Abstract
Microbial communities comprised of phototrophs and heterotrophs hold great promise for sustainable biotechnology. Successful application of these communities relies on the selection of ...appropriate partners. Here we construct four community metabolic models to guide strain selection, pairing phototrophic, sucrose-secreting
Synechococcus elongatus
with heterotrophic
Escherichia coli
K-12,
Escherichia coli
W,
Yarrowia lipolytica
, or
Bacillus subtilis
. Model simulations reveae metabolic exchanges that sustain the heterotrophs in minimal media devoid of any organic carbon source, pointing to
S. elongatus-E. coli
K-12 as the most active community. Experimental validation of flux predictions for this pair confirms metabolic interactions and potential production capabilities. Synthetic communities bypass member-specific metabolic bottlenecks (e.g. histidine- and transport-related reactions) and compensate for lethal genetic traits, achieving up to 27% recovery from lethal knockouts. The study provides a robust modelling framework for the rational design of synthetic communities with optimized growth sustainability using phototrophic partners.
Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the ...coanalysis of up to three two-dimensional (2D) NMR spectra, namely, 13C–1H HSQC (heteronuclear single quantum coherence spectroscopy), 1H–1H TOCSY (total correlation spectroscopy), and 13C–1H HSQC-TOCSY, for the comprehensive, accurate, and efficient performance of this task. The highly versatile and interactive nature of COLMARm permits its application to a wide range of metabolomics samples independent of the magnetic field. Database query is performed using the HSQC spectrum, and the top metabolite hits are then validated against the TOCSY-type experiment(s) by superimposing the expected cross-peaks on the mixture spectrum. In this way the user can directly accept or reject candidate metabolites by taking advantage of the complementary spectral information offered by these experiments and their different sensitivities. The power of COLMARm is demonstrated for a human serum sample uncovering the existence of 14 metabolites that hitherto were not identified by NMR.
Since industrialization began, atmospheric CO2 (CO2) has increased from 270 to 415 ppm and is projected to reach 800-1000 ppm this century. Some Arabidopsis thaliana (Arabidopsis) genotypes delayed ...flowering in elevated CO2 relative to current CO2, while others showed no change or accelerations. To predict genotype-specific flowering behaviors, we must understand the mechanisms driving flowering response to rising CO2. CO2 changes alter photosynthesis and carbohydrates in plants. Plants sense carbohydrate levels, and exogenous carbohydrate application influences flowering time and flowering transcript levels. We asked how organismal changes in carbohydrates and transcription correlate with changes in flowering time under elevated CO2. We used a genotype (SG) of Arabidopsis that was selected for high fitness at elevated CO2 (700 ppm). SG delays flowering under elevated CO2 (700 ppm) relative to current CO2 (400 ppm). We compared SG to a closely related control genotype (CG) that shows no CO2-induced flowering change. We compared metabolomic and transcriptomic profiles in these genotypes at current and elevated CO2 to assess correlations with flowering in these conditions. While both genotypes altered carbohydrates in response to elevated CO2, SG had higher levels of sucrose than CG and showed a stronger increase in glucose and fructose in elevated CO2. Both genotypes demonstrated transcriptional changes, with CG increasing genes related to fructose 1,6-bisphosphate breakdown, amino acid synthesis, and secondary metabolites; and SG decreasing genes related to starch and sugar metabolism, but increasing genes involved in oligosaccharide production and sugar modifications. Genes associated with flowering regulation within the photoperiod, vernalization, and meristem identity pathways were altered in these genotypes. Elevated CO2 may alter carbohydrates to influence transcription in both genotypes and delayed flowering in SG. Changes in the oligosaccharide pool may contribute to delayed flowering in SG. This work extends the literature exploring genotypic-specific flowering responses to elevated CO2.
Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and ...untargeted metabolomics. New computational approaches have emerged to overcome the manual absolute quantitation step of metabolites in one-dimensional (1D) ¹H nuclear magnetic resonance (NMR) spectra. This provides more consistency between inter-laboratory comparisons. Integration of two-dimensional (2D) NMR metabolomics databases under a unified web server allowed for very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMR and mass spectrometry (MS). These hybrid MS/NMR approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing for profiling ever larger number of metabolites in application studies.
A customized metabolomics NMR database, TOCCATA, is introduced, which uses 13C chemical shift information for the reliable identification of metabolites, their spin systems, and isomeric states. ...TOCCATA, whose information was derived from the BMRB and HMDB databases and the literature, currently contains 463 compounds and 801 spin systems, and it can be used through a publicly accessible web server. TOCCATA allows the identification of metabolites in the submillimolar concentration range from 13C–13C total correlation spectroscopy experiments of complex mixtures, which is demonstrated for an Escherichia coli cell lysate, a carbohydrate mixture, and an amino acid mixture, all of which were uniformly 13C-labeled.
The complex metabolic makeup of a biological system, such as a cell, is a key determinant of its biological state providing unique insights into its function. Here we characterize the metabolome of a ...cell by a novel homonuclear 13C 2D NMR approach applied to a nonfractionated uniformly 13C-enriched lysate of E. coli cells and determine de novo their carbon backbone topologies that constitute the “topolome”. A protocol was developed, which first identifies traces in a constant-time 13C–13C TOCSY NMR spectrum that are unique for individual mixture components and then assembles for each trace the corresponding carbon-bond topology network by consensus clustering. This led to the determination of 112 topologies of unique metabolites from a single sample. The topolome is dominated by carbon topologies of carbohydrates (34.8%) and amino acids (45.5%) that can constitute building blocks of more complex structures.
We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS²), and NMR into a single analysis platform to ...accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in
. The NMR/MS² approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.
A customized metabolomics NMR database, termed 1H(13C)-TOCCATA, is introduced, which contains complete 1H and 13C chemical shift information on individual spin systems and isomeric states of common ...metabolites. Since this information directly corresponds to cross sections of 2D 1H–1H TOCSY and 2D 13C–1H HSQC-TOCSY spectra, it allows the straightforward and unambiguous identification of metabolites of complex metabolic mixtures at 13C natural abundance from these types of experiments. The 1H(13C)-TOCCATA database, which is complementary to the previously introduced TOCCATA database for the analysis of uniformly 13C-labeled compounds, currently contains 455 metabolites, and it can be used through a publicly accessible web portal. We demonstrate its performance by applying it to 2D 1H–1H TOCSY and 2D 13C–1H HSQC-TOCSY spectra of a cell lysate from E. coli, which yields a substantial improvement over other databases, as well as 1D NMR-based approaches, in the number of compounds that can be correctly identified with high confidence.
An increasing number of organisms can be fully 13C-labeled, which has the advantage that their metabolomes can be studied by high-resolution two-dimensional (2D) NMR 13C–13C constant-time (CT) total ...correlation spectroscopy (TOCSY) experiments. Individual metabolites can be identified via database searching or, in the case of novel compounds, through the reconstruction of their backbone-carbon topology. Determination of quantitative metabolite concentrations is another key task. Because strong peak overlaps in one-dimensional (1D) NMR spectra prevent straightforward quantification through 1D peak integrals, we demonstrate here the direct use of 13C–13C CT-TOCSY spectra for metabolite quantification. This is accomplished through the quantum mechanical treatment of the TOCSY magnetization transfer at short and long-mixing times or by the use of analytical approximations, which are solely based on the knowledge of the carbon-backbone topologies. The methods are demonstrated for carbohydrate and amino acid mixtures.
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