Biology subjects

Malfertheiner, L.

Publications and source records attributed to Malfertheiner, L..

8 recordsLinked to original sources

bioRxiv2026

Autoinducer-2 functions as both a quorum sensing and metabolic signal in Escherichia coli

Bacteria integrate diverse environmental signals to coordinate behavior, yet the relationship between nutrient sensing and quorum sensing (QS) remains incompletely understood. Autoinducer-2 (AI-2) is unique among QS signals in that its production is tightly linked to central metabolism, raising fundamental questions about the boundary between metabolic and signaling functions. In Escherichia coli, AI-2 coordinates collective behaviors through the lsr operon, whose expression is controlled not only by the AI-2-responsive repressor LsrR but also by the cAMP receptor protein (CRP), placing it at the intersection of carbon sensing and population-level signaling. While inhibition of lsr operon expression by PTS sugars such as glucose was previously established, we demonstrate that non-PTS sugars similarly suppress lsr expression through CRP, further decoupling QS activation from cell density and coupling it to carbon source availability. Systematic analysis of Enterobacteriaceae genomes reveals that CRP binding sites in the lsr promoter region are broadly conserved, indicating that metabolic modulation of AI-2 signaling is an ancestral regulatory feature. Importantly, using a FRET-based biosensor, we show that AI-2 uptake modulates intracellular cAMP levels in a manner resembling non-PTS carbon source transport, suggesting that AI-2 may have originally functioned as a nutrient substrate, with its signaling role emerging subsequently or co-evolving alongside. In support of this hypothesis, we isolated soil- and phyllosphere-associated bacteria capable of utilizing AI-2 as a sole carbon source. Our findings reveal an underappreciated metabolic dimension of AI-2 QS and suggest an evolutionary trajectory in which AI-2 signaling emerged from ancestral carbon utilization pathways. ImportanceQS allows bacteria to coordinate collective behaviors by detecting secreted signaling molecules, yet the evolutionary origins of these systems remain poorly understood. AI-2, one of the most broadly conserved bacterial signals, is derived from central metabolism and processed by machinery in E. coli that strikingly resembles a sugar utilization system. Here, we show that nutrient availability overrides cell density as the primary determinant of AI-2 responsiveness, that this regulatory logic is conserved among Enterobacteriaceae genomes, and that environmental bacteria can grow on AI-2 as a sole carbon source. These findings reframe AI-2 as a signal embedded within, and potentially evolved from, nutrient sensing pathways, with direct implications for understanding how byproducts of cellular metabolism can acquire signaling functions.

microbiology↗

bioRxiv2025

The MicrobeAtlas database: Global trends and insights into Earth's microbial ecosystems

Environmental DNA sequencing has revolutionized our understanding of microbial diversity and ecology. Microbiomes have now been sequenced across the entire planet--from the deep subsurface to the mountain tops--covering a myriad of hosts, biomes, and conditions. Yet, the diversity of sequencing and processing strategies hampers universal insights. MicrobeAtlas unifies more than two million microbiome samples in a single resource, harmonized to facilitate discoveries across technologies. Communities are hierarchically quantified at adjustable SSU rRNA marker gene resolution and feature detailed metadata, including rich geographic information. Connections to genome, phenotype, and ecological resources enable multimodal insights. Microbial lineages can be reliably tracked across environments, including a long tail of rare, uncharacterized species. Recurring community structures and geographic preferences become apparent, and global, taxonomy-specific generalism trends emerge. With MicrobeAtlas (www.microbeatlas.org), both known and newly described species and communities can readily be placed into ecological context, taking full advantage of earlier work.

bioinformatics↗

bioRxiv2025

Microbiome variations in osteoarthritis reflect aging and metabolic factors, not the disease

The gut microbiome is crucial for human health. Its disruption has been linked to several chronic diseases, including joint disorders. The gut-joint axis has been implicated in the pathogenesis of osteoarthritis (OA), but conflicting findings and study limitations have led to uncertainty regarding the role of microbiota. We conducted a multi-cohort gut microbiota analysis in 1,395 OA patients from four European cohorts (Lifelines, EstMB, FINRISK 2002, TwinsUK), using stringent exclusion criteria and matched controls. When assessing microbial diversity, taxa, functional gene profiles, and gut permeability biomarkers, no significant differences were found between OA and controls. Although this does not exclude a causal contribution of the microbiota in the gut-joint-axis, its dysbiosis does not seem to be linked with OA disease progression. Instead, age and BMI appeared as the main contributing factors to microbiome changes. Microbiome studies in complex diseases often face challenges such as small sample sizes, batch effects, and limited ability to match appropriate controls, particularly in single-cohort designs. By combining data from multiple large cohorts, we were able to mitigate these limitations and provide a more robust assessment of microbiome association with OA. Our findings emphasize the need for rigorous study design in microbiome research and challenge the OA-gut dysbiosis hypothesis.

microbiology↗

bioRxiv2025

Enhanced semantic classification of microbiome sample origins using Large Language Models (LLMs)

Over the past decade, central sequence repositories have expanded significantly in size. This vast accumulation of data holds value and enables further studies, provided that the data entries are well annotated. However, the submitter-provided metadata of sequencing records can be of heterogeneous quality, presenting significant challenges for re-use. Here, we test to what extent large language models (LLMs) can be used to cost-effectively automate the re-annotation of sequencing records against a simplified classification scheme of broad ecological environments with relevance to microbiome studies, without retraining. We focused on sequencing samples taken from the environment, for which metadata is important. We employed OpenAI Generative Pretrained Transformer (GPT) models, and assessed scalability, time and cost-effectiveness, as well as performance against a diverse, hand-curated ground-truth benchmark with 1000 examples, that span a wide range of complexity in metadata interpretation. We observed that annotation performance markedly outperforms that of a baseline, manually curated, non-machine-learning keyword-based approach. Changing models (or model parameters) has only minor effects on performance, but prompts need to be carefully designed to match the task. We applied the optimized pipeline to more than 3.8 million sequencing records from the environment, providing coarse-grained yet standardized sampling site annotations covering the globe. Our work demonstrates the effective use of LLMs to simplify and standardize annotation from complex biological metadata.

bioinformatics↗

bioRxiv2025

Unravelling the Core and Accessory Genome Diversity of Enterobacteriaceae in Carbon Metabolism

Enterobacteriaceae are commonly colonizing animal guts and impact health. While strain-specific metabolic features can promote gut colonization, we lack systematic knowledge regarding metabolic diversity and the core metabolism shared among Enterobacteriaceae. To address this gap, we have analyzed the pan-genome of nearly 20,000 genomes. We found that genes necessary for monosaccharide-fuelled mixed acid fermentation are part of the Enterobacteriaceae core genome, while most genes for anaerobic respiration and most carbohydrate utilization genes belong to the accessory genome. Understanding Enterobacteriaceaes metabolic capacity helps clarify the distinction of nutrients consumed by all Enterobacteriaceae, and niche-defining nutrient sources, which are genus-, species- or strain-specific. This knowledge sheds light on bacterial nutrient exploitation during gut colonization in health and disease, aiding in the development of targeted interventions for microbiome research and infectious disease control. The theoretical framework described here can also be adapted to analyze core physiological characteristics of other microbiota taxa.

microbiology↗

bioRxiv2024

Habitat filtering but not microbiota origin controls microbiome transplant outcomes in soil

Human activities cause global losses of soil microbiome diversity and functionality. Microbiota transplants offer a potential solution, but the factors influencing transplant success remain unclear. We investigated how microbiota origin affects microbiome mergers, hypothesizing that native strains through niche preference are better adapted to their habitat and will outcompete non-native ones. To test this, we contrasted transplants between soil microcosm-cultured topsoil or lakewater communities with a community of 21 soil bacteria (SynCom). In both cases, SynCom transplant increased resident productivity but permanently shifted compositions, although its abundance dropped from an initial 50-80% to <1% within two months. Both merged and non-merged communities resembled natural soil microbiota in comparisons with over 81,000 soil, sediment and lake compositional data. Our results show that habitat filtering and niche competition, more than microbiota origin, determine transplant outcomes. Despite the limited proliferation of SynCom transplants, their capacity to instill lasting community trajectory changes opens new paths for microbiome engineering. TEASEREven transiently present microbiota transplants can alter resident microbiome composition through processes governed by habitat filtering.

microbiology↗

bioRxiv2024

Community conservatism is widespread throughout microbial phyla and environments

Evolution gives rise to various long-term phenomena, including Phylogenetic signal, which describes the tendency of related biological taxa to resemble each other in morphology and function. Related taxa tend to also live in similar ecological niches - this trend is termed Niche conservatism. Both concepts are widely used to understand crucial aspects of evolu1on and specia1on and are well-established in animals and plants. The extension of these concepts to microorganisms is however challenging and thus far only assumed. Here, we hypothesize that two closely related microbial species, if indeed similar in both their morphology and their ecological niche, should be found in samples with similar community compositions. We propose "community conservatism" to refer to this, and leverage a database with millions of samples and hundreds of thousands of pairs of microbial taxa to assess their relatedness and the similarity of the communities they occupy. Our findings reveal that community conservatism can be observed globally in all environments and phyla tested, to varying extents. Ecologically specialized taxa show a stronger community conservatism signal than generalists, and the signal can be discerned over nearly all taxonomic ranks. Analyzing community conservatism shows promise to advance our understanding of evolution, speciation, and the mechanisms governing community assembly in microorganisms. Furthermore, we propose it can be used to reintegrate ecological parameters into Operational Taxonomic Unit delimitation.

ecology↗

bioRxiv2023

Discovery of Theta Ribozymes in Gut Phages-Implications for tRNA and Alternative Genetic Coding

Ribozymes, relics of the "RNA world", are essential across all domains of life. Nonetheless, the functions and genomic contexts of recently discovered small ribozymes, such as minimal hepatitis delta virus (HDV)-like ribozymes, remain elusive. Using bioinformatic analyses, we identified a novel subfamily of minimal HDV-like ribozymes, coined theta ribozymes. Hundreds of unique examples were found adjacent to viral tRNAs within Caudoviricetes bacteriophages of the mammalian gut virome. In vitro experiments confirm site-specific self-scission activity, suggesting their involvement in processing tRNA 3-trailers. Intriguingly, a significant fraction of theta ribozymes is associated with viral suppressor tRNAs, potentially regulating the late-stage assembly of recoded bacteriophages. These findings advance the understanding of RNA-based mechanisms underlying the intricate interplay between the bacterial and viral parts of the mammalian gut microbiome. One-Sentence SummaryNewly unveiled theta ribozymes associate with suppressor tRNAs of alternatively coded gut phages: a potential lytic switch.

bioinformatics↗