scholarly journals Bacterial fitness landscapes stratify based on proteome allocation associated with discrete aero-types

2021 ◽  
Vol 17 (1) ◽  
pp. e1008596
Author(s):  
Ke Chen ◽  
Amitesh Anand ◽  
Connor Olson ◽  
Troy E. Sandberg ◽  
Ye Gao ◽  
...  
Keyword(s):  
Systems Biology ◽  
Fitness Landscape ◽  
Phenotypic Trait ◽  
Bacterial Physiology ◽  
Transport Chain ◽  
Scale Models ◽  
Bacterial Fitness ◽  
Atp Generation ◽  
Evolution Dynamics ◽  
Genome Scale

The fitness landscape is a concept commonly used to describe evolution towards optimal phenotypes. It can be reduced to mechanistic detail using genome-scale models (GEMs) from systems biology. We use recently developed GEMs of Metabolism and protein Expression (ME-models) to study the distribution of Escherichia coli phenotypes on the rate-yield plane. We found that the measured phenotypes distribute non-uniformly to form a highly stratified fitness landscape. Systems analysis of the ME-model simulations suggest that this stratification results from discrete ATP generation strategies. Accordingly, we define “aero-types”, a phenotypic trait that characterizes how a balanced proteome can achieve a given growth rate by modulating 1) the relative utilization of oxidative phosphorylation, glycolysis, and fermentation pathways; and 2) the differential employment of electron-transport-chain enzymes. This global, quantitative, and mechanistic systems biology interpretation of fitness landscape formed upon proteome allocation offers a fundamental understanding of bacterial physiology and evolution dynamics.

scholarly journals Synthesizing Systems Biology Knowledge from Omics Using Genome‐Scale Models

PROTEOMICS ◽  
2020 ◽  
Vol 20 (17-18) ◽  
pp. 1900282 ◽  
Author(s):  
Sanjeev Dahal ◽  
James T. Yurkovich ◽  
Hao Xu ◽  
Bernhard O. Palsson ◽  
Laurence Yang
Keyword(s):  
Systems Biology ◽  
Scale Models ◽  
Genome Scale

Systems Biology, Genome-Scale Models, and Metabolic Engineering

2009 ◽  
Author(s):  
Markus Herrgård ◽  
Jin Kim ◽  
Sang Lee ◽  
Bernhard Ø. Palsson ◽  
Hyun Uk Kim ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Systems Biology ◽  
Scale Models ◽  
Genome Scale

scholarly journals Revealing the Metabolic Alterations during Biofilm Development of Burkholderia cenocepacia Based on Genome-Scale Metabolic Modeling

Metabolites ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 221
Author(s):  
Ozlem Altay ◽  
Cheng Zhang ◽  
Hasan Turkez ◽  
Jens Nielsen ◽  
Mathias Uhlén ◽  
...  
Keyword(s):  
Systems Biology ◽  
Alternative Pathway ◽  
Growth Conditions ◽  
Pentose Phosphate ◽  
Burkholderia Cenocepacia ◽  
Bacterial Cells ◽  
Metabolic Remodeling ◽  
Transcriptomics Data ◽  
Biofilm Development ◽  
Genome Scale

Burkholderia cenocepacia is among the important pathogens isolated from cystic fibrosis (CF) patients. It has attracted considerable attention because of its capacity to evade host immune defenses during chronic infection. Advances in systems biology methodologies have led to the emergence of methods that integrate experimental transcriptomics data and genome-scale metabolic models (GEMs). Here, we integrated transcriptomics data of bacterial cells grown on exponential and biofilm conditions into a manually curated GEM of B. cenocepacia. We observed substantial differences in pathway response to different growth conditions and alternative pathway susceptibility to extracellular nutrient availability. For instance, we found that blockage of the reactions was vital through the lipid biosynthesis pathways in the exponential phase and the absence of microenvironmental lysine and tryptophan are essential for survival. During biofilm development, bacteria mostly had conserved lipid metabolism but altered pathway activities associated with several amino acids and pentose phosphate pathways. Furthermore, conversion of serine to pyruvate and 2,5-dioxopentanoate synthesis are also identified as potential targets for metabolic remodeling during biofilm development. Altogether, our integrative systems biology analysis revealed the interactions between the bacteria and its microenvironment and enabled the discovery of antimicrobial targets for biofilm-related diseases.

alpha-Glycerophosphate shuttle in a clonal beta-cell line

1989 ◽  
Vol 256 (1) ◽  
pp. E173-E178 ◽  
Author(s):  
M. D. Meglasson ◽  
K. M. Smith ◽  
D. Nelson ◽  
M. Erecinska
Keyword(s):  
Insulin Secretion ◽  
Cell Line ◽  
Electron Transport Chain ◽  
Direct Evidence ◽  
Mitochondrial Fraction ◽  
Secreting Cell ◽  
Transport Chain ◽  
Beta Cell Line ◽  
Atp Generation ◽  
Hit Cells

It has been proposed that the alpha-glycerophosphate (alpha-GOP) shuttle plays a crucial role in regulation of glycolysis in beta-cells by linking reoxidation of cytosolic NADH to formation of ATP in the electron transport chain (J. Biol. Chem. 265: 8287, 1981). Direct evidence for this suggestion is still lacking, however. In this work the operation of the alpha-GOP shuttle was investigated in the insulin-secreting cell line HIT-T15. The constituent enzymes of the pathway were found to be present in HIT cells. Flavin-linked alpha-GOP dehydrogenase was associated with the mitochondrial fraction, whereas NAD+-dependent alpha-GOP dehydrogenase was localized in the cytosol. In the presence of amobarbital (used to preserve the function of the alpha-GOP shuttle under conditions where oxidation of NADH by the respiratory chain was blocked), glucose increased insulin secretion, O2 consumption, and the cell [ATP]/[ADP] when compared with amobarbital alone. These results indicate that the alpha-GOP shuttle contributes to ATP generation in HIT cells and that its activation may be necessary for the initiation of insulin secretion by glucose.

scholarly journals Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

2020 ◽  
Author(s):  
Colton J. Lloyd ◽  
Jonathan Monk ◽  
Laurence Yang ◽  
Ali Ebrahim ◽  
Bernhard O. Palsson
Keyword(s):  
Amino Acids ◽  
Growth Conditions ◽  
Anaerobic Growth ◽  
Metabolic Phenotype ◽  
E Coli ◽  
Scale Models ◽  
Protein Components ◽  
K 12 ◽  
Genome Scale ◽  
Prosthetic Groups

AbstractSustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated genome-scale models of metabolism and gene expression (ME-models) have the unique ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we use the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME model mostly agree with the standard biomass objective function used in models of metabolism alone (M models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of prebiotic amino acids in the proteins used to sustain anaerobic growth (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E. coli. Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E. coli lifestyles.

scholarly journals Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
N. T. Devika ◽  
Karthik Raman
Keyword(s):  
Short Chain Fatty Acids ◽  
Acetate Production ◽  
Scale Models ◽  
Powerful Approach ◽  
Metabolic Models ◽  
Commercial Applications ◽  
Different Strains ◽  
Genome Scale ◽  
Modelling Approach

AbstractBifidobacteria, the initial colonisers of breastfed infant guts, are considered as the key commensals that promote a healthy gastrointestinal tract. However, little is known about the key metabolic differences between different strains of these bifidobacteria, and consequently, their suitability for their varied commercial applications. In this context, the present study applies a constraint-based modelling approach to differentiate between 36 important bifidobacterial strains, enhancing their genome-scale metabolic models obtained from the AGORA (Assembly of Gut Organisms through Reconstruction and Analysis) resource. By studying various growth and metabolic capabilities in these enhanced genome-scale models across 30 different nutrient environments, we classified the bifidobacteria into three specific groups. We also studied the ability of the different strains to produce short-chain fatty acids, finding that acetate production is niche- and strain-specific, unlike lactate. Further, we captured the role of critical enzymes from the bifid shunt pathway, which was found to be essential for a subset of bifidobacterial strains. Our findings underline the significance of analysing metabolic capabilities as a powerful approach to explore distinct properties of the gut microbiome. Overall, our study presents several insights into the nutritional lifestyles of bifidobacteria and could potentially be leveraged to design species/strain-specific probiotics or prebiotics.

scholarly journals BiGG Models 2020: multi-strain genome-scale models and expansion across the phylogenetic tree

2019 ◽  
Author(s):  
Charles J Norsigian ◽  
Neha Pusarla ◽  
John Luke McConn ◽  
James T Yurkovich ◽  
Andreas Dräger ◽  
...  
Keyword(s):  
Phylogenetic Tree ◽  
Knowledge Base ◽  
The Past ◽  
Scale Models ◽  
Metabolic Models ◽  
New Community ◽  
Genome Annotations ◽  
Genome Scale ◽  
High Quality Genome ◽  
Strain Genome

Abstract The BiGG Models knowledge base (http://bigg.ucsd.edu) is a centralized repository for high-quality genome-scale metabolic models. For the past 12 years, the website has allowed users to browse and search metabolic models. Within this update, we detail new content and features in the repository, continuing the original effort to connect each model to genome annotations and external databases as well as standardization of reactions and metabolites. We describe the addition of 31 new models that expand the portion of the phylogenetic tree covered by BiGG Models. We also describe new functionality for hosting multi-strain models, which have proven to be insightful in a variety of studies centered on comparisons of related strains. Finally, the models in the knowledge base have been benchmarked using Memote, a new community-developed validator for genome-scale models to demonstrate the improving quality and transparency of model content in BiGG Models.

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