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Redundancy has been referred to as a state of no longer being needed or useful. Microbiologists often theorize that the only case of true redundancy in a haploid organism would be a recent gene duplication event, prior to divergence through selective pressure. However, a growing number of examples exist where an organism encodes two genes that appear to perform the same function. For example, many pathogens translocate multiple effector proteins into hosts. While disruption of individual effector genes does not result in a discernable phenotype, deleting genes in combination impairs pathogenesis: this has been described as redundancy. In many cases, this apparent redundancy could be due to limitations of laboratory models of pathogenesis that do not fully recapitulate the disease process. Alternatively, it is possible that the selective advantage achieved by this perceived redundancy is too subtle to be measured in the laboratory. Moreover, there are numerous possibilities for different types of redundancy. The most common and recognized form of redundancy is functional redundancy whereby two proteins have similar biochemical activities and substrate specificities allowing each one to compensate in the absence of the other. However, redundancy can also exist between seemingly unrelated proteins that manipulate the same or complementary host cell pathways. In this article, we outline 5 types of redundancy in pathogenesis: molecular, target, pathway, cellular process, and system redundancy that incorporate the biochemical activities, the host target specificities and the impact of effector function on the pathways and cellular process they modulate. For each type of redundancy, we provide examples from Legionella pathogenesis as this organism employs over 300 secreted virulence proteins and loss of individual proteins rarely impacts intracellular growth. We also discuss selective pressures that drive the maintenance of redundant mechanisms, the current methods used to resolve redundancy and features that distinguish between redundant and non-redundant virulence mechanisms.

Network theory has become an excellent method of choice through which biological data are smoothly integrated to gain insights into complex biological problems. Understanding protein structure, folding, and function has been an important problem, which is being extensively investigated by the network approach. Since the sequence uniquely determines the structure, this review focuses on the networks of non-covalently connected amino acid side chains in proteins. Questions in structural biology are addressed within the framework of such a formalism. While general applications are mentioned in this review, challenging problems which have demanded the attention of scientific community for a long time, such as allostery and protein folding, are considered in greater detail. Our aim has been to explore these important problems through the eyes of networks. Various methods of constructing protein structure networks (PSN) are consolidated. They include the methods based on geometry, edges weighted by different schemes, and also bipartite network of protein-nucleic acid complexes. A number of network metrics that elegantly capture the general features as well as specific features related to phenomena, such as allostery and protein model validation, are described. Additionally, an integration of network theory with ensembles of equilibrium structures of a single protein or that of a large number of structures from the data bank has been presented to perceive complex phenomena from network perspective. Finally, we discuss briefly the capabilities, limitations, and the scope for further explorations of protein structure networks.

SUMMARYA panel of monoclonal antibodies (MAbs) raised against an Indian strain of Japanese encephalitis (JE) virus was used to map topographically the epitopes on the envelope protein. Two separate clusters of epitopes were revealed. On the basis of reactivity in haemagglutination inhibition (HI), neutralization (NT), passive protection and antibody-dependent plaque enhancement (ADPE) assays with the MAbs, five functional domains (A, B, C, D and E) were delineated. The flavivirus cross-reactive domain for HI (A) was distinct. The JE virus-specific domain for HI (B) was in continuum with those domains representing non-HI JE virus-specific MAbs (C) and flavivirus cross-reactive MAbs (D). Domain E, which mapped close to domain D was represented by two MAbs that reacted with both JE virus and uninfected cell nuclei. Four conclusions can be drawn. (i) Two distinct antigenic domains were associated with HI, (ii) HI and NT in vivo and in vitro were dissociated functions, (iii) ADPE activity was solely linked with the A domain and (iv) all MAbs reacting with epitopes in the B domain had HI/NT/protective activity but failed to show ADPE. The B domain might therefore be considered the most suitable for development of synthetic or genetically engineered vaccines.

Like the p16, SMAD4, and RB1 genes, FAM190A (alias CCSER1) lies at a consensus site of homogeneous genomic deletions in human cancer. FAM190A transcripts in 40% of cancers also contain in-frame deletions of evolutionarily conserved exons. Its gene function was unknown. We found an internal deletion of the FAM190A gene in a pancreatic cancer having prominent focal multinuclearity. The experimental knockdown of FAM190A expression by shRNA caused focal cytokinesis defects, multipolar mitosis, and multinuclearity as observed in time-lapse microscopy. FAM190A was localized to the γ-tubulin ring complex of early mitosis and to the midbody in late cytokinesis by immunofluorescence assay and was present in the nuclear fraction of unsynchronized cells by immunoblot. FAM190A interacted with EXOC1 and Ndel1, which function in cytoskeletal organization and the cell division cycle. Levels of FAM190A protein peaked 12 hours after release from thymidine block, corresponding to M-phase. Slower-migrating phosphorylated forms accumulated toward M-phase and disappeared after release from a mitotic block and before cytokinesis. Studies of FAM190A alterations may provide mechanistic insights into mitotic dysregulation and multinuclearity in cancer. We propose that FAM190A is a regulator or structural component required for normal mitosis and that both the rare truncating mutations and common in-frame deletion alteration of FAM190A may contribute to the chromosomal instability of cancer.

Protein structure space is believed to consist of a finite set of discrete folds, unlike the protein sequence space which is astronomically large, indicating that proteins from the available sequence space are likely to adopt one of the many folds already observed. In spite of extensive sequence-structure correlation data, protein structure prediction still remains an open question with researchers having tried different approaches (experimental as well as computational). One of the challenges of protein structure prediction is to identify the native protein structures from a milieu of decoys/models. In this work, a rigorous investigation of Protein Structure Networks (PSNs) has been performed to detect native structures from decoys/models. Ninety four parameters obtained from network studies have been optimally combined with Support Vector Machines (SVM) to derive a general metric to distinguish decoys/models from the native protein structures with an accuracy of 94.11%. Recently, for the first time in the literature we had shown that PSN has the capability to distinguish native proteins from decoys. A major difference between the present work and the previous study is to explore the transition profiles at different strengths of non-covalent interactions and SVM has indeed identified this as an important parameter. Additionally, the SVM trained algorithm is also applied to the recent CASP10 predicted models. The novelty of the network approach is that it is based on general network properties of native protein structures and that a given model can be assessed independent of any reference structure. Thus, the approach presented in this paper can be valuable in validating the predicted structures. A web-server has been developed for this purpose and is freely available at .

Population differences in age-related diseases and cancer could stem from differences in diet. To characterize DNA strand-breaking activities in selected foods/beverages, flavorings, and some of their constituent chemicals, we used p53R cells, a cellular assay sensitive to such breaks. Substances testing positive included reference chemicals: quinacrine (peak response, 51X) and etoposide (33X); flavonoids: EGCG (19X), curcumin (12X), apigenin (9X), and quercetin (7X); beverages: chamomile (11X), green (21X), and black tea (26X) and coffee (3 to 29X); and liquid smoke (4 to 28X). Damage occurred at dietary concentrations: etoposide near 5 μg/ml produced responses similar to a 1:1000 dilution of liquid smoke, a 1:20 dilution of coffee, and a 1:5 dilution of tea. Pyrogallol-related chemicals and tannins are present in dietary sources and individually produced strong activity: pyrogallol (30X), 3-methoxycatechol (25X), gallic acid (21X), and 1,2,4-benzenetriol (21X). From structure-activity relationships, high activities depended on specific orientations of hydroxyls on the benzene ring. Responses accompanied cellular signals characteristic of DNA breaks such as H2AX phosphorylation. Breaks were also directly detected by comet assay. Cellular toxicological effects of foods and flavorings could guide epidemiologic and experimental studies of potential disease risks from DNA strand-breaking chemicals in diets.

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