Adaptive Evolution of Phosphorus Metabolism in Prochlorococcus

Adaptation to a limiting element involves mitigation of multiple elemental imbalances

About 20 elements underlie biology and thus constrain biomass production. Recent systems-level observations indicate that altered supply of one element impacts the processing of most elements encompassing an organism (i.e. ionome). Little is known about the evolutionary tendencies of ionomes as populations adapt to distinct biogeochemical environments. We evolved the bacterium Serratia marcescens under five conditions (i.e. low carbon, nitrogen, phosphorus, iron or manganese) that limited the yield of the ancestor compared with replete medium, and measured the concentrations and use efficiency of these five, and five other elements. Both physiological responses of the ancestor, as well as evolutionary responses of descendants to experimental environments involved changes in the content and use efficiencies of the limiting element, and several others. Differences in coefficients of variation in elemental contents based on biological functions were evident, with those involved in biochemical building (C, N, P, S) varying least, followed by biochemical balance (Ca, K, Mg, Na), and biochemical catalysis (Fe, Mn). Finally, descendants evolved to mitigate elemental imbalances evident in the ancestor in response to limiting conditions. Understanding the tendencies of such ionomic responses will be useful to better forecast biological responses to geochemical changes.

A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series

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.

A metabolic modeling platform for the computation of microbial ecosystems in time and space (COMETS)

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are emerging as a valuable avenue for predicting, understanding and designing microbial communities. Computation of microbial ecosystems in time and space (COMETS) extends dynamic flux balance analysis to generate simulations of multiple microbial species in molecularly complex and spatially structured environments. Here we describe how to best use and apply the most recent version of COMETS, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, evolutionary dynamics and extracellular enzyme activity modules. In addition to a command-line option, COMETS includes user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, as well as comprehensive documentation and tutorials. This protocol provides a detailed guideline for installing, testing and applying COMETS to different scenarios, generating simulations that take from a few minutes to several days to run, with broad applicability to microbial communities across biomes and scales.

Elucidation of trophic interactions in an unusual single-cell nitrogen-fixing symbiosis using metabolic modeling

Marine nitrogen-fixing microorganisms are an important source of fixed nitrogen in oceanic ecosystems. The colonial cyanobacterium Trichodesmium and diatom symbionts were thought to be the primary contributors to oceanic N₂ fixation until the discovery of the unusual uncultivated symbiotic cyanobacterium UCYN-A (Candidatus Atelocyanobacterium thalassa). UCYN-A has atypical metabolic characteristics lacking the oxygen-evolving photosystem II, the tricarboxylic acid cycle, the carbon-fixation enzyme RuBisCo and de novo biosynthetic pathways for a number of amino acids and nucleotides. Therefore, it is obligately symbiotic with its single-celled haptophyte algal host. UCYN-A receives fixed carbon from its host and returns fixed nitrogen, but further insights into this symbiosis are precluded by both UCYN-A and its host being uncultured. In order to investigate how this syntrophy is coordinated, we reconstructed bottom-up genome-scale metabolic models of UCYN-A and its algal partner to explore possible trophic scenarios, focusing on nitrogen fixation and biomass synthesis. Since both partners are uncultivated and only the genome sequence of UCYN-A is available, we used the phylogenetically related Chrysochromulina tobin as a proxy for the host. Through the use of flux balance analysis (FBA), we determined the minimal set of metabolites and biochemical functions that must be shared between the two organisms to ensure viability and growth. We quantitatively investigated the metabolic characteristics that facilitate daytime N₂ fixation in UCYN-A and possible oxygen-scavenging mechanisms needed to create an anaerobic environment to allow nitrogenase to function. This is the first application of an FBA framework to examine the tight metabolic coupling between uncultivated microbes in marine symbiotic communities and provides a roadmap for future efforts focusing on such specialized systems.

Reduction of dinitrogen gas to biologically useful forms via nitrogen fixation is a key component of the biogeochemical cycle. In the marine environment, the cyanobacteria UCYN-A (Candidatus Atelocyanobacterium thalassa) has been found to be a primary contributor to biological nitrogen fixation at a global scale. UCYN-A exhibits a highly streamlined genome which lacks genes coding for essential cyanobacterial processes such as the energy-generating TCA cycle, oxygen-producing photosystem II, the carbon-fixing RuBisCo and de novo production pathways for numerous amino acids and nucleotides. Thus, it exists in a symbiosis with unicellular planktonic algae where it exchanges fixed nitrogen for fixed carbon with its host. However, both UCYN-A and its symbiotic partner remain uncultured under laboratory conditions. This necessitates implementing a computational approach to glean insights into UCYN-A’s unique physiology and metabolic processes governing the symbiotic association. To this end, we develop a constraints-based framework that infers all possible trophic scenarios consistent with the observed data. Possible mechanisms employed by UCYN-A to accommodate diazotrophy with daytime carbon fixation by the host (i.e., two mutually incompatible processes) are also elucidated. We envision that the developed framework using UCYN-A and its algal host will be used as a roadmap and motivate the study of similarly unique microbial systems in the future.

The maximum growth rate hypothesis is correct for eukaryotic photosynthetic organisms, but not cyanobacteria

The (maximum) growth rate (µ_max ) hypothesis predicts that cellular and tissue phosphorus (P) concentrations should increase with increasing growth rate, and RNA should also increase as most of the P is required to make ribosomes. Using published data, we show that though there is a strong positive relationship between the µ_max of all photosynthetic organisms and their P content (% dry weight), leading to a relatively constant P productivity, the relationship with RNA content is more complex. In eukaryotes there is a strong positive relationship between µ_max and RNA content expressed as % dry weight, and RNA constitutes a relatively constant 25% of total P. In prokaryotes the rRNA operon copy number is the important determinant of the amount of RNA present in the cell. The amount of phospholipid expressed as % dry weight increases with increasing µ_max in microalgae. The relative proportions of each of the five major P-containing constituents is remarkably constant, except that the proportion of RNA is greater and phospholipids smaller in prokaryotic than eukaryotic photosynthetic organisms. The effect of temperature differences between studies was minor. The evidence for and against P-containing constituents other than RNA being involved with ribosome synthesis and functioning is discussed.

Dynamic Allocation of Carbon Storage and Nutrient-Dependent Exudation in a Revised Genome-Scale Model of Prochlorococcus

Microbial life in the oceans impacts the entire marine ecosystem, global biogeochemistry and climate. The marine cyanobacterium Prochlorococcus, an abundant component of this ecosystem, releases a significant fraction of the carbon fixed through photosynthesis, but the amount, timing and molecular composition of released carbon are still poorly understood. These depend on several factors, including nutrient availability, light intensity and glycogen storage. Here we combine multiple computational approaches to provide insight into carbon storage and exudation in Prochlorococcus. First, with the aid of a new algorithm for recursive filling of metabolic gaps (ReFill), and through substantial manual curation, we extended an existing genome-scale metabolic model of Prochlorococcus MED4. In this revised model (iSO595), we decoupled glycogen biosynthesis/degradation from growth, thus enabling dynamic allocation of carbon storage. In contrast to standard implementations of flux balance modeling, we made use of forced influx of carbon and light into the cell, to recapitulate overflow metabolism due to the decoupling of photosynthesis and carbon fixation from growth during nutrient limitation. By using random sampling in the ensuing flux space, we found that storage of glycogen or exudation of organic acids are favored when the growth is nitrogen limited, while exudation of amino acids becomes more likely when phosphate is the limiting resource. We next used COMETS to simulate day-night cycles and found that the model displays dynamic glycogen allocation and exudation of organic acids. The switch from photosynthesis and glycogen storage to glycogen depletion is associated with a redistribution of fluxes from the Entner–Doudoroff to the Pentose Phosphate pathway. Finally, we show that specific gene knockouts in iSO595 exhibit dynamic anomalies compatible with experimental observations, further demonstrating the value of this model as a tool to probe the metabolic dynamic of Prochlorococcus.

Relations between mercury fractions and microbial community components in seawater under the presence and absence of probable phosphorus limitation conditions

Microbial transformations of toxic monomethylmercury (MMHg) and dissolved gaseous mercury (DGM) at the lower levels of the marine food web are not well understood, especially in oligotrophic and phosphorus-limited seas. To examine the effects of probable phosphorus limitation (^PP-limitation) on relations between mercury (Hg) fractions and microorganisms, we determined the total mercury (THg), total methylated mercury (MeHg), DGM, and microbiological and chemical parameters in the Central Adriatic Sea. Using statistical analysis, we assessed the potential microbial effects on Hg transformations and bioaccumulation. Only in the absence of ^PP-limitation conditions (^NO-PP-limitation) is MeHg significantly related to most chemical and microbial parameters, indicating metabolism-dependent Hg transformations. The heterotrophic activity of low nucleic acid bacteria (abundant in oligotrophic regions) seems responsible for most of Hg methylation under ^NO-PP-limitation. Under these conditions, DGM is strongly related to microbial fractions and chlorophyll a, indicating biological DGM production, which is probably not metabolically induced, as most of these relations are also observed under ^PP-limitation. MMHg biomagnification was observed through an increased bioaccumulation factor from microseston to mesozooplankton. Our results indicate that Hg transformations and uptake might be enhanced under ^NO-PP-limitation conditions, emphasizing their impact on the transfer of Hg to higher trophic levels.

Quantitative Proteomics Reveals Common and Specific Responses of a Marine Diatom Thalassiosira pseudonana to Different Macronutrient Deficiencies

Macronutrients such as nitrogen (N), phosphorus (P), and silicon (Si) are essential for the productivity and distribution of diatoms in the ocean. Responses of diatoms to a particular macronutrient deficiency have been investigated, however, we know little about their common or specific responses to different macronutrients. Here, we investigated the physiology and quantitative proteomics of a diatom Thalassiosira pseudonana grown in nutrient-replete, N-, P-, and Si-deficient conditions. Cell growth was ceased in all macronutrient deficient conditions while cell volume and cellular C content under P- and Si-deficiencies increased. Contents of chlorophyll a, protein and cellular N decreased in both N- and P-deficient cells but chlorophyll a and cellular N increased in the Si-deficient cells. Cellular P content increased under N- and Si-deficiencies. Proteins involved in carbon fixation and photorespiration were down-regulated under all macronutrient deficiencies while neutral lipid synthesis and carbohydrate accumulation were enhanced. Photosynthesis, chlorophyll biosynthesis, and protein biosynthesis were down-regulated in both N- and P-deficient cells, while Si transporters, light-harvesting complex proteins, chloroplastic ATP synthase, plastid transcription and protein synthesis were up-regulated in the Si-deficient cells. Our results provided insights into the common and specific responses of T. pseudonana to different macronutrient deficiencies and identified specific proteins potentially indicating a particular macronutrient deficiency.

Ediacara biota flourished in oligotrophic and bacterially dominated marine environments across Baltica

Middle-to-late Ediacaran (575–541 Ma) marine sedimentary rocks record the first appearance of macroscopic, multicellular body fossils, yet little is known about the environments and food sources that sustained this enigmatic fauna. Here, we perform a lipid biomarker and stable isotope (δ¹⁵N_total and δ¹³C_TOC) investigation of exceptionally immature late Ediacaran strata (<560 Ma) from multiple locations across Baltica. Our results show that the biomarker assemblages encompass an exceptionally wide range of hopane/sterane ratios (1.6–119), which is a broad measure of bacterial/eukaryotic source organism inputs. These include some unusually high hopane/sterane ratios (22–119), particularly during the peak in diversity and abundance of the Ediacara biota. A high contribution of bacteria to the overall low productivity may have bolstered a microbial loop, locally sustaining dissolved organic matter as an important organic nutrient. These oligotrophic, shallow-marine conditions extended over hundreds of kilometers across Baltica and persisted for more than 10 million years.

The environments and food sources that sustained Ediacara biota 575-541 million years ago remain unclear. Here, the authors perform lipid biomarker and isotopic analyses on biota fossil-containing Ediacaran strata from Baltica and propose the presence of a microbial loop bolstered by bacteria.

Light-Enhanced Microbial Organic Carbon Yield

Molecular evidence for proteorhodopsin- and bacteriochlorophyll-based photoheterotrophy is widespread in oligotrophic marine microbial community metagenomes, and has been implicated in light-enhanced growth rates, substrate uptake rates, and anapleurotic carbon fixation, thus complicating the web of interactions within the ‘microbial loop.’ We quantified photoheterotrophic metabolism of the oxidized organic acid glycolate, a fast-turnover and exclusively phytoplankton-derived substrate at an oligotrophic site in the subtropical North Pacific Ocean. As expected, concentration-dependent changes in uptake rates were observed over the diel cycle, with maxima occurring at midday. Although no light-enhanced substrate uptake rates were observed, samples exposed to light altered the balance between assimilation and respiration, resulting in an approximately four-fold increase in glycolate-specific assimilation efficiency. Energy demand for such a metabolic adjustment was linearly related to light, consistent with photoheterotrophy.

Establishing the phylogeny of Prochlorococcus with a new alignment-free method

Prochlorococcus marinus, one of the most abundant marine cyanobacteria in the global ocean, is classified into low-light (LL) and high-light (HL) adapted ecotypes. These two adapted ecotypes differ in their ecophysiological characteristics, especially whether adapted for growth at high-light or low-light intensities. However, some evolutionary relationships of Prochlorococcus phylogeny remain to be resolved, such as whether the strains SS120 and MIT9211 form a monophyletic group. We use the Natural Vector (NV) method to represent the sequence in order to identify the phylogeny of the Prochlorococcus. The natural vector method is alignment free without any model assumptions. This study added the covariances of amino acids in protein sequence to the natural vector method. Based on these new natural vectors, we can compute the Hausdorff distance between the two clades which represents the dissimilarity. This method enables us to systematically analyze both the dataset of ribosomal proteomes and the dataset of 16s-23s rRNA sequences in order to reconstruct the phylogeny of Prochlorococcus. Furthermore, we apply classification to inspect the relationship of SS120 and MIT9211. From the reconstructed phylogenetic trees and classification results, we may conclude that the SS120 does not cluster with MIT9211. This study demonstrates a new method for performing phylogenetic analysis. The results confirm that these two strains do not form a monophyletic clade in the phylogeny of Prochlorococcus.

A Genome-Scale Model of Shewanella piezotolerans Simulates Mechanisms of Metabolic Diversity and Energy Conservation

The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.

Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea.

IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.