Biology subjects

Kremer, K.

Publications and source records attributed to Kremer, K..

7 recordsLinked to original sources

bioRxiv2026

Multi-Chain Hamiltonian Replica Exchange Framework for Probing Transient Helices and Order-Disorder Transitions in Proteins

Simulations have emerged as a pillar in biophysics to understand behavior at the molecular scale, in particular for proteins such as intrinsically disordered proteins. These often show transient folding with long-lived states that are challenging to efficiently sample using conventional simulations. Here, we show that Hamiltonian replica-exchange at the level of hydrogen bonds can be used to systematically explore the conformational landscape of proteins. Investigating the IM30 protein, a partially alpha helical protein, under the PLUM coarse-grain force-field, we show that this approach straightforwardly allows characterization of local helix stability, which would be otherwise hard to obtain. For instance, we show that some regions of the conserved coiled-coil structure are less stable than others. By combining the different replicas with principal component analysis, we are able to dissect the conformational landscape of the IM30 protein. Taken together, this indicates that enhanced sampling remains an important part of simulations, allowing insights that cannot be easily obtained in traditional simulations.

biophysics↗

bioRxiv2026

SUMO paralogues differentially affect phase separation and aggregation of intrinsically disordered proteins

SUMO, the small ubiquitin-like modifier, modulates interactions of folded proteins, but also affects the dynamics of biomolecular condensates. Moreover, SUMO can directly impinge on the biophysical properties of its targets, often increasing their solubility. TDP-43 is an RNA-binding protein containing an intrinsically disordered domain that participates in protein phase separation. Its aggregation, linked to neurodegenerative diseases, is counteracted by SUMOylation, but the underlying principles are poorly understood. We now reveal distinct mechanisms of how the two isoforms, SUMO1 and SUMO2, act on TDP-43. While SUMO1 inhibits phase separation by blocking TDP-43s self-assembly site, SUMO2 enhances phase separation via proximity-induced self-interaction involving its N-terminus and promotes a liquid-like state that prevents aggregation. The latter represents a general principle by which SUMO solubilises other targets. Our findings provide insight into how SUMOylation regulates transitions between soluble, liquid-like and aggregated states.

molecular biology↗

bioRxiv2025

Long vs. short read sequencing for microbial ecology of sedimentary environments: a case study from Lake Arnon, Switzerland

The subsurface biosphere remains poorly characterized, with many resident microorganisms uncultured and lacking genomic references. Despite the growing accessibility of shotgun metagenomics, 16S rRNA gene sequencing remains a standard tool for microbial community profiling, often relying on sequence similarity to reference databases such as SILVA to infer taxonomy and potential function. However, in environments with low biomass and high proportions of unknown lineages, such as deeper sedimentary environments, the accuracy of these inferences and our ability to capture rare taxa remain uncertain. A better inference of these rare taxa may now be possible with the advent of accurate long-read applications that have recently become available. Here we provide a comparison of long-read (PacBio) and short-read (Illumina NextSeq) 16S rRNA approaches for microbial communities from a sediment core of Lake Arnon (Switzerland). We compared community composition in environmental samples and mock controls to evaluate the strengths and limitations of each method. While sequencing technology significantly influenced observed community structure, sediment depth had an even stronger effect. Taxonomic profiles were broadly consistent across methods for most bacterial groups, but archaeal diversity was underrepresented in the long-read data, likely due to primer mismatch. When detected, long-read sequencing offered more accurate taxonomic resolution, often down to the species level, enabling better inference of metabolic potential. Beta diversity patterns were similar at broad taxonomic levels between methods, though more detailed metrics such as species contributions to beta diversity (SCBD) and co-occurrence networks showed enhanced resolution and specificity in long-read datasets. Our results highlight the critical importance of primer design, in particular for capturing archaeal taxa that play important roles in the deep biosphere. With improved primer coverage and continued cost reductions, long-read sequencing holds strong potential for advancing our understanding of subsurface microbial identity, structure and function.

ecology↗

bioRxiv2025

Limited value of Nanopore adaptive sampling in a long-read metagenomic profiling workflow of clinical sputum samples

Oxford Nanopore adaptive sampling (NAS) is a method by which the long-read sequencing flowcell accepts or rejects DNA molecules that are actively being sequenced based on their initial [~]500bp sequences, selectively increasing target data output. NAS promises up to 5-10x enrichment of target sequencing yield without additional sample preparation, but this optimal performance is dependent on ideal sample parameters which may be difficult to achieve under many real-world use-cases. We evaluated the use of NAS with the current R10.4.1 flowcell chemistry for profiling clinical sputum metagenomes, achieving at best 3.1x enrichment of bacterial sequence output due to the shorter read lengths ([~]2.5kb) from the PCR amplification necessary to compensate for low DNA extraction yields. More critically, we encountered rapid pore loss during our runs that reduced total sequencing yield by an estimated 80%. We were unable to mitigate the pore loss despite extensive attempts to reduce contaminant carry-over, and we could not determine its cause but ruled out NAS and pore underloading as contributing factors. We conclude that the utility of NAS is often limited by the characteristics of the metagenomic sample studied, and that the factors contributing to pore loss need to be resolved before ONT sequencing can be reliably applied to long-read metagenomics.

microbiology↗

bioRxiv2025

Verification of emerging genomic mutations in Mycobacterium tuberculosis allows transmission chains to be distinguished in an epidemiological typing cluster extending over thirty years.

Whole genome sequencing (WGS) is able to identify epidemiological links between Mycobacterium tuberculosis isolates. Recent clustering can be ruled out using a pre-defined single nucleotide polymorphism (SNP) threshold. If WGS clusters grow significantly over time limited genetic variability hampers epidemiological investigations. Newly emerging (informative) SNPs in isolates of an extended cluster growing for more than 30 years to >150 cases in the Netherlands were analysed. WGS data was analyzed from 61 sequencing files from 54 patients. Genomic positions that varied within the cluster isolates were carefully screened for minority populations in other isolates from the cluster. A transmission scheme was generated on the basis of WGS data alone then compared to the epidemiological information available. Fifty-two informative SNPs were identified, eight of which were also detected as mixed variants. One emerging SNP in dnaA (1199G>A R400H) has been observed in other transmitted strains and may be under selection. There was high concordance between the transmission chains suggested on basis of the newly emerging SNPs and scenarios identified using classical epidemiological cluster investigations. Analysis of filtered SNPs accumulating in the genome of M. tuberculosis in large clusters contains information on transmission dynamics and can be used to support epidemiological investigations.

microbiology↗

bioRxiv2024

Multiple levels of transcriptional regulation control glycolate metabolism in Paracoccus denitrificans

The hydroxyacid glycolate is a highly abundant carbon source in the environment. Glycolate is produced by unicellular photosynthetic organisms and excreted at petagram scales to the environment, where it serves as growth substrate for heterotrophic bacteria. In microbial metabolism, glycolate is first oxidized to glyoxylate by the enzyme glycolate oxidase. The recently described {beta}-hydroxyaspartate cycle (BHAC) subsequently mediates the carbon-neutral assimilation of glyoxylate into central metabolism in ubiquitous Alpha- and Gammaproteobacteria. While the reaction sequence of the BHAC was elucidated in Paracoccus denitrificans, little is known about the regulation of glycolate and glyoxylate assimilation in this relevant alphaproteobacterial model organism. Here, we show that regulation of glycolate metabolism in P. denitrificans is surprisingly complex, involving two regulators, the IclR-type transcription factor BhcR that acts as an activator for the BHAC gene cluster, as well as the GntR-type transcriptional regulator GlcR, a previously unidentified repressor that controls the production of glycolate oxidase. Furthermore, an additional layer of regulation is exerted at the global level, which involves the transcriptional regulator CceR that controls the switch between glycolysis and gluconeogenesis in P. denitrificans. Together, these regulators control glycolate metabolism in P. denitrificans, allowing the organism to assimilate glycolate together with other carbon substrates in a simultaneous fashion, rather than sequentially. Our results show that the metabolic network of Alphaproteobacteria shows a high degree of flexibility to react to the availability of multiple substrates in the environment.

microbiology↗

bioRxiv2020

Investigating the conformational ensembles of intrinsically-disordered proteins with a simple physics-based model

Intrinsically disordered proteins (IDPs) play an important role in an array of biological processes but present a number of fundamental challenges for computational modeling. Recently, simple polymer models have re-gained popularity for interpreting the experimental characterization of IDPs. Homopolymer theory provides a strong foundation for understanding generic features of phenomena ranging from single-chain conformational dynamics to the properties of entangled polymer melts, but is difficult to extend to the copolymer context. This challenge is magnified for proteins due to the variety of competing interactions and large deviations in side-chain properties. In this work, we apply a simple physics-based coarse-grained model for describing largely disordered conformational ensembles of peptides, based on the premise that sampling sterically-forbidden conformations can compromise the faithful description of both static and dynamical properties. The Hamiltonian of the employed model can be easily adjusted to investigate the impact of distinct interactions and sequence specificity on the randomness of the resulting conformational ensemble. In particular, starting with a bead-spring-like model and then adding more detailed interactions one by one, we construct a hierarchical set of models and perform a detailed comparison of their properties. Our analysis clarifies the role of generic attractions, electrostatics and side-chain sterics, while providing a foundation for developing efficient models for IDPs that retain an accurate description of the hierarchy of conformational dynamics, which is nontrivially influenced by interactions with surrounding proteins and solvent molecules.

biophysics↗