The novel chelator lipid 3(nitrilotriacetic acid)-ditetradecylamine (NTA3-DTDA) promotes stable binding of His-tagged proteins to liposomal membranes: Potent anti-tumor responses induced by simultaneously targeting antigen, cytokine and costimulatory signals to T cells

Recent studies indicate that the chelator lipid nitrilotriacetic acid ditetradecylamine (NTA-DTDA) can be used to engraft T cell costimulatory molecules onto tumor cell membranes, potentially circumventing the need for genetic manipulation of the cells for development of cell- or membrane-based tumor vaccines. Here, we show that a related lipid 3(nitrilotriacetic acid)-ditetradecylamine (NTA₃-DTDA, which has three NTA moieties in its headgroup instead of one) is several-fold more effective than NTA-DTDA at promoting stable His-tagged protein engraftment. IAsys biosensor studies show that binding of His-tagged B7.1 (B7.1-6H) to NTA₃-DTDA-containing membranes, exhibit a faster on-rate and a slower off-rate, compared to membranes containing NTA-DTDA. Also, NTA₃-DTDA-containing liposomes and plasma membrane vesicles (PMV) engrafted with B7.1-6H and CD40-6H exhibit greater binding to T cells, in vitro and in vivo. Engrafted NTA₃-DTDA-containing PMV encapsulated cytokines such as IL-2, IL-12, GM-CSF and IFN-γ, allowing targeted delivery of both antigen and cytokine to T cells, and stimulation of antigen-specific T cell proliferation and cytotoxicity. Importantly, use of B7.1-CD40-engrafted PMV containing IL-2 and IL-12 as a vaccine in DBA/2J mice induced protection against challenge with syngeneic tumor cells (P815 mammary mastocytoma), and regression of established tumors. The results show that stable protein engraftment onto liposomal membranes using NTA₃-DTDA can be used to simultaneously target associated antigen, costimulatory molecules and cytokines to T cells in vivo, inducing strong anti-tumor responses and immunotherapeutic effect.     

Endogenous IL-18 in experimentally induced asthma affects cytokine serum levels but is irrelevant for clinical symptoms

T cells and T cell derived cytokines are involved in the complex pathogenesis of asthma. The role of the cytokine IL-18 however, is not clearly defined so far. On the one hand side IL-18 induces Th1-type cytokines and thereby might counter-regulate Th2-mediated allergic asthma. On the other hand IL-18 also bears pro-inflammatory effects possibly enhancing experimental asthma. In order to elucidate the role of IL-18 in allergic pulmonary inflammation typical symptoms were compared after induction of experimental asthma in IL-18^−/− and in wild type mice. Asthma was induced using ovalbumin (OVA) as allergen for sensitization and challenge. Sham sensitized and OVA challenged mice served as controls. Bronchoalveolar lavage-fluid cytology, leukocyte infiltration in lung tissues, serum levels of OVA-specific IgE and cytokines, and lung function were analyzed. Clear differences could be observed between control and asthmatic mice, both in wild type and IL-18^−/− animals. Surprisingly, no differences were found between asthmatic wild type and IL-18^−/− mice. Thus, in contrast to conflicting data in the literature IL-18 did not suppress or enhance the pulmonary allergic immune response in a murine experimental model of asthma.     

Using squat testing to predict training loads for the deadlift, lunge, step-up, and leg extension exercises

The purpose of this study was to determine whether there is a linear relationship between the squat and a variety of quadriceps resistance training exercises for the purpose of creating prediction equations for the determination of quadriceps exercise loads based on the squat load. Six-repetition maximums (RMs) of the squat, as well as four common resistance training exercises that activate the quadriceps including the deadlift, lunge, step-up, and leg extension, were determined for each subject. Subjects included 21 college students. Data were evaluated using linear regression analysis to predict quadriceps exercise loads from 6RM squat data and were cross-validated with the prediction of sum of squares statistic. Analysis of the data revealed that the squat is a significant predictor of loads for the dead lift (R2 = 0.81, standard error of the estimate [SEE] = 12.50 kg), lunge (R2 = 0.62, SEE = 12.57 kg), step-up (R2 = 0.71, SEE = 9.58 kg), and leg extension (R2=0.67, SEE = 10.26 kg) exercises. Based on the analysis of the data, the following 6RM prediction equations were devised for each exercise: (a) deadlift load = squat load (0.83) + 14.92 kg, (b) lunge load = squat load (0.52) + 14.82 kg, (c) step-up load = squat load (0.50) + 3.32 kg, and (d) leg extension load = squat load (0.48) + 9.58 kg. Results from testing core exercises such as the squat can provide useful data for the assignment of loads for other exercises.     

Development of a fission yeast-based high-throughput screen to identify chemical regulators of cAMP phosphodiesterases

Cyclic nucleotide phosphodiesterases (PDEs) comprise a superfamily of enzymes that serve as drug targets in many human diseases. There is a continuing need to identify high-specificity inhibitors that affect individual PDE families or even subtypes within a single family. The authors describe a fission yeast-based high-throughput screen to detect inhibitors of heterologously expressed adenosine 3',5'-cyclic monophosphate (cAMP) PDEs. The utility of this system is demonstrated by the construction and characterization of strains that express mammalian PDE2A, PDE4A, PDE4B, and PDE8A and respond appropriately to known PDE2A and PDE4 inhibitors. High-throughput screens of 2 bioactive compound libraries for PDE inhibitors using strains expressing PDE2A, PDE4A, PDE4B, and the yeast PDE Cgs2 identified known PDE inhibitors and members of compound classes associated with PDE inhibition. The authors verified that the furanocoumarin imperatorin is a PDE4 inhibitor based on its ability to produce a PDE4-specific elevation of cAMP levels. This platform can be used to identify PDE activators, as well as genes encoding PDE regulators, which could serve as targets for future drug screens.     

Species richness of herbivores on exotic host plants increases with time since introduction of the host

Aim Species richness of insect herbivores feeding on exotic plants increases with abundance as well as range size of the host in the area of introduction. The formation of these herbivore assemblages requires a certain amount of time, and the richness of insect faunas should also increase with the length of time an exotic plant has been present in the introduced range. Location Central Europe. Methods We analysed the variation in species richness of leaf‐chewing Lepidoptera larvae and sap‐sucking Auchenorrhyncha (Hemiptera) associated with 103 exotic woody plant species in Germany in relation to time since introduction, range size, growth form (trees versus shrubs), biogeographical origin (distance from Central Europe) and taxonomic isolation of the host plant (presence or absence of a native congener in the introduced area). Results Using simple correlation analyses we found for Lepidoptera and Auchenorrhyncha that species richness increased with time since introduction of the host plant. For the Lepidoptera the increase of species richness with time since introduction remained significant even after removing the effects of all other independent variables. Main conclusions Our results provide some evidence that assemblages of insects on exotic plants do not reach saturation within a time scale of few hundred years. This contrasts with previous findings for crop plants.     

Combining classifiers for improved classification of proteins from sequence or structure

Background  

Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there has been considerable interest in using discriminative learning algorithms, in particular support vector machines (SVMs), for classification of proteins. However, because sufficiently many positive examples are required to train such classifiers, all SVM-based methods are hampered by limited coverage.     

Proteome profiling of breast tumors by gel electrophoresis and nanoscale electrospray ionization mass spectrometry

We have conducted proteome-wide analysis of fresh surgery specimens derived from breast cancer patients, using an approach that integrates size-based intact protein fractionation, nanoscale liquid separation of peptides, electrospray ion trap mass spectrometry, and bioinformatics. Through this approach, we have acquired a large amount of peptide fragmentation spectra from size-resolved fractions of the proteomes of several breast tumors, tissue peripheral to the tumor, and samples from patients undergoing noncancer surgery. Label-free quantitation was used to generate protein abundance maps for each proteome and perform comparative analyses. The mass spectrometry data revealed distinct qualitative and quantitative patterns distinguishing the tumors from healthy tissue as well as differences between metastatic and non-metastatic human breast cancers including many established and potential novel candidate protein biomarkers. Selected proteins were evaluated by Western blotting using tumors grouped according to histological grade, size, and receptor expression but differing in nodal status. Immunohistochemical analysis of a wide panel of breast tumors was conducted to assess expression in different types of breast cancers and the cellular distribution of the candidate proteins. These experiments provided further insights and an independent validation of the data obtained by mass spectrometry and revealed the potential of this approach for establishing multimodal markers for early metastasis, therapy outcomes, prognosis, and diagnosis in the future.