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Nitschke, R.

Publications and source records attributed to Nitschke, R..

7 recordsLinked to original sources

Supra-regular recursion in primate vocal sequences

Complex syntax is the widely accepted demarcation between animal and human communication. Although animal vocal systems occasionally contain pockets of syntax-like structures, their grammars are thought to be at best regular, whereas human language is supra-regular, i.e., including at least context-free computational complexity. Leveraging a new likelihood method for probabilistic formal grammars, we show that the call sequences of three phylogenetically diverse nonhuman primates (bonobos, olive colobus monkeys, common marmosets) include parts that are most likely generated by supra-regular recursive grammars, similar to human language. These findings challenge syntax as the major transition in hominid evolution and opens up prospects for alternative evolutionary scenarios.

animal behavior and cognition↗

Parameters for stable Notch-independent Her6 oscillations across a frequency spectrum in neural stem cell populations

Neural proliferation zones drive the major growth phases of the vertebrate brain. Notch signaling and HES/Her transcription factors control neural stem cell (NSC) maintenance and neurogenesis, however the dynamic regulation of neural proliferation zones to sustain growth is not well understood. Notch-independent expression of the zebrafish HES1 homolog her6 in the larval brain is required for NSC maintenance and growth. We generated an mNeonGreen knock-in into the her6 locus and quantified Her6-mNeonGreen oscillations in vivo in distinct NSC populations. Her6 oscillates cell-autonomously across a broader frequency range, unaffected by inhibition of Notch signaling, and robustly reinitiated after experimental perturbations. Mathematical modelling reveals that Her6 oscillations prevail only when both transcript and protein degradation rate constants are equal. These intrinsic control parameters may have evolved to enable the Her6 oscillator to robustly maintain stemness during proliferative phases irrespective of local Notch signaling cues, and to provide for lineage stability while retaining plasticity for lineage progression.

developmental biology↗

Microtubule anchoring and coupling of CD20 to the RhoA/Rock1 pathway

CD20 is a B cell-specific four-helix transmembrane protein and a prominent target of therapeutic anti-CD20 antibodies. CD20 is localized within a membrane nanocluster harboring the IgD class B cell antigen receptor (IgD-BCR) where it functions as a gatekeeper for the resting state of naive B lymphocytes. How CD20 exerts its gatekeeper function is not yet known. Using Ramos and human peripheral blood B cells, we show here that the serine/threonine kinase PKC{delta}, constitutively phosphorylates serine residues at the cytosolic tails of CD20. The phosphorylated CD20 becomes a target for 14-3-3 adaptor proteins that link CD20 to the RhoA GDP/GTP exchange factor GEF-H1 and the microtubule (MT) network controlling the stability of the IgD-BCR nanocluster. The binding of anti-CD20 antibodies results in MT disassembly and the replacement of the GEF-H1/CD20 complex by a RhoA-GTP/ROCK1/CD20 complex which drives actomyosin contractility. Our study suggests that CD20 not only maintains the resting state, but also orchestrates the MT/actin switch in active B lymphocytes. This could have implications for treatment with anti-CD20 antibodies and may help to optimize therapeutic protocols. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/656301v2_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@1cfe15aorg.highwire.dtl.DTLVardef@d3ee14org.highwire.dtl.DTLVardef@1b375eforg.highwire.dtl.DTLVardef@103c9dd_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Long-term quality assessment and monitoring of light microscope performance through accessible and reliable protocols, tools and metrics

Reliable, reproducible and comparable results are what biology requires from microscopy. To achieve that level of confidence, monitoring the stability of the microscope performance over time with standardized quality testing routines is essential for mining quantitative data. Three levels of microscope quality control procedures should be considered: i) usage of accessible and affordable tools and samples, ii) execution of easy and fast, preferably automatized, acquisition protocols, iii) analysis of data in the most automated way possible with adequate metrics for long-term monitoring. In this paper, we test the acquisition protocols on the mainly used microscope techniques (wide-field, spinning disk and confocal microscopy) with simple quality control tools. Seven protocols specify metrics on measuring the lateral and axial resolution (Point-Spread Function) of the system, field flatness, chromatic aberrations and co-registration, illumination power monitoring and stability, stage drift and positioning repeatability and finally temporal and spatial noise sources of camera detectors. We designed an ImageJ/FiJi java plugin named MetroloJ_QC to incorporate the identified metrics and automatize the data processing for the analysis. After processing and comparing the data of microscopes from more than ten imaging facilities, we test the robustness of the metrics and the protocols by determining experimental limit values. Our results give a first extensive characterization of the quality control procedures of a light microscope, with an automated data processing and experimental limit values that can be used by core facility staff and researchers to monitor the microscope performance over time.

scientific communication and education↗

Micro-Meta App: an interactive software tool to facilitate the collection of microscopy metadata based on community-driven specifications

For the information content of microscopy images to be appropriately interpreted, reproduced, and meet FAIR (Findable Accessible Interoperable and Reusable) principles, they should be accompanied by detailed descriptions of microscope hardware, image acquisition settings, image pixel and dimensional structure, and instrument performance. Nonetheless, the thorough documentation of imaging experiments is significantly impaired by the lack of community-sanctioned easy-to-use software tools to facilitate the extraction and collection of relevant microscopy metadata. Here we present Micro-Meta App, an intuitive open-source software designed to tackle these issues that was developed in the context of nascent global bioimaging community organizations, including BioImaging North America (BINA) and QUAlity Assessment and REProducibility in Light Microscopy (QUAREP-LiMi), whose goal is to improve reproducibility, data quality and sharing value for imaging experiments. The App provides a user-friendly interface for building comprehensive descriptions of the conditions utilized to produce individual microscopy datasets as specified by the recently proposed 4DN-BINA-OME tiered-system of Microscopy Metadata model. To achieve this goal the App provides a visual guide for a microscope-user to: 1) interactively build diagrammatic representations of hardware configurations of given microscopes that can be easily reused and shared with colleagues needing to document similar instruments. 2) Automatically extracts relevant metadata from image files and facilitates the collection of missing image acquisition settings and calibration metrics associated with a given experiment. 3) Output all collected Microscopy Metadata to interoperable files that can be used for documenting imaging experiments and shared with the community. In addition to significantly lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training users that have limited knowledge of the intricacies of light microscopy experiments. To ensure wide-adoption by microscope-users with different needs Micro-Meta App closely interoperates with MethodsJ2 and OMERO.mde, two complementary tools described in parallel manuscripts.

bioinformatics↗

Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model

1 -Digital light microscopy provides powerful tools for quantitatively probing the real-time dynamics of subcellular structures. While the power of modern microscopy techniques is undeniable, rigorous record-keeping and quality control are required to ensure that imaging data may be properly interpreted (quality), reproduced (reproducibility), and used to extract reliable information and scientific knowledge which can be shared for further analysis (value). Keeping notes on microscopy experiments and quality control procedures ought to be straightforward, as the microscope is a machine whose components are defined and the performance measurable. Nevertheless, to this date, no universally adopted community-driven specifications exist that delineate the required information about the microscope hardware and acquisition settings (i.e., microscopy "data provenance" metadata) and the minimally accepted calibration metrics (i.e., microscopy quality control metadata) that should be automatically recorded by both commercial microscope manufacturers and customized microscope developers. In the absence of agreed guidelines, it is inherently difficult for scientists to create comprehensive records of imaging experiments and ensure the quality of resulting image data or for manufacturers to incorporate standardized reporting and performance metrics. To add to the confusion, microscopy experiments vary greatly in aim and complexity, ranging from purely descriptive work to complex, quantitative and even sub-resolution studies that require more detailed reporting and quality control measures. To solve this problem, the 4D Nucleome Initiative (4DN) (1, 2) Imaging Standards Working Group (IWG), working in conjunction with the BioImaging North America (BINA) Quality Control and Data Management Working Group (QC-DM-WG) (3), here propose light Microscopy Metadata specifications that scale with experimental intent and with the complexity of the instrumentation and analytical requirements. They consist of a revision of the Core of the Open Microscopy Environment (OME) Data Model, which forms the basis for the widely adopted Bio-Formats library (4-6), accompanied by a suite of three extensions, each with three tiers, allowing the classification of imaging experiments into levels of increasing imaging and analytical complexity (7, 8). Hence these specifications not only provide an OME-based comprehensive set of metadata elements that should be recorded, but they also specify which subset of the full list should be recorded for a given experimental tier. In order to evaluate the extent of community interest, an extensive outreach effort was conducted to present the proposed metadata specifications to members of several core-facilities and international bioimaging initiatives including the European Light Microscopy Initiative (ELMI), Global BioImaging (GBI), and European Molecular Biology Laboratory (EMBL) - European Bioinformatics Institute (EBI). Consequently, close ties were established between our endeavour and the undertakings of the recently established QUAlity Assessment and REProducibility for Instruments and Images in Light Microscopy global community initiative (9). As a result this flexible 4DN-BINA-OME (NBO namespace) framework (7, 8) represents a turning point towards achieving community-driven Microscopy Metadata standards that will increase data fidelity, improve repeatability and reproducibility, ease future analysis and facilitate the verifiable comparison of different datasets, experimental setups, and assays, and it demonstrates the method for future extensions. Such universally accepted microscopy standards would serve a similar purpose as the Encode guidelines successfully adopted by the genomic community (10, 11). The intention of this proposal is therefore to encourage participation, critiques and contributions from the entire imaging community and all stakeholders, including research and imaging scientists, facility personnel, instrument manufacturers, software developers, standards organizations, scientific publishers, and funders.

bioinformatics↗

Image-derived Models of Cell Organization Changes During Differentiation of PC12 Cells

Cellular differentiation is a complex process requiring the coordination of many cellular components. PC12 cells are a popular model system to study changes driving and accompanying neuronal differentiation. While significant attention has been paid to changes in transcriptional regulation and protein signaling, much less is known about the changes in cell organization that accompany PC12 differentiation. Fluorescence microscopy can provide extensive information about this, although photobleaching and phototoxicity frequently limit the ability to continuously observe changes in single cells over the many days that differentiation occurs. Here we describe a generative model of differentiation-associated changes in cell and nuclear shape and their relationship to mitochondrial distribution constructed from images of different cells at discrete time points. We show that our spherical harmonic-based model can accurately represent cell and nuclear shapes by measuring reconstruction errors. We then learn a regression model that relates cell and nuclear shape and mitochondrial distribution and observe that the predictive accuracy generally increases during differentiation. Most importantly, we propose a method, based on cell matching and linear interpolation in the shape space, to model the dynamics of cell differentiation using only static images. Without any prior knowledge, the method produces a realistic shape evolution process.\n\nAuthor Summary\n\nCellular differentiation is an important process that is challenging to study due to the number of organizational changes it includes and the different time scales over which it occurs. Fluorescent microscopy is widely used to study cell dynamics and differentiation, but photobleaching and phototoxicity often make it infeasible to continuously observe a single cell undergoing differentiation for several days. In this work, we described a method to model aspects of the dynamics of PC12 cell differentiation without continuous imaging. We constructed accurate representations of cell and nuclear shapes and quantified the relationships between shapes and mitochondrial distributions. We used these to construct a generative model and combined it with a matching process to infer likely sequences of the changes in single cells undergoing differentiation.

cell biology↗