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From Liebel-lab
Welcome to Liebel-Lab @ KIT - Karlsruhe Institute of Technology -
BioInterfaces Programme
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Our Research Interests:
- Next Generation High Content Screening platform research and developments.
- Novel Microscopy methods, in vivo, 5D, transparent Data logistics, (ultra-)fast image-processing, data analysis and bioinformatic crosslinking.
- Life Science Informatics
- We combine biology, engineering, search engine technology, image processing, robotics, bioinformatitics and 103% fun in one team.
Overview
(in vivo) Assay Development
Every novel screening platform starts with a specific biological question. We focus our developments on the biological problem not on a specific technology.
We work mostly with the zebrafish model system.
- For the DOPAMINET project http://dopaminet.eu we currently develop a method for rapid 3D zebrafish imaging (1000s of embryos).
Knowledge crosslinking - project "Sciencenet": Towards the integration of all scientific data"
"Goal: Search of > 1.000.000.000 distributed scientific documents in one second"
We develop novel tools to access knowledge distributed across 1000s of different databases and data sinks.
- Sciencenet (alpha) Main portal (ALL sciencenet search engines)
- Sciencenet Bioinformatic Harvester Search
- Sciencenet OAI p2p search engine
- Sciencenet Free software foundation search engine
- Geocache search engine
- KIT search engine
High Content Screen Data Visualization and handling
- AskMe Screen Library: An easy to use software tool that allows data publishing and sharing.
- A simple to use little desktop tool by which users are able to publish and share their own scientific data or websites.
- The tool handles large scale image data sets from HCS experiments by providing a dataset preview.
- All collected meta information is presented in corresponding experiment descriptor files in both human and computer readable form.
- This data publication method follows the principle of a Linked Open Data architecture (Berners-Lee, 2006) and is already the foundation for a semantically enriched web.
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- Our Open microscopy Demo-Server - sponsored by Steinbuch Centre for Computing
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See Jason Swedlows lab and OME Project
Knowledge crosslinking - project: "Bioinformatic Harvester",
- We developed "Bioinformatic Harvester" to access knowledge in over >50 bioinformatic databases.
- We developed "Harvester42" a meta search engine which integrates >50 major search engines.
- See more on the Search_engine_research portal
Intelligent High Content Screening microscopes
We develop novel high-content and high-resolution screening microscopes and methods, often with an industrial partner (Olympus Europa, Leica Microsystems).
Many biological assays require identification of a “structure of interest” before high resolution and high quality imaging. A “structure of interest” can be, for example, a rare cell phase (metaphase), a transfected cell amongst many non-transfected cells or a GFP label in a specific organ of a transgenic Zebrafish. For these challenges we developed, in cooperation with Frank Sieckmann, Leica Microsystems, the Computer Aided Microscopy (CAM) technology. CAM uses the low magnification objectives of a microscope in combination with online real-time image processing techniques to identify a priori defined structures of interest. After initial detection the CAM microscopes switch automatically to high resolution set-ups and start complex image acquisition experiments, for example, 3D multicolour time-lapse experiments. Hundreds of samples can be processed overnight, which was previously impossible to do.
- For more see the High_content_screening portal
(real-time) Large Scale Image processing (hardware and software developments)
- High Content Screening platforms generate 10.000s to 1.000.000s of images per assay.
Often 200.000 images / day per single microscope need to be processed. We developed silent 24 core high end image processing PCs, which work close to the microscopes. Ideally they analyze image data in real-time. Currently the "image boxes" can store 10 TByte and process (write data) at 1,2 GByte/sec, which is ~20x faster than "regular" PCs.
- We develop powerful image processing algorithms and computer cluster processing methods in Matlab, Definiens, Labview Vision, ImageJ
- See the Image_processing portal for details
Lab automation and Robotics (Schulz group IAI)
We develop novel lab automation solutions and imaging robots. See robo-videos on the Biorobotics page.
- project: zebrafish sorting robot (left), allows fully automated sorting of zebrafish embryos in 96/384 well plates
- project: parallel screening microscope, uses 4 cameras in parallel for rapid Microtiter plate screening (e.g. zebrafish heart beat frequency measurements.
Large Scale Data facility LSDF (Wezel group (SCC))
- 1000s or even 1.000.000s of images need to be handled, analyzed and stored for every new assay.
- We develop storage and processing methods which allow parallel high speed microscope operation.
- Thanks to KITs LSDF (Large Scale Data facility), we have access to a long term storage solution.
Transparent data handling: Project "Plexus"
- See more on the Search_engine_research portal
Industrial collaborations and products
In collaboration with companies we initiated, helped, improved the following commercial products:
- Leica HCS Matrix Screen software + CAM (Computer Aided microscopy) interface
- Scan^R High Content Screening Microscope (Olympus Europa)
- Leica Microsystems automatic water immersion objective
- See more on the Industrial_collaborations page
Alumni projects
- Harvester-Sequence Sequence realtime search (4 genomes parallel) (collaboration Avi Epstein EMBL)
- A custom designed CHIP for high speed sequence search and comparison (indluding partial matches in realtime!!)
- Test Harvester-Sequence search.
Latest publication
- Biotechniques: Automated feature detection and imaging for high-resolution screening of zebrafish embryos.. 2011 May;50(5):319-24.
Peravali R, Gehrig J, Giselbrecht S, Lütjohann DS, Hadzhiev Y, Müller F, Liebel U.
http://www.ncbi.nlm.nih.gov/pubmed/21548893
- "Sciencenet" - Towards a global search and share engine for all scientific knowledge.
- Modern biological experiments create vast amounts of data which are geographically distributed. These datasets consist of petabytes of raw data and billions of documents. Yet to the best of our knowledge, a search engine technology that searches and crosslinks all different data types in life sciences does not exist. We have developed a prototype distributed scientific search engine technology, “Sciencenet”, which facilitates rapid searching over this large data space. By “bringing the search engine to the data” we do not require server farms. This platform also allows users to contribute to the search index and publish their large scale data to support e-Science. Furthermore, a community-driven method guarantees that only scientific content is crawled and presented. Our peer-to-peer approach is sufficiently scalalable for the science web without performance or capacity tradeoff.
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- BMC Biology "A high-throughput chemically induced inflammation assay in zebrafish"
http://www.biomedcentral.com/1741-7007/8/151
- Background
Studies on innate immunity have benefited from the introduction of zebrafish as a model system. Transgenic fish expressing fluorescent proteins in leukocyte populations allow direct, quantitative visualization of an inflammatory response in vivo. It has been proposed that this animal model can be used for high-throughput screens aimed at the identification of novel immuno-modulatory lead compounds. However, current assays require invasive manipulation of fish individually, thus preventing high content screening.
- Results
Here, we show that specific, non-invasive damage to lateral line neuromast cells can induce a robust acute inflammatory response. Exposure of fish larvae to sub-lethal concentrations of copper sulfate selectively damages the sensory hair cell population inducing infiltration of leukocytes to neuromasts within 20 minutes. Inflammation can be assayed in real-time using transgenic fish expressing fluorescent proteins in leukocytes or by histochemical assays in fixed larvae. We demonstrate the usefulness of this method for chemical and genetic screens to detect the effect of immuno-modulatory compounds and mutations affecting the leukocyte response. Moreover, we transformed the assay into a high-throughput screening method by using a customized automated imaging and processing system that quantifies the magnitude of the inflammatory reaction.
- Conclusions
This approach allows rapid screening of thousands of compounds or mutagenized zebrafish for effects on inflammation and enables the identification of novel players in the regulation of innate immunity and potential lead compounds towards new immuno-modulatory therapies. We have called this method the Chemically-Induced Inflammation Assay, or ChIn Assay. See Commentary article: http://www.biomedcentral.com/1741-7007/8/148.
