Benchmarking hybrid assembly approaches for genomic analyses of bacterial pathogens using Illumina and Oxford Nanopore sequencing

Genome Analysis of Japanese Yersinia pseudotuberculosis Strains Isolated From Kawasaki Disease Patients and Other Sources and Their Phylogenetic Positions in the Global Y. pseudotuberculosis Population

Yersinia pseudotuberculosis (Ypt) is a gram-negative bacterium that infects both humans and animals primarily through fecal‒oral transmission. While Ypt causes acute gastroenteritis in humans, an association with Kawasaki disease (KD), a disease that primarily affects infants and young children and causes multisystemic vasculitis, has also been suspected. Although KD represents a significant health concern worldwide, the highest annual incidence rate is reported in Japan. Previously, a geographical origin-dependent population structure of Ypt comprising the Asian, transitional, and European clades was proposed. However, genomic data on KD-associated Ypt strains is currently unavailable. In this study, to analyze the phylogenetic and genomic features of KD-associated strains, we determined the whole-genome sequences of 35 Japanese Ypt strains, including 11 KD-associated strains, and constructed a genome set (n = 204) representing the global population of Ypt by adding publicly available Ypt genomes. In a phylogenetic analysis, all sequenced Japanese strains, including the KD-associated strains, belonged to the Asian clade, which appeared to be the ancestral clade of Ypt, and the KD-associated strains belonged to multiple lineages in this clade. Strains from patients with Far East scarlet-like fever (FESLF), a KD-related disease, also belonged to the Asian clade. Moreover, no KD strain-specific genes were identified in pan-genome-wide association study analyses. Notably, however, the gene encoding a superantigen called Yersinia pseudotuberculosis-derived mitogen (YPM) showed a distribution pattern highly biased to the Asian clade. Although further studies are needed, our results suggest that Asian clade strains may have a greater potential to trigger KD.

Plaseval: a framework for comparing and evaluating plasmid detection tools

BACKGROUND

Plasmids play a major role in the transfer of antimicrobial resistance (AMR) genes among bacteria via horizontal gene transfer. The identification of plasmids in short-read assemblies is a challenging problem and a very active research area. Plasmid binning aims at detecting, in a draft genome assembly, groups (bins) of contigs likely to originate from the same plasmid. Several methods for plasmid binning have been developed recently, such as PlasBin-flow, HyAsP, gplas, MOB-suite, and plasmidSPAdes. This motivates the problem of evaluating the performances of plasmid binning methods, either against a given ground truth or between them.

RESULTS

We describe PlasEval, a novel method aimed at comparing the results of plasmid binning tools. PlasEval computes a dissimilarity measure between two sets of plasmid bins, that can originate either from two plasmid binning tools, or from a plasmid binning tool and a ground truth set of plasmid bins. The PlasEval dissimilarity accounts for the contig content of plasmid bins, the length of contigs and is repeat-aware. Moreover, the dissimilarity score computed by PlasEval is broken down into several parts, that allows to understand qualitative differences between the compared sets of plasmid bins. We illustrate the use of PlasEval by benchmarking four recently developed plasmid binning tools-PlasBin-flow, HyAsP, gplas, and MOB-recon-on a data set of 53 E. coli bacterial genomes.

CONCLUSION

Analysis of the results of plasmid binning methods using PlasEval shows that their behaviour varies significantly. PlasEval can be used to decide which specific plasmid binning method should be used for a specific dataset. The disagreement between different methods also suggests that the problem of plasmid binning on short-read contigs requires further research. We believe that PlasEval can prove to be an effective tool in this regard. PlasEval is publicly available at https://github.com/acme92/PlasEval.

Simple, reference-independent assessment to empirically guide correction and polishing of hybrid microbial community metagenomic assembly

Hybrid metagenomic assembly of microbial communities, leveraging both long- and short-read sequencing technologies, is becoming an increasingly accessible approach, yet its widespread application faces several challenges. High-quality references may not be available for assembly accuracy comparisons common for benchmarking, and certain aspects of hybrid assembly may benefit from dataset-dependent, empiric guidance rather than the application of a uniform approach. In this study, several simple, reference-free characteristics-particularly coding gene content and read recruitment profiles-were hypothesized to be reliable indicators of assembly quality improvement during iterative error-fixing processes. These characteristics were compared to reference-dependent genome- and gene-centric analyses common for microbial community metagenomic studies. Two laboratory-scale bioreactors were sequenced with short- and long-read platforms, and assembled with commonly used software packages. Following long read assembly, long read correction and short read polishing were iterated up to ten times to resolve errors. These iterative processes were shown to have a substantial effect on gene- and genome-centric community compositions. Simple, reference-free assembly characteristics, specifically changes in gene fragmentation and short read recruitment, were robustly correlated with advanced analyses common in published comparative studies, and therefore are suitable proxies for hybrid metagenome assembly quality to simplify the identification of the optimal number of correction and polishing iterations. As hybrid metagenomic sequencing approaches will likely remain relevant due to the low added cost of short-read sequencing for differential coverage binning or the ability to access lower abundance community members, it is imperative that users are equipped to estimate assembly quality prior to downstream analyses.

A metagenomic approach to demystify the anaerobic digestion black box and achieve higher biogas yield: a review

The increasing reliance on fossil fuels and the growing accumulation of organic waste necessitates the exploration of sustainable energy alternatives. Anaerobic digestion (AD) presents one such solution by utilizing secondary biomass to produce biogas while reducing greenhouse gas emissions. Given the crucial role of microbial activity in anaerobic digestion, a deeper understanding of the microbial community is essential for optimizing biogas production. While metagenomics has emerged as a valuable tool for unravelling microbial composition and providing insights into the functional potential in biodigestion, it falls short of interpreting the functional and metabolic interactions, limiting a comprehensive understanding of individual roles in the community. This emphasizes the significance of expanding the scope of metagenomics through innovative tools that highlight the often-overlooked, yet crucial, role of microbiota in biomass digestion. These tools can more accurately elucidate microbial ecological fitness, shared metabolic pathways, and interspecies interactions. By addressing current limitations and integrating metagenomics with other omics approaches, more accurate predictive techniques can be developed, facilitating informed decision-making to optimize AD processes and enhance biogas yields, thereby contributing to a more sustainable future.

ESKAPE pathogens: antimicrobial resistance, epidemiology, clinical impact and therapeutics

The rise of antibiotic resistance and a dwindling antimicrobial pipeline have been recognized as emerging threats to public health. The ESKAPE pathogens - Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp. - were initially identified as critical multidrug-resistant bacteria for which effective therapies were rapidly needed. Now, entering the third decade of the twenty-first century, and despite the introduction of several new antibiotics and antibiotic adjuvants, such as novel β-lactamase inhibitors, these organisms continue to represent major therapeutic challenges. These bacteria share several key biological features, including adaptations for survival in the modern health-care setting, diverse methods for acquiring resistance determinants and the dissemination of successful high-risk clones around the world. With the advent of next-generation sequencing, novel tools to track and combat the spread of these organisms have rapidly evolved, as well as renewed interest in non-traditional antibiotic approaches. In this Review, we explore the current epidemiology and clinical impact of this important group of bacterial pathogens and discuss relevant mechanisms of resistance to recently introduced antibiotics that affect their use in clinical settings. Furthermore, we discuss emerging therapeutic strategies needed for effective patient care in the era of widespread antimicrobial resistance.

A Broad Spectrum Lasso Peptide Antibiotic Targeting the Bacterial Ribosome

Lasso peptides, biologically active molecules with a distinct structurally constrained knotted fold, are natural products belonging to the class of ribosomally-synthesized and posttranslationally modified peptides (RiPPs). Lasso peptides act upon several bacterial targets, but none have been reported to inhibit the ribosome, one of the main antibiotic targets in the bacterial cell. Here, we report the identification and characterization of the lasso peptide antibiotic, lariocidin (LAR), and its internally cyclized derivative, lariocidin B (LAR-B), produced by Paenabacillussp. M2, with broad-spectrum activity against many bacterial pathogens. We show that lariocidins inhibit bacterial growth by binding to the ribosome and interfering with protein synthesis. Structural, genetic, and biochemical data show that lariocidins bind at a unique site in the small ribosomal subunit, where they interact with the 16S rRNA and aminoacyl-tRNA, inhibiting translocation and inducing miscoding. LAR is unaffected by common resistance mechanisms, has a low propensity for generating spontaneous resistance, shows no human cell toxicity, and has potent in vivo activity in a mouse model of Acinetobacter baumannii infection. Our finding of the first ribosome-targeting lasso peptides uncovers new routes toward discovering alternative protein synthesis inhibitors and offers a new chemical scaffold for developing much-needed antibacterial drugs.

Comparisons of genome assembly tools for characterization of Mycobacterium tuberculosis genomes using hybrid sequencing technologies

Background

Next-generation sequencing of Mycobacterium tuberculosis, the infectious agent causing tuberculosis, is improving the understanding of genomic diversity of circulating lineages and strain-types, and informing knowledge of drug resistance mutations. An increasingly popular approach to characterizing M. tuberculosis genomes (size: 4.4 Mbp) and variants (e.g., single nucleotide polymorphisms (SNPs)) involves the de novo assembly of sequence data.

Methods

We compared the performance of genome assembly tools (Unicycler, RagOut, and RagTag) on sequence data from nine drug resistant M. tuberculosis isolates (multi-drug (MDR) n = 1; pre-extensively-drug (pre-XDR) n = 8) generated using Illumina HiSeq, Oxford Nanopore Technology (ONT) PromethION, and PacBio platforms.

Results

Our investigation found that Unicycler-based assemblies had significantly higher genome completeness (~98.7%; p values = 0.01) compared to other assembler tools (RagOut = 98.6%, and RagTag = 98.6%). The genome assembly sizes (bp) across isolates and sequencers based on RagOut was significantly longer (p values < 0.001) (4,418,574 ± 8,824 bp) than Unicycler and RagTag assemblies (Unicycler = 4,377,642 ± 55,257 bp, and RagTag = 4,380,711 ± 51,164 bp). RagOut-based assemblies had the fewest contigs (~32) and the longest genome size (4,418,574 bp; vs. H37Rv reference size 4,411,532 bp) and therefore were chosen for downstream analysis. Pan-genome analysis of Illumina and PacBio hybrid assemblies revealed the greatest number of detected genes (4,639 genes; H37Rv reference contains 3,976 genes), while Illumina and ONT hybrid assemblies produced the highest number of SNPs. The number of genes from hybrid assemblies with ONT and PacBio long-reads (mean: 4,620 genes) was greater than short-read assembly alone (4,478 genes). All nine RagOut hybrid genome assemblies detected known mutations in genes associated with MDR-TB and pre-XDR-TB.

Conclusions

Unicycler software performed the best in terms of achieving contiguous genomes, whereas RagOut improved the quality of Unicycler's genome assemblies by providing a longer genome size. Overall, our approach has demonstrated that short-read and long-read hybrid assembly can provide a more complete genome assembly than short-read assembly alone by detecting pan-genomes and more genes, including IS6110, and SNPs.

From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology

Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.

Benchmarking short and long read polishing tools for nanopore assemblies: achieving near-perfect genomes for outbreak isolates

BACKGROUND

Oxford Nanopore provides high throughput sequencing platforms able to reconstruct complete bacterial genomes with 99.95% accuracy. However, even small levels of error can obscure the phylogenetic relationships between closely related isolates. Polishing tools have been developed to correct these errors, but it is uncertain if they obtain the accuracy needed for the high-resolution source tracking of foodborne illness outbreaks.

RESULTS

We tested 132 combinations of assembly and short- and long-read polishing tools to assess their accuracy for reconstructing the genome sequences of 15 highly similar Salmonella enterica serovar Newport isolates from a 2020 onion outbreak. While long-read polishing alone improved accuracy, near perfect accuracy (99.9999% accuracy or ~ 5 nucleotide errors across the 4.8 Mbp genome, excluding low confidence regions) was only obtained by pipelines that combined both long- and short-read polishing tools. Notably, medaka was a more accurate and efficient long-read polisher than Racon. Among short-read polishers, NextPolish showed the highest accuracy, but Pilon, Polypolish, and POLCA performed similarly. Among the 5 best performing pipelines, polishing with medaka followed by NextPolish was the most common combination. Importantly, the order of polishing tools mattered i.e., using less accurate tools after more accurate ones introduced errors. Indels in homopolymers and repetitive regions, where the short reads could not be uniquely mapped, remained the most challenging errors to correct.

CONCLUSIONS

Short reads are still needed to correct errors in nanopore sequenced assemblies to obtain the accuracy required for source tracking investigations. Our granular assessment of the performance of the polishing pipelines allowed us to suggest best practices for tool users and areas for improvement for tool developers.

Advancing metagenome-assembled genome-based pathogen identification: unraveling the power of long-read assembly algorithms in Oxford Nanopore sequencing

Oxford Nanopore sequencing is one of the high-throughput sequencing technologies that facilitates the reconstruction of metagenome-assembled genomes (MAGs). This study aimed to assess the potential of long-read assembly algorithms in Oxford Nanopore sequencing to enhance the MAG-based identification of bacterial pathogens using both simulated and mock communities. Simulated communities were generated to mimic those on fresh spinach and in surface water. Long reads were produced using R9.4.1+SQK-LSK109 and R10.4 + SQK-LSK112, with 0.5, 1, and 2 million reads. The simulated bacterial communities included multidrug-resistant Salmonella enterica serotypes Heidelberg, Montevideo, and Typhimurium in the fresh spinach community individually or in combination, as well as multidrug-resistant Pseudomonas aeruginosa in the surface water community. Real data sets of the ZymoBIOMICS HMW DNA Standard were also studied. A bioinformatic pipeline (MAGenie, freely available at https://github.com/jackchen129/MAGenie) that combines metagenome assembly, taxonomic classification, and sequence extraction was developed to reconstruct draft MAGs from metagenome assemblies. Five assemblers were evaluated based on a series of genomic analyses. Overall, Flye outperformed the other assemblers, followed by Shasta, Raven, and Unicycler, while Canu performed least effectively. In some instances, the extracted sequences resulted in draft MAGs and provided the locations and structures of antimicrobial resistance genes and mobile genetic elements. Our study showcases the viability of utilizing the extracted sequences for precise phylogenetic inference, as demonstrated by the consistent alignment of phylogenetic topology between the reference genome and the extracted sequences. R9.4.1+SQK-LSK109 was more effective in most cases than R10.4+SQK-LSK112, and greater sequencing depths generally led to more accurate results.IMPORTANCEBy examining diverse bacterial communities, particularly those housing multiple Salmonella enterica serotypes, this study holds significance in uncovering the potential of long-read assembly algorithms to improve metagenome-assembled genome (MAG)-based pathogen identification through Oxford Nanopore sequencing. Our research demonstrates that long-read assembly stands out as a promising avenue for boosting precision in MAG-based pathogen identification, thus advancing the development of more robust surveillance measures. The findings also support ongoing endeavors to fine-tune a bioinformatic pipeline for accurate pathogen identification within complex metagenomic samples.

Bacterial dynamics of the plastisphere microbiome exposed to sub-lethal antibiotic pollution

BACKGROUND

Antibiotics and microplastics are two major aquatic pollutants that have been associated to antibiotic resistance selection in the environment and are considered a risk to human health. However, little is known about the interaction of these pollutants at environmental concentrations and the response of the microbial communities in the plastisphere to sub-lethal antibiotic pollution. Here, we describe the bacterial dynamics underlying this response in surface water bacteria at the community, resistome and mobilome level using a combination of methods (next-generation sequencing and qPCR), sequencing targets (16S rRNA gene, pre-clinical and clinical class 1 integron cassettes and metagenomes), technologies (short and long read sequencing), and assembly approaches (non-assembled reads, genome assembly, bacteriophage and plasmid assembly).

RESULTS

Our results show a shift in the microbial community response to antibiotics in the plastisphere microbiome compared to surface water communities and describe the bacterial subpopulations that respond differently to antibiotic and microplastic pollution. The plastisphere showed an increased tolerance to antibiotics and selected different antibiotic resistance bacteria (ARB) and antibiotic resistance genes (ARGs). Several metagenome assembled genomes (MAGs) derived from the antibiotic-exposed plastisphere contained ARGs, virulence factors, and genes involved in plasmid conjugation. These include Comamonas, Chryseobacterium, the opportunistic pathogen Stenotrophomonas maltophilia, and other MAGs belonging to genera that have been associated to human infections, such as Achromobacter. The abundance of the integron-associated ciprofloxacin resistance gene aac(6')-Ib-cr increased under ciprofloxacin exposure in both freshwater microbial communities and in the plastisphere. Regarding the antibiotic mobilome, although no significant changes in ARG load in class 1 integrons and plasmids were observed in polluted samples, we identified three ARG-containing viral contigs that were integrated into MAGs as prophages.

CONCLUSIONS

This study illustrates how the selective nature of the plastisphere influences bacterial response to antibiotics at sub-lethal selective pressure. The microbial changes identified here help define the selective role of the plastisphere and its impact on the maintenance of environmental antibiotic resistance in combination with other anthropogenic pollutants. This research highlights the need to evaluate the impact of aquatic pollutants in environmental microbial communities using complex scenarios with combined stresses. Video Abstract.

Can long-read sequencing tackle the barriers, which the next-generation could not? A review

The large-scale heterogeneity of genetic diseases necessitated the deeper examination of nucleotide sequence alterations enhancing the discovery of new targeted drug attack points. The appearance of new sequencing techniques was essential to get more interpretable genomic data. In contrast to the previous short-reads, longer lengths can provide a better insight into the potential health threatening genetic abnormalities. Long-reads offer more accurate variant identification and genome assembly methods, indicating advances in nucleotide deflect-related studies. In this review, we introduce the historical background of sequencing technologies and show their benefits and limits, as well. Furthermore, we highlight the differences between short- and long-read approaches, including their unique advances and difficulties in methodologies and evaluation. Additionally, we provide a detailed description of the corresponding bioinformatics and the current applications.

Snakemake workflows for long-read bacterial genome assembly and evaluation

With the advancement of long-read sequencing technologies and their increasing use for bacterial genomics, several methods for generating genome assemblies from error-prone long reads have been developed. These are complemented by various tools for assembly polishing using either long reads, short reads, or reference genomes. End users are therefore left with a plethora of possible combinations of programs for obtaining a final trusted assembly. Hence, there is also a need to measure the completeness and accuracy of such assemblies, for which, again, several evaluation methods implemented in various programs are available. In order to automatically run multiple genome assembly and evaluation programs at once, I developed two workflows for the workflow management system Snakemake, which provide end users with an easy-to-run solution for testing various genome assemblies from their sequencing data. Both workflows use the conda packaging system, so there is no need for manual installation of each program.

Availability & Implementation

The workflows are available as open source software under the MIT license at github.com/pmenzel/ont-assembly-snake and github.com/pmenzel/score-assemblies.

Hybrid Illumina-Nanopore assembly improves identification of multilocus sequence types and antimicrobial resistance genes of Staphylococcus aureus isolated from Vermont dairy farms: comparison to Illumina-only and R9.4.1 nanopore-only assemblies

Antimicrobial resistance (AMR) in Staphylococcus aureus is a pressing public health challenge with significant implications for the dairy industry, encompassing bovine mastitis concerns and potential zoonotic threats. To delve deeper into the resistance mechanisms of S. aureus, this study employed a hybrid whole genome assembly approach that synergized the precision of Illumina with the continuity of Oxford Nanopore. A total of 62 isolates, collected from multiple sources from Vermont dairy farms, were sequenced using the GridION Oxford Nanopore R9.4.1 platform and the Illumina platform, and subsequently processed through our long-read first bioinformatics pipeline. Our analyses showcased the hybrid-assembled genome's superior completeness compared to Oxford Nanopore (R9.4.1)-only or Illumina-only assembled genomes. Furthermore, the hybrid assembly accurately determined multilocus sequence typing (MLST) strain types across all isolates. The comprehensive probe for antibiotic resistance genes (ARGs) using databases like CARD, Resfinder, and MEGARES 2.0 characterized AMR in S. aureus isolates from Vermont dairy farms, and revealed the presence of notable resistance genes, including beta-lactam genes blaZ, blaI, and blaR. In conclusion, the hybrid assembly approach emerged as a tool for uncovering the genomic nuances of S. aureus isolates collected from multiple sources on dairy farms. Our findings offer a pathway for detecting AMR gene prevalence and shaping AMR management strategies crucial for safeguarding human and animal health.

Deciphering the genomes of motility-deficient mutants of Vibrio alginolyticus 138-2

The motility of Vibrio species plays a pivotal role in their survival and adaptation to diverse environments and is intricately associated with pathogenicity in both humans and aquatic animals. Numerous mutant strains of Vibrio alginolyticus have been generated using UV or EMS mutagenesis to probe flagellar motility using molecular genetic approaches. Identifying these mutations promises to yield valuable insights into motility at the protein structural physiology level. In this study, we determined the complete genomic structure of 4 reference specimens of laboratory V. alginolyticus strains: a precursor strain, V. alginolyticus 138-2, two strains showing defects in the lateral flagellum (VIO5 and YM4), and one strain showing defects in the polar flagellum (YM19). Subsequently, we meticulously ascertained the specific mutation sites within the 18 motility-deficient strains related to the polar flagellum (they fall into three categories: flagellar-deficient, multi-flagellar, and chemotaxis-deficient strains) by whole genome sequencing and mapping to the complete genome of parental strains VIO5 or YM4. The mutant strains had an average of 20.6 (±12.7) mutations, most of which were randomly distributed throughout the genome. However, at least two or more different mutations in six flagellar-related genes were detected in 18 mutants specifically selected as chemotaxis-deficient mutants. Genomic analysis using a large number of mutant strains is a very effective tool to comprehensively identify genes associated with specific phenotypes using forward genetics.

Three Rounds of Read Correction Significantly Improve Eukaryotic Protein Detection in ONT Reads

BACKGROUND

Eukaryotes' whole-genome sequencing is crucial for species identification, gene detection, and protein annotation. Oxford Nanopore Technology (ONT) is an affordable and rapid platform for sequencing eukaryotes; however, the relatively higher error rates require computational and bioinformatic efforts to produce more accurate genome assemblies. Here, we evaluated the effect of read correction tools on eukaryote genome completeness, gene detection and protein annotation.

METHODS

Reads generated by ONT of four eukaryotes, C. albicans, C. gattii, S. cerevisiae, and P. falciparum, were assembled using minimap2 and underwent three rounds of read correction using flye, medaka and racon. The generates consensus FASTA files were compared for total length (bp), genome completeness, gene detection, and protein-annotation by QUAST, BUSCO, BRAKER1 and InterProScan, respectively.

RESULTS

Genome completeness was dependent on the assembly method rather than on the read correction tool; however, medaka performed better than flye and racon. Racon significantly performed better than flye and medaka in gene detection, while both racon and medaka significantly performed better than flye in protein-annotation.

CONCLUSION

We show that three rounds of read correction significantly affect gene detection and protein annotation, which are dependent on assembly quality in preference to assembly completeness.

Benchmarking DNA isolation methods for marine metagenomics

Metagenomics is a powerful tool to study marine microbial communities. However, obtaining high-quality environmental DNA suitable for downstream sequencing applications is a challenging task. The quality and quantity of isolated DNA heavily depend on the choice of purification procedure and the type of sample. Selection of an appropriate DNA isolation method for a new type of material often entails a lengthy trial and error process. Further, each DNA purification approach introduces biases and thus affects the composition of the studied community. To account for these problems and biases, we systematically investigated efficiency of DNA purification from three types of samples (water, sea sediment, and digestive tract of a model invertebrate Magallana gigas) with eight commercially available DNA isolation kits. For each kit-sample combination we measured the quantity of purified DNA, extent of DNA fragmentation, the presence of PCR-inhibiting contaminants, admixture of eukaryotic DNA, alpha-diversity, and reproducibility of the resulting community composition based on 16S rRNA amplicons sequencing. Additionally, we determined a "kitome", e.g., a set of contaminating taxa inherent for each type of purification kit used. The resulting matrix of evaluated parameters allows one to select the best DNA purification procedure for a given type of sample.

The Utilization of Reference-Guided Assembly and In Silico Libraries Improves the Draft Genome of Clarias batrachus and Culter alburnus

Long-read sequencing technologies can generate highly contiguous genome assemblies compared to short-read methods. However, their higher cost often poses a significant barrier. To address this, we explore the utilization of mapping-based genome assembly and reference-guided assembly as cost-effective alternative approaches. We assess the efficacy of these approaches in improving the contiguity of Clarias batrachus and Culter alburnus draft genomes. Our findings demonstrate that employing an iterative mapping strategy leads to a reduction in assembly errors. Specifically, after three iterations, the Mismatches per 100 kbp value for the C. batrachus genome decreased from 2447.20 to 2432.67, reaching a minimum of 2422.67 after two iterations. Additionally, the N50 value for the C. batrachus genome increased from 362,143 to 1,315,126 bp, with a maximum of 1,315,403 bp after two iterations. Furthermore, we achieved Mismatches per 100 kbp values of 3.70 for the reference-guided assembly of C. batrachus and 0.34 for C. alburnus. Correspondingly, the N50 value for the C. batrachus and C. alburnus genomes increased from 362,143 bp and 3,686,385 bp to 2,026,888 bp and 43,735,735 bp, respectively. Finally, we successfully utilized the improved C. batrachus and C. alburnus genomes to compare genome studies using the combined approach of Ragout and Ragtag. Through a comprehensive comparative analysis of mapping-based and reference-guided genome assembly methods, we shed light on the specific contributions of reference-guided assembly in reducing assembly errors and improving assembly continuity and integrity. These advancements establish reference-guided assembly and the utilization of in silico libraries as a promising and suitable approach for comparative genomics studies.

Extracellular oil production by Rhodotorula paludigena BS15 for biorefinery without complex downstream processes

To realize biomass refinery without complex downstream processes, we extensively screened for microbial strains that efficiently produce extracellular oil from sugars. Rhodotorula paludigena (formerly Rhodosporidium paludigenum) BS15 was found to efficiently produce polyol esters of fatty acids (PEFAs), which mainly comprised of 3-acetoxypalmitic acid and partially acetylated mannitol/arabinitol. To evaluate the performance of this strain, fed-batch fermentation was demonstrated on a flask scale, and 110 g/L PEFA and 103 g/L dry cells were produced in 12 days. To the best of our knowledge, the strain BS15 exhibited the highest PEFA titer (g/L) ever to be reported so far. Because the PEFA precipitated at the bottom of the culture broth, it could be easily recovered by simply discarding the upper phase. Various carbon sources can be utilized for cell growth and/or PEFA production, which signifies the potential for converting diverse biomass sources. Two different types of next-generation sequencers, Illumina HiSeq and Oxford Nanopore PromethION, were used to analyze the whole-genome sequence of the strain BS15. The integrative data analysis generated a high-quality and reliable reference genome for PEFA-producing R. paludigena. The 22.5-M base genome sequence and the estimated genes were registered in Genbank (accession numbers BQKY01000001-BQKY01000019). KEY POINTS: • R. paludigena BS15 was isolated after an extensive screening of extracellular oil producers from natural sources. • Fed-batch fermentation of R. paludigena BS15 yielded 110 g/L of PEFA, which is the highest titer ever reported to date. • Combined analysis using Illumina and Oxford Nanopore sequencers produced the near-complete genome sequence.

Evaluation of metagenomic assembly methods for the detection and characterization of antimicrobial resistance determinants and associated mobilizable elements

Antimicrobial resistance genes (ARGs) can be transferred between members of a bacterial population by mobile genetic elements (MGE). Understanding the risk of these transfer events is important in monitoring and predicting antimicrobial resistance (AMR), especially in the context of a One Health Continuum. However, there is no universally accepted method for detection of ARGs and MGEs, and especially for determining their linkages. This study used publicly available shotgun metagenomic DNA short-read (Illumina, 100 bp paired-end) sequence data from samples across the One Health Continuum (including beef cattle composite feces from feedlots, catch basin water at feedlots, agricultural soil from feedlot manured surrounding fields, and urban/municipal sewage influent from two municipal wastewater treatment plants) to develop a workflow to identify and associate ARGs and MGEs. ARG- and MGE-based targeted-assemblies with available short-read data were unable to meet this analysis goal. In contrast, de novo assembly of contigs provided enough sequence context to associate ARGs and MGEs, without compromising discovery rate. However, to estimate the relative abundance of these elements, unassembled sequence data must still be used.

Scalable and versatile container-based pipelines for de novo genome assembly and bacterial annotation

Background: Advancements in DNA sequencing technology have transformed the field of bacterial genomics, allowing for faster and more cost effective chromosome level assemblies compared to a decade ago. However, transforming raw reads into a complete genome model is a significant computational challenge due to the varying quality and quantity of data obtained from different sequencing instruments, as well as intrinsic characteristics of the genome and desired analyses. To address this issue, we have developed a set of container-based pipelines using Nextflow, offering both common workflows for inexperienced users and high levels of customization for experienced ones. Their processing strategies are adaptable based on the sequencing data type, and their modularity enables the incorporation of new components to address the community's evolving needs. Methods: These pipelines consist of three parts: quality control, de novo genome assembly, and bacterial genome annotation. In particular, the genome annotation pipeline provides a comprehensive overview of the genome, including standard gene prediction and functional inference, as well as predictions relevant to clinical applications such as virulence and resistance gene annotation, secondary metabolite detection, prophage and plasmid prediction, and more. Results: The annotation results are presented in reports, genome browsers, and a web-based application that enables users to explore and interact with the genome annotation results. Conclusions: Overall, our user-friendly pipelines offer a seamless integration of computational tools to facilitate routine bacterial genomics research. The effectiveness of these is illustrated by examining the sequencing data of a clinical sample of Klebsiella pneumoniae.

The impact of applying various de novo assembly and correction tools on the identification of genome characterization, drug resistance, and virulence factors of clinical isolates using ONT sequencing

Oxford Nanopore sequencing technology (ONT) is currently widely used due to its affordability, simplicity, and reliability. Despite the advantage ONT has over next-generation sequencing in detecting resistance genes in mobile genetic elements, its relatively high error rate (10-15%) is still a deterrent. Several bioinformatic tools are freely available for raw data processing and obtaining complete and more accurate genome assemblies. In this study, we evaluated the impact of using mix-and-matched read assembly (Flye, Canu, Wtdbg2, and NECAT) and read correction (Medaka, NextPolish, and Racon) tools in generating complete and accurate genome assemblies, and downstream genomic analysis of nine clinical Escherichia coli isolates. Flye and Canu assemblers were the most robust in genome assembly, and Medaka and Racon correction tools significantly improved assembly parameters. Flye functioned well in pan-genome analysis, while Medaka increased the number of core genes detected. Flye, Canu, and NECAT assembler functioned well in detecting antimicrobial resistance genes (AMR), while Wtdbg2 required correction tools for better detection. Flye was the best assembler for detecting and locating both virulence and AMR genes (i.e., chromosomal vs. plasmid). This study provides insight into the performance of several read assembly and read correction tools for analyzing ONT sequencing reads for clinical isolates.

From contigs towards chromosomes: automatic improvement of long read assemblies (ILRA)

Recent advances in long read technologies not only enable large consortia to aim to sequence all eukaryotes on Earth, but they also allow individual laboratories to sequence their species of interest with relatively low investment. Long read technologies embody the promise of overcoming scaffolding problems associated with repeats and low complexity sequences, but the number of contigs often far exceeds the number of chromosomes and they may contain many insertion and deletion errors around homopolymer tracts. To overcome these issues, we have implemented the ILRA pipeline to correct long read-based assemblies. Contigs are first reordered, renamed, merged, circularized, or filtered if erroneous or contaminated. Illumina short reads are used subsequently to correct homopolymer errors. We successfully tested our approach by improving the genome sequences of Homo sapiens, Trypanosoma brucei, and Leptosphaeria spp., and by generating four novel Plasmodium falciparum assemblies from field samples. We found that correcting homopolymer tracts reduced the number of genes incorrectly annotated as pseudogenes, but an iterative approach seems to be required to correct more sequencing errors. In summary, we describe and benchmark the performance of our new tool, which improved the quality of novel long read assemblies up to 1 Gbp. The pipeline is available at GitHub: https://github.com/ThomasDOtto/ILRA.

Genomic analysis of Enterococcus faecium strain RAOG174 associated with acute chorioamnionitis carried antibiotic resistance gene: is it time for precise microbiological identification for appropriate antibiotic use?

BACKGROUND

Preterm labor syndrome is associated with high perinatal morbidity and mortality, and intra-amniotic infection is a cause of preterm labor. The standard identification of causative microorganisms is based on the use of biochemical phenotypes, together with broth dilution-based antibiotic susceptibility from organisms grown in culture. However, such methods could not provide an accurate epidemiological aspect and a genetic basis of antimicrobial resistance leading to an inappropriate antibiotic administration. Hybrid genome assembly is a combination of short- and long-read sequencing, which provides better genomic resolution and completeness for genotypic identification and characterization. Herein, we performed a hybrid whole genome assembly sequencing of a pathogen associated with acute histologic chorioamnionitis in women presenting with PPROM.

RESULTS

We identified Enterococcus faecium, namely E. faecium strain RAOG174, with several antibiotic resistance genes, including vancomycin and aminoglycoside. Virulence-associated genes and potential bacteriophage were also identified in this genome.

CONCLUSION

We report herein the first study demonstrating the use of hybrid genome assembly and genomic analysis to identify E. faecium ST17 as a pathogen associated with acute histologic chorioamnionitis. The analysis provided several antibiotic resistance-associated genes/mutations and mobile genetic elements. The occurrence of E. faecium ST17 raised the awareness of the colonization of clinically relevant E. faecium and the carrying of antibiotic resistance. This finding has brought the advantages of genomic approach in the identification of the bacterial species and antibiotic resistance gene for E. faecium for appropriate antibiotic use to improve maternal and neonatal care.

SLHSD: hybrid scaffolding method based on short and long reads

In genome assembly, scaffolding can obtain more complete and continuous scaffolds. Current scaffolding methods usually adopt one type of read to construct a scaffold graph and then orient and order contigs. However, scaffolding with the strengths of two or more types of reads seems to be a better solution to some tricky problems. Combining the advantages of different types of data is significant for scaffolding. Here, a hybrid scaffolding method (SLHSD) is present that simultaneously leverages the precision of short reads and the length advantage of long reads. Building an optimal scaffold graph is an important foundation for getting scaffolds. SLHSD uses a new algorithm that combines long and short read alignment information to determine whether to add an edge and how to calculate the edge weight in a scaffold graph. In addition, SLHSD develops a strategy to ensure that edges with high confidence can be added to the graph with priority. Then, a linear programming model is used to detect and remove remaining false edges in the graph. We compared SLHSD with other scaffolding methods on five datasets. Experimental results show that SLHSD outperforms other methods. The open-source code of SLHSD is available at https://github.com/luojunwei/SLHSD.

Whole-Genome Sequencing-Based Resistome Analysis of Nosocomial Multidrug-Resistant Non-Fermenting Gram-Negative Pathogens from the Balkans

Non-fermenting Gram-negative bacilli (NFGNB), such as Pseudomonas aeruginosa and Acinetobacter baumannii, are among the major opportunistic pathogens involved in the global antibiotic resistance epidemic. They are designated as urgent/serious threats by the Centers for Disease Control and Prevention and are part of the World Health Organization’s list of critical priority pathogens. Also, Stenotrophomonas maltophilia is increasingly recognized as an emerging cause for healthcare-associated infections in intensive care units, life-threatening diseases in immunocompromised patients, and severe pulmonary infections in cystic fibrosis and COVID-19 individuals. The last annual report of the ECDC showed drastic differences in the proportions of NFGNB with resistance towards key antibiotics in different European Union/European Economic Area countries. The data for the Balkans are of particular concern, indicating more than 80% and 30% of invasive Acinetobacter spp. and P. aeruginosa isolates, respectively, to be carbapenem-resistant. Moreover, multidrug-resistant and extensively drug-resistant S. maltophilia from the region have been recently reported. The current situation in the Balkans includes a migrant crisis and reshaping of the Schengen Area border. This results in collision of diverse human populations subjected to different protocols for antimicrobial stewardship and infection control. The present review article summarizes the findings of whole-genome sequencing-based resistome analyses of nosocomial multidrug-resistant NFGNBs in the Balkan countries.

Assembling Quality Genomes of Flax Fungal Pathogens from Oxford Nanopore Technologies Data

Flax (Linum usitatissimum L.) is attacked by numerous devastating fungal pathogens, including Colletotrichum lini, Aureobasidium pullulans, and Fusarium verticillioides (Fusarium moniliforme). The effective control of flax diseases follows the paradigm of extensive molecular research on pathogenicity. However, such studies require quality genome sequences of the studied organisms. This article reports on the approaches to assembling a high-quality fungal genome from the Oxford Nanopore Technologies data. We sequenced the genomes of C. lini, A. pullulans, and F. verticillioides (F. moniliforme) and received different volumes of sequencing data: 1.7 Gb, 3.9 Gb, and 11.1 Gb, respectively. To obtain the optimal genome sequences, we studied the effect of input data quality and genome coverage on assembly statistics and tested the performance of different assembling and polishing software. For C. lini, the most contiguous and complete assembly was obtained by the Flye assembler and the Homopolish polisher. The genome coverage had more effect than data quality on assembly statistics, likely due to the relatively low amount of sequencing data obtained for C. lini. The final assembly was 53.4 Mb long and 96.4% complete (according to the glomerellales_odb10 BUSCO dataset), consisted of 42 contigs, and had an N50 of 4.4 Mb. For A. pullulans and F. verticillioides (F. moniliforme), the best assemblies were produced by Canu-Medaka and Canu-Homopolish, respectively. The final assembly of A. pullulans had a length of 29.5 Mb, 99.4% completeness (dothideomycetes_odb10), an N50 of 2.4 Mb and consisted of 32 contigs. F. verticillioides (F. moniliforme) assembly was 44.1 Mb long, 97.8% complete (hypocreales_odb10), consisted of 54 contigs, and had an N50 of 4.4 Mb. The obtained results can serve as a guideline for assembling a de novo genome of a fungus. In addition, our data can be used in genomic studies of fungal pathogens or plant-pathogen interactions and assist in the management of flax diseases.

Evaluation of multiplex nanopore sequencing for Salmonella serotype prediction and antimicrobial resistance gene and virulence gene detection

In a previous study, Multiplex-nanopore-sequencing based whole genome sequencing (WGS) allowed for accurate in silico serotype prediction of Salmonella within one day for five multiplexed isolates, using both SISTR and SeqSero2. Since only ten serotypes were tested in our previous study, the conclusions above were yet to be evaluated in a larger scale test. In the current study we evaluated this workflow with 69 Salmonella serotypes and also explored the feasibility of using multiplex-nanopore-sequencing based WGS for antimicrobial resistance gene (AMR) and virulence gene detection. We found that accurate in silico serotype prediction with nanopore-WGS data was achieved within about five hours of sequencing at a minimum of 30× Salmonella genome coverage, with SeqSero2 as the serotype prediction tool. For each tested isolate, small variations were observed between the AMR/virulence gene profiles from the Illumina and Nanopore sequencing platforms. Taking results generated using Illumina data as the benchmark, the average precision value per isolate was 0.99 for both AMR and virulence gene detection. We found that the resistance gene identifier - RGI identified AMR genes with nanopore data at a much lower accuracy compared to Abricate, possibly due to RGI's less stringent minimum similarity and coverage by default for database matching. This study is an evaluation of multiplex-nanopore-sequencing based WGS as a cost-efficient and rapid Salmonella classification method, and a starting point for future validation and verification of using it as a AMR/virulence gene profiling tool for the food industry. This study paves the way for the application of nanopore sequencing in surveillance, tracking, and risk assessment of Salmonella across the food supply chain.

Genomics of Tenacibaculum Species in British Columbia, Canada

Tenacibaculum is a genus of Gram-negative filamentous bacteria with a cosmopolitan distribution. The research describing Tenacibaculum genomes stems primarily from Norway and Chile due to their impacts on salmon aquaculture. Canadian salmon aquaculture also experiences mortality events related to the presence of Tenacibaculum spp., yet no Canadian Tenacibaculum genomes are publicly available. Ribosomal DNA sequencing of 16S and four species-specific 16S quantitative-PCR assays were used to select isolates cultured from Atlantic salmon with mouthrot in British Columbia (BC), Canada. Ten isolates representing four known and two unknown species of Tenacibaculum were selected for shotgun whole genome sequencing using the Oxford Nanopore's MinION platform. The genome assemblies achieved closed circular chromosomes for seven isolates and long contigs for the remaining three isolates. Average nucleotide identity analysis identified T. ovolyticum, T. maritimum, T. dicentrarchi, two genomovars of T. finnmarkense, and two proposed novel species T. pacificus sp. nov. type strain 18-2881-A^T and T. retecalamus sp. nov. type strain 18-3228-7B^T. Annotation in most of the isolates predicted putative virulence and antimicrobial resistance genes, most-notably toxins (i.e., hemolysins), type-IX secretion systems, and oxytetracycline resistance. Comparative analysis with the T. maritimum type-strain predicted additional toxins and numerous C-terminal secretion proteins, including an M12B family metalloprotease in the T. maritimum isolates from BC. The genomic prediction of virulence-associated genes provides important targets for studies of mouthrot disease, and the annotation of the antimicrobial resistance genes provides targets for surveillance and diagnosis in veterinary medicine.

Accuracy and Completeness of Long Read Metagenomic Assemblies

Microbes influence the surrounding environment and contribute to human health. Metagenomics can be used as a tool to explore the interactions between microbes. Metagenomic assemblies built using long read nanopore data depend on the read level accuracy. The read level accuracy of nanopore sequencing has made dramatic improvements over the past several years. However, we do not know if the increased read level accuracy allows for faster assemblers to make as accurate metagenomic assemblies as slower assemblers. Here, we present the results of a benchmarking study comparing three commonly used long read assemblers, Flye, Raven, and Redbean. We used a prepared DNA standard of seven bacteria as our input community. We prepared a sequencing library using a VolTRAX V2 and sequenced using a MinION mk1b. We basecalled with Guppy v5.0.7 using the super-accuracy model. We found that increasing read depth benefited each of the assemblers, and nearly complete community member chromosomes were assembled with as little as 10× read depth. Polishing assemblies using Medaka had a predictable improvement in quality. We found Flye to be the most robust across taxa and was the most effective assembler for recovering plasmids. Based on Flye's consistency for chromosomes and increased effectiveness at assembling plasmids, we would recommend using Flye in future metagenomic studies.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Nanopore Sequencing for De Novo Bacterial Genome Assembly and Search for Single-Nucleotide Polymorphism

Nanopore sequencing (ONT) is a new and rapidly developing method for determining nucleotide sequences in DNA and RNA. It serves the ability to obtain long reads of thousands of nucleotides without assembly and amplification during sequencing compared to next-generation sequencing. Nanopore sequencing can help for determination of genetic changes leading to antibiotics resistance. This study presents the application of ONT technology in the assembly of an E. coli genome characterized by a deletion of the tolC gene and known single-nucleotide variations leading to antibiotic resistance, in the absence of a reference genome. We performed benchmark studies to determine minimum coverage depth to obtain a complete genome, depending on the quality of the ONT data. A comparison of existing programs was carried out. It was shown that the Flye program demonstrates plausible assembly results relative to others (Shasta, Canu, and Necat). The required coverage depth for successful assembly strongly depends on the size of reads. When using high-quality samples with an average read length of 8 Kbp or more, the coverage depth of 30× is sufficient to assemble the complete genome de novo and reliably determine single-nucleotide variations in it. For samples with shorter reads with mean lengths of 2 Kbp, a higher coverage depth of 50× is required. Avoiding of mechanical mixing is obligatory for samples preparation. Nanopore sequencing can be used alone to determine antibiotics-resistant genetic features of bacterial strains.

Datasets for benchmarking antimicrobial resistance genes in bacterial metagenomic and whole genome sequencing

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.

Systems-Based Approach for Optimization of Assembly-Free Bacterial MLST Mapping

Epidemiological surveillance of bacterial pathogens requires real-time data analysis with a fast turnaround, while aiming at generating two main outcomes: (1) species-level identification and (2) variant mapping at different levels of genotypic resolution for population-based tracking and surveillance, in addition to predicting traits such as antimicrobial resistance (AMR). Multi-locus sequence typing (MLST) aids this process by identifying sequence types (ST) based on seven ubiquitous genome-scattered loci. In this paper, we selected one assembly-dependent and one assembly-free method for ST mapping and applied them with the default settings and ST schemes they are distributed with, and systematically assessed their accuracy and scalability across a wide array of phylogenetically divergent Public Health-relevant bacterial pathogens with available MLST databases. Our data show that the optimal k-mer length for stringMLST is species-specific and that genome-intrinsic and -extrinsic features can affect the performance and accuracy of the program. Although suitable parameters could be identified for most organisms, there were instances where this program may not be directly deployable in its current format. Next, we integrated stringMLST into our freely available and scalable hierarchical-based population genomics platform, ProkEvo, and further demonstrated how the implementation facilitates automated, reproducible bacterial population analysis.

Benchmarking of long-read sequencing, assemblers and polishers for yeast genome

BACKGROUND

The long reads of the third-generation sequencing significantly benefit the quality of the de novo genome assembly. However, its relatively high single-base error rate has been criticized. Currently, sequencing accuracy and throughput continue to improve, and many advanced tools are constantly emerging. PacBio HiFi sequencing and Oxford Nanopore Technologies (ONT) PromethION are two up-to-date platforms with low error rates and ultralong high-throughput reads. Therefore, it is urgently needed to select the appropriate sequencing platforms, depths and genome assembly tools for high-quality genomes in the era of explosive data production.

METHODS

We performed 455 (7 assemblers with 4 polishing pipelines or without polishing on 13 subsets with different depths) and 88 (4 assemblers with or without polishing on 11 subsets with different depths) de novo assemblies of Yeast S288C on high-coverage ONT and HiFi datasets, respectively. The assembly quality was evaluated by Quality Assessment Tool (QUAST), Benchmarking Universal Single-Copy Orthologs (BUSCO) and the newly proposed Comprehensive_score (C_score). In addition, we applied four preferable pipelines to assemble the genome of nonreference yeast strains.

RESULTS

The assembler plays an essential role in genome construction, especially for low-depth datasets. For ONT datasets, Flye is superior to other tools through C_score evaluation. Polishing by Pilon and Medaka improve accuracy and continuity of the preassemblies, respectively, and their combination pipeline worked well in most quality metrics. For HiFi datasets, Flye and NextDenovo performed better than other tools, and polishing is also necessary. Enough data depth is required for high-quality genome construction by ONT (>80X) and HiFi (>20X) datasets.

Complete genome assembly of the levan-positive strain PVFi1 of Pseudomonas savastanoi pv. savastanoi isolated from olive knots in Central Italy

Pseudomonas savastanoi pv. savastanoi, the causal agent of olive knot disease, is a fluorescent Gram-negative bacterium classified, according to the specific LOPAT profile, as Ib. However, during the 90s, a number of atypical non-fluorescent levan-positive strains of Pseudomonas savastanoi pv. savastanoi have been unexpectedly isolated from olive knots in Central Italy. Since its first report, several studies were conducted on this species variant, but its genome sequence has never been reported. The complete genome sequence and two additional plasmids of PVFi1, a representative strain, were here obtained using a hybrid sequencing approach with both Oxford Nanopore Technology and Illumina sequencing. A thorough genomic analysis unravelled several genetic features of this peculiar strain, showing a transposase insertion downstream a fragmented copy of the levansucrase gene. The same features were previously reported on levan-negative Pseudomonas savastanoi pv. savastanoi strains. In addition, a second copy of the levansucrase gene fully equipped for a gene expression and comparable to the levan-positive Pseudomonas savastanoi pv. glycinea, may explain the levan-positive test. This result provides a solid genetic demonstration that the bacterial species Pseudomonas savastanoi contains either levan-positive or levan-negative strains, providing insights for an update of the related LOPAT classification.

Whole-Genome and Transcriptome Sequencing-Based Characterization of Bacillus Cereus NR1 From Subtropical Marine Mangrove and Its Potential Role in Sulfur Metabolism

Sulfur, organosulfur compounds, and sulfides are essential parts of life. Microbial sulfate assimilation is among the most active and ancient metabolic activities in the sulfur cycle that operates in various ecosystems. We analyzed the molecular basis of bacterial characterization. NR1 was isolated and purified from mangrove sediments. Whole-genome sequencing indicated that the NR1 isolate was closely related to Bacillus cereus. The genome contained 5,305 functional genes with a total length of 5,420,664 bp, a GC content of 35.62%, 42 rRNA, and 107 tRNA. DBT-grown cultures exhibited DBT utilization, fleeting emergence of DBT sulfone (DBTO2), and formation of 2-hydroxybiphenyl (2-HBP). Molecular analysis of the PCR products’ dsz operon revealed the presence of dszA, dszB, and dszC genes, which encoded for NR1’s 90% DBT desulfurization activity. Furthermore, 17 sulfur metabolism-related genes, including genes involved in assimilation sulfate reduction, APS and PAPS, and the cys, ssu, and TST gene families, were identified. In sulfate media, alkenesulfonate was converted to sulfite and inhibited ssu enzymes. Downregulated cysK variants were associated with nrnA expression and the regulation of L-cysteine synthesis. These findings established a scientific foundation for further research and application of bacteria to mangrove rehabilitation and ecological treatment by evaluating the bacterial characterization and sulfur degradation metabolic pathway. We used whole-genome and transcriptome sequencing to examine their genetic characteristics.

Draft Genome Sequence of a New Fusarium Isolate Belonging to Fusarium tricinctum Species Complex Collected From Hazelnut in Central Italy

In summer 2019, during a survey on the health status of a hazelnut orchard located in the Tuscia area (the province of Viterbo, Latium, Italy), nuts showing symptoms, such as brown-grayish spots at the bottom of the nuts progressing upward to the apex, and necrotic patches on the bracts and, sometimes, on the petioles, were found and collected for further studies. This syndrome is associated with the nut gray necrosis (NGN), whose main causal agent is Fusarium lateritium. Aiming to increase knowledge about this fungal pathogen, the whole-genome sequencing of a strain isolated from symptomatic hazelnut was performed using long Nanopore reads technology in combination with the higher precision of the Illumina reads, generating a high-quality genome assembly. The following phylogenetic and comparative genomics analysis suggested that this isolate is caused by the F. tricinctum species complex rather than F. lateritium one, as initially hypothesized. Thus, this study demonstrates that different Fusarium species can infect Corylus avellana producing the same symptomatology. In addition, it sheds light onto the genetic features of the pathogen in subject, clarifying facets about its biology, epidemiology, infection mechanisms, and host spectrum, with the future objective to develop specific and efficient control strategies.

Hybrid Assembly Provides Improved Resolution of Plasmids, Antimicrobial Resistance Genes, and Virulence Factors in Escherichia coli and Klebsiella pneumoniae Clinical Isolates

Emerging new sequencing technologies have provided researchers with a unique opportunity to study factors related to microbial pathogenicity, such as antimicrobial resistance (AMR) genes and virulence factors. However, the use of whole-genome sequence (WGS) data requires good knowledge of the bioinformatics involved, as well as the necessary techniques. In this study, a total of nine Escherichia coli and Klebsiella pneumoniae isolates from Norwegian clinical samples were sequenced using both MinION and Illumina platforms. Three out of nine samples were sequenced directly from blood culture, and one sample was sequenced from a mixed-blood culture. For genome assembly, several long-read, (Canu, Flye, Unicycler, and Miniasm), short-read (ABySS, Unicycler and SPAdes) and hybrid assemblers (Unicycler, hybridSPAdes, and MaSurCa) were tested. Assembled genomes from the best-performing assemblers (according to quality checks using QUAST and BUSCO) were subjected to downstream analyses. Flye and Unicycler assemblers performed best for the assembly of long and short reads, respectively. For hybrid assembly, Unicycler was the top-performing assembler and produced more circularized and complete genome assemblies. Hybrid assembled genomes performed substantially better in downstream analyses to predict putative plasmids, AMR genes and β-lactamase gene variants, compared to MinION and Illumina assemblies. Thus, hybrid assembly has the potential to reveal factors related to microbial pathogenicity in clinical and mixed samples.

Evaluation of whole-genome sequence data analysis approaches for short- and long-read sequencing of Mycobacterium tuberculosis

Whole-genome sequencing (WGS) of Mycobacterium tuberculosis (MTB) isolates can be used to get an accurate diagnosis, to guide clinical decision making, to control tuberculosis (TB) and for outbreak investigations. We evaluated the performance of long-read (LR) and/or short-read (SR) sequencing for anti-TB drug-resistance prediction using the TBProfiler and Mykrobe tools, the fraction of genome recovery, assembly accuracies and the robustness of two typing approaches based on core-genome SNP (cgSNP) typing and core-genome multi-locus sequence typing (cgMLST). Most of the discrepancies between phenotypic drug-susceptibility testing (DST) and drug-resistance prediction were observed for the first-line drugs rifampicin, isoniazid, pyrazinamide and ethambutol, mainly with LR sequence data. Resistance prediction to second-line drugs made by both TBProfiler and Mykrobe tools with SR- and LR-sequence data were in complete agreement with phenotypic DST except for one isolate. The SR assemblies were more accurate than the LR assemblies, having significantly (P <0.05) fewer indels and mismatches per 100 kbp. However, the hybrid and LR assemblies had slightly higher genome fractions. For LR assemblies, Canu followed by Racon, and Medaka polishing was the most accurate approach. The cgSNP approach, based on either reads or assemblies, was more robust than the cgMLST approach, especially for LR sequence data. In conclusion, anti-TB drug-resistance prediction, particularly with only LR sequence data, remains challenging, especially for first-line drugs. In addition, SR assemblies appear more accurate than LR ones, and reproducible phylogeny can be achieved using cgSNP approaches.

Characterization of Genetically Modified Microorganisms Using Short- and Long-Read Whole-Genome Sequencing Reveals Contaminations of Related Origin in Multiple Commercial Food Enzyme Products

Despite their presence being unauthorized on the European market, contaminations with genetically modified (GM) microorganisms have repeatedly been reported in diverse commercial microbial fermentation produce types. Several of these contaminations are related to a GM Bacillus velezensis used to synthesize a food enzyme protease, for which genomic characterization remains currently incomplete, and it is unknown whether these contaminations have a common origin. In this study, GM B. velezensis isolates from multiple food enzyme products were characterized by short- and long-read whole-genome sequencing (WGS), demonstrating that they harbor a free recombinant pUB110-derived plasmid carrying antimicrobial resistance genes. Additionally, single-nucleotide polymorphism (SNP) and whole-genome based comparative analyses showed that the isolates likely originate from the same parental GM strain. This study highlights the added value of a hybrid WGS approach for accurate genomic characterization of GMM (e.g., genomic location of the transgenic construct), and of SNP-based phylogenomic analysis for source-tracking of GMM.

Techniques in bacterial strain typing: past, present, and future

PURPOSE OF REVIEW

The advancement of molecular techniques such as whole-genome sequencing (WGS) has revolutionized the field of bacterial strain typing, with important implications for epidemiological surveillance and outbreak investigations. This review summarizes state-of-the-art techniques in strain typing and examines barriers faced by clinical and public health laboratories in implementing these new methodologies.

RECENT FINDINGS

WGS-based methodologies are on track to become the new 'gold standards' in bacterial strain typing, replacing traditional methods like pulsed-field gel electrophoresis and multilocus sequence typing. These new techniques have an improved ability to identify genetic relationships among organisms of interest. Further, advances in long-read sequencing approaches will likely provide a highly discriminatory tool to perform pangenome analyses and characterize relevant accessory genome elements, including mobile genetic elements carrying antibiotic resistance determinants in real time. Barriers to widespread integration of these approaches include a lack of standardized workflows and technical training.

SUMMARY

Genomic bacterial strain typing has facilitated a paradigm shift in clinical and molecular epidemiology. The increased resolution that these new techniques provide, along with epidemiological data, will facilitate the rapid identification of transmission routes with high confidence, leading to timely and effective deployment of infection control and public health interventions in outbreak settings.

Optimizing experimental design for genome sequencing and assembly with Oxford Nanopore Technologies

High quality reference genome sequences are the core of modern genomics. Oxford Nanopore Technologies (ONT) produces inexpensive DNA sequences, but has high error rates, which make sequence assembly and analysis difficult as genome size and complexity increases. Robust experimental design is necessary for ONT genome sequencing and assembly, but few studies have addressed eukaryotic organisms. Here, we present novel results using simulated and empirical ONT and DNA libraries to identify best practices for sequencing and assembly for several model species. We find that the unique error structure of ONT libraries causes errors to accumulate and assembly statistics plateau as sequence depth increases. High-quality assembled eukaryotic sequences require high-molecular-weight DNA extractions that increase sequence read length, and computational protocols that reduce error through pre-assembly correction and read selection. Our quantitative results will be helpful for researchers seeking guidance for de novo assembly projects.

Benchmarking of next and third generation sequencing technologies and their associated algorithms for de novo genome assembly

Genome assemblers are computational tools for de novo genome assembly, based on a plenitude of primary sequencing data. The quality of genome assemblies is estimated by their contiguity and the occurrences of misassemblies (duplications, deletions, translocations or inversions). The rapid development of sequencing technologies has enabled the rise of novel de novo genome assembly strategies. The ultimate goal of such strategies is to utilise the features of each sequencing platform in order to address the existing weaknesses of each sequencing type and compose a complete and correct genome map. In the present study, the hybrid strategy, which is based on Illumina short paired‑end reads and Nanopore long reads, was benchmarked using MaSuRCA and Wengan assemblers. Moreover, the long‑read assembly strategy, which is based on Nanopore reads, was benchmarked using Canu or PacBio HiFi reads were benchmarked using Hifiasm and HiCanu. The assemblies were performed on a computational cluster with limited computational resources. Their outputs were evaluated in terms of accuracy and computational performance. PacBio HiFi assembly strategy outperforms the other ones, while Hi‑C scaffolding, which is based on chromatin 3D structure, is required in order to increase continuity, accuracy and completeness when large and complex genomes, such as the human one, are assembled. The use of Hi‑C data is also necessary while using the hybrid assembly strategy. The results revealed that HiFi sequencing enabled the rise of novel algorithms which require less genome coverage than that of the other strategies making the assembly a less computationally demanding task. Taken together, these developments may lead to the democratisation of genome assembly projects which are now approachable by smaller labs with limited technical and financial resources.