The synchronization of stochastic coupled oscillators is a central problem in physics and an emerging problem in biology, particularly in the context of circadian rhythms. Most measurements on the biological clock are made at the macroscopic level of millions of cells. Here measurements are made on the oscillators in single cells of the model fungal system, Neurospora crassa, with droplet microfluidics and the use of a fluorescent recorder hooked up to a promoter on a clock controlled gene-2 (ccg-2). The oscillators of individual cells are stochastic with a period near 21 hours (h), and using a stochastic clock network ensemble fitted by Markov Chain Monte Carlo implemented on general-purpose graphical processing units (or GPGPUs) we estimated that >94% of the variation in ccg-2 expression was stochastic (as opposed to experimental error). To overcome this stochasticity at the macroscopic level, cells must synchronize their oscillators. Using a classic measure of similarity in cell trajectories within droplets, the intraclass correlation (ICC), the synchronization surface ICC is measured on >25,000 cells as a function of the number of neighboring cells within a droplet and of time. The synchronization surface provides evidence that cells communicate, and synchronization varies with genotype.
RNA regulatory elements play a significant role in gene regulation. Riboswitches, a widespread group of regulatory RNAs, are vital components of many bacterial genomes. These regulatory elements generally function by forming a ligand-induced alternative fold that controls access to ribosome binding sites or other regulatory sites in RNA. Riboswitch-mediated mechanisms are ubiquitous across bacterial genomes. A typical class of riboswitch has its own unique structural and biological complexity, making de novo riboswitch identification a formidable task. Traditionally, riboswitches have been identified through comparative genomics based on sequence and structural homology. The limitations of structural-homology-based approaches, coupled with the assumption that there is a great diversity of undiscovered riboswitches, suggests the need for alternative methods for riboswitch identification, possibly based on features intrinsic to their structure. As of yet, no such reliable method has been proposed.
We used structural entropy of riboswitch sequences as a measure of their secondary structural dynamics. Entropy values of a diverse set of riboswitches were compared to that of their mutants, their dinucleotide shuffles, and their reverse complement sequences under different stochastic context-free grammar folding models. Significance of our results was evaluated by comparison to other approaches, such as the base-pairing entropy and energy landscapes dynamics. Classifiers based on structural entropy optimized via sequence and structural features were devised as riboswitch identifiers and tested on Bacillus subtilis, Escherichia coli, and Synechococcus elongatus as an exploration of structural entropy based approaches. The unusually long untranslated region of the cotH in Bacillus subtilis, as well as upstream regions of certain genes, such as the sucC genes were associated with significant structural entropy values in genome-wide examinations.
Various tests show that there is in fact a relationship between higher structural entropy and the potential for the RNA sequence to have alternative structures, within the limitations of our methodology. This relationship, though modest, is consistent across various tests. Understanding the behavior of structural entropy as a fairly new feature for RNA conformational dynamics, however, may require extensive exploratory investigation both across RNA sequences and folding models.
Riboswitch; Entropy; RNA secondary structure; cotH; sucC
The purpose of this study was to assess the relationship between APOE, life events and engagement, and subjective well-being (as measured by positive and negative affect) among centenarians. Based on the life stress paradigm, we predicted that higher levels of stress would allow APOE to influence positive and negative affect. One hundred and ninety six centenarians and near centenarians (98 years and older) of the Georgia Centenarian Study participated in this research. APOE, positive and negative affect, number of recent (last two years) and life-long (more than 20 years prior to testing) events, as well as a number of life engagement tasks were assessed. Results suggested that centenarians carrying the APOE ε4 allele rated lower in positive affect, number of life-long events, and in engaged lifestyle when compared to centenarians without the APOE ε4 allele (t = 3.43, p < .01, t = 3.19, p < .01, and t = 2.33, p < .05, respectively). Blockwise multiple regressions indicated that APOE ε4 predicted positive but not negative affect after controlling for demographics. Gene-environment interactions were obtained for APOE ε4 and life-long events, suggesting that carriers of the APOE ε4 allele had higher scores of negative affect after having experienced more events, whereas non-carriers had reduced negative affect levels after having experienced more events.
Doing large-scale genomics experiments can be expensive, and so experimenters want to get the most information out of each experiment. To this end the Maximally Informative Next Experiment (MINE) criterion for experimental design was developed. Here we explore this idea in a simplified context, the linear model. Four variations of the MINE method for the linear model were created: MINE-like, MINE, MINE with random orthonormal basis, and MINE with random rotation. Each method varies in how it maximizes the MINE criterion. Theorem 1 establishes sufficient conditions for the maximization of the MINE criterion under the linear model. Theorem 2 establishes when the MINE criterion is equivalent to the classic design criterion of D-optimality. By simulation under the linear model, we establish that the MINE with random orthonormal basis and MINE with random rotation are faster to discover the true linear relation with regression coefficients and observations when . We also establish in simulations with , , and 1000 replicates that these two variations of MINE also display a lower false positive rate than the MINE-like method and additionally, for a majority of the experiments, for the MINE method.
The biological clock affects aging through ras-1 (bd) and lag-1, and these two longevity genes together affect a clock phenotype and the clock oscillator in Neurospora crassa. Using an automated cell-counting technique for measuring conidial longevity, we show that the clock-associated genes lag-1 and ras-1 (bd) are true chronological longevity genes. For example, wild type (WT) has an estimated median life span of 24 days, while the double mutant lag-1, ras-1 (bd) has an estimated median life span of 120 days for macroconidia. We establish the biochemical function of lag-1 by complementing LAG1 and LAC1 in Saccharomyces cerevisiae with lag-1 in N. crassa. Longevity genes can affect the clock as well in that, the double mutant lag-1, ras-1 (bd) can stop the circadian rhythm in asexual reproduction (i.e., banding in race tubes) and lengthen the period of the frequency oscillator to 41 h. In contrast to the ras-1 (bd), lag-1 effects on chronological longevity, we find that this double mutant undergoes replicative senescence (i.e., the loss of replication function with time), unlike WT or the single mutants, lag-1 and ras-1 (bd). These results support the hypothesis that sphingolipid metabolism links aging and the biological clock through a common stress response
Aging; bd; biological clock; lag-1; Neurospora crassa; ras-1
Leukocyte telomere length is widely considered a biomarker of human age and in many studies indicative of health or disease. We have obtained quantitative estimates of telomere length from blood leukocytes in a population sample, confirming results of previous studies that telomere length significantly decreases with age. Telomere length was also positively associated with several measures of healthy aging, but this relationship was dependent on age. We screened two genes known to be involved in telomere maintenance for association with the age-related decline in telomere length observed in our population to identify candidate longevity-associated genes. A single-nucleotide polymorphism located in the SIRT1 gene and another in the 3′ flanking region of XRCC6 had significant effects on telomere length. At each bi-allelic locus, the minor variant was associated with longer telomeres, though the mode of inheritance fitting best differed between the two genes. No statistical interaction was detected for telomere length between the SIRT1 and XRCC6 variants or between these polymorphisms and age. The SIRT1 locus was significantly associated with longevity (P < 0.003). The frequency of the minor allele was higher in long-lived cases than in young controls, which coincides with the protective role of the minor variant for telomere length. In contrast, the XRCC6 variant was not associated with longevity. Furthermore, it did not affect the association of SIRT1 with exceptional survival. The association of the same variant of SIRT1 with longevity was near significant (P < 0.07) in a second population. These results suggest a potential role of SIRT1 in linking telomere length and longevity. Given the differences between this gene and XRCC6, they point to the distinct impact that alternate pathways of telomere maintenance may have on aging and exceptional survival.
SIRT1; XRCC6; Ku; Telomeres; Aging; Longevity
The goals of this article are to (a) establish the concurrent and clinical validity of the Global Deterioration scale in assessing cognitive functions and stages of dementia among centenarians, (b) identify the prevalence of all-cause dementia in representative samples of centenarians, and (c) demonstrate how variations in sample demographic characteristics could significantly affect estimates of dementia prevalence. A quarter of the 244 centenarians in a population-based sample had no objective evidence of memory deficits. Another quarter showed signs of transient confusion, and about half showed classical behavioral signs of dementia with about 15% in each of Global Deterioration scale stages 4–6 and about 5% in the most severe stage 7. Variations in age, gender, race, residence status, and education of the study sample as well as criteria used for dementia rating were found to affect prevalence.
Dementia prevalence; Centenarians; Validation
The search for longevity-determining genes in human has largely neglected the operation of genetic interactions. We have identified a novel combination of common variants of three genes that has a marked association with human lifespan and healthy aging. Subjects were recruited and stratified according to their genetically-inferred ethnic affiliation to account for population structure. Haplotype analysis was performed in three candidate genes, and the haplotype combinations were tested for association with exceptional longevity. An HRAS1 haplotype enhanced the effect of an APOE haplotype on exceptional survival, and a LASS1 haplotype further augmented its magnitude. These results were replicated in a second population. A profile of healthy aging was developed using a deficit accumulation index, which showed that this combination of gene variants is associated with healthy aging. The variation in LASS1 is functional, causing enhanced expression of the gene, and it contributes to healthy aging and greater survival in the tenth decade of life. Thus, rare gene variants need not be invoked to explain complex traits such as aging; instead rare congruence of common gene variants readily fulfills this role. The interaction between the three genes described here suggests new models for cellular and molecular mechanisms underlying exceptional survival and healthy aging that involve lipotoxicity.
Longevity genes; haplotypes; lipotoxicity; healthy aging profile; population stratification
An ensemble of genetic networks that describe how the model fungal system, Neurospora crassa, utilizes quinic acid (QA) as a sole carbon source has been identified previously. A genetic network for QA metabolism involves the genes, qa-1F and qa-1S, that encode a transcriptional activator and repressor, respectively and structural genes, qa-2, qa-3, qa-4, qa-x, and qa-y. By a series of 4 separate and independent, model-guided, microarray experiments a total of 50 genes are identified as QA-responsive and hypothesized to be under QA-1F control and/or the control of a second QA-responsive transcription factor (NCU03643) both in the fungal binuclear Zn(II)2Cys6 cluster family. QA-1F regulation is not sufficient to explain the quantitative variation in expression profiles of the 50 QA-responsive genes. QA-responsive genes include genes with products in 8 mutually connected metabolic pathways with 7 of them one step removed from the tricarboxylic (TCA) Cycle and with 7 of them one step removed from glycolysis: (1) starch and sucrose metabolism; (2) glycolysis/glucanogenesis; (3) TCA Cycle; (4) butanoate metabolism; (5) pyruvate metabolism; (6) aromatic amino acid and QA metabolism; (7) valine, leucine, and isoleucine degradation; and (8) transport of sugars and amino acids. Gene products both in aromatic amino acid and QA metabolism and transport show an immediate response to shift to QA, while genes with products in the remaining 7 metabolic modules generally show a delayed response to shift to QA. The additional QA-responsive cutinase transcription factor-1β (NCU03643) is found to have a delayed response to shift to QA. The series of microarray experiments are used to expand the previously identified genetic network describing the qa gene cluster to include all 50 QA-responsive genes including the second transcription factor (NCU03643). These studies illustrate new methodologies from systems biology to guide model-driven discoveries about a core metabolic network involving carbon and amino acid metabolism in N. crassa.
In the Georgia Centenarian Study (Poon et al., Exceptional Longevity, 2006), centenarian cases and young controls are classified according to three categories (age, ethnic origin, and single nucleotide polymorphisms [SNPs] of candidate longevity genes), where each factor has two possible levels. Here we provide methodologies to determine the minimum sample size needed to detect dependence in 2 × 2 × 2 tables based on Fisher's exact test evaluated exactly or by Markov chain Monte Carlo (MCMC), assuming only the case total L and the control total N are known. While our MCMC method uses serial computing, parallel computing techniques are employed to solve the exact sample size problem. These tools will allow researchers to design efficient sampling strategies and to select informative SNPs. We apply our tools to 2 × 2 × 2 tables obtained from a pilot study of the Georgia Centenarians Study, and the sample size results provided important information for the subsequent major study. A comparison between the results of an exact method and those of a MCMC method showed that the MCMC method studied needed much less computation time on average (10.16 times faster on average for situations examined with S.E. = 2.60), but its sample size results were only valid as a rule for larger sample sizes (in the hundreds).
Exact test; Longevity; Markov chain Monte Carlo; Nonrandom associations; Power; Sample size, Single nucleotide polymorphisms (SNPs); 2 × 2 × 2 table
Used a population-based sample (Georgia Centenarian Study, GCS), to determine proportions of centenarians reaching 100 years as (1) survivors (43%) of chronic diseases first experienced between 0–80 years of age, (2) delayers (36%) with chronic diseases first experienced between 80–98 years of age, or (3) escapers (17%) with chronic diseases only at 98 years of age or older. Diseases fall into two morbidity profiles of 11 chronic diseases; one including cardiovascular disease, cancer, anemia, and osteoporosis, and another including dementia. Centenarians at risk for cancer in their lifetime tended to be escapers (73%), while those at risk for cardiovascular disease tended to be survivors (24%), delayers (39%), or escapers (32%). Approximately half (43%) of the centenarians did not experience dementia. Psychiatric disorders were positively associated with dementia, but prevalence of depression, anxiety, and psychoses did not differ significantly between centenarians and an octogenarian control group. However, centenarians were higher on the Geriatric Depression Scale (GDS) than octogenarians. Consistent with our model of developmental adaptation in aging, distal life events contribute to predicting survivorship outcome in which health status as survivor, delayer, or escaper appears as adaptation variables late in life.
A model-driven discovery process, Computing Life, is used to identify an ensemble of genetic networks that describe the biological clock. A clock mechanism involving the genes white-collar-1 and white-collar-2 (wc-1 and wc-2) that encode a transcriptional activator (as well as a blue-light receptor) and an oscillator frequency (frq) that encodes a cyclin that deactivates the activator is used to guide this discovery process through three cycles of microarray experiments. Central to this discovery process is a new methodology for the rational design of a Maximally Informative Next Experiment (MINE), based on the genetic network ensemble. In each experimentation cycle, the MINE approach is used to select the most informative new experiment in order to mine for clock-controlled genes, the outputs of the clock. As much as 25% of the N. crassa transcriptome appears to be under clock-control. Clock outputs include genes with products in DNA metabolism, ribosome biogenesis in RNA metabolism, cell cycle, protein metabolism, transport, carbon metabolism, isoprenoid (including carotenoid) biosynthesis, development, and varied signaling processes. Genes under the transcription factor complex WCC ( = WC-1/WC-2) control were resolved into four classes, circadian only (612 genes), light-responsive only (396), both circadian and light-responsive (328), and neither circadian nor light-responsive (987). In each of three cycles of microarray experiments data support that wc-1 and wc-2 are auto-regulated by WCC. Among 11,000 N. crassa genes a total of 295 genes, including a large fraction of phosphatases/kinases, appear to be under the immediate control of the FRQ oscillator as validated by 4 independent microarray experiments. Ribosomal RNA processing and assembly rather than its transcription appears to be under clock control, suggesting a new mechanism for the post-transcriptional control of clock-controlled genes.
Members of the genus Pneumocystis are fungal pathogens that cause pneumonia in a wide variety of mammals with debilitated immune systems. Little is known about their basic biological functions, including life cycle, since no species can be cultured continuously outside the mammalian lung. To better understand the pathological process, about 4500 ESTS derived from sequencing of the poly(A) tail ends of P. carinii mRNAs during fulminate infection were annotated and functionally characterized as unassembled reads, and then clustered and reduced to a unigene set with 1042 members. Because of the presence of sequences from other microbial genomes and the rat host, the analysis and compression to a unigene set was necessarily an iterative process. BLASTx analysis of the unassembled reads (UR) vs. the Uni-Prot and TREMBL databases revealed 56% had similarities to existing polypeptides at E values of≤10−6, with the remainder lacking any significant homology. The most abundant transcripts in the UR were associated with stress responses, energy production, transcription and translation. Most (70%) of the UR had similarities to proteins from filamentous fungi (e.g., Aspergillus, Neurospora) and existing P. carinii gene products. In contrast, similarities to proteins of the yeast-like fungi, Schizosaccharomyces pombe and Saccharomyces cerevisiae, predominated in the unigene set. Gene Ontology analysis using BLAST2GO revealed P. carinii dedicated most of its transcripts to cellular and physiological processes (∼80%), molecular binding and catalytic activities (∼70%), and were primarily derived from cell and organellar compartments (∼80%). KEGG Pathway mapping showed the putative P. carinii genes represented most standard metabolic pathways and cellular processes, including the tricarboxylic acid cycle, glycolysis, amino acid biosynthesis, cell cycle and mitochondrial function. Several gene homologs associated with mating, meiosis, and sterol biosynthesis in fungi were identified. Genes encoding the major surface glycoprotein family (MSG), heat shock (HSP70), and proteases (PROT/KEX) were the most abundantly expressed of known P. carinii genes. The apparent presence of many metabolic pathways in P. carinii, sexual reproduction within the host, and lack of an invasive infection process in the immunologically intact host suggest members of the genus Pneumocystis may be adapted parasites and have a compatible relationship with their mammalian hosts. This study represents the first characterization of the expressed genes of a non-culturable fungal pathogen of mammals during the infective process.
The products of five structural genes and two regulatory genes of the qa gene cluster of Neurospora crassa control the
metabolism of quinic acid (QA) as a carbon source. A detailed genetic network model of this metabolic process has been
reported. This investigation is designed to expand the current model of the QA reaction network. The ensemble method of
network identification was used to model RNA profiling data on the qa gene cluster. Through microarray and cluster analysis,
genome-wide identification of RNA transcripts associated with quinic acid metabolism in N. crassa is described and suggests a
connection to other metabolic circuits. More than 100 genes whose products include carbon metabolism, protein degradation
and modification, amino acid metabolism and ribosome synthesis appear to be connected to quinic acid metabolism. The core
of the qa gene cluster network is validated with respect to RNA profiling data obtained from microarrays.
genetic networks; quinic acid; qa gene cluster; genome; microarray
GCSDB is a web-oriented integrated database system for the Georgia Centenarian Study, a phase III, population-based,
multidisciplinary study of centenarians. The Study recruited 244 centenarians and near-centenarians (age 98 and older),
80 octogenarians and 400 young controls in Northern Georgia. GCSDB incorporates more than 40 relational tables
containing data about the participants including demographics, family longevity, physical health, cognition,
neuropsychology, mental health, neuropathology, functional capacity, and genetics. The GCSDB web site includes
detailed information about these tables and functions for genetic and other kinds of data analysis. More data and
functions will be added as the study progresses. GCSDB provides a resource that could be used to identify what
biological, psychological, and social factors as well as their epistatic interactions help these centenarians achieve long
(login information can be obtained from authors)
centenarian; cognition; database; longevity; mental health; neuropathology; neuropsychology; functional capacity; Single Nucleotide Polymorphism (SNPs)