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Plasmids are one of the key drivers of microbial adaptation and evolution. However, their diversity and role in adaptation, especially in extreme environments, remains largely unexplored. In this study, we aimed to identify, characterize, and compare plasmid sequences originating from samples collected from deep-sea hydrothermal vents located in Arctic Mid-Ocean Ridges. To achieve this, we employed, and benchmarked three recently developed plasmid identification tools-PlasX, GeNomad, and PLASMe-on metagenomic data from this unique ecosystem. To date, this is the first direct comparison of these computational methods in the context of data from extreme environments. Upon recovery of plasmid contigs, we performed a multiapproach analysis, focusing on identifying taxonomic and functional biases within datasets originating from each tool. Next, we implemented a majority voting system to identify high-confidence plasmid contigs, enhancing the reliability of our findings. By analysing the consensus plasmid sequences, we gained insights into their diversity, ecological roles, and adaptive significance. Within the high-confidence sequences, we identified a high abundance of Pseudomonadota and Campylobacterota, as well as multiple toxin-antitoxin systems. Our findings ensure a deeper understanding of how plasmids contribute to shaping microbial communities living under extreme conditions of hydrothermal vents, potentially uncovering novel adaptive mechanisms., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)

Over the last 15 years, the costs of DNA sequencing have sharply fallen, effectively shifting the costs of DNA analysis from sequencing to bioinformatic curation and storage. A huge number of available DNA sequences (including genomes and metagenomes) resulted in the development of various tools for sequence annotation. While much effort has been invested into the development of automatic annotation pipelines, manual curation of their results is still necessary in order to obtain a reliable and strictly validated data. Unfortunately, due to its time-consuming nature, manual annotation is now rarely used.In this chapter, a protocol for efficient manual annotation of prokaryotic DNA sequences using a novel bioinformatic tool-MAISEN ( http://maisen.ddlemb.com ), is presented. MAISEN is a free, web-based tool designed to accelerate manual annotation, by providing the user with simple interface and precomputed alignments for each predicted feature. It was designed to be available for every scientist, regardless of their bioinformatic proficiency.

Cultural heritage objects constitute a very diverse environment, inhabited by various bacteria and fungi. The impact of these microorganisms on the degradation of artworks is undeniable, but at the same time, some of them may be applied for the efficient biotreatment of cultural heritage assets. Interventions with microorganisms have been proven to be useful in restoration of artworks, when classical chemical and mechanical methods fail or produce poor or short-term effects. The path to understanding the impact of microbes on historical objects relies mostly on multidisciplinary approaches, combining novel meta-omic technologies with classical cultivation experiments, and physico-chemical characterization of artworks. In particular, the development of metabolomic- and metatranscriptomic-based analyses associated with metagenomic studies may significantly increase our understanding of the microbial processes occurring on different materials and under various environmental conditions. Moreover, the progress in environmental microbiology and biotechnology may enable more effective application of microorganisms in the biotreatment of historical objects, creating an alternative to highly invasive chemical and mechanical methods.