The hypothalamus, composed of multiple nuclei, is essential for maintaining the body’s homeostasis. Within the mediobasal hypothalamus, the arcuate nucleus (ARC) contains key neuronal populations, including appetite-suppressing pro-opiomelanocortin (POMC) neurons that regulate energy and glucose balance. Here, we present a chemically defined, scalable method for differentiating human pluripotent stem cells (hPSCs) into hypothalamic neurons enriched for POMC cells, compatible with robotic cell culture platforms for high-throughput use. Neuronal identity was validated by MERFISH single-cell transcriptomics, RNA-Seq, ATAC-Seq, and comparison to human hypothalamus. The method is robust across multiple hPSC lines, showing consistent induction of ventral diencephalon and hypothalamic markers. Derived neurons display metabolic disease-relevant features, including body mass index (BMI)-associated gene enrichment, and ATAC-Seq identifies potential candidate regulatory regions linked to hypothalamic development and metabolic traits. Functional assays reveal neuronal responses to insulin and the GLP-1 receptor agonist Exendin-4, and transcriptional responses to altered glucose conditions. This platform delivers a physiologically relevant model of human hypothalamic neurons that enables deeper mechanistic and therapeutic studies of metabolic disease.

The human cerebellum is implicated in various neurological and psychiatric diseases, but its complex development and cellular diversity have posed challenges for in vitro modeling. Here, we report the generation of human induced pluripotent stem cell (iPSC)-derived cerebellar organoids (hCBOs) that are characterized by induction of rhombomere 1 (R1) cellular identity and followed by derivation of typical neuronal and glial cell types of the cerebellum. In contrast to forebrain organoids with multiple neural rosettes and inside-out neuronal migration, hCBOs develop a germinal zone on the outermost surface of the organoids with outside-in neuronal migration. These hCBOs produce various neuronal cell types resembling granule neurons, Purkinje cells, Golgi neurons, and deep cerebellar nuclei. By using a glial induction strategy, we generate Bergmann glial cells (BGCs) that serve as scaffolds for migratory granule cells and enhance electrophysiological activity of the hCBOs. Furthermore, by generating hCBOs from patients with Friedreich's ataxia (FRDA), we reveal disease-specific phenotypes that can be reversed by histone deacetylase (HDAC) inhibitors and gene editing by CRISPR-Cas9. Taken together, our advanced hCBO model provides new opportunities to investigate the mechanisms of cerebellar ontogenesis and utilize patient-derived iPSCs for translational research.

The human cerebellum is a specialized brain region that is involved in various neurological and psychiatric diseases but has been challenging to study in vitro due its complex neurodevelopment and cellular diversity. Despite the progress in generating neural tissues from human induced pluripotent stem cells (iPSCs), an organoid model that recapitulates the key features of cerebellar development has not been widely established. Here, we report the generation of a 60-day method for human cerebellar organoids (hCBOs) that is characterized by induction of rhombomere 1 (R1) cellular identity followed by derivation of neuronal and glial cell types of the cerebellum. In contrast to forebrain organoids with multiple neural rosettes and inside-out neuronal migration, hCBOs develop a SOX2+ cerebellar plate on the outermost surface of organoids with outside-in neuronal migration, which is a characteristic hallmark of cerebellar histogenesis. These hCBOs produced various other cell types including granule neurons, Purkinje cells, Golgi neurons, and deep cerebellar nuclei. By using a glial induction strategy, we generate Bergmann glial cells (BGCs) within the hCBOs that not only serve as scaffolds for granule cells migration but also enhance electrophysiological response of the hCBOs. Furthermore, by generating hCBOs from patients with Friedreich's ataxia (FRDA), we revealed abnormal disease-specific phenotypes that could be reversed by histone deacetylase (HDAC) inhibitors and gene editing by CRISPR-Cas9. Taken together, our advanced hCBO model provides new opportunities to investigate the molecular and cellular mechanisms of cerebellar ontogenesis and utilize patient-derived iPSCs for translational research.

Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models.

The hypothalamus, composed of several nuclei, is essential for maintaining our body's homeostasis. The arcuate nucleus (ARC), located in the mediobasal hypothalamus, contains neuronal populations with eminent roles in energy and glucose homeostasis as well as reproduction. These neuronal populations are of great interest for translational research. To fulfill this promise, we used a robotic cell culture platform to provide a scalable and chemically defined approach for differentiating human pluripotent stem cells (hPSCs) into pro-opiomelanocortin (POMC), somatostatin (SST), tyrosine hydroxylase (TH) and gonadotropin-releasing hormone (GnRH) neuronal subpopulations with an ARC-like signature. This robust approach is reproducible across several distinct hPSC lines and exhibits a stepwise induction of key ventral diencephalon and ARC markers in transcriptomic profiling experiments. This is further corroborated by direct comparison to human fetal hypothalamus, and the enriched expression of genes implicated in obesity and type 2 diabetes (T2D). Genome-wide chromatin accessibility profiling by ATAC-seq identified accessible regulatory regions that can be utilized to predict candidate enhancers related to metabolic disorders and hypothalamic development. In depth molecular, cellular, and functional experiments unveiled the responsiveness of the hPSC-derived hypothalamic neurons to hormonal stimuli, such as insulin, neuropeptides including kisspeptin, and incretin mimetic drugs such as Exendin-4, highlighting their potential utility as physiologically relevant cellular models for disease studies. In addition, differential glucose and insulin treatments uncovered adaptability within the generated ARC neurons in the dynamic regulation of POMC and insulin receptors. In summary, the establishment of this model represents a novel, chemically defined, and scalable platform for manufacturing large numbers of hypothalamic arcuate neurons and serves as a valuable resource for modeling metabolic and reproductive disorders.

Development of new non-addictive analgesics requires advanced strategies to differentiate human pluripotent stem cells (hPSCs) into relevant cell types. Following principles of developmental biology and translational applicability, here we developed an efficient stepwise differentiation method for peptidergic and non-peptidergic nociceptors. By modulating specific cell signaling pathways, hPSCs were first converted into SOX10+ neural crest, followed by differentiation into sensory neurons. Detailed characterization, including ultrastructural analysis, confirmed that the hPSC-derived nociceptors displayed cellular and molecular features comparable to native dorsal root ganglion (DRG) neurons, and expressed high-threshold primary sensory neuron markers, transcription factors, neuropeptides, and over 150 ion channels and receptors relevant for pain research and axonal growth/regeneration studies (e.g., TRPV1, NAV1.7, NAV1.8, TAC1, CALCA, GAP43, DPYSL2, NMNAT2). Moreover, after confirming robust functional activities and differential response to noxious stimuli and specific drugs, a robotic cell culture system was employed to produce large quantities of human sensory neurons, which can be used to develop nociceptor-selective analgesics.

Human gliogenesis remains poorly understood, and derivation of astrocytes from human pluripotent stem cells (hPSCs) is inefficient and cumbersome. Here, we report controlled glial differentiation from hPSCs that bypasses neurogenesis, which otherwise precedes astrogliogenesis during brain development and in vitro differentiation. hPSCs were first differentiated into radial glial cells (RGCs) resembling resident RGCs of the fetal telencephalon, and modulation of specific cell signaling pathways resulted in direct and stepwise induction of key astroglial markers (NFIA, NFIB, SOX9, CD44, S100B, glial fibrillary acidic protein [GFAP]). Transcriptomic and genome-wide epigenetic mapping and single-cell analysis confirmed RGC-to-astrocyte differentiation, obviating neurogenesis and the gliogenic switch. Detailed molecular and cellular characterization experiments uncovered new mechanisms and markers for human RGCs and astrocytes. In summary, establishment of a glia-exclusive neural lineage progression model serves as a unique serum-free platform of manufacturing large numbers of RGCs and astrocytes for neuroscience, disease modeling (e.g., Alexander disease), and regenerative medicine.

To address the question of how microbial diversity and function in the oral cavities of children relates to caries diagnosis, we surveyed the supragingival plaque biofilm microbiome in 44 juvenile twin pairs. Using shotgun sequencing, we constructed a genome encyclopedia describing the core supragingival plaque microbiome. Caries phenotypes contained statistically significant enrichments in specific genome abundances and distinct community composition profiles, including strain-level changes. Metabolic pathways that are statistically associated with caries include several sugar-associated phosphotransferase systems, antimicrobial resistance, and metal transport. Numerous closely related previously uncharacterized microbes had substantial variation in central metabolism, including the loss of biosynthetic pathways resulting in auxotrophy, changing the ecological role. We also describe the first complete Gracilibacteria genomes from the human microbiome. Caries is a microbial community metabolic disorder that cannot be described by a single etiology, and our results provide the information needed for next-generation diagnostic tools and therapeutics for caries.IMPORTANCE Oral health has substantial economic importance, with over $100 billion spent on dental care in the United States annually. The microbiome plays a critical role in oral health, yet remains poorly classified. To address the question of how microbial diversity and function in the oral cavities of children relate to caries diagnosis, we surveyed the supragingival plaque biofilm microbiome in 44 juvenile twin pairs. Using shotgun sequencing, we constructed a genome encyclopedia describing the core supragingival plaque microbiome. This unveiled several new previously uncharacterized but ubiquitous microbial lineages in the oral microbiome. Caries is a microbial community metabolic disorder that cannot be described by a single etiology, and our results provide the information needed for next-generation diagnostic tools and therapeutics for caries.

The JCVI pan-genome pipeline is a collection of programs to run PanOCT and tools that support and extend the capabilities of PanOCT. PanOCT (pan-genome ortholog clustering tool) is a tool for pan-genome analysis of closely related prokaryotic species or strains. The JCVI Pan-Genome Pipeline wrapper invokes command-line utilities that prepare input genomes, invoke third-party tools such as NCBI Blast+, run PanOCT, generate a consensus pan-genome, annotate features of the pan-genome, detect sets of genes of interest such as antimicrobial resistance (AMR) genes and generate figures, tables and html pages to visualize the results. The pipeline can run in a hierarchical mode, lowering the RAM and compute resources used. Availability and implementation Source code, demo data, and detailed documentation are freely available at https://github.com/JCVenterInstitute/PanGenomePipeline.

Background: Bacterial pan-genomes, comprised of conserved and variable genes across multiple sequenced bacterial genomes, allow for identification of genomic regions that are phylogenetically discriminating or functionally important. Pan-genomes consist of large amounts of data, which can restrict researchers ability to locate and analyze these regions. Multiple software packages are available to visualize pan-genomes, but currently their ability to address these concerns are limited by using only pre-computed data sets, prioritizing core over variable gene clusters, or by not accounting for pan-chromosome positioning in the viewer. Results: We introduce PanACEA (Pan-genome Atlas with Chromosome Explorer and Analyzer), which utilizes locally-computed interactive web-pages to view ordered pan-genome data. It consists of multi-tiered, hierarchical display pages that extend from pan-chromosomes to both core and variable regions to single genes. Regions and genes are functionally annotated to allow for rapid searching and visual identification of regions of interest with the option that user-supplied genomic phylogenies and metadata can be incorporated. PanACEA's memory and time requirements are within the capacities of standard laptops. The capability of PanACEA as a research tool is demonstrated by highlighting a variable region important in differentiating strains of Enterobacter hormaechei. Conclusions: PanACEA can rapidly translate the results of pan-chromosome programs into an intuitive and interactive visual representation. It will empower researchers to visually explore and identify regions of the panchromosome that are most biologically interesting, and to obtain publication quality images of these regions.

Host-associated microbial communities are influenced by both host genetics and environmental factors. However, factors controlling the human oral microbiome and their impact on disease remain to be investigated. To determine the combined and relative effects of host genotype and environment on oral microbiome composition and caries phenotypes, we profiled the supragingival plaque microbiome of 485 dizygotic and monozygotic twins aged 5-11. Oral microbiome similarity always increased with shared host genotype, regardless of caries state. Additionally, although most of the variation in the oral microbiome was determined by environmental factors, highly heritable oral taxa were identified. The most heritable oral bacteria were not associated with caries state, did not tend to co-occur with other taxa, and decreased in abundance with age and sugar consumption frequency. Thus, while the human oral microbiome composition is influenced by host genetic background, potentially cariogenic taxa are likely not controlled by genetic factors.

SUMMARY:LOCUST is a custom sequence locus typer tool for classifying microbial genomes. It provides a fully automated opportunity to customize the classification of genome-wide nucleotide variant data most relevant to biological research.AVAILABILITY AND IMPLEMENTATION:Source code, demo data, and detailed documentation are freely available at http://sourceforge.net/projects/locustyper .CONTACT:lbrinkac@jcvi.org.SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Background: Ureaplasma urealyticum (UUR) and Ureaplasma parvum (UPA) are sexually transmitted bacteria among humans implicated in a variety of disease states including but not limited to: nongonococcal urethritis, infertility, adverse pregnancy outcomes, chorioamnionitis, and bronchopulmonary dysplasia in neonates. There are 10 distinct serotypes of UUR and 4 of UPA. Efforts to determine whether difference in pathogenic potential exists at the ureaplasma serovar level have been hampered by limitations of antibody-based typing methods, multiple cross-reactions and poor discriminating capacity in clinical samples containing two or more serovars.Results: We determined the genome sequences of the American Type Culture Collection (ATCC) type strains of all UUR and UPA serovars as well as four clinical isolates of UUR for which we were not able to determine serovar designation. UPA serovars had 0.75-0.78 Mbp genomes and UUR serovars were 0.84-0.95 Mbp. The original classification of ureaplasma isolates into distinct serovars was largely based on differences in the major ureaplasma surface antigen called the multiple banded antigen (MBA) and reactions of human and animal sera to the organisms. Whole genome analysis of the 14 serovars and the 4 clinical isolates showed the mba gene was part of a large superfamily, which is a phase variable gene system, and that some serovars have identical sets of mba genes. Most of the differences among serovars are hypothetical genes, and in general the two species and 14 serovars are extremely similar at the genome level.Conclusions: Comparative genome analysis suggests UUR is more capable of acquiring genes horizontally, which may contribute to its greater virulence for some conditions. The overwhelming evidence of extensive horizontal gene transfer among these organisms from our previous studies combined with our comparative analysis indicates that ureaplasmas exist as quasi-species rather than as stable serovars in their native environment. Therefore, differential pathogenicity and clinical outcome of a ureaplasmal infection is most likely not on the serovar level, but rather may be due to the presence or absence of potential pathogenicity factors in an individual ureaplasma clinical isolate and/or patient to patient differences in terms of autoimmunity and microbiome.

Pan-genome ortholog clustering tool (PanOCT) is a tool for pan-genomic analysis of closely related prokaryotic species or strains. PanOCT uses conserved gene neighborhood information to separate recently diverged paralogs into orthologous clusters where homology-only clustering methods cannot. The results from PanOCT and three commonly used graph-based ortholog-finding programs were compared using a set of four publicly available strains of the same bacterial species. All four methods agreed on ∼70% of the clusters and ∼86% of the proteins. The clusters that did not agree were inspected for evidence of correctness resulting in 85 high-confidence manually curated clusters that were used to compare all four methods.

In the past few years, the field of metagenomics has been growing at an accelerated pace, particularly in response to advancements in new sequencing technologies. The large volume of sequence data from novel organisms generated by metagenomic projects has triggered the development of specialized databases and tools focused on particular groups of organisms or data types. Here we describe a pipeline for the functional annotation of viral metagenomic sequence data. The Viral MetaGenome Annotation Pipeline (VMGAP) pipeline takes advantage of a number of specialized databases, such as collections of mobile genetic elements and environmental metagenomes to improve the classification and functional prediction of viral gene products. The pipeline assigns a functional term to each predicted protein sequence following a suite of comprehensive analyses whose results are ranked according to a priority rules hierarchy. Additional annotation is provided in the form of enzyme commission (EC) numbers, GO/MeGO terms and Hidden Markov Models together with supporting evidence.

Motivation: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users. Results: We have developed a workflow management system named Ergatis that enables users to build, execute and monitor pipelines for computational analysis of genomics data. Ergatis contains preconfigured components and template pipelines for a number of common bioinformatics tasks such as prokaryotic genome annotation and genome comparisons. Outputs from many of these components can be loaded into a Chado relational database. Ergatis was designed to be accessible to a broad class of users and provides a user friendly, web-based interface. Ergatis supports high-throughput batch processing on distributed compute clusters and has been used for data management in a number of genome annotation and comparative genomics projects. Availability: Ergatis is an open-source project and is freely available at http://ergatis.sourceforge.net Contact: jorvis@users.sourceforge.net

Pathema (http://pathema.jcvi.org) is one of the eight Bioinformatics Resource Centers (BRCs) funded by the National Institute of Allergy and Infectious Disease (NIAID) designed to serve as a core resource for the bio-defense and infectious disease research community. Pathema strives to support basic research and accelerate scientific progress for understanding, detecting, diagnosing and treating an established set of six target NIAID Category A–C pathogens: Category A priority pathogens; Bacillus anthracis and Clostridium botulinum, and Category B priority pathogens; Burkholderia mallei, Burkholderia pseudomallei, Clostridium perfringens and Entamoeba histolytica. Each target pathogen is represented in one of four distinct clade-specific Pathema web resources and underlying databases developed to target the specific data and analysis needs of each scientific community. All publicly available complete genome projects of phylogenetically related organisms are also represented, providing a comprehensive collection of organisms for comparative analyses. Pathema facilitates the scientific exploration of genomic and related data through its integration with web-based analysis tools, customized to obtain, display, and compute results relevant to ongoing pathogen research. Pathema serves the bio-defense and infectious disease research community by disseminating data resulting from pathogen genome sequencing projects and providing access to the results of inter-genomic comparisons for these organisms.

Abstract Background Burkholderia species exhibit enormous phenotypic diversity, ranging from the nonpathogenic, soil- and water-inhabiting Burkholderia thailandensis to the virulent, host-adapted mammalian pathogen B. mallei. Genomic diversity is evident within Burkholderia species as well. Individual isolates of Burkholderia pseudomallei and B. thailandensis, for example, carry a variety of strain-specific genomic islands (GIs), including putative pathogenicity and metabolic islands, prophage-like islands, and prophages. These GIs may provide some strains with a competitive advantage in the environment and/or in the host relative to other strains. Results Here we present the results of analysis of 37 prophages, putative prophages, and prophage-like elements from six different Burkholderia species. Five of these were spontaneously induced to form bacteriophage particles from B. pseudomallei and B. thailandensis strains and were isolated and fully sequenced; 24 were computationally predicted in sequenced Burkholderia genomes; and eight are previously characterized prophages or prophage-like elements. The results reveal numerous differences in both genome structure and gene content among elements derived from different species as well as from strains within species, due in part to the incorporation of additional DNA, or 'morons' into the prophage genomes. Implications for pathogenicity are also discussed. Lastly, RNAseq analysis of gene expression showed that many of the genes in ϕ1026b that appear to contribute to phage and lysogen fitness were expressed independently of the phage structural and replication genes. Conclusions This study provides the first estimate of the relative contribution of prophages to the vast phenotypic diversity found among the Burkholderiae.

We present the genome sequences of a new clinical isolate of the important human pathogen, Aspergillus fumigatus, A1163, and two closely related but rarely pathogenic species, Neosartorya fischeri NRRL181 and Aspergillus clavatus NRRL1. Comparative genomic analysis of A1163 with the recently sequenced A. fumigatus isolate Af293 has identified core, variable and up to 2% unique genes in each genome. While the core genes are 99.8% identical at the nucleotide level, identity for variable genes can be as low 40%. The most divergent loci appear to contain heterokaryon incompatibility (het) genes associated with fungal programmed cell death such as developmental regulator rosA. Cross-species comparison has revealed that 8.5%, 13.5% and 12.6%, respectively, of A. fumigatus, N. fischeri and A. clavatus genes are species-specific. These genes are significantly smaller in size than core genes, contain fewer exons and exhibit a subtelomeric bias. Most of them cluster together in 13 chromosomal islands, which are enriched for pseudogenes, transposons and other repetitive elements. At least 20% of A. fumigatus-specific genes appear to be functional and involved in carbohydrate and chitin catabolism, transport, detoxification, secondary metabolism and other functions that may facilitate the adaptation to heterogeneous environments such as soil or a mammalian host. Contrary to what was suggested previously, their origin cannot be attributed to horizontal gene transfer (HGT), but instead is likely to involve duplication, diversification and differential gene loss (DDL). The role of duplication in the origin of lineage-specific genes is further underlined by the discovery of genomic islands that seem to function as designated “gene dumps” and, perhaps, simultaneously, as “gene factories”.

MicroRNAs (miRNAs) are small noncoding regulatory RNAs that reduce stability and/or translation of fully or partially sequence-complementary target mRNAs. In order to identify miRNAs and to assess their expression patterns, we sequenced over 250 small RNA libraries from 26 different organ systems and cell types of human and rodents that were enriched in neuronal as well as normal and malignant hematopoietic cells and tissues. We present expression profiles derived from clone count data and provide computational tools for their analysis. Unexpectedly, a relatively small set of miRNAs, many of which are ubiquitously expressed, account for most of the differences in miRNA profiles between cell lineages and tissues. This broad survey also provides detailed and accurate information about mature sequences, precursors, genome locations, maturation processes, inferred transcriptional units, and conservation patterns. We also propose a subclassification scheme for miRNAs for assisting future experimental and computational functional analyses.