Clinical and biological insights from viral genome sequencing

A serotype-specific and tiled amplicon multiplex PCR method for whole genome sequencing of dengue virus

Dengue fever, a mosquito-borne viral disease of significant public health concern in tropical and subtropical regions, is caused by any of the four serotypes of the dengue virus (DENV1-4). Cutting-edge technologies like next-generation sequencing (NGS) are revolutionizing virology, enabling in-depth exploration of DENV's genetic diversity. Here, we present an optimized workflow for full-genome sequencing of DENV 1-4 utilizing tiled amplicon multiplex PCR and Illumina sequencing. Our assay, sequenced on the Illumina MiSeq platform, demonstrates its ability to recover the full-length dengue genome across various viral abundances in clinical specimens with high-quality base coverage. This high quality underscores its suitability for precise examination of intra-host diversity, enriching our understanding of viral evolution and holding potential for improved diagnostic and intervention strategies in regions facing dengue outbreaks.

Whole-Genome Sequencing-Based Confirmatory Methods on RT-qPCR Results for the Detection of Foodborne Viruses in Frozen Berries

Accurate detection, identification, and subsequent confirmation of pathogens causing foodborne illness are essential for the prevention and investigation of foodborne outbreaks. This is particularly true when the causative agent is an enteric virus that has a very low infectious dose and is likely to be present at or near the limit of detection. In this study, whole-genome sequencing (WGS) was combined with either of two non-targeted pre-amplification methods (SPIA and SISPA) to investigate their utility as a confirmatory method for RT-qPCR positive results of foods contaminated with enteric viruses. Frozen berries (raspberries, strawberries, and blackberries) were chosen as the food matrix of interest due to their association with numerous outbreaks of foodborne illness. The hepatitis A virus (HAV) and human norovirus (HuNoV) were used as the contaminating agents. The non-targeted WGS strategy employed in this study could detect and confirm HuNoV and HAV at genomic copy numbers in the single digit range, and in a few cases, identified viruses present in samples that had been found negative by RT-qPCR analyses. However, some RT-qPCR-positive samples could not be confirmed using the WGS method, and in cases with very high Ct values, only a few viral reads and short sequences were recovered from the samples. WGS techniques show great potential for confirmation and identification of virally contaminated food items. The approaches described here should be further optimized for routine application to confirm the viral contamination in berries.

RSV-GenoScan: An automated pipeline for whole-genome human respiratory syncytial virus (RSV) sequence analysis

BACKGROUND

Advances in high-throughput sequencing (HTS) technologies and reductions in sequencing costs have revolutionised the study of genomics and molecular biology by making whole-genome sequencing (WGS) accessible to many laboratories. However, the analysis of WGS data requires significant computational effort, which is the major drawback in implementing WGS as a routine laboratory technique.

OBJECTIVE

Automated pipelines have been developed to overcome this issue, but they do not exist for all organisms. This is the case for human respiratory syncytial virus (RSV), which is a leading cause of lower respiratory tract infections in infants, the elderly, and immunocompromised adults.

RESULTS

We present RSV-GenoScan, a fast and easy-to-use pipeline for WGS analysis of RSV generated by HTS on Illumina or Nanopore platforms. RSV-GenoScan automates the WGS analysis steps directly from the raw sequence data. The pipeline filters the sequence data, maps the reads to the RSV reference genomes, generates a consensus sequence, identifies the RSV subgroup, and lists amino acid mutations, insertions and deletions in the F and G viral genes. This enables the rapid identification of mutations in these coding genes that are known to confer resistance to monoclonal antibodies.

AVAILABILITY

RSV-GenoScan is freely available at https://github.com/AlexandreD-bio/RSV-GenoScan.

Efficient wastewater sample filtration improves the detection of SARS-CoV-2 variants: An extensive analysis based on sequencing parameters

During the SARS-CoV-2 pandemic, many countries established wastewater (WW) surveillance to objectively monitor the level of infection within the population. As new variants continue to emerge, it has become clear that WW surveillance is an essential tool for the early detection of variants. The EU Commission published a recommendation suggesting an approach to establish surveillance of SARS-CoV-2 and its variants in WW, besides specifying the methodology for WW concentration and RNA extraction. Therefore, different groups have approached the issue with different strategies, mainly focusing on WW concentration methods, but only a few groups highlighted the importance of prefiltering WW samples and/or purification of RNA samples. Aiming to obtain high-quality sequencing data allowing variants detection, we compared four experimental conditions generated from the treatment of: i) WW samples by WW filtration and ii) the extracted RNA by DNase treatment, purification and concentration of the extracted RNA. To evaluate the best condition, the results were assessed by focusing on several sequencing parameters, as the outcome of SARS-CoV-2 sequencing from WW is crucial for variant detection. Overall, the best sequencing result was obtained by filtering the WW sample. Moreover, the present study provides an overview of some sequencing parameters to consider when optimizing a method for monitoring SARS-CoV-2 variants from WW samples, which can also be applied to any sample preparation methodology.

Multimodal data fusion using sparse canonical correlation analysis and cooperative learning: a COVID-19 cohort study

Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse linear methods in a COVID-19 patient cohort. This prospective cohort study of 149 adult patients was conducted in a tertiary care academic center. First, we used sparse canonical correlation analysis (CCA) to identify and quantify relationships across different data modalities, including viral genome sequencing, imaging, clinical data, and laboratory results. Then, we used cooperative learning to predict the clinical outcome of COVID-19 patients: Intensive care unit admission. We show that serum biomarkers representing severe disease and acute phase response correlate with original and wavelet radiomics features in the LLL frequency channel (cor(Xu1, Zv1) = 0.596, p value < 0.001). Among radiomics features, histogram-based first-order features reporting the skewness, kurtosis, and uniformity have the lowest negative, whereas entropy-related features have the highest positive coefficients. Moreover, unsupervised analysis of clinical data and laboratory results gives insights into distinct clinical phenotypes. Leveraging the availability of global viral genome databases, we demonstrate that the Word2Vec natural language processing model can be used for viral genome encoding. It not only separates major SARS-CoV-2 variants but also allows the preservation of phylogenetic relationships among them. Our quadruple model using Word2Vec encoding achieves better prediction results in the supervised task. The model yields area under the curve (AUC) and accuracy values of 0.87 and 0.77, respectively. Our study illustrates that sparse CCA analysis and cooperative learning are powerful techniques for handling high-dimensional, multimodal data to investigate multivariate associations in unsupervised and supervised tasks.

An Amplicon-Based Application for the Whole-Genome Sequencing of GI-19 Lineage Infectious Bronchitis Virus Directly from Clinical Samples

Infectious bronchitis virus (IBV) causes a highly contagious respiratory disease in chickens, leading to significant economic losses in the poultry industry worldwide. IBV exhibits a high mutation rate, resulting in the continuous emergence of new variants and strains. A complete genome analysis of IBV is crucial for understanding its characteristics. However, it is challenging to obtain whole-genome sequences from IBV-infected clinical samples due to the low abundance of IBV relative to the host genome. Here, we present a novel approach employing next-generation sequencing (NGS) to directly sequence the complete genome of IBV. Through in silico analysis, six primer pairs were designed to match various genotypes, including the GI-19 lineage of IBV. The primer sets successfully amplified six overlapping fragments by long-range PCR and the size of the amplicons ranged from 3.7 to 6.4 kb, resulting in full coverage of the IBV genome. Furthermore, utilizing Illumina sequencing, we obtained the complete genome sequences of two strains belonging to the GI-19 lineage (QX genotype) from clinical samples, with 100% coverage rates, over 1000 × mean depth coverage, and a high percentage of mapped reads to the reference genomes (96.63% and 97.66%). The reported method significantly improves the whole-genome sequencing of IBVs from clinical samples; thus, it can improve understanding of the epidemiology and evolution of IBVs.

The clinical and epidemiological impacts of whole genomic sequencing on bacterial and virological agents

Whole Genome Sequencing (WGS) is a molecular biology tool consisting in the sequencing of the entire genome of a given organism. Due to its ability to provide the finest available resolution of bacterial and virological genetics, it is used at several levels in the field of infectiology. On an individual scale and through application of a single technique, it enables the typological identification and characterization of strains, the characterization of plasmids, and enhanced search for resistance genes and virulence factors. On a collective scale, it enables the characterization of strains and the determination of phylogenetic links between different microorganisms during community outbreaks and healthcare-associated epidemics. The information provided by WGS enables real-time monitoring of strain-level epidemiology on a worldwide scale, and facilitates surveillance of the resistance dissemination and the introduction or emergence of pathogenic variants in humans or their environment. There are several possible approaches to completion of an entire genome. The choice of one method rather than another is essentially dictated by the matrix, either a clinical sample or a culture isolate, and the clinical objective. WGS is an advanced technology that remains costly despite a gradual decrease in its expenses, potentially hindering its implementation in certain laboratories and thus its use in routine microbiology. Even though WGS is making steady inroads as a reference method, efforts remain needed in view of so harmonizing its interpretations and decreasing the time to generation of conclusive results.

Application of next-generation sequencing to identify different pathogens

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Investigating the etiologies of non-malarial febrile illness in Senegal using metagenomic sequencing

The worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata in a cross-sectional study of febrile patients and healthy controls in a low malaria burden area. Using 16S and untargeted sequencing, we detected viral, bacterial, or eukaryotic pathogens in 23% (38/163) of NMFI cases. Bacteria were the most common, with relapsing fever Borrelia and spotted fever Rickettsia found in 15.5% and 3.8% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosed Plasmodium, including one putative P. ovale infection. We developed a logistic regression model that can distinguish Borrelia from NMFIs with similar presentation based on symptoms and vital signs (F1 score: 0.823). These results highlight the challenge and importance of improved diagnostics, especially for Borrelia, to support diagnosis and surveillance.

Unravelling the enigma of the human microbiome: Evolution and selection of sequencing technologies

The human microbiome plays a crucial role in maintaining health, with advances in high-throughput sequencing technology and reduced sequencing costs triggering a surge in microbiome research. Microbiome studies generally incorporate five key phases: design, sampling, sequencing, analysis, and reporting, with sequencing strategy being a crucial step offering numerous options. Present mainstream sequencing strategies include Amplicon sequencing, Metagenomic Next-Generation Sequencing (mNGS), and Targeted Next-Generation Sequencing (tNGS). Two innovative technologies recently emerged, namely MobiMicrobe high-throughput microbial single-cell genome sequencing technology and 2bRAD-M simplified metagenomic sequencing technology, compensate for the limitations of mainstream technologies, each boasting unique core strengths. This paper reviews the basic principles and processes of these three mainstream and two novel microbiological technologies, aiding readers in understanding the benefits and drawbacks of different technologies, thereby guiding the selection of the most suitable method for their research endeavours.

Innovation and Patenting Activities During COVID-19 and Advancement of Biochemical and Molecular Diagnosis in the Post- COVID-19 Era

The COVID-19 pandemic is to escalate globally and acquire new mutations quickly, so accurate diagnostic technologies play a vital role in controlling and understanding the epidemiology of the disease. A plethora of technologies acquires diagnosis of individuals and informs clinical management of COVID. Some important biochemical parameters for COVID diagnosis are the elevation of liver enzymes, creatinine, and nonspecific inflammatory markers such as C-reactive protein (CRP) and Interleukin 6 (IL-6). The main progression predictors are lymphopenia, elevated D-dimer, and hyperferritinemia, although it is also necessary to consider LDH, CPK, and troponin in the marker panel of diagnosis. Owing to the greater sensitivity and accuracy, molecular technologies such as conventional polymerase chain reaction (PCR), reverse transcription (RT)-PCR, nested PCR, loop-mediated isothermal amplification (LAMP), and xMAP technology have been extensively used for COVID diagnosis for some time now. To make so many diagnostics accessible to general people, many techniques may be exploited, including point of care (POC), also called bedside testing, which is developing as a portable promising tool in pathogen identification. Some other lateral flow assay (LFA)-centered techniques like SHERLOCK, CRISPR-Cas12a (AIOD-CRISPR), and FNCAS9 editor limited uniform detection assay (FELUDA), etc. have shown auspicious results in the rapid detection of pathogens. More recently, low-cost sequencing and advancements in big data management have resulted in a slow but steady rise of next-generation sequencing (NGS)-based approaches for diagnosis that have potential relevance for clinical purposes and may pave the way toward a better future. Due to the COVID-19 pandemic, various institutions provided free, specialized websites and tools to promote research and access to critically needed advanced solutions by alleviating research and analysis of data within a substantial body of scientific and patent literature regarding biochemical and molecular diagnosis published since January 2020. This circumstance is unquestionably unique and difficult for anyone using patent information to find pertinent disclosures at a specific date in a trustworthy manner.

Metagenomics in the fight against zoonotic viral infections: A focus on SARS-CoV-2 analogues

Zoonotic viral infections continue to pose significant threats to global public health, as highlighted by the COVID-19 pandemic caused by the SARS-CoV-2 virus. The emergence of SARS-CoV-2 served as a stark reminder of the potential for zoonotic transmission of viruses from animals to humans. Understanding the origins and dynamics of zoonotic viruses is critical for early detection, prevention, and effective management of future outbreaks. Metagenomics has emerged as a powerful tool for investigating the virome of diverse ecosystems, shedding light on the diversity of viral populations, their hosts, and potential zoonotic spillover events. We provide an in-depth examination of metagenomic approaches, including, NGS metagenomics, shotgun metagenomics, viral metagenomics, and single-virus metagenomics, highlighting their strengths and limitations in identifying and characterizing zoonotic viral pathogens. This review underscores the pivotal role of metagenomics in enhancing our ability to detect, monitor, and mitigate zoonotic viral infections, using SARS-CoV-2 analogues as a case study. We emphasize the need for continued interdisciplinary collaboration among virologists, ecologists, and bioinformaticians to harness the full potential of metagenomic approaches in safeguarding public health against emerging zoonotic threats.

Recovery of complete genome sequences of Crimean-Congo haemorrhagic fever virus (CCHFV) directly from clinical samples: A comparative study between targeted enrichment and metagenomic approaches

Crimean-Congo haemorrhagic fever (CCHF) is the most prevalent human tick-borne viral disease, endemic to the Balkans, Africa, Middle East and Asia. There are currently no licensed vaccines or effective antivirals against CCHF. CCHF virus (CCHFV) has a negative sense segmented tripartite RNA genome consisting of the small (S), medium (M) and large (L) segments. Depending on the segment utilised for genetic affiliation, there are up to 7 circulating lineages of CCHFV. The current lack of geographical representation of CCHFV sequences in various repositories highlights a requirement for increased CCHFV sequencing capabilities in endemic regions. We have optimised and established a multiplex PCR tiling methodology for the targeted enrichment of complete genomes of Europe 1 CCHFV lineage directly from clinical samples and compared its performance to a non-targeted enrichment approach on both short-read and long-read sequencing platforms. We have found a statistically significant increase in mapped viral sequencing reads produced with our targeted enrichment approach. This has allowed us to recover near complete S segment sequences and above 90% of the M and L segment sequences for samples with Ct values as high as 31.3. This study demonstrates the superiority of a targeted enrichment approach for recovery of CCHFV genomic sequences from samples with low virus titre. CCHFV is an important vector-borne human pathogen with wide geographical distribution. The validated methodology reported here adds value to front-line public health laboratories employing genomic sequencing for CCHFV Europe 1 lineage surveillance, particularly in the Balkan and Middle Eastern territories currently monitoring the spread of the pathogen. Tracking the genomic evolution of the virus across regions improves risk assessment and directly informs the development of diagnostics, therapeutics, and vaccines.

Metatranscriptomic RNA-Seq Data Analysis of Virus-Infected Host Cells

RNA sequencing (RNA-seq) analysis of virus-infected host cells enables researchers to study a wide range of phenomena involving host-virus interactions. This includes genomic analysis of the viral population itself, as well as analysis of the transcriptional dynamics of the virus and host during infection. In this chapter, we provide a guide for researchers interested in performing RNA-seq data analysis of virus-infected host cells or cell lines. We outline several bioinformatic protocols for quantifying viral abundance, assembling viral genomes from mixed samples, and performing differential expression analysis, among other common workflows. These workflows can be used as starting points for researchers aiming to analyze RNA-seq datasets of mixed samples containing both host and viral RNA, such as virus-infected cell lines or clinical samples.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

An FM-Index Based High-Throughput Memory-Efficient FPGA Accelerator for Paired-End Short-Read Mapping

This article presents an Ferragina-Manzini index (FM-index) based paired-end short-read mapping hardware accelerator. Four techniques are proposed to significantly reduce the number of memory accesses and operations to improve the throughput. First, an interleaved data structure is proposed to reduce the processing time by 51.8% by leveraging the data locality. Second, the boundaries of possible mapping location candidates can be retrieved within only one memory access by constructing a lookup table along with the FM-index. This reduces the number of DRAM accesses by 60% with only a 64 MB memory overhead. Third, an additional step is added to skip the time-consuming repetitive location candidates filtering conditionally, avoiding unnecessary operations. Lastly, an early termination method is proposed to terminate the mapping process if any location candidate with a high enough alignment score is detected, greatly decreasing the execution time. Overall, the computation time is reduced by 92.6% with only a 2% memory overhead in DRAM. The proposed methods are realized on a Xilinx Alveo U250 FPGA. The proposed FPGA accelerator processes 1,085,812,766 short-reads from the U.S. Food and Drug Administration (FDA) dataset within 35.4 minutes at 200 MHz. It achieves a 1.7-to-18.6× higher throughput and the highest 99.3% accuracy by exploiting the paired-end short-read mapping, compared to state-of-the-art FPGA-based designs.

Complex norovirus transmission dynamics at hospital wards revealed by deep sequencing

Detailed knowledge regarding norovirus transmission within hospitals is limited. We investigated a norovirus hospital outbreak affecting 65 patients at five different wards. PCR showed that 61 (94%) of the patients were infected with genotype II.4 strains. Successful Ion Torrent deep sequencing of GII.4 positive samples from 59 patients followed by phylogenetic analysis revealed that all sequences but two clustered into four distinct clades. Two of the clades belonged to GII.4 Sydney 2012, while the other two belonged to GII.4 New Orleans 2009. One of the clades was predominant at two wards, while two clades were predominant at one ward each. The fourth clade was found in sporadic cases at several wards. Thus, at four out of five wards, variants from one clade were predominant. At one ward, a single clade accounted for all cases, while at three wards the predominant clade accounted for 60%-71% of cases. Analysis of quasispecies variation identified positions that could further discriminate between variants from separate wards. The results illustrate a complex transmission of healthcare-associated norovirus infections and show that sequencing can be used to discriminate between related and unrelated cases.

Genetic diversity and molecular evolution of Seoul virus in Hebei province, China

Seoul virus (SEOV) is a major pathogen which causes hemorrhagic fever with renal syndrome (HFRS), and is present all over the world. However, there are currently few long-term systematic studies of SEOV's phylogenetic and evolutionary mechanisms in epidemic areas. Thus, in this study, we used RT-PCR combined with NGS to obtain the genomes of six SEOV viruses from 1993, as well as 56 Hebei province-specific tissue samples from 1999 to 2022. Phylogenetic analysis showed that the SEOV samples could be divided into seven groups and showed geographic clustering. The geographic region may be the main factor affecting the genetic diversity of SEOV. We also found that SEOV was subject to strong overall purifying selection and positive selection at certain sites during evolution. Recombination events and high nucleotide substitution rates were also shown to accelerate SEOV's evolution. Evolutionary feature of the L segment is more representative of complete genome. Our detailed analysis provides a deeper understanding of the genetic diversity and evolutionary drivers of SEOV within its primary epidemic areas. It will be important to further monitor epidemiological trends and drivers of variation to help increase our understanding of the pathogenicity of SEOV infections.

Whole-genome sequencing to investigate transmission of SARS-CoV-2 in the acute healthcare setting: a systematic review

BACKGROUND

Whole-genome sequencing (WGS) has been used widely to elucidate transmission of SARS-CoV-2 in acute healthcare settings, and to guide infection, prevention, and control (IPC) responses.

AIM

To systematically appraise available literature, published between January 1st, 2020 and June 30th, 2022, describing the implementation of WGS in acute healthcare settings to characterize nosocomial SARS-CoV-2 transmission.

METHODS

Searches of the PubMed, Embase, Ovid MEDLINE, EBSCO MEDLINE, and Cochrane Library databases identified studies in English reporting the use of WGS to investigate SARS-CoV-2 transmission in acute healthcare environments. Publications involved data collected up to December 31st, 2021, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

FINDINGS

In all, 3088 non-duplicate records were retrieved; 97 met inclusion criteria, involving 62 outbreak analyses and 35 genomic surveillance studies. No publications from low-income countries were identified. In 87/97 (90%), WGS supported hypotheses for nosocomial transmission, while in 46 out of 97 (47%) suspected transmission events were excluded. An IPC intervention was attributed to the use of WGS in 18 out of 97 (18%); however, only three (3%) studies reported turnaround times ≤7 days facilitating near real-time IPC action, and none reported an impact on the incidence of nosocomial COVID-19 attributable to WGS.

CONCLUSION

WGS can elucidate transmission of SARS-CoV-2 in acute healthcare settings to enhance epidemiological investigations. However, evidence was not identified to support sequencing as an intervention to reduce the incidence of SARS-CoV-2 in hospital or to alter the trajectory of active outbreaks.

Lateral flow assay of pathogenic viruses and bacteria in healthcare

Healthcare-associated pathogenic viruses and bacteria can have a serious impact on human health and have attracted widespread global attention. The lateral flow assay is a unidirectional detection based on the binding of a target analyte and a bioreceptor on the device via lateral flow. With incredible advantages over traditional chromatographic methods, such as rapid detection, ease of manufacture and cost effectiveness, these test strips are increasingly considered the ideal form for point-of-care applications. This review explores lateral flow assays for pathogenic viruses and bacteria, with a particular focus on methodologies, device components, construction methods, and applications. We anticipate that this review could provide exciting opportunities for developing new lateral flow devices for pathogens and advance related healthcare applications.

Multiplexed CRISPR-based Methods for Pathogen Nucleic Acid Detection

Bacterial and viral pathogens are devastating to human health and well-being. In many regions, dozens of pathogen species and variants co-circulate. Thus, it is important to detect many different species and variants of pathogens in a given sample through multiplexed detection methods. CRISPR-based nucleic acid detection has shown to be a promising step towards an easy-to-use sensitive, specific, and high-throughput method to detect nucleic acids from DNA and RNA viruses and bacteria. Here, we review the current state of multiplexed nucleic acid detection methods with a focus on CRISPR-based methods. We also look toward the future of multiplexed point-of-care diagnostics.

Improving diagnosis of non-malarial fevers in Senegal: Borrelia and the contribution of tick-borne bacteria

The worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata from febrile patients and healthy controls in a low malaria burden area. Using 16S and unbiased sequencing, we detected viral, bacterial, or eukaryotic pathogens in 29% of NMFI cases. Bacteria were the most common, with relapsing fever Borrelia and spotted fever Rickettsia found in 15% and 3.7% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosed Plasmodium, including one putative P. ovale infection. We developed a logistic regression model to distinguish Borrelia from NMFIs with similar presentation based on symptoms and vital signs. These results highlight the challenge and importance of improved diagnostics, especially for Borrelia, to support diagnosis and surveillance.

Mpox: a review of laboratory detection techniques

Mpox (formerly monkeypox) is a zoonotic disease caused by monkeypox virus (MPXV), which, like smallpox, is characterised by skin rashes. While the world is currently grappling with the coronavirus disease 2019 pandemic, the appearance of MPXV has presented a global threat and raised concerns worldwide. Since May 2022, MPXV has spread rapidly in non-endemic mpox areas. As of 27 June 2023, the virus has spread to more than 112 countries and regions, with over 88,060 laboratory-confirmed cases and 147 deaths. Thus, measures to control the mpox epidemic are urgently needed. As the principal methods for identifying and monitoring mpox, laboratory detection techniques play an important role in mpox diagnosis. This review summarises the currently-used laboratory techniques for MPXV detection, discusses progress in improving these methods, and compares the benefits and limitations of various diagnostic detection methods. Currently, nucleic acid amplification tests, such as the polymerase chain reaction, are the most commonly used. Immunological methods have also been applied to diagnose the disease, which can help us discover new features of MPXV, improve diagnostic accuracy, track epidemic trends, and guide future prevention and control strategies, which are also vital for controlling mpox epidemics. This review provides a resource for the scientific community and should stimulate more research and development in alternative diagnostics to be applied to this and future public health crises.

Metagenomic surveillance uncovers diverse and novel viral taxa in febrile patients from Nigeria

Effective infectious disease surveillance in high-risk regions is critical for clinical care and pandemic preemption; however, few clinical diagnostics are available for the wide range of potential human pathogens. Here, we conduct unbiased metagenomic sequencing of 593 samples from febrile Nigerian patients collected in three settings: i) population-level surveillance of individuals presenting with symptoms consistent with Lassa Fever (LF); ii) real-time investigations of outbreaks with suspected infectious etiologies; and iii) undiagnosed clinically challenging cases. We identify 13 distinct viruses, including the second and third documented cases of human blood-associated dicistrovirus, and a highly divergent, unclassified dicistrovirus that we name human blood-associated dicistrovirus 2. We show that pegivirus C is a common co-infection in individuals with LF and is associated with lower Lassa viral loads and favorable outcomes. We help uncover the causes of three outbreaks as yellow fever virus, monkeypox virus, and a noninfectious cause, the latter ultimately determined to be pesticide poisoning. We demonstrate that a local, Nigerian-driven metagenomics response to complex public health scenarios generates accurate, real-time differential diagnoses, yielding insights that inform policy.

Recent Progress in Studies of Porcine Reproductive and Respiratory Syndrome Virus 1 in China

Due to the high incidence of PRRSV mutation and recombination, PRRSV infection is difficult to prevent and control in China and worldwide. Two species of PRRSV, Betaarterivirus suid 1 (PRRSV-1) and Betaarterivirus suid 2 (PRRSV-2), exist in China, and PRRSV-1 has always received less attention in China. However, the number of PRRSV-1 strains detected in China has increased recently. To date, PRRSV-1 has spread to more than 23 regions in China. Based on the phylogenetic analysis of ORF5 and the whole genome of PRRSV-1, Chinese PRRSV-1 can be divided into at least seven independent subgroups. Among them, BJEU06-1-like has become the mainstream subgroup in some regions of China. This subgroup of strains has a 5-aa (4 + 1) characteristic discontinuous deletion pattern at aa 357~aa 360 and aa 411 in Nsp2. Previous studies have indicated that the pathogenicity of PRRSV-1 in China is mild, but recent studies found that the pathogenicity of PRRSV-1 was enhanced in China. Therefore, the emergence of PRRSV-1 deserves attention, and the prevention and control of PRRSV-1 infection in China should be strengthened. PRRSV infection is usually prevented and controlled by a combination of virus monitoring, biosafety restrictions, herd management measures and vaccination. However, the use of PRRSV-1 vaccines is currently banned in China. Thus, we should strengthen the monitoring of PRRSV-1 and the biosafety management of pig herds in China. In this review, we summarize the prevalence of PRRSV-1 in China and clarify the genomic characteristics, pathogenicity, vaccine status, and prevention and control management system of PRRSV-1 in China. Consequently, the purpose of this review is to provide a basis for further development of prevention and control measures for PRRSV-1.

Rapid viral metagenomics using SMART-9N amplification and nanopore sequencing

Emerging and re-emerging viruses are a global health concern. Genome sequencing as an approach for monitoring circulating viruses is currently hampered by complex and expensive methods. Untargeted, metagenomic nanopore sequencing can provide genomic information to identify pathogens, prepare for or even prevent outbreaks. SMART (Switching Mechanism at the 5' end of RNA Template) is a popular approach for RNA-Seq but most current methods rely on oligo-dT priming to target polyadenylated mRNA molecules. We have developed two random primed SMART-Seq approaches, a sequencing agnostic approach 'SMART-9N' and a version compatible rapid adapters  available from Oxford Nanopore Technologies 'Rapid SMART-9N'. The methods were developed using viral isolates, clinical samples, and compared to a gold-standard amplicon-based method. From a Zika virus isolate the SMART-9N approach recovered 10kb of the 10.8kb RNA genome in a single nanopore read. We also obtained full genome coverage at a high depth coverage using the Rapid SMART-9N, which takes only 10 minutes and costs up to 45% less than other methods. We found the limits of detection of these methods to be 6 focus forming units (FFU)/mL with 99.02% and 87.58% genome coverage for SMART-9N and Rapid SMART-9N respectively. Yellow fever virus plasma samples and SARS-CoV-2 nasopharyngeal samples previously confirmed by RT-qPCR with a broad range of Ct-values were selected for validation. Both methods produced greater genome coverage when compared to the multiplex PCR approach and we obtained the longest single read of this study (18.5 kb) with a SARS-CoV-2 clinical sample, 60% of the virus genome using the Rapid SMART-9N method. This work demonstrates that SMART-9N and Rapid SMART-9N are sensitive, low input, and long-read compatible alternatives for RNA virus detection and genome sequencing and Rapid SMART-9N improves the cost, time, and complexity of laboratory work.

Rapid viral metagenomics using SMART-9N amplification and nanopore sequencing

Emerging and re-emerging viruses are a global health concern. Genome sequencing as an approach for monitoring circulating viruses is currently hampered by complex and expensive methods. Untargeted, metagenomic nanopore sequencing can provide genomic information to identify pathogens, prepare for or even prevent outbreaks. SMART (Switching Mechanism at the 5' end of RNA Template) is a popular approach for RNA-Seq but most current methods rely on oligo-dT priming to target polyadenylated mRNA molecules. We have developed two random primed SMART-Seq approaches, a sequencing agnostic approach 'SMART-9N' and a version compatible rapid adapters  available from Oxford Nanopore Technologies 'Rapid SMART-9N'. The methods were developed using viral isolates, clinical samples, and compared to a gold-standard amplicon-based method. From a Zika virus isolate the SMART-9N approach recovered 10kb of the 10.8kb RNA genome in a single nanopore read. We also obtained full genome coverage at a high depth coverage using the Rapid SMART-9N, which takes only 10 minutes and costs up to 45% less than other methods. We found the limits of detection of these methods to be 6 focus forming units (FFU)/mL with 99.02% and 87.58% genome coverage for SMART-9N and Rapid SMART-9N respectively. Yellow fever virus plasma samples and SARS-CoV-2 nasopharyngeal samples previously confirmed by RT-qPCR with a broad range of Ct-values were selected for validation. Both methods produced greater genome coverage when compared to the multiplex PCR approach and we obtained the longest single read of this study (18.5 kb) with a SARS-CoV-2 clinical sample, 60% of the virus genome using the Rapid SMART-9N method. This work demonstrates that SMART-9N and Rapid SMART-9N are sensitive, low input, and long-read compatible alternatives for RNA virus detection and genome sequencing and Rapid SMART-9N improves the cost, time, and complexity of laboratory work.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Molecular evolutionary model based on phylogenetic and mutation analysis of SARS-CoV-2 spike protein sequences from Asian countries: A phylogenomic approach

The lethal pathogenic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection has caused the COVID-19 pandemic, posing serious risks to people. The clove-like spike (S) protein that distinguishes coronaviruses from other viruses is important for viral pathogenicity, evolution, and transmission. The investigation of the unique structural mutations of the SARS-CoV-2 spike protein among 34 Asian countries, as well as the resulting phylogenetic relationship, provided critical information in understanding the pathogenesis. This can be utilized for the discovery of possible treatments and vaccine development. The current study analyzed and depicted phylogenetic and evolutionary models useful for understanding SARS-CoV-2 human-human transmission dynamics in Asian regions with shared land borders. Further, integrated bioinformatics analysis was performed to predict the pathogenic potential and stability of 53 mutational positions among 34 coronavirus strains. Mutations at positions N969K, D614G and S884F have deleterious effects on protein function. These findings are crucial because the Asian mutations could potentially provide a vaccine candidate with co-protection against all SARS-CoV-2 strains. This region is vulnerable because of the high population density and the volume of domestic and international travel for business and tourism. These discoveries would also aid in the development of plans for governments and the general populace to implement all required biocontainment protocols common to all countries.

A simplified, amplicon-based method for whole genome sequencing of human respiratory syncytial viruses

BACKGROUND

Human Respiratory Syncytial Virus (RSV) infections pose a significant risk to human health worldwide, especially for young children. Whole genome sequencing (WGS) provides a useful tool for global surveillance to better understand the evolution and epidemiology of RSV and provide essential information that may impact on antibody treatments, antiviral drug sensitivity and vaccine effectiveness.

OBJECTIVES

Here we report the development of a rapid and simplified amplicon-based one-step multiplex reverse-transcription polymerase chain reaction (mRT-PCR) for WGS of both human RSV-A and RSV-B viruses.

STUDY DESIGN

Two mRT-PCR reactions for each sample were designed to generate amplicons for RSV WGS. This new method was tested and evaluated by sequencing 206 RSV positive clinical samples collected in Australia in 2020 and 2021 with RSV Ct values between 10 and 32.

RESULTS

In silico analysis and laboratory testing revealed that the primers used in the new method covered most of the currently circulating RSV-A and RSV-B. Amplicons generated were suitable for both Illumina and Oxford Nanopore Technologies (ONT) NGS platforms. A success rate of 83.5% with a full coverage for the genome of 98 RSV-A and 74 RSV-B was achieved from all clinical samples tested.

CONCLUSIONS

This assay is simple to set up, robust, easily scalable in sample preparation and relatively inexpensive, and as such, provides a valuable addition to existing NGS RSV WGS methods.

Research Progress on the detection methods of porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome virus (PRRSV) causes clinical syndromes typified as reproductive disorders in sows and respiratory diseases in piglets. PRRSV remains one of the most prevalent pathogens affecting the pig industry, because of its complex infection profile and highly heterogeneous genetic and recombination characteristics. Therefore, a rapid and effective PRRSV detection method is important for the prevention and control of PRRS. With extensive in-depth research on PRRSV detection methods, many detection methods have been improved and promoted. Laboratory methods include techniques based on virus isolation (VI), enzyme-linked immunosorbent assays (ELISA), indirect immunofluorescence assays (IFA), immunoperoxidase monolayer assays (IPMA), polymerase chain reaction (PCR), quantitative real-time PCR (qPCR), digital PCR (dPCR), loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), clustered regularly interspaced short palindromic repeats (CRISPR), metagenomic next-generation sequencing (mNGS), and other methods. This study reviews the latest research on improving the main PRRSV detection methods and discusses their advantages and disadvantages.

Using Multiplex Amplicon PCR Technology to Efficiently and Timely Generate Rift Valley Fever Virus Sequence Data for Genomic Surveillance

Rift Valley fever (RVF) is a febrile vector-borne disease endemic in Africa and continues to spread in new territories. It is a climate-sensitive disease mostly triggered by abnormal rainfall patterns. The disease is associated with high mortality and morbidity in both humans and livestock. RVF is caused by the Rift Valley fever virus (RVFV) of the genus Phlebovirus in the family Phenuiviridae. It is a tripartite RNA virus with three genomic segments: small (S), medium (M) and large (L). Pathogen genomic sequencing is becoming a routine procedure and a powerful tool for understanding the evolutionary dynamics of infectious organisms, including viruses. Inspired by the utility of amplicon-based sequencing demonstrated in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and Ebola, Zika and West Nile viruses, we report an RVFV sample preparation based on amplicon multiplex polymerase chain reaction (amPCR) for template enrichment and reduction of background host contamination. The technology can be implemented rapidly to characterize and genotype RVFV during outbreaks in a near-real-time manner. To achieve this, we designed 74 multiplex primer sets covering the entire RVFV genome to specifically amplify the nucleic acid of RVFV in clinical samples from an animal tissue. Using this approach, we demonstrate achieving complete RVFV genome coverage even from samples containing a relatively low viral load. We report the first primer scheme approach of generating multiplex primer sets for a tripartite virus which can be replicated for other segmented viruses.

Comparative Analysis of Library Preparation Approaches for SARS-CoV-2 Genome Sequencing on the Illumina MiSeq Platform

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for over two years of the COVID-19 pandemic and a global health emergency. Genomic surveillance plays a key role in overcoming the ongoing COVID-19 pandemic despite its relative successive waves and the continuous emergence of new variants. Many technological approaches are currently applied for the whole genome sequencing (WGS) of SARS-CoV-2. They differ in key stages of the process, and they feature some differences in genomic coverage, sequencing depth, and in the accuracy of variant-calling options. In this study, three different protocols for SARS-CoV-2 WGS library construction are compared: an amplicon-based protocol with a commercial primer panel; an amplicon-based protocol with a custom panel; and a hybridization capture protocol. Specific differences in sequencing depth and genomic coverage as well as differences in SNP number were found. The custom panel showed suitable results and a predictable output applicable for the epidemiological surveillance of SARS-CoV-2 variants.

Diversity of RNA viruses of three dominant tick species in North China

Background

A wide range of bacterial pathogens have been identified in ticks, yet the diversity of viruses in ticks is largely unexplored.

Methods

Here, we used metagenomic sequencing to characterize the diverse viromes in three principal tick species associated with pathogens, Haemaphysalis concinna, Dermacentor silvarum, and Ixodes persulcatus, in North China.

Results

A total of 28 RNA viruses were identified and belonged to more than 12 viral families, including single-stranded positive-sense RNA viruses (Flaviviridae, Picornaviridae, Luteoviridae, Solemoviridae, and Tetraviridae), negative-sense RNA viruses (Mononegavirales, Bunyavirales, and others) and double-stranded RNA viruses (Totiviridae and Partitiviridae). Of these, Dermacentor pestivirus-likevirus, Chimay-like rhabdovirus, taiga tick nigecruvirus, and Mukawa virus are presented as novel viral species, while Nuomin virus, Scapularis ixovirus, Sara tick-borne phlebovirus, Tacheng uukuvirus, and Beiji orthonairovirus had been established as human pathogens with undetermined natural circulation and pathogenicity. Other viruses include Norway mononegavirus 1, Jilin partitivirus, tick-borne tetravirus, Pico-like virus, Luteo-like virus 2, Luteo-likevirus 3, Vovk virus, Levivirus, Toti-like virus, and Solemo-like virus as well as others with unknown pathogenicity to humans and wild animals.

Conclusion

In conclusion, extensive virus diversity frequently occurs in Mononegavirales and Bunyavirales among the three tick species. Comparatively, I. persulcatus ticks had been demonstrated as such a kind of host with a significantly higher diversity of viral species than those of H. concinna and D. silvarum ticks. Our analysis supported that ticks are reservoirs for a wide range of viruses and suggested that the discovery and characterization of tick-borne viruses would have implications for viral taxonomy and provide insights into tick-transmitted viral zoonotic diseases.

Next Generation Sequencing for the Analysis of Parvovirus B19 Genomic Diversity

Parvovirus B19 (B19V) is a ssDNA human virus, responsible for an ample range of clinical manifestations. Sequencing of B19V DNA from clinical samples is frequently reported in the literature to assign genotype (genotypes 1-3) and for finer molecular epidemiological tracing. The increasing availability of Next Generation Sequencing (NGS) with its depth of coverage potentially yields information on intrinsic sequence heterogeneity; however, integration of this information in analysis of sequence variation is not routinely obtained. The present work investigated genomic sequence heterogeneity within and between B19V isolates by application of NGS techniques, and by the development of a novel dedicated bioinformatic tool and analysis pipeline, yielding information on two newly defined parameters. The first, α-diversity, is a measure of the amount and distribution of position-specific, normalised Shannon Entropy, as a measure of intra-sample sequence heterogeneity. The second, σ-diversity, is a measure of the amount of inter-sample sequence heterogeneity, also incorporating information on α-diversity. Based on these indexes, further cluster analysis can be performed. A set of 24 high-titre viraemic samples was investigated. Of these, 23 samples were genotype 1 and one sample was genotype 2. Genotype 1 isolates showed low α-diversity values, with only a few samples showing distinct position-specific polymorphisms; a few genetically related clusters emerged when analysing inter-sample distances, correlated to the year of isolation; the single genotype 2 isolate showed the highest α-diversity, even if not presenting polymorphisms, and was an evident outlier when analysing inter-sample distance. In conclusion, NGS analysis and the bioinformatic tool and pipeline developed and used in the present work can be considered effective tools for investigating sequence diversity, an observable parameter that can be incorporated into the quasispecies theory framework to yield a better insight into viral evolution dynamics.

The Emerging Role of the Gut Virome in Health and Inflammatory Bowel Disease: Challenges, Covariates and a Viral Imbalance

Virome research is a rapidly growing area in the microbiome field that is increasingly associated with human diseases, such as inflammatory bowel disease (IBD). Although substantial progress has been made, major methodological challenges limit our understanding of the virota. In this review, we describe challenges that must be considered to accurately report the virome composition and the current knowledge on the virome in health and IBD. First, the description of the virome shows strong methodological biases related to wetlab (e.g., VLP enrichment) and bioinformatics approaches (viral identification and classification). Second, IBD patients show consistent viral imbalances characterized by a high relative abundance of phages belonging to the Caudovirales and a low relative abundance of phages belonging to the Microviridae. Simultaneously, a sporadic contraction of CrAss-like phages and a potential expansion of the lysogenic potential of the intestinal virome are observed. Finally, despite numerous studies that have conducted diversity analysis, it is difficult to draw firm conclusions due to methodological biases. Overall, we present the many methodological and environmental factors that influence the virome, its current consensus in health and IBD, and a contributing hypothesis called the "positive inflammatory feedback loop" that may play a role in the pathophysiology of IBD.

Prevalence of symptoms, comorbidities, and reinfections in individuals infected with Wild-Type SARS-CoV-2, Delta, or Omicron variants: a comparative study in western Mexico

Introduction

The variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been classified into variants of interest (VOIs) or concern (VOCs) to prioritize global monitoring and research on variants with potential risks to public health. The SARS-CoV-2 high-rate mutation can directly impact the clinical disease progression, epidemiological behavior, immune evasion, vaccine efficacy, and transmission rates. Therefore, epidemiological surveillance is crucial for controlling the COVID-19 pandemic. In the present study, we aimed to describe the prevalence of wild-type (WT) SARS-CoV-2 and Delta and Omicron variants in Jalisco State, Mexico, from 2021 to 2022, and evaluate the possible association of these variants with clinical manifestations of COVID-19.

Methods

Four thousand and ninety-eight patients diagnosed with COVID-19 by real-time PCR (COVIFLU, Genes2Life, Mexico) from nasopharyngeal samples from January 2021 to January 2022 were included. Variant identification was performed by the RT-qPCR Master Mut Kit (Genes2Life, Mexico). A study population follow-up was performed to identify patients who had experienced reinfection after being vaccinated.

Results and Discussion

Samples were grouped into variants according to the identified mutations: 46.3% were Omicron, 27.9% were Delta, and 25.8% were WT. The proportions of dry cough, fatigue, headache, muscle pain, conjunctivitis, fast breathing, diarrhea, anosmia, and dysgeusia were significantly different among the abovementioned groups (p < 0.001). Anosmia and dysgeusia were mainly found in WT-infected patients, while rhinorrhea and sore throat were more prevalent in patients infected with the Omicron variant. For the reinfection follow-up, 836 patients answered, from which 85 cases of reinfection were identified (9.6%); Omicron was the VOC that caused all reported reinfection cases. In this study, we demonstrate that the Omicron variant caused the biggest outbreak in Jalisco during the pandemic from late December 2021 to mid-February 2022 but with a less severe form than the one demonstrated by Delta and WT. The co-analysis of mutations and clinical outcomes is a public health strategy with the potential to infer mutations or variants that could increase disease severity and even be an indicator of long-term sequelae of COVID-19.

An Automated Strategy to Handle Antigenic Variability in Immunisation Protocols, Part I: Nanopore Sequencing of Infectious Agent Variants

Infectious agents often challenge therapeutics, from antibiotics resistance to antigenic variability affecting inoculation measures. Over the last decades, genome sequencing arose as an important ally to address such challenges. In bacterial infection, whole-genome-sequencing (WGS) supports tracking pathogenic alterations affecting the human microbiome. In viral infection, the analysis of the relevant sequence of nucleotides helps with determining historical variants of a virus and elucidates details about infection clusters and their distribution. Additionally, genome sequencing is now an important step in inoculation protocols, isolating target genes to design more robust immunisation assays. Ultimately, genetic engineering has empowered repurposing at scale, allowing long-lasting repeating clinical trials to be automated within a much shorter time-frame, by adjusting existing protocols. This is particularly important during sanitary emergencies as the ones caused by the 2014 West African Ebola outbreak, the Zika virus rapid spread in both South and North America in 2015, followed by Asia in 2016, and the pandemic caused by the SARS-CoV-2, which has infected more than 187 million people and caused more than 4 million deaths, worldwide, as per July 2021 statistics. In this scenery, this chapter presents a novel fully automated strategy to handle antigenic variability in immunisation protocols. The methodology comprises of two major steps (1) nanopore sequencing of infectious agent variants - the focus is on the SARS-CoV-2 and its variants; followed by (2) mRNA vector design for immunotherapy. This chapter presents the nanopore sequencing step and Chapter 17 introduces a protocol for mRNA vector design.

Is Xenopus laevis introduction linked with Ranavirus incursion, persistence and spread in Chile?

Ranaviruses have been associated with amphibian, fish and reptile mortality events worldwide and with amphibian population declines in parts of Europe. Xenopus laevis is a widespread invasive amphibian species in Chile. Recently, Frog virus 3 (FV3), the type species of the Ranavirus genus, was detected in two wild populations of this frog near Santiago in Chile, however, the extent of ranavirus infection in this country remains unknown. To obtain more information about the origin of ranavirus in Chile, its distribution, species affected, and the role of invasive amphibians and freshwater fish in the epidemiology of ranavirus, a surveillance study comprising wild and farmed amphibians and wild fish over a large latitudinal gradient (2,500 km) was carried out in 2015-2017. In total, 1,752 amphibians and 496 fish were tested using a ranavirus-specific qPCR assay, and positive samples were analyzed for virus characterization through whole genome sequencing of viral DNA obtained from infected tissue. Ranavirus was detected at low viral loads in nine of 1,011 X. laevis from four populations in central Chile. No other amphibian or fish species tested were positive for ranavirus, suggesting ranavirus is not threatening native Chilean species yet. Phylogenetic analysis of partial ranavirus sequences showed 100% similarity with FV3. Our results show a restricted range of ranavirus infection in central Chile, coinciding with X. laevis presence, and suggest that FV3 may have entered the country through infected X. laevis, which appears to act as a competent reservoir host, and may contribute to the spread the virus locally as it invades new areas, and globally through the pet trade.

Machine Learning Aided Interpretable Approach for Single Nucleotide-Based DNA Sequencing using a Model Nanopore

Solid-state nanopore-based electrical detection of DNA nucleotides with the quantum tunneling technique has emerged as a powerful strategy to be the next-generation sequencing technology. However, experimental complexity has been a foremost obstacle in achieving a more accurate high-throughput analysis with industrial scalability. Here, with one of the nucleotide training data sets of a model monolayer gold nanopore, we have predicted the transmission function for all other nucleotides with root-mean-square error scores as low as 0.12 using the optimized eXtreme Gradient Boosting Regression (XGBR) model. Further, the SHapley Additive exPlanations (SHAP) analysis helped in exploring the interpretability of the XGBR model prediction and revealed the complex relationship between the molecular properties of nucleotides and their transmission functions by both global and local interpretable explanations. Hence, experimental integration of our proposed machine-learning-assisted transmission function prediction method can offer a new direction for the realization of cheap, accurate, and ultrafast DNA sequencing.

Evaluation of tangential flow filtration coupled to long-read sequencing for ostreid herpesvirus type 1 genome assembly

Whole-genome sequencing is widely used to better understand the transmission dynamics, the evolution and the emergence of new variants of viral pathogens. This can bring crucial information to stakeholders for disease management. Unfortunately, aquatic virus genomes are usually difficult to characterize because most of these viruses cannot be easily propagated in vitro. Developing methodologies for routine genome sequencing of aquatic viruses is timely given the ongoing threat of disease emergence. This is particularly true for pathogenic viruses infecting species of commercial interest that are widely exchanged between production basins or countries. For example, the ostreid herpesvirus type 1 (OsHV-1) is a Herpesvirus widely associated with mass mortality events of juvenile Pacific oyster Crassostrea gigas. Genomes of Herpesviruses are large and complex with long direct and inverted terminal repeats. In addition, OsHV-1 is unculturable. It therefore accumulates several features that make its genome sequencing and assembly challenging. To overcome these difficulties, we developed a tangential flow filtration (TFF) method to enrich OsHV-1 infective particles from infected host tissues. This virus purification allowed us to extract high molecular weight and high-quality viral DNA that was subjected to Illumina short-read and Nanopore long-read sequencing. Dedicated bioinformatic pipelines were developed to assemble complete OsHV-1 genomes with reads from both sequencing technologies. Nanopore sequencing allowed characterization of new structural variations and major viral isomers while having 99,98 % of nucleotide identity with the Illumina assembled genome. Our study shows that TFF-based purification method, coupled with Nanopore sequencing, is a promising approach to enable in field sequencing of unculturable aquatic DNA virus.

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.

Targeted genomic sequencing with probe capture for discovery and surveillance of coronaviruses in bats

Public health emergencies like SARS, MERS, and COVID-19 have prioritized surveillance of zoonotic coronaviruses, resulting in extensive genomic characterization of coronavirus diversity in bats. Sequencing viral genomes directly from animal specimens remains a laboratory challenge, however, and most bat coronaviruses have been characterized solely by PCR amplification of small regions from the best-conserved gene. This has resulted in limited phylogenetic resolution and left viral genetic factors relevant to threat assessment undescribed. In this study, we evaluated whether a technique called hybridization probe capture can achieve more extensive genome recovery from surveillance specimens. Using a custom panel of 20,000 probes, we captured and sequenced coronavirus genomic material in 21 swab specimens collected from bats in the Democratic Republic of the Congo. For 15 of these specimens, probe capture recovered more genome sequence than had been previously generated with standard amplicon sequencing protocols, providing a median 6.1-fold improvement (ranging up to 69.1-fold). Probe capture data also identified five novel alpha- and betacoronaviruses in these specimens, and their full genomes were recovered with additional deep sequencing. Based on these experiences, we discuss how probe capture could be effectively operationalized alongside other sequencing technologies for high-throughput, genomics-based discovery and surveillance of bat coronaviruses.

Viral Metagenomics for Identification of Emerging Viruses in Transfusion Medicine

Viral metagenomics has revolutionized our understanding for identification of unknown or poorly characterized viruses. For that reason, metagenomic studies gave been largely applied for virus discovery in a wide variety of clinical samples, including blood specimens. The emerging blood-transmitted virus infections represent important problem for public health, and the emergence of HIV in the 1980s is an example for the vulnerability of Blood Donation systems to such infections. When viral metagenomics is applied to blood samples, it can give a complete overview of the viral nucleic acid abundance, also named "blood virome". Detailed characterization of the blood virome of healthy donors could identify unknown (emerging) viral genomes that might be assumed as hypothetic transfusion threats. However, it is impossible only by application of viral metagenomics to assign that one viral agent could impact blood transfusion. That said, this is a complex issue and will depend on the ability of the infectious agent to cause clinically important infection in blood recipients, the viral stability in blood derivatives and the presence of infectious viruses in blood, making possible its transmission by transfusion. This brief review summarizes information regarding the blood donor virome and some important challenges for use of viral metagenomics in hemotherapy for identification of transfusion-transmitted viruses.

Nationwide and long-term molecular epidemiologic studies of mumps viruses that circulated in Japan between 1986 and 2017

In Japan, major mumps outbreaks still occur every 4–5 years because of low mumps vaccine coverage (30–40%) owing to the voluntary immunization program. Herein, to prepare for a regular immunization program, we aimed to reveal the nationwide and long-term molecular epidemiological trends of the mumps virus (MuV) in Japan. Additionally, we performed whole-genome sequencing (WGS) using next-generation sequencing to assess results from conventional genotyping using MuV sequences of the small-hydrophobic (SH) gene. We analyzed 1,064 SH gene sequences from mumps clinical samples and MuV isolates collected from 25 prefectures from 1986 to 2017. The results showed that six genotypes, namely B (110), F (1), G (900), H (3), J (41), and L (9) were identified, and the dominant genotypes changed every decade in Japan since the 1980s. Genotype G has been exclusively circulating since the early 2000s. Seven clades were identified for genotype G using SH sequence-based classification. To verify the results, we performed WGS on 77 representative isolates of genotype G using NGS and phylogenetically analyzed them. Five clades were identified with high bootstrap values and designated as Japanese clade (JPC)-1, -2, -3, -4, -5. JPC-1 and -3 accounted for over 80% of the total genotype G isolates (68.3 and 13.8%, respectively). Of these, JPC-2 and -5, were newly identified clades in Japan through this study. This is the first report describing the nationwide and long-term molecular epidemiology of MuV in Japan. The results provide information about Japanese domestic genotypes, which is essential for evaluating the mumps elimination progress in Japan after the forthcoming introduction of the mumps vaccine into Japan’s regular immunization program. Furthermore, the study shows that WGS analysis using NGS is more accurate than results obtained from conventional SH sequence-based classification and is a powerful tool for accurate molecular epidemiology studies.

A collaborative approach to improve representation in viral genomic surveillance

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building microbial genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness.

Author summary

Genomic surveillance involves decoding a pathogen’s genetic code to track its spread and evolution. During the pandemic, genomic surveillance programs around the world provided valuable data to scientists, doctors, and public health officials. Knowing the complete SARS-CoV-2 genome has helped detect the emergence of new variants, including ones that are more transmissible or cause more severe disease, and has supported the development of diagnostics, vaccines, and therapeutics. The impact of genomic surveillance on public health depends on representative sampling that accurately reflects the diversity and distribution of populations, as well as rapid turnaround time from sampling to data sharing. After a slow start, SARS-CoV-2 genomic surveillance in the United States grew exponentially. Despite this, many rural regions and ethnic minorities remain poorly represented, leaving significant gaps in the data that informs public health responses. To address this problem, we formed a network of universities and clinics in Louisiana, Georgia, and Mississippi with the goal of increasing SARS-CoV-2 sequencing volume, representation, and equity. Our results demonstrate the advantages of rapidly sequencing pathogens in the same communities where the cases occur and present a model that leverages existing academic and clinical infrastructure for a powerful decentralized genomic surveillance system.

Targeted Whole Genome Sequencing (TWG-Seq) of Cucumber Green Mottle Mosaic Virus Using Tiled Amplicon Multiplex PCR and Nanopore Sequencing

Rapid and reliable detection tools are essential for disease surveillance and outbreak management, and genomic data is essential to determining pathogen origin and monitoring of transmission pathways. Low virus copy number and poor RNA quality can present challenges for genomic sequencing of plant viruses, but this can be overcome by enrichment of target nucleic acid. A targeted whole genome sequencing (TWG-Seq) approach for the detection of cucumber green mottle mosaic virus (CGMMV) has been developed where overlapping amplicons generated using two multiplex RT-PCR assays are then sequenced using the Oxford Nanopore MinION. Near complete coding region sequences were assembled with ≥100× coverage for infected leaf tissue dilution samples with RT-qPCR cycle quantification (Cq) values from 11.8 to 38 and in seed dilution samples with Cq values 13.8 to 27. Consensus sequences assembled using this approach showed greater than 99% nucleotide similarity when compared to genomes produced using metagenomic sequencing. CGMMV could be confidently detected in historical seed isolates with degraded RNA. Whilst limited access to, and costs associated with second-generation sequencing platforms can influence diagnostic outputs, the portable Nanopore technology offers an affordable high throughput sequencing alternative when combined with TWG-Seq for low copy or degraded samples.

Biological and genomic characteristics of two bacteriophages isolated from sewage, using one multidrug-resistant and one non-multidrug-resistant strain of Klebsiella pneumoniae

Bovine mastitis caused by multi-drug resistant (MDR) Klebsiella pneumoniae is difficult to treat with antibiotics, whereas bacteriophages may be a viable alternative. Our objective was to use 2 K. pneumoniae strains, 1 MDR and the other non-MDR, to isolate phages from sewage samples and compare their biological and genomic characteristics. Additionally, phage infected mouse mammary gland was also analyzed by H&E staining and ELISA kits to compare morphology and inflammatory factors, respectively. Based on assessments with double agar plates and transmission electron microscopy, phage CM_Kpn_HB132952 had clear plaques surrounded by translucent halos on the bacterial lawn of K. pneumoniae KPHB132952 and belonged to Siphoviridae, whereas phage CM_Kpn_HB143742 formed a clear plaque on the bacterial lawn of K. pneumoniae KPHB143742 and belonged to Podoviridae. In 1-step growth curves, CM_Kpn_HB132952 and CM_Kpn_HB143742 had burst sizes of 0.34 and 0.73 log₁₀ PFU/mL, respectively. The former had a latent period of 50 min and an optimal multiplicity of infection (MOI) of 0.01, whereas for the latter, the latent period was 30 min (MOI = 1). Phage CM_Kpn_HB132952 had better thermal and acid–base stability than phage CM_Kpn_HB143742. Additionally, both phages had the same host range rate but different host ranges. Based on Illumina NovaSeq, phages CM_Kpn_HB132952 and CM_Kpn_HB143742 had 140 and 145 predicted genes, respectively. Genomic sequencing and phylogenetic tree analysis indicated that both phages were novel phages belonging to the Klebsiella family. Additionally, the histopathological structure and inflammatory factors TNF-α and IL-1β were not significantly different among phage groups and the control group. In conclusion, using 1 MDR and 1 non-MDR strain of K. pneumoniae, we successfully isolated two phages from the same sewage sample, and demonstrated that they had distinct biological and genomic characteristics.

Haplotype assignment of longitudinal viral deep sequencing data using covariation of variant frequencies

Longitudinal deep sequencing of viruses can provide detailed information about intra-host evolutionary dynamics including how viruses interact with and transmit between hosts. Many analyses require haplotype reconstruction, identifying which variants are co-located on the same genomic element. Most current methods to perform this reconstruction are based on a high density of variants and cannot perform this reconstruction for slowly evolving viruses. We present a new approach, HaROLD (HAplotype Reconstruction Of Longitudinal Deep sequencing data), which performs this reconstruction based on identifying co-varying variant frequencies using a probabilistic framework. We illustrate HaROLD on both RNA and DNA viruses with synthetic Illumina paired read data created from mixed human cytomegalovirus (HCMV) and norovirus genomes, and clinical datasets of HCMV and norovirus samples, demonstrating high accuracy, especially when longitudinal samples are available.

HUGE pipeline to measure temporal genetic variation in Drosophila suzukii populations for genetic biocontrol applications

Understanding the fine-scale genome sequence diversity that exists within natural populations is important for developing models of species migration, temporal stability, and range expansion. For invasive species, agricultural pests, and disease vectors, sequence diversity at specific loci in the genome can impact the efficacy of next-generation genetic biocontrol strategies. Here we describe a pipeline for haplotype-resolution genetic variant discovery and quantification from thousands of Spotted Wing Drosophila (Drosophila suzukii, SWD) isolated at two field sites in the North-Central United States (Minnesota) across two seasons. We observed highly similar single nucleotide polymorphism (SNP) frequencies at each genomic location at each field site and year. This supports the hypotheses that SWD overwinters in Minnesota, is annually populated by the same source populations or a combination of both theories. Also, the stable genetic structure of SWD populations allows for the rational design of genetic biocontrol technologies for population suppression.