Project description:Age-related changes in human gut microbiota composition have been reported, and such changes might be influenced by the intake of nutrients or diets. To investigate the effects of aging on the gut microbiota independent of nutrient effects, we analyzed the gut microbiomes of 126 micro-pigs at a wide range of ages from newborns to 10 years old. The micro-pigs were reared in a constantly controlled environment. The diversity of the gut microbiome was found to continuously change with age. We also found associations between age and specific members and functions of the gut microbiome. Consistent with previous studies on the human gut microbiome, beneficial microbes including probiotic bacteria and short-chain fatty acid-producers decreased in older pigs, whereas Bacteroides increased with age. Based on the correlation network, Bacteroides seemed to have an important role in determining the relative abundances of other beneficial microbes. Our results suggest that maintaining beneficial gut microbes at a specific ratio corresponding to a certain age might contribute to a younger gut microbiome-age. Furthermore, due to similarities with the human system, micro-pigs are a useful animal model to elucidate the links between aging and the microbiome.
Project description:Aging is a complex physiological process associated with degenerative disorder of metabolism and immune function, which contributes to the occurrence of senile diseases. The gut microbiota affects systemic inflammation in aging processes probably through metabolism, but their relationship is still unclear. In this study, 16S-rRNA-sequencing technology, gas chromatography-time-of-flight mass spectrometry (GC-TOFMS)-based metabolic profiling, and immune factor analysis combined with advanced differential and association analysis were employed to investigate the correlation between the microbiome, metabolome, and immune factors in male Wistar rats across lifespan. Our findings showed significant changes in the ileum microbiome and serum metabolome compositions across aging process. A two-level strategy was applied to demonstrate that key metabolites associated with age such as 4-hydroxyproline, proline, and lysine were clustered together and positively correlated with beneficial microbes including Bifidobacterium, Lactobacillus, and Akkermansia. Function analysis explored association between serum metabolite class and specific gut bacteria's metabolism pathways. Further correlation analysis on all the alteration patterns provided an interaction network of main immune factors such as IL-10, IgA, IgM, and IgG with key gut bacteria and serum metabolites. This study offers new insights into the relationship between immune factors, serum metabolome, and the gut microbiome.
Project description:Aging has a multi-faceted impact on brain structure, brain function and cognitive task performance, but the interaction of these different age-related changes is largely unexplored. We hypothesize that age-related structural changes alter the functional connectivity within the brain, resulting in altered task performance during cognitive challenges. In this neuroimaging study, we used independent components analysis to identify spatial patterns of coordinated functional activity involved in the performance of a verbal delayed item recognition task from 75 healthy young and 37 healthy old adults. Strength of functional connectivity between spatial components was assessed for age group differences and related to speeded task performance. We then assessed whether age-related differences in global brain volume were associated with age-related differences in functional network connectivity. Both age groups used a series of spatial components during the verbal working memory task and the strength and distribution of functional network connectivity between these components differed across the age groups. Poorer task performance, i.e. slower speed with increasing memory load, in the old adults was associated with decreases in functional network connectivity between components comprised of the supplementary motor area and the middle cingulate and between the precuneus and the middle/superior frontal cortex. Advancing age also led to decreased brain volume; however, there was no evidence to support the hypothesis that age-related alterations in functional network connectivity were the result of global brain volume changes. These results suggest that age-related differences in the coordination of neural activity between brain regions partially underlie differences in cognitive performance.
Project description:We used single cell RNA sequencing to identify transcriptomic changes in immune cells of the distal limb in diabetic Leprdb/db mice at two different ages that have the potential to contribute to the complications of the distal limb associated with diabetes
Project description:BACKGROUND:Human gut microbial functions are often associated with various diseases and host physiologies. Aging, a less explored factor, is also suspected to affect or be affected by microbiome alterations. By combining functional feature selection with supervised classification, we aim to facilitate identification of age-related functional characteristics in metagenomes from several human gut microbiome studies (MetaHIT, MicroAge, MicroObes, Kurokawa et al.'s and Gill et al.'s dataset). RESULTS:We apply two feature selection methods, term frequency-inverse document frequency (TF-iDF) and minimum-redundancy maximum-relevancy (mRMR), to identify functional signatures that differentiate metagenomes by age. After features are reduced, we use a support vector machine (SVM) to predict host age of new metagenomes. Functional features are from protein families (Pfams), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, KEGG ontologies and the Gene Ontology (GO) database. Initial investigations demonstrate that ordination of the functional principal components shows great overlap between different age groups. However, when feature selection is applied, mRMR tightens the ordination cluster for each age group, and TF-iDF offers better linear separation. Both TF-iDF and mRMR were used in conjunction with a SVM classifier and achieved areas under receiver operating characteristic curves (AUCs) 10 to 15% above chance to classify individuals above/below mid-ages (about 38 to 43?years old) using Pfams. Better performance around mid-ages is also observed when using other functional categories and age-balanced dataset. We also identified some age-related Pfams that improved age discrimination at age 65 with another feature selection method called LEfSe, on an age-balanced dataset. The selected functional characteristics identify a broad range of age-relevant metabolisms, such as reduced vitamin B12 synthesis, reduced activity of reductases, increased DNA damage, occurrences of stress responses and immune system compromise, and upregulated glycosyltransferases in the aging population. CONCLUSIONS:Feature selection can yield biologically meaningful results when used in conjunction with classification, and makes age classification of new human gut metagenomes feasible. While we demonstrate the promise of this approach, the data-dependent prediction performance could be further improved. We hypothesize that while the Qin et al. dataset is the most comprehensive to date, even deeper sampling is needed to better characterize and predict the microbiomes' functional content.
Project description:Recent reports highlight improved individual identification using proteomic information from human hair evidence. These reports have stimulated investigation of parameters that affect the utility of proteomic information. In addition to variables already studied relating to processing technique and the anatomic origin of hair shafts, an important variable is hair ageing. Present work focuses on the effect of age on protein profiling and analysis of genetically variant peptides GVPs. Hair protein profiles may be affected by developmental and physiological changes with age of the donor, exposure to different environmental conditions and intrinsic processes, including during storage. First, to explore whether general trends were evident in the population at different ages, hair samples were analyzed from groups of different subjects in their 20s, 40s and 60s. No significant differences were seen as a function of age, but consistent differences were evident between European American and African American hair profiles. Second, samples collected from single individuals at different ages were analyzed. In most cases, these showed few protein expression level differences over periods of 10 years or less, but samples from subjects at 44 and 65 year intervals were distinctly different in profile. The results indicate that use of protein profiling for personal identification, if practical, would be limited to decadal time intervals. Moreover, batch effects were clearly evident in samples processed by different staff. To investigate the contribution of storage at room temperature in affecting the outcomes, the same proteomic digests were analyzed for GVPs. In samples stored over 10 years, GVPs were reduced in number in parallel with the yield of identified proteins and unique peptides. However, a very different picture emerged with respect to personal identification. Numbers of GVPs sufficed to distinguish individuals despite the age differences of the samples. As a practical matter, three hair samples per person provided nearly the maximal number obtained from 5 or 6 samples. The random match probability where the log increased in proportion to the number of GVPs reached as high as 1 in 108. The data indicate that GVP results are dependent primarily on the donor genotype, and thus are consistent despite the ages of the donors and samples and batchwise effects in processing. This conclusion is critical for application to casework where the samples may be in storage for long periods and used to match samples recently collected.
Project description:We collected the hypothalamus of mice of different ages to ascertain the biomarkers of aging via comparing the transcriptome changes between old and young WT (C57BL/6J) mice.
Project description:Cardiac tissue macrophages (cTMs) are abundant in the murine heart but the extent to which the cTM phenotype changes with age is unknown. This study characterizes aging-dependent phenotypic changes in cTM subsets. Using theCx3cr1(GFP/+) mouse reporter line where GFP marks cTMs, and the tissue macrophage marker Mrc1, we show that two major cardiac tissue macrophage subsets, Mrc1-GFP(hi) and Mrc1+GFP(hi) cTMs, are present in the young (<10 week old) mouse heart, and a third subset, Mrc1+GFP(lo), comprises ~50% of total Mrc1+ cTMs from 30 weeks of age. Immunostaining and functional assays show that Mrc1+ cTMs are the principal myeloid sentinels in the mouse heart and that they retain proliferative capacity throughout life. Gene expression profiles of the two Mrc1+ subsets also reveal that Mrc1+GFP(lo) cTMs have a decreased number of immune response genes (Cx3cr1, Lpar6, CD9, Cxcr4, Itga6 and Tgf?r1), and an increased number of fibrogenic genes (Ltc4s, Retnla, Fgfr1, Mmp9 and Ccl24), consistent with a potential role for cTMs in cardiac fibrosis. These findings identify early age-dependent gene expression changes in cTMs, with significant implications for cardiac tissue injury responses and aging-associated cardiac fibrosis.
Project description:Lung function declines with advancing age. To improve our understanding of the structure-function relationships leading to this decline, we investigated structural alterations in the lung and their impact on micromechanics and lung function in the aging mouse. Lung function analysis was performed in 3, 6, 12, 18, and 24 months old C57BL/6 mice (n = 7-8/age), followed by lung fixation and stereological sample preparation. Lung parenchymal volume, total, ductal and alveolar airspace volume, alveolar volume and number, septal volume, septal surface area and thickness were quantified by stereology as well as surfactant producing alveolar epithelial type II (ATII) cell volume and number. Parenchymal volume, total and ductal airspace volume increased in old (18 and 24 months) compared with middle-aged (6 and 12 months) and young (3 months) mice. While the alveolar number decreased from young (7.5 × 106) to middle-aged (6 × 106) and increased again in old (9 × 106) mice, the mean alveolar volume and mean septal surface area per alveolus conversely first increased in middle-aged and then declined in old mice. The ATII cell number increased from middle-aged (8.8 × 106) to old (11.8 × 106) mice, along with the alveolar number, resulting in a constant ratio of ATII cells per alveolus in all age groups (1.4 ATII cells per alveolus). Lung compliance and inspiratory capacity increased, whereas tissue elastance and tissue resistance decreased with age, showing greatest changes between young and middle-aged mice. In conclusion, alveolar size declined significantly in old mice concomitant with a widening of alveolar ducts and late alveolarization. These changes may partly explain the functional alterations during aging. Interestingly, despite age-related lung remodeling, the number of ATII cells per alveolus showed a tightly controlled relation in all age groups.
Project description:The objectives of this study were 2-fold: 1) to compare the expression profiles at specific ages of blood leukocytes from foals stimulated with virulent R. equi with those of unstimulated leukocytes; and, 2) to characterize the age-related changes in the gene expression profile associated with blood leukocytes in response to stimulation with virulent R. equi.