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Recent years have witnessed a convergence of data and methods that allow us to approximate the shape, size, and functional attributes of biological organisms. This is not only limited to traditional model species: given the ability to culture and visualize a specific organism, we can capture both its structural and functional attributes. We present a quantitative model for the colonial diatom Bacillaria paradoxa, an organism that presents a number of unique attributes in terms of form and function. To acquire a digital model of B. paradoxa, we extract a series of quantitative parameters from microscopy videos from both primary and secondary sources. These data are then analyzed using a variety of techniques, including two rival deep learning approaches. We provide an overview of neural networks for non-specialists as well as present a series of analysis on Bacillaria phenotype data. The application of deep learning networks allows for two analytical purposes. Application of the DeepLabv3 pre-trained model extracts phenotypic parameters describing the shape of cells constituting Bacillaria colonies. Application of a semantic model trained on nematode embryogenesis data (OpenDevoCell) provides a means to analyze masked images of potential intracellular features. We also advance the analysis of Bacillaria colony movement dynamics by using templating techniques and biomechanical analysis to better understand the movement of individual cells relative to an entire colony. The broader implications of these results are presented, with an eye towards future applications to both hypothesis-driven studies and theoretical advancements in understanding the dynamic morphology of Bacillaria.

In order to assess the effects of Fe-enrichment on the growth and domoic acid (DA) production of the toxigenic diatom Pseudo-nitzschia multiseries, static cultures that received the addition of different iron (Fe) concentrations were maintained for 30 days. Intra- and extracellular DA concentrations were evaluated over time, and growth and chain-formation were compared to those of non-toxic diatoms, Bacillaria sp. Growth rates of P. multiseries (μ = 0.45–0.73 d−1) were similar among cultures containing different Fe concentrations. Likewise, the similar incidence and length of P. multiseries stepped cell chains (usually 2–4; up to 8-cell long) among the treatments reinforces that the cultures were not growth-inhibited under any condition tested, suggesting an efficient Fe acquisition mechanism. Moreover, DA concentrations were significantly higher under the highest Fe concentration, indicating that Fe is required for toxin synthesis. Bacillaria sp. reached comparable growth rates under the same Fe concentrations, except when the dissolved cell contents from a P. multiseries culture was added. The 50–70% reduction in cell density and 70–90% decrease in total chlorophyll-a content of Bacillaria sp. at early stationary growth phase indicates, for the first time, an allelopathic effect of undetermined compounds released by Pseudo-nitzschia to another diatom species.