Probing the U-Shaped Conformation of Caveolin-1 in a Bilayer

Caveolin induces membrane curvature and drives the formation of caveolae that participate in many crucial cell functions such as endocytosis. The central portion of caveolin-1 contains two helices (H1 and H2) connected by a three-residue break with both N- and C-termini exposed to the cytoplasm. Although a U-shaped configuration is assumed based on its inaccessibility by extracellular matrix probes, caveolin structure in a bilayer remains elusive. This work aims to characterize the structure and dynamics of caveolin-1 (D82–S136; Cav1_82–136) in a DMPC bilayer using NMR, fluorescence emission measurements, and molecular dynamics simulations. The secondary structure of Cav1_82–136 from NMR chemical shift indexing analysis serves as a guideline for generating initial structural models. Fifty independent molecular dynamics simulations (100 ns each) are performed to identify its favorable conformation and orientation in the bilayer. A representative configuration was chosen from these multiple simulations and simulated for 1 μs to further explore its stability and dynamics. The results of these simulations mirror those from the tryptophan fluorescence measurements (i.e., Cav1_82–136 insertion depth in the bilayer), corroborate that Cav1_82–136 inserts in the membrane with U-shaped conformations, and show that the angle between H1 and H2 ranges from 35 to 69°, and the tilt angle of Cav1_82–136 is 27 ± 6°. The simulations also reveal that specific faces of H1 and H2 prefer to interact with each other and with lipid molecules, and these interactions stabilize the U-shaped conformation.     

Second-harmonic generation from organic molecules incorporated in sol-gel matrices

Orientation of optically nonlinear organic molecules inside sol-gel matrices upon application of an external D.C. electrical field is demonstrated for the first time. The quadratic nonlinear response of silicon oxide or transition metal oxide based gels containing organic molecules has been determined from Electric Field Induced Second Harmonic (EFISH) measurements. Large concentrations of Optically Nonlinear Organic Molecules (ONOM) have been either incorporated inside the macromolecular network or chemically bonded to the oxide backbone of the gels. These results demonstrate the feasibility of permanently poled doped sol-gel matrices. Moreover, EFISH measurements performed on organic molecules appear to be a useful tool for monitoring the changes occurring during sol-gel transformations.     

Structural chromosome differentiation between Triticum timopheevii and T. turgidum and T. aestivum

 Chromosome pairing at metaphase-I was analyzed in F₁ hybrids among T. turgidum (AABB), T. aestivum (AABBDD), and T. timopheevii (A^tA^tGG) to study the chromosome structure of T. timopheevii relative to durum (T. turgidum) and bread (T. aestivum) wheats. Individual chromosomes and their arms were identified by means of C-banding. Homologous pairing between the A-genome chromosomes was similar in the three hybrid types AA^tBG, AA^tBGD, and AABBD. However, associations of B-G were less frequent than B-B. Homoeologous associations were also observed, especially in the AA^tBGD hybrids. T. timopheevii chromosomes 1A^t, 2A^t, 5A^t, 7A^t, 2G, 3G, 5G, and 6G do not differ structurally from their counterpart in the A and B genomes. Thus, these three polyploid species inherited translocation 5AL/4AL from the diploid A-genome donor. Chromosome rearrangements that occurred at the tetraploid level were different in T. turgidum and T. timopheevii. Translocation 4AL/7BS and a pericentric inversion of chromosome 4A originated only in the T. turgidum lineage. The two lines of T. timophevii studied carry four different translocations, 6A^tS/1GS, 1GS/4GS, 4GS/4A^tL, and 4A^tL/3A^tL, which most likely arose in that sequence. These structural differences support a diphyletic origin of polyploid wheats. Received: 15 June 1998 / Accepted: 19 August 1998     

Flow cytometry controls, instrument setup, and the determination of positivity.

A frequent goal of flow cytometric analysis is to classify cells as positive or negative for a given marker, or to determine the precise ratio of positive to negative cells. This requires good and reproducible instrument setup, and careful use of controls for analyzing and interpreting the data. The type of controls to include in various kinds of flow cytometry experiments is a matter of some debate and discussion. In this tutorial, we classify controls in various categories, describe the options within each category, and discuss the merits of each option.