Genome-scale in silico metabolic networks of Escherichia coli have been reconstructed. By using a constraintbased in silico model of a reconstructed network, the range of phenotypes exhibited by E. coli under different growth conditions can be computed, and optimal growth phenotypes can be predicted. We hypothesized that the end point of adaptive evolution of E. coli could be accurately described a priori by our in silico model since adaptive evolution should lead to an optimal phenotype. Adaptive evolution of E. coli during prolonged exponential growth was performed with M9 minimal medium supplemented with 2 g of ␣-ketoglutarate per liter, 2 g of lactate per liter, or 2 g of pyruvate per liter at both 30 and 37°C, which produced seven distinct strains. The growth rates, substrate uptake rates, oxygen uptake rates, by-product secretion patterns, and growth rates on alternative substrates were measured for each strain as a function of evolutionary time. Three major conclusions were drawn from the experimental results. First, adaptive evolution leads to a phenotype characterized by maximized growth rates that may not correspond to the highest biomass yield. Second, metabolic phenotypes resulting from adaptive evolution can be described and predicted computationally. Third, adaptive evolution on a single substrate leads to changes in growth characteristics on other substrates that could signify parallel or opposing growth objectives. Together, the results show that genome-scale in silico metabolic models can describe the end point of adaptive evolution a priori and can be used to gain insight into the adaptive evolutionary process for E. coli.Biological systems are fundamentally complex, and thus a systems approach is necessary to account for the diversity of interactions that can occur among the myriad of molecular components that comprise living cells (1,5,14). The use of genome-scale metabolic reconstructions of an organism may prove to be a valuable tool in attempts to account for biological complexity and to elucidate the genotype-phenotype relationship. The annotation of full microbial genome sequences (2, 7) has enabled reconstruction of whole-cell metabolic networks (5,15,19,29). By using these reconstructed networks, detailed analyses of specific biological functions and system properties have been performed (11,12,21,25,27,31). In addition, numerous different in silico approaches have been developed and are available to analyze the properties of metabolic networks (11,16,24,28,34,36). While the rationales underlying the various methods are becoming widely accepted, there still has been limited prospective experimental verification of genome-scale in silico models with regard to their abilities to interpret and predict complex biological processes, such as adaptive evolution.In several studies the workers have productively combined computational and experimental approaches (4,17,32,33). In these studies, the in silico models were constructed and used to analyze specific metabolic subsystems accounting for ...
Conventional methods for the isolation of cancer-related circulating cell-free (ccf) DNA from patient blood (plasma) are time consuming and laborious. A DEP approach utilizing a microarray device now allows rapid isolation of ccf-DNA directly from a small volume of unprocessed blood. In this study, the DEP device is used to compare the ccf-DNA isolated directly from whole blood and plasma from 11 chronic lymphocytic leukemia (CLL) patients and one normal individual. Ccf-DNA from both blood and plasma samples was separated into DEP high-field regions, after which cells (blood), proteins, and other biomolecules were removed by a fluidic wash. The concentrated ccf-DNA was detected on-chip by fluorescence, and then eluted for PCR and DNA sequencing. The complete process from blood to PCR required less than 10 min; an additional 15 min was required to obtain plasma from whole blood. Ccf-DNA from the equivalent of 5 µL of CLL blood and 5 µL of plasma was amplified by PCR using Ig heavy-chain variable (IGHV) specific primers to identify the unique IGHV gene expressed by the leukemic B-cell clone. The PCR and DNA sequencing results obtained by DEP from all 11 CLL blood samples and from 8 of the 11 CLL plasma samples were exactly comparable to the DNA sequencing results obtained from genomic DNA isolated from CLL patient leukemic B cells (gold standard).
The ability to effectively detect disease‐related DNA biomarkers and drug delivery nanoparticles directly in blood is a major challenge for viable diagnostics and therapy monitoring. A DEP method has been developed which allows the rapid isolation, concentration and detection of DNA and nanoparticles directly from human and rat whole blood. Using a microarray device operating at 20 V peak‐to‐peak and 10 kHz, a wide range of high molecular weight (HMW)‐DNA and nanoparticles were concentrated into high‐field regions by positive DEP, while the blood cells were concentrated into the low‐field regions by negative DEP. A simple fluidic wash removes the blood cells while the DNA and nanoparticles remain concentrated in the DEP high‐field regions where they can be detected by fluorescence. HMW‐DNA could be detected at 260 ng/mL, which is a detection level suitable for analysis of disease‐related cell‐free circulating DNA biomarkers. Fluorescent 40 nm nanoparticles could be detected at 9.5 × 109 particles/mL, which is a level suitable for monitoring drug delivery nanoparticles. The ability to rapidly isolate and detect DNA biomarkers and nanoparticles from undiluted whole blood will benefit many diagnostic applications by significantly reducing sample preparation time and complexity.
Dielectrophoretic (DEP) microarray devices allow important cellular nanoparticulate biomarkers and virus to be rapidly isolated, concentrated and detected directly from clinical and biological samples. A variety of sub-micron nanoparticulate entities including cell free circulating (cfc) DNA, mitochondria and virus can be isolated into DEP high-field areas on microelectrodes, while blood cells and other micron-size entities become isolated into DEP low-field areas between the microelectrodes. The nanoparticulate entities are held in the DEP high-field areas while cells are washed away along with proteins and other small molecules which are not affected by the DEP electric fields. DEP carried out on 20 µL of whole blood obtained from Chronic Lymphocytic Leukemia (CLL) patients showed a considerable amount of SYBR Green stained DNA fluorescent material concentrated in the DEP high-field regions. Whole blood obtained from healthy individuals showed little or no fluorescent DNA materials in the DEP high-field regions. Fluorescent T7 bacteriophage virus could be isolated directly from blood samples, and fluorescently stained mitochondria could be isolated from biological buffer samples. Using newer DEP microarray devices, high molecular weight (hmw) DNA could be isolated from serum and detected at levels as low as 8–16 ng/mL.
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