Synthesis,In Vitro Anti-HIV Activity,Cytotoxicity, and Computational Studies of Some New Steroids and Their Pyrazoline and Oxime Analogues

Russian Journal of Bioorganic Chemistry - There is an urgent need for the design and development of new and safer drugs for the treatment of HIV infection, active against the currently resistant...     

In vitro PYOCIN activity ofPseudomonas aeruginosa strains pretreated with antibiotics

Fifty-six selected strains of Pseudomonas aeruginosa belonging to 8 different pyocin types (H, I, 15, 6, PTI-1, PTI-2, PTI-3, PTI-4) were treated with subinhibitory concentrations (MIC/2) of either gentamicin or carbenicillin. Both treatments induced changes in pyocin patterns for all types but at different levels. The percentage of strains that retained their pyocin pattern were more or less equal in both treatments. In treated and untreated producers, the growth inhibition ability for 5 different strains of Enterobacteriaceae (Escherichia coli K12, E. coli EB, Proteus vulgaris, Salmonella typhi, Shigella flexneri) was also investigated. In all pyocin patterns the number of producers that inhibit the growth of these strains was lower after treatment with gentamicin or with carbenicillin, a smaller decrease was detected in the latter treatment. It appeared that the subinhibitory concentrations of these antibiotics are capable of protecting the Enterobacteriaceae strains from the action of the pyocins.     

Lipopolysaccharide and D-galactosamine-induced hepatic injury is mediated by TNF-alpha and not by Fas ligand

Tumor necrosis factor (TNF)-alpha and Fas ligand (FasL) are trimeric proteins that induce apoptosis through similar caspase-dependent pathways. Hepatocytes are particularly sensitive to inflammation-induced programmed cell death, although the contribution of TNF-alpha and/or FasL to this injury response is still unclear. Here, we report that D-galactosamine and lipopolysaccharide-induced liver injury in C57BL/6 mice is associated with increased hepatic expression of both TNF-alpha and FasL mRNA. Pretreatment of mice with a TNF-binding protein improved survival, reduced plasma aspartate aminotransferase concentrations, and attenuated the apoptotic liver injury, as determined histologically and by in situ 3' OH end labeling of fragmented nuclear DNA. In contrast, pretreatment of mice with a murine-soluble Fas fusion protein (Fasfp) had only minimal effect on survival, and apoptotic liver injury was either unaffected or exacerbated depending on the dose of Fasfp employed. Similarly, mice with a spontaneous mutation in FasL (B6Smn.C3H-Fasl(gld) derived from C57BL/6) were equally sensitive to D-galactosamine/lipopolysaccharide-induced shock. We conclude that the shock and apoptotic liver injury after D-galactosamine/lipopolysaccharide treatment are due primarily to TNF-alpha release, whereas increased FasL expression appears to contribute little to the mortality and hepatic injury.     

The N-terminal domain and glycosomal localization of Leishmania initial acyltransferase LmDAT are important for lipophosphoglycan synthesis

Ether glycerolipids of Leishmania major are important membrane components as well as building blocks of various virulence factors. In L. major, the first enzyme of the ether glycerolipid biosynthetic pathway, LmDAT, is an unusual, glycosomal dihydroxyacetonephosphate acyltransferase important for parasite's growth and survival during the stationary phase, synthesis of ether lipids, and virulence. The present work extends our knowledge of this important biosynthetic enzyme in parasite biology. Site-directed mutagenesis of LmDAT demonstrated that an active enzyme was critical for normal growth and survival during the stationary phase. Deletion analyses showed that the large N-terminal extension of this initial acyltransferase may be important for its stability or activity. Further, abrogation of the C-terminal glycosomal targeting signal sequence of LmDAT led to extraglycosomal localization, did not impair its enzymatic activity but affected synthesis of the ether glycerolipid-based virulence factor lipophosphoglycan. In addition, expression of this recombinant form of LmDAT in a null mutant of LmDAT did not restore normal growth and survival during the stationary phase. These results emphasize the importance of this enzyme's compartmentalization in the glycosome for the generation of lipophosphoglycan and parasite's biology.     

Reversible Inactivation and Desiccation Tolerance of Silicified Viruses

Long-distance host-independent virus dispersal is poorly understood, especially for viruses found in isolated ecosystems. To demonstrate a possible dispersal mechanism, we show that bacteriophage T4, archaeal virus Sulfolobus spindle-shaped virus Kamchatka, and vaccinia virus are reversibly inactivated by mineralization in silica under conditions similar to volcanic hot springs. In contrast, bacteriophage PRD1 is not silicified. Moreover, silicification provides viruses with remarkable desiccation resistance, which could allow extensive aerial dispersal.     

CD8+ T Cell Priming by Dendritic Cell Vaccines Requires Antigen Transfer to Endogenous Antigen Presenting Cells

Background

Immunotherapeutic strategies to stimulate anti-tumor immunity are promising approaches for cancer treatment. A major barrier to their success is the immunosuppressive microenvironment of tumors, which inhibits the functions of endogenous dendritic cells (DCs) that are necessary for the generation of anti-tumor CD8+ T cells. To overcome this problem, autologous DCs are generated ex vivo, loaded with tumor antigens, and activated in this non-suppressive environment before administration to patients. However, DC-based vaccines rarely induce tumor regression.

Methodology/Principal Findings

We examined the fate and function of these DCs following their injection using murine models, in order to better understand their interaction with the host immune system. Contrary to previous assumptions, we show that DC vaccines have an insignificant role in directly priming CD8+ T cells, but instead function primarily as vehicles for transferring antigens to endogenous antigen presenting cells, which are responsible for the subsequent activation of T cells.

Conclusions/Significance

This reliance on endogenous immune cells may explain the limited success of current DC vaccines to treat cancer and offers new insight into how these therapies can be improved. Future approaches should focus on creating DC vaccines that are more effective at directly priming T cells, or abrogating the tumor induced suppression of endogenous DCs.     

Fungal interaction between Trichoderma spp. and Pleurotus ostreatus on the enriched solid media with licorice Glycyrrhiza glabra root extract

The aim of this study is to investigate the antifungal activity of mycelia of Pleurotus ostreatus (white oyster mushroom) and licorice (Glycyrrhiza glabra) root extract against three undesirable fungi. They are Trichoderma spp., Trichoderma harzianum I and Trichoderma harzianum II which was tested on PSA (potato sucrose agar) medium enriched with licorice (Glycyrrhiza glabra) root extract (PSA-G media) using three concentrations (0.05, 0.10 and 0.20 g/L) in alone and dual cultures. Trichoderma spp. showed less mycelial growth of 8.75, 9.17 and 9.50 mm/day on PSA-G0.05, PSA-G0.1 and PSA-G0.2 respectively compared with 10.25 mm/day on fresh PSA (control) in dual culture. The best mycelial growth inhibition was recorded on PSA-G0.2 (14.97%) by T. harzianum II in alone culture opposite 63.72% in dual ones. The lower mycelial growth rate of T. harzianum I was 17.75 mm/day on PSA-G0.1 (0.10 g/L). In dual culture, overgrowth time of T. harzianum I had 5 days compared as approx. 6 days in alone culture. Generally, when the concentration of licorice extract increased, the mycelial growth rate of the undesirable fungi decreased. Also, all PSA-G media, especially PSA-G0.2, indicated low growth averages compared with the control (fresh PSA) against the pathogen while this concentration encourages growth of oyster mushroom. Also, this concentration reduced the density of sporulation of green molds; therefore, this concentration can be applied to reduce influence this pathogen in cultivation farm.     

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to “rescue” the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes.The past decade has witnessed rapid progress in mass spectrometry (MS)-based quantitative proteomics with the development of software and data analysis tools to interrogate large amounts of MS data. Quantitative proteomic technologies have shown great potential in delineating dysregulated proteomes in diseases such as cancer (1–4). Quantitative schemes via either stable isotope labeling or label-free quantitation (LFQ)¹ are used widely to assist MS for quantitative assessments of the changes in protein expression, post-translational modifications (5), and protein-protein interactions (6) in many biological systems, including tumor samples (7–11). However, the integration of accuracy, sensitivity, and totality in the analysis of tumor-specific proteoforms from individual patients still remains challenging with the current quantitative platforms. For example, strategies to increase analytical throughput (12) for tumor analysis have utilized the multiplexing advantage of isobaric mass tags such as tandem mass tags or isotope tagging for relative and absolute quantitation (13, 14). However, for routine quantitative analysis of large scale peptides/proteins, tandem mass tags and isotope tagging for relative and absolute quantitation reagents are prohibitively expensive due to the requirement of large amounts of protein as input. The use of added internal peptide standards, derived from isotope-labeled cell lines, or ¹⁸O labeling to quantify peptides (15) allows for quantitation of proteome expression changes; however, these methods require high resolution in both LC separation and MS acquisition for accurate quantitation of overlapping isotopes. The metabolic incorporation of in-spectra quantitative markers through cell culture (16, 17), in vivo quantitation strategies involving amino acid-coded tags (AACT, also known as SILAC or stable isotope labeling by amino acids in cell culture (18)), is still considered the gold standard for accurate quantitation of relative changes in protein abundance across different biological states. However, for tissue proteomics, neither a single cell line as an add-in SILAC standard (19) nor a library of cell lines (a super-SILAC mix (20)) is close to being a universal standard due to peptides that are either missing or present at low levels. The missing internal standards that fail to cover tissue-peptide counterparts, referred to as orphan peptides, preclude quantitative estimation of tissue proteome differences, an issue that has been addressed recently by the addition of peptide standards (21). A more universal labeling strategy such as complete labeling of the equivalent tissue of the organism of interest via stable isotope labeling of mammals (SILAM) has found limited utility (22, 23). The relatively high cost and laborious procedures associated with animal feeding and labeling prevent widespread use of SILAM.Conversely, quantitation of tissue and tumor proteins is very amenable to LFQ and has gained traction recently as an alternative to spiked-in labeled standards (24, 25). Despite the inherent low precision and low throughput of LFQ methods (i.e. multiple separate or independent LC-MS runs as opposed to interdependent, multiplexed LC-MS runs), LFQ does offer some advantages. Running each sample separately provides a higher number of peptide identifications, whereas LFQ avoids issues inherent to multiplexing, such as low or discrepant labeling efficiencies, inaccuracies in sample mixing, and the need for scrambling/switching the isotope-labeled samples to test whether conversion of isotopically labeled arginine to proline impacts results (26). Also LFQ using MS1 peak intensities can significantly improve the sensitivity as much as 60% compared with label-based quantitative methods such as AACT that rely on the MS1 peak intensities (18).We therefore reasoned that the integration of multiple quantitative schemes would provide synergy, higher throughput, and effectiveness to more precisely determine the changes of protein expressions with a larger coverage of given tissue proteome across different tumor subtypes. Specifically, combining peptide abundance differences using both LFQ and AACT label-based, Ratio-of-Ratio (RoR) estimations would greatly increase the overall number of quantifiable peptide/protein changes to distinguish various tumors. When a common set of peptide features cannot be matched and quantitated between two independent LFQ LC-MS runs due to the frequently occurring issues of retention-time misalignment, the labeled-based quantification strategy could provide complementary peptide ratio estimation. Conversely, when LFQ provides quantitation ratios between samples after retention-time alignment of features, a situation may also exist wherein, at minimum, one of the samples lacks a labeled peptide counterpart, making the label-based estimate impossible. To achieve a complementary quantitative scheme, here we report our development of a unified quantitative approach, termed QuantFusion, that uses a multivariate mixed model to interrogate quantifiable peptide data derived from both LFQ and label-based AACT methods from a single MS experimental run. As stated above, LFQ and RoR measurements share complementary information and therefore can be integrated to reduce the number of replicates required for generating the statistically significant LFQ ratios.The complexity of combining dependent outcomes with heterogeneous error structures and varying sample sizes within each protein necessitated the use of a statistical model. We demonstrate the merit of the mixed model-based approach on the integration of the global-scale proteome characteristics implicated in two major breast cancer (BC) subtypes. QuantFusion increased by 65% the number of distinct peptide ratios to highlight BC-subtypic proteome differences. This increase of quantifiable peptide coverage, in turn, increased the number of measurable protein fold-changes by 8% and increased the average precision of quantitative peptide estimates by 181%. The Statistical Analysis Software code used to implement the statistical model along with a test data set used in this study are available to investigators who wish to perform QuantFusion experiments.