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.

Diversity and distribution of benthic dinoflagellates in Tonga include the potentially harmful genera Gambierdiscus and Fukuyoa.

Benthic dinoflagellates that can cause illness, such as ciguatera poisoning (CP), are prevalent around the Pacific but are poorly described in many locations. This study represents the first ecological assessment of benthic harmful algae species in the Kingdom of Tonga, a country where CP occurs regularly. Surveys were conducted in June 2016 in the Tongatapu island group, and in June 2017 across three island groups: Ha'apai, Vava'u, and Tongatapu. Shallow subtidal coastal habitats were investigated by measuring water quality parameters and conducting quadrat surveys. Microalgae samples were collected using either macrophyte collection or the artificial substrate method. Benthic dinoflagellates (Gambierdiscus and/or Fukuyoa, Ostreopsis, and Prorocentrum) were counted using light microscopy, followed by molecular analyses (real-time PCR in 2016 and high throughput sequencing (metabarcoding) in 2017) to identify Gambierdiscus and Fukuyoa to species level. Six species were detected from the Tongatapu island group in 2016 (G. australes, G. carpenteri, G. honu, G. pacificus, F. paulensis, and F. ruetzleri) using real-time PCR. Using the metabarcoding approach in 2017, a total of eight species (G. australes, G. carpenteri, G. honu, G. pacificus, G. cheloniae, G. lewisii, G. polynesiensis, and F. yasumotoi) were detected. Species were detected in mixed assemblages of up to six species, with G. pacificus and G. carpenteri being the most frequently observed. Ha'apai had the highest diversity with eight species detected, which identifies this area as a Gambierdiscus diversity 'hotspot'. Vava'u and Tongatapu had three and six species found respectively. Gambierdiscus polynesiensis, a described ciguatoxin producer and proposed causative agent of CP was found only in Ha'apai and Vava'u in 2017, but not in Tongatapu in either year. Ostreopsis spp. and Prorocentrum spp. were also frequently observed, with Prorocentrum most abundant at the majority of sites. In 2016, the highest number of Gambierdiscus and/or Fukuyoa cells were observed on seagrass (Halodule uninervis) from Sopu, Tongatapu. In 2017, the highest numbers of Gambierdiscus and/or Fukuyoa from artificial substrate samples were recorded in the Halimeda dominant habitat at Neiafu Tahi, Vava'u, a low energy site. This raised the question of the effect of wave motion or currents on abundance measurements from artificial substrates. Differences in detection were noticed between macrophytes and artificial substrates, with higher numbers of species found on artificial substrates. This study provides a baseline of benthic dinoflagellate distributions and diversity for Tonga that may be used for future studies and the development of monitoring programmes.

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.

Predictability of thermal fluctuations influences functional traits of a cosmopolitan marine diatom.

Evolutionary theory predicts that organismal plasticity should evolve in environments that fluctuate regularly. However, in environments that fluctuate less predictably, plasticity may be constrained because environmental cues become less reliable for expressing the optimum phenotype. Here, we examine how the predictability of +5°C temperature fluctuations impacts the phenotype of the marine diatom Thalassiosira pseudonana. Thermal regimes were informed by temperatures experienced by microbes in an ocean simulation and featured regular or irregular temporal sequences of fluctuations that induced mild physiological stress. Physiological traits (growth, cell size, complexity and pigmentation) were quantified at the individual cell level using flow cytometry. Changes in cellular complexity emerged as the first impact of predictability after only 8-11 days, followed by deleterious impacts on growth on days 13-16. Specifically, cells with a history of irregular fluctuation exposure exhibited a 50% reduction in growth compared with the stable reference environment, while growth was 3-18 times higher when fluctuations were regular. We observed no evidence of heat hardening (increasingly positive growth) with recurrent fluctuations. This study demonstrates that unpredictable temperature fluctuations impact this cosmopolitan diatom under ecologically relevant time frames, suggesting shifts in environmental stochasticity under a changing climate could have widespread consequences among ocean primary producers.

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.

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.

Molecular Identification of Gambierdiscus and Fukuyoa (Dinophyceae) from Environmental Samples.

Ciguatera Fish Poisoning (CFP) is increasing across the Pacific and the distribution of the causative dinoflagellates appears to be expanding. Subtle differences in thecal plate morphology are used to distinguish dinoflagellate species, which are difficult to determine using light microscopy. For these reasons we sought to develop a Quantitative PCR assay that would detect all species from both Gambierdiscus and Fukuyoa genera in order to rapidly screen environmental samples for potentially toxic species. Additionally, a specific assay for F. paulensis was developed as this species is of concern in New Zealand coastal waters. Using the assays we analyzed 31 samples from three locations around New Zealand and the Kingdom of Tonga. Fourteen samples in total were positive for Gambierdiscus/Fukuyoa and two samples were also positive using the F. paulensis assay. Samples from the Kermadec Islands were further characterized using high-throughput sequencing metabarcoding. The majority of reads corresponded to Gambierdiscus species with three species identified at all sites (G. australes, G. honu and G. polynesiensis). This is the first confirmed identification of G. polynesiensis, a known ciguatoxin producer, in New Zealand waters. Other known toxin-producing genera were also detected, included Alexandrium, Amphidinium, Azadinium, Dinophysis, Ostreopsis, and Prorocentrum.