MatLab Modelling of Skin Microbial Interaction during Dysbiosis
Two different types of microorganisms are present on the skin, Commensals and Pathogens.
S. epidermidis and C. acnes are the two most fundamental bacteria in the skin and are considered as commensal bacteria because they are harmless in healthy condition. The second type are harmful and pathogenic microbes that colonise the skin and lead to infections and inflammation. S.aureus is one of the most predominant pathogenic bacteria in the skin. (Claudel et al., 2019 ; Fourniere et al., 2020)
In healthy skin microbiota S. epidermidis and C. acnes interact among each other to protect against and prevent pathogens, as well as participate in skin equilibrium with the secretion of beneficial metabolites. Thus they keep each other's population in balance and prevent growth of S.aureus. (Fourniere et al., 2020)
The various interactions can be summarised as follows
- C. acnes inhibits proliferation of S. epidermidis through hydrolyzing sebum triglycerides and release of propionic acid
- C. acnes releases coproporhyrin III promoting S. aureus biofilm
- S. epidermidis inhibits proliferation of C. acnes through succinic acid (Claudel et al., 2019)
- S. epidermidis can inhibit S. aureus biofilm formation with production of the serine protease glutamyl endopeptidase (Esp). Moreover, when Esp-expressing S. epidermidis induces keratinocytes to produce antimicrobial peptides via immune cell signalling, S. aureus is effectively killed. (Byrd et al., 2018)
During a condition called Dysbiosis there is an imbalance in skin microbiota distribution due to which several skin problems are caused. Sudden over-colonisation of the pilosebaceous unit in the skin by C. acnes can lead to a loss of diversification, loss of metabolic balance and potentially causing acne. Recent research has shown that a loss of microbial diversity and loss of balance between C. acnes phylotypes could also lead to dysbiosis. (Fourniere et al., 2020).
The interaction among the skin microbiome during Balanced skin and Disbiosys has been depicted using a simple MATLAB Model.
Figure1 (n1.gif) shows the percentage bacterial distribution and level of metabolite concentration in the normal skin microbiome. A level of 1 on the y-axis in the graphs for metabolite concentration indicates a normal level, values lesser than 1 mean a decrease in concentration relative to the normal level while values higher than 1 indicate a rise in concentration relative to the normal level. A pictorial depiction of microbial distribution is modeled in a 40*40 grid animation as shown in figure 2(n2.gif).
Figure 1: Percentage of bacterial distribution and metabolite concentration in normal skin
Figure 2: A pictorial depiction of microbial distribution
Similarly, for the case of Dysbiosis, figure 3 (d1.gif) and figure 4(d2.gif) depict the bacterial percentage distribution, variation in the levels of various metabolites, and microbial distribution the resolution imbalance in microbial distribution is as seen in the animation.
Figure 3: Percentage of bacterial distribution and metabolite concentration in dysbiosis
Figure 4: A pictorial depiction of microbial distribution in dysbiosis
Assumptions of the Model
The crucial assumptions made in the MATLAB model are as follows:
The skin is modelled as a two dimensional grid on MATLAB that represents a part of the skin also known as the face & scalp sebaceous unit.
Under balanced skin conditions the distribution of skin microbiota is assumed to be 70% C.acnes, 20% S.epidermidis, 1% S.aureus and 9% of other bacteria. (Byrd et al., 2019)
The number of square units in the grid signifies the population density of the different bacteria where each colour is associated with one bacteria. The population density depends on the growth and death rate of each type of bacteria.
The growth and death rates are assumed to be proportional to the concentration of a certain metabolite secreted in the skin. The constants of proportionality have been assumed arbitrarily to fit the model and do not represent actual values.
The proportionality relationships used are
Growth rate of C.acnes and S.epidermidis is constant
Death rate of C.acnes is proportional to the concentration of Succinic acid
Death rate of S.epidermidis is proportional to the concentration of Propionic acid
Growth rate of S.aureus is proportional to the concentration of coproporhyrin III
Death rate of S.aureus is proportional to the concentration of glutamyl endopeptidase (Esp)
During dysbiosis there is a change in the values of proportionality constants for the growth and death rates leading to imbalance in bacterial population density.
Reference (APA format)
- Claudel, J. P., Auffret, N., Leccia, M. T., Poli, F., Corvec, S., & Dréno, B. (2019). Staphylococcus epidermidis: a potential new player in the physiopathology of acne?. Dermatology, 235(4), 287-294.
- Byrd, A. L., Belkaid, Y., & Segre, J. A. (2018). The human skin microbiome. Nature Reviews Microbiology, 16(3), 143-155.
- Fourniere, M., Latire, T., Souak, D., Feuilloley, M. G., & Bedoux, G. (2020). Staphylococcus epidermidis and Cutibacterium acnes: two major sentinels of skin microbiota and the influence of cosmetics. Microorganisms, 8(11), 1752.‘