Microbial metabolic exchange--the chemotype-to-phenotype link.
Ontology highlight
ABSTRACT:
SUBMITTER: Phelan VV
PROVIDER: S-EPMC3869239 | biostudies-literature | 2011 Dec
REPOSITORIES: biostudies-literature
Publications
Microbial metabolic exchange--the chemotype-to-phenotype link.
Phelan Vanessa V VV Liu Wei-Ting WT Pogliano Kit K Dorrestein Pieter C PC
Nature chemical biology 20111215 1
The function of microbial interactions is to enable microorganisms to survive by establishing a homeostasis between microbial neighbors and local environments. A microorganism can respond to environmental stimuli using metabolic exchange-the transfer of molecular factors, including small molecules and proteins. Microbial interactions not only influence the survival of the microbes but also have roles in morphological and developmental processes of the organisms themselves and their neighbors. Th ...[more]
Similar Datasets
Project description:Mono- and multispecies microbial populations alter the chemistry of their surrounding environments during colony development thereby influencing multicellular behavior and interspecies interactions of neighboring microbes. Here we present a methodology that enables the creation of three-dimensional (3D) models of a microbial chemotype that can be correlated to the colony phenotype through multimodal imaging analysis. These models are generated by performing matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) imaging mass spectrometry (IMS) on serial cross-sections of microbial colonies grown on 8 mm deep agar, registering data sets of each serial section in MATLAB to create a model, and then superimposing the model with a photograph of the colonies themselves. As proof-of-principle, 3D models were used to visualize metabolic exchange during microbial interactions between Bacillus subtilis and Streptomyces coelicolor, as well as, Candida albicans and Pseudomonas aeruginosa. The resulting models were able to capture the depth profile of secreted metabolites within the agar medium and revealed properties of certain mass signals that were previously not observable using two-dimensional MALDI-TOF IMS. Most significantly, the 3D models were capable of mapping previously unobserved chemical distributions within the array of sub-surface hyphae of C. albicans and how this chemistry is altered by the presence of P. aeruginosa, an opportunistic pathogen known to alter virulence of C. albicans. It was determined that the presence of C. albicans triggered increased rhamnolipid production by P. aeruginosa, which in turn was capable of inhibiting embedded hyphal growth produced beneath the C. albicans colony at ambient temperature.
| S-EPMC3603389 | biostudies-literature
Project description:We compared the metabolic profiles and the association between LDH-A expression and lactate production in two isogenic murine breast cancer cell lines and tumors (67NR and 4T1). These cell lines were derived from a single mammary tumor and have different growth and metabolic phenotypes.LDH-A expression, lactate concentration, glucose utilization, and oxygen consumption were measured in cells, and the potential relationship between tumor lactate levels [measured by magnetic resonance spectroscopic imaging (MRSI)] and tumor glucose utilization [measured by [(18)F]2-deoxy-2-fluoro-D-glucose positron emission tomography ([(18)F]FDG-PET)] was assessed in orthotopic breast tumors derived from these cell lines.We show a substantial difference in LDH-A expression between 67NR and 4T1 cells under normoxia and hypoxia. We also show that small orthotopic 4T1 tumors generate 10-fold more lactate than corresponding 67NR tumors. The high lactate levels in small primary 4T1 tumors are associated with intense pimonidazole staining (a hypoxia indicator). Less-intense hypoxia staining was observed in the larger 67NR tumors and is consistent with the gradual increase and plateau of lactate concentration in enlarging 67NR tumors.Lactate-MRSI has a greater dynamic range than [(18)F]FDG-PET and may be a more sensitive measure with which to evaluate the aggressive and metastatic potential of primary breast tumors.
| S-EPMC4217119 | biostudies-literature
Project description:Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.
| S-EPMC6586255 | biostudies-literature
Project description:The profiling of 16S rRNA revolutionized the exploration of microbiomes, allowing to describe community composition by enumerating relevant taxa and their abundances. However, taxonomic profiles alone lack interpretability in terms of bacterial metabolism, and their translation into functional characteristics of microbiomes is a challenging task. This bottom-up approach minimally requires a reference collection of major metabolic traits deduced from the complete genomes of individual organisms, an accurate method of projecting these traits from a reference collection to the analyzed amplicon sequence variants (ASVs), and, ultimately, an approach to a microbiome-wide aggregation of predicted individual traits into physiologically relevant cumulative metrics to characterize and compare multiple microbiome samples. In this study, we extended a previously introduced computational approach for the functional profiling of complex microbial communities, which is based on the concept of binary metabolic phenotypes encoding the presence ("1") or absence ("0") of various measurable physiological properties in individual organisms that are termed phenotype carriers or non-carriers, respectively. Derived from complete genomes via metabolic reconstruction, binary phenotypes provide a foundation for the prediction of functional traits for each ASV identified in a microbiome sample. Here, we introduced three distinct mapping schemes for a microbiome-wide phenotype prediction and assessed their accuracy on the 16S datasets of mock bacterial communities representing human gut microbiome (HGM) as well as on two large HGM datasets, the American Gut Project and the UK twins study. The 16S sequence-based scheme yielded a more accurate phenotype predictions, while the taxonomy-based schemes demonstrated a reasonable performance to warrant their application for other types of input data (e.g., from shotgun metagenomics or qPCR). In addition to the abundance-weighted Community Phenotype Indices (CPIs) reflecting the fractional representation of various phenotype carriers in microbiome samples, we employ metrics capturing the diversity of phenotype carriers, Phenotype Alpha Diversity (PAD) and Phenotype Beta Diversity (PBD). In combination with CPI, PAD allows to classify the robustness of metabolic phenotypes by their anticipated stability in the face of potential environmental perturbations. PBD provides a promising approach for detecting the metabolic features potentially contributing to disease-associated metabolic traits as illustrated by a comparative analysis of HGM samples from healthy and Crohn's disease cohorts.
| S-EPMC8185038 | biostudies-literature
Project description:Understanding the metabolic processes associated with aging is key to developing effective management and treatment strategies for age-related diseases. We investigated the metabolic profiles associated with age in a Taiwanese and an American population. ¹H NMR spectral profiles were generated for urine specimens collected from the Taiwanese Social Environment and Biomarkers of Aging Study (SEBAS; n = 857; age 54-91 years) and the Mid-Life in the USA study (MIDUS II; n = 1148; age 35-86 years). Multivariate and univariate linear projection methods revealed some common age-related characteristics in urinary metabolite profiles in the American and Taiwanese populations, as well as some distinctive features. In both cases, two metabolites--4-cresyl sulfate (4CS) and phenylacetylglutamine (PAG)--were positively associated with age. In addition, creatine and β-hydroxy-β-methylbutyrate (HMB) were negatively correlated with age in both populations (p < 4 × 10⁻⁶). These age-associated gradients in creatine and HMB reflect decreasing muscle mass with age. The systematic increase in PAG and 4CS was confirmed using ultraperformance liquid chromatography-mass spectrometry (UPLC-MS). Both are products of concerted microbial-mammalian host cometabolism and indicate an age-related association with the balance of host-microbiome metabolism.
| S-EPMC3835364 | biostudies-literature
Project description:Metabolic crossfeeding is an important process that can broadly shape microbial communities. However, little is known about specific crossfeeding principles that drive the formation and maintenance of individuals within a mixed population. Here, we devised a series of synthetic syntrophic communities to probe the complex interactions underlying metabolic exchange of amino acids. We experimentally analyzed multimember, multidimensional communities of Escherichia coli of increasing sophistication to assess the outcomes of synergistic crossfeeding. We find that biosynthetically costly amino acids including methionine, lysine, isoleucine, arginine, and aromatics, tend to promote stronger cooperative interactions than amino acids that are cheaper to produce. Furthermore, cells that share common intermediates along branching pathways yielded more synergistic growth, but exhibited many instances of both positive and negative epistasis when these interactions scaled to higher dimensions. In more complex communities, we find certain members exhibiting keystone species-like behavior that drastically impact the community dynamics. Based on comparative genomic analysis of >6,000 sequenced bacteria from diverse environments, we present evidence suggesting that amino acid biosynthesis has been broadly optimized to reduce individual metabolic burden in favor of enhanced crossfeeding to support synergistic growth across the biosphere. These results improve our basic understanding of microbial syntrophy while also highlighting the utility and limitations of current modeling approaches to describe the dynamic complexities underlying microbial ecosystems. This work sets the foundation for future endeavors to resolve key questions in microbial ecology and evolution, and presents a platform to develop better and more robust engineered synthetic communities for industrial biotechnology.
| S-EPMC4034247 | biostudies-literature
Project description:Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.
| S-EPMC4690371 | biostudies-literature
Project description:This study is to find the cellular and molecular mechanisms by which a naturally-occurring deltaNp53 isoform causes accelerated aging in humans. The biological function of deltaNp53, which lacks only 40 N-terminal amino acids, represents an example of p53 as a regulator of mammalian aging. When expressed together with WTp53 in mice, ΔNp53 causes an aging phenotype such as shorter life span, reduced body mass, organ atrophy and osteoporosis. Because p53 must form a tetramer to regulate transcription, we generated p53 clones (based upon the structure of the native p53 tetramer) containing one ΔNp53 linked with one WTp53 to form a functional ΔNp53:WTp53 tetramer with 1:1 stoichiometry. Thus, our strategy ensured each p53 tetramer contained 2 ΔNp53 and 2 WTp53 proteins. Importantly, ΔNp53:WTp53 form stable tetramers, based upon gel filtration chromatography and structural analysis using electron microscopy. Furthermore, the ΔNp53:WTp53 tetramer activates transcription equally well compared with WTp53 tetramers in an in vitro reconstituted transcription system. Having verified the stoichiometry, stability, structure, and activity of these ΔNp53:WTp53 tetramers, here we used microarray analysis to compare global gene expression patterns in p53-null H1299 cells expressing either WTp53 or ΔNp53:WTp53. As expected, global gene expression was largely similar, since the differences between ΔNp53:WTp53 tetramers and WTp53 tetramers are slight: only 2 of 4 p53 proteins will be different in the ΔNp53:WTp53 tetramer. Among only several dozen genes that were selectively up- or down-regulated 2-fold or greater, many genes known to regulate mammalian aging were altered in cells expressing ΔNp53:WTp53, including insulin signaling pathway members (IRS1, INPP5D, PLK3, MAP3K1, FGF5) and regulators of glucose metabolism (SLC2A2, CRYAB, LRCH1). Expression of other key metabolic genes were also altered in cells expressing ΔNp53:WTp53 tetramers, suggesting that global me tabolic changes might contribute to ΔNp53:WTp53 pathology. In collaboration with Metabolon (Durham, NC), we identified approximately one hundred metabolites that were significantly up- or down-regulated in H1299 cells expressing ΔNp53:WTp53. The metabolome analysis was a powerful complement to the gene expression data, and further suggested that the mTOR pathway (e.g. across-the-board up-regulation of amino acid levels) and mitochondrial function (e.g. up-regulation of carnitine, important for a-oxidation of fatty acids) was altered in cells expressing ΔNp53:WTp53. These findings were subsequently validated using biochemical and cell-based approaches. Furthermore, whereas equal expression of ΔNp53 and WTp53 cause accelerated aging in mammals, due to alternative splicing and translation initiation ΔNp53 is a naturally-occurring isoform whose expression levels can change throughout the lifetime. Thus, the cellular and molecular mechanisms identified from this work will likely reflect changes common to normal, physiological aging. Comparison of global gene expression profiles in WTp53 or ΔNp53:WTp53 expressed H1299 RNA from FACS sorted GFP positive hybrid to Affymatrix Gene The exp 0, exp 4 and exp 5 are independent replicate/transfections/biological experiments. The exp d, exp e and exp f are control experiments.
| S-ECPF-GEOD-37271 | biostudies-other
Project description:This study is to find the cellular and molecular mechanisms by which a naturally-occurring deltaNp53 isoform causes accelerated aging in humans. The biological function of deltaNp53, which lacks only 40 N-terminal amino acids, represents an example of p53 as a regulator of mammalian aging. When expressed together with WTp53 in mice, ÎNp53 causes an aging phenotype such as shorter life span, reduced body mass, organ atrophy and osteoporosis. Because p53 must form a tetramer to regulate transcription, we generated p53 clones (based upon the structure of the native p53 tetramer) containing one ÎNp53 linked with one WTp53 to form a functional ÎNp53:WTp53 tetramer with 1:1 stoichiometry. Thus, our strategy ensured each p53 tetramer contained 2 ÎNp53 and 2 WTp53 proteins. Importantly, ÎNp53:WTp53 form stable tetramers, based upon gel filtration chromatography and structural analysis using electron microscopy. Furthermore, the ÎNp53:WTp53 tetramer activates transcription equally well compared with WTp53 tetramers in an in vitro reconstituted transcription system. Having verified the stoichiometry, stability, structure, and activity of these ÎNp53:WTp53 tetramers, here we used microarray analysis to compare global gene expression patterns in p53-null H1299 cells expressing either WTp53 or ÎNp53:WTp53. As expected, global gene expression was largely similar, since the differences between ÎNp53:WTp53 tetramers and WTp53 tetramers are slight: only 2 of 4 p53 proteins will be different in the ÎNp53:WTp53 tetramer. Among only several dozen genes that were selectively up- or down-regulated 2-fold or greater, many genes known to regulate mammalian aging were altered in cells expressing ÎNp53:WTp53, including insulin signaling pathway members (IRS1, INPP5D, PLK3, MAP3K1, FGF5) and regulators of glucose metabolism (SLC2A2, CRYAB, LRCH1). Expression of other key metabolic genes were also altered in cells expressing ÎNp53:WTp53 tetramers, suggesting that global me tabolic changes might contribute to ÎNp53:WTp53 pathology. In collaboration with Metabolon (Durham, NC), we identified approximately one hundred metabolites that were significantly up- or down-regulated in H1299 cells expressing ÎNp53:WTp53. The metabolome analysis was a powerful complement to the gene expression data, and further suggested that the mTOR pathway (e.g. across-the-board up-regulation of amino acid levels) and mitochondrial function (e.g. up-regulation of carnitine, important for a-oxidation of fatty acids) was altered in cells expressing ÎNp53:WTp53. These findings were subsequently validated using biochemical and cell-based approaches. Furthermore, whereas equal expression of ÎNp53 and WTp53 cause accelerated aging in mammals, due to alternative splicing and translation initiation ÎNp53 is a naturally-occurring isoform whose expression levels can change throughout the lifetime. Thus, the cellular and molecular mechanisms identified from this work will likely reflect changes common to normal, physiological aging. Comparison of global gene expression profiles in WTp53 or ÎNp53:WTp53 expressed H1299 RNA from FACS sorted GFP positive hybrid to Affymatrix Gene The exp 0, exp 4 and exp 5 are independent replicate/transfections/biological experiments. The exp d, exp e and exp f are control experiments.
2014-05-08 | E-GEOD-37271 | biostudies-arrayexpress
Project description:Metabolic flux analysis (MFA) deals with the experimental determination of steady-state fluxes in metabolic networks. An important feature of the (13)C MFA method is its capability to generate information on both directions of bidirectional reaction steps given by exchange fluxes. The biological interpretation of these exchange fluxes and their relation to thermodynamic properties of the respective reaction steps has never been systematically investigated. As a central result, it is shown here that for a general class of enzyme reaction mechanisms the quotients of net and exchange fluxes measured by (13)C MFA are coupled to Gibbs energies of the reaction steps. To establish this relation the concept of apparent flux ratios of enzymatic isotope-labeling networks is introduced and some computing rules for these flux ratios are given. Application of these rules reveals a conceptional pitfall of (13)C MFA, which is the inherent dependency of measured exchange fluxes on the chosen tracer atom. However, it is shown that this effect can be neglected for typical biochemical reaction steps under physiological conditions. In this situation, the central result can be formulated as a two-sided inequality relating fluxes, pool sizes, and standard Gibbs energies. This relation has far-reaching consequences for metabolic flux analysis, quantitative metabolomics, and network thermodynamics.
| S-EPMC1959540 | biostudies-literature