Development of an In Vitro Compartmentalization Screen for High-Throughput Directed Evolution of [FeFe] Hydrogenases

BACKGROUND: [FeFe] hydrogenase enzymes catalyze the formation and dissociation of molecular hydrogen with the help of a complex prosthetic group composed of common elements. The development of energy conversion technologies based on these renewable catalysts has been hindered by their extreme oxygen sensitivity. Attempts to improve the enzymes by directed evolution have failed for want of a screening platform capable of throughputs high enough to adequately sample heavily mutated DNA libraries. In vitro compartmentalization (IVC) is a powerful method capable of screening for multiple-turnover enzymatic activity at very high throughputs. Recent advances have allowed [FeFe] hydrogenases to be expressed and activated in the cell-free protein synthesis reactions on which IVC is based; however, IVC is a demanding technique with which many enzymes have proven incompatible. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe an extremely high-throughput IVC screen for oxygen-tolerant [FeFe] hydrogenases. We demonstrate that the [FeFe] hydrogenase CpI can be expressed and activated within emulsion droplets, and identify a fluorogenic substrate that links activity after oxygen exposure to the generation of a fluorescent signal. We present a screening protocol in which attachment of mutant genes and the proteins they encode to the surfaces of microbeads is followed by three separate emulsion steps for amplification, expression, and evaluation of hydrogenase mutants. We show that beads displaying active hydrogenase can be isolated by fluorescence-activated cell-sorting, and we use the method to enrich such beads from a mock library. CONCLUSIONS/SIGNIFICANCE: [FeFe] hydrogenases are the most complex enzymes to be produced by cell-free protein synthesis, and the most challenging targets to which IVC has yet been applied. The technique described here is an enabling step towards the development of biocatalysts for a biological hydrogen economy

Free energy estimation of short DNA duplex hybridizations

<p>Abstract</p> <p>Background</p> <p>Estimation of DNA duplex hybridization free energy is widely used for predicting cross-hybridizations in DNA computing and microarray experiments. A number of software programs based on different methods and parametrizations are available for the theoretical estimation of duplex free energies. However, significant differences in free energy values are sometimes observed among estimations obtained with various methods, thus being difficult to decide what value is the accurate one.</p> <p>Results</p> <p>We present in this study a quantitative comparison of the similarities and differences among four published DNA/DNA duplex free energy calculation methods and an extended Nearest-Neighbour Model for perfect matches based on triplet interactions. The comparison was performed on a benchmark data set with 695 pairs of short oligos that we collected and manually curated from 29 publications. Sequence lengths range from 4 to 30 nucleotides and span a large GC-content percentage range. For perfect matches, we propose an extension of the Nearest-Neighbour Model that matches or exceeds the performance of the existing ones, both in terms of correlations and root mean squared errors. The proposed model was trained on experimental data with temperature, sodium and sequence concentration characteristics that span a wide range of values, thus conferring the model a higher power of generalization when used for free energy estimations of DNA duplexes under non-standard experimental conditions.</p> <p>Conclusions</p> <p>Based on our preliminary results, we conclude that no statistically significant differences exist among free energy approximations obtained with 4 publicly available and widely used programs, when benchmarked against a collection of 695 pairs of short oligos collected and curated by the authors of this work based on 29 publications. The extended Nearest-Neighbour Model based on triplet interactions presented in this work is capable of performing accurate estimations of free energies for perfect match duplexes under both standard and non-standard experimental conditions and may serve as a baseline for further developments in this area of research.</p

DNA Microarrays for Identifying Fishes

In many cases marine organisms and especially their diverse developmental stages are difficult to identify by morphological characters. DNA-based identification methods offer an analytically powerful addition or even an alternative. In this study, a DNA microarray has been developed to be able to investigate its potential as a tool for the identification of fish species from European seas based on mitochondrial 16S rDNA sequences. Eleven commercially important fish species were selected for a first prototype. Oligonucleotide probes were designed based on the 16S rDNA sequences obtained from 230 individuals of 27 fish species. In addition, more than 1200 sequences of 380 species served as sequence background against which the specificity of the probes was tested in silico. Single target hybridisations with Cy5-labelled, PCR-amplified 16S rDNA fragments from each of the 11 species on microarrays containing the complete set of probes confirmed their suitability. True-positive, fluorescence signals obtained were at least one order of magnitude stronger than false-positive cross-hybridisations. Single nontarget hybridisations resulted in cross-hybridisation signals at approximately 27% of the cases tested, but all of them were at least one order of magnitude lower than true-positive signals. This study demonstrates that the 16S rDNA gene is suitable for designing oligonucleotide probes, which can be used to differentiate 11 fish species. These data are a solid basis for the second step to create a “Fish Chip” for approximately 50 fish species relevant in marine environmental and fisheries research, as well as control of fisheries products

Small molecule activators of the Trk receptors for neuroprotection

The neurotophin signaling network is critical to the development and survival of many neuronal populations. Especially sensitive to imbalances in the neurotrophin system, cholinergic neurons in the basal forebrain are progressively lost in Alzheimer's disease. Therapeutic use of neurotrophins to prevent this loss is hampered, however, by a number of pharmacological challenges. These include a lack of transport across the blood-brain barrier, rapid degradation in the circulation, and difficulty in production. In this review we discuss the evidence supporting the neurotrophin system's role in preventing neurodegeneration and survey some of the pharmacological strategies being pursued to develop effective therapeutics targeting neurotrophin function