SPERM‐LIMITED FECUNDITY IN NEMATODES: HOW MANY SPERM ARE ENOUGH?

The Bateman principle, which holds that oocytes are the limiting gamete in reproduction, is violated in a variety of species. Self-fertilizing hermaphrodites of the nematode Caenorhabditis elegans provide an example of a system in which sperm number limits lifetime reproductive output, in this species due to the protandrous nature of sperm production that in turn delays the onset of fertilization. This reproductive delay forms the basis of a trade-off between generation time and total fecundity, in which sperm number plays a pivotal role. I use an age-structured population model to describe the number of sperm that maximize fitness, given larval development time and rates of gamete production. The model predicts the evolution of sperm numbers that are consistent with empirical data for C. elegans provided that precocious larval sperm production is taken into account. Several testable hypotheses follow from the model regarding how natural selection and environmental variation may influence patterns of sperm production among populations or species with a similar mode of reproduction.     

Identifying Optimal Models to Represent Biochemical Systems

Biochemical systems involving a high number of components with intricate interactions often lead to complex models containing a large number of parameters. Although a large model could describe in detail the mechanisms that underlie the system, its very large size may hinder us in understanding the key elements of the system. Also in terms of parameter identification, large models are often problematic. Therefore, a reduced model may be preferred to represent the system. Yet, in order to efficaciously replace the large model, the reduced model should have the same ability as the large model to produce reliable predictions for a broad set of testable experimental conditions. We present a novel method to extract an “optimal” reduced model from a large model to represent biochemical systems by combining a reduction method and a model discrimination method. The former assures that the reduced model contains only those components that are important to produce the dynamics observed in given experiments, whereas the latter ensures that the reduced model gives a good prediction for any feasible experimental conditions that are relevant to answer questions at hand. These two techniques are applied iteratively. The method reveals the biological core of a model mathematically, indicating the processes that are likely to be responsible for certain behavior. We demonstrate the algorithm on two realistic model examples. We show that in both cases the core is substantially smaller than the full model.     

Oxidative stress in ecology and evolution: lessons from avian studies

Although oxidative stress is a central topic in biochemical and medical research, the number of reports on its relevance in life‐history studies of non‐human animals is still low. Information about oxidative stress in wild birds may help describe functional interactions among the components of life‐history traits. Currently available evidence suggests that oxidative stress may impart an important physiological cost on longevity, reproduction, immune response or intense physical activity. Given the gaps in our present knowledge, it is still premature to attempt to draw definitive conclusions and basic questions (e.g. how is oxidative stress generated and how do organisms cope with it?) have yet to be fully explored under natural conditions. Therefore, caution is needed in developing hypotheses or drawing general conclusions until additional data become available to perform more rigorous comparative analyses.     

Caenorhabditis elegans as a model system to study aging of learning and memory

The nematode Caenorhabditis elegans is an excellent model organism to study biological processes relevant to a wide variety of human and rodent disease systems. Previous studies have suggested that mutants of the insulin/insulin-like growth factor-1 pathway show life extension and increased stress resistance in various species, including C. elegans, the fruit fly, and the mouse. It has recently been shown that the life-extending mutants, including the age-1 phosphatidylinositol- 3 OH kinase mutants and the daf-2 insulin-like receptor mutants, display improvement in a type of associative learning behavior called thermotaxis learning behavior. The age-1 mutant shows a dramatic threefold extension of the health-span that ensures thermotaxis learning behavior, suggesting strong neuroprotective actions during aging. The age-1 and daf-2 mutants show resistance to multiple forms of stress and upregulates the genes involved in reactive oxygen species scavenging, heat shock, and P450 drug-detoxification. The life-extending mutants may confer resistance to various stress and diseases in neurons. Therefore, C. elegans provides an emerging system for the prevention of age-related deficits in the nervous system and in learning behaviors. This article discusses the aging of learning and memory and the neuroprotection effects of life-extending mutants on learning behaviors.     

Genome-wide prediction of genetic interactions in a metazoan

Genetic interactions provide information about genes and processes with overlapping functions in biological systems. For Saccharomyces cerevisiae, computational integration of multiple types of functional genomic data is used to generate genome-wide predictions of genetic interactions. However, this methodology cannot be applied to the vastly more complex genome of metazoans, and only recently has the first metazoan genome-wide prediction of genetic interactions been reported. The prediction for Caenorhabditis elegans was generated by computationally integrating functional genomic data from S. cerevisiae, C. elegans and Drosophila melanogaster. This achievement is an important step toward system-level understanding of biological systems and human diseases.     

High local genetic diversity and low outcrossing rate in Caenorhabditis elegans natural populations

BACKGROUND: Caenorhabditis elegans is a major model system in biology, yet very little is known about its biology outside the laboratory. In particular, its unusual mode of reproduction with self-fertile hermaphrodites and facultative males raises the question of its frequency of outcrossing in natural populations. RESULTS: We describe the first analysis of C. elegans individuals sampled directly from natural populations. C. elegans is found predominantly in the dauer stage and with a very low frequency of males versus hermaphrodites. Whereas C. elegans was previously shown to display a low worldwide genetic diversity, we find by comparison a surprisingly high local genetic diversity of C. elegans populations; this local diversity is contributed in great part by immigration of new alleles rather than by mutation. Our results on heterozygote frequency, male frequency, and linkage disequilibrium furthermore show that selfing is the predominant mode of reproduction in C. elegans natural populations but that infrequent outcrossing events occur, at a rate of approximately 1%. CONCLUSIONS: Our results give a first insight in the biology of C. elegans in the natural populations. They demonstrate that local populations of C. elegans are genetically diverse and that a low frequency of outcrossing allows for the recombination of these locally diverse genotypes.     

1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in (1)H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.     

铜对秀丽隐杆线虫毒性效应的研究

为了阐明铜(Cu)对秀丽隐杆线虫Caenorhabditis elegans长期作用的毒性效应,对实验室多代筛选的耐铜型秀丽隐杆线虫进行了寿命、衰老、发育、生殖和运动等生物学指标的研究.结果显示耐铜型秀丽隐杆线虫与野生型秀丽隐杆线虫相比其寿命缩短、衰老提前、个体发育受到抑制,且出现繁殖率降低、生殖能力减弱、运动行为存在障碍等一系列生理变化.本文为理解与阐明Cu的毒性效应提供了实验资料,有助于深入开展Cu毒性机理的研究.     

A worm's life

Despite its relative anatomic simplicity, the nematode Caenorhabditis elegans (C. elegans) is a complex multicellular organism. In this review, we describe studies that have contributed to a better understanding of certain aspects of the worm's physiology. We focus on the cellular and molecular basis of the interaction between C. elegans and its environment, including its sensory capacities, the intrinsic biological clock that governs the speed of its life, and on some of the factors that control its life span. We also outline very recent findings that have demonstrated the existence of an innate immune system in C. elegans. Finally, we highlight a number of novel techniques that are transforming the worm from a largely genetic model system into an attractive organism for functional genomic studies.     

Building with a scaffold: emerging strategies for high- to low-level cellular modeling

Computational cellular models are becoming crucial for the analysis of complex biological systems. An important new paradigm for cellular modeling involves building a comprehensive scaffold of molecular interactions and then mining this scaffold to reveal a hierarchy of signaling, regulatory and metabolic pathways. We review the important trends that make this approach feasible and describe how they are spurring the development of models at multiple levels of abstraction. Pathway maps can be extracted from the scaffold using "high-level" computational models, which identify the key components, interactions and influences required for more detailed "low-level" models. Large-scale experimental measurements validate high-level models, whereas targeted experimental manipulations and measurements test low-level models.     

Effect of secondary flow on biological experiments in the cone-plate viscometer: methods for estimating collision frequency, wall shear stress and inter-particle interactions in non-linear flow.

We present a theoretical analysis of fluid flow and particle interactions in the cone-plate viscometer under conditions typically applied in biological studies. The analysis demonstrates that at higher shear rates, besides linear primary flow in the rotational direction, prominent non-linear secondary flow causes additional fluid circulation in the radial direction. Two parameters, the cone angle and Reynolds number, characterize flow in the viscometer over all ranges of shear rate. Our results indicate that secondary flow causes positional variations in: (i) the velocity gradient, (ii) the direction and magnitude of the wall shear stress at the plate surface, (iii) inter-particle collision frequency, (iv) magnitude and periodicity of normal and shear forces applied during particle-particle interactions, and (v) inter-particle attachment times. Thus, secondary flow may significantly influence cellular aggregation, platelet activation and endothelial cell mechanotransduction measurements. Besides cone-plate viscometers, this analysis methodology can also be extended to other experimental systems with complex non-linear flows.     

How structure determines correlations in neuronal networks

Networks are becoming a ubiquitous metaphor for the understanding of complex biological systems, spanning the range between molecular signalling pathways, neural networks in the brain, and interacting species in a food web. In many models, we face an intricate interplay between the topology of the network and the dynamics of the system, which is generally very hard to disentangle. A dynamical feature that has been subject of intense research in various fields are correlations between the noisy activity of nodes in a network. We consider a class of systems, where discrete signals are sent along the links of the network. Such systems are of particular relevance in neuroscience, because they provide models for networks of neurons that use action potentials for communication. We study correlations in dynamic networks with arbitrary topology, assuming linear pulse coupling. With our novel approach, we are able to understand in detail how specific structural motifs affect pairwise correlations. Based on a power series decomposition of the covariance matrix, we describe the conditions under which very indirect interactions will have a pronounced effect on correlations and population dynamics. In random networks, we find that indirect interactions may lead to a broad distribution of activation levels with low average but highly variable correlations. This phenomenon is even more pronounced in networks with distance dependent connectivity. In contrast, networks with highly connected hubs or patchy connections often exhibit strong average correlations. Our results are particularly relevant in view of new experimental techniques that enable the parallel recording of spiking activity from a large number of neurons, an appropriate interpretation of which is hampered by the currently limited understanding of structure-dynamics relations in complex networks.     

Optical silencing of C. elegans cells with arch proton pump

BACKGROUND: Optogenetic techniques using light-driven ion channels or ion pumps for controlling excitable cells have greatly facilitated the investigation of nervous systems in vivo. A model organism, C. elegans, with its small transparent body and well-characterized neural circuits, is especially suitable for optogenetic analyses. METHODOLOGY/PRINCIPAL FINDINGS: We describe the application of archaerhodopsin-3 (Arch), a recently reported optical neuronal silencer, to C. elegans. Arch::GFP expressed either in all neurons or body wall muscles of the entire body by means of transgenes were localized, at least partially, to the cell membrane without adverse effects, and caused locomotory paralysis of worms when illuminated by green light (550 nm). Pan-neuronal expression of Arch endowed worms with quick and sustained responsiveness to such light. Worms reliably responded to repeated periods of illumination and non-illumination, and remained paralyzed under continuous illumination for 30 seconds. Worms expressing Arch in different subsets of motor neurons exhibited distinct defects in the locomotory behavior under green light: selective silencing of A-type motor neurons affected backward movement while silencing of B-type motor neurons affected forward movement more severely. Our experiments using a heat-shock-mediated induction system also indicate that Arch becomes fully functional only 12 hours after induction and remains functional for more than 24 hour. CONCLUSIONS/SGNIFICANCE: Arch can be used for silencing neurons and muscles, and may be a useful alternative to currently widely used halorhodopsin (NpHR) in optogenetic studies of C. elegans.     

Associations between glucocorticoids and sociality across a continuum of vertebrate social behavior

The causes and consequences of individual differences in animal behavior and stress physiology are increasingly studied in wild animals, yet the possibility that stress physiology underlies individual variation in social behavior has received less attention. In this review, we bring together these study areas and focus on understanding how the activity of the vertebrate neuroendocrine stress axis (HPA‐axis) may underlie individual differences in social behavior in wild animals. We first describe a continuum of vertebrate social behaviors spanning from initial social tendencies (proactive behavior) to social behavior occurring in reproductive contexts (parental care, sexual pair‐bonding) and lastly to social behavior occurring in nonreproductive contexts (nonsexual bonding, group‐level cooperation). We then perform a qualitative review of existing literature to address the correlative and causal association between measures of HPA‐axis activity (glucocorticoid levels or GCs) and each of these types of social behavior. As expected, elevated HPA‐axis activity can inhibit social behavior associated with initial social tendencies (approaching conspecifics) and reproduction. However, elevated HPA‐axis activity may also enhance more elaborate social behavior outside of reproductive contexts, such as alloparental care behavior. In addition, the effect of GCs on social behavior can depend upon the sociality of the stressor (cause of increase in GCs) and the severity of stress (extent of increase in GCs). Our review shows that the while the associations between stress responses and sociality are diverse, the role of HPA‐axis activity behind social behavior may shift toward more facilitating and less inhibiting in more social species, providing insight into how stress physiology and social systems may co‐evolve.     

Multiple Skp1-related proteins in Caenorhabditis elegans: diverse patterns of interaction with Cullins and F-box proteins

BACKGROUND: The ubiquitin-proteasome pathway of proteolysis controls the abundance of specific regulatory proteins. The SCF complex is a type of ubiquitin-protein ligase (E3) that contributes to this pathway in many biological systems. In yeast and mammals, the SCF complex consists of common components, including Skp1, Cdc53/Cul1, and Rbx1, as well as variable components known as F-box proteins. Whereas only one functional Skp1 gene is present in the human genome, the genome of Caenorhabditis elegans has now been shown to contain at least 21 Skp1-related (skr) genes. The biochemical properties, expression, and function of the C. elegans SKR proteins were examined. RESULTS: Of the 17 SKR proteins examined, eight (SKR-1, -2, -3, -4, -7, -8, -9, and -10) were shown to interact with C. elegans CUL1 by yeast two-hybrid analysis or a coimmunoprecipitation assay in mammalian cells. Furthermore, SKR proteins exhibited diverse binding specificities for C. elegans F-box proteins. The tissue specificity of expression of the CUL1-interacting SKR proteins was also varied. Suppression of skr-1 or skr-2 genes by double-stranded RNA interference resulted in embryonic death, whereas that of skr-7, -8, -9, or -10 was associated with slow growth and morphological abnormalities. CONCLUSIONS: The multiple C. elegans SKR proteins exhibit marked differences in their association with Cullins and F-box proteins, in tissue specificity of expression, and in phenotypes associated with functional suppression by RNAi. At least eight of the SKR proteins may, like F-box proteins, act as variable components of the SCF complex in C. elegans.     

Stress responses and the mesolimbic dopamine system: social contexts and sex differences

Organisms react to threats with a variety of behavioral, hormonal, and neurobiological responses. The study of biological responses to stress has historically focused on the hypothalamic-pituitary-adrenal axis, but other systems such as the mesolimbic dopamine system are involved. Behavioral neuroendocrinologists have long recognized the importance of the mesolimbic dopamine system in mediating the effects of hormones on species specific behavior, especially aspects of reproductive behavior. There has been less focus on the role of this system in the context of stress, perhaps due to extensive data outlining its importance in reward or approach-based contexts. However, there is steadily growing evidence that the mesolimbic dopamine neurons have critical effects on behavioral responses to stress. Most of these data have been collected from experiments using a small number of animal model species under a limited set of contexts. This approach has led to important discoveries, but evidence is accumulating that mesolimbic dopamine responses are context dependent. Thus, focusing on a limited number of species under a narrow set of controlled conditions constrains our understanding of how the mesolimbic dopamine system regulates behavior in response to stress. Both affiliative and antagonistic social interactions have important effects on mesolimbic dopamine function, and there is preliminary evidence for sex differences as well. This review will highlight the benefits of expanding this approach, and focus on how social contexts and sex differences can impact mesolimbic dopamine stress responses.     

Remodeling of Proteostasis Upon Transition to Adulthood is Linked to Reproduction Onset

Protein folding and clearance networks sense and respond to misfolded and aggregation-prone proteins by activating cytoprotective cell stress responses that safeguard the proteome against damage, maintain the health of the cell, and enhance lifespan. Surprisingly, cellular proteostasis undergoes a sudden and widespread failure early in Caenorhabditis elegans adulthood, with marked consequences on proteostasis functions later in life. These changes in the regulation of quality control systems, such as chaperones, the ubiquitin proteasome system and cellular stress responses, are controlled cell-nonautonomously by the proliferation of germline stem cells. Here, we review recent studies examining changes in proteostasis upon transition to adulthood and how proteostasis is modulated by reproduction onset, focusing on C. elegans. Based on these and our own findings, we propose that the regulation of quality control systems is actively remodeled at the point of transition between development and adulthood to influence the subsequent course of aging.