The impacts of sodium lauroyl sarcosinate in facial cleanser on facial skin microbiome and lipidome

The human skin microbiome and lipidome are essential for skin homeostasis and barrier function, and have become a focus in both dermatological and cosmetic fields. However, the influence of surfactants commonly used in cosmetic products on the skin resident microbiome and lipidome remains poorly characterized.


| INTRODUC TI ON
The human skin is an ecosystem, the skin microbiome and the skin barrier relate symbiotically to affect each other in physical, chemical, and immunological ways. 1 The microbiome of the skin can affect host health both positively and negatively. 2,3On the one hand, skin bacteria exert a beneficial role by producing antimicrobial peptides, 4 disturbing accessory gene regulator quorum sensing pathways, 5,6 stimulating host defence 7 to suppress adventitious pathogens, and upregulating tight junction expression in keratinocytes, 8 generating protective ceramides 9 to strengthen barrier function.On the other hand, an imbalance in skin microbiome homeostasis, known as dysbiosis, may trigger immunological stress, 10 which is associated with a series of inflammatory diseases such as atopic dermatitis (AD) and acne. 11,12e pattern of the skin residential microbial community is mostly dependent on skin environment, particularly the abundance, and composition of the lipids.Skin lipids, composed of sebocyte-, keratinocyte-, and microbe-derived lipids, are among the most important compounds for maintaining skin barrier function. 13Furthermore, skin lipids can be viewed as a growth medium or bacteriostatic agent for residential microbial skin flora. 14Microorganisms metabolize them to produce "active" lipids, which alter skin metabolism.
Maintaining the homeostasis of the skin microbiome and lipidome plays a crucial role in building the skin barrier and maintaining human immune function.
Compared to intestine, the skin microbiome shows the higher individual diversity and is less stable. 15,16Signature differences in the abundance and diversity of the skin microbiome have been revealed even among healthy subjects. 175][26][27][28] Chemical surfactants are common ingredients in skin care products, and serve as emulsifiers, solubilizers, and detergents in creams and lotions. 29,30Surfactants can bind with proteins, remove lipids from the epidermal surface, contribute to the disorganization of liquid crystal structures in the intercellular lipids, and interact with living skin cells. 312][33][34] Meanwhile, surfactants is capable of inhibiting the growth of a number of microorganisms. 35The antimicrobial is associated with its adsorption and penetration by the porous cell wall followed by interacting with components of the cell membrane, lipids, and proteins.Furthermore, the metabolites produced after the degradation of the surfactant by skin microorganisms can also change the skin environment. 36in microbiome has emerged as a new field with high potential to develop disruptive solutions to manage skin health and disease.Although the effects of skincare products on the microbiome have been reported occasionally, 37,38 our knowledge about how surfactants disturb skin microbiome remains limited.As present in China, sodium lauroyl sarcosinate (SLS) is widely used as a surfactant in personal care products such as facial cleaners, shampoos, shower gel, and other cleaning products.However, the effects of SLS on the skin resident microbiome and lipidome remain poorly characterized.Our aim was to explore the influence of SLS used in skincare products on the skin microbiome and lipidome, and investigate the potential harm.To achieve this, we selected healthy volunteers who were instructed to use facial cleaners with or without SLS, and used a self-controlled method to evaluate the impacts.

| Study design and sample collection
The inclusion criteria were as follows: healthy individuals with no obvious skin diseases or hormonal disorders, male and female, ages 20-65.The exclusion criteria included conditions that the individuals with critical illness, mental health problems, smokers, those who had received antibiotics, antifungal drugs treatment within 1 month. 39

| DNA extraction
The cotton swab containing the sample was dipped in PB solution and shaken using a vortex shaker for 2 min (maximum gear 10×).Bacterial cells were collected by centrifugation (4°C, 14000 rpm, 1 min) and total DNA was extracted using the Fast DNA® SPIN Kit for soil (MP Biomedicals Co., Ltd., Shanghai, China) according to the manufacturer's instructions.
Quantitative real-time fluorescence amplification (qRT-PCR) was performed using a Green® Premix Ex Taq™ II kit (Takara Bio Inc., Beijing, China) according to the manufacturer's instructions.All qPCR reactions were conducted in three technical replicates.
Absolute quantitative method (double standard curve method) was selected to analyze the qRT-PCR data.Plasmid standards were used for the absolute quantification of the corresponding gene fragments.
The plasmid copy number was determined based on the molar mass derived from the plasmid and amplicon sequences.For each standard sample, the qRT-PCR system was used to measure the cycle threshold values, which were used to draw a standard curve by plotting the cycle threshold values versus the log value of the copy number.

| 16S rDNA and internal transcribed spacer amplicon sequencing
We entrusted the sequencing of 16S rDNA and internal transcribed spacer (ITS) to Guangzhou Gideo Biotechnology Co., Ltd.The total nucleic acid quality and concentration determined using a nucleic acid protein analyzer (Beckman, USA) and PCR verification met the sequencing requirements.The amplicon was sequenced doubleended (PE250) on the Illumina platform according to standard procedures.The raw fastq files were quality-filtered by DADA2. 42The abundance statistics of each taxonomy was visualized using Krona (version 2.6).The stacked bar plot of the community composition was visualized in R project ggplot2 package 43 (version 2.2.1).
The alpha diversity index is calculated in QIIME 44 (version 1.9.1).

Principal component analysis (PCA) was performed in R project
Vegan package(version 2.5.3).

| Lipidome metabolism
Lipidomic analysis was commissioned to Shanghai Zhongke New Life Co., Ltd.Analyses were performed using an UHPLC Nexera LC-30A ultra performance liquid chromatography system (SHIMADZU, Japan) coupled to Q-Exactive Plus (Thermo Scientific) in Shanghai Applied Protein Technology Co., Ltd.Lipid species were identified using the LipidSearch software version 4.2 (Thermo Scientific™) to process the raw data and for peak alignment, retention time correction and extraction peak area.

| Statistical analysis
Statistical analysis was performed using SPSS (version 26.0).The mean standard error of the mean was calculated for each quantitative data point (SEM).Unpaired samples were analyzed using unpaired t-tests and paired samples were analyzed using paired t-tests.Normally distributed data were analyzed using one-way analysis of variance (ANOVA) followed by a post-hoc Tukey's test to compare the differences between each group.The factoextra package (https:// CRAN.Rproje ct.org/ packa ge= facto extra ) and psych package (https:// CRAN.R-proje ct.org/ packa ge= psych ) in the R platform were used to perform PCA and Spearman's correlations, respectively (R version 4.0.5).

| Evaluation of skin biophysical parameters
The biophysical parameters of the facial skin of volunteers were roughly evaluated based on the changes in skin wrinkles, pores, porphyrins, and superficial lipid.After using a SLS free facial cleanser for 3 weeks, the volunteers showed a significant decrease in wrinkles (Figure 1A) and an increase trend in pores (Figure 1B).
The superficial lipid level showed an increasing trend (Figure 2D), and the porphyrin content, which is an evaluation index of lipophilic microorganisms, 45 showed the same trend significantly (Figure 1C).After continuing to use the SLS-added cleanser for 3 weeks, the content of porphyrins was significantly decreased (Figure 1C), and the content of wrinkles, pores, and superficial lipids appeared stable (Figure 1A,B,D).

| Quantitative analysis of facial skin microorganisms
To gain insight into the biomass variation of bacteria and fungi associated with SLS, 16S rDNA and 18S rDNA were amplified by qRT-PCR.
We found facial cleanser changed the skin microbial abundance, regardless of whether they contain surfactants.This was possibly due to cosmetics may affect the skin environment, such as chemical composition and hydration, as confirmed by previous study. 24,26,46,47mpared to the baseline stage, the copy number of 16S rDNA/ cm 2 skin was significantly higher at the end of the S-Free stage and increased further in the S-Add stage (Figure 2A).In parallel with the increased bacterial abundance, the volunteers' individual differences also increased.We observed that the influence of SLS on fungi abundance was consistent with that on bacteria (Figure 2B).

| Alpha diversity analysis of facial skin microbiome
Accumulation chart analyses of the baseline stage showed that the skin microbiome composition was conserved at high taxonomic levels, while more variance was observed at the lower taxonomic levels (Figure 3), which is in agreement with previous findings. 480][51] The SHDI incorporates both species richness and evenness when assessing community diversity.A higher SHDI value indicates a greater level of α diversity within the community.
The SHDI of the prokaryotic microbial community increased significantly after using the surfactant free facial cleanser for 3 weeks and decreased significantly after using the surfactant added facial cleanser for another 3 weeks (Figure 4A).The SHDI of the eukaryotic microbial community showed a continuous downward trend, but the results were not statistically significant (Figure 4B).

| Principal component analysis of skin microbiome
PCA was used to assess the effects of SLS on skin microbiome structure.Figure 5 shows the variations in the abundance of the dominant species and their major contributions to PC1 and PC2.
Notably, although the differences between individuals were large, similar shifts in the structure of microbiome could be induced by changing facial cleansers.SLS exposure has significant effects on prokaryotic microbiome structure, Acinetobacter, Escherichia-Shigella, Streptococcus, and Ralstonia contributed the most to the variability in the prokaryotic microbiota in the S-Add stage (Figure 5A).Meanwhile, although SLS had little effect on the structure of the eukaryotic microbiome, the dispersion of the dataset increased (Figure 5B).

| Analysis of facial lipidome
Facial lipid composition can provide a readout of microbiome status, and changes in the lipidome might be one of the direct results of using personal care products.After analyzing the data from all the volunteers from three stages, a total of 22 lipid compounds were identified:   Surfactants are widely used in care products and therefore, exposure to surfactants is long-term and continuous.However, their effects on the skin microbiome and lipidome remain poorly understood.We established a self-controlled experimental design to systematically study the effects of SLS by performing multiple-angle analysis of facial skin biophysical parameters, microbial biomass, diversity and structure of microbiome, structure of lipidome, and the relationship between microorganisms and lipids.
According to our analysis of skin biophysical parameters (Figure 1), wrinkles were significantly reduced and pores were significantly enlarged in the S-Free stage, accompanied by the corresponding increase of porphyrin and superficial lipid in the trend.This suggested that the weak cleansing force of the surfactant free facial cleanser led to the protective effect of the sebum barrier and proliferation of lipophilic microorganisms.[54] The biophysical parameters of the volunteers' skin did not change significantly after continuing to use the facial cleanser added SLS for another 3 weeks.We speculate that there are two reasons for this: (1) This may be due to the essential ability of the microbial community of the repaired skin barrier to respond to disturbance, 48,55 and (2) this may be due to the long interval from cleansing to sampling.Generally, while effectively dissolving the lipids on the skin surface, surfactants can also alter the physical properties of microbial cell membranes, resulting in antimicrobial effects. 56We observed an increase in the number of prokaryotic microorganisms in the S-Free stage.Unexpectedly, at the S-Add stage, the increasing trend of prokaryotic microorganisms continued and the difference in microbial number increased among individuals (Figure 2).Up to now, several studies have reported surfactants-resistant bacteria, which were isolated from various environments [57][58][59] and human organs such as lungs. 60Yoko et al. 58 reported that an anionic surfactant linear alkylbenzene sulfonate (LAS) showed the significant bactericidal activity to aquatic bacteria, but the bacteria in the family Enterobacteriaceae were suggested to be commonly resistant to LAS.We found Escherichia-Shigella contributed the most to the variability in the prokaryotic microbiota in the S-Add stage (Figure 5).
As the SHDI decreased and the microbiome structure changed, we speculate that some surfactant resistant strains (Escherichia-Shigella might, a potential candidate) might be responsible for the increase of prokaryotic microorganisms at the S-Add stage.The effect of SLS on the number of eukaryotic microorganisms was not as obvious as that on prokaryotic microorganism numbers.
The SHDI was used to determine the effects of SLS on alpha diversity of skin microbiome (Figure 4).Use of cosmetics was reported to significantly increase the bacterial diversity, 24,61 but has little study on fungi.According to our result, SLS in the facial cleanser significantly reduced bacterial diversity, but had almost no effect on fungal diversity.We speculate that the influence of surfactants on the bacterial diversity is due to the destruction of the lipid layer (chemical barrier), which affects the environment and nutrition of lipophilic microorganisms, such as Cutibacterium and Staphylococcus (Figure 5A).
][34]36 The use of SLS added in facial cleansers shifted the structure of the microbiome, regardless of whether it was a prokaryotic or eukaryotic microbiome (Figure 5).Notably, some genera, such as Acinetobacter, Escherichia-Shigella, and Streptococcus, which contributed most to the variability in the surfactant stage, were considered as the taxon to which opportunistic pathogen species belong.
Ralstonia, not a core genus in the skin, may have the ability to metabolize cosmetics components. 26Lipidome analysis demonstrated that SLS significantly increased the abundance of PG and PC and decreased that of Cer (Figure 6).
Considering that PG serves a primary structural component of prokaryotic membranes, 62 we believe that the increase of PG abundance in the lipidome at the S-Add stage may be related to the increasing of prokaryotic microorganisms caused by the addition of SLS in the facial cleanser.The aforementioned inference is supported by the findings in Figure 2A.The decrease in Cer level indicates a decrease of Staphylococcus epidermidis which secretes a sphingomyelinase that acquires essential nutrients for the bacteria and assists the host in producing ceramides. 9Combining the results of Figure 5A and Figure 6, we considered that the imbalance of lipidome structure provided "soil" for the proliferation of conditional pathogenic bacteria and might aggravate skin diseases or inflammatory reactions.
In brief, SLS in facial cleanser mainly affected the skin lipids and the abundance and structure of prokaryotic microbiome.SLS is an ingredient of concern that has the potential to adversely impact the chemical and microbial barriers, even the physical and immune barriers.Surfactants can enhance the instability of the skin surface microbial community and may provide an opportunity for potentially pathogenic microbes to establish diseases.As this was a pilot study, the sample size was small and the types of surfactants tested were limited.However, these findings are useful for reminding us to be vigilant about the ingredients in personal care products, even the common ingredients, and designing effective formulations for protecting barrier function of skin.

AUTH O R CO NTR I B UTI O N S
-41 A total of 16 volunteers (nine females and seven males, 21-26 years) were selected.All the volunteers signed an informed consent form.During the experiment, the volunteers were required to follow the study design and use the instructed cosmetics.Based on their wide use in the field of daily chemicals, we chose SLS (Panda International Trade Co., Ltd., Shanghai, China) as the representative surfactant.The molecular formula of SLS is C 15 H 28 NO 3 Na.We made a facial cleanser comprising water, maize extract, Lactobacillus fermentation products, glycerol, modified corn starch, betaine, xanthan gum, methyl isothiazolinone, magnesium nitrate, magnesium chloride, and 8% SLS was included during the surfactant-added stage.The facial cleanser was produced by Onlystar Biotechnology Co., Ltd.(Shandong, China).The amount of surfactant added to the products conformed to the limits set by the "Cosmetic Safety and Technical Specification" (2015 edition, China).The experiment was conducted in three stages: (1) the baseline stage, where the volunteers maintained their normal routines; (2) surfactant-free (S-Free) stage, where the volunteers were required to use a surfactant-free facial cleanser for 3 weeks; and (3) surfactant-added (S-Add) stage, where the volunteers were required to use facial cleansers supplemented with 8% SLS for another 3 weeks.Biophysical parameters analysis of the skin and collection of samples were performed at the end of each stage.The volunteers were instructed to wash their faces with clean water one night prior to data collection, and data were collected by 9 am the next day.In this process, the area specified on the sterile specification board (5 × 5 cm each on the left and right cheeks) were swiped 50 times each in a circular motion using disinfected cotton swabs.The cotton swabs were placed in sterile EP tubes and stored at −80°C for nucleic acid and metabolic analyses.

A
standardized process was established for measuring wrinkles, pores, porphyrins, and superficial lipids in the skin using the VISIA® Skin Analysis System (CANFIELD ScientificInc., Parsippany, NJ, USA) and a Skin-SP skin analyzer (Antsci, Guangzhou, China).The requirements for the use of VISIA were as follows: (1) the volunteers were asked to wear hair bands to prevent hair from falling on the face; (2) the volunteers were asked to close eyes all the time to prevent UV light; (3) the volunteers should not have any facial expression during the measurement; (4) the volunteers were asked to keep the same measurement position when measuring for many times.In addition, all the tests were operated in a constant temperature and humidity room.Each test was repeated three times to ensure the accuracy and reliability of the experimental data.

F I G U R E 1
The effect of sodium lauroyl sarcosinate (SLS) on facial skin biophysical parameters: (A) wrinkles, (B) pores, (C) porphyrin, and (D) superficial lipid.Baseline represents baseline stage, where the volunteers maintained their normal routines; S-Free represents SLS-free stage, where the volunteers were required to use a SLS-free facial cleanser for 3 weeks; and S-Add represents SLS-added stage, where the volunteers were required to use facial cleansers supplemented with 8% SLS for another 3 weeks.Biophysical parameters were collected at the end of each stage.The data measured by VISIA® Skin Analysis System and Skin-SP skin analyzer are relative values, which can only be used for comparison between groups.*p < 0.05.F I G U R E 2 The effect of sodium lauroyl sarcosinate on numbers of bacteria and fungi.The quantitative analysis of 16S rDNA (A) and 18S rDNA (B) by qRT-PCR.Copy number/cm 2 represents the copy number of 16S rDNA or 18S rDNA detected on the surface of the facial skin per square centimeter.The representation of groups (Baseline, S-Free, S-Add) is consistent with Figure 1.*p < 0.05; **p < 0.01; ***p < 0.001.

F I G U R E 3
Distribution of prokaryotic and eukaryotic microorganisms of baseline group at phylum and genu levels.

F I G U R E 4
The effect of sodium lauroyl sarcosinate on SHDI of prokaryotic (A) and eukaryotic (B).The representation of groups (Baseline, S-Free, S-Add) is consistent with Figure1.**p < 0.01; ***p < 0.001.

F I G U R E 5
PCA plots based on the prokaryotic (A) and eukaryotic (B) changes.The blue dots represent the baseline group, gray square represents the group without sodium lauroyl sarcosinate (SLS), the yellow triangle represents the group with SLS.Box plots show the overall distribution of PC1 and PC2 scores within each group.*One-way ANOVA p < 0.05; **One-way ANOVA p < 0.01; ***One-way ANOVA p < 0.001.

Fanglu
Yu and Congcong Wang designed the research study.Xuan Meng and Zhaoying Han and Dongxiao Chen contributed essential reagents or tools.Congcong Wang, Fanglu Yu, Zhengmei Huang, Shulin Liu and Dongqing Liu analyzed the data.Fanglu Yu F I G U R E 6 Analysis of facial lipidome.(A) Number of lipid molecules.The abscissa represents the detected lipid subclasses, and the ordinate represents the number of lipid molecules under the subclasses.(B)Volcano plots displaying the differential lipid molecules.The red triangles are lipids with a p < 0.05 and an absolute fold change (log2) larger than two (triangles, up-regulated; inverted-triangles, down-regulated).(C)Heatmap displaying the hierarchical clustering of differential lipid compounds with a p < 0.05 (red, up-regulated; blue, down-regulated).(D)Heatmap for the Spearman r correlations between lipid compounds (Cer, PC, PG) and microorganisms.*p < 0.05; **p < 0.01; # p < 0.1.