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Additional file 1. Appendix

Additional file 3: Table S3. GR methylation in U and C regions for patients by outcome.

Additional file 2. Supplemental Table 2: DEPICT genetic association in pathways.

Additional file 12: Table S1. Total number of ones, zeros and nulls in the sparse matrix for the 163 TFs used in this study.

Additional optimization code (MATLAB). (TXT 2Â kb)

Additional file7: Table S18. DNAmeQTL analysis for the loci significantly associated with DNAme-based XCI status calls. See additional files. These loci were independently tested as DNAmeQTLs in females and males, with some columns color coded based on sex (pink female, light blue male). There are also columns with the median and mean DNAme value at the gene’s island for samples with the reference or alternate allele at that loci; these columns are color coded based on whether the allele is in the range to escape from XCI (DNAme<0.01, blue) or in the range to be subject to XCI (DNAme>0.15, orange). There are mean and median columns for both males and females, but only the female columns are color coded based on XCI status. There are boxes around the genes with female median values with one allele in the range to escape XCI and the other allele in the range to be subject to XCI.

Comparison of gene expression of CD4+ T cells separated from PBMC isolated using CPT and Ficoll. A two-group comparison with permutation analysis for differential expression was performed, as described in Methods, on microarray data to identify differentially expressed genes between CD4+ T cells separated from CPT- and Ficoll-isolated PBMC. Probsets are ranked according to the FDR value. (CSV 26355 kb)

Additional file 2: Table S2. Summary of CHG-based DMGs.

Introduction: The threat bacterial pathogens pose to human health is increasing with the number and distribution of antibiotic-resistant bacteria, while the rate of discovery of new antimicrobials dwindles. Proteomics is playing key roles in understanding the molecular mechanisms of bacterial pathogenesis, and in identifying disease outcome determinants. The physical associations identified by proteomics can provide the means to develop pathogen-specific treatment methods that reduce the spread of antibiotic resistance and alleviate the negative effects of broad-spectrum antibiotics on beneficial bacteria. Areas covered: This review discusses recent trends in proteomics and introduces new and developing approaches that can be applied to the study of protein-protein interactions (PPIs) underlying bacterial pathogenesis. The approaches examined encompass options for mapping proteomes as well as stable and transient interactions in vivo and in vitro. We also explored the coverage of bacterial and human-bacterial PPIs, knowledge gaps in this area, and how they can be filled. Expert commentary: Identifying potential antimicrobial candidates is confounded by the complex molecular biology of bacterial pathogenesis and the lack of knowledge about PPIs underlying this process. Proteomics approaches can offer new perspectives for mechanistic insights and identify essential targets for guiding the discovery of next generation antimicrobials.

Many roles of human platelets in health and disease are linked to their ability to transport and secrete a variety of small molecules and proteins carried in dense (δ-) and α-granules. Determination of granule number and content is important for diagnosis of platelet disorders and for studies of platelet structure, function, and development. We have optimized methods for detection and localization of platelet proteins via antibody and lectin staining, imaging via structured illumination laser fluorescence microscopy (SIM), and three-dimension (3D) image analysis. The methods were validated via comparison with published studies based on electron microscopy and high-resolution fluorescence microscopy. The α-granule cargo proteins thrombospondin-1 (TSP1), osteonectin (SPARC), fibrinogen (FGN), and Von Willebrand factor (VWF) were localized within the granule lumen, as was the proteoglycan serglycin (SRGN). Colocalization analysis indicates that staining with fluorescently labeled wheat germ agglutinin (WGA) allows detection of α-granules as effectively as immunostaining for cargo proteins, with the advantage of not requiring antibodies. RAB27B was observed to be concentrated at dense granules, allowing them to be counted via visual scoring and object analysis. We present a workflow for counting dense and α-granules via object analysis of 3D SIM images of platelets stained for RAB27B and with WGA. Abbreviation: SIM: structured illumination microscopy; WGA: wheat germ agglutinin; FGN: fibrinogen; TSP1: thrombospondin 1; ER: endoplasmic reticulum Platelets support blood clotting, wound healing, and other essential processes. These functions rely on the ability of platelets to transport and release small molecules like serotonin carried in dense granules and a wide range of proteins carried in alpha granules. Several conditions have been linked to abnormalities in one or more of platelet granule number, content, structure, and function. These conditions can be difficult to diagnose because platelet granules are so small they cannot be consistently resolved by conventional light microscopy, while higher power electron microscopy is not widely accessible. The goal of this study was to develop a method for counting and examining platelet dense and alpha granules without the need of electron microscopy. Key to this was the discovery that alpha granules can be reliably stained with the plant lectin wheat germ agglutinin, which has the advantages of being a smaller and less expensive molecule than the antibodies commonly used to detect alpha granule cargo proteins. We also establish that dense granules can be detected with high specificity via antibody staining of the membrane-associated protein RAB27B. We used structured illumination laser fluorescence microscopy to obtain high-resolution images of stained platelets. These were assembled into 3D renders using image analysis software, which was used to validate a protocol for rapidly counting granules within individual platelets. Our method supports the relatively rapid, accurate, and cost-effective assessment of platelet granules. We have already shown that it can confirm dense granule deficiency, and we anticipate that this approach will also prove useful in diagnosing and studying alpha granule abnormalities.