Biology subjects

Kannan, N.

Publications and source records attributed to Kannan, N..

At least 37 records · Page 2Linked to original sources

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

Evolutionary and cellular analysis of the dark pseudokinase PSKH2

Pseudokinases, so named because they lack one or more conserved canonical amino acids that define their catalytically-active relatives, have evolved a variety of biological functions in both prokaryotic and eukaryotic organisms. Human PSKH2 is closely related to the canonical kinase PSKH1, which maps to the CAMK family of protein kinases. Primates encode PSKH2 in the form of a pseudokinase, which is predicted to be catalytically inactive due to loss of the invariant catalytic Asp residue. Although the biological role(s) of vertebrate PSKH2s remains unclear, we previously identified species-level adaptions in PSKH2 that have led to the appearance of kinase or pseudokinase variants in vertebrate genomes alongside a canonical PSKH1 paralog. In this paper we confirm that, as predicted, PSKH2 lacks detectable protein phosphotransferase activity, and exploit structural informatics, biochemistry and cellular proteomics to begin to characterise vertebrate PSKH2 orthologues. AlphaFold 2-based structural analysis predicts functional roles for both the PSKH2 N- and C-regions that flank the pseudokinase domain core, and cellular truncation analysis confirms that the N-terminal domain, which contains a conserved myristoylation site, is required for both stable human PSKH2 expression and localisation to a membrane-rich subcellular fraction containing mitochondrial proteins. Using mass spectrometry-based proteomics, we confirm that human PSKH2 is part of a cellular mitochondrial protein network, and that its expression is regulated through client-status within the HSP90/Cdc37 molecular chaperone system. HSP90 interactions are mediated through binding to the PSKH2 C-terminal tail, leading us to predict that this region might act as both a cis and trans regulatory element, driving outputs linked to the PSKH2 pseudokinase domain that are important for functional signalling.

biochemistry↗

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

Barcoded Competitive Clone-Initiating Cell (BC-CIC) Analysis Reveals Differences in Ovarian Cancer Cell Genotype and Niche Specific Clonal Fitness During Growth and Metastasis In Vivo

During oncogenesis, pathogenic clones develop which contain cells capable of spreading throughout the body, ultimately compromising vital organ functions and physiology. Understanding how metastatic clones develop and spread is critical for improving cancer treatments. However, our understanding of these processes has been hampered by a paucity of quantitative methodologies to comprehensively map, track and characterize such clones. To address this shortcoming, we have developed a DNA barcoding and next-generation sequencing based system-wide clonal tracking technology integrated with a computational data analysis pipeline called Clone-Initiating Cell (CIC) Calculator. The CIC Calculator interfaces with the CIC Morbus Mandala (CIC-MM) plot, a novel tool to visually comprehend and detect four distinct categories that explains their complex relationships with various tissues/organ sites. Further, we describe machine learning approaches to study CIC number, frequency, and estimate clone size and distribution demonstrating distinct growth patterns, and their inter-relationships and their routes of metastatic spread at clonal resolution. We demonstrate these methodologies, using our novel multifunctional lentiviral barcode libraries, and specifically barcoded tubal-ovarian metastatic OVCAR5 cell lines (engineered to express varying levels of metastasis promoting LRRC15 gene) and co-injected cells in a competitive CIC assay into tubal or ovarian sites in highly immunodeficient NSG mice. DNA was isolated from primary tumors, omental/bowel metastasis and system-wide anatomical site/organs. Amplicon sequencing libraries were constructed with spike-in-control barcodes (serving as internal calibration controls) to estimate absolute clone sizes. The computational pipeline CIC Calculator was then used to deconvolute and filter the data, set stringent thresholds, and generate high-quality information on CIC numbers and frequencies, clone sizes, linkages across sites and classify clones based on their extent of metastatic activity. Using of CIC-MM plot, statistical models and machine learning approaches, we generated high-resolution clonal maps of metastasis for each animal. The information generated included clone types and system-wide metastasis, similar and dissimilar clonal patterns of dominance at heterotopic sites and their routes of metastases. The data revealed previously unknown influences of cellular genotype and their implanted sites on selecting certain clones with specific system-wide clonal patterns, and identified rare LRRC15 expressor clones (classified as CIC.Toti) predisposed to exploit all sites, albeit at varying degrees of dominance. The genomic technology and computational methodology described here are tissue-agnostic. They enable rapid adoption for an investigation into various stages of system-wide metastasis and growth of transplantable malignant cells at the highest clonal resolution.

cancer biology↗

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↗

bioRxiv2020

Nucleotide binding, evolutionary insights and interaction partners of the pseudokinase Unc-51-like kinase 4

Unc-51-like kinase 4 (ULK4) is a pseudokinase that has been linked to the development of several diseases. Even though sequence motifs required for ATP binding in kinases are lacking, ULK4 still tightly binds ATP and the presence of the cofactor is required for structural stability of ULK4. Here we present a high-resolution structure of a ULK4-ATP{gamma}S complex revealing a highly unusual ATP binding mode in which the lack of the canonical VAIK motif lysine is compensated by K39, located N-terminal to C. Evolutionary analysis suggests that degradation of active site motifs in metazoan ULK4 has co-occurred with an ULK4 specific activation loop, which stabilizes the C-helix. In addition, cellular interaction studies using BioID and biochemical validation data revealed high confidence interactors of the pseudokinase and armadillo repeat domains. Many of the identified ULK4 interaction partners were centrosomal and tubulin associated proteins and several active kinases suggesting new roles for ULK4. HighlightsStructure of the ULK4 ATP complex reveals a unique ATP binding mode. Disease associated mutations modulate ATP binding and ULK4 stability Degradation of active site motifs co-occurred in evolution with an ULK4 specific activation loop BioID suggests a role of ULK4 regulating centrosomal and cytoskeletal functions

biochemistry↗

bioRxiv2020

Distinct Long-term Effects of Precision X-Radiation on Reflex Saliva Flow Rate and Tissue Integrity in a Preclinical Model of Chronic Hyposalivation

Chronic salivary hypofunction and xerostomia are common side effects of radiation therapy which is an essential component in the curative management in patients with head & neck cancers. Over the years, improvements in delivery techniques such as image-guided intensity modulated radiation therapy have led to improvement in cancer management but chronic hyposalivation continues to be a challenge that causes long-term health implications resulting in compromised quality of life. Recent advances in salivary stem cell research promise new frontier in the treatment of radiation-induced hyposalivation by initiating regeneration of radiation-damaged salivary parenchymal cells. Lack of a standard preclinical immunodeficient model to assess radiation-induced changes objectively and quantitatively in salivary flow rates will impede rapid progress towards the development of cellular therapies for chronic salivary dysfunction and attendant xerostomia. Herein, we report the first fully characterized novel cone-beam computed tomography (CBCT)-guided precision ionizing radiation (IR) induced chronic hyposalivation model in radiosensitive, immunodeficient transgenic NSG-SGM3 mice expressing three human cytokines including c-KIT ligand/stem cell factor. Additionally, we also report a novel and instantaneous method to objectively assess the kinetics of pilocarpine-stimulated salivary flowrate. Comprehensive structural and functional characterization of salivary glands revealed previously unknown and highly complex gender, age, IR dose and salivary gland subtype-specific effects of salivary-ablative precision IR.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pathology↗

bioRxiv2020

Levo in fimo test : A simple test for fecal microbial reconstituted mice

Here we report the first method for rapid on-site monitoring of germfree C57BL/6 mice colonized with feces from conventionally raised mice. The method, named levo in fimo test, readily distinguishes feces from germfree mice and conventionalized germfree mice based on its properties to float or sink in Trumps fixative solution. We validated the test using feces from conventionally raised mice, germfree mice and conventionalized germfree mice, and cross-validated using multiple indicators of microbial presence in feces. Levo in fimo test is a simple, cost-effective, instant yet robust method for on-site monitoring of gut microbial reconstitution in germfree mice.

microbiology↗

bioRxiv2020

Exploring the understudied human kinome for research and therapeutic opportunities

The functions of protein kinases have been widely studied and over 60 kinase inhibitors are FDA-approved drugs. Membership in the human kinome is nonetheless subject to multiple overlapping and inconsistent definitions and is unevenly studied, complicating functional genomics and chemical genetics. We describe objective criteria for refining the definition of the human kinome to comprise an extended set of 710 kinase domains and a more narrowly curated set of 557 protein kinase like (PKL) domains. An online tool (www.kinome.org) makes it possible to sort these sets on multiple structural and functional criteria. Focusing on the least studied one-third of the kinome we find that many proteins are differentially expressed, essential in multiple cell lines, and mutated in the Cancer Genome Atlas. We show that some understudied kinases are high affinity off-targets of clinical-grade compounds and approved drugs and we describe an optimized small molecule library making use of this information for selective kinome perturbation. We conclude that the understudied kinome contains physiologically important proteins, including possible targets for future drug discovery campaigns.

systems biology↗

bioRxiv2020

A novel redox-active switch in Fructosamine-3-kinases expands the regulatory repertoire of the protein kinase superfamily

Aberrant regulation of metabolic kinases by altered redox homeostasis is a major contributing factor in aging and disease such as diabetes. However, the biochemical mechanisms by which metabolic kinases are regulated under oxidative stress is poorly understood. In this study, we demonstrate that the catalytic activity of a conserved family of Fructosamine-3-kinases (FN3Ks), which are evolutionarily related to eukaryotic protein kinases (ePKs), are regulated by redox-active cysteines in the kinase domain. By solving the crystal structure of FN3K homolog from Arabidopsis thaliana (AtFN3K), we demonstrate that it forms an unexpected strand-exchange dimer in which the ATP binding P-loop and adjoining beta strands are swapped between two chains in the dimer. This dimeric configuration is characterized by strained inter-chain disulfide bonds that stabilize the P-loop in an extended conformation. Mutational analysis and solution studies confirm that the strained disulfides function as redox "switches" to reversibly regulate FN3K activity and dimerization. Consistently, we find that human FN3K (HsFN3K), which contains an equivalent P-loop Cys, is also redox-sensitive, whereas ancestral bacterial FN3K homologs, which lack a P-loop Cys, are not. Furthermore, CRISPR knockout of FN3K in human HepG2 cells results in significant upregulation of redox metabolites including glutathione. We propose that redox regulation evolved progressively in FN3Ks in response to changing cellular redox conditions. Our studies provide important new insights into the origin and evolution of redox regulation in the protein kinase superfamily and open new avenues for targeting HsFN3K in diabetic complications.

biochemistry↗

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↗

bioRxiv2019

LF4/MOK and a CDK-related kinase regulate the number and length of cilia in Tetrahymena

The length of cilia is controlled by a poorly understood mechanism that involves members of the conserved RCK kinase group, and among them, the LF4/MOK kinases. In Tetrahymena, a loss of an LF4/MOK ortholog, LF4A, lengthened the locomotory cilia, but also reduced their total number per cell. Without LF4A, cilia assembled faster and showed signs of increased intraflagellar transport (IFT). Consistently, overproduced LF4A shortened cilia and downregulated the IFT. GFP-tagged LF4A, expressed in the native locus and imaged by total internal reflection microscopy, was enriched at the basal bodies and distributed along the shafts of cilia. Within cilia, most LF4A-GFP particles were immobile and a few either diffused or moved by IFT. A forward genetic screen identified a CDK-related kinase, CDKR1, whose loss-of-function suppressed the shortening of cilia caused by overexpression of LF4A, by reducing its kinase activity. A loss of CDKR1 alone lengthened both the locomotory and oral cilia. CDKR1 resembles other known ciliary CDK-related kinases: LF2 of Chlamydomonas, mammalian CCRK and DYF-18 of C. elegans, in lacking the cyclin-binding motif and acting upstream of RCKs. We propose that the total LF4/MOK activity per cilium is dependent on both its activation by an upstream CDK-related kinase and cilium length. Previous studies showed that the rate of assembly is high in growing cilia and decreases as cilia elongate to achieve the steady-state length. We propose that in a longer cilium, the IFT components, which travel from the base to the tip, are subjected to a higher dose of inhibition by the uniformly distributed LF4/MOK. Thus, in a feedback loop, LF4/MOK may translate cilium length into proportional inhibition of IFT, to balance the rates of assembly and disassembly at steady-state.\n\nAuthor summaryCilia are conserved organelles that generate motility and mediate vital sensory functions, including olfaction and vision. Cilia that are either too short or too long fail to generate proper forces or responses to extracellular signals. Several cilia-based diseases (ciliopathies) are associated with defects in cilia length. Here we use the multiciliated model protist Tetrahymena, to study a conserved protein kinase whose activity shortens cilia, LF4/MOK. We find that cells lacking an LF4/MOK kinase of Tetrahymena, LF4A, have excessively long, but also fewer cilia. We show that LF4A decreases the intraflagellar transport, a motility that shuttles ciliary precursors from the cilium base to the tip. Live imaging revealed that LF4A is distributed along cilium length and remains mostly immobile, likely due to its anchoring to ciliary microtubules. We proposed that in longer cilia, the intraflagellar transport machinery is exposed to a higher dose of inhibition by LF4A, which could decrease the rate of cilium assembly, to balance the rate of cilium disassembly in mature cilia that maintain stable length.

cell biology↗

bioRxiv2019

An evolutionary-conserved redox regulatory mechanism in human Ser/Thr protein kinases

Reactive oxygen species (ROS) are products of oxygen metabolism, but are also recognized as endogenous physiological mediators of cellular signaling. Eukaryotic protein kinase (ePK) regulation occurs through reversible phosphorylation events in the flexible activation segment. In this study, we demonstrate that the catalytic phosphotransferase output from the mitotic Ser/Thr kinase Aurora A is also controlled by cysteine (Cys) oxidation. Reversible regulation occurs by direct modification of a conserved residue (Cys 290), which lies adjacent to Thr 288, the activating site of phosphorylation. Strikingly, redox modulation of the Cys 290-equivalent in other ePKs is predicted to be an underappreciated regulatory mechanism, since ~100 human Ser/Thr kinases possess a Cys at this position in the conserved activation loop. Using real-time enzyme assays, we confirm that the presence of the equivalent Cys residue is prognostic for redox-sensitivity amongst a cohort of human CAMK, AGC and AGC-like kinases, including AKT, AMPK, CAMK1, MAPKAP-K2/3 and SIK1-3. Our findings demonstrate that dominant Cys-based redox-switching in the activation segment represents an evolutionary-conserved mode of regulation for a significant subset of the human kinome. This finding has important implications for understanding physiological and pathological signaling responses to ROS, and emphasises the importance of multivalent activation segment regulation in ePKs.\n\nONE-SENTENCE SUMMARYThe catalytic activity of Ser/Thr kinases is regulated through a conserved Cys-based redox mechanism.

biochemistry↗