Abstract:Cyanobacteria are important primary producers in diverse ecosystems, yet little is known about the extent of their metabolic interactions with the environment. We have used an integrated, untargeted metabolic footprinting approach to systematically evaluate the uptake and release of metabolites between a model marine cyanobacterium Synechococcus sp. PCC 7002 and different growth media. It was found that 47 out of 202 detected metabolites were consumed, and an additional 55 metabolites were released by the cell… Show more
“…The compound may be enzymatically transformed to a different compound outside of the cell and then utilized, or it may be simply be imported into the cell and not participate in any metabolism. While strange, the latter scenario has been reported to occur in Cyanobacteria [16]. Fig.…”
BackgroundMixed cultures of different microbial species are increasingly being used to carry out a specific biochemical function in lieu of engineering a single microbe to do the same task. However, knowing how different species’ metabolisms will integrate to reach a desired outcome is a difficult problem that has been studied in great detail using steady-state models. However, many biotechnological processes, as well as natural habitats, represent a more dynamic system. Examining how individual species use resources in their growth medium or environment (exometabolomics) over time in batch culture conditions can provide rich phenotypic data that encompasses regulation and transporters, creating an opportunity to integrate the data into a predictive model of resource use by a mixed community.ResultsHere we use exometabolomic profiling to examine the time-varying substrate depletion from a mixture of 19 amino acids and glucose by two Pseudomonas and one Bacillus species isolated from ground water. Contrary to studies in model organisms, we found surprisingly few correlations between resource preferences and maximal growth rate or biomass composition. We then modeled patterns of substrate depletion, and used these models to examine if substrate usage preferences and substrate depletion kinetics of individual isolates can be used to predict the metabolism of a co-culture of the isolates. We found that most of the substrates fit the model predictions, except for glucose and histidine, which were depleted more slowly than predicted, and proline, glycine, glutamate, lysine and arginine, which were all consumed significantly faster.ConclusionsOur results indicate that a significant portion of a model community’s overall metabolism can be predicted based on the metabolism of the individuals. Based on the nature of our model, the resources that significantly deviate from the prediction highlight potential metabolic pathways affected by species-species interactions, which when further studied can potentially be used to modulate microbial community structure and/or function.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1478-2) contains supplementary material, which is available to authorized users.
“…The compound may be enzymatically transformed to a different compound outside of the cell and then utilized, or it may be simply be imported into the cell and not participate in any metabolism. While strange, the latter scenario has been reported to occur in Cyanobacteria [16]. Fig.…”
BackgroundMixed cultures of different microbial species are increasingly being used to carry out a specific biochemical function in lieu of engineering a single microbe to do the same task. However, knowing how different species’ metabolisms will integrate to reach a desired outcome is a difficult problem that has been studied in great detail using steady-state models. However, many biotechnological processes, as well as natural habitats, represent a more dynamic system. Examining how individual species use resources in their growth medium or environment (exometabolomics) over time in batch culture conditions can provide rich phenotypic data that encompasses regulation and transporters, creating an opportunity to integrate the data into a predictive model of resource use by a mixed community.ResultsHere we use exometabolomic profiling to examine the time-varying substrate depletion from a mixture of 19 amino acids and glucose by two Pseudomonas and one Bacillus species isolated from ground water. Contrary to studies in model organisms, we found surprisingly few correlations between resource preferences and maximal growth rate or biomass composition. We then modeled patterns of substrate depletion, and used these models to examine if substrate usage preferences and substrate depletion kinetics of individual isolates can be used to predict the metabolism of a co-culture of the isolates. We found that most of the substrates fit the model predictions, except for glucose and histidine, which were depleted more slowly than predicted, and proline, glycine, glutamate, lysine and arginine, which were all consumed significantly faster.ConclusionsOur results indicate that a significant portion of a model community’s overall metabolism can be predicted based on the metabolism of the individuals. Based on the nature of our model, the resources that significantly deviate from the prediction highlight potential metabolic pathways affected by species-species interactions, which when further studied can potentially be used to modulate microbial community structure and/or function.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1478-2) contains supplementary material, which is available to authorized users.
“…However, uptake of amino acids by Synechococcus spp. has been documented previously in culture (Baran et al, 2011) and during in situ incubation experiments (Zubkov et al, 2003;Michelou et al, 2007). Taken together, this information emphasizes the need for quantifying the autotrophic contribution to DOM turnover in order to improve models of the ocean carbon cycle.…”
Section: Synechococcus Elongatusmentioning
confidence: 82%
“…Further, the composition of phytoplankton exudates influences microbial community structure over spatial and temporal gradients (Cottrell and Kirchman, 2000;Nelson and Carlson, 2012;Landa et al, 2013). Investigations of DOM released by phytoplankton have shown that its composition is quite variable and is influenced by phylogeny (Romera-Castillo et al, 2011;Becker et al, 2014) and growth conditions (Grossart and Simon, 2007;Baran et al, 2011).…”
Photoautotrophic plankton in the surface ocean release organic compounds that fuel secondary production by heterotrophic bacteria. Here we show that an abundant marine cyanobacterium, Synechococcus elongatus, contributes a variety of nitrogen-rich and sulfur-containing compounds to dissolved organic matter. A combination of targeted and untargeted metabolomics and genomic tools was used to characterize the intracellular and extracellular metabolites of S. elongatus. Aromatic compounds such as 4-hydroxybenzoic acid and phenylalanine, as well as nucleosides (e.g., thymidine, 5'-methylthioadenosine, xanthosine), the organosulfur compound 3-mercaptopropionate, and the plant auxin indole 3-acetic acid, were released by S. elongatus at multiple time points during its growth. Further, the amino acid kynurenine was found to accumulate in the media even though it was not present in the predicted metabolome of S. elongatus. This indicates that some metabolites, including those not predicted by an organism's genome, are likely excreted into the environment as waste; however, these molecules may have broader ecological relevance if they are labile to nearby microbes. The compounds described herein provide excellent targets for quantitative analysis in field settings to assess the source and lability of dissolved organic matter in situ.
“…As mass spectrometry (MS) instruments such as Fourier Transform Ion Cyclotron Resonance (FTICR/MS) (Hirai et al, 2004), capillary electrophoresis (CE/MS) (Soga et al, 2003;Edwards et al, 2006), and liquid chromatography (LC/MS) (Baran et al, 2011(Baran et al, , 2013 are commonly used, they are not widely available. In contrast, GC/MS is a widely-used and generally moreaccessible instrument to microbiologists and soil scientists due its low operational cost, availability of curated metabolite spectral databases, broad analytical scope with good coverage of metabolite classes (carbohydrates, alcohols, sterols, amino acids, fatty acids, etc), as well as widespread application to phospholipid fatty acid analysis (Buyer and Sasser, 2012).…”
Section: The Use Of Untargeted Metabolomics To Understand Dom Composimentioning
a b s t r a c tThe cycling of soil organic matter (SOM) by microorganisms is a critical component of the global carbon cycle but remains poorly understood. There is an emerging view that much of SOM, and especially the dissolved fraction (DOM), is composed of small molecules of plant and microbial origin resulting from lysed cells and released metabolites. Unfortunately, little is known about the small molecule composition of soils and how these molecules are cycled (by microbes or plants or by adsorption to mineral surfaces). The water-extractable organic matter (WEOM) fraction is of particular interest given that this is presumably the most biologically-accessible component of SOM. Here we describe the development of a simple soil metabolomics workflow and a novel spike recovery approach using 13 C bacterial lysates to assess the types of metabolites remaining in the WEOM fraction. Soil samples were extracted with multiple mass spectrometry-compatible extraction buffers (water, 10 mM K 2 SO 4 or NH 4 HCO 3 , 10e100% methanol or isopropanol/methanol/water [3:3:2 v/v/v]) with and without prior chloroform vapor fumigation. Profiling of derivatized extracts was performed using gas chromatography/mass spectrometry (GC/MS) with 55 metabolites identified by comparing fragmentation patterns and retention times with authentic standards. As expected, fumigation, which is thought to lyse microbial cells, significantly increased the range and abundance of metabolites relative to unfumigated samples. To assess the types of microbial metabolites from lysed bacterial cells that remain in the WEOM fraction, an extract was prepared from the soil bacterium Pseudomonas stutzerii RCH2 grown on 13 C acetate. This approach produced highly labeled metabolites that were easily discriminated from the endogenous soil metabolites. Comparing the composition of the fresh bacterial extract with what was recovered following a 15 min incubation with soil revealed that only 27% of the metabolites showed >50% recovery in the WEOM. Many, especially cations (polyamines) and anions, showed <10% recovery. These represent metabolites that may be inaccessible to microbes in this environment and would be most likely to accumulate as SOM presumably due to binding with minerals and negatively-charged clay particles. This study presents a simple untargeted metabolomics workflow for extractable organic matter and an approach to estimate microbial metabolite availability in soils. These methods can be used to further our understanding of SOM and DOM composition and examine the link between metabolic pathways and microbial communities to terrestrial carbon cycling.Published by Elsevier Ltd.
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