PDB3: USE OF BOOTSTRAP IN A COST-OF-ILLNESS STUDY TO DERIVE ACCURACY OF ESTIMATES

Farrando, Jordi;Febles, Maria Dolors ;Henrich, Jordi;Tarrasó, Olga ;Fuertes, J.C.;Pérez, S

Nuclear pores as versatile reference standards for quantitative superresolution microscopy

Quantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions. Here, we exploit the stereotypic arrangement of proteins in the nuclear pore complex as in situ reference structures to characterize the performance of a variety of microscopy modalities. We created four genome edited cell lines in which we endogenously labeled the nucleoporin Nup96 with mEGFP, SNAP-tag, HaloTag or the photoconvertible fluorescent protein mMaple. We demonstrate their use (1) as three-dimensional resolution standards for calibration and quality control, (2) to quantify absolute labeling efficiencies and (3) as precise reference standards for molecular counting. These cell lines will enable the broader community to assess the quality of their microscopes and labels, and to perform quantitative, absolute measurements

Human cytomegalovirus immediate-early 1 protein rewires upstream STAT3 to downstream STAT1 signaling switching an IL6-type to an IFNγ-like response

MN and CP were supported by the Wellcome Trust (www.wellcome.ac.uk) Institutional Strategic Support Fund and CP was supported by the Deutsche Forschungsgemeinschaft (PA 815/2-1; www.dfg.de).The human cytomegalovirus (hCMV) major immediate-early 1 protein (IE1) is best known for activating transcription to facilitate viral replication. Here we present transcriptome data indicating that IE1 is as significant a repressor as it is an activator of host gene expression. Human cells induced to express IE1 exhibit global repression of IL6- and oncostatin M-responsive STAT3 target genes. This repression is followed by STAT1 phosphorylation and activation of STAT1 target genes normally induced by IFNγ. The observed repression and subsequent activation are both mediated through the same region (amino acids 410 to 445) in the C-terminal domain of IE1, and this region serves as a binding site for STAT3. Depletion of STAT3 phenocopies the STAT1-dependent IFNγ-like response to IE1. In contrast, depletion of the IL6 receptor (IL6ST) or the STAT kinase JAK1 prevents this response. Accordingly, treatment with IL6 leads to prolonged STAT1 instead of STAT3 activation in wild-type IE1 expressing cells, but not in cells expressing a mutant protein (IE1dl410-420) deficient for STAT3 binding. A very similar STAT1-directed response to IL6 is also present in cells infected with a wild-type or revertant hCMV, but not an IE1dl410-420 mutant virus, and this response results in restricted viral replication. We conclude that IE1 is sufficient and necessary to rewire upstream IL6-type to downstream IFNγ-like signaling, two pathways linked to opposing actions, resulting in repressed STAT3- and activated STAT1-responsive genes. These findings relate transcriptional repressor and activator functions of IE1 and suggest unexpected outcomes relevant to viral pathogenesis in response to cytokines or growth factors that signal through the IL6ST-JAK1-STAT3 axis in hCMV-infected cells. Our results also reveal that IE1, a protein considered to be a key activator of the hCMV productive cycle, has an unanticipated role in tempering viral replication.Publisher PDFPeer reviewe

A Range of Earth Observation Techniques for Assessing Plant Diversity

AbstractVegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation diversity using RS