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122


Beyond infectious disease: welcome to the era of population microbiology [Editorial]

Pincus, Matthew R; Pei, Zhiheng
PMID: 25439278
ISSN: 0272-2712
CID: 1369202

HIV-induced immunosuppression is associated with colonization by plant pathogens in the gut [Meeting Abstract]

Yang, Liying; Poles, Michael A; Fisch, Gene S; Ma, Yingfei; Nossa, Carlos; Norman, Robert G; Phelan, Joan A; Pei, Zhiheng
ISI:000341276000195
ISSN: 1791-244x
CID: 1267922

Mini-review: perspective of the microbiome in the pathogenesis of urothelial carcinoma

Xu, Weisheng; Yang, Liying; Lee, Peng; Huang, William C; Nossa, Carlos; Ma, Yingfei; Deng, Fang-Ming; Zhou, Ming; Melamed, Jonathan; Pei, Zhiheng
The microbiome is a new center of attention for studies on the pathogenesis of human disease by focusing on the alterations of all microorganisms living in a particular site or system of human body, referred as microbiota. Evidence suggests that microbiota could contribute to the pathogenesis of a number of chronic diseases, including cancers, both locally and remotely. Multiple mechanisms have been proposed and/or proven for the microbiota's role in tumorigenesis, such as via induction of chronic inflammation, genotoxicity, bacterium-mediated cell proliferation, and activation of procarcinogens. Emerging data suggest that indigenous microbiota in the urinary tract may play an important role in the tumorigenesis of urothelial carcinoma, similar to other tumors. Future studies are needed to adequately define the microbiota composition and correlate its change with urothelial carcinoma.
PMCID:4127805
PMID: 25126590
ISSN: 2330-1910
CID: 1126972

Imbalanced expression of Tif1gamma inhibits pancreatic ductal epithelial cell growth

Ligr, Martin; Wu, Xinyu; Daniels, Garrett; Zhang, David; Wang, Huamin; Hajdu, Cristina; Wang, Jinhua; Pan, Ruimin; Pei, Zhiheng; Zhang, Lanjing; Melis, Marcovalerio; Pincus, Matthew R; Saunders, John K; Lee, Peng; Xu, Ruliang
Transcriptional intermediary factor 1 gamma (Tif1gamma) (Ectodermin/PTC7/RFG7/TRIM33) is a transcriptional cofactor with an important role in the regulation of the TGFbeta pathway. It has been suggested that it competes with Smad2/Smad3 for binding to Smad4, or alternatively that it may target Smad4 for degradation, although its role in carcinogenesis is unclear. In this study, we showed that Tif1gamma interacts with Smad1/Smad4 complex in vivo, using both yeast two-hybrid and coimmunoprecipitation assays. We demonstrated that Tif1gamma inhibits transcriptional activity of the Smad1/Smad4 complex through its PHD domain or bromo-domainin pancreatic cells by luciferase assay. Additionally, there is a dynamic inverse relationship between the levels of Tif1gamma and Smad4 in benign and malignant pancreatic cell lines. Overexpression of Tif1gamma resulted in decreased level of Smad4. Both overexpression and knockdown of Tif1gamma resulted in growth inhibition in both benign and cancerous pancreatic cell lines, attributable to a G2-phase cell cycle arrest, but only knockdown of Tif1gamma reduces tumor cell invasiveness in vitro. Our study demonstrated that imbalanced expression of Tif1gamma results in inhibition of pancreatic ductal epithelial cell growth. In addition, knockdown of Tif1gamma may inhibit tumor invasion. These data suggest that Tif1gamma might serve as a potential therapeutic target for pancreatic cancer.
PMCID:4065401
PMID: 24959375
ISSN: 2156-6976
CID: 1051012

Microbiome in reflux disorders and esophageal adenocarcinoma

Yang, Liying; Chaudhary, Noami; Baghdadi, Jonathan; Pei, Zhiheng
The incidence of esophageal adenocarcinoma has increased dramatically in the United States and Europe since the 1970s without apparent cause. Although specific host factors can affect risk of disease, such a rapid increase in incidence must be predominantly environmental. In the stomach, infection with Helicobacter pylori has been linked to chronic atrophic gastritis, an inflammatory precursor of gastric adenocarcinoma. However, the role of H. pylori in the development of esophageal adenocarcinoma is not well established. Meanwhile, several studies have established that a complex microbiome in the distal esophagus might play a more direct role. Transformation of the microbiome in precursor states to esophageal adenocarcinoma-reflux esophagitis and Barrett metaplasia-from a predominance of gram-positive bacteria to mostly gram-negative bacteria raises the possibility that dysbiosis is contributing to pathogenesis. However, knowledge of the microbiome in esophageal adenocarcinoma itself is lacking. Microbiome studies open a new avenue to the understanding of the etiology and pathogenesis of reflux disorders.
PMCID:4120752
PMID: 24855009
ISSN: 1528-9117
CID: 1013072

Human papillomavirus community in healthy persons, defined by metagenomics analysis of human microbiome project shotgun sequencing data sets

Ma, Yingfei; Madupu, Ramana; Karaoz, Ulas; Nossa, Carlos W; Yang, Liying; Yooseph, Shibu; Yachimski, Patrick S; Brodie, Eoin L; Nelson, Karen E; Pei, Zhiheng
Human papillomavirus (HPV) causes a number of neoplastic diseases in humans. Here, we show a complex normal HPV community in a cohort of 103 healthy human subjects, by metagenomics analysis of the shotgun sequencing data generated from the NIH Human Microbiome Project. The overall HPV prevalence was 68.9% and was highest in the skin (61.3%), followed by the vagina (41.5%), mouth (30%), and gut (17.3%). Of the 109 HPV types as well as additional unclassified types detected, most were undetectable by the widely used commercial kits targeting the vaginal/cervical HPV types. These HPVs likely represent true HPV infections rather than transitory exposure because of strong organ tropism and persistence of the same HPV types in repeat samples. Coexistence of multiple HPV types was found in 48.1% of the HPV-positive samples. Networking between HPV types, cooccurrence or exclusion, was detected in vaginal and skin samples. Large contigs assembled from short HPV reads were obtained from several samples, confirming their genuine HPV origin. This first large-scale survey of HPV using a shotgun sequencing approach yielded a comprehensive map of HPV infections among different body sites of healthy human subjects. IMPORTANCE: This nonbiased survey indicates that the HPV community in healthy humans is much more complex than previously defined by widely used kits that are target selective for only a few high- and low-risk HPV types for cervical cancer. The importance of nononcogenic viruses in a mixed HPV infection could be for stimulating or inhibiting a coexisting oncogenic virus via viral interference or immune cross-reaction. Knowledge gained from this study will be helpful to guide the designing of epidemiological and clinical studies in the future to determine the impact of nononcogenic HPV types on the outcome of HPV infections.
PMCID:3993818
PMID: 24522917
ISSN: 0022-538x
CID: 884102

Mini-review: androgen receptor phosphorylation in prostate cancer

Daniels, Garrett; Pei, Zhiheng; Logan, Susan K; Lee, Peng
Androgen receptor (AR) plays an important role in the tumorigenesis and progression of prostate cancer (PCa), and is the primary therapeutic target for PCa treatment. AR activity can be regulated via phosphorylation at multiple phosphorylation sites within the protein. Modifications by phosphorylation alter AR function, including its cellular localization, stability and transcriptional activity, ultimately leading to changes in cancer cell biology and disease progression. Here we present a brief overview of AR phosphorylation sites in PCa, focusing on functional roles of phospho-AR (p-AR) species, relevance in PCa disease progression, and potential as biomarkers and/or therapeutic targets through the use of kinase inhibitors. Additionally, recent evidence has shown the important role of AR activity in the cancer associated stroma on PCa growth and progression. The phosphorylation status of epithelial and stromal AR may be distinct; however, the current data available on stromal AR phosphorylation is limited. Further research will determine global view on the synergistic effects of phosphorylation across multiple AR sites in both epithelial and stromal cells and validate whether together they can be used as prognostic markers and/or effective therapeutic targets for PCa.
PMCID:4219286
PMID: 25374897
ISSN: 2330-1910
CID: 1341312

Human gut microbiome and risk of colorectal cancer, a case-control study [Meeting Abstract]

Ahn, Jiyoung; Sinha, Rashmi; Pei, Zhiheng; Dominianni, Christine; Goedert, James J.; Hayes, Richard B.; Yang, Liying
ISI:000331220600149
ISSN: 0008-5472
CID: 853262

Multiple double-barcoding 16S sequencing on the MiSeq platform to study the gut microbiome in ashkenazi jews with crohn's disease [Meeting Abstract]

Hu, J; Franzen, O; Pei, Z; Itzkowitz, S; Peter, I
BACKGROUND: Crohn's disease (CD) results from defects in the mucosal immune response to luminal factors in genetically susceptible individuals. The role of the gut microbiome in CD pathogenesis has been suggested by several studies. Until recently454-pyrosequencing approach was considered the gold standard for microbiome studies. However, newer, more efficient, and cost-effective technologies are now available(1). Compared to other next-generation platforms, Illumina MiSeq has the advantage of higher throughput, better sequencing accuracy, and a shorter running time (24hrs). In this study, we designed a cost-efficient double-barcoding 16S rRNA sequencing using the MiSeq 2x250 pair-end method to evaluate the performance of MiSeq on 16S rRNA sequencing of the fecal microbiome of Ashkenazi Jews (AJ, a genetically homogeneous high-risk population) with and without Crohn's disease. (Figure presented) METHODS: Stool from 27 AJ-CD patients (in remission) and 16 AJ healthy controls was analyzed. We established a protocol for a multiple double-barcoding 16S rRNA sequencing using the MiSeq system (Fig. 1) and performed a taxon-based and phylogenetic analysis. Total DNA was extracted from the fecal samples and PCRamplified with unique 8-bp barcoded primer sets targeting the 347-803 V3-to-V4 hypervariable regions. The 460bp PCR amplicons were pooled in equal molar amounts and sent for library preparation and sequencing. RESULTS: A single MiSeq run generated a total of ;10 million paired reads. Our quality report revealed more than 95% reads with the average sequencing quality score passing Q30 and more than 50% reads with the quality of any individual base calling passing Q30. After merging, filtering by quality of the individual base calling and read length (>400bp), we obtained, on average, ;10 thousand reads per sample. QIIME pipeline(2) was applied for taxonomy assignment (Fig. 2a) and diversity analysis. Repeated measurements of 8 subjects showed high correlations (r2 > 0.99). We observed a!
EMBASE:71356040
ISSN: 1078-0998
CID: 838112

A comprehensive evaluation of multicategory classification methods for microbiomic data

Statnikov, Alexander; Henaff, Mikael; Narendra, Varun; Konganti, Kranti; Li, Zhiguo; Yang, Liying; Pei, Zhiheng; Blaser, Martin J; Aliferis, Constantin F; Alekseyenko, Alexander V
BACKGROUND: Recent advances in next-generation DNA sequencing enable rapid high-throughput quantitation of microbial community composition in human samples, opening up a new field of microbiomics. One of the promises of this field is linking abundances of microbial taxa to phenotypic and physiological states, which can inform development of new diagnostic, personalized medicine, and forensic modalities. Prior research has demonstrated the feasibility of applying machine learning methods to perform body site and subject classification with microbiomic data. However, it is currently unknown which classifiers perform best among the many available alternatives for classification with microbiomic data. RESULTS: In this work, we performed a systematic comparison of 18 major classification methods, 5 feature selection methods, and 2 accuracy metrics using 8 datasets spanning 1,802 human samples and various classification tasks: body site and subject classification and diagnosis. CONCLUSIONS: We found that random forests, support vector machines, kernel ridge regression, and Bayesian logistic regression with Laplace priors are the most effective machine learning techniques for performing accurate classification from these microbiomic data.
PMCID:3960509
PMID: 24456583
ISSN: 2049-2618
CID: 764032