Cosmetics

Cosmetic industry has to know the effects of a cosmetic product in order to express new claims. For this purpose, it is important to know the impacts of molecules on metabolism (metabolomics)  and on the proteins activities (proteomics). It also needs to know how products are metabolized and to control the biological components used for manufacturing.

We are available to discuss  our analytical methods. Feel free to contact us for any information that may support you for your projects.

Services and technologies

Sample types :

Skin explants, rebuilt skin, punches, fibroblasts, keratinocytes, …, serum, strips, swabs, hairs.

Discovery and determination of effects by relative « label-free » quantification and bioinformatics data processing

This method allows the qualitative and quantitative comparison of different proteomes. Typically this technique is used to compare two conditions, for instance healthy vs unhealthy, treated vs placebo, and so to identify biomarkers which presence or quantity shows a physiological condition.

The samples LC-MS profiles are compared and the different peptides pikes areas are calculated. These areas are compared to those acquired for the same peptides in a reference sample and so a protein relative quantity is determined.

In the same test, it is possible to identify the proteins by comparison with databases.

The relative identification and quantification data are then processed with the CORAVALID module which determines biological processes, molecular functions, cellular components and signaling and metabolic pathways related to analyzed proteins.

This allows to discover positive and toxic effects, and to develop specfic claims.

This approach is particularly well adapted to the study of skin including its microbiota part, as it is the unique way to reach the host and microbiota together, and it allows to know the functional level of the effects.

Demonstration of the effects of an ingredient or a cosmetic

Positive and negative effects are understood in a non-targeted way, bioinformatics allows to understand the impacted metabolic pathways.

Comparison of cells or biopsies or other cutaneous samples that have been treated with an active ingredient or a placebo by high resolution proteomics and associated CORAVALID bioinformatics, to generate a biology report on the useable claims.

Demonstration of the effects of abiotic stress on protein oxidation: RedOxmics.

All of the effects of stress on metabolism are apprehended with a focus on the most sensitive proteins.

Comparison of skin cells or swabs or other cutaneous samples that have undergone stress (UV, pollution, cigarette smoke ...) by high resolution proteomics and associated bioinformatics, integrating an oxidation profile on 18 redox reactions of the 10 sensitive amino acids , and oxidation index OxDeep. A biology report on the overall effects of stress is generated.

Demonstration of the effects of an ingredient or a cosmetic on the phosphorylation of proteins:

Protein phosphorylation is a crucial mechanism in many cellular regulations and strongly involved in virtually all physiological and pathological processes such as signal transduction, cell proliferation, differentiation, apoptosis or metabolism. Signaling processes involving phosphorylation are often deregulated during pathology or stress.

Comparison of cells or biopsies having undergone treatment or placebo by proteomics and high resolution phosphoproteomics and associated bioinformatics, allowing for each phosphorylated protein to know its phosphorylation sites and its changes in phosphorylation abundance. A biology report on the effects on the proteome and phosphoproteome is delivered.

Skin microbiota

The skin is a complex organ that now can be defined as having a human part and a microbial part. This part is the microbiota of the skin, and is very reactive to the effects of the environment. It can be studied with methods of genomics, proteomics, metabolomics.

-       Follow-up by quantitative PCRs of major species or genus, for example Staphylococcus sp. (Firmicutes), Corynebacterium sp. (Actinobacteria), Propionibacterium sp. (Actinobacteria). Other targets are possible depending on wished effects from product positioning, also at species level. Gives answer such as «  the product has/does not have an effect on tested genus ».

-       Metagenomics comparative study of microbiome by NGSequencing 16S rDNA. Gives answer in a report as : « The product/treatment does or does not impact the semi-quantitative composition and microbiome diversity».

-      Metaproteomics comparative study  of microbiome by relative quantification LC-MS/MS « shotgun proteomics » and bioinformatics/biostatistics dedicated data processing and analysis for microbiome : HolXplore^TM. Gives answer in a report as : “ Effects of the product on functions and interactions of host and microbiome simultaneously ”

Ingredient metabolism follow-up.

A fast and reliable identification of metabolites  is a critical point in the discovery of a new cosmetics. The goal is to obtain a fast structural identification and a complete characterization of the major and minor metabolites in one shot.

The method is based on the research and characterization of molecules produced by a treatment given to an organism. Molecules rough formulas are deduced from measured exact masses and isotopic patterns since molecules structures are deduced from their fragmentation patterns.

Follow-up by targeted method

The quantification of an active in a biological environment using a targeted method (Parallel Reaction Monitoring) is a key point to ensure this molecule is delivered at the right dose to its tissular/cellular target (Pharmacokinetics).

The approach is based on the quantification by Mass spectrometry using a targeted method (Multiple Reaction Monitoring). It allows measuring the quantity of the drug and corresponding metabolites.

Biomarkers follow-up

The effects on the physiological status need to be known.

Either the metabolic profiles perturbations (metabonomics) or the protein expression profiles variations (toxico-proteomics) of the treated skin can be followed. The identification and quantification of biomarkers are done using LC-MS/MS spectra differential analysis.

This approach is based on the comparison between positive (treated patients) and negative samples (untreated patients).. Identification of discriminating components (proteins or metabolites) is performed by databases interrogations and their relative quantification is performed by comparing peaks areas of both samples.