Development of an ELISA microarray assay for the sensitive and simultaneous detection of ten biodefense toxins.

Plant and microbial toxins are considered bioterrorism threat agents because of their extreme toxicity and/or ease of availability. Additionally, some of these toxins are increasingly responsible for accidental food poisonings. The current study utilized an ELISA-based protein antibody microarray for the multiplexed detection of ten biothreat toxins, botulinum neurotoxins (BoNT) A, B, C, D, E, F, ricin, shiga toxins 1 and 2 (Stx), and staphylococcus enterotoxin B (SEB), in buffer and complex biological matrices. The multiplexed assay displayed a sensitivity of 1.3 pg mL(-1) (BoNT/A, BoNT/B, SEB, Stx-1 and Stx-2), 3.3 pg mL(-1) (BoNT/C, BoNT/E, BoNT/F) and 8.2 pg mL(-1) (BoNT/D, ricin). All assays demonstrated high accuracy (75-120 percent recovery) and reproducibility (most coefficients of variation <20%). Quantification curves for the ten toxins were also evaluated in clinical samples (serum, plasma, nasal fluid, saliva, stool, and urine) and environmental samples (apple juice, milk and baby food) with overall minimal matrix effects. The multiplex assays were highly specific, with little cross-reactivity observed between the selected toxin antibodies. The results demonstrate a multiplex microarray that improves current immunoassay sensitivity for biological warfare agents in buffer, clinical, and environmental samples.

A semiautomated framework for integrating expert knowledge into disease marker identification.

BACKGROUND: The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. OBJECTIVE: To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. METHODS: The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. RESULTS: The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. CONCLUSIONS: Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.

Structural insights into the functional role of the Hcn sub-domain of the receptor-binding domain of the botulinum neurotoxin mosaic serotype C/D.

Botulinum neurotoxin (BoNT), the causative agent of the deadly neuroparalytic disease botulism, is the most poisonous protein known for humans. Produced by different strains of the anaerobic bacterium Clostridium botulinum, BoNT effects cellular intoxication via a multistep mechanism executed by the three modules of the activated protein. Endocytosis, the first step of cellular intoxication, is triggered by the ~50 kDa, heavy-chain receptor-binding domain (HCR) that is specific for a ganglioside and a protein receptor on neuronal cell surfaces. This dual receptor recognition mechanism between BoNT and the host cell's membrane is well documented and occurs via specific intermolecular interactions with the C-terminal sub-domain, Hcc, of BoNT-HCR. The N-terminal sub-domain of BoNT-HCR, Hcn, comprises ~50% of BoNT-HCR and adopts a ß-sheet jelly roll fold. While suspected in assisting cell surface recognition, no unambiguous function for the Hcn sub-domain in BoNT has been identified. To obtain insights into the potential function of the Hcn sub-domain in BoNT, the first crystal structure of a BoNT with an organic ligand bound to the Hcn sub-domain has been obtained. Here, we describe the crystal structure of BoNT/CD-HCR determined at 1.70 Å resolution with a tetraethylene glycol (PG4) moiety bound in a hydrophobic cleft between ß-strands in the ß-sheet jelly roll fold of the Hcn sub-domain. The PG4 moiety is completely engulfed in the cleft, making numerous hydrophilic (Y932, S959, W966, and D1042) and hydrophobic (S935, W977, L979, N1013, and I1066) contacts with the protein's side chain and backbone that may mimic in vivo interactions with the phospholipid membranes on neuronal cell surfaces. A sulfate ion was also observed bound to residues T1176, D1177, K1196, and R1243 in the Hcc sub-domain of BoNT/CD-HCR. In the crystal structure of a similar protein, BoNT/D-HCR, a sialic acid molecule was observed bound to the equivalent residues suggesting that residues T1176, D1177, K1196, and R1243 in BoNT/CD may play a role in ganglioside binding.

The effects of low-dose irradiation on inflammatory response proteins in a 3D reconstituted human skin tissue model.

Skin responses to moderate and high doses of ionizing radiation include the induction of DNA repair, apoptosis and stress response pathways. Additionally, numerous studies indicate that radiation exposure leads to inflammatory responses in skin cells and tissue. However, the inflammatory response of skin tissue to low-dose radiation (≤10 cGy) is poorly understood. To address this, we have utilized a reconstituted human skin tissue model (MatTek EpiDermFT™) and assessed changes in 23 cytokines, 24 and 48 h after treatment of skin with either 3 or 10 cGy low dose of radiation. Three cytokines, IFN-γ, IL-2, MIP-1α, were significantly altered in response to low-dose radiation. In contrast, seven cytokines were significantly altered in response to a high radiation dose of 200 cGy (IL-2, IL-10, IL-13, IFN-γ, MIP-1α, TNFα and VEGF) or the tumor promoter 12-O-tetradecanoylphorbol 13-acetate (G-CSF, GM-CSF, IL-1α, IL-8, MIP-1α, MIP-1ß and RANTES). Additionally, radiation induced inflammation appears to have a distinct cytokine response relative to the nonradiation induced stressor, TPA. Overall, these results indicate that there are subtle changes in the inflammatory protein levels after exposure to low-dose radiation and this response is a subset of what is seen after a high dose in a human skin tissue model.

Simultaneous and sensitive detection of six serotypes of botulinum neurotoxin using enzyme-linked immunosorbent assay-based protein antibody microarrays.

Botulinum neurotoxins (BoNTs), produced by Clostridium botulinum, are a group of seven (A-G) immunologically distinct proteins and cause the paralytic disease botulism. These toxins are the most poisonous substances known to humans and are potential bioweapon agents. Therefore, it is necessary to develop highly sensitive assays for the detection of BoNTs in both clinical and environmental samples. In the current study, we have developed an enzyme-linked immunosorbent assay (ELISA)-based protein antibody microarray for the sensitive and simultaneous detection of BoNT serotypes A, B, C, D, E, and F. With engineered high-affinity antibodies, the BoNT assays have sensitivities in buffer ranging from 1.3fM (0.2pg/ml) to 14.7fM (2.2pg/ml). Using clinical and food matrices (serum and milk), the microarray is capable of detecting BoNT serotypes A to F to similar levels as in standard buffer. Cross-reactivity between assays for individual serotype was also analyzed. These simultaneous, rapid, and sensitive assays have the potential to measure botulinum toxins in a high-throughput manner in complex clinical, food, and environmental samples.

Structure determination and functional analysis of a chromate reductase from Gluconacetobacter hansenii.

Environmental protection through biological mechanisms that aid in the reductive immobilization of toxic metals (e.g., chromate and uranyl) has been identified to involve specific NADH-dependent flavoproteins that promote cell viability. To understand the enzyme mechanisms responsible for metal reduction, the enzyme kinetics of a putative chromate reductase from Gluconacetobacter hansenii (Gh-ChrR) was measured and the crystal structure of the protein determined at 2.25 Å resolution. Gh-ChrR catalyzes the NADH-dependent reduction of chromate, ferricyanide, and uranyl anions under aerobic conditions. Kinetic measurements indicate that NADH acts as a substrate inhibitor; catalysis requires chromate binding prior to NADH association. The crystal structure of Gh-ChrR shows the protein is a homotetramer with one bound flavin mononucleotide (FMN) per subunit. A bound anion is visualized proximal to the FMN at the interface between adjacent subunits within a cationic pocket, which is positioned at an optimal distance for hydride transfer. Site-directed substitutions of residues proposed to involve in both NADH and metal anion binding (N85A or R101A) result in 90-95% reductions in enzyme efficiencies for NADH-dependent chromate reduction. In comparison site-directed substitution of a residue (S118A) participating in the coordination of FMN in the active site results in only modest (50%) reductions in catalytic efficiencies, consistent with the presence of a multitude of side chains that position the FMN in the active site. The proposed proximity relationships between metal anion binding site and enzyme cofactors is discussed in terms of rational design principles for the use of enzymes in chromate and uranyl bioremediation.

Proteomic analysis of bronchoalveolar lavage fluid proteins from mice infected with Francisella tularensis ssp. novicida.

Francisella tularensis causes the zoonosis tularemia in humans and is one of the most virulent bacterial pathogens. We utilized a global proteomic approach to characterize protein changes in bronchoalveolar lavage fluid from mice exposed to one of three organisms, F. tularensis ssp. novicida, an avirulent mutant of F. tularensis ssp. novicida (F.t. novicida-ΔmglA), and Pseudomonas aeruginosa. The composition of bronchoalveolar lavage fluid (BALF) proteins was altered following infection, including proteins involved in neutrophil activation, oxidative stress, and inflammatory responses. Components of the innate immune response were induced including the acute phase response and the complement system; however, the timing of their induction varied. F. tularensis ssp. novicida infected mice do not appear to have an effective innate immune response in the first hours of infection; however, within 24 h, they show an upregulation of innate immune response proteins. This delayed response is in contrast to P. aeruginosa infected animals which show an early innate immune response. Likewise, F.t. novicida-ΔmglA infection initiates an early innate immune response; however, this response is diminished by 24 h. Finally, this study identifies several candidate biomarkers, including Chitinase 3-like-1 (CHI3L1 or YKL-40) and peroxiredoxin 1, that are associated with F. tularensis ssp. novicida but not P. aeruginosa infection.

The receptor binding domain of botulinum neurotoxin serotype C binds phosphoinositides.

Botulinum neurotoxins (BoNTs) are the most toxic proteins known for humans and animals with an extremely low LD(50) of ∼1 ng/kg. BoNTs generally require a protein and a ganglioside on the cell membrane surface for binding, which is known as a "dual receptor" mechanism for host intoxication. Recent studies have suggested that in addition to gangliosides, other membrane lipids such as phosphoinositides may be involved in the interactions with the receptor binding domain (HCR) of BoNTs for better membrane penetration. Using two independent lipid-binding assays, we tested the interactions of BoNT/C-HCR with lipids in vitro domain. BoNT/C-HCR was found to bind negatively charged phospholipids, preferentially phosphoinositides in both assays. Interactions with phosphoinositides may facilitate tighter binding between neuronal membranes and BoNT/C.

Plasma biomarkers for detecting Hodgkin's lymphoma in HIV patients.

The lifespan of people with human immunodeficiency virus (HIV) infection has increased as a result of effective antiretroviral therapy, and the incidences of the AIDS-defining cancers, non-Hodgkin's lymphoma and Kaposi sarcoma, have declined. Even so, HIV-infected individuals are now at greater risk of other cancers, including Hodgkin's lymphoma (HL). To identify candidate biomarkers for the early detection of HL, we undertook an accurate mass and elution time tag proteomics analysis of individual plasma samples from either HIV-infected patients without HL (controls; n = 14) and from HIV-infected patient samples with HL (n = 22). This analysis identified 60 proteins that were statistically (p<0.05) altered and at least 1.5-fold different between the two groups. At least three of these proteins have previously been reported to be altered in the blood of HL patients that were not known to be HIV positive, suggesting that these markers may be broadly useful for detecting HL. Ingenuity Pathway Analysis software identified "inflammatory response" and "cancer" as the top two biological functions associated with these proteins. Overall, this study validated three plasma proteins as candidate biomarkers for detecting HL, and identified 57 novel candidate biomarkers that remain to be validated. The relationship of these novel candidate biomarkers with cancer and inflammation suggests that they are truly associated with HL and therefore may be useful for the early detection of this cancer in susceptible populations.

Comparative proteomics and pulmonary toxicity of instilled single-walled carbon nanotubes, crocidolite asbestos, and ultrafine carbon black in mice.

Reflecting their exceptional potential to advance a range of biomedical, aeronautic, and other industrial products, carbon nanotube (CNT) production and the potential for human exposure to aerosolized CNTs are increasing. CNTs have toxicologically significant structural and chemical similarities to asbestos (AB) and have repeatedly been shown to cause pulmonary inflammation, granuloma formation, and fibrosis after inhalation/instillation/aspiration exposure in rodents, a pattern of effects similar to those observed following exposure to AB. To determine the degree to which responses to single-walled CNTs (SWCNT) and AB are similar or different, the pulmonary response of C57BL/6 mice to repeated exposures to SWCNTs, crocidolite AB, and ultrafine carbon black (UFCB) were compared using high-throughput global high performance liquid chromatography fourier transform ion cyclotron resonance mass spectrometry (HPLC-FTICR-MS) proteomics, histopathology, and bronchoalveolar lavage cytokine analyses. Mice were exposed to material suspensions (40 micrograms per mouse) twice a week for 3 weeks by pharyngeal aspiration. Histologically, the incidence and severity of inflammatory and fibrotic responses were greatest in mice treated with SWCNTs. SWCNT treatment affected the greatest changes in abundance of identified lung tissue proteins. The trend in number of proteins affected (SWCNT [376] > AB [231] > UFCB [184]) followed the potency of these materials in three biochemical assays of inflammation (cytokines). SWCNT treatment uniquely affected the abundance of 109 proteins, but these proteins largely represent cellular processes affected by AB treatment as well, further evidence of broad similarity in the tissue-level response to AB and SWCNTs. Two high-sensitivity markers of inflammation, one (S100a9) observed in humans exposed to AB, were found and may be promising biomarkers of human response to SWCNT exposure.

Crystal structure of the receptor binding domain of the botulinum C-D mosaic neurotoxin reveals potential roles of lysines 1118 and 1136 in membrane interactions.

The botulinum neurotoxins (BoNTs) produced by different strains of the bacterium Clostridium botulinum are responsible for the disease botulism and include a group of immunologically distinct serotypes (A, B, E, and F) that are considered to be the most lethal natural proteins known for humans. Two BoNT serotypes, C and D, while rarely associated with human infection, are responsible for deadly botulism outbreaks afflicting animals. Also associated with animal infections is the BoNT C-D mosaic protein (BoNT/CD), a BoNT subtype that is essentially a hybrid of the BoNT/C (∼two-third) and BoNT/D (∼one-third) serotypes. While the amino acid sequence of the heavy chain receptor binding (HCR) domain of BoNT/CD (BoNT/CD-HCR) is very similar to the corresponding amino acid sequence of BoNT/D, BoNT/CD-HCR binds synaptosome membranes better than BoNT/D-HCR. To obtain structural insights for the different membrane binding properties, the crystal structure of BoNT/CD-HCR (S867-E1280) was determined at 1.56 Å resolution and compared to previously reported structures for BoNT/D-HCR. Overall, the BoNT/CD-HCR structure is similar to the two sub-domain organization observed for other BoNT HCRs: an N-terminal jellyroll barrel motif and a C-terminal ß-trefoil fold. Comparison of the structure of BoNT/CD-HCR with BoNT/D-HCR indicates that K1118 has a similar structural role as the equivalent residue, E1114, in BoNT/D-HCR, while K1136 has a structurally different role than the equivalent residue, G1132, in BoNT/D-HCR. Lysine-1118 forms a salt bridge with E1247 and may enhance membrane interactions by stabilizing the putative membrane binding loop (K1240-N1248). Lysine-1136 is observed on the surface of the protein. A sulfate ion bound to K1136 may mimic a natural interaction with the negatively changed phospholipid membrane surface. Liposome-binding experiments demonstrate that BoNT/CD-HCR binds phosphatidylethanolamine liposomes more tightly than BoNT/D-HCR.

High-level expression, purification, crystallization and preliminary X-ray crystallographic studies of the receptor-binding domain of botulinum neurotoxin serotype D.

Botulinum neurotoxins (BoNTs) are highly toxic proteins for humans and animals that are responsible for the deadly neuroparalytic disease botulism. Here, details of the expression and purification of the receptor-binding domain (HCR) of BoNT/D in Escherichia coli are presented. Using a codon-optimized cDNA, BoNT/D_HCR was expressed at a high level (150-200 mg per litre of culture) in the soluble fraction. Following a three-step purification protocol, very pure (>98%) BoNT/D_HCR was obtained. The recombinant BoNT/D_HCR was crystallized and the crystals diffracted to 1.65 Šresolution. The crystals belonged to space group P2(1)2(1)2(1), with unit-cell parameters a=60.8, b=89.7, c=93.9 Å. Preliminary crystallographic data analysis revealed the presence of one molecule in the asymmetric unit.

Combined statistical analyses of peptide intensities and peptide occurrences improves identification of significant peptides from MS-based proteomics data.

Liquid chromatography-mass spectrometry-based (LC-MS) proteomics uses peak intensities of proteolytic peptides to infer the differential abundance of peptides/proteins. However, substantial run-to-run variability in intensities and observations (presence/absence) of peptides makes data analysis quite challenging. The missing observations in LC-MS proteomics data are difficult to address with traditional imputation-based approaches because the mechanisms by which data are missing are unknown a priori. Data can be missing due to random mechanisms such as experimental error or nonrandom mechanisms such as a true biological effect. We present a statistical approach that uses a test of independence known as a G-test to test the null hypothesis of independence between the number of missing values across experimental groups. We pair the G-test results, evaluating independence of missing data (IMD) with an analysis of variance (ANOVA) that uses only means and variances computed from the observed data. Each peptide is therefore represented by two statistical confidence metrics, one for qualitative differential observation and one for quantitative differential intensity. We use three LC-MS data sets to demonstrate the robustness and sensitivity of the IMD-ANOVA approach.

Structural analysis of the receptor binding domain of botulinum neurotoxin serotype D.

Botulinum neurotoxins (BoNTs) are the most toxic proteins known. The mechanism for entry into neuronal cells for serotypes A, B, E, F, and G involves a well understood dual receptor (protein and ganglioside) process, however, the mechanism of entry for serotypes C and D remains unclear. To provide structural insights into how BoNT/D enters neuronal cells, the crystal structure of the receptor binding domain (S863-E1276) for this serotype (BoNT/D-HCR) was determined at 1.65Å resolution. While BoNT/D-HCR adopts an overall fold similar to that observed in other known BoNT HCRs, several major structural differences are present. These structural differences are located at, or near, putative receptor binding sites and may be responsible for BoNT/D host preferences. Two loops, S1195-I1204 and K1236-N1244, located on both sides of the putative protein receptor binding pocket, are displaced >10Å relative to the corresponding residues in the crystal structures of BoNT/B and G. Obvious clashes were observed in the putative protein receptor binding site when the BoNT/B protein receptor synaptotagmin II was modeled into the BoNT/D-HCR structure. Although a ganglioside binding site has never been unambiguously identified in BoNT/D-HCR, a shallow cavity in an analogous location to the other BoNT serotypes HCR domains is observed in BoNT/D-HCR that has features compatible with membrane binding. A portion of a loop near the putative receptor binding site, K1236-N1244, is hydrophobic and solvent-exposed and may directly bind membrane lipids. Liposome-binding experiments with BoNT/D-HCR demonstrate that this membrane lipid may be phosphatidylethanolamine.

Proteomic biomarkers in plasma that differentiate rapid and slow decline in lung function in adult cigarette smokers with chronic obstructive pulmonary disease (COPD).

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of morbidity and mortality in the United States and cigarette smoking is a primary determinant of the disease. COPD is characterized by chronic airflow limitation as measured by the forced expiratory volume in one second (FEV(1)). In this study, the plasma proteomes of 38 middle-aged or older adult smokers with mild to moderate COPD, with FEV(1) decline characterized as either rapid (RPD, n = 20) or slow or absent (SLW, n = 18), were interrogated using a comprehensive high-throughput proteomic approach, the accurate mass and time (AMT) tag technology. This technology is based upon a putative mass and time tag database (PMT), high-resolution LC separations and high mass accuracy measurements using FT-ICR MS with a 9.4-T magnetic field. The peptide and protein data were analyzed using three statistical approaches to address ambiguities related to the high proportion of missing data inherent to proteomic analysis. The RPD and SLW groups were differentiated by 55 peptides which mapped to 33 unique proteins. Twelve of the proteins have known roles in the complement or coagulation cascade and, despite an inability to adjust for some factors known to affect lung function decline, suggest potential mechanistic biomarkers associated with the rate of lung function decline in COPD. Whether these proteins are the cause or result of accelerated decline will require further research.

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.

Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation.

Making sound proteomic inferences using ELISA microarray assay requires both an accurate prediction of protein concentration and a credible estimate of its error. We present a method using monotonic spline statistical models (MS), penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to predict ELISA microarray protein concentrations and estimate their prediction errors. We contrast the MSMC (monotone spline Monte Carlo) method with a LNLS (logistic nonlinear least squares) method using simulated and real ELISA microarray data sets.MSMC rendered good fits in almost all tests, including those with left and/or right clipped standard curves. MS predictions were nominally more accurate; especially at the extremes of the prediction curve. MC provided credible asymmetric prediction intervals for both MS and LN fits that were superior to LNLS propagation-of-error intervals in achieving the target statistical confidence. MSMC was more reliable when automated prediction across simultaneous assays was applied routinely with minimal user guidance.

Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy.

The enormous dynamic range of human bodily fluid proteomes poses a significant challenge for current MS-based proteomics technologies as it makes it especially difficult to detect low abundance proteins in human biofluids such as blood plasma, which is an essential aspect for successful biomarker discovery efforts. Here we present a novel tandem IgY12-SuperMix immunoaffinity separation system for enhanced detection of low abundance proteins in human plasma. The tandem IgY12-SuperMix system separates approximately 60 abundant proteins from the low abundance proteins in plasma, allowing for significant enrichment of low abundance plasma proteins in the SuperMix flow-through fraction. High reproducibility of the tandem separations was observed in terms of both sample processing recovery and LC-MS/MS identification results based on spectral count data. The ability to quantitatively measure differential protein abundances following application of the tandem separations was demonstrated by spiking six non-human standard proteins at three different levels into plasma. A side-by-side comparison between the SuperMix flow-through and IgY12 flow-through samples analyzed by both one- and two-dimensional LC-MS/MS revealed a 60-80% increase in proteome coverage as a result of the SuperMix separations, suggesting significantly enhanced detection of low abundance proteins. A total of 695 plasma proteins were confidently identified in a single analysis (with a minimum of two peptides per protein) by coupling the tandem separation strategy with two-dimensional LC-MS/MS, including 42 proteins with reported normal concentrations of approximately 100 pg/ml to 100 ng/ml. The concentrations of two selected proteins, macrophage colony-stimulating factor 1 and matrix metalloproteinase-8, were independently validated by ELISA as 202 pg/ml and 12.4 ng/ml, respectively. Evaluation of binding efficiency revealed that 45 medium abundance proteins were efficiently captured by the SuperMix column with >90% retention. Taken together, these results illustrate the potential broad utilities of this tandem IgY12-SuperMix strategy for proteomics applications involving human biofluids where effectively addressing the dynamic range challenge of the specimen is imperative.

Human cytomegalovirus UL97 kinase activity is required for the hyperphosphorylation of retinoblastoma protein and inhibits the formation of nuclear aggresomes.

Cells infected with human cytomegalovirus in the absence of UL97 kinase activity produce large nuclear aggregates that sequester considerable quantities of viral proteins. A transient expression assay suggested that pp71 and IE1 were also involved in this process, and this suggestion was significant, since both proteins have been reported to interact with components of promyelocytic leukemia (PML) bodies (ND10) and also interact functionally with retinoblastoma pocket proteins (RB). PML bodies have been linked to the formation of nuclear aggresomes, and colocalization studies suggested that viral proteins were recruited to these structures and that UL97 kinase activity inhibited their formation. Proteins associated with PML bodies were examined by Western blot analysis, and pUL97 appeared to specifically affect the phosphorylation of RB in a kinase-dependent manner. Three consensus RB binding motifs were identified in the UL97 kinase, and recombinant viruses were constructed in which each was mutated to assess a potential role in the phosphorylation of RB and the inhibition of nuclear aggresome formation. The mutation of either the conserved LxCxE RB binding motif or the lysine required for kinase activity impaired the ability of the virus to stabilize and phosphorylate RB. We concluded from these studies that both UL97 kinase activity and the LxCxE RB binding motif are required for the phosphorylation and stabilization of RB in infected cells and that this effect can be antagonized by the antiviral drug maribavir. These data also suggest a potential link between RB function and the formation of aggresomes.

High dynamic range characterization of the trauma patient plasma proteome.

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this "divide-and-conquer" strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3,654 different proteins with 1,494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 "classic" cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2,910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1,553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.