Viral metagenomics

Last updated

Environmental Shotgun Sequencing (ESS)
(A) Sampling from habitat
(B) filtering particles, typically by size
(C) Lysis and DNA extraction
(D) cloning and library construction
(E) sequencing the clones
(F) sequence assembly into contigs and scaffolds Environmental shotgun sequencing.png
Environmental Shotgun Sequencing (ESS)
         (A) Sampling from habitat
         (B) filtering particles, typically by size
         (C) Lysis and DNA extraction
         (D) cloning and library construction
         (E) sequencing the clones
         (F) sequence assembly into contigs and scaffolds

Viral metagenomics uses metagenomic technologies to detect viral genomic material from diverse environmental and clinical samples. [1] [2] Viruses are the most abundant biological entity and are extremely diverse; however, only a small fraction of viruses have been sequenced and only an even smaller fraction have been isolated and cultured. [1] [3] Sequencing viruses can be challenging because viruses lack a universally conserved marker gene so gene-based approaches are limited. [3] [4] Metagenomics can be used to study and analyze unculturable viruses and has been an important tool in understanding viral diversity and abundance and in the discovery of novel viruses. [1] [5] [6] For example, metagenomics methods have been used to describe viruses associated with cancerous tumors and in terrestrial ecosystems. [7]

Contents

History

The traditional methods for discovering, characterizing, and assigning viral taxonomy to viruses were based on isolating the virus particle or its nucleic acid from samples. [8] The virus morphology could be visualized using electron microscopy but only if the virus could be isolated in high enough titer to be detected. The virus could be cultured in eukaryotic cell lines or bacteria but only if the appropriate host cell type was known and the nucleic acid of the virus would be detected using PCR but only if a consensus primer was known. [8]

Metagenomics requires no prior knowledge of the viral genome as it does not require a universal marker gene, a primer or probe design. [9] Because this method uses prediction tools to detect viral content of a sample, it can be used to identify new virus species or divergent members of known species.

The earliest metagenomic studies of viruses were carried out on ocean samples in 2002. The sequences that were matched to referenced sequences were predominantly double-stranded DNA bacteriophages and double-stranded algal viruses. [10]

In 2016 the International Committee on Taxonomy of Viruses (ICTV) officially recognized that viral genomes assembled from metagenomic data can be classified using the same procedures for viruses isolated via classical virology approaches. [11]

Challenges

Viral dark matter

In the 2002 metagenomics study the researchers found that 65% of the sequences of DNA and RNA viruses had no matches in the reference databases. [10] This phenomenon of unmatched viral sequences in sequence reference databases is prevalent in viral metagenomics studies and is referred to as “viral dark matter". [3] [8] It is predominantly caused by the lack of complete viral genome sequences of diverse samples in reference databases and the rapid rate of viral evolution. [3] [8]

Virus nucleic acid type diversity

Adding to these challenges, there are seven classes of viruses based on the Baltimore classification system which groups viruses based on their genomic structure and their manner of transcription: there are double-stranded DNA viruses, single-stranded DNA viruses, double-stranded RNA viruses, and single-stranded RNA virus. [12] Single-stranded RNA can be positive or negative sense. These different nucleic acids types need different sequencing approaches and there is no universal gene marker that is conserved for all virus types. [3] [4] Gene-based approaches can only target specific groups of viruses (such as RNA viruses that share a conserved RNA polymerase sequence). [3] [4]

DNA virus bias

There is still a bias towards DNA viruses in reference databases. Common reasons for this bias is because RNA viruses mutate more rapidly than DNA viruses, DNA is easier to handle from samples while RNA is unstable, and more steps are needed for RNA metagenomics analysis (reverse transcription). [4] [8]

Sequence contamination

Sequences can be contaminated with the host organism's' sequences which is particularly troublesome if the host organism of the virus is unknown. [4] There could also be contamination from nucleic acid extraction and PCR. [4]

Methods

Untargeted metagenomics

Metagenomic analysis uses whole genome shotgun sequencing to characterize microbial diversity in clinical and environmental samples. Total DNA and/or RNA are extracted from the samples and are prepared on a DNA or RNA library for sequencing. [9] These methods have been used to sequence the whole genome of Epstein–Barr virus (EBV) and HCV, however, contaminating host nucleic acids can affect the sensitivity to the target viral genome with the proportion of reads related to the target sequence often being low. [13] [14]

The IMG/VR system and the IMG/VR v.2.0 are the largest interactive public virus databases with over 760,000 metagenomic viral sequences and isolate viruses and serves as a starting point for the sequence analysis of viral fragments derived from metagenomic samples. [15] [16]

Targeted metagenomics: amplicon sequencing

While untargeted metagenomics and metatranscriptomics does not need a genetic marker, amplicon sequencing does. It uses a gene that is highly conserved as a genetic marker, but because of the varied nucleic acid types, the marker used has to be for specific groups of viruses. [3] [4] This is done via PCR amplification of primers that are complementary to a known, highly conserved nucleotide sequence. [9] PCR is then followed by whole genome sequencing methods and has been used to track the Ebola virus, [17] Zika Virus, [18] and COVID-19 [19] epidemics. PCR amplicon sequencing is more successful for whole genome sequencing of samples with low concentrations. However, with larger viral genomes and the heterogeneity of RNA viruses multiple overlapping primers may be required to cover the amplification of all genotypes. PCR amplicon sequencing requires knowledge of the viral genome prior to sequencing, appropriate primers, and is highly dependent on viral titers, however, PCR amplicon sequencing is a cheaper evaluation method than metagenomic sequencing when studying known viruses with relatively small genomes. [9]

Targeted metagenomics: enrichment with probes

Target enrichment is a culture independent method that sequences viral genomes directly from a sample using small RNA or DNA probes complementary to the pathogens reference sequence. The probes, which can be bound to a solid phase and capture and pull down complementary DNA sequences in the sample. [9] The presence of overlapping probes increases the tolerance for primer mismatches but their design requires high cost and time so a rapid response is limited. DNA capture is followed by brief PCR cycling and shotgun sequencing. Success of this method is dependent available reference sequences to create the probes and is not suitable for characterization of novel viruses. [9] This method has been used to characterize large and small viruses such as HCV, [14] HSV-1, [20] and HCMV. [21]

Limitations

Viral metagenomics methods can produce erroneous chimerical sequences. [22] [23] These can include in vitro artifacts from amplification and in silico artifacts from assembly. [23] Chimeras can form between unrelated viruses, as well as between viral and eukaryotic sequences. [23] The likelihood of errors is partially mitigated by greater sequencing depth, but chimeras can still form in areas of high coverage if the reads are highly fragmented. [22]

Applications

Agriculture

Plant viruses pose a global threat to crop production but through metagenomic sequencing and viral database creation, modified plant viruses can be used to aid in plant immunity as well as alter physical appearance. [24] Data obtained on plant virus genomes from metagenomic sequencing can be used to create clone viruses to inoculate the plant with to study viral components and biological characterization of viral agents with increased reproducibility. Engineered mutant virus strains have been used to alter the coloration and size of various ornamental plants and promote the health of crops. [25]

Ecology

Viral metagenomics contributes to viral classification without the need of culture based methodologies and has provided vast insights on viral diversity in any system. Metagenomics can be used to study viruses effects on a given ecosystem and how they effect the microbiome as well as monitoring viruses in an ecosystem for possible spillover into human populations. [1] Within the ecosystems, viruses can be studied to determine how they compete with each other as well as viral effects on functions of the host. Viral metagenomics has been used to study unculturable viral communities in marine and soil ecosystems. [7] [26]

Infectious disease research

Viral metagenomics is readily used to discover novel viruses, with a major focus on those zoonotic or pathogenic to humans. Viral databases obtained from metagenomics provides quick response methods to determine viral infections as well as determine drug resistant variants in clinical samples. [9] The contributions of viral metagenomics to viral classification have aided pandemic surveillance efforts as well as made infectious disease surveillance and testing more affordable. [27] Since the majority of human pandemics are zoonotic in origin, metagenomic surveillance can provide faster identification of novel viruses and their reservoirs. [28]

One such surveillance program is the Global Virome Project (GVP) an international collaborative research initiative based at the One Health Institute at the University of California, Davis. [29] [30] The GVP aims to boost infectious disease surveillance around the globe by using low cost sequencing methods in high risk countries to prevent disease outbreaks and to prevent future virus outbreaks. [27] [31]

Medicine

Viral metagenomics has been used to test for virus related cancers and difficult to diagnose cases in clinical diagnostics. [31] This method is most often used when conventional and advanced molecular testing cannot find a causative agent for disease. Metagenomic sequencing can also be used to detect pathogenic viruses in clinical samples and provide real time data for a pathogens presence in a population. [28]

The methods used for clinical viral metagenomics are not standardized, but guidelines have been published by the European Society for Clinical Virology. [32] [33] A mixture of different sequencing platforms are used for clinical viral metagenomics, the most common being instruments from Illumina and Oxford Nanopore Technologies. There are also several different protocols, both for wet lab work and for bioinformatic analysis, that are in use. [34]

See also

Related Research Articles

<span class="mw-page-title-main">Complementary DNA</span> DNA reverse transcribed from RNA

In genetics, complementary DNA (cDNA) is DNA that was reverse transcribed from an RNA. cDNA exists in both single-stranded and double-stranded forms and in both natural and engineered forms.

<span class="mw-page-title-main">Polymerase chain reaction</span> Laboratory technique to multiply a DNA sample for study

The polymerase chain reaction (PCR) is a method widely used to make millions to billions of copies of a specific DNA sample rapidly, allowing scientists to amplify a very small sample of DNA sufficiently to enable detailed study. PCR was invented in 1983 by American biochemist Kary Mullis at Cetus Corporation. Mullis and biochemist Michael Smith, who had developed other essential ways of manipulating DNA, were jointly awarded the Nobel Prize in Chemistry in 1993.

<span class="mw-page-title-main">RNA virus</span> Subclass of viruses

An RNA virus is a virus—other than a retrovirus—that has ribonucleic acid (RNA) as its genetic material. The nucleic acid is usually single-stranded RNA (ssRNA) but it may be double-stranded (dsRNA). Notable human diseases caused by RNA viruses include the common cold, influenza, SARS, MERS, COVID-19, Dengue virus, hepatitis C, hepatitis E, West Nile fever, Ebola virus disease, rabies, polio, mumps, and measles.

<span class="mw-page-title-main">Reverse transcriptase</span> Enzyme which generates DNA

A reverse transcriptase (RT) is an enzyme used to convert RNA genome to DNA, a process termed reverse transcription. Reverse transcriptases are used by viruses such as HIV and hepatitis B to replicate their genomes, by retrotransposon mobile genetic elements to proliferate within the host genome, and by eukaryotic cells to extend the telomeres at the ends of their linear chromosomes. Contrary to a widely held belief, the process does not violate the flows of genetic information as described by the classical central dogma, as transfers of information from RNA to DNA are explicitly held possible.

<span class="mw-page-title-main">Virology</span> Study of viruses

Virology is the scientific study of biological viruses. It is a subfield of microbiology that focuses on their detection, structure, classification and evolution, their methods of infection and exploitation of host cells for reproduction, their interaction with host organism physiology and immunity, the diseases they cause, the techniques to isolate and culture them, and their use in research and therapy.

Viral load, also known as viral burden, is a numerical expression of the quantity of virus in a given volume of fluid, including biological and environmental specimens. It is not to be confused with viral titre or viral titer, which depends on the assay. When an assay for measuring the infective virus particle is done, viral titre often refers to the concentration of infectious viral particles, which is different from the total viral particles. Viral load is measured using body fluids sputum and blood plasma. As an example of environmental specimens, the viral load of norovirus can be determined from run-off water on garden produce. Norovirus has not only prolonged viral shedding and has the ability to survive in the environment but a minuscule infectious dose is required to produce infection in humans: less than 100 viral particles.

<span class="mw-page-title-main">DNA sequencing</span> Process of determining the nucleic acid sequence

DNA sequencing is the process of determining the nucleic acid sequence – the order of nucleotides in DNA. It includes any method or technology that is used to determine the order of the four bases: adenine, guanine, cytosine, and thymine. The advent of rapid DNA sequencing methods has greatly accelerated biological and medical research and discovery.

<span class="mw-page-title-main">Metagenomics</span> Study of genes found in the environment

Metagenomics is the study of genetic material recovered directly from environmental or clinical samples by a method called sequencing. The broad field may also be referred to as environmental genomics, ecogenomics, community genomics or microbiomics.

<span class="mw-page-title-main">Real-time polymerase chain reaction</span> Laboratory technique of molecular biology

A real-time polymerase chain reaction is a laboratory technique of molecular biology based on the polymerase chain reaction (PCR). It monitors the amplification of a targeted DNA molecule during the PCR, not at its end, as in conventional PCR. Real-time PCR can be used quantitatively and semi-quantitatively.

Nucleic acid sequence-based amplification, commonly referred to as NASBA, is a method in molecular biology which is used to produce multiple copies of single stranded RNA. NASBA is a two-step process that takes RNA and anneals specially designed primers, then utilizes an enzyme cocktail to amplify it.

<i>Marnaviridae</i> Family of viruses

Marnaviridae is a family of positive-stranded RNA viruses in the order Picornavirales that infect various photosynthetic marine protists. Members of the family have non-enveloped, icosahedral capsids. Replication occurs in the cytoplasm and causes lysis of the host cell. The first species of this family that was isolated is Heterosigma akashiwo RNA virus (HaRNAV) in the genus Marnavirus, which infects the toxic bloom-forming Raphidophyte alga, Heterosigma akashiwo. As of 2021, there are twenty species across seven genera in this family, as well as many other related virus sequences discovered through metagenomic sequencing that are currently unclassified.

In the diagnostic laboratory, virus infections can be confirmed by a myriad of methods. Diagnostic virology has changed rapidly due to the advent of molecular techniques and increased clinical sensitivity of serological assays.

<span class="mw-page-title-main">Virus</span> Infectious agent that replicates in cells

A virus is a submicroscopic infectious agent that replicates only inside the living cells of an organism. Viruses infect all life forms, from animals and plants to microorganisms, including bacteria and archaea. Viruses are found in almost every ecosystem on Earth and are the most numerous type of biological entity. Since Dmitri Ivanovsky's 1892 article describing a non-bacterial pathogen infecting tobacco plants and the discovery of the tobacco mosaic virus by Martinus Beijerinck in 1898, more than 11,000 of the millions of virus species have been described in detail. The study of viruses is known as virology, a subspeciality of microbiology.

Biological dark matter is an informal term for unclassified or poorly understood genetic material. This genetic material may refer to genetic material produced by unclassified microorganisms. By extension, biological dark matter may also refer to the un-isolated microorganisms whose existence can only be inferred from the genetic material that they produce. Some of the genetic material may not fall under the three existing domains of life: Bacteria, Archaea and Eukaryota; thus, it has been suggested that a possible fourth domain of life may yet be discovered, although other explanations are also probable. Alternatively, the genetic material may refer to non-coding DNA and non-coding RNA produced by known organisms.

<span class="mw-page-title-main">Human virome</span> Total collection of viruses in and on the human body

The human virome is the total collection of viruses in and on the human body. Viruses in the human body may infect both human cells and other microbes such as bacteria. Some viruses cause disease, while others may be asymptomatic. Certain viruses are also integrated into the human genome as proviruses or endogenous viral elements.

<span class="mw-page-title-main">Virome</span>

Virome refers to the assemblage of viruses that is often investigated and described by metagenomic sequencing of viral nucleic acids that are found associated with a particular ecosystem, organism or holobiont. The word is frequently used to describe environmental viral shotgun metagenomes. Viruses, including bacteriophages, are found in all environments, and studies of the virome have provided insights into nutrient cycling, development of immunity, and a major source of genes through lysogenic conversion. Also, the human virome has been characterized in nine organs of 31 Finnish individuals using qPCR and NGS methodologies.

<i>Riboviria</i> Realm of viruses

Riboviria is a realm of viruses that includes all viruses that use a homologous RNA-dependent polymerase for replication. It includes RNA viruses that encode an RNA-dependent RNA polymerase, as well as reverse-transcribing viruses that encode an RNA-dependent DNA polymerase. RNA-dependent RNA polymerase (RdRp), also called RNA replicase, produces RNA from RNA. RNA-dependent DNA polymerase (RdDp), also called reverse transcriptase (RT), produces DNA from RNA. These enzymes are essential for replicating the viral genome and transcribing viral genes into messenger RNA (mRNA) for translation of viral proteins.

Clinical metagenomic next-generation sequencing (mNGS) is the comprehensive analysis of microbial and host genetic material in clinical samples from patients by next-generation sequencing. It uses the techniques of metagenomics to identify and characterize the genome of bacteria, fungi, parasites, and viruses without the need for a prior knowledge of a specific pathogen directly from clinical specimens. The capacity to detect all the potential pathogens in a sample makes metagenomic next generation sequencing a potent tool in the diagnosis of infectious disease especially when other more directed assays, such as PCR, fail. Its limitations include clinical utility, laboratory validity, sense and sensitivity, cost and regulatory considerations.

<i>Redondoviridae</i> Family of viruses

Redondoviruses are a family of human-associated DNA viruses. Their name derives from the inferred circular structure of the viral genome . Redondoviruses have been identified in DNA sequence based surveys of samples from humans, primarily samples from the oral cavity and upper airway.

Virosphere was coined to refer to all those places in which viruses are found or which are affected by viruses. However, more recently virosphere has also been used to refer to the pool of viruses that occurs in all hosts and all environments, as well as viruses associated with specific types of hosts, type of genome or ecological niche.

References

  1. 1 2 3 4 Sommers P, Chatterjee A, Varsani A, Trubl G (September 2021). "Integrating Viral Metagenomics into an Ecological Framework". Annual Review of Virology. 8 (1): 133–158. doi: 10.1146/annurev-virology-010421-053015 . PMID   34033501.
  2. Grasis JA (2018). "Host-Associated Bacteriophage Isolation and Preparation for Viral Metagenomics". Viral Metagenomics. Methods in Molecular Biology. Vol. 1746. New York, NY: Springer New York. pp. 1–25. doi:10.1007/978-1-4939-7683-6_1. ISBN   978-1-4939-7682-9. PMID   29492882. S2CID   3637163 . Retrieved 2022-12-02.
  3. 1 2 3 4 5 6 7 Krishnamurthy SR, Wang D (July 2017). "Origins and challenges of viral dark matter". Virus Research. 239: 136–142. doi:10.1016/j.virusres.2017.02.002. PMID   28192164.
  4. 1 2 3 4 5 6 7 Pappas N, Roux S, Hölzer M, Lamkiewicz K, Mock F, Marz M, Dutilh BE (2021). "Virus Bioinformatics". In Bamford DH, Zuckerman M (eds.). Encyclopedia of Virology (4th ed.). Elsevier. pp. 124–132. doi:10.1016/b978-0-12-814515-9.00034-5. ISBN   978-0-12-814516-6. PMC   7567488 .
  5. Kristensen DM, Mushegian AR, Dolja VV, Koonin EV (January 2010). "New dimensions of the virus world discovered through metagenomics". Trends in Microbiology. 18 (1): 11–19. doi:10.1016/j.tim.2009.11.003. PMC   3293453 . PMID   19942437.
  6. Bernardo P, Albina E, Eloit M, Roumagnac P (May 2013). "[Pathology and viral metagenomics, a recent history]". Médecine/Sciences (in French). 29 (5): 501–508. doi: 10.1051/medsci/2013295013 . PMID   23732099.
  7. 1 2 Alavandi SV, Poornima M (September 2012). "Viral metagenomics: a tool for virus discovery and diversity in aquaculture". Indian Journal of Virology. 23 (2): 88–98. doi:10.1007/s13337-012-0075-2. PMC   3550753 . PMID   23997432.
  8. 1 2 3 4 5 Santiago-Rodriguez TM, Hollister EB (2022-09-16). "Unraveling the viral dark matter through viral metagenomics". Frontiers in Immunology. 13. doi: 10.3389/fimmu.2022.1005107 . ISSN   1664-3224. PMC   9523745 . PMID   36189246.
  9. 1 2 3 4 5 6 7 Houldcroft CJ, Beale MA, Breuer J (March 2017). "Clinical and biological insights from viral genome sequencing". Nature Reviews. Microbiology. 15 (3): 183–192. doi:10.1038/nrmicro.2016.182. PMC   7097211 . PMID   28090077.
  10. 1 2 Breitbart M, Salamon P, Andresen B, Mahaffy JM, Segall AM, Mead D, et al. (October 2002). "Genomic analysis of uncultured marine viral communities". Proceedings of the National Academy of Sciences of the United States of America. 99 (22): 14250–14255. Bibcode:2002PNAS...9914250B. doi: 10.1073/pnas.202488399 . PMC   137870 . PMID   12384570.
  11. Simmonds P, Adams MJ, Benkő M, Breitbart M, Brister JR, Carstens EB, et al. (March 2017). "Consensus statement: Virus taxonomy in the age of metagenomics". Nature Reviews. Microbiology. 15 (3): 161–168. doi: 10.1038/nrmicro.2016.177 . hdl: 1887/114573 . PMID   28134265. S2CID   1478314.
  12. Koonin EV, Krupovic M, Agol VI (2021-08-18). "The Baltimore Classification of Viruses 50 Years Later: How Does It Stand in the Light of Virus Evolution?". Microbiology and Molecular Biology Reviews. 85 (3): e0005321. doi:10.1128/MMBR.00053-21. ISSN   1092-2172. PMC   8483701 . PMID   34259570.
  13. Depledge DP, Palser AL, Watson SJ, Lai IY, Gray ER, Grant P, et al. (2011-11-18). Jhaveri R (ed.). "Specific capture and whole-genome sequencing of viruses from clinical samples". PLOS ONE. 6 (11): e27805. Bibcode:2011PLoSO...627805D. doi: 10.1371/journal.pone.0027805 . PMC   3220689 . PMID   22125625.
  14. 1 2 Thomson E, Ip CL, Badhan A, Christiansen MT, Adamson W, Ansari MA, et al. (October 2016). "Comparison of Next-Generation Sequencing Technologies for Comprehensive Assessment of Full-Length Hepatitis C Viral Genomes". Journal of Clinical Microbiology. 54 (10): 2470–2484. doi:10.1128/jcm.00330-16. PMC   5035407 . PMID   27385709.
  15. Paez-Espino D, Chen IA, Palaniappan K, Ratner A, Chu K, Szeto E, et al. (January 2017). "IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses". Nucleic Acids Research. 45 (D1): D457–D465. doi:10.1093/nar/gkw1030. PMC   5210529 . PMID   27799466.
  16. Paez-Espino D, Roux S, Chen IA, Palaniappan K, Ratner A, Chu K, et al. (January 2019). "IMG/VR v.2.0: an integrated data management and analysis system for cultivated and environmental viral genomes". Nucleic Acids Research. 47 (D1): D678–D686. doi:10.1093/nar/gky1127. PMC   6323928 . PMID   30407573.
  17. Quick J (2019-09-25). "Ebola virus sequencing protocol v1". Protocols.io. doi:10.17504/protocols.io.7nwhmfe. S2CID   216572035 . Retrieved 2022-11-30.
  18. Vlachakis D, Papageorgiou L, Megalooikonomou V (2018-06-13), "Genetic and Geo-Epidemiological Analysis of the Zika Virus Pandemic; Learning Lessons from the Recent Ebola Outbreak", Current Topics in Zika, InTech, doi: 10.5772/intechopen.71505 , ISBN   978-1-78923-270-7, S2CID   90434818
  19. Charre C, Ginevra C, Sabatier M, Regue H, Destras G, Brun S, et al. (July 2020). "Evaluation of NGS-based approaches for SARS-CoV-2 whole genome characterisation". Virus Evolution. 6 (2): veaa075. bioRxiv   10.1101/2020.07.14.201947 . doi: 10.1093/ve/veaa075 . PMC   7665770 . PMID   33318859.
  20. Ebert K, Depledge DP, Breuer J, Harman L, Elliott G (September 2013). "Mode of virus rescue determines the acquisition of VHS mutations in VP22-negative herpes simplex virus 1". Journal of Virology. 87 (18): 10389–10393. doi:10.1128/jvi.01654-13. PMC   3753997 . PMID   23864617.
  21. Depledge DP, Palser AL, Watson SJ, Lai IY, Gray ER, Grant P, et al. (2011-11-18). "Specific capture and whole-genome sequencing of viruses from clinical samples". PLOS ONE. 6 (11): e27805. Bibcode:2011PLoSO...627805D. doi: 10.1371/journal.pone.0027805 . PMC   3220689 . PMID   22125625.
  22. 1 2 García-López R, Vázquez-Castellanos JF, Moya A (September 2015). "Fragmentation and Coverage Variation in Viral Metagenome Assemblies, and Their Effect in Diversity Calculations". Frontiers in Bioengineering and Biotechnology. 3: 141. doi: 10.3389/fbioe.2015.00141 . PMC   4585024 . PMID   26442255.
  23. 1 2 3 Arroyo Mühr LS, Lagheden C, Hassan SS, Kleppe SN, Hultin E, Dillner J (August 2020). "De novo sequence assembly requires bioinformatic checking of chimeric sequences". PLOS ONE. 15 (8): e0237455. Bibcode:2020PLoSO..1537455A. doi: 10.1371/journal.pone.0237455 . PMC   7417191 . PMID   32777809.
  24. Brewer HC, Hird DL, Bailey AM, Seal SE, Foster GD (April 2018). "A guide to the contained use of plant virus infectious clones". Plant Biotechnology Journal. 16 (4): 832–843. doi:10.1111/pbi.12876. PMC   5867029 . PMID   29271098.
  25. Pasin F, Menzel W, Daròs JA (June 2019). "Harnessed viruses in the age of metagenomics and synthetic biology: an update on infectious clone assembly and biotechnologies of plant viruses". Plant Biotechnology Journal. 17 (6): 1010–1026. doi:10.1111/pbi.13084. PMC   6523588 . PMID   30677208.
  26. Pratama AA, van Elsas JD (August 2018). "The 'Neglected' Soil Virome - Potential Role and Impact". Trends in Microbiology. 26 (8): 649–662. doi:10.1016/j.tim.2017.12.004. PMID   29306554. S2CID   25057850.
  27. 1 2 Schmidt C (October 2018). "The virome hunters". Nature Biotechnology. 36 (10): 916–919. doi:10.1038/nbt.4268. PMC   7097093 . PMID   30307913.
  28. 1 2 Roux S, Matthijnssens J, Dutilh BE (2021), "Metagenomics in Virology", Encyclopedia of Virology, Elsevier, pp. 133–140, doi:10.1016/b978-0-12-809633-8.20957-6, ISBN   978-0-12-814516-6, PMC   7157462
  29. Vernimmen T (2020-04-16). "Infectious disease: Making — and breaking — the animal connection". Knowable Magazine | Annual Reviews. doi: 10.1146/knowable-041620-1 . S2CID   218810265.
  30. "Contact". Global Virome Project. Archived from the original on 2022-08-22. Retrieved 2022-08-22.
  31. 1 2 Dutilh BE, Reyes A, Hall RJ, Whiteson KL (September 2017). "Editorial: Virus Discovery by Metagenomics: The (Im)possibilities". Frontiers in Microbiology. 8 (1710): 1710. doi: 10.3389/fmicb.2017.01710 . PMC   5596103 . PMID   28943867.
  32. López-Labrador FX, Brown JR, Fischer N, Harvala H, Van Boheemen S, Cinek O, Sayiner A, Madsen TV, Auvinen E, Kufner V, Huber M, Rodriguez C, Jonges M, Hönemann M, Susi P (2021-01-01). "Recommendations for the introduction of metagenomic high-throughput sequencing in clinical virology, part I: Wet lab procedure". Journal of Clinical Virology. 134: 104691. doi:10.1016/j.jcv.2020.104691. hdl: 10261/257819 . ISSN   1386-6532.
  33. de Vries JJ, Brown JR, Couto N, Beer M, Le Mercier P, Sidorov I, Papa A, Fischer N, Oude Munnink BB, Rodriquez C, Zaheri M, Sayiner A, Hönemann M, Pérez-Cataluña A, Carbo EC (2021-05-01). "Recommendations for the introduction of metagenomic next-generation sequencing in clinical virology, part II: bioinformatic analysis and reporting". Journal of Clinical Virology. 138: 104812. doi:10.1016/j.jcv.2021.104812. hdl: 1887/3249096 . ISSN   1386-6532.
  34. Lopez-Labrador FX, Huber M, Sidorov IA, Brown JR, Cuypers L, Laenen L, Vanmechelen B, Maes P, Fischer N, Pichler I, Storey N, Atkinson L, Schmutz S, Kufner V, van Boheemen S (2024-08-01). "Multicenter benchmarking of short and long read wet lab protocols for clinical viral metagenomics". Journal of Clinical Virology. 173: 105695. doi:10.1016/j.jcv.2024.105695. ISSN   1386-6532.