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Biology subjects

Drew, K.

Publications and source records attributed to Drew, K..

16 recordsLinked to original sources

DirectContacts2: A network of direct physical protein interactions derived from high-throughput mass spectrometry experiments

Cellular function is driven by the activity proteins in stable complexes. Protein complex assembly depends on the direct physical association of component proteins. Advances in macromolecular structure prediction with tools like AlphaFold and RoseTTAFold have greatly improved our ability to model these interactions in silico, but an all-by-all analysis of the human proteomes ~200M possible pairs remains computationally intractable. A comprehensive cellular map of direct protein interactions will therefore be an invaluable resource to direct screening efforts. Here, we present DirectContacts2, a machine learning model that distinguishes direct from indirect protein interactions using features derived from over 25,000 mass spectrometry experiments. Applied to ~26 million human protein pairs, our model outperforms previous resources in identifying direct physical interactions and enriches for accurate structural models including ~2,500 new AlphaFold3 models. Our framework enables structural modeling of disease-relevant complexes (e.g. orofacial digital syndrome (OFDS) complex) offering insights into the molecular consequences of pathogenic mutations (OFD1) and broadly, establishes a highly accurate protein wiring diagram of the cell.

systems biology↗

hu.MAP3.0: Atlas of human protein complexes by integration of > 25,000 proteomic experiments

Macromolecular protein complexes carry out most functions in the cell including essential functions required for cell survival. Unfortunately, we lack the subunit composition for all human protein complexes. To address this gap we integrated >25,000 mass spectrometry experiments using a machine learning approach to identify > 15,000 human protein complexes. We show our map of protein complexes is highly accurate and more comprehensive than previous maps, placing [~]75% of human proteins into their physical contexts. We globally characterize our complexes using protein co-variation data (ProteomeHD.2) and identify co-varying complexes suggesting common functional associations. Our map also generates testable functional hypotheses for 472 uncharacterized proteins which we support using AlphaFold modeling. Additionally, we use AlphaFold modeling to identify 511 mutually exclusive protein pairs in hu.MAP3.0 complexes suggesting complexes serve different functional roles depending on their subunit composition. We identify expression as the primary way cells and organisms relieve the conflict of mutually exclusive subunits. Finally, we import our complexes to EMBL-EBIs Complex Portal (https://www.ebi.ac.uk/complexportal/home) as well as provide complexes through our hu.MAP3.0 web interface (https://humap3.proteincomplexes.org/). We expect our resource to be highly impactful to the broader research community.

systems biology↗

Ancient eukaryotic protein interactions illuminate modern genetic traits and disorders

All eukaryotes share a single-celled ancestor from [~]1.5-1.8 billion years ago, the Last Eukaryotic Common Ancestor (LECA). Roughly half of gene families found in modern eukaryotes were already present in LECA, forming molecular systems that continue to influence genetic diseases and traits today. To investigate these systems, we compared genes across 156 organisms to define a core set of protein-coding gene families likely present in LECA, with a quarter remaining uncharacterized. Integrating >26,000 mass spectrometry proteomics analyses from 31 species, we inferred higher-order complexes among these ancient proteins. This reconstructed interactome reveals both established and novel assemblies, offering a biochemical snapshot of LECAs organization. Finally, by exploring these ancient protein interactions, we found new human gene-disease associations for bone density and congenital birth defects, illustrating the value of ancestral protein networks for modern functional genetics.

evolutionary biology↗

CMA-ES-Rosetta: Blackbox optimization algorithm traverses rugged peptide docking energy landscapes

Energy minimization is necessary for virtually all modeling and design tasks and involves traversing extremely rugged energy landscapes. Although the gradient descent based minimization routines in Rosetta have fast runtimes, due to these rugged landscapes, minimization often converges into high-energy local minima. Alternative numerical optimization techniques, such as evolution strategies, are more robust to rugged landscapes and have been shown to be highly successful on a diverse set of problems. Here we explore the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), a state-of-the-art derivative-free optimization algorithm, as a complementary approach to the default minimizer in Rosetta. We used a benchmark of 26 peptides, from the FlexPepDock Benchmark, to assess the performance of three algorithms in Rosetta, specifically, CMA-ES, Rosettas default minimizer, and a Monte Carlo protocol of small backbone perturbations. We test the algorithms performance on their ability to dock an idealized peptide to a series of hotspots residues (i.e. constraints) along a native peptide. Of the three methods, CMA-ES was able to find the lowest energy conformation for 23 out of 26 benchmark peptides. The application of CMA-ES allows for an alternative optimization method for macromolecular modeling problems with rough energy landscapes.

biophysics↗

Near infrared spectroscopy detection of hemispheric cerebral ischemia following middle cerebral artery occlusion in rats

Timely and sensitive in vivo estimation of ischemic stroke-induced brain infarction are necessary to guide diagnosis and evaluation of treatments efficacy. The gold standard for estimation of the cerebral infarction volume is magnetic resonance imaging (MRI), which is expensive and not readily accessible. Measuring regional cerebral blood flow (rCBF) with Laser Doppler flowmetry (LDF) is the status quo for confirming reduced blood flow in experimental ischemic stroke models. However, rCBF reduction following cerebral artery occlusion often does not correlate with subsequent infarct volume. In the present study, we employed the continuous-wave near infrared spectroscopy (NIRS) technique to monitor cerebral oxygenation during 90 min of the intraluminal middle cerebral artery occlusion (MCAO) in Sprague-Dawley rats (n=8, male). The NIRS device consisted of a controller module and an optical sensor with two LED light sources and two photodiodes making up two parallel channels for monitoring left and right cerebral hemispheres. Optical intensity measurements were converted to deoxyhemoglobin (Hb) and oxyhemoglobin (HbO2) changes relative to a 2-min window prior to MCAO. Area under the curve (auc) for Hb and HbO2 was calculated for the 90-min occlusion period for each hemisphere (ipsilateral and contralateral). To obtain a measure of total ischemia, auc of the contralateral side was subtracted from the ipsilateral side resulting in {Delta}Hb and {Delta}HbO2 parameters. Infarct volume (IV) was calculated by triphenyl tetrazolium chloride (TTC) staining at 24h reperfusion. Results showed a significant negative correlation (r = -0.81, p = 0.03) between {Delta}Hb and infarct volume. In conclusion, our results show feasibility of using a noninvasive optical imaging instrument, namely NIRS, in monitoring cerebral ischemia in a rodent stroke model. This cost-effective, non-invasive technique may improve the rigor of experimental models of ischemic stroke by enabling in vivo longitudinal assessment of cerebral oxygenation and ischemic injury.

neuroscience↗

The protein organization of a red blood cell

Red blood cells (RBCs, erythrocytes) are the simplest primary human cells, lacking nuclei and major organelles, and instead employing about a thousand proteins to dynamically control cellular function and morphology in response to physiological cues. In this study, we defined a canonical RBC proteome and interactome using quantitative mass spectrometry and machine learning. Our data reveal an RBC interactome dominated by protein homeostasis, redox biology, cytoskeletal dynamics, and carbon metabolism. We validated protein complexes through electron microscopy and chemical crosslinking, and with these data, built 3D structural models of the ankyrin/Band 3/Band 4.2 complex that bridges the spectrin cytoskeleton to the RBC membrane. The model suggests spring-link compression of ankyrin may contribute to the characteristic RBC cell shape and flexibility. Taken together, our study provides an in-depth view of the global protein organization of human RBCs and serves as a comprehensive resource for future research.

systems biology↗

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↗

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↗

Functional partitioning of a liquid-like organelle during assembly of axonemal dyneins

Ciliary motility is driven by axonemal dyneins that are assembled in the cytoplasm before deployment to cilia. Motile ciliopathy can result from defects in the dyneins themselves or from defects in factors required for their cytoplasmic pre-assembly. Recent work demonstrates that axonemal dyneins, their specific assembly factors, and broadly acting chaperones are concentrated in liquid-like organelles in the cytoplasm called DynAPs (Dynein Axonemal Particles). Here, we use in vivo imaging to show that inner dynein arm (IDA) and outer dynein arm (ODA) subunits are partitioned into non-overlapping sub-regions within DynAPs. Using affinity purification mass-spectrometry of in vivo interaction partners, we also identify novel partners for inner and outer dynein arms. Among these, we identify C16orf71/Daap1 as a novel axonemal dynein regulator. Daap1 interacts with ODA subunits, localizes specifically to the cytoplasm, is enriched in DynAPs, and is required for the deployment of ODAs to axonemes. Our work reveals a new complexity in the structure and function of a cell-type specific liquid-like organelle that is directly relevant to human genetic disease.

cell biology↗

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↗

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↗

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↗

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↗

A phase separated organelle at the root of motile ciliopathy

Hundreds of different cell types emerge in the developing embryo, each of which must compartmentalize cell type specific biochemical processes in a crowded intracellular environment. To study cell type specific compartmentalization, we examined motile ciliated cells, which must assemble vast numbers of dynein motors to drive ciliary beating, as mutation of dyneins or their assembly factors causes motile ciliopathy. We show that dyneins, their assembly factors, and chaperones all concentrate together in Dynein Assembly Particles (DynAPs). These phase-separated organelles are specific to ciliated cells but share machinery with stress granules. Our data suggest that a common framework underlies ubiquitous and cell-type specific phase separated organelles and that one such organelle is defective in a human genetic disease.

cell biology↗

An Adaptive Geometric Search Algorithm for Macromolecular Scaffold Selection

A wide variety of protein and peptidomimetic design tasks require matching functional three-dimensional motifs to potential oligomeric scaffolds. Enzyme design, for example, aims to graft active-site patterns typically consisting of 3 to 15 residues onto new protein surfaces. Identifying suitable proteins capable of scaffolding such active-site engraftment requires costly searches to identify protein folds that can provide the correct positioning of side chains to host the desired active site. Other examples of biodesign tasks that require simpler fast exact geometric searches of potential side chain positioning include mimicking binding hotspots, design of metal binding clusters and the design of modular hydrogen binding networks for specificity. In these applications the speed and scaling of geometric search limits downstream design to small patterns. Here we present an adaptive algorithm to searching for side chain take-off angles compatible with an arbitrarily specified functional pattern that enjoys substantive performance improvements over previous methods. We demonstrate this method in both genetically encoded (protein) and synthetic (peptidomimetic) design scenarios. Examples of using this method with the Rosetta framework for protein design are provided but our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design).

bioengineering↗

A synthesis of over 9,000 mass spectrometry experiments reveals the core set of human protein complexes

Macromolecular protein complexes carry out many of the essential functions of cells, and many genetic diseases arise from disrupting the functions of such complexes. Currently there is great interest in defining the complete set of human protein complexes, but recent published maps lack comprehensive coverage. Here, through the synthesis of over 9,000 published mass spectrometry experiments, we present hu.MAP, the most comprehensive and accurate human protein complex map to date, containing >4,600 total complexes, >7,700 proteins and >56,000 unique interactions, including thousands of confident protein interactions not identified by the original publications. hu.MAP accurately recapitulates known complexes withheld from the learning procedure, which was optimized with the aid of a new quantitative metric (k-cliques) for comparing sets of sets. The vast majority of complexes in our map are significantly enriched with literature annotations and the map overall shows improved coverage of many disease-associated proteins, as we describe in detail for ciliopathies. Using hu.MAP, we predicted and experimentally validated candidate ciliopathy disease genes in vivo in a model vertebrate, discovering CCDC138, WDR90, and KIAA1328 to be new cilia basal body/centriolar satellite proteins, and identifying ANKRD55 as a novel member of the intraflagellar transport machinery. By offering significant improvements to the accuracy and coverage of human protein complexes, hu.MAP (http://proteincomplexes.org) serves as a valuable resource for better understanding the core cellular functions of human proteins and helping to determine mechanistic foundations of human disease.

systems biology↗