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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.

In recent years, an increasing diversity of species has been recognized within the family Francisellaceae. Unfortunately, novel isolates are sometimes misnamed in initial publications or multiple sources propose different nomenclature for genetically highly similar isolates. Thus, unstructured and occasionally incorrect information can lead to confusion in the scientific community. Historically, detection of Francisella tularensis in environmental samples has been challenging due to the considerable and unknown genetic diversity within the family, which can result in false positive results. We have assembled a comprehensive collection of genome sequences representing most known Francisellaceae species/strains and restructured them according to a taxonomy that is based on phylogenetic structure. From this structured dataset, we identified a small number of genomic regions unique to F. tularensis that are putatively suitable for specific detection of this pathogen in environmental samples. We designed and validated specific PCR assays based on these genetic regions that can be used for the detection of F. tularensis in environmental samples, such as water and air filters.

The Flexible Taxonomy Database framework provides a method for modification and merging official and custom taxonomic databases to create improved databases. Using such databases will increase accuracy and precision of existing methods to classify sequence reads.

The secondary xylem of conifers is composed mainly of tracheids that differ anatomically and chemically from angiosperm xylem cells. There is currently no high-spatial-resolution data available profiling gene expression during wood formation for any coniferous species, which limits insight into tracheid development. RNA-sequencing data from replicated, high-spatial-resolution section series throughout the cambial and woody tissues of Picea abies were used to generate the NorWood.conGenIE.org web resource, which facilitates exploration of the associated gene expression profiles and co-expression networks. Integration within PlantGenIE.org enabled a comparative regulomics analysis, revealing divergent co-expression networks between P. abies and the two angiosperm species Arabidopsis thaliana and Populus tremula for the secondary cell wall (SCW) master regulator NAC Class IIB transcription factors. The SCW cellulose synthase genes (CesAs) were located in the neighbourhoods of the NAC factors in A. thaliana and P. tremula, but not in P. abies. The NorWood co-expression network enabled identification of potential SCW CesA regulators in P. abies. The NorWood web resource represents a powerful community tool for generating evo-devo insights into the divergence of wood formation between angiosperms and gymnosperms and for advancing understanding of the regulation of wood development in P. abies., Bio4Energy

Lignocellulosic plants are the most abundant source of terrestrial biomass and are one of the potential sources of renewable energy that can replace the use of fossil fuels. For a country such as Sweden, where the forest industry accounts for 10% of the total export, there would be large economical benefits associated with increased biomass yield. The availability of research on wood development conducted in conifer tree species, which represent the majority of the forestry in Sweden, is limited and the majority of research has been conducted in model angiosperm species such as Arabidopsis thaliana. However, the large evolutionary distance between angiosperms and gymnosperms limits the possibility to identify orthologous genes and regulatory pathways by comparing sequence similarity alone. At such large evolutionary distances, the identification of gene similarity is, in most cases, not sufficient and additional information is required for functional annotation. In this thesis, two high-spatial resolution datasets profiling wood development were processed; one from the angiosperm tree Populus tremula and the other from the conifer species Picea abies. These datasets were each published together with a web resource including tools for the exploration of gene expression, co-expression and functional enrichment of gene sets. One developed resource allows interactive, comparative co-expression analysis between species to identify conserved and diverged co-expression modules. These tools make it possible to identifying conserved regulatory modules that can focus downstream research and provide biologists with a resource to identify regulatory genes for targeted trait improvement., Lignocellulosa är den vanligast förekommande källan till markburen biomassa och är en av de förnybara energikällor som potentiellt kan ersätta användningen av fossila bränslen. För ett land som Sverige, där skogsindustrin som står för 10 \% av den totala exporten, skulle därför en ökad produktion av biomassa kunna ge stora ekonomiska fördelar. Forskningen på barrträd, som utgör majoriteten av svensk skog är begränsad och den huvudsakliga forskningen som har bedrivits på växter, har skett i modell organismer tillhörande gruppen gömfröiga växter som till exempel i Arabidopsis thaliana. Det evolutionära avståndet mellan gömfröiga (blommor och träd) och nakenfröiga (gran och tall) begränsar dock möjligheten att identifiera regulatoriska system mellan dessa grupper. Vid sådana stora evolutionära avstånd krävs det mer än att bara identifiera en gen i en modellorganism utan ytterligare information krävs som till exempel genuttrycksdata. I denna avhandling har två högupplösta experiment som profilerar vedens utveckling undersökts; ett från gömfröiga träd Populus tremula och det andra från nakenföriga träd (barrträd) Picea abies. Datat som behandlats har publicerats tillsammans med webbsidor med flera olika verktyg för att bland annat visa genuttryck, se korrelationer av genuttryck och test för anrikning av funktionella gener i en grupp. En resurs som utvecklats tillåter interaktiva jämförelser av korrelationer mellan arter för att kunna identifiera moduler (grupper av gener) som bevaras eller skilts åt mellan arter över tid. Identifieringen av sådana bevarade moduler kan hjälpa att fokusera framtida forskning samt ge biologer en möjlighet att identifiera regulatoriska gener för en riktad förbättring av egenskaper hos träd.

Trees represent the largest terrestrial carbon sink and a renewable source of ligno-cellulose. There is significant scope for yield and quality improvement in these largely undomesticated species, however, efforts to engineer new, elite varieties are constrained by the lack of a comprehensive understanding of the transcriptional network underlying cambial growth and wood formation. We generated RNA Sequencing transcriptome data for four mature, wild-growing aspens (Populus tremula) from high-spatial-resolution tangential cryosection series spanning the secondary phloem, vascular cambium, expanding and secondary cell wall forming xylem cells, cell death zone and the previous years annual ring. The transcriptome comprised 28,294 expressed, previously annotated protein-coding genes, 78 novel protein-coding genes and 567 long intergenic non-coding RNAs. Most paralogs originating from the Salicaceae whole genome duplication had diverged expression, with the notable exception of those with high expression during secondary cell wall deposition. We performed co-expression network analysis to identify central transcriptional modules and associated several of these with known biological processes. This revealed previously uncharacterized complexity underlying the regulation of cambial growth and wood formation, with modules forming a continuum of activated processes across the tissues. The high spatial resolution suggested novel roles for known genes involved in xylan and cellulose biosynthesis, regulators of xylem vessel and fiber differentiation and components of lignification. The associated web resource (AspWood, http://aspwood.popgenie.org) integrates the data within a set of interactive tools for exploring the co-expression network of cambial growth and wood formation.

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, BLAST homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the COMPLEX resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight.

Background: Divergence in gene regulation has emerged as a key mechanism underlying species differentiation. Comparative analysis of co-expression networks across species can reveal conservation and divergence in the regulation of genes. Results: We inferred co-expression networks of A. thaliana, Populus spp. and O. sativa using state-of-the-art methods based on mutual information and context likelihood of relatedness, and conducted a comprehensive comparison of these networks across a range of co-expression thresholds. In addition to quantifying gene-gene link and network neighbourhood conservation, we also applied recent advancements in network analysis to do cross-species comparisons of network properties such as scale free characteristics and gene centrality as well as network motifs. We found that in all species the networks emerged as scale free only above a certain co-expression threshold, and that the high-centrality genes upholding this organization tended to be conserved. Network motifs, in particular the feed-forward loop, were found to be significantly enriched in specific functional subnetworks but where much less conserved across species than gene centrality. Although individual gene-gene co-expression had massively diverged, up to similar to 80% of the genes still had a significantly conserved network neighbourhood. For genes with multiple predicted orthologs, about half had one ortholog with conserved regulation and another ortholog with diverged or non-conserved regulation. Furthermore, the most sequence similar ortholog was not the one with the most conserved gene regulation in over half of the cases. Conclusions: We have provided a comprehensive analysis of gene regulation evolution in plants and built a web tool for Comparative analysis of Plant co-Expression networks (ComPlEx, http:// complex. plantgenie. org/). The tool can be particularly useful for identifying the ortholog with the most conserved regulation among several sequence-similar alte

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1990., Includes bibliographical references (leaves 88-95)., by David E. Sundell., M.C.P.

Bioethanol and biogas are two possible alternatives to fossil fuel resources. The second generation fermentations involving lignocellulosic material is one of the latest fields for bioethanol science. In the current work two fermentation yeasts, Saccharomyces cerevisiae J672 and the alternative fermentation yeast Dekkera bruxellensis CBS 11269, were compared in an experimental design for their ability to ferment spruce lignocelluloses. The goal was to find differences between the growth and ethanol yield of the two species. The investigation was done with a multivariate data analysis tool to examine yeast growth and ethanol yield. Four quantitative factors, pH, temperature, concentration of hydrolysate, and initial cell density were used. The analysis also included one qualitative factor with two settings, aerobic and oxygen limited. The five factors were tested in a fractional factorial design created with MODDE software. The results for the experimental design with S. cerevisiae showed that the main significant factor for ethanol yield was oxygen. Oxygen was the most important factor for S. cerevisiae ethanol yield response, oxygen limitation had positive contribution and aerobic environment had negative contribution. The oxygen factor however was not important for growth. pH was a significant factor and high pH was shown to give better response, for both yeast growth and ethanol yield. Oxygen and temperature had negative contribution while the two factors initial cell concentration and concentration of hydrolysate did not show any significant contribution to the model for S. cerevisiae ethanol yield. D. bruxellensis was adapted to spruce hydrolysate before the final experiment. This was because the non adapted D. bruxellensis CBS11269 did not grow well, in the first experiment, and did not build a model. The two models with S. cerevisiae J672 and spruce adapted D. bruxellensis CBS 11269 are therefore not directly comparable. The adapted D. bruxellensis model for