Evaluation of nanopore sequencing technology to identify Salmonella enterica Choleraesuis var. Kunzendorf and Orion var. 15+, 34. Int J Food Microbiol 2021;346:109167. [PMID: 33774575 DOI: 10.1016/j.ijfoodmicro.2021.109167]

Evaluation of Long-Read Sequencing Simulators to Assess Real-World Applications for Food Safety

Shiga toxin-producing Escherichia coli (STEC) and Listeria monocytogenes are routinely responsible for severe foodborne illnesses in the United States. Current identification methods utilized by the U.S. Food Safety Inspection Service require at least four days to identify STEC and six days for L. monocytogenes. Adoption of long-read, whole genome sequencing for food safety testing could significantly reduce the time needed for identification, but method development costs are high. Therefore, the goal of this project was to use NanoSim-H software to simulate Oxford Nanopore sequencing reads to assess the feasibility of sequencing-based foodborne pathogen detection and guide experimental design. Sequencing reads were simulated for STEC, L. monocytogenes, and a 1:1 combination of STEC and Bos taurus genomes using NanoSim-H. At least 2500 simulated reads were needed to identify the seven genes of interest targeted in STEC, and at least 500 reads were needed to detect the gene targeted in L. monocytogenes. Genome coverage of 30x was estimated at 21,521, and 11,802 reads for STEC and L. monocytogenes, respectively. Approximately 5-6% of reads simulated from both bacteria did not align with their respective reference genomes due to the introduction of errors. For the STEC and B. taurus 1:1 genome mixture, all genes of interest were detected with 1,000,000 reads, but less than 1x coverage was obtained. The results suggested sample enrichment would be necessary to detect foodborne pathogens with long-read sequencing, but this would still decrease the time needed from current methods. Additionally, simulation data will be useful for reducing the time and expense associated with laboratory experimentation.

The Lytic Activity of Bacteriophage ZCSE9 against Salmonella enterica and Its Synergistic Effects with Kanamycin

Salmonella, the causative agent of several diseases in humans and animals, including salmonellosis, septicemia, typhoid fever, and fowl typhoid, poses a serious threat to global public health and food safety. Globally, reports of therapeutic failures are increasing because of the increase in bacterial antibiotic resistance. Thus, this work highlights the combined phage–antibiotic therapy as a promising approach to combating bacterial resistance. In this manner, the phage ZCSE9 was isolated, and the morphology, host infectivity, killing curve, combination with kanamycin, and genome analysis of this phage were all examined. Morphologically, phage ZCSE9 is a siphovirus with a relatively broad host range. In addition, the phage can tolerate high temperatures until 80 °C with one log reduction and a basic environment (pH 11) without a significant decline. Furthermore, the phage prevents bacterial growth in the planktonic state, according to the results of the time-killing curve. Moreover, using the phage at MOI 0.1 with kanamycin against five different Salmonella serotypes reduces the required antibiotics to inhibit the growth of the bacteria. Comparative genomics and phylogenetic analysis suggested that phage ZCSE9, along with its close relatives Salmonella phages vB_SenS_AG11 and wksl3, belongs to the genus Jerseyvirus. In conclusion, phage ZCSE9 and kanamycin form a robust heterologous antibacterial combination that enhances the effectiveness of a phage-only approach for combating Salmonella.

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.

Sequoia: A Framework for Visual Analysis of RNA Modifications from Direct RNA Sequencing Data

Oxford Nanopore-based long-read direct RNA sequencing protocols are being increasingly used to study the dynamics of RNA metabolic processes due to improvements in read lengths, increased throughput, decreasing cost, ease of library preparation, and convenience. Long-read sequencing enables single-molecule-based detection of posttranscriptional changes, promising novel insights into the functional roles of RNA. However, fulfilling this potential will necessitate the development of new tools for analyzing and exploring this type of data. Although there are tools that allow users to analyze signal information, such as comparing raw signal traces to a nucleotide sequence, they don't facilitate studying each individual signal instance in each read or perform analysis of signal clusters based on signal similarity. Therefore, we present Sequoia, a visual analytics application that allows users to interactively analyze signals originating from nanopore sequencers and can readily be extended to both RNA and DNA sequencing datasets. Sequoia combines a Python-based backend with a multi-view graphical interface that allows users to ingest raw nanopore sequencing data in Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to find attributes of interest. In this tutorial, we illustrate each individual step involved in running Sequoia and in the process dissect input data characteristics. We show how to generate Nanopore sequencing-based visualizations by leveraging dimensionality reduction and parameter tuning to separate modified RNA sequences from their unmodified counterparts. Sequoia's interactive features enhance nanopore-based computational methodologies. Sequoia enables users to construct rationales and hypotheses and develop insights about the dynamic nature of RNA from the visual analysis. Sequoia is available at https://github.com/dnonatar/Sequoia .

Effect of sub-minimum inhibitory concentration of ceftriaxone on the expression of outer membrane proteins in Salmonella enterica serovar Typhi

Multi-drug resistance (MDR) in Salmonella is one of the major reasons for foodborne outbreaks worldwide. Decreased susceptibility of Salmonella Typhi to first-line drugs such as ceftriaxone, ciprofloxacin, and azithromycin has raised concern. Reduced outer membrane proteins (OMPs) permeability and increased efflux pump transportation are considered to be the main reasons for the emergence of antibiotic resistance in Salmonella. The present study aimed to assess the expression of OMPs at sub-lethal concentrations of ceftriaxone in S. Typhi (Sl5037/BC, and Sl05). The S. Typhi strains were exposed to sub-MIC and half of the sub-MIC concentrations of ceftriaxone at three different time intervals (0 min, 40 min, and 180 min) and analyzed for differential expression of OMPs. Further, the expression variation of OMP encoding genes (yaeT, ompX, lamb, ompA, and ybfM) in response to ceftriaxone was evaluated using real-time PCR. The genes like lamB, ompX, and yaeT showed significant downregulation (p < 0.05) compared to the control without antibiotic exposure, whereas ybfM and ompA showed a moderate downregulation. The expression of omp genes such as lamB, ompA, ompX, ybfM, and yaeT were found to be low in the presence of ceftriaxone, followed by time and dose-dependent. The study provides insights into the possible involvement of OMPs in drug resistance of S. Typhi, which could help develop a therapeutic strategy to combat MDR isolates of S. Typhi.

Subtyping Evaluation of Salmonella Enteritidis Using Single Nucleotide Polymorphism and Core Genome Multilocus Sequence Typing with Nanopore Reads

Whole-genome sequencing (WGS) for public health surveillance and epidemiological investigation of foodborne pathogens predominantly relies on sequencing platforms that generate short reads. Continuous improvement of long-read nanopore sequencing, such as Oxford nanopore technologies (ONT), presents a potential for leveraging multiple advantages of the technology in public health and food industry settings, including rapid turnaround and onsite applicability in addition to superior read length. Using an established cohort of Salmonella Enteritidis isolates for subtyping evaluation, we assessed the technical readiness of nanopore long read sequencing for single nucleotide polymorphism (SNP) analysis and core-genome multilocus sequence typing (cgMLST) of a major foodborne pathogen. By multiplexing three isolates per flow cell, we generated sufficient sequencing depths in <7 h of sequencing for robust subtyping. SNP calls by ONT and Illumina reads were highly concordant despite homopolymer errors in ONT reads (R9.4.1 chemistry). In silico correction of such errors allowed accurate allelic calling for cgMLST and allelic difference measurements to facilitate heuristic detection of outbreak isolates. IMPORTANCE Evaluation, standardization, and implementation of the ONT approach to WGS-based, strain-level subtyping is challenging, in part due to its relatively high base-calling error rates and frequent iterations of sequencing chemistry and bioinformatic analytics. Our study established a baseline for the continuously evolving nanopore technology as a viable solution to high-quality subtyping of Salmonella, delivering comparable subtyping performance when used standalone or together with short-read platforms. This study paves the way for evaluating and optimizing the logistics of implementing the ONT approach for foodborne pathogen surveillance in specific settings.

Comparing Long-Read Assemblers to Explore the Potential of a Sustainable Low-Cost, Low-Infrastructure Approach to Sequence Antimicrobial Resistant Bacteria With Oxford Nanopore Sequencing

Long-read sequencing (LRS) can resolve repetitive regions, a limitation of short read (SR) data. Reduced cost and instrument size has led to a steady increase in LRS across diagnostics and research. Here, we re-basecalled FAST5 data sequenced between 2018 and 2021 and analyzed the data in relation to gDNA across a large dataset (n = 200) spanning a wide GC content (25-67%). We examined whether re-basecalled data would improve the hybrid assembly, and, for a smaller cohort, compared long read (LR) assemblies in the context of antimicrobial resistance (AMR) genes and mobile genetic elements. We included a cost analysis when comparing SR and LR instruments. We compared the R9 and R10 chemistries and reported not only a larger yield but increased read quality with R9 flow cells. There were often discrepancies with ARG presence/absence and/or variant detection in LR assemblies. Flye-based assemblies were generally efficient at detecting the presence of ARG on both the chromosome and plasmids. Raven performed more quickly but inconsistently recovered small plasmids, notably a ∼15-kb Col-like plasmid harboring bla KPC . Canu assemblies were the most fragmented, with genome sizes larger than expected. LR assemblies failed to consistently determine multiple copies of the same ARG as identified by the Unicycler reference. Even with improvements to ONT chemistry and basecalling, long-read assemblies can lead to misinterpretation of data. If LR data are currently being relied upon, it is necessary to perform multiple assemblies, although this is resource (computing) intensive and not yet readily available/useable.

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review

Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.