scholarly journals BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters

2017 ◽  
Author(s):  
Gong Cheng ◽  
Quan Lu ◽  
Ling Ma ◽  
Guocai Zhang ◽  
Liang Xu ◽  
...  
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Gene Clusters ◽  
Biological Research ◽  
Biological Databases ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Bioinformatics Tools ◽  
Bioinformatics Workflow ◽  
Bioinformatics Community

Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists, and thus its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, governmental, and private owners in Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker to analyze and visualize pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various public biological databases. This step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.

scholarly journals BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3948 ◽  
Author(s):  
Gong Cheng ◽  
Quan Lu ◽  
Ling Ma ◽  
Guocai Zhang ◽  
Liang Xu ◽  
...  
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Gene Clusters ◽  
Biological Research ◽  
Biological Databases ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Bioinformatics Tools ◽  
Bioinformatics Workflow ◽  
Bioinformatics Community

Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists; accordingly, its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and to promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, government sources, and private owners in the Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker. The present workflow enables analysis and visualization of pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various publicly available biological databases. The present step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.

scholarly journals BGDMdocker: a Docker workflow for data mining and visualization of bacterial pan-genomes and biosynthetic gene clusters

2017 ◽  
Author(s):  
Gong Cheng ◽  
Quan Lu ◽  
Ling Ma ◽  
Guocai Zhang ◽  
Liang Xu ◽  
...  
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Gene Clusters ◽  
Biological Research ◽  
Biological Databases ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Bioinformatics Tools ◽  
Bioinformatics Workflow ◽  
Bioinformatics Community

Recently, Docker technology has received increasing attention throughout the bioinformatics community. However, its implementation has not yet been mastered by most biologists, and thus its application in biological research has been limited. In order to popularize this technology in the field of bioinformatics and promote the use of publicly available bioinformatics tools, such as Dockerfiles and Images from communities, governmental, and private owners in Docker Hub Registry and other Docker-based resources, we introduce here a complete and accurate bioinformatics workflow based on Docker to analyze and visualize pan-genomes and biosynthetic gene clusters of bacteria. This provides a new solution for bioinformatics mining of big data from various public biological databases. This step-by-step guide creates an integrative workflow through a Dockerfile to allow researchers to build their own Image and run Container easily.

Expanding the Natural Products Heterologous Expression Repertoire in the Model Cyanobacterium Anabaena sp. Strain PCC 7120: Production of Pendolmycin and Teleocidin B-4

2019 ◽  
Author(s):  
Patrick Videau ◽  
Kaitlyn Wells ◽  
Arun Singh ◽  
Jessie Eiting ◽  
Philip Proteau ◽  
...  
Keyword(s):  
Natural Products ◽  
Genome Mining ◽  
Gene Clusters ◽  
Combinatorial Biosynthesis ◽  
Test Case ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Cyanobacterium Anabaena ◽  
Anabaena Sp ◽  
Pcc 7120

Cyanobacteria are prolific producers of natural products and genome mining has shown that many orphan biosynthetic gene clusters can be found in sequenced cyanobacterial genomes. New tools and methodologies are required to investigate these biosynthetic gene clusters and here we present the use of <i>Anabaena </i>sp. strain PCC 7120 as a host for combinatorial biosynthesis of natural products using the indolactam natural products (lyngbyatoxin A, pendolmycin, and teleocidin B-4) as a test case. We were able to successfully produce all three compounds using codon optimized genes from Actinobacteria. We also introduce a new plasmid backbone based on the native <i>Anabaena</i>7120 plasmid pCC7120ζ and show that production of teleocidin B-4 can be accomplished using a two-plasmid system, which can be introduced by co-conjugation.

scholarly journals Global biogeographic sampling of bacterial secondary metabolism

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Zachary Charlop-Powers ◽  
Jeremy G Owen ◽  
Boojala Vijay B Reddy ◽  
Melinda A Ternei ◽  
Denise O Guimarães ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Genome Sequencing ◽  
Geographic Distance ◽  
Gene Clusters ◽  
Natural World ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Road Map ◽  
Two Factors ◽  
Natural Products Discovery

Recent bacterial (meta)genome sequencing efforts suggest the existence of an enormous untapped reservoir of natural-product-encoding biosynthetic gene clusters in the environment. Here we use the pyro-sequencing of PCR amplicons derived from both nonribosomal peptide adenylation domains and polyketide ketosynthase domains to compare biosynthetic diversity in soil microbiomes from around the globe. We see large differences in domain populations from all except the most proximal and biome-similar samples, suggesting that most microbiomes will encode largely distinct collections of bacterial secondary metabolites. Our data indicate a correlation between two factors, geographic distance and biome-type, and the biosynthetic diversity found in soil environments. By assigning reads to known gene clusters we identify hotspots of biomedically relevant biosynthetic diversity. These observations not only provide new insights into the natural world, they also provide a road map for guiding future natural products discovery efforts.

Biosynthetic strategies for tetramic acid formation

2021 ◽  
Author(s):  
Xuhua Mo ◽  
Tobias A. M. Gulder
Keyword(s):  
Molecular Mechanism ◽  
Gene Clusters ◽  
Acid Formation ◽  
Biosynthetic Gene ◽  
Tetramic Acid ◽  
Biosynthetic Gene Clusters ◽  
The Individual ◽  
First Time ◽  
Acid Unit

Over 30 biosynthetic gene clusters for natural tetramate have been identified. This highlight reviews the biosynthetic strategies for formation of tetramic acid unit for the first time, discussing the individual molecular mechanism in detail.

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