A novel liquid chromatography-tandem mass spectrometry method was validated for identification and quantification of diazepam, flunitrazepam and metabolites in reinforced clostridial medium (RCM), a complex matrix used to provide the nutrients required for bacterial growth. The method was designed for subsequent use in the investigation of gastrointestinal bacteria as a potential source of postmortem alteration of drugs of abuse and respective metabolite concentrations. A literature review yielded no experimental means or model for the extraction and analysis of samples from RCM or similar bacterial medium. Development and validation of a new experimental method were therefore critical. In future work, this method could be adapted and extended to similar organic compounds of interest. The calibration curves extended from 0.100 to 500 ng/mL. Analyte recoveries ranged from 95 to 119% and matrix effects from 97 to 119%. Bias was ?±17.6%, within-run precision ?12.2%, and between-run precision ?11.7% across all concentration levels. The limits of detection and quantitation ranged from 0.100 to 1 ng/mL. Dilution integrity was maintained for 1:2 and 1:5 dilutions. Analytes were stable through two freeze-thaw cycles and processed samples for 48 h. Method robustness was evaluated by changes in buffer composition and column temperature as well as samples prepared by an alternate analyst.
Parkinson's disease (PD) is a multifactorial disorder with a complex etiology including genetic risk factors, environmental exposures, and aging. While energy failure and oxidative stress have largely been associated with the loss of dopaminergic cells in PD and the toxicity induced by mitochondrial/environmental toxins, very little is known regarding the alterations in energy metabolism associated with mitochondrial dysfunction and their causative role in cell death progression. In this study, we investigated the alterations in the energy/redox-metabolome in dopaminergic cells exposed to environmental/mitochondrial toxins (paraquat, rotenone, 1-methyl-4-phenylpyridinium [MPP+], and 6-hydroxydopamine [6-OHDA]) in order to identify common and/or different mechanisms of toxicity. A combined metabolomics approach using nuclear magnetic resonance (NMR) and direct-infusion electrospray ionization mass spectrometry (DI-ESI-MS) was used to identify unique metabolic profile changes in response to these neurotoxins. Paraquat exposure induced the most profound alterations in the pentose phosphate pathway (PPP) metabolome. 13C-glucose flux analysis corroborated that PPP metabolites such as glucose-6-phosphate, fructose-6-phosphate, glucono-1,5-lactone, and erythrose-4-phosphate were increased by paraquat treatment, which was paralleled by inhibition of glycolysis and the TCA cycle. Proteomic analysis also found an increase in the expression of glucose-6-phosphate dehydrogenase (G6PD), which supplies reducing equivalents by regenerating nicotinamide adenine dinucleotide phosphate (NADPH) levels. Overexpression of G6PD selectively increased paraquat toxicity, while its inhibition with 6-aminonicotinamide inhibited paraquat-induced oxidative stress and cell death. These results suggest that paraquat "hijacks" the PPP to increase NADPH reducing equivalents and stimulate paraquat redox cycling, oxidative stress, and cell death. Our study clearly demonstrates that alterations in energy metabolism, which are specific for distinct mitochondiral/environmental toxins, are not bystanders to energy failure but also contribute significant to cell death progression.
Depression has been associated with vascular dysfunction, which may be of particular relevance in pregnancy. Asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), and L-arginine play a critical role in vascular function. The objective of this study was to investigate differences in ADMA, SDMA, and L-arginine among pregnant women with major depression compared with pregnant women without depression.
The "omics" era began with transcriptomics and this progressed into proteomics. While useful, these approaches provide only circumstantial information about carbon flow, metabolic status, redox poise, etc. To more directly address these metabolic concerns, researchers have turned to the emerging field of metabolomics. In our laboratories, we frequently use NMR metabolomics to acquire a snapshot of bacterial metabolomes during stressful or transition events. Irrespective of the "omics" method of choice, the experimental outcome depends on the proper cultivation and preparation of bacterial samples. In addition, the integration of these large datasets requires that these cultivation conditions be clearly defined.
Families of distantly related proteins typically have very low sequence identity, which hinders evolutionary analysis and functional annotation. Slowly evolving features of proteins, such as an active site, are therefore valuable for annotating putative and distantly related proteins. To date, a complete evolutionary analysis of the functional relationship of an entire enzyme family based on active-site structural similarities has not yet been undertaken. Pyridoxal-5'-phosphate (PLP) dependent enzymes are primordial enzymes that diversified in the last universal ancestor. Using the comparison of protein active site structures (CPASS) software and database, we show that the active site structures of PLP-dependent enzymes can be used to infer evolutionary relationships based on functional similarity. The enzymes successfully clustered together based on substrate specificity, function, and three-dimensional-fold. This study demonstrates the value of using active site structures for functional evolutionary analysis and the effectiveness of CPASS.
The purpose of this study was to examine circulating maternal follistatin-like 3 (FSTL-3) by gestational age and obesity in pregnancy and preeclampsia. FSTL-3 was quantified in maternal plasma collected in each trimester from prepregnancy body mass index-determined groups: 15 lean and 24 obese controls and 20 obese women who developed preeclampsia. Repeated measures mixed models and logistic regression were conducted (P ? .05). FSTL-3 was not related to maternal adiposity. FSTL-3 changed across pregnancy in lean controls and obese preeclampsia but not in obese controls. FSTL-3 was higher in preeclampsia in the second trimester compared to lean controls and in the third trimester compared to both control groups. Elevated FSTL-3 at mid-gestation was associated with an increased odds of preeclampsia (odds ratio 3.15; 95% confidence interval 1.19-8.36; P = .02). Elevated FSTL-3 concentrations were attributable to preeclampsia and were associated with increased likelihood of later developing preeclampsia, suggesting further study as a biomarker prior to clinically evident disease.
Staphylococcus aureus is a prominent nosocomial pathogen and a major cause of biomaterial-associated infections. The success of S. aureus as a pathogen is due in part to its ability to adapt to stressful environments. As an example, the transition from residing in the nares to residing in the blood or deeper tissues is accompanied by changes in the availability of nutrients and elements such as oxygen and iron. As such, nutrients, oxygen, and iron are important determinants of virulence factor synthesis in S. aureus. In addition to influencing virulence factor synthesis, oxygen and iron are critical cofactors in enzymatic and electron transfer reactions; thus, a change in iron or oxygen availability alters the bacterial metabolome. Changes in metabolism create intracellular signals that alter the activity of metabolite-responsive regulators such as CodY, RpiRc, and CcpA. To assess the extent of metabolomic changes associated with oxygen and iron limitation, S. aureus cells were cultivated in iron-limited medium and/or with decreasing aeration, and the metabolomes were examined by nuclear magnetic resonance (NMR) spectroscopy. As expected, oxygen and iron limitation dramatically decreased tricarboxylic acid (TCA) cycle activity, creating a metabolic block and significantly altering the metabolome. These changes were most prominent during post-exponential-phase growth, when TCA cycle activity was maximal. Importantly, many of the effects of iron limitation were obscured by aeration limitation. Aeration limitation not only obscured the metabolic effects of iron limitation but also overrode the transcription of iron-regulated genes. Finally, in contrast to previous speculation, we confirmed that acidification of the culture medium occurs independent of the availability of iron.
Eleven fatty acid analogues incorporating four-membered carbocycles (cyclobutenes, cyclobutanes, cyclobutanones, and cyclobutanols) were investigated for the ability to inhibit the growth of Mycobacterium smegmatis (Msm) and Mycobacterium tuberculosis (Mtb). A number of the analogues displayed inhibitory activity against both mycobacterial species in minimal media. Several of the molecules displayed potent levels of inhibition against Mtb, with MIC values equal to or below those observed with the anti-tuberculosis drugs D-cycloserine and isoniazid. In contrast, two of the analogues that display the greatest activity against Mtb failed to inhibit E.?coli growth under either set of conditions. Thus, the active molecules identified herein may provide the basis for the development of anti-mycobacterial agents against Mtb.
Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set.
The pharmaceutical industry has significantly contributed to improving human health. Drugs have been attributed to both increasing life expectancy and decreasing health care costs. Unfortunately, there has been a recent decline in the creativity and productivity of the pharmaceutical industry. This is a complex issue with many contributing factors resulting from the numerous mergers, increase in out-sourcing, and the heavy dependency on high-throughput screening (HTS). While a simple solution to such a complex problem is unrealistic and highly unlikely, the inclusion of metabolomics as a routine component of the drug discovery process may provide some solutions to these problems. Specifically, as the binding affinity of a chemical lead is evolved during the iterative structure-based drug design process, metabolomics can provide feedback on the selectivity and the in vivo mechanism of action. Similarly, metabolomics can be used to evaluate and validate HTS leads. In effect, metabolomics can be used to eliminate compounds with potential efficacy and side effect problems while prioritizing well-behaved leads with druglike characteristics.
Pancreatic cancer has a dismal 5 year survival rate of 5.5% that has not been improved over the past 25 years despite an enormous amount of effort. Thus, there is an urgent need to identify truly novel yet druggable protein targets for drug discovery. The human protein DnaJ homologue subfamily A member 1 (DNAJA1) was previously shown to be downregulated 5-fold in pancreatic cancer cells and has been targeted as a biomarker for pancreatic cancer, but little is known about the specific biological function for DNAJA1 or the other members of the DnaJ family encoded in the human genome. Our results suggest the overexpression of DNAJA1 suppresses the stress response capabilities of the oncogenic transcription factor, c-Jun, and results in the diminution of cell survival. DNAJA1 likely activates a DnaK protein by forming a complex that suppresses the JNK pathway, the hyperphosphorylation of c-Jun, and the anti-apoptosis state found in pancreatic cancer cells. A high-quality nuclear magnetic resonance solution structure of the J-domain of DNAJA1 combined with a bioinformatics analysis and a ligand affinity screen identifies a potential DnaK binding site, which is also predicted to overlap with an inhibitory binding site, suggesting DNAJA1 activity is highly regulated.
Nuclear magnetic resonance (NMR) spectroscopy has proven invaluable in the diverse field of chemometrics due to its ability to deliver information-rich spectral datasets of complex mixtures for analysis by techniques such as principal component analysis (PCA). However, NMR datasets present a unique challenge during preprocessing due to differences in phase offsets between individual spectra, thus complicating the correction of random dilution factors that may also occur. We show that simultaneously correcting phase and dilution errors in NMR datasets representative of metabolomics data yields improved cluster quality in PCA scores space, even with significant initial phase errors in the data.
Research examining the source of excess soluble fms-like tyrosine kinase 1 (sFLT1) in preeclampsia has focused on the placenta. The potential contribution of the releasable store of sFLT1 in the systemic vasculature is unknown.
The bacterial genus Corynebacteria contains several pathogenic species that cause diseases such as diphtheria in humans and "cheesy gland" in goats and sheep. Thus, identifying new therapeutic targets to treat Corynebacteria infections is both medically and economically important. CG2496, a functionally uncharacterized protein from Corynebacterium glutamicum, was evaluated using an NMR ligand-affinity screen. A total of 11 compounds from a library of 460 biologically active compounds were shown to selectively bind CG2496 in a highly conserved region of the protein. The best binder was identified to be methiothepin (KD =54 ± 19 µM), an FDA-approved serotonin receptor antagonist. Methiothepin was also shown to inhibit the growth of C.?glutamicum, but not bacteria that lack CG2496 homologs. Our results suggest that CG2496 is a novel therapeutic target and methiothepin is a potential lead compound or structural scaffold for developing new antibiotics specifically targeting Corynebacteria.
Aberrant energy metabolism is a hallmark of cancer. To fulfill the increased energy requirements, tumor cells secrete cytokines/factors inducing muscle and fat degradation in cancer patients, a condition known as cancer cachexia. It accounts for nearly 20% of all cancer-related deaths. However, the mechanistic basis of cancer cachexia and therapies targeting cancer cachexia thus far remain elusive. A ketogenic diet, a high-fat and low-carbohydrate diet that elevates circulating levels of ketone bodies (i.e., acetoacetate, ?-hydroxybutyrate, and acetone), serves as an alternative energy source. It has also been proposed that a ketogenic diet leads to systemic metabolic changes. Keeping in view the significant role of metabolic alterations in cancer, we hypothesized that a ketogenic diet may diminish glycolytic flux in tumor cells to alleviate cachexia syndrome and, hence, may provide an efficient therapeutic strategy.
d-Cycloserine is an effective second line antibiotic used as a last resort to treat multi (MDR)- and extensively (XDR) drug resistant strains of Mycobacterium tuberculosis . d-Cycloserine interferes with the formation of peptidoglycan biosynthesis by competitive inhibition of alanine racemase (Alr) and d-alanine-d-alanine ligase (Ddl). Although the two enzymes are known to be inhibited, the in vivo lethal target is still unknown. Our NMR metabolomics work has revealed that Ddl is the primary target of DCS, as cell growth is inhibited when the production of d-alanyl-d-alanine is halted. It is shown that inhibition of Alr may contribute indirectly by lowering the levels of d-alanine, thus allowing DCS to outcompete d-alanine for Ddl binding. The NMR data also supports the possibility of a transamination reaction to produce d-alanine from pyruvate and glutamate, thereby bypassing Alr inhibition. Furthermore, the inhibition of peptidoglycan synthesis results in a cascading effect on cellular metabolism as there is a shift toward the catabolic routes to compensate for accumulation of peptidoglycan precursors.
The tricarboxylic acid cycle (TCA cycle) is a central metabolic pathway that provides energy, reducing potential, and biosynthetic intermediates. In Staphylococcus aureus, TCA cycle activity is controlled by several regulators (e.g. CcpA, CodY, and RpiRc) in response to the availability of sugars, amino acids, and environmental stress. Developing a bioinformatic search for additional carbon catabolite-responsive regulators in S. aureus, we identified a LysR-type regulator, catabolite control protein E (CcpE), with homology to the Bacillus subtilis CcpC regulator. Inactivation of ccpE in S. aureus strain Newman revealed that CcpE is a positive transcriptional effector of the first two enzymes of the TCA cycle, aconitase (citB) and to a lesser extent citrate synthase (citZ). Consistent with the transcriptional data, aconitase activity dramatically decreased in the ccpE mutant relative to the wild-type strain. The effect of ccpE inactivation on citB transcription and the lesser effect on citZ transcription were also reflected in electrophoretic mobility shift assays where CcpE bound to the citB promoter but not the citZ promoter. Metabolomic studies showed that inactivation of ccpE resulted in increased intracellular concentrations of acetate, citrate, lactate, and alanine, consistent with a redirection of carbon away from the TCA cycle. Taken together, our data suggest that CcpE is a major direct positive regulator of the TCA cycle gene citB.
Genetic testing for personalizing pharmacotherapy is bound to become an important part of clinical routine. To address associated issues with data management and quality, we are creating a semantic knowledge base for clinical pharmacogenetics. The knowledge base is made up of three components: an expressive ontology formalized in the Web Ontology Language (OWL 2 DL), a Resource Description Framework (RDF) model for capturing detailed results of manual annotation of pharmacogenomic information in drug product labels, and an RDF conversion of relevant biomedical datasets. Our work goes beyond the state of the art in that it makes both automated reasoning as well as query answering as simple as possible, and the reasoning capabilities go beyond the capabilities of previously described ontologies.
During growth under conditions of glucose and oxygen excess, Staphylococcus aureus predominantly accumulates acetate in the culture medium, suggesting that the phosphotransacetylase-acetate kinase (Pta-AckA) pathway plays a crucial role in bacterial fitness. Previous studies demonstrated that these conditions also induce the S. aureus CidR regulon involved in the control of cell death. Interestingly, the CidR regulon is comprised of only two operons, both encoding pyruvate catabolic enzymes, suggesting an intimate relationship between pyruvate metabolism and cell death. To examine this relationship, we introduced ackA and pta mutations in S. aureus and tested their effects on bacterial growth, carbon and energy metabolism, cid expression, and cell death. Inactivation of the Pta-AckA pathway showed a drastic inhibitory effect on growth and caused accumulation of dead cells in both pta and ackA mutants. Surprisingly, inactivation of the Pta-AckA pathway did not lead to a decrease in the energy status of bacteria, as the intracellular concentrations of ATP, NAD(+), and NADH were higher in the mutants. However, inactivation of this pathway increased the rate of glucose consumption, led to a metabolic block at the pyruvate node, and enhanced carbon flux through both glycolysis and the tricarboxylic acid (TCA) cycle. Intriguingly, disruption of the Pta-AckA pathway also induced the CidR regulon, suggesting that activation of alternative pyruvate catabolic pathways could be an important survival strategy for the mutants. Collectively, the results of this study demonstrate the indispensable role of the Pta-AckA pathway in S. aureus for maintaining energy and metabolic homeostasis during overflow metabolism.
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, noninvasive, inexpensive, and efficient diagnostic tool for various human diseases. Nevertheless, urinary metabolites have not been extensively explored as a source of biomarkers for MS. 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.
Chronic mountain sickness (CMS) is considered to be a loss of ventilatory acclimatization to high altitude (>2500m) resulting in marked arterial hypoxemia and polycythemia. This case-control study explores the possibility that sleep-disordered breathing (SDB) and associated oxidative stress contribute to the etiology of CMS. Nocturnal respiratory and [Formula: see text] patterns were measured using standard polysomnography techniques and compared between male high-altitude residents (aged 18-25) with preclinical CMS (excessive erythrocytosis (EE), n=20) and controls (n=19). Measures of oxidative stress and antioxidant status included isoprostanes (8-iso-PGF2alpha), superoxide dismutase and ascorbic acid. EE cases had a greater apnea-hypopnea index, a higher frequency of apneas (central and obstructive) and hypopneas during REM sleep, and lower nocturnal [Formula: see text] compared to controls. 8-iso-PGF2alpha was greater in EE than controls, negatively associated with nocturnal [Formula: see text] , and positively associated with hemoglobin concentration. Mild sleep-disordered breathing and oxidative stress are evident in preclinical CMS, suggesting that the resolution of nocturnal hypoxemia or antioxidant treatment may prevent disease progression.
Major depressive disorder (MDD) during pregnancy increases the risk of adverse maternal and infant outcomes. Maternal nutritional status may be a modifiable risk factor for antenatal depression. We evaluated the association between patterns in mid-pregnancy nutritional biomarkers and MDD.
New strategies are needed to circumvent increasing outbreaks of resistant strains of pathogens and to expand the dwindling supply of effective antimicrobials. A common impediment to drug development is the lack of an easy approach to determine the in vivo mechanism of action and efficacy of novel drug leads. Toward this end, we describe an unbiased approach to predict in vivo mechanisms of action from NMR metabolomics data. Mycobacterium smegmatis, a non-pathogenic model organism for Mycobacterium tuberculosis, was treated with 12 known drugs and 3 chemical leads identified from a cell-based assay. NMR analysis of drug-induced changes to the M. smegmatis metabolome resulted in distinct clustering patterns correlating with in vivo drug activity. The clustering of novel chemical leads relative to known drugs provides a mean to identify a protein target or predict in vivo activity.
We previously hypothesized that Staphylococcus epidermidis senses a diverse set of environmental and nutritional factors associated with biofilm formation through a modulation in the activity of the tricarboxylic acid (TCA) cycle. Herein, we report our further investigation of the impact of additional environmental stress factors on TCA cycle activity and provide a detailed description of our NMR methodology. S. epidermidis wild-type strain 1457 was treated with stressors that are associated with biofilm formation, a sublethal dose of tetracycline, 5% NaCl, 2% glucose, and autoinducer-2 (AI-2). As controls and to integrate our current data with our previous study, 4% ethanol stress and iron-limitation were also used. Consistent with our prior observations, the effect of many environmental stress factors on the S. epidermidis metabolome was essentially identical to the effect of TCA cycle inactivation in the aconitase mutant strain 1457-acnA::tetM. A detailed quantitative analysis of metabolite concentration changes using 2D (1)H-(13)C HSQC and (1)H-(1)H TOCSY spectra identified a network of 37 metabolites uniformly affected by the stressors and TCA cycle inactivation. We postulate that the TCA cycle acts as the central pathway in a metabolic signaling network.
In subjects with previous preeclampsia, differences in cardiovascular and/or blood biochemical parameters are present in the nonpregnant state, and a simultaneous assessment of multiple derived indices better differentiates between women with or without previous preeclampsia. We examined 18 previous preeclamptic and 50 previous uncomplicated pregnancies, ?16 months postpartum. Cardiovascular assessment included the following: (1) systemic hemodynamics and mechanics (Doppler echocardiography, tonometry, and oscillometric sphygmomanometry); (2) endothelial function (plethysmography); (3) left ventricular properties (echocardiography); and (4) blood biochemical analyses. Compared to women with previous uncomplicated pregnancies, previous preeclamptics had higher mean (80±1 versus 86±3 mm Hg; P=0.04) and diastolic (64±1 versus 68±2 mm Hg; P=0.04) pressures and total vascular resistance (1562±37 versus 1784±114 dyne · s/cm(5); P=0.03). Systolic blood pressure, arterial compliance, and left ventricular properties were not different. Although heart-to-femoral pulse wave velocity was not different, heart-to-brachial pulse wave velocity tended to be faster in previous preeclamptics (374±8 versus 404±20 cm/s; P=0.06). Stress-induced increase in forearm blood flow was less in previous preeclamptics (245%±21% versus 136%±22%; P=0.01), indicating impaired endothelial function. No significant differences were observed in markers of endothelial activation, dyslipidemia, or oxidative stress; previous preeclamptics tended to have higher glucose level (58.7±1.9 versus 95±5.2 mg/dL; P=0.06). Logistic regression analysis indicated that a simultaneous evaluation of multiple derived indices better discriminated between the 2 groups. The differences in the previous preeclamptic group are in directions known to be associated with greater cardiovascular disease risk later in life.
The Chemistry Department at the University of Nebraska - Lincoln (UNL) is located in Hamilton Hall on the main campus of UNL in Lincoln, NE, USA. This department houses the primary graduate and research program in chemistry in the state of Nebraska. This program includes the traditional fields of analytical chemistry, biochemistry, inorganic chemistry, organic chemistry and physical chemistry. However, this program also contains a great deal of multidisciplinary research in fields that range from bioanalytical and biophysical chemistry to nanomaterials, energy research, catalysis and computational chemistry. Current research in bioanalytical and biophysical chemistry at UNL includes work with separation methods such as HPLC and CE, as well as with techniques such as MS and LC-MS, NMR spectroscopy, electrochemical biosensors, scanning probe microscopy and laser spectroscopy. This article will discuss several of these areas, with an emphasis being placed on research in bioanalytical separations, binding assays and related fields.
Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery.
The incidence of obesity is increasing at an alarming rate. There is compelling evidence that obesity increases the risk of preeclampsia about 3-fold, and in developed countries is the leading attributable risk for the disorder. In this presentation we explore this relationship and propose targets for future studies guided by the much more extensively studied relationship of obesity to cardiovascular disease. We further address the hypothesis that asymmetric dimethyl arginine (ADMA), an endogenous inhibitor of nitric oxide synthase, may be one convergence point for the mechanism by which obesity increases the risk of preeclampsia. We conclude with consideration of the clinical implications of this information.
Large-scale nuclear magnetic resonance (NMR) tube cleaning is currently a bottleneck in high-throughput NMR ligand affinity screens. Expensive alternatives include discarding the NMR tubes after a single use (~US $2-$8/tube), using commercial NMR tube cleaners (~$15,000), and abandoning NMR tubes for flow probe technology (~$75,000). Instead, we describe a relatively inexpensive (~$400) and easily constructed apparatus that can clean 180 NMR tubes per hour while using a modest amount of solvent. The application of this apparatus significantly shortens the time to recycle NMR tubes while avoiding cross-contamination and tube damage.
We report that proteins with the same function bind the same set of small molecules from a standardized chemical library. This observation led to a quantifiable and rapidly adaptable method for protein functional analysis using experimentally derived ligand binding profiles. Ligand binding is measured using a high-throughput NMR ligand affinity screen with a structurally diverse chemical library. The method was demonstrated using a set of 19 proteins with a range of functions. A statistically significant similarity in ligand binding profiles was only observed between the two functionally identical albumins and between the five functionally similar amylases. This new approach is independent of sequence, structure, or evolutionary information and, therefore, extends our ability to analyze and functionally annotate novel genes.
The interaction between DnaG primase and DnaB helicase is essential for stimulating primer synthesis during bacterial DNA replication. The interaction occurs between the N-terminal domain of helicase and the C-terminal domain of primase. Here we present the (1)H, (13)C, and (15)N backbone and side-chain resonance assignments for the C-terminal helicase interaction domain of Staphylococcus aureus primase.
Outside pregnancy, acute caffeine consumption is associated with insulin resistance. We investigated if during pregnancy plasma concentrations of caffeine and its metabolite, paraxanthine, were associated with insulin resistance. Caffeine, paraxanthine, glucose, and insulin were measured and insulin resistance estimated by homeostasis model assessment (HOMA) in banked samples from 251 fasting subjects at mean gestational age of 20.3?±?2.0 weeks. Analysis of covariance and adjusted logistic regression were performed. Most (96.4%) women had caffeine and/or paraxanthine present. Caffeine concentrations in the upper two quartiles (>266 ng/mL) were associated with threefold higher odds of having higher insulin resistance estimated by log HOMA ?75th percentile (third quartile odds ratio [OR], 3.02; 95% confidence interval [CI]: 1.21 to 7.54 and fourth quartile OR, 2.95; 95% CI: 1.19 to 7.31). Paraxanthine concentrations in the upper quartile (>392 ng/mL) were also associated with threefold higher odds of having higher insulin resistance (OR, 3.04; 95% CI: 1.28 to 7.25). Adjusted mean HOMA in the first caffeine-to-paraxanthine ratio quartile was 1.5?±?2.2 versus 1.3?±?2.3 in the fourth quartile ( P?0.01). Both high caffeine and paraxanthine concentrations were associated with insulin resistance, but slow versus fast metabolism did not make an important difference.
A recent analysis of protein sequences deposited in the NCBI RefSeq database indicates that ~8.5 million protein sequences are encoded in prokaryotic and eukaryotic genomes, where ~30% are explicitly annotated as "hypothetical" or "uncharacterized" protein. Our Comparison of Protein Active-Site Structures (CPASS v.2) database and software compares the sequence and structural characteristics of experimentally determined ligand binding sites to infer a functional relationship in the absence of global sequence or structure similarity. CPASS is an important component of our Functional Annotation Screening Technology by NMR (FAST-NMR) protocol and has been successfully applied to aid the annotation of a number of proteins of unknown function.
The association of elevated serum uric acid with the development of hypertension is established outside of pregnancy. We investigated whether first trimester uric acid was associated with the development of the following: gestational hypertension or pre eclampsia, these outcomes stratified by presence of hyperuricemia at delivery since this denotes more severe disease, preterm birth, or small for gestational age (SGA).
Protein sequence space is vast compared to protein fold space. This raises important questions about how structures adapt to evolutionary changes in protein sequences. A growing trend is to regard protein fold space as a continuum rather than a series of discrete structures. From this perspective, homologous protein structures within the same functional classification should reveal a constant rate of structural drift relative to sequence changes. The clusters of orthologous groups (COG) classification system was used to annotate homologous bacterial protein structures in the Protein Data Bank (PDB). The structures and sequences of proteins within each COG were compared against each other to establish their relatedness. As expected, the analysis demonstrates a sharp structural divergence between the bacterial phyla Firmicutes and Proteobacteria. Additionally, each COG had a distinct sequence/structure relationship, indicating that different evolutionary pressures affect the degree of structural divergence. However, our analysis also shows the relative drift rate between sequence identity and structure divergence remains constant.
Staphylococcus epidermidis is a skin-resident bacterium and a major cause of biomaterial-associated infections. The transition from residing on the skin to residing on an implanted biomaterial is accompanied by regulatory changes that facilitate bacterial survival in the new environment. These regulatory changes are dependent upon the ability of bacteria to "sense" environmental changes. In S. epidermidis, disparate environmental signals can affect synthesis of the biofilm matrix polysaccharide intercellular adhesin (PIA). Previously, we demonstrated that PIA biosynthesis is regulated by tricarboxylic acid (TCA) cycle activity. The observations that very different environmental signals result in a common phenotype (i.e. increased PIA synthesis) and that TCA cycle activity regulates PIA biosynthesis led us to hypothesize that S. epidermidis is "sensing" disparate environmental signals through the modulation of TCA cycle activity. In this study, we used NMR metabolomics to demonstrate that divergent environmental signals are transduced into common metabolomic changes that are "sensed" by metabolite-responsive regulators, such as CcpA, to affect PIA biosynthesis. These data clarify one mechanism by which very different environmental signals cause common phenotypic changes. In addition, due to the frequency of the TCA cycle in diverse genera of bacteria and the intrinsic properties of TCA cycle enzymes, it is likely the TCA cycle acts as a signal transduction pathway in many bacteria.
The solution structure of the Bacillus subtilis protein YndB has been solved using NMR to investigate proposed biological functions. The YndB structure exhibits the helix-grip fold, which consists of a ?-sheet with two small and one long ?-helix, forming a hydrophobic cavity that preferentially binds lipid-like molecules. Sequence and structure comparisons with proteins from eukaryotes, prokaryotes, and archaea suggest that YndB is very similar to the eukaryote protein Aha1, which binds to the middle domain of Hsp90 and induces ATPase activity. On the basis of these similarities, YndB has been classified as a member of the activator of Hsp90 ATPase homolog 1-like protein (AHSA1) family with a function that appears to be related to stress response. An in silico screen of a compound library of ? 18,500 lipids was used to identify classes of lipids that preferentially bind YndB. The in silico screen identified, in order of affinity, the chalcone/hydroxychalcone, flavanone, and flavone/flavonol classes of lipids, which was further verified by 2D (1) H-(15) N HSQC NMR titration experiments with trans-chalcone, flavanone, flavone, and flavonol. All of these compounds are typically found in plants as precursors to various flavonoid antibiotics and signaling molecules. The sum of the data suggests an involvement of YndB with the stress response of B. subtilis to chalcone-like flavonoids released by plants due to a pathogen infection. The observed binding of chalcone-like molecules by YndB is likely related to the symbiotic relationship between B. subtilis and plants.
The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are approximately 1100 molecular biology databases dispersed throughout the Internet. To assist in the functional, structural and evolutionary analysis of the abundant number of novel proteins continually identified from whole-genome sequencing, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database. Our database is designed to be versatile and expandable and will not confine analysis to a pre-existing set of data relationships. A fundamental component of this approach is the development of an intuitive query system that incorporates a variety of similarity functions capable of generating data relationships not conceived during the creation of the database. The utility of PROFESS is demonstrated by the analysis of the structural drift of homologous proteins and the identification of potential pancreatic cancer therapeutic targets based on the observation of protein-protein interaction networks. Database URL: http://cse.unl.edu/~profess/
Changes in maternal concentrations of the anti-angiogenic factors, soluble fms-like tyrosine kinase 1 (sFlt1) and soluble endoglin (sEng), and the pro-angiogenic placental growth factor (PlGF) precede the development of preeclampsia in healthy women. The risk of preeclampsia is reduced in women who smoke during pregnancy. The objective of this study was to investigate whether smoking affects concentrations of angiogenic factors (sFlt1, PlGF, and sEng) in women at high risk for developing preeclampsia.
Differences in circulating concentrations of antiangiogenic factors sFlt1 and soluble endoglin (sEng) and the pro-angiogenic growth factor PlGF are reported to precede the onset of preeclampsia weeks to months in low-risk pregnant women. The objective of this study was to investigate whether similar changes can be detected in pregnant women at high-risk to develop the syndrome.
Circulating endothelial progenitor cells (EPCs) may contribute to vascular endothelial cell homeostasis, and low levels of these cells are predictive of cardiovascular disease. We hypothesized that circulating EPCs increase in number during uncomplicated pregnancy but are reduced in women with preeclampsia. Peripheral blood was obtained from pregnant women and from nulligravidas in cross-sectional design. Cells expressing CD34 or CD133, in combination with vascular endothelial growth factor receptor-2 (VEGFR-2), were enumerated by flow cytometry. Both CD34(+)VEGFR-2(+) (doubly positive) and CD133(+)VEGFR-2( +) cells were significantly increased during the second and third trimesters of uncomplicated pregnancy compared to the first trimester. First trimester and nulligravida groups did not differ. Endothelial progenitor cells, quantified by flow cytometry or by circulating angiogenic cell (CAC) culture assay, were significantly reduced in women with preeclampsia compared to third trimester controls. Circulating EPCs appear to increase during normal pregnancy, and comparatively reduced numbers of these cells exist during preeclampsia.
The construction of a consensus tree to summarize the information of a given set of phylogenetic trees is now routinely a part of many studies in systematic biology. One popular method is the majority-rule consensus tree. In this paper we introduce and characterize a new consensus method that refines the majority-rule tree by adding certain compatible clusters satisfying a simple criterion.
Research published in 1972 and 1993 has detailed the demographics, diagnoses, and diagnostic test utilization of adult patients presenting with nontraumatic abdominal pain to the emergency department (ED) at the University of Virginia Hospital. This is an update of those studies, designed to examine the present state of diagnosis and management of abdominal pain, as well as to look at trends during the 35-year span of the investigations.
The Connecticut Department of Public Safety laboratory recently addressed a legal challenge to a hospital alcohol dehydrogenase (ADH)-based serum ethanol determination based on the suggestion of interference by lactate dehydrogenase (LDH)-catalyzed oxidation of lactate. Both ADH- and LDH-oxidations require NAD(+) (present in excess in the assay). NADH produced by LDH-catalyzed lactate oxidation in the assay is interpreted as derived from ethanol. Hepatic trauma was suggested as the basis for elevated levels of lactate and LDH. Clinical laboratory results were evaluated, specifically serum hepatic enzymes, ions, and anion gap. Aspartate aminotransferase (ASAT) and alanine aminotransferase (ALAT) were 229 and 144 U/L, respectively (approximately 8x and 4x reference range midpoint values). Na(+), K(+), Cl(-), and CO(2) levels were 143, 3.0, 112, and 20 meq/L, respectively, yielding an anion gap of 8 meq/L (ref. range 8-15). Serum lactate contributes to "unmeasured anions"; hence, the anion gap was inconsistent with a significant lactate elevation. Based on the slight elevation of ASAT and ALAT, LDH levels were estimated to be elevated to no more than 10-fold. Calculation of the amount of LDH and ADH present in the ethanol assay suggest an ADH/LDH ratio of 200:1. Hence, contribution by lactate oxidation to the serum ethanol concentration in this case would have been negligible.
Large amounts of data from high-throughput metabolomic experiments are commonly visualized using a principal component analysis (PCA) two-dimensional 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 principal component (PC) scores space. A qualitative visual inspection of the clustering pattern in PCA scores plots is a common protocol. This article 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 data set. 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.
BACKGROUND: Drug discovery is a complex and unpredictable endeavor with a high failure rate. Current trends in the pharmaceutical industry have exasperated these challenges and are contributing to the dramatic decline in productivity observed over the last decade. The industrialization of science by forcing the drug discovery process to adhere to assembly-line protocols is imposing unnecessary restrictions, such as short project time-lines. Recent advances in nuclear magnetic resonance are responding to these self-imposed limitations and are providing opportunities to increase the success rate of drug discovery. OBJECTIVE/METHOD: A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented. These include fast NMR data collection protocols and high-throughput protein structure determination, rapid protein-ligand co-structure determination, lead discovery using fragment-based NMR affinity screens, NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FAST-NMR. CONCLUSION: NMR is a critical component of the drug discovery process, where the versatility of the technique enables it to continually expand and evolve its role. NMR is expected to maintain this growth over the next decade with advancements in automation, speed of structure calculation, in-cell imaging techniques, and the expansion of NMR amenable targets.
Vascular endothelial growth factor (VEGF) is a key factor in angiogenesis and is important to carcinogenesis. Previous studies relating circulating levels of VEGF to breast cancer have been limited by small numbers of participants and lack of adjustment for confounders. We studied the association between serum VEGF and breast cancer in an unmatched case-control study of 407 pre- and postmenopausal women (n = 203 cases, n = 204 controls). Logistic regression was used to model the breast cancer risk as a function of natural log transformed VEGF levels adjusted for age, Gail score, education, physical activity, history of breastfeeding, serum testosterone, and hormone therapy (HT) use. The majority of the population was postmenopausal (67.6%) and the average age was 56 years; age and menopausal status were similar among cases and controls. Geometric mean VEGF levels were non-significantly higher in cases (321.4 pg/ml) than controls (291.4 pg/ml; p = 0.21). In a multivariable model, the odds of breast cancer was 37% higher for women with VEGF levels > or =314.2 pg/ml compared to those with levels below 314.2 pg/ml, albeit not significantly (p = 0.16). There was no interaction between VEGF and menopausal status (p = 0.52). In this case-control study, VEGF was not significantly associated with breast cancer risk in pre- and postmenopausal women.
NMR is an integral component of the drug discovery process with applications in lead discovery, validation, and optimization. NMR is routinely used for fragment-based ligand affinity screens, high-resolution protein structure determination, and rapid protein-ligand co-structure modeling. Because of this inherent versatility, NMR is currently making significant contributions in the burgeoning area of metabolomics, where NMR is successfully being used to identify biomarkers for various diseases, to analyze drug toxicity and to determine a drugs in vivo efficacy and selectivity. This review describes advances in NMR-based metabolomics and discusses some recent applications.
Functional similarity is challenging to identify when global sequence and structure similarity is low. Active-sites or functionally relevant regions are evolutionarily more stable relative to the remainder of a protein structure and provide an alternative means to identify potential functional similarity between proteins. We recently developed the FAST-NMR methodology to discover biochemical functions or functional hypotheses of proteins of unknown function by experimentally identifying ligand binding sites. FAST-NMR utilizes our CPASS software and database to assign a function based on a similarity in the structure and sequence of ligand binding sites between proteins of known and unknown function.
Proline utilization A (PutA) is a membrane-associated multifunctional enzyme that catalyzes the oxidation of proline to glutamate in a two-step process. In certain, gram-negative bacteria such as Pseudomonas putida, PutA also acts as an auto repressor in the cytoplasm, when an insufficient concentration of proline is available. Here, the N-terminal residues 1-45 of PutA from P. putida (PpPutA45) are shown to be responsible for DNA binding and dimerization. The solution structure of PpPutA45 was determined using NMR methods, where the protein is shown to be a symmetrical homodimer (12 kDa) consisting of two ribbon-helix-helix (RHH) structures. DNA sequence recognition by PpPutA45 was determined using DNA gel mobility shift assays and NMR chemical shift perturbations (CSPs). PpPutA45 was shown to bind a 14 base-pair DNA oligomer (5-GCGGTTGCACCTTT-3). A model of the PpPutA45-DNA oligomer complex was generated using Haddock 2.1. The antiparallel beta-sheet that results from PpPutA45 dimerization serves as the DNA recognition binding site by inserting into the DNA major groove. The dimeric core of four alpha-helices provides a structural scaffold for the beta-sheet from which residues Thr5, Gly7, and Lys9 make sequence-specific contacts with the DNA. The structural model implies flexibility of Lys9 which can make hydrogen bond contacts with either guanine or thymine. The high sequence and structure conservation of the PutA RHH domain suggest interdomain interactions play an important role in the evolution of the protein.
To determine whether the cellular inflammatory marker of activated macrophages and monocytes, neopterin (NEO), and the acute-phase inflammatory markers sialic acid (SA) and C-reactive protein (CRP) are elevated in pregnancy and further elevated in the pregnancy syndrome preeclampsia.
A multi-step NMR based screening assay is described for identifying and evaluating chemical leads for their ability to bind a target protein. The multi-step NMR assay provides structure-related information while being an integral part of a structure based drug discovery and design program. The fundamental principle of the multi-step NMR assay is to combine distinct 1D and 2D NMR techniques, in such a manner, that the inherent strengths and weakness associated with each technique is complementary to each other in the screen. By taking advantage of the combined strengths of 1D and 2D NMR experiments, it is possible to minimize protein requirements and experiment time and differentiate between non-specific and stoichiometric binders while being able to verify ligand binding, determine a semi-quantitative dissociation constant, identify the ligand binding site and rapidly determine a protein-ligand co-structure. Furthermore, the quality and physical behavior of the ligand is readily evaluated to determine its appropriateness as a chemical lead. The utility of the multi-step NMR assay is demonstrated with the use of PrgI from Salmonella typhimurium and human serum albumin (HSA) as target proteins.
The steroidogenic acute regulatory-related lipid transfer (START) domain is found in both eukaryotes and prokaryotes, with putative functions including signal transduction, transcriptional regulation, GTPase activation and thioester hydrolysis. Here we report the near complete (1)H, (15)N and (13)C backbone and side chain NMR resonance assignments for the Bacillus subtilis START domain protein yndB.
Pseudomonas aeruginosa is the prototypical biofilm-forming gram-negative opportunistic human pathogen. P. aeruginosa is causatively associated with nosocomial infections and with cystic fibrosis. Antibiotic resistance in some strains adds to the inherent difficulties that result from biofilm formation when treating P. aeruginosa infections. Transcriptional profiling studies suggest widespread changes in the proteome during quorum sensing and biofilm development. Many of the proteins found to be upregulated during these processes are poorly characterized from a functional standpoint. Here, we report the solution NMR structure of PA1324, a protein of unknown function identified in these studies, and provide a putative biological functional assignment based on the observed prealbumin-like fold and FAST-NMR ligand screening studies. PA1324 is postulated to be involved in the binding and transport of sugars or polysaccharides associated with the peptidoglycan matrix during biofilm formation.
This Perspective, arising from a workshop held in July 2008 in Buffalo NY, provides an overview of the role NMR has played in the United States Protein Structure Initiative (PSI), and a vision of how NMR will contribute to the forthcoming PSI-Biology program. NMR has contributed in key ways to structure production by the PSI, and new methods have been developed which are impacting the broader protein NMR community.
Staphylococcus aureus is a leading cause of community-associated and nosocomial infections. Imperative to the success of S. aureus is the ability to adapt and utilize nutrients that are readily available. Genomic sequencing suggests that S. aureus has the genes required for synthesis of all twenty amino acids. However, in vitro experimentation demonstrates that staphylococci have multiple amino acid auxotrophies, including arginine. Although S. aureus possesses the highly conserved anabolic pathway that synthesizes arginine via glutamate, we demonstrate here that inactivation of ccpA facilitates the synthesis of arginine via the urea cycle utilizing proline as a substrate. Mutations within putA, rocD, arcB1, argG and argH abolished the ability of S. aureus JE2 ccpA::tetL to grow in the absence of arginine, whereas an interruption in argJBCF, arcB2, or proC had no effect. Furthermore, nuclear magnetic resonance demonstrated that JE2 ccpA::ermB produced (13)C(5) labeled arginine when grown with (13)C(5) proline. Taken together, these data support the conclusion that S. aureus synthesizes arginine from proline during growth on secondary carbon sources. Furthermore, although highly conserved in all sequenced S. aureus genomes, the arginine anabolic pathway (ArgJBCDFGH) is not functional under in vitro growth conditions. Finally, a mutation in argH attenuated virulence in a mouse kidney abscess model in comparison to wild type JE2 demonstrating the importance of arginine biosynthesis in vivo via the urea cycle. However, mutations in argB, argF, and putA did not attenuate virulence suggesting both the glutamate and proline pathways are active and they, or their pathway intermediates, can complement each other in vivo.
Increasing body mass index (BMI) has been associated with less fractional exhaled nitric oxide (Fe(NO)). This may be explained by an increase in the concentration of asymmetric dimethyl arginine (ADMA) relative to L-arginine, which can lead to greater nitric oxide synthase uncoupling.
Metabolic fingerprinting studies rely on interpretations drawn from low-dimensional representations of spectral data generated by methods of multivariate analysis such as principal components analysis and projection to latent structures discriminant analysis. The growth of metabolic fingerprinting and chemometric analyses involving these low-dimensional scores plots necessitates the use of quantitative statistical measures to describe significant differences between experimental groups. Our updated version of the PCAtoTree software provides methods to reliably visualize and quantify separations in scores plots through dendrograms employing both nonparametric and parametric hypothesis testing to assess node significance, as well as scores plots identifying 95% confidence ellipsoids for all experimental groups.
Mycobacterium tuberculosis is a major cause of mortality in human beings on a global scale. The emergence of both multi- (MDR) and extensively-(XDR) drug-resistant strains threatens to derail current disease control efforts. Thus, there is an urgent need to develop drugs and vaccines that are more effective than those currently available. The genome of M. tuberculosis has been known for more than 10 years, yet there are important gaps in our knowledge of gene function and essentiality. Many studies have since used gene expression analysis at both the transcriptomic and proteomic levels to determine the effects of drugs, oxidants, and growth conditions on the global patterns of gene expression. Ultimately, the final response of these changes is reflected in the metabolic composition of the bacterium including a few thousand small molecular weight chemicals. Comparing the metabolic profiles of wild type and mutant strains, either untreated or treated with a particular drug, can effectively allow target identification and may lead to the development of novel inhibitors with anti-tubercular activity. Likewise, the effects of two or more conditions on the metabolome can also be assessed. Nuclear magnetic resonance (NMR) is a powerful technology that is used to identify and quantify metabolic intermediates. In this protocol, procedures for the preparation of M. tuberculosis cell extracts for NMR metabolomic analysis are described. Cell cultures are grown under appropriate conditions and required Biosafety Level 3 containment, harvested, and subjected to mechanical lysis while maintaining cold temperatures to maximize preservation of metabolites. Cell lysates are recovered, filtered sterilized, and stored at ultra-low temperatures. Aliquots from these cell extracts are plated on Middlebrook 7H9 agar for colony-forming units to verify absence of viable cells. Upon two months of incubation at 37 °C, if no viable colonies are observed, samples are removed from the containment facility for downstream processing. Extracts are lyophilized, resuspended in deuterated buffer and injected in the NMR instrument, capturing spectroscopic data that is then subjected to statistical analysis. The procedures described can be applied for both one-dimensional (1D) H NMR and two-dimensional (2D) H-(13)C NMR analyses. This methodology provides more reliable small molecular weight metabolite identification and more reliable and sensitive quantitative analyses of cell extract metabolic compositions than chromatographic methods. Variations of the procedure described following the cell lysis step can also be adapted for parallel proteomic analysis.
An n = ?* interaction between neighboring carbonyl groups has been postulated to stabilize protein structures. Such an interaction would affect the (13)C chemical shielding of the carbonyl groups, whose paramagnetic component is dominated by n = ?* and ? = ?* excitations. Model compound calculations indicate that both the interaction energetics and the chemical shielding of the carbonyl group are instead dominated by a classical dipole-dipole interaction. A set of high-resolution protein structures with associated carbonyl (13)C chemical shift assignments verifies this correlation and provides no evidence for an inter-carbonyl n = ?* interaction.
Aberrant glucose metabolism is one of the hallmarks of cancer that facilitates cancer cell survival and proliferation. Here, we demonstrate that MUC1, a large, type I transmembrane protein that is overexpressed in several carcinomas including pancreatic adenocarcinoma, modulates cancer cell metabolism to facilitate growth properties of cancer cells. MUC1 occupies the promoter elements of multiple genes directly involved in glucose metabolism and regulates their expression. Furthermore, MUC1 expression enhances glycolytic activity in pancreatic cancer cells. We also demonstrate that MUC1 expression enhances in vivo glucose uptake and expression of genes involved in glucose uptake and metabolism in orthotopic implantation models of pancreatic cancer. The MUC1 cytoplasmic tail is known to activate multiple signaling pathways through its interactions with several transcription factors/coregulators at the promoter elements of various genes. Our results indicate that MUC1 acts as a modulator of the hypoxic response in pancreatic cancer cells by regulating the expression/stability and activity of hypoxia-inducible factor-1? (HIF-1?). MUC1 physically interacts with HIF-1? and p300 and stabilizes the former at the protein level. By using a ChIP assay, we demonstrate that MUC1 facilitates recruitment of HIF-1? and p300 on glycolytic gene promoters in a hypoxia-dependent manner. Also, by metabolomic studies, we demonstrate that MUC1 regulates multiple metabolite intermediates in the glucose and amino acid metabolic pathways. Thus, our studies indicate that MUC1 acts as a master regulator of the metabolic program and facilitates metabolic alterations in the hypoxic environments that help tumor cells survive and proliferate under such conditions.
Infectious diseases can be difficult to cure, especially if the pathogen forms a biofilm. After decades of extensive research into the morphology, physiology and genomics of biofilm formation, attention has recently been directed toward the analysis of the cellular metabolome in order to understand the transformation of a planktonic cell to a biofilm. Metabolomics can play an invaluable role in enhancing our understanding of the underlying biological processes related to the structure, formation and antibiotic resistance of biofilms. A systematic view of metabolic pathways or processes responsible for regulating this social structure of microorganisms may provide critical insights into biofilm-related drug resistance and lead to novel treatments. This review will discuss the development of NMR-based metabolomics as a technology to study medically relevant biofilms. Recent advancements from case studies reviewed in this manuscript have shown the potential of metabolomics to shed light on numerous biological problems related to biofilms.
Detecting a small molecular-weight compound by electrospray ionization mass spectrometry (ESI-MS) requires the compound to obtain a charge. Factors such as gas-phase proton affinities and analyte surface activity are correlated with a positive ESI-MS response, but unfortunately it is extremely challenging to predict from a chemical structure alone if a compound is likely to yield an observable molecular-ion peak in an ESI-MS spectrum. Thus, the design of a chemical library for an ESI-MS ligand-affinity screen is particularly daunting. Only 56.9% of the compounds from our FAST-NMR functional library  were detectable by ESI-MS. An analysis of ~1,600 molecular descriptors did not identify any correlation with a positive ESI-MS response that cannot be attributed to a skewed population distribution. Unfortunately, our results suggest that molecular descriptors are not a valuable approach for designing a chemical library for an MS-based ligand affinity screen.
Preeclampsia is a heterogeneous syndrome affecting 3% to 5% of all pregnancies. An imbalance of the antiangiogenic and proangiogenic factors, soluble receptor fms-like tyrosine kinase 1 and placental growth factor (PGF), is thought to contribute to the pathophysiology of preeclampsia. Maternal plasma PGF and soluble receptor fms-like tyrosine kinase 1 were quantified by specific immunoassays in cross-sectional samples from 130 preeclamptic subjects and 342 normotensive controls at delivery and longitudinally in samples from 50 women who developed preeclampsia and 250 normotensive controls. Among women who developed preeclampsia, 46% (n=23) evidenced a pattern of consistently low maternal PGF across pregnancy below the lower 95% CI of controls from 15 weeks gestation to term. In contrast, the remaining 54% (n=27) of women who developed preeclampsia had maternal PGF concentrations similar to or above (n=7) those of normotensive controls. Subjects with low PGF across pregnancy who developed preeclampsia evidenced significantly higher blood pressure in early pregnancy (P<0.05) and, after diagnosis, earlier gestational age at delivery (P<0.05) and more preterm birth (P<0.05) compared with preeclamptic patients with high PGF. A significant subset of women who develop preeclampsia show evidence of consistently low PGF across pregnancy. Low PGF with preeclampsia was associated with preterm delivery compared with preeclamptic patients with high PGF. Identifying women with consistently low plasma PGF during pregnancy may provide a greater understanding of preeclampsia pathophysiology and may provide more focused research and clinical activities.
Since antiquity, humans have used body fluids like saliva, urine and sweat for the diagnosis of diseases. The amount, color and smell of body fluids are still used in many traditional medical practices to evaluate an illness and make a diagnosis. The development and application of analytical methods for the detailed analysis of body fluids has led to the discovery of numerous disease biomarkers. Recently, mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR), and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The goal of these efforts is to identify metabolites that are uniquely correlated with a specific human disease in order to accurately diagnose and treat the malady. In this review we will discuss recent developments in sample preparation, experimental techniques, the identification and quantification of metabolites, and the chemometric tools used to search for biomarkers of human diseases using NMR.
We sought to determine whether haptoglobin (Hp) phenotype is related to preeclampsia risk, or to plasma concentrations of soluble endoglin (sEng), soluble fms-like tyrosine kinase 1 (sFlt-1), and placental growth factor (PlGF).
Understanding how each individuals genetics and physiology influences pharmaceutical response is crucial to the realization of personalized medicine and the discovery and validation of pharmacogenomic biomarkers is key to its success. However, integration of genotype and phenotype knowledge in medical information systems remains a critical challenge. The inability to easily and accurately integrate the results of biomolecular studies with patients medical records and clinical reports prevents us from realizing the full potential of pharmacogenomic knowledge for both drug development and clinical practice. Herein, we describe approaches using Semantic Web technologies, in which pharmacogenomic knowledge relevant to drug development and medical decision support is represented in such a way that it can be efficiently accessed both by software and human experts. We suggest that this approach increases the utility of data, and that such computational technologies will become an essential part of personalized medicine, alongside diagnostics and pharmaceutical products.
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