Oskar E. Karlsson

Metagenomic Detection of Viral Pathogens in Spanish Honeybees: Co- Infection by Aphid Lethal Paralysis, Israel Acute Paralysis and Lake Sinai Viruses

The situation in Europe concerning honeybees has in recent years become increasingly aggravated with steady decline in populations and/or catastrophic winter losses. This has largely been attributed to the occurrence of a variety of known and “unknown”, emerging novel diseases. Previous studies have demonstrated that colonies often can harbour more than one pathogen, making identification of etiological agents with classical methods difficult. By employing an unbiased metagenomic approach, which allows the detection of both unexpected and previously unknown infectious agents, the detection of three viruses, Aphid Lethal Paralysis Virus (ALPV), Israel Acute Paralysis Virus (IAPV), and Lake Sinai Virus (LSV), in honeybees from Spain is reported in this article. The existence of a subgroup of ALPV with the ability to infect bees was only recently reported and this is the first identification of such a strain in Europe. Similarly, LSV appear to be a still unclassified group of viruses with unclear impact on colony health and these viruses have not previously been identified outside of the United States. Furthermore, our study also reveals that these bees carried a plant virus, Turnip Ringspot Virus (TuRSV), potentially serving as important vector organisms. Taken together, these results demonstrate the new possibilities opened up by high-throughput sequencing and metagenomic analysis to study emerging new diseases in domestic and wild animal populations, including honeybees.

The Effect of Preprocessing by Sequence-Independent, Single-Primer Amplification (SISPA) on Metagenomic Detection of Viruses

Compared to routine diagnostics, screening for pathogens in outbreak situations, with or without intentional release, poses demands on the detection technology to not only indicate the presence of already known causative agents but also novel and unexpected pathogens. The metagenomic approach to detecting viral pathogens, using unbiased high-throughput sequencing (HTS), is a well-established methodology with a broad detection range and wide applicability on different sample matrices. To prepare a sample for HTS, the common presequencing steps include homogenization, enrichment, separation (eg, magnetic separation), and amplification. In this initial study, we explored the benefits and drawbacks of preprocessing by sequence-independent, single-primer amplification (SISPA) of nucleic acids by applying the methodology to artificial samples. More specifically, a synthetic metagenome was divided into 2 samples, 1 unamplified and 1 diluted, and amplified by SISPA. Subsequently, both samples were sequenced using the Ion Torrent Personal Genome Machine (PGM), and the resulting datasets were analyzed by using bioinformatics, short read mapping, de novo assembly, BLAST-based taxonomic classification, and visualization. The results indicate that even though SISPA introduces a strong amplification bias, which makes it unsuitable for whole-genome sequencing, it is still useful for detecting and identifying viruses.

The Intestinal Eukaryotic Virome in Healthy and Diarrhoeic Neonatal Piglets

Neonatal porcine diarrhoea of uncertain aetiology has been reported from a number of European countries. The aim of the present study was to use viral metagenomics to examine a potential viral involvement in this diarrhoea and to describe the intestinal virome with focus on eukaryotic viruses. Samples from the distal jejunum of 50 diarrhoeic and 19 healthy piglets from 10 affected herds were analysed. The viral fraction of the samples was isolated and nucleic acids (RNA and DNA fractions) were subjected to sequence independent amplification. Samples from diarrhoeic piglets from the same herds were pooled whereas samples from healthy piglets were analysed individually. In total, 29 clinical samples, plus two negative controls and one positive control consisting of a mock metagenome were sequenced using the Ion Torrent platform. The resulting sequence data was subjected to taxonomic classification using Kraken, Diamond and HMMER. In the healthy specimens, eight different mammalian virus families were detected (Adenoviridae, Anelloviridae, Astroviridae, Caliciviridae, Circoviridae, Parvoviridae, Picornaviridae, and Reoviridae) compared to four in the pooled diarrhoeic samples (Anelloviridae, Circoviridae, Picornaviridae, and Reoviridae). It was not possible to associate a particular virus family with the investigated diarrhoea. In conclusion, this study does not support the hypothesis that the investigated diarrhoea was caused by known mammalian viruses. The results do, however, indicate that known mammalian viruses were present in the intestine as early as 24–48 hours after birth, indicating immediate infection post-partum or possibly transplacental infection.

Metagenomic Detection Methods in Biopreparedness Outbreak Scenarios

In the field of diagnostic microbiology, rapid molecular methods are critically important for detecting pathogens. With rapid and accurate detection, preventive measures can be put in place early, thereby preventing loss of life and further spread of a disease. From a preparedness perspective, early detection and response are important in order to minimize the consequences. During the past 2 decades, advances in next-generation sequencing (NGS) technology have changed the playing field of molecular methods. Today, it is within reach to completely sequence the total microbiological content of a clinical sample, creating a metagenome, in a single week of laboratory work. As new technologies emerge, their dissemination and capacity building must be facilitated, and criteria for use, as well as guidelines on how to report results, must be established. This article focuses on the use of metagenomics, from sample collection to data analysis and to some extent NGS, for the detection of pathogens, the integration of the technique in outbreak response systems, and the risk-based evaluation of sample processing in routine diagnostics labs. The article covers recent advances in the field, current debate, gaps in research, and future directions. Examples of metagenomic detection, as well as possible applications of the methods, are described in various biopreparedness outbreak scenarios.

Metagenomic Approaches to Disclose Disease-Associated Pathogens: Detection of Viral Pathogens in Honeybees

Metagenomic approaches have become invaluable for culture-independent and sequence-independent detection and characterization of disease-associated pathogens. Here, the sequential steps from sampling to verification of results are described for a metagenomic-based approach to detect potential pathogens in honeybees. The pre-sequencing steps are given in detail, but due to the rapid development of sequencing technologies, all platform-specific procedures, as well as subsequent bioinformatics analysis, are more generally described. It should also be noted that this approach could, with minor modifications, be adapted for other organisms and sample matrices.

Molecular approaches to recognize relevant and emerging infectious diseases in animals.

Since the introduction of the first molecular tests, there has been a continuous effort to develop new and improved assays for rapid and efficient detection of infectious agents. This has been motivated by a need for improved sensitivity as well as results that can be easily communicated. The experiences and knowledge gained at the World Organisation for Animal Health (OIE) Collaborating Centre for Biotechnology-based Diagnosis of Infectious Diseases in Veterinary Medicine, Uppsala, Sweden, will here be used to provide an overview of the different molecular approaches that can be used to diagnose and identify relevant and emerging infectious diseases in animals.