Targeting EDEM protects against ER stress and improves development and survival in C. elegans.

EDEM-1, EDEM-2 and EDEM-3 are key players for the quality control of newly synthesized proteins in the endoplasmic reticulum (ER) by accelerating disposal and degradation of misfolded proteins through ER Associated Degradation (ERAD). Although many previous studies reported the role of individual ERAD components especially in cell-based systems, still little is known about the consequences of ERAD dysfunction under physiological and ER stress conditions in the context of a multicellular organism. Here we report the first individual and combined characterization and functional interplay of EDEM proteins in Caenorhabditis elegans using single, double, and triple mutant combinations. We found that EDEM-2 has a major role in the clearance of misfolded proteins from ER under physiological conditions, whereas EDEM-1 and EDEM-3 roles become prominent under acute ER stress. In contrast to SEL-1 loss, the loss of EDEMs in an intact organism induces only a modest ER stress under physiological conditions. In addition, chronic impairment of EDEM functioning attenuated both XBP-1 activation and up-regulation of the stress chaperone GRP78/BiP, in response to acute ER stress. We also show that pre-conditioning to EDEM loss in acute ER stress restores ER homeostasis and promotes survival by activating ER hormesis. We propose a novel role for EDEM in fine-tuning the ER stress responsiveness that affects ER homeostasis and survival.

Machine Learning Analysis of Longevity-Associated Gene Expression Landscapes in Mammals.

One of the important questions in aging research is how differences in transcriptomics are associated with the longevity of various species. Unfortunately, at the level of individual genes, the links between expression in different organs and maximum lifespan (MLS) are yet to be fully understood. Analyses are complicated further by the fact that MLS is highly associated with other confounding factors (metabolic rate, gestation period, body mass, etc.) and that linear models may be limiting. Using gene expression from 41 mammalian species, across five organs, we constructed gene-centric regression models associating gene expression with MLS and other species traits. Additionally, we used SHapley Additive exPlanations and Bayesian networks to investigate the non-linear nature of the interrelations between the genes predicted to be determinants of species MLS. Our results revealed that expression patterns correlate with MLS, some across organs, and others in an organ-specific manner. The combination of methods employed revealed gene signatures formed by only a few genes that are highly predictive towards MLS, which could be used to identify novel longevity regulator candidates in mammals.

MetaboAge DB: a repository of known ageing-related changes in the human metabolome.

Accumulating metabolomics data is starting to become extremely useful in understanding the ageing process, by providing a snapshot into the metabolic state of tissues and organs, at different ages. Molecular studies of such metabolic variations during "normal" ageing can hence guide lifestyle changes and/or medical interventions aimed at improving healthspan and perhaps even lifespan. In this work, we present MetaboAge, a freely accessible database which hosts ageing-related metabolite changes, occurring in healthy individuals. Data is automatically filtered and then manually curated from scientific articles reporting statistically significant associations of human metabolite variations or correlations with ageing. Up to date, MetaboAge contains 408 metabolites annotated with their biological and chemical information, and more than 1515 ageing-related variations, graphically represented on the website grouped by validation methods, sex and age-groups. The MetaboAge database aims to continually structure the expanding information from the field of metabolomics in relation to ageing, thus making it more accessible for further research in gerontology.

Human Ageing Genomic Resources: new and updated databases.

In spite of a growing body of research and data, human ageing remains a poorly understood process. Over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), a collection of databases and tools for studying the biology and genetics of ageing. Here, we present HAGR's main functionalities, highlighting new additions and improvements. HAGR consists of six core databases: (i) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; (ii) the AnAge database of animal ageing and longevity, featuring >4000 species; (iii) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; (iv) the LongevityMap database of human genetic association studies of longevity with >500 entries; (v) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; (vi) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts and regularly updated to ensure a high quality data. Cross-links across our databases and to external resources help researchers locate and integrate relevant information. HAGR is freely available online (http://genomics.senescence.info/).

Systematic analysis of the gerontome reveals links between aging and age-related diseases.

In model organisms, over 2,000 genes have been shown to modulate aging, the collection of which we call the 'gerontome'. Although some individual aging-related genes have been the subject of intense scrutiny, their analysis as a whole has been limited. In particular, the genetic interaction of aging and age-related pathologies remain a subject of debate. In this work, we perform a systematic analysis of the gerontome across species, including human aging-related genes. First, by classifying aging-related genes as pro- or anti-longevity, we define distinct pathways and genes that modulate aging in different ways. Our subsequent comparison of aging-related genes with age-related disease genes reveals species-specific effects with strong overlaps between aging and age-related diseases in mice, yet surprisingly few overlaps in lower model organisms. We discover that genetic links between aging and age-related diseases are due to a small fraction of aging-related genes which also tend to have a high network connectivity. Other insights from our systematic analysis include assessing how using datasets with genes more or less studied than average may result in biases, showing that age-related disease genes have faster molecular evolution rates and predicting new aging-related drugs based on drug-gene interaction data. Overall, this is the largest systems-level analysis of the genetics of aging to date and the first to discriminate anti- and pro-longevity genes, revealing new insights on aging-related genes as a whole and their interactions with age-related diseases.

MitoAge: a database for comparative analysis of mitochondrial DNA, with a special focus on animal longevity.

Mitochondria are the only organelles in the animal cells that have their own genome. Due to a key role in energy production, generation of damaging factors (ROS, heat), and apoptosis, mitochondria and mtDNA in particular have long been considered one of the major players in the mechanisms of aging, longevity and age-related diseases. The rapidly increasing number of species with fully sequenced mtDNA, together with accumulated data on longevity records, provides a new fascinating basis for comparative analysis of the links between mtDNA features and animal longevity. To facilitate such analyses and to support the scientific community in carrying these out, we developed the MitoAge database containing calculated mtDNA compositional features of the entire mitochondrial genome, mtDNA coding (tRNA, rRNA, protein-coding genes) and non-coding (D-loop) regions, and codon usage/amino acids frequency for each protein-coding gene. MitoAge includes 922 species with fully sequenced mtDNA and maximum lifespan records. The database is available through the MitoAge website (www.mitoage.org or www.mitoage.info), which provides the necessary tools for searching, browsing, comparing and downloading the data sets of interest for selected taxonomic groups across the Kingdom Animalia. The MitoAge website assists in statistical analysis of different features of the mtDNA and their correlative links to longevity.

The Digital Ageing Atlas: integrating the diversity of age-related changes into a unified resource.

Multiple studies characterizing the human ageing phenotype have been conducted for decades. However, there is no centralized resource in which data on multiple age-related changes are collated. Currently, researchers must consult several sources, including primary publications, in order to obtain age-related data at various levels. To address this and facilitate integrative, system-level studies of ageing we developed the Digital Ageing Atlas (DAA). The DAA is a one-stop collection of human age-related data covering different biological levels (molecular, cellular, physiological, psychological and pathological) that is freely available online (http://ageing-map.org/). Each of the >3000 age-related changes is associated with a specific tissue and has its own page displaying a variety of information, including at least one reference. Age-related changes can also be linked to each other in hierarchical trees to represent different types of relationships. In addition, we developed an intuitive and user-friendly interface that allows searching, browsing and retrieving information in an integrated and interactive fashion. Overall, the DAA offers a new approach to systemizing ageing resources, providing a manually-curated and readily accessible source of age-related changes.

LongevityMap: a database of human genetic variants associated with longevity.

Understanding the genetic basis of human longevity remains a challenge but could lead to life-extending interventions and better treatments for age-related diseases. Toward this end we developed the LongevityMap (http://genomics.senescence.info/longevity/), the first database of genes, loci, and variants studied in the context of human longevity and healthy ageing. We describe here its content and interface, and discuss how it can help to unravel the genetics of human longevity.

Human Ageing Genomic Resources: integrated databases and tools for the biology and genetics of ageing.

The Human Ageing Genomic Resources (HAGR, http://genomics.senescence.info) is a freely available online collection of research databases and tools for the biology and genetics of ageing. HAGR features now several databases with high-quality manually curated data: (i) GenAge, a database of genes associated with ageing in humans and model organisms; (ii) AnAge, an extensive collection of longevity records and complementary traits for >4000 vertebrate species; and (iii) GenDR, a newly incorporated database, containing both gene mutations that interfere with dietary restriction-mediated lifespan extension and consistent gene expression changes induced by dietary restriction. Since its creation about 10 years ago, major efforts have been undertaken to maintain the quality of data in HAGR, while further continuing to develop, improve and extend it. This article briefly describes the content of HAGR and details the major updates since its previous publications, in terms of both structure and content. The completely redesigned interface, more intuitive and more integrative of HAGR resources, is also presented. Altogether, we hope that through its improvements, the current version of HAGR will continue to provide users with the most comprehensive and accessible resources available today in the field of biogerontology.

scDiffCom: a tool for differential analysis of cell-cell interactions provides a mouse atlas of aging changes in intercellular communication.

Dysregulation of intercellular communication is a hallmark of aging. To better quantify and explore changes in intercellular communication, we present scDiffCom and scAgeCom. scDiffCom is an R package, relying on approximately 5,000 curated ligand-receptor interactions, that performs differential intercellular communication analysis between two conditions from single-cell transcriptomics data. Built upon scDiffCom, scAgeCom is an atlas of age-related cell-cell communication changes covering 23 mouse tissues from 58 single-cell RNA sequencing datasets from Tabula Muris Senis and the Calico murine aging cell atlas. It offers a comprehensive resource of tissue-specific and sex-specific aging dysregulations and highlights age-related intercellular communication changes widespread across the whole body, such as the upregulation of immune system processes and inflammation, the downregulation of developmental processes, angiogenesis and extracellular matrix organization and the deregulation of lipid metabolism. Our analysis emphasizes the relevance of the specific ligands, receptors and cell types regulating these processes. The atlas is available online ( https://scagecom.org ).

Is rate of skin wound healing associated with aging or longevity phenotype?

Wound healing (WH) is a fundamental biological process. Is it associated with a longevity or aging phenotype? In an attempt to answer this question, we compared the established mouse models with genetically modified life span and also an altered rate of WH in the skin. Our analysis showed that the rate of skin WH in advanced ages (but not in the young animals) may be used as a marker for biological age, i.e., to be indicative of the longevity or aging phenotype. The ability to preserve the rate of skin WH up to an old age appears to be associated with a longevity phenotype, whereas a decline in WH-with an aging phenotype. In the young, this relationship is more complex and might even be inversed. While the aging process is likely to cause wounds to heal slowly, an altered WH rate in younger animals could indicate a different cellular proliferation and/or migration capacity, which is likely to affect other major processes such as the onset and progression of cancer. As a point for future studies on WH and longevity, using only young animals might yield confusing or misleading results, and therefore including older animals in the analysis is encouraged.

Knock-down of odr-3 and ife-2 additively extends lifespan and healthspan in C. elegans.

Genetic manipulations can ameliorate the aging process and extend the lifespan of model organisms. The aim of this research was to identify novel genetic interventions that promote both lifespan and healthspan, by combining the effects of multiple longevity-associated gene inactivations in C. elegans. For this, the individual and combined effects of the odr-3 mutation and of ife-2 and cku-70 knock-downs were studied, both in the wild type and daf-16 mutant backgrounds. We found that besides increasing the lifespan of wild type animals, the knock-down of ife-2 (starting at L4) also extends the lifespan and healthspan of long-lived odr-3 mutants. In the daf-16 background, ife-2 and odr-3 impairment exert opposing effects individually, while the daf-16; odr-3; ife-2 deficient animals show a similar lifespan and healthspan as daf-16, suggesting that the odr-3 and ife-2 effector outcomes converge downstream of DAF-16. By contrast, cku-70 knock-down did not extend the lifespan of single or double odr-3; ife-2 inactivated animals, and was slightly deleterious to healthspan. In conclusion, we report that impairment of odr-3 and ife-2 increases lifespan and healthspan in an additive and synergistic manner, respectively, and that this result is not improved by further knocking-down cku-70.

Small molecules for cell reprogramming: a systems biology analysis.

If somatic stem cells would be able to maintain their regenerative capacity over time, this might, to a great extent, resolve rejuvenation issues. Unfortunately, the pool of somatic stem cells is limited, and they undergo cell aging with a consequent loss of functionality. During the last decade, low molecular weight compounds that are able to induce or enhance cell reprogramming have been reported. They were named "Small Molecules" (SMs) and might present definite advantages compared to the exogenous introduction of stemness-related transcription factors (e.g. Yamanaka's factors). Here, we undertook a systemic analysis of SMs and their potential gene targets. Data mining and curation lead to the identification of 92 SMs. The SM targets fall into three major functional categories: epigenetics, cell signaling, and metabolic "switchers". All these categories appear to be required in each SM cocktail to induce cell reprogramming. Remarkably, many enriched pathways of SM targets are related to aging, longevity, and age-related diseases, thus connecting them with cell reprogramming. The network analysis indicates that SM targets are highly interconnected and form protein-protein networks of a scale-free topology. The extremely high contribution of hubs to network connectivity suggests that (i) cell reprogramming may require SM targets to act cooperatively, and (ii) their network organization might ensure robustness by resistance to random failures. All in all, further investigation of SMs and their relationship with longevity regulators will be helpful for developing optimal SM cocktails for cell reprogramming with a perspective for rejuvenation and life span extension.

Systems biology analysis of lung fibrosis-related genes in the bleomycin mouse model.

Tissue fibrosis is a major driver of pathology in aging and is involved in numerous age-related diseases. The lungs are particularly susceptible to fibrotic pathology which is currently difficult to treat. The mouse bleomycin-induced fibrosis model was developed to investigate lung fibrosis and widely used over the years. However, a systematic analysis of the accumulated results has not been performed. We undertook a comprehensive data mining and subsequent manual curation, resulting in a collection of 213 genes (available at the TiRe database, www.tiredb.org ), which when manipulated had a clear impact on bleomycin-induced lung fibrosis. Our meta-analysis highlights the age component in pulmonary fibrosis and strong links of related genes with longevity. The results support the validity of the bleomycin model to human pathology and suggest the importance of a multi-target therapeutic strategy for pulmonary fibrosis treatment.

The NetAge database: a compendium of networks for longevity, age-related diseases and associated processes.

Hundreds of genes and miRNAs have been identified as being involved in the determination of longevity, aging patterns and in the development of age-related diseases (ARDs). The interplay between these genes as well as the role of miRNAs in the context of protein-protein interaction networks has as yet been poorly addressed. This work was undertaken in order to integrate the data accumulated in the field, from a network-based perspective. The results are organized in the NetAge database-an online database and network analysis tools for biogerontological research ( http://www.netage-project.org ). The NetAge database contains gene sets and miRNA-regulated PPI networks for longevity, ARDs and aging-associated processes, and also common signatures (overlapping networks). The database is available through the NetAge website, which provides the necessary bioinformatics tools for searching and browsing the networks, as well as showing network info and statistics. By making these resources available online, we hope to provide the scientific community with a new, network-oriented platform for biogerontological research, and encourage greater participation in the systems biology of aging.

LRRpredictor-A New LRR Motif Detection Method for Irregular Motifs of Plant NLR Proteins Using an Ensemble of Classifiers.

Leucine-rich-repeats (LRRs) belong to an archaic procaryal protein architecture that is widely involved in protein-protein interactions. In eukaryotes, LRR domains developed into key recognition modules in many innate immune receptor classes. Due to the high sequence variability imposed by recognition specificity, precise repeat delineation is often difficult especially in plant NOD-like Receptors (NLRs) notorious for showing far larger irregularities. To address this problem, we introduce here LRRpredictor, a method based on an ensemble of estimators designed to better identify LRR motifs in general but particularly adapted for handling more irregular LRR environments, thus allowing to compensate for the scarcity of structural data on NLR proteins. The extrapolation capacity tested on a set of annotated LRR domains from six immune receptor classes shows the ability of LRRpredictor to recover all previously defined specific motif consensuses and to extend the LRR motif coverage over annotated LRR domains. This analysis confirms the increased variability of LRR motifs in plant and vertebrate NLRs when compared to extracellular receptors, consistent with previous studies. Hence, LRRpredictor is able to provide novel insights into the diversification of LRR domains and a robust support for structure-informed analyses of LRRs in immune receptor functioning.

SynergyAge, a curated database for synergistic and antagonistic interactions of longevity-associated genes.

Interventional studies on genetic modulators of longevity have significantly changed gerontology. While available lifespan data are continually accumulating, further understanding of the aging process is still limited by the poor understanding of epistasis and of the non-linear interactions between multiple longevity-associated genes. Unfortunately, based on observations so far, there is no simple method to predict the cumulative impact of genes on lifespan. As a step towards applying predictive methods, but also to provide information for a guided design of epistasis lifespan experiments, we developed SynergyAge - a database containing genetic and lifespan data for animal models obtained through multiple longevity-modulating interventions. The studies included in SynergyAge focus on the lifespan of animal strains which are modified by at least two genetic interventions, with single gene mutants included as reference. SynergyAge, which is publicly available at www.synergyage.info , provides an easy to use web-platform for browsing, searching and filtering through the data, as well as a network-based interactive module for visualization and analysis.

Gray whale transcriptome reveals longevity adaptations associated with DNA repair and ubiquitination.

One important question in aging research is how differences in genomics and transcriptomics determine the maximum lifespan in various species. Despite recent progress, much is still unclear on the topic, partly due to the lack of samples in nonmodel organisms and due to challenges in direct comparisons of transcriptomes from different species. The novel ranking-based method that we employ here is used to analyze gene expression in the gray whale and compare its de novo assembled transcriptome with that of other long- and short-lived mammals. Gray whales are among the top 1% longest-lived mammals. Despite the extreme environment, or maybe due to a remarkable adaptation to its habitat (intermittent hypoxia, Arctic water, and high pressure), gray whales reach at least the age of 77 years. In this work, we show that long-lived mammals share common gene expression patterns between themselves, including high expression of DNA maintenance and repair, ubiquitination, apoptosis, and immune responses. Additionally, the level of expression for gray whale orthologs of pro- and anti-longevity genes found in model organisms is in support of their alleged role and direction in lifespan determination. Remarkably, among highly expressed pro-longevity genes many are stress-related, reflecting an adaptation to extreme environmental conditions. The conducted analysis suggests that the gray whale potentially possesses high resistance to cancer and stress, at least in part ensuring its longevity. This new transcriptome assembly also provides important resources to support the efforts of maintaining the endangered population of gray whales.

A multidimensional systems biology analysis of cellular senescence in aging and disease.

BACKGROUND: Cellular senescence, a permanent state of replicative arrest in otherwise proliferating cells, is a hallmark of aging and has been linked to aging-related diseases. Many genes play a role in cellular senescence, yet a comprehensive understanding of its pathways is still lacking. RESULTS: We develop CellAge (http://genomics.senescence.info/cells), a manually curated database of 279 human genes driving cellular senescence, and perform various integrative analyses. Genes inducing cellular senescence tend to be overexpressed with age in human tissues and are significantly overrepresented in anti-longevity and tumor-suppressor genes, while genes inhibiting cellular senescence overlap with pro-longevity and oncogenes. Furthermore, cellular senescence genes are strongly conserved in mammals but not in invertebrates. We also build cellular senescence protein-protein interaction and co-expression networks. Clusters in the networks are enriched for cell cycle and immunological processes. Network topological parameters also reveal novel potential cellular senescence regulators. Using siRNAs, we observe that all 26 candidates tested induce at least one marker of senescence with 13 genes (C9orf40, CDC25A, CDCA4, CKAP2, GTF3C4, HAUS4, IMMT, MCM7, MTHFD2, MYBL2, NEK2, NIPA2, and TCEB3) decreasing cell number, activating p16/p21, and undergoing morphological changes that resemble cellular senescence. CONCLUSIONS: Overall, our work provides a benchmark resource for researchers to study cellular senescence, and our systems biology analyses reveal new insights and gene regulators of cellular senescence.

Common gene signature of cancer and longevity.

An association between aging/longevity and cancer has long been suggested, yet the evolutionary and molecular links between these complicated traits remain elusive. Here, we analyze the relationship between longevity- and cancer-associated genes/proteins (LAGs/LAPs and CAGs/CAPs, respectively). Specifically, we address the following questions: (1) to what extent the CAGs and LAGs are evolutionary conserved and how they (or their orthologs) are related to each other in diverse species? (2) Could they act in cooperative manner at a protein level via protein-protein interactions (PPIs) and, if so, by forming a PPI network? We found that (i) the common genes (both LAGs and CAGs) show the same remarkable trend from yeast to humans: tumor suppressors are associated with lifespan extension, whereas the oncogenes are associated with reduced lifespan; (ii) LAPs and CAPs have a significantly higher average connectivity than other proteins in the human interactome; and (iii) LAPs and CAPs may act in cooperative manner via numerous direct and indirect PPIs between themselves and eventually by forming a PPI network. Altogether, the results of this study provide strong evidence for the existence of evolutionary and molecular links between longevity and cancer.