Aging increases cell-to-cell transcriptional variability upon immune stimulation

Proteomics appending a complementary dimension to precision oncotherapy

Recent advances in high-throughput proteomic profiling technologies have facilitated the precise quantification of numerous proteins across multiple specimens concurrently. Researchers have the opportunity to comprehensively analyze the molecular signatures in plentiful medical specimens or disease pattern cell lines. Along with advances in data analysis and integration, proteomics data could be efficiently consolidated and employed to recognize precise elementary molecular mechanisms and decode individual biomarkers, guiding the precision treatment of tumors. Herein, we review a broad array of proteomics technologies and the progress and methods for the integration of proteomics data and further discuss how to better merge proteomics in precision medicine and clinical settings.

Polyploidisation pleiotropically buffers ageing in hepatocytes

BACKGROUND & AIMS

Polyploidy in hepatocytes has been proposed as a genetic mechanism to buffer against transcriptional dysregulation. Here, we aim to demonstrate the role of polyploidy in modulating gene regulatory networks in hepatocytes during ageing.

METHODS

We performed single-nucleus RNA sequencing in hepatocyte nuclei of different ploidy levels isolated from young and old wild-type mice. Changes in the gene expression and regulatory network were compared to three independent strains that were haploinsufficient for HNF4A, CEBPA or CTCF, representing non-deleterious perturbations. Phenotypic characteristics of the liver section were additionally evaluated histologically, whereas the genomic allele composition of hepatocytes was analysed by BaseScope.

RESULTS

We observed that ageing in wild-type mice results in nuclei polyploidy and a marked increase in steatosis. Haploinsufficiency of liver-specific master regulators (HFN4A or CEBPA) results in the enrichment of hepatocytes with tetraploid nuclei at a young age, affecting the genomic regulatory network, and dramatically suppressing ageing-related steatosis tissue wide. Notably, these phenotypes are not the result of subtle disruption to liver-specific transcriptional networks, since haploinsufficiency in the CTCF insulator protein resulted in the same phenotype. Further quantification of genotypes of tetraploid hepatocytes in young and old HFN4A-haploinsufficient mice revealed that during ageing, tetraploid hepatocytes lead to the selection of wild-type alleles, restoring non-deleterious genetic perturbations.

CONCLUSIONS

Our results suggest a model whereby polyploidisation leads to fundamentally different cell states. Polyploid conversion enables pleiotropic buffering against age-related decline via non-random allelic segregation to restore a wild-type genome.

IMPACT AND IMPLICATIONS

The functional role of hepatocyte polyploidisation during ageing is poorly understood. Using single-nucleus RNA sequencing and BaseScope approaches, we have studied ploidy dynamics during ageing in murine livers with non-deleterious genetic perturbations. We have identified that hepatocytes present different cellular states and the ability to buffer ageing-associated dysfunctions. Tetraploid nuclei exhibit robust transcriptional networks and are better adapted to genomically overcome perturbations. Novel therapeutic interventions aimed at attenuating age-related changes in tissue function could be exploited by manipulation of ploidy dynamics during chronic liver conditions.

Histone deacetylase Hos2 regulates protein expression noise by potentially modulating the protein translation machinery

Non-genetic variations derived from expression noise at transcript or protein levels can result in cell-to-cell heterogeneity within an isogenic population. Although cells have developed strategies to reduce noise in some cellular functions, this heterogeneity can also facilitate varying levels of regulation and provide evolutionary benefits in specific environments. Despite several general characteristics of cellular noise having been revealed, the detailed molecular pathways underlying noise regulation remain elusive. Here, we established a dual-fluorescent reporter system in Saccharomyces cerevisiae and performed experimental evolution to search for mutations that increase expression noise. By analyzing evolved cells using bulk segregant analysis coupled with whole-genome sequencing, we identified the histone deacetylase Hos2 as a negative noise regulator. A hos2 mutant down-regulated multiple ribosomal protein genes and exhibited partially compromised protein translation, indicating that Hos2 may regulate protein expression noise by modulating the translation machinery. Treating cells with translation inhibitors or introducing mutations into several Hos2-regulated ribosomal protein genes-RPS9A, RPS28B and RPL42A-enhanced protein expression noise. Our study provides an effective strategy for identifying noise regulators and also sheds light on how cells regulate non-genetic variation through protein translation.

Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging

The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.

Analysis of the heterogeneity and complexity of murine extraorbital lacrimal gland via single-cell RNA sequencing

PURPOSE

The lacrimal gland is essential for maintaining ocular surface health and avoiding external damage by secreting an aqueous layer of the tear film. However, a healthy lacrimal gland's inventory of cell types and heterogeneity remains understudied.

METHODS

Here, 10X Genome-based single-cell RNA sequencing was used to generate an unbiased classification of cellular diversity in the extraorbital lacrimal gland (ELG) of C57BL/6J mice. From 43,850 high-quality cells, we produced an atlas of cell heterogeneity and defined cell types using classic marker genes. The possible functions of these cells were analyzed through bioinformatics analysis. Additionally, the CellChat was employed for a preliminary analysis of the cell-cell communication network in the ELG.

RESULTS

Over 37 subclasses of cells were identified, including seven types of glandular epithelial cells, three types of fibroblasts, ten types of myeloid-derived immune cells, at least eleven types of lymphoid-derived immune cells, and five types of vascular-associated cell subsets. The cell-cell communication network analysis revealed that fibroblasts and immune cells play a pivotal role in the dense intercellular communication network within the mouse ELG.

CONCLUSIONS

This study provides a comprehensive transcriptome atlas and related database of the mouse ELG.

A robust model for cell type-specific interindividual variation in single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) has been widely used to characterize cell types based on their average gene expression profiles. However, most studies do not consider cell type-specific variation across donors. Modelling this cell type-specific inter-individual variation could help elucidate cell type-specific biology and inform genes and cell types underlying complex traits. We therefore develop a new model to detect and quantify cell type-specific variation across individuals called CTMM (Cell Type-specific linear Mixed Model). We use extensive simulations to show that CTMM is powerful and unbiased in realistic settings. We also derive calibrated tests for cell type-specific interindividual variation, which is challenging given the modest sample sizes in scRNA-seq. We apply CTMM to scRNA-seq data from human induced pluripotent stem cells to characterize the transcriptomic variation across donors as cells differentiate into endoderm. We find that almost 100% of transcriptome-wide variability between donors is differentiation stage-specific. CTMM also identifies individual genes with statistically significant stage-specific variability across samples, including 85 genes that do not have significant stage-specific mean expression. Finally, we extend CTMM to partition interindividual covariance between stages, which recapitulates the overall differentiation trajectory. Overall, CTMM is a powerful tool to illuminate cell type-specific biology in scRNA-seq.

Gene regulatory networks in disease and ageing

The precise control of gene expression is required for the maintenance of cellular homeostasis and proper cellular function, and the declining control of gene expression with age is considered a major contributor to age-associated changes in cellular physiology and disease. The coordination of gene expression can be represented through models of the molecular interactions that govern gene expression levels, so-called gene regulatory networks. Gene regulatory networks can represent interactions that occur through signal transduction, those that involve regulatory transcription factors, or statistical models of gene-gene relationships based on the premise that certain sets of genes tend to be coexpressed across a range of conditions and cell types. Advances in experimental and computational technologies have enabled the inference of these networks on an unprecedented scale and at unprecedented precision. Here, we delineate different types of gene regulatory networks and their cell-biological interpretation. We describe methods for inferring such networks from large-scale, multi-omics datasets and present applications that have aided our understanding of cellular ageing and disease mechanisms.

Suv39h-catalyzed H3K9me3 is critical for euchromatic genome organization and the maintenance of gene transcription

H3K9me3-dependent heterochromatin is critical for the silencing of repeat-rich pericentromeric regions and also has key roles in repressing lineage-inappropriate protein-coding genes in differentiation and development. Here, we investigate the molecular consequences of heterochromatin loss in cells deficient in both SUV39H1 and SUV39H2 (Suv39DKO), the major mammalian histone methyltransferase enzymes that catalyze heterochromatic H3K9me3 deposition. We reveal a paradoxical repression of protein-coding genes in Suv39DKO cells, with these differentially expressed genes principally in euchromatic (Tn5-accessible, H3K4me3- and H3K27ac-marked) rather than heterochromatic (H3K9me3-marked) or polycomb (H3K27me3-marked) regions. Examination of the three-dimensional (3D) nucleome reveals that transcriptomic dysregulation occurs in euchromatic regions close to the nuclear periphery in 3D space. Moreover, this transcriptomic dysregulation is highly correlated with altered 3D genome organization in Suv39DKO cells. Together, our results suggest that the nuclear lamina-tethering of Suv39-dependent H3K9me3 domains provides an essential scaffold to support euchromatic genome organization and the maintenance of gene transcription for healthy cellular function.

Specific differences and novel key regulatory genes of sex in influencing exceptional longevity phenotypes

BACKGROUND AND AIMS

Although the life expectancy of women systematically and robustly exceeds that of men, specific differences and molecular mechanisms of sex in influencing longevity phenotypes remain largely unknown. Therefore, we performed transcriptome sequencing of peripheral blood samples to explore regulatory mechanisms of healthy longevity by incorporating sex data.

METHODS

We selected 34 exceptional longevity (age: 98.26 ± 2.45 years) and 16 controls (age: 52.81 ± 9.78) without advanced outcomes from 1363 longevity and 692 controls recruited from Nanning of Guangxi for RNA sequencing 1. The transcriptome sequencing 1 data of 50 samples were compared by longevity and sex to screen differentially expressed genes (DEGs). Then, 121 aging samples (40-110 years old) without advanced outcomes from 355 longevity and 294 controls recruited from Dongxing of Guangxi were selected for RNA sequencing 2. The genes associated with aging from the transcriptome sequencing 2 of 121 aging samples were filtered out. Finally, the gender-related longevity candidate genes and their possible metabolic pathways were verified by cell model of aging and a real-time polymerase chain reaction (RT-PCR).

RESULTS

Metabolism differs between male and female and plays a key role in longevity. Moreover, the principal findings of this study revealed a novel key gene, UGT2B11, that plays an important role in regulating lipid metabolism through the peroxisome proliferator activated receptor gamma (PPARG) signalling pathway and ultimately improving lifespan, particularly in females.

CONCLUSION

The findings suggest specific differences in metabolism affecting exceptional longevity phenotypes between the sexes and offer novel therapeutic targets to extend lifespan by regulating lipid homeostasis.

A high-resolution view of the heterogeneous aging endothelium

Vascular endothelial cell (EC) aging has a strong impact on tissue perfusion and overall cardiovascular health. While studies confined to the investigation of aging-associated vascular readouts in one or a few tissues have already drastically expanded our understanding of EC aging, single-cell omics and other high-resolution profiling technologies have started to illuminate the intricate molecular changes underlying endothelial aging across diverse tissues and vascular beds at scale. In this review, we provide an overview of recent insights into the heterogeneous adaptations of the aging vascular endothelium. We address critical questions regarding tissue-specific and universal responses of the endothelium to the aging process, EC turnover dynamics throughout lifespan, and the differential susceptibility of ECs to acquiring aging-associated traits. In doing so, we underscore the transformative potential of single-cell approaches in advancing our comprehension of endothelial aging, essential to foster the development of future innovative therapeutic strategies for aging-associated vascular conditions.

A single-cell atlas of lung homeostasis reveals dynamic changes during development and aging

Aging is a global challenge, marked in the lungs by function decline and structural disorders, which affects the health of the elderly population. To explore anti-aging strategies, we develop a dynamic atlas covering 45 cell types in human lungs, spanning from embryonic development to aging. We aim to apply the discoveries of lung's development to address aging-related issues. We observe that both epithelial and immune cells undergo a process of acquisition and loss of essential function as they transition from development to aging. During aging, we identify cellular phenotypic alternations that result in reduced pulmonary compliance and compromised immune homeostasis. Furthermore, we find a distinctive expression pattern of the ferritin light chain (FTL) gene, which increases during development but decreases in various types of lung cells during the aging process.

Transcriptional changes are tightly coupled to chromatin reorganization during cellular aging

Human life expectancy is constantly increasing and aging has become a major risk factor for many diseases, although the underlying gene regulatory mechanisms are still unclear. Using transcriptomic and chromosomal conformation capture (Hi-C) data from human skin fibroblasts from individuals across different age groups, we identified a tight coupling between the changes in co-regulation and co-localization of genes. We obtained transcription factors, cofactors, and chromatin regulators that could drive the cellular aging process by developing a time-course prize-collecting Steiner tree algorithm. In particular, by combining RNA-Seq data from different age groups and protein-protein interaction data we determined the key transcription regulators and gene regulatory changes at different life stage transitions. We then mapped these transcription regulators to the 3D reorganization of chromatin in young and old skin fibroblasts. Collectively, we identified key transcription regulators whose target genes are spatially rearranged and correlate with changes in their expression, thereby providing potential targets for reverting cellular aging.

The cycling and aging mouse female reproductive tract at single-cell resolution

The female reproductive tract (FRT) undergoes extensive remodeling during reproductive cycling. This recurrent remodeling and how it shapes organ-specific aging remains poorly explored. Using single-cell and spatial transcriptomics, we systematically characterized morphological and gene expression changes occurring in ovary, oviduct, uterus, cervix, and vagina at each phase of the mouse estrous cycle, during decidualization, and into aging. These analyses reveal that fibroblasts play central-and highly organ-specific-roles in FRT remodeling by orchestrating extracellular matrix (ECM) reorganization and inflammation. Our results suggest a model wherein recurrent FRT remodeling over reproductive lifespan drives the gradual, age-related development of fibrosis and chronic inflammation. This hypothesis was directly tested using chemical ablation of cycling, which reduced fibrotic accumulation during aging. Our atlas provides extensive detail into how estrus, pregnancy, and aging shape the organs of the female reproductive tract and reveals the unexpected cost of the recurrent remodeling required for reproduction.

Genome Instability and DNA Repair in Somatic and Reproductive Aging

Genetic material is constantly subjected to genotoxic insults and is critically dependent on DNA repair. Genome maintenance mechanisms differ in somatic and germ cells as the soma only requires maintenance during an individual's lifespan, while the germline indefinitely perpetuates its genetic information. DNA lesions are recognized and repaired by mechanistically highly diverse repair machineries. The DNA damage response impinges on a vast array of homeostatic processes and can ultimately result in cell fate changes such as apoptosis or cellular senescence. DNA damage causally contributes to the aging process and aging-associated diseases, most prominently cancer. By causing mutations, DNA damage in germ cells can lead to genetic diseases and impact the evolutionary trajectory of a species. The mechanisms ensuring tight control of germline DNA repair could be highly instructive in defining strategies for improved somatic DNA repair. They may provide future interventions to maintain health and prevent disease during aging.

Variability in exercise is linked to improved age-related dysfunctions: A potential role for the constrained-disorder principle-based second-generation artificial intelligence system

Objective: Regular physical activity (PA) promotes mental and physical health. Nevertheless, inactivity is a worldwide pandemic, and methods to augment exercise benefits are required. The constrained disorder principle (CDP) characterizes biological systems based on their inherent variability. We aimed to investigate the association between intra-individual variability in PA and disability among non-athlete adults. Methods: In this retrospective analysis of the longitudinal SHARE survey, we included non-disabled adults aged >50 with at least six visits over 14 years. Self-reported PA frequency was documented bi- to triennially. Low PA intensity was defined as vigorous PA frequency less than once a week. Stable PA was described as an unchanged PA intensity in all consecutive middle observations. The primary outcome was defined as a physical limitation in everyday activities at the end of the survey. Secondary outcomes were cognitive functions, including short-term memory, long-term memory, and verbal fluency. Results: The study included 2,049 non-disabled adults with a mean age of 53 and 49.1% women. In the initially high PA intensity group, variability in PA was associated with increased physical disability prevalence (23.3% vs. 33.2%, stable vs. unstable PA ; P<0.01; adjusted P<0.01). In the initially low PA intensity group, variability was associated with a reduced physical disability (45.6% vs. 33.3%, stable vs. unstable PA ; P=0.02; adjusted P=0.03). There were no statistically significant differences in cognitive parameters between the groups. Among individuals with the same low PA intensity at the beginning and end of follow-up, variability was associated with reduced physical disability (56.9% vs. 36.5%, stable vs. unstable PA ; P=0.02; adjusted P=0.04) and improved short-term memory (score change: -0.28 vs. +0.29, stable vs. unstable PA ; P=0.05). Conclusion: Incorporating variability into PA regimens of inactive adults may enhance their physical and cognitive benefits.

Aerobic exercise training mitigates tumor growth and cancer-induced splenomegaly through modulation of non-platelet platelet factor 4 expression

Exercise training reduces the incidence of several cancers, but the mechanisms underlying these effects are not fully understood. Exercise training can affect the spleen function, which controls the hematopoiesis and immune response. Analyzing different cancer models, we identified that 4T1, LLC, and CT26 tumor-bearing mice displayed enlarged spleen (splenomegaly), and exercise training reduced spleen mass toward control levels in two of these models (LLC and CT26). Exercise training also slowed tumor growth in melanoma B16F10, colon tumor 26 (CT26), and Lewis lung carcinoma (LLC) tumor-bearing mice, with minor effects in mammary carcinoma 4T1, MDA-MB-231, and MMTV-PyMT mice. In silico analyses using transcriptome profiles derived from these models revealed that platelet factor 4 (Pf4) is one of the main upregulated genes associated with splenomegaly during cancer progression. To understand whether exercise training would modulate the expression of these genes in the tumor and spleen, we investigated particularly the CT26 model, which displayed splenomegaly and had a clear response to the exercise training effects. RT-qPCR analysis confirmed that trained CT26 tumor-bearing mice had decreased Pf4 mRNA levels in both the tumor and spleen when compared to untrained CT26 tumor-bearing mice. Furthermore, exercise training specifically decreased Pf4 mRNA levels in the CT26 tumor cells. Aspirin treatment did not change tumor growth, splenomegaly, and tumor Pf4 mRNA levels, confirming that exercise decreased non-platelet Pf4 mRNA levels. Finally, tumor Pf4 mRNA levels are deregulated in The Cancer Genome Atlas Program (TCGA) samples and predict survival in multiple cancer types. This highlights the potential therapeutic value of exercise as a complementary approach to cancer treatment and underscores the importance of understanding the exercise-induced transcriptional changes in the spleen for the development of novel cancer therapies.

Cellular age explains variation in age-related cell-to-cell transcriptome variability

Organs and tissues age at different rates within a single individual. Such asynchrony in aging has been widely observed at multiple levels, from functional hallmarks, such as anatomical structures and physiological processes, to molecular endophenotypes, such as the transcriptome and metabolome. However, we lack a conceptual framework to understand why some components age faster than others. Just as demographic models explain why aging evolves, here we test the hypothesis that demographic differences among cell types, determined by cell-specific differences in turnover rate, can explain why the transcriptome shows signs of aging in some cell types but not others. Through analysis of mouse single-cell transcriptome data across diverse tissues and ages, we find that cellular age explains a large proportion of the variation in the age-related increase in transcriptome variance. We further show that long-lived cells are characterized by relatively high expression of genes associated with proteostasis and that the transcriptome of long-lived cells shows greater evolutionary constraint than short-lived cells. In contrast, in short-lived cell types, the transcriptome is enriched for genes associated with DNA repair. Based on these observations, we develop a novel heuristic model that explains how and why aging rates differ among cell types.

Smurfness-based two-phase model of ageing helps deconvolve the ageing transcriptional signature

Ageing is characterised at the molecular level by six transcriptional 'hallmarks of ageing', that are commonly described as progressively affected as time passes. By contrast, the 'Smurf' assay separates high-and-constant-mortality risk individuals from healthy, zero-mortality risk individuals, based on increased intestinal permeability. Performing whole body total RNA sequencing, we found that Smurfness distinguishes transcriptional changes associated with chronological age from those associated with biological age. We show that transcriptional heterogeneity increases with chronological age in non-Smurf individuals preceding the other five hallmarks of ageing that are specifically associated with the Smurf state. Using this approach, we also devise targeted pro-longevity genetic interventions delaying entry in the Smurf state. We anticipate that increased attention to the evolutionary conserved Smurf phenotype will bring about significant advances in our understanding of the mechanisms of ageing.

Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging

BACKGROUND

Single-cell RNA-sequencing (scRNA-seq) technologies enable the capture of gene expression heterogeneity and consequently facilitate the study of cell-to-cell variability at the cell type level. Although different methods have been proposed to quantify cell-to-cell variability, it is unclear what the optimal statistical approach is, especially in light of challenging data structures that are unique to scRNA-seq data like zero inflation.

RESULTS

We systematically evaluate the performance of 14 different variability metrics that are commonly applied to transcriptomic data for measuring cell-to-cell variability. Leveraging simulations and real datasets, we benchmark the metric performance based on data-specific features, sparsity and sequencing platform, biological properties, and the ability to recapitulate true levels of biological variability based on known gene sets. Next, we use scran, the metric with the strongest all-round performance, to investigate changes in cell-to-cell variability that occur during B cell differentiation and the aging processes. The analysis of primary cell types from hematopoietic stem cells (HSCs) and B lymphopoiesis reveals unique gene signatures with consistent patterns of variable and stable expression profiles during B cell differentiation which highlights the significance of these methods. Identifying differentially variable genes between young and old cells elucidates the regulatory changes that may be overlooked by solely focusing on mean expression changes and we investigate this in the context of regulatory networks.

CONCLUSIONS

We highlight the importance of capturing cell-to-cell gene expression variability in a complex biological process like differentiation and aging and emphasize the value of these findings at the level of individual cell types.

Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge

BACKGROUND

Xenobiotics are primarily metabolized by hepatocytes in the liver, and primary human hepatocytes are the gold standard model for the assessment of drug efficacy, safety, and toxicity in the early phases of drug development. Recent advances in single-cell genomics demonstrate liver zonation and ploidy as main drivers of cellular heterogeneity. However, little is known about the impact of hepatocyte specialization on liver function upon metabolic challenge, including hepatic metabolism, detoxification, and protein synthesis.

RESULTS

Here, we investigate the metabolic capacity of individual human hepatocytes in vitro. We assess how chronic accumulation of lipids enhances cellular heterogeneity and impairs the metabolisms of drugs. Using a phenotyping five-probe cocktail, we identify four functional subgroups of hepatocytes responding differently to drug challenge and fatty acid accumulation. These four subgroups display differential gene expression profiles upon cocktail treatment and xenobiotic metabolism-related specialization. Notably, intracellular fat accumulation leads to increased transcriptional variability and diminishes the drug-related metabolic capacity of hepatocytes.

CONCLUSIONS

Our results demonstrate that, upon a metabolic challenge such as exposure to drugs or intracellular fat accumulation, hepatocyte subgroups display different and heterogeneous transcriptional responses.

Serum Response Factor Reduces Gene Expression Noise and Confers Cell State Stability

The role of serum response factor (Srf), a central mediator of actin dynamics and mechanical signaling, in cell identity regulation is debated to be either a stabilizer or a destabilizer. We investigated the role of Srf in cell fate stability using mouse pluripotent stem cells. Despite the fact that serum-containing cultures yield heterogeneous gene expression, deletion of Srf in mouse pluripotent stem cells leads to further exacerbated cell state heterogeneity. The exaggerated heterogeneity is detectible not only as increased lineage priming but also as the developmentally earlier 2C-like cell state. Thus, pluripotent cells explore more variety of cellular states in both directions of development surrounding naïve pluripotency, a behavior that is constrained by Srf. These results support that Srf functions as a cell state stabilizer, providing rationale for its functional modulation in cell fate intervention and engineering.

Differential variability analysis of single-cell gene expression data

The advent of single-cell RNA sequencing (scRNA-seq) technologies has enabled gene expression profiling at the single-cell resolution, thereby enabling the quantification and comparison of transcriptional variability among individual cells. Although alterations in transcriptional variability have been observed in various biological states, statistical methods for quantifying and testing differential variability between groups of cells are still lacking. To identify the best practices in differential variability analysis of single-cell gene expression data, we propose and compare 12 statistical pipelines using different combinations of methods for normalization, feature selection, dimensionality reduction and variability calculation. Using high-quality synthetic scRNA-seq datasets, we benchmarked the proposed pipelines and found that the most powerful and accurate pipeline performs simple library size normalization, retains all genes in analysis and uses denSNE-based distances to cluster medoids as the variability measure. By applying this pipeline to scRNA-seq datasets of COVID-19 and autism patients, we have identified cellular variability changes between patients with different severity status or between patients and healthy controls.

Ageing-associated phenotypes in mice

Ageing is a continuous process in life featuring progressive damage accumulation that leads to physiological decline, functional deterioration and ultimately death of an organism. Based on the relatively close anatomical and physiological similarity to humans, the mouse has been proven as a valuable model organism in ageing research over the last decades. In this review, we survey methods and tools currently in use to assess ageing phenotypes in mice. We summarize a range of ageing-associated alterations detectable at two major levels of analysis: (1) physiology and pathophysiology and (2) molecular biomarkers. Age-sensitive phenotypes provided in this article may serve to inform future studies targeting various aspects of organismal ageing in mice. In addition, we discuss conceptual and technical challenges faced by previous ageing studies in mice and, where possible, provide recommendations on how to resolve some of these issues.

Individual cell types in C. elegans age differently and activate distinct cell-protective responses

Aging is characterized by a global decline in physiological function. However, by constructing a complete single-cell gene expression atlas, we find that Caenorhabditis elegans aging is not random in nature but instead is characterized by coordinated changes in functionally related metabolic, proteostasis, and stress-response genes in a cell-type-specific fashion, with downregulation of energy metabolism being the only nearly universal change. Similarly, the rates at which cells age differ significantly between cell types. In some cell types, aging is characterized by an increase in cell-to-cell variance, whereas in others, variance actually decreases. Remarkably, multiple resilience-enhancing transcription factors known to extend lifespan are activated across many cell types with age; we discovered new longevity candidates, such as GEI-3, among these. Together, our findings suggest that cells do not age passively but instead react strongly, and individualistically, to events that occur during aging. This atlas can be queried through a public interface.

Aging, adaptation and maladaptation

Aging is accompanied by a dysregulation of adaptive processes. On the one hand, physiological adaptation mechanisms such as learning and memory, immune system plasticity and exercise-dependent muscle remodeling are blunted. On the other hand, several maladaptive processes increase with age including cancer, pathological cardiovascular remodeling and metabolic dysregulation. With increasing age the quotient of beneficial adaptation (Ab) to harmful adaptation (Ah), Ab/Ah, decreases. The adaptation-maladaptation framework of aging entails that there are age-related pathological phenotypes that are the result of activation of physiological adaptation mechanisms (e.g., maladaptation as a result of misdirection of adaptive cascades and molecular damage incurred by adaptation processes) and their occurrence over time might, to some degree, be inevitable. Aging might hence result from the organism's inability to solve the adaptation-maladaptation dilemma. The present work explores the concept of counteracting aging through adaptation and proposes that interventions such as exercise, environmental enrichment and dietary restriction work in counteracting aging because they increase the ratio Ab/Ah by both raising Ab (e.g., by inducing metaplasticity in cells, meaning they raise the adaptability of cells to future stimuli) and decreasing Ah (e.g., through desensitizing certain potentially harmful adaptive mechanisms). Molecules whose aging-related expression changes can explain aspects of dysfunctional adaptation such as CREB and certain immediate early genes are examined and it is delineated how a better understanding of the dynamical organization of adaptation cascades could elucidate the seemingly complex role of adaptation in driving aging as well as protecting against it.

Methylation across the central dogma in health and diseases: new therapeutic strategies

The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.

Heterogeneity of memory T cells in aging

Immune memory is a requisite and remarkable property of the immune system and is the biological foundation of the success of vaccinations in reducing morbidity from infectious diseases. Some vaccines and infections induce long-lasting protection, but immunity to other vaccines and particularly in older adults rarely persists over long time periods. Failed induction of an immune response and accelerated waning of immune memory both contribute to the immuno-compromised state of the older population. Here we review how T cell memory is influenced by age. T cell memory is maintained by a dynamic population of T cells that are heterogeneous in their kinetic parameters under homeostatic condition and their function. Durability of T cell memory can be influenced not only by the loss of a clonal progeny, but also by broader changes in the composition of functional states and transition of T cells to a dysfunctional state. Genome-wide single cell studies on total T cells have started to provide insights on the influence of age on cell heterogeneity over time. The most striking findings were a trend to progressive effector differentiation and the activation of pro-inflammatory pathways, including the emergence of CD4+ and CD8+ cytotoxic subsets. Genome-wide data on antigen-specific memory T cells are currently limited but can be expected to provide insights on how changes in T cell subset heterogeneity and transcriptome relate to durability of immune protection.

A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures

Accurately measuring biological age is crucial for improving healthcare for the elderly population. However, the complexity of aging biology poses challenges in how to robustly estimate aging and interpret the biological significance of the traits used for estimation. Here we present SCALE, a statistical pipeline that quantifies biological aging in different tissues using explainable features learned from literature and single-cell transcriptomic data. Applying SCALE to the "Mouse Aging Cell Atlas" (Tabula Muris Senis) data, we identified tissue-level transcriptomic aging programs for more than 20 murine tissues and created a multitissue resource of mouse quantitative aging-associated genes. We observe that SCALE correlates well with other age indicators, such as the accumulation of somatic mutations, and can distinguish subtle differences in aging even in cells of the same chronological age. We further compared SCALE with other transcriptomic and methylation "clocks" in data from aging muscle stem cells, Alzheimer's disease, and heterochronic parabiosis. Our results confirm that SCALE is more generalizable and reliable in assessing biological aging in aging-related diseases and rejuvenating interventions. Overall, SCALE represents a valuable advancement in our ability to measure aging accurately, robustly, and interpretably in single cells.

Loss of epigenetic suppression of retrotransposons with oncogenic potential in aging mammary luminal epithelial cells

A primary function of DNA methylation in mammalian genomes is to repress transposable elements (TEs). The widespread methylation loss that is commonly observed in cancer cells results in the loss of epigenetic repression of TEs. The aging process is similarly characterized by changes to the methylome. However, the impact of these epigenomic alterations on TE silencing and the functional consequences of this have remained unclear. To assess the epigenetic regulation of TEs in aging, we profiled DNA methylation in human mammary luminal epithelial cells (LEps)-a key cell lineage implicated in age-related breast cancers-from younger and older women. We report here that several TE subfamilies function as regulatory elements in normal LEps, and a subset of these display consistent methylation changes with age. Methylation changes at these TEs occurred at lineage-specific transcription factor binding sites, consistent with loss of lineage specificity. Whereas TEs mainly showed methylation loss, CpG islands (CGIs) that are targets of the Polycomb repressive complex 2 (PRC2) show a gain of methylation in aging cells. Many TEs with methylation loss in aging LEps have evidence of regulatory activity in breast cancer samples. We furthermore show that methylation changes at TEs impact the regulation of genes associated with luminal breast cancers. These results indicate that aging leads to DNA methylation changes at TEs that undermine the maintenance of lineage specificity, potentially increasing susceptibility to breast cancer.

Transcriptomic reprogramming for neuronal age reversal

Aging is a progressive multifaceted functional decline of a biological system. Chronic age-related conditions such as neurodegenerative diseases are leading causes of death worldwide, and they are becoming a pressing problem for our society. To address this global challenge, there is a need for novel, safe, and effective rejuvenation therapies aimed at reversing age-related phenotypes and improving human health. With gene expression being a key determinant of cell identity and function, and in light of recent studies reporting rejuvenation effects through genetic perturbations, we propose an age reversal strategy focused on reprogramming the cell transcriptome to a youthful state. To this end, we suggest using transcriptomic data from primary human cells to predict rejuvenation targets and develop high-throughput aging assays, which can be used in large perturbation screens. We propose neural cells as particularly relevant targets for rejuvenation due to substantial impact of neurodegeneration on human frailty. Of all cell types in the brain, we argue that glutamatergic neurons, neuronal stem cells, and oligodendrocytes represent the most impactful and tractable targets. Lastly, we provide experimental designs for anti-aging reprogramming screens that will likely enable the development of neuronal age reversal therapies, which hold promise for dramatically improving human health.

Considerations for reproducible omics in aging research

Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.

Single cell analysis of transcriptome and open chromatin reveals the dynamics of hair follicle stem cell aging

Aging is defined as the functional decline of tissues and organisms, leading to many human conditions, such as cancer, neurodegenerative diseases, and hair loss. Although stem cell exhaustion is widely recognized as a hallmark of aging, our understanding of cell state changes-specifically, the dynamics of the transcriptome and open chromatin landscape, and their relationship with aging-remains incomplete. Here we present a longitudinal, single-cell atlas of the transcriptome and open chromatin landscape for epithelia cells of the skin across various hair cycle stages and ages in mice. Our findings reveal fluctuating hair follicle stem cell (HF-SC) states, some of which are associated with the progression of the hair cycle during aging. Conversely, inner bulge niche cells display a more linear progression, seemingly less affected by the hair cycle. Further analysis of the open chromatin landscape, determined by single-cell Assay for Transposase-Accessible Chromatin (ATAC) sequencing, demonstrates that reduced open chromatin regions in HF-SCs are associated with differentiation, whereas gained open chromatin regions in HF-SCs are linked to the transcriptional control of quiescence. These findings enhance our understanding of the transcriptional dynamics in HF-SC aging and lay the molecular groundwork for investigating and potentially reversing the aging process in future experimental studies.

Human PBMC scRNA-seq-based aging clocks reveal ribosome to inflammation balance as a single-cell aging hallmark and super longevity

Quantifying aging rate is important for evaluating age-associated decline and mortality. A blood single-cell RNA sequencing dataset for seven supercentenarians (SCs) was recently generated. Here, we generate a reference 28-sample aging cohort to compute a single-cell level aging clock and to determine the biological age of SCs. Our clock model placed the SCs at a blood biological age to between 80.43 and 102.67 years. Compared to the model-expected aging trajectory, SCs display increased naive CD8⁺ T cells, decreased cytotoxic CD8⁺ T cells, memory CD4⁺ T cells, and megakaryocytes. As the most prominent molecular hallmarks at the single-cell level, SCs contain more cells and cell types with high ribosome level, which is associated with and, according to Bayesian network inference, contributes to a low inflammation state and slow aging of SCs. Inhibiting ribosomal activity or translation in monocytes validates such translation against inflammation balance revealed by our single-cell aging clock.

VarID2 quantifies gene expression noise dynamics and unveils functional heterogeneity of ageing hematopoietic stem cells

Variability of gene expression due to stochasticity of transcription or variation of extrinsic signals, termed biological noise, is a potential driving force of cellular differentiation. Utilizing single-cell RNA-sequencing, we develop VarID2 for the quantification of biological noise at single-cell resolution. VarID2 reveals enhanced nuclear versus cytoplasmic noise, and distinct regulatory modes stratified by correlation between noise, expression, and chromatin accessibility. Noise levels are minimal in murine hematopoietic stem cells (HSCs) and increase during differentiation and ageing. Differential noise identifies myeloid-biased Dlk1+ long-term HSCs in aged mice with enhanced quiescence and self-renewal capacity. VarID2 reveals noise dynamics invisible to conventional single-cell transcriptome analysis.

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single-cell resolution

Synthetic glucocorticoids, such as dexamethasone, have been used as a treatment for many immune conditions, such as asthma and, more recently, severe COVID-19. Single-cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single-cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated peripheral blood mononuclear cells from 96 African American children. We used novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we showed that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and showed widespread genetic regulation of the transcriptional dynamics of the gene expression response.

scMEB: a fast and clustering-independent method for detecting differentially expressed genes in single-cell RNA-seq data

BACKGROUND

Cell clustering is a prerequisite for identifying differentially expressed genes (DEGs) in single-cell RNA sequencing (scRNA-seq) data. Obtaining a perfect clustering result is of central importance for subsequent analyses, but not easy. Additionally, the increase in cell throughput due to the advancement of scRNA-seq protocols exacerbates many computational issues, especially regarding method runtime. To address these difficulties, a new, accurate, and fast method for detecting DEGs in scRNA-seq data is needed.

RESULTS

Here, we propose single-cell minimum enclosing ball (scMEB), a novel and fast method for detecting single-cell DEGs without prior cell clustering results. The proposed method utilizes a small part of known non-DEGs (stably expressed genes) to build a minimum enclosing ball and defines the DEGs based on the distance of a mapped gene to the center of the hypersphere in a feature space.

CONCLUSIONS

We compared scMEB to two different approaches that could be used to identify DEGs without cell clustering. The investigation of 11 real datasets revealed that scMEB outperformed rival methods in terms of cell clustering, predicting genes with biological functions, and identifying marker genes. Moreover, scMEB was much faster than the other methods, making it particularly effective for finding DEGs in high-throughput scRNA-seq data. We have developed a package scMEB for the proposed method, which could be available at https://github.com/FocusPaka/scMEB .

Exercise reprograms the inflammatory landscape of multiple stem cell compartments during mammalian aging

Exercise has the ability to rejuvenate stem cells and improve tissue regeneration in aging animals. However, the cellular and molecular changes elicited by exercise have not been systematically studied across a broad range of cell types in stem cell compartments. We subjected young and old mice to aerobic exercise and generated a single-cell transcriptomic atlas of muscle, neural, and hematopoietic stem cells with their niche cells and progeny, complemented by whole transcriptome analysis of single myofibers. We found that exercise ameliorated the upregulation of a number of inflammatory pathways associated with old age and restored aspects of intercellular communication mediated by immune cells within these stem cell compartments. Exercise has a profound impact on the composition and transcriptomic landscape of circulating and tissue-resident immune cells. Our study provides a comprehensive view of the coordinated responses of multiple aged stem cells and niche cells to exercise at the transcriptomic level.

DNA damage-induced stalling of transcription drives aging through gene expression imbalance

Age-related changes in gene expression have long been examined to understand the biology of aging. The hallmarks of aging are biological processes known to be associated with aging, but whether there is a unifying driver of these attributes, is not well understood. With the advent of technology over the last few years, it is quite clear that aging leads to global decline in transcription. In this Perspective, we highlight a new study in Nature Genetics that aimed to determine why global transcription rate reduces with age and how this phenomenon is the driver that interconnects multiple hallmarks of aging. This study recognizes that age-related accumulation of DNA damage, particularly transcription-blocking lesions, stalls RNA polymerase. This phenomenon affects longer genes leading to a gradual loss of transcription and skewing the transcriptome. In order to design a successful aging intervention, future work will be needed to test how some promising therapies in pre-clinical trials target affect transcriptional rate.

T cell aging and Alzheimer’s disease

The brain has long been considered an immune-privileged organ due to the presence of the blood-brain barrier (BBB). However, recent discoveries have revealed the underestimated role of T cells in the brain through the meningeal lymphatic system. Age is the primary risk factor for Alzheimer’s disease (AD), resulting in marked age-dependent changes in T cells. Manipulating peripheral T cell immune response has been shown to impact AD, but the relationship between T cell aging and AD remains poorly understood. Given the limited success of targeting amyloid beta (Aβ) and the growing evidence of T cells’ involvement in non-lymphoid organ aging, a deeper understanding of the relationship between T cells and AD in the context of aging is crucial for advancing therapeutic progress. In this review, we comprehensively examine existing studies on T cells and AD and offer an integrated perspective on their interconnections in the context of aging. This understanding can inform the development of new interventions to prevent or treat AD.

Ageing-associated changes in transcriptional elongation influence longevity

Physiological homeostasis becomes compromised during ageing, as a result of impairment of cellular processes, including transcription and RNA splicing1-4. However, the molecular mechanisms leading to the loss of transcriptional fidelity are so far elusive, as are ways of preventing it. Here we profiled and analysed genome-wide, ageing-related changes in transcriptional processes across different organisms: nematodes, fruitflies, mice, rats and humans. The average transcriptional elongation speed (RNA polymerase II speed) increased with age in all five species. Along with these changes in elongation speed, we observed changes in splicing, including a reduction of unspliced transcripts and the formation of more circular RNAs. Two lifespan-extending interventions, dietary restriction and lowered insulin-IGF signalling, both reversed most of these ageing-related changes. Genetic variants in RNA polymerase II that reduced its speed in worms5 and flies6 increased their lifespan. Similarly, reducing the speed of RNA polymerase II by overexpressing histone components, to counter age-associated changes in nucleosome positioning, also extended lifespan in flies and the division potential of human cells. Our findings uncover fundamental molecular mechanisms underlying animal ageing and lifespan-extending interventions, and point to possible preventive measures.

Rapid emergence of transcriptional heterogeneity upon molecular stress predisposes cells to two distinct states of senescence

Slowing aging can reduce the risk of chronic diseases. In particular, eliminating senescent cells is a promising approach to slow aging. Previous studies found that both cells from older animals and senescent cells have noisy gene expression. Here, we performed a large-scale single-cell RNA-sequencing time course to understand how transcriptional heterogeneity develops among senescent cells. We found that cells experiencing senescence-inducing oxidative stress rapidly adopt one of two major transcriptional states. One senescent cell state is associated with stress response, and the other is associated with tissue remodeling. We did not observe increased stochastic gene expression. This data is consistent with the idea that reproducible, limited, distinct, and coherent transcriptional states exist in senescent cell populations. These physiologically distinct senescent cell subtypes may each affect the aging process in unique ways and constitute a source of heterogeneity in aging.

Molecular Markers of Blood Cell Populations Can Help Estimate Aging of the Immune System

Aging of the immune system involves functional changes in individual cell populations, in hematopoietic tissues and at the systemic level. They are mediated by factors produced by circulating cells, niche cells, and at the systemic level. Age-related alterations in the microenvironment of the bone marrow and thymus cause a decrease in the production of naive immune cells and functional immunodeficiencies. Another result of aging and reduced tissue immune surveillance is the accumulation of senescent cells. Some viral infections deplete adaptive immune cells, increasing the risk of autoimmune and immunodeficiency conditions, leading to a general degradation in the specificity and effectiveness of the immune system in old age. During the COVID-19 pandemic, the state-of-the-art application of mass spectrometry, multichannel flow cytometry, and single-cell genetic analysis have provided vast data on the mechanisms of aging of the immune system. These data require systematic analysis and functional verification. In addition, the prediction of age-related complications is a priority task of modern medicine in the context of the increase in the aged population and the risk of premature death during epidemics. In this review, based on the latest data, we discuss the mechanisms of immune aging and highlight some cellular markers as indicators of age-related immune disbalance that increase the risk of senile diseases and infectious complications.

Decrease in naturally occurring antibodies against epitopes of Alzheimer's disease (AD) risk gene products is associated with cognitive decline in AD

BACKGROUND

Naturally occurring antibodies (NAbs) are germline-encoded immunoglobulins that can bind to and clear out self-neo-epitopes as well as apoptotic and necrotic cells. However, NAbs pathological relevance in Alzheimer's disease (AD) is not well-understood.

METHODS

Twenty-eight candidate proteins encoded by AD-associated genes were selected for this study based on a number of selection criteria, including preferential expression in the brain and B-lymphocyte cells. The levels of NAbs in plasma were analyzed according to their epitopes in age- and gender-matched cognitively normal subjects (CN, n = 56), subjects with mild cognitive impairment (MCI, n = 16) and subjects with AD (n = 56). We aimed to study the levels of their NAbs in plasma and their associations with cognitive decline in individuals with AD.

RESULTS

Of the 28 antigens tested, 17 showed decreased NAbs in individuals with AD; in particular, NAb-TREM2 had an area under the ROC curve of 0.806, with the highest sensitivity (0.370) at 95% specificity among all 28 tests. Further protein-protein interaction networks and functional enrichment analysis suggested that target genes were enriched in AD-related pathological processes classified under "Alzheimer's disease", "neurodegenerative disease" and "amyloidosis". The "Alzheimer's disease" and "neurodegenerative disease" clusters, which converged on the initial "recognition" step of microglial phagocytosis, showed the best diagnostic performance for AD.

CONCLUSIONS

This study suggests a decline in the function of the adaptive immune system in AD, and the levels of circulating NAbs are likely to serve as biomarkers for surveilling the progression of AD.

Immune determinants of the pre-metastatic niche

Primary tumors actively and specifically prime pre-metastatic niches (PMNs), the future sites of organotropic metastasis, preparing these distant microenvironments for disseminated tumor cell arrival. While initial studies of the PMN focused on extracellular matrix alterations and stromal reprogramming, it is increasingly clear that the far-reaching effects of tumors are in great part achieved through systemic and local PMN immunosuppression. Here, we discuss recent advances in our understanding of the tumor immune microenvironment and provide a comprehensive overview of the immune determinants of the PMN's spatiotemporal evolution. Moreover, we depict the PMN immune landscape, based on functional pre-clinical studies as well as mounting clinical evidence, and the dynamic, reciprocal crosstalk with systemic changes imposed by cancer progression. Finally, we outline emerging therapeutic approaches that alter the dynamics of the interactions driving PMN formation and reverse immunosuppression programs in the PMN ensuring early anti-tumor immune responses.

Heterogeneity of fibroblasts is a hallmark of age-associated erectile dysfunction

BACKGROUND

The prevalence of age-associated erectile dysfunction (ED) increases pronouncedly with age. However, the cellular composition and transcriptomic changes of aging penile corpus cavernosum remain largely unclear.

METHODS

Herein, we performed single cell sequencing penile corpus cavernosum from five young with normal erectile response and five old rats with ED.

RESULTS

Clustering analysis identified 19 cell types, such as fibroblasts, myofibroblasts and immune cells. We next revealed their transcriptomic alterations and investigated novel subpopulations of major cell types. Among them, fibroblasts possessed the largest cell number and showed apparent heterogeneity. By performing single-cell entropy analysis on fibroblasts, we observed the age-associated decrease of entropy, and aged fibroblasts were found to adopt senescent secretory phenotype, as evidenced by the high expression of genes associated with the senescence-associated secretory phenotype (SASP). Finally, we constructed a comprehensive intercellular communication network and highlighted key mediators of crosstalk between fibroblasts and other cell types.

CONCLUSIONS

We plotted a cellular atlas of aging cells within penile corpus cavernosum, especially fibroblasts. Our work will deepen the understanding of the heterogeneity among certain cell types within aged penile corpus cavernosum, which will generate positive effects on the future treatment of age-associated ED.

Progress in Discovering Transcriptional Noise in Aging

Increasing stochasticity is a key feature in the aging process. At the molecular level, in addition to genome instability, a well-recognized hallmark of aging, cell-to-cell variation in gene expression was first identified in mouse hearts. With the technological breakthrough in single-cell RNA sequencing, most studies performed in recent years have demonstrated a positive correlation between cell-to-cell variation and age in human pancreatic cells, as well as mouse lymphocytes, lung cells, and muscle stem cells during senescence in vitro. This phenomenon is known as the "transcriptional noise" of aging. In addition to the increasing evidence in experimental observations, progress also has been made to better define transcriptional noise. Traditionally, transcriptional noise is measured using simple statistical measurements, such as the coefficient of variation, Fano factor, and correlation coefficient. Recently, multiple novel methods have been proposed, e.g., global coordination level analysis, to define transcriptional noise based on network analysis of gene-to-gene coordination. However, remaining challenges include a limited number of wet-lab observations, technical noise in single-cell RNA sequencing, and the lack of a standard and/or optimal data analytical measurement of transcriptional noise. Here, we review the recent technological progress, current knowledge, and challenges to better understand transcriptional noise in aging.

Genome-wide RNA polymerase stalling shapes the transcriptome during aging

Gene expression profiling has identified numerous processes altered in aging, but how these changes arise is largely unknown. Here we combined nascent RNA sequencing and RNA polymerase II chromatin immunoprecipitation followed by sequencing to elucidate the underlying mechanisms triggering gene expression changes in wild-type aged mice. We found that in 2-year-old liver, 40% of elongating RNA polymerases are stalled, lowering productive transcription and skewing transcriptional output in a gene-length-dependent fashion. We demonstrate that this transcriptional stress is caused by endogenous DNA damage and explains the majority of gene expression changes in aging in most mainly postmitotic organs, specifically affecting aging hallmark pathways such as nutrient sensing, autophagy, proteostasis, energy metabolism, immune function and cellular stress resilience. Age-related transcriptional stress is evolutionary conserved from nematodes to humans. Thus, accumulation of stochastic endogenous DNA damage during aging deteriorates basal transcription, which establishes the age-related transcriptome and causes dysfunction of key aging hallmark pathways, disclosing how DNA damage functionally underlies major aspects of normal aging.

Construction of a cross-species cell landscape at single-cell level

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging.

Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single-cell resolution

Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single-cell RNA sequencing (scRNA-seq) to characterize an enriched population of human HSPCs obtained from young and elderly healthy individuals.

Based on their transcriptional profile, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain aging-associated changes in hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks (GRNs) and detected regulons that were specifically active in elderly individuals. Using previous findings in healthy cells as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome (MDS) and detected specific alterations of the expression dynamics of genes involved in erythroid differentiation in all patients with MDS such as TRIB2. In addition, the comparison between transcriptional programs and GRNs regulating normal HSPCs and MDS HSPCs allowed identification of regulons that were specifically active in MDS cases such as SMAD1, HOXA6, POU2F2, and RUNX1 suggesting a role of these transcription factors (TFs) in the pathogenesis of the disease.

In summary, we demonstrate that the combination of single-cell technologies with computational analysis tools enable the study of a variety of cellular mechanisms involved in complex biological systems such as early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with perturbations such as aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patients.

Single-cell transcriptomics of peripheral blood in the aging mouse

Compositional and transcriptional changes in the hematopoietic system have been used as biomarkers of immunosenescence and aging. Here, we use single-cell RNA-sequencing to study the aging peripheral blood in mice and characterize the changes in cell-type composition and transcriptional profiles associated with age. We identified 17 clusters from a total of 14,588 single cells. We detected a general upregulation of antigen processing and presentation and chemokine signaling pathways and a downregulation of genes involved in ribosome pathways with age. In old peripheral blood, we also observed an increased percentage of cells expressing senescence markers (Cdkn1a, and Cdkn2a). In addition, we detected a cluster of activated T cells exclusively found in old blood, with lower expression of Cd28 and higher expression of Bcl2 and Cdkn2a, suggesting that the cells are senescent and resistant to apoptosis.