Metagenomic biomarker discovery and explanation

This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.National Institute of Dental and Craniofacial Research (U.S.) (grant DE017106)National Institutes of Health (U.S.) (NIH grant AI078942)Burroughs Wellcome FundNational Institutes of Health (U.S.) (NIH 1R01HG005969

Computational Modeling of the Human Microbiome

The impact of microorganisms on human health has long been acknowledged and studied, but recent advances in research methodologies have enabled a new systems-level perspective on the collections of microorganisms associated with humans, the human microbiome. Large-scale collaborative efforts such as the NIH Human Microbiome Project have sought to kick-start research on the human microbiome by providing foundational information on microbial composition based upon specific sites across the human body. Here, we focus on the four main anatomical sites of the human microbiome: gut, oral, skin, and vaginal, and provide information on site-specific background, experimental data, and computational modeling. Each of the site-specific microbiomes has unique organisms and phenomena associated with them; there are also high-level commonalities. By providing an overview of different human microbiome sites, we hope to provide a perspective where detailed, site-specific research is needed to understand causal phenomena that impact human health, but there is equally a need for more generalized methodology improvements that would benefit all human microbiome research

9th Annual Postdoctoral Science Symposium

The mission of the Annual Postdoctoral Science Symposium (APSS) is to provide a platform for talented postdoctoral fellows throughout the Texas Medical Center to present their work to a wider audience. The MD Anderson Postdoctoral Association convened its inaugural Annual Postdoctoral Science Symposium (APSS) on August 4, 2011. The APSS provides a professional venue for postdoctoral scientists to develop, clarify, and refine their research as a result of formal reviews and critiques of faculty and other postdoctoral scientists. Additionally, attendees discuss current research on a broad range of subjects while promoting academic interactions and enrichment and developing new collaborations

Identification of novel targets for breast cancer by exploring gene switches on a genome scale

<p>Abstract</p> <p>Background</p> <p>An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches.</p> <p>Results</p> <p>We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER) and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2) is uncovered. We further suggest a likely transcription factor that regulates TACSTD2.</p> <p>Conclusions</p> <p>Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.</p

Predicting cardiovascular risk in diabetic patients: arewe all on the same side?

Cardiovascular diseases are the main reason for morbidity and mortality in diabetic patients, and cardiovascular risk is increased at least twofold in men and at least fourfold in women with diabetes compared to non-diabetic populations. Predictive medicine is of the utmost importance in the clinical care of diabetic patients, since predicting cardiovascular risk is essential for modification of risk factors aimed at prevention or delay of future cardiovascular events. The prediction of cardiovascular risk is a valuable tool within the context of patient-centered care, as it includes active participation of diabetic patients in the decision-making process, resulting in higher compliance with the treatments agreed. However, there are differences among the current guidelines of various international authorities, such as the International Diabetes Federation (IDF), European Society of Cardiology (ESC) / European Association for Study of Diabetes (EASD), American College of Cardiology (ACC) / American Heart Association (AHA), American Diabetes Association (ADA), and National Institute for Health and Care Excellence (NICE), for the prediction of cardiovascular risk in diabetic patients. Furthermore, the clinical use of models with classic risk factors and novel biomarkers that would predict cardiovascular risk in diabetic patients from various populations with acceptable precision poses a challenge. Taking into consideration the global diabetes pandemic and its close association with cardiovascular diseases, there is an urgent need for streamlining of current guidelines on the prediction of cardiovascular risk and its use in clinical practice

Modulators of the Acute Inflammatory Response: A Dissertation

Acute inflammatory response is caused by the rapid recruitment of leukocytes, mainly neutrophils and monocytes, from blood to the tissue site. Diverse agents, including invading pathogens, injured or dead cells, and other irritants, may stimulate this response. In the ensuing inflammatory response, the recruited leukocytes and their secreted molecules help in eliminating or containing the injurious agents and promoting tissue regeneration. But often this response is imprecise and can lead to bystander tissue damage. Unchecked neutrophil activation is implicated in the pathology of many inflammatory conditions. An in-depth understanding of the pathways regulating this response, therefore, becomes critical in identifying therapeutic targets for these diseases. In this study, we investigate the role of intestinal commensal bacteria in regulating the acute inflammatory response. Furthermore, we examine the mechanism by which Interleukin-1 (IL-1) controls the inflammatory response to sterile agents. Inflammatory responses have been studied in the context of host defense against pathogens. However, we report that the innate immune system needs to be primed by intestinal flora to enable neutrophil recruitment to diverse microbial or sterile inflammatory signals. This priming requires myeloid differentiation primary response gene (88) (MyD88) signaling. In antibiotic-treated mice, which have depleted intestinal flora, we show that neutrophils get released into the blood from the bone marrow, but have a specific defect in migration into the inflammed tissue. This deficiency can be restored by pre-stimulating the mice with a purified MyD88 ligand. Despite having reduced number of infiltrating neutrophils, antibiotic-treated mice make higher levels of pro-inflammatory cytokines in the tissue, after inflammatory challenge. This suggests that antibiotic-treated mice produce some anti-inflammatory molecule(s) that counteract the effect of the pro-inflammatory cytokines. However, this effect is not due to the overproduction of the anti-inflammatory cytokine, Interleukin-10 (IL-10). In summary, our findings highlight the role of commensals in the development of acute inflammatory responses to microbial and sterile particles. The inflammatory response to sterile dead cells has been shown to be critically dependent upon IL-1. However, several key aspects of the IL-1 signaling cascade including the source of IL-1 and the cellular target of IL-1 were unresolved. We find that in most cases, the injured cells are not a major contributor of IL-1 that is required to propagate the inflammatory signal. On the contrary, we demonstrate that both the isoforms of IL-1, IL-1α/IL-1β are generated by bone marrow-derived, tissue-resident responding cells, upon sensing the injury. We also sought to determine the identity of the cellular target of IL-1 signaling. Previous studies have shown that for cell death-induced neutrophil recruitment, interleukin-1 receptor (IL-1R) expression is required on parenchymal cells. To identify this parenchymal cell, we are currently in the process of making the conditional knockout mouse of IL-1R. The latter would facilitate the parenchymal tissue-specific deletion of IL-1R. In summary, this study reports our progress in unraveling key aspects of IL-1 signaling during sterile inflammation. Taken together, we have identified key modulators of the acute inflammatory response and their mechanisms of regulation. These findings would facilitate the development of new therapies for inflammatory diseases triggered by both microbe and sterile agents

Bioinformatic pipelines to reconstruct and analyse intercellular and hostmicrobe interactions affecting epithelial signalling pathways

The epithelium segregates microorganisms from the immune system through tightly connected cells. The epithelial barrier maintains the integrity of the body, and the microbiome influences this through host-microbe interactions. Therefore its composition has an impact on the host's physiological processes. Disruption in the microbiome composition leads to an impaired epithelial layer. As a consequence, the cell-cell interactions between the epithelium and immune cells will be altered, contributing to inflammation. In this thesis, I examined the interconnectivity of the microbiome, epithelium and immune system in the gastrointestinal tract focusing on the oral cavity and gut in healthy and diseased conditions. I combined multi-omics data with network biology approaches to develop computational pipelines to study host-microbe and cell-cell connections. I used network propagation algorithms to reconstruct intracellular signalling and identify downstream pathways affected by the altered microbiome composition or cell-cell connections. I studied inflammation-related conditions in the oral cavity (periodontitis) and gut (inflammatory bowel disease (IBD)) to reveal the contribution of interspecies and intercellular interactions to diseases. I inferred hostmicrobe protein-protein interaction (HM-PPI) networks between healthy gum-/periodontitisrelated bacteria communities and epithelium, and found altered HM-PPIs during inflammation. I connected the epithelial cells to dendritic cells and identified the Toll-like receptor (TLR) pathway as a potential driver of the inflammation in diseased gingiva. While in the oral cavity I focused on complex microbial communities and their impact on one cell type, I discovered the direct effect of gut commensal bacteria on several immune cells in IBD. This study observed the cell-specific effect of Bacteroides thetaiotaomicron on TLR signalling. The pipelines I developed offer potentially interesting connections that aid detailed mechanistic insight into the relationship between the microbiome, epithelial barrier and immune system. These systems-level analysis tools facilitate the understanding of how microbial proteins may be of therapeutic value in inflammatory diseases