Biology subjects

Clark, N.

Publications and source records attributed to Clark, N..

At least 19 recordsLinked to original sources

bioRxiv2026

SHP2 binds directly to SOS1 to enable RAS activation

The protein-tyrosine phosphatase SHP2 (PTPN11) regulates growth factor- and cytokine-induced RAS/ERK MAP kinase (MAPK) pathway activation, and aberrant SHP2 function causes developmental disorders and cancer1-5. It is widely believed that the catalytic activity of SHP2 is essential for pathway activation1,4,6-8. This view has shaped our interpretation of how germline PTPN11 mutations cause Noonan Syndrome (NS) and NS with Multiple Lentigines (NS-ML)2,9 and how somatic mutations contribute to myeloproliferative neoplasms and solid tumors1. Here we identify a previously undetected, protein-tyrosine phosphatase (PTP) activity-independent mechanism that revises our understanding of how SHP2 promotes RAS/ERK activation. We find that certain mutations of the nucleophilic cysteine that abolish catalytic activity still promote RAS/ERK pathway activation in normal and neoplastic mammalian cells, zebrafish embryos, and mice. Structural studies show that the SHP2 PTP domain binds directly to the Son of Sevenless 1 (SOS1) Dbl homology (DH) domain. Proximity labeling and super-resolution microscopy demonstrate that SHP2/SOS1 interaction occurs in cells and facilitates SOS1 translocation to the plasma membrane to form clusters. Our results overturn decades of dogma on SHP2 regulation of the RAS/ERK pathway and provide new insights into the mechanism of action of disease-associated PTPN11 mutations.

Cancer Biology↗

bioRxiv2026

Polypharmacology of an Optimal Kinase Library

Despite decades of research, current understanding of the spectrum of targets bound by kinase inhibitors remains incomplete. This complicates mechanism of action studies, drug repurposing, and development of new therapies. Here, we describe kinome-wide profiling of an optimal kinase library (OKL) comprising 192 small molecules selected based on stage of clinical development, chemical diversity, and target coverage. Our results show that polypharmacology is widespread and independent of regulatory approval. The generally understood ("assigned") targets of approved molecules are not necessarily the most potently inhibited and off-targets include multiple understudied kinases. Moreover, median selectivity has not increased over time We illustrate how an OKL in combination with detailed kinome profiling can be used to identify potential toxicity targets, repurpose anti-inflammatory drugs for neurodegenerative and infectious diseases, and perform chemical genetic studies. Our studies also highlight how much remains to be discovered about the chemistry and biology of one of the largest classes of human therapeutics.

pharmacology and toxicology↗

bioRxiv2026

BUSTED-PH: Isolating the genomic signatures of convergent phenotypes

Convergent evolution offers a natural test for adaptive predictability, yet pinpointing its molecular basis remains difficult. Current methods often grapple with distinguishing adaptive convergence from background noise, either by demanding overly stringent identical substitutions or relying on low-resolution evolutionary rate shifts. Here we introduce BUSTED-PH (Branch-site Unrestricted Statistical Test for Episodic Diversification - Phenotype), a branch-site codon model that detects phenotype-associated episodic diversifying selection. Unlike standard approaches, BUSTED-PH explicitly contrasts selective regimes between phenotype-positive (foreground) and phenotype-negative (background) lineages, effectively winnowing out spurious associations driven by pervasive background adaptation. BUSTED-PH has already been applied in numerous independent studies, and here we rigorously validate it using canonical positive controls and simulations to confirm high power and strict false positive control. A genome-wide scan of 120 mammalian species using strict statistical criteria (FDR [≤] 0.01) identified 72 genes associated with echolocation; while recovering paradigmatic auditory drivers (e.g., Prestin, TMC1 ), we also uncover novel candidates in physiological support systems ranging from lipid homeostasis to neural development. A parallel analysis of mammalian gigantism identifies 91 genes linked to musculoskeletal reinforcement, organ size governance, and genomic integrity, characterizing the molecular adaptations required to support massive body size. As projects like Zoonomia and the Vertebrate Genomes Project expand comparative datasets, BUSTED-PH provides a robust framework for dissecting the genetic architecture of complex convergent traits.

evolutionary biology↗

bioRxiv2026

Evolutionary rate covariation across malaria parasite species enables inference of protein interactions

Despite publication of the Plasmodium falciparum reference genome over 20 years ago, one-third of its genes remain functionally unannotated, and information is limited for many others. Proteins that act in the same pathway or complex tend to experience similar shifts in evolutionary pressure, such that correlated constraints across species can indicate co-functional proteins. To investigate this connection, we calculated relative evolutionary rates across the genome on a phylogeny of 22 Plasmodium species and assigned each protein-protein pair a score representing the strength of evolutionary rate covariation (ERC). We show that known pathways and interacting proteins across lifecycle stages in Plasmodium have strong ERC signals. By scanning genome-wide for additional proteins showing high ERC with established interacting proteins, we find enrichment of stage expression and physically interacting protein pairs supporting new candidate functions for proteins. More generally, we demonstrate the utility of ERC to prioritize proteins for hypothesis-driven functional follow up by showing that a protein with little functional characterization (PF3D7_0811600) shows high ERC and co-localizes with high molecular weight rhoptry proteins 2 and 3 (RhopH2 and RhopH3), which form an ion channel that enhances parasite permeability of infected red blood cells. The ERC matrix can be queried to extract Plasmodium proteins showing high ERC with any protein of interest to prioritize candidate genes and accelerate discovery of novel functional connections.

evolutionary biology↗

bioRxiv2026

Evolutionary conservation and innovations of RNA polymerase II transcription elongation factors

In eukaryotes, transcription elongation factors (TEFs) associate with RNA Polymerase II (RNAPII) to facilitate gene expression and couple transcription to co-transcriptional processes, including chromatin regulation and RNA processing. To further our understanding of TEF biology, we developed a domain-centric analysis pipeline to perform a broad survey of ten TEF orthologs -- Paf1, Ctr9, Cdc73, Rtf1, Leo1, Spt4, Spt5, Spt6, Spn1, and Elf1 -- across the Tree of Life and analyze their evolutionary patterns in a structural context. We report evidence for all ten TEFs being present in the last eukaryotic common ancestor, indicating that mechanisms of TEF-mediated transcription regulation are both ancient and conserved. However, some early-diverging eukaryotic clades exhibit signs of altered TEF domain composition. A comparative phylogenetic analysis highlighted conserved regions of TEFs that are detected in both metazoans and fungi and other regions that appear clade-specific, detected only in metazoans. These observations, together with additional insights generated from evolutionary rate covariation analysis, shed light on under-characterized aspects of TEFs, including domains for which functions have yet to be dissected.

evolutionary biology↗

bioRxiv2025

Abnormal Lipid Metabolism and Altered Neuronal Support by Astrocytes Lacking Akap11, a Risk Gene for Schizophrenia and Bipolar Disorder

A-Kinase Anchoring Protein 11 (AKAP11) is a shared genetic risk factor for schizophrenia and bipolar disorder, yet its role in the brain remains poorly understood. Through multi-omic analysis of Akap11 mutant mouse brains and cultured astrocytes, we identified significant transcriptomic, proteomic, and metabolomic alterations. Key findings include the upregulation of cholesterol and fatty acid metabolic pathways, accumulation of lipid species such as cholesteryl esters, triacylglycerols, ceramides, and glycerophospholipids, and elevated levels of 3,5-cyclic AMP and protein kinase A (PKA) signaling. These metabolic perturbations manifested as increased lipid droplet accumulation in Akap11 mutant astrocytes, highlighting AKAP11s critical role in regulating intracellular lipid homeostasis. Mechanistically, AKAP11 functions as an autophagy receptor mediating PKA degradation and interacts with endoplasmic reticulum-resident proteins VAP-A and VAP-B through its FFAT motif, providing possible molecular insight into AKAP11s regulation of lipid metabolism. Co-culture experiments with mouse astrocytes and human induced pluripotent stem cell-derived neurons demonstrated that loss of Akap11 in astrocytes, relative to wild-type, increases excitatory neurotransmission and neuronal activity. Collectively, these findings link AKAP11-mediated lipid and synaptic dysregulation to psychiatric disease risk and highlight the potential role of astrocytes in these disorders.

cell biology↗

bioRxiv2025

ERC 2.0 - evolutionary rate covariation update provides more powerful inference of functional interactions across large phylogenies

Evolutionary Rate Covariation (ERC) is an established comparative genomics method that identifies sets of genes sharing patterns of sequence evolution, which suggests shared function. Whereas many functional predictions of ERC have been empirically validated, its predictive power has hitherto been limited by its inability to tackle the large numbers of species in contemporary comparative genomics datasets. This study introduces ERC2.0, an enhanced methodology for studying ERC across phylogenies with hundreds of species and tens of thousands of genes. ERC2.0 improves upon previous iterations of ERC in algorithm speed, normalizing for heteroskedasticity, and normalizing correlations via Fisher transformations. These improvements have resulted in greater statistical power to predict biological function. In exemplar yeast and mammalian datasets, we demonstrate that the predictive power of ERC2.0 is improved relative to the previous method, ERC1.0, and that further improvements are obtained by using larger yeast and mammalian phylogenies. We attribute the improvements to both the larger datasets and improved rate normalization. We demonstrate that ERC2.0 has high predictive accuracy for known annotations and can predict the functions of genes in non-model systems. Our findings underscore the potential for ERC2.0 to be used as a single-pass computational tool in candidate gene screening and functional predictions.

evolutionary biology↗

bioRxiv2024

Minus the Error: Estimating dN/dS and Testing for Natural Selection in the Presence of Residual Alignment Errors

Positive selection is an evolutionary process which increases the frequency of advantageous mutations because they confer a fitness benefit. Inferring the past action of positive selection on protein-coding sequences is fundamental for deciphering phenotypic diversity and the emergence of novel traits. With the advent of genome-wide comparative genomic datasets, researchers can analyze selection not only at the level of individual genes but also globally, delivering systems-level insights into evolutionary dynamics. However, genome-scale datasets are generated with automated pipelines and imperfect curation that does not eliminate all sequencing, annotation, and alignment errors. Positive selection inference methods are highly sensitive to such errors. We present BUSTED-E: a method designed to detect positive selection for amino acid diversification while concurrently identifying some alignment errors. This method builds on the flexible branch-site random effects model (BUSTED) for fitting distributions of dN/dS, with a critical modification: it incorporates an "error-sink" component to represent an abiological evolutionary regime. Using several genome-scale biological datasets that were extensively filtered using state-of-the art automated alignment tools, we show that BUSTED-E identifies pervasive residual alignment errors, produces more realistic estimates of positive selection, reduces bias, and improves biological interpretation. The BUSTED-E model promises to be a more stringent filter to identify positive selection in genome-wide contexts, thus enabling further characterization and validation of the most biologically relevant cases.

evolutionary biology↗

bioRxiv2024

Upscaling production of immunogenic poliovirus virus-like particles in Pichia Pastoris by controlled fermentation

The success of the poliovirus (PV) vaccines has enabled the near-eradication of wild PV, however, their continued use post-eradication poses a significant threat to maintaining a polio-free world. Recombinant virus-like particles (VLPs) that lack the viral genome remove this risk. Here, we demonstrate the production of PV VLPs for all three serotypes by controlled fermentation using Pichia pastoris. We determined the cryo-EM structure of a new PV-2 mutant, termed SC5a, in comparison to PV-2 SC6b VLPs described previously and investigated the immunogenicity of PV-2 SC5a VLPs. Finally, a trivalent immunogenicity trial using bioreactor-derived VLPs of all three serotypes in the presence of Alhydrogel adjuvant, showed that these VLPs outperform the current IPV vaccine in the standard vaccine potency assay, offering the potential for dose-sparing. Overall, these results provide further evidence that yeast-produced VLPs have the potential to be a next-generation polio vaccine in a post-eradication world.

microbiology↗

bioRxiv2024

Mammalian retinal specializations for high acuity vision evolve in response to both foraging strategies and morphological constraints

Vision is a complex sensory system that requires coordination among cellular and morphological traits, and it remains unclear how functional relationships among traits interact with ecological selective pressures to shape the evolution of vision. Many species have specialized high visual acuity regions in the retina defined by patterns of ganglion cell density, which may evolve in response to ecological conditions. For example, ganglion cell density can increase radially towards the center of the retina to form an area centralis, which is thought to improve acuity towards the center of the visual field in predators. Another example is the horizontal streak, where ganglion cells are dense across the center of the retina, which is thought to be beneficial in horizon-dominated habitats. At the morphological level, many have proposed that predation selects for high orbit convergence angles, or forward-facing eyes. We tested these hypotheses in a phylogenetic framework across eutherian mammals and only found support for the association between the horizontal streak and horizon-dominated habitats. We also tested if retinal specializations evolve in response to orbit convergence angles. We found that horizontal streaks were associated with side-facing eyes, which may both facilitate panoramic vision. Previous studies observed that some species with side-facing eyes have an area centralis shifted towards the temporal side of the retina, such that the high acuity region would project forward, but this relationship had not been tested quantitatively. We found that the temporal distance of the area centralis from the center of the retina was inversely correlated with orbit convergence, as predicted. Our work shows a strong relationship between orbit convergence and retinal specializations. We find support that both visual ecology and functional interactions among traits play important roles in the evolution of some ocular traits across mammals.

evolutionary biology↗

bioRxiv2024

Phylogenetic signal in primate tooth enamel proteins and its relevance for paleoproteomics

Ancient tooth enamel, and to some extent dentin and bone, contain characteristic peptides that persist for long periods of time. In particular, peptides from the enamel proteome (enamelome) have been used to reconstruct the phylogenetic relationships of fossil specimens and to estimate divergence times. However, the enamelome is based on only about 10 genes, whose protein products undergo fragmentation post mortem. Moreover, some of the enamelome genes are paralogous or may coevolve. This raises the question as to whether the enamelome provides enough information for reliable phylogenetic inference. We address these considerations on a selection of enamel-associated proteins that has been computationally predicted from genomic data from 232 primate species. We created multiple sequence alignments (MSAs) for each protein and estimated the evolutionary rate for each site and examined which sites overlap with the parts of the protein sequences that are typically isolated from fossils. Based on this, we simulated ancient data with different degrees of sequence fragmentation, followed by phylogenetic analysis. We compared these trees to a reference species tree. Up to a degree of fragmentation that is similar to that of fossil samples from 1-2 million years ago, the phylogenetic placements of most nodes at family level are consistent with the reference species tree. We found that the composition of the proteome influences the phylogenetic placement of Tarsiiformes. For the inference of molecular phylogenies based on paleoproteomic data, we recommend characterizing the evolution of the proteomes from the closest extant relatives to maximize the reliability of phylogenetic inference.

evolutionary biology↗

bioRxiv2023

RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution

Comparative genomics approaches seek to associate evolutionary genetic changes with the evolution of phenotypes across a phylogeny. Many of these methods, including our evolutionary rates based method, RERconverge, lack the capability of analyzing non-ordinal, multicategorical traits. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of multi-categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogenetic permulations on multi-categorical traits. In addition to demonstrating our new method on a three-category diet phenotype, we compare its performance to naive pairwise binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We also present a diagnostic analysis of the new permulations approach demonstrating how the method scales with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotype and that the new ancestral reconstruction drives an improvement in our ability to capture diet-related enriched pathways. Our categorical permulations were able to account for non-uniform null distributions and correct for non-independence in gene rank during pathway enrichment analysis. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution.

bioinformatics↗

bioRxiv2023

SERF2, an RNA G-quadruplex Binding Protein, promotes stress granule formation

Liquid-liquid phase transitions govern a wide range of protein-protein and protein-RNA interactions. Although the importance of multivalency and protein disorder in driving these transitions is clear, there is limited knowledge concerning the structural basis of phase transitions or the conformational changes that accompany this process. In this work, we found that a small human protein, SERF2, is important for the formation of stress granules. We determined the solution NMR structure ensemble of SERF2. We show that SERF2 specifically interacts with non-canonical tetrahelical RNA structures called G-quadruplexes, structures linked to stress granule formation. The biophysical amenability of both SERF2 and RNA G4 quadruplexes have allowed us to characterize the multivalent protein-RNA interactions involved in liquid-liquid phase transitions, the role that protein disorder plays in these transitions, identify the specific contacts involved, and describe how these interactions impact the structural dynamics of the components enabling a detailed understanding of the structural transitions involved in early stages of ribonucleoprotein condensate formation.

cell biology↗

bioRxiv2023

Effects of protein G-quadruplex interactions on phase transitions and protein aggregation

The SERF family of proteins were originally discovered for their ability to accelerate amyloid formation. Znf706 is an uncharacterized protein whose N-terminus is homologous to SERF proteins. We show here that human Znf706 can promote protein aggregation and amyloid formation. Unexpectedly, Znf706 specifically interacts with stable, non-canonical nucleic acid structures known as G-quadruplexes. G-quadruplexes can affect gene regulation and suppress protein aggregation; however, it is unknown if and how these two activities are linked. We find Znf706 binds preferentially to parallel G-quadruplexes with low micromolar affinity, primarily using its N-terminus, and upon interaction, its dynamics are constrained. G-quadruplex binding suppresses Znf706s ability to promote protein aggregation. Znf706 in conjunction with G-quadruplexes therefore may play a role in regulating protein folding. RNAseq analysis shows that Znf706 depletion specifically impacts the mRNA abundance of genes that are predicted to contain high G-quadruplex density. Our studies give insight into how proteins and G-quadruplexes interact, and how these interactions affect both partners and lead to the modulation of protein aggregation and cellular mRNA levels. These observations suggest that the SERF family of proteins, in conjunction with G-quadruplexes, may have a broader role in regulating protein folding and gene expression than previously appreciated.

biochemistry↗

bioRxiv2022

Prediction of local convergent shifts in evolutionary rates with phyloConverge characterizes the phenotypic associations and modularity of regulatory elements

Physiological and morphological adaptations to extreme environments arise from the molecular evolution of protein-coding regions and regulatory elements (REs) that regulate gene expression. Comparative genomics methods can characterize genetic elements that underlie the organism-level adaptations, but convergence analyses of REs are often limited by their evolutionary properties. A RE can be modularly composed of multiple transcription factor binding sites (TFBS) that may each experience different evolutionary pressures. The modular composition and rapid turnover of TFBS also enables a compensatory mechanism among nearby TFBS that allows for weaker sequence conservation/divergence than intuitively expected. Here, we introduce phyloConverge, a comparative genomics method that can perform fast, fine-grained local convergence analysis of genetic elements. phyloConverge calibrates for local shifts in evolutionary rates using a combination of maximum likelihood-based estimation of nucleotide substitution rates and phylogenetic permutation tests. Using the classical convergence case of mammalian adaptation to subterranean environments, we validate that phyloConverge identifies rate-accelerated conserved non-coding elements (CNEs) that are strongly correlated with ocular tissues, with improved specificity compared to competing methods. We use phyloConverge to perform TFBS-scale and nucleotide-scale scoring to dissect each CNE into subregions with uneven convergence signals and demonstrate its utility for understanding the modularity and pleiotropy of REs. Subterranean-accelerated regions are also enriched for molecular pathways and TFBS motifs associated with neuronal phenotypes, suggesting that subterranean eye degeneration may coincide with a remodeling of the nervous system. phyloConverge offers a rapid and accurate approach for understanding the evolution and modularity of regulatory elements underlying phenotypic adaptation.

evolutionary biology↗

bioRxiv2021

Evolutionary rate covariation identifies SLC30A9 (ZnT9) as a mitochondrial zinc transporter.

Recent advances in genome sequencing have led to the identification of new ion and metabolite transporters, many of which have not been characterized. Due to the variety of subcellular localizations, cargo and transport mechanisms, such characterization is a daunting task, and predictive approaches focused on the functional context of transporters are very much needed. Here we present a case for identifying a transporter localization using evolutionary rate covariation (ERC), a computational approach based on pairwise correlations of amino acid sequence evolutionary rates across the mammalian phylogeny. As a case study, we find that poorly characterized transporter SLC30A9 (ZnT9) uniquely and prominently coevolves with several components of the mitochondrial oxidative phosphorylation chain, suggesting mitochondrial localization. We confirmed this computational finding experimentally using recombinant human SLC30A9. SLC30A9 loss caused zinc mishandling in the mitochondria, suggesting that under normal conditions it acts as a zinc exporter. We therefore propose that ERC can be used to predict the functional context of novel transporters and other poorly characterized proteins.

evolutionary biology↗

bioRxiv2021

Complementary evolution of coding and noncoding sequence underlies mammalian hairlessness

Body hair is a defining mammalian characteristic, but several mammals, such as whales, naked mole-rats, and humans, have notably less hair than others. To find the genetic basis of reduced hair quantity, we used our evolutionary-rates-based method, RERconverge, to identify coding and noncoding sequences that evolve at significantly different rates in so-called hairless mammals compared to hairy mammals. Using RERconverge, we performed an unbiased, genome-wide scan over 62 mammal species using 19,149 genes and 343,598 conserved noncoding regions to find genetic elements that evolve at significantly different rates in hairless mammals compared to hairy mammals. We show that these rate shifts resulted from relaxation of evolutionary constraint on hair-related sequences in hairless species. In addition to detecting known and potential novel hair-related genes, we also discovered hundreds of putative hair-related regulatory elements. Computational investigation revealed that genes and their associated noncoding regions show different evolutionary patterns and influence different aspects of hair growth and development. Many genes under accelerated evolution are associated with the structure of the hair shaft itself, while evolutionary rate shifts in noncoding regions also included the dermal papilla and matrix regions of the hair follicle that contribute to hair growth and cycling. Genes that were top-ranked for coding sequence acceleration included known hair and skin genes KRT2, KRT35, PKP1, and PTPRM that surprisingly showed no signals of evolutionary rate shifts in nearby noncoding regions. Conversely, accelerated noncoding regions are most strongly enriched near regulatory hair-related genes and microRNAs, such as mir205, ELF3, and FOXC1, that themselves do not show rate shifts in their protein-coding sequences. Such dichotomy highlights the interplay between the evolution of protein sequence and regulatory sequence to contribute to the emergence of a convergent phenotype.

evolutionary biology↗

bioRxiv2021

Generalizable EEG encoding models with naturalistic audiovisual stimuli

In natural conversations, listeners must attend to what others are saying while ignoring extraneous background sounds. Recent studies have used encoding models to predict electroencephalography (EEG) responses to speech in noise-free listening situations, sometimes referred to as "speech tracking" in EEG. Researchers have analyzed how speech tracking changes with different types of background noise. It is unclear, however, whether neural responses from noisy and naturalistic environments can be generalized to more controlled stimuli. If encoding models for noisy, naturalistic stimuli are generalizable to other tasks, this could aid in data collection from populations who may not tolerate listening to more controlled, less-engaging stimuli for long periods of time. We recorded non-invasive scalp EEG while participants listened to speech without noise and audiovisual speech stimuli containing overlapping speakers and background sounds. We fit multivariate temporal receptive field (mTRF) encoding models to predict EEG responses to pitch, the acoustic envelope, phonological features, and visual cues in both noise-free and noisy stimulus conditions. Our results suggested that neural responses to naturalistic stimuli were generalizable to more controlled data sets. EEG responses to speech in isolation were predicted accurately using phonological features alone, while responses to noisy speech were more accurate when including both phonological and acoustic features. These findings may inform basic science research on speech-in-noise processing. Ultimately, they may also provide insight into auditory processing in people who are hard of hearing, who use a combination of audio and visual cues to understand speech in the presence of noise. Significance StatementUnderstanding spoken language in natural environments requires listeners to parse acoustic and linguistic information in the presence of other distracting stimuli. However, most studies of auditory processing rely on highly controlled stimuli with no background noise, or with background noise inserted at specific times. Here, we compare models where EEG data are predicted based on a combination of acoustic, phonetic, and visual features in highly disparate stimuli - sentences from a speech corpus, and speech embedded within movie trailers. We show that modeling neural responses to highly noisy, audiovisual movies can uncover tuning for acoustic and phonetic information that generalizes to simpler stimuli typically used in sensory neuroscience experiments.

neuroscience↗