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Kinetic transcriptome analysis reveals an essentially intact induction system in a cellulase hyper-producer Trichoderma reesei strain.

Poggi-Parodi D, Bidard F, Pirayre A, Portnoy T, Blugeon C, Seiboth B, Kubicek CP, Le Crom S, Margeot A - Biotechnol Biofuels (2014)

Bottom Line: Cross-comparison of our transcriptome data with previously identified mutations revealed that most genes from our dataset have not been mutated.The fact that few regulated genes have been affected by mutagenesis suggests that the induction mechanism is essentially intact compared to that for the wild-type isolate QM6a and might be engineered for further improvement of T. reesei.Genes from two specific clusters might be potential targets for such genetic engineering.

View Article: PubMed Central - PubMed

Affiliation: IFP Energies nouvelles, 1-4 avenue de Bois-Préau, 92852 Rueil-Malmaison, France ; Sorbonne Universités, UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), F-75005 Paris, France.

ABSTRACT

Background: The filamentous fungus Trichoderma reesei is the main industrial cellulolytic enzyme producer. Several strains have been developed in the past using random mutagenesis, and despite impressive performance enhancements, the pressure for low-cost cellulases has stimulated continuous research in the field. In this context, comparative study of the lower and higher producer strains obtained through random mutagenesis using systems biology tools (genome and transcriptome sequencing) can shed light on the mechanisms of cellulase production and help identify genes linked to performance. Previously, our group published comparative genome sequencing of the lower and higher producer strains NG 14 and RUT C30. In this follow-up work, we examine how these mutations affect phenotype as regards the transcriptome and cultivation behaviour.

Results: We performed kinetic transcriptome analysis of the NG 14 and RUT C30 strains of early enzyme production induced by lactose using bioreactor cultivations close to an industrial cultivation regime. RUT C30 exhibited both earlier onset of protein production (3 h) and higher steady-state productivity. A rather small number of genes compared to previous studies were regulated (568), most of them being specific to the NG 14 strain (319). Clustering analysis highlighted similar behaviour for some functional categories and allowed us to distinguish between induction-related genes and productivity-related genes. Cross-comparison of our transcriptome data with previously identified mutations revealed that most genes from our dataset have not been mutated. Interestingly, the few mutated genes belong to the same clusters, suggesting that these clusters contain genes playing a role in strain performance.

Conclusions: This is the first kinetic analysis of a transcriptomic study carried out under conditions approaching industrial ones with two related strains of T. reesei showing distinctive cultivation behaviour. Our study sheds some light on some of the events occurring in these strains following induction by lactose. The fact that few regulated genes have been affected by mutagenesis suggests that the induction mechanism is essentially intact compared to that for the wild-type isolate QM6a and might be engineered for further improvement of T. reesei. Genes from two specific clusters might be potential targets for such genetic engineering.

No MeSH data available.


Related in: MedlinePlus

Clustering of differentially expressed genes during induction by lactose in both studied strains. From 568 genes identified as significantly regulated among the several expression experiments performed, 532 were gathered in 9 clusters according to their changes during the NG 14 and RUT C30 lactose induction. The average profile of each cluster is shown next to its heat map.
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Fig3: Clustering of differentially expressed genes during induction by lactose in both studied strains. From 568 genes identified as significantly regulated among the several expression experiments performed, 532 were gathered in 9 clusters according to their changes during the NG 14 and RUT C30 lactose induction. The average profile of each cluster is shown next to its heat map.

Mentions: We applied clustering techniques to classify gene expression profiles into groups of similar patterns. From the expression matrix containing 568 differentially expressed genes, we were able to sort 532 of them into 9 clusters according to their expression pattern (Figure 3). All clusters can be classified as “up-regulated” (1, 5, 7–9) or “down-regulated” (2, 3, 4 and 6). Up-regulated clusters include 256 genes (45.1% of the matrix) and down-regulated gene clusters include 276 genes (48.6%).Figure 3


Kinetic transcriptome analysis reveals an essentially intact induction system in a cellulase hyper-producer Trichoderma reesei strain.

Poggi-Parodi D, Bidard F, Pirayre A, Portnoy T, Blugeon C, Seiboth B, Kubicek CP, Le Crom S, Margeot A - Biotechnol Biofuels (2014)

Clustering of differentially expressed genes during induction by lactose in both studied strains. From 568 genes identified as significantly regulated among the several expression experiments performed, 532 were gathered in 9 clusters according to their changes during the NG 14 and RUT C30 lactose induction. The average profile of each cluster is shown next to its heat map.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4279801&req=5

Fig3: Clustering of differentially expressed genes during induction by lactose in both studied strains. From 568 genes identified as significantly regulated among the several expression experiments performed, 532 were gathered in 9 clusters according to their changes during the NG 14 and RUT C30 lactose induction. The average profile of each cluster is shown next to its heat map.
Mentions: We applied clustering techniques to classify gene expression profiles into groups of similar patterns. From the expression matrix containing 568 differentially expressed genes, we were able to sort 532 of them into 9 clusters according to their expression pattern (Figure 3). All clusters can be classified as “up-regulated” (1, 5, 7–9) or “down-regulated” (2, 3, 4 and 6). Up-regulated clusters include 256 genes (45.1% of the matrix) and down-regulated gene clusters include 276 genes (48.6%).Figure 3

Bottom Line: Cross-comparison of our transcriptome data with previously identified mutations revealed that most genes from our dataset have not been mutated.The fact that few regulated genes have been affected by mutagenesis suggests that the induction mechanism is essentially intact compared to that for the wild-type isolate QM6a and might be engineered for further improvement of T. reesei.Genes from two specific clusters might be potential targets for such genetic engineering.

View Article: PubMed Central - PubMed

Affiliation: IFP Energies nouvelles, 1-4 avenue de Bois-Préau, 92852 Rueil-Malmaison, France ; Sorbonne Universités, UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), F-75005 Paris, France.

ABSTRACT

Background: The filamentous fungus Trichoderma reesei is the main industrial cellulolytic enzyme producer. Several strains have been developed in the past using random mutagenesis, and despite impressive performance enhancements, the pressure for low-cost cellulases has stimulated continuous research in the field. In this context, comparative study of the lower and higher producer strains obtained through random mutagenesis using systems biology tools (genome and transcriptome sequencing) can shed light on the mechanisms of cellulase production and help identify genes linked to performance. Previously, our group published comparative genome sequencing of the lower and higher producer strains NG 14 and RUT C30. In this follow-up work, we examine how these mutations affect phenotype as regards the transcriptome and cultivation behaviour.

Results: We performed kinetic transcriptome analysis of the NG 14 and RUT C30 strains of early enzyme production induced by lactose using bioreactor cultivations close to an industrial cultivation regime. RUT C30 exhibited both earlier onset of protein production (3 h) and higher steady-state productivity. A rather small number of genes compared to previous studies were regulated (568), most of them being specific to the NG 14 strain (319). Clustering analysis highlighted similar behaviour for some functional categories and allowed us to distinguish between induction-related genes and productivity-related genes. Cross-comparison of our transcriptome data with previously identified mutations revealed that most genes from our dataset have not been mutated. Interestingly, the few mutated genes belong to the same clusters, suggesting that these clusters contain genes playing a role in strain performance.

Conclusions: This is the first kinetic analysis of a transcriptomic study carried out under conditions approaching industrial ones with two related strains of T. reesei showing distinctive cultivation behaviour. Our study sheds some light on some of the events occurring in these strains following induction by lactose. The fact that few regulated genes have been affected by mutagenesis suggests that the induction mechanism is essentially intact compared to that for the wild-type isolate QM6a and might be engineered for further improvement of T. reesei. Genes from two specific clusters might be potential targets for such genetic engineering.

No MeSH data available.


Related in: MedlinePlus