Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects

Galkin, Fedor; Aliper, Aleksandr; Putin, Evgeny; Kuznetsov, Igor P.; Gladyshev, Vadim N.; Zhavoronkov, Alex

doi:10.1101/507780

Cited by 50 publications

(41 citation statements)

References 96 publications

(60 reference statements)

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“…However, the variation in gut microbiome between populations, as a result of differences in geography, life style, diet, age, genetics and possible other factors has been reported to be more extensive than the variation between males and females [57]. Published literature regarding the effect of age on the gut microbiota indicates that whereas the gut microbiome is very dynamic with increasing microbial diversity in the early years of life, the gut microbiota in healthy adults is relatively stable [58] albeit recent studies do indicate that the gut microbiota can serve as a chronological marker [59,60].…”

Section: Discussionmentioning

confidence: 99%

Metagenomics analysis reveals features unique to Indian distal gut microbiota

et al. 2020

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Various factors including diet, age, geography, culture and socio-economic status have a role in determining the composition of the human gut microbiota. The human gut microbial composition is known to be altered in disease conditions. Considering the important role of the gut microbiome in maintaining homeostasis and overall health, it is important to understand the microbial diversity and the functional metagenome of the healthy gut. Here, we characterized the microbiota of 31 fecal samples from healthy individuals of Indian ethnic tribes from Ladakh, Jaisalmer and Khargone by shotgun metagenomic sequencing. Sequence analysis revealed that Bifidobacterium and Prevotella were the key microbes contributing to the differences among Jaisalmer, Khargone and Ladakh samples at the genus level. Our correlation network study identified carbohydrate-active enzymes and carbohydrate binding proteins that are associated with specific genera in the different Indian geographical regions studied. Network analysis of carbohydrate-active enzymes and genus abundance revealed that the presence of different carbohydrate-active enzymes is driven by differential abundance of genera. The correlation networks were different in the different geographical regions, and these interactions suggest the role of less abundant genera in shaping the gut environment. We compared our data with samples from different countries and found significant differences in taxonomic composition and abundance of carbohydrateactive enzymes in the gut microbiota as compared to the other countries. OPEN ACCESS Citation: Kaur K, Khatri I, Akhtar A, Subramanian S, Ramya TNC (2020) Metagenomics analysis reveals features unique to Indian distal gut microbiota. PLoS ONE 15(4): e0231197. https://doi.org/ 10."Man as a superorganism: Understanding the Human Microbiome (HUM-CSIR-BSC0119)". Funder URL: https://www. csir.res.in/ The funders had no role in study design, immunomodulation [13], defense against pathogens [14], nutrient and energy harvest, and metabolism [15][16][17][18]. Considering the important role of the gut microbiome in maintaining homeostasis, it is important to understand the microbial diversity and the functional metagenome of the healthy gut.Despite the fact that significant intra-and inter-individual variations exist in the taxonomic composition of microbial communities in the human distal gut, there are several initiatives aiming to find common patterns among two or more different groups of interest. Identifying the differences and similarities among the healthy gut microbiota between two geographies has been important to understand the impact of the environment and diet. With this aim, several metagenomics initiatives have been taken in several regions across the world such as China [7,18], Russia [19], Europe [20,21], USA [22], Venezuela [1], Africa [23], Ireland [2], Italy [24], Japan [25] and Korea [26]. Several studies have previously been performed on Indian subjects, too, with their wide focus on healthy and malnourished children [27,28], le...

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Section: Discussionmentioning

confidence: 99%

Metagenomics analysis reveals features unique to Indian distal gut microbiota

et al. 2020

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“…As well, age‐thresholds, if any, for other microbiota products need to be established and reasoned. Waiting for these issues to be further evaluated, a recent investigation demonstrated that some bacteria are important in predicting age, as the abundance and loss of certain bacteria associated with person's lifetime (Galkin et al, ). We thus think that the tryptophan deficiency from a certain age may be associated to the co‐occurring changes in microbial composition and ecological interactions within the gut.…”

Section: Discussionmentioning

confidence: 99%

Functional microbiome deficits associated with ageing: Chronological age threshold

et al. 2019

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Composition of the gut microbiota changes during ageing, but questions remain about whether age is also associated with deficits in microbiome function and whether these changes occur sharply or progressively. The ability to define these deficits in populations of different ages may help determine a chronological age threshold at which deficits occur and subsequently identify innovative dietary strategies for active and healthy ageing. Here, active gut microbiota and associated metabolic functions were evaluated using shotgun proteomics in three well‐defined age groups consisting of 30 healthy volunteers, namely, ten infants, ten adults and ten elderly individuals. Samples from each volunteer at intervals of up to 6 months (n = 83 samples) were used for validation. Ageing gradually increases the diversity of gut bacteria that actively synthesize proteins, that is by 1.4‐fold from infants to elderly individuals. An analysis of functional deficits consistently identifies a relationship between tryptophan and indole metabolism and ageing (p < 2.8e−8). Indeed, the synthesis of proteins involved in tryptophan and indole production and the faecal concentrations of these metabolites are directly correlated (r2 > .987) and progressively decrease with age (r2 > .948). An age threshold for a 50% decrease is observed ca. 11–31 years old, and a greater than 90% reduction is observed from the ages of 34–54 years. Based on recent investigations linking tryptophan with abundance of indole and other “healthy” longevity molecules and on the results from this small cohort study, dietary interventions aimed at manipulating tryptophan deficits since a relatively “young” age of 34 and, particularly, in the elderly are recommended.

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“…These results from both mice and humans suggested that gut microbiota is relatively stable in younger adulthood and it will become more unsteady after entering older age. Recently, researchers studying the gut bacteria of thousands of people found the microbiome could be used as a biological age clock to predict the age according to machine learning [38]. Research on age-dependent patterns of gut microbial diversity in human adults found a strong association between age and alpha diversity was kept until 40 years old [39].…”

Section: Discussionmentioning

confidence: 99%

Ageing-related bacterial features in different segments of the mice gastrointestinal tract

Zhou

Sun

Li³

et al. 2019

Preprint

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Background: Ageing is associated with alternations of gastrointestinal (GI) microbiota according to metagenome sequencing. However, the most commonly used sequencing samples were from feces, therefore it remains unknown how the upper gastrointestinal microbiota changes with age and to what extent the fecal can represent the gastrointestinal microbiota. To investigate associations between the microbiota of whole GI tract and ageing, we compared microbial diversity and composition of six GI segments in different phenotypes with a mouse model. Results: Microbial α and β diversity were significantly different between the upper and lower GI tract. The jejunum and ileum samples had significantly lower phylogenetic diversity than large intestinal and stomach did (P < 0.01). About 22.9% core OTUs (n=80) were shared by the whole GI tract, and fecal represented significantly higher microbiota with content from large intestine than content form upper GI tract (82.7% vs. 65.2%, P <0.001). Sutterella, Aggregatibacter, Lactococcus, Lactobacillus and Streptococus were significantly enriched in the upper GI tract, while 14 anaerobes such as Ruminococcus were significantly enriched in the lower GI tract (P < 0.05). The elderly mice had the significant microbial dissimilarity (both in α and β-diversity) with the young- and middle-aged ones. These differences were dependent on GI segments; especially in the lower GI tract, more obvious variations were found. However, the age-associated change was smaller when it compared with the high-fat diet treated mice. Conclusion: The GI microbiota was gradually changed with age and the changes were affected by GI segments. The microbial interactions with host motivate future studies exploring the specified GI microbiota interventions of disease. Keywords: Healthy ageing, Gut microbiota, 16S rRNA sequencing, Gastrointestinal tract, mice

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Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects

Cited by 50 publications

References 96 publications

Metagenomics analysis reveals features unique to Indian distal gut microbiota

Metagenomics analysis reveals features unique to Indian distal gut microbiota

Functional microbiome deficits associated with ageing: Chronological age threshold

Ageing-related bacterial features in different segments of the mice gastrointestinal tract

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