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Background: Dietary intake has been suggested to be associated with the oral microbiome, but no study has examined the association between overall diet quality and the oral microbiome., Objectives: This study aimed to investigate the cross-sectional association between the Healthy Eating Index-2020 (HEI-2020) and the diversity and composition of the oral microbiome among participants in the Buffalo Osteoporosis and Periodontal Disease (OsteoPerio) Study., Methods: In 1175 postmenopausal women (mean age: 67 ± 7.0 y), we estimated the HEI-2020 scores for each woman from a food frequency questionnaire administered from 1997 to 2000. Bacterial DNA was extracted from subgingival plaque samples and analyzed using 16S ribosomal RNA sequencing. The alpha-diversity (within-sample diversity) and β-diversity (between-sample diversity) across HEI-2020 quartiles were examined using analysis of covariance and permutational multivariate analysis of variance, respectively. The associations between the HEI-2020 score and the relative abundance of microbial taxa were examined by linear regression models. The analyses were further conducted for individual components of the HEI-2020., Results: No statistically significant associations were observed between the HEI-2020 scores and alpha- or beta-diversity. However, greater consumption of seafood, plant proteins, and total protein and lower consumption of added sugars were positively associated with alpha-diversity. After we applied a false detection rate (FDR) correction, higher HEI-2020 scores were significantly associated with decreased abundance of Lautropia, Streptococcus gordonii, Cardiobacterium valvarum, and Cardiobacterium hominis, and increased abundance of Selenomonas sp. oral taxon 133 and Selenomonas dianae (FDR-adjusted P values < 0.10). Additionally, 28 other taxa were identified as being associated with HEI-2020 components., Conclusions: Although the HEI-2020 was associated with the composition, but not the diversity, of the oral microbiome, individual HEI-2020 components were associated with both its diversity and composition. Specific dietary components may have more impact on the diversity and composition of oral microbiome than overall diet quality assessed by the HEI-2020., (Copyright © 2024 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

Background: Alcohol reduces neutrophil function and decreases salivary flow, which could affect the composition of the oral microbiome., Objective: We hypothesized that the α- and β-diversity of the oral microbiome and the relative abundance of bacterial taxa would differ by frequency and type of alcohol consumption., Methods: We used a food frequency questionnaire to assess the frequency of consumption of beer, wine, and liquor (drinks/week) in a sample of 1179 postmenopausal women in the Osteoporosis and Periodontal Disease Study. Women were categorized as nondrinkers, drinking <1 drink/wk, ≥1 to <7 drinks/wk, or ≥7 drinks/wk for total alcohol consumption and for beer, wine, and liquor consumption. The composition and diversity of the oral microbiome was assessed from subgingival plaque samples using 16S ribosomal RNA amplicon sequencing. Permutational multivariate analysis of variance (PERMANOVA) was used to examine β-diversity (between-sample diversity) in the microbiome between alcohol consumption categories. Analysis of covariance was used to examine the mean α-diversity (within-sample diversity), assessed by the Shannon index (species evenness), Chao1 index (species richness), and observed operational taxonomic unit (OTU) count and the mean relative abundance of 245 bacterial taxa across alcohol consumption categories., Results: Over half of the participants (67%) consumed alcohol, with 14% reporting ≥1 drink/d. The β-diversity across categories of total alcohol consumption, but not categories of alcohol type, was statistically significantly different (P for PERMANOVA = 0.016). Mean α-diversity measures were statistically significantly higher (P < 0.05) in the highest category of total alcohol and wine consumption compared to nondrinkers; no significant associations were found for beer or liquor consumption. The relative abundance of 1 OTU, Selenomonassp.&#95;oral&#95;taxon&#95;133, was significantly lower in the highest level of total alcohol consumption compared to nondrinkers after adjustment for multiple comparisons., Conclusions: Alcohol consumption was associated with the diversity and composition of the subgingival microbiome., Competing Interests: Conflict of interest The authors report no conflicts of interest., (Copyright © 2023 American Society for Nutrition. All rights reserved.)

Background: This study investigated the association between menopausal hormone therapy (HT) use and the subgingival microbiome, for which published information is limited., Methods: 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., Results: 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., Conclusions: 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., (© 2022 American Academy of Periodontology.)

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 < 0.05). Positive associations were observed between total carbohydrates, GL, sucrose and 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&#95;[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., (© 2022. The Author(s).)

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 the 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 the 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., (© 2021 John Wiley & Sons Ltd.)

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.

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 < .05, all); which included all Socransky red bacteria (P. gingivalis, T. forsythia, T. denticola). Of 16 microbiota elevated in none/mild disease at baseline, five had statistically significantly lower baseline abundance in non-progressing compared with progressing women (P < 0.05, all), including one Socransky yellow bacteria (S. oralis). When adjusted for baseline age, socioeconomic status, and self-rated general health status, odds ratios for 5-year progression ranged from 1.18 to 1.51 (per 1-standard deviation increment in relative abundance) for microbiota statistically significantly (P < 0.05) positively associated with progression, and from 0.77 to 0.82 for those statistically significantly (P < 0.05) inversely associated with progression. These associations were similar when stratified on baseline levels of pocket depth, gingival bleeding, ACH, and smoking status., Conclusions: These prospective results affirm clearly that subgingival microbiota are measurably elevated several years prior to progression of alveolar bone loss, and include antecedent elevations in previously undocumented taxa additional to known Socransky pathogenic complexes., (© 2020 American Academy of Periodontology.)

Dynamic interactions between gut microbiota and a host's innate and adaptive immune systems play key roles in maintaining intestinal homeostasis and inhibiting inflammation. The gut microbiota metabolizes proteins and complex carbohydrates, synthesize vitamins, and produce an enormous number of metabolic products that can mediate cross-talk between gut epithelial 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 microbiota 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 translocation of bacteria and their metabolic products across the mucosal barrier may increase prevalence of type 2 diabetes, cardiovascular disease, inflammatory bowel disease, autoimmune disease, and a variety of cancers. In this paper, we highlight the pivotal role gut microbiota and their metabolites (short-chain fatty acids (SCFAs)) play in mucosal immunity.

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 < 0.05). The correlations lost significance following Bonferroni correction. Twelve species that differed across age groups (each corrected P < 0.05); 5 (42%) were higher in women ages 50-59 compared to ≥70 (corrected P < 0.05), and 7 (48%) were higher in women 70 years and older., 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 log 2 -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.

Introduction: 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., Aim: 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 < 120 and diastolic < 80; N = 179), elevated BP/Stage I hypertension (systolic 120-139 or diastolic 80-90; N = 106), Stage II hypertension (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 < 0.05)., Conclusions: These data provide novel description of oral subgingival bacteria grouped according to BP status. Additional larger studies including functional analysis and prospective designs will help further assess the potential role of the oral microbiome in BP regulation and hypertension.

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.

Purpose: The 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., Participants: Participants (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 Date: Data 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 Plans: The 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., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

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⁻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.

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.

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 ].

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 (Y177 PLK4 ) 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 (D523N PKCβ ) 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 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., (© 2014 The Authors. **Human Mutation published by Wiley Periodicals, Inc.)