High-resolution shotgun metagenomics: the more data, the better?

In shotgun metagenomics (SM), the state-of-the-art bioinformatic workflows are referred to as high-resolution shotgun metagenomics (HRSM) and require intensive computing and disk storage resources. While the increase in data output of the latest iteration of high-throughput DNA sequencing systems can allow for unprecedented sequencing depth at a minimal cost, adjustments in HRSM workflows will be needed to properly process these ever-increasing sequence datasets. One potential adaptation is to generate so-called shallow SM datasets that contain fewer sequencing data per sample as compared with the more classic high coverage sequencing. While shallow sequencing is a promising avenue for SM data analysis, detailed benchmarks using real-data are lacking. In this case study, we took four public SM datasets, one massive and the others moderate in size and subsampled each dataset at various levels to mimic shallow sequencing datasets of various sequencing depths. Our results suggest that shallow SM sequencing is a viable avenue to obtain sound results regarding microbial community structures and that high-depth sequencing does not bring additional elements for ecological interpretation. More specifically, results obtained by subsampling as little as 0.5 M sequencing clusters per sample were similar to the results obtained with the largest subsampled dataset for human gut and agricultural soil datasets. For an Antarctic dataset, which contained only a few samples, 4 M sequencing clusters per sample was found to generate comparable results to the full dataset. One area where ultra-deep sequencing and maximizing the usage of all data was undeniably beneficial was in the generation of metagenome-assembled genomes.

Gut resistome linked to sexual preference and HIV infection.

BACKGROUND: People living with HIV (PLWH) are at increased risk of acquisition of multidrug resistant organisms due to higher rates of predisposing factors. The gut microbiome is the main reservoir of the collection of antimicrobial resistance determinants known as the gut resistome. In PLWH, changes in gut microbiome have been linked to immune activation and HIV-1 associated complications. Specifically, gut dysbiosis defined by low microbial gene richness has been linked to low Nadir CD4 + T-cell counts. Additionally, sexual preference has been shown to strongly influence gut microbiome composition in PLWH resulting in different Prevotella or Bacteroides enriched enterotypes, in MSM (men-who-have-sex-with-men) or no-MSM, respectively. To date, little is known about gut resistome composition in PLWH due to the scarcity of studies using shotgun metagenomics. The present study aimed to detect associations between different microbiome features linked to HIV-1 infection and gut resistome composition. RESULTS: Using shotgun metagenomics we characterized the gut resistome composition of 129 HIV-1 infected subjects showing different HIV clinical profiles and 27 HIV-1 negative controls from a cross-sectional observational study conducted in Barcelona, Spain. Most no-MSM showed a Bacteroides-enriched enterotype and low microbial gene richness microbiomes. We did not identify differences in resistome diversity and composition according to HIV-1 infection or immune status. However, gut resistome was more diverse in MSM group, Prevotella-enriched enterotype and gut micorbiomes with high microbial gene richness compared to no-MSM group, Bacteroides-enriched enterotype and gut microbiomes with low microbial gene richness. Additionally, gut resistome beta-diversity was different according to the defined groups and we identified a set of differentially abundant antimicrobial resistance determinants based on the established categories. CONCLUSIONS: Our findings reveal a significant correlation between gut resistome composition and various host variables commonly associated with gut microbiome, including microbiome enterotype, microbial gene richness, and sexual preference. These host variables have been previously linked to immune activation and lower Nadir CD4 + T-Cell counts, which are prognostic factors of HIV-related comorbidities. This study provides new insights into the relationship between antibiotic resistance and clinical characteristics of PLWH.

Mitochondrial DNA variants and microbiota: An experimental strategy to identify novel therapeutic potential in chronic inflammatory diseases.

We previously demonstrated that mice carrying natural mtDNA variants of the FVB/NJ strain (m.7778 G>T in the mt-Atp8 gene in mitochondrial complex V), namely C57BL/6 J-mtFVB/NJ (B6-mtFVB), exhibited (i) partial protection from experimental skin inflammatory diseases in an anti-murine type VII collagen antibody-induced skin inflammation model and psoriasiform dermatitis model; (ii) significantly altered metabolites, including short-chain fatty acids, according to targeted metabolomics of liver, skin and lymph node samples; and (iii) a differential composition of the gut microbiota according to bacterial 16 S rRNA gene sequencing of stool samples compared to wild-type C57BL/6 J (B6) mice. To further dissect these disease-contributing factors, we induced an experimental antibody-induced skin inflammatory disease in gnotobiotic mice. We performed shotgun metagenomic sequencing of caecum contents and untargeted metabolomics of liver, CD4+ T cell, and caecum content samples from conventional B6-mtFVB and B6 mice. We identified D-glucosamine as a candidate mediator that ameliorated disease severity in experimental antibody-induced skin inflammation by modulating immune cell function in T cells, neutrophils and macrophages. Because mice carrying mtDNA variants of the FVB/NJ strain show differential disease susceptibility to a wide range of experimental diseases, including diet-induced atherosclerosis in low-density lipoprotein receptor knockout mice and collagen antibody-induced arthritis in DBA/1 J mice, this experimental approach is valuable for identifying novel therapeutic options for skin inflammatory conditions and other chronic inflammatory diseases to which mice carrying specific mtDNA variants show differential susceptibility.

Evaluation of the safety and efficacy of fecal microbiota transplantations in bottlenose dolphins (Tursiops truncatus) using metagenomic sequencing.

AIMS: Gastrointestinal disease is a leading cause of morbidity in bottlenose dolphins (Tursiops truncatus) under managed care. Fecal microbiota transplantation (FMT) holds promise as a therapeutic tool to restore gut microbiota without antibiotic use. This prospective clinical study aimed to develop a screening protocol for FMT donors to ensure safety, determine an effective FMT administration protocol for managed dolphins, and evaluate the efficacy of FMTs in four recipient dolphins. METHODS AND RESULTS: Comprehensive health monitoring was performed on donor and recipient dolphins. Fecal samples were collected before, during, and after FMT therapy. Screening of donor and recipient fecal samples was accomplished by in-house and reference lab diagnostic tests. Shotgun metagenomics was used for sequencing. Following FMT treatment, all four recipient communities experienced engraftment of novel microbial species from donor communities. Engraftment coincided with resolution of clinical signs and a sustained increase in alpha diversity. CONCLUSION: The donor screening protocol proved to be safe in this study and no adverse effects were observed in four recipient dolphins. Treatment coincided with improvement in clinical signs.

Direct metagenomics investigation of non-surgical hard-to-heal wounds: a review.

BACKGROUND: Non-surgical chronic wounds, including diabetes-related foot diseases (DRFD), pressure injuries (PIs) and venous leg ulcers (VLU), are common hard-to-heal wounds. Wound evolution partly depends on microbial colonisation or infection, which is often confused by clinicians, thereby hampering proper management. Current routine microbiology investigation of these wounds is based on in vitro culture, focusing only on a limited panel of the most frequently isolated bacteria, leaving a large part of the wound microbiome undocumented. METHODS: A literature search was conducted on original studies published through October 2022 reporting metagenomic next generation sequencing (mNGS) of chronic wound samples. Studies were eligible for inclusion if they applied 16 S rRNA metagenomics or shotgun metagenomics for microbiome analysis or diagnosis. Case reports, prospective, or retrospective studies were included. However, review articles, animal studies, in vitro model optimisation, benchmarking, treatment optimisation studies, and non-clinical studies were excluded. Articles were identified in PubMed, Google Scholar, Web of Science, Microsoft Academic, Crossref and Semantic Scholar databases. RESULTS: Of the 3,202 articles found in the initial search, 2,336 articles were removed after deduplication and 834 articles following title and abstract screening. A further 14 were removed after full text reading, with 18 articles finally included. Data were provided for 3,628 patients, including 1,535 DRFDs, 956 VLUs, and 791 PIs, with 164 microbial genera and 116 species identified using mNGS approaches. A high microbial diversity was observed depending on the geographical location and wound evolution. Clinically infected wounds were the most diverse, possibly due to a widespread colonisation by pathogenic bacteria from body and environmental microbiota. mNGS data identified the presence of virus (EBV) and fungi (Candida and Aspergillus species), as well as Staphylococcus and Pseudomonas bacteriophages. CONCLUSION: This study highlighted the benefit of mNGS for time-effective pathogen genome detection. Despite the majority of the included studies investigating only 16 S rDNA, ignoring a part of viral, fungal and parasite colonisation, mNGS detected a large number of bacteria through the included studies. Such technology could be implemented in routine microbiology for hard-to-heal wound microbiota investigation and post-treatment wound colonisation surveillance.

Dental plaque microbiota sequence counts for microbial profiling and resistance genes detection.

Shotgun metagenomics sequencing experiments are finding a wide range of applications. Nonetheless, there are still limited guidelines regarding the number of sequences needed to acquire meaningful information for taxonomic profiling and antimicrobial resistance gene (ARG) identification. In this study, we explored this issue in the context of oral microbiota by sequencing with a very high number of sequences (~ 100 million), four human plaque samples, and one microbial community standard and by evaluating the performance of microbial identification and ARGs detection through a downsampling procedure. When investigating the impact of a decreasing number of sequences on quantitative taxonomic profiling in the microbial community standard datasets, we found some discrepancies in the identified microbial species and their abundances when compared to the expected ones. Such differences were consistent throughout downsampling, suggesting their link to taxonomic profiling methods limitations. Overall, results showed that the number of sequences has a great impact on metagenomic samples at the qualitative (i.e., presence/absence) level in terms of loss of information, especially in experiments having less than 40 million reads, whereas abundance estimation was minimally affected, with only slight variations observed in low-abundance species. The presence of ARGs was also assessed: a total of 133 ARGs were identified. Notably, 23% of them inconsistently resulted as present or absent across downsampling datasets of the same sample. Moreover, over half of ARGs were lost in datasets having less than 20 million reads. This study highlights the importance of carefully considering sequencing aspects and suggests some guidelines for designing shotgun metagenomics experiments with the final goal of maximizing oral microbiome analyses. Our findings suggest varying optimized sequence numbers according to different study aims: 40 million for microbiota profiling, 50 million for low-abundance species detection, and 20 million for ARG identification. KEY POINTS: • Forty million sequences are a cost-efficient solution for microbiota profiling • Fifty million sequences allow low-abundance species detection • Twenty million sequences are recommended for ARG identification.

Metagenomic investigations into the microbial consortia, degradation pathways, and enzyme systems involved in the biodegradation of plastics in a tropical lentic pond sediment.

The exploitation of exciting features of plastics for diverse applications has resulted in significant plastic waste generation, which negatively impacts environmental compartments, metabolic processes, and the well-being of aquatic ecosystems biota. A shotgun metagenomic approach was deployed to investigate the microbial consortia, degradation pathways, and enzyme systems involved in the degradation of plastics in a tropical lentic pond sediment (APS). Functional annotation of the APS proteome (ORFs) using the PlasticDB database revealed annotation of 1015 proteins of enzymes such as depolymerase, esterase, lipase, hydrolase, nitrobenzylesterase, chitinase, carboxylesterase, polyesterase, oxidoreductase, polyamidase, PETase, MHETase, laccase, alkane monooxygenase, among others involved in the depolymerization of the plastic polymers. It also revealed that polyethylene glycol (PEG), polyhydroxyalkanoates (PHA), polyhydroxybutyrate (PHB), polylactic acid (PLA), polybutylene adipate terephthalate (PBAT), polyethylene terephthalate (PET), and nylon have the highest number of annotated enzymes. Further annotation using the KEGG GhostKOALA revealed that except for terephthalate, all the other degradation products of the plastic polymers depolymerization such as glyoxylate, adipate, succinate, 1,4-butanediol, ethylene glycol, lactate, and acetaldehyde were further metabolized to intermediates of the tricarboxylic acid cycle. Taxonomic characterization of the annotated proteins using the AAI Profiler and BLASTP revealed that Pseudomonadota members dominate most plastic types, followed by Actinomycetota and Acidobacteriota. The study reveals novel plastic degraders from diverse phyla hitherto not reported to be involved in plastic degradation. This suggests that plastic pollution in aquatic environments is prevalent with well-adapted degrading communities and could be the silver lining in mitigating the impacts of plastic pollution in aquatic environments.

Unknown Circovirus in Immunosuppressed Patient with Hepatitis, France, 2022.

Hepatitis of undetermined origin can be caused by a wide variety of pathogens, sometimes emerging pathogens. We report the discovery, by means of routine shotgun metagenomics, of a new virus belonging to the family Circoviridae, genus Circovirus, in a patient in France who had acute hepatitis of unknown origin.

Ecology, Not Host Phylogeny, Shapes the Oral Microbiome in Closely Related Species.

Host-associated microbiomes are essential for a multitude of biological processes. Placed at the contact zone between external and internal environments, the little-studied oral microbiome has important roles in host physiology and health. Here, we investigate the roles of host evolutionary relationships and ecology in shaping the oral microbiome in three closely related gorilla subspecies (mountain, Grauer's, and western lowland gorillas) using shotgun metagenomics of 46 museum-preserved dental calculus samples. We find that the oral microbiomes of mountain gorillas are functionally and taxonomically distinct from the other two subspecies, despite close evolutionary relationships and geographic proximity with Grauer's gorillas. Grauer's gorillas show intermediate bacterial taxonomic and functional, and dietary profiles. Altitudinal differences in gorilla subspecies ranges appear to explain these patterns, suggesting a close connection between dental calculus microbiomes and the environment, likely mediated through diet. This is further supported by the presence of gorilla subspecies-specific phyllosphere/rhizosphere taxa in the oral microbiome. Mountain gorillas show a high abundance of nitrate-reducing oral taxa, which may promote adaptation to a high-altitude lifestyle by modulating blood pressure. Our results suggest that ecology, rather than evolutionary relationships and geographic distribution, shape the oral microbiome in these closely related species.

Metagenomic Identification of Microbial Signatures Predicting Pancreatic Cancer From a Multinational Study.

BACKGROUND & AIMS: To identify gut and oral metagenomic signatures that accurately predict pancreatic ductal carcinoma (PDAC) and to validate these signatures in independent cohorts. METHODS: We conducted a multinational study and performed shotgun metagenomic analysis of fecal and salivary samples collected from patients with treatment-naïve PDAC and non-PDAC controls in Japan, Spain, and Germany. Taxonomic and functional profiles of the microbiomes were characterized, and metagenomic classifiers to predict PDAC were constructed and validated in external datasets. RESULTS: Comparative metagenomics revealed dysbiosis of both the gut and oral microbiomes and identified 30 gut and 18 oral species significantly associated with PDAC in the Japanese cohort. These microbial signatures achieved high area under the curve values of 0.78 to 0.82. The prediction model trained on the Japanese gut microbiome also had high predictive ability in Spanish and German cohorts, with respective area under the curve values of 0.74 and 0.83, validating its high confidence and versatility for PDAC prediction. Significant enrichments of Streptococcus and Veillonella spp and a depletion of Faecalibacterium prausnitzii were common gut signatures for PDAC in all the 3 cohorts. Prospective follow-up data revealed that patients with certain gut and oral microbial species were at higher risk of PDAC-related mortality. Finally, 58 bacteriophages that could infect microbial species consistently enriched in patients with PDAC across the 3 countries were identified. CONCLUSIONS: Metagenomics targeting the gut and oral microbiomes can provide a powerful source of biomarkers for identifying individuals with PDAC and their prognoses. The identification of shared gut microbial signatures for PDAC in Asian and European cohorts indicates the presence of robust and global gut microbial biomarkers.

Prematurely delivering mothers show reductions of lachnospiraceae in their gut microbiomes.

BACKGROUND: Preterm birth is the leading cause of perinatal morbidity and mortality. Despite evidence shows that imbalances in the maternal microbiome associates to the risk of preterm birth, the mechanisms underlying the association between a perturbed microbiota and preterm birth remain poorly understood. METHOD: Applying shotgun metagenomic analysis on 80 gut microbiotas of 43 mothers, we analyzed the taxonomic composition and metabolic function in gut microbial communities between preterm and term mothers. RESULTS: Gut microbiome of mothers delivering prematurely showed decreased alpha diversity and underwent significant reorganization, especially during pregnancy. SFCA-producing microbiomes, particularly species of Lachnospiraceae, Ruminococcaceae, and Eubacteriaceae, were significantly depleted in preterm mothers. Lachnospiraceae and its species were the main bacteria contributing to species' differences and metabolic pathways. CONCLUSION: Gut microbiome of mothers delivering prematurely has altered and demonstrates the reduction of Lachnospiraceae.

Effects of nitrogen deposition on carbon and nutrient cycling along a natural soil acidity gradient as revealed by metagenomics.

Nitrogen (N) deposition and soil acidification are environmental challenges affecting ecosystem functioning, health, and biodiversity, but their effects on functional genes are poorly understood. Here, we utilized metabarcoding and metagenomics to investigate the responses of soil functional genes to N deposition along a natural soil pH gradient. Soil N content was uncorrelated with pH, enabling us to investigate their effects separately. Soil acidity strongly and negatively affected the relative abundances of most cluster of orthologous gene categories of the metabolism supercategory. Similarly, soil acidity negatively affected the diversity of functional genes related to carbon and N but not phosphorus cycling. Multivariate analyses showed that soil pH was the most important factor affecting microbial and functional gene composition, while the effects of N deposition were less important. Relative abundance of KEGG functional modules related to different parts of the studied cycles showed variable responses to soil acidity and N deposition. Furthermore, our results suggested that the diversity-function relationship reported for other organisms also applies to soil microbiomes. Since N deposition and soil pH affected microbial taxonomic and functional composition to a different extent, we conclude that N deposition effects might be primarily mediated through soil acidification in forest ecosystems.

Integrated Multi-Cohort Analysis of the Parkinson's Disease Gut Metagenome.

BACKGROUND: The gut microbiome is altered in several neurologic disorders, including Parkinson's disease (PD). OBJECTIVES: The aim is to profile the fecal gut metagenome in PD for alterations in microbial composition, taxon abundance, metabolic pathways, and microbial gene products, and their relationship with disease progression. METHODS: Shotgun metagenomic sequencing was conducted on 244 stool donors from two independent cohorts in the United States, including individuals with PD (n = 48, n = 47, respectively), environmental household controls (HC, n = 29, n = 30), and community population controls (PC, n = 41, n = 49). Microbial features consistently altered in PD compared to HC and PC subjects were identified. Data were cross-referenced to public metagenomic data sets from two previous studies in Germany and China to determine generalizable microbiome features. RESULTS: We find several significantly altered taxa between PD and controls within the two cohorts sequenced in this study. Analysis across global cohorts returns consistent changes only in Intestinimonas butyriciproducens. Pathway enrichment analysis reveals disruptions in microbial carbohydrate and lipid metabolism and increased amino acid and nucleotide metabolism in PD. Global gene-level signatures indicate an increased response to oxidative stress, decreased cellular growth and microbial motility, and disrupted intercommunity signaling. CONCLUSIONS: A metagenomic meta-analysis of PD shows consistent and novel alterations in functional metabolic potential and microbial gene abundance across four independent studies from three continents. These data reveal that stereotypic changes in the functional potential of the gut microbiome are a consistent feature of PD, highlighting potential diagnostic and therapeutic avenues for future research. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Unveiling the microbial diversity and functional dynamics of Shiv Kund, Sohna hot spring, India through a shotgun metagenomics approach.

In this research, we examined the microbial diversity in Sohna hot spring, Haryana, India using shotgun metagenome sequencing based on the Illumina Hiseq 4000 sequencing technology. The raw sequence data from metagenomic paired-end libraries were analysed for taxonomic classification, diversity, and functional annotation using MG-RAST online server. The results showed the presence of total of 57 phyla, 931 genera, and 2068 species, predominantly occupied by Moraxellaceae (Gammaproteobacteria). However, at the species level, we reported the presence of some representative pathogenic taxa, such as Acinetobacter baumannii and Moraxella osloensis. The functional annotation predicted at various levels based on SEED-based subsystem, KEGG ortholog identity (KO), Cluster of Orthologous Groups (COGs) database identified the predominance of genes associated with primary and secondary metabolism along with a crucial role in environmental and genetic signals, cellular communication, and cell signalling. Comparative Genome Analysis (CGA) using The Pathosystem Resource Integration Centre (PATRIC) tool based on genome annotation and assembly of the metagenomic libraries for representative taxon Acinetobacter baumannii (NCBI tax id:470) characterized the reads with a unique genome identifier of 470.20380 (A. baumannii DDLJ4) which is evolutionary closer to A. baumannii ATCC 470.17978 400667.7. In addition, the CARD database results about the presence of potential AMR pathotypes and the prevalence of adeABC, adeIJK, abeM gene-specific clusters that function as multidrug efflux pumps. Overall, the results provided a comprehensive insight into virulence and anti-microbial resistance mechanism and could be useful for developing potential drug targets against the possible AMR pathotypes.

Shotgun Metagenomics Reveals Impacts of Copper and Water Heater Anodes on Pathogens and Microbiomes in Hot Water Plumbing Systems.

Hot water building plumbing systems are vulnerable to the proliferation of opportunistic pathogens (OPs), including Legionella pneumophila and Mycobacterium avium. Implementation of copper as a disinfectant could help reduce OPs, but a mechanistic understanding of the effects on the microbial community under real-world plumbing conditions is lacking. Here, we carried out a controlled pilot-scale study of hot water systems and applied shotgun metagenomic sequencing to examine the effects of copper dose (0-2 mg/L), orthophosphate corrosion control agent, and water heater anode materials (aluminum vs magnesium vs powered anode) on the bulk water and biofilm microbiome composition. Metagenomic analysis revealed that, even though a copper dose of 1.2 mg/L was required to reduce Legionella and Mycobacterium numbers, lower doses (e.g., ≤0.6 mg/L) measurably impacted the broader microbial community, indicating that the OP strains colonizing these systems were highly copper tolerant. Orthophosphate addition reduced bioavailability of copper, both to OPs and to the broader microbiome. Functional gene analysis indicated that both membrane damage and interruption of nucleic acid replication are likely at play in copper inactivation mechanisms. This study identifies key factors (e.g., orthophosphate, copper resistance, and anode materials) that can confound the efficacy of copper for controlling OPs in hot water plumbing.

Metagenomics revealing molecular profiles of microbial community structure and metabolic capacity in Bamucuo lake, Tibet.

Microorganisms play critical ecological roles in the global biogeochemical cycles. However, extensive information on the microbial communities in Qinghai-Tibet Plateau (QTP), which is the highest plateau in the world, is still lacking, particularly in high elevation locations above 4500 m. Here, we performed a survey of th e soil and water microbial communities in Bamucuo Lake, Tibet, by using shotgun metagenomic methods. In the soil and water samples, we reconstructed 75 almost complete metagenomic assembly genomes, and 74 of the metagenomic assembly genomes from the water sample represented novel species. Proteobacteria and Actinobacteria were found to be the dominant bacterial phyla, while Euryarchaeota was the dominant archaeal phylum. The largest virus, Pandoravirus salinus, was found in the soil microbial community. We concluded that the microorganisms in Bamucuo Lake are most likely to fix carbon mainly through the 3-hydroxypropionic bi-cycle pathway. This study, for the first time, characterized the microbial community composition and metabolic capacity in QTP high-elevation locations with 4555 m, confirming that QTP is a vast and valuable resource pool, in which many microorganisms can be used to develop new bioactive substances and new antibiotics to which pathogenic microorganisms have not yet developed resistance.

Further Insights into the Gut Microbiota of Cow's Milk Allergic Infants: Analysis of Microbial Functionality and Its Correlation with Three Fecal Biomarkers.

Cow's milk allergy (CMA) is one of the most prevalent food allergies in children. Several studies have demonstrated that gut microbiota influences the acquisition of oral tolerance to food antigens at initial stages of life. Changes in the gut microbiota composition and/or functionality (i.e., dysbiosis) have been linked to inadequate immune system regulation and the emergence of pathologies. Moreover, omic sciences have become an essential tool for the analysis of the gut microbiota. On the other hand, the use of fecal biomarkers for the diagnosis of CMA has recently been reviewed, with fecal calprotectin, α-1 antitrypsin, and lactoferrin being the most relevant. This study aimed at evaluating functional changes in the gut microbiota in the feces of cow's milk allergic infants (AI) compared to control infants (CI) by metagenomic shotgun sequencing and at correlating these findings with the levels of fecal biomarkers (α-1 antitrypsin, lactoferrin, and calprotectin) by an integrative approach. We have observed differences between AI and CI groups in terms of fecal protein levels and metagenomic analysis. Our findings suggest that AI have altered glycerophospholipid metabolism as well as higher levels of lactoferrin and calprotectin that could be explained by their allergic status.

Chromium contamination accentuates changes in the microbiome and heavy metal resistome of a tropical agricultural soil.

The impacts of hexavalent chromium (Cr) contamination on the microbiome, soil physicochemistry, and heavy metal resistome of a tropical agricultural soil were evaluated for 6 weeks in field-moist microcosms consisting of a Cr-inundated agricultural soil (SL9) and an untreated control (SL7). The physicochemistry of the two microcosms revealed a diminution in the total organic matter content and a significant dip in macronutrients phosphorus, potassium, and nitrogen concentration in the SL9 microcosm. Heavy metals analysis revealed the detection of seven heavy metals (Zn, Cu, Fe, Cd, Se, Pb, Cr) in the agricultural soil (SL7), whose concentrations drastically reduced in the SL9 microcosm. Illumina shotgun sequencing of the DNA extracted from the two microcosms showed the preponderance of the phyla, classes, genera, and species of Actinobacteria (33.11%), Actinobacteria_class (38.20%), Candidatus Saccharimonas (11.67%), and Candidatus Saccharimonas aalborgensis (19.70%) in SL7, and Proteobacteria (47.52%), Betaproteobacteria (22.88%), Staphylococcus (16.18%), Staphylococcus aureus (9.76%) in SL9, respectively. Functional annotation of the two metagenomes for heavy metal resistance genes revealed diverse heavy metal resistomes involved in the uptake, transport, efflux, and detoxification of various heavy metals. It also revealed the exclusive detection in SL9 metagenome of resistance genes for chromium (chrB, chrF, chrR, nfsA, yieF), cadmium (czcB/czrB, czcD), and iron (fbpB, yqjH, rcnA, fetB, bfrA, fecE) not annotated in SL7 metagenome. The findings from this study revealed that Cr contamination induces significant shifts in the soil microbiome and heavy metal resistome, alters the soil physicochemistry, and facilitates the loss of prominent members of the microbiome not adapted to Cr stress.

FragGeneScanRs: faster gene prediction for short reads.

BACKGROUND: FragGeneScan is currently the most accurate and popular tool for gene prediction in short and error-prone reads, but its execution speed is insufficient for use on larger data sets. The parallelization which should have addressed this is inefficient. Its alternative implementation FragGeneScan+ is faster, but introduced a number of bugs related to memory management, race conditions and even output accuracy. RESULTS: This paper introduces FragGeneScanRs, a faster Rust implementation of the FragGeneScan gene prediction model. Its command line interface is backward compatible and adds extra features for more flexible usage. Its output is equivalent to the original FragGeneScan implementation. CONCLUSIONS: Compared to the current C implementation, shotgun metagenomic reads are processed up to 22 times faster using a single thread, with better scaling for multithreaded execution. The Rust code of FragGeneScanRs is freely available from GitHub under the GPL-3.0 license with instructions for installation, usage and other documentation ( https://github.com/unipept/FragGeneScanRs ).

UMGAP: the Unipept MetaGenomics Analysis Pipeline.

BACKGROUND: Shotgun metagenomics yields ever richer and larger data volumes on the complex communities living in diverse environments. Extracting deep insights from the raw reads heavily depends on the availability of fast, accurate and user-friendly biodiversity analysis tools. RESULTS: Because environmental samples may contain strains and species that are not covered in reference databases and because protein sequences are more conserved than the genes encoding them, we explore the alternative route of taxonomic profiling based on protein coding regions translated from the shotgun metagenomics reads, instead of directly processing the DNA reads. We therefore developed the Unipept MetaGenomics Analysis Pipeline (UMGAP), a highly versatile suite of open source tools that are implemented in Rust and support parallelization to achieve optimal performance. Six preconfigured pipelines with different performance trade-offs were carefully selected, and benchmarked against a selection of state-of-the-art shotgun metagenomics taxonomic profiling tools. CONCLUSIONS: UMGAP's protein space detour for taxonomic profiling makes it competitive with state-of-the-art shotgun metagenomics tools. Despite our design choices of an extra protein translation step, a broad spectrum index that can identify both archaea, bacteria, eukaryotes and viruses, and a highly configurable non-monolithic design, UMGAP achieves low runtime, manageable memory footprint and high accuracy. Its interactive visualizations allow for easy exploration and comparison of complex communities.