Integration of skin phenome and microbiome reveals the ­key role of bacteria in human skin aging

Abstract

Background: Despite the complexity, distinct ecological niches are believed to primarily drive the skin microbiome composition. Meanwhile, skin aging is a dynamic process with a spectrum of phenotypical changes, making it an attractive model for studying microbiome-phenotype interactions. Although a large number of studies confirmed the impact of chronological age in skin bacterial communities, the understanding of cross-kingdom microbiome variation with skin aging remains minimal. And this is not trivial because one’s skin condition or perceived age may deviate largely from their actual age as skin aging is a complex process combining chronological and extrinsic aging. Results: To this end, 822 facial microbial samples and skin phenotypes from the corresponding area were assessed in a Chinese cohort, the largest population size to date for skin shotgun metagenomic profiling. Our data revealed that among 14 measured variables, porphyrin and chronological age explained the most significant microbial variability. Consistent with previous studies based on 16S rRNA gene sequencing, we revealed increased biodiversity with aging and further specified age-associated species across kingdoms. While the abundance of most bacteria increased with age, two species, Cutibacterium acnes and Aeromicrobium choanae, declined. Microbiome undergoes active function selection from energy demands/growth to stress adaptation along aging. In addition, we characterized microbial changes in skin aging, asa combined consequence of both intrinsic and extrinsic reasons and reflecting the actual dynamic of niche conditions rather than chronological age. Using the multiple linear regression model, we predicted premature-aging/delayed-aging-related microbial species, mainly localizing to Moraxella osloensis and C. acnes. Furthermore, we validated the biological functions in vitro of some host-microbe interactions predicted by the microbiome-skin phenome association network. M. osloensis regulated collagen metabolism, extracellular matrix assembly and promoted cell senescence in human keratinocyte and fibroblast cells. Conclusions: We presume that application of both culture-independent and culture-dependent approaches can advance a good understanding of microbiome-phenotype interactions. Our study is of significance for designing interventions against aging-related skin conditions.

Facial Skin Microbiome Composition and Functional Shift with Aging

“…The results of this study confirmed some observations previously made using 16S rRNA sequencing studies [24][25][26]28,30,33,42] or using more recent whole-genome sequencing (WGS) studies [27,31,32]. The study results first confirmed that microbial diversity increases during aging [24][25][26][27][28][29]41], largely contributed by shifting Proteobacteria populations and Actinobacteria [24,[28][29][30] or Lactobacillales [43].…”

“…Moreover, changes in the microbial functional profile with aging were also reported thanks to deeper functional genomic analyses [25,27,32,35]. Finally, functional evaluation after keratinocytes and fibroblasts treatment by aging-modulated taxa, namely Streptococcus pneumoniae or infantis secretomes [35], or by C. anes and Moraxella osloensis [31], helped to better understand the contribution of those specific taxa to skin aging traits.…”

“…Studies on the cutaneous microbiome, including both microbial and genomic components, across different age groups have highlighted the dynamic nature of skin microbial communities: beginning at the early stage of life following the initial exposure to the maternal microbiome and continuing with shifts in community structure throughout puberty through to old age [23]. Thus, it has been shown that skin microbiome diversity increases with skin aging [24][25][26][27][28] and that this change in diversity is largely contributed by shifting Actinobacteria an Proteobacteria populations [24,29,30] with the Cutibacterium population decreasing on aged skin [26] and more particularly the C. acnes population [24,25,27,31,32], while Corynebacteria populations increase [24,26,29,32,33].…”

“…In that category, interest increased for products addressing skin microbiota supported by studies on differences by age, ethnicity, gender or environmental stress exposure. Consequently, correlations between the age-related changes in the skin microbiome and host metadata (physiology, medication, lifestyle, health or clinical skin features) were broadly investigated [24][25][26][27][28][30][31][32][33]. Interestingly, those correlations highlighted the link between specific taxa or even more precisely specific clades (for S. epidermidis or C. acnes), and clinical skin characteristics such as high or low levels of skin moisture, transepidermal water loss (TEWL), porphyrin, sebum production, dullness, dark spots, wrinkle grade and dermal collagen quantity/quality.…”

A multi-study analysis enables identification of potential microbial features associated with skin aging signs

“…In the present analysis, we focused on samples from cheek skin, which is the key body site for apparent age. More recent studies are shedding additional light on associations of the skin microbiome, notably particular clades of S. epidermidis or C. acnes, with biophysical traits of skin aging, such as collagen quality and quantity (Zhou et al, 2023a;Xia et al, 2023). Our study adds to this nascent, but growing body of knowledge aiming to better understand the implications of the microbiome in skin aging, by identifying the changes associated with signs of skin aging, rather than chronological aging alone.…”