Lignocellulolytic characterization and comparative secretome analysis of a Trichoderma erinaceum strain isolated from decaying sugarcane straw.

The fungus Trichoderma reesei is employed in the production of most enzyme cocktails used by the lignocellulosic biofuels industry today. Despite significant improvements, the cost of the required enzyme preparations remains high, representing a major obstacle for the industrial production of these alternative fuels. In this study, a new Trichoderma erinaceum strain was isolated from decaying sugarcane straw. The enzyme cocktail secreted by the new isolate during growth in pretreated sugarcane straw-containing medium presented higher specific activities of ß-glucosidase, endoxylanase, ß-xylosidase and α-galactosidase than the cocktail of a wild T. reesei strain and yielded more glucose in the hydrolysis of pretreated sugarcane straw. A proteomic analysis of the two strains' secretomes identified a total of 86 proteins, of which 48 were exclusive to T. erinaceum, 35 were exclusive to T. reesei and only 3 were common to both strains. The secretome of T. erinaceum also displayed a higher number of carbohydrate-active enzymes than that of T. reesei (37 and 27 enzymes, respectively). Altogether, these results reveal the significant potential of the T. erinaceum species for the production of lignocellulases, both as a possible source of enzymes for the supplementation of industrial cocktails and as a candidate chassis for enzyme production.

The genome sequence of Propionibacterium acidipropionici provides insights into its biotechnological and industrial potential.

BACKGROUND: Synthetic biology allows the development of new biochemical pathways for the production of chemicals from renewable sources. One major challenge is the identification of suitable microorganisms to hold these pathways with sufficient robustness and high yield. In this work we analyzed the genome of the propionic acid producer Actinobacteria Propionibacterium acidipropionici (ATCC 4875). RESULTS: The assembled P. acidipropionici genome has 3,656,170 base pairs (bp) with 68.8% G + C content and a low-copy plasmid of 6,868 bp. We identified 3,336 protein coding genes, approximately 1000 more than P. freudenreichii and P. acnes, with an increase in the number of genes putatively involved in maintenance of genome integrity, as well as the presence of an invertase and genes putatively involved in carbon catabolite repression. In addition, we made an experimental confirmation of the ability of P. acidipropionici to fix CO2, but no phosphoenolpyruvate carboxylase coding gene was found in the genome. Instead, we identified the pyruvate carboxylase gene and confirmed the presence of the corresponding enzyme in proteome analysis as a potential candidate for this activity. Similarly, the phosphate acetyltransferase and acetate kinase genes, which are considered responsible for acetate formation, were not present in the genome. In P. acidipropionici, a similar function seems to be performed by an ADP forming acetate-CoA ligase gene and its corresponding enzyme was confirmed in the proteome analysis. CONCLUSIONS: Our data shows that P. acidipropionici has several of the desired features that are required to become a platform for the production of chemical commodities: multiple pathways for efficient feedstock utilization, ability to fix CO2, robustness, and efficient production of propionic acid, a potential precursor for valuable 3-carbon compounds.

Raman spectroscopy and chemometrics for on-line control of glucose fermentation by Saccharomyces cerevisiae.

This work presents the use of Raman spectroscopy and chemometrics for on-line control of the fermentation process of glucose by Saccharomyces cerevisiae. In a first approach, an on-line determination of glucose, ethanol, glycerol, and cells was accomplished using multivariate calibration based on partial least squares (PLS). The PLS models presented values of root mean square error of prediction (RMSEP) of 0.53, 0.25, and 0.02% for glucose, ethanol and glycerol, respectively, and RMSEP of 1.02 g L(-1) for cells. In a second approach, multivariate control charts based on multiway principal component analysis (MPCA) were developed for detection of fermentation fault-batch. Two multivariate control charts were developed, based on the squared prediction error (Q) and Hotelling's T(2) . The use of the Q control chart in on-line monitoring was efficient for detection of the faults caused by temperature, type of substrate and contamination, but the T(2) control chart was not able to monitor these faults. On-line monitoring by Raman spectroscopy in conjunction with chemometric procedures allows control of the fermentative process with advantages in relation to reference methods, which require pretreatment, manipulation of samples and are time consuming. Also, the use of multivariate control charts made possible the detection of faults in a simple way, based only on the spectra of the system.