Nutritionalgorithm

addElementTracker(model, Element, rxnTags)

Creates artificial metabolites and reactions that track the flux of a particular element through reactions with specified string tags.

USAGE:

[model] = addElementTracker (model, Element, rxnTags)

INPUTS:

• model – COBRA model structure with minimal fields:

  • .S - stoichiometric matrix

  • .c - objective coefficients

  • .ub - upper flux bounds

  • .lb - lower flux bounds

  • .mets - metabolite identifiers

  • .rxns - reaction identifiers

• Element – element you are interested in (e.g., ‘N’)

• rxnTags – string or cell array containing the strings that mark reactions of interest to keep track of

OUTPUTS:

model – the input model with added tracking reactions and the key “Track” reaction

convert_EX_to_diet(model)

Takes a model with typical exchange reactions (i.e., ‘EX_’) and translates them to uptake (diet) and secretion (exit) reactions.

USAGE:

[model] = convert_EX_to_diet (model)

INPUTS:

model – COBRA model structure with minimal fields:

• .S - stoichiometric matrix

• .c - objective coefficients

• .ub - upper flux bounds

• .lb - lower flux bounds

• .mets - metabolite identifiers

• .rxns - reaction identifiers

OUTPUTS:

model – the input model with new uptake (’Diet_’) and secretion (’Exit_’) reactions

getMolFormula(model, metabolite)

Takes a metabolite in a specified model and returns its molecular formula.

USAGE:

[molStr, molTable] = getMolFormula (model, metabolite)

INPUTS:

• model – COBRA model structure with minimal fields:

  • .mets - metabolite identifiers

  • .metFormulas - elemental formulas

• metabolite – a metabolite identifier present in the model

OUTPUTS:

• molStr – the molecular formula for the specified metabolite

• molTable – a cell array containing the breakdown of the metabolite by element

integrate_cVector_into_model(model)

Incorporates the c vector directly into the model as the reaction ‘obj_fun_rxn’.

USAGE:

[model] = integrate_cVector_into_model (model)

INPUTS:

model – COBRA model structure with minimal fields:

• .S - stoichiometric matrix

• .c - objective coefficients

OUTPUTS:

model – Augmented COBRA model with the objective reaction ‘obj_fun_rxn’ added

nutritionAlgorithm(model, rois, roisMinMax, options)

This algorithm identifies the minimal changes to a diet necessary to get a desired change in one or more reactions of interest (rois). If a metabolite is entered instead of a reaction, the algorithm will optimize the diet with a sink or demand reaction for the corresponding metabolite of interest. For a walkthrough of the algorithm, see NutritionAlgorithmWalkthrough.mlx To cite the algorithm, please cite Weston and Thiele, 2022 and the COBRA Toolbox as specified on opencobra.github.io/cobratoolbox/stable/cite.html

USAGE:

[newDietModel, pointsModel, roiFlux, pointsModelSln, menuChanges, detailedAnalysis] = nutritionAlgorithm (model, rois, roisMinMax, options)

INPUTS:

• model – COBRA model structure with minimal fields:

  • .S - stoichiometric matrix

  • .c - objective coefficients

  • .ub - upper flux bounds

  • .lb - lower flux bounds

  • .mets - metabolite identifiers

  • .rxns - reaction identifiers

  • .osenseStr - objective sense (‘max’ or ‘min’)

• rois – cell array of all reactions of interest

• roisMinMax – cell array of ‘min’/’max’ entries for rois

OPTIONAL INPUTS:

options – Structure containing the optional specifications:

• .display: display results “off” or “on”?

• .roiWeights: a vector of weights for each reaction of interest

default is equal to 1

• .targetedDietRxns: A nx2 cell array that specifies any dietary

items to target and the corresponding weight for adding the item.

• .foodRemovalWeighting: Determines the relationship of food

removal weight with the weights specified by targetedDietRxns. The following are valid inputs for foodRemovalWeighting.

• ‘ones’ -> all dietary reactions from targetedDietRxns have a removal weight of one

• ‘inverse’ -> all dietary reactions from targetedDietRxns have a removal weight of one

• ‘ditto’ -> weights are equal to that of targetedDietRxns

added weights - nx2 cell array -> a customized cell array that functions like targedDietRxns but instead allows costomized weights for removing a food item rather than adding it. - {} empty cell array -> (default) An empty array assumes all dietary reactions are available from removal with a weight of one

• .slnType: Specify if solution should be ‘Detailed’ or ‘Quick’.

  Default setting is ‘Detailed’

• .roiBound: ‘Unbounded’ or ‘Bounded’. Default is ‘Bounded’.

• .foodAddedLimit: Specify a limit to the points produced by

  adding food to the diet

• .foodRemovedLimit: Specify a limit to the points produced by

  removing food from the diet

• .OFS: the Objective Flux Scalar initiates a limiting threshold

for the solution’s objective function performance. A OFS of 1 means that the nutrition algorithm solution will produce a result that is atleast equal to, or greater than the maximum flux of the objective reaction on the original diet

OUTPUTS:

• newDietModel – a copy of the input model with updated diet reaction bounds to reflect recomended dietary changes

• pointsModel – the resulting model that is used to identify recomended dietary changes. It includes points reactions and food added/removed reactions.

• roiFlux – the flux values for each roi in the points solution

• pointsModelSln – the entire points solution to pointsModel

• menuChanges – summarizes the recommended dietary changes

• detailedAnalysis – solutions for each simulation conducted in the detailed analysis