Novel organization and divergent dockerin specificities in the cellulosome system of Ruminococcus flavefaciens

The DNA sequence coding for putative cellulosomal scaffolding protein ScaA from the rumen cellulolytic anaerobe Ruminococcus flavefaciens 17 was completed. The mature protein exhibits a calculated molecular mass of 90,198 Da and comprises three cohesin domains, a C-terminal dockerin, and a unique N-terminal X domain of unknown function. A novel feature of ScaA is the absence of an identifiable cellulose-binding module. Nevertheless, native ScaA was detected among proteins that attach to cellulose and appeared as a glycosylated band migrating at around 130 kDa. The ScaA dockerin was previously shown to interact with the cohesin-containing putative surface-anchoring protein ScaB. Here, six of the seven cohesins from ScaB were overexpressed as histidine-tagged products in E. coli; despite their considerable sequence differences, each ScaB cohesin specifically recognized the native 130-kDa ScaA protein. The binding specificities of dockerins found in R. flavefaciens plant cell wall-degrading enzymes were examined next. The dockerin sequences of the enzymes EndA, EndB, XynB, and XynD are all closely related but differ from those of XynE and CesA. A recombinant ScaA cohesin bound selectively to dockerin-containing fragments of EndB, but not to those of XynE or CesA. Furthermore, dockerin-containing EndB and XynB, but not XynE or CesA, constructs bound specifically to native ScaA. XynE- and CesA-derived probes did however bind a number of alternative R. flavefaciens bands, including an approximately 110-kDa supernatant protein expressed selectively in cultures grown on xylan. Our findings indicate that in addition to the ScaA dockerin-ScaB cohesin interaction, at least two distinct dockerin-binding specificities are involved in the novel organization of plant cell wall-degrading enzymes in this species and suggest that different scaffoldins and perhaps multiple enzyme complexes may exist in R. flavefaciens.     

Restricted distribution of the butyrate kinase pathway among butyrate-producing bacteria from the human colon

The final steps in butyrate synthesis by anaerobic bacteria can occur via butyrate kinase and phosphotransbutyrylase or via butyryl-coenzyme A (CoA):acetate CoA-transferase. Degenerate PCR and enzymatic assays were used to assess the presence of butyrate kinase among 38 anaerobic butyrate-producing bacterial isolates from human feces that represent three different clostridial clusters (IV, XIVa, and XVI). Only four strains were found to possess detectable butyrate kinase activity. These were also the only strains to give PCR products (verifiable by sequencing) with degenerate primer pairs designed within the butyrate kinase gene or between the linked butyrate kinase/phosphotransbutyrylase genes. Further analysis of the butyrate kinase/phosphotransbutyrylase genes of one isolate, L2-50, revealed similar organization to that described previously from different groups of clostridia, along with differences in flanking sequences and phylogenetic relationships. Butyryl-CoA:acetate CoA-transferase activity was detected in all 38 strains examined, suggesting that it, rather than butyrate kinase, provides the dominant route for butyrate formation in the human colonic ecosystem that contains a constantly high concentration of acetate.     

Deciphering membrane protein structures from protein sequences

ABSTRACT: Co-evolving positions within protein sequences have been used as spatial constraints to develop a computational approach for modeling membrane protein structures.     

GeneTools – application for functional annotation and statistical hypothesis testing

Background  

Modern biology has shifted from "one gene" approaches to methods for genomic-scale analysis like microarray technology, which allow simultaneous measurement of thousands of genes. This has created a need for tools facilitating interpretation of biological data in "batch" mode. However, such tools often leave the investigator with large volumes of apparently unorganized information. To meet this interpretation challenge, gene-set, or cluster testing has become a popular analytical tool. Many gene-set testing methods and software packages are now available, most of which use a variety of statistical tests to assess the genes in a set for biological information. However, the field is still evolving, and there is a great need for "integrated" solutions.