Project description:Sperm motility is one of the most important determinants of male fertility. Elucidating the different expression proteins of nomal and asthenospermia spermatozoa should advance our understanding of the underlying molecular mechanisms. Tcte1 null mouse sperm reduced motility and failed to display the forward progressive motile. With tandem mass tag (TMT) labeling and mass spectrometry analysis, 3697 proteins were quantified from Widetype and Tcte1 deficient mouse spermatozoa. Of these proteins, 447 were found to be different expression proteins (DEPs), including 398 proteins down regulated (DDEPs, 89%) and only 49 proteins up regulated.
Project description:The proteome and phosphoproteomics changes were quantified in seminal plasma extracellular vesicles among healthy individuals with normal sperm, nonobstructive azoospermia and obstructive azoospermia using TMT 10-plex by LC-MS/MS.
Project description:Arachidonic acid (ARA) treated and control oocytes in 3 replicates were subjected to the 6-plex TMT labeling, HP-RP fractionation, and LC-MS/MS analysis.
Project description:Two replicates of GV, GVBD, and MII oocytes were subjected to the 6-plex TMT labeling, HP-RP fractionation, and LC-MS/MS analysis. Two labeling experiments were performed for the total four replicates of each stage of oocytes.
Project description:Five replicates of GV, GVBD, and MII oocytes were subjected to the 15-plex TMT labeling, HP-RP fractionation, and LC-MS/MS analysis. For each replicate, 2,000 oocytes were collected from each of the GV, GVBD, and MII stages. Ti4+-IMAC was used to enrich phosphopeptides.
Project description:Tumor formation is in part driven by copy number alterations (CNAs), which can be measured using array Comparative Genomic Hybridization (aCGH). Identifying regions of DNA that are gained or lost in a significant fraction of tumor samples can facilitate identification of genes possibly related to the development of cancer. Until now, no method has been described that provides a statistical framework in which these regions can be identified without prior discretization of the aCGH data. Kernel Convolution - a Statistical Method for Aberrant Region deTection (KC-SMART) is a new approach which inputs continuous aCGH data to identify regions that are significantly aberrant across an entire tumor set. KC-SMART uses kernel convolution to generate a Kernel Smoothed Estimate (KSE) of CNAs across the genome, aggregated over all tumors. By varying the width of the kernel function, a scale space is created which enables the detection of aberrations of varying size. In an analysis of 89 human sporadic breast tumors KC-SMART performs better than a previously published method, STAC. Our method not only identified aberrations that are strongly associated with clinical parameters, but also showed stronger enrichment for known cancer genes in the detected regions. Furthermore, KC-SMART identifies 18 aberrant regions in mammary tumors from p53 conditional knock-out mice. These regions, combined with gene expression micro-array data, point to known cancer genes and novel candidate cancer genes. 19 mouse mammary tumors samples were measured against spleen-derived DNA from the same animal on our in-house aCGH platform. Goal of the study was to assess recurrent genomic aberrations in these tumors. This is a tissue specific knockout of p53. Experiments were perfomed in dye-swap
Project description:Despite the advanced understanding of disease mechanisms, the current therapeutic regimens fail to cure most patients with acute myeloid leukemia (AML). In the present study, we address the role of protein synthesis control in AML leukemia stem cell (LSC) function and leukemia propagation. We apply a murine model of mixed-lineage leukemia-rearranged AML to demonstrate that LSCs synthesize more proteins per hour compared with the bulk of leukemia. Using a genetic model that permits inducible and graded regulation of ribosomal subunit joining, we show that defective ribosome assembly leads to a significant survival advantage by selectively eradicating LSCs but not normal hematopoietic stem and progenitor cells. Finally, transcriptomic and proteomic analyses identify a rare subset of LSCs with immature stem cell signature and high ribosome content that underlies the resistance to defective ribosome assembly. Collectively, our study unveils a critical requirement of high protein synthesis rate for LSC function, highlighting ribosome assembly as a therapeutic target in AML.
Project description:By coupling PDX and cell surface marker screening technologies, we have identified distinct tumor cell sub-populations that are associated with tumor resistance to chemotherapy. In the majority of relapsed tumors, the percentage of the marker-positive cells shifted back to pretreatment levels. SSEA4 is one of the cell surface molecules tested that could distinguish enriched residual tumor cells in all the different TNBC PDX models analyzed. The expression of SSEA4 is associated with tumor resistance to chemotherapy and SSEA4+ cells show increased gene expression of genes involved in response to toxins, cellular import/export, cell migration and EMT. The dataset comprises four different sample groups including SSEA4- and SSEA4+ cell fractions isolated from mouse xenografts of human breast cancer cells. Two technical replicates were generated for each cell fraction. Microarray analysis was performed on the Agilent Whole Human Genome Oligo Microarray 8x60K (v2) platform.
Project description:Earlier we identified the protein degradation properties of small molecule UM171 (Subramaniam et al., 2020, Blood). Here we employed quantitative proteomics approach to map the global targets of UM171. Our study revealed multiple targets including the members of CoREST complex such as RCOR1 and LSD1.