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The power of three in cannabis shotgun proteomics: proteases, databases and search engines.

ABSTRACT: Cannabis research has taken of since the relaxation of the legislation, yet proteomics is still lagging behind. Last year we published three proteomics methods aiming at optimizing protein extraction (Vincent et al Molecules 2019), protein digestion (Vincent et al IJMS 2019) for bottom-up and middle-down proteomics, as well as the analysis of intact proteins for top-down proteomics (Vincent et al Proteomes 2019). The database of Cannabis sativa proteins used in these studies was retrieved from the reference repositories for proteins UniProt which is incomplete and therefore underrepresents the genetic diversity of this species. In this fourth study, we remedy this shortcoming by searching larger databases from various sources. We also compare two search engines, the oldest SEQUEST, and the most popular Mascot. This shotgun proteomics experiment is also utilizing the power of parallel digestions with orthogonal proteases of increasing selectivity, namely chymotrypsin, trypsinLys-C and Asp-N. Our results show that, as expected, the larger the databases the greater the list of accessions identified but the longer the duration of the search. Using orthogonal proteases and different search algorithms increases the total number of proteins identified, most of them common among proteases and algorithms, but many of them unique as well. doi:10.3390/proteomes8020013

INSTRUMENT(S): nLC-ESI-LTQ-Orbitrap mass analyser

ORGANISM(S): Cannabis Sativa (marijuana)

SUBMITTER: Delphine Vincent

PROVIDER: MSV000085379 | MassIVE | Tue May 05 19:26:00 BST 2020

REPOSITORIES: MassIVE

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Project description:Earlier this year we published a method article aimed at optimising protein extraction from mature buds of medicinal cannabis for trypsin-based shotgun proteomics (Vincent, D., et al. Molecules 2019, 24, 659). We then developed a top-down proteomics (TDP) method (Vincent, D., et al. Proteomes 2019, 7, 33). This follow-up study aims at optimising the digestion of medicinal cannabis proteins for identification purposes by bottom-up and middle-down proteomics (BUP and MDP). Four proteases, namely a mixture of trypsin/LysC, GluC, and chymotrypsin, which target different amino acids (AAs) and therefore are orthogonal and cleave proteins more or less frequently, were tested both on their own as well as sequentially or pooled, followed by nLC-MS/MS analyses of the peptide digests. Bovine serum albumin (BSA, 66 kDa) was used as a control of digestion efficiency. With this multiple protease strategy, BSA was reproducibly 97% sequenced, with peptides ranging from 0.7 to 6.4 kD containing 5 to 54 AA residues with 0 to 6 miscleavages. The proteome of mature apical buds from medicinal cannabis was explored more in depth with the identification of 27,123 peptides matching 494 unique accessions corresponding to 229 unique proteins from Cannabis sativa and close relatives, including 130 (57%) additional annotations when the list is compared to that of our previous BUP study (Vincent, D., et al. Molecules 2019, 24, 659). Almost half of the medicinal cannabis proteins were identified with 100% sequence coverage, with peptides composed of 7 to 91 AA residues with up to 9 miscleavages and ranging from 0.6 to 10 kDa, thus falling into the MDP domain. Many post-translational modifications (PTMs) were identified, such as oxidation, phosphorylations, and N-terminus acetylations. This method will pave the way for deeper proteome exploration of the reproductive organs of medicinal cannabis, and therefore for molecular phenotyping within breeding programs. doi:10.3390/ijms20225630

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The power of three in cannabis shotgun proteomics: proteases, databases and search engines.

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