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Summary: Nanometa Live presents a user-friendly interface designed for real-time metagenomic data analysis and pathogen identification utilizing Oxford Nanopore Technologies’ MinION and Flongle flow cells. It offers an efficient workflow and graphical interface for the visualization and interpretation of metagenomic data as it is being generated. Key features include automated BLAST validation, streamlined handling of custom Kraken2 databases, and a simplified graphical user interface for enhanced user experience. Nanometa Live is particularly notable for its capability to run without constant internet or server access once installed, setting it apart from similar tools. It provides a comprehensive view of taxonomic composition and facilitates the detection of user-defined pathogens or other species of interest, catering to both researchers and clinicians. Availability and implementation: Nanometa Live has been implemented as a local web application using the Dash framework with Snakemake handling the data processing. The source code is freely accessible on the GitHub repository at https://github.com/FOIBioinformatics/nanometa_live and it is easily installable using Bioconda. It includes containerization support via Docker and Singularity, ensuring ease of use, reproducibility, and portability.

Climate change is projected to cause alterations in northern coastal systems, including humification and intensified nutrient loads, which can lead to ecosystem imbalances and establishment of new bacterial species. Several potential pathogens, such as different species of Legionella, hide in the environment between infections, some by living inside protozoan host cells. Knowledge about the occurrence of Legionella in natural waters is missing, which disable risk assessments of exposure. We performed a study of the species diversity of Legionella in the northern Baltic Sea (Gulf of Bothnia) during early summer to map their occurrence and to identify possible environmental drivers. We detected Legionella and potential protozoan hosts along gradients of the Gulf of Bothnia. We also for the first time present third generation full-length 16S rRNA amplicon sequencing (Nanopore) to resolve environmental species classification of Legionella, with a method suitable to study all bacteria. Our data show that full length 16S rRNA sequences is sufficient to resolve Legionella while the standard short Illumina sequences did not capture the entire diversity. For accurate species classification of Legionella, harmonization between the Nanopore classification methods is still needed and the bias toward the well-studied Legionella pneumophila need to be resolved. Different Legionella species occurred both in the Bothnian Sea and in the Bothnian Bay and their abundance were linked to humic substances and low salinity. The relative abundance of Legionella was higher in the humic-rich northern waters of the Bothnian Bay. The link between Legionella species and humic substances may be indirect via promotion of the heterotrophic microbial food web, allowing Legionella species and similar bacteria to establish. Humic substances are rich in iron, which has been shown crucial for growth of Legionella species and other pathogens. Considering climate change projections in this regional area

Background: Surface raw water used as a source for drinking water production is a critical resource, sensitive to contamination. We conducted a study on Swedish raw water sources, aiming to identify mutually co-occurring metacommunities of bacteria, and environmental factors driving such patterns. Methods: The water sources were different regarding nutrient composition, water quality, and climate characteristics, and displayed various degrees of anthropogenic impact. Water inlet samples were collected at six drinking water treatment plants over 3 years, totaling 230 samples. The bacterial communities of DNA sequenced samples (n = 175), obtained by 16S metabarcoding, were analyzed using a joint model for taxa abundance. Results: Two major groups of well-defined metacommunities of microorganisms were identified, in addition to a third, less distinct, and taxonomically more diverse group. These three metacommunities showed various associations to the measured environmental data. Predictions for the well-defined metacommunities revealed differing sets of favored metabolic pathways and life strategies. In one community, taxa with methanogenic metabolism were common, while a second community was dominated by taxa with carbohydrate and lipid-focused metabolism. Conclusion: The identification of ubiquitous persistent co-occurring bacterial metacommunities in freshwater habitats could potentially facilitate microbial source tracking analysis of contamination issues in freshwater sources.