Models of life: epigenetics, diversity and cycles

Advancement in the development of single chain antibodies using phage display technology

Phage display technology has become an important research tool in biological research, fundamentally changing the traditional monoclonal antibody preparation process, and has been widely used in the establishment of antigen-antibody libraries, drug design, vaccine research, pathogen detection, gene therapy, antigenic epitope research, and cellular signal transduction research.The phage display is a powerful platform for technology development. Using phage display technology, single chain fragment variable (scFv) can be screened, replacing the disadvantage of the large size of traditional antibodies. Phage display single chain antibody libraries have significant biological implications. Here we describe the types of antibodies, including chimeric antibodies, bispecific antibodies, and scFvs. In addition, we describe the phage display system, phage display single chain antibody libraries, screening of specific antibodies by phage libraries and the application of phage libraries.

Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases

In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease.

The transcription factor Atf1 lowers the transition barrier for nucleosome-mediated establishment of heterochromatin

Transcription factors can exert opposite effects depending on the chromosomal context. The fission yeast transcription factor Atf1 both activates numerous genes in response to stresses and mediates heterochromatic gene silencing in the mating-type region. Investigating this context dependency, we report here that the establishment of silent heterochromatin in the mating-type region occurs at a reduced rate in the absence of Atf1 binding. Quantitative modeling accounts for the observed establishment profiles by a combinatorial recruitment of histone-modifying enzymes: locally by Atf1 at two binding sites and over the whole region by dynamically appearing heterochromatic nucleosomes, a source of which is the RNAi-dependent cenH element. In the absence of Atf1 binding, the synergy is lost, resulting in a slow rate of heterochromatin formation. The system shows how DNA-binding proteins can influence local nucleosome states and thereby potentiate long-range positive feedback on histone-modification reactions to enable heterochromatin formation over large regions in a context-dependent manner.

Dosage Sensing, Threshold Responses, and Epigenetic Memory: A Systems Biology Perspective on Random X-Chromosome Inactivation

X-chromosome inactivation ensures dosage compensation between the sexes in mammals by randomly choosing one out of the two X chromosomes in females for inactivation. This process imposes a plethora of questions: How do cells count their X chromosome number and ensure that exactly one stays active? How do they randomly choose one of two identical X chromosomes for inactivation? And how do they stably maintain this state of monoallelic expression? Here, different regulatory concepts and their plausibility are evaluated in the context of theoretical studies that have investigated threshold behavior, ultrasensitivity, and bistability through mathematical modeling. It is discussed how a twofold difference between a single and a double dose of X-linked genes might be converted to an all-or-nothing response and how mutually exclusive expression can be initiated and maintained. Finally, candidate factors that might mediate the proposed regulatory principles are reviewed.

Why is cyclic dominance so rare?

Natural populations can contain multiple types of coexisting individuals. How does natural selection maintain such diversity within and across populations? A popular theoretical basis for the maintenance of diversity is cyclic dominance, illustrated by the rock-paper-scissor game. However, it appears difficult to find cyclic dominance in nature. Why is this the case? Focusing on continuously produced novel mutations, we theoretically addressed the rareness of cyclic dominance. We developed a model of an evolving population and studied the formation of cyclic dominance. Our results showed that the chance for cyclic dominance to emerge is lower when the newly introduced type is similar to existing types compared to the introduction of an unrelated type. This suggests that cyclic dominance is more likely to evolve through the assembly of unrelated types whereas it rarely evolves within a community of similar types.

Theoretical analysis of Polycomb-Trithorax systems predicts that poised chromatin is bistable and not bivalent

Polycomb (PcG) and Trithorax (TrxG) group proteins give stable epigenetic memory of silent and active gene expression states, but also allow poised states in pluripotent cells. Here we systematically address the relationship between poised, active and silent chromatin, by integrating 73 publications on PcG/TrxG biochemistry into a mathematical model comprising 144 nucleosome modification states and 8 enzymatic reactions. Our model predicts that poised chromatin is bistable and not bivalent. Bivalent chromatin, containing opposing active and silent modifications, is present as an unstable background population in all system states, and different subtypes co-occur with active and silent chromatin. In contrast, bistability, in which the system switches frequently between stable active and silent states, occurs under a wide range of conditions at the transition between monostable active and silent system states. By proposing that bistability and not bivalency is associated with poised chromatin, this work has implications for understanding the molecular nature of pluripotency.

Polycomb and Trithorax group proteins regulate silent and active gene expression states, but also allow poised states in pluripotent cells. Here the authors present a mathematical model that integrates data on Polycomb/ Trithorax biochemistry into a single coherent framework which predicts that poised chromatin is not bivalent as previously proposed, but is bistable, meaning that the system switches frequently between stable active and silent states.

Noncoding RNAs in Polycomb and Trithorax Regulation: A Quantitative Perspective

The question of how noncoding RNAs are involved in Polycomb group (PcG) and Trithorax group (TrxG) regulation has been on an extraordinary journey over the last three decades. Favored models have risen and fallen, and healthy debates have swept back and forth. The field has recently reached a critical mass of compelling data that throws light on several previously unresolved issues. The time is ripe for a fruitful combination of these findings with two other long-running avenues of research, namely the biochemical properties of the PcG/TrxG system and the application of theoretical mathematical models toward an understanding of the system's regulatory properties. I propose that integrating our current knowledge of noncoding RNA into a quantitative biochemical and theoretical framework for PcG and TrxG regulation has the potential to reconcile several apparently conflicting models and identifies fascinating questions for future research.