scholarly journals Identifying the essential nutritional requirements of the probiotic bacteria Bifidobacterium animalis and Bifidobacterium longum through genome-scale modeling

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Marie Schöpping ◽  
Paula Gaspar ◽  
Ana Rute Neves ◽  
Carl Johan Franzén ◽  
Ahmad A. Zeidan
Keyword(s):  
Bifidobacterium Longum ◽  
Defined Medium ◽  
Nutritional Requirements ◽  
Modeling Framework ◽  
Carbohydrate Utilization ◽  
Bifidobacterium Animalis ◽  
Manual Curation ◽  
Constraint Based Modeling ◽  
Complex Culture ◽  
Genome Scale

AbstractAlthough bifidobacteria are widely used as probiotics, their metabolism and physiology remain to be explored in depth. In this work, strain-specific genome-scale metabolic models were developed for two industrially and clinically relevant bifidobacteria, Bifidobacterium animalis subsp. lactis BB-12® and B. longum subsp. longum BB-46, and subjected to iterative cycles of manual curation and experimental validation. A constraint-based modeling framework was used to probe the metabolic landscape of the strains and identify their essential nutritional requirements. Both strains showed an absolute requirement for pantethine as a precursor for coenzyme A biosynthesis. Menaquinone-4 was found to be essential only for BB-46 growth, whereas nicotinic acid was only required by BB-12®. The model-generated insights were used to formulate a chemically defined medium that supports the growth of both strains to the same extent as a complex culture medium. Carbohydrate utilization profiles predicted by the models were experimentally validated. Furthermore, model predictions were quantitatively validated in the newly formulated medium in lab-scale batch fermentations. The models and the formulated medium represent valuable tools to further explore the metabolism and physiology of the two species, investigate the mechanisms underlying their health-promoting effects and guide the optimization of their industrial production processes.

scholarly journals Reconstruction of Litopenaeus vannamei Genome-Scale Metabolic Network Model and Nutritional Requirements Analysis of Different Shrimp Commercial Varieties

2021 ◽  
Vol 12 ◽  
Author(s):  
Chenchen Gao ◽  
Jiarui Yang ◽  
Tong Hao ◽  
Jingjing Li ◽  
Jinsheng Sun
Keyword(s):  
Metabolic Network ◽  
Litopenaeus Vannamei ◽  
Nutritional Requirements ◽  
Feed Conversion ◽  
Carbohydrate Utilization ◽  
Systematic Analysis ◽  
Tyrosine Protein Kinase ◽  
And Control ◽  
Genome Scale ◽  
Feed Conversion Rate

As an important tool for systematic analysis, genome-scale metabolic network (GSMN) model has been widely used in various organisms. However, there are few reports on the GSMNs of aquatic crustaceans. Litopenaeus vannamei is the largest and most productive shrimp species. Feed improvement is one of the important methods to improve the yield of L. vannamei and control water pollution caused by the inadequate absorption of feed. In this work, the first L. vannamei GSMN named iGH3005 was reconstructed and applied to the optimization of feed. iGH3005 was reconstructed based on the genomic data. The model includes 2,292 reactions and 3,005 genes. iGH3005 was used to analyze the nutritional requirements of five different L. vannamei commercial varieties and the genes influencing the metabolism of the nutrients. Based on the simulation, we found that tyrosine-protein kinase src64b like may catalyze different reactions in different commercial varieties. The preference of carbohydrate utilization is different in various commercial varieties, which may due to the different expressions of some genes. In addition, this investigation suggests that a rational and targeted modification in the macronutrient content of shrimp feed would lead to an increase in growth and feed conversion rate. The feed for different commercial varieties should be adjusted accordingly, and possible adjustment schemes were provided. The results of this work provided important information for physiological research and optimization of the components in feed of L. vannamei.

scholarly journals SLIMEr: probing flexibility of lipid metabolism in yeast with an improved constraint-based modeling framework

2018 ◽  
Author(s):  
Benjamín J. Sánchez ◽  
Feiran Li ◽  
Eduard J. Kerkhoven ◽  
Jens Nielsen
Keyword(s):  
Experimental Data ◽  
Saccharomyces Cerevisiae ◽  
Lipid Metabolism ◽  
Acyl Chain ◽  
Energy Costs ◽  
Detailed Data ◽  
Modeling Framework ◽  
Lipid Species ◽  
Constraint Based Modeling ◽  
Genome Scale

SummaryA recurrent problem in genome-scale metabolic models (GEMs) is to correctly represent lipids as biomass requirements, due to the numerous of possible combinations of individual lipid species and the corresponding lack of fully detailed data. In this study we present SLIMEr, a formalism for correctly representing lipid requirements in GEMs using commonly available experimental data. SLIMEr enhances a GEM with mathematical constructs where we Split Lipids Into Measurable Entities (SLIME reactions), in addition to constraints on both the lipid classes and the acyl chain distribution. By implementing SLIMEr on the consensus GEM of Saccharomyces cerevisiae, we can predict accurate amounts of lipid species, analyze the flexibility of the resulting distribution, and compute the energy costs of moving from one metabolic state to another. The approach shows potential for better understanding lipid metabolism in yeast under different conditions. SLIMEr is freely available at https://github.com/SysBioChalmers/SLIMEr.

scholarly journals Genome-Scale Metabolic Network Analysis of the Opportunistic Pathogen Pseudomonas aeruginosa PAO1

2008 ◽  
Vol 190 (8) ◽  
pp. 2790-2803 ◽  
Author(s):  
Matthew A. Oberhardt ◽  
Jacek Puchałka ◽  
Kimberly E. Fryer ◽  
Vítor A. P. Martins dos Santos ◽  
Jason A. Papin
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Metabolic Network ◽  
Opportunistic Pathogen ◽  
Scale Model ◽  
Modeling Framework ◽  
Major Life ◽  
Metabolic Versatility ◽  
A Genome ◽  
Scale Properties ◽  
Genome Scale

ABSTRACT Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.

scholarly journals The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities

2018 ◽  
Vol 35 (13) ◽  
pp. 2332-2334 ◽  
Author(s):  
Federico Baldini ◽  
Almut Heinken ◽  
Laurent Heirendt ◽  
Stefania Magnusdottir ◽  
Ronan M T Fleming ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Microbial Interactions ◽  
Microbial Genome ◽  
Metagenomic Data ◽  
Metabolic Interactions ◽  
Constraint Based Modeling ◽  
Genome Scale

Abstract Motivation The application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes. Results To address this gap, we created a comprehensive toolbox to model (i) microbe–microbe and host–microbe metabolic interactions, and (ii) microbial communities using microbial genome-scale metabolic reconstructions and metagenomic data. The Microbiome Modeling Toolbox extends the functionality of the constraint-based reconstruction and analysis toolbox. Availability and implementation The Microbiome Modeling Toolbox and the tutorials at https://git.io/microbiomeModelingToolbox.

scholarly journals Identification, Characterization, and Antioxidant Potential of Bifidobacterium longum subsp. longum Strains Isolated From Feces of Healthy Infants

2021 ◽  
Vol 12 ◽  
Author(s):  
Li Zhao ◽  
Song Wang ◽  
Jiahuan Dong ◽  
Jialu Shi ◽  
Jiaqi Guan ◽  
...  
Keyword(s):  
Infant Nutrition ◽  
Bifidobacterium Longum ◽  
Antioxidant Properties ◽  
Radical Scavenging ◽  
Reducing Power ◽  
Heat Shock Protein 60 ◽  
Intestinal Epithelial ◽  
Intact Cells ◽  
Bifidobacterium Animalis ◽  
Healthy Infants

Increasing evidence has indicated that oxidative stress is associated with the health of infants. Bifidobacterium, especially B. longum subsp. longum strains, are abundant in the gut microbiota of infants, which may have the potential to ameliorate oxidative damage. Thus, this study aimed to isolate and screen B. longum subsp. longum strains with probiotic characters and antioxidant properties as infants’ dietary supplements. In this study, 24 B. longum subsp. longum strains were isolated from 15 healthy infants identified via 16S rRNA and heat shock protein 60 (hsp60) sequences. B. longum subsp. longum B13, F2, K4, K5, K10, K13, and K15 strains were selected based on high values obtained from autoaggregation, hydrophobicity, and adhesion assays to HT-29 cells. Among these seven strains, B. longum subsp. longum F2, K5, K10, and K15 were selected according to the high tolerance of gastrointestinal tract conditions compared to Bifidobacterium animalis subsp. lactis BB-12. Among these four strains, B. longum subsp. longum K5 was susceptible to common antibiotics and showed the highest intestinal epithelial cell proliferation of CCD 841 CoN. Additionally, B. longum subsp. longum K5 showed a strong antioxidant capacity, and its supernatant exhibited better activity of reducing power, hydroxyl radical scavenging, and DPPH radical scavenging than that of the intact cells with cell-free extracts. The findings indicated that B. longum subsp. longum K5 could be used as a probiotic candidate in infant nutrition.

scholarly journals SLIMEr: probing flexibility of lipid metabolism in yeast with an improved constraint-based modeling framework

2019 ◽  
Vol 13 (1) ◽  
Author(s):  
Benjamín J. Sánchez ◽  
Feiran Li ◽  
Eduard J. Kerkhoven ◽  
Jens Nielsen
Keyword(s):  
Lipid Metabolism ◽  
Modeling Framework ◽  
Constraint Based Modeling

scholarly journals Advances in metabolic flux analysis toward genome-scale profiling of higher organisms

2018 ◽  
Vol 38 (6) ◽  
Author(s):  
Georg Basler ◽  
Alisdair R. Fernie ◽  
Zoran Nikoloski
Keyword(s):  
Large Scale ◽  
Metabolic Flux ◽  
Cell Types ◽  
Flux Analysis ◽  
Metabolic Labeling ◽  
Modeling Framework ◽  
Metabolomics Data ◽  
Technological Advances ◽  
A Genome ◽  
Genome Scale

Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.

scholarly journals Multiple Transporters and Glycoside Hydrolases Are Involved in Arabinoxylan-Derived Oligosaccharide Utilization in Bifidobacterium pseudocatenulatum

2020 ◽  
Vol 86 (24) ◽  
Author(s):  
Yuki Saito ◽  
Akira Shigehisa ◽  
Yohei Watanabe ◽  
Naoki Tsukuda ◽  
Kaoru Moriyama-Ohara ◽  
...  
Keyword(s):  
Abc Transporters ◽  
Binding Proteins ◽  
Molecular Mechanisms ◽  
Bifidobacterium Longum ◽  
Gene Clusters ◽  
Glycoside Hydrolases ◽  
Glycoside Hydrolase Family ◽  
Carbohydrate Utilization ◽  
Bifidobacterium Adolescentis ◽  
Content Type

ABSTRACT Arabinoxylan hydrolysates (AXH) are the hydrolyzed products of the major components of the dietary fiber arabinoxylan. AXH include diverse oligosaccharides varying in xylose polymerization and side residue modifications with arabinose at the O-2 and/or O-3 position of the xylose unit. Previous studies have reported that AXH exhibit prebiotic properties on gut bifidobacteria; moreover, several adult-associated bifidobacterial species (e.g., Bifidobacterium adolescentis and Bifidobacterium longum subsp. longum) are known to utilize AXH. In this study, we tried to elucidate the molecular mechanisms of AXH utilization by Bifidobacterium pseudocatenulatum, which is a common bifidobacterial species found in adult feces. We performed transcriptomic analysis of B. pseudocatenulatum YIT 4072T, which identified three upregulated gene clusters during AXH utilization. The gene clusters encoded three sets of ATP-binding cassette (ABC) transporters and five enzymes belonging to glycoside hydrolase family 43 (GH43). By characterizing the recombinant proteins, we found that three solute-binding proteins of ABC transporters showed either broad or narrow specificity, two arabinofuranosidases hydrolyzed either single- or double-decorated arabinoxylooligosaccharides, and three xylosidases exhibited functionally identical activity. These data collectively suggest that the transporters and glycoside hydrolases, encoded in the three gene clusters, work together to utilize AXH of different sizes and with different side residue modifications. Thus, our study sheds light on the overall picture of how these proteins collaborate for the utilization of AXH in B. pseudocatenulatum and may explain the predominance of this symbiont species in the adult human gut. IMPORTANCE Bifidobacteria commonly reside in the human intestine and possess abundant genes involved in carbohydrate utilization. Arabinoxylan hydrolysates (AXH) are hydrolyzed products of arabinoxylan, one of the most abundant dietary fibers, and they include xylooligosaccharides and those decorated with arabinofuranosyl residues. The molecular mechanism by which B. pseudocatenulatum, a common bifidobacterial species found in adult feces, utilizes structurally and compositionally variable AXH has yet to be extensively investigated. In this study, we identified three gene clusters (encoding five GH43 enzymes and three solute-binding proteins of ABC transporters) that were upregulated in B. pseudocatenulatum YIT 4072T during AXH utilization. By investigating their substrate specificities, we revealed how these proteins are involved in the uptake and degradation of AXH. These molecular insights may provide a better understanding of how resident bifidobacteria colonize the colon.

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