Increasing the coverage of a metapopulation consensus genome by iterative read mapping and assembly

Metagenomic studies of the Gouda cheese microbiota and starter cultures are scarce. During the present study, short-read metagenomic sequencing (Illumina) was applied on 89 Gouda cheese and processed milk samples, which have been investigated before concerning their metabolite and taxonomic composition, the latter applying amplicon-based, high-throughput sequencing (HTS) of the full-length 16S rRNA gene. Selected samples were additionally investigated using long-read metagenomic sequencing (Oxford Nanopore Technologies, ONT). Whereas the species identified by amplicon-based HTS and metagenomic sequencing were identical, the relative abundances of the major species differed significantly. Lactococcus cremoris was more abundant in the metagenomics-based taxonomic analysis compared to the amplicon-based one, whereas the opposite was true for the non-starter lactic acid bacteria (NSLAB). This discrepancy was related to a higher fragmentation of the lactococcal DNA compared with the DNA of other species when applying ONT. Possibly, a higher fragmentation was linked with a higher percentage of dead or metabolically inactive cells, suggesting that full-length 16S rRNA gene amplicon-based HTS might give a more accurate view on active cells. Further, fungi were not abundantly present in the Gouda cheeses examined, whereas about 2% of the metagenomic sequence reads was related to phages, with higher relative abundances in the cheese rinds and long-ripened cheeses. Intraspecies differences found by short-read metagenomic sequencing were in agreement with the amplicon sequence variants obtained previously, confirming the ability of full-length 16S rRNA gene amplicon-based HTS to reach a taxonomic assignment below species level. Metagenome-assembled genomes (MAGs) were retrieved for 15 species, among which the starter cultures Lc. cremoris and Lactococcus lactis and the NSLAB Lacticaseibacillus paracasei, Loigolactobacillus rennini, and Tetragenococcus halophilus, although obtaining MAGs from Lc. cremoris and Lc. lactis was more challenging because of a high intraspecies diversity and high similarity between these species. Long-read metagenomic sequencing could not improve the retrieval of lactococcal MAGs, but, overall, MAGs obtained by long-read metagenomic sequencing solely were superior compared with those obtained by short-read metagenomic sequencing solely, reaching a high-quality draft status of the genomes.

BackgroundGenome assembly into chromosomes facilitates several analyses including cytogenetics, genomics and phylogenetics. Despite rapid development in bioinformatics, however, assembly beyond scaffolds remains challenging, especially in species without closely related well-assembled and available reference genomes. So far, four draft genomes of Rangifer tarandus (caribou or reindeer, a circumpolar distributed cervid species) have been published, but none with chromosome-level assembly. This emblematic northern species is of high interest in ecological studies and conservation since most populations are declining.ResultsWe have designed specific probes based on Oligopaint FISH technology to upgrade the latest published reindeer and caribou chromosome-level genomes. Using this oligonucleotide-based method, we found six mis-assembled scaffolds and physically mapped 68 of the largest scaffolds representing 78% of the most recent R. tarandus genome assembly. Combining physical mapping and comparative genomics, it was possible to document chromosomal evolution among Cervidae and closely related bovids.ConclusionsOur results provide validation for the current chromosome-level genome assembly as well as resources to use chromosome banding in studies of Rangifer tarandus.

Metagenomic sequencing has greatly improved our ability to profile the composition of environmental and host-associated microbial communities. However, the dependency of most methods on reference genomes, which are currently unavailable for a substantial fraction of microbial species, introduces estimation biases. We present an updated and functionally extended tool based on universal (i.e., reference-independent), phylogenetic marker gene (MG)-based operational taxonomic units (mOTUs) enabling the profiling of >7700 microbial species. As more than 30% of them could not previously be quantified at this taxonomic resolution, relative abundance estimates based on mOTUs are more accurate compared to other methods. As a new feature, we show that mOTUs, which are based on essential housekeeping genes, are demonstrably well-suited for quantification of basal transcriptional activity of community members. Furthermore, single nucleotide variation profiles estimated using mOTUs reflect those from whole genomes, which allows for comparing microbial strain populations (e.g., across different human body sites).

<title>Abstract</title> <bold>Background</bold> : Obtaining high precision while maintaining high recall is an ongoing problem for metagenomic taxonomic classification in microbial ecology research. <bold/> Parameter adjustments can achieve this in simulated samples, but in real samples –especially from environments like marine and soil– the proportion of classified reads drops sharply with precision increases. We therefore suggest verification of metagenomic taxonomic classifications obtained from a tool like Kraken by mapping their assigned reads to reference genomes to assess genomic coverage. <bold>Results</bold> : In simulations, filtering the identified species to only those with ³0.5% reference genome coverage removed 99.7% of false-positive taxa. Applying this method to samples from real datasets requires a more nuanced approach that considers sequencing depth, whether the samples are high- or low-microbial biomass, and database completeness with respect to the sampled environment. Nevertheless, we show that clinically relevant Kraken-identified taxa such as <italic>Helicobacter pylori</italic> identified in human stool samples lack any reads mapping to their reference genome and are likely false positives driven by contaminating phage sequences within reference genomes. Similarly, in human blood and tumour datasets, only 18 and 11 species, respectively, have ³1% reference genome coverage and likely represent sample collection or sequencing contaminants. Marine and soil samples pose additional challenges due to lower representation in reference databases, leading to low nucleotide identity between sequenced reads and reference genomes and similarity only at higher taxonomic ranks. <bold>Conclusions</bold> : We recommend genome coverage checking to researchers in all fields of microbial ecology and provide an open-source pipeline on Github (GeCoCheck): https://github.com/R-Wright-1/GeCoCheck.

Whole genome sequencing (WGS) is a key tool in identifying and characterising disease-associated bacteria across clinical, agricultural, and environmental contexts. One increasingly common use of genomic and metagenomic sequencing is in identifying the type and range of antimicrobial resistance (AMR) genes present in bacterial isolates in order to make predictions regarding their AMR phenotype. However, there are a large number of alternative bioinformatics software and pipelines available, which can lead to dissimilar results. It is, therefore, vital that researchers carefully evaluate their genomic and metagenomic AMR analysis methods using a common dataset. To this end, as part of the Microbial Bioinformatics Hackathon and Workshop 2021, a ‘gold standard’ reference genomic and simulated metagenomic dataset was generated containing raw sequence reads mapped against their corresponding reference genome from a range of 174 potentially pathogenic bacteria. These datasets and their accompanying metadata are freely available for use in benchmarking studies of bacteria and their antimicrobial resistance genes and will help improve tool development for the identification of AMR genes in complex samples.

Motivation: For most research approaches, genome analyses are dependent on the existence of a high quality genome reference assembly. However, the local accuracy of an assembly remains difficult to assess and improve. The gEVAL browser allows the user to interrogate an assembly in any region of the genome by comparing it to different datasets and evaluating the concordance. These analyses include: a wide variety of sequence alignments, comparative analyses of multiple genome assemblies, and consistency with optical and other physical maps. gEVAL highlights allelic variations, regions of low complexity, abnormal coverage, and potential sequence and assembly errors, and offers strategies for improvement. Although gEVAL focuses primarily on sequence integrity, it can also display arbitrary annotation including from Ensembl or TrackHub sources. We provide gEVAL web sites for many human, mouse, zebrafish and chicken assemblies to support the Genome Reference Consortium, and gEVAL is also downloadable to enable its use for any organism and assembly.Availability and Implementation: Web Browser: http://geval.sanger.ac.uk, Plugin: http://wchow.github.io/wtsi-geval-plugin.Contact: kj2@sanger.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

IntroductionIn 2021, a type 2 vaccine-derived poliovirus (VDPV2) was isolated from the stool of a patient with acute flaccid paralysis (AFP) admitted to Spain from Senegal. A virological investigation was conducted to characterize and trace the origin of VDPV2.MethodsWe used an unbiased metagenomic approach for the whole-genome sequencing of VDPV2 from the stool (pre-treated with chloroform) and from the poliovirus-positive supernatant. Phylogenetic analyses and molecular epidemiological analyses relying on the Bayesian Markov Chain Monte Carlo methodology were used to determine the geographical origin and estimate the date of the initiating dose of the oral poliovirus vaccine for the imported VDPV2.ResultsWe obtained a high percentage of viral reads per total reads mapped to the poliovirus genome (69.5% for pre-treated stool and 75.8% for isolate) with a great depth of sequencing coverage (5,931 and 11,581, respectively) and complete genome coverage (100%). The two key attenuating mutations in the Sabin 2 strain had reverted (A481G in the 5’UTR and Ile143Thr in VP1). In addition, the genome had a recombinant structure between type-2 poliovirus and an unidentified non-polio enterovirus-C (NPEV-C) strain with a crossover point in the protease-2A genomic region. VP1 phylogenetic analysis revealed that this strain is closely related to VDPV2 strains circulating in Senegal in 2021. According to Bayesian phylogenetics, the most recent common ancestor of the imported VDPV2 could date back 2.6 years (95% HPD: 1.7–3.7) in Senegal. We suggest that all VDPV2s circulating in 2020–21 in Senegal, Guinea, Gambia, and Mauritania have an ancestral origin in Senegal estimated around 2015. All 50 stool samples from healthy case contacts collected in Spain (n = 25) and Senegal (n = 25) and four wastewater samples collected in Spain were poliovirus negative.DiscussionBy using a whole-genome sequencing protocol with unbiased metagenomics from the clinical sample and viral isolate with high sequence coverage, efficiency, and throughput, we confirmed the classification of VDPV as a circulating type. The close genomic linkage with strains from Senegal was consistent with their classification as imported. Given the scarce number of complete genome sequences for NPEV-C in public databases, this protocol could help expand poliovirus and NPEV-C sequencing capacity worldwide.

Tuberculosis remains a major global health problem. Laboratory diagnostic methods that allow effective, early detection of cases are central to management of tuberculosis in the individual patient and in the community. Since the 1880s, laboratory diagnosis of tuberculosis has relied primarily on microscopy and culture. However, microscopy fails to provide species- or lineage-level identification and culture-based workflows for diagnosis of tuberculosis remain complex, expensive, slow, technically demanding and poorly able to handle mixed infections. We therefore explored the potential of shotgun metagenomics, sequencing of DNA from samples without culture or target-specific amplification or capture, to detect and characterise strains from the Mycobacterium tuberculosis complex in smear-positive sputum samples obtained from The Gambia in West Africa. Eight smear- and culture-positive sputum samples were investigated using a differential-lysis protocol followed by a kit-based DNA extraction method, with sequencing performed on a benchtop sequencing instrument, the Illumina MiSeq. The number of sequence reads in each sputum-derived metagenome ranged from 989,442 to 2,818,238. The proportion of reads in each metagenome mapping against the human genome ranged from 20% to 99%. We were able to detect sequences from the M. tuberculosis complex in all eight samples, with coverage of the H37Rv reference genome ranging from 0.002X to 0.7X. By analysing the distribution of large sequence polymorphisms (deletions and the locations of the insertion element IS6110) and single nucleotide polymorphisms (SNPs), we were able to assign seven of eight metagenome-derived genomes to a species and lineage within the M. tuberculosis complex. Two metagenome-derived mycobacterial genomes were assigned to M. africanum, a species largely confined to West Africa; the others that could be assigned belonged to lineages T, H or LAM within the clade of “modern” M. tuberculosis strains. We have provided proof of principle that shotgun metagenomics can be used to detect and characterise M. tuberculosis sequences from sputum samples without culture or target-specific amplification or capture, using an accessible benchtop-sequencing platform, the Illumina MiSeq, and relatively simple DNA extraction, sequencing and bioinformatics protocols. In our hands, sputum metagenomics does not yet deliver sufficient depth of coverage to allow sequence-based sensitivity testing; it remains to be determined whether improvements in DNA extraction protocols alone can deliver this or whether culture, capture or amplification steps will be required. Nonetheless, we can foresee a tipping point when a unified automated metagenomics-based workflow might start to compete with the plethora of methods currently in use in the diagnostic microbiology laboratory.

Clubroot, caused by Plasmodiophora brassicae, is an important disease on Brassica species worldwide. A clubroot resistance gene, Rcr1, with efficacy against pathotype 3 of P. brassicae, was previously mapped to chromosome A03 of B. rapa in pak choy cultivar “Flower Nabana”. In the current study, resistance to pathotypes 2, 5 and 6 was shown to be associated with Rcr1 region on chromosome A03. Bulked segregant RNA sequencing was performed and short read sequences were assembled into 10 chromosomes of the B. rapa reference genome v1.5. For the resistant (R) bulks, a total of 351.8 million (M) sequences, 30,836.5 million bases (Mb) in length, produced 120-fold coverage of the reference genome. For the susceptible (S) bulks, 322.9 M sequences, 28,216.6 Mb in length, produced 109-fold coverage. In total, 776.2 K single nucleotide polymorphisms (SNPs) and 122.2 K insertion / deletion (InDels) in R bulks and 762.8 K SNPs and 118.7 K InDels in S bulks were identified; each chromosome had about 87% SNPs and 13% InDels, with 78% monomorphic and 22% polymorphic variants between the R and S bulks. Polymorphic variants on each chromosome were usually below 23%, but made up 34% of the variants on chromosome A03. There were 35 genes annotated in the Rcr1 target region and variants were identified in 21 genes. The numbers of poly variants differed significantly among the genes. Four out of them encode Toll-Interleukin-1 receptor / nucleotide-binding site / leucine-rich-repeat proteins; Bra019409 and Bra019410 harbored the higher numbers of polymorphic variants, which indicates that they are more likely candidates of Rcr1. Fourteen SNP markers in the target region were genotyped using the Kompetitive Allele Specific PCR method and were confirmed to associate with Rcr1. Selected SNP markers were analyzed with 26 recombinants obtained from a segregating population consisting of 1587 plants, indicating that they were completely linked to Rcr1. Nine SNP markers were used for marker-assisted introgression of Rcr1 into B. napus canola from B. rapa, with 100% accuracy in this study.

High‐throughput genotyping in estimating genetic resources and detecting pathogens in aquaculture

The human microbiome refers to the community of microorganisms, including prokaryotes, viruses, and microbial eukaryotes, that populate the human body. The National Institutes of Health launched an initiative that focuses on describing the diversity of microbial species that are associated with health and disease. The first phase of this initiative includes the sequencing of hundreds of microbial reference genomes, coupled to metagenomic sequencing from multiple body sites. Here we present results from an initial reference genome sequencing of 178 microbial genomes. From 547,968 predicted polypeptides that correspond to the gene complement of these strains, previously unidentified ("novel") polypeptides that had both unmasked sequence length greater than 100 amino acids and no BLASTP match to any nonreference entry in the nonredundant subset were defined. This analysis resulted in a set of 30,867 polypeptides, of which 29,987 (approximately 97%) were unique. In addition, this set of microbial genomes allows for approximately 40% of random sequences from the microbiome of the gastrointestinal tract to be associated with organisms based on the match criteria used. Insights into pan-genome analysis suggest that we are still far from saturating microbial species genetic data sets. In addition, the associated metrics and standards used by our group for quality assurance are presented.

The mapping of DNA-protein interactions is crucial for a full understanding of transcriptional regulation. Chromatin-immunoprecipitation followed by massively parallel sequencing (ChIP-seq) has become the standard technique for analyzing these interactions on a genome-wide scale. We have developed a software system called CASSys (ChIP-seq data Analysis Software System) spanning all steps of ChIP-seq data analysis. It supersedes the laborious application of several single command line tools. CASSys provides functionality ranging from quality assessment and -control of short reads, over the mapping of reads against a reference genome (readmapping) and the detection of enriched regions (peakdetection) to various follow-up analyses. The latter are accessible via a state-of-the-art web interface and can be performed interactively by the user. The follow-up analyses allow for flexible user defined association of putative interaction sites with genes, visualization of their genomic context with an integrated genome browser, the detection of putative binding motifs, the identification of over-represented Gene Ontology-terms, pathway analysis and the visualization of interaction networks. The system is client-server based, accessible via a web browser and does not require any software installation on the client side. To demonstrate CASSys's functionality we used the system for the complete data analysis of a publicly available Chip-seq study that investigated the role of the transcription factor estrogen receptor-α in breast cancer cells.

The surfperches (family Embiotocidae) are a unique group of mostly marine fishes whose phylogenetic position within the Ovalentaria clade (Percomorpha) is still unresolved. As a result of their viviparity and lack of a dispersive larval stage, surfperches are an excellent model for the study of speciation, gene flow, and local adaptation in the ocean. They are also the target of an immensely popular recreational fishery. Very few high-quality molecular resources, however, are available for this group and only for a single species. Here, we describe a highly complete reference genome for the kelp surfperch, Brachyistius frenatus, assembled using a combination of short-read (Illumina, ~47× coverage) and long-read (Oxford Nanopore Technologies, ~27× coverage) sequencing. The 596 Mb assembly has a completeness level of 98.1% (BUSCO), a contig N50 of 2.6 Mb (n = 56), and a contig N90 of 406.6 kb (n = 293). Comparative analysis revealed a high level of synteny between B. frenatus and its close relative, Embiotoca jacksoni. This assembly will serve as a valuable molecular resource upon which future evolutionary dynamics research will build, such as the investigation of local adaptation and the genomic potential for climate adaptation in wild populations.

Cyanobacterial blooms: A player in the freshwater environmental resistome with public health relevance?

BackgroundAdvances in next-generation sequencing (NGS) technology has provided us with an opportunity to analyze and evaluate the rich microbial communities present in all natural environments. The shorter reads obtained from the shortgun technology has paved the way for determining the taxonomic profile of a community by simply aligning the reads against the available reference genomes. While several computational methods are available for taxonomic profiling at the genus- and species-level, none of these methods are effective at the strain-level identification due to the increasing difficulty in detecting variation at that level. Here, we present MetaID, an alignment-free n-gram based approach that can accurately identify microorganisms at the strain level and estimate the abundance of each organism in a sample, given a metagenomic sequencing dataset.ResultsMetaID is an n-gram based method that calculates the profile of unique and common n-grams from the dataset of 2,031 prokaryotic genomes and assigns weights to each n-gram using a scoring function. This scoring function assigns higher weightage to the n-grams that appear in fewer genomes and vice versa; thus, allows for effective use of both unique and common n-grams for species identification. Our 10-fold cross-validation results on a simulated dataset show a remarkable accuracy of 99.7% at the strain-level identification of the organisms in gut microbiome. We also demonstrated that our model shows impressive performance even by using only 25% or 50% of the genome sequences for modeling. In addition to identification of the species, our method can also estimate the relative abundance of each species in the simulated metagenomic samples. The generic approach employed in this method can be applied for accurate identification of a wide variety of microbial species (viruses, prokaryotes and eukaryotes) present in any environmental sample.ConclusionsThe proposed scoring function and approach is able to accurately identify and estimate the entire taxa in any metagenomic community. The weights assigned to the common n-grams by our scoring function are precisely calibrated to match the reads up to the strain level. Our multipronged validation tests demonstrate that MetaID is sufficiently robust to accurately identify and estimate the abundance of each taxon in any natural environment even when using incomplete or partially sequenced genomes.