ABSTRACT: The deposisted data is the deep dive global shotgun bottom-up LC-MS/MS proteome analysis of the Euplotes crassus microorganism. The main objective of the project was to find confirmation of the frameshifts at the protein level.
Project description:Detailed description of an optimally tuned workflow for high throughput middle-down proteomics with the currently available state-of-the-art instrumentation. In this work we describe and critically evaluate the limits of an optimized workflow for the detection of middle-range peptides. First, the work compares the yield of desired longer peptides both by enzymatic and acidic digestion protocols. Second, it uses optimized conditions for sample clean-up and multidimensional LC. Third, we fine-tuned critical MS parameters for improving the detection of middle-range peptides where we comprehensively evaluated ETD, HCD and EThcD fragmentation schemes on all the digests obtained in order to choose the best sequencing method for distinct populations of peptides and with special attention paid to longer peptides.
Project description:Investigation of non-synonymous mutation as a major driver for cancer is essential for discovery of biomarkers and therapeutics. Although, many cancer-associated mutations have been identified through genomics, there is a poor understanding of how they manifest in the proteome. In fact, detection of mutation derived peptides is confounded by technical and biological factors. In this study cancer associated mutations from the COSMIC database were integrated into proteins, to generate cell line specific sequence databases. We used a robust workflow for high-throughput processing of 375 cancer cell lines from the Cancer Cell Line Encyclopedia (CCLE) to identify mutant peptides and generate PRIDE compatible mzTab results. This includes a peptide to genome mapping tool, PepGenome, allowing targeted mapping of mutant peptides. Examining the allelic paired non-mutant reference peptides, we were able to profile significantly more potential mutant peptides and determine allelic biases in the expression and observation of mutant peptides. We present quantification, genomic mapping, and evaluation of 1,336 cancer associated mutant peptides and infer protein allelic bias for 31,219 mutations in. We highlight the problems faced in detecting and characterising mutant peptides by mass spectrometry and show that allelic bias plays a significant role in suppressing the expression of mutant proteoforms.
Project description:pBIC-1a is a IncFIIk-IncFI blaKPC-2-producing plasmid. Transcriptomic analysis was performed to dive deeper into the biology of this prototypical successful plasmid. The transcriptional landscape of pBIC-1a was assessed without antibiotic, and differential analysis after imipenem exposure was performed on E. coli TOP10(pBIC-1a) whole transcriptome.
Project description:To determine what kind of genes are involved in vocal learning ability, we performed microarray experiments using 3 vocal learning species (zebra finch, budgerigar, Anna's hummingbird) and 2 non-vocal learning species(ring dive, and Japanese quail) from bird group. All of the animals are adult males. They were isolated over night and had 1hour light exposure at morning. Birds who did not sing were used in this experiment.
Project description:To determine what kind of genes are involved in vocal learning ability, we performed microarray experiments using 3 vocal learning species (zebra finch, budgerigar, Anna's hummingbird) and 2 non-vocal learning species(ring dive, and Japanese quail) from the bird group. All of the animals are male adults. They were isolated over night and had 1hour light exposure at morning. Birds who did not sing were used in this experiment.
Project description:The breast cancer presents one of the most commonly diagnosed types of cancer among women and its mortality rates remain very high probably due to the diagnosis of this disease is hampered by the lack of an accurate detection method. Since that change of protein expression as well modifications in its glycosylation have been frequently reported in cancer development, the aim of this work was study the differential expression as well modifications of glycosylation of proteins from plasma of women with breast cancer at three different stages of disease. A proteomics approach was used that depleted albumin and IgG from plasma followed by glycoprotein enrichment using immobilized Moraceae lectin (frutalin)-affinity chromatography and data-independent label-free mass spectrometric analysis. As result, 57,016 peptides and 4,175 proteins among all samples were identified. From this, forty proteins present in unbound (PI – proteins that not interacted with lectin) and bound (PII – proteins that interacted with lectin) fractions, were differentially expressed. High levels of apolipoprotein A-II were detected here that were elevated significantly in the early and advanced stages of the disease. Apolipoprotein C-III was detected in both fractions, and its level was increased slightly in the PI fraction of patients with early-stage breast cancer and expressed at higher levels in the PII fraction of patients with early and intermediate stages. Clusterin was present at higher levels in both fractions of patients with early and intermediate stages breast cancer. Our findings reveal a correlation between alterations in protein glycosylation, lipid metabolism, and the progression of breast cancer.
Project description:This study demonstrates how the latest UHPLC (ultra-high-performance liquid chromatography) technology can be combined with high-resolution accurate-mass (HRAM) mass spectrometry (MS) and long columns packed with fully porous particles to improve bottom-up proteomics analysis with nano-flow liquid chromatography mass-spectrometry (nanoLCMS) methods. The increased back pressures from the UHPLC system enabled the use of 75 µm I.D. x 75 cm columns packed with 2 µm particles at a typical 300 nL/min flow rate as well as elevated and reduced flow rates. The constant pressure pump operation at 1500 bar reduced sample loading and column washing/equilibration stages and overall overhead time that maximizes MS utilization time. The versatility of flow rate optimization to balance the sensitivity, throughput with sample loading amount, and capability of using longer gradients contribute to a greater number of peptide and protein identifications for single-shot bottom-up proteomics experiments. The routine proteome profiling and precise quantification of >7,000 proteins with single-shot nanoLC-MS analysis open possibilities for large-scale discovery studies with deep dive into the protein level alterations.