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Genome-wide identification, classification, and expression profiling of serine esterases and other esterase-related proteins in the tobacco hornworm, Manduca sexta.

Zelong MiaoChao XiongXiaolong CaoTisheng ShanQiao JinHaobo Jiang
Published in: Insect science (2022)
Serine esterases (SEs) are hydrolases that catalyze the conversion of carboxylic esters into acids and alcohols. Lipases and carboxylesterases constitute two major groups of SEs. Although over a hundred of insect genomes are known, systematic identification and classification of SEs are rarely performed, likely due to large size and complex composition of the gene family in each species. Considering their key roles in lipid metabolism and other physiological processes, we have categorized 144 M. sexta SEs and SE homologs (SEHs), 114 of which contain a motif of GXSXG. Multiple sequence alignment and phylogenetic tree analysis have revealed 39 neutral lipases (NLs), 3 neutral lipase homologs (NLHs), 11 acidic lipases (ALs), 3 acidic lipase homologs (ALHs), a lipase-3, a triglyceride lipase, a monoglyceride lipase, a hormone-sensitive lipase, and a GDSL lipase. Eighty-three carboxylesterase genes encode 29 α-esterases (AEs), 12 AEHs (e.g., SEH4-1-3), 20 feruloyl esterases (FEs), 2 FEHs, 2 β-esterases (BEs), 2 integument esterases (IEs), 1 IEH, 4 juvenile hormone esterases, 2 acetylcholinesterases, gliotactin, 6 neuroligins, neurotactin, and an uncharacteristic esterase homolog. In addition to these GXSXG proteins, we have identified 26 phospholipases and 13 thioesterases. Expression profiling of these genes in specific tissues and stages has provided insights into their functions including digestion, detoxification, hormone processing, neurotransmission, reproduction, and developmental regulation. In summary, we have established a framework of information on SEs and related proteins in M. sexta to stimulate their research in the model species and comparative investigations in agricultural pests or disease vectors.
Keyphrases
  • genome wide identification
  • genome wide
  • transcription factor
  • machine learning
  • deep learning
  • bioinformatics analysis
  • healthcare
  • heavy metals
  • zika virus
  • social media
  • dna methylation
  • aedes aegypti