Showing papers by "Frank Møller Aarestrup published in 2022"
TL;DR: In this paper , the authors show that methicillin-resistant Staphylococcus aureus appeared in hedgehogs in the pre-antibiotic era, and these lineages spread within the local hedgehog populations and between hedge-hogs and secondary hosts.
Abstract: Abstract The discovery of antibiotics more than 80 years ago has led to considerable improvements in human and animal health. Although antibiotic resistance in environmental bacteria is ancient, resistance in human pathogens is thought to be a modern phenomenon that is driven by the clinical use of antibiotics 1 . Here we show that particular lineages of methicillin-resistant Staphylococcus aureus —a notorious human pathogen—appeared in European hedgehogs in the pre-antibiotic era. Subsequently, these lineages spread within the local hedgehog populations and between hedgehogs and secondary hosts, including livestock and humans. We also demonstrate that the hedgehog dermatophyte Trichophyton erinacei produces two β-lactam antibiotics that provide a natural selective environment in which methicillin-resistant S. aureus isolates have an advantage over susceptible isolates. Together, these results suggest that methicillin resistance emerged in the pre-antibiotic era as a co-evolutionary adaptation of S. aureus to the colonization of dermatophyte-infected hedgehogs. The evolution of clinically relevant antibiotic-resistance genes in wild animals and the connectivity of natural, agricultural and human ecosystems demonstrate that the use of a One Health approach is critical for our understanding and management of antibiotic resistance, which is one of the biggest threats to global health, food security and development.
103 citations
TL;DR: Since its original publication in 2012, ResFinder has undergone a number of improvements including improvement of the code and databases, inclusion of point mutations for selected bacterial species and predictions of phenotypes also for selected species.
Abstract: Antimicrobial resistance (AMR) is one of the most important health threats globally. The ability to accurately identify resistant bacterial isolates and the individual antimicrobial resistance genes (ARGs) is essential for understanding the evolution and emergence of AMR and to provide appropriate treatment. The rapid developments in next-generation sequencing technologies have made this technology available to researchers and microbiologists at routine laboratories around the world. However, tools available for those with limited experience with bioinformatics are lacking, especially to enable researchers and microbiologists in low- and middle-income countries (LMICs) to perform their own studies. The CGE-tools (Center for Genomic Epidemiology) including ResFinder (https://cge.cbs.dtu.dk/services/ResFinder/) was developed to provide freely available easy to use online bioinformatic tools allowing inexperienced researchers and microbiologists to perform simple bioinformatic analyses. The main purpose was and is to provide these solutions for people involved in frontline diagnosis especially in LMICs. Since its original publication in 2012, ResFinder has undergone a number of improvements including improvement of the code and databases, inclusion of point mutations for selected bacterial species and predictions of phenotypes also for selected species. As of 28 September 2021, 820 803 analyses have been performed using ResFinder from 61 776 IP-addresses in 171 countries. ResFinder clearly fulfills a need for several people around the globe and we hope to be able to continue to provide this service free of charge in the future. We also hope and expect to provide further improvements including phenotypic predictions for additional bacterial species.
71 citations
TL;DR: RPC can be used to replace up to 25% of the FM protein in the diet of O. niloticus, while improving the antioxidant capacity, immunocompetence, and disease resistance of the fish.
14 citations
TL;DR: In this paper , the authors used thousands of bacterial genome sequences to comprehensively dissect the evolutionary history of a leading bacterial pathogen of livestock and revealed high-risk clones that undergo more frequent cross-species transmission and which may therefore represent greater threat to public or animal health.
Abstract: Significance The study uses thousands of bacterial genome sequences to comprehensively dissect the evolutionary history of a leading bacterial pathogen of livestock. Remarkably, contemporary bovine mastitis infections due to Staphylococcus aureus can be traced back to historic host switch events that originated in humans up to thousands of years ago. The host jumps were followed by host adaptation by acquisition of different gene combinations followed by global dissemination via established cattle trade links. Our work reveals high-risk clones that undergo more frequent cross-species transmission and which may therefore represent greater threat to public or animal health.
8 citations
TL;DR: In this paper , a proof-of-concept study of metagenomic semi-quantitative pathogen and resistome detection for the diagnosis of urinary tract infection from urine was presented.
Abstract: BackgroundSemi-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.MethodsIn 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.FindingsWe 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.InterpretationThis 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.FundingEU Horizon 2020 Research and Innovation Programme. 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. 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. 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. 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.
5 citations
TL;DR: WGS technologies have the potential to be applied in clinical settings for routine diagnostics purposes and results from local point-prevalence surveys should not be applied at national levels without previously determining possible regional variations.
Abstract: Objectives Implementing whole-genome sequencing (WGS) technologies in clinical microbiology laboratories can increase the amount and quality of information available for healthcare practitioners. In this study, we analysed the applicability of this method and determined the distribution of bacterial species processed in clinical settings in Denmark. Methods We performed a point-prevalence study of all bacterial isolates (n = 2,009) processed and reported in the Clinical Microbiology Laboratories in Denmark in one day in January 2018. We compared species identification as performed by classical methods (MALDI-TOF) and by bioinformatics analysis (KmerFinder and rMLST) of WGS (Illumina NextSeq) data. We compared the national point-prevalence of bacterial isolates observed in clinical settings with the research attention given to those same genera in scientific literature. Results The most prevalent bacterium was Escherichia coli isolated from urine (n = 646), followed by Staphylococcus spp. from skin or soft tissues (n = 197). The distribution of bacterial species throughout the country was not homogeneous. We observed concordance of species identification for all methods in 95.7% (n = 1,919) of isolates, furthermore obtaining concordance for 99.7% (n = 1,999) at genus level. The number of scientific publications in the country did not correlate with the number of bacterial isolates of each genera analysed in this study. Conclusions WGS technologies have the potential to be applied in clinical settings for routine diagnostics purposes. This study also showed that bioinformatics databases should be continuously improved and results from local point-prevalence surveys should not be applied at national levels without previously determining possible regional variations.
4 citations
TL;DR: Standard phenotypic AST results are compared with WGS-based predictions of AMR profiles in bacterial isolates without preselection of defined species, to evaluate the applicability of WGS as a diagnostics method in clinical settings.
Abstract: Antimicrobial susceptibility testing (AST) should be fast and accurate, leading to proper interventions and therapeutic success. Clinical microbiology laboratories rely on phenotypic methods, but the continuous improvement and decrease in the cost of whole-genome sequencing (WGS) technologies make them an attractive alternative. Studies evaluating the performance of WGS-based prediction of antimicrobial resistance (AMR) for selected bacterial species have shown promising results. There are, however, significant gaps in the literature evaluating the applicability of WGS as a diagnostics method in real-life clinical settings against the range of bacterial pathogens experienced there. Thus, we compared standard phenotypic AST results with WGS-based predictions of AMR profiles in bacterial isolates without preselection of defined species, to evaluate the applicability of WGS as a diagnostics method in clinical settings. We collected all bacterial isolates processed by all Danish Clinical Microbiology Laboratories in 1 day. We randomly selected 500 isolates without any preselection of species. We performed AST through standard broth microdilution (BMD) for 488 isolates (n = 6,487 phenotypic AST results) and compared results with in silico antibiograms obtained through WGS (Illumina NextSeq) followed by bioinformatics analyses using ResFinder 4.0 (n = 5,229 comparisons). A higher proportion of AMR was observed for Gram-negative bacteria (10.9%) than for Gram-positive bacteria (6.1%). Comparison of BMD with WGS data yielded a concordance of 91.7%, with discordant results mainly due to phenotypically susceptible isolates harboring genetic AMR determinants. These cases correspond to 6.2% of all isolate-antimicrobial combinations analyzed and to 6.8% of all phenotypically susceptible combinations. We detected fewer cases of phenotypically resistant isolates without any known genetic resistance mechanism, particularly 2.1% of all combinations analyzed, which corresponded to 26.4% of all detected phenotypic resistances. Most discordances were observed for specific combinations of species-antimicrobial: macrolides and tetracycline in streptococci, ciprofloxacin and β-lactams in combination with β-lactamase inhibitors in Enterobacterales, and most antimicrobials in Pseudomonas aeruginosa. WGS has the potential to be used for surveillance and routine clinical microbiology. However, in clinical microbiology settings and especially for certain species and antimicrobial agent combinations, further developments in AMR gene databases are needed to ensure higher concordance between in silico predictions and expected phenotypic AMR profiles.
4 citations
TL;DR: In this article , the authors evaluated the ability of three promising Next Generation Sequencing (NGS) methods to sequence diverse NoV in environmental or food BMS and human stool samples, and evaluated the sensitivity, reproducibility, repeatability and selectivity of metabarcoding, capture-based metagenomics and long amplicon sequencing, considering representative NoV strains from genogroup I and II, and the impact of BMS matrix.
Abstract: Bivalve molluscan shellfish (BMS) contamination with gastroenteritis viruses such as norovirus (NoV) is recognized as a significant public health risk worldwide. These foodborne epidemics are characterized by very low viral concentrations in the implicated foods, and by diverse viruses or multiple NoV strains originating from human sewage, resulting in different strains (co-)infecting the consumers. Next-generation sequencing (NGS) offers promising means to describe the diversity of strains present in BMS or to retrace transmission chains in outbreak settings, but their sensitivity and reproducibility remained to be assessed for this application. In this work, we evaluated the ability of three promising NGS methods to sequence diverse NoV in environmental or food BMS and human stool samples. Using laboratory-prepared samples of known NoV composition, we evaluated the sensitivity, reproducibility, repeatability and selectivity of metabarcoding, capture-based metagenomics and long amplicon sequencing, considering representative NoV strains from genogroup I and II, and the impact of the BMS matrix. The metabarcoding, with separate amplification of polymerase and capsid gene segments followed by Illumina sequencing, was the most sensitive method. It was applied to a selection of 212 BMS samples collected through the European Commission’s NoV baseline survey (BLS), demonstrating a high diversity of NoV sequences found in the BMS which reflect the diversity of NoV strains circulating in the European human population. Besides, a capture-based metagenomics with enrichment of vertebrate viruses was applied on 20 of these BLS samples as well as 20 BMS linked to outbreaks and 10 related human stool samples. In BMS, it yielded NoV sequences compatible with the genomes identified in stool samples, but they were too short to allow definitive confirmation of the infection source. The present report describes NGS methods, including the bioinformatic pipelines, applicable to molecular epidemiology of NoV in BMS, their current limitations and expected outcomes.
4 citations
TL;DR: This collection of sequencing reads from 214,095 metagenomic samples from the European Nucleotide Archive is another step towards establishing global surveillance of AMR and can serve as a resource for further research into the environmental spread and dynamic changes of ARGs.
Abstract: The growing threat of antimicrobial resistance (AMR) calls for new epidemiological surveillance methods, as well as a deeper understanding of how antimicrobial resistance genes (ARGs) have been transmitted around the world. The large pool of sequencing data available in public repositories provides an excellent resource for monitoring the temporal and spatial dissemination of AMR in different ecological settings. However, only a limited number of research groups globally have the computational resources to analyze such data. We retrieved 442 Tbp of sequencing reads from 214,095 metagenomic samples from the European Nucleotide Archive (ENA) and aligned them using a uniform approach against ARGs and 16S/18S rRNA genes. Here, we present the results of this extensive computational analysis and share the counts of reads aligned. Over 6.76∙108 read fragments were assigned to ARGs and 3.21∙109 to rRNA genes, where we observed distinct differences in both the abundance of ARGs and the link between microbiome and resistome compositions across various sampling types. This collection is another step towards establishing global surveillance of AMR and can serve as a resource for further research into the environmental spread and dynamic changes of ARGs.
3 citations
TL;DR: In this article , the authors describe key drivers by combining viral genome sequences with epidemiological data and possible factors of spread into phylodynamic models, and suggest future surveillance activities should be strengthened in Central and Southeast European countries, and enhanced monitoring should be targeted to areas with high agriculture activities.
Abstract: Spread and emergence of West Nile virus (WNV) in Europe have been very different from those observed in North America. Here, we describe key drivers by combining viral genome sequences with epidemiological data and possible factors of spread into phylodynamic models. WNV in Europe has greater lineage diversity than other regions of the world, suggesting repeated introductions and local amplification. Among the six lineages found in Europe, WNV-2a is predominant, has spread to at least 14 countries and evolved into two major co-circulating clusters (A and B). Both of these seem to originate from regions of Central Europe. Viruses of Cluster A emerged earlier and have spread towards the west of Europe with higher genetic diversity. Amongst multiple drivers, high agriculture activities were associated with both spread direction and velocity. Our study suggests future surveillance activities should be strengthened in Central Europe and Southeast European countries, and enhanced monitoring should be targeted to areas with high agriculture activities.
2 citations
TL;DR: In this paper , the authors presented the first global gene catalog of cattle fecal microbiomes, a proxy of the large intestine microbiomes from 436 metagenomes from six countries and provided a global insight into the phylogenetic relationships and the metabolic potential of a rich yet understudied bacterial community and suggest that it provides valuable services to the host.
Abstract: The large intestine is a colonization site of beneficial microbes complementing the nutrition of cattle but also of zoonotic and animal pathogens. Here, we present the first global gene catalog of cattle fecal microbiomes, a proxy of the large intestine microbiomes, from 436 metagenomes from six countries.Phylogenomics suggested that the reconstructed genomes and their close relatives form distinct branches and produced clustering patterns that were reminiscent of the metagenomics sample origin. Bacterial taxa had distinct metabolic profiles, and complete metabolic pathways were mainly linked to carbohydrates and amino acids metabolism. Dietary changes affected the community composition, diversity, and potential virulence. However, predicted enzymes, which were part of complete metabolic pathways, remained present, albeit encoded by different microbes.Our findings provide a global insight into the phylogenetic relationships and the metabolic potential of a rich yet understudied bacterial community and suggest that it provides valuable services to the host. However, we tentatively infer that members of that community are not irreplaceable, because similar to previous findings, symbionts of complex bacterial communities of mammals are expendable if there are substitutes that can perform the same task. Video Abstract.
TL;DR: Macrolide resistance genes were the most common in the sewage plasmidomes and were found in the largest number of unique plasmids, highlighting a potential reservoir of antibiotic resistance for these pathogens from around the globe.
Abstract: Antimicrobial resistance is a global threat to human health, as it inhibits our ability to treat infectious diseases. This study utilizes sewage water plasmidomes to identify plasmid-derived features and highlights antimicrobial resistance genes, particularly macrolide resistance genes, as abundant in sewage water plasmidomes in Firmicutes and Acinetobacter hosts. ABSTRACT Sewage water from around the world contains an abundance of short plasmids, several of which harbor antimicrobial resistance genes (ARGs). The global dynamics of plasmid-derived antimicrobial resistance and functions are only starting to be unveiled. Here, we utilized a previously created data set of 159,332 assumed small plasmids from 24 different global sewage samples. The detailed phylogeny, as well as the interplay between their protein domains, ARGs, and predicted bacterial host genera, were investigated to understand sewage plasmidome dynamics globally. A total of 58,429 circular elements carried genes encoding plasmid-related features, and MASH distance analyses showed a high degree of diversity. A single (yet diverse) cluster of 520 predicted Acinetobacter plasmids was predominant among the European sewage water. Our results suggested a prevalence of plasmid-backbone gene combinations over others. This could be related to selected bacterial genera that act as bacterial hosts. These combinations also mirrored the geographical locations of the sewage samples. Our functional domain network analysis identified three groups of plasmids. However, these backbone domains were not exclusive to any given group, and Acinetobacter was the dominant host genus among the theta-replicating plasmids, which contained a reservoir of the macrolide resistance gene pair msr(E) and mph(E). Macrolide resistance genes were the most common in the sewage plasmidomes and were found in the largest number of unique plasmids. While msr(E) and mph(E) were limited to Acinetobacter, erm(B) was disseminated among a range of Firmicutes plasmids, including Staphylococcus and Streptococcus, highlighting a potential reservoir of antibiotic resistance for these pathogens from around the globe. IMPORTANCE Antimicrobial resistance is a global threat to human health, as it inhibits our ability to treat infectious diseases. This study utilizes sewage water plasmidomes to identify plasmid-derived features and highlights antimicrobial resistance genes, particularly macrolide resistance genes, as abundant in sewage water plasmidomes in Firmicutes and Acinetobacter hosts. The emergence of macrolide resistance in these bacteria suggests that macrolide selective pressure exists in sewage water and that the resident bacteria can readily acquire macrolide resistance via small plasmids.
TL;DR: In this paper , the authors investigated the correlation between ARG abundances in a collection of 214,095 metagenomic datasets and found that more ARGs correlated with each other in human and animal sampling origins than in soil and water environments.
Abstract: The rapid spread of antimicrobial resistance (AMR) is a threat to global health, and the nature of co-occurring antimicrobial resistance genes (ARGs) may cause collateral AMR effects once antimicrobial agents are used. Therefore, it is essential to identify which pairs of ARGs co-occur. Given the wealth of NGS data available in public repositories, we have investigated the correlation between ARG abundances in a collection of 214,095 metagenomic datasets. Using more than 6.76·108 read fragments aligned to ARGs to infer pairwise correlation coefficients, we found that more ARGs correlated with each other in human and animal sampling origins than in soil and water environments. Furthermore, we showed that the correlations serve as risk profiles of resistance co-occurring to critically important antimicrobials. Using these profiles, we found several key ARGs indirectly but strongly selecting for ARGs of critical importance, such as tetracycline ARGs correlating with most forms of resistances. In conclusion, this study highlights the important ARG players indirectly involved in shaping the resistomes of various environments that can serve as monitoring targets in AMR surveillance programs.
TL;DR: The findings show a relatively high proportion of plasmid-carrying isolates suggesting selection pressure due to antibiotic use in the hospital, and co-occurrence of antibiotic resistance and virulence genes in clinical isolates is a public health relevant problem needing attention.
Abstract: Plasmids are infectious double stranded DNA molecules that are found within bacteria. Horizontal gene transfer promotes successful spread of different types of plasmids within or among bacteria species, making their detection an important task for guiding clinical treatment. We used whole genome sequenced data to determine the prevalence of plasmid replicons in clinical bacterial isolates, the presence of resistance and virulence genes in plasmids, and the relationship between resistance and virulence genes within each plasmid. All bacterial sequences were de novo assembled using Unicycler before extraction of plasmids. Assembly graphs were submitted to Gplas+plasflow for plasmid prediction. The predicted plasmid components were validated using PlasmidFinder. A total of 159 (56.2%) out of 283 bacterial isolates were found to carry plasmids, with E. coli, K. pneumoniae and S. aureusbeing the most prevalent plasmid carriers. A total of 27 (87.1%) combined plasmids were found to carry both resistance and virulence genes compared to 4 (12.9%) single plasmids. No statistically significant correlation was found between the number of antimicrobial resistance and virulence genes in plasmids (r =-0.25, p > 0.05). Our findings show a relatively high proportion of plasmid-carrying isolates suggesting selection pressure due to antibiotic use in the hospital. Co-occurrence of antibiotic resistance and virulence genes in clinical isolates is a public health relevant problem needing attention.
TL;DR: This collection of sequencing reads from 214,095 metagenomic samples from the European Nucleotide Archive is another step towards establishing a global surveillance of AMR and can serve as a resource for further research into the environmental spread and dynamic changes of ARGs.
Abstract: The growing threat of antimicrobial resistance (AMR) calls for new epidemiological surveillance methods, as well as a deeper understanding of how antimicrobial resistance genes (ARGs) have transmitted around the world. The large pool of sequencing data available in public repositories provides an excellent resource for monitoring the temporal and spatial dissemination of AMR in different ecological settings. However, only a limited number of research groups globally have the computational resources allowing analyses of such data. We retrieved 442 Tbp of sequencing reads from 214,095 metagenomic samples from the European Nucleotide Archive (ENA) and aligned them using a uniform approach against ARGs and 16S/18S rRNA genes. Here, we present the results of this extensive computational analysis and share the counts of reads aligned. Over 6.76 · 108 read fragments were assigned to ARGs and 3.21 · 109 to rRNA genes, where we observed distinct differences in both the abundance of ARGs and the link between microbiome and resistome compositions across various sampling types. This collection is another step towards establishing a global surveillance of AMR and can serve as a resource for further research into the environmental spread and dynamic changes of ARGs.
TL;DR: In this paper , a random forest classifier was used to identify the source of bacterial chromosomal, plasmid, and bacteriophage sequences from hundreds of bacterial species, which can impact the composition of microbiomes by providing selective advantages to their hosts.
Abstract: Extra-chromosomal genes encoding antimicrobial resistance, metal resistance, and virulence provide selective advantages for bacterial survival under stress conditions and pose serious threats to human and animal health. These accessory genes can impact the composition of microbiomes by providing selective advantages to their hosts. ABSTRACT High-throughput genome sequencing technologies enable the investigation of complex genetic interactions, including the horizontal gene transfer of plasmids and bacteriophages. However, identifying these elements from assembled reads remains challenging due to genome sequence plasticity and the difficulty in assembling complete sequences. In this study, we developed a classifier, using random forest, to identify whether sequences originated from bacterial chromosomes, plasmids, or bacteriophages. The classifier was trained on a diverse collection of 23,211 chromosomal, plasmid, and bacteriophage sequences from hundreds of bacterial species. In order to adapt the classifier to incomplete sequences, each complete sequence was subsampled into 5,000 nucleotide fragments and further subdivided into k-mers. This three-class classifier succeeded in identifying chromosomes, plasmids, and bacteriophages using k-mer distributions of complete and partial genome sequences, including simulated metagenomic scaffolds with minimum performance of 0.939 area under the receiver operating characteristic curve (AUC). This classifier, implemented as SourceFinder, has been made available as an online web service to help the community with predicting the chromosomal, plasmid, and bacteriophage sources of assembled bacterial sequence data (https://cge.food.dtu.dk/services/SourceFinder/). IMPORTANCE Extra-chromosomal genes encoding antimicrobial resistance, metal resistance, and virulence provide selective advantages for bacterial survival under stress conditions and pose serious threats to human and animal health. These accessory genes can impact the composition of microbiomes by providing selective advantages to their hosts. Accurately identifying extra-chromosomal elements in genome sequence data are critical for understanding gene dissemination trajectories and taking preventative measures. Therefore, in this study, we developed a random forest classifier for identifying the source of bacterial chromosomal, plasmid, and bacteriophage sequences.
TL;DR: In this article , the authors implemented a workflow for the detection of parasites from metagenomics data, and employed stringent cut off criteria to limit false positive detections, which could serve as a one-for-all untargeted approach for pathogen detection, including bacteria, viruses and parasites.
Abstract: Despite a yearly death toll of up to one million people due to parasite-related infections, parasites are still neglected in genomics research. While there is progress in the detection of bacteria and viruses using metagenomics in the context of infectious diseases, there are still challenges in metagenomics-based detection of parasites. Here, we implement a workflow for the detection of parasites from metagenomics data. We employ stringent cut off criteria to limit false positive detections. We analysed a total of 7.120 metagenomics samples of which 359 originated from gut microbiomes of livestock (pigs and chicken) from nine countries, and 6.761 from gut microbiomes of humans (adults and infants) from 25 countries. Five parasite-related genera were detected in livestock, of which Blastocystis sp. was detected in 71% of all pig herds and Eimeria in 83% of all chicken flocks. Distinct gut bacterial taxa were associated with Blastocystis sp. abundance in pigs. Nine parasite-related genera were detected in humans. Blastocystis sp. subtypes ST1, ST2, and ST3 were detected in all countries, and ST3 was most predominant. A higher overall prevalence of Blastocystis sp. was observed in low-income countries as compared to high-income countries, and a higher diversity of Blastocystis subtypes (ST1, ST2, ST3, ST4, ST6, ST7, ST8) was detected in high-income countries as compared to low-income countries. The prevalence of Blastocystis sp. in infant gut microbiome samples was lower as compared to adults. Overall, metagenomics-based analysis may be a promising tool for parasite detection from complex microbiome samples in clinical and veterinary medicine. Metagenomics could become the preferred method for parasite detection for a wide range of biological samples. Current parasite detection methods often rely on microscopic examination of the sample or using specific PCR. Metagenomics-based analyses may allow for a faster and more convenient way of detecting parasites in humans and animals, as this approach could serve as a one-for-all untargeted approach for pathogen detection, including bacteria, viruses, and parasites.
TL;DR: This is the first detection of jumbophages in faeces, which were investigated independently of culture, host identification, and size, and based solely on the genome sequence, which opens up opportunities for characterisation of novel in silico phages in vivo from a broad range of gut microbiomes.
Abstract: Microbial communities have huge impacts on their ecosystems and local environments spanning from marine and soil communities to the mammalian gut. Bacteriophages (phages) are important drivers of population control and diversity in the community, but our understanding of complex microbial communities is halted by biased detection techniques. Metagenomics have provided a method of novel phage discovery independent of in vitro culturing techniques and have revealed a large proportion of understudied phages. Here, five large phage genomes, that were previously assembled in silico from pig faecal metagenomes, are detected and observed directly in their natural environment using a modified phageFISH approach, and combined with methods to decrease bias against large phages. These phages are uncultured with unknown hosts. The specific phages were detected by PCR and fluorescent in situ hybridisation in their original faecal samples as well as across other faecal samples. Co-localisation of bacterial signals and phage signals allowed detection of the different stages of phage life cycle. All phages displayed examples of early infection, advanced infection, burst, and free phages. To our knowledge, this is the first detection of jumbophages in faeces, which were investigated independently of culture, host identification, and size, and based solely on the genome sequence. This approach opens up opportunities for characterisation of novel in silico phages in vivo from a broad range of gut microbiomes.