Biology subjects

Armbrust, E. V.

Publications and source records attributed to Armbrust, E. V..

11 recordsLinked to original sources

bioRxiv2021

A flexible Bayesian approach to estimating size-structured matrix population models

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 rate parameters of microbial populations by mechanistically describing changes in microbial cell size distributions over time. And yet, the construction, analysis, and biological interpretation of these models are underdeveloped, as current implementations do not adequately constrain or assess the biological feasibility of parameter values, leading to inference which may provide a good fit to observed size distributions but does not necessarily reflect realistic physiological dynamics. Here we present a flexible Bayesian extension of size-structured MPMs for testing underlying assumptions describing the dynamics of a marine phytoplankton population over the day-night cycle. Our Bayesian framework takes prior scientific knowledge into account and generates biologically interpretable results. Using data from an exponentially growing laboratory culture of the cyanobacterium Prochlorococcus, we herein demonstrate the performance improvements of our approach over current models and isolate previously ignored biological processes, such as respiratory and exudative carbon losses, as critical parameters for the modeling of microbial population dynamics. The results demonstrate that this modeling framework can provide deeper insights into microbial population dynamics provided by flow-cytometry time-series data. Author summaryIdentifying the growth and population dynamics of marine microorganisms in their natural habitat is crucial to understanding the flow of carbon in the oceans but remains a grand challenge due to the invasive nature of current measurement methods. As time-series observations of population size structure have become more commonplace in aquatic environments, matrix population models (MPMs), which aim to mechanistically describe the change in size structure of these populations over time, have gained in popularity over the last decade. However, the underlying assumptions and behavior of MPMs have not been adequately scrutinized, and parameter values are difficult to interpret biologically, leading to inference that may not reflect plausible physiological dynamics. Here, we develop a Bayesian extension of the MPM framework to examine biological assumptions, improve interpretability of model output, and account for additional biological processes. We evaluated the performance of our models on a publicly available dataset of laboratory experiment time-series measurements of the cyanobacterium Prochlorococcus, Earths most abundant photosynthetic organisms, demonstrated the performance improvements of our approach over current models, and isolated previously ignored respiratory and exudative carbon losses as critical parameters for the modeling of microbial population dynamics.

microbiology↗

bioRxiv2021

Diel population dynamics and mortality of Prochlorococcus in the North Pacific Subtropical Gyre

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 function as the primary top-down factor despite high standing viral particle densities while identifying the potential for light-dependent viral traits and non-canonical loss factors to shape the structure and function of marine microbial communities.

ecology↗

bioRxiv2021

Nitrogen fixation in mesoscale eddies of the North Pacific Subtropical Gyre: patterns and mechanisms

1.Mesoscale eddies have been shown to support elevated dinitrogen (N2) fixation rates (NFRs) and abundances of N2-fixing microorganisms (diazotrophs), but the mechanisms underlying these observations are not well understood. We explored relationships among NFRs and cyanobacterial diazotroph abundances in eddy pairs of opposite polarity sampled in the North Pacific Subtropical Gyre and compared our observations to seasonal trends from the Hawaii Ocean Time-series (HOT) program. Consistent with previous reports, we found that NFRs were anomalously high for this region (up to 3.7-fold above previous monthly HOT observations) in the centers of the sampled anticyclones, coinciding with elevated abundances of Crocosphaera in the summertime. We then coupled our field-based observations, together with transcriptomic analyses of nutrient stress marker genes and ecological models, to evaluate potential mechanisms controlling diazotroph abundance and activity at the mesoscale. Specifically, we evaluated the role of biological (via estimates of growth and grazing rates) and physical controls on populations of Crocosphaera, Trichodesmium, and diatom symbionts. Our results suggest that increased Crocosphaera abundances associated with summertime anticyclones resulted from the alleviation of phosphate limitation, allowing cells to grow at rates exceeding grazing losses. In contrast, distributions of larger, buoyant taxa (Trichodesmium and diatom symbionts) appeared less affected by eddy-driven biological controls. Instead, they appeared driven by physical dynamics along frontal boundaries that separate cyclonic and anticyclonic eddies. Together, the interplay of eddy-specific changes in bottom-up control, top-down control, and the physical accumulation of cells likely explains the elevated diazotroph abundances and NFRs associated with anticyclones and eddy fronts.

ecology↗

bioRxiv2021

Simons Collaborative Marine Atlas Project (Simons CMAP): an open-source portal to share, visualize and analyze ocean data

Simons Collaborative Marine Atlas Project (Simons CMAP) is an open-source data portal that interconnects large, complex, and diverse public data sets currently dispersed in different formats across different Oceanography discipline-specific databases. Simons CMAP is designed to streamline the retrieval of custom subsets of data, the generation of data visualizations, and the analyses of diverse data, thus expanding the power of these potentially underutilized data sets for cross-disciplinary studies of ocean processes. We describe a unified architecture that allows numerical model outputs, satellite products, and field observations to be readily shared, mined, and integrated regardless of data set size or resolution. A current focus of Simons CMAP is integration of physical, chemical, and biological data sets essential for characterizing the biogeography of key marine microbes across ocean basins and seasonal cycles. Using a practical example, we demonstrate how our unifying data harmonization plans significantly simplifies and allows for systematic data integration across all Simons CMAP data sets.

ecology↗

bioRxiv2021

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

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 introduce a machine learning model that can predict the in situ nutritional 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 status. 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. In addition, metatranscriptomic data from ship-board incubation experiments revealed that abundant mixotrophic prymnesiophytes from the oligotrophic North Pacific subtropical gyre rapidly remodelled their transcriptome to enhance photosynthesis when supplied with limiting nutrients. Coupling the technique introduced here with experiments designed to reveal the mechanisms driving mixotroph physiology is a promising approach for understanding the ecology of mixotrophic populations in the natural environment. Significance statementMixotrophy is a ubiquitous nutritional strategy in marine ecosystems. Although our understanding of the distribution and abundance of mixotrophic plankton has improved significantly, the functional roles of mixotrophs are difficult to pinpoint, as mixotroph nutritional strategies are flexible and form a continuum between heterotrophy and phototrophy. We employ a machine learning-driven metatranscriptomic technique to assess the nutritional strategies of abundant planktonic populations in situ and demonstrate that mixotrophic populations play varying functional roles along physico-chemical gradients in the North Pacific Ocean, revealing a degree of physiological plasticity unique to aquatic mixotrophs. Our results highlight mechanisms that may dictate the flow of biogeochemical elements and the ecology of the North Pacific Ocean, one of the largest biogeographical provinces on Earth.

ecology↗

bioRxiv2020

Marine community metabolomes carry fingerprints of phytoplankton community composition

Phytoplankton transform inorganic carbon into thousands of biomolecules that represent an important pool of fixed carbon, nitrogen, and sulfur in the surface ocean. Metabolite production differs between phytoplankton, and the flux of these molecules through the microbial food web depends on compound-specific bioavailability to members of a wider microbial community. Yet relatively little is known about the diversity or concentration of metabolites within marine plankton. Here we compare 313 polar metabolites in 21 cultured phytoplankton species and in natural planktonic communities across environmental gradients to show that bulk community metabolomes reflect chemical composition of the phytoplankton community. We also show that groups of compounds have similar patterns across space and taxonomy suggesting that the concentrations of these compounds in the environment are controlled by similar sources and sinks. We quantify several compounds in the surface ocean that represent substantial understudied pools of labile carbon. For example, the N-containing metabolite homarine was up to 3% of particulate carbon and is produced in high concentrations by cultured Synechococcus, and S-containing gonyol accumulated up to 2.5 nM in surface particles and likely originates from dinoflagellates. Our results show that phytoplankton composition directly shapes the carbon composition of the surface ocean. Our findings suggest that in order to access these pools of bioavailable carbon, the wider microbial community must be adapted to phytoplankton community composition. IMPORTANCEMicroscopic 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. Here we explore the abundance and diversity of small biomolecules in planktonic communities across ecological gradients in the North Pacific and within 21 cultured phytoplankton species. Our work demonstrates that phytoplankton diversity is an important determinant of the chemical composition of the highly bioavailable pool of organic carbon in the ocean, and we highlight understudied yet abundant compounds in both the environment and cultured organisms. These findings add to understanding of how the chemical makeup of phytoplankton shapes marine microbial communities where the ability to sense and use biomolecules depends on the chemical structure.

ecology↗

bioRxiv2020

A plastid antiporter as a bioindicator of Thalassiosira pseudonana resilience

Acidification of the ocean due to high atmospheric CO2 levels may increase the resilience of diatoms causing dramatic shifts in abiotic and biotic cycles with lasting implications on marine ecosystems. Here, we report a potential bioindicator of a shift in the resilience of a coastal and centric model diatom Thalassiosira pseudonana under elevated CO2. Specifically, we have discovered, through EGFP-tagging, a plastid membrane localized putative Na+(K+)/H+ antiporter that is significantly upregulated at > 800 ppm CO2, with a potentially important role in maintaining pH homeostasis. Notably, transcript abundance of this antiporter gene was relatively low and constant over the diel cycle under contemporary CO2 conditions. In future acidified oceanic conditions, dramatic oscillations of >10-fold change between nighttime (high) and daytime (low) in transcript abundances of the antiporter gene were associated with increased resilience of T. pseudonana. By analyzing metatranscriptomic data from the Tara Oceans project, we demonstrate that phylogenetically diverse diatoms express homologs of this antiporter across the globe. We propose that the differential between night- and daytime transcript levels of the antiporter could serve as a bioindicator of a shift in the resilience of diatoms in response to high CO2 conditions in marine environments.

systems biology↗

bioRxiv2020

A Kernel-Based Change Detection Method to Map Shifts in Phytoplankton Communities Measured by Flow Cytometry

O_LIAutomated, ship-board flow cytometers provide high-resolution maps of phytoplankton composition over large swaths of the worlds oceans. They therefore pave the way for understanding how environmental conditions shape community structure. Identification of community changes along a cruise transect commonly segments the data into distinct regions. However, existing segmentation methods are generally not applicable to flow cytometry data, as this data is recorded as "point cloud" data, with hundreds or thousands of particles measured during each time interval. Moreover, nonparametric segmentation methods that do not rely on prior knowledge of the number of species, are desirable to map community shifts. C_LIO_LIWe present CytoSegmenter, a kernel-based change-point estimation method for segmenting point cloud data that does not rely on parametric assumptions on the data distributions. Our method relies on a Hilbertian embedding of point clouds that allows us to work with point cloud data similarly to vectorial data. The change-point locations can be found using an efficient dynamic programming algorithm. The method can be used to automatically segment long series of underway flow cytometry data. C_LIO_LIThrough an analysis of 12 cruises, we demonstrate that CytoSegmenter allows us to locate abrupt changes in phytoplankton community structure. We show that the changes in community structure generally coincide with changes in the temperature and salinity of the ocean. We also illustrate how the main parameter of CytoSegmenter can be easily calibrated using limited auxiliary annotated data. C_LIO_LICytoSegmenter is publicly available and implemented in the programming language Python. The method is generally applicable for segmenting series of point cloud data from any domain. Moreover, it readily scales to thousands of point clouds, each containing thousands of points. In the context of underway flow cytometry data, it does not require prior clustering of particles to define taxa labels, eliminating a potential source of error. This represents an important advance in automating the analysis of large datasets now emerging in biological oceanography and other fields. It also allows for the approach to potentially be applied during research cruises. C_LI

ecology↗

bioRxiv2020

Genome-scale metabolic model of the diatom Thalassiosira pseudonana highlights the importance of nitrogen and sulfur metabolism in redox balance

Diatoms are unicellular photosynthetic algae known to secrete organic matter that fuels secondary production in the ocean, though our knowledge of how their physiology impacts the character of dissolved organic matter remains limited. Like all photosynthetic organisms, their use of light for energy and reducing power creates the challenge of avoiding cellular damage. To better understand the interplay between redox balance and organic matter secretion, we reconstructed a genome-scale metabolic model of Thalassiosira pseudonana strain CCMP 1335, a model for diatom molecular biology and physiology, with a 60-year history of studies. The model simulates the metabolic activities of 1,432 genes via a network of 2,792 metabolites produced through 6,079 reactions distributed across six subcellular compartments. Growth was simulated under different steady-state light conditions (5-200 mol photons m-2 s-1) and in a batch culture progressing from exponential growth to nitrate-limitation and nitrogen-starvation. We used the model to examine the dissipation of reductants generated through light-dependent processes and found that when available, nitrate assimilation is an important means of dissipating reductants in the plastid; under nitrate-limiting conditions, sulfate assimilation plays a similar role. The use of either nitrate or sulfate uptake to balance redox reactions leads to the secretion of distinct organic nitrogen and sulfur compounds. Such compounds can be accessed by bacteria in the surface ocean. The model of the diatom Thalassiosira pseudonana provides a mechanistic explanation for the production of ecologically and climatologically relevant compounds that may serve as the basis for intricate, cross-kingdom microbial networks. Diatom metabolism has an important influence on global biogeochemistry; metabolic models of marine microorganisms link genes to ecosystems and may be key to integrating molecular data with models of ocean biogeochemistry.

systems biology↗

bioRxiv2020

Community-scale Synchronization and Temporal Partitioning of Gene Expression, Metabolism, and Lipid Biosynthesis in Oligotrophic Ocean Surface Waters

Sunlight drives daily rhythms of photosynthesis, growth, and division of photoautotrophs throughout the surface oceans. However, the cascading impacts of oscillatory light input on diverse microbial communities and community-scale metabolism remains unclear. Here we use an unsupervised machine learning approach to show that a small number of diel archetypes can explain pervasive periodic dynamics amongst more than 65,000 distinct time series, including transcriptional activity, macromolecules, lipids, and metabolites from the North Pacific Subtropical Gyre. Overall, we find evidence for synchronous timing of carbon-cycle gene expression that underlie daily oscillations in the concentrations of particulate organic carbon. In contrast, we find evidence of asynchronous timing in gene transcription related to nitrogen metabolism and related metabolic processes consistent with temporal niche partitioning amongst microorganisms in the bacterial and eukaryotic domains.

ecology↗

bioRxiv2020

Diel Oscillations of Particulate Metabolites Reflect Synchronized Microbial Activity in the North Pacific Subtropical Gyre

Light is the primary input of energy into the sunlit ocean, driving daily oscillations in metabolism of primary producers. The consequences of this solar forcing have implications for the whole microbial community, yet in situ measurements of metabolites, direct products of cellular activity, over the diel cycle are scarce. We evaluated community-level biochemical consequences of diel oscillations in the North Pacific Subtropical Gyre by quantifying 79 metabolites in particulate organic matter in surface waters every four hours over eight days. Total particulate metabolite concentration peaked at dusk, even when normalized to biomass estimates. The concentrations of 70% of individual metabolites exhibited 24-hour periodicity. Despite the diverse organisms that use them, primary metabolites involved in anabolic processes and redox maintenance had significant 24-hour periodicity. Osmolytes exhibited the largest diel oscillations, implying rapid turnover and metabolic roles beyond cell turgor maintenance. Metatranscriptome analysis revealed the taxa involved in production and consumption of some metabolites, including the osmolyte trehalose. This compound displayed the largest diel oscillations in abundance and was likely produced by the nitrogen-fixing cyanobacterium Crocosphaera for energy storage. These findings demonstrate that paired measurements of particulate metabolites and transcripts resolve strategies microbes use to manage daily energy and redox oscillations.

ecology↗