Biology subjects

Mussig, A. J.

Publications and source records attributed to Mussig, A. J..

6 recordsLinked to original sources

bioRxiv2026

The MiDAS global genome catalog: 53,501 long-read MAGs representing all core prokaryotic genera in the global activated sludge microbiome

Wastewater treatment relies on complex microbial communities, yet existing genome-resolved references for this essential engineered ecosystem remain dominated by short-read assemblies, limiting genome contiguity and linkage between taxonomic and metabolic function. We applied long-read sequencing to activated sludge from 83 globally distributed plants, reconstructing 53,501 metagenome-assembled genomes to establish the Microbial Database of Activated Sludge (MiDAS) global genome catalog. The catalog encompasses high-quality genomes for 12,047 prokaryotic species, 82% of which are not represented in GTDB release 226, and provides a median of 32 high-quality genomes for each of the 250 core prokaryotic genera previously defined in our MiDAS global 16S rRNA gene survey. This enables analyses of predicted functional traits and their ecological context, for example, we identified two sparsely represented Nitrospiraceae genera with conserved nitrite-oxidation genes that are abundant in higher-temperature wastewater treatment plants. In summary, the MiDAS genome catalog provides a framework for linking taxonomy, metabolism and ecological roles in wastewater treatment systems globally.

microbiology↗

bioRxiv2024

Recovery of highly contiguous genomes from complex terrestrial habitats reveals over 15,000 novel prokaryotic species and expands characterization of soil and sediment microbial communities

Genomes are fundamental to understanding microbial ecology and evolution. The emergence of high-throughput, long-read DNA sequencing has enabled recovery of microbial genomes from environmental samples at scale. However, expanding the microbial genome catalogue of soils and sediments has been challenging due to the enormous complexity of these environments. Here, we performed deep, long-read Nanopore sequencing of 154 soil and sediment samples collected across Denmark and through an optimised bioinformatics pipeline, we recovered genomes of 15,314 novel microbial species, including 4,757 high-quality genomes. The recovered microbial genomes span 1,086 novel genera and provide the first high-quality reference genomes for 612 previously known genera, expanding the phylogenetic diversity of the prokaryotic tree of life by 8 %. The long-read assemblies also enabled the recovery of thousands of complete rRNA operons, biosynthetic gene clusters and CRISPR-Cas systems, all of which were underrepresented and highly fragmented in previous terrestrial genome catalogues. Furthermore, the incorporation of the recovered MAGs into public genome databases significantly improved species-level classification rates for soil and sediment metagenomic datasets, thereby enhancing terrestrial microbiome characterization. With this study, we demonstrate that long-read sequencing and optimised bioinformatics, allows cost-effective recovery of high-quality microbial genomes from highly complex ecosystems, which remain the largest untapped source of biodiversity for expanding genome databases and filling in the gaps of the tree of life.

bioinformatics↗

bioRxiv2024

Proposal of Patescibacterium danicum gen. nov., sp. nov. in the ubiquitous ultrasmall bacterial phylum Patescibacteriota phyl. nov.

Candidatus Patescibacteria is a diverse bacterial phylum that is notable for members with ultrasmall cell size, reduced genomes, limited metabolic capabilities and dependence on other prokaryotic hosts. Despite the prevalence of the name Ca. Patescibacteria in the scientific literature, it is not officially recognized under the International Code of Nomenclature of Prokaryotes (ICNP) and lacks a nomenclatural type. Here, we rectify this situation by describing two closely related circular metagenome-assembled genomes (MAGs) and by proposing one of them (ABY1TS) to serve as the nomenclatural type for the species Patescibacterium danicumTS gen. nov., sp. nov. according to the rules of the SeqCode. Rank-normalized phylogenomic inference confirmed the stable placement of P. danicumTS in the class ABY1 within Ca. Patescibacteria. Based on these results, we propose Patescibacterium gen. nov. to serve as the type genus for associated higher taxa, including the phylum Patescibacteriota phyl. nov. We complement our proposal with a genomic characterization, metabolic reconstruction, and biogeographical analysis of Patescibacterium. Our results confirm small genome sizes (< 1Mbp), low GC content (>36%), and the occurrence of long gene coding insertions in the 23S rRNA sequences, along with reduced metabolic potential, inferred symbiotic lifestyle, and a global distribution. In summary, this effort, focused on the fourth-largest phylum in the bacterial domain, aims to provide nomenclatural stability in the scientific literature.

microbiology↗

bioRxiv2022

GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database

The Genome Taxonomy Database (GTDB) and associated taxonomic classification toolkit (GTDB-Tk) have been widely adopted by the microbiology community. However, the growing size of the GTDB bacterial reference tree has resulted in GTDB-Tk requiring substantial amounts of memory (~320 GB) which limits its adoption and ease of use. Here we present an update to GTDB-Tk that uses a divide-and-conquer approach where user genomes are initially placed into a bacterial reference tree with family-level representatives followed by placement into an appropriate class-level subtree comprising species representatives. This substantially reduces the memory requirements of GTDB-Tk while having minimal impact on classification. AvailabilityGTDB-Tk is implemented in Python and licenced under the GNU General Public Licence v3.0. Source code and documentation are available at: https://github.com/ecogenomics/gtdbtk. Contactp.chaumeil@uq.edu.au or donovan.parks@gmail.com

bioinformatics↗

bioRxiv2020

A rank-normalized archaeal taxonomy based on genome phylogeny resolves widespread incomplete and uneven classifications

An increasing wealth of genomic data from cultured and uncultured microorganisms provides the opportunity to develop a systematic taxonomy based on evolutionary relationships. Here we propose a standardized archaeal taxonomy, as part of the Genome Taxonomy Database (GTDB), derived from a 122 concatenated protein phylogeny that resolves polyphyletic groups and normalizes ranks based on relative evolutionary divergence (RED). The resulting archaeal taxonomy is stable under a range of phylogenetic variables, including marker genes, inference methods, corrections for rate heterogeneity and compositional bias, tree rooting scenarios, and expansion of the genome database. Rank normalization was shown to robustly correct for substitution rates varying up to 30-fold using simulated datasets. Taxonomic curation follows the rules of the International Code of Nomenclature of Prokaryotes (ICNP) while taking into account proposals to formally recognise the rank of phylum and to use genome sequences as type material. The taxonomy is based on 2,392 quality screened archaeal genomes, the great majority of which (93.3%) required one or more changes to their existing taxonomy, mostly as a result of incomplete classification. In total, 16 archaeal phyla are described, including reclassification of three major monophyletic units from the former Euryarchaeota and one phylum resulting from uniting the TACK superphylum into a single phylum. The taxonomy is publicly available at the GTDB website (https://gtdb.ecogenomic.org).

microbiology↗

bioRxiv2019

Selection of representative genomes for 24,706 bacterial and archaeal species clusters provide a complete genome-based taxonomy

We recently introduced the Genome Taxonomy Database (GTDB), a phylogenetically consistent, genome-based taxonomy providing rank normalized classifications for nearly 150,000 genomes from domain to genus. However, nearly 40% of the genomes used to infer the GTDB reference tree lack a species name, reflecting the large number of genomes in public repositories without complete taxonomic assignments. Here we address this limitation by proposing 24,706 species clusters which encompass all publicly available bacterial and archaeal genomes when using commonly accepted average nucleotide identity (ANI) criteria for circumscribing species. In contrast to previous ANI studies, we selected a single representative genome to serve as the nomenclatural type for circumscribing each species with type strains used where available. We complemented the 8,792 species clusters with validly or effectively published names with 15,914 de novo species clusters in order to assign placeholder names to the growing number of genomes from uncultivated species. This provides the first complete domain to species taxonomic framework which will improve communication of scientific results.

microbiology↗