Evaluation of a commercial exogenous internal process control for diagnostic RNA virus metagenomics from different animal clinical samples

Non-Targeted RNA Sequencing: Towards the Development of Universal Clinical Diagnosis Methods for Human and Veterinary Infectious Diseases

Metagenomics offers the potential to replace and simplify classical methods used in the clinical diagnosis of human and veterinary infectious diseases. Metagenomics boasts a high pathogen discovery rate and high specificity, advantages absent in most classical approaches. However, its widespread adoption in clinical settings is still pending, with a slow transition from research to routine use. While longer turnaround times and higher costs were once concerns, these issues are currently being addressed by automation, better chemistries, improved sequencing platforms, better databases, and automated bioinformatics analysis. However, many technical options and steps, each producing highly variable outcomes, have reduced the technology's operational value, discouraging its implementation in diagnostic labs. We present a case for utilizing non-targeted RNA sequencing (NT-RNA-seq) as an ideal metagenomics method for the detection of infectious disease-causing agents in humans and animals. Additionally, to create operational value, we propose to identify best practices for the "core" of steps that are invariably shared among many human and veterinary protocols. Reference materials, sequencing procedures, and bioinformatics standards should accelerate the validation processes necessary for the widespread adoption of this technology. Best practices could be determined through "implementation research" by a consortium of interested institutions working on common samples.

Comparison of Three Viral Nucleic Acid Preamplification Pipelines for Sewage Viral Metagenomics

Viral metagenomics is a useful tool for detecting multiple human viruses in urban sewage. However, more refined protocols are required for its effective use in disease surveillance. In this study, we investigated the performance of three different preamplification pipelines (specific to RNA viruses, DNA viruses or both) for viral genome sequencing using spiked-in Phosphate Buffered Saline and sewage samples containing known concentrations of viruses. We found that compared to the pipeline targeting all genome types, the RNA pipeline performed better in detecting RNA viruses in both spiked and unspiked sewage samples, allowing the detection of various mammalian viruses including members from the Reoviridae, Picornaviridae, Astroviridae and Caliciviridae. However, the DNA-specific pipeline did not improve the detection of mammalian DNA viruses. We also measured viral recovery by quantitative reverse transcription polymerase chain reaction and assessed the impact of genetic background (non-viral genetic material) on viral coverage. Our results indicate that viral recoveries were generally lower in sewage (average of 11.0%) and higher in Phosphate Buffered Saline (average of 23.4%) for most viruses. Additionally, spiked-in viruses showed lower genome coverage in sewage, demonstrating the negative effect of genetic background on sequencing. Finally, correlation analysis revealed a relationship between virus concentration and genome normalized reads per million, indicating that viral metagenomic sequencing can be semiquantitative.

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

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

Next-Generation Sequencing for the Detection of Microbial Agents in Avian Clinical Samples

Direct-targeted next-generation sequencing (tNGS), with its undoubtedly superior diagnostic capacity over real-time PCR (RT-PCR), and direct-non-targeted NGS (ntNGS), with its higher capacity to identify and characterize multiple agents, are both likely to become diagnostic methods of choice in the future. tNGS is a rapid and sensitive method for precise characterization of suspected agents. ntNGS, also known as agnostic diagnosis, does not require a hypothesis and has been used to identify unsuspected infections in clinical samples. Implemented in the form of multiplexed total DNA metagenomics or as total RNA sequencing, the approach produces comprehensive and actionable reports that allow semi-quantitative identification of most of the agents present in respiratory, cloacal, and tissue samples. The diagnostic benefits of the use of direct tNGS and ntNGS are high specificity, compatibility with different types of clinical samples (fresh, frozen, FTA cards, and paraffin-embedded), production of nearly complete infection profiles (viruses, bacteria, fungus, and parasites), production of "semi-quantitative" information, direct agent genotyping, and infectious agent mutational information. The achievements of NGS in terms of diagnosing poultry problems are described here, along with future applications. Multiplexing, development of standard operating procedures, robotics, sequencing kits, automated bioinformatics, cloud computing, and artificial intelligence (AI) are disciplines converging toward the use of this technology for active surveillance in poultry farms. Other advances in human and veterinary NGS sequencing are likely to be adaptable to avian species in the future.

RNA sequencing of avian paramyxovirus (Paramyxoviridae, Avulavirinae) isolates from wild mallards in Belgium, 2021: complete genomes and coinfections

We used untargeted RNA sequencing to characterize three Avulavirinae isolates from pooled samples obtained from wild mallards in Belgium in 2021. The complete genome sequences of two avian Orthoavulavirus-1 (AOAV-1) strains and one avian Paraavulavirus-4 (APMV-4) strain were determined confirming hemagglutination inhibition testing of the virus isolates. In addition, the applied sequencing strategy identified an avian influenza virus (AIV) coinfection in all three virus isolates, confirming weak-positive AIV realtime RT-PCR results from the original sample material. In one AOAV-1 isolate, partial sequences covering all genome segments of an AIV of subtype H11N9 could be de novo assembled from the sequencing data. Besides an AIV coinfection, RNA metagenomic data from the APMV-4 isolate also showed evidence of Alpharetrovirus and Megrivirus coinfection. In total, two AOAV-1 of Class II, genotype I.2 and one APMV-4 complete genome sequences were assembled and compared to publicly available sequences, highlighting the importance of surveillance for poultry pathogens in wild birds. Beyond the insights from full genome characterization of virus isolates, untargeted RNA sequencing strategies provide additional insights in the RNA virome of clinical samples as well as their derived virus isolates that are particularly useful when targeting wild avifauna reservoirs of poultry pathogens.

A New Circular Single-Stranded DNA Virus Related with Howler Monkey Associated Porprismacovirus 1 Detected in Children with Acute Gastroenteritis

Putative replication-associated protein (REP) and capsid-like (CAP) proteins are encoded by circular single-stranded DNA viruses (CRESS DNA), which have been found in samples from most eukaryotic groups. However, the details of these viruses’ life cycles and their significance in diseases have yet to be established. We presented and analyzed two full-length CRESS DNA genomes acquired from two children diagnosed with acute gastroenteritis (GI) in the northeast state of Tocantins, Brazil, using next-generation sequencing and a virus-like filtration approach. Both sequences (named SmaCV3BR08 and SmaCV3BR291) are closely similar to a prior CRESS DNA sequence discovered in the feces of a new world monkey (Alouatta caraya) from the United States in 2009 and termed Howler monkey-associated porprismacovirus 1 (Genbank ID: NC 026317). According to our comparative study, these porprismacovirus genomes deviate by 10% at the nucleotide level. For comparative reasons, the divergence between our sequences (SmaCV3BR08 and SmaCV3BR291) and a porprismacovirus recently identified in a human fecal sample from Peru is 37%. These data suggest that there is a great diversity of porprismacoviruses in South America, perhaps more than two species. In addition, the finding of closely related sequences of porprismacoviruses in humans and native monkeys highlights the zoonotic potential of these viruses.

Composition of Eukaryotic Viruses and Bacteriophages in Individuals with Acute Gastroenteritis

Metagenomics based on the next-generation sequencing (NGS) technique is a target-independent assay that enables the simultaneous detection and genomic characterization of all viruses present in a sample. There is a limited amount of data about the virome of individuals with gastroenteritis (GI). In this study, the enteric virome of 250 individuals (92% were children under 5 years old) with GI living in the northeastern and northern regions of Brazil was characterized. Fecal samples were subjected to NGS, and the metagenomic analysis of virus-like particles (VLPs) identified 11 viral DNA families and 12 viral RNA families. As expected, the highest percentage of viral sequences detected were those commonly associated with GI, including rotavirus, adenovirus, norovirus (94.8%, 82% and 71.2%, respectively). The most common co-occurrences, in a single individual, were the combinations of rotavirus-adenovirus, rotavirus-norovirus, and norovirus-adenovirus (78%, 69%, and 62%, respectively). In the same way, common fecal-emerging human viruses were also detected, such as parechovirus, bocaporvirus, cosavirus, picobirnavirus, cardiovirus, salivirus, and Aichivirus. In addition, viruses that infect plants, nematodes, fungi, protists, animals, and arthropods could be identified. A large number of unclassified viral contigs were also identified. We show that the metagenomics approach is a powerful and promising tool for the detection and characterization of different viruses in clinical GI samples.

Metagenomic sequencing determines complete infectious bronchitis virus (avian Gammacoronavirus) vaccine strain genomes and associated viromes in chicken clinical samples

Infectious bronchitis virus (IBV, genus Gammacoronavirus) causes an economically important and highly contagious disease in chicken. Random primed RNA sequencing was applied to two IBV positive clinical samples and one in ovo-passaged virus. The virome of a cloacal swab pool was dominated by IBV (82% of viral reads) allowing de novo assembly of a GI-13 lineage complete genome with 99.95% nucleotide identity to vaccine strain 793B. In addition, substantial read counts (16% of viral reads) allowed the assembly of a near-complete chicken astrovirus genome, while lower read counts identified the presence of chicken calicivirus and avian leucosis virus. Viral reads in a respiratory/intestinal tissue pool were distributed between IBV (22.53%), Sicinivirus (Picornaviridae, 24%), and avian leucosis virus (37.04%). A complete IBV genome with 99.95% nucleotide identity to vaccine strain H120 (lineage GI-1), as well as a near-complete avian leucosis virus genome and a partial Sicinivirus genome were assembled from the tissue sample data. Lower read counts identified chicken calicivirus, Avibirnavirus (infectious bursal disease virus, assembling to 98.85% of segment A and 69.66% of segment B closely related to D3976/1 from Germany, 2017) and avian orthoreovirus, while three avian orthoavulavirus 1 reads confirmed prior real-time RT-PCR result. IBV sequence variation analysis identified both fixed and minor frequency variations in the tissue sample compared to its in ovo-passaged virus. Metagenomic methods allow the determination of complete coronavirus genomes from clinical chicken samples while providing additional insights in RNA virus sequence diversity and coinfecting viruses potentially contributing to pathogenicity.

Microbial metagenomic approach uncovers the first rabbit haemorrhagic disease virus genome in Sub-Saharan Africa

Rabbit Haemorrhagic Disease (RHD) causes high morbidity and mortality in rabbits and hares. Here, we report the first genomic characterization of lagovirus GI.2 virus in domestic rabbits from sub-Saharan Africa. We used an unbiased microbial metagenomic Next Generation Sequencing (mNGS) approach to diagnose the pathogen causing the suspected outbreak of RHD in Ibadan, Nigeria. The liver, spleen, and lung samples of five rabbits from an outbreak in 2 farms were analyzed. The mNGS revealed one full and two partial RHDV2 genomes on both farms. Phylogenetic analysis showed close clustering with RHDV2 lineages from Europe (98.6% similarity with RHDV2 in the Netherlands, and 99.1 to 100% identity with RHDV2 in Germany), suggesting potential importation. Subsequently, all the samples were confirmed by RHDV virus-specific RT-PCR targeting the VP60 gene with the expected band size of 398 bp for the five rabbits sampled. Our findings highlight the need for increased genomic surveillance of RHDV2 to track its origin, understand its diversity and to inform public health policy in Nigeria, and Sub-Saharan Africa.

A theoretical and generalized approach for the assessment of the sample-specific limit of detection for clinical metagenomics

Metagenomics is a powerful tool to identify novel or unexpected pathogens, since it is generic and relatively unbiased. The limit of detection (LOD) is a critical parameter for the routine application of methods in the clinical diagnostic context. Although attempts for the determination of LODs for metagenomics next-generation sequencing (mNGS) have been made previously, these were only applicable for specific target species in defined samples matrices. Therefore, we developed and validated a generalized probability-based model to assess the sample-specific LOD of mNGS experiments (LOD_mNGS). Initial rarefaction analyses with datasets of Borna disease virus 1 human encephalitis cases revealed a stochastic behavior of virus read detection. Based on this, we transformed the Bernoulli formula to predict the minimal necessary dataset size to detect one virus read with a probability of 99%. We validated the formula with 30 datasets from diseased individuals, resulting in an accuracy of 99.1% and an average of 4.5 ± 0.4 viral reads found in the calculated minimal dataset size. We demonstrated by modeling the virus genome size, virus-, and total RNA-concentration that the main determinant of mNGS sensitivity is the virus-sample background ratio. The predicted LOD_mNGS for the respective pathogenic virus in the datasets were congruent with the virus-concentration determined by RT-qPCR. Theoretical assumptions were further confirmed by correlation analysis of mNGS and RT-qPCR data from the samples of the analyzed datasets. This approach should guide standardization of mNGS application, due to the generalized concept of LOD_mNGS.

Increased viral read counts and metagenomic full genome characterization of porcine astrovirus 4 and Posavirus 1 in sows in a swine farm with unexplained neonatal piglet diarrhea

Neonatal diarrhea in piglets may cause major losses in affected pig herds. The present study used random high-throughput RNA sequencing (metagenomic next generation sequencing, mNGS) to investigate the virome of sows from a farm with persistent neonatal piglet diarrhea in comparison to two control farms without diarrhea problems. A variety of known swine gastrointestinal viruses was detected in the control farms as well as in the problem farm (Mamastrovirus, Enterovirus, Picobirnavirus, Posavirus 1, Kobuvirus, Proprismacovirus). A substantial increase in normalized viral read counts was observed in the affected farm compared to the control farms. The increase was attributable to a single viral species in each of the sampled sows (porcine astrovirus 4 and Posavirus 1). The complete genomes of a porcine astrovirus 4 and two co-infecting Posavirus 1 were de novo assembled and characterized. The 6734 nt single-stranded RNA genome of porcine astrovirus 4 (PoAstV-4) strain Belgium/2019 contains three overlapping open reading frames (nonstructural protein 1ab, nonstructural protein 1a, capsid protein). Posavirus 1 strains Belgium/01/2019 and Belgium/02/2019 have a 9814 nt single-stranded positive-sense RNA genome encoding a single open reading frame (polyprotein precursor) containing the five expected Picornavirales-conserved protein domains. The study highlights the potential of mNGS workflows to study unexplained neonatal diarrhea in piglets and contributes to the scarce availability of both PoAstV-4 and Posavirus-1 whole genome sequences from Western Europe.