Search

Green algae belonging to the genus Ulvales are known to produce ulvan which is one of the main polysaccharide components of their cell wall. Ulvan is composed of 3O-sulfate-rhamnose (Rha3S), glucuronic acid (GlcA), iduronic acid (IduA) and xylose (Xyl) distributed in three disaccharide repetition moieties: [→ 4)- β -D-GlcA-(1 → 4)- α -L-Rha3S-(1 →], [→ 4)- α -L-IdoA-(1 → 4)- α -L-Rha3S(1 →] and [→ 4)- β -D-Xyl-(1 → 4)- α -L-Rha3S(1 →]. The ability of bacteria to degrade complex algal polysaccharides such as ulvan is usually encoded in clusters of genes referred to as polysaccharide utilization loci (PUL). Full saccharification of ulvan is expected to require an ulvan lyase, which cleaves the β -(1 → 4)-glycosidic bond between Rha3S and GluA or IduA through a β -elimination mechanism. In addition, enzymes with β -glucuronyl hydrolase, rhamnosidase, xylosidase and sulfatase activity are also expected. Recently, the genomes of several ulvan degrading bacteria were sequenced, which led to the identification of a new family of polysaccharide lyases family 24 (PL24). In this work, we have continued to mine the genomic data of one of the sequenced strains, Alteromonas sp. LOR. Here we report the identification of an ulvan associated PUL residing between open reading frames ( lor_19 – lor_34 ). This PUL contains a TonB dependent receptor, along with an experimentally verified rhamnosidase, a β -glucuronyl hydrolase and predicted sulfatases. Interestingly, we also identified in the PUL a new ulvan lyase (LOR_29) which showed no homology to previously reported ulvan lyases making it a founding member of yet another new family of polysaccharide lyases (PL25). Finally, this enzyme prompted us to mine other genomes where we identified additional potential ulvan PULs harboring this gene in other bacterial species. Taken together our report provides further insight into ulvan degradation mechanisms in bacteria and reveals a new family of polysaccharide lyases.

Surface Acoustic Waves (SAW) were previously shown to inhibit biofilm formation, increase bacterial susceptibility to antibiotic treatment and alter the transcription pattern of Pseudomonas aeruginosa. Here we characterize one gene, sawR (PA3133), that is highly overexpressed when P. aeruginosa is exposed to SAW. SawR is a putative transcription factor belonging to the TetR regulator family. When overexpressed sawR causes numerous phenotypes, including the accumulation of a brown pigment which we identified as pyomelanin. In this study we describe how sawR regulates pyomelanin synthesis. We show that sawR down-regulates the expression levels of hmgA and this causes the accumulation of homogentisic acid which in turn undergoes oxidation and polymerization to pyomelanin. Using bioinformatics, we were able to identify a specific amino acid, arginine 23, which is found within the sawR DNA binding domain and is crucial for its regulatory activity. Our results indicate that sawR does not affect any other genes in the phenylalanine/tyrosine metabolic pathway and its repressive ability on hmgA is not mediated by the hmgA repressor PA2010 (i.e. hmgR). Taken together, our results shed light on the regulatory cascade controlling pyomelanin synthesis and uncover yet another unknown regulator involved in its regulation.

The ability of autonomous biomolecular computing devices to interact directly with biological systems and even with living organisms without any interface represents their main advantage over the electronic computers. This study shows that the expression of fluorescent proteins in live plant cells can be utilized as a highly accurate visual output of DNA-based computing. Each of the two possible outputs of a 2-symbol 2-state finite automaton was represented here by either green or cyan fluorescence in eukaryotic cells. The automata were programmed by the choice of several molecules from a library of 8 transition molecules, each containing a recognition site for a type II endonuclease. Two enzymes, endonuclease and a DNA ligase, as well as ATP, represented the hardware. Each input molecule, in the form of a dsDNA, included a string of symbols, 6 bp each, and a 6 bp terminator. The two detection molecules were also dsDNA, each containing a 4-base sticky end, complementary to the appropriately restricted terminator and a gene encoding for a different fluorescent protein. Computation was carried out by mixing all components in a homogeneous solution, leading to autonomous processing of the input molecule via repetitive cycles of digestion, hybridization, and ligation. The output processing procedure involved the creation of a circular dsDNA that contained the gene of either green fluorescent protein or cyan fluorescent protein. Insertion of these plasmids into onion cells by particle bombardment resulted in either green fluorescent or cyan fluorescent live cells as phenotypical output signals. The plasmid formation was an important step because it served as a quality control gate that transformed a rather noisy output into a clean signal. This process of noise elimination allowed for clean and flawless outputs with high fidelity and zero noise.