Proteomic and lipidomic profiling was performed over a time course of acute hepatitis C virus (HCV) infection in cultured Huh-7.5 cells to gain new insights into the intracellular processes influenced by this virus. Our proteomic data suggest that HCV induces early perturbations in glycolysis, the pentose phosphate pathway, and the citric acid cycle, which favor host biosynthetic activities supporting viral replication and propagation. This is followed by a compensatory shift in metabolism aimed at maintaining energy homeostasis and cell viability during elevated viral replication and increasing cellular stress. Complementary lipidomic analyses identified numerous temporal perturbations in select lipid species (e.g. phospholipids and sphingomyelins) predicted to play important roles in viral replication and downstream assembly and secretion events. The elevation of lipotoxic ceramide species suggests a potential link between HCV-associated biochemical alterations and the direct cytopathic effect observed in this in vitro system. Using innovative computational modeling approaches, we further identified mitochondrial fatty acid oxidation enzymes, which are comparably regulated during in vitro infection and in patients with histological evidence of fibrosis, as possible targets through which HCV regulates temporal alterations in cellular metabolic homeostasis.

Large-scale protein identifications from highly complex protein mixtures have recently been achieved using multidimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) and subsequent database searching with algorithms such as SEQUEST. Here, we describe a probability-based evaluation of false positive rates associated with peptide identifications from three different human proteome samples. Peptides from human plasma, human mammary epithelial cell (HMEC) lysate, and human hepatocyte (Huh)-7.5 cell lysate were separated by strong cation exchange (SCX) chromatography coupled offline with reversed-phase capillary LC-MS/MS analyses. The MS/MS spectra were first analyzed by SEQUEST, searching independently against both normal and sequence-reversed human protein databases, and the false positive rates of peptide identifications for the three proteome samples were then analyzed and compared. The observed false positive rates of peptide identifications for human plasma were significantly higher than those for the human cell lines when identical filtering criteria were used, suggesting that the false positive rates are significantly dependent on sample characteristics, particularly the number of proteins found within the detectable dynamic range. Two new sets of filtering criteria are proposed for human plasma and human cell lines, respectively, to provide an overall confidence of >95% for peptide identifications. The new criteria were compared, using a normalized elution time (NET) criterion (Petritis et al. Anal. Chem. 2003, 75, 1039-1048), with previously published criteria (Washburn et al. Nat. Biotechnol. 2001, 19, 242-247). The results demonstrate that the present criteria provide significantly higher levels of confidence for peptide identifications from mammalian proteomes without greatly decreasing the number of identifications.

The possible combination of specific physicochemical properties operating at unique sites of action within cells and tissues has led to considerable uncertainty surrounding nanomaterial toxic potential. We have investigated the importance of proteins adsorbed onto the surface of two distinct classes of nanomaterials (single-walled carbon nanotubes [SWCNTs]; 10-nm amorphous silica) in guiding nanomaterial uptake or toxicity in the RAW 264.7 macrophage-like model. Albumin was identified as the major fetal bovine or human serum/plasma protein adsorbed onto SWCNTs, while a distinct protein adsorption profile was observed when plasma from the Nagase analbuminemic rat was used. Damaged or structurally altered albumin is rapidly cleared from systemic circulation by scavenger receptors. We observed that SWCNTs inhibited the induction of cyclooxygenase-2 (Cox-2) by lipopolysaccharide (LPS; 1 ng/ml, 6 h) and this anti-inflammatory response was inhibited by fucoidan (scavenger receptor antagonist). Fucoidan also reduced the uptake of fluorescent SWCNTs (Alexa647). Precoating SWCNTs with a nonionic surfactant (Pluronic F127) inhibited albumin adsorption and anti-inflammatory properties. Albumin-coated SWCNTs reduced LPS-mediated Cox-2 induction under serum-free conditions. SWCNTs did not reduce binding of LPS(Alexa488) to RAW 264.7 cells. The profile of proteins adsorbed onto amorphous silica particles (50-1000 nm) was qualitatively different, relative to SWCNTs, and precoating amorphous silica with Pluronic F127 dramatically reduced the adsorption of serum proteins and toxicity. Collectively, these observations suggest an important role for adsorbed proteins in modulating the uptake and toxicity of SWCNTs and nano-sized amorphous silica.

Recent advances in proteomics technologies provide tremendous opportunities for biomarker-related clinical applications; however, the distinctive characteristics of human biofluids such as the high dynamic range in protein abundances and extreme complexity of the proteomes present tremendous challenges. In this review we summarize recent advances in LC-MS-based proteomics profiling and its applications in clinical proteomics as well as discuss the major challenges associated with implementing these technologies for more effective candidate biomarker discovery. Developments in immunoaffinity depletion and various fractionation approaches in combination with substantial improvements in LC-MS platforms have enabled the plasma proteome to be profiled with considerably greater dynamic range of coverage, allowing many proteins at low ng/ml levels to be confidently identified. Despite these significant advances and efforts, major challenges associated with the dynamic range of measurements and extent of proteome coverage, confidence of peptide/protein identifications, quantitation accuracy, analysis throughput, and the robustness of present instrumentation must be addressed before a proteomics profiling platform suitable for efficient clinical applications can be routinely implemented.

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Photosynthetic microbes are of emerging interest as production organisms in biotechnology because they can grow autotrophically using sunlight, an abundant energy source, and CO2, a greenhouse gas. Important traits for such microbes are fast growth and amenability to genetic manipulation. Here we describe Synechococcus elongatus UTEX 2973, a unicellular cyanobacterium capable of rapid autotrophic growth, comparable to heterotrophic industrial hosts such as yeast. Synechococcus UTEX 2973 can be readily transformed for facile generation of desired knockout and knock-in mutations. Genome sequencing coupled with global proteomics studies revealed that Synechococcus UTEX 2973 is a close relative of the widely studied cyanobacterium Synechococcus elongatus PCC 7942, an organism that grows more than two times slower. A small number of nucleotide changes are the only significant differences between the genomes of these two cyanobacterial strains. Thus, our study has unraveled genetic determinants necessary for rapid growth of cyanobacterial strains of significant industrial potential.

High-efficiency nanoscale reversed-phase liquid chromatography (chromatographic peak capacities of approximately 1000: Shen, Y.; Zhao, R.; Berger, S. J.; Anderson, G. A.; Rodriguez, N.; Smith, R. D. Anal. Chem. 2002, 74, 4235. Shen, Y.; Moore, R. J.; Zhao, R.; Blonder, J.; Auberry, D. L.; Masselon, C.; Pasa-Tolic, L.; Hixson, K. K.; Auberry, K. J.; Smith, R. D. Anal. Chem. 2003, 75, 3596.) and strong cation exchange LC was used to obtain ultra-high-efficiency separations (combined chromatographic peak capacities of >10(4)) in conjunction with tandem mass spectrometry (MS/MS) for characterization of the human plasma proteome. Using conservative SEQUEST peptide identification criteria (i.e., without considering chymotryptic or elastic peptides) and peptide LC normalized elution time constraints, the separation quality enabled the identification of proteins over a dynamic range of greater than 8 orders of magnitude in relative abundance using ion trap MS/MS instrumentation. Between 800 and 1682 human proteins were identified, depending on the criteria used for identification, from a total of 365 microg of human plasma. The analyses identified relatively low-level (approximately pg/mL) proteins (e.g., cytokines) coexisting with high-abundance proteins (e.g., mg/mL-level serum albumin).

Candidate proteomic biomarker discovery from human plasma holds both incredible clinical potential as well as significant challenges. The dynamic range of proteins within plasma is known to exceed 10(10), and many potential biomarkers are likely present at lower protein abundances. At present, proteomic based MS analyses provide a dynamic range typically not exceeding approximately 10(3) in a single spectrum, and approximately 10(4)-10(6) when combined with on-line separations (e.g., reversed-phase gradient liquid chromatography), and thus are generally insufficient for low level biomarker detection directly from human plasma. This limitation is providing an impetus for the development of experimental methodologies and strategies to increase the possible number of detections within this biofluid. Discussed is the diversity of available approaches currently used by our laboratory and others to utilize human plasma as a viable medium for biomarker discovery. Various separation, depletion, enrichment, and quantitative efforts as well as recent improvements in MS capabilities have resulted in measurable improvements in the detection and identification of lower abundance proteins (by approximately 10-10(2)). Despite these improvements, further advances are needed to provide a basis for discovery of candidate biomarkers at very low levels. Continued development of depletion and enrichment techniques, coupled with improved pre-MS separations (both at the protein and peptide level) holds promise in extending the dynamic range of proteomic analysis.