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.

DNA adenine methylase, not the PstI restriction-modification system, regulates virulence gene expression in Shiga toxin-producing Escherichia coli.

We previously reported a distinct methylome between the two Shiga toxin-producing Escherichia coli (STEC) O145:H28 strains linked to the 2010 U.S. lettuce-associated outbreak (RM13514) and the 2007 Belgium ice cream-associated outbreak (RM13516), respectively. This difference was thought to be attributed to a prophage encoded type II restriction-modification system (PstI R-M) in RM13514. Here, we characterized this PstI R-M system in comparison to DNA adenine methylase (Dam), a highly conserved enzyme in γ proteobacteria, by functional genomics. Deficiency in Dam led to a differential expression of over 1000 genes in RM13514, whereas deficiency in PstI R-M only impacted a few genes transcriptionally. Dam regulated genes involved in diverse functions, whereas PstI R-M regulated genes mostly encoding transporters and adhesins. Dam regulated a large number of genes located on prophages, pathogenicity islands, and plasmids, including Shiga toxin genes, type III secretion system (TTSS) genes, and enterohemolysin genes. Production of Stx2 in dam mutant was significantly higher than in RM13514, supporting a role of Dam in maintaining lysogeny of Stx2-prophage. However, following mitomycin C treatment, Stx2 in RM13514 was significantly higher than that of dam or PstI R-M deletion mutant, implying that both Dam and PstI R-M contributed to maximum Stx2 production.

Precision Medicine and Precision Public Health in the Era of Pathogen Next-Generation Sequencing.

This brief report serves as an introduction to a supplement of the Journal of Infectious Diseases entitled "Next-Generation Sequencing (NGS) Technologies to Advance Global Infectious Disease Research." We briefly discuss the history of NGS technologies and describe how the techniques developed during the past 40 years have impacted our understanding of infectious diseases. Our focus is on the application of NGS in the context of pathogen genomics. Beyond obvious clinical and public health applications, we also discuss the challenges that still remain within this rapidly evolving field.

Active Targeted Surveillance to Identify Sites of Emergence of Hantavirus.

BACKGROUND: Endemic outbreaks of hantaviruses pose a critical public health threat worldwide. Hantaan orthohantavirus (HTNV) causes hemorrhagic fever with renal syndrome (HFRS) in humans. Using comparative genomic analyses of partial and nearly complete sequences of HTNV from humans and rodents, we were able to localize, with limitations, the putative infection locations for HFRS patients. Partial sequences might not reflect precise phylogenetic positions over the whole-genome sequences; finer granularity of rodent sampling reflects more precisely the circulation of strains. METHODS: Five HFRS specimens were collected. Epidemiological surveys were conducted with the patients during hospitalization. We conducted active surveillance at suspected HFRS outbreak areas. We performed multiplex polymerase chain reaction-based next-generation sequencing to obtain the genomic sequence of HTNV from patients and rodents. The phylogeny of human- and rodent-derived HTNV was generated using the maximum likelihood method. For phylogeographic analyses, the tracing of HTNV genomes from HFRS patients was defined on the bases of epidemiological interviews, phylogenetic patterns of the viruses, and geographic locations of HTNV-positive rodents. RESULTS: The phylogeographic analyses demonstrated genetic clusters of HTNV strains from clinical specimens, with HTNV circulating in rodents at suspected sites of patient infections. CONCLUSIONS: This study demonstrates a major shift in molecular epidemiological surveillance of HTNV. Active targeted surveillance was performed at sites of suspected infections, allowing the high-resolution phylogeographic analysis to reveal the site of emergence of HTNV. We posit that this novel approach will make it possible to identify infectious sources, perform disease risk assessment, and implement preparedness against vector-borne viruses.

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.

Oxalic acid, a molecule at the crossroads of bacterial-fungal interactions.

Oxalic acid is the most ubiquitous and common low molecular weight organic acid produced by living organisms. Oxalic acid is produced by fungi, bacteria, plants, and animals. The aim of this review is to give an overview of current knowledge about the microbial cycling of oxalic acid through ecosystems. Here we review the production and degradation of oxalic acid, as well as its implications in the metabolism for fungi, bacteria, plants, and animals. Indeed, fungi are well known producers of oxalic acid, while bacteria are considered oxalic acid consumers. However, this framework may need to be modified, because the ability of fungi to degrade oxalic acid and the ability of bacteria to produce it, have been poorly investigated. Finally, we will highlight the role of fungi and bacteria in oxalic acid cycling in soil, plant and animal ecosystems.

Bacterial spores, from ecology to biotechnology.

The production of a highly specialized cell structure called a spore is a remarkable example of a survival strategy displayed by bacteria in response to challenging environmental conditions. The detailed analysis and description of the process of sporulation in selected model organisms have generated a solid background to understand the cellular processes leading to the formation of this specialized cell. However, much less is known regarding the ecology of spore-formers. This research gap needs to be filled as the feature of resistance has important implications not only on the survival of spore-formers and their ecology, but also on the use of spores for environmental prospection and biotechnological applications.

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.

Rheinheimera salexigens sp. nov., isolated from a fishing hook, and emended description of the genus Rheinheimera.

A Gram-negative, rod-shaped bacterium, designated KH87T, was isolated from a fishing hook that had been baited and suspended in seawater off O'ahu, Hawai'i. Based on a comparison of 1524 nt of the 16S rRNA gene sequence of strain KH87T, its nearest neighbours were the GammaproteobacteriaRheinheimera nanhaiensis E407-8T (96.2 % identity), Rheinheimera chironomi K19414T (96.0 %), Rheinheimera pacifica KMM 1406T (95.8 %), Rheinheimera muenzenbergensis E49T (95.7 %), Alishewanella solinquinati KMK6T (94.9 %) and Arsukibacterium ikkense GCM72T (94.6 %). Cells of KH87T were motile by a single polar flagellum, strictly aerobic, and catalase- and oxidase-positive. Growth occurred between 4 and 39 °C, and in a circumneutral pH range. Major fatty acids in whole cells of strain KH87T were cis-9-hexadecenoic acid, hexadecanoic acid and cis-11-octadecenoic acid. The quinone system contained mostly menaquinone MK-7, and a minor amount of ubiquinone Q-8. The polar lipid profile contained the major lipids phosphatidylglycerol, phosphatidylserine, phosphatidylethanolamine, an unidentified aminolipid, and a lipid not containing phosphate, an amino group or a sugar moiety. Putrescine was the major polyamine. Physiological, biochemical and genomic data, including obligate halophily, absence of amylolytic activity, a quinone system dominated by MK-7 and DNA G+C content (42.0 mol%) distinguished KH87T from extant Rheinheimera species; strain KH87T was also distinguished by a multi-locus sequence analysis of aligned and concatenated 16S rRNA, gyrB, rpoB and rpoD gene sequences. Based on phenotypic and genotypic differences, the species Rheinheimera salexigens sp. nov. is proposed to accommodate KH87T as the type strain (=ATCC BAA-2715T=CIP 111115T). An emended description of the genus Rheinheimera is also proposed.

Genomic encyclopedia of bacteria and archaea: sequencing a myriad of type strains.

Microbes hold the key to life. They hold the secrets to our past (as the descendants of the earliest forms of life) and the prospects for our future (as we mine their genes for solutions to some of the planet's most pressing problems, from global warming to antibiotic resistance). However, the piecemeal approach that has defined efforts to study microbial genetic diversity for over 20 years and in over 30,000 genome projects risks squandering that promise. These efforts have covered less than 20% of the diversity of the cultured archaeal and bacterial species, which represent just 15% of the overall known prokaryotic diversity. Here we call for the funding of a systematic effort to produce a comprehensive genomic catalog of all cultured Bacteria and Archaea by sequencing, where available, the type strain of each species with a validly published name (currently∼11,000). This effort will provide an unprecedented level of coverage of our planet's genetic diversity, allow for the large-scale discovery of novel genes and functions, and lead to an improved understanding of microbial evolution and function in the environment.

Accurate read-based metagenome characterization using a hierarchical suite of unique signatures.

A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools.

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.

Polynucleobacter necessarius, a model for genome reduction in both free-living and symbiotic bacteria.

We present the complete genomic sequence of the essential symbiont Polynucleobacter necessarius (Betaproteobacteria), which is a valuable case study for several reasons. First, it is hosted by a ciliated protist, Euplotes; bacterial symbionts of ciliates are still poorly known because of a lack of extensive molecular data. Second, the single species P. necessarius contains both symbiotic and free-living strains, allowing for a comparison between closely related organisms with different ecologies. Third, free-living P. necessarius strains are exceptional by themselves because of their small genome size, reduced metabolic flexibility, and high worldwide abundance in freshwater systems. We provide a comparative analysis of P. necessarius metabolism and explore the peculiar features of a genome reduction that occurred on an already streamlined genome. We compare this unusual system with current hypotheses for genome erosion in symbionts and free-living bacteria, propose modifications to the presently accepted model, and discuss the potential consequences of translesion DNA polymerase loss.

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.

Combining compositional data sets introduces error in covariance network reconstruction.

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and inter-kingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

A Practical Approach to Using the Genomic Standards Consortium MIxS Reporting Standard for Comparative Genomics and Metagenomics.

Comparative analysis of (meta)genomes necessitates aggregation, integration, and synthesis of well-annotated data using standards. The Genomic Standards Consortium (GSC) collaborates with the research community to develop and maintain the Minimum Information about any (x) Sequence (MIxS) reporting standard for genomic data. To facilitate the use of the GSC's MIxS reporting standard, we provide a description of the structure and terminology, how to navigate ontologies for required terms in MIxS, and demonstrate practical usage through a soil metagenome example.

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.

Microbial community adaptation to quaternary ammonium biocides as revealed by metagenomics.

Quaternary ammonium compounds (QACs) represent widely used cationic biocides that persist in natural environments. Although microbial degradation, sensitivity and resistance to QACs have been extensively documented, a quantitative understanding of how whole communities adapt to QAC exposure remain elusive. To gain insights into these issues, we exposed a microbial community from a contaminated river sediment to varied levels of benzalkonium chlorides (BACs, a family of QACs) for 3 years. Comparative metagenomic analysis showed that the BAC-fed communities were dramatically decreased in phylogenetic diversity compared with the control (no BAC exposure), resulting presumably from BAC toxicity, and dominated by Pseudomonas species (> 50% of the total). Time-course metagenomics revealed that community adaptation occurred primarily via selective enrichment of BAC-degrading Pseudomonas populations, particularly P. nitroreducens, and secondarily via amino acid substitutions and horizontal transfer of a few selected genes in the Pseudomonas populations, including a gene encoding a PAS/PAC sensor protein and ring-hydroxylating dioxygenase genes. P. nitroreducens isolates were reproducibly recoverable from communities after prolonged periods of no-BAC exposure, suggesting that they are robust BAC-degraders. Our study provides new insights into the mechanisms and tempo of microbial community adaptation to QAC exposure and has implications for treating QACs in biological engineered systems.