A comparison of short-read, HiFi long-read, and hybrid strategies for genome-resolved metagenomics.

Shotgun metagenomics enables the reconstruction of complex microbial communities at a high level of detail. Such an approach can be conducted using both short-read and long-read sequencing data, as well as a combination of both. To assess the pros and cons of these different approaches, we used 22 fecal DNA extracts collected weekly for 11 weeks from two respective lab mice to study seven performance metrics over four combinations of sequencing depth and technology: (i) 20 Gbp of Illumina short-read data, (ii) 40 Gbp of short-read data, (iii) 20 Gbp of PacBio HiFi long-read data, and (iv) 40 Gbp of hybrid (20 Gbp of short-read +20 Gbp of long-read) data. No strategy was best for all metrics; instead, each one excelled across different metrics. The long-read approach yielded the best assembly statistics, with the highest N50 and lowest number of contigs. The 40 Gbp short-read approach yielded the highest number of refined bins. Finally, the hybrid approach yielded the longest assemblies and the highest mapping rate to the bacterial genomes. Our results suggest that while long-read sequencing significantly improves the quality of reconstructed bacterial genomes, it is more expensive and requires deeper sequencing than short-read approaches to recover a comparable amount of reconstructed genomes. The most optimal strategy is study-specific and depends on how researchers assess the trade-off between the quantity and quality of recovered genomes.IMPORTANCEMice are an important model organism for understanding the gut microbiome. When studying these gut microbiomes using DNA techniques, researchers can choose from technologies that use short or long DNA reads. In this study, we perform an extensive benchmark between short- and long-read DNA sequencing for studying mice gut microbiomes. We find that no one approach was best for all metrics and provide information that can help guide researchers in planning their experiments.

Gut content metabarcoding of specialized feeders is not a replacement for environmental DNA assays of seawater in reef environments.

In tropical marine ecosystems, the coral-based diet of benthic-feeding reef fishes provides a window into the composition and health of coral reefs. In this study, for the first time, we compare multi-assay metabarcoding sequences of environmental DNA (eDNA) isolated from seawater and partially digested gut items from an obligate corallivore butterflyfish (Chaetodon lunulatus) resident to coral reef sites in the South China Sea. We specifically tested the proportional and statistical overlap of the different approaches (seawater vs gut content metabarcoding) in characterizing eukaryotic community composition on coral reefs. Based on 18S and ITS2 sequence data, which differed in their taxonomic sensitivity, we found that gut content detections were only partially representative of the eukaryotic communities detected in the seawater based on low levels of taxonomic overlap (3 to 21%) and significant differences between the sampling approaches. Overall, our results indicate that dietary metabarcoding of specialized feeders can be complimentary to, but is no replacement for, more comprehensive environmental DNA assays of reef environments that might include the processing of different substrates (seawater, sediment, plankton) or traditional observational surveys. These molecular assays, in tandem, might be best suited to highly productive but cryptic oceanic environments (kelp forests, seagrass meadows) that contain an abundance of organisms that are often small, epiphytic, symbiotic, or cryptic.

Mammals show distinct functional gut microbiome dynamics to identical series of environmental stressors.

IMPORTANCE: In our manuscript, we report the first interspecific comparative study about the plasticity of the gut microbiota. We conducted a captivity experiment that exposed wild-captured mammals to a series of environmental challenges over 45 days. We characterized their gut microbial communities using genome-resolved metagenomics and modeled how the taxonomic, phylogenetic, and functional microbial dynamics varied across a series of disturbances in both species. Our results indicate that the intrinsic properties (e.g., diversity and functional redundancy) of microbial communities coupled with physiological attributes (e.g., thermal plasticity) of hosts shape the taxonomic, phylogenetic, and functional response of gut microbiomes to environmental stressors, which might influence their contribution to the acclimation and adaptation capacity of animal hosts.

Enriching captivity conditions with natural elements does not prevent the loss of wild-like gut microbiota but shapes its compositional variation in two small mammals.

As continued growth in gut microbiota studies in captive and model animals elucidates the importance of their role in host biology, further pursuit of how to retain a wild-like microbial community is becoming increasingly important to obtain representative results from captive animals. In this study, we assessed how the gut microbiota of two wild-caught small mammals, namely Crocidura russula (Eulipotyphla, insectivore) and Apodemus sylvaticus (Rodentia, omnivore), changed when bringing them into captivity. We analyzed fecal samples of 15 A. sylvaticus and 21 C. russula, immediately after bringing them into captivity and 5 weeks later, spread over two housing treatments: a "natural" setup enriched with elements freshly collected from nature and a "laboratory" setup with sterile artificial elements. Through sequencing of the V3-V4 region of the 16S recombinant RNA gene, we found that the initial microbial diversity dropped during captivity in both species, regardless of treatment. Community composition underwent a change of similar magnitude in both species and under both treatments. However, we did observe that the temporal development of the gut microbiome took different trajectories (i.e., changed in different directions) under different treatments, particularly in C. russula, suggesting that C. russula may be more susceptible to environmental change. The results of this experiment do not support the use of microbially enriched environments to retain wild-like microbial diversities and compositions, yet show that specific housing conditions can significantly affect the drift of microbial communities under captivity.

Whole-Genome Resources and Species-Level Taxonomic Validation of 89 Plant-Pathogenic Xanthomonas Strains Isolated from Various Host Plants.

Bacterial spot disease caused by Xanthomonas spp. is a global threat to tomato and pepper plants. A recent classification of these pathogens indicated the need for a diverse dataset of whole-genome resources. We report whole-genome resources of 89 Xanthomonas strains isolated from Canada (n = 44), the United States (n = 29), Argentina (n = 4), Brazil (n = 3), Costa Rica (n = 3), New Zealand (n = 1), Australia (n = 1), Mexico (n = 1), Taiwan (n = 1), Thailand (n = 1), and unknown (n = 1). Of these strains, 48 were previously identified to species-level based on nongenome-based approaches while 41 strains were classified only at the genus level. The average coverage of the sequencing reads was 103×. The draft genome sizes ranged from 4.53 to 5.46 Mbp with a G + C content of 63.53 to 67.78% and comprised 4,233-5,178 protein-coding sequences. Using average nucleotide identity (ANI) and genome-based DNA-DNA hybridization (gDDH) values, the taxonomic classifications were validated for 38 of the 48 strains previously assigned to species level using other methods. Ten strains previously identified as Xanthomonas campestris, X. axonopodis, X. vasicola, and X. arboricola were incorrectly assigned, and new species-level delineations are proposed. Data from ANI, gDDH, and pangenome phylogeny of shared protein families were used to assign the 41 strains, previously identified only to genus level, into five distinct species: X. euvesicatoria (pv. euvesicatoria or pv. perforans), X. hortorum pv. gardneri, X. vesicatoria, X. campestris, and X. arboricola. These 89 whole-genome sequences of Xanthomonas strains, the majority (49.4%) of which are from Canada, could be useful resources in our understanding of the global population structure and evolution of these pathogens.

Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli.

The increasing prevalence of antimicrobial resistance (AMR) in Campylobacter spp. is a global concern. This study evaluated the use of whole-genome sequencing (WGS) to predict AMR in Campylobacter jejuni and C. coli. A panel of 271 isolates recovered from Canadian poultry was used to compare AMR genotype to antimicrobial susceptibility testing (AST) results (azithromycin, ciprofloxacin, erythromycin, gentamicin, tetracycline, florfenicol, nalidixic acid, telithromycin, and clindamycin). The presence of antibiotic resistance genes (ARGs) was determined for each isolate using five computational approaches to evaluate the effect of: ARG screening software, input data (i.e., raw reads, draft genome assemblies), genome coverage and genome assembly software. Overall, concordance between the genotype and phenotype was influenced by the computational pipelines, level of genome coverage and the type of ARG but not by input data. For example, three of the pipelines showed a 99% agreement between detection of a tet(O) gene and tetracycline resistance, whereas agreement between the detection of tet(O) and TET resistance was 98 and 93% for two pipelines. Overall, higher levels of genome coverage were needed to reliably detect some ARGs; for example, at 15X coverage a tet(O) gene was detected in >70% of the genomes, compared to <60% of the genomes for bla(OXA). No genes associated with florfenicol or gentamicin resistance were found in the set of strains included in this study, consistent with AST results. Macrolide and fluoroquinolone resistance was associated 100% with mutations in the 23S rRNA (A2075G) and gyrA (T86I) genes, respectively. A lower association between a A2075G 23S rRNA gene mutation and resistance to clindamycin and telithromycin (92.8 and 78.6%, respectively) was found. While WGS is an effective approach to predicting AMR in Campylobacter, this study demonstrated the impact that computational pipelines, genome coverage and the genes can have on the reliable identification of an AMR genotype.

Climate-assisted persistence of tropical fish vagrants in temperate marine ecosystems.

Rising temperatures and extreme climate events are propelling tropical species into temperate marine ecosystems, but not all species can persist. Here, we used the heatwave-driven expatriation of tropical Black Rabbitfish (Siganus fuscescens) to the temperate environments of Western Australia to assess the ecological and evolutionary mechanisms that may entail their persistence. Population genomic assays for this rabbitfish indicated little genetic differentiation between tropical residents and vagrants to temperate environments due to high migration rates, which were likely enhanced by the marine heatwave. DNA metabarcoding revealed a diverse diet for this species based on phytoplankton and algae, as well as an ability to feed on regional resources, including kelp. Irrespective of future climate scenarios, these macroalgae-consuming vagrants may self-recruit in temperate environments and further expand their geographic range by the year 2100. This expansion may compromise the health of the kelp forests that form Australia's Great Southern Reef. Overall, our study demonstrates that projected favourable climate conditions, continued large-scale genetic connectivity between populations, and diet versatility are key for tropical range-shifting fish to establish in temperate ecosystems.

In Search of a Soil Moisture Content Simulation Model: Mechanistic and Data Mining Approach Based on TDR Method Results.

Soil moisture content simulation models have continuously been an important research objective. In particular, the comparisons of the performance of different model types deserve proper attention. Therefore, the quality of selected physically-based and statistical models was analyzed utilizing the data from the Time Domain Reflectometry technique. An E-Test measurement system was applied with the reflectogram interpreted into soil volumetric moisture content by proper calibration equations. The gathered data facilitated to calibrate the physical model of Deardorff and establish parameters of: support vector machines, multivariate adaptive regression spline, and boosted trees model. The general likelihood uncertainty estimation revealed the sensitivity of individual model parameters. As it was assumed, a simple structure of statistical models was achieved but no direct physical interpretation of their parameters, contrary to a physically-based method. The TDR technique proved useful for the calibration of different soil moisture models and a satisfactory quality for their future exploitation.

Holo-Omics: Integrated Host-Microbiota Multi-omics for Basic and Applied Biological Research.

From ontogenesis to homeostasis, the phenotypes of complex organisms are shaped by the bidirectional interactions between the host organisms and their associated microbiota. Current technology can reveal many such interactions by combining multi-omic data from both hosts and microbes. However, exploring the full extent of these interactions requires careful consideration of study design for the efficient generation and optimal integration of data derived from (meta)genomics, (meta)transcriptomics, (meta)proteomics, and (meta)metabolomics. In this perspective, we introduce the holo-omic approach that incorporates multi-omic data from both host and microbiota domains to untangle the interplay between the two. We revisit the recent literature on biomolecular host-microbe interactions and discuss the implementation and current limitations of the holo-omic approach. We anticipate that the application of this approach can contribute to opening new research avenues and discoveries in biomedicine, biotechnology, agricultural and aquacultural sciences, nature conservation, as well as basic ecological and evolutionary research.

Marine environmental DNA: Approaches, applications, and opportunities.

Environmental DNA (eDNA) is increasingly being used to document species distributions and habitat use in marine systems, with much of the recent effort focused on leveraging advances in next-generation DNA sequencing to assess and track biodiversity across taxonomic groups. Environmental DNA offers a number of important advantages over traditional survey techniques, including non-invasive sampling, sampling where traditional approaches are impractical or inefficient (e.g. deep oceans), reduced cost, and increased detection sensitivity. However, eDNA applications are currently limited because of an insufficient understanding of the influence of sample source, analytical approach, and marker type on eDNA detections. Because approaches vary considerably among eDNA studies, we present a summary of the current state of the field and emerging best practices. The impact of observed variation in rates of eDNA production, persistence, and transport are also discussed and future research needs are highlighted with the goal of expanding eDNA applications, including the development of statistical models to improve the predictability of eDNA detection and quantification.

Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance.

Whole-genome sequencing (WGS) is used increasingly in public-health laboratories for typing and characterizing foodborne pathogens. To evaluate the performance of existing bioinformatic tools for in silico prediction of antimicrobial resistance (AMR) and serotypes of Salmonella enterica, WGS-based genotype predictions were compared with the results of traditional phenotyping assays. A total of 111 S. enterica isolates recovered from a Canadian baseline study on broiler chicken conducted in 2012-2013 were selected based on phenotypic resistance to 15 different antibiotics and isolates were subjected to WGS. Both SeqSero2 and SISTR accurately determined S. enterica serotypes, with full matches to laboratory results for 87.4 and 89.2% of isolates, respectively, and partial matches for the remaining isolates. Antimicrobial resistance genes (ARGs) were identified using several bioinformatics tools including the Comprehensive Antibiotic Resistance Database - Resistance Gene Identifier (CARD-RGI), Center for Genomic Epidemiology (CGE) ResFinder web tool, Short Read Sequence Typing for Bacterial Pathogens (SRST2 v 0.2.0), and k-mer alignment method (KMA v 1.17). All ARG identification tools had ≥ 99% accuracy for predicting resistance to all antibiotics tested except streptomycin (accuracy 94.6%). Evaluation of ARG detection in assembled versus raw-read WGS data found minimal observable differences that were gene- and coverage- dependent. Where initial phenotypic results indicated isolates were sensitive, yet ARGs were detected, repeat AMR testing corrected discrepancies. All tools failed to find resistance-determining genes for one gentamicin- and two streptomycin-resistant isolates. Further investigation found a single nucleotide polymorphism (SNP) in the nuoF coding region of one of the isolates which may be responsible for the observed streptomycin-resistant phenotype. Overall, WGS-based predictions of AMR and serotype were highly concordant with phenotype determination regardless of computational approach used.

ConFindr: rapid detection of intraspecies and cross-species contamination in bacterial whole-genome sequence data.

Whole-genome sequencing (WGS) of bacterial pathogens is currently widely used to support public-health investigations. The ability to assess WGS data quality is critical to underpin the reliability of downstream analyses. Sequence contamination is a quality issue that could potentially impact WGS-based findings; however, existing tools do not readily identify contamination from closely-related organisms. To address this gap, we have developed a computational pipeline, ConFindr, for detection of intraspecies contamination. ConFindr determines the presence of contaminating sequences based on the identification of multiple alleles of core, single-copy, ribosomal-protein genes in raw sequencing reads. The performance of this tool was assessed using simulated and lab-generated Illumina short-read WGS data with varying levels of contamination (0-20% of reads) and varying genetic distance between the designated target and contaminant strains. Intraspecies and cross-species contamination was reliably detected in datasets containing 5% or more reads from a second, unrelated strain. ConFindr detected intraspecies contamination with higher sensitivity than existing tools, while also being able to automatically detect cross-species contamination with similar sensitivity. The implementation of ConFindr in quality-control pipelines will help to improve the reliability of WGS databases as well as the accuracy of downstream analyses. ConFindr is written in Python, and is freely available under the MIT License at github.com/OLC-Bioinformatics/ConFindr.

DNA metabarcoding assays reveal a diverse prey assemblage for Mobula rays in the Bohol Sea, Philippines.

Diet studies provide base understanding of trophic structure and are a valuable initial step for many fields of marine ecology, including conservation and fisheries biology. Considerable complexity in marine trophic structure can exist due to the presence of highly mobile species with long life spans. Mobula rays are highly mobile, large, planktivorous elasmobranchs that are frequently caught either directly or as bycatch in fisheries, which, combined with their conservative life history strategy, makes their populations susceptible to decline in intensely fished regions. Effective management of these iconic and vulnerable species requires an understanding of the diets that sustain them, which can be difficult to determine using conventional sampling methods. We use three DNA metabarcode assays to identify 44 distinct taxa from the stomachs (n = 101) of four sympatric Mobula ray species (Mobula birostris, Mobula tarapacana, Mobula japanica, and Mobula thurstoni) caught over 3 years (2013-2015) in a direct fishery off Bohol in the Philippines. The diversity and incidence of bony fishes observed in ray diets were unprecedented. Nevertheless, rays showed dietary overlap, with krill (Euphausia) dominating their diet. Our results provide a more detailed assessment of sympatric ray diets than was previously described and reveal the complexity that can exist in food webs at critical foraging habitats.

Environmental DNA metabarcoding studies are critically affected by substrate selection.

Effective biomonitoring is critical for driving management outcomes that ensure long-term sustainability of the marine environment. In recent years, environmental DNA (eDNA), coupled with metabarcoding methodologies, has emerged as a promising tool for generating biotic surveys of marine ecosystems, including those under anthropogenic pressure. However, more empirical data are needed on how to best implement eDNA field sampling approaches to maximize their utility for each specific application. The effect of the substrate chosen for eDNA sampling on the diversity of marine taxa detected by DNA metabarcoding has not yet been systematically analysed, despite aquatic systems being those most commonly targeted for eDNA studies. We investigated the effect of four commonly used eDNA substrates to explore taxonomic diversity: (a) surface water, (b) marine sediment, (c) settlement plates and (d) planktonic tows. With a focus on coastal ports, 332 eDNA samples from Australia (Indian and Southern oceans) and Kazakhstan (Caspian Sea) were collected and analysed by multi-assay DNA metabarcoding. Across study locations, between 30% and 52% of eukaryotic families detected were unique to a particular substrate and <6% of families were found in all four substrates. Taxonomic composition varied significantly depending on the substrate sampled implying that the suitability (and bias) of an eDNA substrate will depend on the focal taxa. These findings demonstrate that single substrate eDNA metabarcoding likely underestimates the total eukaryotic diversity. Future eDNA experimental design should consider incorporating multiple substrates or select substrate(s) best suited to the specific detection of target taxa.

Draft Genome Sequences of Salmonella enterica subsp. enterica Serovar Berta ATCC 8392 and a Nalidixic Acid-Resistant Isolate of This Strain.

ITALIC! Salmonella entericasubspecies ITALIC! entericaserovar Berta has been isolated in multiple animal species and has been implicated in human disease. Here, we report a 4.7-Mbp draft genome sequence of ITALIC! S. entericaserovar Berta (ATCC strain 8392) and a nalidixic acid-resistant isolate derived from this strain.

Draft Whole-Genome Sequences of Escherichia fergusonii Strains Isolated from Beef Trim (GTA-EF02), Ground Beef (GTA-EF03), and Chopped Kale (GTA-EF04).

Escherichia fergusoniiis a Gram-negative, rod-shaped, non-spore-forming member of theEnterobacteriaceaefamily and is a bacterium with both biotechnological applications and implication in human clinical disease. Here, we report the draft genome sequences of three isolates ofE. fergusoniifrom beef trim (GTA-EF02), ground beef (GTA-EF03), and chopped kale (GTA-EF04).

Comparative Evaluation of Genomic and Laboratory Approaches for Determination of Shiga Toxin Subtypes in Escherichia coli.

The determination of Shiga toxin (ST) subtypes can be an important element in the risk characterization of foodborne ST-producing Escherichia coli (STEC) isolates for making risk management decisions. ST subtyping methods include PCR techniques based on electrophoretic or pyrosequencing analysis of amplicons and in silico techniques based on whole genome sequence analysis using algorithms that can be readily incorporated into bioinformatics analysis pipelines for characterization of isolates by their genetic composition. The choice of technique will depend on the performance characteristics of the method and an individual laboratory's access to specialized equipment or personnel. We developed two whole genome sequence-based ST subtyping tools: (i) an in silico PCR algorithm requiring genome assembly to replicate a reference PCR-based method developed by the Statens Serum Institut (SSI) and (ii) an assembly-independent routine in which raw sequencing results are mapped to a database of known ST subtype sequence variants (V-Typer). These tools were evaluated alongside the SSI reference PCR method and a recently described PCR-based pyrosequencing technique. The V-Typer method results corresponded closely with the reference method in the analysis of 67 STEC cultures obtained from a World Health Organization National Reference Laboratory. In contrast, the in silico PCR method failed to detect ST subtypes in several cases, a result which we attribute to assembly-induced errors typically encountered with repetitive gene sequences. The V-Typer can be readily integrated into bioinformatics protocols used in the identification and characterization of foodborne STEC isolates.

Genomic Tools for Customized Recovery and Detection of Foodborne Shiga Toxigenic Escherichia coli.

Genomic antimicrobial resistance (AMR) prediction tools have the potential to support foodborne illness outbreak investigations through their application in the analysis of bacterial genomes from causative strains. The AMR marker profile of a strain of interest, initially identified in outbreak-associated clinical samples, may serve as the basis for customization of selective enrichment media, facilitating its recovery from samples in a food safety investigation. Different possibilities for AMR analyses include the use of comprehensive AMR gene databases such as the Comprehensive Antibiotic Resistance Database, which can be mined with in-house bioinformatics alignment tools (e.g., Antimicrobial Resistance Marker Identifier), or publicly available tools based on clinically relevant acquired AMR gene databases (e.g., ResFinder). In combination with a previously reported pipeline (SigSeekr) designed to identify specific DNA sequences associated with a particular strain for its rapid identification by PCR, it should be possible to deploy custom recovery and identification tools for the efficient detection of priority pathogens such as Shiga toxigenic Escherichia coli (STEC) outbreak strains within the time frame of an active investigation. Using a laboratory STEC strain as a model, trimethoprim resistance identified by both Antimicrobial Resistance Marker Identifier and ResFinder was used as the basis for its selective recovery against a background of commensal E. coli bacteria in ground beef samples. Enrichment in modified tryptic soy broth containing trimethoprim greatly enhanced the recovery of low numbers of model strain cells inoculated in ground beef samples, as verified by the enumeration of colonies on plating media using a strain-specific PCR method to determine the recovery efficiency for the target strain. We discuss the relative merits of different AMR marker prediction tools for this purpose and describe how such tools can be utilized to good effect in a typical outbreak investigation scenario.

Draft Genome Sequence of Salmonella enterica subsp. enterica Serovar Mishmarhaemek Isolated from Bovine Feces.

Salmonella enterica subsp. enterica serovar Mishmarhaemek is a Gram-negative, non-spore-forming, rod-shaped bacterium implicated in human clinical disease. Here, we report a 4.8-Mbp draft genome sequence of a nalidixic acid-resistant isolate of S. serovar Mishmarhaemek.