Bacterial cellulose (BC) is a biodegradable polymer that benefits in purity, crystallinity and superior optical, structural and mechanical properties. Such properties facilitate BC to replace the conventional non-biodegradable materials used, for instance, in sensing applications. However, BC production is largely conducted in conventional medium containing model substrates and complex carbon-containing compounds. Aiming towards the production of eco-friendly piezoelectric-responsive BC films, we isolated and characterized a novel bacterial strain affiliated to Komagataeibacter rhaeticus. The K. rhaeticus ENS9a strain synthesized BC in minimal medium containing crude glycerol, generating a titer of 2.9 ± 0.3 g/L BC. This is, to the best of our knowledge, the highest BC titer reported from an unoptimized minimal medium containing crude glycerol. Interestingly, the films prepared from crude glycerol showed normal force and bending mode sensitivities of 6–11 pC/N and 40–71 pC/N, respectively, demonstrating a green platform to address both bioprocess waste valorization and implementation of cellulose-based alternatives for the non-sustainable and non-biodegradable materials, such as fluoropolymers or lead containing piezoceramics, used in sensing applications. In silico genome analysis predicted genes partaking in carbohydrate metabolism, BC biogenesis, and nitrogen fixation/regulation. Graphic abstract
Despite the development in DNA sequencing technology, improving the number and the length of reads, the process of reconstruction of complete genome sequences, the so called genome assembly, is still complex. Only 13% of the prokaryotic genome sequencing projects have been completed. Draft genome sequences deposited in public databases are fragmented in contigs and may lack the full gene complement. The aim of the present work is to identify assembly errors and improve the assembly process of bacterial genomes. The biological patterns observed in genomic sequences and the application of a priori information can allow the identification of misassembled regions, and the reorganization and improvement of the overall de novo genome assembly. GFinisher starts generating a Fuzzy GC skew graphs for each contig in an assembly and follows breaking down the contigs in critical points in order to reassemble and close them using jFGap. This has been successfully applied to dataset from 96 genome assemblies, decreasing the number of contigs by up to 86%. GFinisher can easily optimize assemblies of prokaryotic draft genomes and can be used to improve the assembly programs based on nucleotide sequence patterns in the genome. The software and source code are available at http://gfinisher.sourceforge.net/.
Vectoral and alignment-free approaches to biological sequence representation have been explored in bioinformatics to efficiently handle big data. Even so, most current methods involve sequence comparisons via alignment-based heuristics and fail when applied to the analysis of large data sets. Here, we present "Spaced Words Projection (SWeeP)", a method for representing biological sequences using relatively small vectors while preserving intersequence comparability. SWeeP uses spaced-words by scanning the sequences and generating indices to create a higher-dimensional vector that is later projected onto a smaller randomly oriented orthonormal base. We constructed phylogenetic trees for all organisms with mitochondrial and bacterial protein data in the NCBI database. SWeeP quickly built complete and accurate trees for these organisms with low computational cost. We compared SWeeP to other alignment-free methods and Sweep was 10 to 100 times quicker than the other techniques. A tool to build SWeep vectors is available at https://sourceforge.net/projects/spacedwordsprojection/.
Tools for genomic island prediction use strategies for genomic comparison analysis and sequence composition analysis. The goal of comparative analysis is to identify unique regions in the genomes of related organisms, whereas sequence composition analysis evaluates and relates the composition of specific regions with other regions in the genome. The goal of this study was to qualitatively and quantitatively evaluate extant genomic island predictors. We chose tools reported to produce significant results using sequence composition prediction, comparative genomics, and hybrid genomics methods. To maintain diversity, the tools were applied to eight complete genomes of organisms with distinct characteristics and belonging to different families. Escherichia coli CFT073 was used as a control and considered as the gold standard because its islands were previously curated in vitro. The results of predictions with the gold standard were manually curated, and the content and characteristics of each predicted island were analyzed. For other organisms, we created GenBank (GBK) files using Artemis software for each predicted island. We copied only the amino acid sequences from the coding sequence and constructed a multi-FASTA file for each predictor. We used BLASTp to compare all results and generate hits to evaluate similarities and differences among the predictions. Comparison of the results with the gold standard revealed that GIPSy produced the best results, covering ~91% of the composition and regions of the islands, followed by Alien Hunter (81%), IslandViewer (47.8%), Predict Bias (31%), GI Hunter (17%), and Zisland Explorer (16%). The tools with the best results in the analyzes of the set of organisms were the same ones that presented better performance in the tests with the gold standard.
Komagataeibacter spp. has been used for the bioconversion of industrial wastes and lignocellulosic hydrolysates to bacterial cellulose (BC). Recently, studies have demonstrated the capacity of Komagataeibacter spp. in the biotransformation of inhibitors found in lignocellulosic hydrolysates, aromatic lignin-derived monomers (LDMs) and acetate. In general, detoxification and BC synthesis from lignocellulosic inhibitors requires a carbon flow from acetyl-coA towards tricarboxylic acid and gluconeogenesis, respectively. However, the related molecular aspects have not yet been identified in Komagataeibacter spp. In this study, we isolated a cellulose-producing bacterium capable of synthesizing BC in a minimal medium containing crude glycerol, a by-product from the biodiesel production process. The isolate, affiliated to Komagataeibacter genus, synthesized cellulose in a minimal medium containing glucose (3.3 ± 0.3 g/L), pure glycerol (2.2 ± 0.1 g/L) and crude glycerol (2.1 ± 0.1 g/L). Genome assembly and annotation identified four copies of bacterial cellulose synthase operon and genes for redirecting the carbon from the central metabolic pathway to gluconeogenesis. According to the genome annotations, a BC production route from acetyl-CoA, a central metabolic intermediate, was hypothesized and was validated using acetate. We identified that when K. rhaeticus ENS9b was grown in a minimal medium supplemented with acetate, BC production was not observed. However, in the presence of readily utilizable substrates, such as spent yeast hydrolysate, acetate supplementation improved BC synthesis.
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