Hormones coordinate developmental, physiological, and behavioral processes within and between all living organisms. They orchestrate and shape organogenesis from early in development, regulate the acquisition, assimilation, and utilization of nutrients to support growth and metabolism, control gamete production and sexual behavior, mediate organismal responses to environmental change, and allow for communication of information between organisms. Genes that code for hormones; the enzymes that synthesize, metabolize, and transport hormones; and hormone receptors are important targets for natural selection, and variation in their expression and function is a major driving force for the evolution of morphology and life history. Hormones coordinate physiology and behavior of populations of organisms, and thus play key roles in determining the structure of populations, communities, and ecosystems. The field of endocrinology is concerned with the study of hormones and their actions. This field is rooted in the comparative study of hormones in diverse species, which has provided the foundation for the modern fields of evolutionary, environmental, and biomedical endocrinology. Comparative endocrinologists work at the cutting edge of the life sciences. They identify new hormones, hormone receptors and mechanisms of hormone action applicable to diverse species, including humans; study the impact of habitat destruction, pollution, and climatic change on populations of organisms; establish novel model systems for studying hormones and their functions; and develop new genetic strains and husbandry practices for efficient production of animal protein. While the model system approach has dominated biomedical research in recent years, and has provided extraordinary insight into many basic cellular and molecular processes, this approach is limited to investigating a small minority of organisms. Animals exhibit tremendous diversity in form and function, life-history strategies, and responses to the environment. A major challenge for life scientists in the 21st century is to understand how a changing environment impacts all life on earth. A full understanding of the capabilities of organisms to respond to environmental variation, and the resilience of organisms challenged by environmental changes and extremes, is necessary for understanding the impact of pollution and climatic change on the viability of populations. Comparative endocrinologists have a key role to play in these efforts.

Insufficient kinetic stability of exoinulinase (EI) restricts its application in many areas including enzymatic transformation of inulin for production of ultra-high fructose syrup and oligofructan, as well as fermentation of inulin into bioethanol. The conventional method for enzyme stabilization involves mutagenesis and therefore risks alteration of an enzyme’s desired properties, such as activity. Here, we report a novel method for stabilization of EI without any modification of its primary sequence. Our method employs domain insertion of an entire EI domain into a thermophilic scaffold protein. Insertion of EI into a loop of a thermophilic maltodextrin-binding protein from Pyrococcus furiosus (PfMBP) resulted in improvement of kinetic stability (the duration over which an enzyme remains active) at 37 degrees C without any compromise in EI activity. Our analysis suggests that the improved kinetic stability at 37 degrees C might originate from a raised kinetic barrier for irreversible conversion of unfolded intermediates to completely inactivated species, rather than an increased energy difference between the folded and unfolded forms.

The adult central nervous system (CNS) of Drosophila is largely composed of relatively homogenous neuronal classes born during larval life. These adult-specific neuron lineages send out initial projections and then arrest development until metamorphosis, when intense sprouting occurs to establish the massive synaptic connections necessary for the behavior and function of the adult fly. In this study, we identified and characterized specific lineages in the adult CNS and described their secondary branch patterns. Because prior studies show that the outgrowth of incumbent remodeling neurons in the CNS is highly dependent on the ecdysone pathway, we investigated the role of ecdysone in the development of the adult-specific neuronal lineages using a dominant-negative construct of the ecdysone receptor (EcR-DN). When EcR-DN was expressed in clones of the adult-specific lineages, neuroblasts persisted longer, but we saw no alteration in the initial projections of the lineages. Defects were observed in secondary arbors of adult neurons, including clumping and cohesion of fine branches, misrouting, smaller arbors and some defasciculation. The defects varied across the multiple neuron lineages in both appearance and severity. These results indicate that the ecdysone receptor complex influences the fine-tuning of connectivity between neuronal circuits, in conjunction with other factors driving outgrowth and synaptic partnering.

Electron crystallography is arguably the only electron cryomicroscopy (cryoEM) technique able to deliver an atomic-resolution structure of membrane proteins embedded in the lipid bilayer. In the electron crystallographic structures of the light driven ion pump, bacteriorhodopsin, and the water channel, aquaporin-0, sufficiently high resolution was obtained and both lipid and protein were visualized, modeled, and described in detail. An extensive network of lipid-protein interactions mimicking native membranes is established and maintained in two-dimensional (2D) crystalline vesicles used for structural analysis by electron crystallography. Lipids are tightly integrated into the protein’s architecture where they can affect the function, structure, quaternary assembly, and the stability of the membrane protein.

Genetic studies of the fruit fly Drosophila have revealed a hierarchy of segmentation genes (maternal, gap, pair-rule and HOX) that subdivide the syncytial blastoderm into sequentially finer-scale coordinates. Within this hierarchy, the pair-rule genes translate gradients of information into periodic stripes of expression. How pair-rule genes function during the progressive mode of segmentation seen in short and intermediate-germ insects is an ongoing question. Here we report that the nuclear receptor Of’E75A is expressed with double segment periodicity in the head and thorax. In the abdomen, Of’E75A is expressed in a unique pattern during posterior elongation, and briefly resembles a sequence that is typical of pair-rule genes. Depletion of Of’E75A mRNA caused loss of a subset of odd-numbered parasegments, as well as parasegment 6. Because these parasegments straddle segment boundaries, we observe fusions between adjacent segments. Finally, expression of Of’E75A in the blastoderm requires even-skipped, which is a gap gene in Oncopeltus. These data show that the function of Of’E75A during embryogenesis shares many properties with canonical pair-rule genes in other insects. They further suggest that parasegment specification may occur through irregular and episodic pair-rule-like activity.

Although the vinegar fly, Drosophila melanogaster, has been a biological model organism for over a century, its emergence as a model system for the study of neurophysiology is comparatively recent. The primary reason for this is that the vinegar fly and its neurons are tiny; up until 5 years ago, it was prohibitively difficult to record intracellularly from individual neurons in the intact Drosophila brain (Wilson et al., 2004). Today, fly electrophysiologists can genetically label neurons with GFP and reliably record from many (but not all) neurons in the fruit fly brain. Using genetic tools to drive expression of fluorescent calcium indicators, light-sensitive ion channels, or cell activity suppressors, we are beginning to understand how the external environment is represented with electrical potentials in Drosophila neurons (for review, see Olsen and Wilson, 2008).

Realistic computational models of single neurons require component ion channels that reproduce experimental findings. Here, a topology-mutating genetic algorithm that searches for the best state diagram and transition-rate parameters to model macroscopic ion-channel behavior is described. Important features of the algorithm include a topology-altering strategy, automatic satisfaction of equilibrium constraints (microscopic reversibility), and multiple-protocol fitting using sequential goal programming rather than explicit weighting. Application of this genetic algorithm to design a sodium-channel model exhibiting both fast and prolonged inactivation yields a six-state model that produces realistic activity-dependent attenuation of action-potential backpropagation in current-clamp simulations of a CA1 pyramidal neuron.

Thioredoxin-interacting protein (Txnip), originally characterized as an inhibitor of thioredoxin, is now known to be a critical regulator of glucose metabolism in vivo. Txnip is a member of the alpha-arrestin protein family; the alpha-arrestins are related to the classical beta-arrestins and visual arrestins. Txnip is the only alpha-arrestin known to bind thioredoxin, and it is not known whether the metabolic effects of Txnip are related to its ability to bind thioredoxin or related to conserved alpha-arrestin function. Here we show that wild type Txnip and Txnip C247S, a Txnip mutant that does not bind thioredoxin in vitro, both inhibit glucose uptake in mature adipocytes and in primary skin fibroblasts. Furthermore, we show that Txnip C247S does not bind thioredoxin in cells, using thiol alkylation to trap the Txnip-thioredoxin complex. Because Txnip function was independent of thioredoxin binding, we tested whether inhibition of glucose uptake was conserved in the related alpha-arrestins Arrdc4 and Arrdc3. Both Txnip and Arrdc4 inhibited glucose uptake and lactate output, while Arrdc3 had no effect. Structure-function analysis indicated that Txnip and Arrdc4 inhibit glucose uptake independent of the C-terminal WW-domain binding motifs, recently identified as important in yeast alpha-arrestins. Instead, regulation of glucose uptake was intrinsic to the arrestin domains themselves. These data demonstrate that Txnip regulates cellular metabolism independent of its binding to thioredoxin and reveal the arrestin domains as crucial structural elements in metabolic functions of alpha-arrestin proteins.

We built a digital nuclear atlas of the newly hatched, first larval stage (L1) of the wild-type hermaphrodite of Caenorhabditis elegans at single-cell resolution from confocal image stacks of 15 individual worms. The atlas quantifies the stereotypy of nuclear locations and provides other statistics on the spatial patterns of the 357 nuclei that could be faithfully segmented and annotated out of the 558 present at this developmental stage. We then developed an automated approach to assign cell names to each nucleus in a three-dimensional image of an L1 worm. We achieved 86% accuracy in identifying the 357 nuclei automatically. This computational method will allow high-throughput single-cell analyses of the post-embryonic worm, such as gene expression analysis, or ablation or stimulation of cells under computer control in a high-throughput functional screen.

In this paper we propose a framework for fully automatic, robust and accurate segmentation of the human pelvis and proximal femur in CT data. We propose a composite statistical shape model of femur and pelvis with a flexible hip joint, for which we extend the common definition of statistical shape models as well as the common strategy for their adaptation. We do not analyze the joint flexibility statistically, but model it explicitly by rotational parameters describing the bent in a ball-and-socket joint. A leave-one-out evaluation on 50 CT volumes shows that image driven adaptation of our composite shape model robustly produces accurate segmentations of both proximal femur and pelvis. As a second contribution, we evaluate a fine grain multi-object segmentation method based on graph optimization. It relies on accurate initializations of femur and pelvis, which our composite shape model can generate. Simultaneous optimization of both femur and pelvis yields more accurate results than separate optimizations of each structure. Shape model adaptation and graph based optimization are embedded in a fully automatic framework.