The rational search for selective anticancer derivatives of the peptide Trichogin GA IV: a multi-technique biophysical approach

Peptaibols are peculiar peptides produced by fungi as weapons against other microorganisms. Previous studies showed that peptaibols are promising peptide-based drugs because they act against cell membranes rather than a specific target, thus lowering the possibility of the onset of multi-drug resistance, and they possess non-coded alpha-amino acid residues that confer proteolytic resistance. Trichogin GA IV (TG) is a short peptaibol displaying antimicrobial and cytotoxic activity. In the present work, we studied thirteen TG analogues, adopting a multidisciplinary approach. We showed that the cytotoxicity is tuneable by single amino-acids substitutions. Many analogues maintain the same level of non-selective cytotoxicity of TG and three analogues are completely non-toxic. Two promising lead compounds, characterized by the introduction of a positively charged unnatural amino-acid in the hydrophobic face of the helix, selectively kill T67 cancer cells without affecting healthy cells. To explain the determinants of the cytotoxicity, we investigated the structural parameters of the peptides, their cell-binding properties, cell localization, and dynamics in the membrane, as well as the cell membrane composition. We show that, while cytotoxicity is governed by the fine balance between the amphipathicity and hydrophobicity, the selectivity depends also on the expression of negatively charged phospholipids on the cell surface

Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and follow-up data

<p>Abstract</p> <p>Background</p> <p>Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression data and clinico-pathological data through a combination of available and newly developed processing tools.</p> <p>Results</p> <p>We developed Survival Online (available at <url>http://ada.dist.unige.it:8080/enginframe/bioinf/bioinf.xml</url>), a Web-based system that allows for the analysis of Affymetrix GeneChip microarrays by using a parallel version of dChip. The user is first enabled to select pre-loaded datasets or single samples thereof, as well as single genes or lists of genes. Expression values of selected genes are then correlated with sample annotation data by uni- or multi-variate Cox regression and survival analyses. The system was tested using publicly available breast cancer datasets and GO (Gene Ontology) derived gene lists or single genes for survival analyses.</p> <p>Conclusion</p> <p>The system can be used by bio-medical researchers without specific computation skills to validate potential biomarkers or multi-gene classifiers. The design of the service, the parallelization of pre-processing tasks and the implementation on an HPC (High Performance Computing) environment make this system a useful tool for validation on several independent datasets.</p

A Grid-based solution for management and analysis of microarrays in distributed experiments

Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip® Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of uploading and accessing distributed datasets through the Grid middleware and against its ability in managing the execution of jobs on distributed computational resources. Results from the Grid test will be discussed in a further paper

Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine

Diffusion kurtosis imaging (DKI) has undisputed advantages over the more classical diffusion magnetic resonance imaging (dMRI) as witnessed by the fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized, in particular in spinal cord (SC) imaging, because of its inherently demanding technological requirements. Due to its extreme sensitivity to non-Gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, which are not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between the SC region and the brain above, managing to apply such a method to the neonatal cohort becomes of utmost importance. This study will (i) mention current methodological challenges associated with the application of advanced dMRI methods, like DKI, in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox for handling the DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present results of its application in a pilot clinical case study. With the proposed pipeline, we preliminarily show that DKI is more sensitive than DTI-related measures to alterations caused by brain white matter injuries in the underlying cervical SC

A digital repository with an extensible data model for biobanking and genomic analysis management

Motivation: Molecular biology laboratories require extensive metadata to improve data collection and analysis. The heterogeneity of the collected metadata grows as research is evolving in to international multi-disciplinary collaborations and increasing data sharing among institutions. Single standardization is not feasible and it becomes crucial to develop digital repositories with flexible and extensible data models, as in the case of modern integrated biobanks management. Results: We developed a novel data model in JSON format to describe heterogeneous data in a generic biomedical science scenario. The model is built on two hierarchical entities: processes and events, roughly corresponding to research studies and analysis steps within a single study. A number of sequential events can be grouped in a process building up a hierarchical structure to track patient and sample history. Each event can produce new data. Data is described by a set of user-defined metadata, and may have one or more associated files. We integrated the model in a web based digital repository with a data grid storage to manage large data sets located in geographically distinct areas. We built a graphical interface that allows authorized users to define new data types dynamically, according to their requirements. Operators compose queries on metadata fields using a flexible search interface and run them on the database and on the grid. We applied the digital repository to the integrated management of samples, patients and medical history in the BIT-Gaslini biobank. The platform currently manages 1800 samples of over 900 patients. Microarray data from 150 analyses are stored on the grid storage and replicated on two physical resources for preservation. The system is equipped with data integration capabilities with other biobanks for worldwide information sharing. Conclusions: Our data model enables users to continuously define flexible, ad hoc, and loosely structured metadata, for information sharing in specific research projects and purposes. This approach can improve sensitively interdisciplinary research collaboration and allows to track patients' clinical records, sample management information, and genomic data. The web interface allows the operators to easily manage, query, and annotate the files, without dealing with the technicalities of the data grid.Peer reviewe

Automatic segmentation of deep intracerebral electrodes in computed tomography scans

Background: Invasive monitoring of brain activity by means of intracerebral electrodes is widely practiced to improve pre-surgical seizure onset zone localization in patients with medically refractory seizures. Stereo-Electroencephalography (SEEG) is mainly used to localize the epileptogenic zone and a precise knowledge of the location of the electrodes is expected to facilitate the recordings interpretation and the planning of resective surgery. However, the localization of intracerebral electrodes on post-implant acquisitions is usually time-consuming (i.e., manual segmentation), it requires advanced 3D visualization tools, and it needs the supervision of trained medical doctors in order to minimize the errors. In this paper we propose an automated segmentation algorithm specifically designed to segment SEEG contacts from a thresholded post-implant Cone-Beam CT volume (0.4 mm, 0.4 mm, 0.8 mm). The algorithm relies on the planned position of target and entry points for each electrode as a first estimation of electrode axis. We implemented the proposed algorithm into DEETO, an open source C++ prototype based on ITK library. Results: We tested our implementation on a cohort of 28 subjects in total. The experimental analysis, carried out over a subset of 12 subjects (35 multilead electrodes; 200 contacts) manually segmented by experts, show that the algorithm: (i) is faster than manual segmentation (i.e., less than 1s/subject versus a few hours) (ii) is reliable, with an error of 0.5 mm +/- 0.06 mm, and (iii) it accurately maps SEEG implants to their anatomical regions improving the interpretability of electrophysiological traces for both clinical and research studies. Moreover, using the 28-subject cohort we show here that the algorithm is also robust (error <0.005 mm) against deep-brain displacements (<12 mm) of the implanted electrode shaft from those planned before surgery. Conclusions: Our method represents, to the best of our knowledge, the first automatic algorithm for the segmentation of SEEG electrodes. The method can be used to accurately identify the neuroanatomical loci of SEEG electrode contacts by a non-expert in a fast and reliable manner.Peer reviewe

a grid enabled web platform for integrated digital biobanking in paediatrics

Motivation and Objectives A solid and integrated biobanking framework is an absolute requirement for high quality investigation in paediatric tumours. The overall goal of our activity is to design and develop a centralized Digital Biobank prototype able to integrate and interconnect an increasing number of local biobanks situated in various centres across Europe. As a first step, we are designing a web-based repository to store all tissue and genomic data from paediatric tumours collected by the G. Gaslini Children's Hospital, in Genoa. The repository satisfies flexibility and extensibility criteria, and is being deployed on a data Grid architecture (Bote-Lorenzo et al., 2004). Methods The repository is designed to contain data from all the tissue and blood samples obtained from infants and children affected by paediatric tumours, such as primary bone tumour and neuroblastoma. Many samples may be extracted from the same patient in a single visit or surgical operation; moreover from a single sample, nucleic acids (i.e. DNA and RNA) may be extracted for further analysis. These extractions could happen more than once, even at a distance of months or even years, if required. In order to satisfy the strict requirements above and ensure the extensibility of the repository, we have adopted a process/event model, already used for designing data and image repositories in Neuroscience (Corradi et al., 2012). The process/event model is a multipurpose taxonomic schema composed by two main generic objects: processes and events. An event can be any 'atomic' operation that is performed on patients or samples, or any processing of data or everything else related to the repository administration and management. A process is defined as a group of sequential events or sub-processes related to an activity, allowing the creation of a sort of hierarchical structure. As an example, the storage of a DNA sample in a specified location within a -80°C freezer and a post-processing step (such as differential expression, survival or correlation/anti-correlation analysis on microarray data) are single events, pertaining respectively to the more general 'Nucleic Acid Extraction' and 'Data Mining' processes. Platform Architecture The repository has a client-server architecture and it is composed by three main components, as shown in Figure 1: Repository portal Database Grid storage The repository portal is designed to make the storage and the navigation of data and information easy, through a simple and transparent web interface. It is a Java Enterprise Edition web application based on several existing open source tools for the development of web applications. The basis of the portal consists in a framework that relies on an Apache Tomcat web application container. It incorporates a database interface layer built through MyBatis, a persistence framework that automates the mapping between SQL databases and objects in Java. To provide users with highly interactive interfaces, some components are designed using the Asynchronous Javascript and XML (AJAX) programming technique. Wherever possible information is exchanged in XML or JavaScript Object Notation (JSON) format. The web portal represents the main access point to all the functionalities available through the overall integration platform, and exposes both user and administrator interfaces. T he repository itself is based on a MySQL database. The database design is fundamental in order to make the repository highly flexible and easily extensible. The core of the database is formed by the two previously described entities: processes and events and their relationships to data and metadata. Existing processes and events are contained in two homonymous tables. Each element in the event table refers to an element in the data table. The information inside the latter represents all the data inserted in the repository. These data can be associated with one or more files accordingly to their data type. The file table contains the logical path of all the stored files. The repository can be configured to store the metadata totally or partially within the database. In this latter case, the metadata are stored as XML descriptions inside the data table, to display the data in a rapid and dynamic way using XSL Transformations, and as records of specific metadata tables, to perform complex queries in an easier way. All data files are contained in the Grid storage, so the database doesn't really have to deal with hundreds of GB of data. Moreover, the number of operators should be quite small, thus making MySQL a reasonable choice as a database. The storage subsystem has been built around the iRODS data grid software (Rajasketar et al., 2010), chosen among others because it allows building a federated and distributed data storage system without the need of central components. Being able to deal with a huge amount of metadata, iRODS is widely used by the research community, also for Next Generation Sequencing Projects (Chiang et al., 2011). Careful attention has been given to security and privacy issues. All data are anonymised and cannot be linked in any way to patients' names, since the connection between clinical and personal data is done using unique identifiers managed exclusively by clinicians. Administrators are able to control users' access by creating groups and their association with pages and functions, define processes, events and all their relationships, define new data types and related metadata, associate them with the related events and manage available ontologies. Normal users, according to their assigned permissions, can insert new data, retrieve patients' information and view all the related data, download stored information, explore processes together with all the related events, data and metadata to have a global picture. The integrated system we envision at a European level will take advantage of the data Grid features provided by iRODS. Each hospital or biobank involved in the virtual community may have a local database and a dedicated separated iRODS system (called iRODS zone) where its own metadata and files can be saved. All the iRODS zones in the community will be federated. Federated iRODS zones are administered separately, but the users in the multiple zones, if given permission, will be able to access data stored in the other zones. If more hospital or research groups are working on the same project or using the same data structure, they may share a single iRODS zone and database. To provide access to the various local databases, federated database systems will be taken into account. Results and Discussion A first prototype of the repository is currently being tested at the Giannina Gaslini Institute, in Genoa. Information on over 1300 tissue samples, with their related DNA and RNA purified samples, have been stored together with administrative and clinical data from more than 700 patients. Three kinds of genomic analyses (i.e. event types) are currently provided, two for DNA samples - Comparative Genomic Hybridization (CGH) array and Multiplex Ligation-dependent Probe Amplification (MLPA) - and one for RNA - microarray analysis. For each analysis it is possible to store one or more files and user customized metadata. New data types can be configured via administrator interface, without additional programming, when new types of analyses or processing are required. The extensibility of our data model with user-defined data types and metadata is a crucial aspect of our implementation. As mentioned before, future developments will comprise the integration of our local biobank at the Gaslini Institute, with similar digital structures located across Europe. We are currently testing a distributed storage configuration, implementing data management policies expressed as rules that are interpreted by the iRODS Rule Engine. Acknowledgements Our research activity is performed in the framework of the 'European Network for Cancer Research in Children and Adolescents' (ENCCA) European project. References Bote-Lorenzo ML, Dimitriadis YA and Gomez-Sanchez E (2004) Grid characteristics and uses: a grid definition, Proceedings of the First European Across Grids Conference, ACG'03, Springer-Verlag, LNCS 2970, 291-298. doi:10.1007/978-3-540-24689-3_36 Chiang GT, Clapham P, Qi G, Sale K and Coates G (2011) Implementing a genomic data management system using iRODS in the Wellcome Trust Sanger Institute BMC Bioinformatics 2011, 12:361. doi:10.1186/1471-2105-12-361 Corradi L, Porro I, Schenone A, Momeni P, Ferrari , Nobili F, Ferrara M, Arnulfo G and Fato MM (2012) A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience, BMC Medical Informatics and Decision Making (in press). JSON (JavaScript Object Notation), [online], http://www.json.org/. MyBatis, [online], http://www.mybatis.org. Rajasketar A, Moore R, Hou C et al. (2010) iRODS Primer: Integrated Rule-Oriented Data Systems. Morgan & Claypool. doi:10.2200/S00233ED1V01Y200912ICR012 XSL Transformations [online], http://www.w3.org/TR/xslt. Note: Figures and tables are available in PDF version only

Mutant MYO1F alters the mitochondrial network and induces tumor proliferation in thyroid cancer

Familial aggregation is a significant risk factor for the development of thyroid cancer and Familial Non-Medullary Thyroid Cancer (FNMTC) accounts for 5-7% of all NMTC. Whole Exome Sequencing analysis in the family affected by FNMTC with oncocytic features where our group previously identified a predisposing locus on chromosome 19p13.2, revealed a novel heterozygous mutation (c.400G>A, NM_012335; p.Gly134Ser) in exon 5 of MYO1F, mapping to the linkage locus. In the thyroid FRTL-5 cell model stably expressing the mutant MYO1F p.Gly134Ser protein we observed an altered mitochondrial network, with increased mitochondrial mass and a significant increase of both intracellular and extracellular Reactive Oxygen Species, compared to cells expressing the wild-type protein or carrying the empty vector. The mutation conferred a significant advantage in colony formation, invasion and anchorage independent growth. These data were corroborated by in vivo studies in zebrafish, since we demonstrated that the mutant MYO1F p.Gly134Ser, when overexpressed, can induce proliferation in whole vertebrate embryos, compared to the wild-type one. MYO1F screening in additional 192 FNMTC families identified another variant in exon 7, which leads to exon skipping, and is predicted to alter the ATP-binding domain in MYO1F. Our study identified for the first time a role for MYO1F in NMTC. This article is protected by copyright. All rights reserved