Biology subjects

von Kleist, M.

Publications and source records attributed to von Kleist, M..

15 recordsLinked to original sources

bioRxiv2026

WarpDemuX-custom - Multiplexed sequence-specific direct RNA sequencing

Nanopore direct RNA sequencing has emerged as a powerful technology for studying RNA and modifications at single-molecule resolution. Although originally developed for polyadenylated RNAs, protocol adaptations have extended its application to non-polyadenylated RNA species, including tRNAs and rRNAs. However, the lack of open and flexible (de)multiplexing solutions remains a limitation for large-scale sequencing studies. Existing community-driven approaches enable multiplexing of polyadenylated RNAs and, more recently, tRNAs, but do not fully address the challenges of targeted sequence-specific Nanopore sequencing of non-polyadenylated RNAs. Here, we present an improved sequence-specific direct RNA sequencing protocol for ribosomal RNAs, achieving enhanced capture and longer read lengths as demonstrated for human 28S rRNA. We complement this protocol with an expanded WarpDemuX software toolbox for flexible sequence-specific (de)multiplexing. We validate the approach using human cell lines carrying knockouts of different C/D box snoRNAs involved in site-specific 2'-O-ribose methylation of 28S rRNA. Our results demonstrate efficient multiplexed detection of sequence-specific RNA molecules and associated modification changes. While established here using rRNA, we validate our approach on another panel of non-polyadenylated RNA species, providing an open and scalable framework for targeted direct RNA sequencing and RNA modification analysis

bioinformatics↗

bioRxiv2026

Increased variability and reduced phenotypic robustness in clonal Drosophila mercatorum

Quantitative genetics predicts that reducing genetic variability should reduce phenotypic variability, a common principle that underlies the widespread use of inbred, isogenic, and clonal animals in biomedical research. Yet extreme homozygosity can also expose recessive deleterious alleles and detoriate developmental buffering, potentially destabilizing rather than canalizing phenotypic outcomes. We tested this conflict directly in Drosophila mercatorum, a facultatively parthenogenic fly species in which pronuclear duplication results in fully homozygous, clonal offspring already after a single generation. Contrary to the expectation that genetic uniformity should reduce phenotypic variability, clonal parthenogenic flies showed changes in trait means, trait-dependent changes in interindividual variation, increased fluctuating asymmetry, and, most consistently, reduced behavioral and developmental canalization across a broad set of parameters. These effects on phenotypes spanned visually guided locomotion, circadian activity, wing morphology, bristle patterning, eye anatomy, brain volume, and serotonergic neuron numbers and were associated with reduced survival under environmental stress. Inbreeding of sexual D. mercatorum reproduced several of these phenotypic changes, whereas a single generation of outcrossing restored phenotypic robustness and the resulting F1 hybrids even exceeded the wild-type controls in several traits, consistent with a hybrid vigor effect. Together, these experiments identify loss of heterozygosity, rather than clonality per se, as the primary driver of developmental instability. Our findings show that genetic uniformity achieved through homozygosity can amplify stochastic phenotypic divergence by weakening developmental canalization, and suggest that the genetic context in which experimental standardization is achieved, especially heterozygosity, matters as much as the degree of genetic uniformity itself.

genetics↗

bioRxiv2025

Non-cell autonomous control of presynaptic remodeling by the hypothalamic autophagy/NPY axis

Macroautophagy/autophagy, a critical cellular degradation pathway essential for maintaining neuronal proteostasis, declines with age and has been increasingly implicated in the regulation of synaptic integrity and circuit resilience. Neuropeptide Y (NPY), the most abundantly expressed neuropeptide in the mammalian brain, has emerged as a key modulator of both autophagy and aging-related processes. In Drosophila, the NPY-family peptide short Neuropeptide F (sNPF) has been shown to causally influence aging-associated changes in synaptic architecture and function, particularly at the presynaptic active zone (AZ), via non-cell autonomous mechanisms. Extending this concept to mammals, we investigated whether NPY and autophagy interact within NPY-secreting neurons to regulate age-related AZ remodeling. Our results indicate that hypothalamic NPY/AgRP neurons may exert geroprotective effects through the release of NPY and potentially other signaling molecules, thereby influencing both metabolic homeostasis and brain-wide synaptic function. These data suggest a conserved role for autophagy in maintaining presynaptic organization and resilience during aging.

neuroscience↗

bioRxiv2025

Native epitranscriptome sequencing reveals Hepatitis B virus RNA stability protected by heavy m6A modification

Although the RNA of Hepatitis B virus (HBV) is known to be regulated by the epitranscriptomic modification N6-methyladenosine (m6A), it remains controversial whether if m6A is beneficial or detrimental for viral replication. Here, we employ Nanopore direct RNA sequencing (DRS) to analyze the HBV m6A epitranscriptome on a single molecule level and elucidate how m6A regulates the HBV replication cycle. We found more than 60% of all HBV RNA in cells are m6A methylated, [~]3x more methylated than host mRNAs. Previously unreported m6A sites were found in pol gene, which when mutated reduced viral production. A sizable proportion of HBV RNAs carry poly(A) tails at least twice as long (>120nt) as cellular mRNAs, with the shorter-tailed population more pronounced among m6A-free transcripts. In contrast, encapsidated RNAs have shorter poly(A) tails and less m6A. Concordantly, pharmacological reduction of viral m6A using the m6A methyltransferase inhibitor STM2457, shortens viral poly(A) tails and reduces viral RNA stability. Our findings thus suggest that the abundance of m6A on viral RNAs protects the surprisingly long viral poly(A) tails and thus enhances RNA stability. Overall, m6A strongly enhances HBV viral replication, in support of RNA modification machinery as a promising class of antiviral targets.

microbiology↗

bioRxiv2025

WarpDemuX-tRNA: barcode multiplexing for nanopore tRNA sequencing

Transfer RNA (tRNA) plays an essential role in protein translation and tRNA modifications are important to their function. Recently, nanopore direct RNA sequencing (dRNA-seq) has shown promising results in the detection of complex tRNA modifications. However, its wider adoption in the tRNA field has been limited by a lack of (de)multiplexing solutions. Here, we present WarpDemuX-tRNA: an extension to the WarpDemuX method specifically optimized for multiplexed nanopore tRNA sequencing. Using consensus-based signal analysis using (soft) Dynamic Time Warping and barycenter averaging, our approach improves barcode feature generation and achieves more robust barcode identification. WarpDemuX-tRNA outperforms the original method and achieves 99% precision and 95% recovery for four barcodes, while reducing computational complexity and runtime to six minutes per one million reads. WarpDemuX-tRNA is an open-source and free-to-use solution to high-throughput nanopore tRNA sequencing, facilitating more accessible, cost-effective and high-throughput studies of tRNA modifications and their regulatory mechanisms.

bioinformatics↗

bioRxiv2025

MoDorado: Enhanced detection of tRNA modifications in nanopore sequencing by off-label use of modification callers

Rapid and accurate identification of tRNA modifications is crucial for understanding their role in protein translation and disease. However, their detection on tRNAs is challenging due to their high modification density. Recently, modification calling models for nanopore direct RNA sequencing became available for pseudouridine ({Psi}), m6A, inosine and m5C, as part of the Dorado basecaller. Applying the {Psi} model to tRNAs, we have mapped both known and novel {Psi} sites in Schizosaccharomyces pombe and assigned the responsible pseudouridine synthetases. Furthermore, we have developed MoDorado, an algorithm to detect modifications beyond those used in model training ("off-label use") by measuring prediction differences of pre-trained machine learning models. By leveraging the {Psi}/m6A/inosine/m5C models, MoDorado detected seven additional modifications (ncm5U, mcm5U, mcm5s2U, m7G, queuosine, m1A, and i6A), thus generating a tRNA modification map of S. pombe. This work demonstrates the potential of pre-trained models in determining the intricate landscape of tRNA modifications.

molecular biology↗

bioRxiv2024

Demultiplexing and barcode-specific adaptive sampling for nanopore direct RNA sequencing

Nanopore direct RNA sequencing (dRNA-seq) enables unique insights into (epi-)transcriptomics. However, applications are currently limited by the lack of accurate and cost-effective sample multiplexing. We introduce WarpDemuX, an ultra-fast and highly accurate adapter-barcoding and demultiplexing approach. WarpDemuX enhances speed and accuracy by fast processing of the raw nanopore signal, use of a lightweight machine-learning algorithm and design of optimized barcode sets. We demonstrate its utility by performing a rapid phenotypic profiling of different SARS-CoV-2 viruses, crucial for pandemic prevention and response, through multiplexed sequencing of longitudinal samples on a single flowcell. This identifies systematic differences in transcript abundance and poly(A) tail lengths during infection. Additionally, integrating WarpDemuX into sequencing control software enables real-time enrichment of target molecules through barcode-specific adaptive sampling, which we demonstrate by enriching low abundance viral RNA. In summary, WarpDemuX is a broadly applicable, high-performance, and economical multiplexing solution for nanopore dRNA-seq, facilitating advanced (epi-)transcriptomic research.

bioinformatics↗

bioRxiv2024

Modeling of HIV-1 prophylactic efficacy and toxicity with islatravir shows non-superiority for oral dosing, but promise as a subdermal implant

HIV prevention with pre-exposure prophylaxis (PrEP) constitutes a major pillar in fighting the ongoing epidemic. While daily oral PrEP adherence may be challenging, long-acting (LA-)PrEP in oral or implant formulations could overcome frequent dosing with convenient administration. The novel drug islatravir (ISL) may be suitable for LA-PrEP, but high doses have been associated with lymphopenia. We developed a mathematical model to predict ISL pro-drug levels in plasma and active intracellular ISL-triphosphate concentrations after oral vs. subdermal implant dosing. Using phase-II trial data, we simulated antiviral effects and estimated HIV risk reduction for multiple dosages and dosing frequencies. We then established non-toxic exposure thresholds and evaluated low-dose regimens. Our findings suggest that implants with 56-62 mg ISL offer safe, effective HIV risk reduction without being toxic. Oral 0.1 mg daily, 3-5 mg weekly, and 10 mg bi-weekly ISL provide comparable efficacy, but weekly and bi-weekly doses resulted in residual toxicity, while adherence requirements for daily dosing were similar to established oral PrEP regimen. Oral 0.5-1 mg on-demand provided > 90% protection, while not being suitable for post-exposure prophylaxis.

systems biology↗

bioRxiv2023

Sequencing accuracy and systematic errors in nanopore direct RNA sequencing

Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been exploring and expanding the potential of dRNA-seq, the sequencing accuracy and error patterns remain understudied. We present the first comprehensive evaluation of accuracy and systematic errors in dRNA-seq data from diverse species, as well as synthetic RNA. Deletions significantly outnumbered mismatches/insertions, while the median read accuracy exhibited species-level variation. In addition to homopolymer errors, we observed systematic biases across nucleotides and heteropolymeric motifs in all species. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines/adenines. Moreover, the systematic errors were strongly dependent on local sequence contexts. By examining raw signal data, we identified underlying signal-level features potentially associated with the error patterns. While read quality scores approximated error rates at base and read levels, failure to detect DNA adapters may lead to data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (base-calling) artefacts. Lastly, we discuss the implications of such error patterns for downstream applications of dRNA-seq data.

bioinformatics↗

bioRxiv2021

Stochastic Simulation Algorithm for effective spreading dynamics on Time-evolving Adaptive NetworX (SSATAN-X)

Modelling and simulating the dynamics of pathogen spreading has been proven crucial to inform public heath decisions, containment strategies, as well as cost-effectiveness calculations. Pathogen spreading is often modelled as a stochastic process that is driven by pathogen exposure on time-evolving contact networks. In adaptive networks, the spreading process depends not only on the dynamics of a contact network, but vice versa, infection dynamics may alter risk behaviour and thus feed back onto contact dynamics, leading to emergent complex dynamics. However, stochastic simulation of pathogen spreading processes on adaptive networks is currently computationally prohibitive. In this manuscript, we propose SSATAN-X, a new algorithm for the accurate stochastic simulation of pathogen spreading on adaptive networks. The key idea of SSATAN-X is to only capture the contact dynamics that are relevant to the spreading process. We show that SSATAN-X captures the contact dynamics and consequently the spreading dynamics accurately. The algorithm achieves up to 100 fold speed-up over the state-of-art stochastic simulation algorithm (SSA). The speed-up with SSATAN-X further increases when the contact dynamics are fast in relation to the spreading process, i.e. if contacts are short-lived and per-exposure infection risks are small, as applicable to most infectious diseases. We envision that SSATAN-X may extend the scope of analysis of pathogen spreading on adaptive networks. Moreover, it may serve to create benchmark data sets to validate novel numerical approaches for simulation, or for the data-driven analysis of the spreading dynamics on adaptive networks. A C++ implementation of the algorithm is available at https://github.com/nmalysheva/SSATAN-X. Author summaryModelling and simulating of infectious disease spreading supports public heath decisions, such as prevention and containment strategies and allows to perform cost-effectiveness calculations. Detailed modelling approaches consider stochastic pathogen spreading on time-evolving contact networks. In adaptive networks, the spreading process depends not only on the dynamics of a contact network, but vice versa, infection dynamics may alter risk behaviour and thus feed back onto contact dynamics. Stochastic simulation of these complex dynamics is currently computationally prohibitive. We propose a new algorithm (SSATAN-X) that can significantly speed up stochastic simulations on adaptive networks, while being accurate at the same time. Our algorithm achieves this speed-up by only considering the contact dynamics that are relevant to the spreading process. The benefit of algorithm is particularly pronounced when contacts are short-lived and per-exposure infection risks are small, which is applicable to most infectious diseases. We envision that SSATAN-X may allow simulation and analysis of pathogen spreading on more complex adaptive networks than previously possible. Moreover, data sets may be created with SSATAN-X that are useful for benchmarking novel numerical schemes and analytic approaches.

systems biology↗

bioRxiv2021

Numerical approaches for the rapid analysis of prophylactic efficacy against HIV with arbitrary drug-dosing schemes

Pre-exposure prophylaxis (PrEP) is an important pillar to prevent HIV transmission. Because of experimental and clinical shortcomings, mathematical models that integrate pharmacological, viral- and host factors are frequently used to quantify clinical efficacy of PrEP. Stochastic simulations of these models provides sample statistics from which the clinical efficacy is approximated. However, many stochastic simulations are needed to reduce the associated sampling error. To remedy the shortcomings of stochastic simulation, we developed three numerical methods that allow predicting the efficacy of arbitrary prophylactic regimen directly from a viral dynamics model, without sampling. We apply the methods to various hypothetical dolutegravir (DTG) prophylaxis scenarios. The approaches are verified against one another, as well as state-of-the-art stochastic simulation. While the methods are more accurate than stochastic simulation, they are superior in terms of computational performance. For example, a continuous 6-month prophylactic profile is computed within a few seconds on a laptop computer. The methods computational performance, therefore, substantially expands the horizon of feasible analysis in the context of PrEP, and possibly other applications. Author summaryPre-exposure prophylaxis (PrEP) is an important tool to prevent HIV transmission. However, experimental identification of parameters that determine prophylactic efficacy is extremely difficult. Clues about these parameters could prove essential for the design of next-generation PrEP compounds. Integrative mathematical models can fill this void: Based on stochastic simulation, a sample statistic can be generated, from which the prophylactic efficacy is estimated. However, for this sample statistic to be accurate, many simulations need to be performed. Here, we introduce three numerical methods to directly compute the prophylactic efficacy from a viral dynamics model, without the need for sampling. Based on several examples with dolutegravir (DTG) -based short- and long-term PrEP, as well as post-exposure prophylaxis we demonstrate the correctness of the new methods and their outstanding computational performance. Due to the methods computational performance, a number of analysis, including formal sensitivity analysis are becoming feasible with the proposed methods.

systems biology↗

bioRxiv2021

Variable brain wiring through scalable and relative synapse formation in Drosophila

Variability of synapse numbers and partners despite identical genes reveals limits of genetic determinism. Non-genetic perturbation of brain wiring can therefore reveal to what extent synapse formation is precise and absolute, or promiscuous and relative. Here, we show the role of relative partner availability for synapse formation in the fly brain through perturbation of developmental temperature. Unexpectedly, slower development at lower temperatures substantially increases axo-dendritic branching, synapse numbers and non-canonical synaptic partnerships of various neurons, while maintaining robust ratios of canonical synapses. Using R7 photoreceptors as a model, we further show that scalability of synapse numbers and ratios is preserved when relative availability of synaptic partners is changed in a DIP{gamma} mutant that ablates R7s preferred synaptic partner. Behaviorally, movement activity scales inversely with synapse numbers, while movement precision and relative connectivity are congruently robust. Hence, the fly genome encodes scalable relative connectivity to develop functional, but not identical, brains. One-Sentence SummaryNon-identical connectivity and behavior result from temperature-dependent synaptic partner availability in Drosophila.

neuroscience↗

bioRxiv2021

Inferring Gene Regulatory Networks from Single Cell RNA-seq Temporal Snapshot Data Requires Higher Order Moments

Single cell RNA-sequencing (scRNA-seq) has become ubiquitous in biology. Recently, there has been a push for using scRNA-seq snapshot data to infer the underlying gene regulatory networks (GRNs) steering cellular function. To date, this aspiration remains unrealised due to technical- and computational challenges. In this work, we focus on the latter, which is under-represented in the literature. We took a systemic approach by subdividing the GRN inference into three fundamental components: the data pre-processing, the feature extraction, and the inference. We saw that the regulatory signature is captured in the statistical moments of scRNA-seq data, and requires computationally intensive minimisation solvers to extract. Furthermore, current data pre-processing might not conserve these statistical moments. Though our moment-based approach is a didactic tool for understanding the different compartments of GRN inference, this line of thinking-finding computationally feasible multi-dimensional statistics of data-is imperative for designing GRN inference methods.

systems biology↗

bioRxiv2019

Autophagy-dependent filopodial kinetics restrict synaptic partner choice during Drosophila brain wiring

Brain wiring is remarkably precise, yet most neurons readily form synapses with incorrect partners when given the opportunity. Dynamic axon-dendritic positioning can restrict synaptogenic encounters, but the spatiotemporal interaction kinetics and their regulation remain essentially unknown inside developing brains. Here we show that the kinetics of axonal filopodia restrict synapse formation and partner choice for neurons that are not otherwise prevented from making incorrect synapses. Using 4D imaging in developing Drosophila brains, we show that filopodial kinetics are regulated by autophagy, a prevalent degradation mechanism whose role in brain development remains poorly understood. With surprising specificity, autophagosomes form in synaptogenic filopodia, followed by filopodial collapse. Altered autophagic degradation of synaptic building material quantitatively regulates synapse formation as shown by computational modeling and genetic experiments. Increased filopodial stability enables incorrect synaptic partnerships. Hence, filopodial autophagy restricts inappropriate partner choice through a process of kinetic exclusion that critically contributes to wiring specificity.

neuroscience↗

bioRxiv2018

Serial synapse formation through filopodial competition for synaptic seeding factors

Following axon pathfinding, growth cones transition from stochastic filopodial exploration to the formation of a limited number of synapses. How the interplay of filopodia and synapse assembly ensures robust connectivity in the brain has remained a challenging problem. Here, we developed a new 4D analysis method for filopodial dynamics and a data-driven computational model of synapse formation for R7 photoreceptor axons in developing Drosophila brains. Our live data support a serial synapse formation model, where at any time point only a single synaptogenic filopodium suppresses the synaptic competence of other filopodia through competition for synaptic seeding factors. Loss of the synaptic seeding factors Syd-1 and Liprin- leads to a loss of this suppression, filopodial destabilization and reduced synapse formation, which is sufficient to cause the destabilization of entire axon terminals. Our model provides a filopodial winner-takes-all mechanism that ensures the formation of an appropriate number of synapses.

neuroscience↗