Project PXD010753

PRIDE Assigned Tags:
Biological Dataset Biomedical Dataset



Proteomics of Asrij perturbed Drosophila lymph glands as a resource for identification of new regulators of hematopoiesis


Hematological disorders result in perturbed homeostasis of the blood system. However, a comprehensive understanding of how physiological and genetic mechanisms regulate blood cell precursor maintenance and differentiation is lacking. Owing to simplicity and ease of genetic analysis, the Drosophila melanogaster lymph gland (LG) is an excellent model to study hematopoiesis. The LG is a multi-lobed structure compartmentalized into precursor and differentiation zones whose geography and identity is regulated by multiple signalling pathways. While additional molecular and functional subtypes are expected there is a paucity of information on gene expression and regulation of hemocyte homeostasis. Hence, we quantitatively analyzed the LG proteome under conditions that maintain precursors or promote their differentiation in vivo, by perturbing expression of Asrij, a conserved endosomal regulator of hematopoiesis. Although technically demanding, we pooled samples obtained from 1500 larval dissections per genotype and using iTRAQ quantitative proteomics, determined the relative expression levels of polypeptides in Asrij knockout (KO) and overexpressing (OV) LGs in comparison to wild type (control). Mass spectrometry data analysis showed that at least 6.5% of the Drosophila proteome is expressed in wild type LGs.Of 2,133 proteins identified, 780 and 208 proteins were common to the previously reported cardiac tube and hemolymph proteomes, respectively, resulting in the identification of 1238 proteins exclusive to the LG. Perturbation of Asrij levels led to differential expression of 619 proteins, of which 23% have human homologs implicated in various diseases. Proteins regulating metabolism, immune system, signal transduction and vesicle-mediated transport were significantly enriched. Immunostaining of representative candidates from the enriched categories and previous reports confirmed 75% of our results and validated the LG proteome. Our study provides, for the first time, an in vivo proteomics resource for identifying novel regulators of hematopoiesis that will also be applicable to understanding vertebrate blood cell development.

Sample Processing Protocol

Lymph gland samples were dissected from third larvae instar and stored at -80 ⁰C. 1500 lymph glands of desired genotype were lysed in 0.5% SDS, homogenized by sonication and centrifuged at 13,000 rpm for 10 minutes at 4 ⁰C followed by protein estimation of the supernatants using bicinchoninic acid (BCA) assay (Pierce, Thermo Scientific) for normalization on gel. Equivalent amounts of protein quantified spectrophotometrically from each sample was reduced and alkylated and then subjected to trypsin digestion (Sequencing Grade Modified Trypsin, Promega Catalog No.:V511A) in an enzyme to substrate ratio of 1:20 (w/w) at 37 ⁰C for 16 hours. Resulting peptides were labeled with iTRAQ reagents as per the manufacturer's protocol and further processed for fractionation. Tandem mass spectrometric analysis of the iTRAQ labeled peptides was carried out using LTQ-Orbitrap Velos mass spectrometer (Thermo Scientific, Bremen, Germany) interfaced with Easy nanoLC II (previously Proxeon, Thermo Scientific, Bremen, Germany). The nanospray ionization source of the mass spectrometer was fitted with a 10 µm emitter tip (New Objective, Woburn, MA) and maintained at 2000 V ion spray voltage. Peptide samples were loaded onto an enrichment column (2 cm × 75μ, Magic AQ C18 material 5μ particle size, 100 Å pore size) in 0.1% formic acid, 5% acetonitrile for 15 min and peptide separation was carried out on analytical column (10 cm × 75μ, Magic AQ C18 material C18 material 5μ particle size, 100 Å pore size) using a linear gradient of 7-35% solvent B (90% acetonitrile in 0.1% formic acid) for 60 minutes at a constant flow rate of 350 nl/minute. Data was acquired using Xcalibur 2.1 (Thermo Scientific, Bremen, Germany) in a data-dependent manner in the m/z range of 350 to 1800 at a mass resolution of 60,000 at 400 m/z at the MS level and 15,000 at 400 m/z at MS/MS level by targeting the top 20 abundant ions for fragmentation using higher energy collisional dissociation at 39% normalized collision energy. The dynamic exclusion option was enabled during data acquisition with exclusion duration of 60 seconds. Lock mass option was enabled for real time calibration using polycyclodimethylsiloxane (m/z, 415.12) ions.

Data Processing Protocol

Raw MS files from the mass spectrometer were peak processed and fed to SEQUEST and MASCOT (version 2.4.1) search engines in the Proteome Discoverer version 2.0 suite (Thermo Fisher Scientific, USA) and compared against the Drosophila melanogaster protein database (release 70, FlyBase, 30, 513 entries) appended with the known contaminants. A precursor mass range of 600-5000 Da and a signal to noise of 1.5 was used for the searches. Enzyme specificity was set to trypsin, allowing for a maximum of one missed cleavage. Variable (oxidation of methionine and phosphorylation of serine, threonine and tyrosine) and fixed (alkylation of cysteine; iTRAQ labelling at N-terminus of the peptide and lysine) modifications were selected. Mass tolerance was set to 15 ppm and 0.1 Da for precursor and fragment ions, respectively. Peptide lists were filtered to remove known contaminants such as BSA and human keratin proteins. To maximize the coverage of identifications, 1% FDR cut-off was used for all the identifications as calculated by percolator algorithm using decoy search approach. Data analysis was performed using custom scripts in R language.


Keshava Prasad T. S., Institute of Bioinformatics, Bangalore, Karnataka, India.
Keshava Prasad, Institute of Bioinformatics, International Technology Park, Bangalore 560066 ( lab head )

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