scholarly journals Improvement of field-deployable metagenomic virus detection by a simple pretreatment method.

2022 ◽  
Author(s):  
Anna S Fomsgaard ◽  
Morten Rasmussen ◽  
Katja Spiess ◽  
Anders Fomsgaard ◽  
Graham J Belsham ◽  
...  
Keyword(s):  
Rna Viruses ◽  
Virus Detection ◽  
Clinical Samples ◽  
Viral Pathogens ◽  
Pretreatment Method ◽  
Genetic Components ◽  
Laboratory Facilities ◽  
Simple Protocol ◽  
Animal Reservoirs ◽  
Generation Sequencing

As both the current COVID-19 pandemic and earlier pandemics have shown, animals are the source for some of the deadliest viral pathogens, which can spread to humans. Therefore, early detection at the point of incidence is crucial to both prevent and understand the threats posed to human health from pathogens in animal reservoirs. Often, the exact genetic nature of these zoonotic pathogens is unknown and advanced laboratory facilities do not exist in most field settings and therefore the development of methods for unbiased metagenomic and point of incidence detection is crucial in order to identify novel viral pathogens in animals with zoonotic and pandemic potential. Here we addressed some of these issues by developing a metagenomic Nanopore next-generation sequencing (mNGS) method for nucleic acids extracted from clinical samples from patients with SARS-CoV-2. To reduce the non-RNA viral genetic components in the samples, we used DNase pretreatment in a syringe followed by filtration and found that these pretreatments increased the number of SARS-CoV2 reads by > 500-fold compared with no pretreatment. The simple protocol, described here, allows for fast (within 6 hours) metagenomic detection of RNA viruses in biological samples exemplified by SARS-CoV-2 detection in clinical throat swabs. This method could also be applied in field settings for point of incidence detection of virus pathogens, thus eliminating the need for transport of infectious samples, cold storage and a specialized laboratory.

scholarly journals Application of Next Generation Sequencing for Diagnostic Testing of Tree Fruit Viruses and Viroids

Plant Disease ◽  
2017 ◽  
Vol 101 (8) ◽  
pp. 1489-1499 ◽  
Author(s):  
M. Rott ◽  
Y. Xiang ◽  
I. Boyes ◽  
M. Belton ◽  
H. Saeed ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Diagnostic Testing ◽  
Virus Detection ◽  
Plant Viruses ◽  
Next Generation ◽  
Viral Pathogens ◽  
Plant Virus Detection ◽  
Biological Indexing ◽  
Tree Fruit ◽  
Generation Sequencing

Conventional detection of viruses and virus-like diseases of plants is accomplished using a combination of molecular, serological, and biological indexing. These are the primary tools used by plant virologists to monitor and ensure trees are free of known viral pathogens. The biological indexing assay, or bioassay, is considered to be the “gold standard” as it is the only method of the three that can detect new, uncharacterized, or poorly characterized viral disease agents. Unfortunately, this method is also the most labor intensive and can take up to three years to complete. Next generation sequencing (NGS) is a technology with rapidly expanding possibilities including potential applications for the detection of plant viruses. In this study, comparisons are made between tree fruit testing by conventional and NGS methods, to demonstrate the efficacy of NGS. A comparison of 178 infected trees, many infected with several viral pathogens, demonstrated that conventional and NGS were equally capable of detecting known viruses and viroids. Comparable results were obtained for 170 of 178 of the specimens. Of the remaining eight specimens, some discrepancies were observed between viruses detected by the two methods, representing less than 5% of the specimens. NGS was further demonstrated to be equal or superior for the detection of new or poorly characterized viruses when compared with a conventional bioassay. These results validated both the effectiveness of conventional virus testing methods and the use of NGS as an additional or alternative method for plant virus detection.

scholarly journals Sandwich-Type DNA Micro-Optode Based on Gold–Latex Spheres Label for Reflectance Dengue Virus Detection

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1820
Author(s):  
Jeningsih ◽  
Ling Ling Tan ◽  
Alizar Ulianas ◽  
Lee Yook Heng ◽  
Nur-Fadhilah Mazlan ◽  
...  
Keyword(s):  
Dengue Virus ◽  
Limit Of Detection ◽  
Virus Detection ◽  
Average Diameter ◽  
Optical Biosensor ◽  
Clinical Samples ◽  
Sandwich Hybridization ◽  
Latex Spheres ◽  
Sandwich Type ◽  
Thiol Binding

A DNA micro-optode for dengue virus detection was developed based on the sandwich hybridization strategy of DNAs on succinimide-functionalized poly(n-butyl acrylate) (poly(nBA-NAS)) microspheres. Gold nanoparticles (AuNPs) with an average diameter of ~20 nm were synthesized using a centrifugation-based method and adsorbed on the submicrometer-sized polyelectrolyte-coated poly(styrene-co-acrylic acid) (PSA) latex particles via an electrostatic method. The AuNP–latex spheres were attached to the thiolated reporter probe (rDNA) by Au–thiol binding to functionalize as an optical gold–latex–rDNA label. The one-step sandwich hybridization recognition involved a pair of a DNA probe, i.e., capture probe (pDNA), and AuNP–PSA reporter label that flanked the target DNA (complementary DNA (cDNA)). The concentration of dengue virus cDNA was optically transduced by immobilized AuNP–PSA–rDNA conjugates as the DNA micro-optode exhibited a violet hue upon the DNA sandwich hybridization reaction, which could be monitored by a fiber-optic reflectance spectrophotometer at 637 nm. The optical genosensor showed a linear reflectance response over a wide cDNA concentration range from 1.0 × 10−21 M to 1.0 × 10−12 M cDNA (R2 = 0.9807) with a limit of detection (LOD) of 1 × 10−29 M. The DNA biosensor was reusable for three consecutive applications after regeneration with mild sodium hydroxide. The sandwich-type optical biosensor was well validated with a molecular reverse transcription polymerase chain reaction (RT-PCR) technique for screening of dengue virus in clinical samples, e.g., serum, urine, and saliva from dengue virus-infected patients under informed consent.

scholarly journals Tiled-ClickSeq for targeted sequencing of complete coronavirus genomes with simultaneous capture of RNA recombination and minority variants

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Elizabeth Jaworski ◽  
Rose M Langsjoen ◽  
Brooke Mitchell ◽  
Barbara Judy ◽  
Patrick Newman ◽  
...  
Keyword(s):  
Full Range ◽  
Virus Genome ◽  
Clinical Samples ◽  
Rna Recombination ◽  
Single Nucleotide ◽  
Reverse Transcription Reaction ◽  
Minority Variants ◽  
Next Generation Sequencing Ngs ◽  
Unique Molecular Identifier ◽  
Generation Sequencing

High-throughput genomics of SARS-CoV-2 is essential to characterize virus evolution and to identify adaptations that affect pathogenicity or transmission. While single-nucleotide variations (SNVs) are commonly considered as driving virus adaption, RNA recombination events that delete or insert nucleic acid sequences are also critical. Whole genome targeting sequencing of SARS-CoV-2 is typically achieved using pairs of primers to generate cDNA amplicons suitable for next-generation sequencing (NGS). However, paired-primer approaches impose constraints on where primers can be designed, how many amplicons are synthesized and requires multiple PCR reactions with non-overlapping primer pools. This imparts sensitivity to underlying SNVs and fails to resolve RNA recombination junctions that are not flanked by primer pairs. To address these limitations, we have designed an approach called ‘Tiled-ClickSeq’, which uses hundreds of tiled-primers spaced evenly along the virus genome in a single reverse-transcription reaction. The other end of the cDNA amplicon is generated by azido-nucleotides that stochastically terminate cDNA synthesis, removing the need for a paired-primer. A sequencing adaptor containing a Unique Molecular Identifier (UMI) is appended to the cDNA fragment using click-chemistry and a PCR reaction generates a final NGS library. Tiled-ClickSeq provides complete genome coverage, including the 5’UTR, at high depth and specificity to the virus on both Illumina and Nanopore NGS platforms. Here, we analyze multiple SARS-CoV-2 isolates and clinical samples to simultaneously characterize minority variants, sub-genomic mRNAs (sgmRNAs), structural variants (SVs) and D-RNAs. Tiled-ClickSeq therefore provides a convenient and robust platform for SARS-CoV-2 genomics that captures the full range of RNA species in a single, simple assay.

scholarly journals Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples

2021 ◽  
Author(s):  
Jutte J.C. de Vries ◽  
Julianne R. Brown ◽  
Nicole Fischer ◽  
Igor A. Sidorov ◽  
Sofia Morfopoulou ◽  
...  
Keyword(s):  
De Novo ◽  
Respiratory Infections ◽  
Limit Of Detection ◽  
Bioinformatic Analysis ◽  
Clinical Samples ◽  
Mixed Infections ◽  
Metagenomic Sequencing ◽  
User Friendliness ◽  
Viral Pathogens ◽  
Clinical Diagnostic

Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories. Methods Metagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analysed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analysed. Results Overall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection. Conclusion A wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.

scholarly journals Investigation of neglected protists Blastocystis sp. and Dientamoeba fragilis in immunocompetent and immunodeficient diarrheal patients using both conventional and molecular methods

2021 ◽  
Vol 15 (10) ◽  
pp. e0009779
Author(s):  
Fakhriddin Sarzhanov ◽  
Funda Dogruman-Al ◽  
Monica Santin ◽  
Jenny G. Maloney ◽  
Ayse Semra Gureser ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Gastrointestinal Symptoms ◽  
Molecular Methods ◽  
Clinical Samples ◽  
Rrna Gene ◽  
Next Generation ◽  
Dientamoeba Fragilis ◽  
Significant Difference ◽  
Generation Sequencing ◽  
Immunocompetent Patients

Introduction The clinical significance of Blastocystis sp. and Dientamoeba fragilis in patients with gastrointestinal symptoms is a controversial issue. Since the pathogenicity of these protists has not been fully elucidated, testing for these organisms is not routinely pursued by most laboratories and clinicians. Thus, the prevalence of these organisms and the subtypes of Blastocystis sp. in human patients in Turkey are not well characterized. This study aimed to determine the prevalence of Blastocystis sp. and D. fragilis in the diarrheic stool samples of immunodeficient and immunocompetent patients using conventional and molecular methods and to identify Blastocystis sp. subtypes using next generation sequencing. Material and methods Individual stool specimens were collected from 245 immunodeficient and 193 immunocompetent diarrheic patients between March 2017 and December 2019 at the Gazi University Training and Research Hospital in Ankara, Turkey. Samples were screened for Blastocystis sp. and D. fragilis by conventional and molecular methods. Molecular detection of both protists was achieved by separate qPCRs targeting a partial fragment of the SSU rRNA gene. Next generation sequencing was used to identify Blastocystis sp. subtypes. Results The prevalence of Blastocystis sp. and D. fragilis was 16.7% and 11.9%, respectively as measured by qPCR. The prevalence of Blastocystis sp. and D. fragilis was lower in immunodeficient patients (12.7% and 10.6%, respectively) compared to immunocompetent patients (21.8% and 13.5%, respectively). Five Blastocystis sp. subtypes were identified and the following subtype distribution was observed: ST3 54.4% (n = 37), ST2 16.2% (n = 11), ST1 4.4% (n = 3), ST6 2.9% (n = 2), ST4 1.5% (n = 1), ST2/ST3 11.8% (n = 8) and ST1/ST3 8.8% (n = 6). There was no statistically significant difference in the distribution of Blastocystis sp. subtypes between immunocompetent and immunodeficient patients. Conclusion and recommendation Our findings demonstrated that Blastocystis sp. and D. fragilis are commonly present in immunocompetent and immunodeficient patients with diarrhea. This study is the first to use next generation sequencing to address the presence of Blastocystis sp. mixed subtypes and intra-subtype variability in clinical samples in Turkey.

scholarly journals Virus detection and identification in minutes using single-particle imaging and deep learning

2020 ◽  
Author(s):  
Nicolas Shiaelis ◽  
Alexander Tometzki ◽  
Leon Peto ◽  
Andrew McMahon ◽  
Christof Hepp ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Single Particle ◽  
Virus Detection ◽  
Diagnostic Methods ◽  
Clinical Samples ◽  
Promising Alternative ◽  
Detection And Identification ◽  
Particle Imaging ◽  
Single Particle Imaging

AbstractThe increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the current COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive viral diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of single intact particles of different viruses. Our assay achieves labeling, imaging and virus identification in less than five minutes and does not require any lysis, purification or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses, with high accuracy. Single-particle imaging combined with deep learning offers a promising alternative to traditional viral diagnostic methods, and has the potential for significant impact.

Microsatellite instability detection using a large next-generation sequencing cancer panel across diverse tumour types

2019 ◽  
Vol 73 (2) ◽  
pp. 83-89 ◽  
Author(s):  
Jiuhong Pang ◽  
Tatyana Gindin ◽  
Mahesh Mansukhani ◽  
Helen Fernandes ◽  
Susan Hsiao
Keyword(s):  
Next Generation Sequencing ◽  
Microsatellite Instability ◽  
Microsatellite Loci ◽  
Clinical Samples ◽  
Next Generation ◽  
Diverse Range ◽  
Tree Classifier ◽  
Generation Sequencing ◽  
Cancer Panel ◽  
Clinical Cases

AimMicrosatellite instability (MSI), a hallmark of DNA mismatch repair deficiency, is a key molecular biomarker with multiple clinical implications including the selection of patients for immunotherapy, identifying patients who may have Lynch syndrome and predicting prognosis in patients with colorectal tumours. Next-generation sequencing (NGS) provides the opportunity to interrogate large numbers of microsatellite loci concurrently with genomic variants. We sought to develop a method to detect MSI that would not require paired normal tissue and would leverage the sequence data obtained from a broad range of tumours tested using our 467-gene NGS Columbia Combined Cancer Panel (CCCP).MethodsAltered mononucleotide and dinucleotide microsatellite loci across the CCCP region of interest were evaluated in clinical samples encompassing a diverse range of tumour types. The number of altered loci was used to develop a decision tree classifier model trained on the retrospectively collected cohort of 107 clinical cases sequenced by the CCCP assay.ResultsThe classifier was able to correctly classify all cases and was then used to analyse a test set of clinical cases (n=112) and was able to correctly predict their MSI status with 100% sensitivity and specificity. Analysis of recurrently altered loci identified alterations in genes involved in DNA repair, signalling and transcriptional regulation pathways, many of which have been implicated in MSI tumours.ConclusionThis study highlights the utility of this approach, which should be applicable to laboratories performing similar testing.

scholarly journals Field-Effect Sensors for Virus Detection: From Ebola to SARS-CoV-2 and Plant Viral Enhancers

2020 ◽  
Vol 11 ◽  
Author(s):  
Arshak Poghossian ◽  
Melanie Jablonski ◽  
Denise Molinnus ◽  
Christina Wege ◽  
Michael J. Schöning
Keyword(s):  
Field Effect ◽  
Point Of Care ◽  
Virus Detection ◽  
Fast Response ◽  
Plant Viruses ◽  
Clinical Samples ◽  
Label Free ◽  
Label Free Detection ◽  
Field Effect Devices ◽  
Long Time

Coronavirus disease 2019 (COVID-19) is a novel human infectious disease provoked by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, no specific vaccines or drugs against COVID-19 are available. Therefore, early diagnosis and treatment are essential in order to slow the virus spread and to contain the disease outbreak. Hence, new diagnostic tests and devices for virus detection in clinical samples that are faster, more accurate and reliable, easier and cost-efficient than existing ones are needed. Due to the small sizes, fast response time, label-free operation without the need for expensive and time-consuming labeling steps, the possibility of real-time and multiplexed measurements, robustness and portability (point-of-care and on-site testing), biosensors based on semiconductor field-effect devices (FEDs) are one of the most attractive platforms for an electrical detection of charged biomolecules and bioparticles by their intrinsic charge. In this review, recent advances and key developments in the field of label-free detection of viruses (including plant viruses) with various types of FEDs are presented. In recent years, however, certain plant viruses have also attracted additional interest for biosensor layouts: Their repetitive protein subunits arranged at nanometric spacing can be employed for coupling functional molecules. If used as adapters on sensor chip surfaces, they allow an efficient immobilization of analyte-specific recognition and detector elements such as antibodies and enzymes at highest surface densities. The display on plant viral bionanoparticles may also lead to long-time stabilization of sensor molecules upon repeated uses and has the potential to increase sensor performance substantially, compared to conventional layouts. This has been demonstrated in different proof-of-concept biosensor devices. Therefore, richly available plant viral particles, non-pathogenic for animals or humans, might gain novel importance if applied in receptor layers of FEDs. These perspectives are explained and discussed with regard to future detection strategies for COVID-19 and related viral diseases.

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