Biology subjects

Ott, A.

Publications and source records attributed to Ott, A..

8 recordsLinked to original sources

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↗

bioRxiv2024

Mechanochemical Patterning Localizes the Organizer of a Luminal Epithelium

The spontaneous emergence of tissue patterns is often attributed to biochemical reaction-diffusion systems. In Hydra tissue regeneration, the formation of a Wnt signaling center serves as a well-known example of such a process. However, despite extensive research, a strictly biochemical mechanism for self-organization in Hydra remains elusive. In this study, we investigated mechanical stimuli and identified a positive feedback loop between Wnt signaling and tissue stretching. We developed a mathematical model of mechanochemical pattern formation in a closed elastic shell, representing regenerating Hydra epithelial spheroids. Our model explains how mechanical forces drive axis formation and predicts the organizers location under various perturbations, providing a more comprehensive understanding of the spatial dynamics involved. Validation by partially confining regenerating tissues showed that the organizer indeed forms in regions with the greatest stretching potential. This work highlights a novel mechanochemical mechanism for luminal epithelium patterning, suggesting that mechanical forces, in addition to biochemical signals, play a crucial role in tissue regeneration and axis specification. Our findings offer broader implications for the role of mechanical forces in tissue organization in various biological systems, opening new avenues for investigating mechanochemical feedback in development and regeneration.

developmental biology↗

bioRxiv2023

New genome scale network modeling and mining workflow for detecting metabolic changes induced by exposure to chemicals

BackgroundThe growing abundance of in vitro omics data, coupled with the necessity to reduce animal testing in the safety assessment of chemical compounds and even eliminate it in the evaluation of cosmetics, highlights the need for adequate computational methodologies. Data from omics technologies allow the exploration of a wide range of biological processes, therefore providing a better understanding of mechanisms of action (MoA) related to chemical exposure in biological systems. However, the analysis of these large datasets remains difficult due to the complexity of modulations spanning multiple biological processes. ResultsTo address this, we propose a strategy to reduce information overload by computing, based on transcriptomics data, a comprehensive metabolic sub-network reflecting the metabolic impact of a chemical. The proposed strategy integrates transcriptomic data to a genome scale metabolic network through enumeration of condition specific metabolic models hence translating transcriptomics data into reaction activity probabilities. Based on these results, graph algorithm is applied to retrieve user readable sub-networks reflecting the possible metabolic MoA (mMoA) of chemicals. This strategy has been implemented as a three-step workflow. The first step consists in building cell condition-specific models reflecting the metabolic impact of each exposure condition while taking into account the diversity of possible optimal solutions with a partial enumeration algorithm. In a second step, we address the challenge of analyzing thousands of enumerated conditions-specific networks by computing differentially activated reactions (DARs) between the two sets of enumerated possible condition-specific models. Finally, in the third step, DARs are grouped into clusters of functionally interconnected metabolic reactions, representing possible mMoA, using the distance-based clustering and subnetwork extraction method. The first part of the workflow was exemplified on eight molecules selected for their known human hepatotoxic outcomes associated with specific MoAs well described in the literature and for which we retrieved primary human hepatocytes (PHH) transcriptomic data in Open TG-GATEs. Then, we further applied this strategy to more precisely model and visualize associated mMoA for two of these eight molecules (amiodarone and valproic acid). The approach proved to go beyond gene-based analysis by identifying mMoA when few genes are significantly differentially expressed (2 differentially expressed genes (DEGs) for amiodarone) or when very large number of genes were differentially expressed (5709 DEGs for valproic acid). In both cases, the results of our strategy well fitted evidence from the literature regarding known MoA. Beyond these confirmations, the workflow highlighted potential other unexplored mMoA. ConclusionThe proposed strategy allows toxicology experts to decipher which part of cellular metabolism is expected to be affected by the exposition to a given chemical. The approach originality resides in the combination of different metabolic modelling approaches (constraint based and graph modelling). The application to two model molecules shows the strong potential of the approach for interpretation and visual mining of complex omics in vitro data. All code is freely available as well as data to reproduce results.

bioinformatics↗

bioRxiv2021

Simultaneous in vivo Pharmacokinetics and Pharmacodynamics of TDF Intravaginal Ring during High-dose Vaginal SHIV Challenge in Pigtail Macaques

The demonstration of complete protection of macaques in a repeated low dose virus challenge by a tenofovir disoproxil fumarate (TDF) intravaginal ring (IVR) and the success of the dapivirine IVR in clinical trials highlighted the potential of IVRs as pre- exposure prophylaxis against HIV. Efficacy of TDF ring was not investigated in sexually active women. Our understanding of the mechanisms of protection is limited. To address this knowledge gap, we performed simultaneous pharmacokinetic and pharmacodynamic analysis of a TDF-IVR at the site of SIV challenge in pigtail macaques at the anatomical and cellular level. Specifically, we challenged TDF-IVR administered pigtail macaques with a single high dose of a non-replicative SIV-based vector containing a dual reporter system that helped us to identify the earliest targets of SIV infection within the mucosa. Two and three days after challenge, the macaques were euthanized and tenofovir (TFV) concentrations were measured in the female reproductive tract (FRT) by HPLC-MS/MS to correlate drug concentrations and SIV-vector transduction efficiency. TFV formed a gradient through the mucosal tissue, with the highest concentrations near the ring, in the upper vagina and endocervix. Despite this, several transduction events were identified with the most common sites being in the ovaries. Moreover, proviral DNA was detected in the cervix and vagina. Thus, our studies demonstrate an uneven distribution of TFV in the FRT of macaques after release from a TDF-IVR that leads to incomplete FRT protection from high viral dose challenge.

pharmacology and toxicology↗

bioRxiv2020

Temporal correlation between oscillating force dipoles drives single cell migration in 3D.

Directional cell locomotion requires symmetry breaking between the front and rear of the cell. In some cells, symmetry breaking manifests itself in a directional flow of actin from the front to the rear of the cell. Many cells, especially in physiological 3D matrices do not show such coherent actin dynamics and present seemingly competing protrusion/retraction dynamics at their front and back. How symmetry breaking manifests itself for such cells is therefore elusive. We take inspiration from the scallop theorem proposed by Purcell for micro-swimmers in Newtonian fluids: self-propelled objects undergoing persistent motion at low Reynolds number must follow a cycle of shape changes that breaks temporal symmetry. We report similar observations for cells crawling in 3D. We quantified cell motion using a combination of 3D live cell imaging, visualization of the matrix displacement and a minimal model with multipolar expansion. We show that our cells embedded in a 3D matrix form myosin-driven force dipoles at both sides of the nucleus, that locally and periodically pinch the matrix. The existence of a phase shift between the two dipoles is required for directed cell motion which manifests itself as cycles with finite area in the dipole-quadrupole diagram, a formal equivalence to the Purcell cycle. We confirm this mechanism by triggering local dipolar contractions with a laser. This leads to directed motion. Our study reveals that these cells control their motility by synchronizing dipolar forces distributed at front and back. This result opens new strategies to externally control cell motion as well as for the design of micro-crawlers.

biophysics↗

bioRxiv2020

A bead-based method for the removal of the amino acid lysine from cell-free transcription-translation systems

Cell-free transcription-translation systems are a versatile tool to study gene expression, enzymatic reactions and biochemical regulation mechanisms. Because cell-free transcription-translation systems are often derived from cell lysates, many different substances, among them amino acids, are present. However, experiments concerning the incorporation of non-canonical amino acids into proteins require a system with negligible amounts of canonical analogs. Here we propose a two-step method for the removal of residual free lysine in an all Escherichia coli-based cell-free expression system. The first step consists of the expression of a high-lysine dummy protein. The second step consists of direct removal via binding between lysine and DNA. The presented method is an efficient, fast and simple way to remove residual lysine without altering the system ability to perform gene expression.

molecular biology↗

bioRxiv2020

Highly coordinated mechanical motion mediated by the microtubule cytoskeletonis a pivotal element of de-novo symmetry breaking in hydraspheroids

The establishment of polarity in cells and tissues is one of the first steps in multicellular development. The eternal embryo hydra can completely regenerate from a disorganized cell cluster or a small fragment of tissue of about 10, 000 cells. During regeneration, the cells first form a hollow cell spheroid, which then undergoes de-novo symmetry breaking to irreversibly polarize. Here, we address the symmetry-related shape changes. Prior to axis establishment, the spheroid of regenerating cells presents inflation oscillations on several timescales that are isotropic in space. There are transient periods of fluctuations in defined arbitrary directions, until these undergo a clearly identified, irreversible transition to directed fluctuations along the future main axis of the regenerating hydra. Stabilized cytosolic actin structures disappear during the de-novo polarization, while polymerized microtubules remain. In our observations applied drugs that depolymerize actin filaments accelerate the symmetry breaking process, while drug-stabilized actin filaments prevent it. Nocodazole-depolymerized microtubules prevent symmetry breaking, but regeneration can be rescued by the microtubule-stabilizing drug paclitaxel at concentrations where microtubular structures start to reappear. We discuss the possibility that mechanical fluctuations induce the orientation and position of microtubules, which contribute to {beta}-catenin nuclear translocation, to increase the organizer-forming-potential of the cells. Our data suggest that in regenerating hydra spheroids, microtubules play a pivotal role in the cooperative polarization process of the self-organizing hydra spheroid.

biophysics↗

bioRxiv2017

Tunable Genotyping-By-Sequencing (tGBS(R)) Enables Reliable Genotyping of Heterozygous Loci

Most Genotyping-by-Sequencing (GBS) strategies suffer from high rates of missing data and high error rates, particularly at heterozygous sites. Tunable genotyping-by-sequencing (tGBS(R)), a novel genome reduction method, consists of the ligation of single-strand oligos to restriction enzyme fragments. DNA barcodes are added during PCR amplification; additional (selective) nucleotides included at the 3-end of the PCR primers result in more genome reduction as compared to conventional GBS methods. By adjusting the number of selective bases different numbers of genomic sites can be targeted for sequencing. Because this genome reduction strategy concentrates sequencing reads on fewer sites, SNP calls are based on more reads than conventional GBS, resulting in higher SNP calling accuracy (>97-99%) even for heterozygous sites and less missing data per marker. tGBS genotyping is expected to be particularly useful for genomic selection, which requires the ability to genotype populations of individuals that are heterozygous at many loci.

genomics↗