Gorik De Samblanx

Assessing genetic diversity among Brettanomyces yeasts by DNA fingerprinting and whole-genome sequencing.

ABSTRACT Brettanomyces yeasts, with the species Brettanomyces (Dekkera) bruxellensis being the most important one, are generally reported to be spoilage yeasts in the beer and wine industry due to the production of phenolic off flavors. However, B. bruxellensis is also known to be a beneficial contributor in certain fermentation processes, such as the production of certain specialty beers. Nevertheless, despite its economic importance, Brettanomyces yeasts remain poorly understood at the genetic and genomic levels. In this study, the genetic relationship between more than 50 Brettanomyces strains from all presently known species and from several sources was studied using a combination of DNA fingerprinting techniques. This revealed an intriguing correlation between the B. bruxellensis fingerprints and the respective isolation source. To further explore this relationship, we sequenced a (beneficial) beer isolate of B. bruxellensis (VIB X9085; ST05.12/22) and compared its genome sequence with the genome sequences of two wine spoilage strains (AWRI 1499 and CBS 2499). ST05.12/22 was found to be substantially different from both wine strains, especially at the level of single nucleotide polymorphisms (SNPs). In addition, there were major differences in the genome structures between the strains investigated, including the presence of large duplications and deletions. Gene content analysis revealed the presence of 20 genes which were present in both wine strains but absent in the beer strain, including many genes involved in carbon and nitrogen metabolism, and vice versa, no genes that were missing in both AWRI 1499 and CBS 2499 were found in ST05.12/22. Together, this study provides tools to discriminate Brettanomyces strains and provides a first glimpse at the genetic diversity and genome plasticity of B. bruxellensis.

Fermentation assays reveal differences in sugar and (off-) flavor metabolism across different Brettanomyces bruxellensis strains

Abstract Brettanomyces (Dekkera) bruxellensis is an ascomycetous yeast of major importance in the food, beverage and biofuel industry. It has been isolated from various man‐made ecological niches that are typically characterized by harsh environmental conditions such as wine, beer, soft drink, etc. Recent comparative genomics studies revealed an immense intraspecific diversity, but it is still unclear whether this genetic diversity also leads to systematic differences in fermentation performance and (off‐)flavor production, and to what extent strains have evolved to match their ecological niche. Here, we present an evaluation of the fermentation properties of eight genetically diverse B. bruxellensis strains originating from beer, wine and soft drinks. We show that sugar consumption and aroma production during fermentation are determined by both the yeast strain and composition of the medium. Furthermore, our results indicate a strong niche adaptation of B. bruxellensis, most clearly for wine strains. For example, only strains originally isolated from wine were able to thrive well and produce the typical Brettanomyces‐related phenolic off‐flavors 4‐ethylguaiacol and 4‐ethylphenol when inoculated in red wine. Sulfite tolerance was found as a key factor explaining the observed differences in fermentation performance and off‐flavor production. Sequence analysis of genes related to phenolic off‐flavor production, however, revealed only marginal differences between the isolates tested, especially at the amino acid level. Altogether, our study provides novel insights in the Brettanomyces metabolism of flavor production, and is highly relevant for both the wine and beer industry.

Nested Lanczos: implicitly restarting an unsymmetric Lanczos algorithm

In this text, we present a generalization of the idea of the Implicitly Restarted Arnoldi method to the unsymmetric Lanczos algorithm, using the two-sided Gram-Schmidt process or using a full Lanczos tridiagonalization. The resulting implicitly restarted Lanczos method is called Nested Lanczos. Nested Lanczos can be combined with an implicit filter. It can also be used in case of breakdown and offers an alternative for look-ahead.

Faster and more intelligent object detection by combining OpenCL and KR

In this paper we present a fast implementation of a robust object detector by using OpenCL. The use of fast object detection is of great use for a broad range of applications in multiple domains. OpenCL allows for scalability to more performant and different types of hardware, with minimal changes to the implementation. By using a GPU as execution device, we exploit the data parallelism opportunities of the algorithm. We also discuss the use of knowledge representation as a means to integrate expert knowledge into applications. This can be used both for faster processing by limiting the searching space, and for applications to work more autonomous by exploiting a higher level of intelligence.

Using implicitly filtered RKS for generalised eigenvalue problems

The rational Krylov sequence (RKS) method can be seen as a generalisation of Arnoldis method. It projects a matrix pencil onto a smaller subspace; this projection results in a small upper Hessenberg pencil. As for the Arnoldi method, RKS can be restarted implicitly, using the QR decomposition of a Hessenberg matrix. This restart comes with a projection of the subspace using a rational function. In this paper, it is shown how the restart can be worked out in practice. In a second part, it is shown when the filtering of the subspace basis can fail and how this failure can be handled by deflating a converged eigenvector from the subspace, using a Schur-decomposition.

Duality in vector Pade´-Hermite approximation problems

Abstract The article defines a class of dual vector Pade-Hermite problems. It describes dual basis matrices for the solution spaces of such problems and proves their properties. We show how degree restrictions can be imposed on vector Pade-Hermite problems and what the effect is on the dual basis matrices. We also show that the classical duality between Pade-Hermite problems of type I and type II is a special case of vector Pade-Hermite duality. This is proved without the classical restrictive assumption of normality. The article proposes an algorithm that solves two dual vector Pade-Hermite problems at the same time, returning dual basis matrices of the respective solution spaces.