Biology subjects

Yeung, W.

Publications and source records attributed to Yeung, W..

16 recordsLinked to original sources

bioRxiv2025

Mistranslation protects against lifespan reduction due to mating in Drosophila melanogaster females.

Accurate translation of genes into proteins is critical to organism fitness, and errors in this process are usually detrimental and cause proteotoxic stress. Mistranslation occurs when the amino acid that is incorporated into the nascent polypeptide chain does not match what is dictated by the genetic code. Valine-to-serine (V[->]S) and threonine-to-serine (T[->]S) mistranslating models of the fruit fly Drosophila melanogaster have demonstrated a surprising, sex-specific increase in virgin female longevity. We predict that the added stressor of reproduction would eliminate this mistranslation-induced lifespan increase since females prioritize reproductive tissues over somatic tissues, and proteotoxic stress would therefore lead to higher protein damage in the soma of mated females. We measured the impact of reproduction on V[->]S and T[->]S mistranslating D. melanogaster by measuring longevity, egg laying, and fecundity. Counter to our prediction, both V[->]S and T[->]S mistranslation led to a sex-specific increase in mated female longevity compared to non-mistranslating controls. Additionally, the risk of death decreased for mated females with mistranslation, beyond the pure additive benefits of mistranslation alone. These effects could not be explained by reduced egg laying or fertilization rates in mistranslating females. Thus, we find that the added proteotoxic stress caused by mistranslation does not exacerbate the detrimental effects of reproduction and instead can ameliorate lifespan decreases due to female reproduction.

genetics↗

bioRxiv2025

Atlas of the Bacterial Serine-Threonine Kinases expands the functional diversity of the kinome

Bacterial serine-threonine protein kinases (STKs) regulate diverse cellular processes associated with cell growth, virulence, and pathogenicity. They are evolutionarily related to the druggable eukaryotic STKs. However, an incomplete knowledge of how bacterial STKs differ from their eukaryotic counterparts and how they have diverged to regulate diverse bacterial signaling functions presents a bottleneck in targeting them for drug discovery efforts. Here, we classified over 300,000 bacterial STK sequences from the NCBI RefSeq non-redundant and UniProt protein databases into 35 canonical and seven non-canonical (pseudokinase) families based on the patterns of evolutionary constraints in the conserved catalytic domain and flanking regulatory domains. Through statistical comparisons, we identified distinguishing features of bacterial STKs, including a distinctive arginine residue in a regulatory helix (C-Helix) that dynamically couples ATP and substrate binding lobes of the kinase domain. Biochemical and peptide-library screens demonstrated that constrained residues contribute to substrate specificity and kinase activation in the Mycobacterium tuberculosis kinase PknB. Collectively, these findings open new avenues for investigating bacterial STK functions in cellular signaling and for the development of selective bacterial STK inhibitors.

bioinformatics↗

bioRxiv2024

Mistranslating tRNA variants have anticodon- and sex-specific impacts on Drosophila melanogaster

Transfer RNAs (tRNAs) are vital in determining the specificity of translation. Mutations in tRNA genes can result in the misincorporation of amino acids into nascent polypeptides in a process known as mistranslation. Since mistranslation has different impacts, depending on the type of amino acid substitution, our goal here was to compare the impact of different mistranslating tRNASer variants on fly development, lifespan, and behaviour. We established two mistranslating fly lines, one with a tRNASer variant that misincorporates serine at valine codons (VS) and the other that misincorporates serine at threonine codons (TaS). While both mistranslating tRNAs increased development time and developmental lethality, the severity of the impacts differed depending on amino acid substitution and sex. The VS variant extended embryonic, larval, and pupal development whereas the TS only extended larval and pupal development. Females, but not males, containing either mistranslating tRNA presented with significantly more anatomical deformities than controls. Mistranslating females also experienced extended lifespan whereas mistranslating male lifespan was unaffected. In addition, mistranslating flies from both sexes showed improved locomotion as they aged, suggesting delayed neurodegeneration. Therefore, although mistranslation causes detrimental effects, we demonstrate that mistranslation also has positive effects on complex traits such as lifespan and locomotion. This has important implications for human health given the prevalence of tRNA variants in humans. PLAIN LANGUAGE SUMMARYMutant tRNA genes can cause mistranslation, the misincorporation of amino acids into proteins, and are associated with several human diseases. This study investigated the role of two tRNA variants that cause threonine-to-serine (TS) or valine-to-serine (VS) substitution. Both variants caused developmental delays and lethality in both sexes and increase prevalence of deformities in females. Surprisingly, female TS and VS flies experienced increased lifespan and mistranslating males and females showed improved locomotion. These results suggest that mistranslation has both positive and negative effects that depend on the tRNA variant and sex of the fly.

genetics↗

bioRxiv2024

Impact of tRNA-induced proline-to-serine mistranslation on the transcriptome of Drosophila melanogaster

Mistranslation is the misincorporation of an amino acid into a polypeptide. Mistranslation has diverse effects on multicellular eukaryotes and is implicated in several human diseases. In Drosophila melanogaster, a serine transfer RNA (tRNA) that misincorporates serine at proline codons (P[->]S) affects male and female flies differently. The mechanisms behind this discrepancy are currently unknown. Here, we compare the transcriptional response of male and female flies to P[->]S mistranslation to identify genes and cellular processes that underlie sex-specific differences. Both males and females downregulate genes associated with various metabolic processes in response to P[->]S mistranslation. Males downregulate genes associated with extracellular matrix organization and response to negative stimuli such as wounding, whereas females downregulate aerobic respiration and ATP synthesis genes. Both sexes upregulate genes associated with gametogenesis, but females also upregulate cell cycle and DNA repair genes. These observed differences in the transcriptional response of male and female flies to P[->]S mistranslation have important implications for the sex-specific impact of mistranslation on disease and tRNA therapeutics. ARTICLE SUMMARYProline-to-serine mistranslation affects male and female flies differently, but the mechanisms underlying this discrepancy are unknown. We present a transcriptomic analysis of male and female flies showing that mistranslation disrupts metabolic pathways and gametogenesis in both sexes, whereas processes such as DNA repair and cell cycle regulation are affected only in one sex. This is the first analysis that characterizes sex-specific effects of mistranslation and provides intriguing avenues for future research to understand how mistranslation affects males and females.

genetics↗

bioRxiv2023

Redox Regulation of Brain Selective Kinases BRSK1/2: Implications for Dynamic Control of the Eukaryotic AMPK family through Cys-based mechanisms

In eukaryotes, protein kinase signaling is regulated by a diverse array of post-translational modifications (PTMs), including phosphorylation of Ser/Thr residues and oxidation of cysteine (Cys) residues. While regulation by activation segment phosphorylation of Ser/Thr residues is well understood, relatively little is known about how oxidation of cysteine residues modulate catalysis. In this study, we investigate redox regulation of the AMPK-related Brain-selective kinases (BRSK) 1 and 2, and detail how broad catalytic activity is directly regulated through reversible oxidation and reduction of evolutionarily conserved Cys residues within the catalytic domain. We show that redox-dependent control of BRSKs is a dynamic and multilayered process involving oxidative modifications of several Cys residues, including the formation of intra-molecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys within an unusual CPE motif at the end of the activation segment. Consistently, mutation of the CPE-Cys increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family.

biochemistry↗

bioRxiv2023

Mechanistic and evolutionary insights into isoform-specific 'supercharging' in DCLK family kinases

Catalytic signaling outputs of protein kinases are dynamically regulated by an array of structural mechanisms, including allosteric interactions mediated by intrinsically disordered segments flanking the conserved catalytic domain. The Doublecortin Like Kinases (DCLKs) are a family of microtubule-associated proteins characterized by a flexible C-terminal autoregulatory tail segment that varies in length across the various human DCLK isoforms. However, the mechanism whereby these isoform-specific variations contribute to unique modes of autoregulation is not well understood. Here, we employ a combination of statistical sequence analysis, molecular dynamics simulations and in vitro mutational analysis to define hallmarks of DCLK family evolutionary divergence, including analysis of splice variants within the DCLK1 sub-family, which arise through alternative codon usage and serve to supercharge the inhibitory potential of the DCLK1 C-tail. We identify co-conserved motifs that readily distinguish DCLKs from all other Calcium Calmodulin Kinases (CAMKs), and a Swiss-army assembly of distinct motifs that tether the C-terminal tail to conserved ATP and substrate-binding regions of the catalytic domain to generate a scaffold for auto-regulation through C-tail dynamics. Consistently, deletions and mutations that alter C-terminal tail length or interfere with co-conserved interactions within the catalytic domain alter intrinsic protein stability, nucleotide/inhibitor-binding, and catalytic activity, suggesting isoform-specific regulation of activity through alternative splicing. Our studies provide a detailed framework for investigating kinome-wide regulation of catalytic output through cis-regulatory events mediated by intrinsically disordered segments, opening new avenues for the design of mechanistically-divergent DCLK1 modulators, stabilizers or degraders.

evolutionary biology↗

bioRxiv2023

Yeast Farnesyltransferase has broad reactivity with CXXX sequences

The current understanding of farnesyltransferase (FTase) specificity was pioneered through investigations of reporters like Ras and Ras-related proteins that possess a C-terminal CaaX motif that consists of 4 amino acid residues: Cysteine - aliphatic1 - aliphatic2 - variable (X). These studies led to the finding that proteins with the CaaX motif are subject to a 3-step post-translational modification pathway involving farnesylation, proteolysis, and carboxylmethylation. Emerging evidence indicates, however, that FTase can farnesylate sequences outside the CaaX motif and that these sequences do not undergo the canonical 3-step pathway. In this work, we report a comprehensive evaluation of all possible CXXX sequences as FTase targets using the reporter Ydj1, an Hsp40 chaperone that only requires farnesylation for its activity. Our genetic and high throughput sequencing approach reveals an unprecedented profile of sequences that yeast FTase can recognize in vivo, which effectively expands the potential target space of FTase within the yeast proteome. We also document that yeast FTase specificity is majorly influenced by restrictive amino acids at a2 and X positions as opposed to the resemblance of CaaX motif as previously regarded. This first complete evaluation of CXXX space expands the complexity of protein isoprenylation and marks a key step forward in understanding the potential scope of targets for this isoprenylation pathway.

genetics↗

bioRxiv2022

Dark kinase annotation, mining and visualization using the Protein Kinase Ontology

The Protein Kinase Ontology (ProKinO) is an integrated knowledge graph that conceptualizes the complex relationships connecting protein kinase sequence, structure, function, and disease in a human and machine-readable format. Here we extend the scope of ProKinO as a discovery tool by including new classes and relationships capturing information on kinase ligand binding sites, expression patterns, and functional features, and demonstrate its application in uncovering new knowledge regarding understudied members of the protein kinase family. Specifically, through graph mining and aggregate SPARQL queries, we identify the p21-activated protein kinase 5 (PAK5) as one of the most frequently mutated dark kinase in human cancers with abnormal expression in multiple cancers, including an unappreciated role in acute myeloid leukemia. We identify recurrent oncogenic mutations in the PAK5 activation loop predicted to alter substrate binding and phosphorylation and identify common ligand/drug binding residues in PAK family kinases, highlighting the potential application of ProKinO in drug discovery. The updated ontology browser and a web component, ProtVista, which allows interactive mining of kinase sequence annotations in 3D structures and Alphafold models, provide a valuable resource for the signaling community. The updated ProKinO database is accessible at http://prokino.uga.edu/browser/.

bioinformatics↗

bioRxiv2022

An explainable unsupervised framework for alignment-free protein classification using sequence embeddings

Protein classification is a cornerstone of biology that relies heavily on alignment-based comparison of primary sequences. However, the systematic classification of large protein superfamilies is impeded by unique challenges in aligning divergent sequence datasets. We developed an alignment-free approach for sequence analysis and classification using embedding vectors generated from pre-trained protein language models that capture underlying protein structural-functional properties from unsupervised training on millions of biologically-observed sequences. We constructed embedding-based trees (with branch support) which depict hierarchical clustering of protein sequences and infer fast/slow evolving sites through interpretable sequence projections. Applied towards diverse protein superfamilies, embedding tree infers Casein Kinase 1 (CK1) as the basal protein kinase clade, identifies convergent functional motifs shared between divergent phosphatase folds, and infers evolutionary relationships between diverse radical S-Adenosyl-L-Methionine (SAM) enzyme families. Overall results indicate that embedding trees effectively capture global data structures, functioning as a general unsupervised approach for visualizing high-dimensional manifolds.

bioinformatics↗

bioRxiv2021

Functional classification and validation of yeast prenylation motifs using machine learning and genetic reporters

Protein prenylation by farnesyltransferase (FTase) is often described as the targeting of a cysteine-containing motif (CaaX) that is enriched for aliphatic amino acids at the a1 and a2 positions, while quite flexible at the X position. Prenylation prediction methods often rely on these features despite emerging evidence that FTase has broader target specificity than previously considered. Using a machine learning approach and training sets based on canonical (prenylated, proteolyzed, and carboxymethylated) and recently identified shunted motifs (prenylation only), this study aims to improve prenylation predictions with the goal of determining the full scope of prenylation potential among the 8000 possible Cxxx sequence combinations. Further, this study aims to subdivide the prenylated sequences as either shunted (i.e., uncleaved) or cleaved (i.e., canonical). Predictions were determined for Saccharomyces cerevisiae FTase and compared to results derived using currently available prenylation prediction methods. In silico predictions were further evaluated using in vivo methods coupled to two yeast reporters, the yeast mating pheromone a-factor and Hsp40 Ydj1p, that represent proteins with canonical and shunted CaaX motifs, respectively. Our machine learning based approach expands the repertoire of predicted FTase targets and provides a framework for functional classification.

biochemistry↗

bioRxiv2021

Evolution of functional diversity in the holozoan tyrosine kinome

The emergence of multicellularity is strongly correlated with the expansion of tyrosine kinases, a conserved family of signaling enzymes that regulates pathways essential for cell-to-cell communication. Although tyrosine kinases have been classified from several model organisms, a molecular-level understanding of tyrosine kinase evolution across all holozoans is currently lacking. Using a hierarchical sequence constraint-based classification of diverse holozoan tyrosine kinases, we construct a new phylogenetic tree that identifies two ancient clades of cytoplasmic and receptor tyrosine kinases separated by the presence of an extended insert segment in the kinase domain connecting the D and E helices. Present in nearly all receptor tyrosine kinases, this fast-evolving insertion imparts diverse functionalities such as post-translational modification sites and regulatory interactions. Eph and EGFR receptor tyrosine kinases are two exceptions which lack this insert, each forming an independent lineage characterized by unique functional features. We also identify common constraints shared across multiple tyrosine kinase families which warrant the designation of three new subgroups: Src Module (SrcM), Insulin Receptor Kinase-Like (IRKL), and Fibroblast, Platelet-derived, Vascular, and growth factor Receptors (FPVR). Subgroup-specific constraints reflect shared autoinhibitory interactions involved in kinase conformational regulation. Conservation analyses describe how diverse tyrosine kinase signaling functions arose through the addition of family-specific motifs upon subgroup-specific features and co-evolving protein domains. We propose the oldest tyrosine kinases, IRKL, SrcM, and Csk, originated from unicellular pre-metazoans and were co-opted for complex multicellular functions. The increased frequency of oncogenic variants in more recent tyrosine kinases suggests that lineage-specific functionalities are selectively altered in human cancers.

evolutionary biology↗

bioRxiv2021

Mapping the glycosyltransferase fold landscape using deep learning

Glycosyltransferases (GTs) play fundamental roles in nearly all cellular processes through the biosynthesis of complex carbohydrates and glycosylation of diverse protein and small molecule substrates. The extensive structural and functional diversification of GTs presents a major challenge in mapping the relationships connecting sequence, structure, fold and function using traditional bioinformatics approaches. Here, we present a convolutional neural network with attention (CNN-attention) based deep learning model that leverages simple secondary structure representations generated from primary sequences to provide GT fold prediction with high accuracy. The model learned distinguishing features free of primary sequence alignment constraints and, unlike other models, is highly interpretable and helped identify common secondary structural features shared by divergent families. The model delineated sequence and structural features characteristic of individual fold types, while classifying them into distinct clusters that group evolutionarily divergent families based on shared secondary structural features. We further extend our model to classify GT families of unknown folds and variants of known folds. By identifying families that are likely to adopt novel folds such as GT91, GT96 and GT97, our studies identify targets for future structural studies and expand the GT fold landscape.

bioinformatics↗

bioRxiv2021

KinOrtho: a method for mapping human kinase orthologs across the tree of life and illuminating understudied kinases

Protein kinases are among the largest druggable family of signaling proteins, involved in various human diseases, including cancers and neurodegenerative disorders. Despite their clinical relevance, nearly 30% of the 545 human protein kinases remain highly understudied. Comparative genomics is a powerful approach for predicting and investigating the functions of understudied kinases. However, an incomplete knowledge of kinase orthologs across fully sequenced kinomes severely limits the application of comparative approaches for illuminating understudied kinases. Here, we propose KinOrtho, a query- and graph-based orthology inference method that combines full-length and domain-based approaches to map one-to-one kinase orthologs across 17 thousand species. Using multiple metrics, we show that KinOrtho performed better than existing methods in identifying kinase orthologs across evolutionarily divergent species and eliminated potential false positives by flagging sequences without a proper kinase domain for further evaluation. We demonstrate the advantage of using domain-based approaches for identifying domain fusion events, highlighting a case between an understudied serine/threonine kinase TAOK1 and a metabolic kinase PIK3C2A with high co-expression in human cells. We also identify evolutionary fission events involving the understudied OBSCN kinase domains, further highlighting the value of domain-based orthology inference approaches. Using KinOrtho-defined orthologs, Gene Ontology annotations, and machine learning, we propose putative biological functions of several understudied kinases, including the role of TP53RK in cell cycle checkpoint(s), the involvement of TSSK3 and TSSK6 in acrosomal vesicle localization, and potential functions for the ULK4 pseudokinase in neuronal development. The well-curated kinome ortholog set can serve as a valuable resource for illuminating understudied kinases, and the KinOrtho framework can be extended to any gene-family of interest.

evolutionary biology↗

bioRxiv2019

Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases

Glycosyltransferases (GTs) are prevalent across the tree of life and regulate nearly all aspects of cellular functions by catalyzing synthesis of glycosidic linkages between diverse donor and acceptor substrates. Despite the availability of GT sequences from diverse organisms, the evolutionary basis for their complex and diverse modes of catalytic and regulatory functions remain enigmatic. Here, based on deep mining of over half a million GT-A fold sequences from diverse organisms, we define a minimal core component shared among functionally diverse enzymes. We find that variations in the common core and the emergence of hypervariable loops extending from the core contributed to the evolution of catalytic and functional diversity. We provide a phylogenetic framework relating diverse GT-A fold families for the first time and show that inverting and retaining mechanisms emerged multiple times independently during the course of evolution. We identify conserved modes of donor and acceptor recognition in evolutionarily divergent families and pinpoint the sequence and structural features for functional specialization. Using the evolutionary information encoded in primary sequences, we trained a machine learning classifier to predict donor specificity with nearly 88% accuracy and deployed it for the annotation of understudied GTs in five model organisms. Our studies provide an evolutionary framework for investigating the complex relationships connecting GT-A fold sequence, structure, function and regulation.

bioinformatics↗

bioRxiv2019

Quantitative Structure-Mutation-Activity Relationship Tests (QSMART) Model for Protein Kinase Inhibitor Response Prediction

Predicting drug sensitivity profiles from genotypes is a major challenge in personalized medicine. Machine learning and deep neural network methods have shown promise in addressing this challenge, but the "black-box" nature of these methods precludes a mechanistic understanding of how and which genomic and proteomic features contribute to the observed drug sensitivity profiles. Here we provide a combination of statistical and neural network framework that not only estimates drug IC50 in cancer cell lines with high accuracy (R2 = 0.861 and RMSE = 0.818) but also identifies features contributing to the accuracy, thereby enhancing explainability. Our framework, termed QSMART, uses a multi-component approach that includes (1) collecting drug fingerprints, cancer cell lines multi-omics features, and drug responses, (2) testing the statistical significance of interaction terms, (3) selecting features by Lasso with Bayesian information criterion, and (4) using neural networks to predict drug response. We evaluate the contribution of each of these components and use a case study to explain the biological relevance of several selected features to protein kinase inhibitor response in non-small cell lung cancer cells. Specifically, we illustrate how interaction terms that capture associations between drugs and mutant kinases quantitatively contribute to the response of two EGFR inhibitors (afatinib and lapatinib) in non-small cell lung cancer cells. Although we have tested QSMART on protein kinase inhibitors, it can be extended across the proteome to investigate the complex relationships connecting genotypes and drug sensitivity profiles.

bioinformatics↗

bioRxiv2018

Repurposing covalent EGFR/HER2 inhibitors for on-target degradation of human Tribbles 2 (TRIB2) pseudokinase

ONE SENTENCE SUMMARYA Tribbles 2 pseudokinase small molecule screen led to the identification of known EGFR/HER2 inhibitors that alter the stability of TRIB2 in vitro and lead to rapid on-target degradation of TRIB2 in human cancer cells.\n\nSHORT ABSTRACTTribbles 2 (TRIB2) is a cancer-associated pseudokinase with a diverse interactome, including the AKT signaling module. Substantial evidence demonstrates that TRIB2 dysregulation is important in multiple human tumors. The non-canonical TRIB2 pseudokinase domain contains a unique cysteine rich region and interacts with a peptide motif in its own C-terminal tail. We demonstrate that TRIB2 is a target for previously described small molecule protein kinase inhibitors, which were originally designed to inhibit the catalytic domain of EGFR/HER2 tyrosine kinases. Using thermal-shift assays and drug repurposing, we classify ligands that stabilize or destabilize the TRIB2 pseudokinase domain. TRIB2 destabilizing agents, including the clinical inhibitor afatinib, lead to rapid and on-target TRIB2 protein degradation in tumor cells, eliciting tractable effects on cell signaling and survival. Our data identifies leads for further development of TRIB2-degrading drugs and highlights compound-induced TRIB2 downregulation, which might be mechanistically relevant for other catalytically-deficient (pseudo)kinases targeted by small molecules.\n\nFULL ABSTRACTA major challenge associated with biochemical and cellular analysis of pseudokinases is the lack of target-validated small molecule ligands with which to probe molecular function. Human Tribbles 2 (TRIB2) is a cancer-associated pseudokinase with a diverse interactome, which includes the canonical AKT signaling module. There is substantial evidence that human TRIB2 is a therapeutic target in both solid tumors and blood cancers. The non-canonical TRIB2 pseudokinase domain contains a unique cysteine-rich region and interacts with a peptide motif in its own C-terminal tail, which was previously shown to drive interaction with cellular E3 ubiquitin ligases. In this study we demonstrate that TRIB2 is a target for previously described small molecule protein kinase inhibitors, which were originally designed to inhibit the canonical catalytic domain of the tyrosine kinases EGFR/HER2. Using a thermal-shift assay, we discovered TRIB2 ligands within the Published Kinase Inhibitor Set (PKIS), and employed a drug repurposing approach to classify compounds that either stabilize or destabilize TRIB2 in vitro. Remarkably, TRIB2 destabilizing agents, including the clinical covalent drug afatinib, lead to rapid and on-target TRIB2 degradation in human cells, eliciting tractable effects on signaling and survival. Our data reveal the first drug-leads for development of TRIB2-degrading ligands, which will also be invaluable for unravelling the cellular mechanisms of TRIB2-based signaling. Our study highlights that small molecule-induced protein downregulation through drug off-targets might be relevant for other inhibitors that serendipitously target pseudokinases.

biochemistry↗