Biology subjects

Keller, M. I.

Publications and source records attributed to Keller, M. I..

4 recordsLinked to original sources

bioRxiv2026

β-Ketoacyl Synthase II Homologs from a Ladderane-Producing Organism Form a Ketosynthase/Chain Length Factor-like functional heterodimer

Ladderanes are extraordinary, highly strained chemical structures consisting of linearly concatenated cyclobutane rings. Ladderane-containing fatty acids are found in the lipids of anaerobic ammonium oxidizing (anammox) bacteria, reducing the proton permeability of their membranes to support their unique metabolism. Almost nothing is known about the biosynthesis of ladderanes, but a gene cluster unique to ladderane-producing bacteria is likely to be involved. This cluster encodes radical SAM enzymes as well as homologs of enzymes known from fatty acid biosynthesis. Amongst these are two homologs of FabF, the enzyme performing chain elongation in canonical fatty acid synthesis. The presence of two chain-elongating enzymes is unexpected; a single one would be expected to suffice, and the fact that one of the two homologs has a mutated, nonfunctional catalytic triad deepens the mystery. Here we present an in-depth characterization of the FabF homologs from anammox organisms, using biochemistry, enzymology, structural biology and computational biology. We show that the two homologs form a heterodimer analogous to the ketosynthase/chain length factor complexes known from polyketide synthases. This heterodimer is capable of performing the decarboxylation of malonate-loaded acyl carrier protein, thus initiating fatty acid biosynthesis. The crystal structure of the heterodimer explains how homodimer formation is avoided, and shows the details of the substrate binding tunnel. Mechanism-based crosslinking studies of wild-type and mutant heterodimers show the influence of residues on both subunits on substrate preference (which differs from canonical FabFs), and, together with computational studies, the crystal structure of the heterodimer in complex with substrate-loaded ACP helps explain its preference for ladderane-specific ACP. The results clearly refute an early proposal for a ladderane biosynthetic mechanism and greatly expand our current knowledge on how anammox bacteria produce their extraordinary lipids.

biochemistry↗

bioRxiv2025

Metalog: curated and harmonised contextual data for global metagenomics samples

Metagenomic sequencing enables the in-depth study of microbes and their functions in humans, animals and the environment. While sequencing data is deposited in public databases, the associated contextual data is often not complete and needs to be retrieved from primary publications. This lack of access to sample-level metadata like clinical data or in situ observations impedes cross-study comparisons and meta-analyses. We therefore created the Metalog database, a repository of manually curated metadata for metagenomics samples across the globe. It contains 73,082 samples from humans (including 58,506 of the gut microbiome), 10,703 animal samples, 5,146 ocean water samples, and 21,802 samples from other environmental habitats such as soil, sediment, or fresh water. Samples have been consistently annotated for a set of habitat-specific core features, such as demographics, disease status and medication for humans, host species and captivity status for animals, and filter sizes and salinity for marine samples. Additionally, all original metadata is provided in tabular form, simplifying focused studies e.g. into nutrient concentrations. Pre-computed taxonomic profiles facilitate rapid data exploration, while links to the SPIRE database enable genome-based analyses. The database is freely available for browsing and download at https://metalog.embl.de/.

microbiology↗

bioRxiv2024

Refined Enterotyping Reveals Dysbiosis in Global Fecal Metagenomes

BackgroundEnterotypes describe human fecal microbiomes grouped by similarity into clusters of microbial community composition, often associated with disease, medications, diet, and lifestyle. Numbers and determinants of enterotypes have been derived by diverse frameworks and applied to cohorts that often lack diversity or inter-cohort comparability. ResultsTo overcome these limitations, we selected 16,772 fecal metagenomes collected from 38 countries to revisit the enterotypes using state-of-the-art fuzzy clustering and found robust clustering regardless of underlying taxonomy, consistent with previous findings. Quantifying the strength of enterotype classifications enriched the enterotype landscape, also reflecting some continuity of microbial compositions. As the classification strength was associated with the patients health status, we established an "Enterotype Dysbiosis Score" (EDS) as a latent covariate for various diseases. ConclusionThis global study confirms the enterotypes, reveals a dysbiosis signal within the enterotype landscape, and enables robust classification of metagenomes with an online "Enterotyper" tool, allowing reproducible analysis in future studies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/607711v3_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1611a2org.highwire.dtl.DTLVardef@dfbb57org.highwire.dtl.DTLVardef@848ac0org.highwire.dtl.DTLVardef@1b15808_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Fecal microbial load is a major determinant of gut microbiome variation and a confounder for disease associations

The microbiota in individual habitats differ both in relative composition and absolute abundance. While sequencing approaches determine only the relative abundances of taxa and genes, experimental techniques for absolute abundance determination are rarely applied to large-scale microbiome studies. Here, we developed a machine learning approach to predict fecal microbial loads (microbial cells per gram) solely from relative abundance data. Applied to large-scale datasets (n = 34,539), we demonstrate that microbial load is the major determinant of gut microbiome variation and associated with numerous host factors. We found that for several diseases, the altered microbial load, not the disease itself, was the main driver of the gut microbiome changes. Adjusting for this effect substantially reduced the significance of more than half of the disease-associated species. Our analysis reveals that the fecal microbial load is a major confounder in microbiome studies, highlighting its importance for understanding microbiome variation in health and disease.

microbiology↗