The knowledge-integrated network biomarkers discovery for major adverse cardiac events

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein-protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein-protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction.     

Overcoming the anaerobic hurdle in phenotypic microarrays: generation and visualization of growth curve data for Desulfovibrio vulgaris Hildenborough

Growing anaerobic microorganisms in phenotypic microarrays (PM) and 96-well microtiter plates is an emerging technology that allows high throughput survey of the growth and physiology and/or phenotype of cultivable microorganisms. For non-model bacteria, a method for phenotypic analysis is invaluable, not only to serve as a starting point for further evaluation, but also to provide a broad understanding of the physiology of an uncharacterized wild-type organism or the physiology/phenotype of a newly created mutant of that organism. Given recent advances in genetic characterization and targeted mutations to elucidate genetic networks and metabolic pathways, high-throughput methods for determining phenotypic differences are essential. Here we outline challenges presented in studying the physiology and phenotype of a sulfate-reducing anaerobic delta proteobacterium, Desulfovibrio vulgaris Hildenborough. Modifications of the commercially available OmniLog system (Hayward, CA) for experimental setup, and configuration, as well as considerations in PM data analysis are presented. Also highlighted here is data viewing software that enables users to view and compare multiple PM data sets. The PM method promises to be a valuable strategy in our systems biology approach to D. vulgaris studies and is readily applicable to other anaerobic and aerobic bacteria.     

Double Superhelix Model of High Density Lipoprotein

High density lipoprotein (HDL), the carrier of so-called “good” cholesterol, serves as the major athero-protective lipoprotein and has emerged as a key therapeutic target for cardiovascular disease. We applied small angle neutron scattering (SANS) with contrast variation and selective isotopic deuteration to the study of nascent HDL to obtain the low resolution structure in solution of the overall time-averaged conformation of apolipoprotein AI (apoA-I) versus the lipid (acyl chain) core of the particle. Remarkably, apoA-I is observed to possess an open helical shape that wraps around a central ellipsoidal lipid phase. Using the low resolution SANS shapes of the protein and lipid core as scaffolding, an all-atom computational model for the protein and lipid components of nascent HDL was developed by integrating complementary structural data from hydrogen/deuterium exchange mass spectrometry and previously published constraints from multiple biophysical techniques. Both SANS data and the new computational model, the double superhelix model, suggest an unexpected structural arrangement of protein and lipids of nascent HDL, an anti-parallel double superhelix wrapped around an ellipsoidal lipid phase. The protein and lipid organization in nascent HDL envisages a potential generalized mechanism for lipoprotein biogenesis and remodeling, biological processes critical to sterol and lipid transport, organismal energy metabolism, and innate immunity.     

Contribution of mobile genetic elements to Desulfovibrio vulgaris genome plasticity

The genome of Desulfovibrio vulgaris strain DePue, a sulfate-reducing Deltaproteobacterium isolated from heavy metal-impacted lake sediment, was completely sequenced and compared with the type strain D. vulgaris Hildenborough. The two genomes share a high degree of relatedness and synteny, but harbour distinct prophage and signatures of past phage encounters. In addition to a highly variable phage contribution, the genome of strain DePue contains a cluster of open-reading frames not found in strain Hildenborough coding for the production and export of a capsule exopolysaccharide, possibly of relevance to heavy metal resistance. Comparative whole-genome microarray analysis on four additional D. vulgaris strains established greater interstrain variation within regions associated with phage insertion and exopolysaccharide biosynthesis.     

Using the stress response to monitor process control: pathways to more effective bioremediation

Environmental contamination with a variety of pollutants has prompted the development of effective bioremediation strategies. But how can these processes be best monitored and controlled? One avenue under investigation is the development of stress response systems as tools for effective and general process control. Although the microbial stress response has been the subject of intensive laboratory investigation, the environmental reflection of the laboratory response to specific stresses has been little explored. However, it is only within an environmental context, in which microorganisms are constantly exposed to multiple changing environmental stresses, that there will be full understanding of microbial adaptive resiliency. Knowledge of the stress response in the environment will facilitate the control of bioremediation and other processes mediated by complex microbial communities.     

Characterization of Coastal Urban Watershed Bacterial Communities Leads to Alternative Community-Based Indicators

Background

Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring.

Methodology/Principal Findings

Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and α-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC∶A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies.

Conclusions/Significance

This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health.