ABSTRACT
Prompt detection of viral respiratory pathogens is crucial in managing respiratory infection including severe acute respiratory infection (SARI). Metagenomics next-generation sequencing (mNGS) and bioinformatics analyses remain reliable strategies for diagnostic and surveillance purposes. This study evaluated the diagnostic utility of mNGS using multiple analysis tools compared with multiplex real-time PCR for the detection of viral respiratory pathogens in children under 5 years with SARI. Nasopharyngeal swabs collected in viral transport media from 84 children admitted with SARI as per the World Health Organization definition between December 2020 and August 2021 in the Free State Province, South Africa, were used in this study. The obtained specimens were subjected to mNGS using the Illumina MiSeq system, and bioinformatics analysis was performed using three web-based analysis tools; Genome Detective, One Codex and Twist Respiratory Viral Research Panel. With average reads of 211323, mNGS detected viral pathogens in 82 (97.6%) of the 84 patients. Viral aetiologies were established in nine previously undetected/missed cases with an additional bacterial aetiology (Neisseria meningitidis) detected in one patient. Furthermore, mNGS enabled the much needed viral genotypic and subtype differentiation and provided significant information on bacterial co-infection despite enrichment for RNA viruses. Sequences of nonhuman viruses, bacteriophages, and endogenous retrovirus K113 (constituting the respiratory virome) were also uncovered. Notably, mNGS had lower detectability rate for severe acute respiratory syndrome coronavirus 2 (missing 18/32 cases). This study suggests that mNGS, combined with multiple/improved bioinformatics tools, is practically feasible for increased viral and bacterial pathogen detection in SARI, especially in cases where no aetiological agent could be identified by available traditional methods.
Subject(s)
Bacterial Infections , COVID-19 , RNA Viruses , Viruses , Humans , Child , Child, Preschool , RNA, Viral/genetics , South Africa , Viruses/genetics , RNA Viruses/genetics , Bacteria/genetics , Metagenomics/methods , High-Throughput Nucleotide Sequencing/methods , Sensitivity and SpecificityABSTRACT
The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on a priori knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens. Metagenomic techniques can nonspecifically sequence all detectable nucleic acids in a sample and therefore do not rely on prior knowledge of a pathogen's genome. While this technology has been reviewed for bacterial diagnostics and adopted in research settings for the detection and characterization of viruses, viral metagenomics has yet to be widely deployed as a diagnostic tool in clinical laboratories. In this review, we highlight recent improvements to the performance of metagenomic viral sequencing, the current applications of metagenomic sequencing in clinical laboratories, as well as the challenges that impede the widespread adoption of this technology.
Subject(s)
Viruses , Viruses/genetics , High-Throughput Nucleotide Sequencing/methods , Bacteria/genetics , Metagenomics/methods , Genome, Viral/geneticsABSTRACT
Emerging infectious disease threats require rapid response tools to inform diagnostics, treatment, and outbreak control. RNA-based metagenomics offers this; however, most approaches are time-consuming and laborious. Here, we present a simple and fast protocol, the RAPIDprep assay, with the aim of providing a cause-agnostic laboratory diagnosis of infection within 24 h of sample collection by sequencing ribosomal RNA-depleted total RNA. The method is based on the synthesis and amplification of double-stranded cDNA followed by short-read sequencing, with minimal handling and clean-up steps to improve processing time. The approach was optimized and applied to a range of clinical respiratory samples to demonstrate diagnostic and quantitative performance. Our results showed robust depletion of both human and microbial rRNA, and library amplification across different sample types, qualities, and extraction kits using a single workflow without input nucleic-acid quantification or quality assessment. Furthermore, we demonstrated the genomic yield of both known and undiagnosed pathogens with complete genomes recovered in most cases to inform molecular epidemiological investigations and vaccine design. The RAPIDprep assay is a simple and effective tool, and representative of an important shift toward the integration of modern genomic techniques with infectious disease investigations.
Subject(s)
High-Throughput Nucleotide Sequencing , Metagenomics , Humans , Metagenomics/methods , High-Throughput Nucleotide Sequencing/methods , Metagenome , Genomics , RNA, Viral/geneticsABSTRACT
OBJECTIVES: The aim of this study is to evaluate the effectiveness of a CRISPR-based human and bacterial ribosomal RNA (rRNA) depletion kit (JUMPCODE Genomics) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shotgun metagenomic sequencing in weakly positive respiratory samples. METHODS: Shotgun metagenomics was performed on 40 respiratory specimens collected from solid organ transplant patients and deceased intensive care unit patients at UCLA Medical Center in late 2020 to early 2021. Human and bacterial rRNA depletion was performed on remnant library pools prior to sequencing by Illumina MiSeq. Data quality was analyzed using Geneious Prime, whereas the identification of SARS-CoV-2 variants and lineages was determined by Pangolin. RESULTS: The average genome coverage of the rRNA-depleted respiratory specimens increased from 72.55% to 93.71% in overall samples and from 29.3% to 83.3% in 15 samples that failed to achieve sufficient genome coverage using the standard method. Moreover, rRNA depletion enhanced genome coverage to over 85% in 11 (73.3%) of 15 low viral load samples with cycle threshold values up to 35, resulting in the identification of genotypes. CONCLUSION: The CRISPR-based human and bacterial rRNA depletion enhanced the sensitivity of SARS-CoV-2 shotgun metagenomic sequencing, especially in low viral load samples.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , RNA, Ribosomal , Metagenomics/methodsABSTRACT
Our knowledge of the role of the gut microbiome in acute coronavirus disease 2019 (COVID-19) and post-acute COVID-19 is rapidly increasing, whereas little is known regarding the contribution of multi-kingdom microbiota and host-microbial interactions to COVID-19 severity and consequences. Herein, we perform an integrated analysis using 296 fecal metagenomes, 79 fecal metabolomics, viral load in 1378 respiratory tract samples, and clinical features of 133 COVID-19 patients prospectively followed for up to 6 months. Metagenomic-based clustering identifies two robust ecological clusters (hereafter referred to as Clusters 1 and 2), of which Cluster 1 is significantly associated with severe COVID-19 and the development of post-acute COVID-19 syndrome. Significant differences between clusters could be explained by both multi-kingdom ecological drivers (bacteria, fungi, and viruses) and host factors with a good predictive value and an area under the curve (AUC) of 0.98. A model combining host and microbial factors could predict the duration of respiratory viral shedding with 82.1% accuracy (error ± 3 days). These results highlight the potential utility of host phenotype and multi-kingdom microbiota profiling as a prognostic tool for patients with COVID-19.
Subject(s)
COVID-19 , Gastrointestinal Microbiome , Humans , Gastrointestinal Microbiome/genetics , Metagenomics/methods , Feces/microbiology , Post-Acute COVID-19 SyndromeABSTRACT
PURPOSE: To evaluate the utility of nanopore sequencing for identifying potential causative pathogens in endophthalmitis, comparing culture results against full-length 16S rRNA nanopore sequencing (16S Nanopore), whole genome nanopore sequencing (Nanopore WGS), and Illumina (Illumina WGS). DESIGN: Cross-sectional diagnostic comparison. METHODS: Patients with clinically suspected endophthalmitis underwent intraocular vitreous biopsy as per standard care. Clinical samples were cultured by conventional methods, together with full-length 16S rRNA and WGS using nanopore and Illumina sequencing platforms. RESULTS: Of 23 patients (median age 68.5 years [range 47-88]; 14 males [61%]), 18 cases were culture-positive. Nanopore sequencing identified the same cultured organism in all of the culture-positive cases and identified potential pathogens in two culture-negative cases (40%). Nanopore WGS was able to additionally detect the presence of bacteriophages in three samples. The agreements at genus level between culture and 16S Nanopore, Nanopore WGS, and Illumina WGS were 75%, 100%, and 78%, respectively. CONCLUSIONS: Whole genome sequencing has higher sensitivity and provides a viable alternative to culture and 16S sequencing for detecting potential pathogens in endophthalmitis. Moreover, WGS has the ability to detect other potential pathogens in culture-negative cases. Whilst Nanopore and Illumina WGS provide comparable data, nanopore sequencing provides potential for cost-effective point-of-care diagnostics.
Subject(s)
Endophthalmitis , Nanopores , Aged , Aged, 80 and over , Cross-Sectional Studies , Endophthalmitis/diagnosis , Humans , Male , Metagenomics/methods , Middle Aged , RNA, Ribosomal, 16S/geneticsABSTRACT
Classification of viruses into their taxonomic ranks (e.g., order, family, and genus) provides a framework to organize an abundant population of viruses. Next-generation metagenomic sequencing technologies lead to a rapid increase in generating sequencing data of viruses which require bioinformatics tools to analyze the taxonomy. Many metagenomic taxonomy classifiers have been developed to study microbiomes, but it is particularly challenging to assign the taxonomy of diverse virus sequences and there is a growing need for dedicated methods to be developed that are optimized to classify virus sequences into their taxa. For taxonomic classification of viruses from metagenomic sequences, we developed VirusTaxo using diverse (e.g., 402 DNA and 280 RNA) genera of viruses. VirusTaxo has an average accuracy of 93% at genus level prediction in DNA and RNA viruses. VirusTaxo outperformed existing taxonomic classifiers of viruses where it assigned taxonomy of a larger fraction of metagenomic contigs compared to other methods. Benchmarking of VirusTaxo on a collection of SARS-CoV-2 sequencing libraries and metavirome datasets suggests that VirusTaxo can characterize virus taxonomy from highly diverse contigs and provide a reliable decision on the taxonomy of viruses.
Subject(s)
COVID-19 , Viruses , Humans , Metagenome , Metagenomics/methods , Phylogeny , SARS-CoV-2/genetics , Viruses/geneticsABSTRACT
Lessons learnt from the COVID-19 pandemic include increased awareness of the potential for zoonoses and emerging infectious diseases that can adversely affect human health. Although emergent viruses are currently in the spotlight, we must not forget the ongoing toll of morbidity and mortality owing to antimicrobial resistance in bacterial pathogens and to vector-borne, foodborne and waterborne diseases. Population growth, planetary change, international travel and medical tourism all contribute to the increasing frequency of infectious disease outbreaks. Surveillance is therefore of crucial importance, but the diversity of microbial pathogens, coupled with resource-intensive methods, compromises our ability to scale-up such efforts. Innovative technologies that are both easy to use and able to simultaneously identify diverse microorganisms (viral, bacterial or fungal) with precision are necessary to enable informed public health decisions. Metagenomics-enabled surveillance methods offer the opportunity to improve detection of both known and yet-to-emerge pathogens.
Subject(s)
COVID-19 , Viruses , Animals , Humans , Metagenomics/methods , Pandemics , Viruses/genetics , ZoonosesABSTRACT
The human gut contains a complex microbiota dominated by bacteriophages but also containing other viruses and bacteria and fungi. There are a growing number of techniques for the extraction, sequencing, and analysis of the virome but currently no standardized protocols. This study established an effective workflow for virome analysis to investigate the virome of stool samples from two understudied ethnic groups from Malaysia: the Jakun and Jehai Orang Asli. By using the virome extraction and analysis workflow with the Oxford Nanopore Technology, long-read sequencing successfully captured close to full-length viral genomes. The virome composition of the two indigenous Malaysian communities were remarkably different from those found in other parts of the world. Additionally, plant viruses found in the viromes of these individuals were attributed to traditional food-seeking methods. This study establishes a human gut virome workflow and extends insights into the healthy human gut virome, laying the groundwork for comparative studies.
Subject(s)
Gastrointestinal Microbiome/genetics , Genome, Viral , Indigenous Peoples , Viruses/genetics , Feces/virology , Female , High-Throughput Nucleotide Sequencing , Humans , Malaysia , Metagenomics/methods , Phylogeny , Virome/genetics , Viruses/classificationABSTRACT
A large gap remains between sequencing a microbial community and characterizing all of the organisms inside of it. Here we develop a novel method to taxonomically bin metagenomic assemblies through alignment of contigs against a reference database. We show that this workflow, BugSplit, bins metagenome-assembled contigs to species with a 33% absolute improvement in F1-score when compared to alternative tools. We perform nanopore mNGS on patients with COVID-19, and using a reference database predating COVID-19, demonstrate that BugSplit's taxonomic binning enables sensitive and specific detection of a novel coronavirus not possible with other approaches. When applied to nanopore mNGS data from cases of Klebsiella pneumoniae and Neisseria gonorrhoeae infection, BugSplit's taxonomic binning accurately separates pathogen sequences from those of the host and microbiota, and unlocks the possibility of sequence typing, in silico serotyping, and antimicrobial resistance prediction of each organism within a sample. BugSplit is available at https://bugseq.com/academic .
Subject(s)
Algorithms , Bacteria/genetics , Computational Biology/methods , Metagenome/genetics , Metagenomics/methods , Nanopore Sequencing/methods , Bacteria/classification , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/virology , Humans , Internet , Pandemics/prevention & control , Reproducibility of Results , SARS-CoV-2/classification , SARS-CoV-2/genetics , SARS-CoV-2/physiologyABSTRACT
The human body is colonized by a wide range of microorganisms. The field of viromics has expanded since the first reports on the detection of viruses via metagenomic sequencing in 2002. With the continued development of reference materials and databases, viral metagenomic approaches have been used to explore known components of the virome and discover new viruses from various types of samples. The virome has attracted substantial interest since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Increasing numbers of studies and review articles have documented the diverse virome in various sites in the human body, as well as interactions between the human host and the virome with regard to health and disease. However, there have been few studies of direct causal relationships. Viral metagenomic analyses often lack standard references and are potentially subject to bias. Moreover, most virome-related review articles have focused on the gut virome and did not investigate the roles of the virome in other sites of the body in human disease. This review presents an overview of viral metagenomics, with updates regarding the relations between alterations in the human virome and the pathogenesis of human diseases, recent findings related to COVID-19, and therapeutic applications related to the human virome.
Subject(s)
Gastrointestinal Microbiome/genetics , Metagenome , Metagenomics/methods , Virome/genetics , Virus Diseases/drug therapy , Animals , COVID-19/therapy , Humans , Mice , Obesity/complications , SARS-CoV-2/genetics , Virus Diseases/therapy , Viruses/classification , Viruses/geneticsABSTRACT
In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: an unsupervised AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4-6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers that appeared after the epidemic started could be connected to mutations, and the BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explain BLSOMs for various topics, such as the tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explain BLSOMs for various eukaryotes, including fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found enrichments in transcription factor-binding sequences in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) could be separated according to their corresponding amino acid.
Subject(s)
Artificial Intelligence , Computational Biology/methods , Genome, Human , Genome, Viral , SARS-CoV-2/genetics , Cluster Analysis , Codon Usage , Humans , Metagenomics/methods , Mutation , RNA, Transfer , Time FactorsABSTRACT
Fast and accurate identification of microbial pathogens is critical for the proper treatment of infections. Traditional culture-based diagnosis in clinics is increasingly supplemented by metagenomic next-generation-sequencing (mNGS). Here, RNA/cDNA-targeted sequencing (meta-transcriptomics using NGS (mtNGS)) is established to reduce the host nucleotide percentage in clinic samples and by combining with Oxford Nanopore Technology (ONT) platforms (meta-transcriptomics using third-generation sequencing, mtTGS) to improve the sequencing time. It shows that mtNGS improves the ratio of microbial reads, facilitates bacterial identification using multiple-strategies, and discovers fungi, viruses, and antibiotic resistance genes, and displaying agreement with clinical findings. Furthermore, longer reads in mtTGS lead to additional improvement in pathogen identification and also accelerate the clinical diagnosis. Additionally, primary tests utilizing direct-RNA sequencing and targeted sequencing of ONT show that ONT displays important potential but must be further developed. This study presents the potential of RNA-targeted pathogen identification in clinical samples, especially when combined with the newest developments in ONT.
Subject(s)
Bronchoalveolar Lavage Fluid/microbiology , High-Throughput Nucleotide Sequencing/methods , Infections/genetics , Metagenomics/methods , RNA/genetics , Sequence Analysis, RNA/methods , Aged , Bronchoalveolar Lavage/methods , Female , Humans , Male , Metagenome/genetics , Middle AgedABSTRACT
The oral microbiome has been connected with lung health and may be of significance in the progression of SARS-CoV-2 infection. Saliva-based SARS-CoV-2 tests provide the opportunity to leverage stored samples for assessing the oral microbiome. However, these collection kits have not been tested for their accuracy in measuring the oral microbiome. Saliva is highly enriched with human DNA and reducing it prior to shotgun sequencing may increase the depth of bacterial reads. We examined both the effect of saliva collection method and sequence processing on measurement of microbiome depth and diversity by 16S rRNA gene amplicon and shotgun metagenomics. We collected 56 samples from 22 subjects. Each subject provided saliva samples with and without preservative, and a subset provided a second set of samples the following day. 16S rRNA gene (V4) sequencing was performed on all samples, and shotgun metagenomics was performed on a subset of samples collected with preservative with and without human DNA depletion before sequencing. We observed that the beta diversity distances within subjects over time was smaller than between unrelated subjects, and distances within subjects were smaller in samples collected with preservative. Samples collected with preservative had higher alpha diversity measuring both richness and evenness. Human DNA depletion before extraction and shotgun sequencing yielded higher total and relative reads mapping to bacterial sequences. We conclude that collecting saliva with preservative may provide more consistent measures of the oral microbiome and depleting human DNA increases yield of bacterial sequences.
Subject(s)
Microbiota/genetics , Saliva/microbiology , Adult , Bacteria/genetics , COVID-19/genetics , DNA/genetics , DNA, Bacterial/genetics , Female , Humans , Male , Metagenome/genetics , Metagenomics/methods , Middle Aged , RNA, Ribosomal, 16S/genetics , SARS-CoV-2/pathogenicity , Sequence Analysis, DNA/methodsABSTRACT
Identifying the animal reservoirs from which zoonotic viruses will likely emerge is central to understanding the determinants of disease emergence. Accordingly, there has been an increase in studies attempting zoonotic "risk assessment." Herein, we demonstrate that the virological data on which these analyses are conducted are incomplete, biased, and rapidly changing with ongoing virus discovery. Together, these shortcomings suggest that attempts to assess zoonotic risk using available virological data are likely to be inaccurate and largely only identify those host taxa that have been studied most extensively. We suggest that virus surveillance at the human-animal interface may be more productive.
Subject(s)
Environmental Monitoring , Virus Diseases , Zoonoses/etiology , Zoonoses/prevention & control , Animals , Biodiversity , Disease Reservoirs/classification , Disease Reservoirs/statistics & numerical data , Environmental Monitoring/methods , Environmental Monitoring/standards , Host Specificity/genetics , Humans , Metagenomics/methods , Metagenomics/organization & administration , Metagenomics/standards , Phylogeny , Risk Assessment , Risk Factors , Selection Bias , Virus Diseases/epidemiology , Virus Diseases/etiology , Virus Diseases/prevention & control , Virus Diseases/transmission , Viruses/classification , Viruses/genetics , Viruses/isolation & purification , Viruses/pathogenicity , Zoonoses/epidemiology , Zoonoses/virologyABSTRACT
According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.
Subject(s)
Alphacoronavirus/isolation & purification , Betacoronavirus/isolation & purification , Chiroptera/virology , Genome, Viral/genetics , Metagenome/genetics , Alphacoronavirus/classification , Alphacoronavirus/genetics , Animals , Betacoronavirus/classification , Betacoronavirus/genetics , Chiroptera/genetics , Computational Biology/methods , Feces/virology , High-Throughput Nucleotide Sequencing , Metagenomics/methods , Moscow , Phycodnaviridae/classification , Phycodnaviridae/genetics , Phycodnaviridae/isolation & purification , Sequence Analysis, DNAABSTRACT
INTRODUCTION: Meningoencephalitis patients are often severely impaired and benefit from early etiological diagnosis, though many cases remain without identified cause. Metagenomics as pathogen agnostic approach can result in additional etiological findings; however, the exact diagnostic yield when used as a secondary test remains unknown. AREAS COVERED: This review aims to highlight recent advances with regard to wet and dry lab methodologies of metagenomic testing and technical milestones that have been achieved. A selection of procedures currently applied in accredited diagnostic laboratories is described in more detail to illustrate best practices. Furthermore, a meta-analysis was performed to assess the additional diagnostic yield utilizing metagenomic sequencing in meningoencephalitis patients. Finally, the remaining challenges for successful widespread implementation of metagenomic sequencing for the diagnosis of meningoencephalitis are addressed in a future perspective. EXPERT OPINION: The last decade has shown major advances in technical possibilities for using mNGS in diagnostic settings including cloud-based analysis. An additional advance may be the current established infrastructure of platforms for bioinformatic analysis of SARS-CoV-2, which may assist to pave the way for global use of clinical metagenomics.
Subject(s)
Genome, Viral/genetics , Meningoencephalitis/diagnosis , Meningoencephalitis/virology , Metagenome/genetics , Diagnostic Tests, Routine , Humans , Metagenomics/methodsABSTRACT
The emergence of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic variants that may alter viral fitness highlights the urgency of widespread next-generation sequencing (NGS) surveillance. To profile genetic variants of the entire SARS-CoV-2 genome, we developed and clinically validated a hybridization capture SARS-CoV-2 NGS assay, integrating novel methods for panel design using double-stranded DNA (dsDNA) biotin-labeled probes, and built accompanying software. This test is the first hybrid capture-based NGS assay given Food and Drug Administration (FDA) emergency use authorization for detection of the SARS-CoV-2 virus. The positive and negative percent agreement (PPA and NPA, respectively) were defined in comparison to the results for an orthogonal real-time reverse transcription polymerase chain reaction (RT-PCR) assay (PPA and NPA, 96.7 and 100%, respectively). The limit of detection was established to be 800 copies/ml with an average fold enrichment of 46,791. Furthermore, utilizing the research-use-only analysis to profile the variants, we identified 55 novel mutations, including 11 in the functionally important spike protein. Finally, we profiled the full nasopharyngeal microbiome using metagenomics and found overrepresentation of 7 taxa and evidence of macrolide resistance in SARS-CoV-2-positive patients. This hybrid capture NGS assay, coupled with optimized software, is a powerful approach to detect and comprehensively map SARS-CoV-2 genetic variants for tracking viral evolution and guiding vaccine updates. IMPORTANCE This is the first FDA emergency-use-authorized hybridization capture-based next-generation sequencing (NGS) assay to detect the SARS-CoV-2 genome. Viral metagenomics and the novel hybrid capture NGS-based assay, along with its research-use-only analysis, can provide important genetic insights into SARS-CoV-2 and other emerging pathogens and improve surveillance and early detection, potentially preventing or mitigating new outbreaks. Better understanding of the continuously evolving SARS-CoV-2 viral genome and the impact of genetic variants may provide individual risk stratification, precision therapeutic options, improved molecular diagnostics, and population-based therapeutic solutions.
Subject(s)
Genetic Variation/genetics , Genome, Viral/genetics , Microbiota/genetics , Nasopharynx/microbiology , SARS-CoV-2/genetics , Anti-Bacterial Agents/pharmacology , COVID-19/pathology , Drug Resistance, Bacterial/genetics , High-Throughput Nucleotide Sequencing , Humans , Limit of Detection , Macrolides/pharmacology , Metagenomics/methods , RNA, Viral/genetics , Reverse Transcriptase Polymerase Chain Reaction , SARS-CoV-2/isolation & purificationABSTRACT
Viruses transmitted by the sweet potato whitefly (Bemisia tabaci) have been detrimental to the sustainable production of cucurbits in the southeastern USA. Surveys were conducted in the fall of 2019 and 2020 in Georgia, a major cucurbit-producing state of the USA, to identify the viruses infecting cucurbits and their distribution. Symptomatic samples were collected and small RNA libraries were prepared and sequenced from three cantaloupes, four cucumbers, and two yellow squash samples. An analysis of the sequences revealed the presence of the criniviruses cucurbit chlorotic yellows virus (CCYV), cucurbit yellow stunting disorder virus (CYSDV), and the begomovirus cucurbit leaf crumple virus (CuLCrV). CuLCrV was detected in 76%, CCYV in 60%, and CYSDV in 43% of the total samples (n = 820) tested. The level of mixed infections was high in all the cucurbits, with most plants tested being infected with at least two of these viruses. Near-complete genome sequences of two criniviruses, CCYV and CYSDV, were assembled from the small RNA sequences. An analysis of the coding regions showed low genetic variability among isolates from different hosts. In phylogenetic analysis, the CCYV isolates from Georgia clustered with Asian isolates, while CYSDV isolates clustered with European and USA isolates. This work enhances our understanding of the distribution of viruses on cucurbits in South Georgia and will be useful to develop strategies for managing the complex of whitefly-transmitted viruses in the region.