Streptococcus gallolyticus subsp. gallolyticus (Sg) has long been known to have a strong association with colorectal cancer (CRC). This knowledge has important clinical implications, and yet little is known about the role of Sg in the development of CRC. Here we demonstrate that Sg promotes human colon cancer cell proliferation in a manner that depends on cell context, bacterial growth phase and direct contact between bacteria and colon cancer cells. In addition, we observed increased level of β-catenin, c-Myc and PCNA in colon cancer cells following incubation with Sg. Knockdown or inhibition of β-catenin abolished the effect of Sg. Furthermore, mice administered with Sg had significantly more tumors, higher tumor burden and dysplasia grade, and increased cell proliferation and β-catenin staining in colonic crypts compared to mice receiving control bacteria. Finally, we showed that Sg is present in the majority of CRC patients and is preferentially associated with tumor compared to normal tissues obtained from CRC patients. These results taken together establish for the first time a tumor-promoting role of Sg that involves specific bacterial and host factors and have important clinical implications.

Ferritin-like molecules are unique to cellular iron homeostasis because they can store iron at concentrations much higher than those dictated by the solubility of Fe 3+ . Very little is known about the protein interactions that deliver iron for storage or promote the mobilization of stored iron from ferritinlike molecules. Here, we report the X-ray crystal structure of Pseudomonas aeruginosa bacterioferritin (Pa-BfrB) in complex with bacterioferritin-associated ferredoxin (Pa-Bfd) at 2.0 Å resolution. As the first example of a ferritin-like molecule in complex with a cognate partner, the structure provides unprecedented insight into the complementary interface that enables the [2Fe-2S] cluster of Pa-Bfd to promote hememediated electron transfer through the BfrB protein dielectric (∼18 Å), a process that is necessary to reduce the core ferric mineral and facilitate mobilization of Fe 2+ . The Pa-BfrB−Bfd complex also revealed the first structure of a Bfd, thus providing a first view to what appears to be a versatile metal binding domain ubiquitous to the large Fer2_BFD family of proteins and enzymes with diverse functions. Residues at the Pa-BfrB−Bfd interface are highly conserved in Bfr and Bfd sequences from a number of pathogenic bacteria, suggesting that the specific recognition between Pa-BfrB and Pa-Bfd is of widespread significance to the understanding of bacterial iron homeostasis.

Assigning valid functions to proteins identified in genome projects is challenging, with over-prediction and database annotation errors major concerns1. We, and others2, are developing computation-guided strategies for functional discovery using “metabolite docking” to experimentally derived3 or homology-based4 three-dimensional structures. Bacterial metabolic pathways often are encoded by “genome neighborhoods” (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by “predicting” the intermediates in the glycolytic pathway in E. coli5. Metabolite docking to multiple binding proteins/enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. We report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed i) the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans-4-hydroxy-L-proline betaine (tHyp-B) and cis-4-hydroxy-D-proline betaine (cHyp-B), and ii) the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guide functional predictions to enable the discovery of new metabolic pathways.

Metabolic pathways in eubacteria and archaea often are encoded by operons and/or gene clusters (genome neighborhoods) that provide important clues for assignment of both enzyme functions and metabolic pathways. We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families. We demonstrate the utility of the GNN approach by predicting in vitro activities and in vivo functions in the proline racemase superfamily (PRS; InterPro IPR008794). The predictions were verified by measuring in vitro activities for 51 proteins in 12 families in the PRS that represent ∼85% of the sequences; in vitro activities of pathway enzymes, carbon/nitrogen source phenotypes, and/or transcriptomic studies confirmed the predicted pathways. The synergistic use of sequence similarity networks3 and GNNs will facilitate the discovery of the components of novel, uncharacterized metabolic pathways in sequenced genomes.DOI: http://dx.doi.org/10.7554/eLife.03275.001

In this study, an attempt has been made to identify expression-based gene biomarkers that can discriminate early and late stage of clear cell renal cell carcinoma (ccRCC) patients. We have analyzed the gene expression of 523 samples to identify genes that are differentially expressed in the early and late stage of ccRCC. First, a threshold-based method has been developed, which attained a maximum accuracy of 71.12% with ROC 0.67 using single gene NR3C2. To improve the performance of threshold-based method, we combined two or more genes and achieved maximum accuracy of 70.19% with ROC of 0.74 using eight genes on the validation dataset. These eight genes include four underexpressed (NR3C2, ENAM, DNASE1L3, FRMPD2) and four overexpressed (PLEKHA9, MAP6D1, SMPD4, C11orf73) genes in the late stage of ccRCC. Second, models were developed using state-of-art techniques and achieved maximum accuracy of 72.64% and 0.81 ROC using 64 genes on validation dataset. Similar accuracy was obtained on 38 genes selected from subset of genes, involved in cancer hallmark biological processes. Our analysis further implied a need to develop gender-specific models for stage classification. A web server, CancerCSP, has been developed to predict stage of ccRCC using gene expression data derived from RNAseq experiments.

Streptococcus gallolyticus subspecies gallolyticus (Sgg) has a strong clinical association with colorectal cancer (CRC) and actively promotes the development of colon tumors. However, the molecular determinants involved in Sgg pathogenicity in the gut are unknown. Bacterial type VII secretion systems (T7SS) mediate pathogen interactions with their host and are important for virulence in pathogenic mycobacteria and Staphylococcus aureus. Through genome analysis, we identified a locus in Sgg strain TX20005 that encodes a putative type VII secretion system (designated as SggT7SST05). We showed that core genes within the SggT7SST05 locus are expressed in vitro and in the colon of mice. Western blot analysis showed that SggEsxA, a protein predicted to be a T7SS secretion substrate, is detected in the bacterial culture supernatant, indicating that this SggT7SST05 is functional. Deletion of SggT7SST05 (TX20005Δesx) resulted in impaired bacterial adherence to HT29 cells and abolished the ability of Sgg to stimulate HT29 cell proliferation. Analysis of bacterial culture supernatants suggest that SggT7SST05-secreted factors are responsible for the pro-proliferative activity of Sgg, whereas Sgg adherence to host cells requires both SggT7SST05-secreted and bacterial surface-associated factors. In a murine gut colonization model, TX20005Δesx showed significantly reduced colonization compared to the parent strain. Furthermore, in a mouse model of CRC, mice exposed to TX20005 had a significantly higher tumor burden compared to saline-treated mice, whereas those exposed to TX20005Δesx did not. Examination of the Sgg load in the colon in the CRC model suggests that SggT7SST05-mediated activities are directly involved in the promotion of colon tumors. Taken together, these results reveal SggT7SST05 as a previously unrecognized pathogenicity determinant for Sgg colonization of the colon and promotion of colon tumors.

Mxr1p (methanol expression regulator 1) functions as a key regulator of methanol metabolism in the methylotrophic yeast Pichia pastoris. In this study, a recombinant Mxr1p protein containing the N-terminal zinc finger DNA binding domain was overexpressed and purified from E. coli cells and its ability to bind to promoter sequences of AOXI encoding alcohol oxidase was examined. In the AOX1 promoter, Mxr1p binds at six different regions. Deletions encompassing these regions result in a significant decrease in AOXI promoter activity in vivo. Based on the analysis of AOXI promoter sequences, a consensus sequence for Mxr1p binding consisting of a core 5' CYCC 3' motif was identified. When the core CYCC sequence is mutated to CYCA, CYCT or CYCM (M = 5-methylcytosine), Mxr1p binding is abolished. Though Mxr1p is the homologue of Saccharomyces cerevisiae Adr1p transcription factor, it does not bind to Adr1p binding site of S. cerevisiae alcohol dehydrogenase promoter (ADH2UAS1). However, two point mutations convert ADH2UAS1 into an Mxr1p binding site. The identification of key DNA elements involved in promoter recognition by Mxr1p is an important step in understanding its function as a master regulator of the methanol utilization pathway in P. pastoris.

Hemophores from Serratia marcescens (HasAsm) and Pseudomonas aeruginosa (HasAp) bind hemin between two loops, which harbor the axial ligands H32 and Y75. Hemin binding to the Y75 loop triggers closing of the H32 loop and enables binding of H32. Because Yersinia pestis HasA (HasAyp) presents a Gln at position 32, we determined the structures of apo-and holo-HasAyp. Surprisingly, the Q32 loop in apo-HasAyp is already in the closed conformation but no residue from the Q32 loop binds hemin in holo-HasAyp. In agreement with the minimal reorganization between the apo-and holo-structures, the hemin on-rate is too fast to detect by conventional stopped-flow measurements.