Lipid Segregation and Membrane Budding Induced by the Peripheral Membrane Binding Protein Annexin A2

The formation of dynamic membrane microdomains is an important phenomenon in many signal transduction and membrane trafficking events. It is driven by intrinsic properties of membrane lipids and integral as well as membrane-associated proteins. Here we analyzed the ability of one peripherally associated membrane protein, annexin A2 (AnxA2), to induce the formation of phosphatidylinositol 4,5-bisphosphate (PI(4,5)P₂)-rich domains in giant unilamellar vesicles (GUVs) of complex lipid composition. AnxA2 is a cytosolic protein that can bind PI(4,5)P₂ and other acidic phospholipids in a Ca²⁺-dependent manner and that has been implicated in cellular membrane dynamics in endocytosis and exocytosis. We show that AnxA2 binding to GUVs induces lipid phase separation and the recruitment of PI(4,5)P₂, cholesterol and glycosphingolipids into larger clusters. This property is observed for the full-length monomeric protein, a mutant derivative comprising the C-terminal protein core domain and for AnxA2 residing in a heterotetrameric complex with its intracellular binding partner S100A10. All AnxA2 derivatives inducing PI(4,5)P₂ clustering are also capable of forming interconnections between PI(4,5)P₂-rich microdomains of adjacent GUVs. Furthermore, they can induce membrane indentations rich in PI(4,5)P₂ and inward budding of these membrane domains into the lumen of GUVs. This inward vesiculation is specific for AnxA2 and not shared with other PI(4,5)P₂-binding proteins such as the pleckstrin homology (PH) domain of phospholipase Cδ1. Together our results indicate that annexins such as AnxA2 can efficiently induce membrane deformations after lipid segregation, a mechanism possibly underlying annexin functions in membrane trafficking.     

Rule-based modeling and simulations of the inner kinetochore structure

Background

Combinatorial complexity is a central problem when modeling biochemical reaction networks, since the association of a few components can give rise to a large variation of protein complexes. Available classical modeling approaches are often insufficient for the analysis of very large and complex networks in detail. Recently, we developed a new rule-based modeling approach that facilitates the analysis of spatial and combinatorially complex problems. Here, we explore for the first time how this approach can be applied to a specific biological system, the human kinetochore, which is a multi-protein complex involving over 100 proteins.

Results

Applying our freely available SRSim software to a large data set on kinetochore proteins in human cells, we construct a spatial rule-based simulation model of the human inner kinetochore. The model generates an estimation of the probability distribution of the inner kinetochore 3D architecture and we show how to analyze this distribution using information theory. In our model, the formation of a bridge between CenpA and an H3 containing nucleosome only occurs efficiently for higher protein concentration realized during S-phase but may be not in G1. Above a certain nucleosome distance the protein bridge barely formed pointing towards the importance of chromatin structure for kinetochore complex formation. We define a metric for the distance between structures that allow us to identify structural clusters. Using this modeling technique, we explore different hypothetical chromatin layouts.

Conclusions

Applying a rule-based network analysis to the spatial kinetochore complex geometry allowed us to integrate experimental data on kinetochore proteins, suggesting a 3D model of the human inner kinetochore architecture that is governed by a combinatorial algebraic reaction network. This reaction network can serve as bridge between multiple scales of modeling. Our approach can be applied to other systems beyond kinetochores.     

Postembryonic lineages of the Drosophila brain: I. Development of the lineage-associated fiber tracts

Neurons of the Drosophila central brain fall into approximately 100 paired groups, termed lineages. Each lineage is derived from a single asymmetrically-dividing neuroblast. Embryonic neuroblasts produce 1,500 primary neurons (per hemisphere) that make up the larval CNS followed by a second mitotic period in the larva that generates approximately 10,000 secondary, adult-specific neurons. Clonal analyses based on previous works using lineage-specific Gal4 drivers have established that such lineages form highly invariant morphological units. All neurons of a lineage project as one or a few axon tracts (secondary axon tracts, SATs) with characteristic trajectories, thereby representing unique hallmarks. In the neuropil, SATs assemble into larger fiber bundles (fascicles) which interconnect different neuropil compartments. We have analyzed the SATs and fascicles formed by lineages during larval, pupal, and adult stages using antibodies against membrane molecules (Neurotactin/Neuroglian) and synaptic proteins (Bruchpilot/N-Cadherin). The use of these markers allows one to identify fiber bundles of the adult brain and associate them with SATs and fascicles of the larval brain. This work lays the foundation for assigning the lineage identity of GFP-labeled MARCM clones on the basis of their close association with specific SATs and neuropil fascicles, as described in the accompanying paper (Wong et al., 2013. Postembryonic lineages of the Drosophila brain: II. Identification of lineage projection patterns based on MARCM clones. Submitted.).     

Predictive systems ecology

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.     

Conformational stabilization of the membrane embedded targeting domain of the lysosomal peptide transporter TAPL for solution NMR

The ATP binding cassette transporter TAPL translocates cytosolic peptides into the lumen of lysosomes driven by the hydrolysis of ATP. Functionally, this transporter can be divided into coreTAPL, comprising the transport function, and an additional N-terminal transmembrane domain called TMD0, which is essential for lysosomal targeting and mediates the interaction with the lysosomal associated membrane proteins LAMP-1 and LAMP-2. To elucidate the structure of this unique domain, we developed protocols for the production of high quantities of cell-free expressed TMD0 by screening different N-terminal expression tags. Independently of the amino acid sequence, high expression was detected for AU-rich sequences in the first seven codons, decreasing the free energy of RNA secondary structure formation at translation initiation. Furthermore, avoiding NGG codons in the region of translation initiation demonstrated a positive effect on expression. For NMR studies, conditions were optimized for high solubilization efficiency, long-term stability, and high quality spectra. A most critical step was the careful exchange of the detergent used for solubilization by the detergent dihexanoylphosphatidylcholine. Several constructs of different size were tested in order to stabilize the fold of TMD0 as well as to reduce the conformation exchange. NMR spectra with sufficient resolution and homogeneity were finally obtained with a TMD0 derivative only modified by a C-terminal His₁₀-tag and containing a codon optimized AT-rich sequence.