scholarly journals A Metabolic Gene Cluster in the Wheat W1 and the Barley Cer-cqu Loci Determines β-Diketone Biosynthesis and Glaucousness

2016 ◽  
Vol 28 (6) ◽  
pp. 1440-1460 ◽  
Author(s):  
Shelly Hen-Avivi ◽  
Orna Savin ◽  
Radu C. Racovita ◽  
Wing-Sham Lee ◽  
Nikolai M. Adamski ◽  
...  
Keyword(s):  
Gene Cluster ◽  
Metabolic Gene

An Aspergillus flavus secondary metabolic gene cluster containing a hybrid PKS–NRPS is necessary for synthesis of the 2-pyridones, leporins

2015 ◽  
Vol 81 ◽  
pp. 88-97 ◽  
Author(s):  
Jeffrey W. Cary ◽  
Valdet Uka ◽  
Zheng Han ◽  
Dieter Buyst ◽  
Pamela Y. Harris-Coward ◽  
...  
Keyword(s):  
Gene Cluster ◽  
Aspergillus Flavus ◽  
Metabolic Gene

scholarly journals Cell Type–Specific Chromatin Decondensation of a Metabolic Gene Cluster in Oats

2009 ◽  
Vol 21 (12) ◽  
pp. 3926-3936 ◽  
Author(s):  
Eva Wegel ◽  
Rachil Koumproglou ◽  
Peter Shaw ◽  
Anne Osbourn
Keyword(s):  
Gene Cluster ◽  
Cell Type ◽  
Chromatin Decondensation ◽  
Metabolic Gene ◽  
Cell Type Specific

Isoeugenol monooxygenase and its putative regulatory gene are located in the eugenol metabolic gene cluster in Pseudomonas nitroreducens Jin1

2010 ◽  
Vol 192 (3) ◽  
pp. 201-209 ◽  
Author(s):  
Ji-Young Ryu ◽  
Jiyoung Seo ◽  
Tatsuya Unno ◽  
Joong-Hoon Ahn ◽  
Tao Yan ◽  
...  
Keyword(s):  
Gene Cluster ◽  
Regulatory Gene ◽  
Metabolic Gene ◽  
Pseudomonas Nitroreducens ◽  
Isoeugenol Monooxygenase

scholarly journals Horizontal Transfer and Death of a Fungal Secondary Metabolic Gene Cluster

2012 ◽  
Vol 4 (3) ◽  
pp. 289-293 ◽  
Author(s):  
Matthew A. Campbell ◽  
Antonis Rokas ◽  
Jason C. Slot
Keyword(s):  
Gene Cluster ◽  
Horizontal Transfer ◽  
Metabolic Gene

scholarly journals The evolutionary origins of the cat attractant nepetalactone in catnip

2020 ◽  
Vol 6 (20) ◽  
pp. eaba0721 ◽  
Author(s):  
Benjamin R. Lichman ◽  
Grant T. Godden ◽  
John P. Hamilton ◽  
Lira Palmer ◽  
Mohamed O. Kamileen ◽  
...  
Keyword(s):  
Comparative Genomics ◽  
Genome Evolution ◽  
Gene Cluster ◽  
Phylogenetic Analyses ◽  
Chemical Diversity ◽  
Flowering Plant ◽  
Present Evidence ◽  
Metabolic Gene ◽  
Evolutionary Origins ◽  
Plant Chemical

Catnip or catmint (Nepeta spp.) is a flowering plant in the mint family (Lamiaceae) famed for its ability to attract cats. This phenomenon is caused by the compound nepetalactone, a volatile iridoid that also repels insects. Iridoids are present in many Lamiaceae species but were lost in the ancestor of the Nepetoideae, the subfamily containing Nepeta. Using comparative genomics, ancestral sequence reconstructions, and phylogenetic analyses, we probed the re-emergence of iridoid biosynthesis in Nepeta. The results of these investigations revealed mechanisms for the loss and subsequent re-evolution of iridoid biosynthesis in the Nepeta lineage. We present evidence for a chronology of events that led to the formation of nepetalactone biosynthesis and its metabolic gene cluster. This study provides insights into the interplay between enzyme and genome evolution in the origins, loss, and re-emergence of plant chemical diversity.

scholarly journals BiG-MAP: an automated pipeline to profile metabolic gene cluster abundance and expression in microbiomes

2020 ◽  
Author(s):  
Victoria Pascal Andreu ◽  
Hannah E Augustijn ◽  
Koen van den Berg ◽  
Justin J.J. van der Hooft ◽  
Michael A Fischbach ◽  
...  
Keyword(s):  
Gene Cluster ◽  
Gene Clusters ◽  
Biosynthetic Gene Cluster ◽  
Oral Microbiome ◽  
Metabolic Potential ◽  
Expression Levels ◽  
Primary And Secondary Metabolites ◽  
Functional Roles ◽  
Metabolic Gene ◽  
Fragmentation Patterns

Microbial gene clusters encoding the biosynthesis of primary and secondary metabolites play key roles in shaping microbial ecosystems and driving microbiome-associated phenotypes. Although effective approaches exist to evaluate the metabolic potential of such bacteria through identification of metabolic gene clusters in their genomes, no automated pipelines exist to profile the abundance and expression levels of such gene clusters in microbiome samples to generate hypotheses about their functional roles and to find associations with phenotypes of interest. Here, we describe BiG-MAP, a bioinformatic tool to profile abundance and expression levels of gene clusters across metagenomic and metatranscriptomic data and evaluate their differential abundance and expression between different conditions. To illustrate its usefulness, we analyzed 47 metagenomic samples from healthy and caries-associated human oral microbiome samples and identified 58 gene clusters, including unreported ones, that were significantly more abundant in either phenotype. Among them, we found the muc operon, a gene cluster known to be associated to tooth decay. Additionally, we found a putative reuterin biosynthetic gene cluster from a Streptococcus strain to be enriched but not exclusively found in healthy samples; metabolomic data from the same samples showed masses with fragmentation patterns consistent with (poly)acrolein, which is known to spontaneously form from the products of the reuterin pathway and has been previously shown to inhibit pathogenic Streptococcus mutans strains. Thus, we show how BiG-MAP can be used to generate new hypotheses on potential drivers of microbiome-associated phenotypes and prioritize the experimental characterization of relevant gene clusters that may mediate them.

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