Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

The effects of parabens on the mechanosensitive channels of E. coli

Parabens are alkyl esters of p-hydroxybenzoic acid used as preservatives in a wide range of food, pharmaceutical, and cosmetic products (Soni et al. Food Chem. Toxicol. 39:513-532, 2001). Despite their common use for over 50 years, their mechanism of action is still unclear. In this study we examined the effects of ethyl and propyl paraben, on gating of the E. coli mechanosensitive channel of large conductance (MscL) reconstituted into azolectin liposomes. We found that propyl and ethyl paraben spontaneously activate MscL. Moreover, the addition of propyl paraben caused an increase in MscL activity and the lowering Of P-1/2, the pressure at which the MscL was opened 50% of the time, the AGO, the free energy required to open the MscL, and the parameter a, which describes the channel sensitivity to pressure. In addition, in silico studies showed that propyl paraben binds to the channel gate of the MscL. The mechanosensitive channel of small conductance was also found to be spontaneously activated by parabens. In summary, our study indicates that one of the previously unidentified mechanisms of action of parabens as antimicrobial agents is via an interaction with the mechanosensitive channels to upset the osmotic gradients in bacteria.

Modeling hybridoma cell metabolism using a generic genome-scale metabolic model of Mus musculus

The reconstructed cellular metabolic network of Mus musculus, based on annotated genomic data, pathway databases, and currently available biochemical and physiological information, is presented. Although incomplete, it represents the first attempt to collect and characterize the metabolic network of a mammalian cell on the basis of genomic data. The reaction network is generic in nature and attempts to capture the carbon, energy, and nitrogen metabolism of the cell. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, including transport reactions between the compartments and the extracellular medium. The reaction list consists of 872 internal metabolites involved in a total of 1220 reactions, whereof 473 relate to known open reading frames. Initial in silico analysis of the reconstructed model is presented.

Clusters of internally primed transcripts reveal novel long noncoding RNAs

Non- protein- coding RNAs ( ncRNAs) are increasingly being recognized as having important regulatory roles. Although much recent attention has focused on tiny 22- to 25- nucleotide microRNAs, several functional ncRNAs are orders of magnitude larger in size. Examples of such macro ncRNAs include Xist and Air, which in mouse are 18 and 108 kilobases ( Kb), respectively. We surveyed the 102,801 FANTOM3 mouse cDNA clones and found that Air and Xist were present not as single, full- length transcripts but as a cluster of multiple, shorter cDNAs, which were unspliced, had little coding potential, and were most likely primed from internal adenine- rich regions within longer parental transcripts. We therefore conducted a genome- wide search for regional clusters of such cDNAs to find novel macro ncRNA candidates. Sixty- six regions were identified, each of which mapped outside known protein- coding loci and which had a mean length of 92 Kb. We detected several known long ncRNAs within these regions, supporting the basic rationale of our approach. In silico analysis showed that many regions had evidence of imprinting and/ or antisense transcription. These regions were significantly associated with microRNAs and transcripts from the central nervous system. We selected eight novel regions for experimental validation by northern blot and RT- PCR and found that the majority represent previously unrecognized noncoding transcripts that are at least 10 Kb in size and predominantly localized in the nucleus. Taken together, the data not only identify multiple new ncRNAs but also suggest the existence of many more macro ncRNAs like Xist and Air.

Evolutionary conservation and murine embryonic expression of the gene encoding the SERTA domain-containing protein CDCA4 (HEPP)

Cdca4 (Hepp) was originally identified as a gene expressed specifically in hematopoietic progenitor cells as opposed to hematopoietic stem cells. More recently, it has been shown to stimulate p53 activity and also lead to p53-independent growth inhibition when overexpressed. We independently isolated the murine Cdca4 gene in a genomic expression-based screen for genes involved in mammalian craniofacial development, and show that Cdca4 is expressed in a spatio-temporally restricted pattern during mouse embryogenesis. In addition to expression in the facial primordia including the pharyngeal arches, Cdca4 is expressed in the developing limb buds, brain, spinal cord, dorsal root ganglia, teeth, eye and hair follicles. Along with a small number of proteins from a range of species, the predicted CDCA4 protein contains a novel SERTA motif in addition to cyclin A-binding and PHD bromodomain-binding regions of homology. While the function of the SERTA domain is unknown, proteins containing this domain have previously been linked to cell cycle progression and chromatin remodelling. Using in silico database mining we have extended the number of evolutionarily conserved orthologues of known SERTA domain proteins and identified an uncharacterised member of the SERTA domain family, SERTAD4, with orthologues to date in human, mouse, rat, dog, cow, Tetraodon and chicken. Immunolocalisation of transiently and stably transfected epitope-tagged CDCA4 protein in mammalian cells suggests that it resides predominantly in the nucleus throughout all stages of the cell cycle. (c) 2006 Elsevier B.V. All rights reserved.

Physiologically based synthetic models of hepatic disposition

Current Physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.

Different routes to pure food allergens: extraction, recombinant techniques and total chemical synthesis for obtaining the plant-food pan-allergen LTP

La richiesta di allergeni puri è in continuo aumento per scopi diagnostici, come standard per metodi di rilevamento e di quantificazione, per l'immunoterapia e per lo studio a livello molecolare dei meccanismi delle reazioni allergiche, al fine di facilitare lo sviluppo di possibili cure. In questa tesi di dottorato sono descritte diverse strategie per l’ottenimento di forme pure di non-specific Lipid Transfer Proteins (nsLTPs), le quali sono state riconosciute essere rilevanti allergeni alimentari in molti frutti e verdure comunemente consumati e sono state definite come modello di veri allergeni alimentari. Una LTP potenzialmente allergenica, non nota in precedenza, è stata isolata dalle mandorle, mentre una LTP dall’allergenicità nota contenuta nelle noci è stata prodotta mediante tecniche di DNA ricombinante. Oltre a questi approcci classici, metodi per la sintesi chimica totale di proteine sono stati applicati per la prima volta alla produzione di un allergene, utilizzando Pru p 3, la LTP prototipica e principale allergene della pesca nell'area mediterranea, come modello. La sintesi chimica totale di proteinepermette di controllarne completamente la sequenza e di studiare la loro funzione a livello atomico. La sua applicazione alla produzione di allergeni costituisce perciò un importante passo avanti nel campo della ricerca sulle allergie alimentari. La proteina Pru p 3 è stata prodotta nella sua intera lunghezza e sono necessari solo due passaggi finali di deprotezione per ottenere il target nella sua forma nativa. Le condizioni sperimentali per tali deprotezioni sono state messe a punto durante la produzione dei peptidi sPru p 3 (1-37) e sPru p 3 (38-91), componenti insieme l'intera proteina. Tecniche avanzate di spettrometria di massa sono state usate per caratterizzare tutti i composti ottenuti, mentre la loro allergenicità è stata studiata attraverso test immunologici o approcci in silico.

Multi-scale approaches to Food Sciences: computational QM and MM explorations at the microscopic level

L'obiettivo principale della politica di sicurezza alimentare è quello di garantire la salute dei consumatori attraverso regole e protocolli di sicurezza specifici. Al fine di rispondere ai requisiti di sicurezza alimentare e standardizzazione della qualità, nel 2002 il Parlamento Europeo e il Consiglio dell'UE (Regolamento (CE) 178/2002 (CE, 2002)), hanno cercato di uniformare concetti, principi e procedure in modo da fornire una base comune in materia di disciplina degli alimenti e mangimi provenienti da Stati membri a livello comunitario. La formalizzazione di regole e protocolli di standardizzazione dovrebbe però passare attraverso una più dettagliata e accurata comprensione ed armonizzazione delle proprietà globali (macroscopiche), pseudo-locali (mesoscopiche), ed eventualmente, locali (microscopiche) dei prodotti alimentari. L'obiettivo principale di questa tesi di dottorato è di illustrare come le tecniche computazionali possano rappresentare un valido supporto per l'analisi e ciò tramite (i) l’applicazione di protocolli e (ii) miglioramento delle tecniche ampiamente applicate. Una dimostrazione diretta delle potenzialità già offerte dagli approcci computazionali viene offerta nel primo lavoro in cui un virtual screening basato su docking è stato applicato al fine di valutare la preliminare xeno-androgenicità di alcuni contaminanti alimentari. Il secondo e terzo lavoro riguardano lo sviluppo e la convalida di nuovi descrittori chimico-fisici in un contesto 3D-QSAR. Denominata HyPhar (Hydrophobic Pharmacophore), la nuova metodologia così messa a punto è stata usata per esplorare il tema della selettività tra bersagli molecolari strutturalmente correlati e ha così dimostrato di possedere i necessari requisiti di applicabilità e adattabilità in un contesto alimentare. Nel complesso, i risultati ci permettono di essere fiduciosi nel potenziale impatto che le tecniche in silico potranno avere nella identificazione e chiarificazione di eventi molecolari implicati negli aspetti tossicologici e nutrizionali degli alimenti.

Design and synthesis of potential antimicrobial agents

Chorismate mutase is one of the essential enzymes in the shikimate pathway and is key to the survival of the organism Mycobacterium tuberculosis. The x-ray crystal structure of this enzyme from Mycobacterium tuberculosis was manipulated to prepare an initial set of in silico protein models of the active site. Known inhibitors of the enzyme were docked into the active site using the flexible ligand / flexible active site side chains approach implemented in CAChe Worksystem (Fujitsu Ltd). The resulting complexes were refined by molecular dynamics studies in explicit water using Amber 9. This yielded a further set of protein models that were used for additional rounds of ligand docking. A binding hypothesis was established for the enzyme and this was used to screen a database of commercially available drug-like compounds. From these results new potential ligands were designed that fitted appropriately into the active site and matched the functional groups and binding motifs founds therein. Some of these compounds and close analogues were then synthesized and submitted for biological evaluation. As a separate part of this thesis, analogues of very active anti-tuberculosis pyridylcarboxamidrazone were also prepared. This was carried out by the addition and the deletion of the substitutions from the lead compound thereby preparing heteroaryl carboxamidrazone derivatives and related compounds. All these compounds were initially evaluated for biological activity against various gram positive organisms and then sent to the TAACF (USA) for screening against Mycobacterium tuberculosis. Some of the new compounds proved to be at least as potent as the original lead compound but less toxic.

MHC class II binding prediction:a little help from a friend

Vaccines are the greatest single instrument of prophylaxis against infectious diseases, with immeasurable benefits to human wellbeing. The accurate and reliable prediction of peptide-MHC binding is fundamental to the robust identification of T-cell epitopes and thus the successful design of peptide- and protein-based vaccines. The prediction of MHC class II peptide binding has hitherto proved recalcitrant and refractory. Here we illustrate the utility of existing computational tools for in silico prediction of peptides binding to class II MHCs. Most of the methods, tested in the present study, detect more than the half of the true binders in the top 5% of all possible nonamers generated from one protein. This number increases in the top 10% and 15% and then does not change significantly. For the top 15% the identified binders approach 86%. In terms of lab work this means 85% less expenditure on materials, labour and time. We show that while existing caveats are well founded, nonetheless use of computational models of class II binding can still offer viable help to the work of the immunologist and vaccinologist.

Characterisation of the plasma membrane subproteome of bloodstream form Trypanosoma brucei

Proteome analysis by conventional approaches is biased against hydrophobic membrane proteins, many of which are also of low abundance. We have isolated plasma membrane sheets from bloodstream forms of Trypanosoma brucei by subcellular fractionation, and then applied a battery of complementary protein separation and identification techniques to identify a large number of proteins in this fraction. The results of these analyses have been combined to generate a subproteome for the pellicular plasma membrane of bloodstream forms of T. brucei as well as a separate subproteome for the pellicular cytoskeleton. In parallel, we have used in silico approaches to predict the relative abundance of proteins potentially expressed by bloodstream form trypanosomes, and to identify likely polytopic membrane proteins, providing quality control for the experimentally defined plasma membrane subproteome. We show that the application of multiple high-resolution proteomic techniques to an enriched organelle fraction is a valuable approach for the characterisation of relatively intractable membrane proteomes. We present here the most complete analysis of a protozoan plasma membrane proteome to date and show the presence of a large number of integral membrane proteins, including 11 nucleoside/nucleobase transporters, 15 ion pumps and channels and a large number of adenylate cyclases hitherto listed as putative proteins.

Bayesian error bars for regression

Regression problems are concerned with predicting the values of one or more continuous quantities, given the values of a number of input variables. For virtually every application of regression, however, it is also important to have an indication of the uncertainty in the predictions. Such uncertainties are expressed in terms of the error bars, which specify the standard deviation of the distribution of predictions about the mean. Accurate estimate of error bars is of practical importance especially when safety and reliability is an issue. The Bayesian view of regression leads naturally to two contributions to the error bars. The first arises from the intrinsic noise on the target data, while the second comes from the uncertainty in the values of the model parameters which manifests itself in the finite width of the posterior distribution over the space of these parameters. The Hessian matrix which involves the second derivatives of the error function with respect to the weights is needed for implementing the Bayesian formalism in general and estimating the error bars in particular. A study of different methods for evaluating this matrix is given with special emphasis on the outer product approximation method. The contribution of the uncertainty in model parameters to the error bars is a finite data size effect, which becomes negligible as the number of data points in the training set increases. A study of this contribution is given in relation to the distribution of data in input space. It is shown that the addition of data points to the training set can only reduce the local magnitude of the error bars or leave it unchanged. Using the asymptotic limit of an infinite data set, it is shown that the error bars have an approximate relation to the density of data in input space.

Proteins accessible to immune surveillance show significant T-cell epitope depletion:implications for vaccine design

T cell activation is the final step in a complex pathway through which pathogen-derived peptide fragments can elicit an immune response. For it to occur, peptides must form stable complexes with Major Histocompatibility Complex (MHC) molecules and be presented on the cell surface. Computational predictors of MHC binding are often used within in silico vaccine design pathways. We have previously shown that, paradoxically, most bacterial proteins known experimentally to elicit an immune response in disease models are depleted in peptides predicted to bind to human MHC alleles. The results presented here, derived using software proven through benchmarking to be the most accurate currently available, show that vaccine antigens contain fewer predicted MHC-binding peptides than control bacterial proteins from almost all subcellular locations with the exception of cell wall and some cytoplasmic proteins. This effect is too large to be explained from the undoubted lack of precision of the software or from the amino acid composition of the antigens. Instead, we propose that pathogens have evolved under the influence of the host immune system so that surface proteins are depleted in potential MHC-binding peptides, and suggest that identification of a protein likely to contain a single immuno-dominant epitope is likely to be a productive strategy for vaccine design.

Multimodal characterisation of sensorimotor oscillations

The studies in this project have investigated the ongoing neuronal network oscillatory activity found in the sensorimotor cortex using two modalities: magnetoencephalography (MEG) and in vitro slice recordings. The results have established that ongoing sensorimotor oscillations span the mu and beta frequency region both in vitro and in MEG recordings, with distinct frequency profiles for each recorded laminae in vitro, while MI and SI show less difference in humans. In addition, these studies show that connections between MI and SI modulate the ongoing neuronal network activity in these areas. The stimulation studies indicate that specific frequencies of stimulation affect the ongoing activity in the sensorimotor cortex. The continuous theta burst stimulation (cTBS) study demonstrates that cTBS predominantly enhances the power of the local ongoing activity. The stimulation studies in this project show limited comparison between modalities, which is informative of the role of connectivity in these effects. However, independently these studies provide novel information on the mechanisms on sensorimotor oscillatory interaction. The pharmacological studies reveal that GABAergic modulation with zolpidem changes the neuronal oscillatory network activity in both healthy and pathological MI. Zolpidem enhances the power of ongoing oscillatory activity in both sensorimotor laminae and in healthy subjects. In contrast, zolpidem attenuates the “abnormal” beta oscillatory activity in the affected hemisphere in Parkinsonian patients, while restoring the hemispheric beta power ratio and frequency variability and thereby improving motor symptomatology. Finally we show that independent signals from MI laminae can be integrated in silico to resemble the aggregate MEG MI oscillatory signals. This highlights the usefulness of combining these two methods when elucidating neuronal network oscillations in the sensorimotor cortex and any interventions.

The antimicrobial action of pseudin-2

The amphibian antimicrobial peptide pseudin-2 is a peptide derived from the skin of the South-American frog Pseudis paradoxa (Olson et al., 2001). This peptide possesses tremendous potential as a therapeutic lead since it has been shown to possess both antimicrobial as well insulin-releasing properties (Olson et al., 2001; Abdel-Wahab et al., 2008). This study aimed to develop pseudin-2’s potential by understanding and improving its properties as an antimicrobial agent. The structure-function relationships of pseudin-2 were explored using a combination of in-vitro and in-silico techniques, with an aim to predict how the structure of the peptide may be altered in order to improve its efficacy. A library of pseudin-2 mutants was generated by randomizing codons at positions 10, 14 and 18 of a synthetic gene, using NNK saturation mutagenesis. Analysis of these novel peptides broadly confirmed, in line with literature precedent, that anti-microbial activity increases with increased positive charge. Specifically, 2 positively-charged residues at positions 10 and 14 and a hydrophobic at position 18 are preferred. However, substitution at position 14 with some polar, non-charged residues also created peptides with antimicrobial activity. Interestingly, the pseudin-2 analogue [10-E, 14-Q, 18-L] which is identical to pseudin-2, except that the residues at positions 10 and 14 are switched, showed no anti-microbial activity at all. Molecular dynamics simulations of pseudin-2 showed that the peptide possesses two equilibrium structures in a membrane environment: a linear and a kinked a-helix which both embed into the membrane at an angle. Biophysical characterization using circular dichroism spectroscopy confirmed that the peptide is helical within the membrane environment whilst linear dichroism established that the peptide has no defined orientation within the membrane. Collectively, these data indicate that Pseudin-2 exerts its antimicrobial activity via the carpet model.