Spatial Analysis and Modeling Tool (SAMT): 2. Applications

The Spatial Analysis and Modeling Tool (SAMT) is a GIS-based analytical software for land use study. This paper demonstrates the capabilities of SAMT as applied in studies of land use and landscape change in the catchment area of the River Quillow, North-East Germany. Neural network and fuzzy models are important features that were incorporated in SAMT. The region of study for this application is a catchment area of about 170 km² and is subdivided into 54,000 grid cells for spatial simulations.Three different applications of SAMT are discussed in this article. The first application involves assessment of the potential soil erosion risk on arable land. This user-defined application combines an economic model (LP model), a temperature-driven crop coverage model and a soil erosion risk model (Universal Soil Loss Equation) using data from tables and map information. The second and third applications are winter wheat yield estimates using, respectively, the fuzzy toolbox SAMT_FUZZY in conjunction with expert knowledge, and using the neural network toolbox SAMT_NN based on observations.     

Unveiling the molecular crosstalk in a human induced pluripotent stem cell-derived cardiac model

In vitro cell-based models that better mimic the human heart tissue are of utmost importance for drug development and cardiotoxicity testing but also as tools to understand mechanisms related with heart disease at cellular and molecular level. Besides, the implementation of analytical tools that allow the depiction and comprehensive understanding of the molecular mechanisms of the crosstalk between the different cell types is also relevant. In this work, we implemented a human cardiac tissue-like in vitro model, derived from human-induced pluripotent stem cell (hiPSC), and evaluated the relevance of the cell–cell communication between the two of the most representative cell populations of the human heart: cardiomyocytes (hiPSC-CM) and endothelial cells (hiPSC-EC). We observed that heterotypic cell communication promotes: (a) structural maturation of hiPSC-CM and (b) deposition of several extracellular matrix components (such as collagens and fibronectin). Overall, the toolbox of analytical techniques used in our study not only enabled us to validate previous reports from the literature on the importance of the presence of hiPSC-EC on hiPSC-CM maturation, but also bring new insights on the molecular mechanisms involved in the communication between these two cell types when cocultured in vitro.     

Metabolic network simulation using logical loop algorithm and Jacobian matrix

A novel method to accomplish efficient numerical simulation of metabolic networks for flux analysis was developed. The only inputs required are the set of stoichiometric balances and the atom mapping matrices of all components of the reaction network. The latter are used to automatically calculate isotopomer mapping matrices. Using the symbolic toolbox of MATLAB the analytical solution of the stoichiometric balance equation system, isotopomer balances and the analytical Jacobian matrix of the total set of stoichiometric and isotopomer balances are created automatically. The number of variables in the isotopomer distribution equation system is significantly reduced applying modified isotopomer mapping matrices. These allow lumping of several consecutive isotopomer reactions into a single one. The solution of the complete system of equations is improved by implementing an iterative logical loop algorithm and using the analytical Jacobian matrix. This new method provided quick and robust convergence to the root of such equation systems in all cases tested. The method was applied to a network of lysine producing Corynebacterium glutamicum. The resulting equation system with the dimension of 546 x 546 was directly derived from 12 isotopomer balance equations. The results obtained yielded identical labeling patterns for metabolites as compared to the relaxation method.     

Analytical approaches to determine cytochrome P450 inhibitory potential of new chemical entities in drug discovery

The use of a cassette incubation of probe substrates with human liver microsomes (HLM) - also known as the 'cocktail' approach - is becoming a widely accepted approach to determine the interaction of new chemical entities (NCEs) with cytochrome P450 enzymes (CYP450) in early drug discovery. This article describes two LC-MS/MS-based analytical methods used at the high-throughput (HT) stage and late discovery (LD) stage for analysis of 'cocktail' incubates to analyze the probe metabolites 1'-hydroxymidazolam (CYP3A4), 4'-hydroxydiclofenac (CYP2C9), dextrorphan (CYP2D6), 1'-hydroxytacrine (CYP1A2) and 4'-hydroxymephenytoin (CYP2C19). The analytical methods are advantageous over currently reported methods due to their sensitivity, shorter analyses times (<2 min/sample for the HT method and 4 min/sample for the LD method) and their ability to monitor a unique set of clinically relevant probe metabolites from a biological incubate containing low microsomal protein (0.1mg/mL). The analytical methods employ the same mobile phase, acetonitrile and 0.1% formic acid, under similar LC-MS/MS conditions. In the HT method, the chromatographic method consists of a short robust step-gradient where the probe metabolites are simultaneously and quickly eluted to enhance throughput. The probe metabolites are chromatographically resolved in the LD stage by utilizing a true linear gradient to obtain optimal peak separation. The IC50 data generated by both analytical methods using single incubations versus cocktail incubations for various test compounds are in good agreement (correlation coefficient (r2)>or=0.98). The scientist conducting the analysis is provided with a choice of method selection depending on the stage of the test compound and on whether throughput or minimizing interference from other co-eluting metabolites is the most important criterion.     

Chromatography-based on- and in-line pre-concentration methods in capillary electrophoresis

Capillary electrophoresis (CE) poses unique challenges in many different analytical applications, mainly to biological and complex samples and when only small amounts of sample are available, due to its low sample consumption. As a consequence, poor limits of detection are usually observed with this technique, especially with UV photodetectors. Minimal or no sample treatment is desirable in any analytical method to avoid external sources of contamination or errors and to provide a high throughput. On- and in-capillary sample pre-concentration strategies, based on solid-phase extraction (SPE) technology can take advantage of both techniques (SPE and CE), while avoiding sample contamination and tedious manipulations when the sample amount is an issue. Moreover, the combination can provide two-dimensional separations. This review collects the most recent strategies that merge SPE technology built on- and in-capillary pre-concentration for increasing sensitivity and/or selectivity.     

Chromatography-based on- and in-line pre-concentration methods in capillary electrophoresis

Capillary electrophoresis (CE) poses unique challenges in many different analytical applications, mainly to biological and complex samples and when only small amounts of sample are available, due to its low sample consumption. As a consequence, poor limits of detection are usually observed with this technique, especially with UV photodetectors. Minimal or no sample treatment is desirable in any analytical method to avoid external sources of contamination or errors and to provide a high throughput. On- and in-capillary sample pre-concentration strategies, based on solid-phase extraction (SPE) technology can take advantage of both techniques (SPE and CE), while avoiding sample contamination and tedious manipulations when the sample amount is an issue. Moreover, the combination can provide two-dimensional separations. This review collects the most recent strategies that merge SPE technology built on- and in-capillary pre-concentration for increasing sensitivity and/or selectivity.     

Cutting-edge multi-level analytical and structural characterization of antibody-drug conjugates: present and future

Introduction: The development and optimization of antibody drug conjugates (ADCs) rely on improving their analytical and bioanalytical characterization, by assessing critical quality attributes (CQAs). Among the CQAs, the glycoprofile, drug load distribution (DLD), the amount of unconjugated antibody (D0), the average drug-to-antibody ratio (DAR), the drug conjugation sites and the residual drug-linker and related product proportions (SMDs) in addition to high and low molecular weight species (H/LMWS), and charge variants are the most important ones.

Areas covered: The analytical and structural toolbox for the characterization of 1^st, 2^d and 3^d generation ADCs was significantly extended in the last 3 years. Here, we reviewed state-of-the-art techniques, such as liquid chromatography, high resolution native and ion mobility mass spectrometry, multidimensional liquid chromatography and capillary electrophoresis hyphenated to mass spectrometry, reported mainly since 2016.

Expert commentary: These emerging techniques allow a deep insight into important CQAs that are related to ADC Chemistry Manufacturing and Control (CMC) as well as an improved understanding of in vitro and in vivo ADC biotransformations. This knowledge and the development of quantitative bioanalytical assays will continue to contribute to early-developability assessment for the optimization of all the ADC components (i.e. antibody, drug, and linker) and help to bring next-generation ADCs into late clinical development and to the market.     

Evaluation of the total antioxidant capacity by using a multipumping flow system with chemiluminescent detection

An automated flow-based procedure for assessment of total antioxidant capacity was developed. It involved a multipumping flow system, a recent approach to flow analysis, and exploited the ability of selected compounds to inhibit the chemiluminescence reactions of luminol or lucigenin with hydrogen peroxide. The system included several discretely actuated solenoid micropumps as the only active components of the flow manifold. This enabled the reproducible insertion and efficient mixing of very low volumes of sample and reagents as well as the transportation of the sample zone toward a flow-through luminometer, where the chemiluminometric response was monitored. With luminol as the chemiluminogenic reagent, linearity of the analytical curves was noted up to 3.2x10(-4), 1.1x10(-3), and 8.8x10(-8) molL-1 for Trolox, ascorbic acid, and resveratrol, respectively. With lucigenin, linear calibration plots up to 2x10(-5) molL-1 of Trolox and 5.7x10(-5)molL-1 of ascorbic acid were obtained. As favorable analytical figures of merit, the measurement precision (RSD typically between 0.2 and 2.0%, n=10), low operational costs, low reagent consumption, sampling rate (160 and 70 h-1), and versatility should be highlighted. The proposed system can be used in distinct analytical circumstances without requiring physical reconfiguration.     

Microarray Data Analysis Toolbox (MDAT): for normalization, adjustment and analysis of gene expression data

SUMMARY: We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression based on five statistical measures. The objects in this toolbox are open source and can be implemented to suit your application. AVAILABILITY: MDAT v1.0 is a Matlab toolbox and requires Matlab to run. MDAT is freely available at http://microarray.omrf.org/publications/2004/knowlton/MDAT.zip.     

Proteomic analysis of lipid microdomains from lipopolysaccharide-activated human endothelial cells

The endothelium plays a critical role in orchestrating the inflammatory response seen during sepsis. Many of the inflammatory effects of Gram-negative sepsis are elicited by lipopolysaccharide (LPS), a glycolipid component of bacterial cell walls. Lipid-rich microdomains have been shown to concentrate components of the LPS signaling system. However, much remains to be learned about which proteins are constituents of lipid microdomains, and how these are regulated following cell activation. Progress in this area would be accelerated by employing global proteomic analyses, but the hydrophobicity of membrane proteins presents an analytical barrier to the effective application of such approaches. Herein, we describe a method to isolate detergent-resistant membranes from endothelial cells, and prepare these samples for proteomic analysis in a way that is compatible with subsequent separations and mass spectrometric (MS) analysis. In the application of these sample preparation and MS analyses, 358 proteins from the lipid-rich microdomains of LPS-activated endothelial cell membranes have been identified of which half are classified as membrane proteins by Gene Ontology. We also demonstrate that the sample preparation method used for solubilization and trypsin digestion of lipid-rich microdomains renders the membrane spanning sequences of transmembrane proteins accessible for endoproteolytic hydrolysis. This analysis sets the analytical foundation for an in-depth probing of LPS signaling in endothelial cells.     

Application of recurrent neural network for online prediction of cell density of recombinant Pichia pastoris producing HBsAg

Abstract

Artificial neural networking (ANN) seems to be a promising soft sensor for implementing current approaches of quality by design (QbD) and process analytical technologies (PAT) in the biopharmaceutical industry. In this study, we aimed to implement best-fitted ANN architecture for online prediction of the biomass amount of recombinant Pichia pastoris (P. pastoris) – expressing intracellular hepatitis B surface antigen (HBsAg) – during the fed-batch fermentation process using methanol as a sole carbon source. For this purpose, at the induction phase of methanol fed-batch fermentation, carbon evolution rate (CER), dissolved oxygen (DO), and methanol feed rate were selected as input vectors and total wet cell weight (WCW) was considered as output vector for the ANN. The obtained results indicated that after training recurrent ANN with data sets of four fed-batch runs, this toolbox could predict the WCW of the next fed-batch fermentation process at each specified time point with high accuracy. The R-squared and root-mean-square error between actual and predicted values were found to be 0.9985 and 13.73, respectively. This verified toolbox could have major importance in the biopharmaceutical industry since recombinant P. pastoris is widely used for the large-scale production of HBsAg.     

High-performance liquid chromatographic determination of finasteride in human plasma using direct injection with column switching

A fully automated column-switching high-performance liquid chromatographic (HPLC) method was developed for the quantification of finasteride [N-(1,1-dimethylethyl)-3-oxo-4-aza-5α-androst-1-ene-17β-carboxamide] in human plasma. Plasma samples were diluted with an equal volume of ethylene glycol-water (40:60, v/v), then the diluted sample (150 μl) was injected into the HPLC system without clean-up. The analyte was retained on a pretreatment column, whereas plasma proteins and other endogenous components were washed out to waste. The analyte was transferred to the analytical column in the heart-cut mode and then detected at 210 nm. A quantification limit of 1 ng/ml was attained. There was a linear relationship between peak height and drug concentration in plasma in the range 1–50 ng/ml. This method was validated and applied to the assay of plasma samples to characterize pharmacokinetic parameters in clinical studies.     

Determination of Ro 23-7637 in dog plasma by multidimensional ion-exchange—reversed-phase high-performance liquid chromatography with ultraviolet detection

Ro 23-7637 (I) is a new drug under development for the treatment of metabolic diseases. A high-performance liquid chromatographic—ultraviolet detection (HPLC—UV) analytical procedure for its analysis in dog plasma was developed and is reported here. Following C₁₈ solid-phase extraction, the sample is applied to a strong cation-exchange column in the first dimension. The analyte and internal standard, Ro 24-4558 (II), are transferred to a base-deactivated C₁₈ reversed-phase column in the second dimension (orthogonal separation mechanism), with UV detection at 254 nm. The reversed-phase solid-phase extraction provides a gross isolation of the drug, based on hydrophobicity. The first-dimension ion-exchange separation allows neutral species and anions to elute with the column void volume, while separating basic species according to pK_a. The second dimension provides a high-resolution separation dependent upon the hydrophobicity of the sample species. The rationale for using orthogonal multidimensional chromatography was that an exhaustive examination of reversed-phase and normal-phase columns invariably resulted in co-elution of I with endogenous plasma components, which limited the sensitivity of the method. We have utilized C₁₈ solid-phase extraction, followed by multidimensional HPLC—UV, to develop an accurate and precise analytical method whose limit of quantitation, 5 ng/ml using 0.5 ml of plasma, is determined by inherent detector sensitivity. Increased sensitivity can be readily achieved by using more sample or by using microbore HPLC on the second dimension.     

Sampling volatile compounds from natural products with headspace/solid-phase micro-extraction

Recent advances in the development of analytical methods based on headspace/solid-phase micro-extraction (HS/SPME) of natural aroma compounds are reviewed, with special emphasis on increasing reproducibility. Representative examples of applications of HS/SPME to the determination of components at trace levels, strategies for fiber selection, and improvement of SPME sampling conditions are presented. Examples of applications to quality control and sample classification, based on aroma profiling were selected to highlight the use of multivariate statistical methods.     

Sampling volatile compounds from natural products with headspace/solid-phase micro-extraction

Recent advances in the development of analytical methods based on headspace/solid-phase micro-extraction (HS/SPME) of natural aroma compounds are reviewed, with special emphasis on increasing reproducibility. Representative examples of applications of HS/SPME to the determination of components at trace levels, strategies for fiber selection, and improvement of SPME sampling conditions are presented. Examples of applications to quality control and sample classification, based on aroma profiling were selected to highlight the use of multivariate statistical methods.     

A part toolbox to tune genetic expression in Bacillus subtilis

Libraries of well-characterised components regulating gene expression levels are essential to many synthetic biology applications. While widely available for the Gram-negative model bacterium Escherichia coli, such libraries are lacking for the Gram-positive model Bacillus subtilis, a key organism for basic research and biotechnological applications. Here, we engineered a genetic toolbox comprising libraries of promoters, Ribosome Binding Sites (RBS), and protein degradation tags to precisely tune gene expression in B. subtilis. We first designed a modular Expression Operating Unit (EOU) facilitating parts assembly and modifications and providing a standard genetic context for gene circuits implementation. We then selected native, constitutive promoters of B. subtilis and efficient RBS sequences from which we engineered three promoters and three RBS sequence libraries exhibiting ∼14 000-fold dynamic range in gene expression levels. We also designed a collection of SsrA proteolysis tags of variable strength. Finally, by using fluorescence fluctuation methods coupled with two-photon microscopy, we quantified the absolute concentration of GFP in a subset of strains from the library. Our complete promoters and RBS sequences library comprising over 135 constructs enables tuning of GFP concentration over five orders of magnitude, from 0.05 to 700 μM. This toolbox of regulatory components will support many research and engineering applications in B. subtilis.     

A luminescent oxygen channeling immunoassay for the determination of insulin in human plasma

The authors describe a homogeneous, sensitive, and rapid bead-based sandwich immunoassay with a broad analytical range for quantifying insulin in human plasma. The assay was performed as a 2-step reaction by incubating the sample with a mixture of biotinylated anti-insulin antibody and beads covalently coated with anti-insulin antibody for 1 h. This was followed by incubation with beads covalently coated with streptavidin for 30 min. After the incubation steps, light generated from a chemiluminescent reaction within the beads was quantitated. The assay was run in 384-well plates with a sample volume of 5 microL. The analytical range extended from 1 to 10,000 pM. Intra-assay precision (% coefficient of variation) ranged from 1.9% to 3.8% for various insulin concentrations. Interassay precision ranged from 4.6% to 7.3%. Assay detection limit was 0.3 pM. There was no interference from moderate hemolysis (with hemoglobin up to 375 mg/dL), bilirubin (up to at least 50 mg/dL), triglyceride (up to at least 1000 mg/dL), biotin (up to at least 7.7 ng/mL), or ascorbic acid (up to 100 mg/dL). However, gross hemolysis did affect the assay. Comparable results were obtained for plasma (ethylenediamine tetra-acetic acid, citrate, and heparin treated) and serum. The correlation with enzyme-linked immunosorbent assay (ELISA) was good (y = 1.25x + 1.19, R(2) = 0.98). This method is convenient and represents an alternative to ELISA.