Biology subjects

Ludwig, R. W.

Publications and source records attributed to Ludwig, R. W..

4 recordsLinked to original sources

bioRxiv2025

Large-scale discovery, analysis, and design of protein energy landscapes

All folded proteins continuously fluctuate between their low-energy native structures and higher energy conformations that can be partially or fully unfolded. These rare states influence protein function, interactions, aggregation, and immunogenicity, yet they remain far less understood than protein native states. Although native protein structures are now often predictable with impressive accuracy, conformational fluctuations and their energies remain largely invisible and unpredictable, and experimental challenges have prevented large-scale measurements that could improve machine learning and physics-based modeling. Here, we introduce a multiplexed experimental approach to analyze the energies of conformational fluctuations for hundreds of protein domains in parallel using intact protein hydrogen-deuterium exchange mass spectrometry. We analyzed 5,778 domains 28-64 amino acids in length, revealing hidden variation in conformational fluctuations even between sequences sharing the same fold and global folding stability. Site-resolved hydrogen exchange NMR analysis of 13 domains showed that these fluctuations often involve entire secondary structural elements with lower stability than the overall fold. Computational modeling of our domains identified structural features that correlated with the experimentally observed fluctuations, enabling us to design mutations that stabilized low-stability structural segments. Our dataset enables new machine learning-based analysis of protein energy landscapes, and our experimental approach promises to reveal these landscapes at unprecedented scale.

biophysics↗

bioRxiv2023

Simultaneous proteome localization and turnover analysis reveals spatiotemporal dynamics of unfolded protein responses

The functions of proteins depend on their spatial and temporal distributions, which are not directly measured by static protein abundance. Under endoplasmic reticulum (ER) stress, the unfolded protein response (UPR) pathway remediates proteostasis in part by altering the turnover kinetics and spatial distribution of proteins. A global view of these spatiotemporal changes has yet to emerge and it is unknown how they affect different cellular compartments and pathways. Here we describe a mass spectrometry-based proteomics strategy and data analysis pipeline, termed Simultaneous Proteome Localization and Turnover (SPLAT), to measure concurrently the changes in protein turnover and subcellular distribution in the same experiment. Investigating two common UPR models of thapsigargin and tunicamycin challenge in human AC16 cells, we find that the changes in protein turnover kinetics during UPR varies across subcellular localizations, with overall slowdown but an acceleration in endoplasmic reticulum and Golgi proteins involved in stress response. In parallel, the spatial proteomics component of the experiment revealed an externalization of amino acid transporters and ion channels under UPR, as well as the migration of RNA-binding proteins toward an endosome co-sedimenting compartment. The SPLAT experimental design classifies heavy and light SILAC labeled proteins separately, allowing the observation of differential localization of new and old protein pools and capturing a partition of newly synthesized EGFR and ITGAV to the ER under stress that suggests protein trafficking disruptions. Finally, application of SPLAT toward human induced pluripotent stem cell derived cardiomyocytes (iPSC-CM) exposed to the cancer drug carfilzomib, identified a selective disruption of proteostasis in sarcomeric proteins as a potential mechanism of carfilzomib-mediated cardiotoxicity. Taken together, this study provides a global view into the spatiotemporal dynamics of human cardiac cells and demonstrates a method for inferring the coordinations between spatial and temporal proteome regulations in stress and drug response.

cell biology↗

bioRxiv2022

Proteogenomic characterization of age and sex interactions in cardiac gene expression

The risks of heart diseases are significantly modulated by biological age and sex, but how these factors influence baseline cardiac gene expression remains incompletely understood. Here we characterized young adult and early aging mouse hearts using proteogenomics to identify age and sex dependent gene expression signatures in the mouse heart. RNA sequencing from 4 months old and 20 months old female and male C57BL/6J hearts identified thousands of genes with differential transcript abundances both between sexes (male vs. female) and across age groups (20 mo. vs. 4 mo.). Sex-associated cardiac genes are broadly distributed, functioning in the TCA cycle, mitochondrial translation, autophagy, and other processes. In addition, we found over 800 genes with differential aging response between male and female, which are enriched in calmodulin signaling and cell cycle regulations. Comparison with mass spectrometry data shows a cluster of metabolism genes with up-regulated transcripts but down-regulated protein levels in aging hearts, consistent with an uncoupling of transcriptional regulations in the genetic program with protein compositions. An analysis of sex-adjusted aging cardiac transcriptomes further revealed widespread remodeling of exon usage patterns that is largely independent from differential gene expression, concomitant with upstream changes in RNA-binding protein and splice factor transcripts. To evaluate the potential impact of the splicing events on proteoform composition in the heart, we applied an RNA-guided-proteomics computational pipeline to analyze the mass spectrometry data, and putatively identified hundreds of splice events with the potential to rewire the cardiac proteome through producing detectable splice isoform specific peptides. Taken together, this study contributes to emerging evidences for considerable sexual dimorphism in the cardiac aging process involving sex-biased aging genes and regulatory networks. Aging hearts are associated with a rewiring of RNA splicing programs, including sex- and age-dependent changes in exon usages and splice patterns that have the potential to influence cardiac protein structure and function. These changes represent an under-investigated aspect of cardiac aging that should be considered in the search for disease mechanisms.

physiology↗

bioRxiv2021

Harmonizing labeling and analytical strategies to obtain protein turnover rates in intact adult animals.

Changes in the abundance of individual proteins in the proteome can be elicited by modulation of protein synthesis (the rate of input of newly synthesized proteins into the protein pool) or degradation (the rate of removal of protein molecules from the pool). A full understanding of proteome changes therefore requires a definition of the roles of these two processes in proteostasis, collectively known as protein turnover. Because protein turnover occurs even in the absence of overt changes in pool abundance, turnover measurements necessitate monitoring the flux of stable isotope labeled precursors through the protein pool such as labeled amino acids or metabolic precursors such as ammonium chloride or heavy water. In cells in culture, the ability to manipulate precursor pools by rapid medium changes is simple, but for more complex systems such as intact animals, the approach becomes more convoluted. Individual methods bring specific complications, and the suitability of different methods has not been comprehensively explored. In this study we compare the turnover rates of proteins across four mouse tissues, obtained from the same inbred mouse strain maintained under identical husbandry conditions, measured using either [13C6]lysine or [2H2]O as the labeling precursor. We show that for long-lived proteins, the two approaches yield essentially identical measures of the first order rate constant for degradation. For short-lived proteins, there is a need to compensate for the slower equilibration of lysine through the precursor pools. We evaluate different approaches to provide that compensation. We conclude that both labels are suitable, but careful determination of precursor enrichment kinetics in amino acid labeling is critical and has a considerable influence on the numerical values of the derived protein turnover rates.

physiology↗