DISTRIBUTION OF INTERTIDAL DIATOMS ASSOCIATED WITH SEDIMENTS IN YAQUINA ESTUARY,OREGON1,2

Sediment samples and environmental data were collected from November 1973 to August 1974 to analyze the distribution of sediment-associated diatom assemblages relative to vertical, horizontal, and seasonal gradients in Yaquina Estuary, Oregon. The distribution of diatoms was regulated primarily by mean salinity and characteristics of the sediment, i.e., mean sediment size and percentage of organic carbon. Prominent taxa in the river above Yaquina Bay exhibited overlapping distributions along the salinity gradient to a location in brackish water where the mean salinity was approximately 5%_o. At this salinity, a relatively sharp discontinuity in the diatom flora existed which appeared to represent the biochemical and biophysical mechanisms involved in the osmotic regulation of fresh- and brackish-water diatoms. Relatively large disparities m the structure of diatom assemblages were found within relatively small areas of Yaquina Bay. These differences were attributed to properties of the sediment. Differences in diatom assemblages relative to variations in light intensity, water temperature and exposure to intertidal emergence were not apparent from the analysis of field data.     

Adiantum diphyllum, a rare and endemic species of Bahia State, Brazil, and its close relatives

Adiantum diphyllum, a species endemic to the coastal forests of Bahia State, Brazil, is characterized and distinguished from other species ofAdiantum with anastomosing veins, elongate sori, and venuloid idioblasts.

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Adiantum diphyllum, uma espécie endêmica das florestas costeiras do leste do Brasil. é caracterizada e distinta das outras espécies deAdiantum com nervuras anastomosadas, soros alongados e idioblastos entre as nervuras.

     

A cluster of fourteen genes from enteropathogenic Escherichia coli is sufficient for the biogenesis of a type IV pilus

Enteropathogenic Escherichia coli (EPEC) adhere to epithelial cells in microcolonies, a pattern termed localized adherence (LA). LA is dependent upon the presence of 50–70MDa plasmids, termed EPEC adherence factor (EAF) plasmids. Expression of an EAF plasm id-encoded type IV fimbria, the bundle-forming pilus (BFP), is associated with the LA phenotype. TnphoA insertions in bfpA, the gene encoding the major structural subunit of the BFP, abolish LA. While bfpA::TnphoA mutants cannot be complemented for LA by plasmids carrying the bfpA gene alone in trans, this work shows that they can be complemented by plasmids carrying the bfpA gene, as well as approximately 10kb of downstream sequence, suggesting that such mutations have polar effects on downstream genes. The identification and characterization of a cluster of 13 genes immediately downstream of bfpA are described. The introduction into a laboratory Escherichia coli strain of a plasmid containing these 14 bfp gene cluster genes, along with pJPN14, a plasmid containing another fragment derived from the EAF plasmid, confers LA ability and BFP biogenesis. However, when a mutation is introduced into the last gene of the bfp cluster, neither LA nor BFP biogenesis is conferred. This work also provides evidence to show that the fragment cloned in pJPN14 encodes a factor(s) which results in increased levels of the pilin protein. Finally, it is shown that expression of the 14 genes in the bfp cluster from an IPTG-inducible promoter, in the absence of pJPN14, is sufficient to reconstitute BFP biogenesis in a laboratory E. cob strain, but is insufficient for LA. This is the first report demonstrating the reconstitution of a type IV pilus in a laboratory E. coli strain with a defined set of genes. The 8FP system should prove to be a useful model for studying the molecular mechanisms of type IV pilus biogenesis.     

Fine-Scale Dissection of Functional Protein Network Organization by Statistical Network Analysis

Revealing organizational principles of biological networks is an important goal of systems biology. In this study, we sought to analyze the dynamic organizational principles within the protein interaction network by studying the characteristics of individual neighborhoods of proteins within the network based on their gene expression as well as protein-protein interaction patterns. By clustering proteins into distinct groups based on their neighborhood gene expression characteristics, we identify several significant trends in the dynamic organization of the protein interaction network. We show that proteins with distinct neighborhood gene expression characteristics are positioned in specific localities in the protein interaction network thereby playing specific roles in the dynamic network connectivity. Remarkably, our analysis reveals a neighborhood characteristic that corresponds to the most centrally located group of proteins within the network. Further, we show that the connectivity pattern displayed by this group is consistent with the notion of “rich club connectivity” in complex networks. Importantly, our findings are largely reproducible in networks constructed using independent and different datasets.     

Optimized Null Model for Protein Structure Networks

Much attention has recently been given to the statistical significance of topological features observed in biological networks. Here, we consider residue interaction graphs (RIGs) as network representations of protein structures with residues as nodes and inter-residue interactions as edges. Degree-preserving randomized models have been widely used for this purpose in biomolecular networks. However, such a single summary statistic of a network may not be detailed enough to capture the complex topological characteristics of protein structures and their network counterparts. Here, we investigate a variety of topological properties of RIGs to find a well fitting network null model for them. The RIGs are derived from a structurally diverse protein data set at various distance cut-offs and for different groups of interacting atoms. We compare the network structure of RIGs to several random graph models. We show that 3-dimensional geometric random graphs, that model spatial relationships between objects, provide the best fit to RIGs. We investigate the relationship between the strength of the fit and various protein structural features. We show that the fit depends on protein size, structural class, and thermostability, but not on quaternary structure. We apply our model to the identification of significantly over-represented structural building blocks, i.e., network motifs, in protein structure networks. As expected, choosing geometric graphs as a null model results in the most specific identification of motifs. Our geometric random graph model may facilitate further graph-based studies of protein conformation space and have important implications for protein structure comparison and prediction. The choice of a well-fitting null model is crucial for finding structural motifs that play an important role in protein folding, stability and function. To our knowledge, this is the first study that addresses the challenge of finding an optimized null model for RIGs, by comparing various RIG definitions against a series of network models.