Computational protocol: Comparative Proteomic Analysis of Hymenolepis diminuta Cysticercoid and Adult Stages

Similar protocols

Protocol publication

[…] For in-gel digestion we used three biological replicates of the adult worms (three adults worms at the same age) and two biological replicates for cysticercoids (cysticercoids in the same age ± 2 days, and minimum 2,000 cysticercoids in each sample). These protein samples were used to obtain three repetitive gels. The stained gel lanes representing each sample (replicate) were cut out in small pieces for in-gel tryptic digestion and LC-MS/MS identification. The gel protein profiles in each three replica gels were comparable. Protein concentration for both developmental stages was 10 μg/ml.Cysticercoid and adult tapeworm somatic proteins of H. diminuta, separated from each other by developmental stage, were cleaned using the PlusOne SDS-PAGE Clean-Up Kit (GE Healthcare, USA). Protein samples were applied to a 12% polyacrylamide gel for 1-DE separation using 1 × TGS (0.025 M Tris, 0.192 M Glycine and 0.1% SDS) as the running buffer in denaturing conditions. To estimate the molecular weight of the proteins, a pre-stained protein standard broad-range marker (Bio-Rad, USA) was loaded on the same gel. The polyacrylamide gel was placed in a Midi-Protean Tera Cell (Bio-Rad, USA) electrophoresis apparatus. Electrophoresis was performed at 200 V constant voltage for 45 min. Separated proteins were stained with a Silver Staining Kit according to the manufacturer's protocol (Krzysztof Kucharczyk Techniki Elektroforetyczne, Poland). To digitize and analyse the repetitiveness of the protein profiles on 1-DE gels, we applied GS-800 Densitometer (Bio-Rad, USA) combined with 1-D Analysis Software Quantity 1 (Bio-Rad, USA). Gel fragments were excised manually from the repetitive gels selected lanes of the stained 1-DE. The whole silver-stained lanes were cut out, including the unstained gel regions between protein bands. Gels and the gel pieces were subjected to in-gel tryptic digestion and liquid chromatography and tandem mass spectrometry (LC-MS/MS) identification. In-gel tryptic digestion was performed by rehydration of the gel pieces with acetonitrile (ACN), reduction with 10 mM DTT in 100 mM NH4HCO3 for 30 min in 57°C and alkylation with 0.5 M iodoacetamide in 100 mM NH4HCO3 (45 min in dark at room temperature). The reduced and alkylated proteins were digested overnight with 10 ng/μl trypsin in 25 mM NH4HCO3 (Promega) at 37°C.The recovered and purified peptide samples (20 μl in total) were subjected to LC-MS/MS identification. Samples were concentrated and desalted on a RP-C18 pre-column (Waters) and further peptide separation was achieved on a nano-Ultra Performance Liquid Chromatography (UPLC) RP-C18 column (Waters, BEH130 C18 column, 75 μm i.d., 250 mm long) of a nanoACQUITY UPLC system, using a 45-min linear ACN gradient. Column outlet was directly coupled to the Electrospray ionization (ESI) ion source of the Orbitrap Velos type mass spectrometer (Thermo), working in the regime of data-dependent MS to MS/MS switch with HCD-type peptide fragmentation. An electrospray voltage of 1.5 kV was used. Raw data files were pre-processed with Mascot Distiller software (version, MatrixScience). The obtained peptide masses and fragmentation spectra were matched to the National Center for Biotechnology Information (NCBI) non-redundant database NCBInr 20140305 (37,425,594 sequences; 13,257,553,858 residues) with a Cestoda filter using the Mascot search engine (Mascot Daemon v. 2.4.0, Mascot Server v. 2.4.1, MatrixScience). The following search parameters were applied: enzyme specificity was set to trypsin, peptide mass tolerance to ±30 ppm and fragment mass tolerance to ±0.1 Da. The protein mass was left as unrestricted and mass values as monoisotopic with one missed cleavage being allowed. Alkylation of cysteine by carbamidomethylation as fixed and oxidation of methionine was set as a variable modification. [...] Protein identification was performed using the Mascot Search Engine (MatrixScience) with the probability-based algorithm. Multidimensional protein Identification Technology-type (MudPIT-type) and the highest number of peptide sequences (or both) were selected. The expected value threshold of 0.05 was used for analysis, which means that all peptide identifications had a <1 in 20 chance of being a random match.Identified proteins were categorized by their molecular function, cellular component and biological processes according to gene ontology information obtained from UniProtKB ( and QuickGO ( databases. […]

Pipeline specifications

Software tools Mascot Distiller, Mascot Server, QuickGO
Databases UniProt UniProtKB ExPASy
Application MS-based untargeted proteomics
Organisms Homo sapiens, Caenorhabditis elegans, Hymenolepis diminuta, Tenebrio molitor, Rattus norvegicus
Diseases Hymenolepiasis, Multiple Sclerosis