Analysis of Metabolomic PCA Data using Tree Diagrams

Large amounts of data from high throughput metabolomic experiments are commonly visualized using a principal component analysis (PCA) 2D scores plot. The question of the similarity or difference between multiple metabolic states then becomes a question of the degree of overlap between their respective data point clusters in PC scores space. A qualitative visual inspection of the clustering pattern in PCA score plots is a common protocol. This report describes the application of tree diagrams and bootstrapping techniques for an improved quantitative analysis of metabolic PCA data clustering. Our PCAtoTree program creates a distance matrix with 100 bootstrap steps that describes the separation of all clusters in a metabolic dataset. Using accepted phylogenetic software, the distance matrix resulting from the various metabolic states is organized into a phylogenetic-like tree format, where bootstrap values ≥ 50 indicate a statistically relevant branch separation. PCAtoTree analysis of two previously published data sets demonstrates the improved resolution of metabolic state differences using tree diagrams. In addition, for metabolomic studies of large numbers of different metabolic states, the tree format provides a better description of similarities and differences between each metabolic state. The approach is also tolerant of sample size variations between different metabolic states

Analysis of Metabolomic PCA Data using Tree Diagrams

Large amounts of data from high throughput metabolomic experiments are commonly visualized using a principal component analysis (PCA) 2D scores plot. The question of the similarity or difference between multiple metabolic states then becomes a question of the degree of overlap between their respective data point clusters in PC scores space. A qualitative visual inspection of the clustering pattern in PCA score plots is a common protocol. This report describes the application of tree diagrams and bootstrapping techniques for an improved quantitative analysis of metabolic PCA data clustering. Our PCAtoTree program creates a distance matrix with 100 bootstrap steps that describes the separation of all clusters in a metabolic dataset. Using accepted phylogenetic software, the distance matrix resulting from the various metabolic states is organized into a phylogenetic-like tree format, where bootstrap values ≥ 50 indicate a statistically relevant branch separation. PCAtoTree analysis of two previously published data sets demonstrates the improved resolution of metabolic state differences using tree diagrams. In addition, for metabolomic studies of large numbers of different metabolic states, the tree format provides a better description of similarities and differences between each metabolic state. The approach is also tolerant of sample size variations between different metabolic states

The potential of urinary metabolites for diagnosing multiple sclerosis

A definitive diagnostic test for multiple sclerosis (MS) does not exist; instead physicians use a combination of medical history, magnetic resonance imaging, and cerebrospinal fluid analysis (CSF). Significant effort has been employed to identify biomarkers from CSF to facilitate MS diagnosis; however none of the proposed biomarkers have been successful to date. Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, non-invasive, inexpensive, and efficient diagnostic tool for various human diseases. Nevertheless, urinary metabolites have not been extensively explored as a source of biomarkers for MS. Instead, we demonstrate that urinary metabolites have significant promise for monitoring disease-progression, and response to treatment in MS patients. NMR analysis of urine permitted the identification of metabolites that differentiate experimental autoimmune encephalomyelitis (EAE)-mice (prototypic disease model for MS) from healthy and MS drug-treated EAE mice

The potential of urinary metabolites for diagnosing multiple sclerosis

A definitive diagnostic test for multiple sclerosis (MS) does not exist; instead physicians use a combination of medical history, magnetic resonance imaging, and cerebrospinal fluid analysis (CSF). Significant effort has been employed to identify biomarkers from CSF to facilitate MS diagnosis; however none of the proposed biomarkers have been successful to date. Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, non-invasive, inexpensive, and efficient diagnostic tool for various human diseases. Nevertheless, urinary metabolites have not been extensively explored as a source of biomarkers for MS. Instead, we demonstrate that urinary metabolites have significant promise for monitoring disease-progression, and response to treatment in MS patients. NMR analysis of urine permitted the identification of metabolites that differentiate experimental autoimmune encephalomyelitis (EAE)-mice (prototypic disease model for MS) from healthy and MS drug-treated EAE mice

Cathelicidin-like Helminth Defence Molecules (HDMs) Absence of Cytotoxic, Anti-microbial and Anti-protozoan Activities Imply a Specific Adaptation to Immune Modulation

Host defence peptides (HDPs) are expressed throughout the animal and plant kingdoms. They have multifunctional roles in the defence against infectious agents of mammals, possessing both bactericidal and immune-modulatory activities. We have identified a novel family of molecules secreted by helminth parasites (helminth defence molecules; HDMs) that exhibit similar structural and biochemical characteristics to the HDPs. Here, we have analyzed the functional activities of four HDMs derived from Schistosoma mansoni and Fasciola hepatica and compared them to human, mouse, bovine and sheep HDPs. Unlike the mammalian HDPs the helminth-derived HDMs show no antimicrobial activity and are non-cytotoxic to mammalian cells (macrophages and red blood cells). However, both the mammalian- and helminth-derived peptides suppress the activation of macrophages by microbial stimuli and alter the response of B cells to cytokine stimulation. Therefore, we hypothesise that HDMs represent a novel family of HDPs that evolved to regulate the immune responses of their mammalian hosts by retaining potent immune modulatory properties without causing deleterious cytotoxic effects. © 2013 Thivierge et al

EMSL Geochemistry, Biogeochemistry and Subsurface Science-Science Theme Advisory Panel Meeting

This report covers the topics of discussion and the recommendations of the panel members. On December 8 and 9, 2010, the Geochemistry, Biogeochemistry, and Subsurface Science (GBSS) Science Theme Advisory Panel (STAP) convened for a more in-depth exploration of the five Science Theme focus areas developed at a similar meeting held in 2009. The goal for the fiscal year (FY) 2011 meeting was to identify potential topical areas for science campaigns, necessary experimental development needs, and scientific members for potential research teams. After a review of the current science in each of the five focus areas, the 2010 STAP discussions successfully led to the identification of one well focused campaign idea in pore-scale modeling and five longer-term potential research campaign ideas that would likely require additional workshops to identify specific research thrusts. These five campaign areas can be grouped into two categories: (1) the application of advanced high-resolution, high mass accuracy experimental techniques to elucidate the interplay between geochemistry and microbial communities in terrestrial ecosystems and (2) coupled computation/experimental investigations of the electron transfer reactions either between mineral surfaces and outer membranes of microbial cells or between the outer and inner membranes of microbial cells

EMSL Pore Scale Modeling Challenge/Workshop

Report covers the background for the workshop, objectives, important research directions, necessary capabilities and overall recommendations

Serotonin in the Pocket

This lesson introduces beginning biochemistry students to the concept of a biomolecule binding site, such as a neurotransmitter receptor site or an enzyme active site. A simple organic molecule, the neurotransmitter serotonin, is the focus of the lesson. A pre-activity guides students in their review of non-covalent interactions prior to engaging in the lesson. During the lesson, students are asked to consider three different points on the serotonin molecule where non-covalent intermolecular forces may act to hold the serotonin molecule in a binding site. After students decide on the appropriate non-covalent forces, they are presented with variations of the serotonin structure. In each case, students are asked to determine whether binding is enhanced or weakened in light of the change. Finally, students explore the likelihood that other common metabolites will also bind in the serotonin-binding site. After completing this lesson, students are able to explain the role of noncovalent interactions in the binding of small metabolite molecules to biologically relevant binding pockets such as receptor binding sites or enzyme active sites