NDLI: Genome-wide analysis of lectins in cyanobacteria: from evolutionary mode to motif patterns

Content Provider	Springer Nature : BioMed Central
Author	Xu, Tongli Cui, Yulin Qin, Song Wang, Yin-Chu
Abstract	Lectins are glycoproteins that can bind to specific carbohydrates, and different lectin families exhibit different biological activities. They are also present in the cyanobacteria and many of them have shown excellent therapeutic effect, which deserve for bioprospecting. However, in comparison to those from terrestrial plants, the current knowledge on cyanobacterial lectins is very limited. To this end, genome-wide analyses were performed to find out their evolutionary mode and motif patterns in 316 genomes of representative taxa. In results, 196 putative cyanobacterial lectins were dig out and 105 of them were classified into known families. Seven lectins were found to be belonged to distinct two lectin families, and they may have the potential activities of both lectin families. Whereas no MFP-2, Chitin, and Nictaba family lectins were found. What’s more, the Legume lectin-like lectin family was found to be the richest and most complex in cyanobacteria, which could be a main research direction for future cyanobacterial lectin bioprospecting and development. Our classification and prediction of cyanobacteria lectins is expected to provide assistance in the development of lectin-based medicine and provide solutions to the current thorny viral and tumor diseases in humans.
Related Links	https://bmcgenomics.biomedcentral.com/counter/pdf/10.1186/s12864-023-09790-8.pdf
Ending Page	8
Page Count	8
Starting Page	1
File Format	HTM / HTML
ISSN	14712164
DOI	10.1186/s12864-023-09790-8
Journal	BMC Genomics
Issue Number	1
Volume Number	24
Language	English
Publisher	BioMed Central
Publisher Date	2023-11-16
Access Restriction	Open
Subject Keyword	Life Sciences Microarrays Proteomics Animal Genetics and Genomics Microbial Genetics and Genomics Plant Genetics and Genomics Lectin Gene family Evolution Cyanobacteria Motif
Content Type	Text
Resource Type	Article
Subject	Biotechnology Genetics
Journal Impact Factor	3.5/2023
5-Year Journal Impact Factor	4.1/2023

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