Application of metabolomics for cosmetics
Podium 47
Presented by: Celine Laperdrix
Omic sciences bring together several disciplines of biology that the name ends by omics such as genomics, transcriptomics, proteomics, metabolomics… If genomic is well known now, metabolomic is a more recent science that focuses on giving the broadest characterisation of the metabolome of one cell, one organ or a whole organism. The metabolome is composed of a large number of small metabolites (e.g from primary metabolites such as sugar, amino acids, nucleic acids, fatty acids, lipids…to secondary metabolites such as polyphenols, alkaloids, drugs, toxins, xenobiotics…). Metabolomics studies are currently done using combinations of liquid chromatography, mass spectrometry and/or nuclear magnetic resonance. One of their goal is to give a comprehensive snapshot of the physiological state of the studied extracts and identify differences between the observed chemical profiles. For each study, it is mandatory to take into account that a metabolite profile results from many factors like the genetic background or the influence of environmental factors.
The human skin is an organ with a surface area reaching 2m2 that provides interface with our environment. It is composed of numerous molecules coming from host cells, microbiota and external molecules, applied deliberately or not. Functioning of skin structures (cells, sweat glands, sebaceous glands, interstitial fluids…) and of its microbiota influence the quantity and the heterogeneity of skin metabolites. But, lifestyle (diet, medicines, smoke…), environment (inside or outside composition of the air, smoke, composition of clothes…) and everything touching our skin may interfere with its metabolites composition, such as cosmetics.
The skin surface can be sampled to detect and quantify metabolites, using metabolomics approaches. It has been done in pathological context, to identify biomarkers signing diseases (fibrosis, psoriasis, Parkinson’s disease or cancer). Until today, nobody has described metabolomics to assess cosmetics or active ingredient impact on skin metabolome. We demonstrated the interest and the great potential of metabolomics for our studies. Diverse methodologies for specimen collection and identification using metabolomics are available. For that study, our aim was to collect skin metabolites following a non-invasive method. In that goal, we avoided biopsy, suction blistering or other too invasive methodologies, as we wanted to access to long treatment effect (few weeks). We have perfected the sampling using swabs, after selection of materials, their preparation, time of contact, etc. Concerning metabolomics analysis, the chosen technology was HPLC hyphenated to high-resolution mass spectrometry (Orbitrap). With that technology, each skin sample chemical profile is described by a list of features. Features are variables with at least three properties: intensity, retention time and mass to charge ratio. The intensities variations of each features were statistically analysed using principal component analysis and T-tests. In theory, every feature could be linked to a metabolite by using the chemical information present in the data. Despite the use of high-resolution mass-spectrometry that identification step is not trivial and that why we have added to our experiment one fragmentation step using Orbitrap system capabilities. With that additional step, we could access (for some features) to MS/MS spectra that can be compared to internal or external databases, gives structural information, and helps in the annotation step.
We used those technics to screen the effect of active ingredients of interest on skin chemical profile. Panellists applied the formulated active on one cheek and the corresponding placebo formula on the other one, twice a day, during 28 days. Results of both were compared to the initial panellist’s skin profiles. With this method, we have found nearly 300 statistically significant features (in positive and in negative modes) that are differentially expressed on the skin. Some of these signals, can be linked to metabolites produced by the skin, the microbiota or both. They represent signature of formulas and active effects. All opened few ways of action and several mechanisms of interest, concerning host skin cells but also concerning skin microbiota.
Metabolomics study is described for the first time in a cosmetic context. It already seems to appear as a real powerful tool to go on in biological efficacy explanation and discovery.
The human skin is an organ with a surface area reaching 2m2 that provides interface with our environment. It is composed of numerous molecules coming from host cells, microbiota and external molecules, applied deliberately or not. Functioning of skin structures (cells, sweat glands, sebaceous glands, interstitial fluids…) and of its microbiota influence the quantity and the heterogeneity of skin metabolites. But, lifestyle (diet, medicines, smoke…), environment (inside or outside composition of the air, smoke, composition of clothes…) and everything touching our skin may interfere with its metabolites composition, such as cosmetics.
The skin surface can be sampled to detect and quantify metabolites, using metabolomics approaches. It has been done in pathological context, to identify biomarkers signing diseases (fibrosis, psoriasis, Parkinson’s disease or cancer). Until today, nobody has described metabolomics to assess cosmetics or active ingredient impact on skin metabolome. We demonstrated the interest and the great potential of metabolomics for our studies. Diverse methodologies for specimen collection and identification using metabolomics are available. For that study, our aim was to collect skin metabolites following a non-invasive method. In that goal, we avoided biopsy, suction blistering or other too invasive methodologies, as we wanted to access to long treatment effect (few weeks). We have perfected the sampling using swabs, after selection of materials, their preparation, time of contact, etc. Concerning metabolomics analysis, the chosen technology was HPLC hyphenated to high-resolution mass spectrometry (Orbitrap). With that technology, each skin sample chemical profile is described by a list of features. Features are variables with at least three properties: intensity, retention time and mass to charge ratio. The intensities variations of each features were statistically analysed using principal component analysis and T-tests. In theory, every feature could be linked to a metabolite by using the chemical information present in the data. Despite the use of high-resolution mass-spectrometry that identification step is not trivial and that why we have added to our experiment one fragmentation step using Orbitrap system capabilities. With that additional step, we could access (for some features) to MS/MS spectra that can be compared to internal or external databases, gives structural information, and helps in the annotation step.
We used those technics to screen the effect of active ingredients of interest on skin chemical profile. Panellists applied the formulated active on one cheek and the corresponding placebo formula on the other one, twice a day, during 28 days. Results of both were compared to the initial panellist’s skin profiles. With this method, we have found nearly 300 statistically significant features (in positive and in negative modes) that are differentially expressed on the skin. Some of these signals, can be linked to metabolites produced by the skin, the microbiota or both. They represent signature of formulas and active effects. All opened few ways of action and several mechanisms of interest, concerning host skin cells but also concerning skin microbiota.
Metabolomics study is described for the first time in a cosmetic context. It already seems to appear as a real powerful tool to go on in biological efficacy explanation and discovery.