The Hypervariable Tpr Multigene Family of Theileria Parasites, Defined by a Conserved, Membrane-Associated, C-Terminal Domain, Includes Several Copies with Defined Orthology Between Species.

Multigene families often play an important role in host-parasite interactions. One of the largest multigene families in Theileria parva, the causative agent of East Coast fever, is the T. parva repeat (Tpr) gene family. The function of the putative Tpr proteins remains unknown. The initial publication of the T. parva reference genome identified 39 Tpr family open reading frames (ORFs) sharing a conserved C-terminal domain. Twenty-eight of these are clustered in a central region of chromosome 3, termed the "Tpr locus", while others are dispersed throughout all four nuclear chromosomes. The Tpr locus contains three of the four assembly gaps remaining in the genome, suggesting the presence of additional, as yet uncharacterized, Tpr gene copies. Here, we describe the use of long-read sequencing to attempt to close the gaps in the reference assembly of T. parva (located among multigene families clusters), characterize the full complement of Tpr family ORFs in the T. parva reference genome, and evaluate their evolutionary relationship with Tpr homologs in other Theileria species. We identify three new Tpr family genes in the T. parva reference genome and show that sequence similarity among paralogs in the Tpr locus is significantly higher than between genes outside the Tpr locus. We also identify sequences homologous to the conserved C-terminal domain in five additional Theileria species. Using these sequences, we show that the evolution of this gene family involves conservation of a few orthologs across species, combined with gene gains/losses, and species-specific expansions.

The Neuroscience Multi-Omic Archive: a BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain.

Scalable technologies to sequence the transcriptomes and epigenomes of single cells are transforming our understanding of cell types and cell states. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Cell Census Network (BICCN) is applying these technologies at unprecedented scale to map the cell types in the mammalian brain. In an effort to increase data FAIRness (Findable, Accessible, Interoperable, Reusable), the NIH has established repositories to make data generated by the BICCN and related BRAIN Initiative projects accessible to the broader research community. Here, we describe the Neuroscience Multi-Omic Archive (NeMO Archive; nemoarchive.org), which serves as the primary repository for genomics data from the BRAIN Initiative. Working closely with other BRAIN Initiative researchers, we have organized these data into a continually expanding, curated repository, which contains transcriptomic and epigenomic data from over 50 million brain cells, including single-cell genomic data from all of the major regions of the adult and prenatal human and mouse brains, as well as substantial single-cell genomic data from non-human primates. We make available several tools for accessing these data, including a searchable web portal, a cloud-computing interface for large-scale data processing (implemented on Terra, terra.bio), and a visualization and analysis platform, NeMO Analytics (nemoanalytics.org).

Making Common Fund data more findable: catalyzing a data ecosystem.

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs' Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs.

Mutagenesis of human genomes by endogenous mobile elements on a population scale.

Several large-scale Illumina whole-genome sequencing (WGS) and whole-exome sequencing (WES) projects have emerged recently that have provided exceptional opportunities to discover mobile element insertions (MEIs) and study the impact of these MEIs on human genomes. However, these projects also have presented major challenges with respect to the scalability and computational costs associated with performing MEI discovery on tens or even hundreds of thousands of samples. To meet these challenges, we have developed a more efficient and scalable version of our mobile element locator tool (MELT) called CloudMELT. We then used MELT and CloudMELT to perform MEI discovery in 57,919 human genomes and exomes, leading to the discovery of 104,350 nonredundant MEIs. We leveraged this collection (1) to examine potentially active L1 source elements that drive the mobilization of new Alu, L1, and SVA MEIs in humans; (2) to examine the population distributions and subfamilies of these MEIs; and (3) to examine the mutagenesis of GENCODE genes, ENCODE-annotated features, and disease genes by these MEIs. Our study provides new insights on the L1 source elements that drive MEI mutagenesis and brings forth a better understanding of how this mutagenesis impacts human genomes.

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex.

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

HMPDACC: a Human Microbiome Project Multi-omic data resource.

The Human Microbiome Project (HMP) explored microbial communities of the human body in both healthy and disease states. Two phases of the HMP (HMP and iHMP) together generated >48TB of data (public and controlled access) from multiple, varied omics studies of both the microbiome and associated hosts. The Human Microbiome Project Data Coordination Center (HMPDACC) was established to provide a portal to access data and resources produced by the HMP. The HMPDACC provides a unified data repository, multi-faceted search functionality, analysis pipelines and standardized protocols to facilitate community use of HMP data. Recent efforts have been put toward making HMP data more findable, accessible, interoperable and reusable. HMPDACC resources are freely available at www.hmpdacc.org.

Capture-based enrichment of Theileria parva DNA enables full genome assembly of first buffalo-derived strain and reveals exceptional intra-specific genetic diversity.

Theileria parva is an economically important, intracellular, tick-transmitted parasite of cattle. A live vaccine against the parasite is effective against challenge from cattle-transmissible T. parva but not against genotypes originating from the African Cape buffalo, a major wildlife reservoir, prompting the need to characterize genome-wide variation within and between cattle- and buffalo-associated T. parva populations. Here, we describe a capture-based target enrichment approach that enables, for the first time, de novo assembly of nearly complete T. parva genomes derived from infected host cell lines. This approach has exceptionally high specificity and sensitivity and is successful for both cattle- and buffalo-derived T. parva parasites. De novo genome assemblies generated for cattle genotypes differ from the reference by ~54K single nucleotide polymorphisms (SNPs) throughout the 8.31 Mb genome, an average of 6.5 SNPs/kb. We report the first buffalo-derived T. parva genome, which is ~20 kb larger than the genome from the reference, cattle-derived, Muguga strain, and contains 25 new potential genes. The average non-synonymous nucleotide diversity (πN) per gene, between buffalo-derived T. parva and the Muguga strain, was 1.3%. This remarkably high level of genetic divergence is supported by an average Wright's fixation index (FST), genome-wide, of 0.44, reflecting a degree of genetic differentiation between cattle- and buffalo-derived T. parva parasites more commonly seen between, rather than within, species. These findings present clear implications for vaccine development, further demonstrated by the ability to assemble nearly all known antigens in the buffalo-derived strain, which will be critical in design of next generation vaccines. The DNA capture approach used provides a clear advantage in specificity over alternative T. parva DNA enrichment methods used previously, such as those that utilize schizont purification, is less labor intensive, and enables in-depth comparative genomics in this apicomplexan parasite.

A comprehensive non-redundant gene catalog reveals extensive within-community intraspecies diversity in the human vagina.

Analysis of metagenomic and metatranscriptomic data is complicated and typically requires extensive computational resources. Leveraging a curated reference database of genes encoded by members of the target microbiome can make these analyses more tractable. In this study, we assemble a comprehensive human vaginal non-redundant gene catalog (VIRGO) that includes 0.95 million non-redundant genes. The gene catalog is functionally and taxonomically annotated. We also construct a vaginal orthologous groups (VOG) from VIRGO. The gene-centric design of VIRGO and VOG provides an easily accessible tool to comprehensively characterize the structure and function of vaginal metagenome and metatranscriptome datasets. To highlight the utility of VIRGO, we analyze 1,507 additional vaginal metagenomes, and identify a high degree of intraspecies diversity within and across vaginal microbiota. VIRGO offers a convenient reference database and toolkit that will facilitate a more in-depth understanding of the role of vaginal microorganisms in women's health and reproductive outcomes.

Strains used in whole organism Plasmodium falciparum vaccine trials differ in genome structure, sequence, and immunogenic potential.

BACKGROUND: Plasmodium falciparum (Pf) whole-organism sporozoite vaccines have been shown to provide significant protection against controlled human malaria infection (CHMI) in clinical trials. Initial CHMI studies showed significantly higher durable protection against homologous than heterologous strains, suggesting the presence of strain-specific vaccine-induced protection. However, interpretation of these results and understanding of their relevance to vaccine efficacy have been hampered by the lack of knowledge on genetic differences between vaccine and CHMI strains, and how these strains are related to parasites in malaria endemic regions. METHODS: Whole genome sequencing using long-read (Pacific Biosciences) and short-read (Illumina) sequencing platforms was conducted to generate de novo genome assemblies for the vaccine strain, NF54, and for strains used in heterologous CHMI (7G8 from Brazil, NF166.C8 from Guinea, and NF135.C10 from Cambodia). The assemblies were used to characterize sequences in each strain relative to the reference 3D7 (a clone of NF54) genome. Strains were compared to each other and to a collection of clinical isolates (sequenced as part of this study or from public repositories) from South America, sub-Saharan Africa, and Southeast Asia. RESULTS: While few variants were detected between 3D7 and NF54, we identified tens of thousands of variants between NF54 and the three heterologous strains. These variants include SNPs, indels, and small structural variants that fall in regulatory and immunologically important regions, including transcription factors (such as PfAP2-L and PfAP2-G) and pre-erythrocytic antigens that may be key for sporozoite vaccine-induced protection. Additionally, these variants directly contributed to diversity in immunologically important regions of the genomes as detected through in silico CD8+ T cell epitope predictions. Of all heterologous strains, NF135.C10 had the highest number of unique predicted epitope sequences when compared to NF54. Comparison to global clinical isolates revealed that these four strains are representative of their geographic origin despite long-term culture adaptation; of note, NF135.C10 is from an admixed population, and not part of recently formed subpopulations resistant to artemisinin-based therapies present in the Greater Mekong Sub-region. CONCLUSIONS: These results will assist in the interpretation of vaccine efficacy of whole-organism vaccines against homologous and heterologous CHMI.

Interactive exploratory data analysis of Integrative Human Microbiome Project data using Metaviz.

The rich data produced by the second phase of the Human Microbiome Project (iHMP) offers a unique opportunity to test hypotheses that interactions between microbial communities and a human host might impact an individual's health or disease status. In this work we describe infrastructure that integrates Metaviz, an interactive microbiome data analysis and visualization tool, with the iHMP Data Coordination Center web portal and the HMP2Data R/Bioconductor package. We describe integrative statistical and visual analyses of two datasets from iHMP using Metaviz along with the metagenomeSeq R/Bioconductor package for statistical analysis of differential abundance analysis. These use cases demonstrate the utility of a combined approach to access and analyze data from this resource.

TwinBLAST: When Two Is Better than One.

Analysis of sequence read pairs can be essential for characterizing structural variation, including junction-spanning pairs of reads (JSPRs) suggesting recent lateral/horizontal gene transfer. TwinBLAST can be used to facilitate this analysis of JSPRs by enabling the visualization and curation of two BLAST reports side by side in a single interface.

Erratum: Strains, functions and dynamics in the expanded Human Microbiome Project.

This corrects the article DOI: 10.1038/nature23889.

Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium.

In order for human microbiome studies to translate into actionable outcomes for health, meta-analysis of reproducible data from population-scale cohorts is needed. Achieving sufficient reproducibility in microbiome research has proven challenging. We report a baseline investigation of variability in taxonomic profiling for the Microbiome Quality Control (MBQC) project baseline study (MBQC-base). Blinded specimen sets from human stool, chemostats, and artificial microbial communities were sequenced by 15 laboratories and analyzed using nine bioinformatics protocols. Variability depended most on biospecimen type and origin, followed by DNA extraction, sample handling environment, and bioinformatics. Analysis of artificial community specimens revealed differences in extraction efficiency and bioinformatic classification. These results may guide researchers in experimental design choices for gut microbiome studies.

Strains, functions and dynamics in the expanded Human Microbiome Project.

The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.

CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.

BACKGROUND: The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. RESULTS: CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CONCLUSIONS: CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.

Distinguishing potential bacteria-tumor associations from contamination in a secondary data analysis of public cancer genome sequence data.

BACKGROUND: A variety of bacteria are known to influence carcinogenesis. Therefore, we sought to investigate if publicly available whole genome and whole transcriptome sequencing data generated by large public cancer genome efforts, like The Cancer Genome Atlas (TCGA), could be used to identify bacteria associated with cancer. The Burrows-Wheeler aligner (BWA) was used to align a subset of Illumina paired-end sequencing data from TCGA to the human reference genome and all complete bacterial genomes in the RefSeq database in an effort to identify bacterial read pairs from the microbiome. RESULTS: Through careful consideration of all of the bacterial taxa present in the cancer types investigated, their relative abundance, and batch effects, we were able to identify some read pairs from certain taxa as likely resulting from contamination. In particular, the presence of Mycobacterium tuberculosis complex in the ovarian serous cystadenocarcinoma (OV) and glioblastoma multiforme (GBM) samples was correlated with the sequencing center of the samples. Additionally, there was a correlation between the presence of Ralstonia spp. and two specific plates of acute myeloid leukemia (AML) samples. At the end, associations remained between Pseudomonas-like and Acinetobacter-like read pairs in AML, and Pseudomonas-like read pairs in stomach adenocarcinoma (STAD) that could not be explained through batch effects or systematic contamination as seen in other samples. CONCLUSIONS: This approach suggests that it is possible to identify bacteria that may be present in human tumor samples from public genome sequencing data that can be examined further experimentally. More weight should be given to this approach in the future when bacterial associations with diseases are suspected.

Genome-wide diversity and gene expression profiling of Babesia microti isolates identify polymorphic genes that mediate host-pathogen interactions.

Babesia microti, a tick-transmitted, intraerythrocytic protozoan parasite circulating mainly among small mammals, is the primary cause of human babesiosis. While most cases are transmitted by Ixodes ticks, the disease may also be transmitted through blood transfusion and perinatally. A comprehensive analysis of genome composition, genetic diversity, and gene expression profiling of seven B. microti isolates revealed that genetic variation in isolates from the Northeast United States is almost exclusively associated with genes encoding the surface proteome and secretome of the parasite. Furthermore, we found that polymorphism is restricted to a small number of genes, which are highly expressed during infection. In order to identify pathogen-encoded factors involved in host-parasite interactions, we screened a proteome array comprised of 174 B. microti proteins, including several predicted members of the parasite secretome. Using this immuno-proteomic approach we identified several novel antigens that trigger strong host immune responses during the onset of infection. The genomic and immunological data presented herein provide the first insights into the determinants of B. microti interaction with its mammalian hosts and their relevance for understanding the selective pressures acting on parasite evolution.

An integrated genomic and transcriptomic survey of mucormycosis-causing fungi.

Mucormycosis is a life-threatening infection caused by Mucorales fungi. Here we sequence 30 fungal genomes, and perform transcriptomics with three representative Rhizopus and Mucor strains and with human airway epithelial cells during fungal invasion, to reveal key host and fungal determinants contributing to pathogenesis. Analysis of the host transcriptional response to Mucorales reveals platelet-derived growth factor receptor B (PDGFRB) signaling as part of a core response to divergent pathogenic fungi; inhibition of PDGFRB reduces Mucorales-induced damage to host cells. The unique presence of CotH invasins in all invasive Mucorales, and the correlation between CotH gene copy number and clinical prevalence, are consistent with an important role for these proteins in mucormycosis pathogenesis. Our work provides insight into the evolution of this medically and economically important group of fungi, and identifies several molecular pathways that might be exploited as potential therapeutic targets.

Functional dynamics of the gut microbiome in elderly people during probiotic consumption.

UNLABELLED: A mechanistic understanding of the purported health benefits conferred by consumption of probiotic bacteria has been limited by our knowledge of the resident gut microbiota and its interaction with the host. Here, we detail the impact of a single-organism probiotic, Lactobacillus rhamnosus GG ATCC 53103 (LGG), on the structure and functional dynamics (gene expression) of the gut microbiota in a study of 12 healthy individuals, 65 to 80 years old. The analysis revealed that while the overall community composition was stable as assessed by 16S rRNA profiling, the transcriptional response of the gut microbiota was modulated by probiotic treatment. Comparison of transcriptional profiles based on taxonomic composition yielded three distinct transcriptome groups that displayed considerable differences in functional dynamics. The transcriptional profile of LGG in vivo was remarkably concordant across study subjects despite the considerable interindividual nature of the gut microbiota. However, we identified genes involved in flagellar motility, chemotaxis, and adhesion from Bifidobacterium and the dominant butyrate producers Roseburia and Eubacterium whose expression was increased during probiotic consumption, suggesting that LGG may promote interactions between key constituents of the microbiota and the host epithelium. These results provide evidence for the discrete functional effects imparted by a specific single-organism probiotic and challenge the prevailing notion that probiotics substantially modify the resident microbiota within nondiseased individuals in an appreciable fashion. IMPORTANCE: Probiotic bacteria have been used for over a century to promote digestive health. Many individuals report that probiotics alleviate a number of digestive issues, yet little evidence links how probiotic microbes influence human health. Here, we show how the resident microbes that inhabit the healthy human gut respond to a probiotic. The well-studied probiotic Lactobacillus rhamnosus GG ATCC 53103 (LGG) was administered in a clinical trial, and a suite of measurements of the resident microbes were taken to evaluate potential changes over the course of probiotic consumption. We found that LGG transiently enriches for functions to potentially promote anti-inflammatory pathways in the resident microbes.