Real age prediction from the transcriptome with RAPToR

CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs-∼58% of the total-from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.

Cell Type-Agnostic Transcriptomic Signatures Enable Uniform Comparisons of Neurodevelopment

Single-cell transcriptomics has revolutionized our understanding of neurodevelopmental cell identities, yet, predicting a cell type's developmental state from its transcriptome remains a challenge. We perform a meta-analysis of developing human brain datasets comprising over 2.8 million cells, identifying both tissue-level and cell-autonomous predictors of developmental age. While tissue composition predicts age within individual studies, it fails to generalize, whereas specific cell type proportions reliably track developmental time across datasets. Training regularized regression models to infer cell-autonomous maturation, we find that a cell type-agnostic model achieves the highest accuracy (error = 2.6 weeks), robustly capturing developmental dynamics across diverse cell types and datasets. This model generalizes to human neural organoids, accurately predicting normal developmental trajectories (R = 0.91) and disease-induced shifts in vitro. Furthermore, it extends to the developing mouse brain, revealing an accelerated developmental tempo relative to humans. Our work provides a unified framework for comparing neurodevelopment across contexts, model systems, and species.

Metformin decelerates aging clock in male monkeys

In a rigorous 40-month study, we evaluated the geroprotective effects of metformin on adult male cynomolgus monkeys, addressing a gap in primate aging research. The study encompassed a comprehensive suite of physiological, imaging, histological, and molecular evaluations, substantiating metformin's influence on delaying age-related phenotypes at the organismal level. Specifically, we leveraged pan-tissue transcriptomics, DNA methylomics, plasma proteomics, and metabolomics to develop innovative monkey aging clocks and applied these to gauge metformin's effects on aging. The results highlighted a significant slowing of aging indicators, notably a roughly 6-year regression in brain aging. Metformin exerts a substantial neuroprotective effect, preserving brain structure and enhancing cognitive ability. The geroprotective effects on primate neurons were partially mediated by the activation of Nrf2, a transcription factor with anti-oxidative capabilities. Our research pioneers the systemic reduction of multi-dimensional biological age in primates through metformin, paving the way for advancing pharmaceutical strategies against human aging.

Stabilizing selection and adaptation shape cis and trans gene expression variation in C. elegans

An outstanding question in the evolution of gene expression is the relative influence of neutral processes versus natural selection, including adaptive change driven by directional selection as well as stabilizing selection, which may include compensatory dynamics. These forces shape patterns of gene expression variation within and between species, including the regulatory mechanisms governing expression in cis and trans. In this study, we interrogate intraspecific gene expression variation among seven wild C. elegans strains, with varying degrees of genomic divergence from the reference strain N2, leveraging this system's unique advantages to comprehensively evaluate gene expression evolution. By capturing allele-specific and between-strain changes in expression, we characterize the regulatory architecture and inheritance mode of gene expression variation within C. elegans and assess their relationship to nucleotide diversity, genome evolutionary history, gene essentiality, and other biological factors. We conclude that stabilizing selection is a dominant influence in maintaining expression phenotypes within the species, and the discovery that genes with higher overall expression tend to exhibit fewer expression differences supports this conclusion, as do widespread instances of cis differences compensated in trans. Moreover, analyses of human expression data replicate our finding that higher expression genes have less variable expression. We also observe evidence for directional selection driving expression divergence, and that expression divergence accelerates with increasing genomic divergence. To provide community access to the data from this first analysis of allele-specific expression in C. elegans, we introduce an interactive web application, where users can submit gene-specific queries to view expression, regulatory pattern, inheritance mode, and other information: https://wildworm.biosci.gatech.edu/ase/.

Retro-age: A unique epigenetic biomarker of aging captured by DNA methylation states of retroelements

Reactivation of retroelements in the human genome has been linked to aging. However, whether the epigenetic state of specific retroelements can predict chronological age remains unknown. We provide evidence that locus-specific retroelement DNA methylation can be used to create retroelement-based epigenetic clocks that accurately measure chronological age in the immune system, across human tissues, and pan-mammalian species. We also developed a highly accurate retroelement epigenetic clock compatible with EPICv.2.0 data that was constructed from CpGs that did not overlap with existing first- and second-generation epigenetic clocks, suggesting a unique signal for epigenetic clocks not previously captured. We found retroelement-based epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, and responsive to antiretroviral therapy. Our findings highlight the utility of retroelement-based biomarkers of aging and support a renewed emphasis on the role of retroelements in geroscience.

The Caenorhabditis elegans cuticle and precuticle: a model for studying dynamic apical extracellular matrices in vivo

Apical extracellular matrices (aECMs) coat the exposed surfaces of animal bodies to shape tissues, influence social interactions, and protect against pathogens and other environmental challenges. In the nematode Caenorhabditis elegans, collagenous cuticle and zona pellucida protein-rich precuticle aECMs alternately coat external epithelia across the molt cycle and play many important roles in the worm's development, behavior, and physiology. Both these types of aECMs contain many matrix proteins related to those in vertebrates, as well as some that are nematode-specific. Extensive differences observed among tissues and life stages demonstrate that aECMs are a major feature of epithelial cell identity. In addition to forming discrete layers, some cuticle components assemble into complex substructures such as ridges, furrows, and nanoscale pillars. The epidermis and cuticle are mechanically linked, allowing the epidermis to sense cuticle damage and induce protective innate immune and stress responses. The C. elegans model, with its optical transparency, facilitates the study of aECM cell biology and structure/function relationships and all the myriad ways by which aECM can influence an organism.

Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony

In aging, physiologic networks decline in function at rates that differ between individuals, producing a wide distribution of lifespan. Though 70% of human lifespan variance remains unexplained by heritable factors, little is known about the intrinsic sources of physiologic heterogeneity in aging. To understand how complex physiologic networks generate lifespan variation, new methods are needed. Here, we present Asynch-seq, an approach that uses gene-expression heterogeneity within isogenic populations to study the processes generating lifespan variation. By collecting thousands of single-individual transcriptomes, we capture the Caenorhabditis elegans "pan-transcriptome"-a highly resolved atlas of non-genetic variation. We use our atlas to guide a large-scale perturbation screen that identifies the decoupling of total mRNA content between germline and soma as the largest source of physiologic heterogeneity in aging, driven by pleiotropic genes whose knockdown dramatically reduces lifespan variance. Our work demonstrates how systematic mapping of physiologic heterogeneity can be applied to reduce inter-individual disparities in aging.

Conserved and specific gene expression patterns in the embryonic development of tardigrades

Tardigrades, commonly known as water bears, are enigmatic organisms characterized by their remarkable resilience to extreme environments despite their simple and compact body structure. To date, there is still much to understand about their evolutionary and developmental features contributing to their special body plan and abilities. This research provides preliminary insights on the conserved and specific gene expression patterns during embryonic development of water bears, focusing on the species Hypsibius exemplaris. The developmental dynamic expression analysis of the genes with various evolutionary age grades indicated that the mid-conserved stage of H. exemplaris corresponds to the period of ganglia and midgut development, with the late embryonic stage showing a transition from non-conserved to conserved state. Additionally, a comparison with Drosophila melanogaster highlighted the absence of certain pathway nodes in development-related pathways, such as Maml and Hairless, which are respectively the transcriptional co-activator and co-repressor of NOTCH regulated genes. We also employed Weighted Gene Co-expression Network Analysis (WGCNA) to investigate the expression patterns of tardigrade-specific genes during embryo development. Our findings indicated that the module containing the highest proportion of tardigrade-specific genes (TSGs) exhibits high expression levels before the mid-conserved stage, potentially playing a role in glutathione and lipid metabolism. These functions may be associated to the ecdysone synthesis and storage cell formation, which is unique to tardigrades.

The effect of developmental variation on expression QTLs in a multi parental Caenorhabditis elegans population

Regulation of gene expression plays a crucial role in developmental processes and adaptation to changing environments. expression quantitative trait locus (eQTL) mapping is a technique used to study the genetic regulation of gene expression using the transcriptomes of recombinant inbred lines (RILs). Typically, the age of the inbred lines at the time of RNA sampling is carefully controlled. This is necessary because the developmental process causes changes in gene expression, complicating the interpretation of eQTL mapping experiments. However, due to genetics and variation in ambient micro-environments, organisms can differ in their "developmental age," even if they are of the same chronological age. As a result, eQTL patterns are affected by developmental variation in gene expression. The model organism Caenorhabditis elegans is particularly suited for studying the effect of developmental variation on eQTL mapping patterns. In a span of days, C. elegans transitions from embryo through 4 larval stages to adult while undergoing massive changes to its transcriptome. Here, we use C. elegans to investigate the effect of developmental age variation on eQTL patterns and present a normalization procedure. We used dynamical eQTL mapping, which includes the developmental age as a cofactor, to separate the variation in development from genotypic variation and explain variation in gene expression levels. We compare classical single marker eQTL mapping and dynamical eQTL mapping using RNA-seq data of ∼200 multi-parental RILs of C. elegans. The results show that (1) many eQTLs are caused by developmental variation, (2) most trans-bands are developmental QTLs, and (3) dynamical eQTL mapping detects additional eQTLs not found with classical eQTL mapping. We recommend that correction for variation in developmental age should be strongly considered in eQTL mapping studies given the large impact of processes like development on the transcriptome.

Retroelement-Age Clocks: Epigenetic Age Captured by Human Endogenous Retrovirus and LINE-1 DNA methylation states

Human endogenous retroviruses (HERVs), the remnants of ancient viral infections embedded within the human genome, and long interspersed nuclear elements 1 (LINE-1), a class of autonomous retrotransposons, are silenced by host epigenetic mechanisms including DNA methylation. The resurrection of particular retroelements has been linked to biological aging. Whether the DNA methylation states of locus specific HERVs and LINEs can be used as a biomarker of chronological age in humans remains unclear. We show that highly predictive epigenetic clocks of chronological age can be constructed from retroelement DNA methylation states in the immune system, across human tissues, and pan-mammalian species. We found retroelement epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, responsive to antiretroviral therapy, and accurate in estimating long-term culture ages of human brain organoids. Our findings support the hypothesis of epigenetic dysregulation of retroelements as a potential contributor to the biological hallmarks of aging.

Histone methyltransferase activity affects metabolism in human cells independently of transcriptional regulation

The N-terminal tails of eukaryotic histones are frequently posttranslationally modified. The role of these modifications in transcriptional regulation is well-documented. However, the extent to which the enzymatic processes of histone posttranslational modification might affect metabolic regulation is less clear. Here, we investigated how histone methylation might affect metabolism using metabolomics, proteomics, and RNA-seq data from cancer cell lines, primary tumour samples and healthy tissue samples. In cancer, the expression of histone methyltransferases (HMTs) was inversely correlated to the activity of NNMT, an enzyme previously characterised as a methyl sink that disposes of excess methyl groups carried by the universal methyl donor S-adenosyl methionine (SAM or AdoMet). In healthy tissues, histone methylation was inversely correlated to the levels of an alternative methyl sink, PEMT. These associations affected the levels of multiple histone marks on chromatin genome-wide but had no detectable impact on transcriptional regulation. We show that HMTs with a variety of different associations to transcription are co-regulated by the Retinoblastoma (Rb) tumour suppressor in human cells. Rb-mutant cancers show increased total HMT activity and down-regulation of NNMT. Together, our results suggest that the total activity of HMTs affects SAM metabolism, independent of transcriptional regulation.

Gentamicin resistance to Escherichia coli related to fatty acid metabolism based on transcriptome analysis

Antibiotic overuse and misuse have promoted the emergence and spread of antibiotic-resistant bacteria. Increasing bacterial resistance to antibiotics is a major healthcare problem, necessitating elucidation of antibiotic resistance mechanisms. In this study, we explored the mechanism of gentamicin resistance by comparing the transcriptomes of antibiotic-sensitive and -resistant Escherichia coli. A total of 410 differentially expressed genes were identified, of which 233 (56.83%) were up-regulated and 177 (43.17%) were down-regulated in the resistant strain compared with the sensitive strain. Gene Ontology (GO) analysis classifies differential gene expression into three main categories: biological processes, cellular components, and molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the up-regulated genes were enriched in eight metabolic pathways, including fatty acid metabolism, which suggests that fatty acid metabolism may be involved in the development of gentamicin resistance in E. coli. This was demonstrated by measuring the acetyl-CoA carboxylase activity, plays a fundamental role in fatty acid metabolism, was increased in gentamicin-resistant E. coli. Treatment of fatty acid synthesis inhibitor, triclosan, promoted gentamicin-mediated killing efficacy to antibiotic-resistant bacteria. We also found that exogenous addition of oleic acid, which involved in fatty acid metabolism, reduced E. coli sensitivity to gentamicin. Overall, our results provide insight into the molecular mechanism of gentamicin resistance development in E. coli.

Beyond the reference: gene expression variation and transcriptional response to RNA interference in Caenorhabditis elegans

Though natural systems harbor genetic and phenotypic variation, research in model organisms is often restricted to a reference strain. Focusing on a reference strain yields a great depth of knowledge but potentially at the cost of breadth of understanding. Furthermore, tools developed in the reference context may introduce bias when applied to other strains, posing challenges to defining the scope of variation within model systems. Here, we evaluate how genetic differences among 5 wild Caenorhabditis elegans strains affect gene expression and its quantification, in general and after induction of the RNA interference (RNAi) response. Across strains, 34% of genes were differentially expressed in the control condition, including 411 genes that were not expressed at all in at least 1 strain; 49 of these were unexpressed in reference strain N2. Reference genome mapping bias caused limited concern: despite hyperdiverse hotspots throughout the genome, 92% of variably expressed genes were robust to mapping issues. The transcriptional response to RNAi was highly strain- and target-gene-specific and did not correlate with RNAi efficiency, as the 2 RNAi-insensitive strains showed more differentially expressed genes following RNAi treatment than the RNAi-sensitive reference strain. We conclude that gene expression, generally and in response to RNAi, differs across C. elegans strains such that the choice of strain may meaningfully influence scientific inferences. Finally, we introduce a resource for querying gene expression variation in this dataset at https://wildworm.biosci.gatech.edu/rnai/.

Mitochondrial aconitase suppresses immunity by modulating oxaloacetate and the mitochondrial unfolded protein response

Accumulating evidence indicates that mitochondria play crucial roles in immunity. However, the role of the mitochondrial Krebs cycle in immunity remains largely unknown, in particular at the organism level. Here we show that mitochondrial aconitase, ACO-2, a Krebs cycle enzyme that catalyzes the conversion of citrate to isocitrate, inhibits immunity against pathogenic bacteria in C. elegans. We find that the genetic inhibition of aco-2 decreases the level of oxaloacetate. This increases the mitochondrial unfolded protein response, subsequently upregulating the transcription factor ATFS-1, which contributes to enhanced immunity against pathogenic bacteria. We show that the genetic inhibition of mammalian ACO2 increases immunity against pathogenic bacteria by modulating the mitochondrial unfolded protein response and oxaloacetate levels in cultured cells. Because mitochondrial aconitase is highly conserved across phyla, a therapeutic strategy targeting ACO2 may eventually help properly control immunity in humans.

Biomarkers of aging

Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.

Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses

Systems vaccinology has defined molecular signatures and mechanisms of immunity to vaccination. However, comparative analysis of immunity to different vaccines is lacking. We integrated transcriptional data of over 3,000 samples, from 820 adults across 28 studies of 13 vaccines and analyzed vaccination-induced signatures of antibody responses. Most vaccines induced signatures of innate immunity and plasmablasts at days 1 and 7, respectively, after vaccination. However, the yellow fever vaccine induced an early transient signature of T and B cell activation at day 1, followed by delayed antiviral/interferon and plasmablast signatures that peaked at days 7 and 14-21, respectively. Thus, there was no evidence for a 'universal signature' that predicted antibody response to all vaccines. However, accounting for the asynchronous nature of responses, we defined a time-adjusted signature that predicted antibody responses across vaccines. These results provide a transcriptional atlas of immunity to vaccination and define a common, time-adjusted signature of antibody responses.