Current Perspectives on High-Throughput Sequencing (HTS) for Adventitious Virus Detection: Upstream Sample Processing and Library Preparation.

A key step for broad viral detection using high-throughput sequencing (HTS) is optimizing the sample preparation strategy for extracting viral-specific nucleic acids since viral genomes are diverse: They can be single-stranded or double-stranded RNA or DNA, and can vary from a few thousand bases to over millions of bases, which might introduce biases during nucleic acid extraction. In addition, viral particles can be enveloped or non-enveloped with variable resistance to pre-treatment, which may influence their susceptibility to extraction procedures. Since the identity of the potential adventitious agents is unknown prior to their detection, efficient sample preparation should be unbiased toward all different viral types in order to maximize the probability of detecting any potential adventitious viruses using HTS. Furthermore, the quality assessment of each step for sample processing is also a critical but challenging aspect. This paper presents our current perspectives for optimizing upstream sample processing and library preparation as part of the discussion in the Advanced Virus Detection Technologies Interest group (AVDTIG) The topics include: use of nuclease treatment to enrich for encapsidated nucleic acids, techniques for amplifying low amounts of virus nucleic acids, selection of different extraction methods, relevant controls, the use of spike recovery experiments, and quality control measures during library preparation.

Modeling an approach to define sensitivity of viral detection in sample matrices-examples with microarray readout.

Advances in viral detection technologies have the potential to increase the safety assurance of medicines produced in biological production systems. However, taking full advantage of these technological advances in the regulated testing environment will require protocols for standardization and performance testing. The most essential performance characteristics of detection methods for these applications include sensitivity, breadth of detection, and consistency. We have evaluated an approach to establishing the suitability of advanced nucleic-acid-based detection systems for characterization of cell substrates and production cultures. This approach is based on selecting relevant challenge viruses, their preparation and characterization, their application to a sample preparation workflow, and quantitation of their recovery by an independent means as well as the advanced detection readout. This approach helps us evaluate the suitability of the workflow for handling diverse sample matrices across manufacturing platforms for vaccines and other biological products, and also suggests a means by which technology users, developers, and regulators may consider the critical performance attributes of novel detection technologies. We have applied this workflow to a novel microarray-based viral detection system in collaboration with Lawrence Livermore National Laboratory. This system is appealing because of the rapid turnaround of results compared to some other advanced detection technologies.

Defining a sample preparation workflow for advanced virus detection and understanding sensitivity by next-generation sequencing.

The application of next-generation sequencing (also known as deep sequencing or massively parallel sequencing) for adventitious agent detection is an evolving field that is steadily gaining acceptance in the biopharmaceutical industry. In order for this technology to be successfully applied, a robust method that can isolate viral nucleic acids from a variety of biological samples (such as host cell substrates, cell-free culture fluids, viral vaccine harvests, and animal-derived raw materials) must be established by demonstrating recovery of model virus spikes. In this report, we implement the sample preparation workflow developed by Feng et. al. and assess the sensitivity of virus detection in a next-generation sequencing readout using the Illumina MiSeq platform. We describe a theoretical model to estimate the detection of a target virus in a cell lysate or viral vaccine harvest sample. We show that nuclease treatment can be used for samples that contain a high background of non-relevant nucleic acids (e.g., host cell DNA) in order to effectively increase the sensitivity of sequencing target viruses and reduce the complexity of data analysis. Finally, we demonstrate that at defined spike levels, nucleic acids from a panel of model viruses spiked into representative cell lysate and viral vaccine harvest samples can be confidently recovered by next-generation sequencing.

A functional myo-inositol catabolism pathway is essential for rhizopine utilization by Sinorhizobium meliloti.

Rhizopine (L-3-O-methyl-scyllo-inosamine) is a symbiosis-specific compound found in alfalfa nodules induced by specific Sinorhizobium meliloti strains. It has been postulated that rhizobial strains able to synthesize and catabolize rhizopine gain a competitive advantage in the rhizosphere. The pathway of rhizopine degradation is analysed here. Since rhizopine is an inositol derivative, it was tested whether inositol catabolism is involved in rhizopine utilization. A genetic locus required for the catabolism of inositol as sole carbon source was cloned from S. meliloti. This locus was delimited by transposon Tn5 mutagenesis and its DNA sequence was determined. Based on DNA similarity studies and enzyme assays, this genetic region was shown to encode an S. meliloti myo-inositol dehydrogenase. Strains that harboured a mutation in the myo-inositol dehydrogenase gene (idhA) did not display myo-inositol dehydrogenase activity, were unable to utilize myo-inositol as sole carbon/energy source, and were unable to catabolize rhizopine. Thus, myo-inositol dehydrogenase activity is essential for rhizopine utilization in S. meliloti.