GSearch: ultra-fast and scalable genome search by combining K-mer hashing with hierarchical navigable small world graphs.

Genome search and/or classification typically involves finding the best-match database (reference) genomes and has become increasingly challenging due to the growing number of available database genomes and the fact that traditional methods do not scale well with large databases. By combining k-mer hashing-based probabilistic data structures (i.e. ProbMinHash, SuperMinHash, Densified MinHash and SetSketch) to estimate genomic distance, with a graph based nearest neighbor search algorithm (Hierarchical Navigable Small World Graphs, or HNSW), we created a new data structure and developed an associated computer program, GSearch, that is orders of magnitude faster than alternative tools while maintaining high accuracy and low memory usage. For example, GSearch can search 8000 query genomes against all available microbial or viral genomes for their best matches (n = ∼318 000 or ∼3 000 000, respectively) within a few minutes on a personal laptop, using ∼6 GB of memory (2.5 GB via SetSketch). Notably, GSearch has an O(log(N)) time complexity and will scale well with billions of genomes based on a database splitting strategy. Further, GSearch implements a three-step search strategy depending on the degree of novelty of the query genomes to maximize specificity and sensitivity. Therefore, GSearch solves a major bottleneck of microbiome studies that require genome search and/or classification.

Why and how to use the SeqCode.

The SeqCode, formally called the Code of Nomenclature of Prokaryotes Described from Sequence Data, is a new code of nomenclature in which genome sequences are the nomenclatural types for the names of prokaryotic species. While similar to the International Code of Nomenclature of Prokaryotes (ICNP) in structure and rules of priority, it does not require the deposition of type strains in international culture collections. Thus, it allows for the formation of permanent names for uncultured prokaryotes whose nearly complete genome sequences have been obtained directly from environmental DNA as well as other prokaryotes that cannot be deposited in culture collections. Because the diversity of uncultured prokaryotes greatly exceeds that of readily culturable prokaryotes, the SeqCode is the only code suitable for naming the majority of prokaryotic species. The start date of the SeqCode was January 1, 2022, and the online Registry (https://seqco.de/) was created to ensure valid publication of names. The SeqCode recognizes all names validly published under the ICNP before 2022. After that date, names validly published under the SeqCode compete with ICNP names for priority. As a result, species can have only one name, either from the SeqCode or ICNP, enabling effective communication and the creation of unified taxonomies of uncultured and cultured prokaryotes. The SeqCode is administered by the SeqCode Committee, which is comprised of the SeqCode Community and elected administrative components. Anyone with an interest in the systematics of prokaryotes is encouraged to join the SeqCode Community and participate in the development of this resource.

Quis custodiet ipsos custodes? A call for community participation in the governance of the SeqCode.

Codes of nomenclature that provide well-regulated and stable frameworks for the naming of taxa are a fundamental underpinning of biological research. These Codes themselves require systems that govern their administration, interpretation and emendment. Here we review the provisions that have been made for the governance of the recently introduced Code of Nomenclature of Prokaryotes Described from Sequence Data (SeqCode), which provides a nomenclatural framework for the valid publication of names of Archaea and Bacteria using isolate genome, metagenome-assembled genome or single-amplified genome sequences as type material. The administrative structures supporting the SeqCode are designed to be open and inclusive. Direction is provided by the SeqCode Community, which we encourage those with an interest in prokaryotic systematics to join.

Andean soil-derived lignocellulolytic bacterial consortium as a source of novel taxa and putative plastic-active enzymes.

An easy and straightforward way to engineer microbial environmental communities is by setting up liquid enrichment cultures containing a specific substrate as the sole source of carbon. Here, we analyzed twenty single-contig high-quality metagenome-assembled genomes (MAGs) retrieved from a microbial consortium (T6) that was selected by the dilution-to-stimulation approach using Andean soil as inoculum and lignocellulose as a selection pressure. Based on genomic metrics (e.g., average nucleotide and amino acid identities) and phylogenomic analyses, 15 out of 20 MAGs were found to represent novel bacterial species, with one of those (MAG_26) belonging to a novel genus closely related to Caenibius spp. (Sphingomonadaceae). Following the rules and requirements of the SeqCode, we propose the name Andeanibacterium colombiense gen. nov., sp. nov. for this taxon. A subsequent functional annotation of all MAGs revealed that MAG_7 (Pseudobacter hemicellulosilyticus sp. nov.) contains 20, 19 and 16 predicted genes from carbohydrate-active enzymes families GH43, GH2 and GH92, respectively. Its lignocellulolytic gene profile resembles that of MAG_2 (the most abundant member) and MAG_3858, both of which belong to the Sphingobacteriaceae family. Using a database that contains experimentally verified plastic-active enzymes (PAZymes), twenty-seven putative bacterial polyethylene terephthalate (PET)-active enzymes (i.e., alpha/beta-fold hydrolases) were detected in all MAGs. A maximum of five putative PETases were found in MAG_3858, and two PETases were found to be encoded by A. colombiense. In conclusion, we demonstrate that lignocellulose-enriched liquid cultures coupled with genome-resolved metagenomics are suitable approaches to unveil the hidden bacterial diversity and its polymer-degrading potential in Andean soil ecosystems.

Towards estimating the number of strains that make up a natural bacterial population.

What a strain is and how many strains make up a natural bacterial population remain elusive concepts despite their apparent importance for assessing the role of intra-population diversity in disease emergence or response to environmental perturbations. To advance these concepts, we sequenced 138 randomly selected Salinibacter ruber isolates from two solar salterns and assessed these genomes against companion short-read metagenomes from the same samples. The distribution of genome-aggregate average nucleotide identity (ANI) values among these isolates revealed a bimodal distribution, with four-fold lower occurrence of values between 99.2% and 99.8% relative to ANI >99.8% or <99.2%, revealing a natural "gap" in the sequence space within species. Accordingly, we used this ANI gap to define genomovars and a higher ANI value of >99.99% and shared gene-content >99.0% to define strains. Using these thresholds and extrapolating from how many metagenomic reads each genomovar uniquely recruited, we estimated that -although our 138 isolates represented about 80% of the Sal. ruber population- the total population in one saltern pond is composed of 5,500 to 11,000 genomovars, the great majority of which appear to be rare in-situ. These data also revealed that the most frequently recovered isolate in lab media was often not the most abundant genomovar in-situ, suggesting that cultivation biases are significant, even in cases that cultivation procedures are thought to be robust. The methodology and ANI thresholds outlined here should represent a useful guide for future microdiversity surveys of additional microbial species.

An ANI gap within bacterial species that advances the definitions of intra-species units.

IMPORTANCE: Bacterial strains and clonal complexes are two cornerstone concepts for microbiology that remain loosely defined, which confuses communication and research. Here we identify a natural gap in genome sequence comparisons among isolate genomes of all well-sequenced species that has gone unnoticed so far and could be used to more accurately and precisely define these and related concepts compared to current methods. These findings advance the molecular toolbox for accurately delineating and following the important units of diversity within prokaryotic species and thus should greatly facilitate future epidemiological and micro-diversity studies across clinical and environmental settings.

A user's guide to the bioinformatic analysis of shotgun metagenomic sequence data for bacterial pathogen detection.

Metagenomics, i.e., shotgun sequencing of the total microbial community DNA from a sample, has become a mature technique but its application to pathogen detection in clinical, environmental, and food samples is far from common or standardized. In this review, we summarize ongoing developments in metagenomic sequence analysis that facilitate its wider application to pathogen detection. We examine theoretical frameworks for estimating the limit of detection for a particular level of sequencing effort, current approaches for achieving species and strain analytical resolution, and discuss some relevant modern tools for these tasks. While these recent advances are significant and establish metagenomics as a powerful tool to provide insights not easily attained by culture-based approaches, metagenomics is unlikely to emerge as a widespread, routine monitoring tool in the near future due to its inherently high detection limits, cost, and inability to easily distinguish between viable and non-viable cells. Instead, metagenomics seems best poised for applications involving special circumstances otherwise challenging for culture-based and molecular (e.g., PCR-based) approaches such as the de novo detection of novel pathogens, cases of co-infection by more than one pathogen, and situations where it is important to assess the genomic composition of the pathogenic population(s) and/or its impact on the indigenous microbiome.

Comparative Genomics Identifies Conserved and Variable TAL Effectors in African Strains of the Cotton Pathogen Xanthomonas citri pv. malvacearum.

Strains of Xanthomonas citri pv. malvacearum cause bacterial blight of cotton, a potentially serious threat to cotton production worldwide, including in sub-Saharan countries. Development of disease symptoms, such as water soaking, has been linked to the activity of a class of type 3 effectors, called transcription activator-like (TAL) effectors, which induce susceptibility genes in the host's cells. To gain further insight into the global diversity of the pathogen, to elucidate their repertoires of TAL effector genes, and to better understand the evolution of these genes in the cotton-pathogenic xanthomonads, we sequenced the genomes of three African strains of X. citri pv. malvacearum using nanopore technology. We show that the cotton-pathogenic pathovar of X. citri is a monophyletic lineage containing at least three distinct genetic subclades, which appear to be mirrored by their repertoires of TAL effectors. We observed an atypical level of TAL effector gene pseudogenization, which might be related to resistance genes that are deployed to control the disease. Our work thus contributes to a better understanding of the conservation and importance of TAL effectors in the interaction with the host plant, which can inform strategies for improving resistance against bacterial blight in cotton.

Development of the SeqCode: A proposed nomenclatural code for uncultivated prokaryotes with DNA sequences as type.

Over the last fifteen years, genomics has become fully integrated into prokaryotic systematics. The genomes of most type strains have been sequenced, genome sequence similarity is widely used for delineation of species, and phylogenomic methods are commonly used for classification of higher taxonomic ranks. Additionally, environmental genomics has revealed a vast diversity of as-yet-uncultivated taxa. In response to these developments, a new code of nomenclature, the Code of Nomenclature of Prokaryotes Described from Sequence Data (SeqCode), has been developed over the last two years to allow naming of Archaea and Bacteria using DNA sequences as the nomenclatural types. The SeqCode also allows naming of cultured organisms, including fastidious prokaryotes that cannot be deposited into culture collections. Several simplifications relative to the International Code of Nomenclature of Prokaryotes (ICNP) are implemented to make nomenclature more accessible, easier to apply and more readily communicated. By simplifying nomenclature with the goal of a unified classification, inclusive of both cultured and uncultured taxa, the SeqCode will facilitate the naming of taxa in every biome on Earth, encourage the isolation and characterization of as-yet-uncultivated taxa, and promote synergies between the ecological, environmental, physiological, biochemical, and molecular biological disciplines to more fully describe prokaryotes.

Naming the unnamed: over 65,000 Candidatus names for unnamed Archaea and Bacteria in the Genome Taxonomy Database.

Thousands of new bacterial and archaeal species and higher-level taxa are discovered each year through the analysis of genomes and metagenomes. The Genome Taxonomy Database (GTDB) provides hierarchical sequence-based descriptions and classifications for new and as-yet-unnamed taxa. However, bacterial nomenclature, as currently configured, cannot keep up with the need for new well-formed names. Instead, microbiologists have been forced to use hard-to-remember alphanumeric placeholder labels. Here, we exploit an approach to the generation of well-formed arbitrary Latinate names at a scale sufficient to name tens of thousands of unnamed taxa within GTDB. These newly created names represent an important resource for the microbiology community, facilitating communication between bioinformaticians, microbiologists and taxonomists, while populating the emerging landscape of microbial taxonomic and functional discovery with accessible and memorable linguistic labels.

SeqCode: a nomenclatural code for prokaryotes described from sequence data.

Most prokaryotes are not available as pure cultures and therefore ineligible for naming under the rules and recommendations of the International Code of Nomenclature of Prokaryotes (ICNP). Here we summarize the development of the SeqCode, a code of nomenclature under which genome sequences serve as nomenclatural types. This code enables valid publication of names of prokaryotes based upon isolate genome, metagenome-assembled genome or single-amplified genome sequences. Otherwise, it is similar to the ICNP with regard to the formation of names and rules of priority. It operates through the SeqCode Registry ( https://seqco.de/ ), a registration portal through which names and nomenclatural types are registered, validated and linked to metadata. We describe the two paths currently available within SeqCode to register and validate names, including Candidatus names, and provide examples for both. Recommendations on minimal standards for DNA sequences are provided. Thus, the SeqCode provides a reproducible and objective framework for the nomenclature of all prokaryotes regardless of cultivability and facilitates communication across microbiological disciplines.

ROCker Models for Reliable Detection and Typing of Short-Read Sequences Carrying ß-Lactamase Genes.

Identification of genes encoding ß-lactamases (BLs) from short-read sequences remains challenging due to the high frequency of shared amino acid functional domains and motifs in proteins encoded by BL genes and related non-BL gene sequences. Divergent BL homologs can be frequently missed during similarity searches, which has important practical consequences for monitoring antibiotic resistance. To address this limitation, we built ROCker models that targeted broad classes (e.g., class A, B, C, and D) and individual families (e.g., TEM) of BLs and challenged them with mock 150-bp- and 250-bp-read data sets of known composition. ROCker identifies most-discriminant bit score thresholds in sliding windows along the sequence of the target protein sequence and hence can account for nondiscriminative domains shared by unrelated proteins. BL ROCker models showed a 0% false-positive rate (FPR), a 0% to 4% false-negative rate (FNR), and an up-to-50-fold-higher F1 score [2 × precision × recall/(precision + recall)] compared to alternative methods, such as similarity searches using BLASTx with various e-value thresholds and BL hidden Markov models, or tools like DeepARG, ShortBRED, and AMRFinder. The ROCker models and the underlying protein sequence reference data sets and phylogenetic trees for read placement are freely available through http://enve-omics.ce.gatech.edu/data/rocker-bla. Application of these BL ROCker models to metagenomics, metatranscriptomics, and high-throughput PCR gene amplicon data should facilitate the reliable detection and quantification of BL variants encoded by environmental or clinical isolates and microbiomes and more accurate assessment of the associated public health risk, compared to the current practice. IMPORTANCE Resistance genes encoding ß-lactamases (BLs) confer resistance to the widely prescribed antibiotic class ß-lactams. Therefore, it is important to assess the prevalence of BL genes in clinical or environmental samples for monitoring the spreading of these genes into pathogens and estimating public health risk. However, detecting BLs in short-read sequence data is technically challenging. Our ROCker model-based bioinformatics approach showcases the reliable detection and typing of BLs in complex data sets and thus contributes toward solving an important problem in antibiotic resistance surveillance. The ROCker models developed substantially expand the toolbox for monitoring antibiotic resistance in clinical or environmental settings.

Toward shotgun metagenomic approaches for microbial source tracking sewage spills based on laboratory mesocosms.

Little is known about the genomic diversity of the microbial communities associated with raw municipal wastewater (sewage), including whether microbial populations specific to sewage exist and how such populations could be used to improve source attribution and apportioning in contaminated waters. Herein, we used the influent of three wastewater treatment plants in Atlanta, Georgia (USA) to perturb laboratory freshwater mesocosms, simulating sewage contamination events, and followed these mesocosms with shotgun metagenomics over a 7-day observational period. We describe 15 abundant non-redundant bacterial metagenome-assembled genomes (MAGs) ubiquitous within all sewage inocula yet absent from the unperturbed freshwater control at our analytical limit of detection. Tracking the dynamics of the populations represented by these MAGs revealed varied decay kinetics, depending on (inferred) phenotypes, e.g., anaerobes decayed faster than aerobes under the well-aerated incubation conditions. Notably, a portion of these populations showed decay patterns similar to those of common markers, Enterococcus and HF183. Despite the apparent decay of these populations, the abundance of ß-lactamase encoding genes remained high throughout incubation relative to the control. Lastly, we constructed genomic libraries representing several different fecal sources and outline a bioinformatic approach which leverages these libraries for identifying and apportioning contamination signal among multiple probable sources using shotgun metagenomic data.

Higher pathogen load in children from Mozambique vs. USA revealed by comparative fecal microbiome profiling.

The infant gut microbiome has lifelong implications on health and immunity but there is still limited understanding of the microbiome differences and similarities between children in low- and middle-income countries (LMICs) vs. high-income countries (HICs). Here, we describe and compare the microbiome profile of children aged under 48 months in two urban areas: Maputo, Mozambique and Atlanta, USA using shotgun metagenomics. The gut microbiome of American children showed distinct development, characterized by higher alpha diversity after infancy, compared to the same age group of African children, and the microbiomes clustered separately based on geographic location or age. The abundances of antibiotic resistance genes (ARGs) and virulence factors (VFs) were significantly higher in Maputo children, driven primarily by several primary and opportunistic pathogens. Most notably, about 50% of Maputo children under the age of two were positive for enterotoxigenic (ETEC) and typical enteropathogenic (EPEC) Escherichia coli diagnostic genes while none of the Atlanta age-matched children showed such a positive signal. In contrast, commensal species such as Phocaeicola vulgatus and Bacteroides caccae were more abundant in Atlanta, potentially reflecting diets rich in animal protein and susceptibility to inflammatory diseases. Overall, our results suggest that the different environments characterizing the two cities have significant, distinctive signatures on the microbiota of children and its development over time. Lack of safe water, sanitation, and hygiene (WASH) conditions and/or unsafe food sources may explain the higher enteric pathogen load among children in Maputo.

Novel bacterial taxa in a minimal lignocellulolytic consortium and their potential for lignin and plastics transformation.

The understanding and manipulation of microbial communities toward the conversion of lignocellulose and plastics are topics of interest in microbial ecology and biotechnology. In this study, the polymer-degrading capability of a minimal lignocellulolytic microbial consortium (MELMC) was explored by genome-resolved metagenomics. The MELMC was mostly composed (>90%) of three bacterial members (Pseudomonas protegens; Pristimantibacillus lignocellulolyticus gen. nov., sp. nov; and Ochrobactrum gambitense sp. nov) recognized by their high-quality metagenome-assembled genomes (MAGs). Functional annotation of these MAGs revealed that Pr. lignocellulolyticus could be involved in cellulose and xylan deconstruction, whereas Ps. protegens could catabolize lignin-derived chemical compounds. The capacity of the MELMC to transform synthetic plastics was assessed by two strategies: (i) annotation of MAGs against databases containing plastic-transforming enzymes; and (ii) predicting enzymatic activity based on chemical structural similarities between lignin- and plastics-derived chemical compounds, using Simplified Molecular-Input Line-Entry System and Tanimoto coefficients. Enzymes involved in the depolymerization of polyurethane and polybutylene adipate terephthalate were found to be encoded by Ps. protegens, which could catabolize phthalates and terephthalic acid. The axenic culture of Ps. protegens grew on polyhydroxyalkanoate (PHA) nanoparticles and might be a suitable species for the industrial production of PHAs in the context of lignin and plastic upcycling.

Transcriptomic and rRNA:rDNA Signatures of Environmental versus Enteric Enterococcus faecalis Isolates under Oligotrophic Freshwater Conditions.

The use of enterococci as a fecal indicator bacterial group for public health risk assessment has been brought into question by recent studies showing that "naturalized" populations of Enterococcus faecalis exist in the extraenteric environment. The extent to which these naturalized E. faecalis organisms can confound water quality monitoring is unclear. To determine if strains isolated from different habitats display different survival strategies and responses, we compared the decay patterns of three E. faecalis isolates from the natural environment (environmental strains) against three human gut isolates (enteric strains) in laboratory mesocosms that simulate an oligotrophic, aerobic freshwater environment. Our results showed similar overall decay rates between enteric and environmental isolates based on viable plate and quantitative PCR (qPCR) counts. However, the enteric isolates exhibited a spike in copy number ratios of 16S rRNA gene transcripts to 16S rRNA gene DNA copies (rRNA:rDNA ratios) between days 1 and 3 of the mesocosm incubations that was not observed in environmental isolates, which could indicate a different stress response. Nevertheless, there was no strong evidence of differential gene expression between environmental and enteric isolates related to habitat adaptation in the accompanying mesocosm metatranscriptomes. Overall, our results provide novel information on how rRNA levels may vary over different growth conditions (e.g., standard lab versus oligotrophic) for this important indicator bacteria. We also observed some evidence for habitat adaptation in E. faecalis; however, this adaptation may not be substantial or consistent enough for integration in water quality monitoring. IMPORTANCE Enterococci are commonly used worldwide to monitor environmental fecal contamination and public health risk for waterborne diseases. However, closely related enterococci strains adapted to living in the extraenteric environment may represent a lower public health risk and confound water quality estimates. We developed an rRNA:rDNA viability assay for E. faecalis (a predominant species within this fecal group) and tested it against both enteric and environmental isolates in freshwater mesocosms to assess whether this approach can serve as a more sensitive water quality monitoring tool. We were unable to reliably distinguish the different isolate types using this assay under the conditions tested; thus, environmental strains should continue to be counted during routine water monitoring. However, this assay could be useful for distinguishing more recent (i.e., higher-risk) fecal pollution because rRNA levels significantly decreased after 1 week in all isolates.

Beach sand oil spills select for generalist microbial populations.

The specialization-disturbance hypothesis predicts that, in the event of a disturbance, generalists are favored, while specialists are selected against. This hypothesis has not been rigorously tested in microbial systems and it remains unclear to what extent it could explain microbial community succession patterns following perturbations. Previous field observations of Pensacola Beach sands that were impacted by the Deepwater Horizon (DWH) oil spill provided evidence in support of the specialization-disturbance hypothesis. However, ecological drift as well as uncounted environmental fluctuations (e.g., storms) could not be ruled out as confounding factors driving these field results. In this study, the specialization-disturbance hypothesis was tested on beach sands, disturbed by DWH crude oil, ex situ in closed laboratory advective-flow chambers that mimic in situ conditions in saturated beach sediments. The chambers were inoculated with weathered DWH oil and unamended chambers served as controls. The time series of shotgun metagenomic and 16S rRNA gene amplicon sequence data from a two-month long incubation showed that functional diversity significantly increased while taxonomic diversity significantly declined, indicating a decrease in specialist taxa. Thus, results from this laboratory study corroborate field observations, providing verification that the specialization-disturbance hypothesis can explain microbial succession patterns in crude oil impacted beach sands.

The Reliability of Metagenome-Assembled Genomes (MAGs) in Representing Natural Populations: Insights from Comparing MAGs against Isolate Genomes Derived from the Same Fecal Sample.

The recovery of metagenome-assembled genomes (MAGs) from metagenomic data has recently become a common task for microbial studies. The strengths and limitations of the underlying bioinformatics algorithms are well appreciated by now based on performance tests with mock data sets of known composition. However, these mock data sets do not capture the complexity and diversity often observed within natural populations, since their construction typically relies on only a single genome of a given organism. Further, it remains unclear if MAGs can recover population-variable genes (those shared by >10% but <90% of the members of the population) as efficiently as core genes (those shared by >90% of the members). To address these issues, we compared the gene variabilities of pathogenic Escherichia coli isolates from eight diarrheal samples, for which the isolate was the causative agent, against their corresponding MAGs recovered from the companion metagenomic data set. Our analysis revealed that MAGs with completeness estimates near 95% captured only 77% of the population core genes and 50% of the variable genes, on average. Further, about 5% of the genes of these MAGs were conservatively identified as missing in the isolate and were of different (non-Enterobacteriaceae) taxonomic origin, suggesting errors at the genome-binning step, even though contamination estimates based on commonly used pipelines were only 1.5%. Therefore, the quality of MAGs may often be worse than estimated, and we offer examples of how to recognize and improve such MAGs to sufficient quality by (for instance) employing only contigs longer than 1,000 bp for binning.IMPORTANCE Metagenome assembly and the recovery of metagenome-assembled genomes (MAGs) have recently become common tasks for microbiome studies across environmental and clinical settings. However, the extent to which MAGs can capture the genes of the population they represent remains speculative. Current approaches to evaluating MAG quality are limited to the recovery and copy number of universal housekeeping genes, which represent a small fraction of the total genome, leaving the majority of the genome essentially inaccessible. If MAG quality in reality is lower than these approaches would estimate, this could have dramatic consequences for all downstream analyses and interpretations. In this study, we evaluated this issue using an approach that employed comparisons of the gene contents of MAGs to the gene contents of isolate genomes derived from the same sample. Further, our samples originated from a diarrhea case-control study, and thus, our results are relevant for recovering the virulence factors of pathogens from metagenomic data sets.