Frequent Assembly of Chimeric Complexes in the Protein Interaction Network of an Interspecies Yeast Hybrid.
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ABSTRACT:
SUBMITTER: Dandage R
PROVIDER: S-EPMC8042767 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Hybridization between species is an important mechanism for the origin of novel lineages and adaptation to new environments. Increased allelic variation and modification of the transcriptional network are the two recognized forces currently deemed to be responsible for the phenotypic properties seen in hybrids. However, since the majority of the biological functions in a cell are carried out by protein complexes, inter-specific protein assemblies therefore represent another important source of natural variation upon which evolutionary forces can act. Here we studied the composition of six protein complexes in two different Saccharomyces "sensu stricto" hybrids, to understand whether chimeric interactions can be freely formed in the cell in spite of species-specific co-evolutionary forces, and whether the different types of complexes cause a change in hybrid fitness. The protein assemblies were isolated from the hybrids via affinity chromatography and identified via mass spectrometry. We found evidence of spontaneous chimericity for four of the six protein assemblies tested and we showed that different types of complexes can cause a variety of phenotypes in selected environments. In the case of TRP2/TRP3 complex, the effect of such chimeric formation resulted in the fitness advantage of the hybrid in an environment lacking tryptophan, while only one type of parental combination of the MBF complex allowed the hybrid to grow under respiratory conditions. These phenotypes were dependent on both genetic and environmental backgrounds. This study provides empirical evidence that chimeric protein complexes can freely assemble in cells and reveals a new mechanism to generate phenotypic novelty and plasticity in hybrids to complement the genomic innovation resulting from gene duplication. The ability to exchange orthologous members has also important implications for the adaptation and subsequent genome evolution of the hybrids in terms of pattern of gene loss.
| S-EPMC3789821 | biostudies-literature
Project description:Protein complexes are typically analyzed by affinity purification and subsequent mass spectrometric analysis. However, in most cases the structure and topology of the complexes remains elusive from such studies. Here we investigate how the yeast two-hybrid system can be used to analyze direct interactions among proteins in a complex. First we tested all pairwise interactions among the seven proteins of Escherichia coli DNA polymerase III as well as an uncharacterized complex that includes MntR and PerR. Four and seven interactions were identified in these two complexes, respectively. In addition, we review Y2H data for three other complexes of known structure which serve as "gold-standards", namely Varicella Zoster Virus (VZV) ribonucleotide reductase (RNR), the yeast proteasome, and bacteriophage lambda. Finally, we review an Y2H analysis of the human spliceosome which may serve as an example for a dynamic mega-complex.
| S-EPMC3517932 | biostudies-literature
Project description:To study the evolution of the yeast protein interaction network, we first classified yeast proteins by their evolutionary histories into isotemporal categories, then analyzed the interaction tendencies within and between the categories, and finally reconstructed the main growth path. We found that two proteins tend to interact with each other if they are in the same or similar categories, but tended to avoid each other otherwise, and that network evolution mirrors the universal tree of life. These observations suggest synergistic selection during network evolution and provide insights into the hierarchical modularity of cellular networks.
| S-EPMC240702 | biostudies-literature
Project description:A systems-level understanding of biological processes and information flow requires the mapping of cellular component interactions, among which protein-protein interactions are particularly important. Fission yeast (Schizosaccharomyces pombe) is a valuable model organism for which no systematic protein-interaction data are available. We exploited gene and protein properties, global genome regulation datasets, and conservation of interactions between budding and fission yeast to predict fission yeast protein interactions in silico. We have extensively tested our method in three ways: first, by predicting with 70-80% accuracy a selected high-confidence test set; second, by recapitulating interactions between members of the well-characterized SAGA co-activator complex; and third, by verifying predicted interactions of the Cbf11 transcription factor using mass spectrometry of TAP-purified protein complexes. Given the importance of the pathway in cell physiology and human disease, we explore the predicted sub-networks centered on the Tor1/2 kinases. Moreover, we predict the histidine kinases Mak1/2/3 to be vital hubs in the fission yeast stress response network, and we suggest interactors of argonaute 1, the principal component of the siRNA-mediated gene silencing pathway, lost in budding yeast but preserved in S. pombe. Of the new high-quality interactions that were discovered after we started this work, 73% were found in our predictions. Even though any predicted interactome is imperfect, the protein network presented here can provide a valuable basis to explore biological processes and to guide wet-lab experiments in fission yeast and beyond. Our predicted protein interactions are freely available through PInt, an online resource on our website (www.bahlerlab.info/PInt).
| S-EPMC3337474 | biostudies-literature
Project description:This work presents the genome sequencing of the lager brewing yeast (Saccharomyces pastorianus) Weihenstephan 34/70, a strain widely used in lager beer brewing. The 25 Mb genome comprises two nuclear sub-genomes originating from Saccharomyces cerevisiae and Saccharomyces bayanus and one circular mitochondrial genome originating from S. bayanus. Thirty-six different types of chromosomes were found including eight chromosomes with translocations between the two sub-genomes, whose breakpoints are within the orthologous open reading frames. Several gene loci responsible for typical lager brewing yeast characteristics such as maltotriose uptake and sulfite production have been increased in number by chromosomal rearrangements. Despite an overall high degree of conservation of the synteny with S. cerevisiae and S. bayanus, the syntenies were not well conserved in the sub-telomeric regions that contain lager brewing yeast characteristic and specific genes. Deletion of larger chromosomal regions, a massive unilateral decrease of the ribosomal DNA cluster and bilateral truncations of over 60 genes reflect a post-hybridization evolution process. Truncations and deletions of less efficient maltose and maltotriose uptake genes may indicate the result of adaptation to brewing. The genome sequence of this interspecies hybrid yeast provides a new tool for better understanding of lager brewing yeast behavior in industrial beer production.
| S-EPMC2673734 | biostudies-literature
Project description:BACKGROUND: Despite clinical research and development in the last decades, infectious diseases remain a top global problem in public health today, being responsible for millions of morbidities and mortalities each year. Therefore, many studies have sought to investigate host-pathogen interactions from various viewpoints in attempts to understand pathogenic and defensive mechanisms, which could help control pathogenic infections. However, most of these efforts have focused predominately on the host or the pathogen individually rather than on a simultaneous analysis of both interaction partners. RESULTS: In this study, with the help of simultaneously quantified time-course Candida albicans-zebrafish interaction transcriptomics and other omics data, a computational framework was developed to construct the interspecies protein-protein interaction (PPI) network for C. albicans-zebrafish interactions based on the inference of ortholog-based PPIs and the dynamic modeling of regulatory responses. The identified C. albicans-zebrafish interspecies PPI network highlights the association between C. albicans pathogenesis and the zebrafish redox process, indicating that redox status is critical in the battle between the host and pathogen. CONCLUSIONS: Advancing from the single-species network construction method, the interspecies network construction approach allows further characterization and elucidation of the host-pathogen interactions. With continued accumulation of interspecies transcriptomics data, the proposed method could be used to explore progressive network rewiring over time, which could benefit the development of network medicine for infectious diseases.
| S-EPMC3751520 | biostudies-literature
Project description:BackgroundDynamic protein-protein interaction networks (DPPIN) can confirm the conditional and temporal features of proteins and protein complexes. In addition, the relation of protein complexes in dynamic networks can provide useful information in understanding the dynamic functionality of PPI networks.ObjectiveIn this paper, an algorithm is presented to discover the temporal association rule from the dynamic PPIN dataset.Material and methodsIn this analytical study, the static protein-protein interaction network is transformed into a dynamic network using the gene expression thresholding to extract the protein complex relations. The number of presented proteins of the dynamic network is large at each time point. This number will increase for extraction of multidimensional rules at different times. By mapping the gold standard protein complexes as reference protein complexes, the number of items decreases from active proteins to protein complexes at each transaction. Extracted sub graphs as protein complexes, at each time point, are weighted according to the reference protein complexes similarity degrees. Mega-transactions and extended items are created based on occurrence bitmap matrix of the reference complexes. Rules will be extracted based on Mega-transactions of protein complexes.ResultsThe proposed method has been evaluated using gold standard protein complex rules. The amount of extracted rules from Biogrid datasets and protein complexes are 281, with support 0.2.ConclusionThe characteristic of the proposed algorithm is the simultaneous extraction of intra-transaction and inter-transaction rules. The results evaluation using EBI data shows the efficiency of the proposed algorithm.
| S-EPMC8649159 | biostudies-literature
Project description:Many cellular functions are mediated by protein-protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment-dependent protein complex dynamics, we used a DNA-barcode-based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that "concerted" protein-centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass-action-based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.
| S-EPMC5527849 | biostudies-literature
Project description:BackgroundThe recently emerged protein interaction network paradigm can provide novel and important insights into the innerworkings of a cell. Yet, the heavy burden of both false positive and false negative protein-protein interaction data casts doubt on the broader usefulness of these interaction sets. Approaches focusing on one-protein-at-a-time have been powerfully employed to demonstrate the high degree of conservation of proteins participating in numerous interactions; here, we expand his 'node' focused paradigm to investigate the relative persistence of 'link' based evolutionary signals in a protein interaction network of S. cerevisiae and point out the value of this relatively untapped source of information.ResultsThe trend for highly connected proteins to be preferably conserved in evolution is stable, even in the context of tremendous noise in the underlying protein interactions as well as in the assignment of orthology among five higher eukaryotes. We find that local clustering around interactions correlates with preferred evolutionary conservation of the participating proteins; furthermore the correlation between high local clustering and evolutionary conservation is accompanied by a stable elevated degree of coexpression of the interacting proteins. We use this conserved interaction data, combined with P. falciparum/Yeast orthologs, as proof-of-principle that high-order network topology can be used comparatively to deduce local network structure in non-model organisms.ConclusionHigh local clustering is a criterion for the reliability of an interaction and coincides with preferred evolutionary conservation and significant coexpression. These strong and stable correlations indicate that evolutionary units go beyond a single protein to include the interactions among them. In particular, the stability of these signals in the face of extreme noise suggests that empirical protein interaction data can be integrated with orthologous clustering around these protein interactions to reliably infer local network structures in non-model organisms.
| S-EPMC1395346 | biostudies-literature
Project description:BACKGROUND: The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4). Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. RESULTS: We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. CONCLUSIONS: We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.
| S-EPMC3215679 | biostudies-literature