Explore the vast range of titles available.

Protein complexes are key macromolecular machines of the cell, but their description remains incomplete. We and others previously reported an experimental strategy for global characterization of native protein assemblies based on chromatographic fractionation of biological extracts coupled to precision mass spectrometry analysis (chromatographic fractionation–mass spectrometry, CF–MS), but the resulting data are challenging to process and interpret. Here, we describe EPIC (elution profile-based inference of complexes), a software toolkit for automated scoring of large-scale CF–MS data to define high-confidence multi-component macromolecules from diverse biological specimens. As a case study, we used EPIC to map the global interactome of Caenorhabditis elegans, defining 612 putative worm protein complexes linked to diverse biological processes. These included novel subunits and assemblies unique to nematodes that we validated using orthogonal methods. The open source EPIC software is freely available as a Jupyter notebook packaged in a Docker container (https://hub.docker.com/r/baderlab/bio-epic/).

The apicomplexan intracellular parasite Toxoplasma gondii is a major food borne pathogen that is highly prevalent in the global population. The majority of the T . gondii proteome remains uncharacterized and the organization of proteins into complexes is unclear. To overcome this knowledge gap, we used a biochemical fractionation strategy to predict interactions by correlation profiling. To overcome the deficit of high-quality training data in non-model organisms, we complemented a supervised machine learning strategy, with an unsupervised approach, based on similarity network fusion. The resulting combined high confidence network, ToxoNet, comprises 2,063 interactions connecting 652 proteins. Clustering identifies 93 protein complexes. We identified clusters enriched in mitochondrial machinery that include previously uncharacterized proteins that likely represent novel adaptations to oxidative phosphorylation. Furthermore, complexes enriched in proteins localized to secretory organelles and the inner membrane complex, predict additional novel components representing novel targets for detailed functional characterization. We present ToxoNet as a publicly available resource with the expectation that it will help drive future hypotheses within the research community.

Protein complexes are key macromolecular machines of the cell, but their description remains incomplete. Our group and others previously reported an experimental strategy for global characterization of native protein assemblies based on chromatographic fractionation of biological extracts coupled to precision mass spectrometry analysis (chromatographic fractionation–mass spectrometry, CF–MS), but the resulting data are challenging to process and interpret. In this thesis, I describe EPIC (elution profile-based inference of complexes), a software toolkit for automated scoring of large-scale CF–MS data to define high-confidence multi-component macromolecules from diverse biological specimens. The software toolkit EPIC is “plug-and-play”, connects to public repositories for automatic data processing, and can be adopted productively to explore the network biology of any model system with little computational expertise required. The optimized CF-MS pipeline and EPIC data analysis workflows described in this thesis can be used to study different biological specimens, including diverse model organisms, to chart protein complexes on a global scale to expand our knowledge of macromolecular networks and their association with physiology, development, evolution and disease. Beyond providing a powerful framework to interpret CF-MS data, as a case study, I used EPIC to map the global interactome of Caenorhabditis elegans (WormMap), an important genetic model, comprising 612 putative multi-protein complexes linked to diverse biological processes. These encompassed new subunits for previously annotated protein complexes as well as novel assemblies seemingly unique to nematodes that we verified using stringent benchmarking criteria as well as by independent orthogonal affinity-purification mass spectrometry validation experiments. To my knowledge, this is the first biochemically-based large-scale map of nematode protein complexes, which provides a rich platform for hypothesis-driven mechanistic investigations of animal biology. The major two outcomes of this dissertation consist of a tool (EPIC) and a knowledgebase (WormMap), which should serve as lasting resources for the broader biological research community.

Synechocystis sp. PCC 6803 is a model organism for studying photosynthesis, energy metabolism, and environmental stress. Though known as the first fully sequenced phototrophic organism, Synechocystis sp. PCC 6803 still has almost half of its proteome without functional annotations. In this study, we obtained 291 protein complexes, including 24,092 protein-protein interactions (PPIs) among 2,062 proteins by using co-fractionation and LC/MS/MS. The additional level of PPIs information not only revealed the roles of photosynthesis in metabolism, cell motility, DNA repair, cell division, and other physiological processes, but also showed how protein functions vary from bacteria to higher plants due to the changed interaction partner. It also allows us to uncover functions of hypothetical proteins, such as Sll0445, Sll0446, Sll0447 participating in photosynthesis and cell motility, and Sll1334 regulating the expression of fatty acid. Here we presented the most extensive protein interaction data in Synechocystis so far, which might provide critical insights into the fundamental molecular mechanism in Cyanobacterium.

Drug Mechanism of Action (MoA) is generally represented as a small repertoire of tissue-independent, high-affinity binding targets. Yet, drug activity and polypharmacology are associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have generated a compendium of drug perturbation profiles for >700 oncology drugs in cell lines representing high-fidelity models of 23 aggressive tumor subtypes and developed an integrative computational framework for the proteome-wide assessment of drug-mediated, tissue-specific differential protein activity. This allows systematic, mechanism-based elucidation of tissue context-specific compound MoA and polypharmacology, including discovery and experimental validation of post-translationally-mediated inhibition of undruggable oncoproteins-such as MYC, CTNNB1, CENPF and UHRF1-as well as previously unknown inhibitors of MAPK, PI3K, and folate pathways, among others, as further suggested by protein structure analysis. This framework can help characterize the MoA of discovery compound libraries, thus supporting more systematic and quantitative approaches to precision oncology.

Polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) are pathologically activated neutrophils that potently impair immunotherapy responses. The chemokine receptor CXCR4, a central regulator of hematopoiesis, represents an attractive PMN-MDSC target1. Here, we fused a secreted CXCR4 partial agonist TFF2 to mouse serum albumin (MSA) and demonstrated that TFF2-MSA peptide synergized with anti-PD-1 to induce tumor regression or eradication, inhibited distant metastases, and prolonged survival in multiple gastric cancer (GC) models. Using histidine decarboxylase (Hdc)-GFP transgenic mice to track PMN-MDSC , we found TFF2-MSA selectively reduced the immunosuppressive Hdc-GFP CXCR4 tumor PMN-MDSCs while preserving proinflammatory neutrophils, thereby boosting CD8 T cell-mediated anti-tumor response together with anti-PD-1. Furthermore, TFF2-MSA systemically reduced PMN-MDSCs and bone marrow granulopoiesis. In contrast, CXCR4 antagonism plus anti-PD-1 failed to provide a similar therapeutic benefit. In GC patients, expanded PMN-MDSCs containing a prominent CXCR4 LOX-1 subset are inversely correlated with the TFF2 level and CD8 T cells in circulation. Collectively, our studies introduce a strategy of using CXCR4 partial agonism to restore anti-PD-1 sensitivity in GC by targeting PMN-MDSCs and granulopoiesis.