Bioinformatics approaches in upgrading microalgal oil for advanced biofuel production through hybrid ORF protein construction

Ihtesham Arshad, Muhammad Ahsan, Imran Zafar, Muhammad Sajid, Sheikh Arslan Sehgal, Waqas Yousaf, Amna Noor, Summya Rashid, Somenath Garai, Meivelu Moovendhan, Rohit Sharma

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Microalgae are promising for biofuel production due to their high oil content and fast biomass growth, but increasing their oil content is essential for economic viability. In this study, we conducted in silico investigations to identify oil-producing genes in various microalgal species. We selected six genes from different species: ACCD and F751_4275 from Chlorella protothecides, C2E21_7193 and C2E21_2849 from Chlorella sorokiniana, and COO60DRAFT_1295191 and COO60DRAFT_1481410 from Scenedesmus sp. We utilized the NCBI genome database and performed BLASTp analysis to identify these genes’ superfamilies (PLN02349, DUF212, BKR SDR, PRK08591, ACCD, and SET LSMT). The open reading frames (ORFs) of the selected genes were analyzed using the ORF Finder tool to determine their lengths and the locations of their start and stop codons. Based on this analysis, we constructed two hybrid ORFs by combining the ORFs from different genes. Hybrid ORF 1 had a length of 5166 base pairs, while hybrid ORF 2 was 3516 base pairs long. The thermodynamic evaluation was performed on these hybrid ORFs to assess their stability and GC content. We translated the hybrid ORF sequences into protein sequences using the Translate feature of Expasy. Tertiary structure predictions and bioinformatics approaches were employed to analyze the permissible regions for amino acid dihedral angles, providing insights into the potential functionality of these hybrid ORF proteins. The results of this study indicated that both hybrid ORFs have the potential to produce high lipid contents, making them promising candidates for biofuel production. However, it is essential to conduct further in vitro experiments to validate the functionality of these hybrid proteins. Our study contributes to understanding oil-producing genes in microalgae and their potential applications in the biofuel and pharmaceutical industries. The identified genes and hybrid ORFs provide valuable insights into microalgae species’ genetic manipulation and biology, paving the way for advancements in renewable energy and other biotechnological applications. Graphical Abstract: [Figure not available: see fulltext.]

Original languageEnglish
JournalBiomass Conversion and Biorefinery
DOIs
StateAccepted/In press - 2023

Keywords

  • Biofuel production
  • Bioinformatics
  • Clone designing
  • Hybrid ORFs
  • In silico analysis
  • Microalgae
  • Open reading frames
  • Protein structure prediction

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