Biology subjects

Marcotte, E. M.

Publications and source records attributed to Marcotte, E. M..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Improving integrative 3D modeling into low- to medium- resolution EM structures with evolutionary couplings

Electron microscopy (EM) continues to provide near-atomic resolution structures for well-behaved proteins and protein complexes. Unfortunately, structures of some complexes are limited to low- to medium-resolution due to biochemical or conformational heterogeneity. Thus, the application of unbiased systematic methods for fitting individual structures into EM maps is important. A method that employs co-evolutionary information obtained solely from sequence data could prove invaluable for quick, confident localization of subunits within these structures. Here, we incorporate the co-evolution of intermolecular amino acids as a new type of distance restraint in the Integrative Modeling Platform (IMP) in order to build three-dimensional models of atomic structures into EM maps ranging from 10-14 [A] in resolution. We validate this method using four complexes of known structure, where we highlight the conservation of intermolecular couplings despite dynamic conformational changes using the BAM complex. Finally, we use this method to assemble the subunits of the bacterial holo-translocon into a model that agrees with previous biochemical data. The use of evolutionary couplings in integrative modeling improves systematic, unbiased fitting of atomic models into medium- to low-resolution EM maps, providing additional information to integrative models lacking in spatial data.

biochemistry↗

bioRxiv2020

Systematic Identification of Protein Phosphorylation-Mediated Interactions

Protein phosphorylation is a key regulatory mechanism involved in nearly every eukaryotic cellular process. Increasingly sensitive mass spectrometry approaches have identified hundreds of thousands of phosphorylation sites but the functions of a vast majority of these sites remain unknown, with fewer than 5% of sites currently assigned a function. To increase our understanding of functional protein phosphorylation we developed an approach for identifying the phosphorylation-dependence of protein assemblies in a systematic manner. A combination of non-specific protein phosphatase treatment, size-exclusion chromatography, and mass spectrometry allowed us to identify changes in protein interactions after the removal of phosphate modifications. With this approach we were able to identify 316 proteins involved in phosphorylation-sensitive interactions. We recovered known phosphorylation-dependent interactors such as the FACT complex and spliceosome, as well as identified novel interactions such as the tripeptidyl peptidase TPP2 and the supraspliceosome component ZRANB2. More generally, we find phosphorylation-dependent interactors to be strongly enriched for RNA-binding proteins, providing new insight into the role of phosphorylation in RNA binding. By searching directly for phosphorylated amino acid residues in mass spectrometry data, we identified the likely regulatory phosphosites on ZRANB2 and FACT complex subunit SSRP1. This study provides both a method and resource for obtaining a better understanding of the role of phosphorylation in native macromolecular assemblies.

systems biology↗

bioRxiv2020

hu.MAP 2.0: Integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies

A general principle of biology is the self-assembly of proteins into functional complexes. Characterizing their composition is, therefore, required for our understanding of cellular functions. Unfortunately, we lack a comprehensive set of protein complexes for human cells. To address this gap, we developed a machine learning framework to identify protein complexes in over 15,000 mass spectrometry experiments which resulted in the identification of nearly 7,000 physical assemblies. We show our resource, hu.MAP 2.0, is more accurate and comprehensive than previous resources and gives rise to many new hypotheses, including for 274 completely uncharacterized proteins. Further, we identify 259 promiscuous proteins that participate in multiple complexes pointing to possible moonlighting roles. We have made hu.MAP 2.0 easily searchable in a web interface (http://humap2.proteincomplexes.org/), which will be a valuable resource for researchers across a broad range of interests including systems biology, structural biology, and molecular explanations of disease.

systems biology↗

bioRxiv2020

Antifungal benzimidazoles disrupt vasculature by targeting one of nine β-tubulins

Thiabendazole (TBZ) is an FDA-approved benzimidazole widely used for its antifungal and antihelminthic properties. We showed previously that TBZ is also a potent vascular disrupting agent and inhibits angiogenesis at the tissue level by dissociating vascular endothelial cells in newly formed blood vessels. Here, we uncover TBZs molecular target and mechanism of action. Using human cell culture, molecular modeling, and humanized yeast, we find that TBZ selectively targets only 1 of 9 human {beta}-tubulin isotypes (TUBB8) to specifically disrupt endothelial cell microtubules. By leveraging epidemiological pesticide resistance data and mining chemical features of commercially used benzimidazoles, we discover that a broader class of benzimidazole compounds, in extensive use for 50 years, also potently disrupt immature blood vessels and inhibit angiogenesis. Thus, besides identifying the molecular mechanism of benzimidazole-mediated vascular disruption, this study presents evidence relevant to the widespread use of these compounds while offering potential new clinical applications.

systems biology↗

bioRxiv2020

A systematic, label-free method for identifying RNA-associated proteins in vivo provides insights into vertebrate ciliary beating

Cell-type specific RNA-associated proteins (RAPs) are essential for development and homeostasis in animals. Despite a massive recent effort to systematically identify RAPs, we currently have few comprehensive rosters of cell-type specific RAPs in vertebrate tissues. Here, we demonstrate the feasibility of determining the RNA-interacting proteome of a defined vertebrate embryonic tissue using DIF-FRAC, a systematic and universal (i.e., label-free) method. Application of DIF-FRAC to cultured tissue explants of Xenopus mucociliary epithelium identified dozens of known RAPs as expected, but also several novel RAPs, including proteins related to assembly of the mitotic spindle and regulation of ciliary beating. In particular, we show that the inner dynein arm tether Cfap44 is an RNA-associated protein that localizes not only to axonemes, but also to liquid-like organelles in the cytoplasm called DynAPs. This result led us to discover that DynAPs are generally enriched for RNA. Together, these data provide a useful resource for a deeper understanding of mucociliary epithelia and demonstrate that DIF-FRAC will be broadly applicable for systematic identification of RAPs from embryonic tissues.

developmental biology↗

bioRxiv2020

Mapping Functional Protein Neighborhoods in the Mouse Brain

New proteomics methods make it possible to determine protein interaction maps at the proteome scale without the need for genetically encoded tags, opening up new organisms and tissue types to investigation. Current molecular and computational methods are oriented towards protein complexes that are soluble, stable, and discrete. However, the mammalian brain, among the most complicated and most heavily studied tissue types, derives many of its unique functions from protein interactions that are neither discrete nor soluble. Proteomics investigations into the global protein interaction landscape of the brain have therefore leveraged non-proteomics datasets to supplement their experiments. Here, we develop a novel, integrative proteomics pipeline and apply it to infer a global map of functional protein neighborhoods in the mouse brain without the aid of external datasets. By leveraging synaptosome enrichment and interactomics methods that target both soluble and insoluble protein fractions, we resolved protein interactions for key neural pathways, including those from refractory subcellular fractions such as the membrane and cytoskeleton. In comparison to external datasets, our observed interactions perform similarly to hand-curated synaptic protein interactions while also suggesting thousands of novel connections. We additionally employed cleavable chemical cross-linkers to detect direct binding partners and provide structural context. Our combined map suggests new protein pathways and novel mechanisms for proteins that underlie neurological diseases, including autism and epilepsy. Our results show that proteomics methods alone are sufficient to determine global interaction maps for proteins that are of broad interest to neuroscience. We anticipate that our map will be used to prioritize new research avenues and will pave the way towards future proteomics techniques that resolve protein interactions at ever greater resolution.

systems biology↗

bioRxiv2020

Solid-Phase Peptide Capture and Release for Bulk and Single-Molecule Proteomics

The field of proteomics has expanded recently with more sensitive techniques for the bulk measurement of peptides as well as single-molecule techniques. One limiting factor for some of these methods is the need for multiple chemical derivatizations and highly pure proteins free of contaminants. We demonstrate a solid-phase capture strategy suitable for the proteolysis, purification, and subsequent chemical modification of peptides. We use this resin on an HEK293T cell lysate and perform one-pot proteolysis, capture, and derivatization to generate a cellular proteome that identified over 40,000 bead-bound peptides. We also show that this capture can be reversed in a traceless manner, such that it is amenable for single-molecule proteomics techniques. With this technique, we perform a fluorescent labeling and C-terminal derivatization on a peptide and subject it to fluorosequencing, demonstrating that washing the resin is sufficient to remove excess dyes and other reagents prior to single-molecule protein sequencing.

biochemistry↗

bioRxiv2019

Simplified geometric representations of protein structures identify complementary interaction interfaces

Protein-protein interactions are critical to protein function, but three-dimensional (3D) arrangements of interacting proteins have proven hard to predict, even given the identities and 3D structures of the interacting partners. Specifically, identifying the relevant pairwise interaction surfaces remains difficult, often relying on shape complementarity with molecular docking while accounting for molecular motions to optimize rigid 3D translations and rotations. However, such approaches can be computationally expensive, and faster, less accurate approximations may prove useful for large-scale prediction and assembly of 3D structures of multi-protein complexes. We asked if a reduced representation of protein geometry retains enough information about molecular properties to predict pairwise protein interaction interfaces that are tolerant of limited structural rearrangements. Here, we describe a cuboid transformation of 3D protein accessible surfaces on which molecular properties such as charge, hydrophobicity, and mutation rate can be easily mapped, implemented in the MorphProt package. Pairs of surfaces are compared to rapidly assess partner-specific potential surface complementarity. On two available benchmarks of 85 overall known protein complexes, we observed F1 scores (a weighted combination of precision and recall) of 19-34% at correctly identifying protein interaction surfaces, comparable to more computationally intensive 3D docking methods in the annual Critical Assessment of PRedicted Interactions. Furthermore, we examined the effect of molecular motion through normal mode simulation on a benchmark receptor-ligand pair and observed no marked loss of predictive accuracy for distortions of up to 6 [A] RMSD. Thus, a cuboid transformation of protein surfaces retains considerable information about surface complementarity, offers enhanced speed of comparison relative to more complex geometric representations, and exhibits tolerance to conformational changes.

bioinformatics↗

bioRxiv2019

Abundances of transcripts, proteins, and metabolites in the cell cycle of budding yeast reveals coordinate control of lipid metabolism

Establishing the pattern of abundance of molecules of interest during cell division has been a long-standing goal of cell cycle studies. In several systems, including the budding yeast Saccharomyces cerevisiae, cell cycle-dependent changes in the transcriptome are well studied. In contrast, few studies queried the proteome during cell division, and they are often plagued by low agreement with each other and with previous transcriptomic datasets. There is also little information about dynamic changes in the levels of metabolites and lipids in the cell cycle. Here, for the first time in any system, we present experiment-matched datasets of the levels of RNAs, proteins, metabolites, and lipids from un-arrested, growing, and synchronously dividing yeast cells. Overall, transcript and protein levels were correlated, but specific processes that appeared to change at the RNA level (e.g., ribosome biogenesis), did not do so at the protein level, and vice versa. We also found no significant changes in codon usage or the ribosome content during the cell cycle. We describe an unexpected mitotic peak in the abundance of ergosterol and thiamine biosynthesis enzymes. Although the levels of several metabolites changed in the cell cycle, by far the most significant changes were in the lipid repertoire, with phospholipids and triglycerides peaking strongly late in the cell cycle. Our findings provide an integrated view of the abundance of biomolecules in the eukaryotic cell cycle and point to a coordinate mitotic control of lipid metabolism.

systems biology↗

bioRxiv2019

Systematic humanization of the yeast cytoskeleton discerns functionally replaceable from divergent human genes

Many gene families have been expanded by gene duplications along the human lineage, relative to ancestral opisthokonts, but the extent to which the duplicated genes function similarly is understudied. Here, we focused on structural cytoskeletal genes involved in critical cellular processes including chromosome segregation, macromolecular transport, and cell shape maintenance. To determine functional redundancy and divergence of duplicated human genes, we systematically humanized the yeast actin, myosin, tubulin, and septin genes, testing [~]85% of human cytoskeletal genes across 7 gene families for their ability to complement a growth defect induced by deletion of the corresponding yeast ortholog. In 5 of 7 families--all but -tubulin and light myosin, we found at least one human gene capable of complementing loss of the yeast gene. Despite rescuing growth defects, we observed differential abilities of human genes to rescue cell morphology, meiosis, and mating defects. By comparing phenotypes of humanized strains with deletion phenotypes of their interaction partners, we identify instances of human genes in the actin and septin families capable of carrying out essential functions, but apparently failing to interact with components of the yeast cytoskeleton, thus leading to abnormal cell morphologies. Overall, we show that duplicated human cytoskeletal genes appear to have diverged such that only a few human genes within each family are capable of replacing the essential roles of their yeast orthologs. The resulting yeast strains with humanized cytoskeletal components now provide surrogate platforms to characterize human genes in simplified eukaryotic contexts.

evolutionary biology↗

bioRxiv2019

A pan-plant protein complex map reveals deep conservation and novel assemblies

Plants are foundational to global ecological and economic systems, yet most plant proteins remain uncharacterized. Protein interaction networks often suggest protein functions and open new avenues to characterize genes and proteins. We therefore systematically determined protein complexes from 13 plant species of scientific and agricultural importance, greatly expanding the known repertoire of stable protein complexes in plants. Using co-fractionation mass spectrometry, we recovered known complexes, confirmed complexes predicted to occur in plants, and identified novel interactions conserved over 1.1 billion years of green plant evolution. Several novel complexes are involved in vernalization and pathogen defense, traits critical to agriculture. We also uncovered plant analogs of animal complexes with distinct molecular assemblies, including a megadalton-scale tRNA multi-synthetase complex. The resulting map offers the first cross-species view of conserved, stable protein assemblies shared across plant cells and provides a mechanistic, biochemical framework for interpreting plant genetics and mutant phenotypes.

systems biology↗

bioRxiv2019

Humanization of yeast genes with multiple human orthologs reveals principles of functional divergence between paralogs

Despite over a billion years of evolutionary divergence, several thousand human genes possess clearly identifiable orthologs in yeast, and many have undergone lineage-specific duplications in one or both lineages. The ortholog conjecture postulates that orthologous genes between species retain ancestral functions despite divergence over vast timescales, but duplicated genes will be free to diverge in function. However, the retention of ancestral functions among co-orthologs between species and within gene families has been difficult to test experimentally at scale. In order to investigate how ancestral functions are retained or lost post-duplication, we systematically replaced hundreds of essential yeast genes with their human orthologs from gene families that have undergone lineage-specific duplications, including those with single duplications (one yeast gene to two human genes, 1:2) or higher-order expansions (1:>2) in the human lineage. We observe a variable pattern of replaceability across different ortholog classes, with an obvious trend towards differential replaceability inside gene families, rarely observing replaceability by all members of a family. We quantify the ability of various properties of the orthologs to predict replaceability, showing that in the case of 1:2 orthologs, replaceability is predicted largely by the divergence and tissue-specific expression of the human co-orthologs, i.e. the human proteins that are less diverged from their yeast counterpart and more ubiquitously expressed across human tissues more often replace their single yeast ortholog. These trends were consistent with in silico simulations demonstrating that when only one ortholog is replaceable, it tends to be the least diverged of the pair. Replaceability of yeast genes having more than two human co-orthologs was marked by retention of orthologous interactions in functional or protein networks as well as by more ancestral subcellular localization. Overall, we performed >400 human gene replaceability assays revealing 56 new human-yeast complementation pairs, thus opening up avenues to further functionally characterize these human genes in a simplified organismal context.

systems biology↗

bioRxiv2019

Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections

Cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are unable to handle heterogeneous mixtures of structures from many macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. Using this approach, we first group a large set of synthetic reprojections from 35 unique macromolecular structures ranging from [~]30 - 3000 kDa into individual homogenous classes. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing reconstruction methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort cryo-EM data from heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.

biochemistry↗

bioRxiv2018

Systematic discovery of endogenous human ribonucleoprotein complexes

RNA-binding proteins (RBPs) play essential roles in biology and are frequently associated with human disease. While recent studies have systematically identified individual RBPs, their higher order assembly into Ribonucleoprotein (RNP) complexes has not been systematically investigated. Here, we describe a proteomics method for systematic identification of RNP complexes in human cells. We identify 1,428 protein complexes that associate with RNA, indicating that over 20% of known human protein complexes contain RNA. To explore the role of RNA in the assembly of each complex, we identify complexes that dissociate, change composition, or form stable protein-only complexes in the absence of RNA. Importantly, these data also provide specific novel insights into the function of well-studied protein complexes not previously known to associate with RNA, including replication factor C (RFC) and cytokinetic centralspindlin complex. Finally, we use our method to systematically identify cell-type specific RNA-associated proteins in mouse embryonic stem cells. We distribute these data as a resource, rna.MAP (rna.proteincomplexes.org) which provides a comprehensive dataset for the study of RNA-associated protein complexes. Our system thus provides a novel methodology for further explorations across human tissues and disease states, as well as throughout all domains of life.\n\nSummaryAn exploration of human protein complexes in the presence and absence of RNA reveals endogenous ribonucleoprotein complexes

systems biology↗

bioRxiv2018

From Space to Sequence and Back Again: Iterative DNA Proximity Ligation and its Applications to DNA-Based Imaging

We extend the concept of DNA proximity ligation from a single readout per oligonucleotide pair to multiple reversible, iterative ligations re-using the same oligonucleotide molecules. Using iterative proximity ligation (IPL), we can in principle capture multiple ligation events between each oligonucleotide and its various neighbors and thus recover a far richer knowledge about their relative positions than single, irreversible ligation events. IPL would thus act to sample and record local molecular neighborhoods. By integrating a unique DNA barcode into each participating oligonucleotide, we can catalog the individual ligation events and thus capture the positional information contained therein in a high throughput manner using next-generation DNA sequencing. We propose that by interpreting IPL sequencing results in the context of graph theory and by applying spring layout algorithms, we can recover geometric patterns of objects labeled by DNA. Using simulations, we demonstrate that we can in principle recover letter patterns photolithographed onto slide surfaces using only IPL sequencing data, illustrating how our technique maps complex spatial configurations into DNA sequences and then - using only this sequence information - recovers them. We complement our theoretical work with an experimental proof-of-concept of iterative proximity ligation on an oligonucleotide population.

bioinformatics↗

bioRxiv2018

Ancestral Reconstruction of Protein Interaction Networks

The molecular and cellular basis of novelty is a major open question in evolutionary biology. Until very recently, the vast majority of cellular phenomena were so difficult to sample that cross-species studies of biochemistry were rare and comparative analysis at the level of biochemical systems was almost impossible. Recent advances in systems biology are changing what is possible, however, and comparative phylogenetic methods that can handle this new data are wanted. Here, we introduce the term \"phylogenetic latent variable models\" (PLVMs, pronounced \"plums\") for a class of models that has recently been used to infer the evolution of cellular states from systems-level molecular data, and develop a new parameterization and fitting strategy that is useful for comparative inference of biochemical networks. We deploy this new framework to infer the ancestral states and evolutionary dynamics of protein-interaction networks by analyzing >16,000 predominantly metazoan co-fractionation and affinity-purification mass spectrometry experiments. Based on these data, we estimate ancestral interactions across unikonts, broadly recovering protein complexes involved in translation, transcription, proteostasis, transport, and membrane trafficking. Using these results, we predict an ancient core of the Commander complex made up of CCDC22, CCDC93, C16orf62, and DSCR3, with more recent additions of COMMD-containing proteins in tetrapods. We also use simulations to develop model fitting strategies and discuss future model developments.

evolutionary biology↗

bioRxiv2018

The many nuanced evolutionary consequences of duplicated genes

Gene duplication is seen as a major source of structural and functional divergence in genome evolution. Under the conventional models of sub- or neofunctionalizaton, functional changes arise in one of the duplicates after duplication. However, we suggest here that the presence of a duplicated gene can result in functional changes to its interacting partners. We explore this hypothesis by in-silico evolution of a heterodimer when one member of the interacting pair is duplicated. We examine how a range of selection pressures and protein structures leads to differential patterns of evolutionary divergence. We find that a surprising number of distinct evolutionary trajectories can be observed even in a simple three member system. Further, we observe that selection to correct dosage imbalance can affect the evolution of the initial function in several unexpected ways. For example, if a duplicate is under selective pressure to avoid binding its original binding partner, this can lead to changes in the binding interface of a non-duplicated interacting partner to exclude the duplicate. Hence, independent of the fate of the duplicate, its presence can impact how the original function operates. Additionally, we introduce a conceptual framework to describe how interacting partners cope with dosage imbalance after duplication. Contextualizing our results within this framework reveals that the evolutionary path taken by a duplicates interacting partners is highly stochastic in nature. Consequently, the fate of duplicate genes may not only be controlled by their own ability to accumulate mutations but also by how interacting partners cope with them.

evolutionary biology↗

bioRxiv2018

Classification of Single Particles from Human Cell Extract Reveals Distinct Structures

Multi-protein complexes are necessary for nearly all cellular processes, and understanding their structure is required for elucidating their function. Current high-resolution strategies in structural biology are effective, but lag behind other fields (e.g. genomics and proteomics) due to their reliance on purified samples rather than characterizing heterogeneous mixtures. Here, we present a method combining single particle analysis by electron microscopy with protein identification by mass spectrometry to structurally characterize macromolecular complexes from extracts of human cells. We obtain three-dimensional structures of native proteasomes directly from ab initio classification of a heterogeneous mixture of protein complexes. In addition, we find an ~1 MDa size structure of unknown composition and reference our proteomics data to suggest possible identities. Our study shows the power of using a shotgun approach to electron microscopy (shotgun EM) when coupled with mass spectrometry as a tool to uncover the structures of macromolecular machines in parallel.

biochemistry↗