Systems analysis of host-parasite interactions.

Parasitic diseases caused by protozoan pathogens lead to hundreds of thousands of deaths per year in addition to substantial suffering and socioeconomic decline for millions of people worldwide. The lack of effective vaccines coupled with the widespread emergence of drug-resistant parasites necessitates that the research community take an active role in understanding host-parasite infection biology in order to develop improved therapeutics. Recent advances in next-generation sequencing and the rapid development of publicly accessible genomic databases for many human pathogens have facilitated the application of systems biology to the study of host-parasite interactions. Over the past decade, these technologies have led to the discovery of many important biological processes governing parasitic disease. The integration and interpretation of high-throughput -omic data will undoubtedly generate extraordinary insight into host-parasite interaction networks essential to navigate the intricacies of these complex systems. As systems analysis continues to build the foundation for our understanding of host-parasite biology, this will provide the framework necessary to drive drug discovery research forward and accelerate the development of new antiparasitic therapies

Mammalian Sperm Motility: Observation and Theory

Mammalian spermatozoa motility is a subject of growing importance because of rising human infertility and the possibility of improving animal breeding. We highlight opportunities for fluid and continuum dynamics to provide novel insights concerning the mechanics of these specialized cells, especially during their remarkable journey to the egg. The biological structure of the motile sperm appendage, the flagellum, is described and placed in the context of the mechanics underlying the migration of mammalian sperm through the numerous environments of the female reproductive tract. This process demands certain specific changes to flagellar movement and motility for which further mechanical insight would be valuable, although this requires improved modeling capabilities, particularly to increase our understanding of sperm progression in vivo. We summarize current theoretical studies, highlighting the synergistic combination of imaging and theory in exploring sperm motility, and discuss the challenges for future observational and theoretical studies in understanding the underlying mechanics.\ud Acronyms and Definitions\ud Acrosome: the cap of the sperm head containing enzymes allowing penetration of the zona pellucida via the acrosome reaction\ud Adenosine triphosphate (ATP): the currency unit of chemical energy transfer in living cells\ud Axoneme: a phylogenetically conserved structure within the eukaryotic flagellum consisting of a ring of nine microtubule doublets and a central pair, frequently referred to as 9 + 2\ud Bending moment density: the moment per unit length associated with flagellar bending; it can be divided into a hydrodynamic moment, an elastic moment (from the flagellar bending stiffness), an active moment (generated by dyneins exerting forces between adjacent microtubule doublets), and a passive moment resisting shear\ud Capacitation: the physiological state of a sperm required for fertilization, which is accompanied by the motility patterns associated with hyperactivation, characterized in saline by high-amplitude asymmetric beating\ud Central pair: a pair of microtubules along the length of the axoneme, symmetrically and slightly offset from the axoneme centerline\ud Cumulus oophorus: the outer vestment of the mammalian egg consisting of hundreds of cells radiating out from the egg embedded within a non-Newtonian hyaluronic acid gel\ud Dynein: a molecular motor within the axoneme, attached between adjacent microtubule doublets, that exerts a shearing force to induce axonemal bending\ud Flagellum: a motile cellular appendage that drives the swimming of sperm and other cells; this article focuses on the eukaryotic flagellum\ud Microtubule doublet: a pair of proteinaceous filament structures running the length of the axoneme; dyneins drive their bending, which induces flagellar motion\ud Mid-piece: the region of a sperm flagellum with a mitochondrial sheath, where ATP is generated\ud Oocyte: the egg\ud Outer dense fibers and fibrous sheath: accessory structures reinforcing the mammalian sperm flagellum; the combined axoneme and accessory structures are referred to as 9+9+2\ud Resistive-force theory: an approximation for the local drag of a slender filament element in Stokes flow (or a viscoelastic generalization thereof)\ud Rheotaxis: directed motility in response to the influence of fluid flow\ud Shear: in the context of the flagellum, the relative movement of adjacent microtubule doublets\ud Slender-body theory: an improved approximation for the local drag on a slender filament element in Stokes flow (or a viscoelastic generalization thereof)\ud Zona pellucida: a tough glycoprotein coat between the human egg and the cumulus oophorus, which a sperm must penetrate for successful fertilizatio

Bridging Physics and Biology Teaching through Modeling

As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life sciences majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both sciences that rely on observations and measurements to construct models of the natural world. In the present theoretical article, we propose that efforts to bridge the teaching of these two disciplines must emphasize shared scientific practices, particularly scientific modeling. We define modeling using language common to both disciplines and highlight how an understanding of the modeling process can help reconcile apparent differences between the teaching of physics and biology. We elaborate how models can be used for explanatory, predictive, and functional purposes and present common models from each discipline demonstrating key modeling principles. By framing interdisciplinary teaching in the context of modeling, we aim to bridge physics and biology teaching and to equip students with modeling competencies applicable across any scientific discipline.Comment: 10 pages, 2 figures, 3 table

Systems Level Modeling of the Cell Cycle Using Budding Yeast

Proteins involved in the regulation of the cell cycle are highly conserved across all eukaryotes, and so a relatively simple eukaryote such as yeast can provide insight into a variety of cell cycle perturbations including those that occur in human cancer. To date, the budding yeast Saccharomyces cerevisiae has provided the largest amount of experimental and modeling data on the progression of the cell cycle, making it a logical choice for in-depth studies of this process. Moreover, the advent of methods for collection of high-throughput genome, transcriptome, and proteome data has provided a means to collect and precisely quantify simultaneous cell cycle gene transcript and protein levels, permitting modeling of the cell cycle on the systems level. With the appropriate mathematical framework and sufficient and accurate data on cell cycle components, it should be possible to create a model of the cell cycle that not only effectively describes its operation, but can also predict responses to perturbations such as variation in protein levels and responses to external stimuli including targeted inhibition by drugs. In this review, we summarize existing data on the yeast cell cycle, proteomics technologies for quantifying cell cycle proteins, and the mathematical frameworks that can integrate this data into representative and effective models. Systems level modeling of the cell cycle will require the integration of high-quality data with the appropriate mathematical framework, which can currently be attained through the combination of dynamic modeling based on proteomics data and using yeast as a model organism

Systems biology in animal sciences

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed ‘omics’ technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A ‘system’ approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with ‘system approaches’ in animal sciences, providing exciting opportunities to predict and modulate animal traits

Challenges for Modeling and Simulation Methods in Systems Biology

Systems Biology is aimed at analyzing the behavior and interrelationships of biological systems and is characterized by combining experimentation, theory, and computation. Dedicated to exploring current challenges, the panel brings together people from a variety of disciplines whose perspectives illuminate diverse facets of Systems Biology and the challenges for modeling and simulation methods