Study of tRNA modifying enzymes and codon usage bias in cancer

Recent evidences indicate that tRNA modifications and tRNA modifying enzymes may play important roles in complex human diseases such as cancer, neurological disorders and mitochondrial-linked diseases. We postulate that expression deregulation of tRNA modifying enzymes affects the level of tRNA modifications and, consequently, their function and the translation efficiency of their tRNA corresponding codons. Due to the degeneracy of the genetic code, most amino acids are encoded by two to six synonymous codons. This degeneracy and the biased usage of synonymous codons cause alterations that can span from protein folding to enhanced translation efficiency of a select gene group. In this work, we focused on cancer and performed a meta-analysis study to compare microarray gene expression profiles, reported by previous studies and evaluate the codon usage of different types of cancer where tRNA modifying enzymes were found de-regulated. A total of 36 different tRNA modifying enzymes were found de-regulated in most cancer datasets analyzed. The codon usage analysis revealed a preference for codons ending in AU for the up-regulated genes, while the down-regulated genes show a preference for GC ending codons. Furthermore, a PCA biplot analysis showed this same tendency. We also analyzed the codon usage of the datasets where the CTU2 tRNA modifying enzyme was found deregulated as this enzyme affects the wobble position (position 34) of specific tRNAs. Our data points to a distinct codon usage pattern between up and downregulated genes in cancer, which might be caused by the deregulation of specific tRNA modifying enzymes. This codon usage bias may augment the transcription and translation efficiency of some genes that otherwise, in a normal situation, would be translated less efficiently.

Bioinformatics analysis of the Pedobacter sp. NL19 genome

The last decades of the 20th century defined the genetic engineering advent, climaxing in the development of techniques, such as PCR and Sanger sequencing. This, permitted the appearance of new techniques to sequencing whole genomes, identified as next-generation sequencing. One of the many applications of these techniques is the in silico search for new secondary metabolites, synthesized by microorganisms exhibiting antimicrobial properties. The peptide antibiotics compounds can be classified in two classes, according to their biosynthesis, in ribosomal or nonribosomal peptides. Lanthipeptides are the most studied ribosomal peptides and are characterized by the presence of lanthionine and methylanthionine that result from posttranslational modifications. Lanthipeptides are divided in four classes, depending on their biosynthetic machinery. In class I, a LanB enzyme dehydrate serine and threonine residues in the C-terminus precursor peptide. Then, these residues undergo a cyclization step performed by a LanC enzyme, forming the lanthionine rings. The cleavage and the transport of the peptide is achieved by the LanP and LanT enzymes, respectively. Although, in class II only one enzyme, LanM, is responsible for the dehydration and cyclization steps and also only one enzyme performs the cleavage and transport, LanT. Pedobacter sp. NL19 is a Gram-negative bacterium, isolated from sludge of an abandon uranium mine, in Viseu (Portugal). Antibacterial activity in vitro was detected against several Gram-positive and Gram-negative bacteria. Sequencing and in silico analysis of NL19 genome revealed the presence of 21 biosynthetic clusters for secondary metabolites, including nonribosomal and ribosomal peptides biosynthetic clusters. Four lanthipeptides clusters were predicted, comprising the precursor peptides, the modifying enzymes (LanB and LanC), and also a bifunctional LanT. This result revealed the hybrid nature of the clusters, comprising characteristics from two distinct classes, which are poorly described in literature. The phylogenetic analysis of their enzymes showed that they clustered within the bacteroidetes clade. Furthermore, hybrid gene clusters were also found in other species of this phylum, revealing that it is a common characteristic in this group. Finally, the analysis of NL19 colonies by MALDI-TOF MS allowed the identification of a 3180 Da mass that corresponds to the predicted mass of a lanthipeptide encoded in one of the clusters. However, this result is not fully conclusive and further experiments are needed to understand the full potential of the compounds encoded in this type of clusters. In conclusion, it was determined that NL19 strain has the potential to produce diverse secondary metabolites, including lanthipeptides that were not functionally characterized so far.