Welcome to the Gerland group -
Physics of Complex Biosystems
In physics, interactions between particles follow laws. In biology, interactions between biomolecules serve a function. These very different points of view are beginning to merge as research over the past years has demonstrated how, in some exemplary cases, the laws of physics constrain the implementation of biological function.
We investigate several such cases. For instance, we study how the spatial arrangement and coordination of enzymes determines the efficiency of a multi-step reaction. These spatial arrangements can be natural (as in biomolecular complexes) or engineered with the modern methods of bio-nanotechnology. In both cases, fundamental functional tradeoffs emerge, which must be characterized to understand the optimization of such systems.
Methods from theoretical physics help to describe the functioning of these complex biomolecular systems on a quantitative level, while the biological function leads to new questions, with many parallels in the engineering disciplines. Seen from this perspective, a bacterium is a microscopic bioreactor programmed by evolution to rebuild itself from a variable set of resources and in fluctuating environments. How is this bioreactor programmed? Which strategies enable the control of a diverse set of physico-chemical processes in a way as to robustly produce a highly complex product? Quantitative analysis and modeling facilitates insight into the underlying design principles.
A key aim in origins of life research is to understand how self-replicating evolving systems can spontaneously emerge in non-equilibrium environments. Informational polymers such as RNA play pivotal roles in these scenarios, as information carriers and, according to the “RNA world” hypothesis, also as the first functional molecules catalyzing reactions. However, it is not clear how RNA strands that are long enough to act as functional molecules came into being.
In order to answer this question, the structure that is already induced by the growth of short informational polymers must be understood. Short informational polymers can grow via a process called templated ligation: Two strands bind (hybridize) next to each other on a third strand, the so-called template, which enables the joining (ligation) of the two strands into one.
We studied how this growth process shapes the length distribution of informational polymers. Using stochastic simulations, we find that the process generally leads to a minimum and a maximum in the length distribution. The maximum constitutes a source of informational polymers of a specific length that can be tuned by changing physical parameters. As such, these strands can serve as the building blocks for a structure-forming process on longer length scales. We theoretically characterize the underlying dynamics that shape the length distribution, and confirm the non-monotonous behavior in a proof-of-principle experiment with DNA strands.
Complex systems, ranging from developing embryos to systems of locally communicating agents, display an apparent capability of “programmable” pattern formation: They reproducibly form target patterns, but those targets can be readily changed. A distinguishing feature of such systems is that their subunits are capable of information processing. Here, we explore schemes for programmable pattern formation within a theoretical framework, in which subunits process local signals to update their discrete state following logical rules. We study systems with different update rules, topologies, and control schemes, assessing their capability of programmable pattern formation and their susceptibility to errors. Only a fraction permits local organizers to dictate any target pattern, by transcribing temporal patterns into spatial patterns, reminiscent of the principle underlying vertebrate somitogenesis. An alternative scheme employing variable rules cannot reach all patterns but is insensitive to the timing of organizer inputs. Our results establish a basis for designing synthetic systems and models of programmable pattern formation closer to real systems.
Chromatin dynamics are mediated by remodeling enzymes and play crucial roles in gene regulation, as established in a paradigmatic model, the S. cerevisiae PHO5 promoter. However, effective nucleosome dynamics, i.e. trajectories of promoter nucleosome configurations, remain elusive. Here, we infer such dynamics from the integration of published single-molecule data capturing multi-nucleosome configurations for repressed to fully active PHO5 promoter states with other existing histone turnover and new chromatin accessibility data. We devised and systematically investigated a new class of 'regulated on-off-slide' models simulating global and local nucleosome (dis)assembly and sliding. Only seven of 68145 models agreed well with all data. All seven models involve sliding and the known central role of the N-2 nucleosome, but regulate promoter state transitions by modulating just one assembly rather than disassembly process. This is consistent with but challenges common interpretations of previous observations at the PHO5 promoter and suggests chromatin opening by binding competition.