ALBERT

Description: Background: The calculation of diffusion-controlled ligand binding rates is important for understanding enzyme mechanisms as well as designing enzyme inhibitors. Methods: We demonstrate the accuracy and effectiveness of a Lagrangian particle-based method, smoothed particle hydrodynamics (SPH), to study diffusion in biomolecular systems by numerically solving the time-dependent Smoluchowski equation for continuum diffusion. Unlike previous studies, a reactive Robin boundary condition (BC), rather than the absolute absorbing (Dirichlet) BC, is considered on the reactive boundaries. This new BC treatment allows for the analysis of enzymes with “imperfect” reaction rates. Results: The numerical method is first verified in simple systems and then applied to the calculation of ligand binding to a mouse acetylcholinesterase (mAChE) monomer. Rates for inhibitor binding to mAChE are calculated at various ionic strengths and compared with experiment and other numerical methods. We find that imposition of the Robin BC improves agreement between calculated and experimental reaction rates. Conclusions: Although this initial application focuses on a single monomer system, our new method provides a framework to explore broader applications of SPH in larger-scale biomolecular complexes by taking advantage of its Lagrangian particle-based nature.

Description: Background: Utilizing kinetic models of biological systems commonly require computational approaches to estimate parameters, posing a variety of challenges due to their highly non-linear and dynamic nature, which is further complicated by the issue of non-identifiability. We propose a novel parameter estimation framework by combining approaches for solving identifiability with a recently introduced filtering technique that can uniquely estimate parameters where conventional methods fail. This framework first conducts a thorough analysis to identify and classify the non-identifiable parameters and provides a guideline for solving them. If no feasible solution can be found, the framework instead initializes the filtering technique with informed prior to yield a unique solution. Results: This framework has been applied to uniquely estimate parameter values for the sucrose accumulation model in sugarcane culm tissue and a gene regulatory network. In the first experiment the results show the progression of improvement in reliable and unique parameter estimation through the use of each tool to reduce and remove non-identifiability. The latter experiment illustrates the common situation where no further measurement data is available to solve the non-identifiability. These results show the successful application of the informed prior as well as the ease with which parallel data sources may be utilized without increasing the model complexity. Conclusion: The proposed unified framework is distinct from other approaches by providing a robust and complete solution which yields reliable and unique parameter estimation even in the face of non-identifiability.

Description: Proteins generally perform their function in a folded state. Residues forming an active site, whether it is a catalytic center or interaction interface, are frequently distant in a protein sequence. Hence, tra...

Description: The practice of counting bacterial colony forming units on agar plates has long been used as a method to estimate the concentration of live bacteria in culture. However, due to the laborious and potentially er...

Description: Background: Sorghum (Sorghum bicolor L. Moench) cultivars store non-structural carbohydrates predominantly as either starch in seeds (grain sorghums) or sugars in stems (sweet sorghums). Previous research determined that sucrose accumulation in sweet sorghum stems was not correlated with the activities of enzymes functioning in sucrose metabolism, and that an apoplasmic transport step may be involved in stem sucrose accumulation. However, the sucrose unloading pathway from stem phloem to storage parenchyma cells remains unelucidated. Sucrose transporters (SUTs) transport sucrose across membranes, and have been proposed to function in sucrose partitioning differences between sweet and grain sorghums. The purpose of this study was to characterize the key differences in carbohydrate accumulation between a sweet and a grain sorghum, to define the path sucrose may follow for accumulation in sorghum stems, and to determine the roles played by sorghum SUTs in stem sucrose accumulation. Results: Dye tracer studies to determine the sucrose transport route revealed that, for both the sweet sorghum cultivar Wray and grain sorghum cultivar Macia, the phloem in the stem veins was symplasmically isolated from surrounding cells, suggesting sucrose was apoplasmically unloaded. Once in the phloem apoplasm, a soluble tracer diffused from the vein to stem parenchyma cell walls, indicating the lignified mestome sheath encompassing the vein did not prevent apoplasmic flux outside of the vein. To characterize carbohydrate partitioning differences between Wray and Macia, we compared the growth, stem juice volume, solute contents, SbSUTs gene expression, and additional traits. Contrary to previous findings, we detected no significant differences in SbSUTs gene expression within stem tissues. Conclusions: Phloem sieve tubes within sweet and grain sorghum stems are symplasmically isolated from surrounding cells; hence, unloading from the phloem likely occurs apoplasmically, thereby defining the location of the previously postulated step for sucrose transport. Additionally, no changes in SbSUTs gene expression were detected in sweet vs. grain sorghum stems, suggesting alterations in SbSUT transcript levels do not account for the carbohydrate partitioning differences between cultivars. A model illustrating sucrose phloem unloading and movement to stem storage parenchyma, and highlighting roles for sucrose transport proteins in sorghum stems is discussed.

Description: The calculation of diffusion-controlled ligand binding rates is important for understanding enzyme mechanisms as well as designing enzyme inhibitors.

Description: Kawasaki Disease (KD) can cause potentially life-threatening coronary arteritis in young children, and has a likely infectious etiology. Transcriptome profiling is a powerful approach to investigate gene expre...

Description: Background: Daily rhythms in mammals are programmed by a master clock in the suprachiasmatic nucleus (SCN). The SCN contains two main compartments (i.e., shell and core), but the role of each region in system-level coordination remains ill defined. Here we use a functional assay to investigate how downstream tissues interpret region-specific outputs by using in vivo exposure to long day photoperiods to temporally dissociate the SCN. We then analyze resulting changes in the rhythms of clocks located throughout the brain and body to examine whether they maintain phase synchrony with the SCN shell or core. Results: Nearly all of the 17 tissues examined in the brain and body maintain phase synchrony with the SCN shell, but not the SCN core, which indicates that downstream oscillators are set by cues controlled specifically by the SCN shell. Interestingly, we also found that SCN dissociation diminished the amplitude of rhythms in core clock gene and protein expression in brain tissues by 50–75 %, which suggests that light-driven changes in the functional organization of the SCN markedly influence the strength of rhythms in downstream tissues. Conclusions: Overall, our results reveal that body clocks receive time-of-day cues specifically from the SCN shell, which may be an adaptive design principle that serves to maintain system-level phase relationships in a changing environment. Further, we demonstrate that lighting conditions alter the amplitude of the molecular clock in downstream tissues, which uncovers a new form of plasticity that may contribute to seasonal changes in physiology and behavior.

Description: Background: Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology. Results: We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86 %, 94.11 %, 84.31 %, 94.30 % and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB. Conclusion: PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

Description: No description available