Prebiotic score

A Prebiotic Score, also known as Prebiotic Activity Score,[1] is a term sometimes used to estimate the health effects of prebiotics in humans or animals. The idea is that prebiotics may have many different effects in the human gut, some of these may be quantified and combined to an overall score. For example, an increase in the populations of bifidobacteria or lactobacilli coincides with a relative increase in prebiotic activity; accordingly, an increase in enteric bacteria strains such as Clostridium perfringens result in a decrease of prebiotic activity.[1] Also, increases and reductions of certain enzymes may be used as factors in a prebiotic score.

Measure of the prebiotic effect

Measure of the prebiotic effect (MPE) is a quantitative analysis that takes into an account a number of dominant bacterial groups and end products of fermentation such as short-chain fatty acids (SCFA) and substrate assimilation.[2] MPE was developed by Jelena Vulevic[3] in conjunction with Glenn R Gibson and Robert Rastall and sponsored by Novartis Consumer Health[4]

Quantitative approaches

Several quantitative approaches have been developed to aid in the analysis of prebiotics and their individual and collective activity within the gut microbiome. These approaches are in part used to calculate the Measure of the Prebiotic Effect or (MPE).[3]

Prebiotic Index (PI)

One of the first quantitative approaches, the Prebiotic index or (PI), is a quantitative tool used to compare the prebiotic effect of dietary oligosaccharides.[5] The Prebiotic Index equation takes into account bifidobacteria (Bif), bacteroides (Bac), lactobacilli (Lac), and clostridia (Clos):
PI = (Bif/Total) - (Bac/Total) + (Lac/Total) - (Clos/Total)[1]

Rate of assimilation

The rate of assimilation is the measure of the substrate assimilation calculated by measuring the substrate concentration over time:[6]
St = substrate concentration after the time interval, t, e.g. in hours; S0 = initial substrate concentration and Ar = rate of substrate assimilation, e.g. per hour, e.g. during the exponential phase of bacterial population growth.
Rate of Assimilation: St = S0 - Art[3]

Rate of growth

Rate of growth is determined by an equation that is based on the rate of growth for the bacterial populations.
Rate of growth uses the following equation:
ln Nt = ln N0 + µt [7]

Adjusted prebiotic index

PIm = μmaxBif + μmaxLac + μmaxEub - μmaxBac - μmaxClos - μmaxEC - μmaxSRB[8]

Total short chain fatty acids

TSCFA = A + B + P + L

where A is acetate, B is butyrate, P is propionate and L is lactate[8]

Ratio of lactate to total short chain fatty acids

Ratio = dL/dTSCFA

Measure of the prebiotic effect

MPE=0.5(X2Y2+Y2Z2+Z2X2)0.5 [8]

See also

References
  1. "Archived copy". Archived from the original on 2015-01-21. Retrieved 2015-01-21.{{cite web}}: CS1 maint: archived copy as title (link)
  2. Charalampopoulos, Dimitris (2009). Prebiotics and Probiotics Science and Technology, Volumes 1-2. Springer Science & Business Media, 2009. p. 223. ISBN 978-0-387-79057-2.
  3. "Prebiotic effect analysis". Patents.google.com. Retrieved 11 July 2018.
  4. Vulevic, Jelena (2004). "Developing a quantitative approach for determining the in vitro prebiotic potential of dietary oligosaccharides". FEMS Microbiology Letters. 236 (1): 153–159. doi:10.1111/j.1574-6968.2004.tb09641.x. PMID 15212805.
  5. Palframan, R; Gibson, GR; Rastall, RA (2003). "Development of a quantitative tool for the comparison of the prebiotic effect of dietary oligosaccharides". Lett. Appl. Microbiol. 37 (4): 281–4. doi:10.1046/j.1472-765x.2003.01398.x. PMID 12969489.
  6. "Prebiotic Effect Analysis". Patentscope.wipo.int. Retrieved 11 July 2018.
  7. "Archived copy" (PDF). Archived from the original (PDF) on 2016-03-05. Retrieved 2015-01-21.{{cite web}}: CS1 maint: archived copy as title (link)
  8. Elise, Moore, Kristina (2011). "BIOLOGICAL ANALYSIS OF PREBIOTICS IN VARIOUS PROCESSED FOOD MATRICES". DigitalCommons@University of Nebraska - Lincoln.
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