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Marine sediments constitute the world's most substantial long-term carbon repository. The microorganisms dwelling in these sediments mediate the transformation of fixed oceanic carbon, but their contribution to the carbon cycle is not fully understood. Previous culture-independent investigations into sedimentary microorganisms have underscored the significance of carbohydrates in the carbon cycle. In this study, we employ a metagenomic methodology to investigate the distribution and abundance of carbohydrate-active enzymes (CAZymes) in 37 marine sediments sites. These sediments exhibit varying oxygen availability and were isolated in diverse regions worldwide. Our comparative analysis is based on the metabolic potential for oxygen utilisation, derived from genes present in both oxic and anoxic environments. We found that extracellular CAZyme modules targeting the degradation of plant and algal detritus, necromass, and host glycans were abundant across all metagenomic samples. The analysis of these results indicates that the oxic/anoxic conditions not only influence the taxonomic composition of the microbial communities, but also affect the occurrence of CAZyme modules involved in the transformation of necromass, algae and plant detritus. To gain insight into the sediment microbial taxa, we reconstructed metagenome assembled genomes (MAG) and examined the presence of primary extracellular carbohydrate active enzyme (CAZyme) modules. Our findings reveal that the primary CAZyme modules and the CAZyme gene clusters discovered in our metagenomes were prevalent in the Bacteroidia, Gammaproteobacteria, and Alphaproteobacteria classes. We compared those MAGs to organisms from the same taxonomic classes found in soil, and we found that they were similar in its CAZyme repertoire, but the soil MAG contained a more abundant and diverse CAZyme content. Furthermore, the data indicate that abundant classes in our metagenomic samples, namely Alphaproteobacteria, Bacteroidia and Gammaproteobacteria, play a pivotal role in carbohydrate transformation within the initial few metres of the sediments. [ABSTRACT FROM AUTHOR]

Expansins are encoded by some phytopathogenic bacteria and evidence indicates that they act as virulence factors for host infection. Here we analysed the expression of exl1 by Pectobacterium brasiliense and Pectobacterium atrosepticum. In both, exl1 gene appears to be under quorum sensing control, and protein Exl1 can be observed in culture medium and during plant infection. Expression of exl1 correlates with pathogen virulence, where symptoms are reduced in a Δexl1 mutant strain of P. atrosepticum. As well as Δexl1 exhibiting less maceration of potato plants, fewer bacteria are observed at distance from the inoculation site. However, bacteria infiltrated into the plant tissue are as virulent as the wild type, suggesting that this is due to alterations in the initial invasion of the tissue. Additionally, swarming from colonies grown on MacConkey soft agar was delayed in the mutant in comparison to the wild type. We found that Exl1 acts on the plant tissue, probably by remodelling of a cell wall component or altering the barrier properties of the cell wall inducing a plant defence response, which results in the production of ROS and the induction of marker genes of the JA, ET and SA signalling pathways in Arabidopsis thaliana. Exl1 inactive mutants fail to trigger such responses. This defence response is protective against Pectobacterium brasiliense and Botrytis cinerea in more than one plant species. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Metagenomics research has recently thrived due to DNA sequencing technologies improvement, driving the emergence of new analysis tools and the growth of taxonomic databases. However, there is no all-purpose strategy that can guarantee the best result for a given project and there are several combinations of software, parameters and databases that can be tested. Therefore, we performed an impartial comparison, using statistical measures of classification for eight bioinformatic tools and four taxonomic databases, defining a benchmark framework to evaluate each tool in a standardized context. Using in silico simulated data for 16S rRNA amplicons and whole metagenome shotgun data, we compared the results from different software and database combinations to detect biases related to algorithms or database annotation. Using our benchmark framework, researchers can define cut-off values to evaluate the expected error rate and coverage for their results, regardless the score used by each software. A quick guide to select the best tool, all datasets and scripts to reproduce our results and benchmark any new method are available at https://github.com/Ales-ibt/Metagenomic-benchmark. Finally, we stress out the importance of gold standards, database curation and manual inspection of taxonomic profiling results, for a better and more accurate microbial diversity description. [ABSTRACT FROM AUTHOR]