Comparison of Illumina and Oxford Nanopore Sequencing Technologies for Pathogen Detection from Clinical Matrices Using Molecular Inversion Probes

Whole-genome sequencing for antimicrobial surveillance: species-specific quality thresholds and data evaluation from the network of the European Union Reference Laboratory for Antimicrobial Resistance genomic proficiency tests of 2021 and 2022

As antimicrobial resistance (AMR) surveillance shifts to genomics, ensuring the quality of whole-genome sequencing (WGS) data produced across laboratories is critical. Participation in genomic proficiency tests (GPTs) not only increases individual laboratories' WGS capacity but also provides a unique opportunity to improve species-specific thresholds for WGS quality control (QC) by repeated resequencing of distinct isolates. Here, we present the results of the EU Reference Laboratory for Antimicrobial Resistance (EURL-AR) network GPTs of 2021 and 2022, which included 25 EU national reference laboratories (NLRs). A total of 392 genomes from 12 AMR-bacteria were evaluated based on WGS QC metrics. Two percent (n = 9) of the data were excluded, due to contamination, and 11% (n = 41) of the remaining genomes were identified as outliers in at least one QC metric and excluded from computation of the adjusted QC thresholds (AQT). Two QC metric correlation groups were identified through linear regression. Eight percent (n = 28) of the submitted genomes, from 11 laboratories, failed one or more of the AQTs. However, only three laboratories (12%) were identified as underperformers, failing across AQTs for uncorrelated QC metrics in at least two genomes. Finally, new species-specific thresholds for "N50" and "number of contigs > 200 bp" are presented for guidance in routine laboratory QC. The continued participation of NRLs in GPTs will reveal WGS workflow flaws and improve AMR surveillance data. GPT data will continue to contribute to the development of reliable species-specific thresholds for routine WGS QC, standardizing sequencing data QC and ensure inter- and intranational laboratory comparability.IMPORTANCEIllumina next-generation sequencing is an integral part of antimicrobial resistance (AMR) surveillance and the most widely used whole-genome sequencing (WGS) platform. The high-throughput, relative low-cost, high discriminatory power, and rapid turnaround time of WGS compared to classical biochemical methods means the technology will likely remain a fundamental tool in AMR surveillance and public health. In this study, we present the current level of WGS capacity among national reference laboratories in the EU Reference Laboratory for AMR network, summarizing applied methodology and statistically evaluating the quality of the obtained sequence data. These findings provide the basis for setting new and revised thresholds for quality metrics used in routine WGS, which have previously been arbitrarily defined. In addition, underperforming participants are identified and encouraged to evaluate their workflows to produce reliable results.

Applications of Nanopore sequencing in precision cancer medicine

Oxford Nanopore Technologies sequencing, also referred to as Nanopore sequencing, stands at the forefront of a revolution in clinical genetics, offering the potential for rapid, long read, and real-time DNA and RNA sequencing. This technology is currently making sequencing more accessible and affordable. In this comprehensive review, we explore its potential regarding precision cancer diagnostics and treatment. We encompass a critical analysis of clinical cases where Nanopore sequencing was successfully applied to identify point mutations, splice variants, gene fusions, epigenetic modifications, non-coding RNAs, and other pivotal biomarkers that defined subsequent treatment strategies. Additionally, we address the challenges of clinical applications of Nanopore sequencing and discuss the current efforts to overcome them.

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.

Comparison of Nanopore and Synthesis-Based Next-Generation Sequencing Platforms for SARS-CoV-2 Variant Monitoring in Wastewater

Shortly after the beginning of the SARS-CoV-2 pandemic, many countries implemented sewage sentinel systems to monitor the circulation of the virus in the population. A fundamental part of these surveillance programs is the variant tracking through sequencing approaches to monitor and identify new variants or mutations that may be of importance. Two of the main sequencing platforms are Illumina and Oxford Nanopore Technologies. Here, we compare the performance of MiSeq (Illumina) and MinION (Oxford Nanopore Technologies), as well as two different data processing pipelines, to determine the effect they may have on the results. MiSeq showed higher sequencing coverage, lower error rate, and better capacity to detect and accurately estimate variant abundances than MinION R9.4.1 flow cell data. The use of different variant callers (LoFreq and iVar) and approaches to calculate the variant proportions had a remarkable impact on the results generated from wastewater samples. Freyja, coupled with iVar, may be more sensitive and accurate than LoFreq, especially with MinION data, but it comes at the cost of having a higher error rate. The analysis of MinION R10.4.1 flow cell data using Freyja combined with iVar narrows the gap with MiSeq performance in terms of read quality, accuracy, sensitivity, and number of detected mutations. Although MiSeq should still be considered as the standard method for SARS-CoV-2 variant tracking, MinION's versatility and rapid turnaround time may represent a clear advantage during the ongoing pandemic.

Technical comparison of MinIon and Illumina technologies for genotyping Chikungunya virus in clinical samples

New-generation sequencing (NGS) techniques have brought the opportunity for genomic monitoring of several microorganisms potentially relevant to public health. The establishment of different methods with different mechanisms provides a wide choice, taking into account several aspects. With that in mind, the present aim of the study was to compare basic genomic sequencing metrics that could potentially impact genotyping by nanopores from Oxford Nanopore Technologies and by synthesis from Illumina in clinical samples positive for Chikungunya (CHIKV). Among the metrics studied, running time, read production, and Q score were better represented in Illumina sequencing, while the MinIOn platform showed better response time and greater diversity of generated files. That said, it was possible to establish differences between the studied metrics in addition to verifying that the distinctions in the methods did not impact the identification of the CHIKV virus genotype.

Gut microbiome profiling of neonates using Nanopore MinION and Illumina MiSeq sequencing

This study aimed to evaluate the difference in gut microbiomes between preterm and term infants using third-generation long-read sequencing (Oxford Nanopore Technologies, ONT) compared with an established gold standard, Illumina (second-generation short-read sequencing). A total of 69 fecal samples from 51 term (T) and preterm (P) infants were collected at 7 and 28 days of life. Gut colonization profiling was performed by 16S rRNA gene sequencing using ONT. We used Illumina to validate and compare the patterns in 13 neonates. Using bioinformatic analysis, we identified features that differed between P and T. Both T1 and P1 microbiomes were dominated by Firmicutes (Staphylococcus and Enterococcus), whereas sequentially showed dominant transitions to Lactobacillus (p < 0.001) and Streptococcus in T2 (p = 0.001), and pathogenic bacteria (Klebsiella) in P2 (p = 0.001). The abundance of beneficial bacteria (Bifidobacterium and Lactobacillus) increased in T2 (p = 0.026 and p < 0.001, respectively). These assignments were correlated with the abundance at the species-level. Bacterial α-diversity increased in T (p = 0.005) but not in P (p = 0.156), and P2 showed distinct β-diversity clustering than T2 (p = 0.001). The ONT reliably identified pathogenic bacteria at the genus level, and taxonomic profiles were comparable to those identified by Illumina at the genus level. This study shows that ONT and Illumina are highly correlated. P and T had different microbiome profiles, and the α- and β-diversity varied. ONT sequencing has potential for pathogen detection in neonates in clinical settings.

A case for investment in clinical metagenomics in low-income and middle-income countries

Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.

Challenges and Opportunities for Global Genomic Surveillance Strategies in the COVID-19 Era

Global SARS-CoV-2 genomic surveillance efforts have provided critical data on the ongoing evolution of the virus to inform best practices in clinical care and public health throughout the pandemic. Impactful genomic surveillance strategies generally follow a multi-disciplinary pipeline involving clinical sample collection, viral genotyping, metadata linkage, data reporting, and public health responses. Unfortunately, current limitations in each of these steps have compromised the overall effectiveness of these strategies. Biases from convenience-based sampling methods can obfuscate the true distribution of circulating variants. The lack of standardization in genotyping strategies and bioinformatic expertise can create bottlenecks in data processing and complicate interpretation. Limitations and inconsistencies in clinical and demographic data collection and sharing can slow the compilation and limit the utility of comprehensive datasets. This likewise can complicate data reporting, restricting the availability of timely data. Finally, gaps and delays in the implementation of genomic surveillance data in the public health sphere can prevent officials from formulating effective mitigation strategies to prevent outbreaks. In this review, we outline current SARS-CoV-2 global genomic surveillance methods and assess roadblocks at each step of the pipeline to identify potential solutions. Evaluating the current obstacles that impede effective surveillance can improve both global coordination efforts and pandemic preparedness for future outbreaks.

Expedited retrieval of high-quality Usutu virus genomes via Nanopore sequencing with and without target enrichment

Usutu virus (USUV) is a mosquito-borne zoonotic virus and one of the causes of flavivirus encephalitis in birds and occasionally in humans. USUV rapidly disperses in a susceptible host and vector environment, as is the case in South and Central Europe. However, compared to other flaviviruses, USUV has received less research attention and there is therefore limited access to whole-genome sequences and also to in-depth phylogenetic and phylodynamic analyses. To ease future molecular studies, this study compares first- (partial sequencing via Sanger), second- (Illumina), and third-generation (MinION Nanopore) sequencing platforms for USUV. With emphasis on MinION Nanopore sequencing, cDNA-direct and target-enrichment (amplicon-based) sequencing approaches were validated in parallel. The study was based on four samples from succumbed birds commonly collected throughout Germany. The samples were isolated from various sample matrices, organs as well as blood cruor, and included three different USUV lineages. We concluded that depending on the focus of a research project, amplicon-based MinION Nanopore sequencing can be an ideal cost- and time-effective alternative to Illumina in producing optimal genome coverage. It can be implemented for an array of lab- or field-based objectives, including among others: phylodynamic studies and the analysis of viral quasispecies.

Nanopore-based metagenomic sequencing for the rapid and precise detection of pathogens among immunocompromised cancer patients with suspected infections

Cancer patients are at high risk of infections and infection-related mortality; thereby, prompt diagnosis and precise anti-infectives treatment are critical. This study aimed to evaluate the performance of nanopore amplicon sequencing in identifying microbial agents among immunocompromised cancer patients with suspected infections. This prospective study enlisted 56 immunocompromised cancer patients with suspected infections. Their body fluid samples such as sputum and blood were collected, and potential microbial agents were detected in parallel by nanopore amplicon sequencing and the conventional culture method. Among the 56 body fluid samples, 47 (83.9%) samples were identified to have at least one pathogen by nanopore amplicon sequencing, but only 25 (44.6%) samples exhibited a positive finding by culture. Among 31 culture-negative samples, nanopore amplicon sequencing successfully detected pathogens in 22 samples (71.0%). Nanopore amplicon sequencing showed a higher sensitivity in pathogen detection than that of the conventional culture method (83.9% vs. 44.6%, P<0.001), and this advantage both existed in blood samples (38.5% vs. 0%, P=0.039) and non-blood samples (97.7% vs. 58.1%, P<0.001). Compared with the culture method, nanopore amplicon sequencing illustrated more samples with bacterial infections (P<0.001), infections from fastidious pathogens (P=0.006), and co-infections (P<0.001). The mean turnaround time for nanopore amplicon sequencing was about 17.5 hours, which was shorter than that of the conventional culture assay. This study suggested nanopore amplicon sequencing as a rapid and precise method for detecting pathogens among immunocompromised cancer patients with suspected infections. The novel and high-sensitive method will improve the outcomes of immunocompromised cancer patients by facilitating the prompt diagnosis of infections and precise anti-infectives treatment.