Unraveling the mammalian secretory pathway through systems biology data analysis and algorithm development. The mammalian secretory system is key to organismal development, cell-cell communication, and all other cellular functions, since the pathway is the biosynthetic route for thousands of secreted hormones, extracellular matrix modifiers, membrane proteins, and glycans. Its central role also makes it a hub for disease. Alzheimer's disease is associated with plaques formed from proteins that are misfolded in the secretory pathway. Cancer cells alter their microenvironment through the secretion of growth factors and modification of cell surface glycans. Many infectious diseases interact with membrane proteins and glycans during the infection process. While the secretory pathway has been studied extensively for more than a century, the complexity of the system has made it difficult to unravel how thousands of chaperonins, enzymes, transporters, glycans, metabolites, lipids, and RNAs function together to influence health and disease. The goal of this proposed research program is to develop a detailed knowledge base of the secretory pathway and to develop algorithms and tools to use the network for data visualization, analysis, and model simulations, thereby enabling researchers to elucidate how each component influences the system. We will further to apply these tools with large scale single and dual sgRNA/CRISPR screens in order to elucidate novel interactions and mechanisms regulating protein secretion. Specifically, (i) the knowledge base will contain detailed information about all macromolecules involved in the translation, folding, modification, glycosylation, and secretion of proteins. This further includes metabolism, which fuels the pathway. The known functions of each pathway member will be detailed, and their interactions will be described. Since the knowledge base will be organized to enable its use for systems biology analyses, (ii) visualization tools and analysis algorithms will be developed and deployed to identify how changes in each component influence the ability to secrete individual proteins or synthesize specific glycans. (iii) We will leverage the model to integrate large omics data sets we are generating with collaborators (e.g., metabolomics, ribosomal profiling, proteomics, and CRISPR-Cas9 activation and loss-of-function screens) to study regulation of tissue-specific protein secretion. (iv) We will leverage the data to elucidate novel interactions and functions for poorly characterized members of the secretory pathway. This research program will provide, for the first time, a well-defined and curated knowledge base for this complex system, and enable the use of diverse computational systems biology tools to identify the molecular mechanisms underlying different cell phenotypes stemming from changes in the secretory pathway.
Each human cell contains a system for secreting proteins and other large molecules, called the secretory pathway, and changes in pathway activity are seen in most diseases, exhibited as pathological changes in protein secretion and glycan structures or entrance of pathogens. Since the complexity of the mammalian secretory pathway has stymied efforts to elucidate the perturbed mechanisms in disease, we are developing a detailed reconstruction of the secretory pathway, including the known functions of each protein and how they interact with each other. Furthermore, we are developing techniques to use this knowledgebase to analyze complex data sets and to develop computational models of its processes.
| Brunk, Elizabeth; Chang, Roger L; Xia, Jing et al. (2018) Characterizing posttranslational modifications in prokaryotic metabolism using a multiscale workflow. Proc Natl Acad Sci U S A 115:11096-11101 |
| Rupp, Oliver; MacDonald, Madolyn L; Li, Shangzhong et al. (2018) A reference genome of the Chinese hamster based on a hybrid assembly strategy. Biotechnol Bioeng 115:2087-2100 |
| Kuo, Chih-Chung; Chiang, Austin Wt; Shamie, Isaac et al. (2018) The emerging role of systems biology for engineering protein production in CHO cells. Curr Opin Biotechnol 51:64-69 |
| Spahn, Philipp N; Bath, Tyler; Weiss, Ryan J et al. (2017) PinAPL-Py: A comprehensive web-application for the analysis of CRISPR/Cas9 screens. Sci Rep 7:15854 |
| Richelle, Anne; Lewis, Nathan E (2017) Improvements in protein production in mammalian cells from targeted metabolic engineering. Curr Opin Syst Biol 6:1-6 |
| Kallehauge, Thomas Beuchert; Li, Shangzhong; Pedersen, Lasse Ebdrup et al. (2017) Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion. Sci Rep 7:40388 |
| Abdel-Haleem, Alyaa M; Lewis, Nathan E; Jamshidi, Neema et al. (2017) The Emerging Facets of Non-Cancerous Warburg Effect. Front Endocrinol (Lausanne) 8:279 |
| Shen, John Paul; Zhao, Dongxin; Sasik, Roman et al. (2017) Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions. Nat Methods 14:573-576 |
| Spahn, Philipp N; Hansen, Anders H; Kol, Stefan et al. (2017) Predictive glycoengineering of biosimilars using a Markov chain glycosylation model. Biotechnol J 12: |
| Opdam, Sjoerd; Richelle, Anne; Kellman, Benjamin et al. (2017) A Systematic Evaluation of Methods for Tailoring Genome-Scale Metabolic Models. Cell Syst 4:318-329.e6 |
Showing the most recent 10 out of 12 publications
