Biology subjects

Kaster, A.-K.

Publications and source records attributed to Kaster, A.-K..

9 recordsLinked to original sources

bioRxiv2026

Integrating Microbial Ecology and Sustainability: Linking Agricultural Waste Gas Streams to Microbial Community Shifts in a Photobioreactor

Photobioreactors (PBRs) coupled to animal housing offer potential for mitigating gaseous emissions such as CO2 and NH3 while simultaneously producing biomass. Here, we present a time-resolved characterization of microbial community dynamics, with a focus on the genetic potential for carbon and nitrogen metabolism. Using a cone-shaped, helical PBR cultivating Arthrospira platensis (Spirulina) and supplied with exhaust air from a chicken house, we characterized microbial communities over continuous exhaust-air exposure and periodic biomass harvesting. Microbiome and gene-centric profiling revealed temporal variation in community composition and in the representation of genes associated with carbon and nitrogen metabolism. Cycle-based dissolved inorganic nitrogen balances showed that the decrease in dissolved inorganic nitrogen was only partially recovered in harvested biomass, while ammonia-oxidizing microorganisms were associated with structured, low-light niches. These observations indicate ammonia-oxidizing potential but do not establish a quantitatively relevant nitrification flux. Structured carrier matrices provided attached-growth niches harboring microbial populations underrepresented in the circulating suspension, while pre-colonized carriers facilitated biomass development during re-inoculation. Overall, our results show that coupling PBRs to agricultural exhaust streams can support biomass production while sustaining spatially structured microbial communities with taxonomic and functional potential. These findings may inform their further development for emission mitigation and circular biomass production.

microbiology↗

bioRxiv2026

Engineered DNA materials shape microbial physiology and ecological selection

Extracellular DNA (eDNA) is both a structural component of microbial biofilms and a potential reservoir of genetic information, yet its role as an ecological material remains largely unexplored. Here we establish engineered extracellular materials as determinants of microbial physiology and community assembly across increasing biological complexity. A three-dimensional DNA hydrogel altered bacterial stress-associated responses, elicited species-dependent phenotypes and transcriptional changes in a defined consortium, and shaped community succession in wastewater-derived microbiomes. Distinct responses to surface-bound oligonucleotides reveal that DNA presentation matters beyond its mere presence. Strikingly, metagenomic sequencing identified rare, hydrogel-specific candidate junctions linking material-derived DNA to microbial genomic sequences, suggesting a previously unexplored interface between extracellular DNA materials and microbial genetic information. These findings reveal a dual role for engineered DNA: its material organization shapes microbial physiology and ecological selection, while its encoded sequences may engage with microbial genomic processes.

microbiology↗

bioRxiv2026

MOFTy: Multimodal Gaussian Process Factor Analysis with Numerical Information Field Theory

Multimodal Gaussian process factor analysis provides a flexible framework for dimensionality reduction in temporally or spatially resolved omics data. Existing approaches, however, typically rely on pre-specified Gaussian process kernel families and do not explicitly separate each latent factor into a component capturing gradual, smooth variation and a complementary component capturing fine-scale, non-smooth variation. Here, we present MOFTy, a Bayesian multimodal factor analysis framework based on numerical information field theory (NIFTy) that replaces fixed kernel families with the flexible correlated field model in NIFTy and enables explicit additive component separation within each latent factor with quantified uncertainty. NIFTy has been successfully applied to high-resolution Bayesian imaging in astrophysics and facilitates scalable, curvature-aware variational inference for efficient posterior approximations. We validate MOFTy on simulated data; applications to published multi-omics data demonstrate that MOFTy disentangles latent spatial structures by separating smooth gradients from localized fine-scale heterogeneity in human glioblastoma and recovers cross-modal patterns in a mouse gastrulation dataset.

bioinformatics↗

bioRxiv2026

Deciphering functional dark matter: Machine and deep learning-based processing of protein embeddings enables targeted function discoveries

The ever-expanding catalogue of uncharacterized proteins - the so called functional dark matter - poses a major challenge for biotechnological and biomedical exploitation. Functional assessment of most proteins is hindered by the technical limitations of annotation transfer and by the propagation of erroneous annotations in databases. The common denominator here is the reliance on sequence similarities. However, these become inaccurate below certain thresholds and can diverge even at sequence identities around 70%. To approach this challenge, we implemented a strategy using embeddings generated by protein language models for targeted function discovery (PE-TFD). Datasets of proteins representing target as well as non-target functions were used to train supervised learning models. The resulting ensemble models yielded interpretable prediction scores, enabling the exploration of databases without relying on multiple sequence alignments or structural information. We here tested PE-TFD for the discovery of novel hydrogenases as proof-of-concept, resulting in the novel discovery of 773 [NiFe] and 1,929 [FeFe] hydrogenases that were not detected by established sequence- or profile-based approaches. Structural analyses supported their non-random nature and further revealed a significant number of enzymes lacking prior functional annotation. Our framework therefore enables interpretable function discovery in large-scale datasets and the exploitation of functional dark matter. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=148 HEIGHT=200 SRC="FIGDIR/small/728830v1_ufig1.gif" ALT="Figure 1"> View larger version (67K): org.highwire.dtl.DTLVardef@1d69b0corg.highwire.dtl.DTLVardef@5d5ee8org.highwire.dtl.DTLVardef@1ddd7org.highwire.dtl.DTLVardef@8b5b97_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Chlorophyll a degradation in Prokaryotes

Chlorophyll is one of the most abundant pigments on Earth. Although its degradation is well understood in plants, the role of prokaryotes in this process - despite their vast metabolic capabilities - remains unknown. Recent developments in the field of AI-predicted protein structures have opened new avenues for investigating functional homologies between evolutionary-distant organisms previously inaccessible through traditional sequence- or profile-based methods. Here, we present the first evidence of Chlorophyll a (Chl a) degradation by prokaryotes, discovered through a novel bioinformatic framework which bridges the gap across the domains of life via structural alignments of functionally characterised plant proteins, followed by structure similarity graph-based clustering. Metagenomic sequencing data was assembled and binned, yielding over 70,000 medium- to high-quality genomes in total, furthermore publicly available datasets containing genomes from prokaryotic isolates, metagenome-assembled genomes, as well as single-cell genomes were then mined for prokaryotic homologues of Chl a degradation genes. Our analysis revealed over 400 genomes from diverse taxonomic groups and habitats that possess a complete pathway, more than 50% stemming from isolates. Additionally, many other genomes harbour partial pathways, suggesting that Chl a degradation capabilities are globally widespread across diverse ecosystems. We then validated our in silico findings using the model organism Shewanella acanthi and confirmed its Chl a degradation capability via growth experiments, fluorescence spectroscopy and HPLC analyses. Our findings reveal a previously unrecognised pathway in prokaryotes, highlighting the power of structure-based remote homology detection for uncovering metabolic capabilities and evolutionary relationships.

microbiology↗

bioRxiv2025

Health or disease: a question of rhizomicrobial ecology? The case of Grapevine Trunk Disease

AimsThe incidence of the apoplectic breakdown associated with grapevine trunk diseases (GTDs) is promoted by climate change, which has become a challenge for viticulture worldwide. Outbreak of these conditional diseases is expected to depend on the rhizomicrobiome. However, the impact of the rhizomicrobiome on grapevine resilience has remained poorly understood, particularly regarding its ecological aspects. This study explores the link between GTDs, the rhizomicrobiome, and soil chemistry in vineyards along the Upper Rhine. MethodsUsing amplicon sequencing for both fungal and prokaryotic communities, we show that around half of the fungal rhizosphere community is endowed with pathotrophic potential, independently of the health status of the plant, including seventeen previously reported GTD-associated taxa, predominantly Black Foot Disease. ResultsIn contrast to fungi, bacterial diversity is shifted depending on the micronutrients Fe, Cu, Mn, and Zn. Moreover, taxa enriched in the rhizosphere of asymptomatic vines, such as Pseudophialocephala and Collarina for the mycobiome, and Caulobacter, Kitasatospora, and Entotheonellaceae for the bacteriome, showed correlations with soil properties. The most prominent feature associated with disease outbreaks was drastic changes of microbial co-occurrence networks. These were significantly increased in the fungi, especially for GTDs taxa, such as Fomitoporia, Stereum, Phaeomoniella, and Neofusicoccum. By contrast, there was a depletion of many bacteria and their microbial interactions under disease outbreak such as Isoptericola, Caulobacter, Rhodomicrobium and Thioprofundum. ConclusionThus, likely microbial interactions and not the mere presence of GTDs taxa explains disease outbreak. This finding opens new strategies for sustainable management of GTDs.

ecology↗

bioRxiv2025

Cover crop root channels promote bacterial adaptation to drought in the maize rhizosphere

BackgroundIncreasing drought frequency poses a significant threat to agricultural productivity. A promising strategy to enhance crop resilience against drought is the utilisation of root channels left by winter cover crops, which can improve access to subsoil water and nutrients for subsequent cash crops like maize (Zea mays L.). The impact of drought on bacterial communities inhabiting these root channels remains largely unknown. Here, we investigated drought-induced shifts in maize rhizosphere bacterial communities and their functional adaptation in cover crop root channels across three soil types in northern Germany (Luvisol, Podzol, and Phaeozem). ResultsUsing a multi-omics approach (16S rRNA gene amplicon sequencing, qPCR, and metaproteomics), we identified significant taxonomic and functional responses to drought. A rise in the abundance of K-strategist bacterial communities indicate a shift towards stress-tolerant populations with drought. Under drought stress, the relative abundances of Acidobacteriota, Actinomycetota, Planctomycetota, and Pseudomonadota increased, while Chloroflexota, Methylomirabilota, Ca. Patescibacteria, and Verrucomicrobiota declined. Functional analyses revealed that drought-stressed aerobic taxa among the Pseudomonadota and Verrucomicrobiota upregulated the glyoxylate cycle, potentially enhancing carbon and energy conservation, and increased antioxidant defences (catalase-glutathione peroxidase and methionine cycle-transsulfuration pathway). These drought-mitigating strategies were especially pronounced in root channels formed by Brassicaceae and Poaceae cover crops in the Luvisol and Podzol soils. ConclusionsThese findings demonstrate the functional plasticity of rhizosphere bacterial communities in reused root channels in response to drought, highlighting the potential to leverage microbiome-mediated resilience for agricultural practices. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/651044v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@7c3f69org.highwire.dtl.DTLVardef@127182forg.highwire.dtl.DTLVardef@1a4bb61org.highwire.dtl.DTLVardef@9f7c4_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Midi-metagenomics: A novel approach for cultivation independent microbial genome reconstruction from environmental samples

Since the majority of microbial organisms still evade cultivation attempts, genomic insights into many taxa are limited to cultivation-independent approaches. However, current methods of metagenomics and single cell genome sequencing have individual drawbacks, which can limit the quality as well as completeness of the reconstructed genomes. Current attempts to combine both approaches still use amplification techniques which are prone to bias. Here, we propose a novel approach for the purpose of genome reconstructions, that utilizes the potential of cell sorting for targeted enrichment and depletion of different cell types to create distinct cell fractions of sufficient size, circumventing amplification. By distributing sequencing efforts over these fractions as well as the original sample, co-assemblies become highly optimized for co-abundance variation based binning approaches. "Midi-metagenomics" enables accurate metagenome assembled genome (MAG) reconstruction from individual sorted samples with higher quality than co-assembly of multiple distinct samples and has potential for the targeted enrichment and sequencing of microbial dark matter.

genomics↗

bioRxiv2022

A genetically-encoded three-colour stress biosensor reveals multimodal response at single cell level and spatiotemporal dynamics of biofilms

The plethora of chemical, physical, and biological factors that can damage microbial cells has triggered the evolution of sophisticated stress response (SR) mechanisms. While individual SR pathways have been monitored with genetically encoded reporters, sensor concepts for the detection of multimodal effects of stressing conditions in living microorganisms are still lacking. Orthogonally detectable red, green, and blue fluorescent proteins combined in a single vector system, dubbed RGB-S reporter, enable the simultaneous, independent and real-time analysis of the stress response in Escherichia coli to physiological stress, genotoxicity, and cytotoxicity. The sensor system can be read out via conventional fluorescence microscopy or microtiter plate analysis and can also be combined with Fluorescent Activated Cell Sorting (FACS) and subsequent transcriptome analysis. Various stressors, such as the biotechnologically relevant 2-propanol, lead to the activation of one, two or all three SRs, which can have a significant impact on non-stress-related metabolic pathways. Implemented in microfluidic cultivation with confocal fluorescence microscopy imaging, the technology enabled spatiotemporal analysis of live biofilms to discover stratified subpopulations of bacteria with heterogeneous stress responses.

microbiology↗