GENERALLY...

..., I enjoy combining quantitative experiments and mathemetical theories to understand biological systems.

Many biological phenomena exhibit complex dynamical behaviors that often cannot be intuitively understood from the interaction among its part alone. In these cases a theoretical analysis of the systems dynamics including its phase space and critical points can be very insightful; sometimes they are the only way to gain a sufficient understanding at all. In order to test such theoretical analysis quantitative experiments are required. My general research interest is to perform such quantitative experiments and to describe the observed biological phenomena in mathematical terms.

CURRENTLY...

..., I work on olfactory coding in the insect brain.

Please see below and the Laurent-lab page for details.

PREVIOUSLY...

..., I have worked on different projects in developmental biology, molecular and cellular biophysics, and theoretical solid state physics.

Please see even further below for even further details.

Olfactory coding in the insect brain

I study how the sense of smell is processed in insects (locust) in a brain structure called the antenna lobe.

Within the antenna lobe the two neuron types - projection neurons (PN) and local interneurons (LN) - form a recurrent network.

These neurons have been shown to exhibit synchronized, oscillatory firing patterns. These patterns are specific for each PN and odor condition, furthermore they change over time - even for a constant odor stimulus. Hence this firing pattern represents a spatio-temporal code ("spatio"="different PNs"; "temporal"="changes in time"). The summed activity of these PNs - measured with a local field potential (LFP) - shows oscillatory activity, hence the PNs are synchronized. I am interested to understand how this dynamic pattern arrises due to the network properties and what odor information it represents (and computes).

I use multi-unit recording techniques (“tetrodes”) to measure these firing patterns among many PN at the same time. In order to increase the number of simultaneously recorded neurons I collaborated with Sotiris Masmanidis and Jiangang Du to develop and sucessfully test new tetrodes.

These probes have the features that their electrodes are placed on both sides of shaft - which increases the recording density - and that the shafts are arranged in three dimensions - which allows the localization of neurons in space. This work has been published in J. Neurophys (2009).

Synchrony in the zebrafish segmentation clock

Vertebrate segmentation is driven by the so-called segmentation clock – a multi-cellular network of genetic oscillators. In zebrafish these cellular oscillators are mutually coupled via the intercellular Delta-Notch signaling pathway leading to synchrony among these oscillators. How this synchrony is established and how its loss determines the position of segmentation defects in Delta and Notch mutants was unknown.

In order to analyze the clock’s synchrony dynamics I developed together with Andrew Oates a widely applicable experimental method for quantitative gene perturbation based on Morpholinos and the gamma-secretase inhibitor DAPT.

Using these inhibitors in a concentration dependent manner we generated fish that had their segmentation defects at specific postions (termed "Anterior Limit of Defect"="ALD")

Applying a physical theory of coupled phase oscillators we were able to account for thes ALD in a quantitative way, i.e. we related segmentation phenotype (ALD) to the coupling strength among cells due to Delta-Notch (inhibitor concentration).

Furthermore we showed experimentally that synchrony among genetic oscillators can be established by simultaneous gene induction and by self-organization.

This work led to a deeper understanding of the synchrony dynamics among coupled genetic oscillators. Furthermore we were able to quantify key parameters of the system such as the developmental noise, the coupling strength among genetic oscillators, mRNA decay rates, and the robustness of this system. This work was published in Science (2007) .

How molecular motors shape the sperm beat

During my Ph.D. thesis I was interested understanding the beating motion of sperm tails so I joined the biophysics lab of Jonathon Howard.

Sperm tails (or more generally cilia and eukaryotic flagella) are organelles that contain a structure called axoneme, which consists of microtubules and a large number of dynein motors. These molecular motors drive the sliding motion between those microtubules. Since the microtubules are structurally attached at the base of the axoneme this sliding motion is converted into an oscillatory beat pattern. How the collective activity of these dynein motors is coordinated in space and time to achieve beat patterns with specific frequency, shapes, and amplitudes was unknown.

To eludicate the nature of this motor coordination I inferred the mechanical properties of the motors by analyzing the shape of beating bull sperm: I imaged steadily beating bull sperm using a high speed camera and measured their shape with high precision using a Fourier averaging technique.

In collaboration with Andreas Hilfinger and Frank Jülicher (Max Planck Institute for the Physics of Complex Systems, Dresden) we compared this experimental data with wave forms calculated for different scenarios of motor coordination. Agreement between observed and calculated wave forms was obtained only if significant sliding between microtubules occurred at the base and if interdoublet sliding regulates motor activity.

We therefore concluded that the flagellar beat patterns are determined by an interplay of the basal properties of the axoneme and the mechanical feedback of dynein motors. We suggested that the microscopic origin of such “sliding control” is the load dependent detachment rate of motors. Furthermore, we suggested a novel mechanism by which changes in basal compliance could reverse the direction of beat propagation. This work was published in the HFSP Journal (2007).

Self-organization of sea urchin sperm

During my Ph.D. with Jonathon Howard I discovered a self-organized pattern involving a large number of sea urchin sperms. I discovered that at very high surface densities about 10 of these sperms swim around a common center ("vortex"). Many of such vortices are densely, nearly hexagonally packed.

The sperm tails within a vortex fare synchronized in a form of a quantized rotating wave.

In collaboration with Karsten Kruse we developed a model based that explains the overall vortex array. This model predicted that this pattern should appear above a critical sperm density.

I tested and confirmed this prediction experimentally. The value of this critical density allowed to infer the hydrodynamic interaction force between two sperms. This force was ~0.03 pN, which surprisingly is much smaller than the typical force of a molecular motor.

Related self-organized patterns can be found among cilia, which also contain axonemes. Cilia have been known for a long time to synchronize into metachronal waves thereby collectively enhancing fluid transport. From the observed critical point in the sperm vortex array we proposed that these ciliary metachronal waves are similarly switched due to critical points, furthermore that the similar interaction forces should hold. This work was published in Science (2005) .

Transmission coefficients

During my Diploma Thesis with Ingrid Mertig I developed and successfully tested a method to compute electronic transmission coefficients through mesoscopic layers, i.e. layers with the thickness of only a few atoms and where quantum effects play a significant role.

The important feature of the method I developed is that it starts from the electronic structure of a periodic superlattice, which had been calculated self-consistently within a screened Korringa-Kohn-Rostoker (KKR) method.

The computation of such transmission coefficients is important e.g. to understand the giant magneto resistance (GMR), which enabled the miniaturization of modern hard-drives (incl. those used in the early iPods) and for which discovery the Physics Nobel Prize was awarded in 2007. This work was published in Phys. Rev. B (2001).