Global modulation of cellular transcription by human cytomegalovirus is initiated by viral glycoprotein B

Human cytomegalovirus (HCMV) infection alters the expression of many cellular genes, including IFN-stimulated genes (ISGs) [Zhu, H., Cong, J.-P., Mamtora, G., Gingeras, T. & Shenk, T. (1998) Proc. Natl. Acad. Sci. USA 95, 14470–14475]. By using high-density cDNA microarrays, we show that the HCMV-regulated gene expression profile in fibroblasts does not differ substantially from the response generated by IFN. Furthermore, we identified the specific viral component triggering this response as the envelope glycoprotein B (gB). Cells treated with gB, but not other herpesviral glycoproteins, exhibited the same transcriptional profile as HCMV-infected cells. Thus, the interaction of gB with its as yet unidentified cellular receptor is the principal mechanism by which HCMV alters cellular gene expression early during infection. These findings highlight a pioneering paradigm for the consequences of virus–receptor interactions.

A new isoleucine substitution of Val-20 in transthyretin tetramers selectively impairs dimer-dimer contacts and causes systemic amyloidosis.

The most frequent form of inherited amyloidoses is associated with mutations in the transthyretin (TTR) gene coding for 127-amino acid residues of four identical, noncovalently linked subunits that form a pair of dimers in the plasma protein complex. Amyloid fibrils containing the variant and to a lesser extent the wild-type form of the TTR molecule are deposited in various organs, including peripheral nerves and the myocardium, with polyneuropathy and cardiomyopathy as major clinical manifestations. So far, more than 40 distinct amino acid substitutions distributed throughout the TTR sequence over 30 positions have been found to be correlated with an increased amyloidogenicity of TTR. Most of these amyloidogenic amino acid substitutions are suspected to alter the conformation and stability of the monomer. Here we identify and characterize by protein and DNA analysis a novel amyloidogenic Val-20 to Ile mutation in a German three-generation family. The index patient suffered from severe amyloid cardiomyopathy at the age of 60. Conformational stability and unfolding behavior of the Ile-20 monomer in urea gradients was found to be almost indistinguishable from that of wild-type TTR. In contrast, tetramer stability was significantly reduced in agreement with the expected change in the interactions between the two opposing dimers via the side chain of Ile-20. Our observations provide strong evidence for the view that amyloidogenic amino acid substitutions in TTR facilitate the conversion of tetrameric TTR complexes into those conformational intermediates of the TTR folding pathway that have an intrinsic amyloidogenic potential.

Global properties of the mapping between local amino acid sequence and local structure in proteins.

Local protein structure prediction efforts have consistently failed to exceed approximately 70% accuracy. We characterize the degeneracy of the mapping from local sequence to local structure responsible for this failure by investigating the extent to which similar sequence segments found in different proteins adopt similar three-dimensional structures. Sequence segments 3-15 residues in length from 154 different protein families are partitioned into neighborhoods containing segments with similar sequences using cluster analysis. The consistency of the sequence-to-structure mapping is assessed by comparing the local structures adopted by sequence segments in the same neighborhood in proteins of known structure. In the 154 families, 45% and 28% of the positions occur in neighborhoods in which one and two local structures predominate, respectively. The sequence patterns that characterize the neighborhoods in the first class probably include virtually all of the short sequence motifs in proteins that consistently occur in a particular local structure. These patterns, many of which occur in transitions between secondary structural elements, are an interesting combination of previously studied and novel motifs. The identification of sequence patterns that consistently occur in one or a small number of local structures in proteins should contribute to the prediction of protein structure from sequence.

The new dysmorphology: application of insights from basic developmental biology to the understanding of human birth defects.

Information obtained from studies of developmental and cellular processes in lower organisms is beginning to make significant contributions to the understanding of the pathogenesis of human birth defects, and it is now becoming possible to treat birth defects as inborn errors of development. Mutations in genes for transcription factors, receptors, cell adhesion molecules, intercellular junctions, molecules involved in signal transduction, growth factors, structural proteins, enzymes, and transporters have been identified in genetically caused human malformations and dysplasias. The identification of these mutations and the analysis of their developmental effects have been greatly facilitated by the existence of natural or engineered models in the mouse and even of related mutations in Drosophila, and in some instances a remarkable conservation of function in development has been observed, even between widely separated species.

Prediction of protein folding class using global description of amino acid sequence.

We present a method for predicting protein folding class based on global protein chain description and a voting process. Selection of the best descriptors was achieved by a computer-simulated neural network trained on a data base consisting of 83 folding classes. Protein-chain descriptors include overall composition, transition, and distribution of amino acid attributes, such as relative hydrophobicity, predicted secondary structure, and predicted solvent exposure. Cross-validation testing was performed on 15 of the largest classes. The test shows that proteins were assigned to the correct class (correct positive prediction) with an average accuracy of 71.7%, whereas the inverse prediction of proteins as not belonging to a particular class (correct negative prediction) was 90-95% accurate. When tested on 254 structures used in this study, the top two predictions contained the correct class in 91% of the cases.