Search

Abstract Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. We find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics.

The recent development of biological sensors has extended marine plankton studies from conducting laboratory bench work to in vivo and real-time observations. Flow cytometry (FCM) has shed new light on marine microorganisms since the 1980s through its single-cell approach and robust detection of the smallest cells. FCM records valuable optical properties of light scattering and fluorescence from cells passing in a single file in front of a narrow-collimated light source, recording tens of thousands of cells within a few minutes. Depending on the instrument settings, the sampling strategy, and the automation level, it resolves the spatial and temporal distribution of microbial marine prokaryotes and eukaryotes. Cells are usually classified and grouped on cytograms by experts and are still lacking standards, reducing data sharing capacities. Therefore, the need to make FCM data sets FAIR (Findability, Accessibility, Interoperability, and Reusability of digital assets) is becoming critical. In this paper, we present a consensus vocabulary for the 13 most common marine microbial groups observed with FCM using blue and red-light excitation. The authors designed a common layout on two-dimensional log-transformed cytograms reinforced by a decision tree that facilitates the characterization of groups. The proposed vocabulary aims at standardising data analysis and definitions, to promote harmonisation and comparison of data between users and instruments. This represents a much-needed step towards FAIRification of flow cytometric data collected in various marine environments.

The rates of cell growth, division, and carbon loss of microbial populations are key parameters for understanding how organisms interact with their environment and how they contribute to the carbon cycle. However, the invasive nature of current analytical methods has hindered efforts to reliably quantify these parameters. In recent years, size-structured matrix population models (MPMs) have gained popularity for estimating division rates of microbial populations by mechanistically describing changes in microbial cell size distributions over time. Motivated by the mechanistic structure of these models, we employ a Bayesian approach to extend size-structured MPMs to capture additional biological processes describing the dynamics of a marine phytoplankton population over the day-night cycle. Our Bayesian framework is able to take prior scientific knowledge into account and generate biologically interpretable results. Using data from an exponentially growing laboratory culture of the cyanobacterium Prochlorococcus, we isolate respiratory and exudative carbon losses as critical parameters for the modeling of their population dynamics. The results suggest that this modeling framework can provide deeper insights into microbial population dynamics provided by size distribution time-series data.

Microscopic phytoplankton transform 100 million tons of inorganic carbon into thousands of different organic compounds each day. The structure of each chemical is critical to its biological and ecosystem function, yet the diversity of biomolecules produced by marine microbial communities remained mainly unexplored, especially small polar molecules which are often considered the currency of the microbial loop.

Fueled by light, phytoplankton produce the organic matter that supports ocean ecosystems and carbon sequestration. Ocean change impacts microbial metabolism with repercussions for biogeochemical cycling.

Diatoms are able to react to biotic and abiotic stress, such as competition, predation and unfavorable growth conditions, by producing bioactive compounds including polyunsaturated aldehydes (PUAs). PUAs have been shown to act against grazers and either enhance or inhibit the growth of different phytoplankton and bacteria both in culture and in the field. Presence of nanomolar concentrations of dissolved PUAs in seawater has been reported in the North Adriatic Sea (Mediterranean), suggesting that these compounds are released in seawater following diatom cell lysis. However, the origin of the PUAs and their effects on natural phytoplankton assemblages remain unclear. Here we present data from four oceanographic cruises that took place during diatom blooms in the northern Adriatic Sea where concentrations of particulate and dissolved PUAs were monitored along with phytoplankton cell lysis. Cell lysis was positively correlated with both concentrations of particulate and dissolved PUAs (R = 0.69 and R = 0.77, respectively), supporting the hypothesis that these compounds are released by cell lysis. However, the highest concentration of dissolved PUAs (2.53 nM) was measured when cell lysis was high (0.24 d(-1)) but no known PUA-producing diatoms were detected, suggesting either that other organisms can produce PUAs or that PUA-producing enzymes retain activity extracellularly after diatom cells have lysed. Although in situ concentrations of dissolved PUAs were one to three orders of magnitude lower than those typically used in laboratory culture experiments, we argue that concentrations produced in the field could induce similar effects to those observed in culture and therefore may help shape plankton community composition and function in the oceans.

Diatoms are an important group of eukaryotic phytoplankton, responsible for about 20% of global primary productivity. Study of the functional role of chemical signaling within phytoplankton assemblages is still in its infancy although recent reports in diatoms suggest the existence of chemical-based defense strategies. Here, we demonstrate how the accurate perception of diatom-derived reactive aldehydes can determine cell fate in diatoms. In particular, the aldehyde (2E,4E/Z)-decadienal (DD) can trigger intracellular calcium transients and the generation of nitric oxide (NO) by a calcium-dependent NO synthase-like activity, which results in cell death. However, pretreatment of cells with sublethal doses of aldehyde can induce resistance to subsequent lethal doses, which is reflected in an altered calcium signature and kinetics of NO production. We also present evidence for a DD-derived NO-based intercellular signaling system for the perception of stressed bystander cells. Based on these findings, we propose the existence of a sophisticated stress surveillance system in diatoms, which has important implications for understanding the cellular mechanisms responsible for acclimation versus death during phytoplankton bloom successions.

We demonstrate the ability of flow cytometry to determine species specific cellular carbon and chlorophyll content in vivo by using laboratory cultures of phytoplankton encompassing a wide range of cell sizes. When applied to the large Atlantic Meridional Transect flow cytometry dataset, we reveal patterns in the species-specific phytoplankton carbon (C), chlorophyll (Chl) and C:Chl ratio. For Prochlorococcus the range of C:Chl is between 2 – 604; for Synechococcus 0.5 – 558. Using a Random Forest machine learning approach, we show that predictability of phytoplankton C:Chl, dominated by the prevalence of Prochlorococcus, is largely driven by silicate and nitrite concentration in the Atlantic Ocean.