Novel Strategy to Quantitate Delayed Aging by Caloric Restriction
Novel Strategy to Quantitate Delayed Aging by Caloric Restriction
批准号:
10570275
负责人:
ALEXEY V TERSKIKH
金额:
$25.02万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-02-15 至 2024-01-31
关键词:
ATAC-seqAccelerationAgeAgingAnimalsBiologicalBiological AgingBiological MarkersBiology of AgingBloodCD3 AntigensCalibrationCaloric RestrictionCellsChromatinChronologyControl AnimalDNA MethylationData PoolingData SetDevelopmentDietDietary InterventionDoxorubicinEpigenetic ProcessExclusionGene ExpressionGeneticGenomeGenomicsHepatocyteHeterochromatinHumanIndividualInterventionLinear RegressionsLiverLongevityMachine LearningMeasuresMethodsMethylationMicroscopyMiningMolecularMusNuclearPatternPeripheral Blood Mononuclear CellPhenotypePopulationProcessRegimenResearchSamplingSerumSiteStainsTissuesTrainingTranscriptXCL1 geneYeastsage relatedcandidate markercell typecost effectivedeep learningdietary restrictionepigenetic markerepigenomeexperimental studyfascinatefrailtygenome sequencinghealthspanindexingmanmicroscopic imagingmimeticsnovel strategiesregression algorithmscreeningsexsmall moleculetooltranscriptome sequencingwhole genome
中文摘要
项目摘要
衰老与发生在整个基因组中的因果表观遗传变化有关,正如酵母中首次显示的那样
还有蠕虫DNA甲基化时钟识别人类血液和其他组织中的CpG位点,具有年龄依赖性
变化所有这些时钟都依赖于线性回归算法或深度学习来选择CpG甲基化
具有最适合实足年龄的水平的地点;与实足年龄的线性回归预测的偏差,
有些人认为每个人的年龄是生物年龄的一种量度。这样的生物计算
年龄有几个限制。我们开发了新的方法“表观遗传景观的显微成像”
(MIEL)-时钟,它植根于单细胞水平的表观基因组拓扑分析,以测量年龄-
染色质景观的依赖性签名。MIEL捕获表观遗传标记的核染色模式
并采用自动显微镜和机器学习来确定细胞的多参数特征,
状态我们提供了初步的证据,功率的MIEL时钟,成功地区分几种类型的
我们的初步实验使用阿霉素(DOX)治疗,
热量限制(CR)表明,MIEL时钟成功地检测到DOX治疗后衰老的加速-
CR饮食后的衰老和减缓。因为CR稳健而一致地延长了最大寿命
并在不同物种中延迟生物衰老,成功应用的CR方案作为一种无与伦比的
了解衰老生物学的研究工具。在这里,我们建议采用CR方案,以确定
MIEL时钟的力量,以量化老化过程的减缓,并直接比较和对比MIEL-
CR和对照小鼠中肝细胞的时钟、RNA-seq和ATAC-seq特征。但需要说明的是
一种尺寸并不适合所有人,针对遗传背景和性别优化的饮食可以适用于有益的影响,
健康和长寿。鉴于我们的研究组成,完成特定目标将产生一个独特的
直接比较MIEL-时钟与CR范例的经典基因组读数的数据集。后者构成
一个丰富的数据库,用于年龄相关变化的分子挖掘,并将有助于证实
MIEL-clock作为一种简单、经济、高通量的单细胞读出和筛选平台,用于评估
饮食干预有可能减缓衰老过程,并确定小分子米梅-
的CR。
英文摘要
PROJECT SUMMARY
Aging is associated with causal epigenetic changes that occur throughout the genome, as first shown in yeast
and worms. DNA methylation clocks identify CpG sites in human blood and other tissues with age-dependent
changes. All such clocks depend on linear regression algorithms or deep learning to select CpGs methylation
sites with levels that best fit chronological age; the deviation from the linear regression prediction of chronologi-
cal age for each individual is considered, by some, a measure of biological age. Such computation of biological
age has several limitations. We developed novel approach “Microscopic Imaging of Epigenetic Landscapes”
(MIEL)-clock, which is rooted in the analysis of epigenome topography at the single cell level to measure age-
dependent signature of chromatin landscape. MIEL captures patterns of nuclear staining of epigenetic marks
and employs automated microscopy and machine learning to determine multiparametric signature of cellular
state. We provide preliminary evidence for the power of MIEL-clock to successfully distinguish several types of
young and old cells in mice and man. Our preliminary experiments using Doxorubicin (DOX) treatment, and
Caloric Restriction (CR) indicate that MIEL-clock successfully detects acceleration of aging after DOX treat-
ment and slowdown of aging after CR diet. Because CR robustly and consistently increases maximum lifespan
and delays biological aging in diverse species, successfully applied CR regimen serves as an incomparable
research tool for understanding the biology of aging. Here we propose to employ CR regimens to determine
the power of MIEL-clock to quantitate slowdown of aging process and to directly compare and contrast MIEL-
clock, RNA-seq and ATAC-seq signatures of liver hepatocytes in CR and control mice. With the caveat that
one-size does not fit all, a diet optimized for genetic background and sex can be applied to beneficially impact
healthspan and longevity. Given the composition of our study, completion of Specific Aims will yield a unique
dataset directly comparing MIEL-clock to the classical genomic readouts of CR paradigm. The latter constitute
a rich data pool for molecular mining of age-associated changes and will serve to corroborate the utility of
MIEL-clock as a simple, cost effective, high throughput single-cell readout and screening platform for evaluat-
ing dietary interventions with potential to slow down the aging process and identifying small molecules mimet-
ics of CR.
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