Advancing the microbiome research community.

The human microbiome has become a recognized factor in promoting and maintaining health. We outline opportunities in interdisciplinary research, analytical rigor, standardization, and policy development for this relatively new and rapidly developing field. Advances in these aspects of the research community may in turn advance our understanding of human microbiome biology.

Pluripotency of a founding field: rebranding developmental biology.

The field of developmental biology has declined in prominence in recent decades, with off-shoots from the field becoming more fashionable and highly funded. This has created inequity in discovery and opportunity, partly due to the perception that the field is antiquated or not cutting edge. A 'think tank' of scientists from multiple developmental biology-related disciplines came together to define specific challenges in the field that may have inhibited innovation, and to provide tangible solutions to some of the issues facing developmental biology. The community suggestions include a call to the community to help 'rebrand' the field, alongside proposals for additional funding apparatuses, frameworks for interdisciplinary innovative collaborations, pedagogical access, improved science communication, increased diversity and inclusion, and equity of resources to provide maximal impact to the community.

Critical Assessment of Metagenome Interpretation: the second round of challenges.

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

Acipenserid herpesvirus 2 genome and partial validation of a qPCR for its detection in white sturgeon Acipenser transmontanus.

White sturgeon Acipenser transmontanus is the primary species used for caviar and sturgeon meat production in the USA. An important pathogen of white sturgeon is acipenserid herpesvirus 2 (AciHV-2). In this study, 4 archived isolates from temporally discrete natural outbreaks spanning the past 30 yr were sequenced via Illumina and Oxford Nanopore Technologies platforms. Assemblies of approximately 134 kb were obtained for each isolate, and the putative ATPase subunit of the terminase gene was selected as a potential quantitative PCR (qPCR) target based on sequence conservation among AciHV-2 isolates and low sequence homology with other important viral pathogens. The qPCR was repeatable and reproducible, with a linear dynamic range covering 5 orders of magnitude, an efficiency of approximately 96%, an R2 of 0.9872, and an analytical sensitivity of 103 copies per reaction after 35 cycles. There was no cross-reaction with other known viruses or closely related sturgeon species, and no inhibition by sturgeon DNA. Clinical accuracy was assessed from white sturgeon juveniles exposed to AciHV-2 by immersion. Viral culture (gold standard) and qPCR were in complete agreement for both cell culture negative and cell culture positive samples, indicating that this assay has 100% relative accuracy compared to cell culture during an active outbreak. The availability of a whole-genome sequence for AciHV-2 and a highly specific and sensitive qPCR assay for detection of AciHV-2 in white sturgeon lays a foundation for further studies on host-pathogen interactions while providing a specific and rapid test for AciHV-2 in captive and wild populations.

Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets.

BACKGROUND: Long-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates. RESULTS: Our results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing. CONCLUSIONS: Our critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

MQF and buffered MQF: quotient filters for efficient storage of k-mers with their counts and metadata.

BACKGROUND: Specialized data structures are required for online algorithms to efficiently handle large sequencing datasets. The counting quotient filter (CQF), a compact hashtable, can efficiently store k-mers with a skewed distribution. RESULT: Here, we present the mixed-counters quotient filter (MQF) as a new variant of the CQF with novel counting and labeling systems. The new counting system adapts to a wider range of data distributions for increased space efficiency and is faster than the CQF for insertions and queries in most of the tested scenarios. A buffered version of the MQF can offload storage to disk, trading speed of insertions and queries for a significant memory reduction. The labeling system provides a flexible framework for assigning labels to member items while maintaining good data locality and a concise memory representation. These labels serve as a minimal perfect hash function but are ~ tenfold faster than BBhash, with no need to re-analyze the original data for further insertions or deletions. CONCLUSIONS: The MQF is a flexible and efficient data structure that extends our ability to work with high throughput sequencing data.

Whole genome variant association across 100 dogs identifies a frame shift mutation in DISHEVELLED 2 which contributes to Robinow-like syndrome in Bulldogs and related screw tail dog breeds.

Domestic dog breeds exhibit remarkable morphological variations that result from centuries of artificial selection and breeding. Identifying the genetic changes that contribute to these variations could provide critical insights into the molecular basis of tissue and organismal morphogenesis. Bulldogs, French Bulldogs and Boston Terriers share many morphological and disease-predisposition traits, including brachycephalic skull morphology, widely set eyes and short stature. Unlike other brachycephalic dogs, these breeds also exhibit vertebral malformations that result in a truncated, kinked tail (screw tail). Whole genome sequencing of 100 dogs from 21 breeds identified 12.4 million bi-allelic variants that met inclusion criteria. Whole Genome Association of these variants with the breed defining phenotype of screw tail was performed using 10 cases and 84 controls and identified a frameshift mutation in the WNT pathway gene DISHEVELLED 2 (DVL2) (Chr5: 32195043_32195044del, p = 4.37 X 10-37) as the most strongly associated variant in the canine genome. This DVL2 variant was fixed in Bulldogs and French Bulldogs and had a high allele frequency (0.94) in Boston Terriers. The DVL2 variant segregated with thoracic and caudal vertebral column malformations in a recessive manner with incomplete and variable penetrance for thoracic vertebral malformations between different breeds. Importantly, analogous frameshift mutations in the human DVL1 and DVL3 genes cause Robinow syndrome, a congenital disorder characterized by similar craniofacial, limb and vertebral malformations. Analysis of the canine DVL2 variant protein showed that its ability to undergo WNT-induced phosphorylation is reduced, suggesting that altered WNT signaling may contribute to the Robinow-like syndrome in the screwtail breeds.

Centromere location in Arabidopsis is unaltered by extreme divergence in CENH3 protein sequence.

During cell division, spindle fibers attach to chromosomes at centromeres. The DNA sequence at regional centromeres is fast evolving with no conserved genetic signature for centromere identity. Instead CENH3, a centromere-specific histone H3 variant, is the epigenetic signature that specifies centromere location across both plant and animal kingdoms. Paradoxically, CENH3 is also adaptively evolving. An ongoing question is whether CENH3 evolution is driven by a functional relationship with the underlying DNA sequence. Here, we demonstrate that despite extensive protein sequence divergence, CENH3 histones from distant species assemble centromeres on the same underlying DNA sequence. We first characterized the organization and diversity of centromere repeats in wild-type Arabidopsis thaliana We show that A. thaliana CENH3-containing nucleosomes exhibit a strong preference for a unique subset of centromeric repeats. These sequences are largely missing from the genome assemblies and represent the youngest and most homogeneous class of repeats. Next, we tested the evolutionary specificity of this interaction in a background in which the native A. thaliana CENH3 is replaced with CENH3s from distant species. Strikingly, we find that CENH3 from Lepidium oleraceum and Zea mays, although specifying epigenetically weaker centromeres that result in genome elimination upon outcrossing, show a binding pattern on A. thaliana centromere repeats that is indistinguishable from the native CENH3. Our results demonstrate positional stability of a highly diverged CENH3 on independently evolved repeats, suggesting that the sequence specificity of centromeres is determined by a mechanism independent of CENH3.

Sequencing data discovery with MetaSeek.

SUMMARY: Sequencing data resources have increased exponentially in recent years, as has interest in large-scale meta-analyses of integrated next-generation sequencing datasets. However, curation of integrated datasets that match a user's particular research priorities is currently a time-intensive and imprecise task. MetaSeek is a sequencing data discovery tool that enables users to flexibly search and filter on any metadata field to quickly find the sequencing datasets that meet their needs. MetaSeek automatically scrapes metadata from all publicly available datasets in the Sequence Read Archive, cleans and parses messy, user-provided metadata into a structured, standard-compliant database and predicts missing fields where possible. MetaSeek provides a web-based graphical user interface and interactive visualization dashboard, as well as a programmatic API to rapidly search, filter, visualize, save, share and download matching sequencing metadata. AVAILABILITY AND IMPLEMENTATION: The MetaSeek online interface is available at https://www.metaseek.cloud/. The MetaSeek database can also be accessed via API to programmatically search, filter and download all metadata. MetaSeek source code, metadata scrapers and documents are available at https://github.com/MetaSeek-Sequencing-Data-Discovery/metaseek/.

ANISEED 2017: extending the integrated ascidian database to the exploration and evolutionary comparison of genome-scale datasets.

ANISEED (www.aniseed.cnrs.fr) is the main model organism database for tunicates, the sister-group of vertebrates. This release gives access to annotated genomes, gene expression patterns, and anatomical descriptions for nine ascidian species. It provides increased integration with external molecular and taxonomy databases, better support for epigenomics datasets, in particular RNA-seq, ChIP-seq and SELEX-seq, and features novel interactive interfaces for existing and novel datatypes. In particular, the cross-species navigation and comparison is enhanced through a novel taxonomy section describing each represented species and through the implementation of interactive phylogenetic gene trees for 60% of tunicate genes. The gene expression section displays the results of RNA-seq experiments for the three major model species of solitary ascidians. Gene expression is controlled by the binding of transcription factors to cis-regulatory sequences. A high-resolution description of the DNA-binding specificity for 131 Ciona robusta (formerly C. intestinalis type A) transcription factors by SELEX-seq is provided and used to map candidate binding sites across the Ciona robusta and Phallusia mammillata genomes. Finally, use of a WashU Epigenome browser enhances genome navigation, while a Genomicus server was set up to explore microsynteny relationships within tunicates and with vertebrates, Amphioxus, echinoderms and hemichordates.

FGF4 retrogene on CFA12 is responsible for chondrodystrophy and intervertebral disc disease in dogs.

Chondrodystrophy in dogs is defined by dysplastic, shortened long bones and premature degeneration and calcification of intervertebral discs. Independent genome-wide association analyses for skeletal dysplasia (short limbs) within a single breed (PBonferroni = 0.01) and intervertebral disc disease (IVDD) across breeds (PBonferroni = 4.0 × 10-10) both identified a significant association to the same region on CFA12. Whole genome sequencing identified a highly expressed FGF4 retrogene within this shared region. The FGF4 retrogene segregated with limb length and had an odds ratio of 51.23 (95% CI = 46.69, 56.20) for IVDD. Long bone length in dogs is a unique example of multiple disease-causing retrocopies of the same parental gene in a mammalian species. FGF signaling abnormalities have been associated with skeletal dysplasia in humans, and our findings present opportunities for both selective elimination of a medically and financially devastating disease in dogs and further understanding of the ever-growing complexity of retrogene biology.

Tackling soil diversity with the assembly of large, complex metagenomes.

The large volumes of sequencing data required to sample deeply the microbial communities of complex environments pose new challenges to sequence analysis. De novo metagenomic assembly effectively reduces the total amount of data to be analyzed but requires substantial computational resources. We combine two preassembly filtering approaches--digital normalization and partitioning--to generate previously intractable large metagenome assemblies. Using a human-gut mock community dataset, we demonstrate that these methods result in assemblies nearly identical to assemblies from unprocessed data. We then assemble two large soil metagenomes totaling 398 billion bp (equivalent to 88,000 Escherichia coli genomes) from matched Iowa corn and native prairie soils. The resulting assembled contigs could be used to identify molecular interactions and reaction networks of known metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes Orthology database. Nonetheless, more than 60% of predicted proteins in assemblies could not be annotated against known databases. Many of these unknown proteins were abundant in both corn and prairie soils, highlighting the benefits of assembly for the discovery and characterization of novelty in soil biodiversity. Moreover, 80% of the sequencing data could not be assembled because of low coverage, suggesting that considerably more sequencing data are needed to characterize the functional content of soil.

Microbial Community Analysis with Ribosomal Gene Fragments from Shotgun Metagenomes.

Shotgun metagenomic sequencing does not depend on gene-targeted primers or PCR amplification; thus, it is not affected by primer bias or chimeras. However, searching rRNA genes from large shotgun Illumina data sets is computationally expensive, and no approach exists for unsupervised community analysis of small-subunit (SSU) rRNA gene fragments retrieved from shotgun data. We present a pipeline, SSUsearch, to achieve the faster identification of short-subunit rRNA gene fragments and enabled unsupervised community analysis with shotgun data. It also includes classification and copy number correction, and the output can be used by traditional amplicon analysis platforms. Shotgun metagenome data using this pipeline yielded higher diversity estimates than amplicon data but retained the grouping of samples in ordination analyses. We applied this pipeline to soil samples with paired shotgun and amplicon data and confirmed bias against Verrucomicrobia in a commonly used V6-V8 primer set, as well as discovering likely bias against Actinobacteria and for Verrucomicrobia in a commonly used V4 primer set. This pipeline can utilize all variable regions in SSU rRNA and also can be applied to large-subunit (LSU) rRNA genes for confirmation of community structure. The pipeline can scale to handle large amounts of soil metagenomic data (5 Gb memory and 5 central processing unit hours to process 38 Gb [1 lane] of trimmed Illumina HiSeq2500 data) and is freely available at https://github.com/dib-lab/SSUsearch under a BSD license.

Ribosomal Database Project: data and tools for high throughput rRNA analysis.

Ribosomal Database Project (RDP; http://rdp.cme.msu.edu/) provides the research community with aligned and annotated rRNA gene sequence data, along with tools to allow researchers to analyze their own rRNA gene sequences in the RDP framework. RDP data and tools are utilized in fields as diverse as human health, microbial ecology, environmental microbiology, nucleic acid chemistry, taxonomy and phylogenetics. In addition to aligned and annotated collections of bacterial and archaeal small subunit rRNA genes, RDP now includes a collection of fungal large subunit rRNA genes. RDP tools, including Classifier and Aligner, have been updated to work with this new fungal collection. The use of high-throughput sequencing to characterize environmental microbial populations has exploded in the past several years, and as sequence technologies have improved, the sizes of environmental datasets have increased. With release 11, RDP is providing an expanded set of tools to facilitate analysis of high-throughput data, including both single-stranded and paired-end reads. In addition, most tools are now available as open source packages for download and local use by researchers with high-volume needs or who would like to develop custom analysis pipelines.

Hsp90 and hepatobiliary transformation during sea lamprey metamorphosis.

BACKGROUND: Biliary atresia (BA) is a human infant disease with inflammatory fibrous obstructions in the bile ducts and is the most common cause for pediatric liver transplantation. In contrast, the sea lamprey undergoes developmental BA with transient cholestasis and fibrosis during metamorphosis, but emerges as a fecund adult. Therefore, sea lamprey liver metamorphosis may serve as an etiological model for human BA and provide pivotal information for hepatobiliary transformation and possible therapeutics. RESULTS: We hypothesized that liver metamorphosis in sea lamprey is due to transcriptional reprogramming that dictates cellular remodeling during metamorphosis. We determined global gene expressions in liver at several metamorphic landmark stages by integrating mRNA-Seq and gene ontology analyses, and validated the results with real-time quantitative PCR, histological and immunohistochemical staining. These analyses revealed that gene expressions of protein folding chaperones, membrane transporters and extracellular matrices were altered and shifted during liver metamorphosis. HSP90, important in protein folding and invertebrate metamorphosis, was identified as a candidate key factor during liver metamorphosis in sea lamprey. Blocking HSP90 with geldanamycin facilitated liver metamorphosis and decreased the gene expressions of the rate limiting enzyme for cholesterol biosynthesis, HMGCoA reductase (hmgcr), and bile acid biosynthesis, cyp7a1. Injection of hsp90 siRNA for 4 days altered gene expressions of met, hmgcr, cyp27a1, and slc10a1. Bile acid concentrations were increased while bile duct and gall bladder degeneration was facilitated and synchronized after hsp90 siRNA injection. CONCLUSIONS: HSP90 appears to play crucial roles in hepatobiliary transformation during sea lamprey metamorphosis. Sea lamprey is a useful animal model to study postembryonic development and mechanisms for hsp90-induced hepatobiliary transformation.

Scaling metagenome sequence assembly with probabilistic de Bruijn graphs.

Deep sequencing has enabled the investigation of a wide range of environmental microbial ecosystems, but the high memory requirements for de novo assembly of short-read shotgun sequencing data from these complex populations are an increasingly large practical barrier. Here we introduce a memory-efficient graph representation with which we can analyze the k-mer connectivity of metagenomic samples. The graph representation is based on a probabilistic data structure, a Bloom filter, that allows us to efficiently store assembly graphs in as little as 4 bits per k-mer, albeit inexactly. We show that this data structure accurately represents DNA assembly graphs in low memory. We apply this data structure to the problem of partitioning assembly graphs into components as a prelude to assembly, and show that this reduces the overall memory requirements for de novo assembly of metagenomes. On one soil metagenome assembly, this approach achieves a nearly 40-fold decrease in the maximum memory requirements for assembly. This probabilistic graph representation is a significant theoretical advance in storing assembly graphs and also yields immediate leverage on metagenomic assembly.

Integrated analyses of genome-wide DNA occupancy and expression profiling identify key genes and pathways involved in cellular transformation by a Marek's disease virus oncoprotein, Meq.

Marek's disease (MD) is an economically significant disease in chickens that is caused by the highly oncogenic Marek's disease virus (MDV). A major unanswered question is the mechanism of MDV-induced tumor formation. Meq, a bZIP transcription factor discovered in the 1990s, is critically involved in viral oncogenicity, but only a few of its host target genes have been described, impeding our understanding of MDV-induced tumorigenesis. Using chromatin immunoprecipitation-sequencing (ChIP-seq) and microarray analysis, a high-confidence list of Meq binding sites in the chicken genome and a global transcriptome of Meq-responsive genes were generated. Meq binding sites were found to be enriched in the promoter regions of upregulated genes but not in those of downregulated genes. ChIP-seq was also performed for c-Jun, a known heterodimeric partner of Meq. The close location of binding sites of Meq and c-Jun was noted, suggesting cooperativity between these two factors in modulating transcription. Pathway analysis indicated that Meq transcriptionally regulates many genes that are part of several signaling pathways including the extracellular signal-regulated kinase /mitogen-activated protein kinase (ERK/MAPK), Jak-STAT, and ErbB pathways, which are critical for oncogenesis and/or include signaling mediators involved in apoptosis. Meq activates oncogenic signaling cascades by transcriptionally activating major kinases in the ERK/MAPK pathway and simultaneously repressing phosphatases, as verified using inhibitors of MEK and ERK1/2 in a cell proliferation assay. This study provides significant insights into the mechanistic basis of Meq-dependent cell transformation.

Biogeographic distribution of five Antarctic cyanobacteria using large-scale k-mer searching with sourmash branchwater.

Cyanobacteria form diverse communities and are important primary producers in Antarctic freshwater environments, but their geographic distribution patterns in Antarctica and globally are still unresolved. There are however few genomes of cultured cyanobacteria from Antarctica available and therefore metagenome-assembled genomes (MAGs) from Antarctic cyanobacteria microbial mats provide an opportunity to explore distribution of uncultured taxa. These MAGs also allow comparison with metagenomes of cyanobacteria enriched communities from a range of habitats, geographic locations, and climates. However, most MAGs do not contain 16S rRNA gene sequences, making a 16S rRNA gene-based biogeography comparison difficult. An alternative technique is to use large-scale k-mer searching to find genomes of interest in public metagenomes. This paper presents the results of k-mer based searches for 5 Antarctic cyanobacteria MAGs from Lake Fryxell and Lake Vanda, assigned the names Phormidium pseudopriestleyi FRX01, Microcoleus sp. MP8IB2.171, Leptolyngbya sp. BulkMat.35, Pseudanabaenaceae cyanobacterium MP8IB2.15, and Leptolyngbyaceae cyanobacterium MP9P1.79 in 498,942 unassembled metagenomes from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). The Microcoleus sp. MP8IB2.171 MAG was found in a wide variety of environments, the P. pseudopriestleyi MAG was found in environments with challenging conditions, the Leptolyngbyaceae cyanobacterium MP9P1.79 MAG was only found in Antarctica, and the Leptolyngbya sp. BulkMat.35 and Pseudanabaenaceae cyanobacterium MP8IB2.15 MAGs were found in Antarctic and other cold environments. The findings based on metagenome matches and global comparisons suggest that these Antarctic cyanobacteria have distinct distribution patterns ranging from locally restricted to global distribution across the cold biosphere and other climatic zones.