The white-rot fungi Phlebia radiata and Dichomitus squalens in wood-based cultures: expression of laccases, lignin peroxidases, and oxalate decarboxylase

Basidiomycetous white-rot fungi are the only organisms that can efficiently decompose all the components of wood. Moreover, white-rot fungi possess the ability to mineralize recalcitrant lignin polymer with their extracellular, oxidative lignin-modifying enzymes (LMEs), i.e. laccase, lignin peroxidase (LiP), manganese peroxidase (MnP), and versatile peroxidase (VP). Within one white-rot fungal species LMEs are typically present as several isozymes encoded by multiple genes. This study focused on two effi cient lignin-degrading white-rot fungal species, Phlebia radiata and Dichomitus squalens. Molecular level knowledge of the LMEs of the Finnish isolate P. radiata FBCC43 (79, ATCC 64658) was complemented with cloning and characterization of a new laccase (Pr-lac2), two new LiP-encoding genes (Pr-lip1, Pr-lip4), and Pr-lip3 gene that has been previously described only at cDNAlevel. Also, two laccase-encoding genes (Ds-lac3, Ds-lac4) of D. squalens were cloned and characterized for the first time. Phylogenetic analysis revealed close evolutionary relationships between the P. radiata LiP isozymes. Distinct protein phylogeny for both P. radiata and D. squalens laccases suggested different physiological functions for the corresponding enzymes. Supplementation of P. radiata liquid culture medium with excess Cu2+ notably increased laccase activity and good fungal growth was achieved in complex medium rich with organic nitrogen. Wood is the natural substrate of lignin-degrading white-rot fungi, supporting production of enzymes and metabolites needed for fungal growth and the breakdown of lignocellulose. In this work, emphasis was on solid-state wood or wood-containing cultures that mimic the natural growth conditions of white-rot fungi. Transcript analyses showed that wood promoted expression of all the presently known LME-encoding genes of P. radiata and laccase-encoding genes of D. squalens. Expression of the studied individual LME-encoding genes of P. radiata and D. squalens was unequal in transcript quantities and apparently time-dependent, thus suggesting the importance of several distinct LMEs within one fungal species. In addition to LMEs, white-rot fungi secrete other compounds that are important in decomposition of wood and lignin. One of these compounds is oxalic acid, which is a common metabolite of wood-rotting fungi. Fungi produce also oxalic-acid degrading enzymes of which the most widespread is oxalate decarboxylase (ODC). However, the role of ODC in fungi is still ambiguous with propositions from regulation of intra and extracellular oxalic acid levels to a function in primary growth and concomitant production of ATP. In this study, intracellular ODC activity was detected in four white-rot fungal species, and D. squalens showed the highest ODC activity upon exposure to oxalic acid. Oxalic acid was the most common organic acid secreted by the ODC-positive white-rot fungi and the only organic acid detected in wood cultures. The ODC-encoding gene Ds-odc was cloned from two strains of D. squalens showing the first characterization of an odc-gene from a white-rot polypore species. Biochemical properties of the D. squalens ODC resembled those described for other basidiomycete ODCs. However, the translated amino acid sequence of Ds-odc has a novel N-terminal primary structure with a repetitive Ala-Ser-rich region of ca 60 amino acid residues in length. Expression of the Ds-odc transcripts suggested a constitutive metabolic role for the corresponding ODC enzyme. According to the results, it is proposed that ODC may have an essential implication for the growth and basic metabolism of wood-decaying fungi.

Discovering hidden structures in molecular data using a Bayesian partition model approach

Advancements in the analysis techniques have led to a rapid accumulation of biological data in databases. Such data often are in the form of sequences of observations, examples including DNA sequences and amino acid sequences of proteins. The scale and quality of the data give promises of answering various biologically relevant questions in more detail than what has been possible before. For example, one may wish to identify areas in an amino acid sequence, which are important for the function of the corresponding protein, or investigate how characteristics on the level of DNA sequence affect the adaptation of a bacterial species to its environment. Many of the interesting questions are intimately associated with the understanding of the evolutionary relationships among the items under consideration. The aim of this work is to develop novel statistical models and computational techniques to meet with the challenge of deriving meaning from the increasing amounts of data. Our main concern is on modeling the evolutionary relationships based on the observed molecular data. We operate within a Bayesian statistical framework, which allows a probabilistic quantification of the uncertainties related to a particular solution. As the basis of our modeling approach we utilize a partition model, which is used to describe the structure of data by appropriately dividing the data items into clusters of related items. Generalizations and modifications of the partition model are developed and applied to various problems. Large-scale data sets provide also a computational challenge. The models used to describe the data must be realistic enough to capture the essential features of the current modeling task but, at the same time, simple enough to make it possible to carry out the inference in practice. The partition model fulfills these two requirements. The problem-specific features can be taken into account by modifying the prior probability distributions of the model parameters. The computational efficiency stems from the ability to integrate out the parameters of the partition model analytically, which enables the use of efficient stochastic search algorithms.

Mu in vitro transposition applications in protein engineering

Transposons, mobile genetic elements that are ubiquitous in all living organisms have been used as tools in molecular biology for decades. They have the ability to move into discrete DNA locations with no apparent homology to the target site. The utility of transposons as molecular tools is based on their ability to integrate into various DNA sequences efficiently, producing extensive mutant clone libraries that can be used in various molecular biology applications. Bacteriophage Mu is one of the most useful transposons due to its well-characterized and simple in vitro transposition reaction. This study establishes the properties of the Mu in vitro transposition system as a versatile multipurpose tool in molecular biology. In addition, this study describes Mu-based applications for engineering proteins by random insertional transposon mutagenesis in order to study structure-function relationships in proteins. We initially characterized the properties of the minimal Mu in vitro transposition system. We showed that the Mu transposition system works efficiently and accurately and produces insertions into a wide spectrum of target sites in different DNA molecules. Then, we developed a pentapeptide insertion mutagenesis strategy for inserting random five amino acid cassettes into proteins. These protein variants can be used especially for screening important sites for protein-protein interactions. Also, the system may produce temperature-sensitive variants of the protein of interest. Furthermore, we developed an efficient screening system for high-resolution mapping of protein-protein interfaces with the pentapeptide insertion mutagenesis. This was accomplished by combining the mutagenesis with subsequent yeast two-hybrid screening and PCR-based genetic footprinting. This combination allows the analysis of the whole mutant library en masse, without the need for producing or isolating separate mutant clones, and the protein-protein interfaces can be determined at amino acid accuracy. The system was validated by analysing the interacting region of JFC1 with Rab8A, and we show that the interaction is mediated via the JFC1 Slp homology domain. In addition, we developed a procedure for the production of nested sets of N- and C-terminal deletion variants of proteins with the Mu system. These variants are useful in many functional studies of proteins, especially in mapping regions involved in protein-protein interactions. This methodology was validated by analysing the region in yeast Mso1 involved in an interaction with Sec1. The results of this study show that the Mu in vitro transposition system is versatile for various applicational purposes and can efficiently be adapted to random protein engineering applications for functional studies of proteins.