Publications by authors named "Olaf Ronneberger"

41 Publications

Highly accurate protein structure prediction for the human proteome.

Nature 2021 Aug 22;596(7873):590-596. Epub 2021 Jul 22.

European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.

Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure. Here we markedly expand the structural coverage of the proteome by applying the state-of-the-art machine learning method, AlphaFold, at a scale that covers almost the entire human proteome (98.5% of human proteins). The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence. We introduce several metrics developed by building on the AlphaFold model and use them to interpret the dataset, identifying strong multi-domain predictions as well as regions that are likely to be disordered. Finally, we provide some case studies to illustrate how high-quality predictions could be used to generate biological hypotheses. We are making our predictions freely available to the community and anticipate that routine large-scale and high-accuracy structure prediction will become an important tool that will allow new questions to be addressed from a structural perspective.
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http://dx.doi.org/10.1038/s41586-021-03828-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387240PMC
August 2021

Highly accurate protein structure prediction with AlphaFold.

Nature 2021 Aug 15;596(7873):583-589. Epub 2021 Jul 15.

DeepMind, London, UK.

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined, but this represents a small fraction of the billions of known protein sequences. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence-the structure prediction component of the 'protein folding problem'-has been an important open research problem for more than 50 years. Despite recent progress, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14), demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.
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http://dx.doi.org/10.1038/s41586-021-03819-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371605PMC
August 2021

Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study.

J Med Internet Res 2021 Jul 12;23(7):e26151. Epub 2021 Jul 12.

DeepMind, London, United Kingdom.

Background: Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment while also introducing interoperator variability, resulting in downstream radiation dose differences. Although auto-segmentation algorithms offer a potentially time-saving solution, the challenges in defining, quantifying, and achieving expert performance remain.

Objective: Adopting a deep learning approach, we aim to demonstrate a 3D U-Net architecture that achieves expert-level performance in delineating 21 distinct head and neck organs at risk commonly segmented in clinical practice.

Methods: The model was trained on a data set of 663 deidentified computed tomography scans acquired in routine clinical practice and with both segmentations taken from clinical practice and segmentations created by experienced radiographers as part of this research, all in accordance with consensus organ at risk definitions.

Results: We demonstrated the model's clinical applicability by assessing its performance on a test set of 21 computed tomography scans from clinical practice, each with 21 organs at risk segmented by 2 independent experts. We also introduced surface Dice similarity coefficient, a new metric for the comparison of organ delineation, to quantify the deviation between organ at risk surface contours rather than volumes, better reflecting the clinical task of correcting errors in automated organ segmentations. The model's generalizability was then demonstrated on 2 distinct open-source data sets, reflecting different centers and countries to model training.

Conclusions: Deep learning is an effective and clinically applicable technique for the segmentation of the head and neck anatomy for radiotherapy. With appropriate validation studies and regulatory approvals, this system could improve the efficiency, consistency, and safety of radiotherapy pathways.
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http://dx.doi.org/10.2196/26151DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314151PMC
July 2021

Author Correction: U-Net: deep learning for cell counting, detection, and morphometry.

Nat Methods 2019 Apr;16(4):351

Department of Computer Science, Albert-Ludwigs-University, Freiburg, Germany.

In the version of this paper originally published, one of the affiliations for Dominic Mai was incorrect: "Center for Biological Systems Analysis (ZBSA), Albert-Ludwigs-University, Freiburg, Germany" should have been "Life Imaging Center, Center for Biological Systems Analysis, Albert-Ludwigs-University, Freiburg, Germany." This change required some renumbering of subsequent author affiliations. These corrections have been made in the PDF and HTML versions of the article, as well as in any cover sheets for associated Supplementary Information.
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http://dx.doi.org/10.1038/s41592-019-0356-4DOI Listing
April 2019

U-Net: deep learning for cell counting, detection, and morphometry.

Nat Methods 2019 01 17;16(1):67-70. Epub 2018 Dec 17.

Department of Computer Science, Albert-Ludwigs-University, Freiburg, Germany.

U-Net is a generic deep-learning solution for frequently occurring quantification tasks such as cell detection and shape measurements in biomedical image data. We present an ImageJ plugin that enables non-machine-learning experts to analyze their data with U-Net on either a local computer or a remote server/cloud service. The plugin comes with pretrained models for single-cell segmentation and allows for U-Net to be adapted to new tasks on the basis of a few annotated samples.
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http://dx.doi.org/10.1038/s41592-018-0261-2DOI Listing
January 2019

Clinically applicable deep learning for diagnosis and referral in retinal disease.

Nat Med 2018 09 13;24(9):1342-1350. Epub 2018 Aug 13.

NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology, London, UK.

The volume and complexity of diagnostic imaging is increasing at a pace faster than the availability of human expertise to interpret it. Artificial intelligence has shown great promise in classifying two-dimensional photographs of some common diseases and typically relies on databases of millions of annotated images. Until now, the challenge of reaching the performance of expert clinicians in a real-world clinical pathway with three-dimensional diagnostic scans has remained unsolved. Here, we apply a novel deep learning architecture to a clinically heterogeneous set of three-dimensional optical coherence tomography scans from patients referred to a major eye hospital. We demonstrate performance in making a referral recommendation that reaches or exceeds that of experts on a range of sight-threatening retinal diseases after training on only 14,884 scans. Moreover, we demonstrate that the tissue segmentations produced by our architecture act as a device-independent representation; referral accuracy is maintained when using tissue segmentations from a different type of device. Our work removes previous barriers to wider clinical use without prohibitive training data requirements across multiple pathologies in a real-world setting.
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http://dx.doi.org/10.1038/s41591-018-0107-6DOI Listing
September 2018

Data-Driven Modeling of Intracellular Auxin Fluxes Indicates a Dominant Role of the ER in Controlling Nuclear Auxin Uptake.

Cell Rep 2018 03;22(11):3044-3057

Institute of Biology II, University of Freiburg, 79104 Freiburg, Germany. Electronic address:

In plants, the phytohormone auxin acts as a master regulator of developmental processes and environmental responses. The best characterized process in the auxin regulatory network occurs at the subcellular scale, wherein auxin mediates signal transduction into transcriptional programs by triggering the degradation of Aux/IAA transcriptional repressor proteins in the nucleus. However, whether and how auxin movement between the nucleus and the surrounding compartments is regulated remain elusive. Using a fluorescent auxin analog, we show that its diffusion into the nucleus is restricted. By combining mathematical modeling with time course assays on auxin-mediated nuclear signaling and quantitative phenotyping in single plant cell systems, we show that ER-to-nucleus auxin flux represents a major subcellular pathway to directly control nuclear auxin levels. Our findings propose that the homeostatically regulated auxin pool in the ER and ER-to-nucleus auxin fluxes underpin auxin-mediated downstream responses in plant cells.
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http://dx.doi.org/10.1016/j.celrep.2018.02.074DOI Listing
March 2018

An objective comparison of cell-tracking algorithms.

Nat Methods 2017 Dec 30;14(12):1141-1152. Epub 2017 Oct 30.

i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.
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http://dx.doi.org/10.1038/nmeth.4473DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777536PMC
December 2017

Automated analysis of retinal imaging using machine learning techniques for computer vision.

F1000Res 2016 5;5:1573. Epub 2016 Jul 5.

DeepMind, London, EC4A 3TW, UK.

There are almost two million people in the United Kingdom living with sight loss, including around 360,000 people who are registered as blind or partially sighted. Sight threatening diseases, such as diabetic retinopathy and age related macular degeneration have contributed to the 40% increase in outpatient attendances in the last decade but are amenable to early detection and monitoring. With early and appropriate intervention, blindness may be prevented in many cases. Ophthalmic imaging provides a way to diagnose and objectively assess the progression of a number of pathologies including neovascular ("wet") age-related macular degeneration (wet AMD) and diabetic retinopathy. Two methods of imaging are commonly used: digital photographs of the fundus (the 'back' of the eye) and Optical Coherence Tomography (OCT, a modality that uses light waves in a similar way to how ultrasound uses sound waves). Changes in population demographics and expectations and the changing pattern of chronic diseases creates a rising demand for such imaging. Meanwhile, interrogation of such images is time consuming, costly, and prone to human error. The application of novel analysis methods may provide a solution to these challenges. This research will focus on applying novel machine learning algorithms to automatic analysis of both digital fundus photographs and OCT in Moorfields Eye Hospital NHS Foundation Trust patients. Through analysis of the images used in ophthalmology, along with relevant clinical and demographic information, DeepMind Health will investigate the feasibility of automated grading of digital fundus photographs and OCT and provide novel quantitative measures for specific disease features and for monitoring the therapeutic success.
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http://dx.doi.org/10.12688/f1000research.8996.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5082593PMC
July 2016

A 3D digital atlas of the Nicotiana tabacum root tip and its use to investigate changes in the root apical meristem induced by the Agrobacterium 6b oncogene.

Plant J 2017 Oct 11;92(1):31-42. Epub 2017 Aug 11.

Department of Molecular Mechanisms of Phenotypic Plasticity, Institut de Biologie Moléculaire des Plantes, Rue du Général Zimmer 12, 67084, Strasbourg, France.

Using the intrinsic Root Coordinate System (iRoCS) Toolbox, a digital atlas at cellular resolution has been constructed for Nicotiana tabacum roots. Mitotic cells and cells labeled for DNA replication with 5-ethynyl-2'-deoxyuridine (EdU) were mapped. The results demonstrate that iRoCS analysis can be applied to roots that are thicker than those of Arabidopsis thaliana without histological sectioning. A three-dimensional (3-D) analysis of the root tip showed that tobacco roots undergo several irregular periclinal and tangential divisions. Irrespective of cell type, rapid cell elongation starts at the same distance from the quiescent center, however, boundaries between cell proliferation and transition domains are cell-type specific. The data support the existence of a transition domain in tobacco roots. Cell endoreduplication starts in the transition domain and continues into the elongation zone. The tobacco root map was subsequently used to analyse root organization changes caused by the inducible expression of the Agrobacterium 6b oncogene. In tobacco roots that express the 6b gene, the root apical meristem was shorter and radial cell growth was reduced, but the mitotic and DNA replication indexes were not affected. The epidermis of 6b-expressing roots produced less files and underwent abnormal periclinal divisions. The periclinal division leading to mature endodermis and cortex3 cell files was delayed. These findings define additional targets for future studies on the mode of action of the Agrobacterium 6b oncogene.
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http://dx.doi.org/10.1111/tpj.13631DOI Listing
October 2017

A new fate mapping system reveals context-dependent random or clonal expansion of microglia.

Nat Neurosci 2017 Jun 17;20(6):793-803. Epub 2017 Apr 17.

Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Microglia constitute a highly specialized network of tissue-resident immune cells that is important for the control of tissue homeostasis and the resolution of diseases of the CNS. Little is known about how their spatial distribution is established and maintained in vivo. Here we establish a new multicolor fluorescence fate mapping system to monitor microglial dynamics during steady state and disease. Our findings suggest that microglia establish a dense network with regional differences, and the high regional turnover rates found challenge the universal concept of microglial longevity. Microglial self-renewal under steady state conditions constitutes a stochastic process. During pathology this randomness shifts to selected clonal microglial expansion. In the resolution phase, excess disease-associated microglia are removed by a dual mechanism of cell egress and apoptosis to re-establish the stable microglial network. This study unravels the dynamic yet discrete self-organization of mature microglia in the healthy and diseased CNS.
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http://dx.doi.org/10.1038/nn.4547DOI Listing
June 2017

Gland segmentation in colon histology images: The glas challenge contest.

Med Image Anal 2017 01 3;35:489-502. Epub 2016 Sep 3.

Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK. Electronic address:

Colorectal adenocarcinoma originating in intestinal glandular structures is the most common form of colon cancer. In clinical practice, the morphology of intestinal glands, including architectural appearance and glandular formation, is used by pathologists to inform prognosis and plan the treatment of individual patients. However, achieving good inter-observer as well as intra-observer reproducibility of cancer grading is still a major challenge in modern pathology. An automated approach which quantifies the morphology of glands is a solution to the problem. This paper provides an overview to the Gland Segmentation in Colon Histology Images Challenge Contest (GlaS) held at MICCAI'2015. Details of the challenge, including organization, dataset and evaluation criteria, are presented, along with the method descriptions and evaluation results from the top performing methods.
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http://dx.doi.org/10.1016/j.media.2016.08.008DOI Listing
January 2017

A benchmark for comparison of dental radiography analysis algorithms.

Med Image Anal 2016 Jul 28;31:63-76. Epub 2016 Feb 28.

Centre for Imaging Sciences, The University of Manchester, UK.

Dental radiography plays an important role in clinical diagnosis, treatment and surgery. In recent years, efforts have been made on developing computerized dental X-ray image analysis systems for clinical usages. A novel framework for objective evaluation of automatic dental radiography analysis algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2015 Bitewing Radiography Caries Detection Challenge and Cephalometric X-ray Image Analysis Challenge. In this article, we present the datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. The main contributions of the challenge include the creation of the dental anatomy data repository of bitewing radiographs, the creation of the anatomical abnormality classification data repository of cephalometric radiographs, and the definition of objective quantitative evaluation for comparison and ranking of the algorithms. With this benchmark, seven automatic methods for analysing cephalometric X-ray image and two automatic methods for detecting bitewing radiography caries have been compared, and detailed quantitative evaluation results are presented in this paper. Based on the quantitative evaluation results, we believe automatic dental radiography analysis is still a challenging and unsolved problem. The datasets and the evaluation software will be made available to the research community, further encouraging future developments in this field. (http://www-o.ntust.edu.tw/~cweiwang/ISBI2015/).
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http://dx.doi.org/10.1016/j.media.2016.02.004DOI Listing
July 2016

The polarity protein Inturned links NPHP4 to Daam1 to control the subapical actin network in multiciliated cells.

J Cell Biol 2015 Dec;211(5):963-73

Renal Division, Department of Medicine, University of Freiburg Medical Center, 79106 Freiburg, Germany Centre for Biological Signaling Studies, 79104 Freiburg, Germany

Motile cilia polarization requires intracellular anchorage to the cytoskeleton; however, the molecular machinery that supports this process remains elusive. We report that Inturned plays a central role in coordinating the interaction between cilia-associated proteins and actin-nucleation factors. We observed that knockdown of nphp4 in multiciliated cells of the Xenopus laevis epidermis compromised ciliogenesis and directional fluid flow. Depletion of nphp4 disrupted the subapical actin layer. Comparison to the structural defects caused by inturned depletion revealed striking similarities. Furthermore, coimmunoprecipitation assays demonstrated that the two proteins interact with each other and that Inturned mediates the formation of ternary protein complexes between NPHP4 and DAAM1. Knockdown of daam1, but not formin-2, resulted in similar disruption of the subapical actin web, whereas nphp4 depletion prevented the association of Inturned with the basal bodies. Thus, Inturned appears to function as an adaptor protein that couples cilia-associated molecules to actin-modifying proteins to rearrange the local actin cytoskeleton.
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http://dx.doi.org/10.1083/jcb.201502043DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4674276PMC
December 2015

Spontaneous and electric field-controlled front-rear polarization of human keratinocytes.

Mol Biol Cell 2015 Dec 30;26(24):4373-86. Epub 2015 Sep 30.

Center for Systems Biology, University of Freiburg, 79104 Freiburg, Germany Renal Division, University Hospital Freiburg, 79106 Freiburg, Germany BIOSS Centre for Biological Signalling Studies, University of Freiburg, 79104 Freiburg, Germany Imagine Institute, Paris Descartes University-Sorbonne Paris Cité, 75015 Paris, France

It has long been known that electrical fields (EFs) are able to influence the direction of migrating cells, a process commonly referred to as electrotaxis or galvanotaxis. Most studies have focused on migrating cells equipped with an existing polarity before EF application, making it difficult to delineate EF-specific pathways. Here we study the initial events in front-rear organization of spreading keratinocytes to dissect the molecular requirements for random and EF-controlled polarization. We find that Arp2/3-dependent protrusive forces and Rac1/Cdc42 activity were generally required for both forms of polarization but were dispensable for controlling the direction of EF-controlled polarization. By contrast, we found a crucial role for extracellular pH as well as G protein coupled-receptor (GPCR) or purinergic signaling in the control of directionality. The normal direction of polarization toward the cathode was reverted by lowering extracellular pH. Polarization toward the anode was also seen at neutral pH when GPCR or purinergic signaling was inhibited. However, the stepwise increase of extracellular pH in this scenario led to restoration of cathodal polarization. Overall our work puts forward a model in which the EF uses distinct polarization pathways. The cathodal pathway involves GPCR/purinergic signaling and is dominant over the anodal pathway at neutral pH.
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http://dx.doi.org/10.1091/mbc.E14-12-1580DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4666133PMC
December 2015

B cell antigen receptors of the IgM and IgD classes are clustered in different protein islands that are altered during B cell activation.

Sci Signal 2015 Sep 15;8(394):ra93. Epub 2015 Sep 15.

BIOSS Centre for Biological Signalling Studies, University of Freiburg, D-79104 Freiburg, Germany. Department of Molecular Immunology, Institute of Biology III at the Faculty of Biology of the University of Freiburg, D-79104, and at the Max Planck Institute of Immunobiology and Epigenetics, D-79108 Freiburg, Germany.

The B cell antigen receptors (BCRs) play an important role in the clonal selection of B cells and their differentiation into antibody-secreting plasma cells. Mature B cells have both immunoglobulin M (IgM) and IgD types of BCRs, which have identical antigen-binding sites and are both associated with the signaling subunits Igα and Igβ, but differ in their membrane-bound heavy chain isoforms. By two-color direct stochastic optical reconstruction microscopy (dSTORM), we showed that IgM-BCRs and IgD-BCRs reside in the plasma membrane in different protein islands with average sizes of 150 and 240 nm, respectively. Upon B cell activation, the BCR protein islands became smaller and more dispersed such that the IgM-BCRs and IgD-BCRs were found in close proximity to each other. Moreover, specific stimulation of one class of BCR had minimal effects on the organization of the other. These conclusions were supported by the findings from two-marker transmission electron microscopy and proximity ligation assays. Together, these data provide evidence for a preformed multimeric organization of BCRs on the plasma membrane that is remodeled after B cell activation.
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http://dx.doi.org/10.1126/scisignal.2005887DOI Listing
September 2015

Amotl2a interacts with the Hippo effector Yap1 and the Wnt/β-catenin effector Lef1 to control tissue size in zebrafish.

Elife 2015 Sep 3;4:e08201. Epub 2015 Sep 3.

Developmental Biology, Institute for Biology I, Faculty of Biology, Albert Ludwigs University of Freiburg, Freiburg im Breisgau, Germany.

During development, proliferation must be tightly controlled for organs to reach their appropriate size. While the Hippo signaling pathway plays a major role in organ growth control, how it senses and responds to increased cell density is still unclear. In this study, we use the zebrafish lateral line primordium (LLP), a group of migrating epithelial cells that form sensory organs, to understand how tissue growth is controlled during organ formation. Loss of the cell junction-associated Motin protein Amotl2a leads to overproliferation and bigger LLP, affecting the final pattern of sensory organs. Amotl2a function in the LLP is mediated together by the Hippo pathway effector Yap1 and the Wnt/β-catenin effector Lef1. Our results implicate for the first time the Hippo pathway in size regulation in the LL system. We further provide evidence that the Hippo/Motin interaction is essential to limit tissue size during development.
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http://dx.doi.org/10.7554/eLife.08201DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4596637PMC
September 2015

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge.

Neuroimage 2015 May 31;111:562-79. Epub 2015 Jan 31.

Biomedical Image Analysis (BioMedIA) Group, Department of Computing, Imperial College London, UK.

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.
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http://dx.doi.org/10.1016/j.neuroimage.2015.01.048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4943029PMC
May 2015

The Rac1 regulator ELMO controls basal body migration and docking in multiciliated cells through interaction with Ezrin.

Development 2015 Jan;142(1):174-84

Renal Division, University Hospital Freiburg, Freiburg 79106, Germany

Cilia are microtubule-based organelles that are present on most cells and are required for normal tissue development and function. Defective cilia cause complex syndromes with multiple organ manifestations termed ciliopathies. A crucial step during ciliogenesis in multiciliated cells (MCCs) is the association of future basal bodies with the apical plasma membrane, followed by their correct spacing and planar orientation. Here, we report a novel role for ELMO-DOCK1, which is a bipartite guanine nucleotide exchange factor complex for the small GTPase Rac1, and for the membrane-cytoskeletal linker Ezrin, in regulating centriole/basal body migration, docking and spacing. Downregulation of each component results in ciliopathy-related phenotypes in zebrafish and disrupted ciliogenesis in Xenopus epidermal MCCs. Subcellular analysis revealed a striking impairment of basal body docking and spacing, which is likely to account for the observed phenotypes. These results are substantiated by showing a genetic interaction between elmo1 and ezrin b. Finally, we provide biochemical evidence that the ELMO-DOCK1-Rac1 complex influences Ezrin phosphorylation and thereby probably serves as an important molecular switch. Collectively, we demonstrate that the ELMO-Ezrin complex orchestrates ciliary basal body migration, docking and positioning in vivo.
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http://dx.doi.org/10.1242/dev.112250DOI Listing
January 2015

Correction of inter-scanner and within-subject variance in structural MRI based automated diagnosing.

Neuroimage 2014 Sep 29;98:405-15. Epub 2014 Apr 29.

Freiburg Brain Imaging Center, University Medical Center, University of Freiburg, Freiburg, Germany; Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg, Germany; Department of Neurology, University Medical Center Freiburg, Freiburg, Germany.

Automated analysis of structural magnetic resonance images is a promising way to improve early detection of neurodegenerative brain diseases. Clinical applications of such methods involve multiple scanners with potentially different hardware and/or acquisition sequences and demographically heterogeneous groups. To improve classification performance, we propose to correct effects of subject-specific covariates (such as age, total intracranial volume, and sex) as well as effects of scanner by using a non-linear Gaussian process model. To test the efficacy of the correction, we performed classification of carriers of the genetic mutation leading to Huntington's disease (HD) versus healthy controls. Half of the HD carriers were free of typical HD symptoms and had an estimated 5 to 20years before onset of clinical symptoms, thus providing a model for preclinical diagnosis of a neurodegenerative disease. Structural magnetic resonance brain images were acquired at four sites with pairs of sites which had the identical scanner type, equipment, and acquisition parameters. For automatic classification, we used spatially normalized probabilistic maps of gray matter, then removed confounding effects by Gaussian process regression, and then performed classification with a support vector machine. Voxel-based morphometry of gray matter maps showed disease effects that were spatially wider spread than effects of scanner, but no significant interactions between scanner and disease were found. A model trained with data from a single scanner generalized well to data from a different scanner. When confounding diagnostics groups and scanner during training, e.g. by using controls from one scanner and gene carriers from another, classification accuracy dropped significantly in many cases. By regressing out confounds with Gaussian process regression, the performance levels were comparable to those obtained in scenarios without confound. We conclude that models trained on data acquired with a single scanner generalized well to data acquired with a different same-generation scanner even when the vendor differed. When confounding grouping and scanner during training is unavoidable to gather training data, regressing out inter-scanner and between-subject variability can reduce the loss in accuracy due to the confound.
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http://dx.doi.org/10.1016/j.neuroimage.2014.04.057DOI Listing
September 2014

The iRoCS Toolbox--3D analysis of the plant root apical meristem at cellular resolution.

Plant J 2014 Mar 12;77(5):806-14. Epub 2014 Feb 12.

Institute for Computer Science, Albert Ludwigs University Freiburg, Georges Köhler Allee, Gebäude 52, D-79110, Freiburg, Germany.

To achieve a detailed understanding of processes in biological systems, cellular features must be quantified in the three-dimensional (3D) context of cells and organs. We described use of the intrinsic root coordinate system (iRoCS) as a reference model for the root apical meristem of plants. iRoCS enables direct and quantitative comparison between the root tips of plant populations at single-cell resolution. The iRoCS Toolbox automatically fits standardized coordinates to raw 3D image data. It detects nuclei or segments cells, automatically fits the coordinate system, and groups the nuclei/cells into the root's tissue layers. The division status of each nucleus may also be determined. The only manual step required is to mark the quiescent centre. All intermediate outputs may be refined if necessary. The ability to learn the visual appearance of nuclei by example allows the iRoCS Toolbox to be easily adapted to various phenotypes. The iRoCS Toolbox is provided as an open-source software package, licensed under the GNU General Public License, to make it accessible to a broad community. To demonstrate the power of the technique, we measured subtle changes in cell division patterns caused by modified auxin flux within the Arabidopsis thaliana root apical meristem.
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http://dx.doi.org/10.1111/tpj.12429DOI Listing
March 2014

Variational attenuation correction in two-view confocal microscopy.

BMC Bioinformatics 2013 Dec 18;14:366. Epub 2013 Dec 18.

Department of Computer Science, Albert-Ludwigs-Universität, Georges-Köhler-Allee Geb, 52, 79110 Freiburg, Germany.

Background: Absorption and refraction induced signal attenuation can seriously hinder the extraction of quantitative information from confocal microscopic data. This signal attenuation can be estimated and corrected by algorithms that use physical image formation models. Especially in thick heterogeneous samples, current single view based models are unable to solve the underdetermined problem of estimating the attenuation-free intensities.

Results: We present a variational approach to estimate both, the real intensities and the spatially variant attenuation from two views of the same sample from opposite sides. Assuming noise-free measurements throughout the whole volume and pure absorption, this would in theory allow a perfect reconstruction without further assumptions. To cope with real world data, our approach respects photon noise, estimates apparent bleaching between the two recordings, and constrains the attenuation field to be smooth and sparse to avoid spurious attenuation estimates in regions lacking valid measurements.

Conclusions: We quantify the reconstruction quality on simulated data and compare it to the state-of-the art two-view approach and commonly used one-factor-per-slice approaches like the exponential decay model. Additionally we show its real-world applicability on model organisms from zoology (zebrafish) and botany (Arabidopsis). The results from these experiments show that the proposed approach improves the quantification of confocal microscopic data of thick specimen.
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http://dx.doi.org/10.1186/1471-2105-14-366DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3878336PMC
December 2013

Validation of fluorescence molecular tomography/micro-CT multimodal imaging in vivo in rats.

Mol Imaging Biol 2014 Jun;16(3):350-61

Institute for Macromolecular Chemistry, University of Freiburg, 79104, Freiburg, Germany.

Purpose: Rats are important preclinical models for studying breast cancer metastasis and bone pathologies. In these research areas, fluorescence molecular tomography (FMT) is commonly applied for quantitative three-dimensional (3D) imaging in mice. However, uncertainties due to strong depth dependency of FMT signal and spatial resolution require a validation study in rats.

Procedure: FMT performance in rats was assessed based on co-registered FMT/micro-computed tomography (micro-CT) reconstructed volumes obtained from optical phantoms and from models relevant for tumor imaging, bone remodeling and biodistribution analysis of nanoparticles.

Results: FMT reconstructions within 20-mm-thick optical phantoms were accurate (95 ± 11 % recovery), precise (CV ≤ 8 %) and linear (R(2) > 0.9788) over a range of 78-2,500 nM of the near infrared fluorescent agent VivoTag 750 (VT(750)). In vivo, implanted defined fluorescent targets yielded a recovery of 105 ± 5 % and successfully co-registered with micro-CT delineated structures. Additionally, using the bone-targeting imaging agent Osteosense 750, regions of neo bone formation identified by FMT could be mapped to the region of epiphyseal growth plates observed in micro-CT images. Finally, as a proof of concept, to monitor nanoparticulate drug pharmacokinetics in rat subjects the accumulation/clearance of VT(750)-albumin conjugate in/from the liver was followed at 11 different time points over a period of 2 weeks by FMT/micro-CT.

Conclusions: FMT imaging has been validated in optical phantoms as well as in 160 g rats, and sequential FMT/micro-CT imaging can be considered as a useful tool for preclinical research in rats.
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http://dx.doi.org/10.1007/s11307-013-0698-8DOI Listing
June 2014

Non-directional radial intercalation dominates deep cell behavior during zebrafish epiboly.

Biol Open 2013 Aug 3;2(8):845-54. Epub 2013 Jun 3.

Department of Computer Science, Albert-Ludwigs-University Freiburg , Georges-Koehler-Allee Geb 052, 79110 Freiburg , Germany ; BIOSS - Centre for Biological Signalling Studies, Albert-Ludwigs-University Freiburg , Schänzlestrasse 18, 79104 Freiburg , Germany.

Epiboly is the first coordinated cell movement in most vertebrates and marks the onset of gastrulation. During zebrafish epiboly, enveloping layer (EVL) and deep cells spread over the vegetal yolk mass with a concomitant thinning of the deep cell layer. A prevailing model suggests that deep cell radial intercalations directed towards the EVL would drive deep cell epiboly. To test this model, we have globally recorded 3D cell trajectories for zebrafish blastomeres between sphere and 50% epiboly stages, and developed an image analysis framework to determine intercalation events, intercalation directionality, and migration speed for cells at specific positions within the embryo. This framework uses Voronoi diagrams to compute cell-to-cell contact areas, defines a feature-based spatio-temporal model for intercalation events and fits an anatomical coordinate system to the recorded datasets. We further investigate whether epiboly defects in MZspg mutant embryos devoid of Pou5f1/Oct4 may be caused by changes in intercalation behavior. In wild-type and mutant embryos, intercalations orthogonal to the EVL occur with no directional bias towards or away from the EVL, suggesting that there are no directional cues that would direct intercalations towards the EVL. Further, we find that intercalation direction is independent of the previous intercalation history of individual deep cells, arguing against cues that would program specific intrinsic directed migration behaviors. Our data support a dynamic model in which deep cells during epiboly migrate into space opening between the EVL and the yolk syncytial layer. Genetic programs determining cell motility may control deep cell dynamic behavior and epiboly progress.
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http://dx.doi.org/10.1242/bio.20134614DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3744077PMC
August 2013

Automated processing of zebrafish imaging data: a survey.

Zebrafish 2013 Sep 12;10(3):401-21. Epub 2013 Jun 12.

Karlsruhe Institute of Technology, Karlsruhe, Germany.

Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.
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http://dx.doi.org/10.1089/zeb.2013.0886DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3760023PMC
September 2013

Semi-automatic determination of cell surface areas used in systems biology.

Front Biosci (Elite Ed) 2013 Jan 1;5:533-45. Epub 2013 Jan 1.

BIOSS Centre for Biological Signaling Studies, University of Freiburg, Germany.

Quantitative biology requires high precision measurement of cellular parameters such as surface areas or volumes. Here, we have developed an integrated approach in which the data from 3D confocal microscopy and 2D high-resolution transmission electron microscopy were combined. The volumes and diameters of the cells within one population were automatically measured from the confocal data sets. The perimeter of the cell slices was measured in the TEM images using a semi-automated segmentation into background, cytoplasm and nucleus. These data in conjunction with approaches from stereology allowed for an unbiased estimate of surface areas with high accuracy. We have determined the volumes and surface areas of the cells and nuclei of six different immune cell types. In mast cells for example, the resulting cell surface was 3.5 times larger than the theoretical surface assuming the cell was a sphere with the same volume. Thus, our accurate data can now serve as inputs in modeling approaches in systems immunology.
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http://dx.doi.org/10.2741/e635DOI Listing
January 2013

Vertebrate kidney tubules elongate using a planar cell polarity-dependent, rosette-based mechanism of convergent extension.

Nat Genet 2012 Dec 11;44(12):1382-7. Epub 2012 Nov 11.

Department of Medicine, Renal Division, University of Freiburg Medical Center, Freiburg, Germany.

Cystic kidney diseases are a global public health burden, affecting over 12 million people. Although much is known about the genetics of kidney development and disease, the cellular mechanisms driving normal kidney tubule elongation remain unclear. Here, we used in vivo imaging to show for the first time that mediolaterally oriented cell intercalation is fundamental to vertebrate kidney morphogenesis. Unexpectedly, we found that kidney tubule elongation is driven in large part by a myosin-dependent, multicellular rosette-based mechanism, previously only described in Drosophila melanogaster. In contrast to findings in Drosophila, however, non-canonical Wnt and planar cell polarity (PCP) signaling is required to control rosette topology and orientation during vertebrate kidney tubule elongation. These data resolve long-standing questions concerning the role of PCP signaling in the developing kidney and, moreover, establish rosette-based intercalation as a deeply conserved cellular engine for epithelial morphogenesis.
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http://dx.doi.org/10.1038/ng.2452DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4167614PMC
December 2012

Shroom3 is required downstream of FGF signalling to mediate proneuromast assembly in zebrafish.

Development 2012 Dec 7;139(24):4571-81. Epub 2012 Nov 7.

Centre for Biological Signalling Studies, University of Freiburg, Schänzlestrasse 18, D-79104 Freiburg, Germany.

During development, morphogenetic processes require a precise coordination of cell differentiation, cell shape changes and, often, cell migration. Yet, how pattern information is used to orchestrate these different processes is still unclear. During lateral line (LL) morphogenesis, a group of cells simultaneously migrate and assemble radially organized cell clusters, termed rosettes, that prefigure LL sensory organs. This process is controlled by Fibroblast growth factor (FGF) signalling, which induces cell fate changes, cell migration and cell shape changes. However, the exact molecular mechanisms induced by FGF activation that mediate these changes on a cellular level are not known. Here, we focus on the mechanisms by which FGFs control apical constriction and rosette assembly. We show that apical constriction in the LL primordium requires the activity of non-muscle myosin. We demonstrate further that shroom3, a well-known regulator of non-muscle myosin activity, is expressed in the LL primordium and that its expression requires FGF signalling. Using gain- and loss-of-function experiments, we demonstrate that Shroom3 is the main organizer of cell shape changes during rosette assembly, probably by coordinating Rho kinase recruitment and non-muscle myosin activation. In order to quantify morphogenesis in the LL primordium in an unbiased manner, we developed a unique trainable 'rosette detector'. We thus propose a model in which Shroom3 drives rosette assembly in the LL downstream of FGF in a Rho kinase- and non-muscle myosin-dependent manner. In conclusion, we uncovered the first mechanistic link between patterning and morphogenesis during LL sensory organ formation.
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http://dx.doi.org/10.1242/dev.083253DOI Listing
December 2012

Functional and structural MRI biomarkers to detect pre-clinical neurodegeneration.

Curr Alzheimer Res 2013 Feb;10(2):125-34

Department of Psychiatry and Psychotherapy, Section of Gerontopsychiatry and Neuropsychology, Freiburg Brain Imaging, University Medical Center Freiburg, Freiburg, Germany.

The availability of an accurate genetic test to identify Huntington's Disease (HD) in the pre-symptomatic stage makes HD an important model to develop biomarkers for other neurodegenerative diseases, such as pre-clinical Alzheimer's Disease. We reasoned that functional changes, measured by functional MRI (fMRI), would precede gray matter changes and that performing a task specifically affected by the disease would carry the clearest signature. Separate cohorts of HD gene mutations carriers and controls performed four different fMRI tasks, probing functions either primarly affected by the disease (i.e. motor control), higher cognitive functions (i.e. working memory and irritability), or basic sensory functions (i.e. auditory system). With the aim to compare fMRI and structural MRI biomarkers, all subjects underwent an additional high-resolution T1-weighted MRI. Best classification performance was achived from fMRI-based activations with motor sequence tapping and task-induced irritation. Classification performance based on gray matter probability maps was also significantly above chance and similar to that of fMRI. Both were sufficiently informative to separate gene mutation carriers that were on average 17 years before predicted disease onset from controls with up to 80% accuracy. Further analyses showed that classification accuracy was best in regions of interest with low within-group heterogeneity in relation to disease specific changes. Our study indicates that structural and some functional markers can accurately detect pre-clinical neurodegeneration. However, the lower variability and easier processing of the strucutral MRI data make latter the more useful tool for disease detection in a clinical setting.
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http://dx.doi.org/10.2174/1567205011310020002DOI Listing
February 2013
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