TICAL - a web-tool for multivariate image clustering and data topology preserving visualization

In life science research bioimaging is often used to study two kinds of features in a sample simultaneously: morphology and co-location of molecular components. While bioimaging technology is rapidly proposing and improving new multidimensional imaging platforms, bioimage informatics has to keep pace in order to develop algorithmic approaches to support biology experts in the complex task of data analysis. One particular problem is the availability and applicability of sophisticated image analysis algorithms via the web so different users can apply the same algorithms to their data (sometimes even to the same data to get the same results) and independently from her/his whereabouts and from the technical features of her/his computer. In this paper we describe TICAL, a visual data mining approach to multivariate microscopy analysis which can be applied fully through the web.We describe the algorithmic approach, the software concept and present results obtained for different example images

A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages

Loyek C, Kölling J, Langenkämper D, Niehaus K, Nattkemper TW. A Web2.0 Strategy for the Collaborative Analysis of Complex Bioimages. In: Gama J, Bradley E, Hollmén J, eds. Advances in Intelligent Data Analysis X: 10th International Symposium, IDA 2011, Porto, Portugal, October 29-31, 2011. Proceedings. Lecture Notes in Computer Science. Vol 7014. Berlin, Heidelberg: Springer; 2011: 258-269

Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging

Gorzolka K, Kölling J, Nattkemper TW, Niehaus K. Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging. PLOS ONE. 2016;11(3): e0150208.MALDI mass spectrometry imaging was performed to localize metabolites during the first seven days of the barley germination. Up to 100 mass signals were detected of which 85 signals were identified as 48 different metabolites with highly tissue-specific localizations. Oligosaccharides were observed in the endosperm and in parts of the developed embryo. Lipids in the endosperm co-localized in dependency on their fatty acid compositions with changes in the distributions of diacyl phosphatidylcholines during germination. 26 potentially antifungal hordatines were detected in the embryo with tissue-specific localizations of their glycosylated, hydroxylated, and O-methylated derivates. In order to reveal spatio-temporal patterns in local metabolite compositions, multiple MSI data sets from a time series were analyzed in one batch. This requires a new preprocessing strategy to achieve comparability between data sets as well as a new strategy for unsupervised clustering. The resulting spatial segmentation for each time point sample is visualized in an interactive cluster map and enables simultaneous interactive exploration of all time points. Using this new analysis approach and visualization tool germination-dependent developments of metabolite patterns with single MS position accuracy were discovered. This is the first study that presents metabolite profiling of a cereals’ germination process over time by MALDI MSI with the identification of a large number of peaks of agronomically and industrially important compounds such as oligosaccharides, lipids and antifungal agents. Their detailed localization as well as the MS cluster analyses for on-tissue metabolite profile mapping revealed important information for the understanding of the germination process, which is of high scientific interest

Spatio-temporal analysis of metabolite profiles during barley germination

Kölling J, Gorzolka K, Niehaus K, Nattkemper TW. Spatio-temporal analysis of metabolite profiles during barley germination. Presented at the German Conference on Bioinformatics (GCB), Bielefeld, Germany

Detection and visualization of communities in mass spectrometry imaging data.

Wüllems K, Kölling J, Bednarz H, Niehaus K, Hans VH, Nattkemper TW. Detection and visualization of communities in mass spectrometry imaging data. BMC Bioinformatics. 2019;20(1): 303.BACKGROUND: The spatial distribution and colocalization of functionally related metabolites is analysed in order to investigate the spatial (and functional) aspects of molecular networks. We propose to consider community detection for the analysis of m/z-images to group molecules with correlative spatial distribution into communities so they hint at functional networks or pathway activity. To detect communities, we investigate a spectral approach by optimizing the modularity measure. We present an analysis pipeline and an online interactive visualization tool to facilitate explorative analysis of the results. The approach is illustrated with synthetical benchmark data and two real world data sets (barley seed and glioblastoma section).; RESULTS: For the barley sample data set, our approach is able to reproduce the findings of a previous work that identified groups of molecules with distributions that correlate with anatomical structures of the barley seed. The analysis of glioblastoma section data revealed that some molecular compositions are locally focused, indicating the existence of a meaningful separation in at least two areas. This result is in line with the prior histological knowledge. In addition to confirming prior findings, the resulting graph structures revealed new subcommunities of m/z-images (i.e. metabolites) with more detailed distribution patterns. Another result of our work is the development of an interactive webtool called GRINE (Analysis of GRaph mapped Image Data NEtworks).; CONCLUSIONS: The proposed method was successfully applied to identify molecular communities of laterally co-localized molecules. For both application examples, the detected communities showed inherent substructures that could easily be investigated with the proposed visualization tool. This shows the potential of this approach as a complementary addition to pixel clustering methods

WHIDE—a web tool for visual data mining colocation patterns in multivariate bioimages

Motivation: Bioimaging techniques rapidly develop toward higher resolution and dimension. The increase in dimension is achieved by different techniques such as multitag fluorescence imaging, Matrix Assisted Laser Desorption / Ionization (MALDI) imaging or Raman imaging, which record for each pixel an N-dimensional intensity array, representing local abundances of molecules, residues or interaction patterns. The analysis of such multivariate bioimages (MBIs) calls for new approaches to support users in the analysis of both feature domains: space (i.e. sample morphology) and molecular colocation or interaction. In this article, we present our approach WHIDE (Web-based Hyperbolic Image Data Explorer) that combines principles from computational learning, dimension reduction and visualization in a free web application

Disruption of the sialic acid/Siglec-9 axis improves antibody-mediated neutrophil cytotoxicity towards tumor cells

Upregulation of surface expressed sialoglycans on tumor cells is one of the mechanisms which promote tumor growth and progression. Specifically, the interactions of sialic acids with sialic acid-binding immunoglobulin-like lectins (Siglecs) on lymphoid or myeloid cells transmit inhibitory signals and lead to suppression of anti-tumor responses. Here, we show that neutrophils express among others Siglec-9, and that EGFR and HER2 positive breast tumor cells express ligands for Siglec-9. Treatment of tumor cells with neuraminidases or a sialyl transferase inhibitor significantly reduced binding of a soluble recombinant Siglec-9-Fc fusion protein, while EGFR and HER2 expression remained unchanged. Importantly, the cytotoxic activity of neutrophils driven by therapeutic EGFR or HER2 antibodies in vitro was increased by blocking the sialic acid/Siglec interaction, either by reducing tumor cell sialylation or by a Siglec-9 blocking antibody containing an effector silenced Fc domain. In vivo a short-term xenograft mouse model confirmed the improved therapeutic efficacy of EGFR antibodies against sialic acid depleted, by a sialyltransferase inhibitor, tumor cells compared to untreated cells. Our studies demonstrate that sialic acid/Siglec interactions between tumor cells and myeloid cells can impair antibody dependent tumor cell killing, and that Siglec-9 on polymorphonuclear cells (PMN) is critically involved. Considering that PMN are often a highly abundant cell population in the tumor microenvironment, Siglec-9 constitutes a promising target for myeloid checkpoint blockade to improve antibody-based tumor immunotherapy

Unforeseen plant phenotypic diversity in a dry and grazed world

23 páginas..- 4 figuras y 7 figuras.- 50 referencias y 90 referenciasEarth harbours an extraordinary plant phenotypic diversity1 that is at risk from ongoing global changes2,3. However, it remains unknown how increasing aridity and livestock grazing pressure—two major drivers of global change4,5,6—shape the trait covariation that underlies plant phenotypic diversity1,7. Here we assessed how covariation among 20 chemical and morphological traits responds to aridity and grazing pressure within global drylands. Our analysis involved 133,769 trait measurements spanning 1,347 observations of 301 perennial plant species surveyed across 326 plots from 6 continents. Crossing an aridity threshold of approximately 0.7 (close to the transition between semi-arid and arid zones) led to an unexpected 88% increase in trait diversity. This threshold appeared in the presence of grazers, and moved toward lower aridity levels with increasing grazing pressure. Moreover, 57% of observed trait diversity occurred only in the most arid and grazed drylands, highlighting the phenotypic uniqueness of these extreme environments. Our work indicates that drylands act as a global reservoir of plant phenotypic diversity and challenge the pervasive view that harsh environmental conditions reduce plant trait diversity8,9,10. They also highlight that many alternative strategies may enable plants to cope with increases in environmental stress induced by climate change and land-use intensification.This research was funded by the European Research Council (ERC Grant agreement 647038 1004 [BIODESERT]) and Generalitat Valenciana (CIDEGENT/2018/041). N.G. was supported by CAP 20–25 (16-IDEX-0001) and the AgreenSkills+ fellowship programme which has received funding from the European Union’s Seventh Framework Programme under grant agreement FP7-609398 (AgreenSkills+ contract). F.T.M. acknowledges support from the King Abdullah University of Science and Technology (KAUST), the KAUST Climate and Livability Initiative, the University of Alicante (UADIF22-74 and VIGROB22-350), the Spanish Ministry of Science and Innovation (PID2020-116578RB-I00), and the Synthesis Center (sDiv) of the German Centre for Integrative Biodiversity Research Halle–Jena–Leipzig (iDiv). Y.L.B.-P. was supported by a Marie Sklodowska-Curie Actions Individual Fellowship (MSCA-1018 IF) within the European Program Horizon 2020 (DRYFUN Project 656035). H.S. is supported by a María Zambrano fellowship funded by the Ministry of Universities and European Union-Next Generation plan. L.W. acknowledges support from the US National Science Foundation (EAR 1554894). G.M.W. acknowledges support from the Australian Research Council (DP210102593) and TERN. M.B is supported by a Ramón y Cajal grant from Spanish Ministry of Science (RYC2021-031797-I). L.v.d.B. and K.T. were supported by the German Research Foundation (DFG) Priority Program SPP-1803 (TI388/14-1). A.F. acknowledges the financial support from ANID PIA/BASAL FB210006 and Millenium Science Initiative Program NCN2021-050. A.J. was supported by the Bavarian Research Alliance for travel and field work (BayIntAn UBT 2017 61). A.L. and L.K. acknowledge support from the German Research Foundation, DFG (grant CRC TRR228) and German Federal Government for Science and Education, BMBF (grants 01LL1802C and 01LC1821A). B.B. and S.U. were supported by the Taylor Family-Asia Foundation Endowed Chair in Ecology and Conservation Biology. P.J.R. and A.J.M. acknowledge support from Fondo Europeo de Desarrollo Regional through the FEDER Andalucía operative programme, FEDER-UJA 1261180 project. E.M.-J. and C.P. acknowledge support from the Spanish Ministry of Science and Innovation (PID2020-116578RB-I00). D.J.E. was supported by the Hermon Slade Foundation. J.D. and A.Rodríguez acknowledge support from the FCT (2020.03670.CEECIND and SFRH/BDP/108913/2015, respectively), as well as from the MCTES, FSE, UE and the CFE (UIDB/04004/2021) research unit financed by FCT/MCTES through national funds (PIDDAC). S.C.R. acknowledges support from the US Department of Energy (DE-SC-0008168), US Department of Defense (RC18-1322), and the US Geological Survey Ecosystems Mission Area. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US government. E.H.-S. acknowledges support from Mexican National Science and Technology Council (CONACYT PN 5036 and 319059). A.N. and C. Branquinho. acknowledge the support from FCT—Fundação para a Ciência e a Tecnologia (CEECIND/02453/2018/CP1534/CT0001, PTDC/ASP-SIL/7743/ 2020, UIDB/00329/2020), from AdaptForGrazing project (PRR-C05-i03-I-000035) and from LTsER Montado platform (LTER_EU_PT_001). Field work of G.P. and J.M.Z. was supported by UNRN (PI 40-C-873).Peer reviewe

Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands

14 páginas.- 4 figuras.- 67 referencias.- The online version contains supplementary material available at https://doi.org/10.1038/s41477-024-01670-7Perennial plants create productive and biodiverse hotspots, known as fertile islands, beneath their canopies. These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure and herbivore type, climate and plant functional traits on 24 soil physical and chemical attributes that represent proxies of key ecosystem services related to decomposition, soil fertility, and soil and water conservation. To do this, we conducted a standardized global survey of 288 plots at 88 sites in 25 countries worldwide. We show that aridity and plant traits are the major factors associated with the magnitude of plant effects on fertile islands in grazed drylands worldwide. Grazing pressure had little influence on the capacity of plants to support fertile islands. Taller and wider shrubs and grasses supported stronger island effects. Stable and functional soils tended to be linked to species-rich sites with taller plants. Together, our findings dispel the notion that grazing pressure or herbivore type are linked to the formation or intensification of fertile islands in drylands. Rather, our study suggests that changes in aridity, and processes that alter island identity and therefore plant traits, will have marked effects on how perennial plants support and maintain the functioning of drylands in a more arid and grazed world.This research was supported by the European Research Council (ERC grant 647038 (BIODESERT) awarded to F.T.M.) and Generalitat Valenciana (CIDEGENT/2018/041). D.J.E. was supported by the Hermon Slade Foundation (HSF21040). J. Ding was supported by the National Natural Science Foundation of China Project (41991232) and the Fundamental Research Funds for the Central Universities of China. M.D.-B. acknowledges support from TED2021-130908B-C41/AEI/10.13039/501100011033/Unión Europea Next Generation EU/PRTR and the Spanish Ministry of Science and Innovation for the I + D + i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. O.S. was supported by US National Science Foundation (Grants DEB 1754106, 20-25166), and Y.L.B.-P. by a Marie Sklodowska-Curie Actions Individual Fellowship (MSCA-1018 IF) within the European Program Horizon 2020 (DRYFUN Project 656035). K.G. and N.B. acknowledge support from the German Federal Ministry of Education and Research (BMBF) SPACES projects OPTIMASS (FKZ: 01LL1302A) and ORYCS (FKZ: FKZ01LL1804A). B.B. was supported by the Taylor Family-Asia Foundation Endowed Chair in Ecology and Conservation Biology, and M. Bowker by funding from the School of Forestry, Northern Arizona University. C.B. acknowledges funding from the National Natural Science Foundation of China (41971131). D.B. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096), and A. Fajardo support from ANID PIA/BASAL FB 210006 and the Millennium Science Initiative Program NCN2021-050. M.F. and H.E. received funding from Ferdowsi University of Mashhad (grant 39843). A.N. and M.K. acknowledge support from FCT (CEECIND/02453/2018/CP1534/CT0001, SFRH/BD/130274/2017, PTDC/ASP-SIL/7743/2020, UIDB/00329/2020), EEA (10/CALL#5), AdaptForGrazing (PRR-C05-i03-I-000035) and LTsER Montado platform (LTER_EU_PT_001) grants. O.V. acknowledges support from the Hungarian Research, Development and Innovation Office (NKFI KKP 144096). L.W. was supported by the US National Science Foundation (EAR 1554894). Y.Z. and X.Z. were supported by the National Natural Science Foundation of China (U2003214). H.S. is supported by a María Zambrano fellowship funded by the Ministry of Universities and European Union-Next Generation plan. The use of any trade, firm or product names does not imply endorsement by any agency, institution or government. Finally, we thank the many people who assisted with field work and the landowners, corporations and national bodies that allowed us access to their land.Peer reviewe

Towards Protein Network Analysis using TIS Imaging and Exploratory Data Analysis

Langenkämper D, Kölling J, Khan M, Rajpoot N, Nattkemper TW. Towards Protein Network Analysis using TIS Imaging and Exploratory Data Analysis. Presented at the Workshop on Computational Systems Biology (WCSB), Zürich, Switzerland.Identification, analysis and visualization of functional molecular networks are key objectives in systems biology and the logical extension of existing molecular profiling techniques. Here we used TIS (toponome imaging system) imaging to visualize co-location of proteins in tissue samples, thereby integrating two distinct information domains, morphology and molecular interaction. Using a library of 13 selected dye-conjugated antibodies, TIS recorded a stack of 13 fluorescence images, each showing the same visual field, with high fluorescence values indicating the presence of the corresponding bio-molecule or protein. We show first results obtained using machine learning approaches that allow the identification and spatial analysis of co-location patterns without manual thresholding. The authors believe that TIS imaging in combination with advanced visual data mining methods can contribute substantially to addressing several outstanding issues in systems biology where molecular co-location is involved