The development of a model system and high throughput assay for the study of interactions between zinc finger proteins and DNA

It has been recognised for some time that a full code of amino acid-based recognition of DNA sequences would be useful. Several approaches, which utilise small DNA binding motifs called zinc fingers, are presently employed. None of the current approaches successfully combine a combinatorial approach to the elucidation of a code with a single stage high throughput screening assay. The work outlined here describes the development of a model system for the study of DNA protein interactions and the development of a high throughput assay for detection of such interactions. A zinc finger protein was designed which will bind with high affinity and specificity to a known DNA sequence. For future work it is possible to mutate the region of the zinc finger responsible for the specificity of binding, in order to observe the effect on the DNA / protein interactions. The zinc finger protein was initially synthesised as a His tagged product. It was not possible however to develop a high throughput assay using the His tagged zinc finger protein. The gene encoding the zinc finger protein was altered and the protein synthesised as a Glutathione S-Transferase (GST) fusion product. A successful assay was developed using the GST protein and Scintillation Proximity Assay technology (Amersham Pharmacia Biotech). The scintillation proximity assay is a dynamic assay that allows the DNA protein interactions to be studied in "real time". This assay not only provides a high throughput method of screening zinc finger proteins for potential ligands but also allows the effect of addition of reagents or competitor ligands to be monitored.

Quality control of high throughput screening

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Quality control of high throughput screening

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

The integration of ProxiMAX randomisation with CIS display for the high-throughput production of novel peptides

Saturation mutagenesis is a powerful tool in modern protein engineering. This can allow the analysis of potential new properties thus allowing key residues within a protein to be targeted and randomised. However, the creation of large libraries using conventional saturation mutagenesis with degenerate codons (NNN or NNK) has inherent redundancy and disparities in residue representation. In this we describe the combination of ProxiMAX randomisation and CIS display for the use of generating novel peptides. Unlike other methods ProxiMAX randomisation does not require any intricate chemistry but simply utilises synthetic DNA and molecular biology techniques. Designed ‘MAX’ oligonucleotides were ligated, amplified and digested in an iterative cycle. Results show that randomised ‘MAX’ codons can be added sequentially to the base sequence creating a series of randomised non-degenerate codons that can subsequently be inserted into a gene. CIS display (Isogencia, UK) is an in vitro DNA based screening method that creates a genotype to phenotype link between a peptide and the nucleic acid that encodes it. The use of straight forward in vitro transcription/translation and other molecular biology techniques permits ease of use along with flexibility making it a potent screening technique. Using ProxiMAX randomisation in combination with CIS display, the aim is to produce randomised anti-nerve growth factor (NGF) and calcitonin gene-related (CGRP) peptides to demonstrate the high-throughput nature of this combination.

High-throughput manufacturing of size-tuned liposomes by a new microfluidics method using enhanced statistical tools for characterization

Microfluidics has recently emerged as a new method of manufacturing liposomes, which allows for reproducible mixing in miliseconds on the nanoliter scale. Here we investigate microfluidics-based manufacturing of liposomes. The aim of these studies was to assess the parameters in a microfluidic process by varying the total flow rate (TFR) and the flow rate ratio (FRR) of the solvent and aqueous phases. Design of experiment and multivariate data analysis were used for increased process understanding and development of predictive and correlative models. High FRR lead to the bottom-up synthesis of liposomes, with a strong correlation with vesicle size, demonstrating the ability to in-process control liposomes size; the resulting liposome size correlated with the FRR in the microfluidics process, with liposomes of 50 nm being reproducibly manufactured. Furthermore, we demonstrate the potential of a high throughput manufacturing of liposomes using microfluidics with a four-fold increase in the volumetric flow rate, maintaining liposome characteristics. The efficacy of these liposomes was demonstrated in transfection studies and was modelled using predictive modeling. Mathematical modelling identified FRR as the key variable in the microfluidic process, with the highest impact on liposome size, polydispersity and transfection efficiency. This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes. Furthermore, the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.

Implementing an adaptive sending rate by exploiting SNR in relation to throughput over Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have emerged as a key technology for the next generation of wireless networking. Instead ofbeing another type of ad-hoc networking, WMNs diversify the capabilities of ad-hoc networks. There are many kinds of protocols that work over WMNs, such as IEEE 802.11a/b/g, 802.15 and 802.16. To bring about a high throughput under varying conditions, these protocols have to adapt their transmission rate. While transmission rate is a significant part, only a few algorithms such as Auto Rate Fallback (ARF) or Receiver Based Auto Rate (RBAR) have been published. In this paper we will show MAC, packet loss and physical layer conditions play important role for having good channel condition. Also we perform rate adaption along with multiple packet transmission for better throughput. By allowing for dynamically monitored, multiple packet transmission and adaptation to changes in channel quality by adjusting the packet transmission rates according to certain optimization criteria improvements in performance can be obtained. The proposed method is the detection of channel congestion by measuring the fluctuation of signal to the standard deviation of and the detection of packet loss before channel performance diminishes. We will show that the use of such techniques in WMN can significantly improve performance. The effectiveness of the proposed method is presented in an experimental wireless network testbed via packet-level simulation. Our simulation results show that regardless of the channel condition we were to improve the performance in the throughput.