QUANTITATIVE AND FUNCTIONAL ANALYSIS PIPELINE FOR LABEL-FREE METAPROTEOMICS DATA AND ITS APPLICATIONS

Since the large-scale metaproteome was first reported in 2005, metaproteomics has advanced at a tremendous rate both in its quantitative and qualitative metrics. Furthermore metaproteomics is now being applied as a general tool in microbial ecology in a large variety of environmental studies. Though metaproteomics is becoming a useful and even a standard tool for the microbial ecologist, standardized bioinformatics pipelines are not readily available. Therefore, we developed quantitative and functional analysis pipeline for metaproteomics (QFAM) to help analyze large and complicated metaproteomics data in a robust and timely fashion with outputs designed to be simple and clearly understood by the microbial ecologist. QFAM starts by running peptide-spectrum searches against resultant MS/MS datasets with mixed metagenome/appropriate protein FASTA database. Its primary search algorithm is MyriMatch/IDPicker. MyriMatch/IDPicker uses multi-CPUs effectively, has an accurate scoring-system, correctly use the high MS accuracy data, and finally has a robust method for protein determination. These are required features for metaproteomics requiring large protein database and complicated peptide-structure. QFAM has quantitative (QAM) and functional (FAM) analysis to provide dependable protein signatures and confident information for understanding the characteristics of the metaproteome. QAM employs a ’selfea’ R package, which provides probability models as well as Cohen’s effect sizes. Our benchmark data test and Monte Carlo simulation results show that selfea can reduce false positives efficiently while losing few true positives; one of the key goals of proteomics and/or metaproteomics experiments. FAM has two modules: BioSystems and COG analysis. The BioSystems module is most appropriate for well-annotated model organisms, such as humans, whereas the COG module is useful for less-annotated microorganisms and metagenome sequences. Both modules provide an enrichment test using Fisher’s exact-test and a significance test using selfea. With two statistics, FAM generates differentially enriched functional terms that are insightful for discerning biological information held behind the metaproteome data. Two application studies in chapter 4 and 5 show how QFAM can be employed for metaproteomics data analysis. QFAM is distinguished from other proteomics pipelines by multiprocessing as well as quantitative and functional analysis

Cyclic AMP Regulation of Protein Lysine Acetylation in Mycobacterium Tuberculosis

Protein lysine acetylation networks can regulate central processes such as carbon metabolism and gene expression in bacteria. In Escherichia coli, cyclic-AMP (cAMP) regulates protein lysine acetyltransferase (PAT) activity at the transcriptional level, but in Mycobacterium tuberculosis, fusion of a cyclic-nucleotide binding domain to a Gcn5-like PAT domain enables direct cAMP control of protein acetylation. Here we describe the allosteric activation mechanism of M. tuberculosis PAT. The crystal structures of the auto-inhibited and cAMP-activated PAT reveal that cAMP binds to a cryptic site in the regulatory domain over 32 Å from the catalytic site. An extensive conformational rearrangement relieves auto-inhibition by a substrate-mimicking lid that covers the protein-substrate binding surface. A steric double latch couples the domains by harnessing a classic, cAMP-mediated, conformational switch. The structures suggest general features that enable the evolution of long-range communication between linked domains

Low-energy Spectra of the t-J-Type Models Studied by Variational Approach

We discuss recent progress of understanding the phenomena observed in high Tc cuprates by studying the d-wave resonating-valence-bond (d-RVB) based trial wave functions for the 2-dimensional t-J-type models. Treat exactly the strong correlation between electrons by numerical approach, we examine the evolution of ground states described by different variational wave functions and properties of the quasi-hole and -particle excitations of the d-RVB superconducting (SC) state. Properties related to the Fermi surface geometry deduced from quasi-hole energy dispersion of the SC state is shown to be consistent with the observation by photoemission spectroscopy. With the calculated spectral weights (SW's) for adding and removing an electron, we found not only the anti-correlation between conductance peak height and width between peaks seen in tunneling experiments, but also unique properties due to strong correlation which need to be verified by future experiments.Comment: 6 revtex pages with 5 (.eps) figures. To appear in a special volume of Journal of Magnetism and Magnetic Materials for the ICM 2006 proceeding

Intraventricular Hemorrhage Caused by Lateral Ventricular Meningioma: A Case Report

Meningiomas causing intracranial hemorrhage are rare, and hemorrhage from a lateral ventricular meningioma seems to be even rarer. We report a case of trigonal meningioma in a 43-year-old woman who presented with intraventricular hemorrhage, and describe the CT, MRI and angiographic findings

Impact of Dietary Resistant Starch on the Human Gut Microbiome, Metaproteome, and Metabolome

Diet can influence the composition of the human microbiome, and yet relatively few dietary ingredients have been systematically investigated with respect to their impact on the functional potential of the microbiome. Dietary resistant starch (RS) has been shown to have health benefits, but we lack a mechanistic understanding of the metabolic processes that occur in the gut during digestion of RS. Here, we collected samples during a dietary crossover study with diets containing large or small amounts of RS. We determined the impact of RS on the gut microbiome and metabolic pathways in the gut, using a combination of “omics” approaches, including 16S rRNA gene sequencing, metaproteomics, and metabolomics. This multiomics approach captured changes in the abundance of specific bacterial species, proteins, and metabolites after a diet high in resistant starch (HRS), providing key insights into the influence of dietary interventions on the gut microbiome. The combined data showed that a high-RS diet caused an increase in the ratio of Firmicutes to Bacteroidetes, including increases in relative abundances of some specific members of the Firmicutes and concurrent increases in enzymatic pathways and metabolites involved in lipid metabolism in the gut

False Positive Immunoglobulin M Antibody to Cytomegalovirus in Child with Infectious Mononucleosis Caused by Epstein-Barr Virus Infection

A 16-month-old boy was admitted because of cough that had lasted for 10 days. The patient showed severe hepatomegaly incidentally, and dual positivity of Immunoglobulin (Ig) M to Epstein-Barr virus (EBV) viral capsid antigen (VCA) and cytomegalovirus (CMV). On the basis of seroconversion to Epstein-Barr nuclear antigen (EBNA) Ig G positivity and reduced CMV Ig M titer with persistently negative CMV Ig G, a definite diagnosis of EBV-induced infectious mononucleosis was established 1 year 2 month later

Size Dependence of Metal-Insulator Transition in Stoichiometric Fe3O4 Nanocrystals

Magnetite (Fe3O4) is one of the most actively studied materials with a famous metal-insulator transition (MIT), so-called the Verwey transition at around 123 K. Despite the recent progress in synthesis and characterization of Fe3O4 nanocrystals (NCs), it is still an open question how the Verwey transition changes on a nanometer scale. We herein report the systematic studies on size dependence of the Verwey transition of stoichiometric Fe3O4 NCs. We have successfully synthesized stoichiometric and uniform-sized Fe3O4 NCs with sizes ranging from 5 to 100 nm. These stoichiometric Fe3O4 NCs show the Verwey transition when they are characterized by conductance, magnetization, cryo-XRD, and heat capacity measurements. The Verwey transition is weakly size-dependent and becomes suppressed in NCs smaller than 20 nm before disappearing completely for less than 6 nm, which is a clear, yet highly interesting indication of a size effect of this well-known phenomena. Our current work will shed new light on this ages-old problem of Verwey transition.Comment: 18 pages, 4 figures, Nano Letters (accepted

The relationship between the frequency of news release and the information asymmetry: The role of uninformed trading

This paper shows that the degree of information asymmetry is lower for firms with more frequent news releases. The relation holds for various measures of information asymmetry such as the probability of information-based trading (. PIN), permanent price impact, and adverse selection component of bid-ask spread, even after adjusting for endogeneity between news release and information asymmetry. By decomposing the PIN into intensities of uninformed and informed trades, similarly to Brown and Hillegeist (2007), we find that intensity of uninformed trading increases much more than that of informed trading for firms with more frequent news releases. As a result, information asymmetry, as is measured by PIN, decreases for such firms due to the large increase in the intensity of uninformed trading. Our findings highlight not only the importance of news releases in leveling the playing field of investors but also the role of uninformed investors in reducing trading cost due to information asymmetry. © 2013 Elsevier B.V..Srinivasan Sankaraguruswamy, Jianfeng Shen, Takeshi Yamad