Biology subjects

McWhite, C. D.

Publications and source records attributed to McWhite, C. D..

13 recordsLinked to original sources

bioRxiv2026

Representing biological concepts as directions in foundation model embeddings

Biological foundation models encode rich information about protein structure, function, and cellular state in high-dimensional embeddings, but accessing specific biological properties typically relies on additional, task-specific prediction models. Here, we show that diverse biological properties can be mapped to interpretable, reusable directions in embedding space. In the Concept Activation Vector (CAV) approach, examples representing a concept are distinguished from a background set using a linear model, and the resulting weight vector defines the CAV for that concept. In protein embeddings, CAVs recover Gene Ontology and Enzyme Commission annotations, localize Pfam domains, reveal novel structural relationships, and capture DNA-binding and protein-interaction interface specificity. In single-cell embeddings, CAVs isolate cancer-associated expression transitions, and gene variation along these axes substantially agrees with conventional differential-expression analysis despite being a distinct computational approach. Together, these results establish concept directions as a common representation, enabling diverse biological features to be compared, localized, and manipulated.

bioinformatics↗

bioRxiv2026

A bifunctional coiled-coil protein generates the membrane-within-condensate architecture of the CO2-fixing pyrenoid

How membranes are integrated into biomolecular condensates is a fundamental question in cell biology. In the algal pyrenoid, an organelle responsible for one-third of global carbon fixation, CO2-delivering thylakoid membranes must penetrate a phase-separated condensate of the CO2-fixing enzyme Rubisco, but the mechanism governing membrane recruitment into the condensate remains unknown. Here, we demonstrate that the Chlamydomonas reinhardtii protein MITH1 acts as a molecular anchor that brings membrane into the pyrenoid condensate. MITH1 dimerizes into an extended coiled coil with an N-terminal amphipathic helix that binds thylakoid membrane. The coiled coil contains multiple novel binding sites for the Rubisco large subunit, allowing the condensate to wet onto the membrane. The coiled coil extends away from the membrane and promotes membrane organization within the condensate. These findings solve a longstanding mechanistic question in pyrenoid biogenesis and reveal general principles for how membranes are integrated into biological condensates.

molecular biology↗

bioRxiv2025

VerteBrain reveals novel neural and non-neural protein assemblies conserved across vertebrate evolution

Protein-protein interactions underlie core brain functions, including neurotransmitter release, receptor activation, and intracellular signaling essential for learning, memory, and cognition. Here, we systematically map conserved brain protein interactions across five vertebrate species-rabbit, chicken, dolphin, pig, and mouse-using co-fractionation and immunoprecipitation mass spectrometry. From 2,197 biochemical fractions, we identify over 81,000 high-confidence interactions among 6,108 conserved proteins. This interaction map (VerteBrain) reveals both regulatory and structural complexes, including extensive synaptonemal protein associations likely involved in inter-neuronal coordination. Conservation across species underscores essential roles in neuronal and glial function, as well as in additional tissues for more widely expressed complexes. The VerteBrain dataset uncovers candidate disease mechanisms, including roles for ARHGEF1 in short stature syndromes, synaptic vesicle trafficking complexes in epilepsy, and RELCH in congenital deafness. VerteBrain provides a publicly accessible framework for investigating brain protein interactions and their relevance to human neurological disorders.

systems biology↗

bioRxiv2025

Landscape of human protein-coding somatic mutations across tissues and individuals

Although somatic mutations are fundamentally important to human biology, disease, and aging, many outstanding questions remain about their rates, spectrum, and determinants in apparently healthy tissues. Here, we performed high-coverage exome sequencing on 265 samples from 14 GTEx donors sampled for a median of 17.5 tissues per donor (spanning 46 total tissues). Using a novel probabilistic method tailored to the unique structure of our data, we identified 8,470 somatic variants. We leverage our compendium of somatic mutations to quantify the burden of deleterious somatic variants among tissues and individuals, identify molecular features such as chromatin accessibility that exhibit significantly elevated somatic mutation rates, provide novel biological insights into mutational mechanisms, and infer developmental trajectories based on patterns of multi-tissue somatic mosaicism. Our data provides a high-resolution portrait of somatic mutations across genes, tissues, and individuals.

genomics↗

bioRxiv2024

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↗

bioRxiv2023

Spatially resolved proteomics of the stomatal lineage: polarity complexes for cell divisions and stomatal pores

Cell polarity is used to guide asymmetric divisions and create morphologically diverse cells. We find that two oppositely oriented cortical polarity domains present during the asymmetric divisions in the Arabidopsis stomatal lineage are reconfigured into polar domains marking ventral (pore-forming) and outward facing domains of maturing stomatal guard cells. Proteins that define these opposing polarity domains were used as baits in miniTurboID-based proximity labeling. Among differentially enriched proteins we find kinases, putative microtubule-interacting proteins, polar SOSEKIs with their effector ANGUSTIFOLIA, and using AI-facilitated protein structure prediction models, we identify their potential interaction interfaces. Functional and localization analysis of polarity protein OPL2 and its newly discovered partners suggest a positive interaction with mitotic microtubules and a potential role in cytokinesis. This combination of cutting-edge proteomics and structural modeling with live cell imaging provides insights into how polarity is rewired in different cell types and cell cycle stages.

developmental biology↗

bioRxiv2022

Systematic identification and characterization of novel genes in the regulation and biogenesis of photosynthetic machinery

Photosynthesis is central to food production and the Earths biogeochemistry, yet the molecular basis for its regulation remains poorly understood. Here, using high-throughput genetics in the model eukaryotic alga Chlamydomonas reinhardtii, we identify with high confidence (FDR<0.11) 70 previously-uncharacterized genes required for photosynthesis. We then provide a resource of mutant proteomes that enables functional characterization of these novel genes by revealing their relationship to known genes. The data allow assignment of 34 novel genes to the biogenesis or regulation of one or more specific photosynthetic complexes. Additional analysis uncovers at least seven novel critical regulatory proteins, including five Photosystem I mRNA maturation factors and two master regulators: MTF1, which impacts chloroplast gene expression directly; and PMR1, which impacts expression via nuclear-expressed factors. Our work provides a rich resource identifying novel regulatory and functional genes and placing them into pathways, thereby opening the door to a system-level understanding of photosynthesis. HighlightsO_LIHigh-confidence identification of 70 previously-uncharacterized genes required for photosynthesis C_LIO_LIProteomic analysis of mutants allows assignment of function to novel genes C_LIO_LICharacterization of 5 novel Photosystem I mRNA maturation factors validates this resource C_LIO_LIMTF1 and PMR1 identified as master regulators of photosynthesis C_LI

cell biology↗

bioRxiv2022

Vector-clustering Multiple Sequence Alignment: Aligning into the twilight zone of protein sequence similarity with protein language models

Multiple sequence alignment is a critical step in the study of protein sequence and function. Typically, multiple sequence alignment algorithms progressively align pairs of sequences and combine these alignments with the aid of a guide tree. These alignment algorithms use scoring systems based on substitution matrices to measure amino-acid similarities. While successful, standard methods struggle on sets of proteins with low sequence identity - the so-called twilight zone of protein alignment. For these difficult cases, another source of information is needed. Protein language models are a powerful new approach that leverage massive sequence datasets to produce high-dimensional contextual embeddings for each amino acid in a sequence. These embeddings have been shown to reflect physicochemical and higher-order structural and functional attributes of amino acids within proteins. Here, we present a novel approach to multiple sequence alignment, based on clustering and ordering amino acid contextual embeddings. Our method for aligning semantically consistent groups of proteins circumvents the need for many standard components of multiple sequence alignment algorithms, avoiding initial guide tree construction, intermediate pairwise alignments, gap penalties, and substitution matrices. The added information from contextual embeddings leads to higher accuracy alignments for structurally similar proteins with low amino-acid similarity. We anticipate that protein language models will become a fundamental component of the next generation of algorithms for generating MSAs. Software availability: https://github.com/clairemcwhite/vcmsa

bioinformatics↗

bioRxiv2022

Alternative proteoforms and proteoform-dependent assemblies in humans and plants

Variability of proteins at the sequence level creates an enormous potential for proteome complexity. Exploring the depths and limits of this complexity is an ongoing goal in biology. Here, we systematically survey human and plant high-throughput bottom-up native proteomics data for protein truncation variants, where substantial regions of the full-length protein are missing from an observed protein product. In humans, Arabidopsis, and the green alga Chlamydomonas, approximately one percent of observed proteins show a short form, which we can assign by comparison to RNA isoforms as either likely deriving from transcript-directed processes or limited proteolysis. While some detected protein fragments align with known splice forms and protein cleavage events, multiple examples are previously undescribed, such as our observation of fibrocystin proteolysis and nuclear translocation in a green alga. We find that truncations occur almost entirely between structured protein domains, even when short forms are derived from transcript variants. Intriguingly, multiple endogenous protein truncations of phase-separating translational proteins resemble cleaved proteoforms produced by enteroviruses during infection. Some truncated proteins are also observed in both humans and plants, suggesting that they date to the last eukaryotic common ancestor. Finally, we describe novel proteoform-specific protein complexes, where loss of a domain may accompany complex formation.

systems biology↗

bioRxiv2022

A Chloroplast Protein Atlas Reveals Novel Structures and Spatial Organization of Biosynthetic Pathways

Chloroplasts are eukaryotic photosynthetic organelles that drive the global carbon cycle. Despite their importance, our understanding of their protein composition, function, and spatial organization remains limited. Here, we determined the localizations of 1,032 candidate chloroplast proteins by using fluorescent protein tagging in the model alga Chlamydomonas reinhardtii. The localizations provide insights into the functions of hundreds of poorly-characterized proteins, including identifying novel components of nucleoids, plastoglobules, and the pyrenoid. We discovered and further characterized novel organizational features, including eleven chloroplast punctate structures, cytosolic crescent structures, and diverse unexpected spatial distributions of enzymes within the chloroplast. We observed widespread protein targeting to multiple organelles, identifying proteins that likely function in multiple compartments. We also used machine learning to predict the localizations of all Chlamydomonas proteins. The strains and localization atlas developed here will serve as a resource to enable studies of chloroplast architecture and functions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/493820v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@19c871eorg.highwire.dtl.DTLVardef@16ac46corg.highwire.dtl.DTLVardef@859b7dorg.highwire.dtl.DTLVardef@1a3446e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LI1,032 candidate chloroplast proteins localized by fluorescent tagging. C_LIO_LIThis protein atlas reveals novel chloroplast structures, functional regions, and components. C_LIO_LIPrevalent dual-organelle localization suggests extensive cross-compartment coordination. C_LIO_LIAtlas-trained machine learning predicts localizations of all C. reinhardtii proteins. C_LI

plant biology↗

bioRxiv2021

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↗

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↗

bioRxiv2016

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↗