Discerning of Antimicrobial peptides (AMPs) from whole genome sequenced tropical and subtropical fruit crops

Recent outbreaks of infectious diseases caused by multidrug-resistant organisms have served as a stark reminder of the urgent need for novel antimicrobial medicines to protect public health. Anti-microbial peptides (AMPs) have attracted a lot of interest over the last thirty years because of their unique membrane-active antimicrobial mechanism and broad-spectrum activity. These AMPs have a wide range of applications in different fields. It is considered as cationic host defence peptides, anionic antimicrobial peptides/proteins, cationic amphipathic peptides, host defence peptides and alpha-helical antimicrobial peptides. They can protect against a variety of infection-causing organisms, such as bacteria, fungi, parasites, viruses, and tumour cells, and they also have immunomodulatory effects. In the present research, the whole genome sequenced tropical and subtropical fruit crops such as mango, jack, carambola, ber and date palm were selected for the identification of anti-microbial peptides. The whole-genome sequence (WGS) was annotated with the DRAMP database for the retrieval of active anti-microbial peptides. The potential anti-microbial peptides were retrieved in two ways through BLAST and Macrel prediction. Predicted AMPs through both the tools were taken into physicochemical property calculation such as net charge, length of sequence /peptide, hydrophobicity, iso-electric point and amphiphilicity index with the use of the DBAASP database. Based on physicochemical properties calculations the anti-microbial properties were comparatively analyzed and many predicted AMPs had the potential to be utilized against various targets. The study resulted in identifying 44,774 potential AMPs from the selected five tropical and subtropical fruit crops. All the Data from the analysis are stored in the public domain of the Mendeley website. Anyone can access further studies that may result in green technology in controlling diseases both for plants and animals, including human beings.

由多重耐药微生物引发的近期传染病暴发，已为公共卫生防护敲响警钟，凸显了研发新型抗菌药物的迫切性。抗菌肽（Anti-microbial Peptides, AMPs）因独特的膜靶向抗菌机制与广谱抗菌活性，在近三十年来受到广泛关注。此类抗菌肽应用场景覆盖多个领域，可被归类为阳离子宿主防御肽、阴离子抗菌肽/蛋白、阳离子两亲肽、宿主防御肽以及α螺旋抗菌肽。它们可抵御多种致病微生物，包括细菌、真菌、寄生虫、病毒与肿瘤细胞，同时具备免疫调节活性。
本研究选取全基因组已测序的热带、亚热带果树作物（包括芒果、波罗蜜、杨桃、枣与海枣）用于抗菌肽的挖掘鉴定。全基因组序列（Whole Genome Sequence, WGS）通过DRAMP数据库进行注释，以检索活性抗菌肽。潜在抗菌肽通过BLAST与Macrel预测两种方式完成检索。利用DBAASP数据库，对两种工具预测得到的抗菌肽开展理化性质计算，涵盖净电荷、肽段长度、疏水性、等电点以及两亲性指数。基于理化性质计算结果，对抗菌活性进行对比分析，结果显示多数预测得到的抗菌肽具备针对多种致病靶点的应用潜力。
本研究从上述5种热带、亚热带果树中共鉴定得到44774条潜在抗菌肽。全部分析数据已上传至Mendeley平台的公开数据集库，任何研究者均可基于此开展后续研究，有望开发出可用于防控植物、动物（包括人类）疾病的绿色技术。