Age‐dependent changes and biomarkers of aging in Caenorhabditis elegans

Caenorhabditis elegans is an exceptionally valuable model for aging research because of many advantages, including its genetic tractability, short lifespan, and clear age‐dependent physiological changes. Aged C. elegans display a decline in their anatomical and functional features, including tissue integrity, motility, learning and memory, and immunity. Caenorhabditis elegans also exhibit many age‐associated changes in the expression of microRNAs and stress‐responsive genes and in RNA and protein quality control systems. Many of these age‐associated changes provide information on the health of the animals and serve as valuable biomarkers for aging research. Here, we review the age‐dependent changes in C. elegans and their utility as aging biomarkers indicative of the physiological status of aging.     

Conservation of physiological dysregulation signatures of aging across primates

Two major goals in the current biology of aging are to identify general mechanisms underlying the aging process and to explain species differences in aging. Recent research in humans suggests that one important driver of aging is dysregulation, the progressive loss of homeostasis in complex biological networks. Yet, there is a lack of comparative data for this hypothesis, and we do not know whether dysregulation is widely associated with aging or how well signals of homeostasis are conserved. To address this knowledge gap, we use unusually detailed longitudinal biomarker data from 10 species of nonhuman primates housed in research centers and data from two human populations to test the hypotheses that (a) greater dysregulation is associated with aging across primates and (b) physiological states characterizing homeostasis are conserved across primates to degrees associated with phylogenetic proximity. To evaluate dysregulation, we employed a multivariate distance measure, calculated from sets of biomarkers, that is associated with aging and mortality in human populations. Dysregulation scores positively correlated with age and risk of mortality in most nonhuman primates studied, and signals of homeostatic state were significantly conserved across species, declining with phylogenetic distance. Our study provides the first broad demonstration of physiological dysregulation associated with aging and mortality risk in multiple nonhuman primates. Our results also imply that emergent signals of homeostasis are evolutionarily conserved, although with notable variation among species, and suggest promising directions for future comparative studies on dysregulation and the aging process.     

Circadian regulation in aging: Implications for spaceflight and life on earth

Alterations in the circadian system are characteristic of aging on Earth. With the decline in physiological processes due to aging, several health concerns including vision loss, cardiovascular disorders, cognitive impairments, and muscle mass loss arise in elderly populations. Similar health risks are reported as “red flag” risks among astronauts during and after a long-term Space exploration journey. However, little is known about the common molecular alterations underlying terrestrial aging and space-related aging in astronauts, and controversial conclusions have been recently reported. In light of the regulatory role of the circadian clock in the maintenance of human health, we review here the overlapping role of the circadian clock both on aging on Earth and spaceflight with a focus on the four most affected systems: visual, cardiovascular, central nervous, and musculoskeletal systems. In this review, we briefly introduce the regulatory role of the circadian clock in specific cellular processes followed by alterations in those processes due to aging. We next summarize the known molecular alterations associated with spaceflight, highlighting involved clock-regulated genes in space flown Drosophila, nematodes, small mammals, and astronauts. Finally, we discuss common genes that are altered in terms of their expression due to aging on Earth and spaceflight. Altogether, the data elaborated in this review strengthen our hypothesis regarding the timely need to include circadian dysregulation as an emerging hallmark of aging on Earth and beyond.     

Dynamics of lipids and metabolites during the cell cycle of Chlamydomonas reinhardtii

Metabolites and lipids are the final products of enzymatic processes, distinguishing the different cellular functions and activities of single cells or whole tissues. Understanding these cellular functions within a well‐established model system requires a systemic collection of molecular and physiological information. In the current report, the green alga Chlamydomonas reinhardtii was selected to establish a comprehensive workflow for the detailed multi‐omics analysis of a synchronously growing cell culture system. After implementation and benchmarking of the synchronous cell culture, a two‐phase extraction method was adopted for the analysis of proteins, lipids, metabolites and starch from a single sample aliquot of as little as 10–15 million Chlamydomonas cells. In a proof of concept study, primary metabolites and lipids were sampled throughout the diurnal cell cycle. The results of these time‐resolved measurements showed that single compounds were not only coordinated with each other in different pathways, but that these complex metabolic signatures have the potential to be used as biomarkers of various cellular processes. Taken together, the developed workflow, including the synchronized growth of the photoautotrophic cell culture, in combination with comprehensive extraction methods and detailed metabolic phenotyping has the potential for use in in‐depth analysis of complex cellular processes, providing essential information for the understanding of complex biological systems.     

Potentials of single‐cell biology in identification and validation of disease biomarkers

Single‐cell biology is considered a new approach to identify and validate disease‐specific biomarkers. However, the concern raised by clinicians is how to apply single‐cell measurements for clinical practice, translate the message of single‐cell systems biology into clinical phenotype or explain alterations of single‐cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single‐cell gene sequencing in the identification and development of disease‐specific biomarkers, the definition and significance of single‐cell biology and single‐cell systems biology in the understanding of single‐cell full picture, the development and establishment of whole‐cell models in the validation of targeted biological function and the figure and meaning of single‐molecule imaging in single cell to trace intra‐single‐cell molecule expression, signal, interaction and location. We headline the important role of single‐cell biology in the discovery and development of disease‐specific biomarkers with a special emphasis on understanding single‐cell biological functions, e.g. mechanical phenotypes, single‐cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi‐dimensional, multi‐layer, multi‐crossing and stereoscopic single‐cell biology definitely benefits the discovery and development of disease‐specific biomarkers.     

Seasonality of carotenoid‐based plumage coloration: modelling wavelength‐specific change through spectral reconstruction

Plumage coloration has provided important model systems for research on signal expression. Whilst it had previously been assumed that moulting provided the only mechanism to change plumage coloration, recent studies have shown plumage colours to be seasonally dynamic, with implications both for the quantification of expression and for any signalling role. However, the mechanistic processes underlying such change remain uncertain. Here, we describe within‐moult shifts in expression of a carotenoid‐based colour trait – the yellow ventral plumage of the great tit Parus major – over a nine‐month timespan. We report that plumage chromaticity (‘colour’) – but not achromaticity (‘brightness’) – exhibits a marked seasonal decline, independent of sex, age or body condition, and at a constant rate across twelve environmentally heterogeneous plots within our study site. To gain a greater understanding of the mechanisms underlying this change we employed a spectral reconstruction approach, that generates predicted spectra for any timepoint within the sampling period. By comparing spectra for both early and late in the moult we show that the seasonal decline in chromaticity is driven by both a marked reduction in ultraviolet (UV) reflectance and, to a lesser extent, loss of active carotenoid pigments. Thus, our study shows that seasonal loss of chromaticity in the great tit is driven by altered reflectance primarily in the UV section of the spectrum, a finding made possible by the use of spectral compartmentalisation and multi‐parallel modelling to produce reconstructed spectra. Whether change in plumage coloration influences signal function will depend on the dynamics of the signalling system but it could clearly inflate patterns such as assortative mating and should be considered in studies of colour expression.     

Impact of early personal‐history characteristics on the Pace of Aging: implications for clinical trials of therapies to slow aging and extend healthspan

Therapies to extend healthspan are poised to move from laboratory animal models to human clinical trials. Translation from mouse to human will entail challenges, among them the multifactorial heterogeneity of human aging. To inform clinical trials about this heterogeneity, we report how humans’ pace of biological aging relates to personal‐history characteristics. Because geroprotective therapies must be delivered by midlife to prevent age‐related disease onset, we studied young‐adult members of the Dunedin Study 1972–73 birth cohort (n = 954). Cohort members’ Pace of Aging was measured as coordinated decline in the integrity of multiple organ systems, by quantifying rate of decline across repeated measurements of 18 biomarkers assayed when cohort members were ages 26, 32, and 38 years. The childhood personal‐history characteristics studied were known predictors of age‐related disease and mortality, and were measured prospectively during childhood. Personal‐history characteristics of familial longevity, childhood social class, adverse childhood experiences, and childhood health, intelligence, and self‐control all predicted differences in cohort members’ adulthood Pace of Aging. Accumulation of more personal‐history risks predicted faster Pace of Aging. Because trials of anti‐aging therapies will need to ascertain personal histories retrospectively, we replicated results using cohort members’ retrospective personal‐history reports made in adulthood. Because many trials recruit participants from clinical settings, we replicated results in the cohort subset who had recent health system contact according to electronic medical records. Quick, inexpensive measures of trial participants’ early personal histories can enable clinical trials to study who volunteers for trials, who adheres to treatment, and who responds to anti‐aging therapies.     

Statistical Distance as a Measure of Physiological Dysregulation Is Largely Robust to Variation in Its Biomarker Composition

Physiological dysregulation may underlie aging and many chronic diseases, but is challenging to quantify because of the complexity of the underlying systems. Recently, we described a measure of physiological dysregulation, D_M, that uses statistical distance to assess the degree to which an individual’s biomarker profile is normal versus aberrant. However, the sensitivity of D_M to details of the calculation method has not yet been systematically assessed. In particular, the number and choice of biomarkers and the definition of the reference population (RP, the population used to define a “normal” profile) may be important. Here, we address this question by validating the method on 44 common clinical biomarkers from three longitudinal cohort studies and one cross-sectional survey. D_Ms calculated on different biomarker subsets show that while the signal of physiological dysregulation increases with the number of biomarkers included, the value of additional markers diminishes as more are added and inclusion of 10-15 is generally sufficient. As long as enough markers are included, individual markers have little effect on the final metric, and even D_Ms calculated from mutually exclusive groups of markers correlate with each other at r~0.4-0.5. We also used data subsets to generate thousands of combinations of study populations and RPs to address sensitivity to differences in age range, sex, race, data set, sample size, and their interactions. Results were largely consistent (but not identical) regardless of the choice of RP; however, the signal was generally clearer with a younger and healthier RP, and RPs too different from the study population performed poorly. Accordingly, biomarker and RP choice are not particularly important in most cases, but caution should be used across very different populations or for fine-scale analyses. Biologically, the lack of sensitivity to marker choice and better performance of younger, healthier RPs confirm an interpretation of D_M physiological dysregulation and as an emergent property of a complex system.     

Using measures of single‐cell physiology and physiological state to understand organismic aging

Genetically identical organisms in homogeneous environments have different lifespans and healthspans. These differences are often attributed to stochastic events, such as mutations and ‘epimutations’, changes in DNA methylation and chromatin that change gene function and expression. But work in the last 10 years has revealed differences in lifespan‐ and health‐related phenotypes that are not caused by lasting changes in DNA or identified by modifications to DNA or chromatin. This work has demonstrated persistent differences in single‐cell and whole‐organism physiological states operationally defined by values of reporter gene signals in living cells. While some single‐cell states, for example, responses to oxygen deprivation, were defined previously, others, such as a generally heightened ability to make proteins, were, revealed by direct experiment only recently, and are not well understood. Here, we review technical progress that promises to greatly increase the number of these measurable single‐cell physiological variables and measureable states. We discuss concepts that facilitate use of single‐cell measurements to provide insight into physiological states and state transitions. We assert that researchers will use this information to relate cell level physiological readouts to whole‐organism outcomes, to stratify aging populations into groups based on different physiologies, to define biomarkers predictive of outcomes, and to shed light on the molecular processes that bring about different individual physiologies. For these reasons, quantitative study of single‐cell physiological variables and state transitions should provide a valuable complement to genetic and molecular explanations of how organisms age.     

Biomarkers of aging in Drosophila

Low environmental temperature and dietary restriction (DR) extend lifespan in diverse organisms. In the fruit fly Drosophila, switching flies between temperatures alters the rate at which mortality subsequently increases with age but does not reverse mortality rate. In contrast, DR acts acutely to lower mortality risk; flies switched between control feeding and DR show a rapid reversal of mortality rate. Dietary restriction thus does not slow accumulation of aging‐related damage. Molecular species that track the effects of temperatures on mortality but are unaltered with switches in diet are therefore potential biomarkers of aging‐related damage. However, molecular species that switch upon instigation or withdrawal of DR are thus potential biomarkers of mechanisms underlying risk of mortality, but not of aging‐related damage. Using this approach, we assessed several commonly used biomarkers of aging‐related damage. Accumulation of fluorescent advanced glycation end products (AGEs) correlated strongly with mortality rate of flies at different temperatures but was independent of diet. Hence, fluorescent AGEs are biomarkers of aging‐related damage in flies. In contrast, five oxidized and glycated protein adducts accumulated with age, but were reversible with both temperature and diet, and are therefore not markers either of acute risk of dying or of aging‐related damage. Our approach provides a powerful method for identification of biomarkers of aging.     

The processive kinetics of gene conversion in bacteria

Gene conversion, non‐reciprocal transfer from one homologous sequence to another, is a major force in evolutionary dynamics, promoting co‐evolution in gene families and maintaining similarities between repeated genes. However, the properties of the transfer – where it initiates, how far it proceeds and how the resulting conversion tracts are affected by mismatch repair – are not well understood. Here, we use the duplicate tuf genes in Salmonella as a quantitatively tractable model system for gene conversion. We selected for conversion in multiple different positions of tuf, and examined the resulting distributions of conversion tracts in mismatch repair‐deficient and mismatch repair‐proficient strains. A simple stochastic model accounting for the essential steps of conversion showed excellent agreement with the data for all selection points using the same value of the conversion processivity, which is the only kinetic parameter of the model. The analysis suggests that gene conversion effectively initiates uniformly at any position within a tuf gene, and proceeds with an effectively uniform conversion processivity in either direction limited by the bounds of the gene.     

Lifestyle impacts on the aging‐associated expression of biomarkers of DNA damage and telomere dysfunction in human blood

Cellular aging is characterized by telomere shortening, which can lead to uncapping of chromosome ends (telomere dysfunction) and activation of DNA damage responses. There is some evidence that DNA damage accumulates during human aging and that lifestyle factors contribute to the accumulation of DNA damage. Recent studies have identified a set of serum markers that are induced by telomere dysfunction and DNA damage, and these markers showed an increased expression in blood during human aging. Here, we investigated the influence of lifestyle factors (such as exercise, smoking, body mass) on the aging‐associated expression of serum markers of DNA damage (CRAMP, EF‐1α, stathmin, n‐acetyl‐glucosaminidase and chitinase) in comparison with other described markers of cellular aging (p16^INK4a upregulation and telomere shortening) in human peripheral blood. The study shows that lifestyle factors have an age‐independent impact on the expression level of biomarkers of DNA damage. Smoking and increased body mass indices were associated with elevated levels of biomarkers of DNA damage independent of the age of the individuals. In contrast, exercise was associated with an age‐independent reduction in the expression of biomarkers of DNA damage in human blood. The expression of biomarkers of DNA damage correlated positively with p16^INK4a expression and negatively with telomere length in peripheral blood T‐lymphocytes. Together, these data provide experimental evidence that both aging and lifestyle impact on the accumulation of DNA damage during human aging.     

A systems biology view of blood vessel growth and remodelling

Blood travels throughout the body in an extensive network of vessels – arteries, veins and capillaries. This vascular network is not static, but instead dynamically remodels in response to stimuli from cells in the nearby tissue. In particular, the smallest vessels – arterioles, venules and capillaries – can be extended, expanded or pruned, in response to exercise, ischaemic events, pharmacological interventions, or other physiological and pathophysiological events. In this review, we describe the multi‐step morphogenic process of angiogenesis – the sprouting of new blood vessels – and the stability of vascular networks in vivo. In particular, we review the known interactions between endothelial cells and the various blood cells and plasma components they convey. We describe progress that has been made in applying computational modelling, quantitative biology and high‐throughput experimentation to the angiogenesis process.     

Efficient search,mapping, and optimization of multi‐protein genetic systems in diverse bacteria

Developing predictive models of multi‐protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi‐protein expression space across a > 10,000‐fold range with tailored search parameters and well‐predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram‐positive and gram‐negative bacterial hosts. We then combined the search algorithm with system‐level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence‐expression‐activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate‐limiting steps in metabolism. Creating sequence‐expression‐activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs.     

Evidence for a multi‐peak adaptive landscape in the evolution of trophic morphology in terapontid fishes

Using the Australian marine‐freshwater terapontid fishes as a model system, we examined the role of dietary phenotypic optima in an adaptive macro‐evolutionary landscape. Comparative modelling relying on both a priori and data‐driven identification of selective regimes suggested multi‐peak models as best describing much of the dietary phenotypic landscape of terapontids. Both approaches identified common phenotypic optima for different lineages of marine and freshwater herbivores, and minimal differentiation between carnivores and omnivores, irrespective of their phylogenetic relationships, as the model best describing morphological evolution. Significant correlations also existed between these phenotypic axes and proportions of non‐animal dietary items in species’ diets. While simulation results provided evidence for a multi‐peak adaptive landscape in the evolution of trophic morphology in terapontids, they could not rule out chance convergence in these adaptive peaks. However, they do provide scope for identifying areas for more detailed, functionally specific study of phenotypic convergence in herbivorous terapontid trophic habits. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 113 , 623–634.     

Genes acting in longevity-related pathways in the endoparasitoid,Pteromalus puparum

Among insects, lifespans vary over a broad range, from the short-lived mayflies to the 17-year periodical cicadas. Generally, lifespans are determined by a phase in life, the reproductive lifespan, which varies among species. Numerous pathways, such as the insulin/insulin-like growth factor signaling pathway, the target of rapamycin pathway and the mitogen-activated protein kinase/extracellular signal-regulated kinases pathways, influence aging and lifespan. Components of these pathways were identified as lifespan-related genes, including genes mediating growth, metabolism, development, resistance, and other processes. Many age-related genes have been discovered in fruit flies, honeybees, and ants among other insect species. Studies of insect aging and longevity can help understand insect biology and develop new pest management technologies. In this paper, we interrogated the new Pteromalus puparum genome, from which we predicted 133 putative lifespan-related genes based on their homology with known lifespan-related genes of Drosophila melanogaster. These genes function in five signaling pathways and three physiological processes. The conserved domain structures of these genes were predicted and their expression patterns were analyzed. Amino acid sequence alignments and domain structure analysis indicate that most components remain conserved across at least six insect orders. The data in this paper will facilitate future work on parasitoid lifespans, which may have economic value in biocontrol programs.     

Biomarker signatures of aging

Because people age differently, age is not a sufficient marker of susceptibility to disabilities, morbidities, and mortality. We measured nineteen blood biomarkers that include constituents of standard hematological measures, lipid biomarkers, and markers of inflammation and frailty in 4704 participants of the Long Life Family Study (LLFS), age range 30–110 years, and used an agglomerative algorithm to group LLFS participants into clusters thus yielding 26 different biomarker signatures. To test whether these signatures were associated with differences in biological aging, we correlated them with longitudinal changes in physiological functions and incident risk of cancer, cardiovascular disease, type 2 diabetes, and mortality using longitudinal data collected in the LLFS. Signature 2 was associated with significantly lower mortality, morbidity, and better physical function relative to the most common biomarker signature in LLFS, while nine other signatures were associated with less successful aging, characterized by higher risks for frailty, morbidity, and mortality. The predictive values of seven signatures were replicated in an independent data set from the Framingham Heart Study with comparable significant effects, and an additional three signatures showed consistent effects. This analysis shows that various biomarker signatures exist, and their significant associations with physical function, morbidity, and mortality suggest that these patterns represent differences in biological aging. The signatures show that dysregulation of a single biomarker can change with patterns of other biomarkers, and age‐related changes of individual biomarkers alone do not necessarily indicate disease or functional decline.