Corynebacterium glutamicum is the major host for the industrial production of amino acids and has become one of the best studied model organisms in microbial biotechnology. Rational strain construction has led to an improvement of producer strains and to a variety of novel producer strains with a broad substrate and product spectrum. A key factor for the success of these approaches is detailed knowledge of transcriptional regulation in C. glutamicum. Here, we present a large compendium of 927 manually curated microarray-based transcriptional profiles for wild-type and engineered strains detecting genome-wide expression changes of the 3,047 annotated genes in response to various environmental conditions or in response to genetic modifications. The replicates within the 927 experiments were combined to 304 microarray sets ordered into six categories that were used for differential gene expression analysis. Hierarchical clustering confirmed that no outliers were present in the sets. The compendium provides a valuable resource for future fundamental and applied research with C. glutamicum and contributes to a systemic understanding of this microbial cell factory. Measurement(s) Gene Expression Analysis Technology Type(s) Two Color Microarray Factor Type(s) WT condition A vs. WT condition B ⢠Plasmid-based gene overexpression in parental strain vs. parental strain with empty vector control ⢠Deletion mutant vs. parental strain Sample Characteristic - Organism Corynebacterium glutamicum Sample Characteristic - Environment laboratory environment Sample Characteristic - Location Germany.
A manually curated compendium of expression profiles for the microbial cell factory Corynebacterium glutamicum.
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作者:Kranz Angela, Polen Tino, Kotulla Christian, Arndt Annette, Bosco Graziella, Bussmann Michael, Chattopadhyay Ava, Cramer Annette, Davoudi Cedric-Farhad, Degner Ursula, Diesveld Ramon, Freiherr von Boeselager Raphael, Gärtner Kim, Gätgens Cornelia, Georgi Tobias, Geraths Christian, Haas Sabine, Heyer Antonia, Hünnefeld Max, Ishige Takeru, Kabus Armin, Kallscheuer Nicolai, Kever Larissa, Klaffl Simon, Kleine Britta, KoÄan Martina, Koch-Koerfges Abigail, Kraxner Kim J, Krug Andreas, Krüger Aileen, Küberl Andreas, Labib Mohamed, Lange Christian, Mack Christina, Maeda Tomoya, Mahr Regina, Majda Stephan, Michel Andrea, Morosov Xenia, Müller Olga, Nanda Arun M, Nickel Jens, Pahlke Jennifer, Pfeifer Eugen, Platzen Laura, Ramp Paul, Rittmann Doris, Schaffer Steffen, Scheele Sandra, Spelberg Stephanie, Schulte Julia, Schweitzer Jens-Eric, Sindelar Georg, Sorger-Herrmann Ulrike, Spelberg Markus, Stansen Corinna, Tharmasothirajan Apilaasha, Ooyen Jan van, van Summeren-Wesenhagen Philana, Vogt Michael, Witthoff Sabrina, Zhu Lingfeng, Eikmanns Bernhard J, Oldiges Marco, Schaumann Georg, Baumgart Meike, Brocker Melanie, Eggeling Lothar, Freudl Roland, Frunzke Julia, Marienhagen Jan, Wendisch Volker F, Bott Michael
| 期刊: | Scientific Data | 影响因子: | 6.900 |
| 时间: | 2022 | 起止号: | 2022 Oct 1; 9(1):594 |
| doi: | 10.1038/s41597-022-01706-7 | ||
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