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Highlighted authors are members of the University of Jena.

  1. Examining the healthy human microbiome concept

    Year of publicationPublished in:Nature Reviews Microbiology R. Joos, K. Boucher, A. Lavelle, M. Arumugam, M. Blaser, M. Claesson, G. Clarke, P. Cotter, L. De Sordi, M. Dominguez-Bello, B. Dutilh, S. Ehrlich, T. Ghosh, C. Hill, C. Junot, L. Lahti, T. Lawley, T. Licht, E. Maguin, T. Makhalanyane, J. Marchesi, J. Matthijnssens, J. Raes, J. Ravel, A. Salonen, P. Scanlan, A. Shkoporov, C. Stanton, I. Thiele, I. Tolstoy, J. Walter, B. Yang, N. Yutin, A. Zhernakova, H. Zwart, L. Derosa, L. Zitvogel, P. Veiga, C. Vecchi, J. Trebicka, D. Serra, N. Segata, R. Schierwagen, A. Sarati, J. Rodriquez, M. Rhimi, P. Ravaud, P. Prost, N. Pons, F. Pinto, V. Morozova, A. Metwaly, A. Kriaa, A. Krag, S. Kampshoff, A. Jarde, A. Iyappan, M. Israelsen, D. Hazenbrink, Z. Hassani, D. Haller, Y. Godoy, A. Fasano, C. Druart, M. Cordaillat-Simmons, M. Claesson, F. Carraturo, I. Boutron, P. Bork, H. Blottière, F. Betsou, A. Typas, F. Asnicar, J. Doré, R. Ross
    University Bibliography Jena:
    fsu_mods_00017943External link

  2. Summary of taxonomy changes ratified by the International Committee on Taxonomy of Viruses (ICTV) from the Bacterial Viruses Subcommittee, 2025

    Year of publicationPublished in:The Journal of general virology D. Turner, E. Adriaenssens, R. Amann, P. Bardy, N. Bartlau, J. Barylski, S. Błażejak, M. Bouzari, A. Briegel, Y. Briers, D. Carrillo, X. Chen, D. Claessen, R. Cook, M. Crisci, A. Dechesne, P. Deptula, B. Dutilh, B. Ely, L. Fieseler, P. Fogg, A. Fukudome, M. Ganjoor, I. Gientka, K. Holmfeldt, P. Kalatzis, K. Kauffman, A. Kempff, P. Knezevic, E. Koonin, A. Kropinski, M. Krupovic, I. Kurtböke, K. Lambon, R. Lavigne, S. Lehman, H. Liu, C. Lood, R. Lurz, S. Mäntynen, C. Matrishin, M. Middelboe, A. Millard, C. Moraru, D. Nielsen, F. Nobrega, T. Nunoura, H. Oksanen, V. Ongenae, B. Parra, C. Pas, J. Pogliano, M. Poranen, S. Potipimpanon, A. Prichard, H. Pye, D. Rothschild-Rodriguez, D. Rozen, J. Santini, Y. Sha, D. Shymialevich, B. Sokołowska, A. Soleimani-Delfan, P. Średnicka, P. Tavares, A. Telatin, I. Tolstoy, S. Urayama, V. van Neer, F. Vogensen, Q. Wen, A. Wichels, M. Wójcicki, . Ictv Taxonomy Summary Consortium
    This article summarises the activities of the International Committee on Taxonomy of Viruses Bacterial Viruses Subcommittee, detailing developments in the classification of bacterial viruses. We provide here an overview of all new, abolished, moved and renamed taxa proposed in 2024, approved by the Executive Committee, and ratified by membership vote in 2025. Through the collective efforts of 74 international contributors of taxonomy proposals in this round, 43 ratified proposals have led to the creation of one new phylum, one class, four orders, 33 families, 14 subfamilies, 194 genera and 995 species. These proposals mark significant progress in refining the taxonomy of bacterial viruses. Key updates include the creation of new orders and families that include existing taxa to better reflect genomic and evolutionary relationships. As sequencing and bioinformatics approaches continue to advance, further expansion and refinements in viral taxonomy can be anticipated in the coming years.
    University Bibliography Jena:
    fsu_mods_00028013External link

  4. Tunturi virus isolates and metagenome-assembled viral genomes provide insights into the virome of Acidobacteriota in Arctic tundra soils

    Year of publicationPublished in:Microbiome T. Demina, H. Marttila, I. Pessi, M. Männistö, B. Dutilh, S. Roux, J. Hultman
    Background: Arctic soils are climate-critical areas, where microorganisms play crucial roles in nutrient cycling processes. Acidobacteriota are phylogenetically and physiologically diverse bacteria that are abundant and active in Arctic tundra soils. Still, surprisingly little is known about acidobacterial viruses in general and those residing in the Arctic in particular. Here, we applied both culture-dependent and -independent methods to study the virome of Acidobacteriota in Arctic soils. Results: Five virus isolates, Tunturi 1–5, were obtained from Arctic tundra soils, Kilpisjärvi, Finland (69°N), using Tunturiibacter spp. strains originating from the same area as hosts. The new virus isolates have tailed particles with podo- (Tunturi 1, 2, 3), sipho- (Tunturi 4), or myovirus-like (Tunturi 5) morphologies. The dsDNA genomes of the viral isolates are 63–98 kbp long, except Tunturi 5, which is a jumbo phage with a 309-kbp genome. Tunturi 1 and Tunturi 2 share 88% overall nucleotide identity, while the other three are not related to one another. For over half of the open reading frames in Tunturi genomes, no functions could be predicted. To further assess the Acidobacteriota-associated viral diversity in Kilpisjärvi soils, bulk metagenomes from the same soils were explored and a total of 1881 viral operational taxonomic units (vOTUs) were bioinformatically predicted. Almost all vOTUs (98%) were assigned to the class Caudoviricetes. For 125 vOTUs, including five (near-)complete ones, Acidobacteriota hosts were predicted. Acidobacteriota-linked vOTUs were abundant across sites, especially in fens. Terriglobia-associated proviruses were observed in Kilpisjärvi soils, being related to proviruses from distant soils and other biomes. Approximately genus- or higher-level similarities were found between the Tunturi viruses, Kilpisjärvi vOTUs, and other soil vOTUs, suggesting some shared groups of Acidobacteriota viruses across soils. Conclusions: This study provides acidobacterial virus isolates as laboratory models for future research and adds insights into the diversity of viral communities associated with Acidobacteriota in tundra soils. Predicted virus-host links and viral gene functions suggest various interactions between viruses and their host microorganisms. Largely unknown sequences in the isolates and metagenome-assembled viral genomes highlight a need for more extensive sampling of Arctic soils to better understand viral functions and contributions to ecosystem-wide cycling processes in the Arctic. ¹dEr⁵zbⁿHYtsQKⁱgHwMEJhVⁱdeo Abstract
    University Bibliography Jena:
    fsu_mods_00023295External link

  5. SpeSpeNet: an interactive and user-friendly tool to create and explore microbial correlation networks

    Year of publicationPublished in:ISME Communications A. Van Eijnatten, L. Van Zon, E. Manousou, M. Bikineeva, E. Wubs, W. Van der Putten, E. Morriën, B. Dutilh, L. Snoek
    Correlation networks are commonly used to explore microbiome data. In these networks, nodes are microbial taxa and edges represent correlations between their abundances. As clusters of correlating taxa (co-abundance clusters) often indicate a shared response to environmental drivers, network visualization contributes to the system understanding. Currently,most tools for creating and visualizing co-abundance networks from microbiome data either require the researcher to have coding skills or are not user-friendly, with high time expenditure and limited customizability. Furthermore, existing tools lack a focus on the association between environmental drivers and the structure of the microbiome, even though many edges in correlation networks can be understood through a shared association of two taxa with the environment. For these reasons, we developed SpeSpeNet (Species-Species Network, https://tbb.bio.uu.nl/SpeSpeNet), a practical and user-friendly R-shiny tool to construct and visualize correlation networks from taxonomic abundance tables. The details of data preprocessing, network construction, and visualization are automated, require no programming ability for the web version, and are highly customizable, including associations with user-provided environmental data. Here, we present the details of SpeSpeNet and demonstrate its utility using three case studies.
    University Bibliography Jena:
    fsu_mods_00026957External link

  6. Machine learning enables scalable and systematic hierarchical virus taxonomy

    Year of publicationPublished in:Nature Biotechnology: the science and business of biotechnology B. Bolduc, O. Zablocki, D. Turner, H. Bin Jang, J. Guo, E. Adriaenssens, B. Dutilh, M. Sullivan
    University Bibliography Jena:
    fsu_mods_00029607External link

  7. Exogenous carbon-to-nitrogen imbalance drives soil viral roles in microbial carbon mineralization and necromass accrual

    Year of publicationPublished in:Soil Biology and Biochemistry: SBB S. Wang, J. López Arcondo, N. Xie, Y. Wang, Y. Zhang, M. Radosevich, B. Dutilh, X. Liang
    University Bibliography Jena:
    fsu_mods_00027037External link

  8. Prophage induction drives soybean rhizobacterial community differentiation and nutrient cycling benefiting root development

    Year of publicationPublished in:ISME Communications Y. Zhong, Y. Zhang, J. Luis López Arcondo, R. Xu, M. Radosevich, J. Dangl, B. Dutilh, X. Liang
    Bacteriophages, lytic or lysogenic, play critical roles in structuring different soil bacteriomes and driving their functionality. Lysogeny is favored in the plant rhizosphere and may play a major role in plant–rhizobacteria assembly and function. However, the ecological footprint and consequence of prophage activity in the rhizosphere are poorly understood. Here, we conducted a 35-day pot experiment to examine how prophage induction influences soybean rhizosphere viromes and bacterial communities, along with associated changes in nutrient cycling and plant development. The results showed that mitomycin C-induced prophage induction triggered immense viral production, altering virome structure—with more observed species richness in the rhizosphere. We observed a greater impact on the rhizosphere virome than on the bulk soil virome. The resulting lysis decreased the soil organic matter content but significantly increased dissolved organic carbon and nitrate contents in the soil, which improved soil nutrient conditions and stimulated soybean root development. Prophage induction markedly influenced the rhizobacterial community structure, resulting in reduced community diversity. The enrichment of fast-growing bacterial populations was stimulated, suggesting that viral lysis increased microbial activities and accelerated nutrient turnover. The bacterial interaction network was drastically shifted, with complexity being decreased in the bulk soil and increased in the rhizosphere, potentially stimulating the differentiation of the bacterial communities. Together, our results demonstrated that induction of prophages can cause extensive nutrient turnover and variations in plant–rhizobacteria interactions, driving the rhizobacterial community assembly process. This study provides novel insights into the mechanisms of phages controlling microbial function in primary production and soil carbon storage by modulating microbial traits (e.g., carbon use efficiency, growth rate, death, and community assembly) and via processes like the viral shunt.
    University Bibliography Jena:
    fsu_mods_00029118External link

  9. Unveiling the Kadaknath Gut Microbiome: Early Growth Phase Spatiotemporal Diversity

    Year of publicationPublished in:Microbiology Research A. Nair, S. Doijad, M. Suryavanshi, A. Dey, S. Singh Malik, B. Dutilh, S. Barbuddhe
    The early growth phase is a critical period for the development of the chicken gut microbiome. In this study, the spatiotemporal diversity of the gastrointestinal microbiota, shifts in taxonomic composition, and relative abundances of the main bacterial taxa were characterized in Kadaknath, a high-value indigenous Indian chicken breed, using sequencing of the V3–V4 region 16S rRNA gene. To assess microbiome composition and bacterial abundance shifts, three chickens per growth phase (3, 28, and 35 days) were sampled, with microbiota analyzed from three gut regions (crop, small intestine, and ceca) per bird. The results revealed Firmicutes as the most abundant phylum and Lactobacillus as the dominant genus across all stages. Lactobacillus was particularly abundant in the crop at early stages (3 and 28 days), while the ceca exhibited a transition towards the dominance of genus Phocaeicola by day 35. Microbial richness and evenness increased with age, reflecting microbiome maturation, and the analyses of the microbial community composition revealed distinct spatiotemporal differences, with the ceca on day 35 showing the highest differentiation. Pathogen analysis highlighted a peak in poultry-associated taxa Campylobacter, Staphylococcus, and Clostridium paraputrificum in 3-day-old Kadaknath, particularly in the small intestine, underscoring the vulnerability of early growth stages. These findings provide critical insights into age-specific microbiome development and early life-stage susceptibility to pathogens, emphasizing the need for targeted interventions to optimize poultry health management and growth performance.
    University Bibliography Jena:
    fsu_mods_00023419External link

  10. Ultrafast and accurate sequence alignment and clustering of viral genomes

    Year of publicationPublished in:Nature methods: techniques for life scientists and chemists A. Zielezinski, A. Gudyś, J. Barylski, K. Siminski, P. Rozwalak, B. Dutilh, S. Deorowicz
    University Bibliography Jena:
    fsu_mods_00025017External link

  11. Chemical characteristics vectors map the chemical space of natural biomes from untargeted mass spectrometry data

    Year of publicationPublished in:Journal of Cheminformatics P. Peets, A. Litos, K. Dührkop, D. Garza, J. van der Hooft, S. Böcker, B. Dutilh
    University Bibliography Jena:
    fsu_mods_00025218External link

  12. Benchmarking bioinformatic virus identification tools using real-world metagenomic data across biomes

    Year of publicationPublished in:Genome biology : biology for the post-genomic era L. Wu, Y. Wijesekara, G. Piedade, N. Pappas, C. Brussaard, B. Dutilh
    Background: As most viruses remain uncultivated, metagenomics is currently the main method for virus discovery. Detecting viruses in metagenomic data is not trivial. In the past few years, many bioinformatic virus identification tools have been developed for this task, making it challenging to choose the right tools, parameters, and cutoffs. As all these tools measure different biological signals, and use different algorithms and training and reference databases, it is imperative to conduct an independent benchmarking to give users objective guidance. Results: We compare the performance of nine state-of-the-art virus identification tools in thirteen modes on eight paired viral and microbial datasets from three distinct biomes, including a new complex dataset from Antarctic coastal waters. The tools have highly variable true positive rates (0–97%) and false positive rates (0–30%). PPR-Meta best distinguishes viral from microbial contigs, followed by DeepVirFinder, VirSorter2, and VIBRANT. Different tools identify different subsets of the benchmarking data and all tools, except for Sourmash, find unique viral contigs. Performance of tools improved with adjusted parameter cutoffs, indicating that adjustment of parameter cutoffs before usage should be considered. Conclusions: Together, our independent benchmarking facilitates selecting choices of bioinformatic virus identification tools and gives suggestions for parameter adjustments to viromics researchers.
    University Bibliography Jena:
    fsu_mods_00012492External link
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