Comprehensive genome data analysis of Pseudomonas benzopyrenica Ch9-16 Isolated from chili powder

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-05-12 DOI:10.1016/j.dib.2025.111634

Mayra Paola Mena Navarro , Merle Ariadna Espinosa Bernal , Ana Laura Vega Rodríguez , Daniel Alejandro Ferrusca Bernal , Juan Enrique de Jesús López , María Carlota García Gutiérrez , Karla Isabel Lira de León , Miguel Angel Ramos López , Aldo Amaro Reyes , José Alberto Rodríguez Morales , Héctor Pool , Carlos Guzmán Martínez , Erika Álvarez Hidalgo , Juan Campos Guillén

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引用次数: 0

Abstract

We provide a comprehensive genome analysis of Pseudomonas benzopyrenica Ch9–16, a bacterial strain isolated from chili powder processed in Fresnillo, Zacatecas, Mexico. The genome was sequenced using the Illumina NovaSeq platform. Bioinformatic analyses, including assembly and annotation, were conducted on the BV-BRC platform. The genome, comprising 18 contigs and approximately 5.3 million base pairs with a GC content of 65.19 % and 4854 protein-coding sequences. Analysis identified multiple antibiotic resistance genes (ARGs) and virulence genes. This genome data serves as a valuable resource for understanding this bacterial specie and contributes to the database of microorganisms isolated from chili powder. The genome data was deposited at National Center for Biotechnology Information (NCBI) under accession number Bioproject ID PRJNA1062060, Bio Sample ID SAMN45486407. The genome accession number was JBLHDL000000000.

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辣椒粉中苯并芘假单胞菌Ch9-16的基因组数据分析

我们对苯并芘假单胞菌Ch9-16进行了全面的基因组分析，这是一种从墨西哥萨卡特卡斯州Fresnillo加工的辣椒粉中分离出来的细菌菌株。基因组测序使用Illumina NovaSeq平台。在BV-BRC平台上进行生物信息学分析，包括组装和注释。该基因组包含18个contigs，约530万个碱基对，GC含量为65.19%，共有4854个蛋白编码序列。分析鉴定出多种抗生素耐药基因和毒力基因。该基因组数据为了解该细菌种类提供了宝贵的资源，并有助于建立从辣椒粉中分离的微生物数据库。基因组数据保存在国家生物技术信息中心（NCBI），登录号为Bioproject ID PRJNA1062060， Bio Sample ID SAMN45486407。基因组加入号为JBLHDL000000000。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.