Lack of evidence for increased transcriptional noise in aged tissues

Transcriptional Heterogeneity and Differential Response of Rod Photoreceptor Pathway Uncovered by Single-Cell RNA Sequencing of the Aging Mouse Retina

Visual function deteriorates throughout the natural course of aging. Age-related structural and functional adaptations are observed in the retina, the light-sensitive neuronal tissue of the eye where visual perception begins. Molecular mechanisms underlying retinal aging are still poorly understood, highlighting the need to identify biomarkers for better prognosis and alleviation of aging-associated vision impairment. Here, we investigate dynamics of transcriptional dysregulation in the retina and identify affected pathways within distinct retinal cell types. Using an optimized protocol for single-cell RNA sequencing of mouse retinas at 3, 12, 18, and 24 months, we detect a progressive increase in the number of differentially expressed genes across all retinal cell types. The extent and direction of expression changes varies, with photoreceptor, bipolar, and Müller cells showing the maximum number of differentially expressed genes at all age groups. Furthermore, our analyses uncover transcriptionally distinct, heterogeneous subpopulations of rod photoreceptors and bipolar cells, distributed across distinct areas of the retina. Our findings provide a plausible molecular explanation for enhanced susceptibility of rod cells to aging and correlate with the observed loss of scotopic sensitivity in elderly individuals.

Adaptations of neutrophils in cancer

There is a renewed interest in neutrophil biology, largely instigated by their prominence in cancer. From an immunologist's perspective, a conceptual breakthrough is the realization that prototypical inflammatory, cytotoxic leukocytes can be tamed to promote the survival and growth of other cells. This has sparked interest in defining the biological principles and molecular mechanisms driving the adaptation of neutrophils to cancer. Yet, many questions remain: is this adaptation mediated by reprogramming mature neutrophils inside the tumoral mass, or rather by rewiring granulopoiesis in the bone marrow? Why, in some instances, are neutrophils beneficial and in others detrimental to cancer? How many different functional programs can be induced in neutrophils by tumors, and is this dependent on the type of tumor? This review summarizes what we know about these questions and discusses therapeutic strategies based on our incipient knowledge of how neutrophils adapt to cancer.

Profiling the transcriptomic age of single-cells in humans

Although aging clocks predicting the age of individual organisms have been extensively studied, the age of individual cells remained largely unexplored. Most recently single-cell omics clocks were developed for the mouse, however, extensive profiling the age of human cells is still lacking. To fill this gap, here we use available scRNA-seq data of 1,058,909 blood cells of 508 healthy, human donors (between 19 and 75 years), for developing single-cell transcriptomic clocks and predicting the age of human blood cells. By the application of the proposed cell-type-specific single-cell clocks, our main observations are that (i) transcriptomic age is associated with cellular senescence; (ii) the transcriptomic age of classical monocytes as well as naive B and T cells is decreased in moderate COVID-19 followed by an increase for some cell types in severe COVID-19; and (iii) the human embryo cells transcriptomically rejuvenated at the morulae and blastocyst stages. In summary, here we demonstrate that single-cell transcriptomic clocks are useful tools to investigate aging and rejuvenation at the single-cell level.

Loss of coordination between basic cellular processes in human aging

Age-related loss of gene expression coordination has been reported for distinct cell types and may lead to impaired cellular function. Here we propose a method for quantifying age-related changes in transcriptional regulatory relationships between genes, based on a model learned from external data. We used this method to uncover age-related trends in gene-gene relationships across eight human tissues, which demonstrates that reduced co-expression may also result from coordinated transcriptional responses. Our analyses reveal similar numbers of strengthening and weakening gene-gene relationships with age, impacting both tissue-specific (for example, coagulation in blood) and ubiquitous biological functions. Regulatory relationships becoming weaker with age were established mostly between genes operating in distinct cellular processes. As opposed to that, regulatory relationships becoming stronger with age were established both within and between different cellular functions. Our work reveals that, although most transcriptional regulatory gene-gene relationships are maintained during aging, those with declining regulatory coupling result mostly from a loss of coordination between distinct cellular processes.

Chronic disease incidence explained by stepwise models and co-occurrence among them

Multimorbidity (MM) is the co-occurrence of two or more chronic diseases. We provided a dynamic approach revealing the MM complexity constructing a multistep incidence-age model for all patients with MM between 2014 and 2021 in the Basque Health System, Spain. The multistep model, with eight steps for males and nine for females, is a very well-fitting representation of MM. To gain insight into the MM components, we modeled the 19 diseases used to calculate the Charlson Comorbidity Index (CCI). We observed that the CCI diseases formed a complex interaction network. Hierarchical clustering of the incidence-age profiles clustered the CCI diseases into low- and high-risk of dying pathologies. Diseases with a higher number of steps are better represented by a multistep model. Anatomically, diseases associated with the central nervous system have the highest number of steps, followed by those associated with the kidney, heart, peripheral vasulature, pancreas, joints, cerebral vasculature, lung, stomach, and liver.

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.

Translation is an emerging constraint on protein homeostasis in ageing

Proteins are molecular machines that provide structure and perform vital transport, signalling and enzymatic roles. Proteins expressed by cells require tight regulation of their concentration, folding, localisation, and modifications; however, this state of protein homeostasis is continuously perturbed by tissue-level stresses. While cells in healthy tissues are able to buffer against these perturbations, for example, by expression of chaperone proteins, protein homeostasis is lost in ageing, and can lead to protein aggregation characteristic of protein folding diseases. Here, we review reports of a progressive disconnect between transcriptomic and proteomic regulation during cellular ageing. We discuss how age-associated changes to cellular responses to specific stressors in the tissue microenvironment are exacerbated by loss of ribosomal proteins, ribosomal pausing, and mistranslation.

Aging clocks based on accumulating stochastic variation

Aging clocks have provided one of the most important recent breakthroughs in the biology of aging, and may provide indicators for the effectiveness of interventions in the aging process and preventive treatments for age-related diseases. The reproducibility of accurate aging clocks has reinvigorated the debate on whether a programmed process underlies aging. Here we show that accumulating stochastic variation in purely simulated data is sufficient to build aging clocks, and that first-generation and second-generation aging clocks are compatible with the accumulation of stochastic variation in DNA methylation or transcriptomic data. We find that accumulating stochastic variation is sufficient to predict chronological and biological age, indicated by significant prediction differences in smoking, calorie restriction, heterochronic parabiosis and partial reprogramming. Although our simulations may not explicitly rule out a programmed aging process, our results suggest that stochastically accumulating changes in any set of data that have a ground state at age zero are sufficient for generating aging clocks.

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 neural network-based model framework for cell-fate decisions and development

Gene regulatory networks (GRNs) fulfill the essential function of maintaining the stability of cellular differentiation states by sustaining lineage-specific gene expression, while driving the progression of development. However, accounting for the relative stability of intermediate differentiation stages and their divergent trajectories remains a major challenge for models of developmental biology. Here, we develop an empirical data-based associative GRN model (AGRN) in which regulatory networks store multilineage stage-specific gene expression profiles as associative memory patterns. These networks are capable of responding to multiple instructive signals and, depending on signal timing and identity, can dynamically drive the differentiation of multipotent cells toward different cell state attractors. The AGRN dynamics can thus generate diverse lineage-committed cell populations in a robust yet flexible manner, providing an attractor-based explanation for signal-driven cell fate decisions during differentiation and offering a readily generalizable modelling tool that can be applied to a wide variety of cell specification systems.

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.

Transcriptional maintenance of cortical somatostatin interneuron subtype identity during migration

Although cardinal cortical interneuron identity is established upon cell-cycle exit, it remains unclear whether specific interneuron subtypes are pre-established, and if so, how their identity is maintained prior to circuit integration. We conditionally removed Sox6 (Sox6-cKO) in migrating somatostatin (Sst+) interneurons and assessed the effects on their mature identity. In adolescent mice, five of eight molecular Sst+ subtypes were nearly absent in the Sox6-cKO cortex without a reduction in cell number. Sox6-cKO cells displayed electrophysiological maturity and expressed genes enriched within the broad class of Sst+ interneurons. Furthermore, we could infer subtype identity prior to cortical integration (embryonic day 18.5), suggesting that the loss in subtype was due to disrupted subtype maintenance. Conversely, Sox6 removal at postnatal day 7 did not disrupt marker expression in the mature cortex. Therefore, Sox6 is necessary during migration for maintenance of Sst+ subtype identity, indicating that subtype maintenance requires active transcriptional programs.

Systems genetics approaches for understanding complex traits with relevance for human disease

Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.

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.

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.

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.

Age or lifestyle-induced accumulation of genotoxicity is associated with a length-dependent decrease in gene expression

DNA damage has long been advocated as a molecular driver of aging. DNA damage occurs in a stochastic manner, and is therefore more likely to accumulate in longer genes. The length-dependent accumulation of transcription-blocking damage, unlike that of somatic mutations, should be reflected in gene expression datasets of aging. We analyzed gene expression as a function of gene length in several single-cell RNA sequencing datasets of mouse and human aging. We found a pervasive age-associated length-dependent underexpression of genes across species, tissues, and cell types. Furthermore, we observed length-dependent underexpression associated with UV-radiation and smoke exposure, and in progeroid diseases, Cockayne syndrome, and trichothiodystrophy. Finally, we studied published gene sets showing global age-related changes. Genes underexpressed with aging were significantly longer than overexpressed genes. These data highlight a previously undetected hallmark of aging and show that accumulation of genotoxicity in long genes could lead to reduced RNA polymerase II processivity.

Strategies of neutrophil diversification

Neutrophils are formidable defenders. Their vast numbers, constant production, high cytotoxicity and capacity to produce extracellular traps, underlie their ability to efficiently protect in a microorganism-rich world. However, neutrophils are much more than immune sentinels, as evidenced by the expanding repertoire of functions discovered in the context of tissue homeostasis, regeneration or chronic pathologies. In this Perspective, we discuss general functional features of the neutrophil compartment that may be relevant in most, if not all, physiological scenarios in which they participate, including specialization in naïve tissues, transcriptional noise in the bloodstream as a potential strategy for diversification and functional bias in inflammatory sites. We intentionally present the reader with more questions than answers and propose models and approaches that we hope will shed new light onto the biology of these fascinating cells and spark new directions of research.

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.