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1.  Cell Tracking Accuracy Measurement Based on Comparison of Acyclic Oriented Graphs 
PLoS ONE  2015;10(12):e0144959.
Tracking motile cells in time-lapse series is challenging and is required in many biomedical applications. Cell tracks can be mathematically represented as acyclic oriented graphs. Their vertices describe the spatio-temporal locations of individual cells, whereas the edges represent temporal relationships between them. Such a representation maintains the knowledge of all important cellular events within a captured field of view, such as migration, division, death, and transit through the field of view. The increasing number of cell tracking algorithms calls for comparison of their performance. However, the lack of a standardized cell tracking accuracy measure makes the comparison impracticable. This paper defines and evaluates an accuracy measure for objective and systematic benchmarking of cell tracking algorithms. The measure assumes the existence of a ground-truth reference, and assesses how difficult it is to transform a computed graph into the reference one. The difficulty is measured as a weighted sum of the lowest number of graph operations, such as split, delete, and add a vertex and delete, add, and alter the semantics of an edge, needed to make the graphs identical. The measure behavior is extensively analyzed based on the tracking results provided by the participants of the first Cell Tracking Challenge hosted by the 2013 IEEE International Symposium on Biomedical Imaging. We demonstrate the robustness and stability of the measure against small changes in the choice of weights for diverse cell tracking algorithms and fluorescence microscopy datasets. As the measure penalizes all possible errors in the tracking results and is easy to compute, it may especially help developers and analysts to tune their algorithms according to their needs.
doi:10.1371/journal.pone.0144959
PMCID: PMC4686175  PMID: 26683608
2.  The SUMOylation Pathway Restricts Gene Transduction by Adeno-Associated Viruses 
PLoS Pathogens  2015;11(12):e1005281.
Adeno-associated viruses are members of the genus dependoviruses of the parvoviridae family. AAV vectors are considered promising vectors for gene therapy and genetic vaccination as they can be easily produced, are highly stable and non-pathogenic. Nevertheless, transduction of cells in vitro and in vivo by AAV in the absence of a helper virus is comparatively inefficient requiring high multiplicity of infection. Several bottlenecks for AAV transduction have previously been described, including release from endosomes, nuclear transport and conversion of the single stranded DNA into a double stranded molecule. We hypothesized that the bottlenecks in AAV transduction are, in part, due to the presence of host cell restriction factors acting directly or indirectly on the AAV-mediated gene transduction. In order to identify such factors we performed a whole genome siRNA screen which identified a number of putative genes interfering with AAV gene transduction. A number of factors, yielding the highest scores, were identified as members of the SUMOylation pathway. We identified Ubc9, the E2 conjugating enzyme as well as Sae1 and Sae2, enzymes responsible for activating E1, as factors involved in restricting AAV. The restriction effect, mediated by these factors, was validated and reproduced independently. Our data indicate that SUMOylation targets entry of AAV capsids and not downstream processes of uncoating, including DNA single strand conversion or DNA damage signaling. We suggest that transiently targeting SUMOylation will enhance application of AAV in vitro and in vivo.
Author Summary
SUMOylation is a post-translational modification in which a small protein (SUMO) is covalently attached to target proteins. Three key enzymes are controlling this modification: The E1 activating complex composed of the heterodimer Sae1/Sae2, the E2 conjugation enzyme Ubc9 and one of many E3 enzymes which specifically recognize the target protein. SUMOylation regulates many processes such as protein stability, intracellular localization and protein-protein interactions. In our study we identified SUMOylation to be regulating transduction of cells by the human parvovirus adeno-associated virus (AAV). Targeting the E1 or E2 complex by RNA interference led to increased AAV transduction. We also identified putative E3 enzymes involved in this mechanism. Our data indicates that this regulation is mediated by the AAV capsid and it affects different AAV serotypes. Targeting SUMOylation might be a strategy to enhance AAV gene transduction.
doi:10.1371/journal.ppat.1005281
PMCID: PMC4666624  PMID: 26625259
3.  A benchmark for comparison of cell tracking algorithms 
Bioinformatics  2014;30(11):1609-1617.
Motivation: Automatic tracking of cells in multidimensional time-lapse fluorescence microscopy is an important task in many biomedical applications. A novel framework for objective evaluation of cell tracking algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2013 Cell Tracking Challenge. In this article, we present the logistics, datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark.
Results: The main contributions of the challenge include the creation of a comprehensive video dataset repository and the definition of objective measures for comparison and ranking of the algorithms. With this benchmark, six algorithms covering a variety of segmentation and tracking paradigms have been compared and ranked based on their performance on both synthetic and real datasets. Given the diversity of the datasets, we do not declare a single winner of the challenge. Instead, we present and discuss the results for each individual dataset separately.
Availability and implementation: The challenge Web site (http://www.codesolorzano.com/celltrackingchallenge) provides access to the training and competition datasets, along with the ground truth of the training videos. It also provides access to Windows and Linux executable files of the evaluation software and most of the algorithms that competed in the challenge.
Contact: codesolorzano@unav.es
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btu080
PMCID: PMC4029039  PMID: 24526711
4.  Live cell assays to identify regulators of ER to Golgi trafficking 
Traffic (Copenhagen, Denmark)  2012;13(3):416-432.
We applied fluorescence microscopy based quantitative assays to living cells to identify regulators of ER to Golgi trafficking and/or Golgi complex maintenance. We first validated an automated procedure to identify factors, which influence Golgi to ER re-localization of GalT-CFP after brefeldin A (BFA) addition and/or wash-out. We then tested 14 proteins that localize to the ER and/or Golgi complex when over-expressed for a role in ER to Golgi trafficking. Nine of them interfered with the rate of BFA induced redistribution of GalT-CFP from the Golgi complex to the ER, 6 of them interfered with GalT-CFP redistribution from the ER to a juxtanuclear region (i.e., Golgi complex) after BFA wash-out, and 6 of them were positive effectors in both assays. Notably, our live cell approach captures regulator function in ER to Golgi trafficking, that were missed in previous fixed cell assays; as well as assigns putative roles for other less characterized proteins. Moreover, we show that our assays can be extended to RNAi and chemical screens.
doi:10.1111/j.1600-0854.2011.01318.x
PMCID: PMC3711101  PMID: 22132776
Brefeldin A (BFA); GalT; ER to Golgi trafficking; YIPF; GOT1B; USE1; SACM1L
5.  miR-17-5p Regulates Endocytic Trafficking through Targeting TBC1D2/Armus 
PLoS ONE  2012;7(12):e52555.
miRNA cluster miR-17-92 is known as oncomir-1 due to its potent oncogenic function. miR-17-92 is a polycistronic cluster that encodes 6 miRNAs, and can both facilitate and inhibit cell proliferation. Known targets of miRNAs encoded by this cluster are largely regulators of cell cycle progression and apoptosis. Here, we show that miRNAs encoded by this cluster and sharing the seed sequence of miR-17 exert their influence on one of the most essential cellular processes – endocytic trafficking. By mRNA expression analysis we identified that regulation of endocytic trafficking by miR-17 can potentially be achieved by targeting of a number of trafficking regulators. We have thoroughly validated TBC1D2/Armus, a GAP of Rab7 GTPase, as a novel target of miR-17. Our study reveals regulation of endocytic trafficking as a novel function of miR-17, which might act cooperatively with other functions of miR-17 and related miRNAs in health and disease.
doi:10.1371/journal.pone.0052555
PMCID: PMC3527550  PMID: 23285084
6.  Recruitment and activation of a lipid kinase by hepatitis C virus NS5A is essential for integrity of the membranous replication compartment 
Cell host & microbe  2011;9(1):32-45.
SUMMARY
Hepatitis C virus (HCV) is a major causative agent of chronic liver disease in humans. To gain insight into host factor requirements for HCV replication we performed a siRNA screen of the human kinome and identified 13 different kinases, including phosphatidylinositol-4 kinase III alpha (PI4KIIIα) as required for HCV replication. Consistent with elevated levels of the PI4KIIIα product phosphatidylinositol-4-phosphate (PI4P) detected in HCV infected cultured hepatocytes and liver tissue from chronic hepatitis C patients, the enzymatic activity of PI4KIIIα was critical for HCV replication. Viral nonstructural protein 5A (NS5A) was found to interact with PI4KIIIα and stimulate its kinase activity. The absence of PI4KIIIα activity induced a dramatic change in the ultrastructural morphology of the membranous HCV replication complex. Our analysis suggests that the direct activation of a lipid kinase by HCV NS5A contributes critically to the integrity of the membranous viral replication complex.
doi:10.1016/j.chom.2010.12.002
PMCID: PMC3433060  PMID: 21238945
7.  Normalizing for individual cell population context in the analysis of high-content cellular screens 
BMC Bioinformatics  2011;12:485.
Background
High-content, high-throughput RNA interference (RNAi) offers unprecedented possibilities to elucidate gene function and involvement in biological processes. Microscopy based screening allows phenotypic observations at the level of individual cells. It was recently shown that a cell's population context significantly influences results. However, standard analysis methods for cellular screens do not currently take individual cell data into account unless this is important for the phenotype of interest, i.e. when studying cell morphology.
Results
We present a method that normalizes and statistically scores microscopy based RNAi screens, exploiting individual cell information of hundreds of cells per knockdown. Each cell's individual population context is employed in normalization. We present results on two infection screens for hepatitis C and dengue virus, both showing considerable effects on observed phenotypes due to population context. In addition, we show on a non-virus screen that these effects can be found also in RNAi data in the absence of any virus. Using our approach to normalize against these effects we achieve improved performance in comparison to an analysis without this normalization and hit scoring strategy. Furthermore, our approach results in the identification of considerably more significantly enriched pathways in hepatitis C virus replication than using a standard analysis approach.
Conclusions
Using a cell-based analysis and normalization for population context, we achieve improved sensitivity and specificity not only on a individual protein level, but especially also on a pathway level. This leads to the identification of new host dependency factors of the hepatitis C and dengue viruses and higher reproducibility of results.
doi:10.1186/1471-2105-12-485
PMCID: PMC3259109  PMID: 22185194
8.  Detecting host factors involved in virus infection by observing the clustering of infected cells in siRNA screening images 
Bioinformatics  2010;26(18):i653-i658.
Motivation: Detecting human proteins that are involved in virus entry and replication is facilitated by modern high-throughput RNAi screening technology. However, hit lists from different laboratories have shown only little consistency. This may be caused by not only experimental discrepancies, but also not fully explored possibilities of the data analysis. We wanted to improve reliability of such screens by combining a population analysis of infected cells with an established dye intensity readout.
Results: Viral infection is mainly spread by cell–cell contacts and clustering of infected cells can be observed during spreading of the infection in situ and in vivo. We employed this clustering feature to define knockdowns which harm viral infection efficiency of human Hepatitis C Virus. Images of knocked down cells for 719 human kinase genes were analyzed with an established point pattern analysis method (Ripley's K-function) to detect knockdowns in which virally infected cells did not show any clustering and therefore were hindered to spread their infection to their neighboring cells. The results were compared with a statistical analysis using a common intensity readout of the GFP-expressing viruses and a luciferase-based secondary screen yielding five promising host factors which may suit as potential targets for drug therapy.
Conclusion: We report of an alternative method for high-throughput imaging methods to detect host factors being relevant for the infection efficiency of viruses. The method is generic and has the potential to be used for a large variety of different viruses and treatments being screened by imaging techniques.
Contact: r.eils@dkfz.de; r.koenig@dkfz.de
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btq398
PMCID: PMC2935410  PMID: 20823335

Results 1-8 (8)