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  • Shcherbakova, Daria M.; Cammer, Natasha Cox; Huisman, Tsipora M.; Verkhusha, Vladislav V.; Hodgson, Louis (2018)
    Direct visualization and light control of several cellular processes is a challenge, owing to the spectral overlap of available genetically encoded probes. Here we report the most red-shifted monomeric near-infrared (NIR) fluorescent protein, miRFP720, and the fully NIR Forster resonance energy transfer (FRET) pair miRFP670-miRFP720, which together enabled design of biosensors compatible with CFP-YFP imaging and blue-green optogenetic tools. We developed a NIR biosensor for Rac1 GTPase and demonstrated its use in multiplexed imaging and light control of Rho GTPase signaling pathways. Specifically, we combined the Rac1 biosensor with CFP-YFP FRET biosensors for RhoA and for Rac1-GDI binding, and concurrently used the LOV-TRAP tool for upstream Rac1 activation. We directly observed and quantified antagonism between RhoA and Rac1 dependent on the RhoA-downstream effector ROCK; showed that Rac1 activity and GDI binding closely depend on the spatiotemporal coordination between these two molecules; and simultaneously observed Rac1 activity during optogenetic manipulation of Rac1.
  • Peltola, Olli; Vesala, Timo; Gao, Yao; Raty, Olle; Alekseychik, Pavel; Aurela, Mika; Chojnicki, Bogdan; Desai, Ankur R.; Dolman, Albertus J.; Euskirchen, Eugenie S.; Friborg, Thomas; Goeckede, Mathias; Helbig, Manuel; Humphreys, Elyn; Jackson, Robert B.; Jocher, Georg; Joos, Fortunat; Klatt, Janina; Knox, Sara H.; Kowalska, Natalia; Kutzbach, Lars; Lienert, Sebastian; Lohila, Annalea; Mammarella, Ivan; Nadeau, Daniel F.; Nilsson, Mats B.; Oechel, Walter C.; Peichl, Matthias; Pypker, Thomas; Quinton, William; Rinne, Janne; Sachs, Torsten; Samson, Mateusz; Schmid, Hans Peter; Sonnentag, Oliver; Wille, Christian; Zona, Donatella; Aalto, Tuula (2019)
    Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process ("bottom-up") or inversion ("top-down") models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45 degrees N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash-Sutcliffe model efficiency = 0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3-41.2, 95% confidence interval calculated from a RF model ensemble), 31 (21.4-39.9) or 38 (25.9-49.5) Tg(CH4) yr(-1). To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at
  • Shcherbakova, Daria M.; Stepanenko, Olesya V.; Turoverov, Konstantin K.; Verkhusha, Vladislav V. (2018)
    Since mammalian tissue is relatively transparent to near-infrared (NIR) light, NIR fluorescentproteins(FPs) engineeredfrombacterialphytochromeshave become widely used probes for non-invasive in vivo imaging. Recently, these genetically encoded NIR probes have been substantially improved, enabling imaging experiments that were not possible previously. Here, we discuss the use of monomeric NIR FPs and NIR biosensors for multiplexed imaging with common visible GFP-based probes and blue light-activatable optogenetic tools. These NIR probes are suitable for visualization of functional activities from molecular to organismal levels. In combination with advanced imaging techniques, such as two-photon microscopy with adaptive optics, photoacoustic tomography and its recent modification reversibly switchable photoacoustic computed tomography, NIR probes allow subcellular resolution at millimeter depths.
  • Karasev, M. M.; Stepanenko, O. V.; Rumyantsev, K. A.; Turoverov, K. K.; Verkhusha, V. V. (2019)
    High transparency, low light-scattering, and low autofluorescence of mammalian tissues in the near-infrared (NIR) spectral range (650-900 nm) open a possibility for in vivo imaging of biological processes at the micro-and macroscales to address basic and applied problems in biology and biomedicine. Recently, probes that absorb and fluoresce in the NIR optical range have been engineered using bacterial phytochromes-natural NIR light-absorbing photoreceptors that regulate metabolism in bacteria. Since the chromophore in all these proteins is biliverdin, a natural product of heme catabolism in mammalian cells, they can be used as genetically encoded fluorescent probes, similarly to GFP-like fluorescent proteins. In this review, we discuss photophysical and biochemical properties of NIR fluorescent proteins, reporters, and biosensors and analyze their characteristics required for expression of these molecules in mammalian cells. Structural features and molecular engineering of NIR fluorescent probes are discussed. Applications of NIR fluorescent proteins and biosensors for studies of molecular processes in cells, as well as for tissue and organ visualization in whole-body imaging in vivo, are described. We specifically focus on the use of NIR fluorescent probes in advanced imaging technologies that combine fluorescence and bioluminescence methods with photoacoustic tomography.