Discovery of potent BET bromodomain 1 stereoselective inhibitors using DNA-encoded chemical library selections.

BRDT, BRD2, BRD3, and BRD4 comprise the bromodomain and extraterminal (BET) subfamily which contain two similar tandem bromodomains (BD1 and BD2). Selective BD1 inhibition phenocopies effects of tandem BET BD inhibition both in cancer models and, as we and others have reported of BRDT, in the testes. To find novel BET BD1 binders, we screened >4.5 billion molecules from our DNA-encoded chemical libraries with BRDT-BD1 or BRDT-BD2 proteins in parallel. A compound series enriched only by BRDT-BD1 was resynthesized off-DNA, uncovering a potent chiral compound, CDD-724, with >2,000-fold selectivity for inhibiting BRDT-BD1 over BRDT-BD2. CDD-724 stereoisomers exhibited remarkable differences in inhibiting BRDT-BD1, with the R-enantiomer (CDD-787) being 50-fold more potent than the S-enantiomer (CDD-786). From structure­activity relationship studies, we produced CDD-956, which maintained picomolar BET BD1 binding potency and high selectivity over BET BD2 proteins and had improved stability in human liver microsomes over CDD-787. BROMOscan profiling confirmed the excellent pan-BET BD1 affinity and selectivity of CDD-787 and CDD-956 on BD1 versus BD2 and all other BD-containing proteins. A cocrystal structure of BRDT-BD1 bound with CDD-956 was determined at 1.82 Å and revealed BRDT-BD1­specific contacts with the αZ and αC helices that explain the high affinity and selectivity for BET BD1 versus BD2. CDD-787 and CDD-956 maintain cellular BD1-selectivity in NanoBRET assays and show potent antileukemic activity in acute myeloid leukemia cell lines. These BET BD1-specific and highly potent compounds are structurally unique and provide insight into the importance of chirality to achieve BET specificity.

Discovery and characterization of bromodomain 2-specific inhibitors of BRDT.

Bromodomain testis (BRDT), a member of the bromodomain and extraterminal (BET) subfamily that includes the cancer targets BRD2, BRD3, and BRD4, is a validated contraceptive target. All BET subfamily members have two tandem bromodomains (BD1 and BD2). Knockout mice lacking BRDT-BD1 or both bromodomains are infertile. Treatment of mice with JQ1, a BET BD1/BD2 nonselective inhibitor with the highest affinity for BRD4, disrupts spermatogenesis and reduces sperm number and motility. To assess the contribution of each BRDT bromodomain, we screened our collection of DNA-encoded chemical libraries for BRDT-BD1 and BRDT-BD2 binders. High-enrichment hits were identified and resynthesized off-DNA and examined for their ability to compete with JQ1 in BRDT and BRD4 bromodomain AlphaScreen assays. These studies identified CDD-1102 as a selective BRDT-BD2 inhibitor with low nanomolar potency and >1,000-fold selectivity over BRDT-BD1. Structure-activity relationship studies of CDD-1102 produced a series of additional BRDT-BD2/BRD4-BD2 selective inhibitors, including CDD-1302, a truncated analog of CDD-1102 with similar activity, and CDD-1349, an analog with sixfold selectivity for BRDT-BD2 versus BRD4-BD2. BROMOscan bromodomain profiling confirmed the great affinity and selectivity of CDD-1102 and CDD-1302 on all BET BD2 versus BD1 with the highest affinity for BRDT-BD2. Cocrystals of BRDT-BD2 with CDD-1102 and CDD-1302 were determined at 2.27 and 1.90 Å resolution, respectively, and revealed BRDT-BD2 specific contacts that explain the high affinity and selectivity of these compounds. These BD2-specific compounds and their binding to BRDT-BD2 are unique compared with recent reports and enable further evaluation of their nonhormonal contraceptive potential in vitro and in vivo.

tmVar 3.0: an improved variant concept recognition and normalization tool.

MOTIVATION: Previous studies have shown that automated text-mining tools are becoming increasingly important for successfully unlocking variant information in scientific literature at large scale. Despite multiple attempts in the past, existing tools are still of limited recognition scope and precision. RESULT: We propose tmVar 3.0: an improved variant recognition and normalization system. Compared to its predecessors, tmVar 3.0 recognizes a wider spectrum of variant-related entities (e.g. allele and copy number variants), and groups together different variant mentions belonging to the same genomic sequence position in an article for improved accuracy. Moreover, tmVar 3.0 provides advanced variant normalization options such as allele-specific identifiers from the ClinGen Allele Registry. tmVar 3.0 exhibits state-of-the-art performance with over 90% in F-measure for variant recognition and normalization, when evaluated on three independent benchmarking datasets. tmVar 3.0 as well as annotations for the entire PubMed and PMC datasets are freely available for download. AVAILABILITY AND IMPLEMENTATION: https://github.com/ncbi/tmVar3.

C-N Coupling of DNA-Conjugated (Hetero)aryl Bromides and Chlorides for DNA-Encoded Chemical Library Synthesis.

DNA-encoded chemical library (DECL) screens are a rapid and economical tool to identify chemical starting points for drug discovery. As a robust transformation for drug discovery, palladium-catalyzed C-N coupling is a valuable synthetic method for the construction of DECL chemical matter; however, currently disclosed methods have only been demonstrated on DNA-attached (hetero)aromatic iodide and bromide electrophiles. We developed conditions utilizing an N-heterocyclic carbene-palladium catalyst that extends this reaction to the coupling of DNA-conjugated (hetero)aromatic chlorides with (hetero)aromatic and select aliphatic amine nucleophiles. In addition, we evaluated steric and electronic effects within this catalyst series, carried out a large substrate scope study on two representative (hetero)aryl bromides, and applied this newly developed method within the construction of a 63 million-membered DECL.

Palladium-Catalyzed Hydroxycarbonylation of (Hetero)aryl Halides for DNA-Encoded Chemical Library Synthesis.

A strategy for DNA-compatible, palladium-catalyzed hydroxycarbonylation of (hetero)aryl halides on DNA-chemical conjugates has been developed. This method generally provided the corresponding carboxylic acids in moderate to very good conversions for (hetero)aryl iodides and bromides, and in poor to moderate conversions for (hetero)aryl chlorides. These conditions were further validated by application within a DNA-encoded chemical library synthesis and subsequent discovery of enriched features from the library in selection experiments against two protein targets.

MRG15 is required for pre-mRNA splicing and spermatogenesis.

Splicing can be epigenetically regulated and involved in cellular differentiation in somatic cells, but the interplay of epigenetic factors and the splicing machinery during spermatogenesis remains unclear. To study these interactions in vivo, we generated a germline deletion of MORF-related gene on chromosome 15 (MRG15), a multifunctional chromatin organizer that binds to methylated histone H3 lysine 36 (H3K36) in introns of transcriptionally active genes and has been implicated in regulation of histone acetylation, homology-directed DNA repair, and alternative splicing in somatic cells. Conditional KO (cKO) males lacking MRG15 in the germline are sterile secondary to spermatogenic arrest at the round spermatid stage. There were no significant alterations in meiotic division and histone acetylation. Specific mRNA sequences disappeared from 66 germ cell-expressed genes in the absence of MRG15, and specific intronic sequences were retained in mRNAs of 4 genes in the MRG15 cKO testes. In particular, introns were retained in mRNAs encoding the transition proteins that replace histones during sperm chromatin condensation. In round spermatids, MRG15 colocalizes with splicing factors PTBP1 and PTBP2 at H3K36me3 sites between the exons and single intron of transition nuclear protein 2 (Tnp2). Thus, our results reveal that MRG15 is essential for pre-mRNA splicing during spermatogenesis and that epigenetic regulation of pre-mRNA splicing by histone modification could be useful to understand not only spermatogenesis but also, epigenetic disorders underlying male infertile patients.

Minimum information and guidelines for reporting a multiplexed assay of variant effect.

Multiplexed assays of variant effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines have led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms.

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

Probiotics stimulate enterocyte migration and microbial diversity in the neonatal mouse intestine.

Beneficial microbes and probiotics show promise for the treatment of pediatric gastrointestinal diseases. However, basic mechanisms of probiosis are not well understood, and most investigations have been performed in germ-free or microbiome-depleted animals. We sought to functionally characterize probiotic-host interactions in the context of normal early development. Outbred CD1 neonatal mice were orally gavaged with one of two strains of human-derived Lactobacillus reuteri or an equal volume of vehicle. Transcriptome analysis was performed on enterocyte RNA isolated by laser-capture microdissection. Enterocyte migration and proliferation were assessed by labeling cells with 5-bromo-2'-deoxyuridine, and fecal microbial community composition was determined by 16S metagenomic sequencing. Probiotic ingestion altered gene expression in multiple canonical pathways involving cell motility. L. reuteri strain DSM 17938 dramatically increased enterocyte migration (3-fold), proliferation (34%), and crypt height (29%) compared to vehicle-treated mice, whereas strain ATCC PTA 6475 increased cell migration (2-fold) without affecting crypt proliferative activity. In addition, both probiotic strains increased the phylogenetic diversity and evenness between taxa of the fecal microbiome 24 h after a single probiotic gavage. These experiments identify two targets of probiosis in early development, the intestinal epithelium and the gut microbiome, and suggest novel mechanisms for probiotic strain-specific effects.

Accessing clinical-grade genomic classification data through the ClinGen Data Platform.

The Clinical Genome Resource (ClinGen) serves as an authoritative resource on the clinical relevance of genes and variants. In order to support our curation activities and to disseminate our findings to the community, we have developed a Data Platform of informatics resources backed by standardized data models. In this workshop we demonstrate our publicly available resources including curation interfaces, (Variant Curation Interface, CIViC), supporting infrastructure (Allele Registry, Genegraph), and data models (SEPIO, GA4GH VRS, VA).

Development and application of a computable genotype model in the GA4GH Variation Representation Specification.

As the diversity of genomic variation data increases with our growing understanding of the role of variation in health and disease, it is critical to develop standards for precise inter-system exchange of these data for research and clinical applications. The Global Alliance for Genomics and Health (GA4GH) Variation Representation Specification (VRS) meets this need through a technical terminology and information model for disambiguating and concisely representing variation concepts. Here we discuss the recent Genotype model in VRS, which may be used to represent the allelic composition of a genetic locus. We demonstrate the use of the Genotype model and the constituent Haplotype model for the precise and interoperable representation of pharmacogenomic diplotypes, HGVS variants, and VCF records using VRS and discuss how this can be leveraged to enable interoperable exchange and search operations between assayed variation and genomic knowledgebases.

Minimum information and guidelines for reporting a Multiplexed Assay of Variant Effect.

Multiplexed Assays of Variant Effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines has led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.

The Genboree Microbiome Toolset and the analysis of 16S rRNA microbial sequences.

BACKGROUND: Microbial metagenomic analyses rely on an increasing number of publicly available tools. Installation, integration, and maintenance of the tools poses significant burden on many researchers and creates a barrier to adoption of microbiome analysis, particularly in translational settings. METHODS: To address this need we have integrated a rich collection of microbiome analysis tools into the Genboree Microbiome Toolset and exposed them to the scientific community using the Software-as-a-Service model via the Genboree Workbench. The Genboree Microbiome Toolset provides an interactive environment for users at all bioinformatic experience levels in which to conduct microbiome analysis. The Toolset drives hypothesis generation by providing a wide range of analyses including alpha diversity and beta diversity, phylogenetic profiling, supervised machine learning, and feature selection. RESULTS: We validate the Toolset in two studies of the gut microbiota, one involving obese and lean twins, and the other involving children suffering from the irritable bowel syndrome. CONCLUSIONS: By lowering the barrier to performing a comprehensive set of microbiome analyses, the Toolset empowers investigators to translate high-volume sequencing data into valuable biomedical discoveries.

Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome.

BACKGROUND & AIMS: The intestinal microbiomes of healthy children and pediatric patients with irritable bowel syndrome (IBS) are not well defined. Studies in adults have indicated that the gastrointestinal microbiota could be involved in IBS. METHODS: We analyzed 71 samples from 22 children with IBS (pediatric Rome III criteria) and 22 healthy children, ages 7-12 years, by 16S ribosomal RNA gene sequencing, with an average of 54,287 reads/stool sample (average 454 read length = 503 bases). Data were analyzed using phylogenetic-based clustering (Unifrac), or an operational taxonomic unit (OTU) approach using a supervised machine learning tool (randomForest). Most samples were also hybridized to a microarray that can detect 8741 bacterial taxa (16S rRNA PhyloChip). RESULTS: Microbiomes associated with pediatric IBS were characterized by a significantly greater percentage of the class γ-proteobacteria (0.07% vs 0.89% of total bacteria, respectively; P < .05); 1 prominent component of this group was Haemophilus parainfluenzae. Differences highlighted by 454 sequencing were confirmed by high-resolution PhyloChip analysis. Using supervised learning techniques, we were able to classify different subtypes of IBS with a success rate of 98.5%, using limited sets of discriminant bacterial species. A novel Ruminococcus-like microbe was associated with IBS, indicating the potential utility of microbe discovery for gastrointestinal disorders. A greater frequency of pain correlated with an increased abundance of several bacterial taxa from the genus Alistipes. CONCLUSIONS: Using 16S metagenomics by PhyloChip DNA hybridization and deep 454 pyrosequencing, we associated specific microbiome signatures with pediatric IBS. These findings indicate the important association between gastrointestinal microbes and IBS in children; these approaches might be used in diagnosis of functional bowel disorders in pediatric patients.

Host response to probiotics determined by nutritional status of rotavirus-infected neonatal mice.

OBJECTIVES: Beneficial microbes and probiotics are promising agents for the prevention and treatment of enteric and diarrheal diseases in children; however, little is known about their in vivo mechanisms of action. We used a neonatal mouse model of rotavirus diarrhea to gain insight into how probiotics ameliorate acute gastroenteritis. METHODS: Rotavirus-infected mice were treated with 1 of 2 strains of human-derived Lactobacillus reuteri. We assessed intestinal microbiome composition with 16S metagenomic sequencing, enterocyte migration and proliferation with 5-bromo-2'-deoxyuridine, and antibody and cytokine concentrations with multiplex analyses of intestinal explant cultures. RESULTS: Probiotics reduced diarrhea duration, improved intestinal histopathology, and enhanced intestinal microbiome richness and phylogenetic diversity. The magnitude of reduction of diarrhea by probiotics was strain specific and influenced by nutritional status. L reuteri DSM 17938 reduced diarrhea duration by 0, 1, and 2 days in underweight, normal weight, and overweight pups, respectively. The magnitude of reduction of diarrhea duration correlated with increased enterocyte proliferation and migration. Strain ATCC PTA 6475 reduced diarrhea duration by 1 day in all of the mice without increasing enterocyte proliferation. Both probiotic strains decreased concentrations of proinflammatory cytokines, including macrophage inflammatory protein-1α and interleukin-1ß, in all of the animals, and increased rotavirus-specific antibodies in all but the underweight animals. Body weight also influenced the host response to rotavirus, in terms of diarrhea duration, enterocyte turnover, and antibody production. CONCLUSIONS: These data suggest that probiotic enhancement of enterocyte proliferation, villus repopulation, and virus-specific antibodies may contribute to diarrhea resolution, and that nutritional status influences the host response to both beneficial microbes and pathogens.

Clinical diagnosis of metabolic disorders using untargeted metabolomic profiling and disease-specific networks learned from profiling data.

Untargeted metabolomics is a global molecular profiling technology that can be used to screen for inborn errors of metabolism (IEMs). Metabolite perturbations are evaluated based on current knowledge of specific metabolic pathway deficiencies, a manual diagnostic process that is qualitative, has limited scalability, and is not equipped to learn from accumulating clinical data. Our purpose was to improve upon manual diagnosis of IEMs in the clinic by developing novel computational methods for analyzing untargeted metabolomics data. We employed CTD, an automated computational diagnostic method that "connects the dots" between metabolite perturbations observed in individual metabolomics profiling data and modules identified in disease-specific metabolite co-perturbation networks learned from prior profiling data. We also extended CTD to calculate distances between any two individuals (CTDncd) and between an individual and a disease state (CTDdm), to provide additional network-quantified predictors for use in diagnosis. We show that across 539 plasma samples, CTD-based network-quantified measures can reproduce accurate diagnosis of 16 different IEMs, including adenylosuccinase deficiency, argininemia, argininosuccinic aciduria, aromatic L-amino acid decarboxylase deficiency, cerebral creatine deficiency syndrome type 2, citrullinemia, cobalamin biosynthesis defect, GABA-transaminase deficiency, glutaric acidemia type 1, maple syrup urine disease, methylmalonic aciduria, ornithine transcarbamylase deficiency, phenylketonuria, propionic acidemia, rhizomelic chondrodysplasia punctata, and the Zellweger spectrum disorders. Our approach can be used to supplement information from biochemical pathways and has the potential to significantly enhance the interpretation of variants of uncertain significance uncovered by exome sequencing. CTD, CTDdm, and CTDncd can serve as an essential toolset for biological interpretation of untargeted metabolomics data that overcomes limitations associated with manual diagnosis to assist diagnosticians in clinical decision-making. By automating and quantifying the interpretation of perturbation patterns, CTD can improve the speed and confidence by which clinical laboratory directors make diagnostic and treatment decisions, while automatically improving performance with new case data.

The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification.

Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced "verse"), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH).

A Mild, DNA-Compatible Nitro Reduction Using B2(OH)4.

A hypodiboric acid system for the reduction of nitro groups on DNA-chemical conjugates has been developed. This transformation provided good to excellent yields of the reduced amine product for a variety of functionalized aromatic, heterocyclic, and aliphatic nitro compounds. DNA tolerance to reaction conditions, extension to decigram scale reductions, successful use in a DNA-encoded chemical library synthesis, and subsequent target selection are also described.

Quantitative Comparison of Enrichment from DNA-Encoded Chemical Library Selections.

DNA-encoded chemical libraries (DELs) provide a high-throughput and cost-effective route for screening billions of unique molecules for binding affinity for diverse protein targets. Identifying candidate compounds from these libraries involves affinity selection, DNA sequencing, and measuring enrichment in a sample pool of DNA barcodes. Successful detection of potent binders is affected by many factors, including selection parameters, chemical yields, library amplification, sequencing depth, sequencing errors, library sizes, and the chosen enrichment metric. To date, there has not been a clear consensus about how enrichment from DEL selections should be measured or reported. We propose a normalized  z-score enrichment metric using a binomial distribution model that satisfies important criteria that are relevant for analysis of DEL selection data. The introduced metric is robust with respect to library diversity and sampling and allows for quantitative comparisons of enrichment of n-synthons from parallel DEL selections. These features enable a comparative enrichment analysis strategy that can provide valuable information about hit compounds in early stage drug discovery.

ClinGen Pathogenicity Calculator: a configurable system for assessing pathogenicity of genetic variants.

BACKGROUND: The success of the clinical use of sequencing based tests (from single gene to genomes) depends on the accuracy and consistency of variant interpretation. Aiming to improve the interpretation process through practice guidelines, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have published standards and guidelines for the interpretation of sequence variants. However, manual application of the guidelines is tedious and prone to human error. Web-based tools and software systems may not only address this problem but also document reasoning and supporting evidence, thus enabling transparency of evidence-based reasoning and resolution of discordant interpretations. RESULTS: In this report, we describe the design, implementation, and initial testing of the Clinical Genome Resource (ClinGen) Pathogenicity Calculator, a configurable system and web service for the assessment of pathogenicity of Mendelian germline sequence variants. The system allows users to enter the applicable ACMG/AMP-style evidence tags for a specific allele with links to supporting data for each tag and generate guideline-based pathogenicity assessment for the allele. Through automation and comprehensive documentation of evidence codes, the system facilitates more accurate application of the ACMG/AMP guidelines, improves standardization in variant classification, and facilitates collaborative resolution of discordances. The rules of reasoning are configurable with gene-specific or disease-specific guideline variations (e.g. cardiomyopathy-specific frequency thresholds and functional assays). The software is modular, equipped with robust application program interfaces (APIs), and available under a free open source license and as a cloud-hosted web service, thus facilitating both stand-alone use and integration with existing variant curation and interpretation systems. The Pathogenicity Calculator is accessible at http://calculator.clinicalgenome.org . CONCLUSIONS: By enabling evidence-based reasoning about the pathogenicity of genetic variants and by documenting supporting evidence, the Calculator contributes toward the creation of a knowledge commons and more accurate interpretation of sequence variants in research and clinical care.