136 research outputs found

    Evaluation of a Droplet Digital Polymerase Chain Reaction Format for DNA Copy Number Quantification

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    ABSTRACT: Droplet digital polymerase chain reaction (ddPCR) is a new technology that was recently commercialized to enable the precise quantification of target nucleic acids in a sample. ddPCR measures absolute quantities by counting nucleic acid molecules encapsulated in discrete, volumetrically defined, water-in-oil droplet partitions. This novel ddPCR format offers a simple workflow capable of generating highly stable partitioning of DNA molecules. In this study, we assessed key performance parameters of the ddPCR system. A linear ddPCR response to DNA concentration was obtained from 0.16 % through to 99.6 % saturation in a 20,000 droplet assay corresponding to more than 4 orders of magnitude of target DNA copy number per ddPCR. Analysis of simplex and duplex assays targeting two distinct loci in the Lambda DNA genome using the ddPCR platform agreed, within their expanded uncertainties, with values obtained using a lower density microfluidic chamber based digital PCR (cdPCR). A relative expanded uncertainty under 5 % was achieved for copy number concentration using ddPCR. This level of uncertainty is much lower than values typically observed for quantification of specific DNA target sequences using currently commercially available real-time and digital cdPCR technologies

    Evolutionary potential and adaptation of Banksia attenuata (Proteaceae) to climate and fire regime in southwestern Australia, a global biodiversity hotspot

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    Substantial climate changes are evident across Australia, with declining rainfall and rising temperature in conjunction with frequent fires. Considerable species loss and range contractions have been predicted; however, our understanding of how genetic variation may promote adaptation in response to climate change remains uncertain. Here we characterized candidate genes associated with rainfall gradients, temperatures, and fire intervals through environmental association analysis. We found that overall population adaptive genetic variation was significantly affected by shortened fire intervals, whereas declining rainfall and rising temperature did not have a detectable influence. Candidate SNPs associated with rainfall and high temperature were diverse, whereas SNPs associated with specific fire intervals were mainly fixed in one allele. Gene annotation further revealed four genes with functions in stress tolerance, the regulation of stomatal opening and closure, energy use, and morphogenesis with adaptation to climate and fire intervals. B. attenuata may tolerate further changes in rainfall and temperature through evolutionary adaptations based on their adaptive genetic variation. However, the capacity to survive future climate change may be compromised by changes in the fire regime

    The study of atmospheric ice-nucleating particles via microfluidically generated droplets

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    Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 10³–10⁶ ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK’s annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies

    The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020

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    Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology

    Listening to ecosystems: data-rich acoustic monitoring through landscape-scale sensor networks

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    Ecologists have many ways to measure and monitor ecosystems, each of which can reveal details about the processes unfolding therein. Acoustic recording combined with machine learning methods for species detection can provide remote, automated monitoring of species richness and relative abundance. Such recordings also open a window into how species behave and compete for niche space in the sensory environment. These opportunities are associated with new challenges: the volume and velocity of such data require new approaches to species identification and visualization. Here we introduce a newly-initiated acoustic monitoring network across the subtropical island of Okinawa, Japan, as part of the broader OKEON (Okinawa Environmental Observation Network) project. Our aim is to monitor the acoustic environment of Okinawa’s ecosystems and use these space–time data to better understand ecosystem dynamics. We present a pilot study based on recordings from five field sites conducted over a one-month period in the summer. Our results provide a proof of concept for automated species identification on Okinawa, and reveal patterns of biogenic vs. anthropogenic noise across the landscape. In particular, we found correlations between forest land cover and detection rates of two culturally important species in the island soundscape: the Okinawa Rail and Ruddy Kingfisher. Among the soundscape indices we examined, NDSI, Acoustic Diversity and the Bioacoustic Index showed both diurnal patterns and differences among sites. Our results highlight the potential utility of remote acoustic monitoring practices that, in combination with other methods can provide a holistic picture of biodiversity. We intend this project as an open resource, and wish to extend an invitation to researchers interested in scientific collaboration
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