Controlled activation of protein rotational dynamics using smart hydrogel tethering.

Stimulus-responsive hydrogel materials that stabilize and control protein dynamics have the potential to enable a range of applications that take advantage of the inherent specificity and catalytic efficiencies of proteins. Here we describe the modular construction of a hydrogel using an engineered calmodulin (CaM) within a poly(ethylene glycol) (PEG) matrix that involves the reversible tethering of proteins through an engineered CaM-binding sequence. For these measurements, maltose binding protein (MBP) was isotopically labeled with (13)C and (15)N, permitting dynamic structural measurements using TROSY-HSQC NMR spectroscopy. The protein dynamics is suppressed upon initial formation of hydrogels, with a concomitant increase in protein stability. Relaxation of the hydrogel matrix following transient heating results in enhanced protein dynamics and resolution of substrate-induced large-amplitude domain rearrangements.

Studying Salmonellae and Yersiniae host-pathogen interactions using integrated 'omics and modeling.

Salmonella and Yersinia are two distantly related genera containing species with wide host-range specificity and pathogenic capacity. The metabolic complexity of these organisms facilitates robust lifestyles both outside of and within animal hosts. Using a pathogen-centric systems biology approach, we are combining a multi-omics (transcriptomics, proteomics, metabolomics) strategy to define properties of these pathogens under a variety of conditions including those that mimic the environments encountered during pathogenesis. These high-dimensional omics datasets are being integrated in selected ways to improve genome annotations, discover novel virulence-related factors, and model growth under infectious states. We will review the evolving technological approaches toward understanding complex microbial life through multi-omic measurements and integration, while highlighting some of our most recent successes in this area.

A multi-omic systems approach to elucidating Yersinia virulence mechanisms.

The underlying mechanisms that lead to dramatic differences between closely related pathogens are not always readily apparent. For example, the genomes of Yersinia pestis (YP) the causative agent of plague with a high mortality rate and Yersinia pseudotuberculosis (YPT) an enteric pathogen with a modest mortality rate are highly similar with some species specific differences; however the molecular causes of their distinct clinical outcomes remain poorly understood. In this study, a temporal multi-omic analysis of YP and YPT at physiologically relevant temperatures was performed to gain insights into how an acute and highly lethal bacterial pathogen, YP, differs from its less virulent progenitor, YPT. This analysis revealed higher gene and protein expression levels of conserved major virulence factors in YP relative to YPT, including the Yop virulon and the pH6 antigen. This suggests that adaptation in the regulatory architecture, in addition to the presence of unique genetic material, may contribute to the increased pathogenecity of YP relative to YPT. Additionally, global transcriptome and proteome responses of YP and YPT revealed conserved post-transcriptional control of metabolism and the translational machinery including the modulation of glutamate levels in Yersiniae. Finally, the omics data was coupled with a computational network analysis, allowing an efficient prediction of novel Yersinia virulence factors based on gene and protein expression patterns.

Identifying low pH active and lactate-utilizing taxa within oral microbiome communities from healthy children using stable isotope probing techniques.

BACKGROUND: Many human microbial infectious diseases including dental caries are polymicrobial in nature. How these complex multi-species communities evolve from a healthy to a diseased state is not well understood. Although many health- or disease-associated oral bacteria have been characterized in vitro, their physiology within the complex oral microbiome is difficult to determine with current approaches. In addition, about half of these species remain uncultivated to date with little known besides their 16S rRNA sequence. Lacking culture-based physiological analyses, the functional roles of uncultivated species will remain enigmatic despite their apparent disease correlation. To start addressing these knowledge gaps, we applied a combination of Magnetic Resonance Spectroscopy (MRS) with RNA and DNA based Stable Isotope Probing (SIP) to oral plaque communities from healthy children for in vitro temporal monitoring of metabolites and identification of metabolically active and inactive bacterial species. METHODOLOGY/PRINCIPAL FINDINGS: Supragingival plaque samples from caries-free children incubated with (13)C-substrates under imposed healthy (buffered, pH 7) and diseased states (pH 5.5 and pH 4.5) produced lactate as the dominant organic acid from glucose metabolism. Rapid lactate utilization upon glucose depletion was observed under pH 7 conditions. SIP analyses revealed a number of genera containing cultured and uncultivated taxa with metabolic capabilities at pH 5.5. The diversity of active species decreased significantly at pH 4.5 and was dominated by Lactobacillus and Propionibacterium species, both of which have been previously found within carious lesions from children. CONCLUSIONS/SIGNIFICANCE: Our approach allowed for identification of species that metabolize carbohydrates under different pH conditions and supports the importance of Lactobacilli and Propionibacterium in the development of childhood caries. Identification of species within healthy subjects that are active at low pH can lead to a better understanding of oral caries onset and generate appropriate targets for preventative measures in the early stages.

An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92.

BACKGROUND: Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. RESULTS: Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. CONCLUSIONS: Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.

A Bayesian integration model of high-throughput proteomics and metabolomics data for improved early detection of microbial infections.

High-throughput (HTP) technologies offer the capability to evaluate the genome, proteome, and metabolome of an organism at a global scale. This opens up new opportunities to define complex signatures of disease that involve signals from multiple types of biomolecules. However, integrating these data types is difficult due to the heterogeneity of the data. We present a Bayesian approach to integration that uses posterior probabilities to assign class memberships to samples using individual and multiple data sources; these probabilities are based on lower-level likelihood functions derived from standard statistical learning algorithms. We demonstrate this approach on microbial infections of mice, where the bronchial alveolar lavage fluid was analyzed by three HTP technologies, two proteomic and one metabolomic. We demonstrate that integration of the three datasets improves classification accuracy to approximately 89% from the best individual dataset at approximately 83%. In addition, we present a new visualization tool called Visual Integration for Bayesian Evaluation (VIBE) that allows the user to observe classification accuracies at the class level and evaluate classification accuracies on any subset of available data types based on the posterior probability models defined for the individual and integrated data.

Solution-state NMR investigation of DNA binding interactions in Escherichia coli formamidopyrimidine-DNA glycosylase (Fpg): a dynamic description of the DNA/protein interface.

Formamidopyrimidine-DNA glycosylase (Fpg) is a base excision repair (BER) protein that removes oxidative DNA lesions. Recent crystal structures of Fpg bound to DNA revealed residues involved in damage recognition and enzyme catalysis, but failed to shed light on the dynamic nature of the processes. To examine the structural and dynamic changes that occur in solution when Fpg binds DNA, NMR spectroscopy was used to study Escherichia coli Fpg free in solution and bound to a double-stranded DNA oligomer containing 1,3-propanediol (13-PD), a non-hydrolyzable abasic-site analogue. Only 209 out of a possible 251 (83%) free-precession 15N/1H HSQC cross peaks were observed and 180 of these were assignable, indicating that approximately 30% of the residues undergo intermediate motion on the NMR timescale, broadening the resonances beyond detection or making them intractable in backbone assignment experiments. The majority of these affected residues were in the polypeptide linker region and the interface between the N- and C-terminal domains. DNA titration experiments revealed line broadening and chemical shift perturbations for backbone amides nearby and distant from the DNA binding surface, but failed to quench the intermediate timescale motion observed for free Fpg, including those residues directly involved in DNA binding, notwithstanding a nanomolar dissociation constant for 13-PD binding. Indeed, after binding to 13-PD, at least approximately 40% of the Fpg residues undergo intermediate timescale motion even though all other residues exhibit tight DNA binding characteristic of slow exchange. CPMG-HSQC experiments revealed millisecond to microsecond motion for the backbone amides of D91 and H92 that were quenched upon binding 13-PD. In free Fpg, heteronuclear 1H-15N NOE experiments detected picosecond timescale backbone motion in the alphaF-beta9 loop, the region primarily responsible for chemically discriminating 8-oxoguanine (8-oxoG) over normal guanine, that was quenched after binding 13-PD. Collectively, these observations reveal that, in solution, Fpg is a very dynamic molecule even after binding damaged DNA. Such motion, especially at the DNA binding surface, may be key to its processive search for DNA damage and its catalytic functions once it recognizes damaged DNA.

Compensating bends in a 16-base-pair DNA oligomer containing a T(3)A(3) segment: A NMR study of global DNA curvature.

In-phase ligated DNA containing T(n)A(n) segments fail to exhibit the retarded polyacrylamide gel electrophoresis (PAGE) migration observed for in-phase ligated A(n)T(n) segments, a behavior thought to be correlated with macroscopic DNA curvature. The lack of macroscopic curvature in ligated T(n)A(n) segments is thought to be due to cancellation of bending in regions flanking the TpA steps. To address this issue, solution-state NMR, including residual dipolar coupling (RDC) restraints, was used to determine a high-resolution structure of [d(CGAGGTTTAAACCTCG)2], a DNA oligomer containing a T3A3 tract. The overall magnitude and direction of bending, including the regions flanking the central TpA step, was measured using a radius of curvature, Rc, analysis. The Rc for the overall molecule indicated a small magnitude of global bending (Rc = 138 +/- 23 nm) towards the major groove, whereas the Rc for the two halves (72 +/- 33 nm and 69 +/- 14 nm) indicated greater localized bending into the minor groove. The direction of bending in the regions flanking the TpA step is in partial opposition (109 degrees), contributing to cancellation of bending. The cancellation of bending did not correlate with a pattern of roll values at the TpA step, or at the 5' and 3' junctions, of the T3A3 segment, suggesting a simple junction/roll model is insufficient to predict cancellation of DNA bending in all T(n)A(n) junction sequence contexts. Importantly, Rc analysis of structures refined without RDC restraints lacked the precision and accuracy needed to reliably measure bending.

Crystallization and preliminary crystallographic analysis of an Enterococcus faecalis repressor protein, CylR2, involved in regulating cytolysin production through quorum-sensing.

CylR2 is one of two regulatory proteins associated with the quorum-sensing-dependent synthesis of cytolysin in the common pathogen Enterococcus faecalis. The protein was expressed with a C-terminal six-histidine tag and purified to homogeneity with a cobalt-affinity column followed by size-exclusion chromatography. Both native and SeMet proteins were produced and crystallized. Complete X-ray diffraction data sets were collected from a native crystal, which diffracted to 2.3 angstroms resolution, and a SeMet crystal, which diffracted to 2.1 angstroms. The crystals were tetragonal, belonging to space group P4(1) or P4(3), with unit-cell parameters a = b = 66.2, c = 40.9 angstroms, alpha = beta = gamma = 90 degrees. Based on the calculated Matthews coefficient of 2.6 angstroms3 Da(-1) as well as analysis of anomalous difference Patterson maps, the asymmetric unit most likely contains two molecules of CylR2.

Force field dependence of NMR-Based, restrained molecular dynamics DNA structure calculations including an analysis of the influence of residual dipolar coupling restraints.

Restrained molecular dynamics is widely used to calculate DNA structures from NMR data. Here, results of an in silico experiment show that the force field can be significant compared to the NMR restraints in driving the final structures to converge. Specifically, we observed that i) the influence of the force field leads to artificially tight convergence within final families of structures and ii) the precision and character of resulting structures depend on the choice of force field used in the calculations. A canonical B-DNA model was used as a target structure. Distances, dihedral angles, and simulated residual dipolar couplings were measured in the target structure and used as restraints. X-PLOR and Discover, which use force fields developed for CHARMM and AMBER programs, respectively, were tested and found to produce different final structures despite the use of identical distance and dihedral restraints. Incorporation of residual dipolar coupling restraints in X-PLOR improves convergence with the target structure and between families of structures indicating that the force field dependence can potentially be overcome if residual dipolar coupling restraints are employed.