Gene expression signatures in primary immunodeficiencies: the experience from human disease and mouse models

Extensive research on molecular genetics in recent decades has provided a wealth of information regarding the underlying mechanisms of primary immunodeficiency diseases. The microarray technology has made its entry into the molecular biology research area and hereby enabled signature expression profiling of whole species genomes. Perhaps no other methodological approach has transformed molecular biology more in recent years than the use of microarrays. Microarray technology has led the way from studies of the individual biological functions of a few related genes, proteins or, at best, pathways towards more global investigations of cellular activity. The development of this technology immediately yielded new and interesting information, and has produced more data than can be currently dealt with. It has also helped to realize that even a 'horizontally exhaustive' molecular analysis is insufficient. Applications of this tool in primary immunodeficiency studies have generated new information, which has led to a better understanding of the underlying basic biology of the diseases. Also, the technology has been used as an exploratory tool to disease genes in immunodeficiency diseases of unknown cause as in the case of the CD3Delta-chain and the MAPBPIP deficiency. For X-linked agammaglobulinemia, the technique has provided better understanding of the genes influenced by Btk. There is considerable hope that the microarray technology will lead to a better understanding of disease processes and the molecular phenotypes obtained from microarray experiments may represent a new tool for diagnosis of the disease.     

Developing a scuba trail vulnerability index (STVI): a case study from a Mediterranean MPA

Scuba diving is now one of the major form of commercial use of marine protected areas (MPAs) around the world and the control of its potential impacts on the marine environment represents a fundamental key to manage this recreational activity in highly dived areas. A potential tool to tackle such issues has been thought to be the definition of a value of recreational carrying capacity of an area, but this approach has been rarely considered management-effective. Therefore, the first step for effectively managing scuba-diving should be ‘bottom-up’: characterizing the benthic communities potentially affected by diving and evaluating their vulnerability. Aim of this paper is to propose a tool to define an index of vulnerability for dive trails (STVI: scuba trail vulnerability index). This has taken into consideration both physical and biological features of each trail. All the considered features are represented by non-quantitative variables, because either they are purely qualitative or their quantitative measurement is impractical. The management of such qualitative information and its translation into a formal methodology was performed by means of fuzzy logic, which has been repeatedly proposed as a powerful technique to develop indices of environmental quality. The approach adopted in this study provided a useful tool for the preliminary assessment of the potential vulnerability of benthic assemblages to scuba-diving and may represent an alternative method to the assessment of carrying capacity. The application of this index will enable management strategies for potentially reducing the degradation of benthic organisms/assemblages, and allowing a sustainable use of MPAs.     

The Macaque Social Responsiveness Scale (mSRS): A Rapid Screening Tool for Assessing Variability in the Social Responsiveness of Rhesus Monkeys (Macaca mulatta)

Understanding the biological mechanisms underlying human neuropsychiatric disorders, such as autism spectrum disorder (ASD), has been hindered by the lack of a robust, translational animal model. Rhesus monkeys (Macaca mulatta) display many of the same social behaviors that are affected in ASD, making them an excellent animal species in which to model social impairments. However, the social impairments associated with ASD may reflect extreme ends of a continuous distribution of traits. Thus, to validate the rhesus monkey as an animal model for studying social impairments that has strong translational relevance for ASD, researchers need an easily-implemented measurement tool that can quantify variation in social behavior dimensionally. The Social Responsiveness Scale (SRS) is a 65-item survey that identifies both typical and atypical social behaviors in humans that covary with ASD symptom severity. A chimpanzee SRS has already been validated and the current study adapted this tool for use in the rhesus monkey (mSRS). Fifteen raters completed the mSRS for 105 rhesus monkeys living at the Yerkes National Primate Research Center. The mSRS scores showed a unimodal distribution with a positive skew that identified 6 statistical outliers. Inter-rater reliability was very strong, but only 17 of the 36 questions showed positive intra-item reliability. The results of an exploratory factor analysis identified 3 factors that explained over 60% of the variance, with 12 items significantly loading onto the primary factor. These items reflected behaviors associated with social avoidance, social anxiety or inflexibility and social confidence. These initial findings are encouraging and suggest that variability in the social responsiveness of rhesus monkeys can be quantified using the mSRS: a tool that has strong translational relevance for human disorders. With further modification, the mSRS may provide an promising new direction for research on the biological mechanisms underlying social impairments.     

A four-dimensional simulation model of tumour response to radiotherapy in vivo: parametric validation considering radiosensitivity, genetic profile and fractionation

The aim of this paper is to present the current state of a four-dimensional simulation model of solid tumour growth and response to radiotherapy developed by our group. The most prominent points of the algorithms describing the fundamental biological phenomena involved are outlined. A specific application of the model to a selected clinical case of glioblastoma multiforme is described and comparative studies are performed, using various exploratory values of the model parameters. Qualitative agreement with clinical observations has been achieved. Special emphasis is laid on the variability of radiosensitivity parameters throughout the cell cycle and on the influence of the genetic profile of the tumour on its radiosensitivity. The results of the simulation are three-dimensionally reconstructed. A valuable tool for getting insight into the biology of tumour growth and response to radiotherapy and at the same time an advanced patient specific decision support system is expected to emerge after the completion of the necessary extensive clinical evaluation.     

Videomicroscopic extraction of specific information on cell proliferation and migration in vitro

In vitro cell imaging is a useful exploratory tool for cell behavior monitoring with a wide range of applications in cell biology and pharmacology. Combined with appropriate image analysis techniques, this approach has been shown to provide useful information on the detection and dynamic analysis of cell events. In this context, numerous efforts have been focused on cell migration analysis. In contrast, the cell division process has been the subject of fewer investigations. The present work focuses on this latter aspect and shows that, in complement to cell migration data, interesting information related to cell division can be extracted from phase-contrast time-lapse image series, in particular cell division duration, which is not provided by standard cell assays using endpoint analyses. We illustrate our approach by analyzing the effects induced by two sigma-1 receptor ligands (haloperidol and 4-IBP) on the behavior of two glioma cell lines using two in vitro cell models, i.e., the low-density individual cell model and the high-density scratch wound model. This illustration also shows that the data provided by our approach are suggestive as to the mechanism of action of compounds, and are thus capable of informing the appropriate selection of further time-consuming and more expensive biological evaluations required to elucidate a mechanism.     

Enabling dynamic network analysis through visualization in TVNViewer

ABSTRACT: BACKGROUND: Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development of TVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. RESULTS: In this paper, we demonstrate visualization techniques for dynamic network analysis by using TVNViewer to analyze yeast cell cycle and breast cancer progression datasets. CONCLUSIONS: TVNViewer is a powerful new visualization tool for the analysis of biological networks that change across time or space.     

Improved detection of overrepresentation of Gene-Ontology annotations with parent child analysis

MOTIVATION: High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic such as differential expression. Exploring Gene Ontology (GO) annotations for such lists of genes has become a widespread practice to get first insights into the potential biological meaning of the experiment. The standard statistical approach to measuring overrepresentation of GO terms cannot cope with the dependencies resulting from the structure of GO because they analyze each term in isolation. Especially the fact that annotations are inherited from more specific descendant terms can result in certain types of false-positive results with potentially misleading biological interpretation, a phenomenon which we term the inheritance problem. RESULTS: We present here a novel approach to analysis of GO term overrepresentation that determines overrepresentation of terms in the context of annotations to the term's parents. This approach reduces the dependencies between the individual term's measurements, and thereby avoids producing false-positive results owing to the inheritance problem. ROC analysis using study sets with overrepresented GO terms showed a clear advantage for our approach over the standard algorithm with respect to the inheritance problem. Although there can be no gold standard for exploratory methods such as analysis of GO term overrepresentation, analysis of biological datasets suggests that our algorithm tends to identify the core GO terms that are most characteristic of the dataset being analyzed.     

Onto-Tools,the toolkit of the modern biologist: Onto-Express,Onto-Compare,Onto-Design and Onto-Translate

Onto-Tools is a set of four seamlessly integrated databases: Onto-Express, Onto-Compare, Onto-Design and Onto-Translate. Onto-Express is able to automatically translate lists of genes found to be differentially regulated in a given condition into functional profiles characterizing the impact of the condition studied upon various biological processes and pathways. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. Once the initial exploratory analysis identified a number of relevant biological processes, specific mechanisms of interactions can be hypothesized for the conditions studied. Currently, many commercial arrays are available for the investigation of specific mechanisms. Each such array is characterized by a biological bias determined by the extent to which the genes present on the array represent specific pathways. Onto-Compare is a tool that allows efficient comparisons of any sets of commercial or custom arrays. Using Onto-Compare, a researcher can determine quickly which array, or set of arrays, covers best the hypotheses studied. In many situations, no commercial arrays are available for specific biological mechanisms. Onto-Design is a tool that allows the user to select genes that represent given functional categories. Onto-Translate allows the user to translate easily lists of accession numbers, UniGene clusters and Affymetrix probes into one another. All tools above are seamlessly integrated. The Onto-Tools are available online at http://vortex.cs.wayne.edu/Projects.html.     

Differences in spatio-temporal behavior of zebrafish in the open tank paradigm after a short-period confinement into dark and bright environments

The open tank paradigm, also known as novel tank diving test, is a protocol used to evaluate the zebrafish behavior. Several characteristics have been described for this species, including scototaxis, which is the natural preference for dark environments in detriment of bright ones. However, there is no evidence regarding the influence of "natural stimuli" in zebrafish subjected to novelty-based paradigms. In this report, we evaluated the spatio-temporal exploratory activity of the short-fin zebrafish phenotype in the open tank after a short-period confinement into dark/bright environments. A total of 44 animals were individually confined during a 10-min single session into one of three environments: black-painted, white-painted, and transparent cylinders (dark, bright, and transparent groups). Fish were further subjected to the novel tank test and their exploratory profile was recorded during a 15-min trial. The results demonstrated that zebrafish increased their vertical exploratory activity during the first 6-min, where the bright group spent more time and travelled a higher distance in the top area. Interestingly, all behavioral parameters measured for the dark group were similar to the transparent one. These data were confirmed by automated analysis of track and occupancy plots and also demonstrated that zebrafish display a classical homebase formation in the bottom area of the tank. A detailed spatio-temporal study of zebrafish exploratory behavior and the construction of representative ethograms showed that the experimental groups presented significant differences in the first 3-min vs. last 3-min of test. Although the main factors involved in these behavioral responses still remain ambiguous and require further investigation, the current report describes an alternative methodological approach for assessing the zebrafish behavior after a forced exposure to different environments. Additionally, the analysis of ethologically-relevant patterns across time could be a potential phenotyping tool to evaluate the zebrafish exploratory profile in the open tank task.     

Toward computational systems biology

The development and successful application of high-throughput technologies are transforming biological research. The large quantities of data being generated by these technologies have led to the emergence of systems biology, which emphasizes large-scale, parallel characterization of biological systems and integration of fragmentary information into a coherent whole. Complementing the reductionist approach that has dominated biology for the last century, mathematical modeling is becoming a powerful tool to achieve an integrated understanding of complex biological systems and to guide experimental efforts of engineering biological systems for practical applications. Here I give an overview of current mainstream approaches in modeling biological systems, highlight specific applications of modeling in various settings, and point out future research opportunities and challenges.     

Building Taxon Substitution Guidelines on a Biological Control Foundation

When a species becomes extinct, its ecological functions are lost as well. Taxon substitution is a controversial approach to restoring such functions via introduction of non‐native species known to serve similar functions elsewhere. Due to the possibility of nontarget effects from such introductions, taxon substitution has been proposed and implemented in only a few systems, but these attempts have successfully restored functions. As a conservation tool, taxon substitution bears similarity to biological control, wherein species are also introduced for their ecological function with consideration of potential nontarget effects. To improve both the safety and efficacy of taxon substitution, regulatory bodies that currently issue guidelines for biological control can do the same for taxon substitution. Indeed, many biological control guidelines would apply well to taxon substitution. We examine the standard practices followed by biological control programs and propose corresponding taxon substitution guidelines. Integration of taxon substitution into the existing national and international environmental management conversation will improve the tool and has the potential to enhance conservation efforts across a wide diversity of systems if appropriate and stringent precautions are taken.     

Environmental DNA analysis for macro-organisms: species distribution and more

In an era of severe biodiversity loss, biological monitoring is becoming increasingly essential. The analysis of environmental DNA (eDNA) has emerged as a new approach that could revolutionize the biological monitoring of aquatic ecosystems. Over the past decade, macro-organismal eDNA analysis has undergone significant developments and is rapidly becoming established as the golden standard for non-destructive and non-invasive biological monitoring. In this review, I summarize the development of macro-organismal eDNA analysis to date and the techniques used in this field. I also discuss the future perspective of these analytical methods in combination with sophisticated analytical techniques for DNA research developed in the fields of molecular biology and molecular genetics, including genomics, epigenomics, and single-cell technologies. eDNA analysis, which to date has been used primarily for determining the distribution of organisms, is expected to develop into a tool for elucidating the physiological state and behaviour of organisms. The fusion of microbiology and macrobiology through an amalgamation of these technologies is anticipated to lead to the future development of an integrated biology.     

Food webs: a ladder for picking strawberries or a practical tool for practical problems?

While food webs have provided a rich vein of research material over the last 50 years, they have largely been the subject matter of the pure ecologist working in natural habitats. While there are some notable exceptions to this trend, there are, as I explain in this paper, many applied questions that could be answered using a food web approach. The paper is divided into two halves. The first half provides a brief review of six areas where food webs have begun to be used as an applied tool: restoration ecology, alien species, biological control, conservation ecology, habitat management and global warming. The second half outlines five areas in which a food web approach could prove very rewarding: urban ecology, agroecology, habitat fragmentation, cross-habitat food webs and ecosystem services.     

Tat-mediated protein delivery in living Caenorhabditis elegans

The Tat protein from HIV-1 fused with heterologous proteins traverses biological membranes in a transcellular process called: protein transduction. This has already been successfully exploited in various biological models, but never in the nematode worm Caenorhabditis elegans. TAT-eGFP or GST-eGFP proteins were fed to C. elegans worms, which resulted in the specific localization of Tat-eGFP to epithelial intestinal cells. This system represents an efficient tool for transcellular transduction in C. elegans intestinal cells. Indeed, this approach avoids the use of tedious purification steps to purify the TAT fusion proteins and allows for rapid analyses of the transduced proteins. In addition, it may represent an efficient tool to functionally analyze the mechanisms of protein transduction as well as to complement RNAi/KO in the epithelial intestinal system. To sum up, the advantage of this technology is to combine the potential of bacterial expression system and the Tat-mediated transduction technique in living worm.     

An improved algorithm for anisotropic nonlinear diffusion for denoising cryo-tomograms

Cryo-electron tomography is an imaging technique with an unique potential for visualizing large complex biological specimens. It ensures preservation of the biological material but the resulting cryotomograms are extremely noisy. Sophisticated denoising techniques are thus essential for allowing the visualization and interpretation of the information contained in the cryotomograms. Here a software tool based on anisotropic nonlinear diffusion is described for filtering cryotomograms. The approach reduces local noise and meanwhile enhances both curvilinear and planar structures. In the program a novel solution of the partial differential equation has been implemented, which allows a reliable estimation of derivatives and, furthermore, reduces computation time and memory requirements. Several criteria have been included to automatically select the optimal stopping time. The behaviour of the denoising approach is tested for visualizing filamentous structures in cryotomograms.     

Identifying associations between pig pathologies using a multi-dimensional machine learning methodology

ABSTRACT: BACKGROUND: Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously. RESULTS: Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis) appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum) and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology. CONCLUSIONS: The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.     

Gene Clustering via Integrated Markov Models Combining Individual and Pairwise Features

Clustering of genes into groups sharing common characteristics is a useful exploratory technique for a number of subsequent computational analysis. A wide range of clustering algorithms have been proposed in particular to analyze gene expression data, but most of them consider genes as independent entities or include relevant information on gene interactions in a suboptimal way. We propose a probabilistic model that has the advantage to account for individual data (e.g., expression) and pairwise data (e.g., interaction information coming from biological networks) simultaneously. Our model is based on hidden Markov random field models in which parametric probability distributions account for the distribution of individual data. Data on pairs, possibly reflecting distance or similarity measures between genes, are then included through a graph, where the nodes represent the genes, and the edges are weighted according to the available interaction information. As a probabilistic model, this model has many interesting theoretical features. In addition, preliminary experiments on simulated and real data show promising results and points out the gain in using such an approach. Availability: The software used in this work is written in C++ and is available with other supplementary material at http://mistis.inrialpes.fr/people/forbes/transparentia/supplementary.html.     

Network,degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune system

Recently, the network paradigm, an application of graph theory to biology, has proven to be a powerful approach to gaining insights into biological complexity, and has catalyzed the advancement of systems biology. In this perspective and focusing on the immune system, we propose here a more comprehensive view to go beyond the concept of network. We start from the concept of degeneracy, one of the most prominent characteristic of biological complexity, defined as the ability of structurally different elements to perform the same function, and we show that degeneracy is highly intertwined with another recently-proposed organizational principle, i.e. 'bow tie architecture'. The simultaneous consideration of concepts such as degeneracy, bow tie architecture and network results in a powerful new interpretative tool that takes into account the constructive role of noise (stochastic fluctuations) and is able to grasp the major characteristics of biological complexity, i.e. the capacity to turn an apparently chaotic and highly dynamic set of signals into functional information.