Lindley, Anthony James Willis (2023) Design, fabrication and characterisation of a low-cost, acoustically focussed imaging flow cytometer for automated analysis of phytoplankton. University of Southampton, Doctoral Thesis, 247pp.
Abstract
Phytoplankton are a diverse group of organisms which are globally important from perspectives of ecology, environmental health, climate and socioeconomics, yet are severely understudied. The ocean is vast and largely inaccessible, and while many recent advances have taken place in the in situ measurement of physiochemical variables, analysing phytoplankton abundance and diversity is still a major challenge. Bulk approaches such as fluorimetry and satellite colorimetry, which each measure the fundamental properties of an entire phytoplankton population, can provide abundance and crude taxonomic data at a large spatial scale. Despite widespread use of these techniques, there remains a need for higher taxonomic and spatiotemporal resolution data that can only be provided by light microscopy and flow cytometry, two time-consuming and expensive methods. To address these challenges, this thesis details the development of a novel, high-throughput, acoustically focussed Imaging Flow Cytometer for low-cost imaging of phytoplankton in natural water samples, making use of off-the-shelf optical and mechanical components. Acoustic focussing is used as it is a contact-free, gentle and reliable particle positioning method which allows high-throughput imaging of cells. Analytical and experimental testing of the acoustic focussing performance is detailed using Finite Element Modelling and imaging of polystyrene beads as a proxy for phytoplankton. A protocol for measurement of imaging resolution is developed and verified before being used to characterise the optical performance of the device. In order to rapidly and automatically analyse the images captured by the device, various image processing techniques were investigated. In the finalised system, cutting-edge convolutional neural networks were designed, implemented, and verified by way of comparison with manual counting of plankton cells within images. Finally, to demonstrate the effectiveness of the cytometer to address real research challenges, two experiments are described. In the first, the device automatically and successfully measures the density of preserved plankton cells within a test sample with an accuracy comparable to manual microscopy, the gold standard for this analysis. In the second experiment, the unique capability of the cytometer to generate high-temporal resolution measurements of live cells within growing cultures over an extended period was demonstrated. This experiment showed a discrepancy between the automatic measurements and manual verification, which is discussed at length, in the process uncovering a potential systemic bias occurring in phytoplankton research. The implications of these findings are explored.
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