Self-assembly in polyoxometalate and metal coordination-based systems: synthetic approaches and developments

Utilizing new experimental approaches and gradual understanding of the underlying chemical processes has led to advances in the self-assembly of inorganic and metal–organic compounds at a very fast pace over the last decades. Exploitation of unveiled information originating from initial experimental observations has sparked the development of new families of compounds with unique structural characteristics and functionalities. The main source of inspiration for numerous research groups originated from the implementation of the design element along with the discovery of new chemical components which can self-assemble into complex structures with wide range of sizes, topologies and functionalities. Not only do self-assembled inorganic and metal–organic chemical systems belong to families of compounds with configurable structures, but also have a vast array of physical properties which reflect the chemical information stored in the various “modular” molecular subunits. The purpose of this short review article is not the exhaustive discussion of the broad field of inorganic and metal–organic chemical systems, but the discussion of some representative examples from each category which demonstrate the implementation of new synthetic approaches and design principles

Modeling viral coevolution: HIV multi-clonal persistence and competition dynamics

The coexistence of different viral strains (quasispecies) within the same host are nowadays observed for a growing number of viruses, most notably HIV, Marburg and Ebola, but the conditions for the formation and survival of new strains have not yet been understood. We present a model of HIV quasispecies competition, that describes the conditions of viral quasispecies coexistence under different immune system conditions. Our model incorporates both T and B cells responses, and we show that the role of B cells is important and additive to that of T cells. Simulations of coinfection (simultaneous infection) and superinfection (delayed secondary infection) scenarios in the early stages (days) and in the late stages of the infection (years) are in agreement with emerging molecular biology findings. The immune response induces a competition among similar phenotypes, leading to differentiation (quasi-speciation), escape dynamics and complex oscillations of viral strain abundance. We found that the quasispecies dynamics after superinfection or coinfection has time scales of several months and becomes even slower when the immune system response is weak. Our model represents a general framework to study the speed and distribution of HIV quasispecies during disease progression, vaccination and therapy.Comment: 20 pages, 10 figure

Biological applications of the theory of birth-and-death processes

In this review, we discuss the applications of the theory of birth-and-death processes to problems in biology, primarily, those of evolutionary genomics. The mathematical principles of the theory of these processes are briefly described. Birth-and-death processes, with some straightforward additions such as innovation, are a simple, natural formal framework for modeling a vast variety of biological processes such as population dynamics, speciation, genome evolution, including growth of paralogous gene families and horizontal gene transfer, and somatic evolution of cancers. We further describe how empirical data, e.g., distributions of paralogous gene family size, can be used to choose the model that best reflects the actual course of evolution among different versions of birth-death-and-innovation models. It is concluded that birth-and-death processes, thanks to their mathematical transparency, flexibility and relevance to fundamental biological process, are going to be an indispensable mathematical tool for the burgeoning field of systems biology.Comment: 29 pages, 4 figures; submitted to "Briefings in Bioinformatics

The Self Model and the Conception of Biological Identity in Immunology

The self/non-self model, first proposed by F.M. Burnet, has dominated immunology for sixty years now. According to this model, any foreign element will trigger an immune reaction in an organism, whereas endogenous elements will not, in normal circumstances, induce an immune reaction. In this paper we show that the self/non-self model is no longer an appropriate explanation of experimental data in immunology, and that this inadequacy may be rooted in an excessively strong metaphysical conception of biological identity. We suggest that another hypothesis, one based on the notion of continuity, gives a better account of immune phenomena. Finally, we underscore the mapping between this metaphysical deflation from self to continuity in immunology and the philosophical debate between substantialism and empiricism about identity

Beyond self-eating: The control of nonautophagic functions and signaling pathways by autophagy-related proteins.

The identification of conserved autophagy-related proteins (ATGs) that mediate bulk degradation of cytosolic material laid the foundation for breakthroughs linking autophagy to a litany of physiological processes and disease conditions. Recent discoveries are revealing that these same ATGs orchestrate processes that are related to, and yet clearly distinct from, classic autophagy. Autophagy-related functions include secretion, trafficking of phagocytosed material, replication and egress of viral particles, and regulation of inflammatory and immune signaling cascades. Here, we define common processes dependent on ATGs, and discuss the challenges in mechanistically separating autophagy from these related pathways. Elucidating the molecular events that distinguish how individual ATGs function promises to improve our understanding of the origin of diseases ranging from autoimmunity to cancer

The immune system and other cognitive systems

In the following pages we propose a theory on cognitive systems and the common strategies of perception, which are at the basis of their function. We demonstrate that these strategies are easily seen to be in place in known cognitive systems such as vision and language. Furthermore we show that taking these strategies into consideration implies a new outlook on immune function calling for a new appraisal of the immune system as a cognitive system

Causality, Information and Biological Computation: An algorithmic software approach to life, disease and the immune system

Biology has taken strong steps towards becoming a computer science aiming at reprogramming nature after the realisation that nature herself has reprogrammed organisms by harnessing the power of natural selection and the digital prescriptive nature of replicating DNA. Here we further unpack ideas related to computability, algorithmic information theory and software engineering, in the context of the extent to which biology can be (re)programmed, and with how we may go about doing so in a more systematic way with all the tools and concepts offered by theoretical computer science in a translation exercise from computing to molecular biology and back. These concepts provide a means to a hierarchical organization thereby blurring previously clear-cut lines between concepts like matter and life, or between tumour types that are otherwise taken as different and may not have however a different cause. This does not diminish the properties of life or make its components and functions less interesting. On the contrary, this approach makes for a more encompassing and integrated view of nature, one that subsumes observer and observed within the same system, and can generate new perspectives and tools with which to view complex diseases like cancer, approaching them afresh from a software-engineering viewpoint that casts evolution in the role of programmer, cells as computing machines, DNA and genes as instructions and computer programs, viruses as hacking devices, the immune system as a software debugging tool, and diseases as an information-theoretic battlefield where all these forces deploy. We show how information theory and algorithmic programming may explain fundamental mechanisms of life and death.Comment: 30 pages, 8 figures. Invited chapter contribution to Information and Causality: From Matter to Life. Sara I. Walker, Paul C.W. Davies and George Ellis (eds.), Cambridge University Pres