Combinatorial in Vitro and in Silico Approach To Describe Shear-Force Dependent Uptake of Nanoparticles in Microfluidic Vascular Models.

In the present work, we combine experimental and computational methods to define the critical shear stress as an alternative parameter for nanotoxicological and nanomedical evaluations using an in vitro microfluidic vascular model. We demonstrate that our complementary in vitro and in silico approach is well suited to assess the fluid flow velocity above which clathrin-mediated (active) nanoparticle uptake per cell decreases drastically although higher numbers of nanoparticles per cell are introduced. Results of our study revealed a critical shear stress of 1.

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints.

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated.

Microfluidic Migration and Wound Healing Assay Based on Mechanically Induced Injuries of Defined and Highly Reproducible Areas.

All cell migration and wound healing assays are based on the inherent ability of adherent cells to move into adjacent cell-free areas, thus providing information on cell culture viability, cellular mechanisms and multicellular movements. Despite their widespread use for toxicological screening, biomedical research and pharmaceutical studies, to date no satisfactory technological solutions are available for the automated, miniaturized and integrated induction of defined wound areas. To bridge this technological gap, we have developed a lab-on-a-chip capable of mechanically inducing circular cell-free areas within confluent cell layers.

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

Background: Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too.

Trend analysis of performance parameters of pre-packed columns for protein chromatography over a time span of ten years.

Pre-packed small scale chromatography columns are increasingly used for process development, for determination of design space in bioprocess development, and for post-licence process verifications. The packing quality of 30,000 pre-packed columns delivered to customers over a period 10 years has been analyzed by advanced statistical tools. First, the data were extracted and checked for inconsistencies, and then were tabulated and made ready for statistical processing using the programming language Perl (https://www.

Which sets of elementary flux modes form thermodynamically feasible flux distributions?

Elementary flux modes (EFMs) are non-decomposable steady-state fluxes through metabolic networks. Every possible flux through a network can be described as a superposition of EFMs. The definition of EFMs is based on the stoichiometry of the network, and it has been shown previously that not all EFMs are thermodynamically feasible.

Designing minimal microbial strains of desired functionality using a genetic algorithm.

Background: The rational, in silico prediction of gene-knockouts to turn organisms into efficient cell factories is an essential and computationally challenging task in metabolic engineering. Elementary flux mode analysis in combination with constraint minimal cut sets is a particularly powerful method to identify optimal engineering targets, which will force an organism into the desired metabolic state. Given an engineering objective, it is theoretically possible, although computationally impractical, to find the best minimal intervention strategies.

Exact quantification of cellular robustness in genome-scale metabolic networks.

Motivation: Robustness, the ability of biological networks to uphold their functionality in spite of perturbations, is a key characteristic of all living systems. Although several theoretical approaches have been developed to formalize robustness, it still eludes an exact quantification. Here, we present a rigorous and quantitative approach for the structural robustness of metabolic networks by measuring their ability to tolerate random reaction (or gene) knockouts.

ICT: isotope correction toolbox.

Summary: Isotope tracer experiments are an invaluable technique to analyze and study the metabolism of biological systems. However, isotope labeling experiments are often affected by naturally abundant isotopes especially in cases where mass spectrometric methods make use of derivatization. The correction of these additive interferences--in particular for complex isotopic systems--is numerically challenging and still an emerging field of research.

Avoiding the Enumeration of Infeasible Elementary Flux Modes by Including Transcriptional Regulatory Rules in the Enumeration Process Saves Computational Costs.

Despite the significant progress made in recent years, the computation of the complete set of elementary flux modes of large or even genome-scale metabolic networks is still impossible. We introduce a novel approach to speed up the calculation of elementary flux modes by including transcriptional regulatory information into the analysis of metabolic networks. Taking into account gene regulation dramatically reduces the solution space and allows the presented algorithm to constantly eliminate biologically infeasible modes at an early stage of the computation procedure.

Predicting genetic engineering targets with Elementary Flux Mode Analysis: a review of four current methods.

Elementary flux modes (EFMs) are a well-established tool in metabolic modeling. EFMs are minimal, feasible, steady state pathways through a metabolic network. They are used in various approaches to predict targets for genetic interventions in order to increase production of a molecule of interest via a host cell.

Metabolomics integrated elementary flux mode analysis in large metabolic networks.

Elementary flux modes (EFMs) are non-decomposable steady-state pathways in metabolic networks. They characterize phenotypes, quantify robustness or identify engineering targets. An EFM analysis (EFMA) is currently restricted to medium-scale models, as the number of EFMs explodes with the network's size.

tEFMA: computing thermodynamically feasible elementary flux modes in metabolic networks.

Unlabelled: : Elementary flux modes (EFMs) are important structural tools for the analysis of metabolic networks. It is known that many topologically feasible EFMs are biologically irrelevant. Therefore, tools are needed to find the relevant ones.

Design of optimally constructed metabolic networks of minimal functionality.

Background: Metabolic engineering aims to design microorganisms that will generate a product of interest at high yield. Thus, a variety of in silico modeling strategies has been applied successfully, including the concepts of elementary flux modes (EFMs) and constrained minimal cut sets (cMCSs). The EFMs (minimal, steady state pathways through the system) can be calculated given a metabolic model.

Comparison and improvement of algorithms for computing minimal cut sets.

Background: Constrained minimal cut sets (cMCSs) have recently been introduced as a framework to enumerate minimal genetic intervention strategies for targeted optimization of metabolic networks. Two different algorithmic schemes (adapted Berge algorithm and binary integer programming) have been proposed to compute cMCSs from elementary modes. However, in their original formulation both algorithms are not fully comparable.

Fast computation of minimal cut sets in metabolic networks with a Berge algorithm that utilizes binary bit pattern trees.

Minimal cut sets are a valuable tool for analyzing metabolic networks and for identifying optimal gene intervention strategies by eliminating unwanted metabolic functions and keeping desired functionality. Minimal cut sets rely on the concept of elementary flux modes, which are sets of indivisible metabolic pathways under steady-state condition. However, the computation of minimal cut sets is nontrivial, as even medium-sized metabolic networks with just 100 reactions easily have several hundred million elementary flux modes.

Elementary flux modes in a nutshell: properties, calculation and applications.

Elementary flux mode (EFM) analysis allows the unbiased decomposition of a metabolic network into minimal functional units, making it a powerful tool for metabolic engineering. While the use of EFM analysis (EFMA) is still limited by the size of the models it can handle, EFMA has been successfully applied to solve real-world metabolic engineering problems. Here we provide a user-oriented introduction to EFMA, provide examples of recent applications, analyze current research strategies to overcome the computational restrictions and give an overview over current approaches, which aim to identify and calculate only biologically relevant EFMs.

regEfmtool: speeding up elementary flux mode calculation using transcriptional regulatory rules in the form of three-state logic.

Despite the considerable progress made in recent years, the computation of the complete set of elementary flux modes of large or even genome-scale metabolic networks is still impossible. We present regEfmtool which is an extension to efmtool that utilizes transcriptional regulatory networks for the computation of elementary flux modes. The implemented extension significantly decreases the computational costs for the calculation of elementary flux modes, such as runtime, memory usage and disk space by omitting biologically infeasible solutions.

Designing optimal cell factories: integer programming couples elementary mode analysis with regulation.

Background: Elementary mode (EM) analysis is ideally suited for metabolic engineering as it allows for an unbiased decomposition of metabolic networks in biologically meaningful pathways. Recently, constrained minimal cut sets (cMCS) have been introduced to derive optimal design strategies for strain improvement by using the full potential of EM analysis. However, this approach does not allow for the inclusion of regulatory information.

Rapid liposome quality assessment using a lab-on-a-chip.

Although liposomes have many outstanding features such as biocompatibility, biodegradability, low toxicity and structural diversity, and are successfully applied in many areas of chemistry and biotechnology, a lack of characterization standards and quality control tools are still inhibiting the translation of liposome technology into clinical routine. The greatest obstacle to clinical scale commercialization is the inability to ensure liposome formulation stability because small size variations or altered surface chemistries can significantly influence in vivo distribution and excretion kinetics that could in turn lead to unpredictable therapy outcomes. To enhance the product development process we have developed a microfluidic biochip containing embedded dielectric microsensors capable of providing quantitative results on formulation composition and stability based on the monitoring of the unique electric properties of liposomes.

Monitoring cellular stress responses to nanoparticles using a lab-on-a-chip.

As nanotechnology moves towards widespread commercialization, new technologies are needed to adequately address the potential health impact of nanoparticles (NPs). Assessing the safety of over 30,000 NPs through animal testing would not only be expensive, but it would also raise a number of ethical considerations. Furthermore, existing in vitro cell-based assays are not sufficient in scope to adequately address the complexity of cell-nanoparticle interactions including NP translocation, accumulation and co-transport of e.

3D numerical simulation of a lab-on-a-chip--increasing measurement sensitivity of interdigitated capacitors by passivation optimization.

Interdigital electrode structures (IDES) play a major role in many technical and analytical applications. In particular, they are a key technology in modern lab-on-a-chip (LOC) devices. As high sensitivity is a key component of any (bio)analytical method, the presented work is aimed at designing a novel dielectric sensing system, which exhibits maximum sensor sensitivity using passivated dielectric microsensors.

Development of a disposable microfluidic biochip for multiparameter cell population measurements.

An under recognized cause of preventable mortality is healthcare-associated (nosocomial) infections such as biofilms found on implants and catheters. About 5% of U.S.