Siena, June 28, 2013
Department of Information Engineering and Mathematical Sciences
Via Roma, 56, 53100 Siena (Aula 103)



Ilan Lobel (Stern School of Business, New York University)

Social Learning and Aggregate Network Uncertainty

E-mail: ilobel at stern.nyu.edu


Luis R. Comolli (Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720)

Self-assembly, lattice growth, and supramolecular order of a bacterial S-layer protein resolved by 2D and 3D cryo-TEM

E-mail: lrcomolli at lbl.gov




Social Learning and Aggregate Network Uncertainty

Ilan Lobel

We study the equilibrium of a model of learning in networks, where agents learn about the state of the world by observing the actions of their neighbors. Agents observe their local neighborhoods and form beliefs about the overall network topology. When agents have very different beliefs about the overall topology of the network, we say the model has aggregate network uncertainty. We show that network uncertainty creates failures of social learning that are far more significant than previously known failure mechanisms, such as herding. We also show that popular network models such as preferential attachment lead to successful learning outcomes despite the network uncertainty. Joint work with Evan Sadler (NYU).
The paper is available at http://pages.stern.nyu.edu/~ilobel/NetworkUncertainty.pdf


Self-assembly, lattice growth, and supramolecular order of a bacterial S-layer protein resolved by 2D and 3D cryo-TEM

Luis R. Comolli

S-layers are a two-dimensional protein or glycoprotein paracrystalline lattices that cover the surfaces of many bacterial and archaeal cells. As they constitute the first interface of interaction between microorganisms and their environment, hosts, and predators, they are of great biological interest; they are involved in key processes such as cell adhesion, pathogenicity, drug resistance, and mineralization. Their nanoscale periodic, porous structure and relative ease of manipulation give them great potential for nano-biotechnological applications. However, details of the assembly process are not yet known for any S-layer and high resolution structural information is still very limited. Here we use cryo-transmission electron microscopy (cryo-TEM) to reveal the two-dimensional (2D) paracrystalline protein network of an S-layer and further decipher two types of assembly into bilayers in three dimensions (3D). We report a 2D structural analysis of the expanding boundary of isolated Lysinibacillus sphaericus S-layer (SbpA) growing on a graphene support. As the active self-assembling S-layers are instantly frozen all conformational states present at the expanding boundary on the graphene flat support are captured. We find that the SbpA homotetrameric subunits spanning the lattice are not preassembled and fully folded prior to incorporation. Instead, the addition of monomers to the open boundary happens in concert with the maturation of the adjacent homotetrameric subunits. We also report that a truncated SbpA (rSbpA) protein assembles into stable bilayers, which we characterized using cryogenic-electron microscopy, tomography, and X-ray spectroscopy. We find that emergence of this super-molecular architecture is the outcome of hierarchical processes; the proteins condense in solution to form 2-D lattices, which then stack parallel to one another to create isotropic bilayered assemblies. Within this bilayered structure, registry between lattices in two layers was disclosed whereas the intrinsic symmetry in each layer was altered. Comparison of these data to images of wild-type SbpA layers on intact cells gave insight into the interactions responsible for bilayer formation. These results establish a platform for engineering S-layer assemblies with 3-D architecture.

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