Piper, M. | Search bioRxiv

bioRxiv2018

VideoTagger: User-Friendly Software for Annotating Video Experiments of Any Duration

BackgroundScientific insight is often sought by recording and analyzing large quantities of video. While easy access to cameras has increased the quantity of collected videos, the rate at which they can be analyzed remains a major limitation. Often, bench scientists struggle with the most basic problem that there is currently no user-friendly, flexible, and open source software tool with which to watch and annotate these videos.\n\nResultsWe have created the VideoTagger tool to address these and many of the other associated challenges of video analysis. VideoTagger allows non-programming users to efficiently explore, annotate, and visualize large quantities of video data, within their existing experimental protocols. Further, it is built to accept programmed plugins written in Python, to enable seamless integration with other sophisticated computer-aided analyses.\n\nWe tested VideoTagger ourselves, and have a growing base of users in other scientific disciplines. Capitalising on the unique features of VideoTagger to play back infinite lengths of video footage at various speeds, we annotated 39h of a Drosophila melanogaster lifespan video, at approximately 10-15x faster than real-time. We then used these labels to train a machine-learning plugin, which we used to annotate an additional 538h of footage automatically. In this way, we found that flies fall over spontaneously with increasing frequency as they age, and also spend longer durations struggling to right themselves. Ageing in flies is typically defined by length of life. We propose that this new mobility measure of ageing could help the discovery of mechanisms in biogerontology, refining our definition of what healthy ageing means in this extremely small, but widely used, invertebrate.\n\nConclusionsWe show how VideoTagger is sufficiently flexible for studying lengthy and/or numerous video experiments, thus directly improving scientists productivity across varied domains.

animal behavior and cognition↗

bioRxiv2017

A strain-specific multiplex RT-PCR for Australian rabbit haemorrhagic disease viruses uncovers a new recombinant virus variant in rabbits and hares

Rabbit haemorrhagic disease virus (RHDV, or GI.1), is a calicivirus in the genus Lagovirus that has been widely utilised in Australia as a biological control agent for the management of overabundant wild European rabbit (Oryctolagus cuniculus) populations since 1996. Recently, two exotic incursions of pathogenic lagoviruses have been reported in Australia; GI.1a-Aus, previously called RHDVa-Aus, is a GI.1a virus detected in January 2014, and the novel lagovirus GI.2 (previously known as RHDV2). Furthermore, an additional GI.1a strain, GI.1a-K5 (also known as 08Q712), was released nationwide in March 2017 as a supplementary tool for wild rabbit management. To discriminate between these lagoviruses, a highly sensitive strain-specific multiplex RT-PCR assay was developed, which allows fast, cost-effective, and sensitive detection of the four pathogenic lagoviruses currently known to be circulating in Australia. In addition, we developed a universal qRT-PCR assay to be used in conjunction with the multiplex assay that broadly detects all four viruses and facilitates quantification of viral RNA load in samples. These assays enable rapid detection, identification, and quantification of pathogenic lagoviruses in the Australian context. Using these assays, a novel recombinant lagovirus was detected in rabbit tissues samples, which contained the non-structural genes of GI.1a-Aus and the structural genes of GI.2. This variant was also recovered from the liver of a European brown hare (Lepus europaeus). The impact of this novel recombinant on Australian wild lagomorph populations and its competitiveness in relation to circulating field strains, particularly GI.2, requires further studies.

microbiology↗