results suggest that RbbA appears to function together with YhjD as part of a regulatory network that impacts bacterial oxidative phosphorylation and translation efficiency.
PLoS ONE 01/2011; 6(4):e18510. · 4.09 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: In addition to widespread use in reducing the symptoms of colds and flu, Echinacea is traditionally employed to treat fungal and bacterial infections. However, to date the mechanism of antimicrobial activity of Echinacea extracts remains unclear. We utilized a set of ∼4,600 viable gene deletion mutants of Saccharomyces cerevisiae to identify mutations that increase sensitivity to Echinacea. Thus, a set of chemical-genetic profiles for 16 different Echinacea treatments was generated, from which a consensus set of 23 Echinacea-sensitive mutants was identified. Of the 23 mutants, only 16 have a reported function. Ten of these 16 are involved in cell wall integrity/structure suggesting that a target for Echinacea is the fungal cell wall. Follow-up analyses revealed an increase in sonication-associated cell death in the yeasts S. cerevisiae and Cryptococcus neoformans after Echinacea extract treatments. Furthermore, fluorescence microscopy showed that Echinacea-treated S. cerevisiae was significantly more prone to cell wall damage than non-treated cells. This study further demonstrates the potential of gene deletion arrays to understand natural product antifungal mode of action and provides compelling evidence that the fungal cell wall is a target of Echinacea extracts and may thus explain the utility of this phytomedicine in treating mycoses.
Medical mycology: official publication of the International Society for Human and Animal Mycology 11/2010; 48(7):949-58. · 2.13 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: 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.
Methods in molecular biology (Clifton, N.J.) 01/2010; 587:99-111.
-
[show abstract]
[hide abstract]
ABSTRACT: 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).
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.
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.
BMC Chemical Biology 01/2010; 10:6. · 1.60 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: 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.
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.
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).
BMC Genomics 01/2009; 9:583. · 4.07 Impact Factor
-
Imelda J Galván,
Nadereh Mir-Rashed, Matthew Jessulat,
Monica Atanya,
Ashkan Golshani,
Tony Durst,
Philippe Petit,
Virginie Treyvaud Amiguet,
Teun Boekhout,
Richard Summerbell,
Isabel Cruz,
John T Arnason,
Myron L Smith
[show abstract]
[hide abstract]
ABSTRACT: Bioassay-guided fractionation of Chimaphila umbellata (L.) W. Bart (Pyrolaceae) ethanol extracts led to the identification of 2,7-dimethyl-1,4-naphthoquinone (chimaphilin) as the principal antifungal component. The structure of chimaphilin was confirmed by 1H and 13C NMR spectroscopy. The antifungal activity of chimaphilin was evaluated using the microdilution method with Saccharomyces cerevisiae (0.05mg/mL) and the dandruff-associated fungi Malassezia globosa (0.39mg/mL) and Malassezia restricta (0.55mg/mL). Pronounced antioxidant activity of C. umbellata crude extract was also identified using the DPPH (2,2-diphenyl-1-picrylhydrazyl) assay, suggesting this phytomedicine has an antioxidant function in wound healing. A chemical-genetic profile was completed with chimaphilin using approximately 4700 S. cerevisiae gene deletion mutants. Cellular roles of deleted genes in the most susceptible mutants and secondary assays indicate that the targets for chimaphilin include pathways involved in cell wall biogenesis and transcription.
Phytochemistry 03/2008; 69(3):738-46. · 3.35 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: 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.
Archives of Biochemistry and Biophysics 02/2008; 469(2):157-64. · 2.93 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Numerous functional genomics approaches have been developed to study the model organism yeast, Saccharomyces cerevisiae, with the aim of systematically understanding the biology of the cell. Some of these techniques are based on yeast growth differences under different conditions, such as those generated by gene mutations, chemicals or both. Manual inspection of the yeast colonies that are grown under different conditions is often used as a method to detect such growth differences.
Here, we developed a computerized image analysis system called Growth Detector (GD), to automatically acquire quantitative and comparative information for yeast colony growth. GD offers great convenience and accuracy over the currently used manual growth measurement method. It distinguishes true yeast colonies in a digital image and provides an accurate coordinate oriented map of the colony areas. Some post-processing calculations are also conducted. Using GD, we successfully detected a genetic linkage between the molecular activity of the plant-derived antifungal compound berberine and gene expression components, among other cellular processes. A novel association for the yeast mek1 gene with DNA damage repair was also identified by GD and confirmed by a plasmid repair assay. The results demonstrate the usefulness of GD for yeast functional genomics research.
GD offers significant improvement over the manual inspection method to detect relative yeast colony size differences. The speed and accuracy associated with GD makes it an ideal choice for large-scale functional genomics investigations.
BMC Bioinformatics 02/2007; 8:117. · 2.75 Impact Factor
