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Kinetoplastids, including Trypanosoma brucei, control gene expression primarily at the posttranscriptional level. Nuclear mRNA export is an important, but understudied, step in this process. The general heterodimeric export factors, Mex67/Mtr2, function in the export of mRNAs and tRNAs in T. brucei, but RNA binding proteins (RBPs) that regulate export processes by controlling the dynamics of Mex67/Mtr2 ribonucleoprotein formation or transport have not been identified. Here, we report that DRBD18, an essential and abundant T. brucei RBP, associates with Mex67/Mtr2 in vivo, likely through its direct interaction with Mtr2. DRBD18 downregulation results in partial accumulation of poly(A)+ mRNA in the nucleus, but has no effect on localization of intron-containing or mature tRNAs. Comprehensive analysis of transcriptomes from whole cell and cytosol in DRBD18 knockdown parasites demonstrates that depletion of DRBD18 leads to impairment of nuclear export of a subset of mRNAs. CLIP experiments reveal association of DRBD18 with several of these mRNAs. Moreover, DRBD18 knockdown leads to a partial accumulation of the Mex67/Mtr2 export receptors in the nucleus. Taken together, the current study supports a model in which DRBD18 regulates the selective nuclear export of mRNAs by promoting the mobilization of export competent mRNPs to the cytosol through the nuclear pore complex.

This study investigated the association between menopausal hormone therapy (HT) use and the subgingival microbiome, for which published information is limited.This cross-sectional study included 1270 postmenopausal women, aged 53-81 years, who completed clinical examinations. Detailed information on HT use (type, delivery mode, duration) was obtained from questionnaires. HT use was categorized into three groups (never, former, current). 16S rRNA sequencing was performed on subgingival plaque samples obtained during dental examinations. Operational taxonomic units were centered log2-ratio (CLR) transformed to account for the compositional data structure. Analysis of variance was used to compare mean microbial relative abundances across HT categories with Benjamini-Hochberg correction.Significantly higher alpha diversity (Shannon Index) and beta diversity (Aitchison distance) was observed in never compared with current HT users (p 0.05, each). Of the total 245 microbial taxa identified, 18 taxa differed significantly among the three HT groups, 11 of which were higher in current users and seven of which were lower in current users as compared with never users (p 0.05, each). Differences in relative abundance between never and current HT users were materially unchanged after adjustment for age, body mass index, and oral hygiene.Relative abundance of several subgingival bacteria differed significantly between never and current HT users in a cohort of postmenopausal women. Additional studies are needed to determine the extent that these relationships might account for the previously reported inverse association between HT use and periodontal disease in older women.

BACKGROUND The aim of this study was to quantify the association between subgingival microbiota and periodontal disease progression in older women, for which limited published data exist. METHODS A total of 1016 postmenopausal women, aged 53 to 81 years, completed baseline (1997 to 2001) and 5-year (2002 to 2006) dental exams that included probing depth, clinical attachment level, gingival bleeding, and radiographic alveolar crestal height (ACH). Baseline microbiota were measured in subgingival plaque using 16S rRNA sequencing. Associations between 52 microbiota we previously found statistically significantly associated with clinical periodontal disease at baseline, were examined with disease progression. The traditional Socransky microbiota complexes also were evaluated. Side-by-side radiograph comparisons were used to define progression as ≥2 teeth with ≥1 mm ACH loss or ≥1 new tooth loss to periodontitis. The association between baseline centered log(2) ratio transformed microbial relative abundances and 5-year periodontal disease progression was measured with generalized linear models. RESULTS Of 36 microbiota we previously showed were elevated in moderate/severe disease at baseline, 24 had statistically significantly higher baseline mean relative abundance in progressing compared with non-progressing women (P

Limited research exists on carbohydrate intake and oral microbiome diversity and composition assessed with next-generation sequencing. We aimed to better understand the association between habitual carbohydrate intake and the oral microbiome, as the oral microbiome has been associated with caries, periodontal disease, and systemic diseases. We investigated if total carbohydrates, starch, monosaccharides, disaccharides, fiber, or glycemic load (GL) were associated with the diversity and composition of oral bacteria in subgingival plaque samples of 1204 post-menopausal women. Carbohydrate intake and GL were assessed from a food frequency questionnaire, and adjusted for energy intake. The V3–V4 region of the 16S rRNA gene from subgingival plaque samples were sequenced to identify the relative abundance of microbiome compositional data expressed as operational taxonomic units (OTUs). The abundance of OTUs were centered log(2)-ratio transformed to account for the compositional data structure. Associations between carbohydrate/GL intake and microbiome alpha-diversity measures were examined using linear regression. PERMANOVA analyses were conducted to examine microbiome beta-diversity measures across quartiles of carbohydrate/GL intake. Associations between intake of carbohydrates and GL and the abundance of the 245 identified OTUs were examined by using linear regression. Total carbohydrates, GL, starch, lactose, and sucrose intake were inversely associated with alpha-diversity measures. Beta-diversity across quartiles of total carbohydrates, fiber, GL, sucrose, and galactose, were all statistically significant (p for PERMANOVA p Streptococcus mutans; GL and both Sphingomonas HOT 006 and Scardovia wiggsiae; and sucrose and Streptococcus lactarius. A negative association was observed between lactose and Aggregatibacter segnis, and between sucrose and both TM7_[G-1] HOT 346 and Leptotrichia HOT 223. Intake of total carbohydrate, GL, and sucrose were inversely associated with subgingival bacteria alpha-diversity, the microbial beta-diversity varied by their intake, and they were associated with the relative abundance of specific OTUs. Higher intake of sucrose, or high GL foods, may influence poor oral health outcomes (and perhaps systemic health outcomes) in older women via their influence on the oral microbiome.

Background The extent to which the composition and diversity of the oral microbiome varies with age is not clearly understood. Methods The 16S rRNA gene of subgingival plaque in 1219 women, aged 53–81 years, was sequenced and its taxonomy annotated against the Human Oral Microbiome Database (v.14.5). Composition of the subgingival microbiome was described in terms of centered log(2)-ratio (CLR) transformed OTU values, relative abundance, and prevalence. Correlations between microbiota abundance and age were evelauted using Pearson Product Moment correlations. P-values were corrected for multiple testing using the Bonferroni method. Results Of the 267 species identified overall, Veillonella dispar was the most abundant bacteria when described by CLR OTU (mean 8.3) or relative abundance (mean 8.9%); whereas Streptococcus oralis, Veillonella dispar and Veillonella parvula were most prevalent (100%, all) when described as being present at any amount. Linear correlations between age and several CLR OTUs (Pearson r = − 0.18 to 0.18), of which 82 (31%) achieved statistical significance (P P P Conclusions We identified associations between several bacterial species and age across the age range of postmenopausal women studied. Understanding the functions of these bacteria could identify intervention targets to enhance oral health in later life.

Understanding of the oral microbiome in relation to periodontal disease in older adults is limited. The composition and diversity of the subgingival microflora and their oligotypes in health and levels of periodontal disease were investigated in this study on older postmenopausal women. The 16S rRNA gene was sequenced using the Illumina MiSeq platform in 1,206 women aged 53 to 81 y. Presence and severity of periodontal disease were defined by Centers for Disease Control and Prevention/American Academy of Periodontology criteria. Composition of the microbiome was determined by 16S rRNA amplicon sequencing and the abundance of taxa described by the centered log2-ratio (CLR) transformed operational taxonomic unit (OTU) values. Differences according to periodontal disease status were determined by analysis of variance with Bonferroni correction. Bacteria oligotypes associated with periodontal disease and health were determined by minimum entropy decomposition and their functions estimated in silico using PICRUSt. Prevalence of none/mild, moderate, and severe periodontal disease was 25.1%, 58.3%, and 16.6%, respectively. Alpha diversity of the microbiome differed significantly across the 3 periodontal disease categories. β-Diversity differed between no/mild and severe periodontal disease, although considerable overlap was noted. Of the 267 bacterial species identified at ≥0.02% abundance, 56 (20.9%) differed significantly in abundance according to periodontal disease status. Significant linear correlations for pocket depth and clinical attachment level with bacterial amounts were observed for several taxa. Of the taxa differing in abundance according to periodontal disease status, 53% had multiple oligotypes appearing to differ between none/mild and severe periodontal disease. Among older women, taxonomic differences in subgingival microbiome composition and diversity were observed in relation to clinical periodontal disease measures. Potential differences in bacterial subspecies (oligotypes) and their function were also identified in periodontal disease compared with health.

OBJECTIVES: A possible role of the oral microbiome, specifically oral nitrate reducing flora, in blood pressure (BP) homeostasis, if proven etiologic in nature, could lead to novel mechanism-based therapy to improve hypertension prevention and control. This cross-sectional study characterized and compared the oral microbiome between four study groups based on BP status among 446 postmenopausal women aged 53-82 years. METHODS: Three study groups were not taking hypertension medication and were separated based on BP, as follows: normal BP (systolic 140 or diastolic > 90; N=42). The forth group consisted of anyone taking hypertension medications, regardless of BP (N=119). Subgingival microbiome composition was determined using 16S rRNA sequencing with the Illumina MiSeq platform. Kruskal-Wallis tests were used to compare species-level relative abundance of bacterial operational taxonomic units across the four groups. RESULTS: Sixty-five bacterial species demonstrated significant differences in relative abundance in women with elevated BP or using hypertension medication as compared to those with normal BP. After correction for multiple testing, two species, Prevotella oral (species 317) and Streptococcus oralis, remained significant and were lower in abundance among women taking antihypertension medications compared to those with normal BP (corrected P

Patients with chronic kidney disease (CKD) and end-stage renal disease suffer from increased cardiovascular events and cardiac mortality. Prior studies have demonstrated that a portion of this enhanced risk can be attributed to the accumulation of microbiota-derived toxic metabolites, with most studies focusing on the sulfonated form of p-cresol (PCS). However, unconjugated p-cresol (uPC) itself was never assessed due to rapid and extensive first-pass metabolism that results in negligible serum concentrations of uPC. These reports thus failed to consider the host exposure to uPC prior to hepatic metabolism. In the current study, not only did we measure the effect of altering the intestinal microbiota on lipid accumulation in coronary arteries, but we also examined macrophage lipid uptake and handling pathways in response to uPC. We found that atherosclerosis-prone mice fed a high-fat diet exhibited significantly higher coronary artery lipid deposits upon receiving fecal material from CKD mice. Furthermore, treatment with uPC increased total cholesterol, triglycerides, and hepatic and aortic fatty deposits in non-CKD mice. Studies employing an in vitro macrophage model demonstrated that uPC exposure increased apoptosis whereas PCS did not. Additionally, uPC exhibited higher potency than PCS to stimulate LDL uptake and only uPC induced endocytosis- and pinocytosis-related genes. Pharmacological inhibition of varying cholesterol influx and efflux systems indicated that uPC increased macrophage LDL uptake by activating macropinocytosis. Overall, these findings indicate that uPC itself had a distinct effect on macrophage biology that might have contributed to increased cardiovascular risk in patients with CKD.

Factor H (FH) is a critical regulator of the alternative complement pathway and its deficiency or mutation underlie kidney diseases such as dense deposit disease. Since vascular dysfunction is an important facet of kidney disease, maintaining optimal function of the lining endothelial cells is important for vascular health. To investigate the molecular mechanisms that are regulated by FH in endothelial cells, FH deficient and sufficient mouse kidney endothelial cell cultures were established. Endothelial FH deficiency resulted in cytoskeletal remodeling, increased angiogenic potential, loss of cellular layer integrity and increased cell proliferation. FH reconstitution prevented these FH-dependent proliferative changes. Respiratory flux analysis showed reduced basal mitochondrial respiration, ATP production and maximal respiratory capacity in FH deficient endothelial cells, while proton leak remained unaltered. Similar changes were observed in FH deficient human glomerular endothelial cells indicating the translational potential of these studies. Gene expression analysis revealed that the FH-dependent gene changes in mouse kidney endothelial cells include significant upregulation of genes involved in inflammation and the complement system. The transcription factor nuclear factor-kB, that regulates many biological processes, was translocated from the cytoplasm to the nucleus in the absence of FH. Thus, our studies show the functional relevance of intrinsic FH in kidney endothelial cells in man and mouse.

Systemic lupus erythematosus (lupus) is a global health problem where 20–80% patients display cognitive problems and central nervous system (CNS) dysfunction. Early diagnosis and treatment of lupus remains a clinical challenge. Exercise improves experimental lupus nephritis. However, the effects of exercise in CNS lupus remains unknown. This study investigates the effects of controlled exercise (CE) that consisted of treadmill walking (5 m/min for 10 min everyday) on experimental CNS lupus using the well-established mouse model, MRL/lpr mice. The MRL/lpr mice were subjected to CE from 8 weeks (preclinical) to 16 weeks (disease). Multiplex gene expression analysis revealed significant upregulation of genes involved in neurite growth, proliferation and synaptic plasticity, and a decrease in inflammatory genes including complement proteins, NFkB, chemokines and cytokines in exercised mice compared to the unmanipulated, age-matched controls. The loss of blood–brain barrier integrity, astrogliosis and edema seen in MRL/lpr mice were reduced with exercise. Exercised mice performed better in behavioral assessments such as open field, nesting, and tail suspension test. For the first time our results show that a supervised, well-regulated and controlled exercise regimen alleviates CNS lupus and could potentially serve as an intervention strategy to improve the quality of life. Exercise could also serve as an adjunct therapy for lupus and other neuroinflammatory diseases, thereby reducing the need for the current therapies with toxic side effects. The validity of the findings and a safe exercise regimen needs to be established by additional studies in patients.

Gut bacterial microbiota is altered in patients with advanced renal disease and those on dialysis. However, it is not clear yet what bacterial composition changes are due to the renal insufficiency per se, and what are in result of the accompanying interventions and comorbid conditions. Most studies analyzed diabetic nephropathy, hypertensive nephropathy, and glomerulonephritis patients which might have directly influenced the microbiome regardless of alterations in renal function. We present in this report changes in gut bacterial microbiota in a highly selected group of patients with strict inclusion criteria to eliminate the effects of the confounding factors on the microbiome composition. We conducted multiple analysis approaches according to participants’ renal function to further understand microbiome alteration in different degrees of renal insufficiency. An interesting group of bacteria showed a step-wise change in relative abundance in response to the three groups’ analysis. These bacteria either decreased or increased from mild, moderate to severe renal insufficiency indicating strong and direct effects of the uremic milieu on its relative abundance. We also ran a sensitivity analysis that took into account an assembly of the significant taxa observed in an approach to investigate whether these taxa can fully explain the separation noted between the groups. We determined the projected metabolic pathways altered according to the gut microbiota composition changes. This report not only delineates with a higher certainty the effects of alteration in renal function on the microbiome, but also explores the possible role of dysbiosis on comorbid conditions through alterations in the projected metabolic pathways. Impact statement The heterogeneity of the renal disease, therapeutic interventions, and the original cause of the renal failure, all directly affect the microbiota. We delineate in this report the direct effect of decreased renal function on the bacterial composition following stringent criteria to eliminate the possibilities of other confounding factors and dissect the direct effects of the uremic milieu. We analyzed the microbiome following three different approaches to further evaluate the effects of mild, moderate and advanced renal insufficiency on the microbiome. We also present here a detailed functional analysis of the projected altered pathways secondary to changes in the microbiome composition.

Several lines of evidence suggest that gut bacterial microbiota is altered in patients with chronic kidney disease (CKD), though the mechanism of which this dysbiosis takes place is not well understood. Recent studies delineated changes in gut microbiota in both CKD patients and experimental animal models using microarray chips. We present 16S ribosomal RNA gene sequencing of both stool pellets and small bowel contents of C57BL/6J mice that underwent a remnant kidney model and establish that changes in microbiota take place in the early gastrointestinal tract. Increased intestinal urea concentration has been hypothesized as a leading contributor to dysbiotic changes in CKD. We show that urea transporters (UT)-A and UT-B mRNA are both expressed throughout the whole gastrointestinal tract. The noted increase in intestinal urea concentration appears to be independent of UTs’ expression. Urea supplementation in drinking water resulted in alteration in bacterial gut microbiota that is quite different than that seen in CKD. This indicates that increased intestinal urea concentration might not fully explain the CKD- associated dysbiosis.

Dynamic interactions between gut microbiota and a host’s innate and adaptive immune systems are essential in maintaining intestinal homeostasis and inhibiting inflammation. Gut microbiota metabolizes proteins and complex carbohydrates, synthesizes vitamins, and produces an enormous number of metabolic products that can mediate cross-talk between gut epithelium and immune cells. As a defense mechanism, gut epithelial cells produce a mucosal barrier to segregate microbiota from host immune cells and reduce intestinal permeability. An impaired interaction between gut bacteria and the mucosal immune system can lead to an increased abundance of potentially pathogenic gram-negative bacteria and their associated metabolic changes, disrupting the epithelial barrier and increasing susceptibility to infections. Gut dysbiosis, or negative alterations in gut microbial composition, can also dysregulate immune responses, causing inflammation, oxidative stress, and insulin resistance. Over time, chronic dysbiosis and the leakage of microbiota and their metabolic products across the mucosal barrier may increase prevalence of type 2 diabetes, cardiovascular disease, autoimmune disease, inflammatory bowel disease, and a variety of cancers. In this paper, we highlight the pivotal role gut bacteria and their metabolic products (short-chain fatty acids (SCFAs)) which play in mucosal immunity.

PurposeThe Buffalo Osteoporosis and Periodontal Disease (OsteoPerio) study is a prospective cohort study focused on the relationship between the microbiome and oral and systemic health outcomes in postmenopausal women. The cohort was established to examine how the oral microbiome is affected by (and how it affects) periodontal disease presence, severity and progression and to characterise the relationship between the microbiome, lifestyle habits and systemic disease outcomes.ParticipantsParticipants (n=1342) were postmenopausal women who were participating in the Women’s Health Initiative observational study at the Buffalo, New York clinical centre. There were 1026 participants at the 5-year follow-up visit and 518 at the 15-year visit.Findings to dateData collected include questionnaires, anthropometric measures, serum blood and saliva samples. At each clinic visit, participants completed a comprehensive oral examination to measure oral health and the oral microbiome. Preliminary findings have contributed to our understanding of risk factors for periodontal disease and the relationship between the oral microbiome and periodontal disease.Future plansThe novel microbiome data collected on a large sample of participants at three time points will be used to answer a variety of research questions focused on temporal changes in the microbiome and the relationship between the oral microbiome and oral and systemic disease outcomes. Little is currently known about the relationship between the oral microbiome and health outcomes in older adults; data from the OsteoPerio cohort will fill this gap. Microbiome samples are currently being analysed using next-generation sequencing technology with an anticipated completion date of late 2018.

Aging invokes physiological changes, such as immunosenescence and inflammation, that could increase host susceptibility to oral microbiome shifts that enable periodontitis progression in later life. At present, there is a dearth of studies specifically evaluating the oral microbiome and periodontitis in older adults. We used high-throughput untargeted sequencing methods and functional metagenomic analyses to assess and compare the subgingival biofilm of postmenopausal women (mean age 71 years) according to periodontitis status. Subgingival plaque samples were obtained from 15 postmenopausal women with no periodontitis, and from 15 women with severe periodontitis, determined by probing measures. The 16S rRNA gene (V1&ndash, V3 region) was sequenced on the 454 FLX platform. The PICRUSt technique was used to provide information on what the potential functional characteristics of microbiota might be in healthy, compared with diseased, periodontium. The subgingival microbiome associated with periodontitis showed clear differences to that associated with health. Of the 464 species identified, 22.8% had elevated abundance in disease, while only 6.3% had elevated abundance in health. Among the 12 most prevalent organisms in periodontitis, one-half have previously been recognized as periodontal pathogens by other investigators. The subgingival microbiome in periodontitis contained genes that could code for specific activities, including microbial mobility, synthesis of endotoxin, and proteolytic degradation. The healthy microbiome included genes that could code for sustaining microbial life, including encoding for transporters, glycolysis, gluconeogenesis, the Krebs cycle, and protein kinases. In the present study on postmenopausal women, aged 60 and older, the subgingival microbiome differed in composition and potential function between those with and without periodontitis. Studies of functional gene expression, such as transcriptomics, are needed to definitively identify the molecules carrying out functions associated with pathogenic subgingival complexes. This, in turn, could lead to identification of targets for enhanced management of periodontitis and, possibly, other diseases, in later life.

Many bioinformatics resources with unique perspectives on the protein landscape are currently available. However, generating new knowledge from these resources requires interoperable workflows that support cross-resource queries. In this study, we employ federated queries linking information from the Protein Kinase Ontology, iPTMnet, Protein Ontology, neXtProt, and the Mouse Genome Informatics to identify key knowledge gaps in the functional coverage of the human kinome and prioritize understudied kinases, cancer variants and post-translational modifications (PTMs) for functional studies. We identify 32 functional domains enriched in cancer variants and PTMs and generate mechanistic hypotheses on overlapping variant and PTM sites by aggregating information at the residue, protein, pathway and species level from these resources. We experimentally test the hypothesis that S768 phosphorylation in the C-helix of EGFR is inhibitory by showing that oncogenic variants altering S768 phosphorylation increase basal EGFR activity. In contrast, oncogenic variants altering conserved phosphorylation sites in the ‘hydrophobic motif’ of PKCβII (S660F and S660C) are loss-of-function in that they reduce kinase activity and enhance membrane translocation. Our studies provide a framework for integrative, consistent, and reproducible annotation of the cancer kinomes.

FLT3 is frequently mutated and overexpressed in acute myelogenous leukemia (AML) and other hematologic malignancies. Although signaling events downstream of FLT3 receptor tyrosine kinase have been studied in depth, molecular mechanisms of how FLT3 expression is regulated at the post-transcriptional level in particular remain elusive. In this study, we investigated the roles of an RNA binding protein MSI2 as a regulator of FLT3 expression. MSI2 and FLT3 are significantly co-regulated in human AML and chronic myelogenous leukemia in blast crisis (BC-CML). Genetic loss of MSI2 leads to down-regulation of the FLT3 receptor in both AML and BC-CML cells and concomitant impairment of clonogenic growth potential. Furthermore, we demonstrate that MSI2 protein is physically bound to FLT3 mRNA transcripts, suggesting post-transcriptional control of FLT3 expression. Collectively, these results reveal a novel mode of FLT3 regulation essential for leukemia growth, which may aid in designing a targeted therapy to treat human myeloid leukemia.

Protein kinases represent a large and diverse family of evolutionarily related proteins that are abnormally regulated in human cancers. Although genome sequencing studies have revealed thousands of variants in protein kinases, translating “big” genomic data into biological knowledge remains a challenge. Here, we describe an ontological framework for integrating and conceptualizing diverse forms of information related to kinase activation and regulatory mechanisms in a machine readable, human understandable form. We demonstrate the utility of this framework in analyzing the cancer kinome, and in generating testable hypotheses for experimental studies. Through the iterative process of aggregate ontology querying, hypothesis generation and experimental validation, we identify a novel mutational hotspot in the αC-β4 loop of the kinase domain and demonstrate the functional impact of the identified variants in epidermal growth factor receptor (EGFR) constitutive activity and inhibitor sensitivity. We provide a unified resource for the kinase and cancer community, ProKinO, housed at http://vulcan.cs.uga.edu/prokino.

Reprogrammed cellular metabolism is a common characteristic observed in various cancers. However, whether metabolic changes directly regulate cancer development and progression remains poorly understood. Here we show that BCAT1, a cytosolic aminotransferase for branched-chain amino acids (BCAAs), is aberrantly activated and functionally required for chronic myeloid leukaemia (CML) in humans and in mouse models of CML. BCAT1 is upregulated during progression of CML and promotes BCAA production in leukaemia cells by aminating the branched-chain keto acids. Blocking BCAT1 gene expression or enzymatic activity induces cellular differentiation and impairs the propagation of blast crisis CML both in vitro and in vivo. Stable-isotope tracer experiments combined with nuclear magnetic resonance-based metabolic analysis demonstrate the intracellular production of BCAAs by BCAT1. Direct supplementation with BCAAs ameliorates the defects caused by BCAT1 knockdown, indicating that BCAT1 exerts its oncogenic function through BCAA production in blast crisis CML cells. Importantly, BCAT1 expression not only is activated in human blast crisis CML and de novo acute myeloid leukaemia, but also predicts disease outcome in patients. As an upstream regulator of BCAT1 expression, we identified Musashi2 (MSI2), an oncogenic RNA binding protein that is required for blast crisis CML. MSI2 is physically associated with the BCAT1 transcript and positively regulates its protein expression in leukaemia. Taken together, this work reveals that altered BCAA metabolism activated through the MSI2-BCAT1 axis drives cancer progression in myeloid leukaemia.

Multiple sequence alignments (MSAs) are a fundamental analysis tool used throughout biology to investigate relationships between protein sequence, structure, function, evolutionary history, and patterns of disease-associated variants. However, their widespread application in systems biology research is currently hindered by the lack of user-friendly tools to simultaneously visualize, manipulate and query the information conceptualized in large sequence alignments, and the challenges in integrating MSAs with multiple orthogonal data such as cancer variants and post-translational modifications, which are often stored in heterogeneous data sources and formats. Here, we present the Multiple Sequence Alignment Ontology (MSAOnt), which represents a profile or consensus alignment in an ontological format. Subsets of the alignment are easily selected through the SPARQL Protocol and RDF Query Language for downstream statistical analysis or visualization. We have also created the Kinome Viewer (KinView), an interactive integrative visualization that places eukaryotic protein kinase cancer variants in the context of natural sequence variation and experimentally determined post-translational modifications, which play central roles in the regulation of cellular signaling pathways. Using KinView, we identified differential phosphorylation patterns between tyrosine and serine/threonine kinases in the activation segment, a major kinase regulatory region that is often mutated in proliferative diseases. We discuss cancer variants that disrupt phosphorylation sites in the activation segment, and show how KinView can be used as a comparative tool to identify differences and similarities in natural variation, cancer variants and post-translational modifications between kinase groups, families and subfamilies. Based on KinView comparisons, we identify and experimentally characterize a regulatory tyrosine (Y177PLK4) in the PLK4 C-terminal activation segment region termed the P+1 loop. To further demonstrate the application of KinView in hypothesis generation and testing, we formulate and validate a hypothesis explaining a novel predicted loss-of-function variant (D523NPKCβ) in the regulatory spine of PKCβ, a recently identified tumor suppressor kinase. KinView provides a novel, extensible interface for performing comparative analyses between subsets of kinases and for integrating multiple types of residue specific annotations in user friendly formats.

Protein phosphorylation lies at the heart of cell signalling, and somatic mutation(s) in kinases drives and sustains a multitude of human diseases, including cancer. The human protein kinase superfamily (the kinome) encodes approximately 50 ‘pseudokinases’, which were initially predicted to be incapable of dynamic cell signalling when compared with canonical enzymatically active kinases. This assumption was supported by bioinformatics, which showed that amino acid changes at one or more key loci, making up the nucleotide-binding site or phosphotransferase machinery, were conserved in multiple vertebrate and non-vertebrate pseudokinase homologues. Protein kinases are highly attractive targets for drug discovery, as evidenced by the approval of almost 30 kinase inhibitors in oncology, and the successful development of the dual JAK1/2 (Janus kinase 1/2) inhibitor ruxolitinib for inflammatory indications. However, for such a large (>550) protein family, a remarkable number have still not been analysed at the molecular level, and only a surprisingly small percentage of kinases have been successfully targeted clinically. This is despite evidence that many are potential candidates for the development of new therapeutics. Indeed, several recent reports confirm that disease-associated pseudokinases can bind to nucleotide co-factors at concentrations achievable in the cell. Together, these findings suggest that drug targeting using either ATP-site or unbiased ligand-discovery approaches should now be attempted using the validation technology currently employed to evaluate their classic protein kinase counterparts. In the present review, we discuss members of the human pseudokinome repertoire, and catalogue somatic amino acid pseudokinase mutations that are emerging as the depth and clinical coverage of the human cancer pseudokinome expand.

The growing volume of biomedical data available on the Web has contributed to numerous scientific advancements. At the same time, the complex, versatile and disparate nature of the data can overburden the knowledge discovery and data-driven hypothesis generation by scientists. Ontologies have been proposed to address the data integration challenge, however, creating useful domain-specific ontologies and populating them with high quality instances is tedious and time-consuming. In this paper, we present the mOntage framework to rapidly create ontologies representing data in a specific area of interest. We show how the mOntage framework can be used to create and populate biomedical ontologies from existing data sources. The classes and properties of the ontology being created are mapped to and instantiated from the existing data sources by executing suitable SPARQL queries. We illustrate our framework by creating a Phosphatase Ontology and show how it can serve as an important source of knowledge in the area of phosphatases.

Background Signaling proteins such as protein kinases adopt a diverse array of conformations to respond to regulatory signals in signaling pathways. Perhaps the most fundamental conformational change of a kinase is the transition between active and inactive states, and defining the conformational features associated with kinase activation is critical for selectively targeting abnormally regulated kinases in diseases. While manual examination of crystal structures have led to the identification of key structural features associated with kinase activation, the large number of kinase crystal structures (~3,500) and extensive conformational diversity displayed by the protein kinase superfamily poses unique challenges in fully defining the conformational features associated with kinase activation. Although some computational approaches have been proposed, they are typically based on a small subset of crystal structures using measurements biased towards the active site geometry. Results We utilize an unbiased informatics based machine learning approach to classify all eukaryotic protein kinase conformations deposited in the PDB. We show that the orientation of the activation segment, measured by φ, ψ, χ1, and pseudo-dihedral angles more accurately classify kinase crystal conformations than existing methods. We show that the formation of the K-E salt bridge is statistically dependent upon the activation segment orientation and identify evolutionary differences between the activation segment conformation of tyrosine and serine/threonine kinases. We provide evidence that our method can identify conformational changes associated with the binding of allosteric regulatory proteins, and show that the greatest variation in inactive structures comes from kinase group and family specific side chain orientations. Conclusion We have provided the first comprehensive machine learning based classification of protein kinase active/inactive conformations, taking into account more structures and measurements than any previous classification effort. Further, our unbiased classification of inactive structures reveals residues associated with kinase functional specificity. To enable classification of new crystal structures, we have made our classifier publicly accessible through a stand-alone program housed at https://github.com/esbg/kinconform [DOI:10.5281/zenodo.249090]. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1506-2) contains supplementary material, which is available to authorized users.