Multi-trait diversification in marine diatoms in constant and warmed environments.

Phytoplankton are photosynthetic marine microbes that affect food webs, nutrient cycles and climate regulation. Their roles are determined by correlated phytoplankton functional traits including cell size, chlorophyll content and cellular composition. Here, we explore patterns of evolution in interrelated trait values and correlations. Because both chance events and natural selection contribute to phytoplankton trait evolution, we used population bottlenecks to diversify six genotypes of Thalassiosirid diatoms. We then evolved them as large populations in two environments. Interspecific variation and within-species evolution were visualized for nine traits and their correlations using reduced axes (a trait-scape). Our main findings are that shifts in trait values resulted in movement of evolving populations within the trait-scape in both environments, but were more frequent when large populations evolved in a novel environment. Which trait relationships evolved was population-specific, but greater departures from ancestral trait correlations were associated with lower population growth rates. There was no single master trait that could be used to understand multi-trait evolution. Instead, repeatable multi-trait evolution occurred along a major axis of variation defined by several diatom traits and trait relationships. Because trait-scapes capture changes in trait relationships and values together, they offer an insightful way to study multi-trait variation.

Direct observations of microbial community succession on sinking marine particles.

Microbial community dynamics on sinking particles control the amount of carbon that reaches the deep ocean and the length of time that carbon is stored, with potentially profound impacts on Earth's climate. A mechanistic understanding of the controls on sinking particle distributions has been hindered by limited depth- and time-resolved sampling and methods that cannot distinguish individual particles. Here, we analyze microbial communities on nearly 400 individual sinking particles in conjunction with more conventional composite particle samples to determine how particle colonization and community assembly might control carbon sequestration in the deep ocean. We observed community succession with corresponding changes in microbial metabolic potential on the larger sinking particles transporting a significant fraction of carbon to the deep sea. Microbial community richness decreased as particles aged and sank; however, richness increased with particle size and the attenuation of carbon export. This suggests that the theory of island biogeography applies to sinking marine particles. Changes in POC flux attenuation with time and microbial community composition with depth were reproduced in a mechanistic ecosystem model that reflected a range of POC labilities and microbial growth rates. Our results highlight microbial community dynamics and processes on individual sinking particles, the isolation of which is necessary to improve mechanistic models of ocean carbon uptake.

Genus-Wide Transcriptional Landscapes Reveal Correlated Gene Networks Underlying Microevolutionary Divergence in Diatoms.

Marine microbes like diatoms make up the base of marine food webs and drive global nutrient cycles. Despite their key roles in ecology, biogeochemistry, and biotechnology, we have limited empirical data on how forces other than adaptation may drive diatom diversification, especially in the absence of environmental change. One key feature of diatom populations is frequent extreme reductions in population size, which can occur both in situ and ex situ as part of bloom-and-bust growth dynamics. This can drive divergence between closely related lineages, even in the absence of environmental differences. Here, we combine experimental evolution and transcriptome landscapes (t-scapes) to reveal repeated evolutionary divergence within several species of diatoms in a constant environment. We show that most of the transcriptional divergence can be captured on a reduced set of axes, and that repeatable evolution can occur along a single major axis of variation defined by core ortholog expression comprising common metabolic pathways. Previous work has associated specific transcriptional changes in gene networks with environmental factors. Here, we find that these same gene networks diverge in the absence of environmental change, suggesting these pathways may be central in generating phenotypic diversity as a result of both selective and random evolutionary forces. If this is the case, these genes and the functions they encode may represent universal axes of variation. Such axes that capture suites of interacting transcriptional changes during diversification improve our understanding of both global patterns in local adaptation and microdiversity, as well as evolutionary forces shaping algal cultivation.

Mechanistic constraints on the trade-off between photosynthesis and respiration in response to warming.

Phytoplankton are responsible for half of all oxygen production and drive the ocean carbon cycle. Metabolic theory predicts that increasing global temperatures will cause phytoplankton to become more heterotrophic and smaller. Here, we uncover the metabolic trade-offs between cellular space, energy, and stress management driving phytoplankton thermal acclimation and how these might be overcome through evolutionary adaptation. We show that the observed relationships between traits such as chlorophyll, lipid content, C:N, and size can be predicted on the basis of the metabolic demands of the cell, the thermal dependency of transporters, and changes in membrane lipids. We suggest that many of the observed relationships are not fixed physiological constraints but rather can be altered through adaptation. For example, the evolution of lipid metabolism can favor larger cells with higher lipid content to mitigate oxidative stress. These results have implications for rates of carbon sequestration and export in a warmer ocean.

Identification of microbial metabolic functional guilds from large genomic datasets.

Heterotrophic microbes play an important role in the Earth System as key drivers of major biogeochemical cycles. Specifically, the consumption rate of organic matter is set by the interaction between diverse microbial communities and the chemical and physical environment in which they reside. Modeling these dynamics requires reducing the complexity of microbial communities and linking directly with biogeochemical functions. Microbial metabolic functional guilds provide one approach for reducing microbial complexity and incorporating microbial biogeochemical functions into models. However, we lack a way to identify these guilds. In this study, we present a method for defining metabolic functional guilds from annotated genomes, which are derived from both uncultured and cultured organisms. This method utilizes an Aspect Bernoulli (AB) model and was tested on three large genomic datasets with 1,733-3,840 genomes each. Ecologically relevant microbial metabolic functional guilds were identified including guilds related to DMSP degradation, dissimilatory nitrate reduction to ammonia, and motile copiotrophy. This method presents a way to generate hypotheses about functions co-occurring within individual microbes without relying on cultured representatives. Applying the concept of metabolic functional guilds to environmental samples will provide new insight into the role that heterotrophic microbial communities play in setting rates of carbon cycling.

The Microbiological Drivers of Temporally Dynamic Dimethylsulfoniopropionate Cycling Processes in Australian Coastal Shelf Waters.

The organic sulfur compounds dimethylsulfoniopropionate (DMSP) and dimethyl sulfoxide (DMSO) play major roles in the marine microbial food web and have substantial climatic importance as sources and sinks of dimethyl sulfide (DMS). Seasonal shifts in the abundance and diversity of the phytoplankton and bacteria that cycle DMSP are likely to impact marine DMS (O) (P) concentrations, but the dynamic nature of these microbial interactions is still poorly resolved. Here, we examined the relationships between microbial community dynamics with DMS (O) (P) concentrations during a 2-year oceanographic time series conducted on the east Australian coast. Heterogenous temporal patterns were apparent in chlorophyll a (chl a) and DMSP concentrations, but the relationship between these parameters varied over time, suggesting the phytoplankton and bacterial community composition were affecting the net DMSP concentrations through differential DMSP production and degradation. Significant increases in DMSP were regularly measured in spring blooms dominated by predicted high DMSP-producing lineages of phytoplankton (Heterocapsa, Prorocentrum, Alexandrium, and Micromonas), while spring blooms that were dominated by predicted low DMSP-producing phytoplankton (Thalassiosira) demonstrated negligible increases in DMSP concentrations. During elevated DMSP concentrations, a significant increase in the relative abundance of the key copiotrophic bacterial lineage Rhodobacterales was accompanied by a three-fold increase in the gene, encoding the first step of DMSP demethylation (dmdA). Significant temporal shifts in DMS concentrations were measured and were significantly correlated with both fractions (0.2-2 µm and >2 µm) of microbial DMSP lyase activity. Seasonal increases of the bacterial DMSP biosynthesis gene (dsyB) and the bacterial DMS oxidation gene (tmm) occurred during the spring-summer and coincided with peaks in DMSP and DMSO concentration, respectively. These findings, along with significant positive relationships between dsyB gene abundance and DMSP, and tmm gene abundance with DMSO, reinforce the significant role planktonic bacteria play in producing DMSP and DMSO in ocean surface waters. Our results highlight the highly dynamic nature and myriad of microbial interactions that govern sulfur cycling in coastal shelf waters and further underpin the importance of microbial ecology in mediating important marine biogeochemical processes.

Bacterial chemotaxis to saccharides is governed by a trade-off between sensing and uptake.

To swim up gradients of nutrients, E. coli senses nutrient concentrations within its periplasm. For small nutrient molecules, periplasmic concentrations typically match extracellular concentrations. However, this is not necessarily the case for saccharides, such as maltose, which are transported into the periplasm via a specific porin. Previous observations have shown that, under various conditions, E. coli limits maltoporin abundance so that, for extracellular micromolar concentrations of maltose, there are predicted to be only nanomolar concentrations of free maltose in the periplasm. Thus, in the micromolar regime, the total uptake of maltose from the external environment into the cytoplasm is limited not by the abundance of cytoplasmic transport proteins but by the abundance of maltoporins. Here, we present results from experiments and modeling suggesting that this porin-limited transport enables E. coli to sense micromolar gradients of maltose despite having a high-affinity ABC transport system that is saturated at these micromolar levels. We used microfluidic assays to study chemotaxis of E. coli in various gradients of maltose and methyl-aspartate and leveraged our experimental observations to develop a mechanistic transport-and-sensing chemotaxis model. Incorporating this model into agent-based simulations, we discover a trade-off between uptake and sensing: although high-affinity transport enables higher uptake rates at low nutrient concentrations, it severely limits the range of dynamic sensing. We thus propose that E. coli may limit periplasmic uptake to increase its chemotactic sensitivity, enabling it to use maltose as an environmental cue.

Microbial metabolites in the marine carbon cycle.

One-quarter of photosynthesis-derived carbon on Earth rapidly cycles through a set of short-lived seawater metabolites that are generated from the activities of marine phytoplankton, bacteria, grazers and viruses. Here we discuss the sources of microbial metabolites in the surface ocean, their roles in ecology and biogeochemistry, and approaches that can be used to analyse them from chemistry, biology, modelling and data science. Although microbial-derived metabolites account for only a minor fraction of the total reservoir of marine dissolved organic carbon, their flux and fate underpins the central role of the ocean in sustaining life on Earth.

Microbes contribute to setting the ocean carbon flux by altering the fate of sinking particulates.

Sinking particulate organic carbon out of the surface ocean sequesters carbon on decadal to millennial timescales. Predicting the particulate carbon flux is therefore critical for understanding both global carbon cycling and the future climate. Microbes play a crucial role in particulate organic carbon degradation, but the impact of depth-dependent microbial dynamics on ocean-scale particulate carbon fluxes is poorly understood. Here we scale-up essential features of particle-associated microbial dynamics to understand the large-scale vertical carbon flux in the ocean. Our model provides mechanistic insight into the microbial contribution to the particulate organic carbon flux profile. We show that the enhanced transfer of carbon to depth can result from populations struggling to establish colonies on sinking particles due to diffusive nutrient loss, cell detachment, and mortality. These dynamics are controlled by the interaction between multiple biotic and abiotic factors. Accurately capturing particle-microbe interactions is essential for predicting variability in large-scale carbon cycling.

Biogeographical and seasonal dynamics of the marine Roseobacter community and ecological links to DMSP-producing phytoplankton.

Ecological interactions between marine bacteria and phytoplankton play a pivotal role in governing the ocean's major biogeochemical cycles. Among these, members of the marine Roseobacter Group (MRG) can establish mutualistic relationships with phytoplankton that are, in part, maintained by exchanges of the organosulfur compound, dimethylsulfoniopropionate (DMSP). Yet most of what is known about these interactions has been derived from culture-based laboratory studies. To investigate temporal and spatial co-occurrence patterns between members of the MRG and DMSP-producing phytoplankton we analysed 16S and 18S rRNA gene amplicon sequence variants (ASVs) derived from 5 years of monthly samples from seven environmentally distinct Australian oceanographic time-series. The MRG and DMSP-producer communities often displayed contemporaneous seasonality, which was greater in subtropical and temperate environments compared to tropical environments. The relative abundance of both groups varied latitudinally, displaying a poleward increase, peaking (MRG at 33% of total bacteria, DMSP producers at 42% of eukaryotic phototrophs) during recurrent spring-summer phytoplankton blooms in the most temperate site (Maria Island, Tasmania). Network analysis identified 20,140 significant positive correlations between MRG ASVs and DMSP producers and revealed that MRGs exhibit significantly stronger correlations to high DMSP producers relative to other DMSP-degrading bacteria (Pelagibacter, SAR86 and Actinobacteria). By utilising the power of a continental network of oceanographic time-series, this study provides in situ confirmation of interactions found in laboratory studies and demonstrates that the ecological dynamics of an important group of marine bacteria are shaped by the production of an abundant and biogeochemically significant organosulfur compound.

A High-Throughput Assay for Quantifying Phenotypic Traits of Microalgae.

High-throughput methods for phenotyping microalgae are in demand across a variety of research and commercial purposes. Many microalgae can be readily cultivated in multi-well plates for experimental studies which can reduce overall costs, while measuring traits from low volume samples can reduce handling. Here we develop a high-throughput quantitative phenotypic assay (QPA) that can be used to phenotype microalgae grown in multi-well plates. The QPA integrates 10 low-volume, relatively high-throughput trait measurements (growth rate, cell size, granularity, chlorophyll a, neutral lipid content, silicification, reactive oxygen species accumulation, and photophysiology parameters: ETRmax, Ik, and alpha) into one workflow. We demonstrate the utility of the QPA on Thalassiosira spp., a cosmopolitan marine diatom, phenotyping six strains in a standard nutrient rich environment (f/2 media) using the full 10-trait assay. The multivariate phenotypes of strains can be simplified into two dimensions using principal component analysis, generating a trait-scape. We determine that traits show a consistent pattern when grown in small volume compared to more typical large volumes. The QPA can thus be used for quantifying traits across different growth environments without requiring exhaustive large-scale culturing experiments, which facilitates experiments on trait plasticity. We confirm that this assay can be used to phenotype newly isolated diatom strains within 4 weeks of isolation. The QPA described here is highly amenable to customisation for other traits or unicellular taxa and provides a framework for designing high-throughput experiments. This method will have applications in experimental evolution, modelling, and for commercial applications where screening of phytoplankton traits is of high importance.

The evolution of trait correlations constrains phenotypic adaptation to high CO2 in a eukaryotic alga.

Microbes form the base of food webs and drive biogeochemical cycling. Predicting the effects of microbial evolution on global elemental cycles remains a significant challenge due to the sheer number of interacting environmental and trait combinations. Here, we present an approach for integrating multivariate trait data into a predictive model of trait evolution. We investigated the outcome of thousands of possible adaptive walks parameterized using empirical evolution data from the alga Chlamydomonas exposed to high CO2. We found that the direction of historical bias (existing trait correlations) influenced both the rate of adaptation and the evolved phenotypes (trait combinations). Critically, we use fitness landscapes derived directly from empirical trait values to capture known evolutionary phenomena. This work demonstrates that ecological models need to represent both changes in traits and changes in the correlation between traits in order to accurately capture phytoplankton evolution and predict future shifts in elemental cycling.

Mechanistic model of nutrient uptake explains dichotomy between marine oligotrophic and copiotrophic bacteria.

Marine bacterial diversity is immense and believed to be driven in part by trade-offs in metabolic strategies. Here we consider heterotrophs that rely on organic carbon as an energy source and present a molecular-level model of cell metabolism that explains the dichotomy between copiotrophs-which dominate in carbon-rich environments-and oligotrophs-which dominate in carbon-poor environments-as the consequence of trade-offs between nutrient transport systems. While prototypical copiotrophs, like Vibrios, possess numerous phosphotransferase systems (PTS), prototypical oligotrophs, such as SAR11, lack PTS and rely on ATP-binding cassette (ABC) transporters, which use binding proteins. We develop models of both transport systems and use them in proteome allocation problems to predict the optimal nutrient uptake and metabolic strategy as a function of carbon availability. We derive a Michaelis-Menten approximation of ABC transport, analytically demonstrating how the half-saturation concentration is a function of binding protein abundance. We predict that oligotrophs can attain nanomolar half-saturation concentrations using binding proteins with only micromolar dissociation constants and while closely matching transport and metabolic capacities. However, our model predicts that this requires large periplasms and that the slow diffusion of the binding proteins limits uptake. Thus, binding proteins are critical for oligotrophic survival yet severely constrain growth rates. We propose that this trade-off fundamentally shaped the divergent evolution of oligotrophs and copiotrophs.

Understanding water and energy fluxes in the Amazonia: Lessons from an observation-model intercomparison.

Tropical forests are an important part of global water and energy cycles, but the mechanisms that drive seasonality of their land-atmosphere exchanges have proven challenging to capture in models. Here, we (1) report the seasonality of fluxes of latent heat (LE), sensible heat (H), and outgoing short and longwave radiation at four diverse tropical forest sites across Amazonia-along the equator from the Caxiuanã and Tapajós National Forests in the eastern Amazon to a forest near Manaus, and from the equatorial zone to the southern forest in Reserva Jaru; (2) investigate how vegetation and climate influence these fluxes; and (3) evaluate land surface model performance by comparing simulations to observations. We found that previously identified failure of models to capture observed dry-season increases in evapotranspiration (ET) was associated with model overestimations of (1) magnitude and seasonality of Bowen ratios (relative to aseasonal observations in which sensible was only 20%-30% of the latent heat flux) indicating model exaggerated water limitation, (2) canopy emissivity and reflectance (albedo was only 10%-15% of incoming solar radiation, compared to 0.15%-0.22% simulated), and (3) vegetation temperatures (due to underestimation of dry-season ET and associated cooling). These partially compensating model-observation discrepancies (e.g., higher temperatures expected from excess Bowen ratios were partially ameliorated by brighter leaves and more interception/evaporation) significantly biased seasonal model estimates of net radiation (Rn ), the key driver of water and energy fluxes (LE ~ 0.6 Rn and H ~ 0.15 Rn ), though these biases varied among sites and models. A better representation of energy-related parameters associated with dynamic phenology (e.g., leaf optical properties, canopy interception, and skin temperature) could improve simulations and benchmarking of current vegetation-atmosphere exchange and reduce uncertainty of regional and global biogeochemical models.

A unified theory for organic matter accumulation.

Organic matter constitutes a key reservoir in global elemental cycles. However, our understanding of the dynamics of organic matter and its accumulation remains incomplete. Seemingly disparate hypotheses have been proposed to explain organic matter accumulation: the slow degradation of intrinsically recalcitrant substrates, the depletion to concentrations that inhibit microbial consumption, and a dependency on the consumption capabilities of nearby microbial populations. Here, using a mechanistic model, we develop a theoretical framework that explains how organic matter predictably accumulates in natural environments due to biochemical, ecological, and environmental factors. Our framework subsumes the previous hypotheses. Changes in the microbial community or the environment can move a class of organic matter from a state of functional recalcitrance to a state of depletion by microbial consumers. The model explains the vertical profile of dissolved organic carbon in the ocean and connects microbial activity at subannual timescales to organic matter turnover at millennial timescales. The threshold behavior of the model implies that organic matter accumulation may respond nonlinearly to changes in temperature and other factors, providing hypotheses for the observed correlations between organic carbon reservoirs and temperature in past earth climates.

DMSP synthesis genes distinguish two types of DMSP producer phenotypes.

Dimethylsulfoniopropionate (DMSP) is an important organic carbon and sulfur source in the surface ocean that fuels microbial activity and significantly impacts Earth's climate. After three decades of research, the cellular role(s) of DMSP and environmental drivers of production remain enigmatic. Recent work suggests that cellular DMSP concentrations, and changes in these concentrations in response to environmental stressors, define two major groups of DMSP producers: high DMSP producers that contain ≥ 50 mM intracellular DMSP and low DMSP producers that contain < 50 mM. Here we show that two recently described DMSP synthesis genes (DSYB and TpMT2) may differentiate these two DMSP phenotypes. A survey of prokaryotic and eukaryotic isolates found a significant correlation between the presence of DSYB and TpMT2 genes and previous measurements of high and low DMSP concentrations, respectively. Phylogenetic analysis demonstrated that DSYB and TpMT2 form two distinct clades. DSYB and TpMT2 were also found to be globally abundant in in situ surface communities, and their taxonomic annotations were similar to those observed for isolates. The strong correlation of the DSYB and TpMT2 synthesis genes with high and low producer phenotypes establishes a foundation for direct quantification of DMSP producers, enabling significantly improved predictions of DMSP in situ.

Multivariate trait analysis reveals diatom plasticity constrained to a reduced set of biological axes.

Trait-based approaches to phytoplankton ecology have gained traction in recent decades as phenotypic traits are incorporated into ecological and biogeochemical models. Here, we use high-throughput phenotyping to explore both intra- and interspecific constraints on trait combinations that are expressed in the cosmopolitan marine diatom genus Thalassiosira. We demonstrate that within Thalassiosira, phenotypic diversity cannot be predicted from genotypic diversity, and moreover, plasticity can create highly divergent phenotypes that are incongruent with taxonomic grouping. Significantly, multivariate phenotypes can be represented in reduced dimensional space using principal component analysis with 77.7% of the variance captured by two orthogonal axes, here termed a 'trait-scape'. Furthermore, this trait-scape can be recovered with a reduced set of traits. Plastic responses to the new environments expanded phenotypic trait values and the trait-scape, however, the overall pattern of response to the new environments was similar between strains and many trait correlations remained constant. These findings demonstrate that trait-scapes can be used to reveal common constraints on multi-trait plasticity in phytoplankton with divergent underlying phenotypes. Understanding how to integrate trait correlational constraints and trade-offs into theoretical frameworks like biogeochemical models will be critical to predict how microbial responses to environmental change will impact elemental cycling now and into the future.

Microbial evolutionary strategies in a dynamic ocean.

Marine microbes form the base of ocean food webs and drive ocean biogeochemical cycling. Yet little is known about the ability of microbial populations to adapt as they are advected through changing conditions. Here, we investigated the interplay between physical and biological timescales using a model of adaptation and an eddy-resolving ocean circulation climate model. Two criteria were identified that relate the timing and nature of adaptation to the ratio of physical to biological timescales. Genetic adaptation was impeded in highly variable regimes by nongenetic modifications but was promoted in more stable environments. An evolutionary trade-off emerged where greater short-term nongenetic transgenerational effects (low-γ strategy) enabled rapid responses to environmental fluctuations but delayed genetic adaptation, while fewer short-term transgenerational effects (high-γ strategy) allowed faster genetic adaptation but inhibited short-term responses. Our results demonstrate that the selective pressures for organisms within a single water mass vary based on differences in generation timescales resulting in different evolutionary strategies being favored. Organisms that experience more variable environments should favor a low-γ strategy. Furthermore, faster cell division rates should be a key factor in genetic adaptation in a changing ocean. Understanding and quantifying the relationship between evolutionary and physical timescales is critical for robust predictions of future microbial dynamics.

Evidence for contrasting roles of dimethylsulfoniopropionate production in Emiliania huxleyi and Thalassiosira oceanica.

Dimethylsulfoniopropionate (DMSP) is a globally abundant marine metabolite and a significant source of organic carbon and sulfur for marine microbial ecosystems with the potential to influence climate regulation. However, the physiological function of DMSP has remained enigmatic for >30 yr. Recent insight suggests that there are different physiological roles for DMSP based on the cellular DMSP concentrations in producers. Differential production of DMSP was tested with multiple physiological experiments that altered nitrate availability, salinity and temperature to create stressed growth and target different metabolic conditions in Emiliania huxleyi, a high DMSP producer and Thalassiosira oceanica, a low DMSP producer. Emiliania huxleyi intracellular DMSP did not respond to metabolically imbalanced conditions, while Thalassiosira oceanica intracellular DMSP was significantly correlated to stressed growth rate across all conditions tested and exhibited a plastic response on a timescale of hours in nonsteady-state. The previous assumption that proposed DMSP mechanism(s) can be universally applied to all producers is shown to be unlikely. Rather, two distinct ecological roles for DMSP likely exist that differ by producer type, where: (1) the primary role of DMSP in high producers is a constitutive compatible solute; and (2) DMSP production in low producers is a finely tuned stress response.