Biology subjects

Wouters, J.

Publications and source records attributed to Wouters, J..

28 records · Page 2Linked to original sources

bioRxiv2019

Radiosafe micro-computed tomography for longitudinal evaluation of murine disease models

Implementation of in vivo high-resolution micro-computed tomography (CT), a powerful tool for longitudinal analysis of murine lung disease models, is hampered by the lack of data on cumulative low-dose radiation effects on the investigated disease models. We aimed to measure radiation doses and effects of repeated CT scans, to establish cumulative radiation levels and scan protocols without relevant toxicity. Lung metastasis, inflammation and fibrosis models and healthy mice were weekly scanned over one-month with CT using high-resolution respiratory-gated 4D and expiration-weighted 3D protocols, comparing 5-times weekly scanned animals with controls. Radiation dose was measured by ionization chamber, optical fiberradioluminescence probe and thermoluminescent detectors in a mouse phantom. Dose effects were evaluated by in vivo CT and bioluminescence imaging read-outs, gold standard endpoint evaluation and blood cell counts. Weekly exposure to 4D CT, dose of 540-699 mGy/scan, did not alter lung metastatic load nor affected healthy mice. We found a disease-independent decrease in circulating blood platelets and lymphocytes after repeated 4D CT. This effect was eliminated by optimizing a 3D protocol, reducing dose to 180-233 mGy/scan while maintaining equally high-quality images. We established CT safety limits and protocols for weekly repeated whole-body acquisitions with proven safety for the overall health status, lung, disease process and host responses under investigation, including the radiosensitive blood cell compartment.

physiology↗

bioRxiv2019

SHYBRID: A graphical tool for generating hybrid ground-truth spiking data for evaluating spike sorting performance

Spike sorting is the process of retrieving the spike times of individual neurons that are present in an extracellular neural recording. Over the last decades, many spike sorting algorithms have been published. In an effort to guide a user towards a specific spike sorting algorithm, given a specific recording setting (i.e., brain region and recording device), we provide an open-source graphical tool for the generation of hybrid ground-truth data in Python. Hybrid ground-truth data is a data-driven modelling paradigm in which spikes from a single unit are moved to a different location on the recording probe, thereby generating a virtual unit of which the spike times are known. The tool enables a user to efficiently generate hybrid ground-truth datasets and make informed decisions between spike sorting algorithms, fine-tune the algorithm parameters towards the used recording setting, or get a deeper understanding of those algorithms.

neuroscience↗

bioRxiv2019

Single-cell gene regulatory network analysis reveals new melanoma cell states and transition trajectories during phenotype switching

Melanoma is notorious for its cellular heterogeneity, which is at least partly due to its ability to transition between alternate cell states. Similarly to EMT, melanoma cells with a melanocytic phenotype can switch to a mesenchymal-like phenotype. However, scattered emerging evidence indicates that additional, intermediate state(s) may exist. In order to search for such new melanoma states and decipher their underlying gene regulatory network (GRN), we extensively studied ten patient-derived melanoma cultures by single-cell RNA-seq of >39,000 cells. Although each culture exhibited a unique transcriptome, we identified shared gene regulatory networks that underlie the extreme melanocytic and mesenchymal cell states, as well as one (stable) intermediate state. The intermediate state was corroborated by a distinct open chromatin landscape and governed by the transcription factors EGR3, NFATC2, and RXRG. Single-cell migration assays established that this \"transition\" state exhibits an intermediate migratory phenotype. Through a dense time-series sampling of single cells and dynamic GRN inference, we unraveled the sequential and recurrent arrangement of transcriptional programs at play during phenotype switching that ultimately lead to the mesenchymal cell state. We provide the scRNA-Seq data with 39,263 melanoma cells on our SCope platform and the ATAC-seq data on a UCSC hub to jointly serve as a resource for the melanoma field. Together, this exhaustive analysis of melanoma cell state diversity indicates that additional states exists between the two extreme melanocytic and mesenchymal-like states. The GRN we identified may serve as a new putative target to prevent the switch to mesenchymal cell state and thereby, acquisition of metastatic and drug resistant potential.

genomics↗

bioRxiv2019

The effect of stimulus envelope shape on the auditory steady-state response

Auditory steady-state responses (ASSRs) are auditory evoked potentials that reflect phase-locked neural activity to periodic stimuli. ASSRs are often evoked by tones with a modulated envelope, with sinusoidal envelopes being most common. However, it is unclear if and how the shape of the envelope affects ASSR responses. In this study, we used various trapezoidal modulated tones to evoke ASSRs (modulation frequency = 40 Hz) and studied the effect of four envelope parameters: attack time, hold time, decay time and off time. ASSR measurements in 20 normal hearing subjects showed that envelope shape significantly influenced responses: increased off time and/or increased decay time led to responses with a larger signal-to-noise-ratio (SNR). Response phase delay was significantly influenced by attack time and to a lesser degree by off time. We also simulated neural population responses that approximate ASSRs with a model of the auditory periphery (Bruce et al. 2018). The modulation depth of the simulated responses, i.e. the difference between maximum and minimum firing rate, correlated highly with the response SNRs found in the ASSR measurements. Longer decay time and off time enhanced the modulation depth both by decreasing the minimum firing rate and by increasing the maximum firing rate. In conclusion, custom envelopes with long decay and off time provide larger response SNRs and the benefit over the commonly used sinusoidal envelope was in the range of several dB.

neuroscience↗

bioRxiv2018

The effect of presentation level on spectrotemporal modulation detection

The understanding of speech in noise relies (at least partially) on spectrotemporal modulation sensitivity. This sensitivity can be measured by spectral ripple tests, which can be administered at different presentation levels. However, it is not known how presentation level affects spectrotemporal modulation thresholds. In this work, we present behavioral data for normal-hearing adults which show that at higher ripple densities (2 and 4 ripples/oct), increasing presentation level led to worse discrimination thresholds. Results of a computational model suggested that the higher thresholds could be explained by a worsening of the spectrotemporal representation in the auditory nerve due to broadening of cochlear filters and neural activity saturation. Our results demonstrate the importance of taking presentation level into account when administering spectrotemporal modulation detection tests.

neuroscience↗

bioRxiv2018

High-dimensional single cell-analysis of lymphocytic activation in melanoma

In melanoma, the lymphocytic infiltrate is a prognostic parameter classified morphologically into "brisk", "non-brisk" and "absent" entailing a functional association that has never been proved. Recently, it has been shown that lymphocytic populations can be very heterogeneous, and that anti-PD-1 immunotherapy supports activated T cells. Here, we characterize the immune landscape in primary melanoma by high-dimensional single cell multiplex analysis in tissue sections (MILAN technique) followed by image analysis, RT-PCR and shotgun proteomics. We observed that the brisk and non-brisk patterns are heterogeneous functional categories that can be further sub-classified into active, transitional or exhausted. The classification of primary melanomas based on the functional paradigm also shows correlation with spontaneous regression, and an improved prognostic value than that of the brisk classification. Finally, the main inflammatory cell subpopulations that are present in the microenvironment associated with activation and exhaustion and their spatial relationships are described using neighbourhood analysis.

cancer biology↗

bioRxiv2018

Cis-topic modelling of single cell epigenomes

Single-cell epigenomics provides new opportunities to decipher genomic regulatory programs from heterogeneous samples and dynamic processes. We present a probabilistic framework called cisTopic, to simultaneously discover \"cis-regulatory topics\" and stable cell states from sparse single-cell epigenomics data. After benchmarking cisTopic on single-cell ATAC-seq data, single-cell DNA methylation data, and semi-simulated single-cell ChIP-seq data, we use cisTopic to predict regulatory programs in the human brain and validate these by aligning them with co-expression networks derived from single-cell RNA-seq data. Next, we performed a time-series single-cell ATAC-seq experiment after SOX10 perturbations in melanoma cultures, where cisTopic revealed dynamic regulatory topics driven by SOX10 and AP-1. Finally, machine learning and enhancer modelling approaches allowed to predict cell type specific SOX10 and SOX9 binding sites based on topic specific co-regulatory motifs. cisTopic is available as an R/Bioconductor package at http://github.com/aertslab/cistopic.

bioinformatics↗

bioRxiv2018

Epigallocatechin-3-Gallate Improves Facial Dysmorphology Associated with Down Syndrome

In Down syndrome (DS), the overall genetic imbalance caused by trisomy of chromosome 21 leads to a complex pleiotropic phenotype that involves a recognizable set of facial traits. Several studies have shown the potential of epigallocatechin-3-gallate (EGCG), a green tea flavanol, as a therapeutic tool for alleviating different developmental alterations associated with DS, such as cognitive impairment, skull dysmorphologies, and skeletal deficiencies. Here we provide for the first time experimental and clinical evidence of the potential benefits of EGCG treatment to facial morphology. Our results showed that mouse models treated with low dose of EGCG during pre- and postnatal development improved facial dysmorphology. However, the same treatment at high dose produced disparate facial morphology changes with an extremely wide and abnormal range of variation. Our observational study in humans revealed that EGCG treatment since early in development is associated with intermediate facial phenotypes and significant facial improvement scores. Overall, our findings suggest a potential beneficial effect of ECGC on facial development, which requires further research to pinpoint the optimal dosages of EGCG that reliably improve DS phenotypes. Current evidence warns against the non-prescribed intake of this supplement as a health-promoting measure.

pathology↗

bioRxiv2018

Speech intelligibility predicted from neural entrainment of the speech envelope

Speech intelligibility is currently measured by scoring how well a person can identify a speech signal. The results of such behavioral measures reflect neural processing of the speech signal, but are also influenced by language processing, motivation and memory. Very often electrophysiological measures of hearing give insight in the neural processing of sound. However, in most methods non-speech stimuli are used, making it hard to relate the results to behavioral measures of speech intelligibility. The use of natural running speech as a stimulus in electrophysiological measures of hearing is a paradigm shift which allows to bridge the gap between behavioral and electrophysiological measures. Here, by decoding the speech envelope from the electroencephalogram, and correlating it with the stimulus envelope, we demonstrate an electrophysiological measure of neural processing of running speech. We show that behaviorally measured speech intelligibility is strongly correlated with our electrophysiological measure. Our results pave the way towards an objective and automatic way of assessing neural processing of speech presented through auditory prostheses, reducing confounds such as attention and cognitive capabilities. We anticipate that our electrophysiological measure will allow better differential diagnosis of the auditory system, and will allow the development of closed-loop auditory prostheses that automatically adapt to individual users.

neuroscience↗

bioRxiv2017

SCENIC: Single-Cell Regulatory Network Inference And Clustering

Single-cell RNA-seq allows building cell atlases of any given tissue and infer the dynamics of cellular state transitions during developmental or disease trajectories. Both the maintenance and transitions of cell states are encoded by regulatory programs in the genome sequence. However, this regulatory code has not yet been exploited to guide the identification of cellular states from single-cell RNA-seq data. Here we describe a computational resource, called SCENIC (Single Cell rEgulatory Network Inference and Clustering), for the simultaneous reconstruction of gene regulatory networks (GRNs) and the identification of stable cell states, using single-cell RNA-seq data. SCENIC outperforms existing approaches at the level of cell clustering and transcription factor identification. Importantly, we show that cell state identification based on GRNs is robust towards batch-effects and technical-biases. We applied SCENIC to a compendium of single-cell data from the mouse and human brain and demonstrate that the proper combinations of transcription factors, target genes, enhancers, and cell types can be identified. Moreover, we used SCENIC to map the cell state landscape in melanoma and identified a gene regulatory network underlying a proliferative melanoma state driven by MITF and STAT and a contrasting network controlling an invasive state governed by NFATC2 and NFIB. We further validated these predictions by showing that two transcription factors are predominantly expressed in early metastatic sentinel lymph nodes. In summary, SCENIC is the first method to analyze scRNA-seq data using a network-centric, rather than cell-centric approach. SCENIC is generic, easy to use, and flexible, and allows for the simultaneous tracing of genomic regulatory programs and the mapping of cellular identities emerging from these programs. Availability: SCENIC is available as an R workflow based on three new R/Bioconductor packages: GENIE3, RcisTarget and AUCell. As scalable alternative to GENIE3, we also provide GRNboost, paving the way towards the network analysis across millions of single cells.

bioinformatics↗