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Research article - Peer-reviewed, 2020

A knowledge-driven protocol for prediction of proteins of interest with an emphasis on biosynthetic pathways

Joshi AG, Harini K, Meenakshi I, Shafi KM, Pasha SN, Mahita J, Sajeevan RS, Karpe SD, Ghosh P, Nitish S, Gandhimathi A, Mathew OK, Prasanna SH, Malini M, Mutt E, Naika M, Ravooru N, Rao RM, Shingate PN, Sukhwal A, Sunitha MS, Upadhyay AK, Vinekar RS, Sowdhamini R

Abstract

This protocol describes a stepwise process to identify proteins of interest from a query proteome derived from NGS data. We implemented this protocol on Moringa oleifera transcriptome to identify proteins involved in secondary metabolite and vitamin biosynthesis and ion transport. This knowledge-driven protocol identifies proteins using an integrated approach involving sensitive sequence search and evolutionary relationships. We make use of functionally important residues (FIR) specific for the query protein family identified through its homologous sequences and literature. We screen protein hits based on the clustering with true homologues through phylogenetic tree reconstruction complemented with the FIR mapping. The protocol was validated for the protein hits through qRT-PCR and transcriptome quantification. Our protocol demonstrated a higher specificity as compared to other methods, particularly in distinguishing cross-family hits. This protocol was effective in transcriptome data analysis of M. oleifera as described in Pasha et al.
• Knowledge-driven protocol to identify secondary metabolite synthesizing protein in a highly specific manner.

• Use of functionally important residues for screening of true hits.

• Beneficial for metabolite pathway reconstruction in any (species, metagenomics) NGS data.

Published in

MethodsX
2020, volume: 7, article number: 101053
Publisher: Elsevier {BV}

Authors' information

Joshi, Adwait G.
National Centre for Biological Sciences (NCBS)
Harini, K.
National Centre for Biological Sciences (NCBS)
Iyer, Meenakshi S.
National Centre for Biological Sciences (NCBS)
Shafi, K. Mohamed
National Centre for Biological Sciences (NCBS)
Pasha, Shaik Naseer
National Centre for Biological Sciences (NCBS)
Mahita, Jarjapu
National Centre for Biological Sciences (NCBS)
National Centre for Biological Sciences (NCBS)
Karpe, Snehal D.
National Centre for Biological Sciences (NCBS)
Ghosh, Pritha
National Centre for Biological Sciences (NCBS)
Sathyanarayanan, Nitish
National Centre for Biological Sciences (NCBS)
Gandhimathi, A.
National Centre for Biological Sciences (NCBS)
Mathew, Oommen K.
Tata Institute of Fundamental Research (TIFR)
Prasanna, Subramanian Hari
National Centre for Biological Sciences (NCBS)
Malini, Manoharan
National Centre for Biological Sciences (NCBS)
Mutt, Eshita
National Centre for Biological Sciences (NCBS)
Naika, Mahantesha B. N.
National Centre for Biological Sciences (NCBS)
Ravooru, Nithin
National Centre for Biological Sciences (NCBS)
Rao, Rajas M.
National Centre for Biological Sciences (NCBS)
Shingate, Prashant N.
National Centre for Biological Sciences (NCBS)
Sukhwal, Anshul
National Centre for Biological Sciences (NCBS)

UKÄ Subject classification

Bioinformatics (Computational Biology)

Publication Identifiers

DOI: https://doi.org/10.1016/j.mex.2020.101053

URI (permanent link to this page)

https://res.slu.se/id/publ/120205