Pseudomonas aeruginosa PAO1 Is Attracted to Bovine Bile in a Novel, Cystic Fibrosis-Derived Bronchial Epithelial Cell Model.

Cystic fibrosis (CF) is a life-threatening, inherited, multi-organ disease that renders patients susceptible throughout their lives to chronic and ultimately deteriorating protracted pulmonary infections. Those infections are dominated in adulthood by the opportunistic pathogen, Pseudomonas aeruginosa (Pa). As with other advancing respiratory illnesses, people with CF (pwCF) also frequently suffer from gastroesophageal reflux disease (GERD), including bile aspiration into the lung. GERD is a major co-morbidity factor in pwCF, with a reported prevalence of 35-81% in affected individuals. Bile is associated with the early acquisition of Pa in CF patients and in vitro studies show that it causes Pa to adopt a chronic lifestyle. We hypothesized that Pa is chemoattracted to bile in the lung environment. To evaluate, we developed a novel chemotaxis experimental system mimicking the lung environment using CF-derived bronchial epithelial (CFBE) cells which allowed for the evaluation of Pa (strain PAO1) chemotaxis in a physiological scenario superior to the standard in vitro systems. We performed qualitative and quantitative chemotaxis tests using this new experimental system, and microcapillary assays to demonstrate that bovine bile is a chemoattractant for Pa and is positively correlated with bile concentration. These results further buttress the hypothesis that bile likely contributes to the colonization and pathogenesis of Pa in the lung, particularly in pwCF.

The Arginine Catabolism-Derived Amino Acid l-ornithine Is a Chemoattractant for Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a common, opportunistic bacterial pathogen among patients with cystic fibrosis, asthma, and chronic obstructive pulmonary disease. During the course of these diseases, l-ornithine, a non-proteinogenic amino acid, becomes more abundant. P. aeruginosa is chemotactic towards other proteinogenic amino acids. Here, we evaluated the chemotaxis response of P. aeruginosa towards l-ornithine. Our results show that l-ornithine serves as a chemoattractant for several strains of P. aeruginosa, including clinical isolates, and that the chemoreceptors involved in P. aeruginosa PAO1 are PctA and PctB. It seems likely that P. aeruginosa's chemotactic response to l-ornithine might be a common feature and thus could potentially contribute to pathogenesis processes during colonization and infection scenarios.

Gene characteristics predicting missense, nonsense and frameshift mutations in tumor samples.

BACKGROUND: Because driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples. RESULTS: We used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations- positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified. CONCLUSIONS: By comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.

Identification of gene expression levels in primary melanoma associated with clinically meaningful characteristics.

Factors influencing melanoma survival include sex, age, clinical stage, lymph node involvement, as well as Breslow thickness, presence of tumor-infiltrating lymphocytes based on histological analysis of primary melanoma, mitotic rate, and ulceration. Identification of genes whose expression in primary tumors is associated with these key tumor/patient characteristics can shed light on molecular mechanisms of melanoma survival. Here, we show results from a gene expression analysis of formalin-fixed paraffin-embedded primary melanomas with extensive clinical annotation. The Cancer Genome Atlas data on primary melanomas were used for validation of nominally significant associations. We identified five genes that were significantly associated with the presence of tumor-infiltrating lymphocytes in the joint analysis after adjustment for multiple testing: IL1R2, PPL, PLA2G3, RASAL1, and SGK2. We also identified two genes significantly associated with melanoma metastasis to the regional lymph nodes (PIK3CG and IL2RA), and two genes significantly associated with sex (KDM5C and KDM6A). We found that LEF1 was significantly associated with Breslow thickness and CCNA2 and UBE2T with mitosis. RAD50 was the gene most significantly associated with survival, with a higher level of expression associated with worse survival.

High-Throughput Analysis of DNA Break-Induced Chromosome Rearrangements by Amplicon Sequencing.

The mechanistic understanding of how DNA double-strand breaks (DSB) are repaired is rapidly advancing in part due to the advent of inducible site-specific break model systems as well as the employment of next-generation sequencing (NGS) technologies to sequence repair junctions at high depth. Unfortunately, the sheer volume of data produced by these methods makes it difficult to analyze the structure of repair junctions manually or with other general-purpose software. Here, we describe methods to produce amplicon libraries of DSB repair junctions for sequencing, to map the sequencing reads, and then to use a robust, custom python script, Hi-FiBR, to analyze the sequence structure of mapped reads. The Hi-FiBR analysis processes large data sets quickly and provides information such as number and type of repair events, size of deletion, size of insertion and inserted sequence, microhomology usage, and whether mismatches are due to sequencing error or biological effect. The analysis also corrects for common alignment errors generated by sequencing read mapping tools, allowing high-throughput analysis of DSB break repair fidelity to be accurately conducted regardless of which suite of NGS analysis software is available.

PI3K/Akt/mTOR Signaling and Plasma Membrane Proteins Are Implicated in Responsiveness to Adjuvant Dendritic Cell Vaccination for Metastatic Colorectal Cancer.

PURPOSE: We have previously demonstrated that patients with metastatic colorectal cancer who exhibit immune responses to a dendritic cell (DC) vaccine have superior recurrence-free survival following surgery, compared with patients in whom responses do not occur. We sought to characterize the patterns of T-lymphocyte infiltration and somatic mutations in metastases that are associated with and predictive of response to the DC vaccine. EXPERIMENTAL DESIGN: Cytotoxic, memory, and regulatory T cells in resected metastases and surrounding normal liver tissue from 22 patients (11 responders and 11 nonresponders) were enumerated by immunohistochemistry prior to vaccine administration. In conjunction with tumor sequencing, the combined multivariate and collapsing method was used to identify gene mutations that are associated with vaccine response. We also derived a response prediction score for each patient using his/her tumor genotype data and variant association effect sizes computed from the other 21 patients; greater weighting was placed on gene products with cell membrane-related functions. RESULTS: There was no correlation between vaccine response and intratumor, peritumor, or hepatic densities of T-cell subpopulations. Associated genes were found to be enriched in the PI3K/Akt/mTOR signaling axis (P < 0.001). Applying a consistent prediction score cutoff over 22 rounds of leave-one-out cross-validation correctly inferred vaccine response in 21 of 22 patients (95%). CONCLUSIONS: Adjuvant DC vaccination has shown promise as a form of immunotherapy for patients with metastatic colorectal cancer. Its efficacy may be influenced by somatic mutations that affect pathways involving PI3K, Akt, and mTOR, as well as tumor surface proteins. Clin Cancer Res; 23(2); 399-406. ©2016 AACR.