Bioinformatic methods in applied genomic research

Here I will focus on three main topics that best address and include the projects I have been working in during my three year PhD period that I have spent in different research laboratories addressing both computationally and practically important problems all related to modern molecular genomics. The first topic is the use of livestock species (pigs) as a model of obesity, a complex human dysfunction. My efforts here concern the detection and annotation of Single Nucleotide Polymorphisms. I developed a pipeline for mining human and porcine sequences. Starting from a set of human genes related with obesity the platform returns a list of annotated porcine SNPs extracted from a new set of potential obesity-genes. 565 of these SNPs were analyzed on an Illumina chip to test the involvement in obesity on a population composed by more than 500 pigs. Results will be discussed. All the computational analysis and experiments were done in collaboration with the Biocomputing group and Dr.Luca Fontanesi, respectively, under the direction of prof. Rita Casadio at the Bologna University, Italy. The second topic concerns developing a methodology, based on Factor Analysis, to simultaneously mine information from different levels of biological organization. With specific test cases we develop models of the complexity of the mRNA-miRNA molecular interaction in brain tumors measured indirectly by microarray and quantitative PCR. This work was done under the supervision of Prof. Christine Nardini, at the “CAS-MPG Partner Institute for Computational Biology” of Shangai, China (co-founded by the Max Planck Society and the Chinese Academy of Sciences jointly) The third topic concerns the development of a new method to overcome the variety of PCR technologies routinely adopted to characterize unknown flanking DNA regions of a viral integration locus of the human genome after clinical gene therapy. This new method is entirely based on next generation sequencing and it reduces the time required to detect insertion sites, decreasing the complexity of the procedure. This work was done in collaboration with the group of Dr. Manfred Schmidt at the Nationales Centrum für Tumorerkrankungen (Heidelberg, Germany) supervised by Dr. Annette Deichmann and Dr. Ali Nowrouzi. Furthermore I add as an Appendix the description of a R package for gene network reconstruction that I helped to develop for scientific usage (http://www.bioconductor.org/help/bioc-views/release/bioc/html/BUS.html).

Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Statistical mechanics formalism and methods for the analysis of real networks

This thesis provides a thoroughly theoretical background in network theory and shows novel applications to real problems and data. In the first chapter a general introduction to network ensembles is given, and the relations with “standard” equilibrium statistical mechanics are described. Moreover, an entropy measure is considered to analyze statistical properties of the integrated PPI-signalling-mRNA expression networks in different cases. In the second chapter multilayer networks are introduced to evaluate and quantify the correlations between real interdependent networks. Multiplex networks describing citation-collaboration interactions and patterns in colorectal cancer are presented. The last chapter is completely dedicated to control theory and its relation with network theory. We characterise how the structural controllability of a network is affected by the fraction of low in-degree and low out-degree nodes. Finally, we present a novel approach to the controllability of multiplex networks

Methods and strategies to identify the mode of action of phytoactive compounds

Small molecules affecting biological processes in plants are widely used in agricultural practice as herbicides or plant growth regulators and in basic plant sciences as probes to study the physiology of plants. Most of the compounds were identified in large screens by the agrochemical industry, as phytoactive natural products and more recently, novel phytoactive compounds originated from academic research by chemical screens performed to induce specific phenotypes of interest. The aim of the present PhD thesis is to evaluate different approaches used for the identification of the primary mode of action (MoA) of a phytoactive compound. Based on the methodologies used for MoA identification, three approaches are discerned: a phenotyping approach, an approach based on a genetic screen and a biochemical screening approach.rnFour scientific publications resulting from my work are presented as examples of how a phenotyping approach can successfully be applied to describe the plant MoA of different compounds in detail.rnI. A subgroup of cyanoacrylates has been discovered as plant growth inhibitors. A set of bioassays indicated a specific effect on cell division. Cytological investigations of the cell division process in plant cell cultures, studies of microtubule assembly with green fluorescent protein marker lines in vivo and cross resistant studies with Eleusine indica plants harbouring a mutation in alpha-tubulin, led to the description of alpha-tubulin as a target site of cyanoacrylates (Tresch et al., 2005).rnII. The MoA of the herbicide flamprop-m-methyl was not known so far. The studies described in Tresch et al. (2008) indicate a primary effect on cell division. Detailed studies unravelled a specific effect on mitotic microtubule figures, causing a block in cell division. In contrast to other inhibitors of microtubule rearrangement such as dinitroanilines, flamprop-m-methyl did not influence microtubule assembly in vitro. An influence of flamprop-m-methyl on a target within the cytoskeleton signalling network could be proposed (Tresch et al., 2008).rnIII. The herbicide endothall is a protein phosphatase inhibitor structurally related to the natural product cantharidin. Bioassay studies indicated a dominant effect on dark-growing cells that was unrelated to effects observed in the light. Cytological characterisation of the microtubule cytoskeleton in corn tissue and heterotrophic tobacco cells showed a specific effect of endothall on mitotic spindle formation and ultrastructure of the nucleus in combination with a decrease of the proliferation index. The observed effects are similar to those of other protein phosphatase inhibitors such as cantharidin and the structurally different okadaic acid. Additionally, the observed effects show similarities to knock-out lines of the TON1 pathway, a protein phosphatase-regulated signalling pathway. The data presented in Tresch et al. (2011) associate endothall’s known in vitro inhibition of protein phosphatases with in vivo-effects and suggest an interaction between endothall and the TON1 pathway.rnIV. Mefluidide as a plant growth regulator induces growth retardation and a specific phenotype indicating an inhibition of fatty acid biosynthesis. A test of the cuticle functionality suggested a defect in the biosynthesis of very-long-chain fatty acids (VLCFA) or waxes. Metabolic profiling studies showed similarities with different groups of VLCFA synthesis inhibitors. Detailed analyses of VLCFA composition in tissues of duckweed (Lemna paucicostata) indicated a specific inhibition of the known herbicide target 3 ketoacyl-CoA synthase (KCS). Inhibitor studies using a yeast expression system established for plant KCS proteins verified the potency of mefluidide as an inhibitor of plant KCS enzymes. It could be shown that the strength of inhibition varied for different KCS homologues. The Arabidopsis Cer6 protein, which induces a plant growth phenotype similar to mefluidide when knocked out, was one of the most sensitive KCS enzymes (Tresch et al., 2012).rnThe findings of my own work were combined with other publications reporting a successful identification of the MoA and primary target proteins of different compounds or compound classes.rnA revised three-tier approach for the MoA identification of phytoactive compounds is proposed. The approach consists of a 1st level aiming to address compound stability, uniformity of effects in different species, general cytotoxicity and the effect on common processes like transcription and translation. Based on these findings advanced studies can be defined to start the 2nd level of MoA characterisation, either with further phenotypic characterisation, starting a genetic screen or establishing a biochemical screen. At the 3rd level, enzyme assays or protein affinity studies should show the activity of the compound on the hypothesized target and should associate the in vitro effects with the in vivo profile of the compound.

Key issues in diagnosing and treating acute aortic syndromes: results from the metropolitan area of Bologna network

Background: Survival of patients with Acute Aortic Syndrome (AAS) may relate to the speed of diagnosis. Diagnostic delay is exacerbated by non classical presentations such as myocardial ischemia or acute heart failure (AHF). However little is known about clinical implications and pathophysiological mechanisms of Troponin T elevation and AHF in AAS. Methods and Results: Data were collected from a prospective metropolitan AAS registry (398 patients diagnosed between 2000 and 2013). Troponin T values (either standard or high sensitivity assay, HS) were available in 248 patients (60%) of the registry population; the overall frequency of troponin positivity was 28% (ranging from 16% to 54%, using standard or HS assay respectively, p = 0.001). Troponin positivity was associated with a twofold increased risk of long in-hospital diagnostic time (OR 1.92, 95% CI 1.05-3.52, p = 0.03), but not with in-hospital mortality. The combination of positive troponin and ACS-like ECG abnormalities resulted in a significantly increased risk of inappropriate therapy due to a misdiagnosis of ACS (OR 2.48, 95% CI 1.12-5.54, p = 0.02). Patients with AHF were identified by the presence of dyspnea as presentation symptom or radiological signs of pulmonary congestion or cardiogenic shock. The overall frequency of AHF was 28 % (32% type A vs. 20% type B AAS, p = 0.01). AHF was due to a variety of pathophysiological mechanisms including cardiac tamponade (26%), aortic regurgitation (25%), myocardial ischemia (17%), hypertensive crisis (10%). AHF was associated with increased surgical delay and with increased risk of in-hospital death (adjusted OR 1.97 95% CI1.13-3.37,p=0.01). Conclusions: Troponin positivity (particularly HS) was a frequent finding in AAS. Abnormal troponin values were strongly associated with ACS-like ECG findings, in-hospital diagnostic delay, and inappropriate therapy. AHF was associated with increased surgical delay and was an independent predictor of in-hospital mortality.

Simulating event related potentials in tasks involving conflict resolution: a neural network

In this thesis, the main Executive Control theories are exposed. Methods typical of Cognitive and Computational Neuroscience are introduced and the role of behavioural tasks involving conflict resolution in the response elaboration, after the presentation of a stimulus to the subject, are highlighted. In particular, the Eriksen Flanker Task and its variants are discussed. Behavioural data, from scientific literature, are illustrated in terms of response times and error rates. During experimental behavioural tasks, EEG is registered simultaneously. Thanks to this, event related potential, related with the current task, can be studied. Different theories regarding relevant event related potential in this field - such as N2, fERN (feedback Error Related Negativity) and ERN (Error Related Negativity) – are introduced. The aim of this thesis is to understand and simulate processes regarding Executive Control, including performance improvement, error detection mechanisms, post error adjustments and the role of selective attention, with the help of an original neural network model. The network described here has been built with the purpose to simulate behavioural results of a four choice Eriksen Flanker Task. Model results show that the neural network can simulate response times, error rates and event related potentials quite well. Finally, results are compared with behavioural data and discussed in light of the mentioned Executive Control theories. Future perspective for this new model are outlined.

Modulation of network excitability and epileptiform activity in the hippocampus of immature rats by the activation of GlyRs

Epileptic seizures are the manifestations of epilepsy, which is a major neurological disorder and occurs with a high incidence during early childhood. A fundamental mechanism underlying epileptic seizures is loss of balance between neural excitation and inhibition toward overexcitation. Glycine receptor (GlyR) is ionotropic neurotransmitter receptor that upon binding of glycine opens an anion pore and mediates in the adult nervous system a consistent inhibitory action. While previously it was assumed that GlyRs mediate inhibition mainly in the brain stem and spinal cord, recent studies reported the abundant expression of GlyRs throughout the brain, in particular during neuronal development. But no information is available regarding whether activation of GlyRs modulates neural network excitability and epileptiform activities in the immature central nervous system (CNS). Therefore the study in this thesis addresses the role of GlyRs in the modulation of neuronal excitability and epileptiform activity in the immature rat brain. By using in vitro intact corticohippocampal formation (CHF) of rats at postnatal days 4-7 and electrophysiological methods, a series of pharmacological examinations reveal that GlyRs are directly implicated in the control of hippocampal excitation levels at this age. In this thesis I am able to show that GlyRs are functionally expressed in the immature hippocampus and exhibit the classical pharmacology of GlyR, which can be activated by both glycine and the presumed endogenous agonist taurine. This study also reveals that high concentration of taurine is anticonvulsive, but lower concentration of taurine is proconvulsive. A substantial fraction of both the pro- and anticonvulsive effects of taurine is mediated via GlyRs, although activation of GABAA receptors also considerably contributes to the taurine effects. Similarly, glycine exerts both pro- and anticonvulsive effects at low and high concentrations, respectively. The proconvulsive effects of taurine and glycine depend on NKCC1-mediated Cl- accumulation, as bath application of NKCC1 inhibitor bumetanide completely abolishes proconvulsive effects of low taurine and glycine concentrations. Inhibition of GlyRs with low concentration of strychnine triggers epileptiform activity in the CA3 region of immature CHF, indicating that intrinsically an inhibitory action of GlyRs overwhelms its depolarizing action in the immature hippocampus. Additionally, my study indicates that blocking taurine transporters to accumulate endogenous taurine reduces epileptiform activity via activation of GABAA receptors, but not GlyRs, while blocking glycine transporters has no observable effect on epileptiform activity. From the main results of this study it can be concluded that in the immature rat hippocampus, activation of GlyRs mediates both pro- and anticonvulsive effects, but that a persistent activation of GlyRs is required to prevent intrinic neuronal overexcitability. In summary, this study uncovers an important role of GlyRs in the modulation of neuronal excitability and epileptiform activity in the immature rat hippocampus, and indicates that glycinergic system can potentially be a new therapeutic target against epileptic seizures of children.

Hierarchical Approach for Survivable Network Design

A central design challenge facing network planners is how to select a cost-effective network configuration that can provide uninterrupted service despite edge failures. In this paper, we study the Survivable Network Design (SND) problem, a core model underlying the design of such resilient networks that incorporates complex cost and connectivity trade-offs. Given an undirected graph with specified edge costs and (integer) connectivity requirements between pairs of nodes, the SND problem seeks the minimum cost set of edges that interconnects each node pair with at least as many edge-disjoint paths as the connectivity requirement of the nodes. We develop a hierarchical approach for solving the problem that integrates ideas from decomposition, tabu search, randomization, and optimization. The approach decomposes the SND problem into two subproblems, Backbone design and Access design, and uses an iterative multi-stage method for solving the SND problem in a hierarchical fashion. Since both subproblems are NP-hard, we develop effective optimization-based tabu search strategies that balance intensification and diversification to identify near-optimal solutions. To initiate this method, we develop two heuristic procedures that can yield good starting points. We test the combined approach on large-scale SND instances, and empirically assess the quality of the solutions vis-à-vis optimal values or lower bounds. On average, our hierarchical solution approach generates solutions within 2.7% of optimality even for very large problems (that cannot be solved using exact methods), and our results demonstrate that the performance of the method is robust for a variety of problems with different size and connectivity characteristics.

Analysis Methodology for Flow-level Evaluation of a Hybrid Mobile-Sensor Network

Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper focuses on a hybrid mobile-sensor network identify- ing potential advantages and challenges of its use and defining feasible applications. The main value of the paper, however, is in the proposed analysis approach to evaluate the performance at the mobile network side given the mixed mobile-sensor traffic. The approach combines packet- level analysis with modelling of flow-level behaviour and can be applied for the study of various application scenarios. In this paper we consider two applications with distinct traffic models namely multimedia traffic and best-effort traffic.

UAVNet: A Mobile Wireless Mesh Network Using Unmanned Aerial Vehicles

We developed UAVNet, a framework for the autonomous deployment of a flying Wireless Mesh Network using small quadrocopter-based Unmanned Aerial Vehicles (UAVs). The flying wireless mesh nodes are automatically interconnected to each other and building an IEEE 802.11s wireless mesh network. The implemented UAVNet prototype is able to autonomously interconnect two end systems by setting up an airborne relay, consisting of one or several flying wireless mesh nodes. The developed software includes basic functionality to control the UAVs and to setup, deploy, manage, and monitor a wireless mesh network. Our evaluations have shown that UAVNet can significantly improve network performance.

Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations

PURPOSE: There is a need for valid and reliable short scales that can be used to assess social networks and social supports and to screen for social isolation in older persons. DESIGN AND METHODS: The present study is a cross-national and cross-cultural evaluation of the performance of an abbreviated version of the Lubben Social Network Scale (LSNS-6), which was used to screen for social isolation among community-dwelling older adult populations in three European countries. Based on the concept of lack of redundancy of social ties we defined clinical cut-points of the LSNS-6 for identifying persons deemed at risk for social isolation. RESULTS: Among all three samples, the LSNS-6 and two subscales (Family and Friends) demonstrated high levels of internal consistency, stable factor structures, and high correlations with criterion variables. The proposed clinical cut-points showed good convergent validity, and classified 20% of the respondents in Hamburg, 11% of those in Solothurn (Switzerland), and 15% of those in London as at risk for social isolation. IMPLICATIONS: We conclude that abbreviated scales such as the LSNS-6 should be considered for inclusion in practice protocols of gerontological practitioners. Screening older persons based on the LSNS-6 provides quantitative information on their family and friendship ties, and identifies persons at increased risk for social isolation who might benefit from in-depth assessment and targeted interventions.

Outcomes and patterns of failure in solitary plasmacytoma: a multicenter Rare Cancer Network study of 258 patients

PURPOSE: To assess the outcomes and patterns of failure in solitary plasmacytoma (SP). METHODS AND MATERIALS: The data from 258 patients with bone (n = 206) or extramedullary (n = 52) SP without evidence of multiple myeloma (MM) were collected. A histopathologic diagnosis was obtained for all patients. Most (n = 214) of the patients received radiotherapy (RT) alone; 34 received chemotherapy and RT, and 8 surgery alone. The median radiation dose was 40 Gy. The median follow-up was 56 months (range 7-245). RESULTS: The median time to MM development was 21 months (range 2-135), with a 5-year probability of 45%. The 5-year overall survival, disease-free survival, and local control rate was 74%, 50%, and 86%, respectively. On multivariate analyses, the favorable factors were younger age and tumor size <4 cm for survival; younger age, extramedullary localization, and RT for disease-free survival; and small tumor and RT for local control. Bone localization was the only predictor of MM development. No dose-response relationship was found for doses >30 Gy, even for larger tumors. CONCLUSION: Progression to MM remains the main problem. Patients with extramedullary SP had the best outcomes, especially when treated with moderate-dose RT. Chemotherapy and/or novel therapies should be investigated for bone or bulky extramedullary SP.

Drug eluting and bare metal stents in people with and without diabetes: collaborative network meta-analysis

Objective To compare the effectiveness and safety of three types of stents (sirolimus eluting, paclitaxel eluting, and bare metal) in people with and without diabetes mellitus. Design Collaborative network meta-analysis. Data sources Electronic databases (Medline, Embase, the Cochrane Central Register of Controlled Trials), relevant websites, reference lists, conference abstracts, reviews, book chapters, and proceedings of advisory panels for the US Food and Drug Administration. Manufacturers and trialists provided additional data. Review methods Network meta-analysis with a mixed treatment comparison method to combine direct within trial comparisons between stents with indirect evidence from other trials while maintaining randomisation. Overall mortality was the primary safety end point, target lesion revascularisation the effectiveness end point. Results 35 trials in 3852 people with diabetes and 10 947 people without diabetes contributed to the analyses. Inconsistency of the network was substantial for overall mortality in people with diabetes and seemed to be related to the duration of dual antiplatelet therapy (P value for interaction 0.02). Restricting the analysis to trials with a duration of dual antiplatelet therapy of six months or more, inconsistency was reduced considerably and hazard ratios for overall mortality were near one for all comparisons in people with diabetes: sirolimus eluting stents compared with bare metal stents 0.88 (95% credibility interval 0.55 to 1.30), paclitaxel eluting stents compared with bare metal stents 0.91 (0.60 to 1.38), and sirolimus eluting stents compared with paclitaxel eluting stents 0.95 (0.63 to 1.43). In people without diabetes, hazard ratios were unaffected by the restriction. Both drug eluting stents were associated with a decrease in revascularisation rates compared with bare metal stents in people both with and without diabetes. Conclusion In trials that specified a duration of dual antiplatelet therapy of six months or more after stent implantation, drug eluting stents seemed safe and effective in people both with and without diabetes.