With Ian George, Youjia Zhou, Kevin Hicks, Bei Wang, and Jared Rutter

×   Status: Working Papers

Electrum: Visualization, analysis, and contextualization of protein-metabolite interaction datasets

Abstract

Motivation: Metabolic enzymes dictating the biophysical outcomes of cells are controlled by numerous allosteric interactions where a particular metaboliteacts as an enzymatic trigger. While various protein-metabolite allosteric interactions have been identified and described, it is difficult and time-consuming todo so. Thus, over the course of the last decade, we have developed an at-scale method for the identification of these interactions, which we call “massspectrometry integrated with equilibrium dialysis for the discovery of allostery systematically”, or “MIDAS”. The capabilities needed to take sets ofprotein-metabolite interactions and visualize them and identify regulatory-relevant patterns within these cohorts has not yet been developed.
Results: In order to provide a user-friendly web portal for analyzing protein-metabolite interaction data, we developed Electrum. Electrum acts as a centralrepository for MIDAS-generated protein-metabolite interaction data and standardizes the database formatting required for storing this data type. Electrumincludes various visual features that enable the exploration and analysis of these data. To aid in the biological contextualization of these data, we include theability to query these protein-metabolite interactions for biologically relevant information from existing databases, such as the Human Metabolome Databaseand the Reactome Knowledgebase. In order to facilitate the identification of regulatory relevant patterns within the data, we built tools that systematicallyquery human metabolism and metabolite sub-structures and identify common sub-structures enrichments within metabolites that interact with a given protein.

Ian George

Youjia Zhou

Kevin Hicks

Bei Wang

Jared Rutter

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Software Paper

With Youjia Zhou, Yeyun Ouyang, T. Cameron Waller, Ahmad Cluntun, Megan Conway, Tyler Van Ry, Ian George, Sara Nowinski, James Cox, Bei Wang, and Jared Rutter

bioRxiv, 2020

×   Status: Working Papers

Network-aware reaction pattern recognition reveals regulatory signatures of mitochondrial dysfunction

Abstract

Metabolism forms a complex, interdependent network, and perturbations can have indirect effects that are pervasive. Identifying these patterns and their consequences is difficult, particularly when the effects occur across canonical pathways, and these difficulties have long acted as a bottleneck in metabolic data analysis. This challenge is compounded by technical limitations in metabolomics approaches that garner incomplete datasets. Current network-based tools generally utilize pathway-level analysis lacking the granular resolution required to provide context into the effects of all perturbations, regardless of magnitude, across the metabolic network. To address these shortcomings, we introduce algorithms that allow for the real-time extraction of regulatory patterns and trends from user data. To minimize the impact of missing measurements within the metabolic network, we introduce methods that enable complex pattern recognition across multiple reactions. These tools are available interactively within the user-friendly Metaboverse app (https://github.com/Metaboverse) to facilitate exploration and hypothesis generation. We demonstrate that expected signatures are accurately captured by Metaboverse. Using public lung adenocarcinoma data, we identify a previously undescribed multi-dimensional signature that correlated with survival outcomes in lung adenocarcinoma patients. Using a model of respiratory deficiency, we identify relevant and previously unreported regulatory patterns that suggest an important compensatory role for citrate during mitochondrial dysfunction. This body of work thus demonstrates that Metaboverse can identify and decipher complex signals from data that have been otherwise difficult to identify with previous approaches.

Youjia Zhou

Yeyun Ouyang

T. Cameron Waller

Ahmad Cluntun

Megan Conway

Tyler Van Ry

Ian George

Sara Nowinski

James Cox

Bei Wang

Jared Rutter

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Software Paper

With Jonathan Belyeu, Jeffrey Morgan, Yeyun Ouyang, Alex Bott, Aaron Quinlan, Jason Gertz, and Jared Rutter

PLoS Computational Biology, 2020

×   Status: Published Work

XPRESSyourself: Enhancing, Standardizing, and Automating Ribosome Profiling Computational Analyses Yields Improved Insight into Data

Abstract

Ribosome profiling, an application of nucleic acid sequencing for monitoring ribosome activity, has revolutionized our understanding of protein translation dynamics. This technique has been available for a decade, yet the current state and standardization of publicly available computational tools for these data is bleak. We introduce XPRESSyourself, an analytical toolkit that eliminates barriers and bottlenecks associated with this specialized data type by filling gaps in the computational toolset for both experts and non-experts of ribosome profiling. XPRESSyourself automates and standardizes analysis procedures, decreasing time-to-discovery and increasing reproducibility. This toolkit acts as a reference implementation of current best practices in ribosome profiling analysis. We demonstrate this toolkit’s performance on publicly available ribosome profiling data by rapidly identifying hypothetical mechanisms related to neurodegenerative phenotypes and neuroprotective mechanisms of the small-molecule ISRIB during acute cellular stress. XPRESSyourself brings robust, rapid analysis of ribosome-profiling data to a broad and ever-expanding audience and will lead to more reproducible and accessible measurements of translation regulation. XPRESSyourself software is perpetually open-source under the GPL-3.0 license and is hosted at https://github.com/XPRESSyourself/, where users can access additional documentation and report software issues.

Jonathan Belyeu

Jeffrey Morgan

Yeyun Ouyang

Alex Bott

Aaron Quinlan

Jason Gertz

Jared Rutter

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Software Publication

With Kevin Hicks, Ahmad Cluntun, Heidi Schubert, Sean Hackett, Paul Leonard, Mariana Ajalla Aleixo, Aubrie Blevins, Paige Barta, Samantha Tilley, Sarah Fogarty, Jacob Winter, Hee-Chul Ahn, Karen Allen, Samuel Block, Iara Cardoso, Jianping Ding, Ingrid Dreveny, Clarke Gasper, Quinn Ho, Atsushi Matsuura, Michael Palladino, Sabin Prajapati, PengKai Sun, Kai Tittmann, Dean Tolan, Judith Unterlass, Andrew VanDemark, Matthew Vander Heiden, Bradley Webb, Cai-Hong Yun, PengKai Zhap, Christopher Hill, Maria Cristina Nonato, Florian Muller, Daniel Gottschling, James Cox, and Jared Rutter

bioRxiv, 2021

With Jacob Winter, Heidi Fresenius, Heather Keys, Corey Cunningham, Jeremy Ryan, Deepika Sirohi, Sheryl Tripp, Paige Barta, Neeraj Agarwal, Anthony Letai, David Sabatini, Matthew Wohlever, and Jared Rutter

bioRxiv, 2021

With Ahmad Cluntun, Rachit Badolia, Sandra Lettlova, Mark Parnell, Thirupura Shankar, Nikolaos Diakos, Kristofor Olson, Iosif Taleb, Sean Tatum, Corey Cunningham, Tyler Van Ry, Alex Bott, Aspasia Thodou Krokidi, Sarah Fogarty, Sophia Skedros, Wojciech Swiatek, Xuejing Yu, Bai Luo, Shannon Merx, Sutip Navankasattusas, James Cox, Gregory Ducker, William Holland, Stephen McKellar, Jared Rutter, and Stavros Drakos

Cell Metabolism, 2021

With Sara Nowinski, Ashley Solmonson, Scott Rusin, J. Alan Maschek, Claire Bensard, Sarah Fogarty, Mi-Young Jeong, Sandra Lettlova, Jeffrey Morgan, Yeyun Ouyang, Bradley Naylor, Joao Paulo, Katsuhiko Funai, James Cox, Steven Gygi, Dennis Winge, Ralph DeBerardinis, and Jared Rutter

eLife, 2020

With T. Cameron Waller, Alexander Lex, Brian Chapman, and Jared Rutter

GigaScience, 2020

With Casey Hughes, Troy K. Coody, Mi-Young Jeong, Dennis Winge, and Adam Hughes

Cell, 2020

With Claire Bensard, Dona Wisidagama, Kristofor Olson, Nathan Krah, John Schell, Sara Nowinski, Sarah Fogarty, Alex Bott, Peng Wei, Katja Dove, Jason Tanner, Vanja Panic, Ahmad Cluntun, Sandra Lettlova, Christian Earl, David Namnath, Karina Vázquez-Arreguín, Claudio Villanueva, Dean Tantin, L. Charles Murtaugh, Kimberley Evason, Gregory Ducker, Carl Thummel, and Jared Rutter

Cell Metabolism, 2019

With Jonathan Van Vranken, Sara Nowinski, Katie Clowers, Mi-Young Jeong, Yeyun Ouyang, Jeremy Gygi, Steven Gygi, Dennis Winge, Jared Rutter

Molecular Cell, 2018