Comparison of Oxford Nanopore Technologies and Illumina MiSeq sequencing with mock communities and agricultural soil

Advances in Host Depletion and Pathogen Enrichment Methods for Rapid Sequencing-Based Diagnosis of Bloodstream Infection

Bloodstream infection is a major cause of morbidity and death worldwide. Timely and appropriate treatment can reduce mortality among critically ill patients. Current diagnostic methods are too slow to inform precise antibiotic choice, leading to the prescription of empirical antibiotics, which may fail to cover the resistance profile of the pathogen, risking poor patient outcomes. Additionally, overuse of broad-spectrum antibiotics may lead to more resistant organisms, putting further pressure on the dwindling pipeline of antibiotics, and risk transmission of these resistant organisms in the health care environment. Therefore, rapid diagnostics are urgently required to better inform antibiotic choice early in the course of treatment. Sequencing offers great promise in reducing time to microbiological diagnosis; however, the amount of host DNA compared with the pathogen in patient samples presents a significant obstacle. Various host-depletion and bacterial-enrichment strategies have been used in samples, such as saliva, urine, or tissue. However, these methods have yet to be collectively integrated and/or extensively explored for rapid bloodstream infection diagnosis. Although most of these workflows possess individual strengths, their lack of analytical/clinical sensitivity and/or comprehensiveness demands additional improvements or synergistic application. This review provides a distinctive classification system for various methods based on their working principles to guide future research, and discusses their strengths and limitations and explores potential avenues for improvement to assist the reader in workflow selection.

Contributions of Long-Read Sequencing for the Detection of Antimicrobial Resistance

BACKGROUND

In the context of increasing antimicrobial resistance (AMR), whole-genome sequencing (WGS) of bacteria is considered a highly accurate and comprehensive surveillance method for detecting and tracking the spread of resistant pathogens. Two primary sequencing technologies exist: short-read sequencing (50-300 base pairs) and long-read sequencing (thousands of base pairs). The former, based on Illumina sequencing platforms (ISPs), provides extensive coverage and high accuracy for detecting single nucleotide polymorphisms (SNPs) and small insertions/deletions, but is limited by its read length. The latter, based on platforms such as Oxford Nanopore Technologies (ONT), enables the assembly of genomes, particularly those with repetitive regions and structural variants, although its accuracy has historically been lower.

RESULTS

We performed a head-to-head comparison of these techniques to sequence the K. pneumoniae VS17 isolate, focusing on blaNDM resistance gene alleles in the context of a surveillance program. Discrepancies between the ISP (blaNDM-4 allele identified) and ONT (blaNDM-1 and blaNDM-5 alleles identified) were observed. Conjugation assays and Sanger sequencing, used as the gold standard, confirmed the validity of ONT results. This study demonstrates the importance of long-read or hybrid assemblies for accurate carbapenemase resistance gene identification and highlights the limitations of short reads in the context of gene duplications or multiple alleles.

CONCLUSIONS

In this proof-of-concept study, we conclude that recent long-read sequencing technology may outperform standard short-read sequencing for the accurate identification of carbapenemase alleles. Such information is crucial given the rising prevalence of strains producing multiple carbapenemases, especially as WGS is increasingly used for epidemiological surveillance and infection control.

Unveiling errors in soil microbial community sequencing: a case for reference soils and improved diagnostics for nanopore sequencing

The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.

CRISPR-Cas guide RNA indel analysis using CRISPResso2 with Nanopore sequencing data

OBJECTIVE

Insertion and deletion (indel) analysis of CRISPR-Cas guide RNAs (gRNAs) is crucial in gene editing to assess gRNA efficiency and indel frequency. This study evaluates the utility of CRISPResso2 with Oxford Nanopore sequencing data (nCRISPResso2) for gRNA indel screening, compared to two common Sanger sequencing-based methods, TIDE and ICE. To achieve this, sheep and horse fibroblasts were transfected with Cas9 and a gRNA targeting the myostatin (MSTN) gene. DNA was subsequently extracted, and PCR products exceeding 600 bp were sequenced using both Sanger and Nanopore sequencing. Indel profiling was then conducted using TIDE, ICE, and nCRISPResso2.

RESULTS

Comparison revealed close correspondence in indel formation among methods. For the sheep MSTN gRNA, indel percentages were 52%, 58%, and 64% for TIDE, ICE, and nCRISPResso2, respectively. Horse MSTN gRNA showed 81%, 87%, and 86% edited amplicons for TIDE, ICE, and nCRISPResso2. The frequency of each type of indel was also comparable among the three methods, with nCRISPResso2 and ICE aligning the closest. nCRISPResso2 offers a viable alternative for CRISPR-Cas gRNA indel screening, especially with large amplicons unsuitable for Illumina sequencing. CRISPResso2's compatibility with Nanopore data enables cost-effective and efficient indel profiling, yielding results comparable to common Sanger sequencing-based methods.

Comparative analysis of bottom trawl and nanopore sequencing in fish biodiversity assessment: The sylt outer reef example

The assessment of fish diversity is crucial for effective conservation and management strategies, especially in ecologically sensitive regions such as marine protected areas. This study contrasts the effectiveness of environmental DNA (eDNA) metabarcoding analysis employing Nanopore technology with compare beam trawl surveys at the Sylt Outer Reef, a Natura 2000 site in the North Sea, Germany. Out of the 17 fish species caught in a bottom trawl (using a 3m beam trawl), 14 were also identified through eDNA extracted from water samples. The three species not detected in the eDNA results were absent because they lacked representation in public DNA databases. The eDNA method detected twice as many fish species as the beam trawl, totalling 36 species, of which 14 were also detected by the trawl. Additionally, the selection of primers (Mifish) facilitated the identification of one marine mammal species, the harbour porpoise. In conclusion, the findings underscore the potential of eDNA coupled with MinION sequencing (Long read technology) as a robust tool for biodiversity assessment, surpassing traditional methods in detecting species richness.

GROND: a quality-checked and publicly available database of full-length 16S-ITS-23S rRNA operon sequences

Sequence comparison of 16S rRNA PCR amplicons is an established approach to taxonomically identify bacterial isolates and profile complex microbial communities. One potential application of recent advances in long-read sequencing technologies is to sequence entire rRNA operons and capture significantly more phylogenetic information compared to sequencing of the 16S rRNA (or regions thereof) alone, with the potential to increase the proportion of amplicons that can be reliably classified to lower taxonomic ranks. Here we describe GROND (Genome-derived Ribosomal Operon Database), a publicly available database of quality-checked 16S-ITS-23S rRNA operons, accompanied by multiple taxonomic classifications. GROND will aid researchers in analysis of their data and act as a standardised database to allow comparison of results between studies.

Improving Bacterial Metagenomic Research through Long-Read Sequencing

Metagenomic sequencing analysis is central to investigating microbial communities in clinical and environmental studies. Short-read sequencing remains the primary approach for metagenomic research; however, long-read sequencing may offer advantages of improved metagenomic assembly and resolved taxonomic identification. To compare the relative performance for metagenomic studies, we simulated short- and long-read datasets using increasingly complex metagenomes comprising 10, 20, and 50 microbial taxa. Additionally, we used an empirical dataset of paired short- and long-read data generated from mouse fecal pellets to assess real-world performance. We compared metagenomic assembly quality, taxonomic classification, and metagenome-assembled genome (MAG) recovery rates. We show that long-read sequencing data significantly improve taxonomic classification and assembly quality. Metagenomic assemblies using simulated long reads were more complete and more contiguous with higher rates of MAG recovery. This resulted in more precise taxonomic classifications. Principal component analysis of empirical data demonstrated that sequencing technology affects compositional results as samples clustered by sequence type, not sample type. Overall, we highlight strengths of long-read metagenomic sequencing for microbiome studies, including improving the accuracy of classification and relative abundance estimates. These results will aid researchers when considering which sequencing approaches to use for metagenomic projects.

Differential microbiota shift on whole romaine lettuce subjected to source or forward processing and on fresh-cut products during cold storage

Romaine lettuce in the U.S. is primarily grown in California or Arizona and either processed near the growing regions (source processing) or transported long distance for processing in facilities serving distant markets (forward processing). Recurring outbreaks of Escherichia coli O157:H7 implicating romaine lettuce in recent years, which sometimes exhibited patterns of case clustering in Northeast and Midwest, have raised industry concerns over the potential impact of forward processing on romaine lettuce food safety and quality. In this study, freshly harvested romaine lettuce from a commercial field destined for both forward and source processing channels was tracked from farm to processing facility in two separate trials. Whole-head romaine lettuce and packaged fresh-cut products were collected from both forward and source facilities for microbiological and product quality analyses. High-throughput amplicon sequencing targeting16S rRNA gene was performed to describe shifts in lettuce microbiota. Total aerobic bacteria and coliform counts on whole-head lettuce and on fresh-cut lettuce at different storage times were significantly (p < 0.05) higher for those from the forward processing facility than those from the source processing facility. Microbiota on whole-head lettuce and on fresh-cut lettuce showed differential shifting after lettuce being subjected to source or forward processing, and after product storage. Consistent with the length of pre-processing delays between harvest and processing, the lettuce quality scores of source-processed romaine lettuce, especially at late stages of 2-week storage, was significantly higher than of forward-processed product (p < 0.05).

Enhancing microbiome research in sub-Saharan Africa

While there are lighthouse examples of microbiome research in sub-Saharan Africa (SSA), a significant proportion of local researchers face several challenges. Here, we highlight prevailing issues limiting microbiome research in SSA and suggest potential technological, societal, and research-based solutions. We emphasize the need for considerable investment in infrastructures, training, and appropriate funding to democratize modern technologies with a view to providing useful data to improve human health.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

Exploring Long-Read Metagenomics for Full Characterization of Shiga Toxin-Producing Escherichia coli in Presence of Commensal E. coli

The characterization of Shiga toxin-producing Escherichia coli (STEC) is necessary to assess their pathogenic potential, but isolation of the strain from complex matrices such as milk remains challenging. In previous work, we have shown the potential of long-read metagenomics to characterize eae-positive STEC from artificially contaminated raw milk without isolating the strain. The presence of multiple E. coli strains in the sample was shown to potentially hinder the correct characterization of the STEC strain. Here, we aimed at determining the STEC:commensal ratio that would prevent the characterization of the STEC. We artificially contaminated pasteurized milk with different ratios of an eae-positive STEC and a commensal E. coli and applied the method previously developed. Results showed that the STEC strain growth was better than the commensal E. coli after enrichment in acriflavine-supplemented BPW. The STEC was successfully characterized in all samples with at least 10 times more STEC post-enrichment compared to the commensal E. coli. However, the presence of equivalent proportions of STEC and commensal E. coli prevented the full characterization of the STEC strain. This study confirms the potential of long-read metagenomics for STEC characterization in an isolation-free manner while refining its limit regarding the presence of background E. coli strains.