Biology subjects

Kuhn, S.

Publications and source records attributed to Kuhn, S..

24 records · Page 2Linked to original sources

bioRxiv2020

Decoding and blocking the bacterial lipid flippase MprF yields a novel anti-virulence strategy

The pandemic of antibiotic resistance represents a major human health threat demanding new antimicrobial strategies. MprF is the synthase and flippase of the phospholipid lysyl-phosphatidylglycerol that increases virulence and resistance of methicillin-resistant Staphylococcus aureus (MRSA) and other pathogens to cationic host defense peptides and antibiotics. With the aim to design MprF inhibitors that could sensitize MRSA to both, human antimicrobials and antibiotics and support the clearance of staphylococcal infections with minimal selection pressure, we developed MprF-targeting monoclonal antibodies, which bound and blocked the MprF flippase subunit. Antibody M-C7.1 targeted a specific loop in the flippase domain that proved to be exposed at both sides of the bacterial membrane, thereby enhancing the mechanistic understanding into bacterial lipid translocation. M-C7.1 rendered MRSA susceptible to host antimicrobial peptides and antibiotics such as daptomycin. Moreover, it impaired MRSA survival in human phagocytes, which recommends MprF inhibitors for new anti-MRSA approaches. MprF-directed monoclonal antibodies provide a proof of concept for development of precisely targeted anti-virulence approaches, which block bacterial antimicrobial resistance mechanisms.

microbiology↗

bioRxiv2019

A semi-automated technique for adenoma quantification in the ApcMin mouse using FeatureCounter

Colorectal cancer is a major contributor to death and disease worldwide. The ApcMin mouse is a widely used model of intestinal neoplasia, as it carries a mutation also found in human colorectal cancers. However, the method most commonly used to quantify tumour burden in these mice is manual adenoma counting, which is time consuming and poorly suited to standardization across different laboratories. We describe a method to produce suitable photographs of the small intestine, process them with an ImageJ macro, FeatureCounter, which automatically locates image features potentially corresponding to adenomas, and a machine learning pipeline to identify and quantify them. Compared to a manual method, the specificity (or True Negative Rate, TNR) and sensitivity (or True Positive Rate, TPR) of this method in detecting adenomas are similarly high at about 80% and 87%, respectively. Importantly, total adenoma area measures derived from the automatically-called tumours were just as capable of distinguishing high-burden from low-burden mice as those established manually. Overall, our strategy is quicker, helps control experimenter bias and yields a greater wealth of information about each tumour, thus providing a convenient route to getting consistent and reliable results from a study.

cancer biology↗

bioRxiv2019

Oomycete small RNAs invade the plant RNA-induced silencing complex for virulence

Fungal small RNAs (sRNAs) hijack the plant RNA silencing pathway to manipulate host gene expression, named cross-kingdom RNA interference (ckRNAi). It is currently unknown how conserved and significant ckRNAi is for microbial virulence. Here, we found for the first time that sRNAs of a pathogen representing the oomycete kingdom invade the host plants Argonaute (AGO)/RNA-induced silencing complex. To demonstrate the functionality of the plant-invading oomycete Hyaloperonospora arabidopsidis sRNAs (HpasRNAs), we designed a novel CRISPR endoribonuclease Csy4/GUS repressor reporter to visualize in situ pathogen-induced target suppression in Arabidopsis thaliana host plant. By using 5 RACE-PCR we demonstrated HpasRNAs-directed cleavage of plant mRNAs. The significant role of HpasRNAs together with AtAGO1 in virulence was demonstrated by plant atago1 mutants and by transgenic Arabidopsis expressing a target mimic to block HpasRNAs, that both exhibited enhanced resistance. Individual HpasRNA plant targets contributed to host immunity, as Arabidopsis gene knockout or HpasRNA-resistant gene versions exhibited quantitative enhanced or reduced susceptibility, respectively. Together with previous reports, we found that ckRNAi is conserved among oomycete and fungal pathogens.

microbiology↗

bioRxiv2017

The Influence Of Study Characteristics On Coordinate-Based fMRI Meta-Analyses

Given the increasing amount of neuroimaging studies, there is a growing need to summarize published results. Coordinate-based meta-analyses use the locations of statistically significant local maxima with possibly the associated effect sizes to aggregate studies. In this paper, we investigate the influence of key characteristics of a coordinate-based meta-analysis on (1) the balance between false and true positives and (2) the reliability of the outcome from a coordinate-based meta-analysis. More particularly, we consider the influence of the chosen group level model at the study level (fixed effects, ordinary least squares or mixed effects models), the type of coordinate-based meta-analysis (Activation Likelihood Estimation, fixed effects and random effects meta-analysis) and the amount of studies included in the analysis (10, 20 or 35). To do this, we apply a resampling scheme on a large dataset (N = 1400) to create a test condition and compare this with an independent evaluation condition. The test condition corresponds to subsampling participants into studies and combine these using meta-analyses. The evaluation condition corresponds to a high-powered group analysis. We observe the best performance when using mixed effects models in individual studies combined with a random effects meta-analysis. This effect increases with the number of studies included in the meta-analysis. We also show that the popular Activation Likelihood Estimation procedure is a valid alternative, though the results depend on the chosen threshold for significance. Furthermore, this method requires at least 20 to 35 studies. Finally, we discuss the differences, interpretations and limitations of our results.

neuroscience↗

bioRxiv2017

Consistent local dynamics in the brain across sessions are revealed by whole brain modeling of resting state activity

Resting state fMRI has been the primary tool for studying the functional organization of the human brain. However, even at so-called \"rest\", ongoing brain activity and its underlying physiological organization is highly dynamic and yet most of the information generated so far comes from group analysis. Here we developed an imaging-based technique capable of portraying information of local dynamics at a single-subject level reliably by using a whole-brain model that estimates a local bifurcation parameter, which reflects if a brain region presents stable, asynchronous or transitory oscillations. Using 50 longitudinal resting state sessions of one single subject and single resting state sessions from a group of 50 participants we demonstrated that individual global and local brain dynamics can be estimated consistently with respect to a reference group using only a scanning time of 15 to 20 minutes. We also showed that brain hubs are closer to a transition point between synchronous and asynchronous oscillatory dynamics and that dynamics in frontal areas have larger variations compared to other regions. Finally, we analyzed the variability and error of these dynamics and found high symmetry between hemispheres, which interestingly was reduced by adding more sessions. The framework presented here can be used to study functional brain dynamics on an individual level, opening new avenues for possible clinical applications.\n\nBullet pointsLocal brain dynamics are consistent across scans.\n\nFour scans of five minutes each are enough to get highly reliable and consistent results.\n\nHub areas are in a transition point between a synchronous and asynchronous regime.\n\nVariability and error of local dynamics presented high symmetry between hemispheres.

neuroscience↗

bioRxiv2016

Behavioural, modeling, and electrophysiological evidence for domain-generality in human metacognition

Metacognition, or the capacity to introspect on ones own mental states, has been mostly characterized through confidence reports in visual tasks. A pressing question is to what extent the results from visual studies generalize to other domains. Answering this question allows determining whether metacognition operates through shared, domain-general mechanisms, or through idiosyncratic, domain-specific mechanisms. Here, we report three new lines of evidence for decisional and post-decisional mechanisms arguing for the domain-generality of metacognition. First, metacognitive efficiency correlated between auditory, tactile, visual, and audiovisual tasks. Second, confidence in an audiovisual task was best modeled using supramodal formats based on integrated representations of auditory and visual signals. Third, confidence in correct responses involved similar electrophysiological markers for visual and audiovisual tasks that are associated with motor preparation preceding the perceptual judgment. We conclude that the domain-generality of metacognition relies on supramodal confidence estimates and decisional signals that are shared across sensory modalities.

neuroscience↗