ABSTRACT
BACKGROUND: Leptospiraceae comprise a diverse family of spirochetal bacteria, of which many are involved in infectious diseases of animals and humans. Local leptospiral diversity in domestic animals is often poorly understood. Here we describe the incidental detection of Leptospira (L.) licerasiae in an Austrian pig. CASE PRESENTATION: During an experiment to characterize the pathogenesis of L. interrogans serovar Icterohaemorrhagiae in pigs, cultivation of a urine sample from a non-challenged contact pig resulted in growth of a spirochetal bacterium that tested negative for pathogenic Leptospira (LipL32 gene). PCR, Sanger sequencing and standard serotyping further confirmed that the recovered isolate was clearly different from the challenge strain L. interrogans serovar Icterohaemorrhagiae used in the animal experiment. Whole genome sequencing revealed that the isolate belongs to the species L. licerasiae, a tropical member of the Leptospiraceae, with no prior record of detection in Europe. CONCLUSIONS: This is the first report describing the occurrence of L. licerasiae in Europe. Since L. licerasiae is considered to have intermediate pathogenicity, it will be important to follow the geographical distribution of this species and its pathogenic and zoonotic potential in more detail.
Subject(s)
Leptospira , Leptospirosis , Swine Diseases , Animals , Swine , Leptospirosis/veterinary , Leptospirosis/microbiology , Leptospira/isolation & purification , Leptospira/genetics , Swine Diseases/microbiology , AustriaABSTRACT
Childhood stunting is associated with impaired cognitive development and increased risk of infections, morbidity, and mortality. The composition of the enteric microbiota may contribute to the pathogenesis of stunting. We systematically reviewed and synthesized data from studies using high-throughput genomic sequencing methods to characterize the gut microbiome in stunted versus non-stunted children under 5 years in LMICs. We included 14 studies from Asia, Africa, and South America. Most studies did not report any significant differences in the alpha diversity, while a significantly higher beta diversity was observed in stunted children in four out of seven studies that reported beta diversity. At the phylum level, inconsistent associations with stunting were observed for Bacillota, Pseudomonadota, and Bacteroidota phyla. No single genus was associated with stunted children across all 14 studies, and some associations were incongruent by specific genera. Nonetheless, stunting was associated with an abundance of pathobionts that could drive inflammation, such as Escherichia/Shigella and Campylobacter, and a reduction of butyrate producers, including Faecalibacterium, Megasphera, Blautia, and increased Ruminoccoccus. An abundance of taxa thought to originate in the oropharynx was also reported in duodenal and fecal samples of stunted children, while metabolic pathways, including purine and pyrimidine biosynthesis, vitamin B biosynthesis, and carbohydrate and amino acid degradation pathways, predicted linear growth. Current studies show that stunted children can have distinct microbial patterns compared to non-stunted children, which could contribute to the pathogenesis of stunting.
Subject(s)
Bacteria , Gastrointestinal Microbiome , Growth Disorders , Child, Preschool , Humans , Infant , Infant, Newborn , Bacteria/classification , Bacteria/genetics , Bacteria/isolation & purification , Feces/microbiology , Growth Disorders/microbiology , Growth Disorders/etiology , High-Throughput Nucleotide SequencingABSTRACT
Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. We find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics.
Subject(s)
Ecosystem , Prochlorococcus , Oceans and Seas , Food Chain , Population Dynamics , Seawater/microbiology , Pacific OceanABSTRACT
Objectives: Extended-spectrum ß-lactamase-producing Escherichia coli (ESBL-Ec) are frequently acquired during international travel, contributing to the global spread of antimicrobial resistance. Human-adapted ESBL-Ec are predicted to exhibit increased intestinal carriage duration, resulting in a higher likelihood of onward human-to-human transmission. Yet, bacterial determinants of increased carriage duration are unknown. Previous studies analysed small traveller cohorts, with short follow-up times, or did not employ high-resolution molecular typing, and were thus unable to identify bacterial traits associated with long-term carriage after recent acquisition. We aimed to identify which ESBL-Ec lineages are associated with increased carriage duration after return from international travel. Methods: In a prospective cohort study of 2001 international travellers, we analysed 160 faecal ESBL-Ec isolates from all 38 travellers who acquired ESBL-Ec during travel and subsequently carried ESBL-Ec for at least 12 months after return, by whole-genome sequencing. For 17 travellers, we confirmed the long-term carriage of ESBL-Ec strains through single nucleotide variant typing. To identify determinants of increased carriage duration, we compared the 17 long-term carriers (≥12 months of carriage) with 33 age-, sex- and destination-matched short-term carriers (<1 month of carriage). Long-read sequencing was employed to investigate long-term ESBL plasmid carriage. Results: We show that in healthy travellers with very low antibiotic usage, extra-intestinal pathogenic lineages of E. coli (ExPEC) are significantly more likely to persist than other E. coli lineages. The long-term carriage of E. coli from ExPEC lineages is mainly driven by sequence type 131 and phylogroup D E. coli. Conclusions: Although ExPEC lineages frequently cause extra-intestinal infections such as bloodstream infections, our results indicate that ExPEC lineages are also efficient intestinal colonizers, which potentially contributes to their onward transmission.
ABSTRACT
Meta'omic data on microbial diversity and function accrue exponentially in public repositories, but derived information is often siloed according to data type, study or sampled microbial environment. Here we present SPIRE, a Searchable Planetary-scale mIcrobiome REsource that integrates various consistently processed metagenome-derived microbial data modalities across habitats, geography and phylogeny. SPIRE encompasses 99 146 metagenomic samples from 739 studies covering a wide array of microbial environments and augmented with manually-curated contextual data. Across a total metagenomic assembly of 16 Tbp, SPIRE comprises 35 billion predicted protein sequences and 1.16 million newly constructed metagenome-assembled genomes (MAGs) of medium or high quality. Beyond mapping to the high-quality genome reference provided by proGenomes3 (http://progenomes.embl.de), these novel MAGs form 92 134 novel species-level clusters, the majority of which are unclassified at species level using current tools. SPIRE enables taxonomic profiling of these species clusters via an updated, custom mOTUs database (https://motu-tool.org/) and includes several layers of functional annotation, as well as crosslinks to several (micro-)biological databases. The resource is accessible, searchable and browsable via http://spire.embl.de.
Subject(s)
Databases, Factual , Metagenome , Microbiota , Metagenomics , Microbiota/geneticsABSTRACT
BACKGROUND: Inappropriate antimicrobial usage is a key driver of antimicrobial resistance (AMR). Low- and middle-income countries (LMICs) are disproportionately burdened by AMR and young children are especially vulnerable to infections with AMR-bearing pathogens. The impact of antibiotics on the microbiome, selection, persistence, and horizontal spread of AMR genes is insufficiently characterized and understood in children in LMICs. This systematic review aims to collate and evaluate the available literature describing the impact of antibiotics on the infant gut microbiome and resistome in LMICs. METHODS AND FINDINGS: In this systematic review, we searched the online databases MEDLINE (1946 to 28 January 2023), EMBASE (1947 to 28 January 2023), SCOPUS (1945 to 29 January 2023), WHO Global Index Medicus (searched up to 29 January 2023), and SciELO (searched up to 29 January 2023). A total of 4,369 articles were retrieved across the databases. Duplicates were removed resulting in 2,748 unique articles. Screening by title and abstract excluded 2,666 articles, 92 articles were assessed based on the full text, and 10 studies met the eligibility criteria that included human studies conducted in LMICs among children below the age of 2 that reported gut microbiome composition and/or resistome composition (AMR genes) following antibiotic usage. The included studies were all randomized control trials (RCTs) and were assessed for risk of bias using the Cochrane risk-of-bias for randomized studies tool. Overall, antibiotics reduced gut microbiome diversity and increased antibiotic-specific resistance gene abundance in antibiotic treatment groups as compared to the placebo. The most widely tested antibiotic was azithromycin that decreased the diversity of the gut microbiome and significantly increased macrolide resistance as early as 5 days posttreatment. A major limitation of this study was paucity of available studies that cover this subject area. Specifically, the range of antibiotics assessed did not include the most commonly used antibiotics in LMIC populations. CONCLUSION: In this study, we observed that antibiotics significantly reduce the diversity and alter the composition of the infant gut microbiome in LMICs, while concomitantly selecting for resistance genes whose persistence can last for months following treatment. Considerable heterogeneity in study methodology, timing and duration of sampling, and sequencing methodology in currently available research limit insights into antibiotic impacts on the microbiome and resistome in children in LMICs. More research is urgently needed to fill this gap in order to better understand whether antibiotic-driven reductions in microbiome diversity and selection of AMR genes place LMIC children at risk for adverse health outcomes, including infections with AMR-bearing pathogens.
Subject(s)
Anti-Bacterial Agents , Gastrointestinal Microbiome , Infant , Child , Humans , Child, Preschool , Anti-Bacterial Agents/adverse effects , Developing Countries , Gastrointestinal Microbiome/genetics , Azithromycin , Drug Resistance, Microbial/geneticsABSTRACT
The interpretation of genomic, transcriptomic and other microbial 'omics data is highly dependent on the availability of well-annotated genomes. As the number of publicly available microbial genomes continues to increase exponentially, the need for quality control and consistent annotation is becoming critical. We present proGenomes3, a database of 907 388 high-quality genomes containing 4 billion genes that passed stringent criteria and have been consistently annotated using multiple functional and taxonomic databases including mobile genetic elements and biosynthetic gene clusters. proGenomes3 encompasses 41 171 species-level clusters, defined based on universal single copy marker genes, for which pan-genomes and contextual habitat annotations are provided. The database is available at http://progenomes.embl.de/.
Subject(s)
Genome , Prokaryotic Cells , Databases, Genetic , Genomics , Molecular Sequence Annotation , Bacteria/classification , Bacteria/geneticsABSTRACT
The eggNOG (evolutionary gene genealogy Non-supervised Orthologous Groups) database is a bioinformatics resource providing orthology data and comprehensive functional information for organisms from all domains of life. Here, we present a major update of the database and website (version 6.0), which increases the number of covered organisms to 12 535 reference species, expands functional annotations, and implements new functionality. In total, eggNOG 6.0 provides a hierarchy of over 17M orthologous groups (OGs) computed at 1601 taxonomic levels, spanning 10 756 bacterial, 457 archaeal and 1322 eukaryotic organisms. OGs have been thoroughly annotated using recent knowledge from functional databases, including KEGG, Gene Ontology, UniProtKB, BiGG, CAZy, CARD, PFAM and SMART. eggNOG also offers phylogenetic trees for all OGs, maximising utility and versatility for end users while allowing researchers to investigate the evolutionary history of speciation and duplication events as well as the phylogenetic distribution of functional terms within each OG. Furthermore, the eggNOG 6.0 website contains new functionality to mine orthology and functional data with ease, including the possibility of generating phylogenetic profiles for multiple OGs across species or identifying single-copy OGs at custom taxonomic levels. eggNOG 6.0 is available at http://eggnog6.embl.de.
Subject(s)
Databases, Genetic , Genomics , Phylogeny , Computational Biology , Eukaryota/geneticsABSTRACT
BACKGROUND: Taxonomic profiling is a fundamental task in microbiome research that aims to detect and quantify the relative abundance of microorganisms in biological samples. Available methods using shotgun metagenomic data generally depend on the deposition of sequenced and taxonomically annotated genomes, usually from cultures of isolated strains, in reference databases (reference genomes). However, the majority of microorganisms have not been cultured yet. Thus, a substantial fraction of microbial community members remains unaccounted for during taxonomic profiling, particularly in samples from underexplored environments. To address this issue, we developed the mOTU profiler, a tool that enables reference genome-independent species-level profiling of metagenomes. As such, it supports the identification and quantification of both "known" and "unknown" species based on a set of select marker genes. RESULTS: We present mOTUs3, a command line tool that enables the profiling of metagenomes for >33,000 species-level operational taxonomic units. To achieve this, we leveraged the reconstruction of >600,000 draft genomes, most of which are metagenome-assembled genomes (MAGs), from diverse microbiomes, including soil, freshwater systems, and the gastrointestinal tract of ruminants and other animals, which we found to be underrepresented by reference genomes. Overall, two thirds of all species-level taxa lacked a reference genome. The cumulative relative abundance of these newly included taxa was low in well-studied microbiomes, such as the human body sites (6-11%). By contrast, they accounted for substantial proportions (ocean, freshwater, soil: 43-63%) or even the majority (pig, fish, cattle: 60-80%) of the relative abundance across diverse non-human-associated microbiomes. Using community-developed benchmarks and datasets, we found mOTUs3 to be more accurate than other methods and to be more congruent with 16S rRNA gene-based methods for taxonomic profiling. Furthermore, we demonstrate that mOTUs3 increases the resolution of well-known microbial groups into species-level taxa and helps identify new differentially abundant taxa in comparative metagenomic studies. CONCLUSIONS: We developed mOTUs3 to enable accurate species-level profiling of metagenomes. Compared to other methods, it provides a more comprehensive view of prokaryotic community diversity, in particular for currently underexplored microbiomes. To facilitate comparative analyses by the research community, it is released with >11,000 precomputed profiles for publicly available metagenomes and is freely available at: https://github.com/motu-tool/mOTUs . Video Abstract.
Subject(s)
Metagenome , Microbiota , Swine , Cattle , Animals , RNA, Ribosomal, 16S/genetics , Metagenome/genetics , Metagenomics , Microbiota/genetics , SoilABSTRACT
BACKGROUND: Semi-quantitative bacterial culture is the reference standard to diagnose urinary tract infection, but culture is time-consuming and can be unreliable if patients are receiving antibiotics. Metagenomics could increase diagnostic accuracy and speed by sequencing the microbiota and resistome directly from urine. We aimed to compare metagenomics to culture for semi-quantitative pathogen and resistome detection from urine. METHODS: In this proof-of-concept study, we prospectively included consecutive urine samples from a clinical diagnostic laboratory in Amsterdam. Urine samples were screened by DNA concentration, followed by PCR-free metagenomic sequencing of randomly selected samples with a high concentration of DNA (culture positive and negative). A diagnostic index was calculated as the product of DNA concentration and fraction of pathogen reads. We compared results with semi-quantitative culture using area under the receiver operating characteristic curve (AUROC) analyses. We used ResFinder and PointFinder for resistance gene detection and compared results to phenotypic antimicrobial susceptibility testing for six antibiotics commonly used for urinary tract infection treatment: nitrofurantoin, ciprofloxacin, fosfomycin, cotrimoxazole, ceftazidime, and ceftriaxone. FINDINGS: We screened 529 urine samples of which 86 were sequenced (43 culture positive and 43 culture negative). The AUROC of the DNA concentration-based screening was 0·85 (95% CI 0·81-0·89). At a cutoff value of 6·0 ng/mL, culture positivity was ruled out with a negative predictive value of 91% (95% CI 87-93; 26 of 297 samples), reducing the number of samples requiring sequencing by 56% (297 of 529 samples). The AUROC of the diagnostic index was 0·87 (95% CI 0·79-0·95). A diagnostic index cutoff value of 17·2 yielded a positive predictive value of 93% (95% CI 85-97) and a negative predictive value of 69% (55-80), correcting for a culture-positive prevalence of 66%. Gram-positive pathogens explained eight (89%) of the nine false-negative metagenomic test results. Agreement of phenotypic and genotypic antimicrobial susceptibility testing varied between 71% (22 of 31 samples) and 100% (six of six samples), depending on the antibiotic tested. INTERPRETATION: This study provides proof-of-concept of metagenomic semi-quantitative pathogen and resistome detection for the diagnosis of urinary tract infection. The findings warrant prospective clinical validation of the value of this approach in informing patient management and care. FUNDING: EU Horizon 2020 Research and Innovation Programme.
Subject(s)
Metagenomics , Urinary Tract Infections , Anti-Bacterial Agents/pharmacology , Humans , Metagenomics/methods , Prospective Studies , Sequence Analysis, DNA , Urinary Tract Infections/diagnosisABSTRACT
Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.
Subject(s)
Metagenome , Metagenomics , Archaea/genetics , Metagenomics/methods , Reproducibility of Results , Sequence Analysis, DNA , SoftwareABSTRACT
Phylogenetic analyses are widely used in microbiological research, for example to trace the progression of bacterial outbreaks based on whole-genome sequencing data. In practice, multiple analysis steps such as de novo assembly, alignment and phylogenetic inference are combined to form phylogenetic workflows. Comprehensive benchmarking of the accuracy of complete phylogenetic workflows is lacking. To benchmark different phylogenetic workflows, we simulated bacterial evolution under a wide range of evolutionary models, varying the relative rates of substitution, insertion, deletion, gene duplication, gene loss and lateral gene transfer events. The generated datasets corresponded to a genetic diversity usually observed within bacterial species (≥95â% average nucleotide identity). We replicated each simulation three times to assess replicability. In total, we benchmarked 19 distinct phylogenetic workflows using 8 different simulated datasets. We found that recently developed k-mer alignment methods such as kSNP and ska achieve similar accuracy as reference mapping. The high accuracy of k-mer alignment methods can be explained by the large fractions of genomes these methods can align, relative to other approaches. We also found that the choice of de novo assembly algorithm influences the accuracy of phylogenetic reconstruction, with workflows employing SPAdes or skesa outperforming those employing Velvet. Finally, we found that the results of phylogenetic benchmarking are highly variable between replicates. We conclude that for phylogenomic reconstruction, k-mer alignment methods are relevant alternatives to reference mapping at the species level, especially in the absence of suitable reference genomes. We show de novo genome assembly accuracy to be an underappreciated parameter required for accurate phylogenomic reconstruction.
Subject(s)
Benchmarking , Genome , Algorithms , Phylogeny , WorkflowABSTRACT
Complex assemblages of microbes in the surface ocean are responsible for approximately half of global carbon fixation. The persistence of high taxonomic diversity despite competition for a small suite of relatively homogeneously distributed nutrients, that is, 'the paradox of the plankton', represents a long-standing challenge for ecological theory. Here we find evidence consistent with temporal niche partitioning of nitrogen assimilation processes over a diel cycle in the North Pacific Subtropical Gyre. We jointly analysed transcript abundances, lipids and metabolites and discovered that a small number of diel archetypes can explain pervasive periodic dynamics. Metabolic pathway analysis of identified diel signals revealed asynchronous timing in the transcription of nitrogen uptake and assimilation genes among different microbial groups-cyanobacteria, heterotrophic bacteria and eukaryotes. This temporal niche partitioning of nitrogen uptake emerged despite synchronous transcription of photosynthesis and central carbon metabolism genes and associated macromolecular abundances. Temporal niche partitioning may be a mechanism by which microorganisms in the open ocean mitigate competition for scarce resources, supporting community coexistence.
Subject(s)
Cyanobacteria , Microbiota , Cyanobacteria/genetics , Nitrogen/metabolism , Plankton/genetics , SeawaterABSTRACT
Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.
Subject(s)
Metagenome , Metagenomics , Anti-Bacterial Agents/pharmacology , Drug Resistance, Microbial , Ecosystem , Humans , Metagenome/geneticsABSTRACT
The mOTU profiler, or mOTUs for short, is a software tool that enables the profiling of microbial communities in terms of their taxonomic composition, relative abundance of metabolically active members, and diversity of strain populations. To this end, it maintains a database of single-copy phylogenetic marker gene sequences, which are used as a reference to which short read metagenomic and metatranscriptomic reads are mapped for the identification and quantification of microbial taxa. Here, we describe the most common use cases of the mOTU profiler in two basic protocols. Additional supporting protocols provide information on its installation and in-depth guidance on adjusting its settings for increasing or decreasing the stringency with which taxa are detected and quantified, as well as for customizing the output file format. Guidelines for understanding the profiling results are provided, along with additional information on unique features, methodological details, and the development history of the tool. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Metagenomic and metatranscriptomic mOTU profiling Basic Protocol 2: Metagenomic SNV profiling Support Protocol 1: Installing mOTUs Support Protocol 2: Profiling pipeline-step by step Support Protocol 3: The mOTUs profiling routine using advanced parameters Support Protocol 4: Metagenomic SNV calling: advanced parameters.
Subject(s)
Metagenomics , Microbiota , Humans , Metagenome , Microbiota/genetics , Phylogeny , SoftwareABSTRACT
BACKGROUND: Oceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean's interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth. RESULTS: We leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins. CONCLUSIONS: Combining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes. Video abstract.
Subject(s)
Microbiota , Seawater , Bacteria/genetics , Oceans and Seas , PhylogenyABSTRACT
Genomes are critical units in microbiology, yet ascertaining quality in prokaryotic genome assemblies remains a formidable challenge. We present GUNC (the Genome UNClutterer), a tool that accurately detects and quantifies genome chimerism based on the lineage homogeneity of individual contigs using a genome's full complement of genes. GUNC complements existing approaches by targeting previously underdetected types of contamination: we conservatively estimate that 5.7% of genomes in GenBank, 5.2% in RefSeq, and 15-30% of pre-filtered "high-quality" metagenome-assembled genomes in recent studies are undetected chimeras. GUNC provides a fast and robust tool to substantially improve prokaryotic genome quality.
Subject(s)
Chimerism , Computational Biology/methods , Genome, Bacterial , Metagenome , Proteobacteria/genetics , Software , Contig Mapping , Metagenomics/methods , Phylogeny , Prokaryotic Cells/cytology , Prokaryotic Cells/metabolismABSTRACT
Sunlight is the most important environmental control on diel fluctuations in phytoplankton activity, and understanding diel microbial processes is essential to the study of oceanic biogeochemical cycles. Yet, little is known about the in situ temporal dynamics of phytoplankton metabolic activities and their coordination across different populations. We investigated diel orchestration of phytoplankton activity in photosynthesis, photoacclimation, and photoprotection by analyzing pigment and quinone distributions in combination with metatranscriptomes in surface waters of the North Pacific Subtropical Gyre (NPSG). We found diel cycles in pigment abundances resulting from the balance of their synthesis and consumption. These dynamics suggest that night represents a metabolic recovery phase, refilling cellular pigment stores, while photosystems are remodeled towards photoprotection during daytime. Transcript levels of genes involved in photosynthesis and pigment metabolism had synchronized diel expression patterns among all taxa, reflecting the driving force light imparts upon photosynthetic organisms in the ocean, while other environmental factors drive niche differentiation. For instance, observed decoupling of diel oscillations in transcripts and related pigments indicates that pigment abundances are modulated by environmental factors extending beyond gene expression/regulation reinforcing the need to combine metatranscriptomics with proteomics and metabolomics to fully understand the timing of these critical processes in situ.
Subject(s)
Phytoplankton , Seawater , Gene Expression Regulation , Oceans and SeasABSTRACT
Ammonia-oxidizing archaea (AOA) are among the most abundant and ubiquitous microorganisms in the ocean, exerting primary control on nitrification and nitrogen oxides emission. Although united by a common physiology of chemoautotrophic growth on ammonia, a corresponding high genomic and habitat variability suggests tremendous adaptive capacity. Here, we compared 44 diverse AOA genomes, 37 from species cultivated from samples collected across diverse geographic locations and seven assembled from metagenomic sequences from the mesopelagic to hadopelagic zones of the deep ocean. Comparative analysis identified seven major marine AOA genotypic groups having gene content correlated with their distinctive biogeographies. Phosphorus and ammonia availabilities as well as hydrostatic pressure were identified as selective forces driving marine AOA genotypic and gene content variability in different oceanic regions. Notably, AOA methylphosphonate biosynthetic genes span diverse oceanic provinces, reinforcing their importance for methane production in the ocean. Together, our combined comparative physiological, genomic, and metagenomic analyses provide a comprehensive view of the biogeography of globally abundant AOA and their adaptive radiation into a vast range of marine and terrestrial habitats.
Subject(s)
Ammonia , Archaea , Archaea/genetics , Nitrification , Nutrients , Oxidation-Reduction , PhylogenyABSTRACT
INTRODUCTION: Metagenomics is increasingly considered for clinical diagnostics. In order for this technology to become integrated in the clinical microbiology laboratory, process controls are required. Molecular diagnostic tests typically integrate an internal control (IC) to detect potential sources of variation and technical failure. However, few studies report on the integration of an IC in metagenomics. AIM: We aimed to develop an easy-to-use IC method for the process control of library preparation and sequencing applied to metagenomics in clinical microbiology diagnostics using Thermus thermophilus DNA. METHODOLOGY: DNA was extracted from urine samples and sequenced on the Ion Torrent Proton in the absence and presence of incremental concentrations (0.5-2-5%) of IC. Between aliquots of each sample, we compared the IC relative abundance (RA), and after in silico subtraction of IC reads, analysed microbial composition and the RA of pathogens. The optimal IC concentration was defined as the lowest concentration still detectable in all samples with the smallest impact on the microbial composition. RESULTS: The RA of IC correlated linearly with the spiked IC concentration (r2 = 0.99). IC added in a concentration of 0.5% of the total DNA concentration was detectable in all sample aliquots, regardless of human-bacterial DNA proportion, and after in silico removal gave the smallest difference in RA of pathogens compared to the sample aliquot sequenced in the absence of IC. The microbial composition in the presence and absence of IC was highly similar after in silico removal of IC reads (median BC-dissimilarity per sample: 0.059), provided samples had a mean of >10,000 bacterial reads. CONCLUSION: T. thermophilus DNA at a percentage of 0.5% of the total DNA concentration was successfully applied for the process control of metagenomics of urine samples. We demonstrated negligible alterations in sample microbial composition after in silico subtraction of IC reads. This approach contributes toward implementation of metagenomics in the clinical microbiology laboratory.