A genomic epidemiological study shows that prevalence of antimicrobial resistance in Enterobacterales is associated with the livestock host, as well as antimicrobial usage

Enterobacterales from livestock are potentially important reservoirs for antimicrobial resistance (AMR) to pass through the food chain to humans, thereby increasing the AMR burden and affecting our ability to tackle infections. In this study 168 isolates from four genera of the order Enterobacterales, primarily Escherichia coli, were purified from livestock (cattle, pigs and sheep) faeces from 14 farms in the United Kingdom. Their genomes were resolved using long- and short-read sequencing to analyse AMR genes and their genetic context, as well as to explore the relationship between AMR burden and on-farm antimicrobial usage (AMU), in the three months prior to sampling. Although E. coli isolates were genomically diverse, phylogenetic analysis using a core-genome SNP tree indicated pig isolates to generally be distinct from sheep isolates, with cattle isolates being intermediates. Approximately 28 % of isolates harboured AMR genes, with the greatest proportion detected in pigs, followed by cattle then sheep; pig isolates also harboured the highest number of AMR genes per isolate. Although 90 % of sequenced isolates harboured diverse plasmids, only 11 % of plasmids (n=58 out of 522) identified contained AMR genes, with 91 % of AMR plasmids being from pig, 9 % from cattle and none from sheep isolates; these results indicated that pigs were a principle reservoir of AMR genes harboured by plasmids and likely to be involved in their horizontal transfer. Significant associations were observed between AMU (mg kg−1) and AMR. As both the total and the numbers of different antimicrobial classes used on-farm increased, the risk of multi-drug resistance (MDR) in isolates rose. However, even when AMU on pig farms was comparatively low, pig isolates had increased likelihood of being MDR; harbouring relatively more resistances than those from other livestock species. Therefore, our results indicate that AMR prevalence in livestock is not only influenced by recent AMU on-farm but also livestock-related factors, which can influence the AMR burden in these reservoirs and its plasmid mediated transmission

Environmental metabarcoding reveals contrasting belowground and aboveground fungal communities from poplar at a Hg phytomanagement site

Characterization of microbial communities in stressful conditions at a field level is rather scarce, especially when considering fungal communities from aboveground habitats. We aimed at characterizing fungal communities from different poplar habitats at a Hg-contaminated phytomanagement site by using Illumina-based sequencing, network analysis approach, and direct isolation of Hg-resistant fungal strains. The highest diversity estimated by the Shannon index was found for soil communities, which was negatively affected by soil Hg concentration. Among the significant correlations between soil operational taxonomic units (OTUs) in the co-occurrence network, 80% were negatively correlated revealing dominance of a pattern of mutual exclusion. The fungal communities associated with Populus roots mostly consisted of OTUs from the symbiotic guild, such as members of the Thelephoraceae, thus explaining the lowest diversity found for root communities. Additionally, root communities showed the highest network connectivity index, while rarely detected OTUs from the Glomeromycetes may have a central role in the root network. Unexpectedly high richness and diversity were found for aboveground habitats, compared to the root habitat. The aboveground habitats were dominated by yeasts from the Lalaria, Davidiella, and Bensingtonia genera, not detected in belowground habitats. Leaf and stem habitats were characterized by few dominant OTUs such as those from the Dothideomycete class producing mutual exclusion with other OTUs. Aureobasidium pullulans, one of the dominating OTUs, was further isolated from the leaf habitat, in addition to Nakazawaea populi species, which were found to be Hg resistant. Altogether, these findings will provide an improved point of reference for microbial research on inoculation-based programs of tailings dumps

Persistence of dissolved organic matter explained by molecular changes during its passage through soil

Dissolved organic matter affects fundamental biogeochemical processes in the soil such as nutrient cycling and organic matter storage. The current paradigm is that processing of dissolved organic matter converges to recalcitrant molecules (those that resist degradation) of low molecular mass and high molecular diversity through biotic and abiotic processes. Here we demonstrate that the molecular composition and properties of dissolved organic matter continuously change during soil passage and propose that this reflects a continual shifting of its sources. Using ultrahigh-resolution mass spectrometry and nuclear magnetic resonance spectroscopy, we studied the molecular changes of dissolved organic matter from the soil surface to 60 cm depth in 20 temperate grassland communities in soil type Eutric Fluvisol. Applying a semi-quantitative approach, we observed that plant-derived molecules were first broken down into molecules containing a large proportion of low-molecular-mass compounds. These low-molecular-mass compounds became less abundant during soil passage, whereas larger molecules, depleted in plant-related ligno-cellulosic structures, became more abundant. These findings indicate that the small plant-derived molecules were preferentially consumed by microorganisms and transformed into larger microbial-derived molecules. This suggests that dissolved organic matter is not intrinsically recalcitrant but instead persists in soil as a result of simultaneous consumption, transformation and formation

A genomic epidemiological study shows that prevalence of antimicrobial resistance in Enterobacterales is associated with the livestock host, as well as antimicrobial usagee

Enterobacterales from livestock are potentially important reservoirs for antimicrobial resistance (AMR) to pass through the food chain to humans, thereby increasing the AMR burden and affecting our ability to tackle infections. In this study 168 isolates from four genera of the order Enterobacterales , primarily Escherichia coli , were purified from livestock (cattle, pigs and sheep) faeces from 14 farms in the United Kingdom. Their genomes were resolved using long- and short-read sequencing to analyse AMR genes and their genetic context, as well as to explore the relationship between AMR burden and on-farm antimicrobial usage (AMU), in the three months prior to sampling. Although E. coli isolates were genomically diverse, phylogenetic analysis using a core-genome SNP tree indicated pig isolates to generally be distinct from sheep isolates, with cattle isolates being intermediates. Approximately 28 % of isolates harboured AMR genes, with the greatest proportion detected in pigs, followed by cattle then sheep; pig isolates also harboured the highest number of AMR genes per isolate. Although 90 % of sequenced isolates harboured diverse plasmids, only 11 % of plasmids (n=58 out of 522) identified contained AMR genes, with 91 % of AMR plasmids being from pig, 9 % from cattle and none from sheep isolates; these results indicated that pigs were a principle reservoir of AMR genes harboured by plasmids and likely to be involved in their horizontal transfer. Significant associations were observed between AMU (mg kg−1) and AMR. As both the total and the numbers of different antimicrobial classes used on-farm increased, the risk of multi-drug resistance (MDR) in isolates rose. However, even when AMU on pig farms was comparatively low, pig isolates had increased likelihood of being MDR; harbouring relatively more resistances than those from other livestock species. Therefore, our results indicate that AMR prevalence in livestock is not only influenced by recent AMU on-farm but also livestock-related factors, which can influence the AMR burden in these reservoirs and its plasmid mediated transmission

The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

Background Shotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (~ 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, ‘ResPipe’. Results Taxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve &lt; 1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike of Thermus thermophilus DNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment. Conclusions Sequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available (https://gitlab.com/hsgweon/ResPipe).</p

Population-level faecal metagenomic profiling as a tool to predict antimicrobial resistance in Enterobacterales isolates causing invasive infections: An exploratory study across Cambodia, Kenya, and the UK

Background Antimicrobial resistance (AMR) in Enterobacterales is a global health threat. Capacity for individual-level surveillance remains limited in many countries, whilst population-level surveillance approaches could inform empiric antibiotic treatment guidelines. Methods In this exploratory study, a novel approach to population-level prediction of AMR in Enterobacterales clinical isolates using metagenomic (Illumina) profiling of pooled DNA extracts from human faecal samples was developed and tested. Taxonomic and AMR gene profiles were used to derive taxonomy-adjusted population-level AMR metrics. Bayesian modelling, and model comparison based on cross-validation, were used to evaluate the capacity of each metric to predict the number of resistant Enterobacterales invasive infections at a population-level, using available bloodstream/cerebrospinal fluid infection data. Findings Population metagenomes comprised samples from 177, 157, and 156 individuals in Kenya, the UK, and Cambodia, respectively, collected between September 2014 and April 2016. Clinical data from independent populations included 910, 3356 and 197 bacterial isolates from blood/cerebrospinal fluid infections in Kenya, the UK and Cambodia, respectively (samples collected between January 2010 and May 2017). Enterobacterales were common colonisers and pathogens, and faecal taxonomic/AMR gene distributions and proportions of antimicrobial-resistant Enterobacterales infections differed by setting. A model including terms reflecting the metagenomic abundance of the commonest clinical Enterobacterales species, and of AMR genes known to either increase the minimum inhibitory concentration (MIC) or confer clinically-relevant resistance, had a higher predictive performance in determining population-level resistance in clinical Enterobacterales isolates compared to models considering only AMR gene information, only taxonomic information, or an intercept-only baseline model (difference in expected log predictive density compared to best model, estimated using leave-one-out cross-validation: intercept-only model = -223 [95% credible interval (CI): -330,-116]; model considering only AMR gene information = -186 [95% CI: -281,-91]; model considering only taxonomic information = -151 [95% CI: -232,-69]). Interpretation Whilst our findings are exploratory and require validation, intermittent metagenomics of pooled samples could represent an effective approach for AMR surveillance and to predict population-level AMR in clinical isolates, complementary to ongoing development of laboratory infrastructures processing individual samples

Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes

Illumina sequencing allows rapid, cheap and accurate whole genome bacterial analyses, but short reads (<300 bp) do not usually enable complete genome assembly. Long-read sequencing greatly assists with resolving complex bacterial genomes, particularly when combined with short-read Illumina data (hybrid assembly). However, it is not clear how different long-read sequencing methods affect hybrid assembly accuracy. Relative automation of the assembly process is also crucial to facilitating high-throughput complete bacterial genome reconstruction, avoiding multiple bespoke filtering and data manipulation steps. In this study, we compared hybrid assemblies for 20 bacterial isolates, including two reference strains, using Illumina sequencing and long reads from either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences (PacBio) sequencing platforms. We chose isolates from the family Enterobacteriaceae, as these frequently have highly plastic, repetitive genetic structures, and complete genome reconstruction for these species is relevant for a precise understanding of the epidemiology of antimicrobial resistance. We de novo assembled genomes using the hybrid assembler Unicycler and compared different read processing strategies, as well as comparing to long-read-only assembly with Flye followed by short-read polishing with Pilon. Hybrid assembly with either PacBio or ONT reads facilitated high-quality genome reconstruction, and was superior to the long-read assembly and polishing approach evaluated with respect to accuracy and completeness. Combining ONT and Illumina reads fully resolved most genomes without additional manual steps, and at a lower consumables cost per isolate in our setting. Automated hybrid assembly is a powerful tool for complete and accurate bacterial genome assembly