Jessica E. Prenni

Portrait of a pathogen: the Mycobacterium tuberculosis proteome in vivo.

Background Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a facultative intracellular pathogen that can persist within the host. The bacteria are thought to be in a state of reduced replication and metabolism as part of the chronic lung infection. Many in vitro studies have dissected the hypothesized environment within the infected lung, defining the bacterial response to pH, starvation and hypoxia. While these experiments have afforded great insight, the picture remains incomplete. The only way to study the combined effects of these environmental factors and the mycobacterial response is to study the bacterial response in vivo. Methodology/Principal Findings We used the guinea pig model of tuberculosis to examine the bacterial proteome during the early and chronic stages of disease. Lungs were harvested thirty and ninety days after aerosol challenge with Mtb, and analyzed by liquid chromatography-mass spectrometry. To date, in vivo proteomics of the tubercle bacillus has not been described and this work has generated the first large-scale shotgun proteomic data set, comprising over 500 unique protein identifications. Cell wall and cell wall processes, and intermediary metabolism and respiration were the two major functional classes of proteins represented in the infected lung. These classes of proteins displayed the greatest heterogeneity indicating important biological processes for establishment of a productive bacterial infection and its persistence. Proteins necessary for adaptation throughout infection, such as nitrate/nitrite reduction were found at both time points. The PE-PPE protein class, while not well characterized, represented the third most abundant category and showed the most consistent expression during the infection. Conclusions/Significance Cumulatively, the results of this work may provide the basis for rational drug design – identifying numerous Mtb proteins, from essential kinases to products involved in metal regulation and cell wall remodeling, all present throughout the course of infection.

Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease.

Analyses of circulating metabolites in large prospective epidemiological studies could lead to improved prediction and better biological understanding of coronary heart disease (CHD). We performed a mass spectrometry-based non-targeted metabolomics study for association with incident CHD events in 1,028 individuals (131 events; 10 y. median follow-up) with validation in 1,670 individuals (282 events; 3.9 y. median follow-up). Four metabolites were replicated and independent of main cardiovascular risk factors [lysophosphatidylcholine 18∶1 (hazard ratio [HR] per standard deviation [SD] increment = 0.77, P-value<0.001), lysophosphatidylcholine 18∶2 (HR = 0.81, P-value<0.001), monoglyceride 18∶2 (MG 18∶2; HR = 1.18, P-value = 0.011) and sphingomyelin 28∶1 (HR = 0.85, P-value = 0.015)]. Together they contributed to moderate improvements in discrimination and re-classification in addition to traditional risk factors (C-statistic: 0.76 vs. 0.75; NRI: 9.2%). MG 18∶2 was associated with CHD independently of triglycerides. Lysophosphatidylcholines were negatively associated with body mass index, C-reactive protein and with less evidence of subclinical cardiovascular disease in additional 970 participants; a reverse pattern was observed for MG 18∶2. MG 18∶2 showed an enrichment (P-value = 0.002) of significant associations with CHD-associated SNPs (P-value = 1.2×10−7 for association with rs964184 in the ZNF259/APOA5 region) and a weak, but positive causal effect (odds ratio = 1.05 per SD increment in MG 18∶2, P-value = 0.05) on CHD, as suggested by Mendelian randomization analysis. In conclusion, we identified four lipid-related metabolites with evidence for clinical utility, as well as a causal role in CHD development.

The Identification and Location of Succinyl Residues and the Characterization of the Interior Arabinan Region Allow for a Model of the Complete Primary Structure of Mycobacterium tuberculosis Mycolyl Arabinogalactan

The complex cell wall of Mycobacterium tuberculosis is the hallmark of acid fast bacteria and is responsible for much of its physiological characteristics. Hence, much effort has been made to determine its primary structure. Such studies have been hampered by its extreme complexity. Also, its insolubility leads to difficulties determining the presence or absence of base labile groups. We have used an endogenous arabinase to solubilize the arabinan region of the cell wall and have shown using mass spectrometry and NMR that succinyl esters are present on O2 of the inner-branched 1,3,5-α-d-arabinofuranosyl residues. In addition, an inner arabinan region of 14 linear α-1,5 arabinofuranosyl residues has been identified. These and earlier results now allow the presentation of a model of the entire primary structure of the mycobacterial mycolyl arabinogalactan highlighted by three arabinan chains of 31 residues each.

Rice Bran Fermented with Saccharomyces boulardii Generates Novel Metabolite Profiles with Bioactivity

Emerging evidence supporting chronic disease fighting properties of rice bran has advanced the development of stabilized rice bran for human use as a functional food and dietary supplement. A global and targeted metabolomic investigation of stabilized rice bran fermented with Saccharomyces boulardii was performed in three rice varieties. Metabolites from S. boulardii-fermented rice bran were detected by gas chromatography−mass spectrometry (GC−MS) and assessed for bioactivity compared to nonfermented rice bran in normal and malignant lymphocytes. Global metabolite profiling revealed significant differences in the metabolome that led to discovery of candidate compounds modulated by S. boulardii fermentation. Fermented rice bran extracts from three rice varieties reduced growth of human B lymphomas compared to each variety’s nonfermented control and revealed that fermentation differentially altered bioactive compounds. These data support that integration of global and targeted metabolite analysis can be utilized for assessing health properties of rice bran phytochemicals that are enhanced by yeast fermentation and that differ across rice varieties.

Linker histone H1.0 interacts with an extensive network of proteins found in the nucleolus

The H1 linker histones are abundant chromatin-associated DNA-binding proteins. Recent evidence suggests that linker histones also may function through protein–protein interactions. To gain a better understanding of the scope of linker histone involvement in protein–protein interactions, we used a proteomics approach to identify H1-binding proteins in human nuclear extracts. Full-length H1.0 and H1.0 lacking its C-terminal domain (CTD) were used for protein pull-downs. A total of 107 candidate H1.0 binding proteins were identified by LC-MS/MS. About one-third of the H1.0-dependent interactions were mediated by the CTD, and two-thirds by the N-terminal domain-globular domain fragment. Many of the proteins pulled down by H1.0 were core splicing factors. Another group of H1-binding proteins functions in rRNA biogenesis. H1.0 also pulled down numerous ribosomal proteins and proteins involved in cellular transport. Strikingly, nearly all of the H1.0-binding proteins are found in the nucleolus. Quantitative biophysical studies with recombinant proteins confirmed that H1.0 directly binds to FACT and the splicing factors SF2/ASF and U2AF65. Our results demonstrate that H1.0 interacts with an extensive network of proteins that function in RNA metabolism in the nucleolus, and suggest that a new paradigm for linker histone action is in order.

Activator-dependent p300 Acetylation of Chromatin in Vitro ENHANCEMENT OF TRANSCRIPTION BY DISRUPTION OF REPRESSIVE NUCLEOSOME-NUCLEOSOME INTERACTIONS

Condensation of chromatin into higher order structures is mediated by intra- and interfiber nucleosome-nucleosome interactions. Our goals in this study were to determine the impact specific activator-dependent histone acetylation had on chromatin condensation and to ascertain whether acetylation-induced changes in chromatin condensation were related to changes in RNA polymerase II (RNAPII) activity. To accomplish this, an in vitro model system was constructed in which the purified transcriptional activators, Tax and phosphorylated CREB (cAMP-response element-binding protein), recruited the p300 histone acetyltransferase to nucleosomal templates containing the human T-cell leukemia virus type-1 promoter sequences. We find that activator-dependent p300 histone acetylation disrupted both inter- and intrafiber nucleosome-nucleosome interactions and simultaneously led to enhanced RNAPII transcription from the decondensed model chromatin. p300 histone acetyltransferase activity had two distinct components: non-targeted, ubiquitous activity in the absence of activators and activator-dependent activity targeted primarily to promoter-proximal nucleosomes. Mass spectrometry identified several unique p300 acetylation sites on nucleosomal histone H3 (H3K9, H3K27, H3K36, and H3K37). Collectively, our data have important implications for understanding both the mechanism of RNAPII transcriptional regulation by chromatin and the molecular determinants of higher order chromatin structure.

RAMClust: a novel feature clustering method enables spectral-matching-based annotation for metabolomics data.

Metabolomic data are frequently acquired using chromatographically coupled mass spectrometry (MS) platforms. For such datasets, the first step in data analysis relies on feature detection, where a feature is defined by a mass and retention time. While a feature typically is derived from a single compound, a spectrum of mass signals is more a more-accurate representation of the mass spectrometric signal for a given metabolite. Here, we report a novel feature grouping method that operates in an unsupervised manner to group signals from MS data into spectra without relying on predictability of the in-source phenomenon. We additionally address a fundamental bottleneck in metabolomics, annotation of MS level signals, by incorporating indiscriminant MS/MS (idMS/MS) data implicitly: feature detection is performed on both MS and idMS/MS data, and feature-feature relationships are determined simultaneously from the MS and idMS/MS data. This approach facilitates identification of metabolites using in-source MS and/or idMS/MS spectra from a single experiment, reduces quantitative analytical variation compared to single-feature measures, and decreases false positive annotations of unpredictable phenomenon as novel compounds. This tool is released as a freely available R package, called RAMClustR, and is sufficiently versatile to group features from any chromatographic-spectrometric platform or feature-finding software.

Upregulation of the Phthiocerol Dimycocerosate Biosynthetic Pathway by Rifampin-Resistant, rpoB Mutant Mycobacterium tuberculosis

Multidrug-resistant tuberculosis has emerged as a major threat to tuberculosis control. Phylogenetically related rifampin-resistant actinomycetes with mutations mapping to clinically dominant Mycobacterium tuberculosis mutations in the rpoB gene show upregulation of gene networks encoding secondary metabolites. We compared the expressed proteomes and metabolomes of two fully drug-susceptible clinical strains of M. tuberculosis (wild type) to those of their respective rifampin-resistant, rpoB mutant progeny strains with confirmed rifampin monoresistance following antitubercular therapy. Each of these strains was also used to infect gamma interferon- and lipopolysaccharide-activated murine J774A.1 macrophages to analyze transcriptional responses in a physiologically relevant model. Both rpoB mutants showed significant upregulation of the polyketide synthase genes ppsA-ppsE and drrA, which constitute an operon encoding multifunctional enzymes involved in the biosynthesis of phthiocerol dimycocerosate and other lipids in M. tuberculosis, but also of various secondary metabolites in related organisms, including antibiotics, such as erythromycin and rifamycins. ppsA (Rv2931), ppsB (Rv2932), and ppsC (Rv2933) were also found to be upregulated more than 10-fold in the Beijing rpoB mutant strain relative to its wild-type parent strain during infection of activated murine macrophages. In addition, metabolomics identified precursors of phthiocerol dimycocerosate, but not the intact molecule itself, in greater abundance in both rpoB mutant isolates. These data suggest that rpoB mutation in M. tuberculosis may trigger compensatory transcriptional changes in secondary metabolism genes analogous to those observed in related actinobacteria. These findings may assist in developing novel methods to diagnose and treat drug-resistant M. tuberculosis infections.

Descriptive proteomic analysis shows protein variability between closely related clinical isolates of Mycobacterium tuberculosis

The use of isobaric tags such as iTRAQ allows the relative and absolute quantification of hundreds of proteins in a single experiment for up to eight different samples. More classical techniques such as 2‐DE can offer a complimentary approach for the analysis of complex protein samples. In this study, the proteomes of secreted and cytosolic proteins of genetically closely related strains of Mycobacterium tuberculosis were analyzed. Analysis of 2‐D gels afforded 28 spots with variations in protein abundance between strains. These were identified by MS/MS. Meanwhile, a rigorous statistical analysis of iTRAQ data allowed the identification and quantification of 101 and 137 proteins in the secreted and cytosolic fractions, respectively. Interestingly, several differences in protein levels were observed between the closely related strains BE, C28 and H6. Seven proteins related to cell wall and cell processes were more abundant in BE, while enzymes related to metabolic pathways (GltA2, SucC, Gnd1, Eno) presented lower levels in the BE strain. Proteins involved in iron and sulfur acquisition (BfrB, ViuB, TB15.3 and SseC2) were more abundant in C28 and H6. In general, iTRAQ afforded rapid identification of fine differences between protein levels such as those presented between closely related strains. This provides a platform from which the relevance of these differences can be assessed further using complimentary proteomic and biological modeling methods.

Assigning precursor–product ion relationships in indiscriminant MS/MS data from non-targeted metabolite profiling studies

Tandem mass spectrometry using precursor ion selection (MS/MS) is an invaluable tool for structural elucidation of small molecules. In non-targeted metabolite profiling studies, instrument duty cycle limitations and experimental costs have driven efforts towards alternate approaches. Recently, researchers have begun to explore methods for collecting indiscriminant MS/MS (idMS/MS) data in which the fragmentation process does not involve precursor ion isolation. While this approach has many advantages, importantly speed, sensitivity and coverage, confident assignment of precursor–product ion relationships is challenging, which has inhibited broad adoption of the technique. Here, we present an approach that uses open source software to improve the assignment of precursor–product relationships in idMS/MS data by appending a dataset-wide correlational analysis to existing tools. The utility of the approach was demonstrated using a dataset of standard compounds spiked into a malt-barley background, as well as unspiked human serum. The workflow was able to recreate idMS/MS spectra which are highly similar to standard MS/MS spectra of authentic standards, even in the presence of a complex matrix background. The application of this approach has the potential to generate high quality idMS/MS spectra for each detectable molecular feature, which will streamline the identification process for non-targeted metabolite profiling studies.