Biology subjects

Arlt, C.

Publications and source records attributed to Arlt, C..

9 recordsLinked to original sources

bioRxiv2026

Data-derived agents reveal dynamical reservoirs in mouse cortex for adaptive behavior

Animals generate behaviors that are robust to perturbations yet adaptable to changing conditions. How neural population dynamics support this balance between robustness and flexibility remains unclear. We address this question in goal-directed navigation by combining large-scale calcium imaging from mouse cortex with a data-derived modeling framework. We trained agents to navigate in a simulative environment while recapitulating mouse neural and behavioral data trial-by-trial. Data-derived agents discovered novel dynamics of chaotic attractors, characterized by intrinsically variable trajectories confined within overall goal-specific attracting landscapes. These dynamics support reliable goal achievement while maintaining a structured distribution of navigational trajectories. Circuit-level analyses and perturbations reveal mechanisms that stabilize chaos and enhance behavioral adaptability in the data-derived agents. Thus, through our new modeling approach that emphasizes closed-loop interactions between behavior and neural dynamics, we reveal chaos as a functional principle for flexible behavior.

neuroscience↗

bioRxiv2026

Revisiting p53:Sirt1 interaction in the light of controlling p53 acetylation levels

The NAD+-dependent deacetylase sirtuin 1 (Sirt1) is known to regulate the tumor suppressor p53 via deacetylation, but the structural basis of the protein-protein interaction between full-length p53 and Sirt1 has so far remained elusive. We apply an integrated approach, combining structural mass spectrometry (MS) with data-driven molecular docking, to study the interaction between human p53 and Sirt1. Sirt1 was found to bind exclusively to acetylated p53 forming complexes with a 1:1 stoichiometry, irrespectively of p53s oligomeric state. The lysine residue at position 582 (K582) in p53 was identified as predominant acetylation site showing a selective Sirt1-dependent deacetylation at this position. Cross-linking mass spectrometry (XL-MS) provided valuable distance constraints between p53 and Sirt1. Specifically, cross-links created between p53-K382 / Sirt1-K427 and p53-K120 / Sirt1-K622 give hints on a highly flexible interface. Molecular docking was conducted based on the distance constraints imposed by the cross-links, positioning Sirt1 at the DNA-binding and tetramerization domains of p53. This gives a rationale for a steric exclusion of additional Sirt1 molecules binding to p53. We present the first structural model of the full-length p53:Sirt1 (1:1) complex, establishing a mechanistic framework that links p53 activity to its Sirt1-controlled acetylation status.

biochemistry↗

bioRxiv2025

Regulatory Analysis of Root Architectural and Anatomical Adaptation to Nitrate and Ammonium in Brachypodium distachyon

Root system architecture plays an important role in nitrate and ammonium uptake, the two primary nitrogen (N) forms essential for plant growth. Plants deploy different strategies to optimize the N uptake by roots, based on a complicated regulatory network that controls root phenotype and physiology. Here, we studied the response of root architecture to varying N applications in the model species Brachypodium distachyon. Using a combination of phenotypic and transcriptomic analyses, we examined how different forms and concentrations of ammonium and nitrate affect root growth, biomass allocation, and N uptake. N concentrations significantly influence root traits such as root length, root hair development, and aerenchyma formation in response to nitrate and ammonium. Plants grown in ammonium conditions had thin but highly branched roots, whereas nitrate application resulted in shorter, thicker roots with denser root hair at higher nitrate concentrations. Furthermore, using advanced co-expression network analysis, we identified an Atypical Aspartic Protease (APs) gene encoding an aspartyl protease family protein and a phosphoenolpyruvate carboxylase 1 (PEPC1) gene in brachypodium, which potentially control the root architectural and anatomical adaptions to different N form. APs expression showed a positive correlation with total root length and lateral root development, along with a negative correlation with root hair density. In contrast, PEPC1 exhibited positive correlations with cortex, stele, root cross-sectional areas, and root hair density, while showing a negative correlation with total root length. These genes likely play an important role in the transcriptional regulatory networks involved in these adaptive responses, which highlight the complex interplay between root morphology, nitrogen metabolism, and environmental nutrient conditions.

plant biology↗

bioRxiv2024

The role of methylation and structural variants in shaping the recombination landscape of barley

Meiotic recombination is not only a key mechanism for sexual adaptation in eukaryotes but crucial for the accumulation of beneficial alleles in breeding populations. The effective manipulation of recombination requires, however, a better understanding of the mechanisms regulating the rate and distribution of recombination events in genomes. Here, we identified the genomic features that best explain the recombination variation among a diverse set of segregating populations of barley at a resolution of 1 Mbp and investigated how methylation and structural variants determine recombination hotspots and coldspots at a high-resolution of 10 kb. Hotspots were found to be in proximity to genes and the genetic effects not assigned to methylation were found to be the most important factor explaining differences in recombination rates among populations along with the methylation and the parental sequence divergence. Interestingly, the inheritance of a highly-methylated genomic fragment from one parent only was enough to generate a coldspot, but both parents must be equally low methylated at a genomic segment to allow a hotspot. The parental sequence divergence was shown to have a sigmoidal correlation with recombination indicating an upper limit of mismatch among homologous chromosomes for CO formation. Structural variants (SVs) were shown to suppress COs, and their type and size were not found to influence that effect. Methylation and SVs act jointly determining the location of coldspots in barley and the weight of their relative effect depends on the genomic region. Our findings suggest that recombination in barley is highly predictable, occurring mostly in multiple short sections located in the proximity to genes and being modulated by local levels of methylation and SV load.

genomics↗

bioRxiv2023

Evidence that the Isc Iron-Sulfur Cluster Biogenesis Machinery Delivers Iron for -Cofactor Biosynthesis in Escherichia coli

[NiFe]-hydrogenases have a bimetallic NiFe(CN)2CO cofactor in their large, catalytic subunit. The 136 Da Fe(CN)2CO group of this cofactor is assembled on a distinct HypC-HypD scaffold complex prior to delivery to the apo-catalytic subunit, but the intracellular source of the iron ion is unresolved. Native mass spectrometric (native MS) analysis of HypCD complexes defined the [4Fe-4S] cluster associated with HypD and identified +26 - 28 Da and +136 Da modifications specifically associated with HypC. A HypCC2A variant dissociated from its complex with native HypD lacked all modifications. HypC dissociated from HypCD complexes isolated from Escherichia coli strains deleted for the iscS or iscU genes, encoding core components of the Isc iron-sulfur cluster biogenesis machinery, specifically lacked the +136 Da modification; however, it was retained on HypC isolated from suf mutants. The presence or absence of the +136 Da modification on the HypCD complex correlated with the hydrogenase enzyme activity profiles of the respective mutant strains. Notably, the [4Fe-4S] cluster on HypD was identified in all HypCD complexes analyzed. These results suggest that the iron of the Fe(CN)2CO group on HypCD derives from the Isc machinery, while either the Isc or the Suf machinery can deliver the [4Fe-4S] cluster to HypD.

microbiology↗

bioRxiv2022

Structural Assessment of the Full-Length Wild-Type Tumor Suppressor Protein p53 by Mass Spectrometry-Guided Computational Modeling

The tetrameric tumor suppressor p53 represents a great challenge for 3D-structural analysis due to its high degree of intrinsic disorder (ca. 40%). We aim to shed light on the structural and functional roles of p53s C-terminal region in full-length, wild-type human p53 tetramer and their importance for DNA binding. For this, we employed complementary techniques of structural mass spectrometry (MS) in an integrated approach with AI-based computational modeling. Our results show no major conformational differences in p53 between DNA-bound and DNA-free states, but reveal a substantial compaction of p53s C-terminal region. This supports the proposed mechanism of unspecific DNA binding to the C-terminal region of p53 prior to transcription initiation by specific DNA binding to the core domain of p53. The synergies between complementary structural MS techniques and computational modeling as pursued in our integrative approach is envisioned to serve as general strategy for studying intrinsically disordered proteins (IDPs) and intrinsically disordered region (IDRs).

biochemistry↗

bioRxiv2022

Structural variants in the barley gene pool: precision and sensitivity to detect them using short-read sequencing and their association with gene expression and phenotypic variation

In human genetics, several studies have shown that phenotypic variation is more likely to be caused by structural variants (SV) than by single nucleotide variants (SNV). However, accurate while cost-efficient discovery of SV in complex genomes remains challenging. The objectives of our study were to (i) facilitate SV discovery studies by benchmarking SV callers and their combinations with respect to their sensitivity and precision to detect SV in the barley genome, (ii) characterize the occurrence and distribution of SV clusters in the genomes of 23 barley inbreds that are the parents of a unique resource for mapping quantitative traits, the double round robin population, (iii) quantify the association of SV clusters with transcript abundance, and (iv) evaluate the use of SV clusters for the prediction of phenotypic traits. In our computer simulations based on a sequencing coverage of 25x, a sensitivity >70% and precision >95% was observed for all combinations of SV types and SV length categories if the best combination of SV callers was used. We observed a significant (P < 0.05) association of gene-associated SV clusters with global gene-specific gene expression. Furthermore, about 9% of all SV clusters that were within 5kb of a gene were significantly (P < 0.05) associated with the gene expression of the corresponding gene. The prediction ability of SV clusters was higher compared to that of single nucleotide polymorphisms from an array across the seven studied phenotypic traits. These findings suggest the usefulness of exploiting SV information when fine mapping and cloning the causal genes underlying quantitative traits as well as the high potential of using SV clusters for the prediction of phenotypes in diverse germplasm sets.

genomics↗

bioRxiv2021

Cognitive experience alters cortical involvement in navigation decisions

The neural correlates of decision-making have been investigated extensively, and recent work aims to identify under what conditions cortex is actually necessary for making accurate decisions. We discovered that mice with distinct cognitive experiences, beyond sensory and motor learning, use different cortical areas and neural activity patterns to solve the same task, revealing past learning as a critical determinant of whether cortex is necessary for decision-making. We used optogenetics and calcium imaging to study the necessity and neural activity of multiple cortical areas in mice with different training histories. Posterior parietal cortex and retrosplenial cortex were mostly dispensable for accurate decision-making in mice performing a simple navigation-based decision task. In contrast, these areas were essential for the same simple task when mice were previously trained on complex tasks with delay periods or association switches. Multi-area calcium imaging showed that, in mice with complex-task experience, single-neuron activity had higher selectivity and neuron-neuron correlations were weaker, leading to codes with higher task information. Therefore, past experience sets the landscape for how future tasks are solved by the brain and is a key factor in determining whether cortical areas have a causal role in decision-making.

neuroscience↗

bioRxiv2020

Inferring brain-wide interactions using data-constrained recurrent neural network models

Behavior arises from the coordinated activity of numerous anatomically and functionally distinct brain regions. Modern experimental tools allow unprecedented access to large neural populations spanning many interacting regions brain-wide. Yet, understanding such large-scale datasets necessitates both scalable computational models to extract meaningful features of inter-region communication and principled theories to interpret those features. Here, we introduce Current-Based Decomposition (CURBD), an approach for inferring brain-wide interactions using data-constrained recurrent neural network models that directly reproduce experimentally-obtained neural data. CURBD leverages the functional interactions inferred by such models to reveal directional currents between multiple brain regions. We first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. We then apply CURBD to multi-region neural recordings obtained from mice during running, macaques during Pavlovian conditioning, and humans during memory retrieval to demonstrate the widespread applicability of CURBD to untangle brain-wide interactions underlying behavior from a variety of neural datasets.

neuroscience↗