Systematic assessment of template-based genome-scale metabolic models created with the BiGG Integration Tool.

Genome-scale metabolic models (GEMs) are essential tools for in silico phenotype prediction and strain optimisation. The most straightforward GEMs reconstruction approach uses published models as templates to generate the initial draft, requiring further curation. Such an approach is used by BiGG Integration Tool (BIT), available for merlin users. This tool uses models from BiGG Models database as templates for the draft models. Moreover, BIT allows the selection between different template combinations. The main objective of this study is to assess the draft models generated using this tool and compare them BIT, comparing these to CarveMe models, both of which use the BiGG database, and curated models. For this, three organisms were selected, namely Streptococcus thermophilus, Xylella fastidiosa and Mycobacterium tuberculosis. The models' variability was assessed using reactions and genes' metabolic functions. This study concluded that models generated with BIT for each organism were differentiated, despite sharing a significant portion of metabolic functions. Furthermore, the template seems to influence the content of the models, though to a lower extent. When comparing each draft with curated models, BIT had better performances than CarveMe in all metrics. Hence, BIT can be considered a fast and reliable alternative for draft reconstruction for bacteria models.

UPIMAPI, reCOGnizer and KEGGCharter: Bioinformatics tools for functional annotation and visualization of (meta)-omics datasets.

Omics and meta-omics technologies are powerful approaches to explore microorganisms' functions, but the sheer size and complexity of omics datasets often turn the analysis into a challenging task. Software developed for omics and meta-omics analyses, together with knowledgebases encompassing information on genes, proteins, taxonomic and functional annotation, among other types of information, are valuable resources for analyzing omics data. Although several bioinformatics resources are available for meta-omics analyses, many require significant computational expertise. Web interfaces are more user-friendly, but often struggle to handle large data files, such as those obtained in metagenomics, metatranscriptomics, or metaproteomics experiments. In this work, we present three novel bioinformatics tools, which are available through user-friendly command-line interfaces, can be run sequentially or stand-alone, and combine popular resources for functional annotation. UPIMAPI performs sequence homology-based annotation and obtains data from UniProtKB (e.g., protein names, EC numbers, Gene Ontology, Taxonomy, cross-references to external databases). reCOGnizer performs multithreaded domain homology-based annotation of protein sequences with several functional databases (i.e., CDD, NCBIfam, Pfam, Protein Clusters, SMART, TIGRFAM, COG and KOG) and in addition, obtains information on domain names and descriptions and EC numbers. KEGGCharter represents omics results, including differential gene expression, in KEGG metabolic pathways. In addition, it shows the taxonomic assignment of the enzymes represented, which is particularly useful in metagenomics studies in which several microorganisms are present. reCOGnizer, UPIMAPI and KEGGCharter together provide a comprehensive and complete functional characterization of large datasets, facilitating the interpretation of microbial activities in nature and in biotechnological processes.

Corksorb Enhances Alkane Degradation by Hydrocarbonoclastic Bacteria.

Biosorbent materials are effective in the removal of spilled oil from water, but their effect on hydrocarbonoclastic bacteria is not known. Here, we show that corksorb, a cork-based biosorbent, enhances growth and alkane degradation by Rhodococcus opacus B4 (Ro) and Alcanivorax borkumensis SK2 (Ab). Ro and Ab degraded 96 ± 1% and 72 ± 2%, respectively, of a mixture of n-alkanes (2 g L-1) in the presence of corksorb. These values represent an increase of 6 and 24%, respectively, relative to the assays without corksorb. The biosorbent also increased the growth of Ab by 51%. However, no significant changes were detected in the expression of genes involved in alkane uptake and degradation in the presence of corksorb relative to the control without the biosorbent. Nevertheless, transcriptomics analysis revealed an increased expression of rRNA and tRNA coding genes, which confirms the higher metabolic activity of Ab in the presence of corksorb. The effect of corksorb is not related to the release of soluble stimulating compounds, but rather to the presence of the biosorbent, which was shown to be essential. Indeed, scanning electron microscopy images and downregulation of pili formation coding genes, which are involved in cell mobility, suggest that cell attachment on corksorb is a determinant for the improved activity. Furthermore, the existence of native alkane-degrading bacteria in corksorb was revealed, which may assist in situ bioremediation. Hence, the use of corksorb in marine oil spills may induce a combined effect of sorption and stimulated biodegradation, with high potential for enhancing in situ bioremediation processes.

Effect of Sub-Stoichiometric Fe(III) Amounts on LCFA Degradation by Methanogenic Communities.

Long-chain fatty acids (LCFA) are common contaminants in municipal and industrial wastewater that can be converted anaerobically to methane. A low hydrogen partial pressure is required for LCFA degradation by anaerobic bacteria, requiring the establishment of syntrophic relationships with hydrogenotrophic methanogens. However, high LCFA loads can inhibit methanogens, hindering biodegradation. Because it has been suggested that anaerobic degradation of these compounds may be enhanced by the presence of alternative electron acceptors, such as iron, we investigated the effect of sub-stoichiometric amounts of Fe(III) on oleate (C18:1 LCFA) degradation by suspended and granular methanogenic sludge. Fe(III) accelerated oleate biodegradation and hydrogenotrophic methanogenesis in the assays with suspended sludge, with H2-consuming methanogens coexisting with iron-reducing bacteria. On the other hand, acetoclastic methanogenesis was delayed by Fe(III). These effects were less evident with granular sludge, possibly due to its higher initial methanogenic activity relative to suspended sludge. Enrichments with close-to-stoichiometric amounts of Fe(III) resulted in a microbial community mainly composed of Geobacter, Syntrophomonas, and Methanobacterium genera, with relative abundances of 83-89%, 3-6%, and 0.2-10%, respectively. In these enrichments, oleate was biodegraded to acetate and coupled to iron-reduction and methane production, revealing novel microbial interactions between syntrophic LCFA-degrading bacteria, iron-reducing bacteria, and methanogens.