Human Cytokinome: a new challenge for systems biology

Cytokines play an important role in the evolution of inflammatory processes. Therefore, they are also key components of the cancer evolution, a disease recognized to depend on chronic inflammation. On the whole, we define cytokinome as the totality of these proteins and their interactions in and around biological cells. Understanding the complex interaction network of cytokines in patients affected from cancers should be very useful both to follow the cancer evolution from its early steps and to define innovative therapeutic strategies by using systems biology approaches.     

The evolution of molecular biology into systems biology

Systems analysis has historically been performed in many areas of biology, including ecology, developmental biology and immunology. More recently, the genomics revolution has catapulted molecular biology into the realm of systems biology. In unicellular organisms and well-defined cell lines of higher organisms, systems approaches are making definitive strides toward scientific understanding and biotechnological applications. We argue here that two distinct lines of inquiry in molecular biology have converged to form contemporary systems biology.     

The nature of systems biology

The advent of functional genomics has enabled the molecular biosciences to come a long way towards characterizing the molecular constituents of life. Yet, the challenge for biology overall is to understand how organisms function. By discovering how function arises in dynamic interactions, systems biology addresses the missing links between molecules and physiology. Top-down systems biology identifies molecular interaction networks on the basis of correlated molecular behavior observed in genome-wide "omics" studies. Bottom-up systems biology examines the mechanisms through which functional properties arise in the interactions of known components. Here, we outline the challenges faced by systems biology and discuss limitations of the top-down and bottom-up approaches, which, despite these limitations, have already led to the discovery of mechanisms and principles that underlie cell function.     

Toward a conceptual framework for biology

Science progresses faster when researchers operate within an explicit framework of concepts and theories, but currently biology has no explicit, overarching conceptual framework and few general theories. The single general theory currently recognized is that of evolution, which was put forth by Charles Darwin 150 years ago. Recently, Scheiner and Willig (2008) explicated a similarly general theory of ecology. In this paper, using the theory of evolution as an exemplar, I discuss the nature of theory in biology and put forth an overarching theory, as well as new general theories for cells, organisms, and genetics. Along with the theories of evolution and ecology, these constitute a general conceptual framework for the biological sciences. This framework reveals linkages among the various parts of biology, makes explicit the assumptions behind more narrow theories and models, and provides new insights into the structures of biological theories. This framework can also be used as a teaching tool, moving the teaching of biology beyond the transference of a vast compendium of facts. My hope is that this essay will lead to a vigorous discussion and debate across all of biology about the nature and structure of its theories.     

(Glyco)sphingolipidology: an amazing challenge and opportunity for systems biology

Sphingolipids are found in essentially all eukaryotes and in some prokaryotes and viruses, where they influence cell structure, signaling and interactions with the extracellular environment. Because of the combinatorial nature of their biosynthesis, the sphingolipidome comprises untold thousands of species that encompass bioactive backbones and complex phospho- and glycolipids. Mass spectrometry is able to analyze a growing fraction of the sphingolipidome and is beginning to provide information about localization. Use of these structure specific, quantitative methods is producing insights, and surprises, regarding sphingolipid structure, metabolism, function and disease. Dealing with such large data sets poses special challenges for systems biology, but the intrinsic and elegant interrelationships among these compounds might provide a key to dealing with the complexity of the sphingolipidome.     

Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge

Background:

Genome sciences have experienced an increasing demand for efficient text-processing tools that can extract biologically relevant information from the growing amount of published literature. In response, a range of text-mining and information-extraction tools have recently been developed specifically for the biological domain. Such tools are only useful if they are designed to meet real-life tasks and if their performance can be estimated and compared. The BioCreative challenge (Critical Assessment of Information Extraction in Biology) consists of a collaborative initiative to provide a common evaluation framework for monitoring and assessing the state-of-the-art of text-mining systems applied to biologically relevant problems.

Results:

The Second BioCreative assessment (2006 to 2007) attracted 44 teams from 13 countries worldwide, with the aim of evaluating current information-extraction/text-mining technologies developed for one or more of the three tasks defined for this challenge evaluation. These tasks included the recognition of gene mentions in abstracts (gene mention task); the extraction of a list of unique identifiers for human genes mentioned in abstracts (gene normalization task); and finally the extraction of physical protein-protein interaction annotation-relevant information (protein-protein interaction task). The 'gold standard' data used for evaluating submissions for the third task was provided by the interaction databases MINT (Molecular Interaction Database) and IntAct.

Conclusion:

The Second BioCreative assessment almost doubled the number of participants for each individual task when compared with the first BioCreative assessment. An overall improvement in terms of balanced precision and recall was observed for the best submissions for the gene mention (F score 0.87); for the gene normalization task, the best results were comparable (F score 0.81) compared with results obtained for similar tasks posed at the first BioCreative challenge. In case of the protein-protein interaction task, the importance and difficulties of experimentally confirmed annotation extraction from full-text articles were explored, yielding different results depending on the step of the annotation extraction workflow. A common characteristic observed in all three tasks was that the combination of system outputs could yield better results than any single system. Finally, the development of the first text-mining meta-server was promoted within the context of this community challenge.

     

The systems biology of signaling pathways

Signaling networks play the central role in the regulation of processes in a single cell and in the entire body. A recent breakthrough in technologies for systems biology, which combine experimental and mathematical methods, permits scientists to model signaling pathways in an individual cell and in cell populations. This approach provides new information on mechanisms that regulate a variety of biological processes. Here we discuss the mathematical formalisms that are applied to signaling pathway modeling and relevant experimental methods.     

Cryo-electron tomography: The challenge of doing structural biology in situ

The mitotic segregation apparatus composed of microtubules and chromatin functions to faithfully partition a duplicated genome into two daughter cells. Microtubules exert extensional pulling force on sister chromatids toward opposite poles, whereas pericentric chromatin resists with contractile springlike properties. Tension generated from these opposing forces silences the spindle checkpoint to ensure accurate chromosome segregation. It is unknown how the cell senses tension across multiple microtubule attachment sites, considering the stochastic dynamics of microtubule growth and shortening. In budding yeast, there is one microtubule attachment site per chromosome. By labeling several chromosomes, we find that pericentromeres display coordinated motion and stretching in metaphase. The pericentromeres of different chromosomes exhibit physical linkage dependent on centromere function and structural maintenance of chromosomes complexes. Coordinated motion is dependent on condensin and the kinesin motor Cin8, whereas coordinated stretching is dependent on pericentric cohesin and Cin8. Linking of pericentric chromatin through cohesin, condensin, and kinetochore microtubules functions to coordinate dynamics across multiple attachment sites.     

Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis

Epistasis plays an important role in the genetic architecture of common human diseases and can be viewed from two perspectives, biological and statistical, each derived from and leading to different assumptions and research strategies. Biological epistasis is the result of physical interactions among biomolecules within gene regulatory networks and biochemical pathways in an individual such that the effect of a gene on a phenotype is dependent on one or more other genes. In contrast, statistical epistasis is defined as deviation from additivity in a mathematical model summarizing the relationship between multilocus genotypes and phenotypic variation in a population. The goal of this essay is to review definitions and examples of biological and statistical epistasis and to explore the relationship between the two. Specifically, we present and discuss the following two questions in the context of human health and disease. First, when does statistical evidence of epistasis in human populations imply underlying biomolecular interactions in the etiology of disease? Second, when do biomolecular interactions produce patterns of statistical epistasis in human populations?Answers to these two reciprocal questions will provide an important framework for using genetic information to improve our ability to diagnose, prevent and treat common human diseases. We propose that systems biology will provide the necessary information for addressing these questions and that model systems such as bacteria, yeast and digital organisms will be a useful place to start. BioEssays 27:637–646, 2005. © 2005 Wiley Periodicals, Inc.     

The challenge of personalized cell biology: The example of microvillus inclusion disease

Whole exome sequencing now provides a tool for rapid analysis of patients manifesting congenital diseases. Congenital diarrheal diseases provide a critical example of the challenges of combining identification of genetic mutations responsible for disease with characterization of the cell biological and cell physiological deficits observed in patients. Recent studies exploring the cellular events associated with loss of functional Myosin 5B (MYO5B) have demonstrated the importance of cell biological and physiological analyses to provide a greater understanding of the implications of pathological mutations. Development of enteroids derived from biopsies of patients with complex congenital diarrheal diseases provides a critical resource for evaluation of the cell biological impact of specific monogenic mutations on enterocyte function. The ability to identify putative causative mutations for congenital disease now provides an opportunity to coordinate the efforts of physicians and cell biologists in an effort to provide patients with personalized cell biology analysis to improve patient diagnosis and treatment.     

Interfacing systems biology and synthetic biology

A report of BioSysBio 2009, the IET conference on Synthetic Biology, Systems Biology and Bioinformatics, Cambridge, UK, 23-25 March 2009.     

Small RNA biology is systems biology

During the last decade small regulatory RNA (srRNA) emerged as central players in the regulation of gene expression in all kingdoms of life. Multiple pathways for srRNA biogenesis and diverse mechanisms of gene regulation may indicate that srRNA regulation evolved independently multiple times. However, small RNA pathways share numerous properties, including the ability of a single srRNA to regulate multiple targets. Some of the mechanisms of gene regulation by srRNAs have significant effect on the abundance of free srRNAs that are ready to interact with new targets. This results in indirect interactions among seemingly unrelated genes, as well as in a crosstalk between different srRNA pathways. Here we briefly review and compare the major srRNA pathways, and argue that the impact of srRNA is always at the system level. We demonstrate how a simple mathematical model can ease the discussion of governing principles. To demonstrate these points we review a few examples from bacteria and animals.     

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.