EDGE COVID-19: a web platform to generate submission-ready genomes from SARS-CoV-2 sequencing efforts.

SUMMARY: Genomics has become an essential technology for surveilling emerging infectious disease outbreaks. A range of technologies and strategies for pathogen genome enrichment and sequencing are being used by laboratories worldwide, together with different and sometimes ad hoc, analytical procedures for generating genome sequences. A fully integrated analytical process for raw sequence to consensus genome determination, suited to outbreaks such as the ongoing COVID-19 pandemic, is critical to provide a solid genomic basis for epidemiological analyses and well-informed decision making. We have developed a web-based platform and integrated bioinformatic workflows that help to provide consistent high-quality analysis of SARS-CoV-2 sequencing data generated with either the Illumina or Oxford Nanopore Technologies (ONT). Using an intuitive web-based interface, this workflow automates data quality control, SARS-CoV-2 reference-based genome variant and consensus calling, lineage determination and provides the ability to submit the consensus sequence and necessary metadata to GenBank, GISAID and INSDC raw data repositories. We tested workflow usability using real world data and validated the accuracy of variant and lineage analysis using several test datasets, and further performed detailed comparisons with results from the COVID-19 Galaxy Project workflow. Our analyses indicate that EC-19 workflows generate high-quality SARS-CoV-2 genomes. Finally, we share a perspective on patterns and impact observed with Illumina versus ONT technologies on workflow congruence and differences. AVAILABILITY AND IMPLEMENTATION: https://edge-covid19.edgebioinformatics.org, and https://github.com/LANL-Bioinformatics/EDGE/tree/SARS-CoV2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A public website for the automated assessment and validation of SARS-CoV-2 diagnostic PCR assays.

SUMMARY: Polymerase chain reaction-based assays are the current gold standard for detecting and diagnosing SARS-CoV-2. However, as SARS-CoV-2 mutates, we need to constantly assess whether existing PCR-based assays will continue to detect all known viral strains. To enable the continuous monitoring of SARS-CoV-2 assays, we have developed a web-based assay validation algorithm that checks existing PCR-based assays against the ever-expanding genome databases for SARS-CoV-2 using both thermodynamic and edit-distance metrics. The assay-screening results are displayed as a heatmap, showing the number of mismatches between each detection and each SARS-CoV-2 genome sequence. Using a mismatch threshold to define detection failure, assay performance is summarized with the true-positive rate (recall) to simplify assay comparisons. AVAILABILITY AND IMPLEMENTATION: The assay evaluation website and supporting software are Open Source and freely available at https://covid19.edgebioinformatics.org/#/assayValidation, https://github.com/jgans/thermonucleotide BLAST and https://github.com/LANL-Bioinformatics/assay_validation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Uncovering the Core Microbiome and Distribution of Palmerolide in Synoicum adareanum Across the Anvers Island Archipelago, Antarctica.

Polar marine ecosystems hold the potential for bioactive compound biodiscovery, based on their untapped macro- and microorganism diversity. Characterization of polar benthic marine invertebrate-associated microbiomes is limited to few studies. This study was motivated by our interest in better understanding the microbiome structure and composition of the ascidian, Synoicum adareanum, in which palmerolide A (PalA), a bioactive macrolide with specificity against melanoma, was isolated. PalA bears structural resemblance to a hybrid nonribosomal peptide-polyketide that has similarities to microbially-produced macrolides. We conducted a spatial survey to assess both PalA levels and microbiome composition in S. adareanum in a region of the Antarctic Peninsula near Anvers Island (64° 46'S, 64° 03'W). PalA was ubiquitous and abundant across a collection of 21 ascidians (3 subsamples each) sampled from seven sites across the Anvers Island Archipelago. The microbiome composition (V3-V4 16S rRNA gene sequence variants) of these 63 samples revealed a core suite of 21 bacterial amplicon sequence variants (ASVs)-20 of which were distinct from regional bacterioplankton. ASV co-occurrence analysis across all 63 samples yielded subgroups of taxa that may be interacting biologically (interacting subsystems) and, although the levels of PalA detected were not found to correlate with specific sequence variants, the core members appeared to occur in a preferred optimum and tolerance range of PalA levels. These results, together with an analysis of the biosynthetic potential of related microbiome taxa, describe a conserved, high-latitude core microbiome with unique composition and substantial promise for natural product biosynthesis that likely influences the ecology of the holobiont.

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform.

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the ease of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. This bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research.

"Candidatus Nitrosotenuis aquarius," an Ammonia-Oxidizing Archaeon from a Freshwater Aquarium Biofilter.

Ammonia is a metabolic waste product excreted by aquatic organisms that causes toxicity when it accumulates. Aquaria and aquaculture systems therefore use biological filters that promote the growth of nitrifiers to convert ammonia to nitrate. Ammonia-oxidizing bacteria (AOB) have been isolated from aquarium biofilters and are available as commercial supplements, but recent evidence suggests that ammonia-oxidizing archaea (AOA) are abundant in aquarium biofilters. In this study, we report the cultivation and closed genome sequence of the novel AOA representative "Candidatus Nitrosotenuis aquarius," which was enriched from a freshwater aquarium biofilter. "Ca Nitrosotenuis aquarius" oxidizes ammonia stoichiometrically to nitrite with a concomitant increase in thaumarchaeotal cells and a generation time of 34.9 h. "Ca Nitrosotenuis aquarius" has an optimal growth temperature of 33°C, tolerates up to 3 mM NH4Cl, and grows optimally at 0.05% salinity. Transmission electron microscopy revealed that "Ca Nitrosotenuis aquarius" cells are rod shaped, with a diameter of ∼0.4 µm and length ranging from 0.6 to 3.6 µm. In addition, these cells possess surface layers (S-layers) and multiple proteinaceous appendages. Phylogenetically, "Ca Nitrosotenuis aquarius" belongs to the group I.1a Thaumarchaeota, clustering with environmental sequences from freshwater aquarium biofilters, aquaculture systems, and wastewater treatment plants. The complete 1.70-Mbp genome contains genes involved in ammonia oxidation, bicarbonate assimilation, flagellum synthesis, chemotaxis, S-layer production, defense, and protein glycosylation. Incubations with differential inhibitors indicate that "Ca Nitrosotenuis aquarius"-like AOA contribute to ammonia oxidation within the aquarium biofilter from which it originated.IMPORTANCE Nitrification is a critical process for preventing ammonia toxicity in engineered biofilter environments. This work describes the cultivation and complete genome sequence of a novel AOA representative enriched from a freshwater aquarium biofilter. In addition, despite the common belief in the aquarium industry that AOB mediate ammonia oxidation, the present study suggests an in situ role for "Ca Nitrosotenuis aquarius"-like AOA in freshwater aquarium biofilters.

ADEPT, a dynamic next generation sequencing data error-detection program with trimming.

BACKGROUND: Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. RESULTS: In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the true positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. CONCLUSIONS: ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.

Nearly finished genomes produced using gel microdroplet culturing reveal substantial intraspecies genomic diversity within the human microbiome.

The majority of microbial genomic diversity remains unexplored. This is largely due to our inability to culture most microorganisms in isolation, which is a prerequisite for traditional genome sequencing. Single-cell sequencing has allowed researchers to circumvent this limitation. DNA is amplified directly from a single cell using the whole-genome amplification technique of multiple displacement amplification (MDA). However, MDA from a single chromosome copy suffers from amplification bias and a large loss of specificity from even very small amounts of DNA contamination, which makes assembling a genome difficult and completely finishing a genome impossible except in extraordinary circumstances. Gel microdrop cultivation allows culturing of a diverse microbial community and provides hundreds to thousands of genetically identical cells as input for an MDA reaction. We demonstrate the utility of this approach by comparing sequencing results of gel microdroplets and single cells following MDA. Bias is reduced in the MDA reaction and genome sequencing, and assembly is greatly improved when using gel microdroplets. We acquired multiple near-complete genomes for two bacterial species from human oral and stool microbiome samples. A significant amount of genome diversity, including single nucleotide polymorphisms and genome recombination, is discovered. Gel microdroplets offer a powerful and high-throughput technology for assembling whole genomes from complex samples and for probing the pan-genome of naturally occurring populations.

Adaptation genomics of a small-colony variant in a Pseudomonas chlororaphis 30-84 biofilm.

The rhizosphere-colonizing bacterium Pseudomonas chlororaphis 30-84 is an effective biological control agent against take-all disease of wheat. In this study, we characterize a small-colony variant (SCV) isolated from a P. chlororaphis 30-84 biofilm. The SCV exhibited pleiotropic phenotypes, including small cell size, slow growth and motility, low levels of phenazine production, and increased biofilm formation and resistance to antimicrobials. To better understand the genetic alterations underlying these phenotypes, RNA and whole-genome sequencing analyses were conducted comparing an SCV to the wild-type strain. Of the genome's 5,971 genes, transcriptomic profiling indicated that 1,098 (18.4%) have undergone substantial reprograming of gene expression in the SCV. Whole-genome sequence analysis revealed multiple alterations in the SCV, including mutations in yfiR (cyclic-di-GMP production), fusA (elongation factor), and cyoE (heme synthesis) and a 70-kb deletion. Genetic analysis revealed that the yfiR locus plays a major role in controlling SCV phenotypes, including colony size, growth, motility, and biofilm formation. Moreover, a point mutation in the fusA gene contributed to kanamycin resistance. Interestingly, the SCV can partially switch back to wild-type morphologies under specific conditions. Our data also support the idea that phenotypic switching in P. chlororaphis is not due to simple genetic reversions but may involve multiple secondary mutations. The emergence of these highly adherent and antibiotic-resistant SCVs within the biofilm might play key roles in P. chlororaphis natural persistence.

A programmable droplet-based microfluidic device applied to multiparameter analysis of single microbes and microbial communities.

We present a programmable droplet-based microfluidic device that combines the reconfigurable flow-routing capabilities of integrated microvalve technology with the sample compartmentalization and dispersion-free transport that is inherent to droplets. The device allows for the execution of user-defined multistep reaction protocols in 95 individually addressable nanoliter-volume storage chambers by consecutively merging programmable sequences of picoliter-volume droplets containing reagents or cells. This functionality is enabled by "flow-controlled wetting," a droplet docking and merging mechanism that exploits the physics of droplet flow through a channel to control the precise location of droplet wetting. The device also allows for automated cross-contamination-free recovery of reaction products from individual chambers into standard microfuge tubes for downstream analysis. The combined features of programmability, addressability, and selective recovery provide a general hardware platform that can be reprogrammed for multiple applications. We demonstrate this versatility by implementing multiple single-cell experiment types with this device: bacterial cell sorting and cultivation, taxonomic gene identification, and high-throughput single-cell whole genome amplification and sequencing using common laboratory strains. Finally, we apply the device to genome analysis of single cells and microbial consortia from diverse environmental samples including a marine enrichment culture, deep-sea sediments, and the human oral cavity. The resulting datasets capture genotypic properties of individual cells and illuminate known and potentially unique partnerships between microbial community members.

Rapid evaluation and quality control of next generation sequencing data with FaQCs.

BACKGROUND: Next generation sequencing (NGS) technologies that parallelize the sequencing process and produce thousands to millions, or even hundreds of millions of sequences in a single sequencing run, have revolutionized genomic and genetic research. Because of the vagaries of any platform's sequencing chemistry, the experimental processing, machine failure, and so on, the quality of sequencing reads is never perfect, and often declines as the read is extended. These errors invariably affect downstream analysis/application and should therefore be identified early on to mitigate any unforeseen effects. RESULTS: Here we present a novel FastQ Quality Control Software (FaQCs) that can rapidly process large volumes of data, and which improves upon previous solutions to monitor the quality and remove poor quality data from sequencing runs. Both the speed of processing and the memory footprint of storing all required information have been optimized via algorithmic and parallel processing solutions. The trimmed output compared side-by-side with the original data is part of the automated PDF output. We show how this tool can help data analysis by providing a few examples, including an increased percentage of reads recruited to references, improved single nucleotide polymorphism identification as well as de novo sequence assembly metrics. CONCLUSION: FaQCs combines several features of currently available applications into a single, user-friendly process, and includes additional unique capabilities such as filtering the PhiX control sequences, conversion of FASTQ formats, and multi-threading. The original data and trimmed summaries are reported within a variety of graphics and reports, providing a simple way to do data quality control and assurance.

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows.

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

Genomic and Phenotypic Characterization of Shiga Toxin-Producing Escherichia albertii Strains Isolated from Wild Birds in a Major Agricultural Region in California.

Escherichia albertii is an emerging foodborne pathogen. To better understand the pathogenesis and health risk of this pathogen, comparative genomics and phenotypic characterization were applied to assess the pathogenicity potential of E. albertii strains isolated from wild birds in a major agricultural region in California. Shiga toxin genes stx2f were present in all avian strains. Pangenome analyses of 20 complete genomes revealed a total of 11,249 genes, of which nearly 80% were accessory genes. Both core gene-based phylogenetic and accessory gene-based relatedness analyses consistently grouped the three stx2f-positive clinical strains with the five avian strains carrying ST7971. Among the three Stx2f-converting prophage integration sites identified, ssrA was the most common one. Besides the locus of enterocyte effacement and type three secretion system, the high pathogenicity island, OI-122, and type six secretion systems were identified. Substantial strain variation in virulence gene repertoire, Shiga toxin production, and cytotoxicity were revealed. Six avian strains exhibited significantly higher cytotoxicity than that of stx2f-positive E. coli, and three of them exhibited a comparable level of cytotoxicity with that of enterohemorrhagic E. coli outbreak strains, suggesting that wild birds could serve as a reservoir of E. albertii strains with great potential to cause severe diseases in humans.

Bridging Place-Based Astrobiology Education with Genomics, Including Descriptions of Three Novel Bacterial Species Isolated from Mars Analog Sites of Cultural Relevance.

Democratizing genomic data science, including bioinformatics, can diversify the STEM workforce and may, in turn, bring new perspectives into the space sciences. In this respect, the development of education and research programs that bridge genome science with "place" and world-views specific to a given region are valuable for Indigenous students and educators. Through a multi-institutional collaboration, we developed an ongoing education program and model that includes Illumina and Oxford Nanopore sequencing, free bioinformatic platforms, and teacher training workshops to address our research and education goals through a place-based science education lens. High school students and researchers cultivated, sequenced, assembled, and annotated the genomes of 13 bacteria from Mars analog sites with cultural relevance, 10 of which were novel species. Students, teachers, and community members assisted with the discovery of new, potentially chemolithotrophic bacteria relevant to astrobiology. This joint education-research program also led to the discovery of species from Mars analog sites capable of producing N-acyl homoserine lactones, which are quorum-sensing molecules used in bacterial communication. Whole genome sequencing was completed in high school classrooms, and connected students to funded space research, increased research output, and provided culturally relevant, place-based science education, with participants naming three novel species described here. Students at St. Andrew's School (Honolulu, Hawai'i) proposed the name Bradyrhizobium prioritasuperba for the type strain, BL16AT, of the new species (DSM 112479T = NCTC 14602T). The nonprofit organization Kauluakalana proposed the name Brenneria ulupoensis for the type strain, K61T, of the new species (DSM 116657T = LMG = 33184T), and Hawai'i Baptist Academy students proposed the name Paraflavitalea speifideiaquila for the type strain, BL16ET, of the new species (DSM 112478T = NCTC 14603T).

Comparative Genomics Applied to Systematically Assess Pathogenicity Potential in Shiga Toxin-Producing Escherichia coli O145:H28.

Shiga toxin-producing Escherichia coli (STEC) O145:H28 can cause severe disease in humans and is a predominant serotype in STEC O145 environmental isolates. Here, comparative genomics was applied to a set of clinical and environmental strains to systematically evaluate the pathogenicity potential in environmental strains. While the core genes-based tree separated all O145:H28 strains from the non O145:H28 reference strains, it failed to segregate environmental strains from the clinical. In contrast, the accessory genes-based tree placed all clinical strains in the same clade regardless of their genotypes or serotypes, apart from the environmental strains. Loss-of-function mutations were common in the virulence genes examined, with a high frequency in genes related to adherence, autotransporters, and the type three secretion system. Distinct differences in pathogenicity islands LEE, OI-122, and OI-57, the acid fitness island, and the tellurite resistance island were detected between the O145:H28 and reference strains. A great amount of genetic variation was detected in O145:H28, which was mainly attributed to deletions, insertions, and gene acquisition at several chromosomal "hot spots". Our study demonstrated a distinct virulence gene repertoire among the STEC O145:H28 strains originating from the same geographical region and revealed unforeseen contributions of loss-of-function mutations to virulence evolution and genetic diversification in STEC.

Precise Genomic Riboregulator Control of Metabolic Flux in Microbial Systems.

Engineered microbes can be used for producing value-added chemicals from renewable feedstocks, relieving the dependency on nonrenewable resources such as petroleum. These microbes often are composed of synthetic metabolic pathways; however, one major problem in establishing a synthetic pathway is the challenge of precisely controlling competing metabolic routes, some of which could be crucial for fitness and survival. While traditional gene deletion and/or coarse overexpression approaches do not provide precise regulation, cis-repressors (CRs) are RNA-based regulatory elements that can control the production levels of a particular protein in a tunable manner. Here, we describe a protocol for a generally applicable fluorescence-activated cell sorting technique used to isolate eight subpopulations of CRs from a semidegenerate library in Escherichia coli, followed by deep sequencing that permitted the identification of 15 individual CRs with a broad range of protein production profiles. Using these new CRs, we demonstrated a change in production levels of a fluorescent reporter by over two orders of magnitude and further showed that these CRs are easily ported from E. coli to Pseudomonas putida. We next used four CRs to tune the production of the enzyme PpsA, involved in pyruvate to phosphoenolpyruvate (PEP) conversion, to alter the pool of PEP that feeds into the shikimate pathway. In an engineered P. putida strain, where carbon flux in the shikimate pathway is diverted to the synthesis of the commodity chemical cis,cis-muconate, we found that tuning PpsA translation levels increased the overall titer of muconate. Therefore, CRs provide an approach to precisely tune protein levels in metabolic pathways and will be an important tool for other metabolic engineering efforts.

Towards increased accuracy and reproducibility in SARS-CoV-2 next generation sequence analysis for public health surveillance.

During the COVID-19 pandemic, SARS-CoV-2 surveillance efforts integrated genome sequencing of clinical samples to identify emergent viral variants and to support rapid experimental examination of genome-informed vaccine and therapeutic designs. Given the broad range of methods applied to generate new viral genomes, it is critical that consensus and variant calling tools yield consistent results across disparate pipelines. Here we examine the impact of sequencing technologies (Illumina and Oxford Nanopore) and 7 different downstream bioinformatic protocols on SARS-CoV-2 variant calling as part of the NIH Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Tracking Resistance and Coronavirus Evolution (TRACE) initiative, a public-private partnership established to address the COVID-19 outbreak. Our results indicate that bioinformatic workflows can yield consensus genomes with different single nucleotide polymorphisms, insertions, and/or deletions even when using the same raw sequence input datasets. We introduce the use of a specific suite of parameters and protocols that greatly improves the agreement among pipelines developed by diverse organizations. Such consistency among bioinformatic pipelines is fundamental to SARS-CoV-2 and future pathogen surveillance efforts. The application of analysis standards is necessary to more accurately document phylogenomic trends and support data-driven public health responses.

Benchmark datasets for SARS-CoV-2 surveillance bioinformatics.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. Methods: We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study. Results: The benchmark datasets focus on the two most widely used sequencing platforms: long read sequencing data from the Oxford Nanopore Technologies platform and short read sequencing data from the Illumina platform. There are six datasets: three were derived from recent publications; two were derived from data mining public databases to answer common questions not covered by published datasets; one unique dataset representing common sequence failures was obtained by rigorously scrutinizing data that did not pass quality checks. The dataset summary table, data mining script and quality control (QC) values for all sequence data are publicly available on GitHub: https://github.com/CDCgov/datasets-sars-cov-2. Discussion: The datasets presented here were generated to help public health laboratories build sequencing and bioinformatics capacity, benchmark different workflows and pipelines, and calibrate QC thresholds to ensure sequencing quality. Together, improvements in these areas support accurate and timely outbreak investigation and surveillance, providing actionable data for pandemic management. Furthermore, these publicly available and standardized benchmark data will facilitate the development and adjudication of new pipelines.

Discovery of an Antarctic Ascidian-Associated Uncultivated Verrucomicrobia with Antimelanoma Palmerolide Biosynthetic Potential.

The Antarctic marine ecosystem harbors a wealth of biological and chemical innovation that has risen in concert over millennia since the isolation of the continent and formation of the Antarctic circumpolar current. Scientific inquiry into the novelty of marine natural products produced by Antarctic benthic invertebrates led to the discovery of a bioactive macrolide, palmerolide A, that has specific activity against melanoma and holds considerable promise as an anticancer therapeutic. While this compound was isolated from the Antarctic ascidian Synoicum adareanum, its biosynthesis has since been hypothesized to be microbially mediated, given structural similarities to microbially produced hybrid nonribosomal peptide-polyketide macrolides. Here, we describe a metagenome-enabled investigation aimed at identifying the biosynthetic gene cluster (BGC) and palmerolide A-producing organism. A 74-kbp candidate BGC encoding the multimodular enzymatic machinery (hybrid type I-trans-AT polyketide synthase-nonribosomal peptide synthetase and tailoring functional domains) was identified and found to harbor key features predicted as necessary for palmerolide A biosynthesis. Surveys of ascidian microbiome samples targeting the candidate BGC revealed a high correlation between palmerolide gene targets and a single 16S rRNA gene variant (R = 0.83 to 0.99). Through repeated rounds of metagenome sequencing followed by binning contigs into metagenome-assembled genomes, we were able to retrieve a nearly complete genome (10 contigs) of the BGC-producing organism, a novel verrucomicrobium within the Opitutaceae family that we propose here as "Candidatus Synoicihabitans palmerolidicus." The refined genome assembly harbors five highly similar BGC copies, along with structural and functional features that shed light on the host-associated nature of this unique bacterium. IMPORTANCE Palmerolide A has potential as a chemotherapeutic agent to target melanoma. We interrogated the microbiome of the Antarctic ascidian, Synoicum adareanum, using a cultivation-independent high-throughput sequencing and bioinformatic strategy. The metagenome-encoded biosynthetic machinery predicted to produce palmerolide A was found to be associated with the genome of a member of the S. adareanum core microbiome. Phylogenomic analysis suggests the organism represents a new deeply branching genus, "Candidatus Synoicihabitans palmerolidicus," in the Opitutaceae family of the Verrucomicrobia phylum. The Ca. Synoicihabitans palmerolidicus 4.29-Mb genome encodes a repertoire of carbohydrate-utilizing and transport pathways, a chemotaxis system, flagellar biosynthetic capacity, and other regulatory elements enabling its ascidian-associated lifestyle. The palmerolide producer's genome also contains five distinct copies of the large palmerolide biosynthetic gene cluster that may provide structural complexity of palmerolide variants.

Bioinformatic and Mechanistic Analysis of the Palmerolide PKS-NRPS Biosynthetic Pathway From the Microbiome of an Antarctic Ascidian.

Complex interactions exist between microbiomes and their hosts. Increasingly, defensive metabolites that have been attributed to host biosynthetic capability are now being recognized as products of host-associated microbes. These unique metabolites often have bioactivity targets in human disease and can be purposed as pharmaceuticals. Polyketides are a complex family of natural products that often serve as defensive metabolites for competitive or pro-survival purposes for the producing organism, while demonstrating bioactivity in human diseases as cholesterol lowering agents, anti-infectives, and anti-tumor agents. Marine invertebrates and microbes are a rich source of polyketides. Palmerolide A, a polyketide isolated from the Antarctic ascidian Synoicum adareanum, is a vacuolar-ATPase inhibitor with potent bioactivity against melanoma cell lines. The biosynthetic gene clusters (BGCs) responsible for production of secondary metabolites are encoded in the genomes of the producers as discrete genomic elements. A candidate palmerolide BGC was identified from a S. adareanum microbiome-metagenome based on a high degree of congruence with a chemical structure-based retrobiosynthetic prediction. Protein family homology analysis, conserved domain searches, active site and motif identification were used to identify and propose the function of the ∼75 kbp trans-acyltransferase (AT) polyketide synthase-non-ribosomal synthase (PKS-NRPS) domains responsible for the stepwise synthesis of palmerolide A. Though PKS systems often act in a predictable co-linear sequence, this BGC includes multiple trans-acting enzymatic domains, a non-canonical condensation termination domain, a bacterial luciferase-like monooxygenase (LLM), and is found in multiple copies within the metagenome-assembled genome (MAG). Detailed inspection of the five highly similar pal BGC copies suggests the potential for biosynthesis of other members of the palmerolide chemical family. This is the first delineation of a biosynthetic gene cluster from an Antarctic microbial species, recently proposed as Candidatus Synoicihabitans palmerolidicus. These findings have relevance for fundamental knowledge of PKS combinatorial biosynthesis and could enhance drug development efforts of palmerolide A through heterologous gene expression.

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale.

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.