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Gaire TN, Odland C, Zhang B, Slizovskiy I, Jorgenson B, Wehri T, Meneguzzi M, Wass B, Schuld J, Hanson D, Doster E, Singer J, Cannon J, Asmus A, Ray T, Dee S, Nerem J, Davies P, Noyes NR. Slaughtering processes impact microbial communities and antimicrobial resistance genes of pig carcasses. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174394. [PMID: 38955276 DOI: 10.1016/j.scitotenv.2024.174394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 06/27/2024] [Accepted: 06/28/2024] [Indexed: 07/04/2024]
Abstract
Several steps in the abattoir can influence the presence of microbes and associated resistance genes (ARGs) on the animal carcasses used for further meat processing. We investigated how these processes influence the resistome-microbiome of groups of pigs with different on-farm antimicrobial exposure status, from the moment they entered the abattoir until the end of carcass processing. Using a targeted enrichment metagenomic approach, we identified 672 unique ARGs conferring resistance to 43 distinct AMR classes from pooled skin (N = 42) and carcass swabs (N = 63) collected sequentially before, during, and after the slaughter process and food safety interventions. We observed significant variations in the resistome and microbial profiles of pigs before and after slaughter, as well as a significant decline in ARG counts, diversity, and microbial DNA load during slaughter and carcass processing, irrespective of prior antimicrobial treatments on the farm. These results suggest that existing interventions in the abattoir are effective in reducing not only the pathogen load but also the overall bacterial burden, including ARGs on pork carcasses. Concomitant with reductions in microbial and ARG counts, we observed an increase in the relative abundance of non-drug-specific ARGs, such as those conferring resistance to metals and biocides, and in particular mercury. Using a strict colocalization procedure, we found that most mercury ARGs were associated with genomes from the Pseudomonadaceae and Enterobacteriaceae families. Collectively, these findings demonstrate that slaughter and processing practices within the abattoir can shape the microbial and ARG profiles of pork carcasses during the transition from living muscle to meat.
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Affiliation(s)
- Tara N Gaire
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Carissa Odland
- Pipestone Veterinary Services, Pipestone, MN, USA; Wholestone Farms, NE, USA
| | - Bingzhou Zhang
- State Key Laboratory of Agricultural Microbiology, College of Animal Sciences and Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China
| | - Ilya Slizovskiy
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Blake Jorgenson
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Thomas Wehri
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Mariana Meneguzzi
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Britta Wass
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | | | - Dan Hanson
- Pipestone Applied Research, Pipestone, MN, USA
| | - Enrique Doster
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Jacob Singer
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | | | - Aaron Asmus
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA; Hormel Foods, Austin, MN, USA
| | - Tui Ray
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Scott Dee
- Pipestone Applied Research, Pipestone, MN, USA
| | - Joel Nerem
- Pipestone Applied Research, Pipestone, MN, USA
| | - Peter Davies
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA
| | - Noelle R Noyes
- Department of Veterinary Population Medicine (VPM), College of Veterinary Medicine, University of Minnesota, Saint Paul, MN, USA.
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2
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Wang MX, Lou EG, Sapoval N, Kim E, Kalvapalle P, Kille B, Elworth RAL, Liu Y, Fu Y, Stadler LB, Treangen TJ. Olivar: towards automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens. Nat Commun 2024; 15:6306. [PMID: 39060254 PMCID: PMC11282221 DOI: 10.1038/s41467-024-49957-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 06/25/2024] [Indexed: 07/28/2024] Open
Abstract
Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 15 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer mismatches overlapping with primers and predicted PCR byproducts. We also compare Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluate Olivar on real wastewater samples and found that Olivar has up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available online as a web application at https://olivar.rice.edu and can be installed locally as a command line tool with Bioconda. Source code, installation guide, and usage are available at https://github.com/treangenlab/Olivar .
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Affiliation(s)
- Michael X Wang
- Department of Bioengineering, Rice University, Houston, TX, 77030, USA
| | - Esther G Lou
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA
| | - Nicolae Sapoval
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Eddie Kim
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Prashant Kalvapalle
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA
| | - Bryce Kille
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - R A Leo Elworth
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Yunxi Liu
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Yilei Fu
- Department of Computer Science, Rice University, Houston, TX, 77005, USA
| | - Lauren B Stadler
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA.
| | - Todd J Treangen
- Department of Bioengineering, Rice University, Houston, TX, 77030, USA.
- Department of Computer Science, Rice University, Houston, TX, 77005, USA.
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3
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Mourik K, Sidorov I, Carbo EC, van der Meer D, Boot A, Kroes ACM, Claas ECJ, Boers SA, de Vries JJC. Comparison of the performance of two targeted metagenomic virus capture probe-based methods using reference control materials and clinical samples. J Clin Microbiol 2024; 62:e0034524. [PMID: 38757981 PMCID: PMC11237577 DOI: 10.1128/jcm.00345-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 04/05/2024] [Indexed: 05/18/2024] Open
Abstract
Viral enrichment by probe hybridization has been reported to significantly increase the sensitivity of viral metagenomics. This study compares the analytical performance of two targeted metagenomic virus capture probe-based methods: (i) SeqCap EZ HyperCap by Roche (ViroCap) and (ii) Twist Comprehensive Viral Research Panel workflow, for diagnostic use. Sensitivity, specificity, and limit of detection were analyzed using 25 synthetic viral sequences spiked in increasing proportions of human background DNA, eight clinical samples, and American Type Culture Collection (ATCC) Virome Virus Mix. Sensitivity and specificity were 95% and higher for both methods using the synthetic and reference controls as gold standard. Combining thresholds for viral sequence read counts and genome coverage [respectively 500 reads per million (RPM) and 10% coverage] resulted in optimal prediction of true positive results. Limits of detection were approximately 50-500 copies/mL for both methods as determined by ddPCR. Increasing proportions of spike-in cell-free human background sequences up to 99.999% (50 ng/mL) did not negatively affect viral detection, suggesting effective capture of viral sequences. These data show analytical performances in ranges applicable to clinical samples, for both probe hybridization metagenomic approaches. This study supports further steps toward more widespread use of viral metagenomics for pathogen detection, in clinical and surveillance settings using low biomass samples. IMPORTANCE Viral metagenomics has been gradually applied for broad-spectrum pathogen detection of infectious diseases, surveillance of emerging diseases, and pathogen discovery. Viral enrichment by probe hybridization methods has been reported to significantly increase the sensitivity of viral metagenomics. During the past years, a specific hybridization panel distributed by Roche has been adopted in a broad range of different clinical and zoonotic settings. Recently, Twist Bioscience has released a new hybridization panel targeting human and animal viruses. This is the first report comparing the performance of viral metagenomic hybridization panels.
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Affiliation(s)
- Kees Mourik
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Igor Sidorov
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Ellen C. Carbo
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | | | | | - Aloysius C. M. Kroes
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Eric C. J. Claas
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Stefan A. Boers
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
| | - Jutte J. C. de Vries
- Department of Medical Microbiology, Leiden University Center for Infectious Diseases, Leiden University Medical Center, Leiden, the Netherlands
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4
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Young MG, Straub TJ, Worby CJ, Metsky HC, Gnirke A, Bronson RA, van Dijk LR, Desjardins CA, Matranga C, Qu J, Villicana JB, Azimzadeh P, Kau A, Dodson KW, Schreiber HL, Manson AL, Hultgren SJ, Earl AM. Distinct Escherichia coli transcriptional profiles in the guts of recurrent UTI sufferers revealed by pangenome hybrid selection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.29.582780. [PMID: 38463963 PMCID: PMC10925322 DOI: 10.1101/2024.02.29.582780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Low-abundance members of microbial communities are difficult to study in their native habitats. This includes Escherichia coli, a minor, but common inhabitant of the gastrointestinal tract and opportunistic pathogen, including of the urinary tract, where it is the primary pathogen. While multi-omic analyses have detailed critical interactions between uropathogenic Escherichia coli (UPEC) and the bladder that mediate UTI outcome, comparatively little is known about UPEC in its pre-infection reservoir, partly due to its low abundance there (<1% relative abundance). To accurately and sensitively explore the genomes and transcriptomes of diverse E. coli in gastrointestinal communities, we developed E. coli PanSelect which uses a set of probes designed to specifically recognize and capture E. coli's broad pangenome from sequencing libraries. We demonstrated the ability of E. coli PanSelect to enrich, by orders of magnitude, sequencing data from diverse E. coli using a mock community and a set of human stool samples collected as part of a cohort study investigating drivers of recurrent urinary tract infections (rUTI). Comparisons of genomes and transcriptomes between E. coli residing in the gastrointestinal tracts of women with and without a history of rUTI suggest that rUTI gut E. coli are responding to increased levels of oxygen and nitrate, suggestive of mucosal inflammation, which may have implications for recurrent disease. E. coli PanSelect is well suited for investigations of native in vivo biology of E. coli in other environments where it is at low relative abundance, and the framework described here has broad applicability to other highly diverse, low abundance organisms.
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Affiliation(s)
- Mark G Young
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Timothy J Straub
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Colin J Worby
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Hayden C Metsky
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Andreas Gnirke
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Ryan A Bronson
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Lucas R van Dijk
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
- Delft Bioinformatics Lab, Delft University of Technology, Van Mourik Broekmanweg 6, Delft, 2628 XE, The Netherlands
| | | | - Christian Matranga
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - James Qu
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Jesús Bazan Villicana
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Philippe Azimzadeh
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew Kau
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA
- Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, MO, USA
- Division of Allergy and Immunology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Karen W Dodson
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA
- Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, MO, USA
| | - Henry L Schreiber
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA
- Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, MO, USA
| | - Abigail L Manson
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
| | - Scott J Hultgren
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA
- Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, MO, USA
| | - Ashlee M Earl
- Infectious Disease & Microbiome Program, Broad Institute, Cambridge, MA 02142, USA
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5
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Rosenbaum W, Bovinder Ylitalo E, Castel G, Sjödin A, Larsson P, Wigren Byström J, Forsell MNE, Ahlm C, Pettersson L, Tuiskunen Bäck A. Hybrid capture-based next-generation sequencing of new and old world Orthohantavirus strains and wild-type Puumala isolates from humans and bank voles. J Clin Virol 2024; 172:105672. [PMID: 38574565 DOI: 10.1016/j.jcv.2024.105672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 03/20/2024] [Accepted: 03/24/2024] [Indexed: 04/06/2024]
Abstract
Orthohantaviruses, transmitted primarily by rodents, cause hemorrhagic fever with renal syndrome (HFRS) in Eurasia and hantavirus pulmonary syndrome in the Americas. These viruses, with documented human-to-human transmission, exhibit a wide case-fatality rate, 0.5-40 %, depending on the virus species, and no vaccine or effective treatment for severe Orthohantavirus infections exists. In Europe, the Puumala virus (PUUV), carried by the bank vole Myodes glareolus, causes a milder form of HFRS. Despite the reliance on serology and PCR for diagnosis, the three genomic segments of Swedish wild-type PUUV have yet to be completely sequenced. We have developed a targeted hybrid-capture method aimed at comprehensive genomic sequencing of wild-type PUUV isolates and the identification of other Orthohantaviruses. Our custom-designed panel includes >11,200 probes covering the entire Orthohantavirus genus. Using this panel, we sequenced complete viral genomes from bank vole lung tissue, human plasma samples, and cell-cultured reference strains. Analysis revealed that Swedish PUUV isolates belong to the Northern Scandinavian lineage, with nucleotide diversity ranging from 2.8 % to 3.7 % among them. Notably, no significant genotypic differences were observed between the viral sequences from reservoirs and human cases except in the nonstructural protein. Despite the high endemicity of PUUV in Northern Sweden, these are the first complete Swedish wild-type PUUV genomes and substantially increase our understanding of PUUV evolution and epidemiology. The panel's sensitivity enables genomic sequencing of human samples with viral RNA levels reflecting the natural progression of infection and underscores our panel's diagnostic value, and could help to uncover novel Orthohantavirus transmission routes.
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Affiliation(s)
- William Rosenbaum
- Department of Medical Biosciences, Umeå University, SE-90185, Umeå, Sweden
| | | | - Guillaume Castel
- CBGP, INRAE, CIRAD, Institut Agro, IRD, Univ Montpellier, Montpellier, France
| | - Andreas Sjödin
- CBRN Security and Defence, Swedish Defence Research Agency - FOI, Umeå, Sweden
| | - Pär Larsson
- Clinical Genomics Umeå, Umeå University, SE-90185, Umeå, Sweden
| | | | - Mattias N E Forsell
- Department of Clinical Microbiology, Umeå University, SE-90185, Umeå, Sweden
| | - Clas Ahlm
- Department of Clinical Microbiology, Umeå University, SE-90185, Umeå, Sweden
| | - Lisa Pettersson
- Department of Clinical Microbiology, Umeå University, SE-90185, Umeå, Sweden
| | - Anne Tuiskunen Bäck
- Department of Clinical Microbiology, Umeå University, SE-90185, Umeå, Sweden.
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6
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Meng Z, Wang S, Yu L, Zhao K, Wu T, Zhu X, Yang N, Qiao Q, Ma J, Wu B, Ge Y, Cui L. A novel fast hybrid capture sequencing method for high-efficiency common human coronavirus whole-genome acquisition. mSystems 2024; 9:e0122223. [PMID: 38564711 PMCID: PMC11097644 DOI: 10.1128/msystems.01222-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 03/14/2024] [Indexed: 04/04/2024] Open
Abstract
Rapid and accurate sequencing of the entire viral genome, coupled with continuous monitoring of genetic changes, is crucial for understanding the epidemiology of coronaviruses. We designed a novel method called micro target hybrid capture system (MT-Capture) to enable whole-genome sequencing in a timely manner. The novel design of probes used in target binding exhibits a unique and synergistic "hand-in-hand" conjugation effect. The entire hybrid capture process is within 2.5 hours, overcoming the time-consuming and complex operation characteristics of the traditional liquid-phase hybrid capture (T-Capture) system. By designing specific probes for these coronaviruses, MT-Capture effectively enriched isolated strains and 112 clinical samples of coronaviruses with cycle threshold values below 37. Compared to multiplex PCR sequencing, it does not require frequent primer updates and has higher compatibility. MT-Capture is highly sensitive and capable of tracking variants.IMPORTANCEMT-Capture is meticulously designed to enable the efficient acquisition of the target genome of the common human coronavirus. Coronavirus is a kind of virus that people are generally susceptible to and is epidemic and infectious, and it is the virus with the longest genome among known RNA viruses. Therefore, common human coronavirus samples are selected to evaluate the accuracy and sensitivity of MT-Capture. This method utilizes innovative probe designs optimized through probe conjugation techniques, greatly shortening the time and simplifying the handwork compared with traditional hybridization capture processes. Our results demonstrate that MT-Capture surpasses multiplex PCR in terms of sensitivity, exhibiting a thousandfold increase. Moreover, MT-Capture excels in the identification of mutation sites. This method not only is used to target the coronaviruses but also may be used to diagnose other diseases, including various infectious diseases, genetic diseases, or tumors.
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Affiliation(s)
- Zixinrong Meng
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Shuo Wang
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Liping Yu
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Kangchen Zhao
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Tao Wu
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Xiaojuan Zhu
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Ning Yang
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qiao Qiao
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Junyan Ma
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Bin Wu
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Yiyue Ge
- School of Public Health, Nanjing Medical University, Nanjing, China
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Lunbiao Cui
- School of Public Health, Nanjing Medical University, Nanjing, China
- NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Medical Key Laboratory of Pathogenic Microbiology in Emerging Major Infectious Diseases, Jiangsu Province Engineering Research Center of Health Emergency, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
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7
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Quek ZBR, Ng SH. Hybrid-Capture Target Enrichment in Human Pathogens: Identification, Evolution, Biosurveillance, and Genomic Epidemiology. Pathogens 2024; 13:275. [PMID: 38668230 PMCID: PMC11054155 DOI: 10.3390/pathogens13040275] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/11/2024] [Accepted: 03/18/2024] [Indexed: 04/29/2024] Open
Abstract
High-throughput sequencing (HTS) has revolutionised the field of pathogen genomics, enabling the direct recovery of pathogen genomes from clinical and environmental samples. However, pathogen nucleic acids are often overwhelmed by those of the host, requiring deep metagenomic sequencing to recover sufficient sequences for downstream analyses (e.g., identification and genome characterisation). To circumvent this, hybrid-capture target enrichment (HC) is able to enrich pathogen nucleic acids across multiple scales of divergences and taxa, depending on the panel used. In this review, we outline the applications of HC in human pathogens-bacteria, fungi, parasites and viruses-including identification, genomic epidemiology, antimicrobial resistance genotyping, and evolution. Importantly, we explored the applicability of HC to clinical metagenomics, which ultimately requires more work before it is a reliable and accurate tool for clinical diagnosis. Relatedly, the utility of HC was exemplified by COVID-19, which was used as a case study to illustrate the maturity of HC for recovering pathogen sequences. As we unravel the origins of COVID-19, zoonoses remain more relevant than ever. Therefore, the role of HC in biosurveillance studies is also highlighted in this review, which is critical in preparing us for the next pandemic. We also found that while HC is a popular tool to study viruses, it remains underutilised in parasites and fungi and, to a lesser extent, bacteria. Finally, weevaluated the future of HC with respect to bait design in the eukaryotic groups and the prospect of combining HC with long-read HTS.
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Affiliation(s)
- Z. B. Randolph Quek
- Defence Medical & Environmental Research Institute, DSO National Laboratories, Singapore 117510, Singapore
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8
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Cai Y, Lv J, Li R, Huang X, Wang S, Bao Z, Zeng Q. Deqformer: high-definition and scalable deep learning probe design method. Brief Bioinform 2024; 25:bbae007. [PMID: 38305453 PMCID: PMC10835675 DOI: 10.1093/bib/bbae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 12/22/2023] [Accepted: 01/01/2024] [Indexed: 02/03/2024] Open
Abstract
Target enrichment sequencing techniques are gaining widespread use in the field of genomics, prized for their economic efficiency and swift processing times. However, their success depends on the performance of probes and the evenness of sequencing depth among each probe. To accurately predict probe coverage depth, a model called Deqformer is proposed in this study. Deqformer utilizes the oligonucleotides sequence of each probe, drawing inspiration from Watson-Crick base pairing and incorporating two BERT encoders to capture the underlying information from the forward and reverse probe strands, respectively. The encoded data are combined with a feed-forward network to make precise predictions of sequencing depth. The performance of Deqformer is evaluated on four different datasets: SNP panel with 38 200 probes, lncRNA panel with 2000 probes, synthetic panel with 5899 probes and HD-Marker panel for Yesso scallop with 11 000 probes. The SNP and synthetic panels achieve impressive factor 3 of accuracy (F3acc) of 96.24% and 99.66% in 5-fold cross-validation. F3acc rates of over 87.33% and 72.56% are obtained when training on the SNP panel and evaluating performance on the lncRNA and HD-Marker datasets, respectively. Our analysis reveals that Deqformer effectively captures hybridization patterns, making it robust for accurate predictions in various scenarios. Deqformer leads to a novel perspective for probe design pipeline, aiming to enhance efficiency and effectiveness in probe design tasks.
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Affiliation(s)
- Yantong Cai
- MOE Key Laboratory of Marine Genetics and Breeding & Fang Zongxi Center for Marine Evo-Devo, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
| | - Jia Lv
- MOE Key Laboratory of Marine Genetics and Breeding & Fang Zongxi Center for Marine Evo-Devo, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
| | - Rui Li
- MOE Key Laboratory of Marine Genetics and Breeding & Fang Zongxi Center for Marine Evo-Devo, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
| | - Xiaowen Huang
- MOE Key Laboratory of Marine Genetics and Breeding & Fang Zongxi Center for Marine Evo-Devo, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
| | - Shi Wang
- MOE Key Laboratory of Marine Genetics and Breeding & Fang Zongxi Center for Marine Evo-Devo, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
- Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao 266237, China
- Southern Marine Science and Engineer Guangdong Laboratory, Guangzhou, China
- Key Laboratory of Tropical Aquatic Germplasm of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Sanya 572000, China
| | - Zhenmin Bao
- Southern Marine Science and Engineer Guangdong Laboratory, Guangzhou, China
- Key Laboratory of Tropical Aquatic Germplasm of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Sanya 572000, China
| | - Qifan Zeng
- MOE Key Laboratory of Marine Genetics and Breeding & Fang Zongxi Center for Marine Evo-Devo, College of Marine Life Sciences, Ocean University of China, Qingdao 266003, China
- Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao 266237, China
- Southern Marine Science and Engineer Guangdong Laboratory, Guangzhou, China
- Key Laboratory of Tropical Aquatic Germplasm of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Sanya 572000, China
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9
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Chen S, Wang C, Zou Y, Zong Z, Xue Y, Jia J, Dong L, Zhao L, Chen L, Liu L, Chen W, Huang H. Tuberculosis-targeted next-generation sequencing and machine learning: An ultrasensitive diagnostic strategy for paucibacillary pulmonary tuberculosis and tuberculous meningitis. Clin Chim Acta 2024; 553:117697. [PMID: 38145644 DOI: 10.1016/j.cca.2023.117697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/03/2023] [Accepted: 12/04/2023] [Indexed: 12/27/2023]
Abstract
BACKGROUND Existing diagnostic approaches for paucibacillary tuberculosis (TB) are limited by the low sensitivity of testing methods and difficulty in obtaining suitable samples. METHODS An ultrasensitive TB diagnostic strategy was established, integrating efficient and specific TB targeted next-generation sequencing and machine learning models, and validated in clinical cohorts to test plasma cfDNA, cerebrospinal fluid (CSF) DNA collected from tuberculous meningitis (TBM) and pediatric pulmonary TB (PPTB) patients. RESULTS In the detection of 227 samples, application of the specific thresholds of CSF DNA (AUC = 0.974) and plasma cfDNA (AUC = 0.908) yielded sensitivity of 97.01 % and the specificity of 95.65 % in CSF samples and sensitivity of 82.61 % and specificity of 86.36 % in plasma samples, respectively. In the analysis of 44 paired samples from TBM patients, our strategy had a high concordance of 90.91 % (40/44) in plasma cfDNA and CSF DNA with both sensitivity of 95.45 % (42/44). In the PPTB patient, the sensitivity of the TB diagnostic strategy yielded higher sensitivity on plasma specimen than Xpert assay on gastric lavage (28.57 % VS. 15.38 %). CONCLUSIONS Our TB diagnostic strategy provides greater detection sensitivity for paucibacillary TB, while plasma cfDNA as an easily collected specimen, could be an appropriate sample type for PTB and TBM diagnosis.
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Affiliation(s)
- Suting Chen
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Congli Wang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yijun Zou
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaojing Zong
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China; Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi 563001, China
| | - Yi Xue
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Junnan Jia
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Lingling Dong
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Liping Zhao
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China
| | - Lu Chen
- Beijing Macroµ-test Bio-Tech Co., Ltd., Beijing 101300, China
| | - Licheng Liu
- Beijing Macroµ-test Bio-Tech Co., Ltd., Beijing 101300, China
| | - Weijun Chen
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Hairong Huang
- National Clinical Laboratory on Tuberculosis, Beijing Key Laboratory for Drug-resistant Tuberculosis Research, Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
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10
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Kok CR, Mulakken N, Thissen JB, Grey SF, Avila-Herrera A, Upadhyay MM, Lisboa FA, Mabery S, Elster EA, Schobel SA, Be NA. Targeted metagenomic assessment reflects critical colonization in battlefield injuries. Microbiol Spectr 2023; 11:e0252023. [PMID: 37874143 PMCID: PMC10714869 DOI: 10.1128/spectrum.02520-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 09/18/2023] [Indexed: 10/25/2023] Open
Abstract
IMPORTANCE Microbial contamination in combat wounds can lead to opportunistic infections and adverse outcomes. However, current microbiological detection has a limited ability to capture microbial functional genes. This work describes the application of targeted metagenomic sequencing to profile wound bioburden and capture relevant wound-associated signatures for clinical utility. Ultimately, the ability to detect such signatures will help guide clinical decisions regarding wound care and management and aid in the prediction of wound outcomes.
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Affiliation(s)
- Car Reen Kok
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California, USA
| | - Nisha Mulakken
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, California, USA
| | - James B. Thissen
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California, USA
| | - Scott F. Grey
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences (USUHS), Bethesda, Maryland, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
| | - Aram Avila-Herrera
- Computing Directorate, Lawrence Livermore National Laboratory, Livermore, California, USA
| | - Meenu M. Upadhyay
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences (USUHS), Bethesda, Maryland, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
| | - Felipe A. Lisboa
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences (USUHS), Bethesda, Maryland, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Shalini Mabery
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California, USA
| | - Eric A. Elster
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences (USUHS), Bethesda, Maryland, USA
- Walter Reed National Military Medical Center, Bethesda, Maryland, USA
| | - Seth A. Schobel
- Surgical Critical Care Initiative (SC2i), Uniformed Services University of the Health Sciences (USUHS), Bethesda, Maryland, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
| | - Nicholas A. Be
- Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California, USA
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11
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Wang MX, Lou EG, Sapoval N, Kim E, Kalvapalle P, Kille B, Elworth RAL, Liu Y, Fu Y, Stadler LB, Treangen TJ. Olivar: automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.11.528155. [PMID: 36824759 PMCID: PMC9948974 DOI: 10.1101/2023.02.11.528155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 2 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly. Here we present Olivar, a first step towards a fully automated, variant-aware design of tiled amplicons for pathogen genomes. Olivar converts each nucleotide of the target genome into a numeric risk score, capturing undesired sequence features that should be avoided. In a direct comparison with PrimalScheme, we show that Olivar has fewer SNPs overlapping with primers and predicted PCR byproducts. We also compared Olivar head-to-head with ARTIC v4.1, the most widely used primer set for SARS-CoV-2 sequencing, and show Olivar yields similar read mapping rates (~90%) and better coverage to the manually designed ARTIC v4.1 amplicons. We also evaluated Olivar on real wastewater samples and found that Olivar had up to 3-fold higher mapping rates while retaining similar coverage. In summary, Olivar automates and accelerates the generation of tiled amplicons, even in situations of high mutation frequency and/or density. Olivar is available as a web application at https://olivar.rice.edu. Olivar can also be installed locally as a command line tool with Bioconda. Source code, installation guide and usage are available at https://github.com/treangenlab/Olivar.
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Affiliation(s)
- Michael X. Wang
- Department of Bioengineering, Rice University, Houston, 77030, USA
| | - Esther G. Lou
- Department of Civil and Environmental Engineering, Rice University, Houston, 77005, USA
| | - Nicolae Sapoval
- Department of Computer Science, Rice University, Houston, 77005, USA
| | - Eddie Kim
- Department of Computer Science, Rice University, Houston, 77005, USA
| | - Prashant Kalvapalle
- Department of Civil and Environmental Engineering, Rice University, Houston, 77005, USA
| | - Bryce Kille
- Department of Computer Science, Rice University, Houston, 77005, USA
| | - R. A. Leo Elworth
- Department of Computer Science, Rice University, Houston, 77005, USA
| | - Yunxi Liu
- Department of Computer Science, Rice University, Houston, 77005, USA
| | - Yilei Fu
- Department of Computer Science, Rice University, Houston, 77005, USA
| | - Lauren B. Stadler
- Department of Civil and Environmental Engineering, Rice University, Houston, 77005, USA
| | - Todd J. Treangen
- Department of Computer Science, Rice University, Houston, 77005, USA
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12
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Oguzie JU, Petros BA, Oluniyi PE, Mehta SB, Eromon PE, Nair P, Adewale-Fasoro O, Ifoga PD, Odia I, Pastusiak A, Gbemisola OS, Aiyepada JO, Uyigue EA, Edamhande AP, Blessing O, Airende M, Tomkins-Tinch C, Qu J, Stenson L, Schaffner SF, Oyejide N, Ajayi NA, Ojide K, Ogah O, Abejegah C, Adedosu N, Ayodeji O, Liasu AA, Okogbenin S, Okokhere PO, Park DJ, Folarin OA, Komolafe I, Ihekweazu C, Frost SDW, Jackson EK, Siddle KJ, Sabeti PC, Happi CT. Metagenomic surveillance uncovers diverse and novel viral taxa in febrile patients from Nigeria. Nat Commun 2023; 14:4693. [PMID: 37542071 PMCID: PMC10403498 DOI: 10.1038/s41467-023-40247-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 07/10/2023] [Indexed: 08/06/2023] Open
Abstract
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.
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Affiliation(s)
- Judith U Oguzie
- Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | - Brittany A Petros
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Harvard-MIT Program in Health Sciences and Technology, Cambridge, MA, 02139, USA
- Harvard/MIT MD-PhD Program, Boston, MA, 02115, USA
- Systems, Synthetic, and Quantitative Biology PhD Program, Department of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Paul E Oluniyi
- Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Samar B Mehta
- Department of Medicine, University of Maryland Medical Center, Baltimore, MA, USA
| | - Philomena E Eromon
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | - Parvathy Nair
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Opeoluwa Adewale-Fasoro
- Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | - Peace Damilola Ifoga
- Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | - Ikponmwosa Odia
- Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria
| | | | - Otitoola Shobi Gbemisola
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | | | | | | | - Osiemi Blessing
- Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria
| | - Michael Airende
- Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria
| | - Christopher Tomkins-Tinch
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - James Qu
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Liam Stenson
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Nicholas Oyejide
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | - Nnenna A Ajayi
- Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria
| | - Kingsley Ojide
- Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria
| | - Onwe Ogah
- Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria
| | | | | | | | | | | | | | - Daniel J Park
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Onikepe A Folarin
- Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | - Isaac Komolafe
- Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria
| | | | - Simon D W Frost
- Microsoft Premonition, Redmond, WA, USA
- London School of Hygiene and Tropical Medicine, London, UK
| | | | - Katherine J Siddle
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Molecular Microbiology and Immunology, Brown University, Providence, RI, USA.
| | - Pardis C Sabeti
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
| | - Christian T Happi
- Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Osun State, Nigeria.
- African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State, Nigeria.
- Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria.
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
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13
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Masters NB, Beck AS, Mathis AD, Leung J, Raines K, Paul P, Stanley SE, Weg AL, Pieracci EG, Gearhart S, Jumabaeva M, Bankamp B, Rota PA, Sugerman DE, Gastañaduy PA. Measles virus transmission patterns and public health responses during Operation Allies Welcome: a descriptive epidemiological study. Lancet Public Health 2023; 8:e618-e628. [PMID: 37516478 PMCID: PMC10411127 DOI: 10.1016/s2468-2667(23)00130-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 06/07/2023] [Accepted: 06/20/2023] [Indexed: 07/31/2023]
Abstract
BACKGROUND On Aug 29, 2021, Operation Allies Welcome (OAW) was established to support the resettlement of more than 80 000 Afghan evacuees in the USA. After identification of measles among evacuees, incoming evacuee flights were temporarily paused, and mass measles vaccination of evacuees aged 6 months or older was introduced domestically and overseas, with a 21-day quarantine period after vaccination. We aimed to evaluate patterns of measles virus transmission during this outbreak and the impact of control measures. METHODS We conducted a measles outbreak investigation among Afghan evacuees who were resettled in the USA as part of OAW. Patients with measles were defined as individuals with an acute febrile rash illness between Aug 29, 2021, and Nov 26, 2021, and either laboratory confirmation of infection or epidemiological link to a patient with measles with laboratory confirmation. We analysed the demographics and clinical characteristics of patients with measles and used epidemiological information and whole-genome sequencing to track transmission pathways. A transmission model was used to evaluate the effects of vaccination and other interventions. FINDINGS 47 people with measles (attack rate: 0·65 per 1000 evacuees) were reported in six US locations housing evacuees in four states. The median age of patients was 1 year (range 0-26); 33 (70%) were younger than 5 years. The age distribution shifted during the outbreak towards infants younger than 12 months. 20 (43%) patients with wild-type measles virus had rash onset after vaccination. No fatalities or community spread were identified, nor further importations after flight resumption. In a non-intervention scenario, transmission models estimated that a median of 5506 cases (IQR 10-5626) could have occurred. Infection clusters based on epidemiological criteria could be delineated into smaller clusters using phylogenetic analyses; however, sequences with few substitution count differences did not always indicate single lines of transmission. INTERPRETATION Implementation of control measures limited measles transmission during OAW. Our findings highlight the importance of integration between epidemiological and genetic information in discerning between individual lines of transmission in an elimination setting. FUNDING US Centers for Disease Control and Prevention.
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Affiliation(s)
- Nina B Masters
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA; Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Andrew S Beck
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Adria D Mathis
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jessica Leung
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Kelley Raines
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Prabasaj Paul
- Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Scott E Stanley
- Office of the Joint Staff Surgeon, The Joint Staff, Department of Defense, Washington, DC, USA
| | - Alden L Weg
- Office of the Joint Staff Surgeon, The Joint Staff, Department of Defense, Washington, DC, USA
| | - Emily G Pieracci
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Shannon Gearhart
- Division of Global Migration and Quarantine, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Madina Jumabaeva
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA; Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Bettina Bankamp
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Paul A Rota
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - David E Sugerman
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Paul A Gastañaduy
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
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14
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Baumeier C, Harms D, Aleshcheva G, Gross U, Escher F, Schultheiss HP. Advancing Precision Medicine in Myocarditis: Current Status and Future Perspectives in Endomyocardial Biopsy-Based Diagnostics and Therapeutic Approaches. J Clin Med 2023; 12:5050. [PMID: 37568452 PMCID: PMC10419903 DOI: 10.3390/jcm12155050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/24/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
The diagnosis and specific and causal treatment of myocarditis and inflammatory cardiomyopathy remain a major clinical challenge. Despite the rapid development of new imaging techniques, endomyocardial biopsies remain the gold standard for accurate diagnosis of inflammatory myocardial disease. With the introduction and continued development of immunohistochemical inflammation diagnostics in combination with viral nucleic acid testing, myocarditis diagnostics have improved significantly since their introduction. Together with new technologies such as miRNA and gene expression profiling, quantification of specific immune cell markers, and determination of viral activity, diagnostic accuracy and patient prognosis will continue to improve in the future. In this review, we summarize the current knowledge on the pathogenesis and diagnosis of myocarditis and inflammatory cardiomyopathies and highlight future perspectives for more in-depth and specialized biopsy diagnostics and precision, personalized medicine approaches.
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Affiliation(s)
- Christian Baumeier
- Institute of Cardiac Diagnostics and Therapy, IKDT GmbH, 12203 Berlin, Germany; (D.H.); (G.A.); (U.G.); (H.-P.S.)
| | - Dominik Harms
- Institute of Cardiac Diagnostics and Therapy, IKDT GmbH, 12203 Berlin, Germany; (D.H.); (G.A.); (U.G.); (H.-P.S.)
- Department of Infectious Diseases, Robert Koch Institute, 13353 Berlin, Germany
| | - Ganna Aleshcheva
- Institute of Cardiac Diagnostics and Therapy, IKDT GmbH, 12203 Berlin, Germany; (D.H.); (G.A.); (U.G.); (H.-P.S.)
| | - Ulrich Gross
- Institute of Cardiac Diagnostics and Therapy, IKDT GmbH, 12203 Berlin, Germany; (D.H.); (G.A.); (U.G.); (H.-P.S.)
| | - Felicitas Escher
- Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Campus Virchow Klinikum, 13353 Berlin, Germany;
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, 10785 Berlin, Germany
| | - Heinz-Peter Schultheiss
- Institute of Cardiac Diagnostics and Therapy, IKDT GmbH, 12203 Berlin, Germany; (D.H.); (G.A.); (U.G.); (H.-P.S.)
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15
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Batool M, Galloway-Peña J. Clinical metagenomics-challenges and future prospects. Front Microbiol 2023; 14:1186424. [PMID: 37448579 PMCID: PMC10337830 DOI: 10.3389/fmicb.2023.1186424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 06/12/2023] [Indexed: 07/15/2023] Open
Abstract
Infections lacking precise diagnosis are often caused by a rare or uncharacterized pathogen, a combination of pathogens, or a known pathogen carrying undocumented or newly acquired genes. Despite medical advances in infectious disease diagnostics, many patients still experience mortality or long-term consequences due to undiagnosed or misdiagnosed infections. Thus, there is a need for an exhaustive and universal diagnostic strategy to reduce the fraction of undocumented infections. Compared to conventional diagnostics, metagenomic next-generation sequencing (mNGS) is a promising, culture-independent sequencing technology that is sensitive to detecting rare, novel, and unexpected pathogens with no preconception. Despite the fact that several studies and case reports have identified the effectiveness of mNGS in improving clinical diagnosis, there are obvious shortcomings in terms of sensitivity, specificity, costs, standardization of bioinformatic pipelines, and interpretation of findings that limit the integration of mNGS into clinical practice. Therefore, physicians must understand the potential benefits and drawbacks of mNGS when applying it to clinical practice. In this review, we will examine the current accomplishments, efficacy, and restrictions of mNGS in relation to conventional diagnostic methods. Furthermore, we will suggest potential approaches to enhance mNGS to its maximum capacity as a clinical diagnostic tool for identifying severe infections.
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Affiliation(s)
| | - Jessica Galloway-Peña
- Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States
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16
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Carvajal-Barriga EJ, Fitzgerald W, Dimitriadis EK, Margolis L, Fields RD. Sulfated endospermic nanocellulose crystals prevent the transmission of SARS-CoV-2 and HIV-1. Sci Rep 2023; 13:6959. [PMID: 37117231 PMCID: PMC10141831 DOI: 10.1038/s41598-023-33686-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 04/17/2023] [Indexed: 04/30/2023] Open
Abstract
Biomaterials with antimicrobial activity are gaining attention due to their biodegradability and efficacy in interacting with a wide range of microorganisms. A new cellulose nano-biomaterial, endospermic nanocellulose crystals (ENC) obtained from parenchymal tissue of ivory nut endosperm, has a natural capacity as a universal binder. This feature is enhanced when it is chemically functionalized, and can be exploited in the fight against microbes. We tested the ability of sulfated ENC in aqueous suspension to encapsulate viruses through a crosslinking reaction mediated by cations. 0.25% w/v ENC suspensions efficiently encapsulated spike (S) protein, preventing its interaction with ACE2 receptor. ENC was further able to encapsulate SARS-CoV-2 pseudoviruses and prevent infection of 293T-hsACE2 cells. ENC also suppressed infection of MT-4 cells with HIV-1LAI.04. This antiviral activity of sulfated ENC is due to the irreversible interaction of ENC with viral particles mediated by crosslinking, as antiviral activity was less effective in the absence of cations. Additionally, ENC was used as a matrix to immobilize recombinant ACE2 receptors and anti-S IgG, creating molecular lures that efficiently inhibited SARS-CoV-2 infections in vitro. These results show that sulfated ENC from ivory nuts can be used as an efficient antiviral material.
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Affiliation(s)
- Enrique Javier Carvajal-Barriga
- Nervous System Development and Plasticity Section, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
- Neotropical Center for the Biomass Research, Pontificia Universidad Católica del Ecuador, Quito, Pichincha, Ecuador
| | - Wendy Fitzgerald
- Section On Intercellular Interactions, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Emilios K Dimitriadis
- Biomedical Engineering and Physical Science Shared Resource Program, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
| | - Leonid Margolis
- Section On Intercellular Interactions, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - R Douglas Fields
- Nervous System Development and Plasticity Section, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
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17
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Koh WLC, Poh SE, Lee CK, Chan THM, Yan G, Kong KW, Lau L, Lee WYT, Cheng C, Hoon S, Seow Y. Towards a Rapid-Turnaround Low-Depth Unbiased Metagenomics Sequencing Workflow on the Illumina Platforms. Bioengineering (Basel) 2023; 10:bioengineering10050520. [PMID: 37237590 DOI: 10.3390/bioengineering10050520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 04/20/2023] [Accepted: 04/21/2023] [Indexed: 05/28/2023] Open
Abstract
Unbiased metagenomic sequencing is conceptually well-suited for first-line diagnosis as all known and unknown infectious entities can be detected, but costs, turnaround time and human background reads in complex biofluids, such as plasma, hinder widespread deployment. Separate preparations of DNA and RNA also increases costs. In this study, we developed a rapid unbiased metagenomics next-generation sequencing (mNGS) workflow with a human background depletion method (HostEL) and a combined DNA/RNA library preparation kit (AmpRE) to address this issue. We enriched and detected bacterial and fungal standards spiked in plasma at physiological levels with low-depth sequencing (<1 million reads) for analytical validation. Clinical validation also showed 93% of plasma samples agreed with the clinical diagnostic test results when the diagnostic qPCR had a Ct < 33. The effect of different sequencing times was evaluated with the 19 h iSeq 100 paired end run, a more clinically palatable simulated iSeq 100 truncated run and the rapid 7 h MiniSeq platform. Our results demonstrate the ability to detect both DNA and RNA pathogens with low-depth sequencing and that iSeq 100 and MiniSeq platforms are compatible with unbiased low-depth metagenomics identification with the HostEL and AmpRE workflow.
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Affiliation(s)
- Winston Lian Chye Koh
- Bioinformatic Institute, A*STAR (Agency for Science, Technology and Research), Singapore 138632, Singapore
| | - Si En Poh
- Institute of Molecular and Cell Biology, A*STAR (Agency for Science, Technology and Research), Singapore 138673, Singapore
| | - Chun Kiat Lee
- Department of Laboratory Medicine, National University Hospital, Singapore 119228, Singapore
| | - Tim Hon Man Chan
- Department of Laboratory Medicine, National University Hospital, Singapore 119228, Singapore
| | - Gabriel Yan
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
- Division of Microbiology, Department of Laboratory Medicine, National University Health System, Singapore 119228, Singapore
| | - Kiat Whye Kong
- Institute of Molecular and Cell Biology, A*STAR (Agency for Science, Technology and Research), Singapore 138673, Singapore
| | - Lalita Lau
- Institute of Molecular and Cell Biology, A*STAR (Agency for Science, Technology and Research), Singapore 138673, Singapore
| | | | - Clark Cheng
- Paths Diagnostics Pte Limited, Singapore 349317, Singapore
| | - Shawn Hoon
- Institute of Molecular and Cell Biology, A*STAR (Agency for Science, Technology and Research), Singapore 138673, Singapore
| | - Yiqi Seow
- Institute of Molecular and Cell Biology, A*STAR (Agency for Science, Technology and Research), Singapore 138673, Singapore
- Genome Institute of Singapore, A*STAR (Agency for Science, Technology and Research), Singapore 138672, Singapore
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18
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A case for investment in clinical metagenomics in low-income and middle-income countries. THE LANCET. MICROBE 2023; 4:e192-e199. [PMID: 36563703 DOI: 10.1016/s2666-5247(22)00328-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 10/24/2022] [Accepted: 10/25/2022] [Indexed: 12/24/2022]
Abstract
Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.
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19
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High-depth sequencing characterization of viral dynamics across tissues in fatal COVID-19 reveals compartmentalized infection. Nat Commun 2023; 14:574. [PMID: 36732505 PMCID: PMC9894515 DOI: 10.1038/s41467-022-34256-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 10/17/2022] [Indexed: 02/04/2023] Open
Abstract
SARS-CoV-2 distribution and circulation dynamics are not well understood due to challenges in assessing genomic data from tissue samples. We develop experimental and computational workflows for high-depth viral sequencing and high-resolution genomic analyses from formalin-fixed, paraffin-embedded tissues and apply them to 120 specimens from six subjects with fatal COVID-19. To varying degrees, viral RNA is present in extrapulmonary tissues from all subjects. The majority of the 180 viral variants identified within subjects are unique to individual tissue samples. We find more high-frequency (>10%) minor variants in subjects with a longer disease course, with one subject harboring ten such variants, exclusively in extrapulmonary tissues. One tissue-specific high-frequency variant was a nonsynonymous mutation in the furin-cleavage site of the spike protein. Our findings suggest adaptation and/or compartmentalized infection, illuminating the basis of extrapulmonary COVID-19 symptoms and potential for viral reservoirs, and have broad utility for investigating human pathogens.
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20
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Hong M, Peng D, Fu A, Wang X, Zheng Y, Xia L, Shi W, Qian C, Li Z, Liu F, Wu Q. The application of nanopore targeted sequencing in the diagnosis and antimicrobial treatment guidance of bloodstream infection of febrile neutropenia patients with hematologic disease. J Cell Mol Med 2023; 27:506-514. [PMID: 36722317 PMCID: PMC9930421 DOI: 10.1111/jcmm.17651] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 11/12/2022] [Accepted: 12/06/2022] [Indexed: 02/02/2023] Open
Abstract
Traditional microbiological methodology has limited sensitivity, detection range, and turnaround times in diagnosis of bloodstream infection in Febrile Neutropenia (FN) patients. A more rapid and sensitive detection technology is urgently needed. Here we used the newly developed Nanapore targeted sequencing (NTS) to diagnose the pathogens in blood samples. The diagnostic performance (sensitivity, specificity and turnaround time) of NTS detection of 202 blood samples from FN patients with hematologic disease was evaluated in comparison to blood culture and nested Polymerase Chain Reaction (PCR) followed by sanger sequence. The impact of NTS results on antibiotic treatment modification, the effectivity and mortality of the patients under the guidance of NTS results were assessed. The data showed that NTS had clinical sensitivity of 92.11%, clinical specificity of 78.41% compared with the blood culture and PCR combination. Importantly, the turnaround time for NTS was <24 h for all specimens, and the pre-report time within 6 h in emergency cases was possible in clinical practice. Among 118 NTS positive patients, 98.3% patients' antibiotic regimens were guided according to NTS results. There was no significant difference in effectivity and mortality rate between Antibiotic regimen switched according to NTS group and Antibiotic regimen covering pathogens detected by NTS group. Therefore, NTS could yield a higher sensitivity, specificity and shorter turnaround time for broad-spectrum pathogens identification in blood samples detection compared with traditional tests. It's also a good guidance in clinical targeted antibiotic treatment for FN patients with hematologic disease, thereby emerging as a promising technology for detecting infectious disease.
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Affiliation(s)
- Mei Hong
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Danyue Peng
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Aisi Fu
- Wuhan Dgensee Clinical Laboratory Co., Ltd.WuhanChina
| | - Xian Wang
- Wuhan Dgensee Clinical Laboratory Co., Ltd.WuhanChina
| | - Yabiao Zheng
- Wuhan Dgensee Clinical Laboratory Co., Ltd.WuhanChina
| | - Linghui Xia
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Wei Shi
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Chenjing Qian
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Zixuan Li
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Fang Liu
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Qiuling Wu
- Institute of Hematology, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
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21
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Ashall J, Shah S, Biggs JR, Chang JNR, Jafari Y, Brady OJ, Mai HK, Lien LT, Do Thai H, Nguyen HAT, Anh DD, Iwasaki C, Kitamura N, Van Loock M, Herrera-Taracena G, Rasschaert F, Van Wesenbeeck L, Yoshida LM, Hafalla JCR, Hue S, Hibberd ML. A phylogenetic study of dengue virus in urban Vietnam shows long-term persistence of endemic strains. Virus Evol 2023; 9:vead012. [PMID: 36926448 PMCID: PMC10013730 DOI: 10.1093/ve/vead012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 10/31/2022] [Accepted: 02/15/2023] [Indexed: 02/17/2023] Open
Abstract
Dengue virus (DENV) causes repeated outbreaks of disease in endemic areas, with patterns of local transmission strongly influenced by seasonality, importation via human movement, immunity, and vector control efforts. An understanding of how each of these interacts to enable endemic transmission (continual circulation of local virus strains) is largely unknown. There are times of the year when no cases are reported, often for extended periods of time, perhaps wrongly implying the successful eradication of a local strain from that area. Individuals who presented at a clinic or hospital in four communes in Nha Trang, Vietnam, were initially tested for DENV antigen presence. Enrolled positive individuals then had their corresponding household members invited to participate, and those who enrolled were tested for DENV. The presence of viral nucleic acid in all samples was confirmed using quantitative polymerase chain reaction, and positive samples were then whole-genome sequenced using an amplicon and target enrichment library preparation techniques and Illumina MiSeq sequencing technology. Generated consensus genome sequences were then analysed using phylogenetic tree reconstruction to categorise sequences into clades with a common ancestor, enabling investigations of both viral clade persistence and introductions. Hypothetical introduction dates were additionally assessed using a molecular clock model that calculated the time to the most recent common ancestor (TMRCA). We obtained 511 DENV whole-genome sequences covering four serotypes and more than ten distinct viral clades. For five of these clades, we had sufficient data to show that the same viral lineage persisted for at least several months. We noted that some clades persisted longer than others during the sampling time, and by comparison with other published sequences from elsewhere in Vietnam and around the world, we saw that at least two different viral lineages were introduced into the population during the study period (April 2017-2019). Next, by inferring the TMRCA from the construction of molecular clock phylogenies, we predicted that two of the viral lineages had been present in the study population for over a decade. We observed five viral lineages co-circulating in Nha Trang from three DENV serotypes, with two likely to have remained as uninterrupted transmission chains for a decade. This suggests clade cryptic persistence in the area, even during periods of low reported incidence.
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Affiliation(s)
- James Ashall
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Sonal Shah
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Joseph R Biggs
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Jui-Ning R Chang
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Yalda Jafari
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Oliver J Brady
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Huynh Kim Mai
- Department of Microbiology and Immunology, Pasteur Institute of Nha Trang, Xương Huân, Nha Trang, 650000, Vietnam
| | - Le Thuy Lien
- Department of Microbiology and Immunology, Pasteur Institute of Nha Trang, Xương Huân, Nha Trang, 650000, Vietnam
| | - Hung Do Thai
- Department of Microbiology and Immunology, Pasteur Institute of Nha Trang, Xương Huân, Nha Trang, 650000, Vietnam
| | - Hien Anh Thi Nguyen
- National Institute of Hygiene and Epidemiology, 1 P. Yec Xanh, Phạm Đình Hổ, Hai Bà Trưng, Hà Nội, 100000, Vietnam
| | - Dang Duc Anh
- National Institute of Hygiene and Epidemiology, 1 P. Yec Xanh, Phạm Đình Hổ, Hai Bà Trưng, Hà Nội, 100000, Vietnam
| | - Chihiro Iwasaki
- Paediatric Infectious Diseases Department, Institute of Tropical Medicine, Nagasaki University, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan
| | - Noriko Kitamura
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Paediatric Infectious Diseases Department, Institute of Tropical Medicine, Nagasaki University, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan
| | - Marnix Van Loock
- Janssen R&D, Janssen Pharmaceutica NV, Turnhoutseweg 30, Beerse B-2340, Belgium
| | - Guillermo Herrera-Taracena
- Janssen Global Public Health, Janssen Research & Development, LLC, 800 Ridgeview Drive, Horsham, PA 19044, USA
| | - Freya Rasschaert
- Janssen R&D, Janssen Pharmaceutica NV, Turnhoutseweg 30, Beerse B-2340, Belgium
| | | | - Lay-Myint Yoshida
- Paediatric Infectious Diseases Department, Institute of Tropical Medicine, Nagasaki University, 1-12-4 Sakamoto, Nagasaki 852-8523, Japan
| | - Julius Clemence R Hafalla
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Stephane Hue
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.,Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Martin L Hibberd
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
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22
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Sandybayev N, Beloussov V, Strochkov V, Solomadin M, Granica J, Yegorov S. Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome. Microorganisms 2022; 10:microorganisms10122327. [PMID: 36557580 PMCID: PMC9785614 DOI: 10.3390/microorganisms10122327] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/17/2022] [Accepted: 11/21/2022] [Indexed: 11/25/2022] Open
Abstract
The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.
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Affiliation(s)
- Nurlan Sandybayev
- Kazakhstan-Japan Innovation Center, Kazakh National Agrarian Research University, Almaty 050010, Kazakhstan
- Correspondence: ; Tel.: +7-778312-2058
| | - Vyacheslav Beloussov
- Kazakhstan-Japan Innovation Center, Kazakh National Agrarian Research University, Almaty 050010, Kazakhstan
- Molecular Genetics Laboratory TreeGene, Almaty 050009, Kazakhstan
| | - Vitaliy Strochkov
- Kazakhstan-Japan Innovation Center, Kazakh National Agrarian Research University, Almaty 050010, Kazakhstan
| | - Maxim Solomadin
- School of Pharmacy, Karaganda Medical University, Karaganda 100000, Kazakhstan
| | - Joanna Granica
- Molecular Genetics Laboratory TreeGene, Almaty 050009, Kazakhstan
| | - Sergey Yegorov
- Michael G. DeGroote Institute for Infectious Disease Research, Faculty of Health Sciences, McMaster University, Hamilton, ON L8S 4LB, Canada
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23
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Slizovskiy IB, Oliva M, Settle JK, Zyskina LV, Prosperi M, Boucher C, Noyes NR. Target-enriched long-read sequencing (TELSeq) contextualizes antimicrobial resistance genes in metagenomes. MICROBIOME 2022; 10:185. [PMID: 36324140 PMCID: PMC9628182 DOI: 10.1186/s40168-022-01368-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 09/02/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Metagenomic data can be used to profile high-importance genes within microbiomes. However, current metagenomic workflows produce data that suffer from low sensitivity and an inability to accurately reconstruct partial or full genomes, particularly those in low abundance. These limitations preclude colocalization analysis, i.e., characterizing the genomic context of genes and functions within a metagenomic sample. Genomic context is especially crucial for functions associated with horizontal gene transfer (HGT) via mobile genetic elements (MGEs), for example antimicrobial resistance (AMR). To overcome this current limitation of metagenomics, we present a method for comprehensive and accurate reconstruction of antimicrobial resistance genes (ARGs) and MGEs from metagenomic DNA, termed target-enriched long-read sequencing (TELSeq). RESULTS Using technical replicates of diverse sample types, we compared TELSeq performance to that of non-enriched PacBio and short-read Illumina sequencing. TELSeq achieved much higher ARG recovery (>1,000-fold) and sensitivity than the other methods across diverse metagenomes, revealing an extensive resistome profile comprising many low-abundance ARGs, including some with public health importance. Using the long reads generated by TELSeq, we identified numerous MGEs and cargo genes flanking the low-abundance ARGs, indicating that these ARGs could be transferred across bacterial taxa via HGT. CONCLUSIONS TELSeq can provide a nuanced view of the genomic context of microbial resistomes and thus has wide-ranging applications in public, animal, and human health, as well as environmental surveillance and monitoring of AMR. Thus, this technique represents a fundamental advancement for microbiome research and application. Video abstract.
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Affiliation(s)
- Ilya B Slizovskiy
- Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA
| | - Marco Oliva
- Department of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA
| | - Jonathen K Settle
- Department of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA
| | - Lidiya V Zyskina
- Program in Human-Computer Interaction, College of Information Studies, University of Maryland, College Park, MD, USA
| | - Mattia Prosperi
- Data Intelligence Systems Lab, Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Christina Boucher
- Department of Computer and Information Science and Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, USA
| | - Noelle R Noyes
- Food-Centric Corridor, Infectious Disease Laboratory, Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA.
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24
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Hilt EE, Ferrieri P. Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases. Genes (Basel) 2022; 13:genes13091566. [PMID: 36140733 PMCID: PMC9498426 DOI: 10.3390/genes13091566] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/24/2022] [Accepted: 08/26/2022] [Indexed: 12/03/2022] Open
Abstract
Next-generation sequencing (NGS) technologies have become increasingly available for use in the clinical microbiology diagnostic environment. There are three main applications of these technologies in the clinical microbiology laboratory: whole genome sequencing (WGS), targeted metagenomics sequencing and shotgun metagenomics sequencing. These applications are being utilized for initial identification of pathogenic organisms, the detection of antimicrobial resistance mechanisms and for epidemiologic tracking of organisms within and outside hospital systems. In this review, we analyze these three applications and provide a comprehensive summary of how these applications are currently being used in public health, basic research, and clinical microbiology laboratory environments. In the public health arena, WGS is being used to identify and epidemiologically track food borne outbreaks and disease surveillance. In clinical hospital systems, WGS is used to identify multi-drug-resistant nosocomial infections and track the transmission of these organisms. In addition, we examine how metagenomics sequencing approaches (targeted and shotgun) are being used to circumvent the traditional and biased microbiology culture methods to identify potential pathogens directly from specimens. We also expand on the important factors to consider when implementing these technologies, and what is possible for these technologies in infectious disease diagnosis in the next 5 years.
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25
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Kuchinski KS, Duan J, Himsworth C, Hsiao W, Prystajecky NA. ProbeTools: designing hybridization probes for targeted genomic sequencing of diverse and hypervariable viral taxa. BMC Genomics 2022; 23:579. [PMID: 35953803 PMCID: PMC9371634 DOI: 10.1186/s12864-022-08790-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 07/18/2022] [Indexed: 11/29/2022] Open
Abstract
Background Sequencing viruses in many specimens is hindered by excessive background material from hosts, microbiota, and environmental organisms. Consequently, enrichment of target genomic material is necessary for practical high-throughput viral genome sequencing. Hybridization probes are widely used for enrichment in many fields, but their application to viral sequencing faces a major obstacle: it is difficult to design panels of probe oligo sequences that broadly target many viral taxa due to their rapid evolution, extensive diversity, and genetic hypervariability. To address this challenge, we created ProbeTools, a package of bioinformatic tools for generating effective viral capture panels, and for assessing coverage of target sequences by probe panel designs in silico. In this study, we validated ProbeTools by designing a panel of 3600 probes for subtyping the hypervariable haemagglutinin (HA) and neuraminidase (NA) genome segments of avian-origin influenza A viruses (AIVs). Using in silico assessment of AIV reference sequences and in vitro capture on egg-cultured viral isolates, we demonstrated effective performance by our custom AIV panel and ProbeTools’ suitability for challenging viral probe design applications. Results Based on ProbeTool’s in silico analysis, our panel provided broadly inclusive coverage of 14,772 HA and 11,967 NA reference sequences. For each reference sequence, we calculated the percentage of nucleotide positions covered by our panel in silico; 90% of HA and NA references sequences had at least 90.8 and 95.1% of their nucleotide positions covered respectively. We also observed effective in vitro capture on a representative collection of 23 egg-cultured AIVs that included isolates from wild birds, poultry, and humans and representatives from all HA and NA subtypes. Forty-two of forty-six HA and NA segments had over 98.3% of their nucleotide positions significantly enriched by our custom panel. These in vitro results were further used to validate ProbeTools’ in silico coverage assessment algorithm; 89.2% of in silico predictions were concordant with in vitro results. Conclusions ProbeTools generated an effective panel for subtyping AIVs that can be deployed for genomic surveillance, outbreak prevention, and pandemic preparedness. Effective probe design against hypervariable AIV targets also validated ProbeTools’ design and coverage assessment algorithms, demonstrating their suitability for other challenging viral capture applications. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08790-4.
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Affiliation(s)
- Kevin S Kuchinski
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada. .,, Vancouver, Canada.
| | - Jun Duan
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Chelsea Himsworth
- Animal Health Centre, British Columbia Ministry of Agriculture, Food, and Fisheries, Abbotsford, British Columbia, Canada.,School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - William Hsiao
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Natalie A Prystajecky
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.,Public Health Laboratory, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
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26
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Metsky HC, Welch NL, Pillai PP, Haradhvala NJ, Rumker L, Mantena S, Zhang YB, Yang DK, Ackerman CM, Weller J, Blainey PC, Myhrvold C, Mitzenmacher M, Sabeti PC. Designing sensitive viral diagnostics with machine learning. Nat Biotechnol 2022; 40:1123-1131. [PMID: 35241837 PMCID: PMC9287178 DOI: 10.1038/s41587-022-01213-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 01/07/2022] [Indexed: 12/20/2022]
Abstract
Design of nucleic acid-based viral diagnostics typically follows heuristic rules and, to contend with viral variation, focuses on a genome's conserved regions. A design process could, instead, directly optimize diagnostic effectiveness using a learned model of sensitivity for targets and their variants. Toward that goal, we screen 19,209 diagnostic-target pairs, concentrated on CRISPR-based diagnostics, and train a deep neural network to accurately predict diagnostic readout. We join this model with combinatorial optimization to maximize sensitivity over the full spectrum of a virus's genomic variation. We introduce Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT), a system for automated design, and use it to design diagnostics for 1,933 vertebrate-infecting viral species within 2 hours for most species and within 24 hours for all but three. We experimentally show that ADAPT's designs are sensitive and specific to the lineage level and permit lower limits of detection, across a virus's variation, than the outputs of standard design techniques. Our strategy could facilitate a proactive resource of assays for detecting pathogens.
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Affiliation(s)
- Hayden C Metsky
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA.
| | - Nicole L Welch
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Virology Program, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA
| | | | - Nicholas J Haradhvala
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Biophysics Program, Harvard Medical School, Boston, MA, USA
| | - Laurie Rumker
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Bioinformatics and Integrative Genomics Program, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Sreekar Mantena
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Yibin B Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - David K Yang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cheri M Ackerman
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
| | | | - Paul C Blainey
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Engineering, MIT, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research at MIT, Cambridge, MA, USA
| | - Cameron Myhrvold
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Michael Mitzenmacher
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Pardis C Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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27
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Alanko JN, Slizovskiy IB, Lokshtanov D, Gagie T, Noyes NR, Boucher C. Syotti: scalable bait design for DNA enrichment. Bioinformatics 2022; 38:i177-i184. [PMID: 35758776 PMCID: PMC9235489 DOI: 10.1093/bioinformatics/btac226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Bait enrichment is a protocol that is becoming increasingly ubiquitous as it has been shown to successfully amplify regions of interest in metagenomic samples. In this method, a set of synthetic probes ('baits') are designed, manufactured and applied to fragmented metagenomic DNA. The probes bind to the fragmented DNA and any unbound DNA is rinsed away, leaving the bound fragments to be amplified for sequencing. Metsky et al. demonstrated that bait-enrichment is capable of detecting a large number of human viral pathogens within metagenomic samples. RESULTS We formalize the problem of designing baits by defining the Minimum Bait Cover problem, show that the problem is NP-hard even under very restrictive assumptions, and design an efficient heuristic that takes advantage of succinct data structures. We refer to our method as Syotti. The running time of Syotti shows linear scaling in practice, running at least an order of magnitude faster than state-of-the-art methods, including the method of Metsky et al. At the same time, our method produces bait sets that are smaller than the ones produced by the competing methods, while also leaving fewer positions uncovered. Lastly, we show that Syotti requires only 25 min to design baits for a dataset comprised of 3 billion nucleotides from 1000 related bacterial substrains, whereas the method of Metsky et al. shows clearly super-linear running time and fails to process even a subset of 17% of the data in 72 h. AVAILABILITY AND IMPLEMENTATION https://github.com/jnalanko/syotti. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jarno N Alanko
- Department of Computer Science, University of Helsinki, Helsinki, Finland
- Faculty of Computer Science, Dalhousie University, Halifax, Canada
| | - Ilya B Slizovskiy
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
| | - Daniel Lokshtanov
- Department of Computer Science, University of California, Santa Barbara, CA, USA
| | - Travis Gagie
- Faculty of Computer Science, Dalhousie University, Halifax, Canada
| | - Noelle R Noyes
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, USA
| | - Christina Boucher
- Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA
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28
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Shi Y, Wang G, Lau HCH, Yu J. Metagenomic Sequencing for Microbial DNA in Human Samples: Emerging Technological Advances. Int J Mol Sci 2022; 23:ijms23042181. [PMID: 35216302 PMCID: PMC8877284 DOI: 10.3390/ijms23042181] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 02/06/2022] [Accepted: 02/11/2022] [Indexed: 02/04/2023] Open
Abstract
Whole genome metagenomic sequencing is a powerful platform enabling the simultaneous identification of all genes from entirely different kingdoms of organisms in a complex sample. This technology has revolutionised multiple areas from microbiome research to clinical diagnoses. However, one of the major challenges of a metagenomic study is the overwhelming non-microbial DNA present in most of the host-derived specimens, which can inundate the microbial signals and reduce the sensitivity of microorganism detection. Various host DNA depletion methods to facilitate metagenomic sequencing have been developed and have received considerable attention in this context. In this review, we present an overview of current host DNA depletion approaches along with explanations of their underlying principles, advantages and disadvantages. We also discuss their applications in laboratory microbiome research and clinical diagnoses and, finally, we envisage the direction of the further perfection of metagenomic sequencing in samples with overabundant host DNA.
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Affiliation(s)
| | | | | | - Jun Yu
- Correspondence: ; Tel.: +852-37636099; Fax:+852-21445330
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29
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Feng G, Zhang J, Zhang Y, Li C, Zhang D, Li Y, Zhou H, Li N, Xiao P. Metagenomic Analysis of Togaviridae in Mosquito Viromes Isolated From Yunnan Province in China Reveals Genes from Chikungunya and Ross River Viruses. Front Cell Infect Microbiol 2022; 12:849662. [PMID: 35223559 PMCID: PMC8878809 DOI: 10.3389/fcimb.2022.849662] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 01/24/2022] [Indexed: 12/12/2022] Open
Abstract
We collected 5,500 mosquitoes belonging to six species in three locations in China. Their viromes were tested using metagenomic sequencing and bioinformatic analysis. The affluent viral sequences that were detected and annotated belong to 22 viral taxonomic families. Then, PCR was performed to confirm the results, followed by phylogenetic analysis. Herein, part of mosquito virome was identified, including chikungunya virus (CHIKV), Getah virus (GETV), and Ross river virus (RRV). After metagenomic analysis, seven CHIKV sequences were verified by PCR amplification, among which CHIKV-China/YN2018-1 had the highest homology with the CHIKV isolated in Senegal, 1983, with a nucleotide (nt) identity of at least 81%, belonging to genotype West Africa viral genes. Five GETV sequences were identified, which had a high homology with the GETV sequences isolated from Equus caballus in Japan, 1978, with a (nt) identity of at least 97%. The newly isolated virus CHIKV-China/YN2018-1 became more infectious after passage of the BHK-21 cell line to the Vero cell line. The newly identified RRV gene had the highest homology with the 2006 RRV isolate from Australia, with a (nt) identity of at least 94%. In addition, numerous known and unknown viruses have also been detected in mosquitoes from Yunnan province, China, and propagation tests will be carried out.
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Affiliation(s)
- Guanrong Feng
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
| | - Jinyong Zhang
- Institute of Military Veterinary Medicine, Academy of Military Medical Sciences, Changchun, China
| | - Ying Zhang
- College of Veterinary Medicine, College of Animal Science, Jilin University, Changchun, China
| | - Chenghui Li
- College of Agriculture, Yanbian University, Yanji, China
| | - Duo Zhang
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
| | - Yiquan Li
- Academician Workstation of Jilin Province, Changchun University of Chinese Medicine, Changchun, China
| | | | - Nan Li
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
- *Correspondence: Nan Li, ; Pengpeng Xiao,
| | - Pengpeng Xiao
- Wenzhou Key Laboratory for Virology and Immunology, Institute of Virology, Wenzhou University, Wenzhou, China
- *Correspondence: Nan Li, ; Pengpeng Xiao,
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30
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Guzzo GL, Andrews JM, Weyrich LS. The Neglected Gut Microbiome: Fungi, Protozoa, and Bacteriophages in Inflammatory Bowel Disease. Inflamm Bowel Dis 2022; 28:1112-1122. [PMID: 35092426 PMCID: PMC9247841 DOI: 10.1093/ibd/izab343] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Indexed: 12/14/2022]
Abstract
The gut microbiome has been implicated in the pathogenesis of inflammatory bowel disease (IBD). Studies suggest that the IBD gut microbiome is less diverse than that of the unaffected population, a phenomenon often referred to as dysbiosis. However, these studies have heavily focused on bacteria, while other intestinal microorganisms-fungi, protozoa, and bacteriophages-have been neglected. Of the nonbacterial microbes that have been studied in relation to IBD, most are thought to be pathogens, although there is evidence that some of these species may instead be harmless commensals. In this review, we discuss the nonbacterial gut microbiome of IBD, highlighting the current biases, limitations, and outstanding questions that can be addressed with high-throughput DNA sequencing methods. Further, we highlight the importance of studying nonbacterial microorganisms alongside bacteria for a comprehensive view of the whole IBD biome and to provide a more precise definition of dysbiosis in patients. With the rise in popularity of microbiome-altering therapies for the treatment of IBD, such as fecal microbiota transplantation, it is important that we address these knowledge gaps to ensure safe and effective treatment of patients.
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Affiliation(s)
- Gina L Guzzo
- Address correspondence to: Gina L. Guzzo, The University of Adelaide, Adelaide, South Australia, Australia ()
| | - Jane M Andrews
- Inflammatory Bowel Disease Service, Department of Gastroenterology and Hepatology, Royal Adelaide Hospital and School of Medicine, Faculty of Health Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Laura S Weyrich
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia,Department of Anthropology and Huck Institutes of the Life Sciences, Pennsylvania State University, State College, PA, USA
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31
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Mazur FG, Morinisi LM, Martins JO, Guerra PPB, Freire CCM. Exploring Virome Diversity in Public Data in South America as an Approach for Detecting Viral Sources From Potentially Emerging Viruses. Front Genet 2022; 12:722857. [PMID: 35126446 PMCID: PMC8814814 DOI: 10.3389/fgene.2021.722857] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 11/29/2021] [Indexed: 11/13/2022] Open
Abstract
The South American continent presents a great diversity of biomes, whose ecosystems are constantly threatened by the expansion of human activity. The emergence and re-emergence of viral populations with impact on the human population and ecosystem have shown increases in the last decades. In deference to the growing accumulation of genomic data, we explore the potential of South American-related public databases to detect signals that contribute to virosphere research. Therefore, our study aims to investigate public databases with emphasis on the surveillance of viruses with medical and ecological relevance. Herein, we profiled 120 "sequence read archives" metagenomes from 19 independent projects from the last decade. In a coarse view, our analyses identified only 0.38% of the total number of sequences from viruses, showing a higher proportion of RNA viruses. The metagenomes with the most important viral sequences in the analyzed environmental models were 1) aquatic samples from the Amazon River, 2) sewage from Brasilia, and 3) soil from the state of São Paulo, while the models of animal transmission were detected in mosquitoes from Rio Janeiro and Bats from Amazonia. Also, the classification of viral signals into operational taxonomic units (OTUs) (family) allowed us to infer from metadata a probable host range in the virome detected in each sample analyzed. Further, several motifs and viral sequences are related to specific viruses with emergence potential from Togaviridae, Arenaviridae, and Flaviviridae families. In this context, the exploration of public databases allowed us to evaluate the scope and informative capacity of sequences from third-party public databases and to detect signals related to viruses of clinical or environmental importance, which allowed us to infer traits associated with probable transmission routes or signals of ecological disequilibrium. The evaluation of our results showed that in most cases the size and type of the reference database, the percentage of guanine-cytosine (GC), and the length of the query sequences greatly influence the taxonomic classification of the sequences. In sum, our findings describe how the exploration of public genomic data can be exploited as an approach for epidemiological surveillance and the understanding of the virosphere.
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Affiliation(s)
| | | | | | | | - Caio C. M. Freire
- Department Genetics and Evolution, UFSCar—Federal University of São Carlos, São Carlos, Brazil
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32
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Dickson ZW, Hackenberger D, Kuch M, Marzok A, Banerjee A, Rossi L, Klowak JA, Fox-Robichaud A, Mossmann K, Miller MS, Surette MG, Golding GB, Poinar H. Probe design for simultaneous, targeted capture of diverse metagenomic targets. CELL REPORTS METHODS 2021; 1:100069. [PMID: 35474894 PMCID: PMC9017208 DOI: 10.1016/j.crmeth.2021.100069] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/10/2021] [Accepted: 08/05/2021] [Indexed: 11/20/2022]
Abstract
The compounding challenges of low signal, high background, and uncertain targets plague many metagenomic sequencing efforts. One solution has been DNA capture, wherein probes are designed to hybridize with target sequences, enriching them in relation to their background. However, balancing probe depth with breadth of capture is challenging for diverse targets. To find this balance, we have developed the HUBDesign pipeline, which makes use of sequence homology to design probes at multiple taxonomic levels. This creates an efficient probe set capable of simultaneously and specifically capturing known and related sequences. We validated HUBDesign by generating probe sets targeting the breadth of coronavirus diversity, as well as a suite of bacterial pathogens often underlying sepsis. In separate experiments demonstrating significant, simultaneous enrichment, we captured SARS-CoV-2 and HCoV-NL63 in a human RNA background and seven bacterial strains in human blood. HUBDesign (https://github.com/zacherydickson/HUBDesign) has broad applicability wherever there are multiple organisms of interest.
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Affiliation(s)
- Zachery W. Dickson
- Department of Biology, McMaster University, Hamilton, ON L8S 4K1, Canada
| | - Dirk Hackenberger
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
| | - Melanie Kuch
- McMaster aDNA Center, Department of Anthropology, McMaster University, Hamilton, ON L8S 4L9, Canada
| | - Art Marzok
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
- McMaster Immunology Research Center, McMaster University, Hamilton, ON L8S 4K1, Canada
| | - Arinjay Banerjee
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
- McMaster Immunology Research Center, McMaster University, Hamilton, ON L8S 4K1, Canada
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S 4K1, Canada
- Vaccine and Infectious Disease Organization, Department of Veterinary Microbiology, University of Saskatchewan, Saskatoon, SK S7N 5E3, Canada
| | - Laura Rossi
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
| | | | | | - Karen Mossmann
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
- McMaster Immunology Research Center, McMaster University, Hamilton, ON L8S 4K1, Canada
- Department of Medicine, McMaster University, Hamilton, ON L8S 4K1, Canada
| | - Matthew S. Miller
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
- McMaster Immunology Research Center, McMaster University, Hamilton, ON L8S 4K1, Canada
| | - Michael G. Surette
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
- Department of Medicine, McMaster University, Hamilton, ON L8S 4K1, Canada
| | | | - Hendrik Poinar
- Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON L8S 4K1, Canada
- Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
- McMaster aDNA Center, Department of Anthropology, McMaster University, Hamilton, ON L8S 4L9, Canada
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33
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Gan M, Wu B, Yan G, Li G, Sun L, Lu G, Zhou W. Combined nanopore adaptive sequencing and enzyme-based host depletion efficiently enriched microbial sequences and identified missing respiratory pathogens. BMC Genomics 2021; 22:732. [PMID: 34627155 PMCID: PMC8501638 DOI: 10.1186/s12864-021-08023-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 09/17/2021] [Indexed: 12/12/2022] Open
Abstract
Background Enzyme-based host depletion significantly improves the sensitivity of clinical metagenomics. Recent studies found that real-time adaptive sequencing of DNA molecules was achieved using a nanopore sequencing machine, which enabled effective enrichment of microbial sequences. However, few studies have compared the enzyme-based host depletion and nanopore adaptive sequencing for microbial enrichment efficiency. Results To compare the host depletion and microbial enrichment efficiency of enzyme-based and adaptive sequencing methods, the present study collected clinical samples from eight children with respiratory tract infections. The same respiratory samples were subjected to standard methods, adaptive sequencing methods, enzyme-based host depletion methods, and the combination of adaptive sequencing and enzyme-based host depletion methods. We compared the host depletion efficiency, microbial enrichment efficiency, and pathogenic microorganisms detected between the four methods. We found that adaptive sequencing, enzyme-based host depletion and the combined methods significantly enriched the microbial sequences and significantly increased the diversity of microorganisms (p value < 0.001 for each method compared to standard). The highest microbial enrichment efficiency was achieved using the combined method. Compared to the standard method, the combined method increased the microbial reads by a median of 113.41-fold (interquartile range 23.32–327.72, maximum 1812), and the number of genera by a median of 70-fold (interquartile range 56.75–86.75, maximum 164). The combined method detected 6 pathogens in 4 samples with a median read of 547, compared to 5 pathogens in 4 samples with a median read of 4 using the standard method. Conclusion The combined method is an effective, easy-to-run method for enriching microbial sequences in clinical metagenomics from sputum and bronchoalveolar lavage fluid samples and may improve the sensitivity of clinical metagenomics for other host-derived clinical samples. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08023-0.
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Affiliation(s)
- Mingyu Gan
- Center for Molecular Medicine, Pediatric Research Institute, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China
| | - Bingbing Wu
- Center for Molecular Medicine, Pediatric Research Institute, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China
| | - Gangfeng Yan
- Department of Pediatric Emergency and Critical Care Medicine, Children's Hospital of Fudan University, National Children's Medical Center, 399 Wanyuan Road, Shanghai, 201102, China
| | - Gang Li
- Center for Molecular Medicine, Pediatric Research Institute, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China
| | - Li Sun
- Department of Rheumatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China
| | - Guoping Lu
- Department of Pediatric Emergency and Critical Care Medicine, Children's Hospital of Fudan University, National Children's Medical Center, 399 Wanyuan Road, Shanghai, 201102, China.
| | - Wenhao Zhou
- Center for Molecular Medicine, Pediatric Research Institute, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China. .,Department of Neonates, Key Laboratory of Neonatal Diseases, Ministry of Health, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
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34
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Beaudry MS, Thomas JC, Baptista RP, Sullivan AH, Norfolk W, Devault A, Enk J, Kieran TJ, Rhodes OE, Perry-Dow KA, Rose LJ, Bayona-Vásquez NJ, Oladeinde A, Lipp EK, Sanchez S, Glenn TC. Escaping the fate of Sisyphus: assessing resistome hybridization baits for antimicrobial resistance gene capture. Environ Microbiol 2021; 23:7523-7537. [PMID: 34519156 DOI: 10.1111/1462-2920.15767] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 09/03/2021] [Accepted: 09/07/2021] [Indexed: 11/30/2022]
Abstract
Finding, characterizing and monitoring reservoirs for antimicrobial resistance (AMR) is vital to protecting public health. Hybridization capture baits are an accurate, sensitive and cost-effective technique used to enrich and characterize DNA sequences of interest, including antimicrobial resistance genes (ARGs), in complex environmental samples. We demonstrate the continued utility of a set of 19 933 hybridization capture baits designed from the Comprehensive Antibiotic Resistance Database (CARD)v1.1.2 and Pathogenicity Island Database (PAIDB)v2.0, targeting 3565 unique nucleotide sequences that confer resistance. We demonstrate the efficiency of our bait set on a custom-made resistance mock community and complex environmental samples to increase the proportion of on-target reads as much as >200-fold. However, keeping pace with newly discovered ARGs poses a challenge when studying AMR, because novel ARGs are continually being identified and would not be included in bait sets designed prior to discovery. We provide imperative information on how our bait set performs against CARDv3.3.1, as well as a generalizable approach for deciding when and how to update hybridization capture bait sets. This research encapsulates the full life cycle of baits for hybridization capture of the resistome from design and validation (both in silico and in vitro) to utilization and forecasting updates and retirement.
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Affiliation(s)
- Megan S Beaudry
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Jesse C Thomas
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, 29808, USA
| | - Rodrigo P Baptista
- Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA.,Center for Tropical and Emerging Diseases, University of Georgia, Athens, GA, 30602, USA
| | - Amanda H Sullivan
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA
| | - William Norfolk
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Alison Devault
- Daicel Arbor Biosciences, 5840 Interface Dr., Suite 101, Ann Arbor, MI, 48103, USA
| | - Jacob Enk
- Daicel Arbor Biosciences, 5840 Interface Dr., Suite 101, Ann Arbor, MI, 48103, USA
| | - Troy J Kieran
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Olin E Rhodes
- Savannah River Ecology Laboratory, University of Georgia, Aiken, SC, 29808, USA.,Odum School of Ecology, University of Georgia, Athens, GA, 30602, USA
| | - K Allison Perry-Dow
- Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Laura J Rose
- Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Natalia J Bayona-Vásquez
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA.,Division of Natural Science and Mathematics, Oxford College, Emory University, Oxford, GA, 30054, USA
| | - Adelumola Oladeinde
- Bacterial Epidemiology and Antimicrobial Resistance Research Unit, U.S. National Poultry Research Center, USDA Agricultural Research Service, Athens, GA, 30605, USA
| | - Erin K Lipp
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA
| | - Susan Sanchez
- Department of Infectious Diseases, University of Georgia, Athens, GA, 30602, USA
| | - Travis C Glenn
- Department of Environmental Health Science, University of Georgia, Athens, GA, 30602, USA.,Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA
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35
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Piantadosi A, Mukerji SS, Ye S, Leone MJ, Freimark LM, Park D, Adams G, Lemieux J, Kanjilal S, Solomon IH, Ahmed AA, Goldstein R, Ganesh V, Ostrem B, Cummins KC, Thon JM, Kinsella CM, Rosenberg E, Frosch MP, Goldberg MB, Cho TA, Sabeti P. Enhanced Virus Detection and Metagenomic Sequencing in Patients with Meningitis and Encephalitis. mBio 2021; 12:e0114321. [PMID: 34465023 PMCID: PMC8406231 DOI: 10.1128/mbio.01143-21] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/02/2021] [Indexed: 01/21/2023] Open
Abstract
Meningitis and encephalitis are leading causes of central nervous system (CNS) disease and often result in severe neurological compromise or death. Traditional diagnostic workflows largely rely on pathogen-specific tests, sometimes over days to weeks, whereas metagenomic next-generation sequencing (mNGS) profiles all nucleic acid in a sample. In this single-center, prospective study, 68 hospitalized patients with known (n = 44) or suspected (n = 24) CNS infections underwent mNGS from RNA and DNA to identify potential pathogens and also targeted sequencing of viruses using hybrid capture. Using a computational metagenomic classification pipeline based on KrakenUniq and BLAST, we detected pathogen nucleic acid in cerebrospinal fluid (CSF) from 22 subjects, 3 of whom had no clinical diagnosis by routine workup. Among subjects diagnosed with infection by serology and/or peripheral samples, we demonstrated the utility of mNGS to detect pathogen nucleic acid in CSF, importantly for the Ixodes scapularis tick-borne pathogens Powassan virus, Borrelia burgdorferi, and Anaplasma phagocytophilum. We also evaluated two methods to enhance the detection of viral nucleic acid, hybrid capture and methylated DNA depletion. Hybrid capture nearly universally increased viral read recovery. Although results for methylated DNA depletion were mixed, it allowed the detection of varicella-zoster virus DNA in two samples that were negative by standard mNGS. Overall, mNGS is a promising approach that can test for multiple pathogens simultaneously, with efficacy similar to that of pathogen-specific tests, and can uncover geographically relevant infectious CNS disease, such as tick-borne infections in New England. With further laboratory and computational enhancements, mNGS may become a mainstay of workup for encephalitis and meningitis. IMPORTANCE Meningitis and encephalitis are leading global causes of central nervous system (CNS) disability and mortality. Current diagnostic workflows remain inefficient, requiring costly pathogen-specific assays and sometimes invasive surgical procedures. Despite intensive diagnostic efforts, 40 to 60% of people with meningitis or encephalitis have no clear cause of CNS disease identified. As diagnostic uncertainty often leads to costly inappropriate therapies, the need for novel pathogen detection methods is paramount. Metagenomic next-generation sequencing (mNGS) offers the unique opportunity to circumvent these challenges using unbiased laboratory and computational methods. Here, we performed comprehensive mNGS from 68 prospectively enrolled patients with known (n = 44) or suspected (n = 24) CNS viral infection from a single center in New England and evaluated enhanced methods to improve the detection of CNS pathogens, including those not traditionally identified in the CNS by nucleic acid detection. Overall, our work helps elucidate how mNGS can become integrated into the diagnostic toolkit for CNS infections.
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Affiliation(s)
- Anne Piantadosi
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
- Emory University School of Medicine, Atlanta, Georgia, USA
| | - Shibani S. Mukerji
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Simon Ye
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Harvard-MIT Program of Health Sciences and Technology, Cambridge, Massachusetts, USA
| | - Michael J. Leone
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Lisa M. Freimark
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Daniel Park
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Gordon Adams
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jacob Lemieux
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Sanjat Kanjilal
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Isaac H. Solomon
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Pathology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Asim A. Ahmed
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Pediatrics, Harvard Medical School, Children’s Hospital, Boston, Massachusetts, USA
| | - Robert Goldstein
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Vijay Ganesh
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Bridget Ostrem
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Kaelyn C. Cummins
- Division of Infectious Diseases, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Jesse M. Thon
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Cormac M. Kinsella
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Eric Rosenberg
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Matthew P. Frosch
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Marcia B. Goldberg
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Tracey A. Cho
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- University of Iowa, Department of Neurology, Iowa City, Iowa, USA
| | - Pardis Sabeti
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
- Department of Immunology and Infectious Disease, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
- Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
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36
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Channumsin M, Ciosi M, Masiga D, Auty H, Turner CM, Kilbride E, Mable BK. Blood meal analysis of tsetse flies ( Glossina pallidipes: Glossinidae) reveals higher host fidelity on wild compared with domestic hosts. Wellcome Open Res 2021; 6:213. [PMID: 34703903 PMCID: PMC8513123 DOI: 10.12688/wellcomeopenres.16978.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/12/2021] [Indexed: 11/20/2022] Open
Abstract
Background: Changes in climate and land use can alter risk of transmission of parasites between domestic hosts and wildlife, particularly when mediated by vectors that can travel between populations. Here we focused on tsetse flies (genus Glossina), the cyclical vectors for both Human African Trypanosomiasis (HAT) and Animal African Trypanosomiasis (AAT). The aims of this study were to investigate three issues related to G. palldipes from Kenya: 1) the diversity of vertebrate hosts that flies fed on; 2) whether host feeding patterns varied in relation to type of hosts, tsetse feeding behaviour, site or tsetse age and sex; and 3) if there was a relationship between trypanosome detection and host feeding behaviours or host types. Methods: Sources of blood meals of Glossina pallidipes were identified by sequencing of the mitochondrial cytochrome b gene and analyzed in relationship with previously determined trypanosome detection in the same flies. Results: In an area dominated by wildlife but with seasonal presence of livestock (Nguruman), 98% of tsetse fed on single wild host species, whereas in an area including a mixture of resident domesticated animals, humans and wildlife (Shimba Hills), 52% of flies fed on more than one host species. Multiple Correspondence Analysis revealed strong correlations between feeding pattern, host type and site but these were resolved along a different dimension than trypanosome status, sex and age of the flies. Conclusions: Our results suggest that individual G. pallidipes in interface areas may show higher feeding success on wild hosts when available but often feed on both wild and domesticated hosts. This illustrates the importance of G. pallidipes as a vector connecting the sylvatic and domestic cycles of African trypanosomes.
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Affiliation(s)
- Manun Channumsin
- Faculty of Veterinary Medicine, Rajamangala University of Technology Tawan-Ok, Chonburi, 20230, Thailand
| | - Marc Ciosi
- Institute of Molecular, Cell and Systems Biology, University of glasgow, University Place, Glasgow, G12 8QQ, UK
| | - Dan Masiga
- International Centre of Insect Physiology and Ecology (ICIPE), Nairobi, P.O. Box 30772, 00100, Kenya
| | - Harriet Auty
- Institute of Biodiversity, Animal Health and Comparative Medicine (BAHCM), University of Glasgow, University Place, Glasgow, G12 8QQ, UK
| | - C. Michael Turner
- Institute of Infection Immunity and Inflammation (III), University of Glasgow, University Place, Glasgow, G12 8QQ, UK
| | - Elizabeth Kilbride
- Institute of Biodiversity, Animal Health and Comparative Medicine (BAHCM), University of Glasgow, University Place, Glasgow, G12 8QQ, UK
| | - Barbara K. Mable
- Institute of Biodiversity, Animal Health and Comparative Medicine (BAHCM), University of Glasgow, University Place, Glasgow, G12 8QQ, UK
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37
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Rachtman E, Bafna V, Mirarab S. CONSULT: accurate contamination removal using locality-sensitive hashing. NAR Genom Bioinform 2021; 3:lqab071. [PMID: 34377979 PMCID: PMC8340999 DOI: 10.1093/nargab/lqab071] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 06/30/2021] [Accepted: 07/19/2021] [Indexed: 12/27/2022] Open
Abstract
A fundamental question appears in many bioinformatics applications: Does a sequencing read belong to a large dataset of genomes from some broad taxonomic group, even when the closest match in the set is evolutionarily divergent from the query? For example, low-coverage genome sequencing (skimming) projects either assemble the organelle genome or compute genomic distances directly from unassembled reads. Using unassembled reads needs contamination detection because samples often include reads from unintended groups of species. Similarly, assembling the organelle genome needs distinguishing organelle and nuclear reads. While k-mer-based methods have shown promise in read-matching, prior studies have shown that existing methods are insufficiently sensitive for contamination detection. Here, we introduce a new read-matching tool called CONSULT that tests whether k-mers from a query fall within a user-specified distance of the reference dataset using locality-sensitive hashing. Taking advantage of large memory machines available nowadays, CONSULT libraries accommodate tens of thousands of microbial species. Our results show that CONSULT has higher true-positive and lower false-positive rates of contamination detection than leading methods such as Kraken-II and improves distance calculation from genome skims. We also demonstrate that CONSULT can distinguish organelle reads from nuclear reads, leading to dramatic improvements in skim-based mitochondrial assemblies.
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Affiliation(s)
- Eleonora Rachtman
- Bioinformatics and Systems Biology Graduate Program, UC San Diego, CA 92093, USA
| | - Vineet Bafna
- Department of Computer Science and Engineering, UC San Diego, CA 92093, USA
| | - Siavash Mirarab
- Department of Electrical and Computer Engineering, UC San Diego, CA 92093, USA
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38
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O'Neal AJ, Hanson MR. The Enterovirus Theory of Disease Etiology in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Critical Review. Front Med (Lausanne) 2021; 8:688486. [PMID: 34222292 PMCID: PMC8253308 DOI: 10.3389/fmed.2021.688486] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 05/26/2021] [Indexed: 02/06/2023] Open
Abstract
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system disease whose etiological basis has not been established. Enteroviruses (EVs) as a cause of ME/CFS have sometimes been proposed, as they are known agents of acute respiratory and gastrointestinal infections that may persist in secondary infection sites, including the central nervous system, muscle, and heart. To date, the body of research that has investigated enterovirus infections in relation to ME/CFS supports an increased prevalence of chronic or persistent enteroviral infections in ME/CFS patient cohorts than in healthy individuals. Nevertheless, inconsistent results have fueled a decline in related studies over the past two decades. This review covers the aspects of ME/CFS pathophysiology that are consistent with a chronic enterovirus infection and critically reviews methodologies and approaches used in past EV-related ME/CFS studies. We describe the prior sample types that were interrogated, the methods used and the limitations to the approaches that were chosen. We conclude that there is considerable evidence that prior outbreaks of ME/CFS were caused by one or more enterovirus groups. Furthermore, we find that the methods used in prior studies were inadequate to rule out the presence of chronic enteroviral infections in individuals with ME/CFS. Given the possibility that such infections could be contributing to morbidity and preventing recovery, further studies of appropriate biological samples with the latest molecular methods are urgently needed.
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Affiliation(s)
- Adam J O'Neal
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, United States
| | - Maureen R Hanson
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY, United States
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39
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Development of a capture sequencing assay for enhanced detection and genotyping of tick-borne pathogens. Sci Rep 2021; 11:12384. [PMID: 34117323 PMCID: PMC8196166 DOI: 10.1038/s41598-021-91956-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 05/31/2021] [Indexed: 02/05/2023] Open
Abstract
Inadequate sensitivity has been the primary limitation for implementing high-throughput sequencing for studies of tick-borne agents. Here we describe the development of TBDCapSeq, a sequencing assay that uses hybridization capture probes that cover the complete genomes of the eleven most common tick-borne agents found in the United States. The probes are used for solution-based capture and enrichment of pathogen nucleic acid followed by high-throughput sequencing. We evaluated the performance of TBDCapSeq to surveil samples that included human whole blood, mouse tissues, and field-collected ticks. For Borrelia burgdorferi and Babesia microti, the sensitivity of TBDCapSeq was comparable and occasionally exceeded the performance of agent-specific quantitative PCR and resulted in 25 to > 10,000-fold increase in pathogen reads when compared to standard unbiased sequencing. TBDCapSeq also enabled genome analyses directly within vertebrate and tick hosts. The implementation of TBDCapSeq could have major impact in studies of tick-borne pathogens by improving detection and facilitating genomic research that was previously unachievable with standard sequencing approaches.
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40
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Highly multiplexed oligonucleotide probe-ligation testing enables efficient extraction-free SARS-CoV-2 detection and viral genotyping. Mod Pathol 2021; 34:1093-1103. [PMID: 33536572 PMCID: PMC7856856 DOI: 10.1038/s41379-020-00730-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 11/25/2020] [Accepted: 11/25/2020] [Indexed: 02/04/2023]
Abstract
There is an urgent and unprecedented need for sensitive and high-throughput molecular diagnostic tests to combat the SARS-CoV-2 pandemic. Here we present a generalized version of the RNA-mediated oligonucleotide Annealing Selection and Ligation with next generation DNA sequencing (RASL-seq) assay, called "capture RASL-seq" (cRASL-seq), which enables highly sensitive (down to ~1-100 pfu/ml or cfu/ml) and highly multiplexed (up to ~10,000 target sequences) detection of pathogens. Importantly, cRASL-seq analysis of COVID-19 patient nasopharyngeal (NP) swab specimens does not involve nucleic acid purification or reverse transcription, steps that have introduced supply bottlenecks into standard assay workflows. Our simplified protocol additionally enables the direct and efficient genotyping of selected, informative SARS-CoV-2 polymorphisms across the entire genome, which can be used for enhanced characterization of transmission chains at population scale and detection of viral clades with higher or lower virulence. Given its extremely low per-sample cost, simple and automatable protocol and analytics, probe panel modularity, and massive scalability, we propose that cRASL-seq testing is a powerful new technology with the potential to help mitigate the current pandemic and prevent similar public health crises.
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41
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Amit S, Barua L, Kafy AA. Countering violent extremism using social media and preventing implementable strategies for Bangladesh. Heliyon 2021; 7:e07121. [PMID: 34124401 PMCID: PMC8173274 DOI: 10.1016/j.heliyon.2021.e07121] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/06/2021] [Accepted: 05/18/2021] [Indexed: 01/11/2023] Open
Abstract
Globally, more than 85% of youth use social media daily in the medium of Facebook, Youtube, Twitter, etc., which is more than 70% for Bangladesh. The young population of Bangladesh is rapidly embracing social media through the internet and afflicted with the malaise of countering violent extremism (CVE), often through Facebook. Given the increasing connectedness that the internet and social media offer, it is crucial that the fight against CVE shift to the digital space. Extremists are increasingly adopting novel ways and means based on technology to draw unsuspecting youth to their cause. It is essential to establish effective implementable strategies to stop the CVE activities using social media in Bangladesh. This study aims to identify existing initiatives globally in the space of disruptive online technologies that have yielded some success in preventing CVE. Various publications such as journal and news articles, TV news, and blogs have been used as data sources for this study. Also, fifteen expert interviews have been conducted to identify the most effective strategies for CVE in Bangladesh. Through the content analysis, the study highlights successful efforts and explores technology-based initiatives that can be deployed in Bangladesh to minimize the impact of VE activities through online technology. Finally, recommendations for strategies to restrict VE activities through technologies have been suggested that can be potentially implemented by the Bangladesh government by coordinating with international donor agencies and CVE practitioners. The research output recommends that Bangladesh and other less developed countries can concurrently deal with CVE by successfully using cutting-edge online/digital technologies.
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Affiliation(s)
- Sajid Amit
- Center for Enterprise and Society, University of Liberal Arts Bangladesh (ULAB), Dhanmondi, Dhaka 1209, Bangladesh
| | - Lumbini Barua
- Center for Enterprise and Society, University of Liberal Arts Bangladesh (ULAB), Dhanmondi, Dhaka 1209, Bangladesh
| | - Abdulla-Al Kafy
- ICLEI South Asia, Rajshahi City Corporation, Rajshahi 6200, Bangladesh.,Department of Urban & Regional Planning, Rajshahi University of Engineering & Technology, Rajshahi 6203, Bangladesh
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42
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Frost JR, Schulz H, McLachlan E, Hiebert J, Severini A. An enrichment method for capturing mumps virus whole genome sequences directly from clinical specimens. J Virol Methods 2021; 294:114176. [PMID: 33957163 DOI: 10.1016/j.jviromet.2021.114176] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 04/16/2021] [Accepted: 04/24/2021] [Indexed: 10/21/2022]
Abstract
Recently there has been a significant increase in the number of mumps outbreaks occurring in highly vaccinated populations. These outbreaks are often due to a mumps genotype G virus, where sequencing of the SH gene does not reveal enough genetic diversity to sufficient to resolve outbreaks. This has elevated the need to be able to sequence complete mumps viruses from clinical samples without laborious methods. Here we describe a probe enrichment method that allows for whole genome sequencing of the mumps virus directly from clinical specimens. Using 136 clinical samples, we show this method allows for a significant increase in the percentage of viral sequencing reads, resulting in the capture of mumps genomes. This method will be an asset in investigating future mumps outbreaks.
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Affiliation(s)
- Jasmine Rae Frost
- Department of Medical Microbiology and Infectious Diseases, Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Helene Schulz
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Elizabeth McLachlan
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Joanne Hiebert
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Alberto Severini
- Department of Medical Microbiology and Infectious Diseases, Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada; National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada.
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43
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Liu YX, Qin Y, Chen T, Lu M, Qian X, Guo X, Bai Y. A practical guide to amplicon and metagenomic analysis of microbiome data. Protein Cell 2021; 12:315-330. [PMID: 32394199 PMCID: PMC8106563 DOI: 10.1007/s13238-020-00724-8] [Citation(s) in RCA: 326] [Impact Index Per Article: 108.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 04/10/2020] [Indexed: 12/22/2022] Open
Abstract
Advances in high-throughput sequencing (HTS) have fostered rapid developments in the field of microbiome research, and massive microbiome datasets are now being generated. However, the diversity of software tools and the complexity of analysis pipelines make it difficult to access this field. Here, we systematically summarize the advantages and limitations of microbiome methods. Then, we recommend specific pipelines for amplicon and metagenomic analyses, and describe commonly-used software and databases, to help researchers select the appropriate tools. Furthermore, we introduce statistical and visualization methods suitable for microbiome analysis, including alpha- and beta-diversity, taxonomic composition, difference comparisons, correlation, networks, machine learning, evolution, source tracing, and common visualization styles to help researchers make informed choices. Finally, a step-by-step reproducible analysis guide is introduced. We hope this review will allow researchers to carry out data analysis more effectively and to quickly select the appropriate tools in order to efficiently mine the biological significance behind the data.
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Affiliation(s)
- Yong-Xin Liu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
- CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing, 100049, China.
- CAS-JIC Centre of Excellence for Plant and Microbial Science, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yuan Qin
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing, 100049, China
- CAS-JIC Centre of Excellence for Plant and Microbial Science, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tong Chen
- National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Meiping Lu
- Department of Rheumatology Immunology & Allergy, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310053, China
| | - Xubo Qian
- Department of Rheumatology Immunology & Allergy, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, 310053, China
| | - Xiaoxuan Guo
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing, 100049, China
- CAS-JIC Centre of Excellence for Plant and Microbial Science, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yang Bai
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
- CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing, 100049, China.
- CAS-JIC Centre of Excellence for Plant and Microbial Science, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
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44
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Genome-Based Targeted Sequencing as a Reproducible Microbial Community Profiling Assay. mSphere 2021; 6:6/2/e01325-20. [PMID: 33827913 PMCID: PMC8546724 DOI: 10.1128/msphere.01325-20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Current sequencing-based methods for profiling microbial communities rely on marker gene (e.g., 16S rRNA) or metagenome shotgun sequencing (mWGS) analysis. We present an approach based on a single-primer extension reaction using a highly multiplexed oligonucleotide probe pool. This approach, termed MA-GenTA (microbial abundances from genome tagged analysis), enables quantitative, straightforward, cost-effective microbiome profiling that combines desirable features of both 16S rRNA and mWGS strategies. The use of multiple probes per target genome and rigorous probe design criteria enabled robust determination of relative abundance. To test the utility of the MA-GenTA assay, probes were designed for 830 genome sequences representing bacteria present in mouse stool specimens. Comparison of the MA-GenTA data with mWGS data demonstrated excellent correlation down to 0.01% relative abundance and a similar number of organisms detected per sample. Despite the incompleteness of the reference database, nonmetric multidimensional scaling (NMDS) clustering based on the Bray-Curtis dissimilarity metric of sample groups was consistent between MA-GenTA, mWGS, and 16S rRNA data sets. MA-GenTA represents a potentially useful new method for microbiome community profiling based on reference genomes. IMPORTANCE New methods for profiling the microbial communities can create new approaches to understanding the composition and function of those communities. In this study, we combined bacterial genome-specific probe design with a highly multiplexed single primer extension reaction as a new method to profile microbial communities, using stool from various mouse strains as a test case. This method, termed MA-GenTA, was benchmarked against 16S rRNA gene sequencing and metagenome sequencing methods and delivered similar relative abundance and clustering data. Since the probes were generated from reference genomes, MA-GenTA was also able to provide functional pathway data for the stool microbiome in the assayed samples. The method is more informative than 16S rRNA analysis while being less costly than metagenome shotgun sequencing.
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45
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Lagerborg KA, Normandin E, Bauer MR, Adams G, Figueroa K, Loreth C, Gladden-Young A, Shaw B, Pearlman L, Shenoy ES, Hooper D, Pierce VM, Zachary KC, Park DJ, MacInnis BL, Lemieux JE, Sabeti PC, Reilly SK, Siddle KJ. DNA spike-ins enable confident interpretation of SARS-CoV-2 genomic data from amplicon-based sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.03.16.435654. [PMID: 33758855 PMCID: PMC7987014 DOI: 10.1101/2021.03.16.435654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortium's amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.
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Affiliation(s)
- Kim A Lagerborg
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Harvard Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Erica Normandin
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Matthew R Bauer
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Harvard Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA 02115, USA
| | - Gordon Adams
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Katherine Figueroa
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Christine Loreth
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | | | - Bennett Shaw
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Leah Pearlman
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Erica S Shenoy
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - David Hooper
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Virginia M Pierce
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
- Pediatric Infectious Disease Unit, MassGeneral Hospital for Children, Boston, MA, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
| | - Kimon C Zachary
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Infection Control Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Daniel J Park
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
| | - Bronwyn L MacInnis
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA 02115, USA
| | - Jacob E Lemieux
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Pardis C Sabeti
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA 02115, USA
- Howard Hughes Medical Institute, 4000 Jones Bridge Rd, Chevy Chase, MD 20815, USA
| | - Steven K Reilly
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Katherine J Siddle
- Broad Institute of Harvard and MIT, 415 Main Street, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
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Delorey TM, Ziegler CGK, Heimberg G, Normand R, Yang Y, Segerstolpe A, Abbondanza D, Fleming SJ, Subramanian A, Montoro DT, Jagadeesh KA, Dey KK, Sen P, Slyper M, Pita-Juárez YH, Phillips D, Bloom-Ackerman Z, Barkas N, Ganna A, Gomez J, Normandin E, Naderi P, Popov YV, Raju SS, Niezen S, Tsai LTY, Siddle KJ, Sud M, Tran VM, Vellarikkal SK, Amir-Zilberstein L, Atri DS, Beechem J, Brook OR, Chen J, Divakar P, Dorceus P, Engreitz JM, Essene A, Fitzgerald DM, Fropf R, Gazal S, Gould J, Grzyb J, Harvey T, Hecht J, Hether T, Jane-Valbuena J, Leney-Greene M, Ma H, McCabe C, McLoughlin DE, Miller EM, Muus C, Niemi M, Padera R, Pan L, Pant D, Pe’er C, Pfiffner-Borges J, Pinto CJ, Plaisted J, Reeves J, Ross M, Rudy M, Rueckert EH, Siciliano M, Sturm A, Todres E, Waghray A, Warren S, Zhang S, Zollinger DR, Cosimi L, Gupta RM, Hacohen N, Hide W, Price AL, Rajagopal J, Tata PR, Riedel S, Szabo G, Tickle TL, Hung D, Sabeti PC, Novak R, Rogers R, Ingber DE, Jiang ZG, Juric D, Babadi M, Farhi SL, Stone JR, Vlachos IS, Solomon IH, Ashenberg O, Porter CB, Li B, Shalek AK, Villani AC, Rozenblatt-Rosen O, Regev A. A single-cell and spatial atlas of autopsy tissues reveals pathology and cellular targets of SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.02.25.430130. [PMID: 33655247 PMCID: PMC7924267 DOI: 10.1101/2021.02.25.430130] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The SARS-CoV-2 pandemic has caused over 1 million deaths globally, mostly due to acute lung injury and acute respiratory distress syndrome, or direct complications resulting in multiple-organ failures. Little is known about the host tissue immune and cellular responses associated with COVID-19 infection, symptoms, and lethality. To address this, we collected tissues from 11 organs during the clinical autopsy of 17 individuals who succumbed to COVID-19, resulting in a tissue bank of approximately 420 specimens. We generated comprehensive cellular maps capturing COVID-19 biology related to patients' demise through single-cell and single-nucleus RNA-Seq of lung, kidney, liver and heart tissues, and further contextualized our findings through spatial RNA profiling of distinct lung regions. We developed a computational framework that incorporates removal of ambient RNA and automated cell type annotation to facilitate comparison with other healthy and diseased tissue atlases. In the lung, we uncovered significantly altered transcriptional programs within the epithelial, immune, and stromal compartments and cell intrinsic changes in multiple cell types relative to lung tissue from healthy controls. We observed evidence of: alveolar type 2 (AT2) differentiation replacing depleted alveolar type 1 (AT1) lung epithelial cells, as previously seen in fibrosis; a concomitant increase in myofibroblasts reflective of defective tissue repair; and, putative TP63+ intrapulmonary basal-like progenitor (IPBLP) cells, similar to cells identified in H1N1 influenza, that may serve as an emergency cellular reserve for severely damaged alveoli. Together, these findings suggest the activation and failure of multiple avenues for regeneration of the epithelium in these terminal lungs. SARS-CoV-2 RNA reads were enriched in lung mononuclear phagocytic cells and endothelial cells, and these cells expressed distinct host response transcriptional programs. We corroborated the compositional and transcriptional changes in lung tissue through spatial analysis of RNA profiles in situ and distinguished unique tissue host responses between regions with and without viral RNA, and in COVID-19 donor tissues relative to healthy lung. Finally, we analyzed genetic regions implicated in COVID-19 GWAS with transcriptomic data to implicate specific cell types and genes associated with disease severity. Overall, our COVID-19 cell atlas is a foundational dataset to better understand the biological impact of SARS-CoV-2 infection across the human body and empowers the identification of new therapeutic interventions and prevention strategies.
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Affiliation(s)
- Toni M. Delorey
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Carly G. K. Ziegler
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Health Sciences & Technology, Harvard Medical School & Massachusetts Institute of Technology, Boston, MA 02115, USA
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
- Harvard Graduate Program in Biophysics, Harvard University, Cambridge, MA 02138, USA
| | - Graham Heimberg
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Rachelly Normand
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02115, USA
- Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yiming Yang
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Asa Segerstolpe
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Domenic Abbondanza
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Stephen J. Fleming
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ayshwarya Subramanian
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | | | - Karthik A. Jagadeesh
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Kushal K. Dey
- Department of Epidemiology, Harvard School of Public Health
| | - Pritha Sen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Michal Slyper
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Yered H. Pita-Juárez
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Devan Phillips
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Zohar Bloom-Ackerman
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nick Barkas
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, Helsinki, Finland
- Analytical & Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - James Gomez
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Erica Normandin
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Pourya Naderi
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
| | - Yury V. Popov
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Siddharth S. Raju
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Sebastian Niezen
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Linus T.-Y. Tsai
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA 02115
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Katherine J. Siddle
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Malika Sud
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Victoria M. Tran
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Shamsudheen K. Vellarikkal
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Liat Amir-Zilberstein
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Deepak S. Atri
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Olga R. Brook
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Jonathan Chen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Phylicia Dorceus
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Jesse M. Engreitz
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics and BASE Initiative, Stanford University School of Medicine
| | - Adam Essene
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA 02115
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Donna M. Fitzgerald
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Robin Fropf
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Steven Gazal
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Joshua Gould
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - John Grzyb
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
| | - Tyler Harvey
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Jonathan Hecht
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Tyler Hether
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Judit Jane-Valbuena
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | | | - Hui Ma
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Cristin McCabe
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Daniel E. McLoughlin
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Christoph Muus
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
| | - Mari Niemi
- Institute for Molecular Medicine Finland, Helsinki, Finland
| | - Robert Padera
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
- Harvard-MIT Division of Health Sciences and Technology, Cambridge MA
- Department of Pathology, Harvard Medical School, Boston, MA 02115, USA
| | - Liuliu Pan
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Deepti Pant
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA 02115
- Boston Nutrition and Obesity Research Center Functional Genomics and Bioinformatics Core Boston, MA 02115, USA
| | - Carmel Pe’er
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | | | - Christopher J. Pinto
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Jacob Plaisted
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
| | - Jason Reeves
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Marty Ross
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Melissa Rudy
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | | | - Alexander Sturm
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ellen Todres
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Avinash Waghray
- Harvard Stem Cell Institute, Cambridge, MA, USA
- Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Sarah Warren
- NanoString Technologies Inc., Seattle, WA 98109, USA
| | - Shuting Zhang
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Lisa Cosimi
- Infectious Diseases Division, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Rajat M. Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Divisions of Cardiovascular Medicine and Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Winston Hide
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Alkes L. Price
- Department of Epidemiology, Harvard School of Public Health
| | - Jayaraj Rajagopal
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Stefan Riedel
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Gyongyi Szabo
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
| | - Timothy L. Tickle
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Deborah Hung
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Department of Molecular Biology and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, USA
| | - Richard Novak
- Wyss Institute for Biologically Inspired Engineering, Harvard University
| | - Robert Rogers
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Massachusetts General Hospital, MA 02114, USA
| | - Donald E. Ingber
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138
- Wyss Institute for Biologically Inspired Engineering, Harvard University
- Vascular Biology Program and Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA USA
| | - Z. Gordon Jiang
- Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Beth Israel Deaconess Medical Center, MA 02115, USA
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Dejan Juric
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
- Massachusetts General Hospital Cancer Center, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Mehrtash Babadi
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Samouil L. Farhi
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - James R. Stone
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Ioannis S. Vlachos
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02115, USA
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
- Harvard Medical School Initiative for RNA Medicine, Boston, MA 02115, USA
- Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA 02115, USA
| | - Isaac H. Solomon
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA 02115
| | - Orr Ashenberg
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Caroline B.M. Porter
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
| | - Bo Li
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Alex K. Shalek
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Program in Health Sciences & Technology, Harvard Medical School & Massachusetts Institute of Technology, Boston, MA 02115, USA
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
- Harvard Graduate Program in Biophysics, Harvard University, Cambridge, MA 02138, USA
- Harvard Medical School, Boston, MA 02115, USA
- Harvard Stem Cell Institute, Cambridge, MA, USA
- Program in Computational & Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Program in Immunology, Harvard Medical School, Boston, MA 02115, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alexandra-Chloé Villani
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Center for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA, USA
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Current address: Genentech, 1 DNA Way, South San Francisco, CA, USA
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A streamlined clinical metagenomic sequencing protocol for rapid pathogen identification. Sci Rep 2021; 11:4405. [PMID: 33623127 PMCID: PMC7902651 DOI: 10.1038/s41598-021-83812-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 01/21/2021] [Indexed: 12/11/2022] Open
Abstract
Metagenomic next-generation sequencing (mNGS) holds promise as a diagnostic tool for unbiased pathogen identification and precision medicine. However, its medical utility depends largely on assay simplicity and reproducibility. In the current study, we aimed to develop a streamlined Illumina and Oxford Nanopore-based DNA/RNA library preparation protocol and rapid data analysis pipeline. The Illumina sequencing-based mNGS method was first developed and evaluated using a set of samples with known aetiology. Its sensitivity for RNA viruses (influenza A, H1N1) was < 6.4 × 102 EID50/mL, and a good correlation between viral loads and mapped reads was observed. Then, the rapid turnaround time of Nanopore sequencing was tested by sequencing influenza A virus and adenoviruses. Furthermore, 11 respiratory swabs or sputum samples pre-tested for a panel of pathogens were analysed, and the pathogens identified by Illumina sequencing showed 81.8% concordance with qPCR results. Additional sequencing of cerebrospinal fluid (CSF) samples from HIV-1-positive patients with meningitis/encephalitis detected HIV-1 RNA and Toxoplasma gondii sequences. In conclusion, we have developed a simplified protocol that realizes efficient metagenomic sequencing of a variety of clinical samples and pathogen identification in a clinically meaningful time frame.
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Fitzpatrick AH, Rupnik A, O'Shea H, Crispie F, Keaveney S, Cotter P. High Throughput Sequencing for the Detection and Characterization of RNA Viruses. Front Microbiol 2021; 12:621719. [PMID: 33692767 PMCID: PMC7938315 DOI: 10.3389/fmicb.2021.621719] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 01/20/2021] [Indexed: 12/12/2022] Open
Abstract
This review aims to assess and recommend approaches for targeted and agnostic High Throughput Sequencing of RNA viruses in a variety of sample matrices. HTS also referred to as deep sequencing, next generation sequencing and third generation sequencing; has much to offer to the field of environmental virology as its increased sequencing depth circumvents issues with cloning environmental isolates for Sanger sequencing. That said however, it is important to consider the challenges and biases that method choice can impart to sequencing results. Here, methodology choices from RNA extraction, reverse transcription to library preparation are compared based on their impact on the detection or characterization of RNA viruses.
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Affiliation(s)
- Amy H. Fitzpatrick
- Food Biosciences, Teagasc Food Research Centre, Fermoy, Ireland
- Shellfish Microbiology, Marine Institute, Oranmore, Ireland
- Biological Sciences, Munster Technological University, Cork, Ireland
| | | | - Helen O'Shea
- Biological Sciences, Munster Technological University, Cork, Ireland
| | - Fiona Crispie
- Food Biosciences, Teagasc Food Research Centre, Fermoy, Ireland
| | | | - Paul Cotter
- Food Biosciences, Teagasc Food Research Centre, Fermoy, Ireland
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Wylezich C, Calvelage S, Schlottau K, Ziegler U, Pohlmann A, Höper D, Beer M. Next-generation diagnostics: virus capture facilitates a sensitive viral diagnosis for epizootic and zoonotic pathogens including SARS-CoV-2. MICROBIOME 2021; 9:51. [PMID: 33610182 DOI: 10.1186/s40168-020-00973-z/figures/4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 12/07/2020] [Indexed: 05/18/2023]
Abstract
BACKGROUND The detection of pathogens in clinical and environmental samples using high-throughput sequencing (HTS) is often hampered by large amounts of background information, which is especially true for viruses with small genomes. Enormous sequencing depth can be necessary to compile sufficient information for identification of a certain pathogen. Generic HTS combining with in-solution capture enrichment can markedly increase the sensitivity for virus detection in complex diagnostic samples. METHODS A virus panel based on the principle of biotinylated RNA baits was developed for specific capture enrichment of epizootic and zoonotic viruses (VirBaits). The VirBaits set was supplemented by a SARS-CoV-2 predesigned bait set for testing recent SARS-CoV-2-positive samples. Libraries generated from complex samples were sequenced via generic HTS (without enrichment) and afterwards enriched with the VirBaits set. For validation, an internal proficiency test for emerging epizootic and zoonotic viruses (African swine fever virus, Ebolavirus, Marburgvirus, Nipah henipavirus, Rift Valley fever virus) was conducted. RESULTS The VirBaits set consists of 177,471 RNA baits (80-mer) based on about 18,800 complete viral genomes targeting 35 epizootic and zoonotic viruses. In all tested samples, viruses with both DNA and RNA genomes were clearly enriched ranging from about 10-fold to 10,000-fold for viruses including distantly related viruses with at least 72% overall identity to viruses represented in the bait set. Viruses showing a lower overall identity (38% and 46%) to them were not enriched but could nonetheless be detected based on capturing conserved genome regions. The internal proficiency test supports the improved virus detection using the combination of HTS plus targeted enrichment but also points to the risk of cross-contamination between samples. CONCLUSIONS The VirBaits approach showed a high diagnostic performance, also for distantly related viruses. The bait set is modular and expandable according to the favored diagnostics, health sector, or research question. The risk of cross-contamination needs to be taken into consideration. The application of the RNA-baits principle turned out to be user friendly, and even non-experts can easily use the VirBaits workflow. The rapid extension of the established VirBaits set adapted to actual outbreak events is possible as shown for SARS-CoV-2. Video abstract.
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Affiliation(s)
- Claudia Wylezich
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany.
| | - Sten Calvelage
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Kore Schlottau
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Ute Ziegler
- Institute of Novel and Emerging Infectious Diseases, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Anne Pohlmann
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Dirk Höper
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Martin Beer
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
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Wylezich C, Calvelage S, Schlottau K, Ziegler U, Pohlmann A, Höper D, Beer M. Next-generation diagnostics: virus capture facilitates a sensitive viral diagnosis for epizootic and zoonotic pathogens including SARS-CoV-2. MICROBIOME 2021; 9:51. [PMID: 33610182 PMCID: PMC7896545 DOI: 10.1186/s40168-020-00973-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 12/07/2020] [Indexed: 05/15/2023]
Abstract
BACKGROUND The detection of pathogens in clinical and environmental samples using high-throughput sequencing (HTS) is often hampered by large amounts of background information, which is especially true for viruses with small genomes. Enormous sequencing depth can be necessary to compile sufficient information for identification of a certain pathogen. Generic HTS combining with in-solution capture enrichment can markedly increase the sensitivity for virus detection in complex diagnostic samples. METHODS A virus panel based on the principle of biotinylated RNA baits was developed for specific capture enrichment of epizootic and zoonotic viruses (VirBaits). The VirBaits set was supplemented by a SARS-CoV-2 predesigned bait set for testing recent SARS-CoV-2-positive samples. Libraries generated from complex samples were sequenced via generic HTS (without enrichment) and afterwards enriched with the VirBaits set. For validation, an internal proficiency test for emerging epizootic and zoonotic viruses (African swine fever virus, Ebolavirus, Marburgvirus, Nipah henipavirus, Rift Valley fever virus) was conducted. RESULTS The VirBaits set consists of 177,471 RNA baits (80-mer) based on about 18,800 complete viral genomes targeting 35 epizootic and zoonotic viruses. In all tested samples, viruses with both DNA and RNA genomes were clearly enriched ranging from about 10-fold to 10,000-fold for viruses including distantly related viruses with at least 72% overall identity to viruses represented in the bait set. Viruses showing a lower overall identity (38% and 46%) to them were not enriched but could nonetheless be detected based on capturing conserved genome regions. The internal proficiency test supports the improved virus detection using the combination of HTS plus targeted enrichment but also points to the risk of cross-contamination between samples. CONCLUSIONS The VirBaits approach showed a high diagnostic performance, also for distantly related viruses. The bait set is modular and expandable according to the favored diagnostics, health sector, or research question. The risk of cross-contamination needs to be taken into consideration. The application of the RNA-baits principle turned out to be user friendly, and even non-experts can easily use the VirBaits workflow. The rapid extension of the established VirBaits set adapted to actual outbreak events is possible as shown for SARS-CoV-2. Video abstract.
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Affiliation(s)
- Claudia Wylezich
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany.
| | - Sten Calvelage
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Kore Schlottau
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Ute Ziegler
- Institute of Novel and Emerging Infectious Diseases, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Anne Pohlmann
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Dirk Höper
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
| | - Martin Beer
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health, Südufer 10, 17493, Greifswald-Insel Riems, Germany
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