Clinical PathoScope: rapid alignment and filtration for accurate pathogen identification in clinical samples using unassembled sequencing data.

BACKGROUND: The use of sequencing technologies to investigate the microbiome of a sample can positively impact patient healthcare by providing therapeutic targets for personalized disease treatment. However, these samples contain genomic sequences from various sources that complicate the identification of pathogens. RESULTS: Here we present Clinical PathoScope, a pipeline to rapidly and accurately remove host contamination, isolate microbial reads, and identify potential disease-causing pathogens. We have accomplished three essential tasks in the development of Clinical PathoScope. First, we developed an optimized framework for pathogen identification using a computational subtraction methodology in concordance with read trimming and ambiguous read reassignment. Second, we have demonstrated the ability of our approach to identify multiple pathogens in a single clinical sample, accurately identify pathogens at the subspecies level, and determine the nearest phylogenetic neighbor of novel or highly mutated pathogens using real clinical sequencing data. Finally, we have shown that Clinical PathoScope outperforms previously published pathogen identification methods with regard to computational speed, sensitivity, and specificity. CONCLUSIONS: Clinical PathoScope is the only pathogen identification method currently available that can identify multiple pathogens from mixed samples and distinguish between very closely related species and strains in samples with very few reads per pathogen. Furthermore, Clinical PathoScope does not rely on genome assembly and thus can more rapidly complete the analysis of a clinical sample when compared with current assembly-based methods. Clinical PathoScope is freely available at: http://sourceforge.net/projects/pathoscope/.

Reactivation of adiponectin expression in obese patients after bariatric surgery.

BACKGROUND: Bariatric surgery can resolve type 2 diabetes in morbidly obese patients. However, the underlying mechanism is unknown. This study aimed to identify potential biomarkers or molecular pathways that are altered after bariatric surgery in diabetic and nondiabetic patients. METHODS: The study enrolled 17 morbidly obese patients undergoing bariatric surgery. Eight of the patients were diabetic, and nine were nondiabetic. In addition, a control group of four nonobese, nondiabetic volunteers was included. Patient blood samples were drawn before and after the operation. All blood samples were stabilized in Paxgene tubes (PreAnalytix). Total RNA was extracted and purified using the Paxgene Blood RNA Kit. For each sample, 100 ng of total RNA was amplified and labeled using the Ovation RNA Amplification System V2 with the Ovation Whole Blood reagent before hybridization to an Affymetrix Focus array containing more than 8,500 verified genes. Microarray results were analyzed with the GeneSpring GX 10.0 program, which uses an analysis of variance (ANOVA), and verified with real-time quantitative polymerase chain reaction (QPCR) using SYBR green (ABI). RESULTS: Microarray analysis showed that 167 genes were upregulated and 39 were downregulated in the obese diabetic patients. Preoperatively, adiponectin was downregulated 1.5-fold in diabetic versus nondiabetic patients. This was confirmed with quantitative PCR analysis. Preoperatively, morbidly obese patients showed a 3.12-fold downregulation of adiponectin expression versus the control group (p = 0.05). Interestingly, postoperative adiponectin levels were upregulated 2.79-fold (p = 0.02), which is close to the level of the normal control group. CONCLUSIONS: Adiponectin is dysregulated in obese patients and significantly dysregulated in obese diabetic patients. These findings correlate with the association between low levels of adiponectin and a predisposition to insulin resistance or diabetes. The data suggest that reactivation of adiponectin expression may play a part in the resolution of type 2 diabetes after bariatric surgery. Therefore, targeting adiponectin may help to develop alternative treatments for diabetes.

Adiponectin but not leptin is involved in early hepatic disease in morbidly obese patients.

BACKGROUND: Pathologic changes in the liver are common in morbidly obese patients, and insulin resistance may potentiate the progression of nonalcoholic steatohepatitis to fibrosis and cirrhosis. This study investigates the impact of leptin and adiponectin in morbidly obese diabetic and nondiabetic patients with regard to histopathologic changes in the liver. METHODS: Thirty-seven morbidly obese patients who underwent bariatric surgery with liver biopsies were enrolled in the study. Fourteen were diabetic and 23 were nondiabetic. Intraoperative liver tissue was sent for histopathologic analysis and extraneous intraoperative tissue was snap-frozen in liquid nitrogen. Total RNA was extracted and RNA was reverse transcribed to cDNA. Real-time quantitative PCR was performed to determine relative gene expression levels. The data were analyzed using a logarithmic transformation and normalized by 18S ribosome expression. Student's t test was used for statistical analysis with p < or = 0.05 as significant. RESULTS: Adiponectin expression was downregulated 4.4-fold (p < or = 0.05) in liver samples with evidence of inflammation on pathology. When hepatic inflammation was evaluated separately, there were no statistically significant differences in adiponectin levels between the diabetic and nondiabetic patients. However, overall adiponectin levels in hepatic samples of diabetic patients were 3.8-fold higher than those of nondiabetic patients (p < or = 0.05). There were no significant differences in leptin levels regardless of hepatic pathology or diabetic status. CONCLUSIONS: This study illustrates that there is a downregulation of adiponectin in morbidly obese patients with inflammatory infiltrates in the liver. Variations in adiponectin levels could be an indicator of disease progression since inflammatory infiltrates are commonly associated with nonalcoholic steatohepatitis (NASH) in morbidly obese patients. Currently, we are using human myofibroblasts derived from livers of morbidly obese people to further investigate the molecular mechanisms involved in the progression of fatty liver to fibrosis and cirrhosis.

Genome-wide analysis of BP1 transcriptional targets in breast cancer cell line Hs578T.

Homeobox genes are known to be critically important in tumor development and progression. The BP1 (Beta Protein 1) gene, an isoform of DLX4, belongs to the Distal-less (DLX) subfamily of homeobox genes and encodes a homeodomain-containing transcription factor. Our studies have shown that the BP1 gene was overexpressed in 81% of primary breast cancer and its expression was closely correlated with the progression of breast cancer. However, the exact role of BP1 in breast has yet to be elucidated. Therefore, it is important to explore the potential transcriptional targets of BP1 via whole genome-scale screening. In this study, we used the chromatin immunoprecipitation on chip (ChIP-on-chip) and gene expression microarray assays to identify candidate target genes and gene networks, which are directly regulated by BP1 in ER negative (ER-) breast cancer cells. After rigorous bioinformatic and statistical analysis for both ChIP-on-chip and expression microarray gene lists, 18 overlapping genes were noted and verified. Those potential target genes are involved in a variety of tumorigenic pathways, which sheds light on the functional mechanisms of BP1 in breast cancer development and progression.

Dysregulation of gene expression within the peroxisome proliferator activated receptor pathway in morbidly obese patients.

BACKGROUND: The causes of obesity are multifactorial but may include dysregulation of a family of related genes, such as the peroxisome proliferator activated receptor gamma (PPARgamma). When activated, the PPARgamma pathway promotes lipid metabolism. This study used microarray technology to evaluate differential gene expression profiles in obese patients undergoing bariatric surgery. METHODS: The study enrolled six morbidly obese patients with a body mass index (BMI) exceeding 35 and four nonobese individuals. Blood samples were stabilized in PaxGene tubes (PreAnalytiX), and total RNA was extracted. Next, 100 ng of total RNA was amplified and labeled using the Ovation RNA Amplification System V2 with the Ovation whole-blood reagent (NuGen) before it was hybridized to an Affymetrix (Santa Clara, CA) focus array containing more than 8,500 verified genes. The data were analyzed using an analysis of variance (ANOVA) (p < 0.05) in the GeneSpring program, and potential pathways were identified with the Ingenuity program. Real-time quantitative reverse transcriptase-polymerase chain reaction was used to validate the array data. RESULTS: A total of 97 upregulated genes and 125 downregulated genes were identified. More than a 1.5-fold change was identified between the morbidly obese patients and the control subjects for a cluster of dysregulated genes involving pathways regulating cell metabolism and lipid formation. Specifically, the PPARgamma pathway showed a plethora of dysregulated genes including tumor necrosis factor-alpha (TNFalpha). In morbidly obese patients, TNFalpha expression was increased (upregulated) 1.6-fold. These findings were confirmed using quantitative polymerase chain reaction with a 2.8-fold change. CONCLUSIONS: Microarrays are a powerful tool for identifying biomarkers indicating morbid obesity by analyzing differential gene expression profiles. This study confirms the association of PPARgamma with morbid obesity. Also, these findings in blood support previous work documented in tissue (omentum, liver, and stomach). Based on these findings in blood, the authors plan to explore postoperative changes in gene expression by analyzing blood samples after bariatric surgery. Ultimately, these findings may promote the development of therapeutic agents targeted to specific dysfunctional genes.