Immunodominant tuberculosis CD8 antigens preferentially restricted by HLA-B

CD8(+) T cells are essential for host defense to intracellular bacterial pathogens such as Mycobacterium tuberculosis (Mtb), Salmonella species, and Listeria monocytogenes, yet the repertoire and dominance pattern of human CD8 antigens for these pathogens remains poorly characterized. Tuberculosis (TB), the disease caused by Mtb infection, remains one of the leading causes of infectious morbidity and mortality worldwide and is the most frequent opportunistic infection in individuals with HIV/AIDS. Therefore, we undertook this study to define immunodominant CD8 Mtb antigens. First, using IFN-gamma ELISPOT and synthetic peptide arrays as a source of antigen, we measured ex vivo frequencies of CD8(+) T cells recognizing known immunodominant CD4(+) T cell antigens in persons with latent tuberculosis infection. In addition, limiting dilution was used to generate panels of Mtb-specific T cell clones. Using the peptide arrays, we identified the antigenic specificity of the majority of T cell clones, defining several new epitopes. In all cases, peptide representing the minimal epitope bound to the major histocompatibility complex (MHC)-restricting allele with high affinity, and in all but one case the restricting allele was an HLA-B allele. Furthermore, individuals from whom the T cell clone was isolated harbored high ex vivo frequency CD8(+) T cell responses specific for the epitope, and in individuals tested, the epitope represented the single immunodominant response within the CD8 antigen. We conclude that Mtb-specific CD8(+) T cells are found in high frequency in infected individuals and are restricted predominantly by HLA-B alleles, and that synthetic peptide arrays can be used to define epitope specificities without prior bias as to MHC binding affinity. These findings provide an improved understanding of immunodominance in humans and may contribute to a development of an effective TB vaccine and improved immunodiagnostics.     

Comparative proteome profiling and functional analysis of chronic myelogenous leukemia cell lines

The aim of the present study was the molecular profiling of different Ph+ chronic myelogenous leukemia (CML) cell lines (LAMA84, K562, and KCL22) by a proteomic approach. By employing two-dimensional gel electrophoresis combined with mass spectrometry analysis, we have identified 191 protein spots corresponding to 142 different proteins. Among these, 63% were cancer-related proteins and 74% were described for the first time in leukemia cells. Multivariate analysis highlighted significant differences in the global proteomic profile of the three CML cell lines. In particular, the detailed analysis of 35 differentially expressed proteins revealed that LAMA84 cells preferentially expressed proteins associated with an invasive behavior, while K562 and KCL22 cells preferentially expressed proteins involved in drug resistance. These data demonstrate that these CML cell lines, although representing the same pathological phenotype, show characteristics in their protein expression profile that suggest different phenotypic leukemia subclasses. These data contribute a new potential characterization of the CML phenotype and may help to understand interpatient variability in the progression of disease and in the efficacy of a treatment.     

Unsupervised fluorescence lifetime imaging microscopy for high content and high throughput screening

Proteomics and cellomics clearly benefit from the molecular insights in cellular biochemical events that can be obtained by advanced quantitative microscopy techniques like fluorescence lifetime imaging microscopy and F?rster resonance energy transfer imaging. The spectroscopic information detected at the molecular level can be combined with cellular morphological estimators, the analysis of cellular localization, and the identification of molecular or cellular subpopulations. This allows the creation of powerful assays to gain a detailed understanding of the molecular mechanisms underlying spatiotemporal cellular responses to chemical and physical stimuli. This work demonstrates that the high content offered by these techniques can be combined with the high throughput levels offered by automation of a fluorescence lifetime imaging microscope setup capable of unsupervised operation and image analysis. Systems and software dedicated to image cytometry for analysis and sorting represent important emerging tools for the field of proteomics, interactomics, and cellomics. These techniques could soon become readily available both to academia and the drug screening community by the application of new all-solid-state technologies that may results in cost-effective turnkey systems. Here the application of this screening technique to the investigation of intracellular ubiquitination levels of alpha-synuclein and its familial mutations that are causative for Parkinson disease is shown. The finding of statistically lower ubiquitination of the mutant alpha-synuclein forms supports a role for this modification in the mechanism of pathological protein aggregation.     

Different quaternary structures of human RECQ1 are associated with its dual enzymatic activity

RecQ helicases are essential for the maintenance of chromosome stability. In addition to DNA unwinding, some RecQ enzymes have an intrinsic DNA strand annealing activity. The function of this dual enzymatic activity and the mechanism that regulates it is, however, unknown. Here, we describe two quaternary forms of the human RECQ1 helicase, higher-order oligomers consistent with pentamers or hexamers, and smaller oligomers consistent with monomers or dimers. Size exclusion chromatography and transmission electron microscopy show that the equilibrium between the two assembly states is affected by single-stranded DNA (ssDNA) and ATP binding, where ATP or ATPγS favors the smaller oligomeric form. Our three-dimensional electron microscopy reconstructions of human RECQ1 reveal a complex cage-like structure of approximately 120 Å × 130 Å with a central pore. This oligomeric structure is stabilized under conditions in which RECQ1 is proficient in strand annealing. In contrast, competition experiments with the ATPase-deficient K119R and E220Q mutants indicate that RECQ1 monomers, or tight binding dimers, are required for DNA unwinding. Collectively, our findings suggest that higher-order oligomers are associated with DNA strand annealing, and lower-order oligomers with DNA unwinding.     

Sarcopenic obesity and inflammation in the InCHIANTI study.

The aging process is often paralleled by decreases in muscle and increases in fat mass. At the extreme these two processes lead to a condition known as "sarcopenic obesity" (Roubenoff R. Ann NY Acad Sci 904: 553-557, 2000). Research suggests that inflammatory cytokines produced by adipose tissue, especially visceral fat, accelerate muscle catabolism and thus contribute to the vicious cycle that initiates and sustains sarcopenic obesity. We tested the hypothesis that obesity and poor muscle strength, hallmarks of sarcopenic obesity, are associated with high circulating levels of proinflammatory cytokines in a random sample of the residents of two municipalities in the Chianti geographic area (Tuscany, Italy). The study sample consisted of 378 men and 493 women 65 yr and older with complete data on anthropometrics, handgrip strength, and inflammatory markers. Participants were cross-classified according to sex-specific tertiles of waist circumference and grip strength and according to a cut point for obesity of body mass index > or =30 kg/m(2). After adjusting for age, sex, education, smoking history, physical activity, and history of comorbid diseases, components of sarcopenic obesity were associated with elevated levels of IL-6, C-reactive protein, IL-1 receptor antagonist, and soluble IL-6 receptor (P < 0.05). Our findings suggest that global obesity and, to a greater extent, central obesity directly affect inflammation, which in turn negatively affects muscle strength, contributing to the development and progression of sarcopenic obesity. These results suggest that proinflammatory cytokines may be critical in both the development and progression of sarcopenic obesity.     

Coenzyme Q10 protects against β-cell toxicity induced by pravastatin treatment of hypercholesterolemia

New onset of diabetes is associated with the use of statins. We have recently demonstrated that pravastatin-treated hypercholesterolemic LDL receptor knockout (LDLr^−/−) mice exhibit reductions in insulin secretion and increased islet cell death and oxidative stress. Here, we hypothesized that these diabetogenic effects of pravastatin could be counteracted by treatment with the antioxidant coenzyme Q ₁₀ (CoQ ₁₀), an intermediate generated in the cholesterol synthesis pathway. LDLr ^−/− mice were treated with pravastatin and/or CoQ ₁₀ for 2 months. Pravastatin treatment resulted in a 75% decrease of liver CoQ ₁₀ content. Dietary CoQ ₁₀ supplementation of pravastatin-treated mice reversed fasting hyperglycemia, improved glucose tolerance (20%) and insulin sensitivity (>2-fold), and fully restored islet glucose-stimulated insulin secretion impaired by pravastatin (40%). Pravastatin had no effect on insulin secretion of wild-type mice. In vitro, insulin-secreting INS1E cells cotreated with CoQ ₁₀ were protected from cell death and oxidative stress induced by pravastatin. Simvastatin and atorvastatin were more potent in inducing dose-dependent INS1E cell death (10–15-fold), which were also attenuated by CoQ ₁₀ cotreatment. Together, these results demonstrate that statins impair β-cell redox balance, function and viability. However, CoQ ₁₀ supplementation can protect the statins detrimental effects on the endocrine pancreas.     

Aspirin inhibits cancer stem cells properties and growth of glioblastoma multiforme through Rb1 pathway modulation

Several clinical studies indicated that the daily use of aspirin or acetylsalicylic acid reduces the cancer risk via cyclooxygenases (Cox-1 and Cox-2) inhibition. In addition, aspirin-induced Cox-dependent and -independent antitumor effects have also been described. Here we report, for the first time, that aspirin treatment of human glioblastoma cancer (GBM) stem cells, a small population responsible for tumor progression and recurrence, is associated with reduced cell proliferation and motility. Aspirin did not interfere with cell viability but induced cell-cycle arrest. Exogenous prostaglandin E₂ significantly increased cell proliferation but did not abrogate the aspirin-mediated growth inhibition, suggesting a Cox-independent mechanism. These effects appear to be mediated by the increase of p21 ^waf1 and p27 ^Kip1, associated with a reduction of Cyclin D1 and Rb1 protein phosphorylation, and involve the downregulation of key molecules responsible for tumor development, that is, Notch1, Sox2, Stat3, and Survivin. Our results support a possible role of aspirin as adjunctive therapy in the clinical management of GBM patients.     

A new generation of predictive models: The added value of hybrid models for manufacturing processes of therapeutic proteins

Due to the lack of complete understanding of metabolic networks and reaction pathways, establishing a universal mechanistic model for mammalian cell culture processes remains a challenge. Contrarily, data-driven approaches for modeling these processes lack extrapolation capabilities. Hybrid modeling is a technique that exploits the synergy between the two modeling methods. Although mammalian cell cultures are among the most relevant processes in biotechnology and indeed looks ideal for hybrid modeling, their application has only been proposed but never developed in the literature. This study provides a quantitative assessment of the improvement brought by hybrid models with respect to the state-of-the-art statistical predictive models in the context of therapeutic protein production. This is illustrated using a dataset obtained from a 3.5 L fed-batch experiment. With the goal to robustly define the process design space, hybrid models reveal a superior capability to predict the time evolution of different process variables using only the initial and process conditions in comparison to the statistical models. Hybrid models not only feature more accurate prediction results but also demonstrate better robustness and extrapolation capabilities. For the future application, this study highlights the added value of hybrid modeling for model-based process optimization and design of experiments.