Inference algorithms for gene networks: a statistical mechanics analysis

The inference of gene regulatory networks from high throughput gene expression data is one of the major challenges in systems biology. This paper aims at analysing and comparing two different algorithmic approaches. The first approach uses pairwise correlations between regulated and regulating genes; the second one uses message-passing techniques for inferring activating and inhibiting regulatory interactions. The performance of these two algorithms can be analysed theoretically on well-defined test sets, using tools from the statistical physics of disordered systems like the replica method. We find that the second algorithm outperforms the first one since it takes into account collective effects of multiple regulators

Exploring the potential of 3D Zernike descriptors and SVM for protein\u2013protein interface prediction

Abstract Background The correct determination of protein–protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task. Results In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein–Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI). Conclusions The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction task, and that optimality strongly depends on the class of proteins whose interface we want to characterise. We postulate that different protein classes should be treated separately and that it is necessary to identify an optimal set of features for each protein class

Understanding the Dynamics of Gene Regulatory Systems : Characterisation and Clinical Relevance of cis-Regulatory Polymorphisms

Peer reviewedPublisher PD

Regulation of candidate genes in black point formation in barley.

Black point of barley refers to discolouration of the embryo end of the grain. Downgrading of malting barley to feed grade due to black point results in significant economic loss to the Australian barley industry. Given that black point normally occurs in regions of Australia that experience high humidity during grain fill, humidity most probably contributes to the severity of black point in susceptible varieties. Previous studies have excluded fungal infection as a cause but enzymatic browning reaction has been recently hypothesised as responsible for black point. More specifically, a role for peroxidases has been proposed. The first major focus of this study was to confirm under what environmental conditions black point formation was likely to occur and whether there was genetic variation contributing to the phenotype. The occurrence of high humidity and low temperatures was associated with the formation of black point in susceptible varieties, with early maturing varieties being more susceptible to black point. These environmental conditions probably create a moist environment during grain development in which the developing grain cannot dry out, enabling stress or wounding to the embryo that subsequently results in black point formation. Analysis combining two South Australian sites (Hatherleigh and Port Wakefield, SA) identified QTL for black point formation on chromosomes 2H (QBpt.AlSl-2H) and 3H QBpt.AlSl-3H) at positions 83.4 cM and 102.6 cM respectively. Additive by environment effects were substantial at both QTL. Linkage of the QTL on chromosome 2H with the earliness per se (eps2) locus and the observation that early maturing varieties were usually more susceptible to black point established a probable association between earliness and black point susceptibility. When an early maturing(susceptible) variety was planted later so that it matured at the same time as a later maturing (tolerant) variety there was no significant difference in black point scores. The second focus of this study was to characterise a number of candidate genes more than likely linked to black point by investigating expression levels during grain fill and subsequently mapping the genomic regions responsible for those changes in expression. Candidate genes chosen were Quinone Reductase (HvQR), Phenylalanine Ammonia Lyase (HvPAL), Barley Peroxidase 1 (HvBP1), stress-related Peroxidase (HvPrx7) and Lipoxygenase A (HvLoxA). Differential expression as detected using northern analysis, between susceptible and tolerant varieties, was only observed for HvBP1, HvPrx7 and HvQR. Quantitative PCR (qPCR)confirmed that HvBP1 and HvPrx7 expression was up to two times higher in black point susceptible varieties during all stages of grain development, while HvQR expression was significantly higher in the hard dough and mature stages of grain fill in susceptible varieties. Increased expression for HvBP1 and HvPrx7 (approximately two-fold) was also apparent in the tolerant variety Alexis between symptomatic and asymptomatic grains. The qPCR data was then used as a quantitative trait, to score the expression of these candidate genes in an Alexis/Sloop double haploid (DH) mapping population. Areas of the genome potentially involved in the regulation of these candidates (expression QTL or eQTL) were mapped on chromosomes 2H (for HvPrx7 and HvBP1) and 5H (for HvQR and HvBP1). The eQTL for HvPrx7 and HvQR were located in the same regions as the corresponding genes, suggesting their expression is regulated via cis-acting factors. In contrast, while HvBP1 is located on 3H, eQTL were located on 2H and 5H suggesting trans-acting factors were involved. The use of comparative mapping studies between barley and rice identified a number of transcription factor genes within these eQTL. The final component of this study was to investigate how HvBP1 and HvPrx7 expression might be affected by examining their promoters and potential interactors with those promoters. Promoter regions for the susceptible variety Sloop and tolerant variety Alexis were isolated, compared and analysed for known motifs. Particular emphasis was placed on those elements that were associated with embryo and endosperm specific expression or responses to environmental stresses. Several regions containing single nucleotide polymorphisms (SNPs) between the promoters from the tolerant and susceptible varieties were identified. A 160 bp region for HvBP1 and 380 bp region for HvPrx7 were used in Yeast One Hybrid (Y1H) screening to identify potential regulatory proteins. In particular, a potential bZIP-containing factor which interacted with the promoter of HvPrx7 was further characterised. Interaction was confirmed by a gel shift assay and gene expression by northern analysis showed expression at the milk, soft dough and hard dough stages of grain development. Increased expression was apparent in the susceptible variety Sloop. The eQTL, Y1H and environmental studies have furthered our understanding of genes that could be involved in the regulation of black point formation under conditions of low temperature and high humidity. This information will contribute to assessing the roles these genes play in black point formation under certain environmental conditions, and more broadly, will assist in improving breeding for resistant barley varieties.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 201

Novel translational approaches to the search for precision therapies for acute respiratory distress syndrome.

In the 50 years since acute respiratory distress syndrome (ARDS) was first described, substantial progress has been made in identifying the risk factors for and the pathogenic contributors to the syndrome and in characterising the protein expression patterns in plasma and bronchoalveolar lavage fluid from patients with ARDS. Despite this effort, however, pharmacological options for ARDS remain scarce. Frequently cited reasons for this absence of specific drug therapies include the heterogeneity of patients with ARDS, the potential for a differential response to drugs, and the possibility that the wrong targets have been studied. Advances in applied biomolecular technology and bioinformatics have enabled breakthroughs for other complex traits, such as cardiovascular disease or asthma, particularly when a precision medicine paradigm, wherein a biomarker or gene expression pattern indicates a patient's likelihood of responding to a treatment, has been pursued. In this Review, we consider the biological and analytical techniques that could facilitate a precision medicine approach for ARDS

Ancient Pbx-Hox signatures define hundreds of vertebrate developmental enhancers

Background: Gene regulation through cis-regulatory elements plays a crucial role in development and disease. A major aim of the post-genomic era is to be able to read the function of cis-regulatory elements through scrutiny of their DNA sequence. Whilst comparative genomics approaches have identified thousands of putative regulatory elements, our knowledge of their mechanism of action is poor and very little progress has been made in systematically de-coding them. Results: Here, we identify ancient functional signatures within vertebrate conserved non-coding elements (CNEs) through a combination of phylogenetic footprinting and functional assay, using genomic sequence from the sea lamprey as a reference. We uncover a striking enrichment within vertebrate CNEs for conserved binding-site motifs of the Pbx-Hox hetero-dimer. We further show that these predict reporter gene expression in a segment specific manner in the hindbrain and pharyngeal arches during zebrafish development. Conclusions: These findings evoke an evolutionary scenario in which many CNEs evolved early in the vertebrate lineage to co-ordinate Hox-dependent gene-regulatory interactions that pattern the vertebrate head. In a broader context, our evolutionary analyses reveal that CNEs are composed of tightly linked transcription-factor binding-sites (TFBSs), which can be systematically identified through phylogenetic footprinting approaches. By placing a large number of ancient vertebrate CNEs into a developmental context, our findings promise to have a significant impact on efforts toward de-coding gene-regulatory elements that underlie vertebrate development, and will facilitate building general models of regulatory element evolution

Evolutionary Algorithms

Evolutionary algorithms (EAs) are population-based metaheuristics, originally inspired by aspects of natural evolution. Modern varieties incorporate a broad mixture of search mechanisms, and tend to blend inspiration from nature with pragmatic engineering concerns; however, all EAs essentially operate by maintaining a population of potential solutions and in some way artificially 'evolving' that population over time. Particularly well-known categories of EAs include genetic algorithms (GAs), Genetic Programming (GP), and Evolution Strategies (ES). EAs have proven very successful in practical applications, particularly those requiring solutions to combinatorial problems. EAs are highly flexible and can be configured to address any optimization task, without the requirements for reformulation and/or simplification that would be needed for other techniques. However, this flexibility goes hand in hand with a cost: the tailoring of an EA's configuration and parameters, so as to provide robust performance for a given class of tasks, is often a complex and time-consuming process. This tailoring process is one of the many ongoing research areas associated with EAs.Comment: To appear in R. Marti, P. Pardalos, and M. Resende, eds., Handbook of Heuristics, Springe

Molecular Markers of Pancreatic β-cell Death

Abstract Loss of insulin-producing β-cells is central to the development of Type 1 diabetes (T1D). Currently, we lack diagnostic tools to quantitate this β-cell loss. Non-protein coding RNAs called microRNAs (miRNAs/miRs) play an important role in islet development and function. Recent detection of miRNAs in peripheral circulation, has renewed interest in microRNA biomarkers of diabetes. Comparably, circulating insulin cell-free (cf)DNA has been proposed as a direct biomarker of β-cell death. DNA methylation studies have identified specific sites within DNA that are unmethylated in β-cells but methylated in other cell types, thus providing a handle to discriminate between cfDNA from β-/non-β-cells. Previous research carried out in the Hardikar lab identified a signature of 20 miRNAs (the ‘RAPID’ signature) with potential as a biomarker of β-cell death. The RAPID signature was revised to accommodate other microRNAs finally constituting a panel of 50 microRNAs (PREDICT T1D panel). An analysis of these 50 miRNAs, as well as insulin cfDNA in serum/plasma from individuals before, during and after clinical diagnosis of T1D is presented. Human islet cell death assays using sodium nitroprusside exposure identified a subset of 27 miRNAs and insulin cfDNA associated with islet cell stress/death. Non-obese diabetic mice (N=32) were found to have elevated candidate miRNAs prior to immune infiltration and glycaemic dysfunction. This trend was also noted in the human progression to T1D; 26 miRNAs were elevated in (N=19) high-risk individuals and those at diagnosis (N=199) but decreased within 6-weeks after diagnosis. Furthermore, candidate miRNAs exhibited differential abundance with disease duration, residual C-peptide, and microvascular complications in 180 subjects with prolonged T1D. At diagnosis, miRNAs and cfDNA associated with GAD III autoantibody titres (N=167 P-values range from 0.044 to <0.0001) and HbA1c levels (N=187, P-values range from 0.047 to 0.00095). Such biomarkers may inform medical researchers as to how to predict the development of T1D, monitor response to interventions such as islet transplantation, vaccines & drugs aiming to retard β-cell loss. In basic research, such an assay may help to select treatments to block β-cell death and guide the development of new treatments to lessen the burden of diabetes

Silk-fibronectin protein alloy fibres support cell adhesion and viability as a high strength, matrix fibre analogue

Silk is a natural polymer with broad utility in biomedical applications because it exhibits general biocompatibility and high tensile material properties. While mechanical integrity is important for most biomaterial applications, proper function and integration also requires biomaterial incorporation into complex surrounding tissues for many physiologically relevant processes such as wound healing. In this study, we spin silk fibroin into a protein alloy fibre with whole fibronectin using wet spinning approaches in order to synergize their respective strength and cell interaction capabilities. Results demonstrate that silk fibroin alone is a poor adhesive surface for fibroblasts, endothelial cells, and vascular smooth muscle cells in the absence of serum. However, significantly improved cell attachment is observed to silk-fibronectin alloy fibres without serum present while not compromising the fibres' mechanical integrity. Additionally, cell viability is improved up to six fold on alloy fibres when serum is present while migration and spreading generally increase as well. These findings demonstrate the utility of composite protein alloys as inexpensive and effective means to create durable, biologically active biomaterials.T32 EB006359 - NIBIB NIH HH