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:Recombinant proteins are of great interest in glycobiology and proteomics, known especially for their reproducibility and accessibility. However, variation in glycosylation among recombinant glycoproteins is not well understood and may depend on numerous conditions in the biomanufacturing process. In order to confidently assess variation in glycosylation measurements, it is vital to both optimize the measurement of, and determine the degree of variation between, distributions of glycosylation on specific sites of glycoproteins. This is especially important for glycoproteins that are known to have rapid sequence changes, such as with different influenza strains. In this study, eight strains of recombinant influenza hemagglutinin and neuraminidase produced from HEK293 cell line were obtained from four vendors and digestion was conducted using a series of complex multi-enzymatic methods designed to isolate glycopeptide sequons. Site-specific glycosylation profiles of intact glycopeptides were produced using mass spectrometric evaluation on an orbitrap system and compared using spectral similarity scores. Variation in glycan abundances and distribution was most pronounced between different strains of virus (similarity score = 383 out of 1000), whereas replicates resulted in low variation (similarity score = 957 out of 1000). Glycan variation was also measured based on differences between vendors, lots, batches, protease digestion, and intra-protein site. The most abundant glycans in all of these influenza glycoproteins were monofucosylated and complex, as reported by other laboratories. However, it was found that different vendors can produce very different glycan distributions for the same glycosylation site. Notably, it is demonstrated that glycan distributions are similar for conserved regions of influenza glycoproteins. Overall, these methods present a potential use in developing reproducible measurements of glycosylated biologics for quality control or making more informed decisions in biomanufacturing.
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:In recent years, high-throughput technologies have contributed to development a more precise picture of the human proteome. However, 2,129 proteins remain listed as missing proteins (MPs) in the newest neXtProt release (2019-02). The main reasons for MPs are a low abundance, low-molecular-weight (LMW), unexpected modifications, membrane characteristics, etc. Moreover, more than 50% of the MS/MS data have not been successfully identified in shotgun proteomics. Open-pFind, an efficient open search engine, recently released by the pFind group in China, presents an opportunity to identify these buried MPs in complex samples. Proteins and potential MPs were identified using Open-pFind and three other search engines to compare their performance and efficiency with three large-scale datasets digested by different enzymes. Our results demonstrated that Open-pFind identified 29.9-47.5% more peptide-spectrum matches (PSMs), 48.0-63.9% more peptides sequences (with modifications) and 22.7-38.1% more peptide sequences (regardless of modifications) than those identified by the second-best search engine. As a result, Open-pFind detected 7.5-19.3% more candidate MPs than those by the second-best search engine. In total, 5 (PE2) of the 150 candidate MPs identified by Open-pFind were verified from two unique peptides containing more than 9 amino acids (AA) by using spectrum theoretical prediction with pDeep, and synthesized peptide matching with pBuild, after spectrum quality analysis, isobaric post-translational modification, and single amino acid variant (SAAV) filtering. These five verified MPs can be ranked in the PE1 level. In addition, three other candidate MPs were verified with two unique peptides (one peptide containing more than 9 AA) and the other containing only 8 AA), which were slightly lower than the criteria listed by C-HPP, and required additional verification information. More importantly, unexpected modifications were detected in these MPs. Another 141 MPs were listed as candidates, but required additional verification information.
Project description:Denisovans are an extinct hominin group defined by ancient genomes of Middle to Late Pleistocene fossils from southern Siberia. Although genomic evidence suggests their widespread distribution throughout eastern Asia and possibly Oceania, so far only a few fossils from the Altai and Tibet are confidently identified molecularly as Denisovan. We identified a hominin mandible (Penghu 1) from Taiwan (10,000 to 70,000 years ago or 130,000 to 190,000 years ago) as belonging to a male Denisovan by applying ancient protein analysis. We retrieved 4241 amino acid residues and identified two Denisovan-specific variants. The increased fossil sample of Denisovans demonstrates their wider distribution, including warm and humid regions, as well as their shared distinct robust dentognathic traits that markedly contrast with their sister group, Neanderthals.
Project description:We developed an optimized multi-shot proteomics workflow based on high-resolution offline high pH reversed-phase peptide separation of high peptide loads collecting many fractions that were in turn analyzed by short online chromatographic separations and fast peptide sequencing using orbitrap tandem mass spectrometry.
Project description:In order to identify more MPs and get deeper proteomic data of testis. We applied high-pH reverse phase (RP) HPLC to fractionate complex samples.On the other hand, to enhance protein coverage, multi-protease strategies were used for 10% SDS-PAGE short separation samples.
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 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: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.