The dramatic increase of genome sequences across multiple species is exponentially increasing the number of predicted proteins with unknown function. The traditional """"""""one at a time approach"""""""" of characterizing factors will always be essential, but it helps to be able to have a global view of the functional connections between and among these proteins in order to aid in the generation of specific hypotheses. One important way to study protein function is to be able to ascertain which other proteins are associated with it. In this proposal, we aim to systematically generate a protein-protein interaction (PPI) data in the model organism, S. pombe. Next to budding yeast, the fission yeast S. pombe has the most easily manipulatable genome of any eukaryotic model organism, and yet it is evolutionarily distinct from S. cerevisiae.
We aim to generate the fission yeast PPI map using a two-pronged platform: yeast two-hybrid methodology and co-affinity purification followed by mass spectrometry (AP/MS) approach. This work brings together two individuals (Yu and Krogan) who worked together to generate the most comprehensive co-complex PPI map to date in any organism (S. cerevisiae) using the AP/MS strategy (Krogan et al., Nature, 2006). Furthermore, more recently, Yu generated the most comprehensive two-hybrid dataset to date, also in budding yeast (Yu et al., Science, 2008). Therefore, we argue that, between the two groups, we have the experimental and bioinformatic expertise to carry out a comprehensive analysis of the protein interactome in fission yeast. From a purely evolutionary standpoint, valuable information would be obtained by comparing the interactome networks from both organisms since these two yeasts diverged around 330-420 million years ago. Additionally, analysis of interaction networks in S. pombe will provide novel information that cannot be obtained from studies performed with S. cerevisiae. For example, in its large complex centromere structure, the restriction of spindle construction to mitotic entry, redundant and inefficient origins of replication, gene regulation by histone methylation and chromodomain heterochromatin proteins, gene and transposon regulation by the RNAi pathway, telomere binding proteins, and the presence of introns in most genes, S. pombe is more similar to metazoans than is S. cerevisiae. Therefore, this project will not only have a huge impact on the fission yeast field but also will fuel evolutionary studies and will allow for interrogation of biological systems that are present in higher organisms but not in budding yeast.
While our knowledge of specific disease causing pathways has been increasing rapidly, our ability to harness this knowledge for therapeutic strategies has been hampered by the complex inter-connected nature of the different proteins and pathways. In this study, we aim to generate a protein-protein interaction dataset in the model organism S. pombe which will allow for evolutionary comparison of physical interactomes across different species and will facilitate the functional interrogation of many pathways that also exist in mammalian cells, many of which are perturbed in disease states.
|Liang, Siqi; Tippens, Nathaniel D; Zhou, Yaoda et al. (2017) iRegNet3D: three-dimensional integrated regulatory network for the genomic analysis of coding and non-coding disease mutations. Genome Biol 18:10|
|Vo, Tommy V; Das, Jishnu; Meyer, Michael J et al. (2016) A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human. Cell 164:310-323|
|Meyer, Michael J; Lapcevic, Ryan; Romero, Alfonso E et al. (2016) mutation3D: Cancer Gene Prediction Through Atomic Clustering of Coding Variants in the Structural Proteome. Hum Mutat 37:447-56|
|Guo, Yu; Alexander, Katherine; Clark, Andrew G et al. (2016) Integrated network analysis reveals distinct regulatory roles of transcription factors and microRNAs. RNA 22:1663-1672|
|Meyer, Michael J; Geske, Philip; Yu, Haiyuan (2016) BISQUE: locus- and variant-specific conversion of genomic, transcriptomic and proteomic database identifiers. Bioinformatics 32:1598-600|
|Pu, Mintie; Ni, Zhuoyu; Wang, Minghui et al. (2015) Trimethylation of Lys36 on H3 restricts gene expression change during aging and impacts life span. Genes Dev 29:718-31|
|Das, Jishnu; Gayvert, Kaitlyn M; Bunea, Florentina et al. (2015) ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers. BMC Genomics 16:263|
|Bastos de Oliveira, Francisco Meirelles; Kim, Dongsung; Cussiol, José Renato et al. (2015) Phosphoproteomics reveals distinct modes of Mec1/ATR signaling during DNA replication. Mol Cell 57:1124-32|
|Das, Jishnu; Gayvert, Kaitlyn M; Yu, Haiyuan (2014) Predicting cancer prognosis using functional genomics data sets. Cancer Inform 13:85-8|
|Das, Jishnu; Fragoza, Robert; Lee, Hao Ran et al. (2014) Exploring mechanisms of human disease through structurally resolved protein interactome networks. Mol Biosyst 10:9-17|
Showing the most recent 10 out of 19 publications