Charting host-microbe co-metabolism in skin aging and application to metagenomics data

基因组 微生物群 皮肤老化 生物 人体皮肤 人体微生物群 计算生物学 基因 细菌 遗传学 医学 皮肤病科
作者
Wynand Alkema,Jos Boekhorst,Robyn T. Eijlander,Steve Schnittger,Fini De Gruyter,Sabina Lukovac,K Schilling,Guus A. M. Kortman
出处
期刊:PLOS ONE [Public Library of Science]
卷期号:16 (11): e0258960-e0258960 被引量:4
标识
DOI:10.1371/journal.pone.0258960
摘要

During aging of human skin, a number of intrinsic and extrinsic factors cause the alteration of the skin's structure, function and cutaneous physiology. Many studies have investigated the influence of the skin microbiome on these alterations, but the molecular mechanisms that dictate the interplay between these factors and the skin microbiome are still not fully understood. To obtain more insight into the connection between the skin microbiome and the human physiological processes involved in skin aging, we performed a systematic study on interconnected pathways of human and bacterial metabolic processes that are known to play a role in skin aging. The bacterial genes in these pathways were subsequently used to create Hidden Markov Models (HMMs), which were applied to screen for presence of defined functionalities in both genomic and metagenomic datasets of skin-associated bacteria. These models were further applied on 16S rRNA gene sequencing data from skin microbiota samples derived from female volunteers of two different age groups (25-28 years ('young') and 59-68 years ('old')). The results show that the main bacterial pathways associated with aging skin are those involved in the production of pigmentation intermediates, fatty acids and ceramides. This study furthermore provides evidence for a relation between skin aging and bacterial enzymes involved in protein glycation. Taken together, the results and insights described in this paper provide new leads for intervening with bacterial processes that are associated with aging of human skin.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
通~发布了新的文献求助10
刚刚
1秒前
科目三应助Arnold采纳,获得10
1秒前
润润轩轩发布了新的文献求助10
2秒前
宗笑晴发布了新的文献求助10
2秒前
lucky完成签到,获得积分10
2秒前
糖糖发布了新的文献求助10
3秒前
3秒前
跳跃尔容完成签到,获得积分10
4秒前
wyblobin完成签到,获得积分10
4秒前
4秒前
5秒前
沉默沛岚完成签到,获得积分10
5秒前
丰知然应助宇文宛菡采纳,获得10
5秒前
所所应助tu采纳,获得30
6秒前
mechefy完成签到,获得积分10
6秒前
鲤鱼萧完成签到,获得积分10
7秒前
宗笑晴完成签到,获得积分10
7秒前
8秒前
小蘑菇应助头发乱了采纳,获得10
8秒前
代萌萌发布了新的文献求助10
9秒前
jucy发布了新的文献求助50
9秒前
9秒前
Lz完成签到,获得积分10
9秒前
Hello应助葛辉辉采纳,获得10
9秒前
秦嘉旎完成签到,获得积分10
10秒前
华仔应助通~采纳,获得10
10秒前
万能图书馆应助半颗橙子采纳,获得10
10秒前
樱铃完成签到,获得积分10
11秒前
11秒前
上官若男应助俭朴的明轩采纳,获得10
11秒前
1199发布了新的文献求助10
12秒前
英姑应助包容的过客采纳,获得10
13秒前
标致的战斗机完成签到,获得积分10
13秒前
科研人发布了新的文献求助10
14秒前
hl完成签到,获得积分10
14秒前
14秒前
14秒前
科研通AI5应助dingdong采纳,获得10
15秒前
Jasper应助幸福胡萝卜采纳,获得10
15秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527742
求助须知:如何正确求助?哪些是违规求助? 3107867
关于积分的说明 9286956
捐赠科研通 2805612
什么是DOI,文献DOI怎么找? 1540026
邀请新用户注册赠送积分活动 716884
科研通“疑难数据库(出版商)”最低求助积分说明 709762