The emergence of longevous populations.
Ontology highlight
ABSTRACT:
SUBMITTER: Colchero F
PROVIDER: S-EPMC5137748 | biostudies-literature | 2016 Nov
REPOSITORIES: biostudies-literature
Publications
The emergence of longevous populations.
Colchero Fernando F Rau Roland R Jones Owen R OR Barthold Julia A JA Conde Dalia A DA Lenart Adam A Nemeth Laszlo L Scheuerlein Alexander A Schoeley Jonas J Torres Catalina C Zarulli Virginia V Altmann Jeanne J Brockman Diane K DK Bronikowski Anne M AM Fedigan Linda M LM Pusey Anne E AE Stoinski Tara S TS Strier Karen B KB Baudisch Annette A Alberts Susan C SC Vaupel James W JW
Proceedings of the National Academy of Sciences of the United States of America 20161121 48
The human lifespan has traversed a long evolutionary and historical path, from short-lived primate ancestors to contemporary Japan, Sweden, and other longevity frontrunners. Analyzing this trajectory is crucial for understanding biological and sociocultural processes that determine the span of life. Here we reveal a fundamental regularity. Two straight lines describe the joint rise of life expectancy and lifespan equality: one for primates and the second one over the full range of human experien ...[more]
Similar Datasets
Project description:Gut microbiota of centenarians has garnered significant attention in recent years, with most studies concentrating on the analysis of microbial composition. However, there is still limited knowledge regarding the consistent signatures of specific species and their biological functions, as well as the potential causal relationship between gut microbiota and longevity. To address this, we performed the fecal metagenomic analysis of eight longevous populations at the species and functional level, and employed the Mendelian randomization (MR) analysis to infer the causal associations between microbial taxa and longevity-related traits. We observed that several species including Eisenbergiella tayi, Methanobrevibacter smithii, Hungatella hathewayi, and Desulfovibrio fairfieldensis were consistently enriched in the gut microbiota of long-lived individuals compared to younger elderly and young adults across multiple cohorts. Analysis of microbial pathways and enzymes indicated that E. tayi plays a role in the protein N-glycosylation, while M. smithii is involved in the 3-dehydroquinate and chorismate biosynthesis. Furthermore, H. hathewayi makes a distinct contribution to the purine nucleobase degradation I pathway, potentially assisting the elderly in maintaining purine homeostasis. D. fairfieldensis contributes to the menaquinone (vitamin K2) biosynthesis, which may help prevent age-related diseases such as osteoporosis-induced fractures. According to MR results, Hungatella was significantly positively correlated with parental longevity, and Desulfovibrio also exhibited positive associations with lifespan and multiple traits related to parental longevity. Additionally, Alistipes and Akkermansia muciniphila were consistently enriched in the gut microbiota of the three largest cohorts of long-lived individuals, and MR analysis also suggests their potential causal relationships with longevity. Our findings reveal longevity-associated gut microbial signatures, which are informative for understanding the role of microbiota in regulating longevity and aging.
| S-EPMC11364081 | biostudies-literature
Project description:Recent work shows strong evidence of ancestry-based assortative mating in spouse pairs of the older generation of the Framingham Heart Study. Here, we extend this analysis to two studies of human longevity: the Long Life Family Study (LLFS), and the New England Centenarian Study (NECS). In the LLFS, we identified 890 spouse pairs spanning two generations, while in the NECS we used data from 102 spouse pairs including offspring of centenarians. We used principal components of genome-wide genotype data to demonstrate strong evidence of ancestry-based assortative mating in spouse pairs of the older generation and also confirm the decreasing trend of endogamy in more recent generations. These findings in studies of human longevity suggest that spouses marrying into longevous families may not be powerful controls for genetic association studies, and that there may be important ethnicity-specific, genetic influences and/or gene-environment interactions that influence extreme survival in old generations. In addition, the decreasing trend of genetic similarity of more recent generations might have ramifications for the incidence of homozygous rare variants necessary for survival to the most extreme ages.
| S-EPMC5702482 | biostudies-literature
Project description:The emergence and re-emergence of pathogens remains a major public health concern. Unfortunately, when and where pathogens will (re-)emerge is notoriously difficult to predict, as the erratic nature of those events is reinforced by the stochastic nature of pathogen evolution during the early phase of an epidemic. For instance, mutations allowing pathogens to escape host resistance may boost pathogen spread and promote emergence. Yet, the ecological factors that govern such evolutionary emergence remain elusive because of the lack of ecological realism of current theoretical frameworks and the difficulty of experimentally testing their predictions. Here, we develop a theoretical model to explore the effects of the heterogeneity of the host population on the probability of pathogen emergence, with or without pathogen evolution. We show that evolutionary emergence and the spread of escape mutations in the pathogen population is more likely to occur when the host population contains an intermediate proportion of resistant hosts. We also show that the probability of pathogen emergence rapidly declines with the diversity of resistance in the host population. Experimental tests using lytic bacteriophages infecting their bacterial hosts containing Clustered Regularly Interspaced Short Palindromic Repeat and CRISPR-associated (CRISPR-Cas) immune defenses confirm these theoretical predictions. These results suggest effective strategies for cross-species spillover and for the management of emerging infectious diseases.
| S-EPMC6171948 | biostudies-literature
Project description:The idea that populations are spatially structured has become a very powerful concept in ecology, raising interest in many research areas. However, despite dispersal being a core component of the concept, it typically does not consider the movement behavior underlying any dispersal. Using individual-based simulations in continuous space, we explored the emergence of a spatially structured population in landscapes with spatially heterogeneous resource distribution and with organisms following simple area-concentrated search (ACS); individuals do not, however, perceive or respond to any habitat attributes per se but only to their foraging success. We investigated the effects of different resource clustering pattern in landscapes (single large cluster vs. many small clusters) and different resource density on the spatial structure of populations and movement between resource clusters of individuals. As results, we found that foraging success increased with increasing resource density and decreasing number of resource clusters. In a wide parameter space, the system exhibited attributes of a spatially structured populations with individuals concentrated in areas of high resource density, searching within areas of resources, and "dispersing" in straight line between resource patches. "Emigration" was more likely from patches that were small or of low quality (low resource density), but we observed an interaction effect between these two parameters. With the ACS implemented, individuals tended to move deeper into a resource cluster in scenarios with moderate resource density than in scenarios with high resource density. "Looping" from patches was more likely if patches were large and of high quality. Our simulations demonstrate that spatial structure in populations may emerge if critical resources are heterogeneously distributed and if individuals follow simple movement rules (such as ACS). Neither the perception of habitat nor an explicit decision to emigrate from a patch on the side of acting individuals is necessary for the emergence of such spatial structure.
| S-EPMC9712486 | biostudies-literature
Project description:Neutrophil surveillance is central to nanoparticle clearance. Silver nanoparticles (AgNP) have numerous uses, however conflicting evidence exists as to their impact on neutrophils and whether they trigger damaging inflammation. Neutrophil's importance in innate defence and regulating immune networks mean it's essential we understand AgNP's impact on neutrophil function. Human neutrophil viability following AgNP or Ag Bulk treatment was analysed by flow cytometry and AnV/PI staining. Whilst AgNP exposure did not increase the total number of apoptotic neutrophils, the number of late apoptotic neutrophils was increased, suggesting AgNP increase transit through apoptosis. Mature (CD16bright/CD62Lbright), immature (CD16dim/CD62Lbright) and apoptotic (CD16dim/CD62Ldim) neutrophil populations were evident within isolated neutrophil preparations. AgNP exposure significantly reduced CD62L staining of CD16bright/CD62Lbright neutrophils, and increased CD16 staining of CD16dim/CD62Lbright populations, suggesting AgNPs trigger neutrophil activation and maturation, respectively. AgNP exposure dramatically increased IL-8, yet not classical pro-inflammatory cytokine release, suggesting AgNP triggers neutrophil activation, without pro-inflammation or damaging, necrotic cell death. For the first time, we show AgNPs differentially affect distinct sub-populations of circulating human neutrophils; activating mature neutrophils with the emergence of CD16bright/CD62Ldim neutrophils. This may stimulate particle clearance without harmful inflammation, challenging previous assumptions that silver nanomaterials induce neutrophil toxicity and damaging inflammatory responses.
| S-EPMC5951814 | biostudies-other
Project description:Evolutionary dynamics are controlled by a number of driving forces, such as natural selection, random genetic drift and dispersal. In this perspective article, we aim to emphasize that these forces act at the population level, and that it is a challenge to understand how they emerge from the stochastic and deterministic behaviour of individual cells. Even the most basic steric interactions between neighbouring cells can couple evolutionary outcomes of otherwise unrelated individuals, thereby weakening natural selection and enhancing random genetic drift. Using microbial examples of varying degrees of complexity, we demonstrate how strongly cell-cell interactions influence evolutionary dynamics, especially in pattern-forming systems. As pattern formation itself is subject to evolution, we propose to study the feedback between pattern formation and evolutionary dynamics, which could be key to predicting and potentially steering evolutionary processes. Such an effort requires extending the systems biology approach from the cellular to the population scale.This article is part of the theme issue 'Self-organization in cell biology'.
| S-EPMC5904294 | biostudies-literature
Project description:Microbial biophotovoltaics (BPV) offers a biological solution for renewable energy production by using photosynthetic microorganisms as light absorbers. Although abiotic engineering approaches, e.g., electrode modification and device optimization, can enhance the electrochemical communication between living cells and electrodes, the power densities of BPV are still low due to the weak exoelectrogenic activity of photosynthetic microorganisms. Here, we develop a BPV based on a D-lactate mediated microbial consortium consisting of photosynthetic cyanobacteria and exoelectrogenic Shewanella. By directing solar energy from photons to D-lactate, then to electricity, this BPV generates a power density of over 150 mW·m-2 in a temporal separation setup. Furthermore, a spatial-temporal separation setup with medium replenishment enables stable operation for over 40 days with an average power density of 135 mW·m-2. These results demonstrate the electron flow constrained microbial consortium can facilitate electron export from photosynthetic cells and achieve an efficient and durable power output.
| S-EPMC6753107 | biostudies-literature
Project description:Haplogroup J1 is a prevalent Y-chromosome lineage within the Near East. We report the frequency and YSTR diversity data for its major sub-clade (J1e). The overall expansion time estimated from 453 chromosomes is 10,000 years. Moreover, the previously described J1 (DYS388=13) chromosomes, frequently found in the Caucasus and eastern Anatolian populations, were ancestral to J1e and displayed an expansion time of 9000 years. For J1e, the Zagros/Taurus mountain region displays the highest haplotype diversity, although the J1e frequency increases toward the peripheral Arabian Peninsula. The southerly pattern of decreasing expansion time estimates is consistent with the serial drift and founder effect processes. The first such migration is predicted to have occurred at the onset of the Neolithic, and accordingly J1e parallels the establishment of rain-fed agriculture and semi-nomadic herders throughout the Fertile Crescent. Subsequently, J1e lineages might have been involved in episodes of the expansion of pastoralists into arid habitats coinciding with the spread of Arabic and other Semitic-speaking populations.
| S-EPMC2987219 | biostudies-literature
Project description:BackgroundVector-borne disease transmission is dependent on the many nuances of the contact event between infectious and susceptible hosts. Virus acquisition from a viremic human to a susceptible mosquito is often assumed to be nearly perfect and almost always uniform across the infectious period. Dengue transmission models that have previously addressed variability in human to vector transmission dynamics do not account for the variation in infectiousness of a single individual, and subsequent infection of naïve mosquitoes. Understanding the contribution of this variability in human infectiousness is especially important in the context of introduction events where an infected individual carries the virus into a population of competent vectors. Furthermore, it could affect the ability to detect an epidemic (and the timing of detection) following introduction.MethodsWe constructed a stochastic, compartmental model to describe the heterogeneity of human viremia and calculate the probability of a successful introduction, taking into account the viremia level (and thus acquisition potential) of the index case on, and after, the day of introduction into a susceptible population and varying contact rates between the human and mosquito populations. We then compared the results of this model with those generated by a simpler model that has the same average infectiousness but only a single infectious class.ResultsWe found that the infectivity of the index case as well as the contact rate affected the probability of emergence, but that contact rate had the most significant effect. We also found that the interaction between contact rate and the infectiousness of the index case affected the time to detection relative to the peak of the epidemic curve. Additionally, when compared to our model that accounts for variable infectiousness, a model with a single infectious class underestimates the probability of emergence and transmission intensity.ConclusionUnderstanding the interplay between individual human heterogeneity of infectiousness and the rate of contact with the vector population will be important when predicting the likelihood, detection, and magnitude of an outbreak.
| S-EPMC4082489 | biostudies-literature
Project description:Ecological and evolutionary dynamics have been historically regarded as unfolding at broadly separated timescales. However, these two types of processes are nowadays well-documented to intersperse much more tightly than traditionally assumed, especially in communities of microorganisms. Advancing the development of mathematical and computational approaches to shed novel light onto eco-evolutionary problems is a challenge of utmost relevance. With this motivation in mind, here we scrutinize recent experimental results showing evidence of rapid evolution of tolerance by lag in bacterial populations that are periodically exposed to antibiotic stress in laboratory conditions. In particular, the distribution of single-cell lag times-i.e., the times that individual bacteria from the community remain in a dormant state to cope with stress-evolves its average value to approximately fit the antibiotic-exposure time. Moreover, the distribution develops right-skewed heavy tails, revealing the presence of individuals with anomalously large lag times. Here, we develop a parsimonious individual-based model mimicking the actual demographic processes of the experimental setup. Individuals are characterized by a single phenotypic trait: their intrinsic lag time, which is transmitted with variation to the progeny. The model-in a version in which the amplitude of phenotypic variations grows with the parent's lag time-is able to reproduce quite well the key empirical observations. Furthermore, we develop a general mathematical framework allowing us to describe with good accuracy the properties of the stochastic model by means of a macroscopic equation, which generalizes the Crow-Kimura equation in population genetics. Even if the model does not account for all the biological mechanisms (e.g., genetic changes) in a detailed way-i.e., it is a phenomenological one-it sheds light onto the eco-evolutionary dynamics of the problem and can be helpful to design strategies to hinder the emergence of tolerance in bacterial communities. From a broader perspective, this work represents a benchmark for the mathematical framework designed to tackle much more general eco-evolutionary problems, thus paving the road to further research avenues.
| S-EPMC8492070 | biostudies-literature