Historical and recent evidence for close relationships among Rickettsia parkeri,R. conorii,R. africae,and R. sibirica: Implications for rickettsial taxonomy

Rickettsia parkeri, a member of the spotted fever group rickettsias, was first described in 1939 and was thought to be non‐pathogenic until recently, when it was found to cause a spotted fever‐like illness in humans and areas of necrosis (eschars) at the sites of tick bites. Accordingly, there is currently much interest in this emerging pathogen. In this study, all published articles concerning R. parkeri were reviewed and analyzed for evidence of relatedness among this agent and other spotted fever group (SFG) rickettsiae which also produce similar clinical syndromes and/or eschars, including R. conorii, R. africae, and R. sibirica. A synthesis of the historical (antigenic) and recent (molecular) data supporting a phylogenetic sub‐grouping of these SFG organisms is presented and comments are offered about the taxonomy of rickettsial organisms in general, and R. parkeri in particular.     

The control of flower initiation by gibberellin in Helianthus annuus L. (sunflower), a non-photoperiodic plant

The involvement of gibberellins in the control of flowering of sunflower was studied by direct application of GA₃ to the apex of the plants, analysis of the endogenous levels of gibberellin-like substances at different plant ages, and indirectly by the application of paclobutrazol, an inhibitor of gibberellin synthesis. GA₃ speeded-up flower initiation and floral apex development. The time of GA₃ application was more critical than the amount of GA₃ applied. The endogenous levels of gibberellin-like compounds increased significantly by day 15 after sowing. The application of paclobutrazol markedly delayed floral initiation and this effect was also depedent on plant age. Both GA₃ and paclobutrazol had their greatest effects between 10 and 20 days after sowing suggesting that an increase in gibberellins in that time period plays a role in floral initiation.     

Trace elements in rock salt and their bioavailability estimated from solubility in acid

In this study, 18 partly commercially available samples of rock salt from Austria, Germany, Pakistan, Poland, Switzerland, and Ukraine were investigated with respect to their content of trace elements using instrumental neutron activation analysis. Elements detected were Al, Ba, Br, Ca, Ce, Cl, Co, Cr, Cs, Eu, Fe, Hf, La, Mn, Na, Rb, Sb, Sc, Sm, Sr, Ta, Tb, Th, and Zn, some of them only in individual cases. An estimation of the bioavailability of these trace elements was performed by dissolving an equivalent of the sodium chloride samples in diluted hydrochloric acid (simulating stomach acid), filtering off the insoluble components, and analyzing the evaporated filtrate. It could be shown that in most cases bioactive trace elements like Fe can be found in rock salt in the form of almost insoluble compounds and are therefore not significantly bioavailable, whereas thorium, for example, was partly bioavailable in two cases. A significant contribution to the recommended daily intake of metal trace elements by using rock salt for nutrition can be excluded.     

Joint multiple quantitative trait loci mapping for allometries of body compositions and metabolic traits to body weights in broiler

In order to map quantitative trait loci (QTLs) for allometries of body compositions and metabolic traits in chicken, we phenotypically characterize the allometric growths of multiple body components and metabolic traits relative to BWs using joint allometric scaling models and then establish random regression models (RRMs) to fit genetic effects of markers and minor polygenes derived from the pedigree on the allometric scalings. Prior to statistically inferring the QTLs for the allometric scalings by solving the RRMs, the LASSO technique is adopted to rapidly shrink most of marker genetic effects to zero. Computer simulation analysis confirms the reliability and adaptability of the so-called LASSO-RRM mapping method. In the F₂ population constructed by multiple families, we formulate two joint allometric scaling models of body compositions and metabolic traits, in which six of nine body compositions are tested as significant, while six of eight metabolic traits are as significant. For body compositions, a total of 14 QTLs, of which 9 dominant, were detected to be associated with the allometric scalings of drumstick, fat, heart, shank, liver and spleen to BWs; while for metabolic traits, a total of 19 QTLs also including 9 dominant be responsible for the allometries of T4, IGFI, IGFII, GLC, INS, IGR to BWs. The detectable QTLs or highly linked markers can be used to regulate relative growths of the body components and metabolic traits to BWs in marker-assisted breeding of chickens.     

Gene expression changes associated with cytotoxicity identified using cDNA arrays

In order to investigate gene expression changes associated with cytotoxicity, we used cDNA arrays to monitor the expression of over 5,000 genes in response to toxic stress in the HepG2 liver cell line. Cells were treated with cytotoxic doses of acetaminophen, caffeine or thioacetamide for nine time points ranging from 1 to 24 h. Samples of mRNA from each time point were used to prepare radiolabeled cDNA, which was hybridized to nylon-membrane-based cDNA arrays. High-stringency washes were applied to reduce cross-hybridization. Analysis of spot intensities revealed that each compound led to approximately 150-250 gene expression changes that were sustained over at least three adjacent time points. The affected genes could be classified into clusters based on their temporal patterns of differential expression. A common set of 44 genes showed similar expression changes in response to all three compounds. Of these changes, 90% could be confirmed by quantitative RT-PCR analysis. The results indicate that detailed array-based time-course studies, coupled with a sensitive and highly specific confirmation assay, provide a powerful means of identifying cytotoxicity-associated gene expression changes. Electronic Publication     

An Arabidopsis lipid map reveals differences between tissues and dynamic changes throughout development

Mass spectrometry is the predominant analytical tool used in the field of plant lipidomics. However, there are many challenges associated with the mass spectrometric detection and identification of lipids because of the highly complex nature of plant lipids. Studies into lipid biosynthetic pathways, gene functions in lipid metabolism, lipid changes during plant growth and development, and the holistic examination of the role of plant lipids in environmental stress responses are often hindered. Here, we leveraged a robust pipeline that we previously established to extract and analyze lipid profiles of different tissues and developmental stages from the model plant Arabidopsis thaliana. We analyzed seven tissues at several different developmental stages and identified more than 200 lipids from each tissue analyzed. The data were used to create a web-accessible in silico lipid map that has been integrated into an electronic Fluorescent Pictograph (eFP) browser. This in silico library of Arabidopsis lipids allows the visualization and exploration of the distribution and changes of lipid levels across selected developmental stages. Furthermore, it provides information on the characteristic fragments of lipids and adducts observed in the mass spectrometer and their retention times, which can be used for lipid identification. The Arabidopsis tissue lipid map can be accessed at http://bar.utoronto.ca/efp_arabidopsis_lipid/cgi-bin/efpWeb.cgi .     

DPHL:A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.