Over the past ten years or so, the Teichmann group and others have shown that the ensemble of transcriptional regulatory interactions in a cell or organism forms a network, which can be described and analysed using bioinformatics, graph theory and mathematical modelling to reveal profound new insights (e.g. Teichmann & Babu, Nature Genet., 2004; Luscombe et al., Nature, 2004). Transcriptional regulatory networks control development and differentiation (e.g. Soneji et al., Ann. N.Y. Acad. Sci., 2007), and here we propose to study the differentiation of T helper cell types of the immune system. The T helper (Th) cell system, one terminal branch of haematopoiesis (Reiner, Cell, 2007), is an experimentally amenable model of differentiation with the added advantage that the various Th cell types can be obtained in large amounts as homogeneous populations. It is also of fundamental importance to human health. The Th cell system regulates immune responses, and impairment of the T helper cell compartment leads to dramatic immune deficiency as seen in late-phase HIV infections (7). Misbalanced differentiation from naïve T helper cells to one of the currently known subtypes, Th1, 2 and 17 and iTregs, is causally involved in diseases like autoimmunity and allergy (Reiner, Cell, 2007). The whole Th differentiation process from naïve Th cells to the three mature subtypes (Th1, 2 and 17) as well as iTregs, can be followed in large numbers of primary cells, and can be accurately simulated in vitro from primary T cells (Reiner, Cell, 2007). The signalling within and between cells in tissues that takes place in most animal developmental and differentiation process is limited in Th differentiation, as the cells are practically not matrix-associated, and their inter-cell interactions are well characterised and can be simulated in vitro (Reiner, Cell, 2007). Therefore, the Th system provides an ideal model to study the transcriptional changes ensuing upon differentiation. There are several fundamental questions about the role of transcriptional regulation in differentiation that can be addressed in this system. First, only a handful of transcription factors (TFs) have been identified for each subtype. Therefore, we propose to identify new candidate transcription factors for each Th subtype by deep sequencing (RNA-seq) of each subtype in a timecourse, and subsequent bioinformatics analysis of the data. This will provide insight into the complexity of the network underlying differentiation into each subtype. Secondly, we will look for binding sites of these transcription factors using both computational screens and Chromatin Immunoprecipitation followed by sequencing (ChIP-seq). It will be crucial to have ChIP-grade antibodies for these transcription factors. We know already from published microarray data that there are will be a number of transcription factors in Th cells that are poorly characterised, with either no antibody or no ChIP-grade antibody commercially available. This is where antibody development is essential, and where Abcam will be instrumental in driving the project forward. These ChIP-seq and computational analyses will shed light on the molecules involved and the topology of their interactions. Thirdly, by superimposing ChIP-seq data of histone modifications on these transcriptional regulatory interactions, we will evaluate the role of chromatin-level regulation in the differentiation process.

Prior work by the Millner laboratory, principally arising from EC Framework 6 Project ELISHA, led to the development of a new electrochemical immunosensor platform. ELISHA immunosensors comprise immobilised antibodies on the surface of a transducer and can be interrogated by AC impedance or electrical pulse decay after binding the analyte to be interrogated. The sensors are truly reagentless and measurement is simply 'incubate and read' with quantification of the analyte being carried out against a calibration curve. Background signal is typically much less than 10-15% of specific signal and can be accounted by two main approaches; tuning of the sensor surface chemistry for the analyte and matrix in which it occurs, and subtraction of a 'control' electrode signal that bears a non-specific antibody. To date we have demonstrated the ELISHA principle for >30 analytes, ranging from heavy metal ions, through small molecules like pesticides and antibiotics, macromolecules such as various protein markers of disease, and up to viruses and bacteria. ELISHA immunosensors function in 'real' fluids such as milk, serum and blood, urine and saliva with no prior processing. We are now at a stage where ELISHA commercialisation is being actively pursued and the challenge is to understand how best to fabricate immunosensor chips to acceptable batch reproducibility. In addition we wish to develop multi-analyte 'mini-array'chips where a panel of up to 10-12 analytes can be measured simultaneously within a sample. Discussion with both medical and veterinary companies and with the biotech industry servicing life science R & D indicates this to be a major requirement. Against this background Abcam Ltd, globally one of the major suppliers of antibodies for R & D; wish to collaborate with us in developing such a multi-analyte platform which for them will represent a future product portfolio. For the academic partner, the alliance would give access to Abcam's very large product portfolio and expertise in producing and handling all types of antibodies. The project strategy will be to examine ELISHA biosensor fabrication and interrogation at four key points. These are electrode (transducer) design, optimisation of transducer composition and nanostructure, optimisation of surface chemistry for antibody coupling from the several approaches available to us, and choice of best interrogation strategy. To accomplish these aims we will work with panels of antibodies, where the analytes are also readily available. Electrodes will be fabricated by both screen printing and inkjet procedures and several multi-electrode layouts will be compared. Then a range of conducting polymeric surfaces will be compared, bearing appropriate pendant chemical groups (amine, hydroxyl, and thiol) to permit gentle chemical coupling of antibodies to the transducer surface. Direct coupling and affinity mediated coupling (avidin/biotin, complementary oliognucleotide pairs), and non-specific versus oriented antibody immobilisation, will be compared. Finally, low frequency AC impedance interrogation protocols will be compared with fast pulsed electrochemical approaches we have developed; if the fast pulsed methodology gives reproducible measurements this would represent a step improvement in biosensor interrogation. During the project we will focus on antibody/analyte sets for which is an analytical requirement is known by Abcam to exist within the R& D community (e.g. cytokines, second messengers, protein and peptide neurotransmitters). We also have expertise in place to drive onward development of any successful findings emerging from this project. ELISHA Systems Ltd, a spin-out from project ELISHA and Uniscan Instruments Ltd, a partner in the ELISHA project, already have IP in place and a prototype ELISHA chip reader respectively which could be further developed to produce a simple handheld chip reader for the generic multi-analyte immunosensors we hope to develop.

Over the past ten years or so, the Teichmann group and others have shown that the ensemble of transcriptional regulatory interactions in a cell or organism forms a network, which can be described and analysed using bioinformatics, graph theory and mathematical modelling to reveal profound new insights (e.g. Teichmann & Babu, Nature Genet., 2004; Luscombe et al., Nature, 2004). Transcriptional regulatory networks control development and differentiation (e.g. Soneji et al., Ann. N.Y. Acad. Sci., 2007), and here we propose to study the differentiation of T helper cell types of the immune system. The T helper (Th) cell system, one terminal branch of haematopoiesis (Reiner, Cell, 2007), is an experimentally amenable model of differentiation with the added advantage that the various Th cell types can be obtained in large amounts as homogeneous populations. It is also of fundamental importance to human health. The Th cell system regulates immune responses, and impairment of the T helper cell compartment leads to dramatic immune deficiency as seen in late-phase HIV infections (7). Misbalanced differentiation from naïve T helper cells to one of the currently known subtypes, Th1, 2 and 17 and iTregs, is causally involved in diseases like autoimmunity and allergy (Reiner, Cell, 2007). The whole Th differentiation process from naïve Th cells to the three mature subtypes (Th1, 2 and 17) as well as iTregs, can be followed in large numbers of primary cells, and can be accurately simulated in vitro from primary T cells (Reiner, Cell, 2007). The signalling within and between cells in tissues that takes place in most animal developmental and differentiation process is limited in Th differentiation, as the cells are practically not matrix-associated, and their inter-cell interactions are well characterised and can be simulated in vitro (Reiner, Cell, 2007). Therefore, the Th system provides an ideal model to study the transcriptional changes ensuing upon differentiation. There are several fundamental questions about the role of transcriptional regulation in differentiation that can be addressed in this system. First, only a handful of transcription factors (TFs) have been identified for each subtype. Therefore, we propose to identify new candidate transcription factors for each Th subtype by deep sequencing (RNA-seq) of each subtype in a timecourse, and subsequent bioinformatics analysis of the data. This will provide insight into the complexity of the network underlying differentiation into each subtype. Secondly, we will look for binding sites of these transcription factors using both computational screens and Chromatin Immunoprecipitation followed by sequencing (ChIP-seq). It will be crucial to have ChIP-grade antibodies for these transcription factors. We know already from published microarray data that there are will be a number of transcription factors in Th cells that are poorly characterised, with either no antibody or no ChIP-grade antibody commercially available. This is where antibody development is essential, and where Abcam will be instrumental in driving the project forward. These ChIP-seq and computational analyses will shed light on the molecules involved and the topology of their interactions. Thirdly, by superimposing ChIP-seq data of histone modifications on these transcriptional regulatory interactions, we will evaluate the role of chromatin-level regulation in the differentiation process.

Over the past ten years or so, the Teichmann group and others have shown that the ensemble of transcriptional regulatory interactions in a cell or organism forms a network, which can be described and analysed using bioinformatics, graph theory and mathematical modelling to reveal profound new insights (e.g. Teichmann & Babu, Nature Genet., 2004; Luscombe et al., Nature, 2004). Transcriptional regulatory networks control development and differentiation (e.g. Soneji et al., Ann. N.Y. Acad. Sci., 2007), and here we propose to study the differentiation of T helper cell types of the immune system. The T helper (Th) cell system, one terminal branch of haematopoiesis (Reiner, Cell, 2007), is an experimentally amenable model of differentiation with the added advantage that the various Th cell types can be obtained in large amounts as homogeneous populations. It is also of fundamental importance to human health. The Th cell system regulates immune responses, and impairment of the T helper cell compartment leads to dramatic immune deficiency as seen in late-phase HIV infections (7). Misbalanced differentiation from naïve T helper cells to one of the currently known subtypes, Th1, 2 and 17 and iTregs, is causally involved in diseases like autoimmunity and allergy (Reiner, Cell, 2007). The whole Th differentiation process from naïve Th cells to the three mature subtypes (Th1, 2 and 17) as well as iTregs, can be followed in large numbers of primary cells, and can be accurately simulated in vitro from primary T cells (Reiner, Cell, 2007). The signalling within and between cells in tissues that takes place in most animal developmental and differentiation process is limited in Th differentiation, as the cells are practically not matrix-associated, and their inter-cell interactions are well characterised and can be simulated in vitro (Reiner, Cell, 2007). Therefore, the Th system provides an ideal model to study the transcriptional changes ensuing upon differentiation. There are several fundamental questions about the role of transcriptional regulation in differentiation that can be addressed in this system. First, only a handful of transcription factors (TFs) have been identified for each subtype. Therefore, we propose to identify new candidate transcription factors for each Th subtype by deep sequencing (RNA-seq) of each subtype in a timecourse, and subsequent bioinformatics analysis of the data. This will provide insight into the complexity of the network underlying differentiation into each subtype. Secondly, we will look for binding sites of these transcription factors using both computational screens and Chromatin Immunoprecipitation followed by sequencing (ChIP-seq). It will be crucial to have ChIP-grade antibodies for these transcription factors. We know already from published microarray data that there are will be a number of transcription factors in Th cells that are poorly characterised, with either no antibody or no ChIP-grade antibody commercially available. This is where antibody development is essential, and where Abcam will be instrumental in driving the project forward. These ChIP-seq and computational analyses will shed light on the molecules involved and the topology of their interactions. Thirdly, by superimposing ChIP-seq data of histone modifications on these transcriptional regulatory interactions, we will evaluate the role of chromatin-level regulation in the differentiation process.

Many people with Parkinson's disease do not respond well to therapy with the most widely-used drug called L-DOPA, having uncontrollable body movements that make them feel ashamed or even fall and get injured. We and other doctors think that this occurs because proteins called dopamine receptors associate in unusual structures called heteromers in nerve cells. However, no one knows how and where heteromers are formed, whether they affect other receptors and if it actually makes people feel bad. We have shown that there really are many more heteromers in brains of the animals with experimental Parkinson's disease put on human therapy. Now, we want to use special animals that will enable us to see where heteromers are formed. Further, we made contacts with companies to make smaller proteins of our design that will break heteromers apart, which could then be used to prevent side effects of drugs. A part of the brain that is essential for manifestations of Parkinson's disease is called striatum. It is controlled by inflow of impulses that release a substance called dopamine. The main problem of Parkinson's disease is that the source of dopamine is lost. In therapy, L-DOPA serves to compensate for the lack of dopamine. Importantly, not all nerve cells in striatum are the same: there are two subtypes with contrasting properties, particularly how they react to dopamine. Nerve cells communicate and transmit information across structures called synapses. The sending nerve cell (presynaptic) relays the information by releasing chemical transmitters. The receiving cell (postsynaptic) detects that signal by specialized receptor proteins present on its body or fine extensions called dendrites. At the points of contact, dendrites have bud-like protrusions called dendritic spines that possess molecular machinery necessary to process the signal. Different types of dopamine receptors in striatal spines respond to dopamine differently, transmitting the signal in a specific way. Normally they stand apart, but can also aggregate into heteromers, which will transmit the signal in a different way. Among other specialized receptor proteins in spines are AMPA and NMDA receptors, responsible for nearly all of the fast communication between neurones in the brain. A lot is known about interplay between AMPA, NMDA and dopamine receptors, both in health and Parkinson's disease. For example, we know many ways how they affect each other to work more or less strongly or how the signals from one receptor make other receptors to incorporate into the synapse or completely leave it, thus modulating the overall synaptic function. Almost nothing is, however, known whether the same rules apply when dopamine receptor-heteromers are present, or about the consequences they may have in Parkinson's disease. This is important because it could tell us why patient's brains make wrong calculations and send wrong signals that result in unwanted movements. To answer all these questions, we will use special animals that allow us to tell between subtypes of nerve cells in striatum, even allowing us to see when heteromers are present in them, because they become fluorescent. We will apply chemicals that cause Parkinson's disease-like condition in these animals. Then, using special methods, we will be able to track the fluorescent dopamine receptor heteromers and see them within the living cells. To achieve this, we will use a powerful confocal microscopy to see tiny details within nerve cells. We are good in applying this methodology, so we can minimize the number of animals used. Understanding what heteromers do and how they themselves are regulated will help us try to find the way to prevent them from overtaking control over striatum. This will help us devise a new strategy in fight against Parkinson's disease and the deleterious side effects of its treatment.