Facial Skin Microbiota-Mediated Host Response to Pollution Stress Revealed by Microbiome Networks of Individual

The Causal Relationship Between Skin Microbiota and Facial Aging: A Mendelian Randomization Study

BACKGROUND

Facial aging is a complex process influenced by environmental factors, genetics, and lifestyle. The contribution of the skin microbiota to this process remains poorly understood.

METHODS

This two-sample Mendelian randomization (MR) study was performed using genome-wide genotype data from the UK Biobank and previously published studies on skin microbiota. The primary approach for MR analyses included inverse-variance weighting (IVW), MR-Egger regression, simple mode, weighted median, and weighted mode methods. Sensitivity analyses were performed to assess heterogeneity and pleiotropy, and reverse-direction MR analyses were performed to evaluate potential reverse causation.

RESULTS

The MR analysis identified ten skin microbiotas with potential causal relationships with facial aging. Protective skin microbiotas included Genus Finegoldia, ASV011 [Staphylococcus (unc.)], ASV008 [Staphylococcus (unc.)], phylum Firmicutes, Family Rhodobacteraceae, and ASV021 [Micrococcus (unc.)], which were negatively associated with facial aging. Conversely, Order Pseudomonadales, Family Moraxellaceae, ASV039 [Acinetobacter (unc.)], and phylum Bacteroidetes were positively associated with facial aging, indicating a risk factor for accelerated aging. Sensitivity analyses confirmed the robustness of these findings, and reverse-direction MR analyses did not suggest any reverse causation.

CONCLUSION

This study identified specific skin microbial that may influence facial aging and offered new insights into the rejuvenation strategies.

NO LEVEL ASSIGNED

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Compositional Variations between Adult and Infant Skin Microbiome: An Update

Human skin and its commensal microbiome form the first layer of protection to the outside world. A dynamic microbial ecosystem of bacteria, fungi and viruses, with the potential to respond to external insult, the skin microbiome has been shown to evolve over the life course with an alteration in taxonomic composition responding to altered microenvironmental conditions on human skin. This work sought to investigate the taxonomic, diversity and functional differences between infant and adult leg skin microbiomes. A 16S rRNA gene-based metataxonomic analysis revealed significant differences between the infant and adult skin groups, highlighting differential microbiome profiles at both the genus and species level. Diversity analysis reveals differences in the overall community structure and associated differential predicted functional profiles between the infant and adult skin microbiome suggest differing metabolic processes are present between the groups. These data add to the available information on the dynamic nature of skin microbiome during the life course and highlight the predicted differential microbial metabolic process that exists on infant and adult skin, which may have an impact on the future design and use of cosmetic products that are produced to work in consort with the skin microbiome.

Translational informatics for human microbiota: data resources, models and applications

With the rapid development of human intestinal microbiology and diverse microbiome-related studies and investigations, a large amount of data have been generated and accumulated. Meanwhile, different computational and bioinformatics models have been developed for pattern recognition and knowledge discovery using these data. Given the heterogeneity of these resources and models, we aimed to provide a landscape of the data resources, a comparison of the computational models and a summary of the translational informatics applied to microbiota data. We first review the existing databases, knowledge bases, knowledge graphs and standardizations of microbiome data. Then, the high-throughput sequencing techniques for the microbiome and the informatics tools for their analyses are compared. Finally, translational informatics for the microbiome, including biomarker discovery, personalized treatment and smart healthcare for complex diseases, are discussed.

InferLoop: leveraging single-cell chromatin accessibility for the signal of chromatin loop

Deciphering cell-type-specific 3D structures of chromatin is challenging. Here, we present InferLoop, a novel method for inferring the strength of chromatin interaction using single-cell chromatin accessibility data. The workflow of InferLoop is, first, to conduct signal enhancement by grouping nearby cells into bins, and then, for each bin, leverage accessibility signals for loop signals using a newly constructed metric that is similar to the perturbation of the Pearson correlation coefficient. In this study, we have described three application scenarios of InferLoop, including the inference of cell-type-specific loop signals, the prediction of gene expression levels and the interpretation of intergenic loci. The effectiveness and superiority of InferLoop over other methods in those three scenarios are rigorously validated by using the single-cell 3D genome structure data of human brain cortex and human blood, the single-cell multi-omics data of human blood and mouse brain cortex, and the intergenic loci in the GWAS Catalog database as well as the GTEx database, respectively. In addition, InferLoop can be applied to predict loop signals of individual spots using the spatial chromatin accessibility data of mouse embryo. InferLoop is available at https://github.com/jumphone/inferloop.

Deleterious Effect of Air Pollution on Human Microbial Community and Bacterial Flora: A Short Review

A balanced microbiota composition is requisite for normal physiological functions of the human body. However, several environmental factors such as air pollutants may perturb the human microbiota composition. It is noticeable that currently around 99% of the world's population is breathing polluted air. Air pollution's debilitating health impacts have been studied scrupulously, including in the human gut microbiota. Nevertheless, air pollution's impact on other microbiotas of the human body is less understood so far. In the present review, the authors have summarized and discussed recent studies' outcomes related to air pollution-driven microbiotas' dysbiosis (including oral, nasal, respiratory, gut, skin, and thyroid microbiotas) and its potential multi-organ health risks.

Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks

Co-occurrence networks inferred from the abundance data of microbial communities are widely applied to predict microbial interactions. However, the high workloads of bacterial isolation and the complexity of the networks themselves constrained experimental demonstrations of the predicted microbial associations and interactions. Here, we integrate droplet microfluidics and bar-coding logistics for high-throughput bacterial isolation and cultivation from environmental samples, and experimentally investigate the relationships between taxon pairs inferred from microbial co-occurrence networks. We collected Potamogeton perfoliatus plants (including roots) and associated sediments from Beijing Olympic Park wetland. Droplets of series diluted homogenates of wetland samples were inoculated into 126 96-well plates containing R2A and TSB media. After 10 days of cultivation, 65 plates with > 30% wells showed microbial growth were selected for the inference of microbial co-occurrence networks. We cultivated 129 bacterial isolates belonging to 15 species that could represent the zero-level OTUs (Zotus) in the inferred co-occurrence networks. The co-cultivations of bacterial isolates corresponding to the prevalent Zotus pairs in networks were performed on agar plates and in broth. Results suggested that positively associated Zotu pairs in the co-occurrence network implied complicated relations including neutralism, competition, and mutualism, depending on bacterial isolate combination and cultivation time.

Alteration of barrier properties, stratum corneum ceramides and microbiome composition in response to lotion application on cosmetic dry skin

Xerosis, commonly referred to as dry skin, is a common dermatological condition affecting almost a third of the population. Successful treatment of the condition traditionally involves the application of cosmetic products facilitating the moisturisation of the skin with a range of ingredients including glycerol and fatty acids. While the effectiveness of these treatments is not in question, limited information exists on the impact on the skin microbiome following use of these products and the improvement in skin hydration. Here, we describe improvements in skin barrier properties together with increased levels of cholesterol, ceramides and long-chain fatty acids following application of Body Lotion. Concomitant alterations in the skin microbiome are also seen via 16S rRNA metataxonomics, in combination with both traditional and novel informatics analysis. Following 5 weeks of lotion use, beneficial skin bacteria are increased, with improvements in microbiome functional potential, and increases in pathways associated with biosynthesis of multiple long chain fatty acids.

Recent Advances in Understanding the Structure and Function of the Human Microbiome

Trillions of microbes live within our bodies in a deep symbiotic relationship. Microbial populations vary across body sites, driven by differences in the environment, immunological factors, and interactions between microbial species. Major advances in genome sequencing enable a better understanding of microbiome composition. However, most of the microbial taxa and species of the human microbiome are still unknown. Without revealing the identity of these microbes as a first step, we cannot appreciate their role in human health and diseases. A shift in the microbial balance, termed dysbiosis, is linked to a broad range of diseases from simple colitis and indigestion to cancer and dementia. The last decade has witnessed an explosion in microbiome research that led to a better understanding of the microbiome structure and function. This understanding leads to potential opportunities to develop next-generation microbiome-based drugs and diagnostic biomarkers. However, our understanding is limited given the highly personalized nature of the microbiome and its complex and multidirectional interactions with the host. In this review, we discuss: (1) our current knowledge of microbiome structure and factors that shape the microbial composition, (2) recent associations between microbiome dysbiosis and diseases, and (3) opportunities of new microbiome-based therapeutics. We analyze common themes, promises, gaps, and challenges of the microbiome research.