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158 Publications
Showing 31-40 of 158 resultsThe R‐specific alcohol dehydrogenase from Lactobacillus brevis (Lb‐ADH) catalyzes the enantioselective reduction of prochiral ketones to the corresponding secondary alcohols. It is stable and has broad substrate specificity. These features make this enzyme an attractive candidate for biotechnological applications. A drawback is its preference for NADP(H) as a cofactor, which is more expensive and labile than NAD(H). Structure‐based computational protein engineering was used to predict mutations to alter the cofactor specificity of Lb‐ADH. Mutations were introduced into Lb‐ADH and tested against the substrate acetophenone, with either NAD(H) or NADP(H) as cofactor. The mutant Arg38Pro showed fourfold increased activity with acetophenone and NAD(H) relative to the wild type. Both Arg38Pro and wild type exhibit a pH optimum of 5.5 with NAD(H) as cofactor, significantly more acidic than with NADP(H). These and related Lb‐ADH mutants may prove useful for the green synthesis of pharmaceutical precursors.
The sense of taste is a specialized chemosensory system dedicated to the evaluation of food and drink. Despite the fact that vertebrates and insects have independently evolved distinct anatomic and molecular pathways for taste sensation, there are clear parallels in the organization and coding logic between the two systems. There is now persuasive evidence that tastant quality is mediated by labeled lines, whereby distinct and strictly segregated populations of taste receptor cells encode each of the taste qualities.
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.
This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided to train and tune algorithms in advance. Participants were also allowed to use additional proprietary training data for that purpose. All teams then had to apply their methods to 10 test datasets and submit the obtained results. Employed algorithms include statistical shape models, atlas registration, level-sets, graph-cuts and rule-based systems. All results were compared to reference segmentations five error measures that highlight different aspects of segmentation accuracy. All measures were combined according to a specific scoring system relating the obtained values to human expert variability. In general, interactive methods reached higher average scores than automatic approaches and featured a better consistency of segmentation quality. However, the best automatic methods (mainly based on statistical shape models with some additional free deformation) could compete well on the majority of test images. The study provides an insight in performance of different segmentation approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.
Correlated mutation analyses (CMA) on multiple sequence alignments are widely used for the prediction of the function of amino acids. The accuracy of CMA-based predictions is mainly determined by the number of sequences, by their evolutionary distances, and by the quality of the alignments. These criteria are best met in structure-based sequence alignments of large super-families. So far, CMA-techniques have mainly been employed to study the receptor interactions. The present work shows how a novel CMA tool, called Comulator, can be used to determine networks of functionally related residues in enzymes. These analyses provide leads for protein engineering studies that are directed towards modification of enzyme specificity or activity. As proof of concept, Comulator has been applied to four enzyme super-families: the isocitrate lyase/phoshoenol-pyruvate mutase super-family, the hexokinase super-family, the RmlC-like cupin super-family, and the FAD-linked oxidases super-family. In each of those cases networks of functionally related residue positions were discovered that upon mutation influenced enzyme specificity and/or activity as predicted. We conclude that CMA is a powerful tool for redesigning enzyme activity and selectivity.
The genetically encoded calcium indicator GCaMP2 shows promise for neural network activity imaging, but is currently limited by low signal-to-noise ratio. We describe x-ray crystal structures as well as solution biophysical and spectroscopic characterization of GCaMP2 in the calcium-free dark state, and in two calcium-bound bright states: a monomeric form that dominates at intracellular concentrations observed during imaging experiments and an unexpected domain-swapped dimer with decreased fluorescence. This series of structures provides insight into the mechanism of Ca2+-induced fluorescence change. Upon calcium binding, the calmodulin (CaM) domain wraps around the M13 peptide, creating a new domain interface between CaM and the circularly permuted enhanced green fluorescent protein domain. Residues from CaM alter the chemical environment of the circularly permuted enhanced green fluorescent protein chromophore and, together with flexible inter-domain linkers, block solvent access to the chromophore. Guided by the crystal structures, we engineered a series of GCaMP2 point mutants to probe the mechanism of GCaMP2 function and characterized one mutant with significantly improved signal-to-noise. The mutation is located at a domain interface and its effect on sensor function could not have been predicted in the absence of structural data.
Ambulation after spinal cord injury is possible with the aid of neuroprosthesis employing functional electrical stimulation (FES). Individuals with incomplete spinal cord injury (iSCI) retain partial volitional control of muscles below the level of injury, necessitating careful integration of FES with intact voluntary motor function for efficient walking. In this study, the intramuscular electromyogram (iEMG) was used to detect the intent to step and trigger FES-assisted walking in a volunteer with iSCI via an implanted neuroprosthesis consisting of two channels of bipolar iEMG signal acquisition and 12 independent channels of stimulation. The detection was performed with two types of classifiers- a threshold-based classifier that compared the running mean of the iEMG with a discrimination threshold to generate the trigger and a pattern recognition classifier that compared the time-history of the iEMG with a specified template of activity to generate the trigger whenever the cross-correlation coefficient exceeded a discrimination threshold. The pattern recognition classifier generally outperformed the threshold-based classifier, particularly with respect to minimizing False Positive triggers. The overall True Positive rates for the threshold-based classifier were 61.6% and 87.2% for the right and left steps with overall False Positive rates of 38.4% and 33.3%. The overall True Positive rates for the left and right step with the pattern recognition classifier were 57.2% and 93.3% and the overall False Positive rates were 11.9% and 24.4%. The subject showed no preference for either the threshold or pattern recognition-based classifier as determined by the Usability Rating Scale (URS) score collected after each trial and both the classifiers were perceived as moderately easy to use.
The central complex is a prominent structure in the Drosophila brain. Visual learning experiments in the flight simulator, with flies with genetically altered brains, revealed that two groups of horizontal neurons in one of its substructures, the fan-shaped body, were required for Drosophila visual pattern memory. However, little is known about the role of other components of the central complex for visual pattern memory. Here we show that a small set of neurons in the ellipsoid body, which is another substructure of the central complex and connected to the fan-shaped body, is also required for visual pattern memory. Localized expression of rutabaga adenylyl cyclase in either the fan-shaped body or the ellipsoid body is sufficient to rescue the memory defect of the rut(2080) mutant. We then performed RNA interference of rutabaga in either structure and found that they both were required for visual pattern memory. Additionally, we tested the above rescued flies under several visual pattern parameters, such as size, contour orientation, and vertical compactness, and revealed differential roles of the fan-shaped body and the ellipsoid body for visual pattern memory. Our study defines a complex neural circuit in the central complex for Drosophila visual pattern memory.
The microtubule cytoskeleton has proven to be an effective target for cancer therapeutics. One class of drugs, known as microtubule stabilizing agents (MSAs), binds to microtubule polymers and stabilizes them against depolymerization. The prototype of this group of drugs, Taxol, is an effective chemotherapeutic agent used extensively in the treatment of human ovarian, breast, and lung carcinomas. Although electron crystallography and photoaffinity labeling experiments determined that the binding site for Taxol is in a hydrophobic pocket in beta-tubulin, little was known about the effects of this drug on the conformation of the entire microtubule. A recent study from our laboratory utilizing hydrogen-deuterium exchange (HDX) in concert with various mass spectrometry (MS) techniques has provided new information on the structure of microtubules upon Taxol binding. In the current study we apply this technique to determine the binding mode and the conformational effects on chicken erythrocyte tubulin (CET) of another MSA, discodermolide, whose synthetic analogues may have potential use in the clinic. We confirmed that, like Taxol, discodermolide binds to the taxane binding pocket in beta-tubulin. However, as opposed to Taxol, which has major interactions with the M-loop, discodermolide orients itself away from this loop and toward the N-terminal H1-S2 loop. Additionally, discodermolide stabilizes microtubules mainly via its effects on interdimer contacts, specifically on the alpha-tubulin side, and to a lesser extent on interprotofilament contacts between adjacent beta-tubulin subunits. Also, our results indicate complementary stabilizing effects of Taxol and discodermolide on the microtubules, which may explain the synergy observed between the two drugs in vivo.
Neurobiologists address neural structure, development, and function at the level of "macrocircuits" (how different brain compartments are interconnected; what overall pattern of activity they produce) and at the level of "microcircuits" (how connectivity and physiology of individual neurons and their processes within a compartment determine the functional output of this compartment). Work in our lab aims at reconstructing the developing Drosophila brain at both levels. Macrocircuits can be approached conveniently by reconstructing the pattern of brain lineages, which form groups of neurons whose projections form cohesive fascicles interconnecting the compartments of the larval and adult brain. The reconstruction of microcircuits requires serial section electron microscopy, due to the small size of terminal neuronal processes and their synaptic contacts. Because of the amount of labor that traditionally comes with this approach, very little is known about microcircuitry in brains across the animal kingdom. Many of the problems of serial electron microscopy reconstruction are now solvable with digital image recording and specialized software for both image acquisition and postprocessing. In this chapter, we introduce our efforts to reconstruct the small Drosophila larval brain and discuss our results in light of the published data on neuropile ultrastructure in other animal taxa.