Metabolic modeling of Rosmarinic acid biosynthetic pathway

Rosmarinic acid (RA) is an ester of caffeic acid and 3, 4-dihydroxyphenyllacticacid. It is commonly found in Coleus blumei, Salvia officinalis, Melissa officinalis and Rosmarinus officinalis. The biosynthesis of RA starts with precursor molecules L-phenylalanine and L-tyrosine. Simulation of RA biosynthetic pathway was done using Gepasi Software, includes the reaction kinetics of each step of the pathway and different integration methods such as Euler's method. Optimization of the significant parameters responsible for RA biosynthesis was carried out. As the goal of the work was to increase the productivity of i.e. to maximize the concentration of the RA, the final concentration of RA ([RA]t) was selected as an objective function and selected initial concentration of the Caffeoyl-3'-4'hydroxyphenyllactic acid (3'C4HPLA) as parameter constraint and varied its initial concentration as: 0≤ [3'C4HPLA]i ≤ 0.025. Several optimization methods such as Simulated annealing, Evolutionary algorithms and Genetic algorithms were used to optimize the objective function. After optimization the final concentration of RA was slightly higher (4.566132e-002 mM) than before optimization (4.047119e- 002 mM). On the basis of results obtained, it is clear that 4-hydroxyphenyllactic acid and 3'C4HPLA play major role in the high productivity of the RA.     

Sequence analysis and homology modeling of laccase from Pycnoporus cinnabarinus

Industrial effluents of textile, paper, and leather industries contain various toxic dyes as one of the waste material. It imparts major impact on human health as well as environment. The white rot fungus Pycnoporus cinnabarinus Laccase is generally used to degrade these toxic dyes. In order to decipher the mechanism of process by which Laccase degrade dyes, it is essential to know its 3D structure. Homology modeling was performed in presented work, by satisfying Spatial restrains using Modeller Program, which is considered as standard in this field, to generate 3D structure of Laccase in unison, SWISSMODEL web server was also utilized to generate and verify the alternative models. We observed that models created using Modeller stands better on structure evaluation tests. This study can further be used in molecular docking techniques, to understand the interaction of enzyme with its mediators like 2, 2-azinobis (3-ethylbenzthiazoline-6-sulfonate) (ABTS) and Vanillin that are known to enhance the Laccase activity.     

Integration of the effects of animal and dietary factors on total dry matter intake of dairy cows fed silage-based diets

An empirical regression model for the prediction of total dry matter intake (DMI) of dairy cows was developed and compared with four published intake models. The model was constructed to include both animal and dietary factors, which are known to affect DMI. For model development, a data set based on individual cow data from 10 change-over and four continuous milk production studies was collected (n = 1554). Relevant animal (live weight (LW), days in milk (DIM), parity and breed) and dietary (total and concentrate DMI, concentrate composition, forage digestibility and fermentation quality) data were collected. The model factors were limited to those that are available before the diets are fed to animals, that is, standardized energy corrected milk (sECM) yield, LW, DIM and diet quality (total diet DMI index (TDMI index)). As observed ECM yield is a function of both the production potential of the cow and diet quality, ECM yield standardized for DIM, TDMI index and metabolizable protein concentration was used in modelling. In the individual data set, correlation coefficients between sECM and TDMI index or DIM were much weaker (0.16 and 0.03) than corresponding coefficients with observed ECM (0.65 and 0.46), respectively. The model was constructed with a mixed model regression analysis using cow within trial as a random factor. The following mixed model was estimated for DMI prediction: DMI (kg DM/day) = -2.9 (±0.56)+0.258 (±0.011) × sECM (kg/day) + 0.0148 (±0.0009) × LW (kg) -0.0175 (±0.001) × DIM -5.85 (±0.41) × exp (-0.03 × DIM) + 0.09 (±0.002) × TDMI index. The mixed DMI model was evaluated with a treatment mean data set (207 studies, 992 diets), and the following relationship was found: Observed DMI (kg DM/day) = -0.10 (±0.33) + 1.004 (±0.019) × Predicted DMI (kg DM/day) with an adjusted residual mean square error of 0.362 kg/day. Evaluation of the residuals did not result in a significant mean bias or linear slope bias, and random error accounted for proportionally >0.99 of the error. In conclusion, the DMI model developed is considered robust because of low mean prediction error, accurate and precise validation, and numerically small differences in the parameter values of model variables when estimated with mixed or simple regression models. The Cornell Net Carbohydrate and Protein System was the most accurate of the four other published DMI models evaluated using individual or treatment mean data, but in most cases mean and linear slope biases were relatively high, and, interestingly, there were large differences in both mean and linear slope biases between the two data sets.     

COPD association and repeatability of blood biomarkers in the ECLIPSE cohort

Background

There is a need for biomarkers to better characterise individuals with COPD and to aid with the development of therapeutic interventions. A panel of putative blood biomarkers was assessed in a subgroup of the Evaluation of COPD Longitudinally to Identify Surrogate Endpoints (ECLIPSE) cohort.

Methods

Thirty-four blood biomarkers were assessed in 201 subjects with COPD, 37 ex-smoker controls with normal lung function and 37 healthy non-smokers selected from the ECLIPSE cohort. Biomarker repeatability was assessed using baseline and 3-month samples. Intergroup comparisons were made using analysis of variance, repeatability was assessed through Bland-Altman plots, and correlations between biomarkers and clinical characteristics were assessed using Spearman correlation coefficients.

Results

Fifteen biomarkers were significantly different in individuals with COPD when compared to former or non-smoker controls. Some biomarkers, including tumor necrosis factor-α and interferon-γ, were measurable in only a minority of subjects whilst others such as C-reactive protein showed wide variability over the 3-month replication period. Fibrinogen was the most repeatable biomarker and exhibited a weak correlation with 6-minute walk distance, exacerbation rate, BODE index and MRC dyspnoea score in COPD subjects. 33% (66/201) of the COPD subjects reported at least 1 exacerbation over the 3 month study with 18% (36/201) reporting the exacerbation within 30 days of the 3-month visit. CRP, fibrinogen interleukin-6 and surfactant protein-D were significantly elevated in those COPD subjects with exacerbations within 30 days of the 3-month visit compared with those individuals that did not exacerbate or whose exacerbations had resolved.

Conclusions

Only a few of the biomarkers assessed may be useful in diagnosis or management of COPD where the diagnosis is based on airflow obstruction (GOLD). Further analysis of more promising biomarkers may reveal utility in subsets of patients. Fibrinogen in particular has emerged as a potentially useful biomarker from this cohort and requires further investigation.

Trial Registration

SCO104960, clinicaltrials.gov identifier {"type":"clinical-trial","attrs":{"text":"NCT00292552","term_id":"NCT00292552"}}NCT00292552     

Cellular aging leads to functional heterogeneity of hematopoietic stem cells: a modeling perspective

Hematopoietic stem cells (HSCs) are the source for the life-long supply of functional cells in peripheral blood while they simultaneously maintain their own reserve pool. However, there is accumulating evidence that HSCs are themselves subject to quantitative and qualitative exhaustion. Although several processes linked to mitotic activity can potentially account for the observed aging phenomena (e.g., DNA damage, telomere shortening, epigenetic modification), a precise understanding of HSC exhaustion is still missing. It is particularly unclear how individual aging processes on the single-cell level translate on the phenotypic level of the overall tissue and whether there is a functional implication of an age-structured HSC population. We address these issues by applying a novel mathematical model of HSC organization in which division-specific, cumulative alterations of stem cell quality determine the phenotypic and functional appearance of the overall cell population. Adapting the model to a number of basic experimental findings, we quantify the level of additional heterogeneity that is introduced by a population of individually aging cells. Based on this model, we are able to conclude that division-dependent processes of cellular aging explain a wide range of phenomena on HSC exhaustion and that HSC aging needs to be considered as a highly heterogeneous process. We furthermore report that functional heterogeneity between young and old HSCs appears closely similar to the phenomena described for long- and short-term repopulating cells. We speculate whether differential, division-coupled stem cell aging introduces an intra-animal variability that also accounts for heterogeneity with respect to the repopulation ability of HSCs.     

Homology modeling and consensus protein disorder prediction of human filamin

Filamins are dimeric actin-binding proteins participating in the organization of the actin-based cytoskeleton. Their modular domain organization is made up of an N-terminal actin-binding domain composed of two CH domains followed by flexible rod regions that consist of 24 Ig-like domains. Homology modeling was used to model human filamin using Modeller 9v5. The resulting model assessed by Verify 3D and PROCHECK showed that the final model is reliable. The conformational disorder prediction of human filamin residues were also mapped on the validated structure of human filamin. Prediction of protein disorder in filamin structures will help structural biologists to find suitable targets to be analyzed and for understanding protein function.     

A rapid protein structure alignment algorithm based on a text modeling technique

Structural alignment of proteins is widely used in various fields of structural biology. In order to further improve the quality of alignment, we describe an algorithm for structural alignment based on text modelling techniques. The technique firstly superimposes secondary structure elements of two proteins and then, models the 3D-structure of the protein in a sequence of alphabets. These sequences are utilized by a step-by-step sequence alignment procedure to align two protein structures. A benchmark test was organized on a set of 200 non-homologous proteins to evaluate the program and compare it to state of the art programs, e.g. CE, SAL, TM-align and 3D-BLAST. On average, the results of all-against-all structure comparison by the program have a competitive accuracy with CE and TM-align where the algorithm has a high running speed like 3D-BLAST.     

Using Sculptor and Situs for simultaneous assembly of atomic components into low-resolution shapes

We describe an integrated software system called Sculptor that combines visualization capabilities with molecular modeling algorithms for the analysis of multi-scale data sets. Sculptor features extensive special purpose visualization techniques that are based on modern GPU programming and are capable of representing complex molecular assemblies in real-time. The integration of graphics and modeling offers several advantages. The user interface not only eases the usually steep learning curve of pure algorithmic techniques, but it also permits instant analysis and post-processing of results, as well as the integration of results from external software. Here, we implemented an interactive peak-selection strategy that enables the user to explore a preliminary score landscape generated by the colors tool of Situs. The interactive placement of components, one at a time, is advantageous for low-resolution or ambiguously shaped maps, which are sometimes difficult to interpret by the fully automatic peak selection of colors. For the subsequent refinement of the preliminary models resulting from both interactive and automatic peak selection, we have implemented a novel simultaneous multi-body docking in Sculptor and Situs that softly enforces shape complementarities between components using the normalization of the cross-correlation coefficient. The proposed techniques are freely available in Situs version 2.6 and Sculptor version 2.0.     

Plastic microfluidic chip for continuous-flow polymerase chain reaction: simulations and experiments

A continuous flow polymerase chain reaction (CF-PCR) device comprises a single fluidic channel that is heated differentially to create spatial temperature variations such that a sample flowing through it experiences the thermal cycling required to induce amplification. This type of device can provide an effective means to detect the presence of a small amount of nucleic acid in very small sample volumes. CF-PCR is attractive for global health applications due to its less stringent requirements for temperature control than for other designs. For mass production of inexpensive CF-PCR devices, fabrication via thermoplastic molding will likely be necessary. Here we study the optimization of a PCR assay in a polymeric CF-PCR device. Three channel designs, with varying residence time ratios for the three PCR steps (denaturation, annealing, and extension), were modeled, built, and tested. A standardized assay was run on the three different chips, and the PCR yields were compared. The temperature gradient profiles of the three designs and the residence times of simulated DNA molecules flowing through each temperature zone were predicted using computational methods. PCR performance predicted by simulation corresponded to experimental results. The effects of DNA template size and cycle time on PCR yield were also studied. The experiments and simulations presented here guided the CF-PCR chip design and provide a model for predicting the performance of new CF-PCR designs prior to actual chip manufacture, resulting in faster turn around time for new device and assay design. Taken together, this framework of combined simulation and experimental development has greatly reduced assay development time for CF-PCR in our lab.