The Systems Biology of Single-Cell Aging

Thioredoxin (Trx): A redox target and modulator of cellular senescence and aging-related diseases

Thioredoxin (Trx) is a compact redox-regulatory protein that modulates cellular redox state by reducing oxidized proteins. Trx exhibits dual functionality as an antioxidant and a cofactor for diverse enzymes and transcription factors, thereby exerting influence over their activity and function. Trx has emerged as a pivotal biomarker for various diseases, particularly those associated with oxidative stress, inflammation, and aging. Recent clinical investigations have underscored the significance of Trx in disease diagnosis, treatment, and mechanistic elucidation. Despite its paramount importance, the intricate interplay between Trx and cellular senescence-a condition characterized by irreversible growth arrest induced by multiple aging stimuli-remains inadequately understood. In this review, our objective is to present a comprehensive and up-to-date overview of the structure and function of Trx, its involvement in redox signaling pathways and cellular senescence, its association with aging and age-related diseases, as well as its potential as a therapeutic target. Our review aims to elucidate the novel and extensive role of Trx in senescence while highlighting its implications for aging and age-related diseases.

Sis2 regulates yeast replicative lifespan in a dose-dependent manner

Application of microfluidic platforms facilitated high-precision measurements of yeast replicative lifespan (RLS); however, comparative quantification of lifespan across strain libraries has been missing. Here we microfluidically measure the RLS of 307 yeast strains, each deleted for a single gene. Despite previous reports of extended lifespan in these strains, we found that 56% of them did not actually live longer than the wild-type; while the remaining 44% showed extended lifespans, the degree of extension was often different from what was previously reported. Deletion of SIS2 gene led to the largest RLS increase observed. Sis2 regulated yeast lifespan in a dose-dependent manner, implying a role for the coenzyme A biosynthesis pathway in lifespan regulation. Introduction of the human PPCDC gene in the sis2Δ background neutralized the lifespan extension. RNA-seq experiments revealed transcriptional increases in cell-cycle machinery components in sis2Δ background. High-precision lifespan measurement will be essential to elucidate the gene network governing lifespan.

Systems Biology of Ageing

The ageing process is highly complex involving multiple processes operating at different biological levels. Systems Biology presents an approach using integrative computational and laboratory study that allows us to address such complexity. The approach relies on the computational analysis of knowledge and data to generate predictive models that may be validated with further laboratory experimentation. Our understanding of ageing is such that translational opportunities are within reach and systems biology offers a means to ensure that optimal decisions are made. We present an overview of the methods employed from bioinformatics and computational modelling and describe some of the insights into ageing that have been gained.

A complex systems approach to aging biology

Having made substantial progress understanding molecules, cells, genes and pathways, aging biology research is now moving toward integration of these parts, attempting to understand how their joint dynamics may contribute to aging. Such a shift of perspective requires the adoption of a formal complex systems framework, a transition being facilitated by large-scale data collection and new analytical tools. Here, we provide a theoretical framework to orient researchers around key concepts for this transition, notably emergence, interaction networks and resilience. Drawing on evolutionary theory, network theory and principles of homeostasis, we propose that organismal function is accomplished by the integration of regulatory mechanisms at multiple hierarchical scales, and that the disruption of this ensemble causes the phenotypic and functional manifestations of aging. We present key examples at scales ranging from sub-organismal biology to clinical geriatrics, outlining how this approach can potentially enrich our understanding of aging.

In Silico Investigation of the Biological Implications of Complex DNA Damage with Emphasis in Cancer Radiotherapy through a Systems Biology Approach

Different types of DNA lesions forming in close vicinity, create clusters of damaged sites termed as “clustered/complex DNA damage” and they are considered to be a major challenge for DNA repair mechanisms resulting in significant repair delays and induction of genomic instability. Upon detection of DNA damage, the corresponding DNA damage response and repair (DDR/R) mechanisms are activated. The inability of cells to process clustered DNA lesions efficiently has a great impact on the normal function and survival of cells. If complex lesions are left unrepaired or misrepaired, they can lead to mutations and if persistent, they may lead to apoptotic cell death. In this in silico study, and through rigorous data mining, we have identified human genes that are activated upon complex DNA damage induction like in the case of ionizing radiation (IR) and beyond the standard DNA repair pathways, and are also involved in cancer pathways, by employing stringent bioinformatics and systems biology methodologies. Given that IR can cause repair resistant lesions within a short DNA segment (a few nm), thereby augmenting the hazardous and toxic effects of radiation, we also investigated the possible implication of the most biologically important of those genes in comorbid non-neoplastic diseases through network integration, as well as their potential for predicting survival in cancer patients.

Modeling aging and its impact on cellular function and organismal behavior

Aging is a complex phenomenon of functional decay in a biological organism. Although the effects of aging are readily recognizable in a wide range of organisms, the cause(s) of aging are ill defined and poorly understood. Experimental methods on model organisms have driven significant insight into aging as a process, but have not provided a complete model of aging. Computational biology offers a unique opportunity to resolve this gap in our knowledge by generating extensive and testable models that can help us understand the fundamental nature of aging, identify the presence and characteristics of unaccounted aging factor(s), demonstrate the mechanics of particular factor(s) in driving aging, and understand the secondary effects of aging on biological function. In this review, we will address each of the above roles for computational biology in aging research. Concurrently, we will explore the different applications of computational biology to aging in single-celled versus multicellular organisms. Given the long history of computational biogerontological research on lower eukaryotes, we emphasize the key future goals of gradually integrating prior models into a holistic map of aging and translating successful models to higher-complexity organisms.

Senolytics and the compression of late-life mortality

Senescent cells play an important role in mammalian ageing and in the etiology of age-related diseases. Treatment of mice with senolytics - drugs that selectively remove senescent cells - causes an extension of median lifespan but has little effect on maximum lifespan. Postponement of some mortality to later ages, without a corresponding increase in maximum mortality, can be termed 'compression of mortality'. When we fit the standard Gompertz mortality model to the survival data following senolytic treatment, we find an increase in the slope parameter, commonly described as the 'actuarial ageing rate'. These observations raise important questions about the actions of senolytic treatments and their effects on health and survival, which are not yet sufficiently understood. To explore how the survival data from senolytics experiments might be explained, we combine a recent exploration of the evolutionary basis of cellular senescence with theoretical consideration of the molecular processes that might be involved. We perform numerical simulations of senescent cell accumulation and senolytic treatment in an ageing population. The simulations suggest that while senolytics diminish the burden of senescent cells, they may also impair the general repair capacity of the organism, leading to a faster accumulation post-treatment of new senescent cells. Our results suggest a framework to address the benefits and possible side effects of senolytic therapies, with the potential to aid in the design of optimal treatment regimens.

Oklahoma Nathan Shock Aging Center - assessing the basic biology of aging from genetics to protein and function

The Oklahoma Shock Nathan Shock Center is designed to deliver unique, innovative services that are not currently available at most institutions. The focus of the Center is on geroscience and the development of careers of young investigators. Pilot grants are provided through the Research Development Core to junior investigators studying aging/geroscience throughout the USA. However, the services of our Center are available to the entire research community studying aging and geroscience. The Oklahoma Nathan Shock Center provides researchers with unique services through four research cores. The Multiplexing Protein Analysis Core uses the latest mass spectrometry technology to simultaneously measure the levels, synthesis, and turnover of hundreds of proteins associated with pathways of importance to aging, e.g., metabolism, antioxidant defense system, proteostasis, and mitochondria function. The Genomic Sciences Core uses novel next-generation sequencing that allows investigators to study the effect of age, or anti-aging manipulations, on DNA methylation, mitochondrial genome heteroplasmy, and the transcriptome of single cells. The Geroscience Redox Biology Core provides investigators with a comprehensive state-of-the-art assessment of the oxidative stress status of a cell, e.g., measures of oxidative damage and redox couples, which are important in aging as well as many major age-related diseases as well as assays of mitochondrial function. The GeroInformatics Core provides investigators assistance with data analysis, which includes both statistical support as well as analysis of large datasets. The Core also has developed number of unique software packages to help with interpretation of results and discovery of new leads relevant to aging. In addition, the Geropathology Research Resource in the Program Enhancement Core provides investigators with pathological assessments of mice using the recently developed Geropathology Grading Platform.

A yeast-optimized single-cell transcriptomics platform elucidates how mycophenolic acid and guanine alter global mRNA levels

Stochastic gene expression leads to inherent variability in expression outcomes even in isogenic single-celled organisms grown in the same environment. The Drop-Seq technology facilitates transcriptomic studies of individual mammalian cells, and it has had transformative effects on the characterization of cell identity and function based on single-cell transcript counts. However, application of this technology to organisms with different cell size and morphology characteristics has been challenging. Here we present yeastDrop-Seq, a yeast-optimized platform for quantifying the number of distinct mRNA molecules in a cell-specific manner in individual yeast cells. Using yeastDrop-Seq, we measured the transcriptomic impact of the lifespan-extending compound mycophenolic acid and its epistatic agent guanine. Each treatment condition had a distinct transcriptomic footprint on isogenic yeast cells as indicated by distinct clustering with clear separations among the different groups. The yeastDrop-Seq platform facilitates transcriptomic profiling of yeast cells for basic science and biotechnology applications.

A systems pharmacology approach to identify the autophagy-inducing effects of Traditional Persian medicinal plants

Aging is correlated with several complex diseases, including type 2 diabetes, neurodegeneration diseases, and cancer. Identifying the nature of this correlation and treatment of age-related diseases has been a major subject of both modern and traditional medicine. Traditional Persian Medicine (TPM) embodies many prescriptions for the treatment of ARDs. Given that autophagy plays a critical role in antiaging processes, the present study aimed to examine whether the documented effect of plants used in TPM might be relevant to the induction of autophagy? To this end, the TPM-based medicinal herbs used in the treatment of the ARDs were identified from modern and traditional references. The known phytochemicals of these plants were then examined against literature for evidence of having autophagy inducing effects. As a result, several plants were identified to have multiple active ingredients, which indeed regulate the autophagy or its upstream pathways. In addition, gene set enrichment analysis of the identified targets confirmed the collective contribution of the identified targets in autophagy regulating processes. Also, the protein-protein interaction (PPI) network of the targets was reconstructed. Network centrality analysis of the PPI network identified mTOR as the key network hub. Given the well-documented role of mTOR in inhibiting autophagy, our results hence support the hypothesis that the antiaging mechanism of TPM-based medicines might involve autophagy induction. Chemoinformatics study of the phytochemicals using docking and molecular dynamics simulation identified, among other compounds, the cyclo-trijuglone of Juglans regia L. as a potential ATP-competitive inhibitor of mTOR. Our results hence, provide a basis for the study of TPM-based prescriptions using modern tools in the quest for developing synergistic therapies for ARDs.

Identifying longevity associated genes by integrating gene expression and curated annotations

Aging is a complex process with poorly understood genetic mechanisms. Recent studies have sought to classify genes as pro-longevity or anti-longevity using a variety of machine learning algorithms. However, it is not clear which types of features are best for optimizing classification performance and which algorithms are best suited to this task. Further, performance assessments based on held-out test data are lacking. We systematically compare five popular classification algorithms using gene ontology and gene expression datasets as features to predict the pro-longevity versus anti-longevity status of genes for two model organisms (C. elegans and S. cerevisiae) using the GenAge database as ground truth. We find that elastic net penalized logistic regression performs particularly well at this task. Using elastic net, we make novel predictions of pro- and anti-longevity genes that are not currently in the GenAge database.

Aging is a complex process with poorly understood genetic mechanisms. Recent studies have sought to classify genes as pro-longevity or anti-longevity using a variety of machine learning algorithms. However, it is not clear which types of features are best for optimizing classification performance and which algorithms are best suited to this task. Further, performance assessments based on held-out test data are lacking. We systematically compare five popular classification algorithms using gene ontology and gene expression datasets as features to predict the pro-longevity versus anti-longevity status of genes for two model organisms (nematode worms and yeast) using the GenAge database as ground truth. We find that elastic net penalized logistic regression performs particularly well at this task. Using elastic net, we make novel predictions of pro- and anti-longevity genes that are not currently in the GenAge database.

Quantitative Insights into Age-Associated DNA-Repair Inefficiency in Single Cells

Although double-strand break (DSB) repair is essential for a cell's survival, little is known about how DSB repair mechanisms are affected by age. Here we characterize the impact of cellular aging on the efficiency of single-strand annealing (SSA), a DSB repair mechanism. We measure SSA repair efficiency in young and old yeast cells and report a 23.4% decline in repair efficiency. This decline is not due to increased use of non-homologous end joining. Instead, we identify increased G1 phase duration in old cells as a factor responsible for the decreased SSA repair efficiency. Expression of 3xCLN2 leads to higher SSA repair efficiency in old cells compared with expression of 1xCLN2, confirming the involvement of cell-cycle regulation in age-associated repair inefficiency. Examining how SSA repair efficiency is affected by sequence heterology, we find that heteroduplex rejection remains high in old cells. Our work provides insights into the links between single-cell aging and DSB repair efficiency.

Surface Active Agents and Their Health-Promoting Properties: Molecules of Multifunctional Significance

Surface active agents (SAAs) are molecules with the capacity to adsorb to solid surfaces and/or fluid interfaces, a property that allows them to act as multifunctional ingredients (e.g., wetting and dispersion agents, emulsifiers, foaming and anti-foaming agents, lubricants, etc.) in a widerange of the consumer products of various industrial sectors (e.g., pharmaceuticals, cosmetics, personal care, detergents, food, etc.). Given their widespread utilization, there is a continuously growing interest to explore their role in consumer products (relevant to promoting human health) and how such information can be utilized in order to synthesize better chemical derivatives. In this review article, weaimed to provide updated information on synthetic and biological (biosurfactants) SAAs and their health-promoting properties (e.g., anti-microbial, anti-oxidant, anti-viral, anti-inflammatory, anti-cancer and anti-aging) in an attempt to better define some of the underlying mechanism(s) by which they exert such properties.

Characterization of the impact of GMP/GDP synthesis inhibition on replicative lifespan extension in yeast

Slowing down aging-associated accumulation of molecular damage or its prevention represents a promising therapeutic paradigm to combat aging-related disease and death. While several chemical compounds extend lifespan in model organisms, their mechanism of action is often unknown, reducing their therapeutic potential. Using a systematic approach, here we characterize the impact of the GMP pathway on yeast lifespan and elucidate GMP synthesis inhibition as a lifespan extension mechanism. We further discover that proteasome activation extends lifespan in part through the GMP pathway. GMP synthesis inhibition exerts its lifespan extension effect independently of the canonical nutrient-sensing pathway regulating lifespan. Exposing longitudinally aging yeast cells to GMP pathway inhibition in an age-dependent manner, we demonstrate that the lifespan extension is facilitated by slowing, rather than reversing, the aging process in cells. Using a GUK1 mutant with lower GMP-to-GDP conversion activity, we observe lifespan extension, suggesting that reduced GDP level by itself can also extend yeast lifespan. These findings elucidate the involvement of nucleotide metabolism in the aging process. The existence of clinically-approved GMP pathway inhibitors elicits the potential of a new class of therapeutics for aging-related disorders.

Recent advances in understanding the mechanisms determining longevity

The field of aging research has progressed significantly over the past decades. Exogenously and endogenously inflicted molecular damage ranging from genotoxic to organellar damage drives the aging process. Repair mechanisms and compensatory responses counteract the detrimental consequences of the various damage types. Here, we discuss recent progress in understanding cellular mechanisms and interconnections between signaling pathways that control longevity. We summarize cell-autonomous and non-cell-autonomous mechanisms that impact the cellular and organismal aging process

Stochastic modeling of aging cells reveals how damage accumulation, repair, and cell-division asymmetry affect clonal senescence and population fitness

BACKGROUND

Asymmetry during cellular division, both in the uneven partitioning of damaged cellular components and of cell volume, is a cell biological phenomenon experienced by many unicellular organisms. Previous work based on a deterministic model claimed that such asymmetry in the partitioning of cell volume and of aging-associated damage confers a fitness benefit in avoiding clonal senescence, primarily by diversifying the cellular population. However, clonal populations of unicellular organisms are already naturally diversified due to the inherent stochasticity of biological processes.

RESULTS

Applying a model of aging cells that accounts for natural cell-to-cell variations across a broad range of parameter values, here we show that the parameters directly controlling the accumulation and repair of damage are the most important factors affecting fitness and clonal senescence, while the effects of both segregation of damaged components and division asymmetry are frequently minimal and generally context-dependent.

CONCLUSIONS

We conclude that damage segregation and division asymmetry, perhaps counterintuitively, are not necessarily beneficial from an evolutionary perspective.

Metabolic Alterations in Aging Macrophages: Ingredients for Inflammaging?

Aging is a complex process with an impact on essentially all organs. Declined cellular repair causes increased damage at genomic and proteomic levels upon aging. This can lead to systemic changes in metabolism and pro-inflammatory cytokine production, resulting in low-grade inflammation, or 'inflammaging'. Tissue macrophages, gatekeepers of parenchymal homeostasis and integrity, are prime inflammatory cytokine producers, as well as initiators and regulators of inflammation. In this opinion piece, we summarize intrinsic alterations in macrophage phenotype and function with age. We propose that alternatively activated macrophages (M2-like), which are yet pro-inflammatory, can accumulate in tissues and promote inflammaging. Age-related increases in endoplasmic reticulum stress and mitochondrial dysfunction might be cell-intrinsic forces driving this unusual phenotype.