Biology subjects

Bader, R.

Publications and source records attributed to Bader, R..

6 recordsLinked to original sources

bioRxiv2023

RdDM mutants reduce histone methylation rather than DNA methylation at the paramutated maize b1 enhancer

Paramutation is the transfer of mitotically and meiotically heritable silencing information between two alleles. With paramutation at the maize booster1 (b1) locus, the low expressed B epiallele heritably changes the high expressed B-I epiallele into B with 100% frequency. This requires specific tandem repeats and multiple components of the RNA-directed DNA methylation (RdDM) pathway, including the RNA-dependent RNA polymerase (RdRP, mediator of paramutation1, MOP1), the second-largest subunit of RNA polymerase IV and V (NRP(D/E)2a, mediator of paramutation2, MOP2), and the largest subunit of RNA Polymerase IV (NRPD1, mediator of paramutation3, MOP3). Mutations in mop genes prevent paramutation and release silencing at the B epiallele. In this study we investigated the effect of mutations in mop1, mop2 and mop3 on chromatin structure and DNA methylation at the B epiallele, and especially the regulatory hepta-repeat 100 kb upstream of the b1 gene. We show that mutations in mop1 and mop3 result in decreased repressive histone modifications H3K9me2 and H3K27me2 at the hepta-repeat. Associated with this decrease are partial activation of the hepta-repeat enhancer function, formation of a multi-loop structure, and elevated b1 expression. In mop2 mutants, which do not show elevated b1 expression, H3K9me2 and H3K27me2 and a single-loop structure like in wild type B are retained. Surprisingly, high DNA methylation levels at the B hepta-repeat remains in all three mutants. Our results raise the possibility of MOP factors mediating RNA-directed histone methylation rather than RNA-directed DNA methylation at the b1 locus.

plant biology↗

bioRxiv2020

Collective migration of human osteoblasts in direct current electric field

Under both physiological (development, regeneration) and pathological conditions (cancer metastasis), cells migrate while sensing environmental cues in the form of mechanical, chemical or electrical stimuli. Although it is known that osteoblasts respond to exogenous electric fields, the underlying mechanism of electrotactic collective movement of human osteoblasts is unclear. Theoretical approaches to study electrotactic cell migration until now mainly used reaction-diffusion models, and did not consider the effect of electric field on single-cell motility, or incorporate spatially dependent cell-to-cell interactions. Here, we present a computational model that takes into account cell interactions and describes cell migration in direct current electric field. We compare this model with in vitro experiments in which human primary osteoblasts are exposed to direct current electric field of varying field strength. Our results show that cell-cell interactions and fluctuations in the migration direction together lead to anode-directed collective migration of osteoblasts. Author summaryElectrotactic migration of cells involves directed movement of a large number of single cells under the influence of external electric field. Influencing the migration behaviour of osteoblasts by external direct current electric field offers a promising approach towards building highly effective implants for bone regeneration. We present a computational model for electrotactic migration of osteoblasts subject to external direct current electric field. Our model considers individual cells that interact with each other and the external electric field, and, replicates the experimental observations, based on single-cell analysis, of the response of osteoblasts to electrical stimulation of varying strengths for 7 hours. Our results suggest that tracking trajectories of individual cells provide a way of determining the role of various interactions of a cell in collective migration. Our model provides a framework that links single cell response to the large scale collective dynamics.

biophysics↗

bioRxiv2020

Feasibility of Integrating Canine Olfaction with Chemical and Microbial Profiling of Urine to Detect Lethal Prostate Cancer

Prostate cancer is the second leading cause of cancer death in men in the developed world. A more sensitive and specific detection strategy for lethal prostate cancer beyond serum prostate specific antigen (PSA) population screening is urgently needed. Diagnosis by canine olfaction, using dogs trained to detect cancer by smell, has been shown to be both specific and sensitive. While dogs themselves are impractical as scalable diagnostic sensors, machine olfaction for cancer detection is testable. However, studies bridging the divide between clinical diagnostic techniques, artificial intelligence, and molecular analysis remains difficult due to the significant divide between these disciplines. We tested the clinical feasibility of a cross-disciplinary, integrative approach to early prostate cancer biosensing in urine using trained canine olfaction, volatile organic compound (VOC) analysis by gas chromatography-mass spectroscopy (GC-MS) artificial neural network (ANN)-assisted examination, and microbial profiling in a double-blinded pilot study. Two dogs were trained to detect Gleason 9 prostate cancer in urine collected from biopsy-confirmed patients. Biopsy-negative controls were used to assess canine specificity as prostate cancer biodetectors. Urine samples were simultaneously analyzed for their VOC content in headspace via GC-MS and urinary microbiota content via 16S rDNA Illumina sequencing. In addition, the dogs diagnoses were used to train an ANN to detect significant peaks in the GC-MS data. The canine olfaction system was 71% sensitive and between 70-76% specific at detecting Gleason 9 prostate cancer. We have also confirmed VOC differences by GC-MS and microbiota differences by 16S rDNA sequencing between cancer positive and biopsy-negative controls. Furthermore, the trained ANN identified regions of interest in the GC-MS data, informed by the canine diagnoses. Methodology and feasibility are established to inform larger-scale studies using canine olfaction, urinary VOCs, and urinary microbiota profiling to develop machine olfaction diagnostic tools. Scalable multi-disciplinary tools may then be compared to PSA screening for earlier, non-invasive, more specific and sensitive detection of clinically aggressive prostate cancers in urine samples.

cancer biology↗

bioRxiv2020

High feature overlap reveals the importance of anterior and medial temporal lobe structures for learning by means of fast mapping

Contrary to traditional theories of declarative memory, it has recently been shown that novel, arbitrary associations can be rapidly and directly integrated into cortical memory networks by means of a learning procedure called fast mapping (FM), possibly bypassing time-consuming hippocampal-neocortical consolidation processes. In the typical FM paradigm, a picture of a previously unknown item is presented next to a picture of a previously known item and participants answer a question referring to an unfamiliar label. It is assumed that they thereby incidentally create associations between the unknown item and the label. However, contradictory findings have been reported and factors moderating rapid cortical integration through FM yet need to be identified. In the context of previous behavioral results showing rapid semantic integration through FM especially if the unknown and the known item shared many features, we propose that due to its computational mechanisms during the processing of complex and particularly highly similar objects, the perirhinal cortex might be especially qualified to support the rapid incorporation of these associations into cortical memory networks within the FM paradigm. We therefore expected that a high degree of feature overlap between the unknown and the known item would trigger strong engagement of the perirhinal cortex at encoding, which in turn might enhance rapid cortical integration of the novel picture-label associations. Within an fMRI experiment, we observed stronger activation for subsequent hits than misses during encoding in the perirhinal cortex and an associated anterior temporal network if the items shared many features than if they shared few features, indicating that the perirhinal cortex indeed contributes to the acquisition of novel associations by means of FM if feature overlap is high.

neuroscience↗

bioRxiv2019

Usefulness of a familiarity signal during recognition depends on test format: Neurocognitive evidence for a core assumption of the CLS framework

Familiarity-based discrimination between studied target items and similar foils in yes/no recognition memory tests is relatively poor. According to the complementary learning systems (CLS) framework this is due do a relatively small difference in familiarity strength between these two item classes. The model, however, also predicts that when targets and corresponding similar foils are presented next to each other in a forced-choice corresponding (FCC) test format, familiarity values for targets and foils can be directly compared because in each trial, targets are reliably more familiar than their corresponding foils. In contrast, when forced-choice displays contain non-corresponding foils (FCNC) which are similar to other studied items (but not the target), familiarity should not be diagnostic because familiarity values are not directly comparable (as in yes/no-tasks). We compared ERP old/new effects (ERPs of targets vs. foils) when participants were tested with FCC vs. FCNC displays after having intentionally encoded pictures of objects. As predicted, the mid-frontal old/new effect which is associated with familiarity was significantly larger in FCC compared to FCNC displays. Moreover, the target-foil amplitude difference predicted the accuracy of the recognition judgment in a given trial. This is one of the very few studies which support the assumption of the CLS framework that the test format can influence the diagnosticity of familiarity. Moreover, it implies that the mid-frontal old/new effect does not reflect the mean difference in the familiarity signal itself between studied and non-studied items but reflects the task-adequate assessment of the familiarity signal.

neuroscience↗

bioRxiv2019

Feature overlap modulates rapid semantic but not lexical integration of novel associations by means of fast mapping

There is evidence that rapid integration of novel associations into cortical networks is possible if associations are acquired through a learning procedure called fast mapping (FM). FM requires precise visual discrimination of sometimes highly similar pictures of a previously unknown and a known item, and linking an unfamiliar label to the unknown item. In order to shed light on the mechanisms underlying learning through FM, we manipulated feature overlap between the two items as potential modulating factor. In Experiment 1, we found that labels of the unknown items generally evoked instantaneous lexical competition when encoded through FM, indicating rapid integration into lexical networks. In Experiment 2, we observed semantic priming immediately after FM encoding but only if the items shared many features. This indicates that whereas feature overlap leaves item-level lexical integration unaffected, it might mediate semantic integration of arbitrary picture-label associations, which could explain contradictory findings in the literature.\n\nHighlightsO_LIWe examined cortical integration of associations using implicit memory measures.\nC_LIO_LIFast mapping enables immediate integration of associations into cortical networks.\nC_LIO_LISemantic integration requires the discrimination between items sharing many features.\nC_LIO_LIItem-level lexical integration is unaffected by feature overlap.\nC_LI

neuroscience↗