Flux balance analysis

It encloses a brief description of flux balance analysis tools, flux measuring software, methods, advantages and comparable applications to the other software's and analysis techniques and discussion so on steady - constraint based analysis modelling, reconstruction of metabolic pathways and different constraints. etc.

1. Flux balance Analysis Presented by: Jyoti (191503) M.Sc. Biotechnology IInd Year Central University of Haryana

2. Introduction- Metabolic Flux  Metabolic Flux is the ra te of passage of material, or of a specified substance or molecular fragment, through a given metabolic pathway Or we can say Flux/metabolic flux is the rate of turnover of molecules through a metabolic pathway. Flux is regulated by the enzymes involved in a pathway. Within cells, regulation of flux is vital for all metabolic pathways to regulate the metabolic pathway's activity under different conditions. Unit of flux is – mmoles/g/h

3. As given in the figure, we can measure the uptake rates of glucose, the production rates of carbon dioxide, acetate, ethanol, glycerol, pyruvate, succinate etc. and the rate of synthesis of the key macromolecules like DNA, RNA, protein and lipids and carbohydrates. Reference: https://www.researchgate.net/figure/Estimation-of-flux-distribution-within-the-central-metabolic-pathways-based-on-the_fig1_14007873

4. Why study metabolic flux?  For optimization of pathways in metabolic engineering. Identification of disease states associated with metabolic changes. To understand metabolic regulation. To ensure in vivo activity of metabolic pathway.  helps to understand the contribution of  metabolic  alterations to pathology . As we have discuss some traditional approach of metabolic modelling using coupled ordinary differential equations , FBA (flux balance analysis) requires very little information in terms of enzyme kinetic parameters and concentration of metabolites in the system

5. Flux Balance Analysis Flux balance analysis (FBA) is a powerful tool for the constraint-based analyses of metabolic networks, to identify steady state flux distributions and metabolic capabilities of biochemical networks . FBA is based on the principle of conservation of mass in a network, which utilizes the stoichiometric matrix and a biologically relevant objective function to identify optimal reaction flux distributions. Constraint based analysis of metabolic flux which is more effective than modelling based. It involves: system definition determining reaction stoichiometries relevant objective function and addition of other biochemical constraints optimization.

6. https://slideplayer.com/slide/9402106/28/images/5/Formulation+of+Flux+Balance+Analysis.jpg

7. Model preparation and refinement: Reconstruction of metabolic networks It is a process through which the various components of the metabolic network of a biological system, viz. the genes, proteins, reactions and metabolites that participate in metabolic activity are identified, categorized and inter-connected to form a network. This system is a single cell of interest and building on the genomic sequence as a scaffold, reconstructions can incorporate hundreds of reactions that approximate the entire metabolic activity of a cell. The study of fluxes through such networks is informative and can give interesting insights even in the absence of detailed kinetic information. Uses linear optimization to determine the steady-state reaction flux distribution in a metabolic network by maximizing an objective function, such as ATP production or growth rate

8. Metabolic reconstruction Kyoto Encyclopaedia of Genes and Genomes (KEGG) - Pathway databases for several organisms BioCyc - Pathway databases for several organisms PEDANT - Genome annotations Reactome - Curated database of biological processes in humans Biomodels.net - Kinetic models of pathways, many published models from literature BRENDA - Biochemical and molecular information on enzymes SABIO-RK Database - System for the analysis of biochemical pathways – reaction kinetics Software tools Constraint-based reconstruction and analysis (COBRA) - Interfaces with MATLAB for extensive analysis of networks using FBA; performs gene deletions – single and multiple MetaFluxNet - Metabolic flux analysis CellNetAnalyzer - Structural and functional analysis of cellular networks SNA: Stoichiometric network analysis - Mathematica toolbox for stoichiometric network analysis Yana - Network reconstruction, visualization and analysis PathwayAnalyser - FBA and MoMA of metabolic networks; gene deletion studies Systems Biology Research Tool - Multiple methods for analysing stoichiometric networks SBML Software Guide - Resource list for software tools, model databases

9. Dynamic mass balance of the metabolic system : Using the stoichiometric matrix Sm*n relating the flux rates of enzymatic reactions vn*1 to time derivatives of metabolite concentrations xm*1 as dx=dt ¼ Sv v = [(v1v2.......... Vni) b1 b2....... Bnext] T At steady state, dx/dt¼ Sv ¼ 0. Therefore, the required flux distribution belongs to the null space of S. Adding constraints Constraints may be of four types :- (I) physico-chemical constraints, (ii) spatial or topological constraints, (iii) condition dependent environmental constraints and (iv) regulatory

10. Reference : https://link.springer.com/article/10.1007/s11306-015-0823-6?shared-article-renderer

11. Adding of biomass function FBA can alter a number of mathematically accepted solution to the steady state problems like Sv=o; but biological interest that we need is the one which produce desired metabolite in correct proportion.   when modelling the growth of an organism the objective function is generally defined as biomass. Linear programming can be used to find a single optimal solution. The most common biological optimization goal for a whole-organism metabolic network would be to choose the flux vector v that maximize the biomass function and denoted as Vbiomass or simply Vb Max Vb s.t. Sv=0

12. Advantages: L ess intensive input data required for constructing the model. C omputationally inexpensive. Time saver as it can calculate steady-state metabolic fluxes for large models over 2000 reactions in just few seconds on modern personal computers.  In bioprocessing engineering, it systematically identify modifications to the metabolic networks of microbes which are used in fermentation processes that improve product yields of industrially important chemicals such as ethanol and succinic acid . used for the identification of drug targets In various diseases.

13. Applications

14. Reference:- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3108565/ https://www.researchgate.net/publication/24201584_Flux_Balance_Analysis_of_Biological_Systems_Applications_and_Challenges