The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics

Abstract

Intricate networks of single-celled eukaryotes (protists) dominate carbon flow in the ocean. Their growth, demise, and interactions with other microorganisms drive the fluxes of biogeochemical elements through marine ecosystems. Mixotrophic protists are capable of both photosynthesis and ingestion of prey and are dominant components of open-ocean planktonic communities. Yet the role of mixotrophs in elemental cycling is obscured by their capacity to act as primary producers or heterotrophic consumers depending on factors that remain largely uncharacterized. Here, we develop and apply a machine learning model that predicts the in situ trophic mode of aquatic protists based on their patterns of gene expression. This approach leverages a public collection of protist transcriptomes as a training set to identify a subset of gene families whose transcriptional profiles predict trophic mode. We applied our model to nearly 100 metatranscriptomes obtained during two oceanographic cruises in the North Pacific and found community-level and population-specific evidence that abundant open-ocean mixotrophic populations shift their predominant mode of nutrient and carbon acquisition in response to natural gradients in nutrient supply and sea surface temperature. Metatranscriptomic data from ship-board incubation experiments revealed that abundant mixotrophic prymnesiophytes from the oligotrophic North Pacific subtropical gyre rapidly remodeled their transcriptome to enhance photosynthesis when supplied with limiting nutrients. Coupling this approach with experiments designed to reveal the mechanisms driving mixotroph physiology provides an avenue toward understanding the ecology of mixotrophy in the natural environment.

Divergent functions of two clades of flavodoxin in diatoms mitigate oxidative stress and iron limitation

“…Community composition, nutrient availability (Gradoville et al, 2020; Juranek et al, 2020; Lambert et al, 2022; Park et al, 2022; Pinedo-González et al, 2020), and flavodoxin transcriptional patterns (Fig. 5A, B, Fig.…”

“…Triplicate carboys with no amendment served as a control. After 4 days, the samples were filtered in the same way as the transect samples (Lambert et al, 2022).…”

“…Lanes from left to right: DNA ladder (size in bp), WT, two WTlike clones (5,16), three knock-out (Flav KO) clones (9, 14,1), negative control. C. Sequence of targeted deletion in TpFlav in WT, 5), Flav KO (1,9,14) (Coesel et al, 2021;Durham et al, 2019;Groussman et al, 2021;Lambert et al, 2022). Central part represents the specific search, annotation and quantification of flavodoxins.…”

Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges

“…Environmental metatranscriptomics-led SML is currently limited. However, the approach has been shown to uncover the mixotrophic processes of protists in response to nutrient gradients in the Pacific Ocean ( Lambert et al, 2021 ), thereby demonstrating that trophic modes can be readily predicted from metatranscriptomic data.…”

Marine Microeukaryote Metatranscriptomics: Sample Processing and Bioinformatic Workflow Recommendations for Ecological Applications

“…Marine metatranscriptomic studies to date have been conducted across spatial and temporal scales (e.g., Sun et al, 2020;Becker et al, 2021;Cohen et al, 2021;Coesel et al, 2021;Groussman et al, 2021;Harke et al, 2021;Muratore et al, 2022), and in concert with experimental incubations/microcosms in which key biological, chemical and/or physical parameters are manipulated (e.g., Alexander et al, 2015b;Bertrand et al, 2015;Lampe et al, 2018). Such metatranscriptomic investigations into marine protists have expanded our understanding of their nutrient physiology (Alexander et al, 2015a;Pearson et al, 2015;Lampe et al, 2018;Caputi et al, 2019;Kolody et al, 2019), nutritional modes (Hu et al, 2018;Lambert et al, 2021), coastal bloom dynamics (Gong et al, 2017;Ji et al, 2018;Metegnier et al, 2020), and contributions to ocean biogeochemistry (Carradec et al, 2018;Cohen et al, 2021).…”