Transcriptional mechanisms underlying sensitization of peripheral sensory neurons by Granulocyte-/Granulocyte-macrophage colony stimulating factors

Background: Cancer-associated pain is a major cause of poor quality of life in cancer patients and is frequently resistant to conventional therapy. Recent studies indicate that some hematopoietic growth factors, namely granulocyte macrophage colony stimulating factor (GMCSF) and granulocyte colony stimulating factor (GCSF), are abundantly released in the tumor microenvironment and play a key role in regulating tumor-nerve interactions and tumor-associated pain by activating receptors on dorsal root ganglion (DRG) neurons. Moreover, these hematopoietic factors have been highly implicated in postsurgical pain, inflammatory pain and osteoarthritic pain. However, the molecular mechanisms via which G-/GMCSF bring about nociceptive sensitization and elicit pain are not known. Results: In order to elucidate G-/GMCSF mediated transcriptional changes in the sensory neurons, we performed a comprehensive, genome-wide analysis of changes in the transcriptome of DRG neurons brought about by exposure to GMCSF or GCSF. We present complete information on regulated genes and validated profiling analyses and report novel regulatory networks and interaction maps revealed by detailed bioinformatics analyses. Amongst these, we validate calpain 2, matrix metalloproteinase 9 (MMP9) and a RhoGTPase Rac1 as well as Tumor necrosis factor alpha (TNFα) as transcriptional targets of G-/GMCSF and demonstrate the importance of MMP9 and Rac1 in GMCSF-induced nociceptor sensitization. Conclusion: With integrative approach of bioinformatics, in vivo pharmacology and behavioral analyses, our results not only indicate that transcriptional control by G-/GMCSF signaling regulates a variety of established pain modulators, but also uncover a large number of novel targets, paving the way for translational analyses in the context of pain disorders

Temporal variations in CO2 and CO at Ahmedabad in western India

About 70% of the anthropogenic CO2 is emitted from the megacities and urban areas of the world. In-situ simultaneous measurements of carbon dioxide (CO2) and carbon monoxide (CO) have been made using a state-of-the-art laser based cavity ring down spectroscopy technique at Ahmedabad, an urban site in western India, from November 2013 to May 2015 with a break during March to June 2014. Annual average concentrations of CO2 and CO have been found to be 413.0+/-13.7 ppm and 0.50+/-0.37 ppm respectively. Both the species show strong seasonality, with lower concentrations of 400.3+/-6.8 ppm and 0.19+/-0.13 ppm, respectively during the south-west monsoon, and higher values of 419.6+/-22.8 ppm and 0.72+/-0.68 ppm, respectively in autumn (SON). Strong diurnal variations are also observed for both the species. The common factors for diurnal cycles of CO2 and CO are the vertical mixing and rush hour traffic, while the influence of biospheric fluxes is also seen in CO2 diurnal cycle. Using CO and CO2 covariation, we differentiate the anthropogenic and biospheric components of CO2 and found that significant contributions of biospheric respiration and anthropogenic emission in the late night (00:00-05:00 IST) and evening rush hours (18:00-22:00 IST) respectively. We compute total yearly emission of CO to be 69.2+/-0.07 Gg for the study region using the observed CO:CO2 correlation slope and bottom-up CO2 emission inventory. This calculated emission of CO is 52% larger than the estimated emission of CO by the EDGAR inventory. The observations of CO2 have been compared with an atmospheric chemistry transport model (i.e., ACTM), which incorporates various components of CO2 fluxes. ACTM is able to capture the basic variabilities, but both diurnal and seasonal amplitudes are largely underestimated compared to the observations. We attribute this underestimation by model to uncertainties in terrestrial biosphere fluxes and coarse model resolution. The fossil fuel signal from the model shows fairly good correlation with observed CO2 variations, which supports the overall dominance of fossil fuel emissions over the biospheric fluxes in this urban region.Discussion Pape

Tumor cell network integration in glioma represents a stemness feature

BACKGROUND: Malignant gliomas including glioblastomas are characterized by a striking cellular heterogeneity, which includes a subpopulation of glioma cells that becomes highly resistant by integration into tumor microtube (TM)-connected multicellular networks. METHODS: A novel functional approach to detect, isolate, and characterize glioma cell subpopulations with respect to in vivo network integration is established, combining a dye staining method with intravital two-photon microscopy, Fluorescence-Activated Cell Sorting (FACS), molecular profiling, and gene reporter studies. RESULTS: Glioblastoma cells that are part of the TM-connected tumor network show activated neurodevelopmental and glioma progression gene expression pathways. Importantly, many of them revealed profiles indicative of increased cellular stemness, including high expression of nestin. TM-connected glioblastoma cells also had a higher potential for reinitiation of brain tumor growth. Long-term tracking of tumor cell nestin expression in vivo revealed a stronger TM network integration and higher radioresistance of the nestin-high subpopulation. Glioblastoma cells that were both nestin-high and network-integrated were particularly able to adapt to radiotherapy with increased TM formation. CONCLUSION: Multiple stem-like features are strongly enriched in a fraction of network-integrated glioma cells, explaining their particular resilience

Correlated MRI and Ultramicroscopy (MR-UM) of Brain Tumors Reveals Vast Heterogeneity of Tumor Infiltration and Neoangiogenesis in Preclinical Models and Human Disease

Diffuse tumor infiltration into the adjacent parenchyma is an effective dissemination mechanism of brain tumors. We have previously developed correlated high field magnetic resonance imaging and ultramicroscopy (MR-UM) to study neonangiogenesis in a glioma model. In the present study we used MR-UM to investigate tumor infiltration and neoangiogenesis in a translational approach. We compare infiltration and neoangiogenesis patterns in four brain tumor models and the human disease: whereas the U87MG glioma model resembles brain metastases with an encapsulated growth and extensive neoangiogenesis, S24 experimental gliomas mimic IDH1 wildtype glioblastomas, exhibiting infiltration into the adjacent parenchyma and along white matter tracts to the contralateral hemisphere. MR-UM resolves tumor infiltration and neoangiogenesis longitudinally based on the expression of fluorescent proteins, intravital dyes or endogenous contrasts. Our study demonstrates the huge morphological diversity of brain tumor models regarding their infiltrative and neoangiogenic capacities and further establishes MR-UM as a platform for translational neuroimaging

Temporal variations of atmospheric CO2 and CO at Ahmedabad in western India

About 70 % of the anthropogenic carbon dioxide (CO2) is emitted from the megacities and urban areas of the world. In order to draw effective emission mitigation policies for combating future climate change as well as independently validating the emission inventories for constraining their large range of uncertainties, especially over major metropolitan areas of developing countries, there is an urgent need for greenhouse gas measurements over representative urban regions. India is a fast developing country, where fossil fuel emissions have increased dramatically in the last three decades and are predicted to continue to grow further by at least 6 % per year through to 2025. The CO2 measurements over urban regions in India are lacking. To overcome this limitation, simultaneous measurements of CO2 and carbon monoxide (CO) have been made at Ahmedabad, a major urban site in western India, using a state-of-the-art laser-based cavity ring down spectroscopy technique from November 2013 to May 2015. These measurements enable us to understand the diurnal and seasonal variations in atmospheric CO2 with respect to its sources (both anthropogenic and biospheric) and biospheric sinks. The observed annual average concentrations of CO2 and CO are 413.0 ± 13.7 and 0.50 ± 0.37 ppm respectively. Both CO2 and CO show strong seasonality with lower concentrations (400.3 ± 6.8 and 0.19 ± 0.13 ppm) during the south-west monsoon and higher concentrations (419.6 ± 22.8 and 0.72 ± 0.68 ppm) during the autumn (SON) season. Strong diurnal variations are also observed for both the species. The common factors for the diurnal cycles of CO2 and CO are vertical mixing and rush hour traffic, while the influence of biospheric fluxes is also seen in the CO2 diurnal cycle. Using CO and CO2 covariation, we differentiate the anthropogenic and biospheric components of CO2 and found significant contributions of biospheric respiration and anthropogenic emissions in the late night (00:00–05:00 h, IST) and evening rush hours (18:00–22:00 h) respectively. We compute total yearly emissions of CO to be 69.2 ± 0.07 Gg for the study region using the observed CO : CO2 correlation slope and bottom-up CO2 emission inventory. This calculated emission of CO is 52 % larger than the estimated emission of CO by the emissions database for global atmospheric research (EDGAR) inventory. The observations of CO2 have been compared with an atmospheric chemistry-transport model (ACTM), which incorporates various components of CO2 fluxes. ACTM is able to capture the basic variabilities, but both diurnal and seasonal amplitudes are largely underestimated compared to the observations. We attribute this underestimation by the model to uncertainties in terrestrial biosphere fluxes and coarse model resolution. The fossil fuel signal from the model shows fairly good correlation with observed CO2 variations, which supports the overall dominance of fossil fuel emissions over the biospheric fluxes in this urban region.by Naveen Chandra, Shyam Lal, S. Venkataramani, Prabir K. Patra and Varun Shee

Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues

Understanding the nano-architecture of protein machines in diverse subcellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While single-molecule localization microscopy techniques allow the visualization and identification of cellular structures with near-molecular resolution, multiplex-labeling of tens of target proteins within the same sample has not yet been achieved routinely. However, single sample multiplexing is essential to detect patterns that threaten to get lost in multi-sample averaging. Here, we report maS3TORM (multiplexed automated serial staining stochastic optical reconstruction microscopy), a microscopy approach capable of fully automated 3D direct STORM (dSTORM) imaging and solution exchange employing a re-staining protocol to achieve highly multiplexed protein localization within individual biological samples. We demonstrate 3D super-resolution images of 15 targets in single cultured cells and 16 targets in individual neuronal tissue samples with <10 nm localization precision, allowing us to define distinct nano-architectural features of protein distribution within the presynaptic nerve terminal

Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues

Understanding the nano-architecture of protein machines in diverse sub-cellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While singlemolecule localization microscopy techniques allow the visualization and identification of cellular structures with near-molecular resolution, multiplex-labeling of tens of target proteins within the same sample has not yet been achieved routinely. However, single sample multiplexing is essential to detect patterns that threaten to get lost in multi-sample averaging. Here, we report maS3TORM (multiplexed automated serial staining stochastic optical reconstruction microscopy), a microscopy approach capable of fully automated 3D dSTORM imaging and solution exchange employing a re-staining protocol to achieve highly multiplexed protein localization within individual biological samples. We demonstrate 3D super-resolution images of 15 target proteins in single cultured cells and 16 targets in individual neuronal tissue samples with <10 nm localization precision. This allowed us to define novel nano-architectural features of protein distribution within the presynaptic nerve terminal

Enhanced labeling density and whole-cell 3D dSTORM imaging by repetitive labeling of target proteins

With continuing advances in the resolving power of super-resolution microscopy, the inefficient labeling of proteins with suitable fluorophores becomes a limiting factor. For example, the low labeling density achieved with antibodies or small molecule tags limits attempts to reveal local protein nano-architecture of cellular compartments. On the other hand, high laser intensities cause photobleaching within and nearby an imaged region, thereby further reducing labeling density and impairing multi-plane whole-cell 3D super-resolution imaging. Here, we show that both labeling density and photobleaching can be addressed by repetitive application of trisNTA-fluorophore conjugates reversibly binding to a histidine-tagged protein by a novel approach called single-epitope repetitive imaging (SERI). For single-plane super-resolution microscopy, we demonstrate that, after multiple rounds of labeling and imaging, the signal density is increased. Using the same approach of repetitive imaging, washing and re-labeling, we demonstrate whole-cell 3D super-resolution imaging compensated for photobleaching above or below the imaging plane. This proof-of-principle study demonstrates that repetitive labeling of histidine-tagged proteins provides a versatile solution to break the 'labeling barrier' and to bypass photobleaching in multi-plane, whole-cell 3D experiments

Enhanced labeling density and whole-cell 3D dSTORM imaging by repetitive labeling of target proteins

Abstract With continuing advances in the resolving power of super-resolution microscopy, the inefficient labeling of proteins with suitable fluorophores becomes a limiting factor. For example, the low labeling density achieved with antibodies or small molecule tags limits attempts to reveal local protein nano-architecture of cellular compartments. On the other hand, high laser intensities cause photobleaching within and nearby an imaged region, thereby further reducing labeling density and impairing multi-plane whole-cell 3D super-resolution imaging. Here, we show that both labeling density and photobleaching can be addressed by repetitive application of trisNTA-fluorophore conjugates reversibly binding to a histidine-tagged protein by a novel approach called single-epitope repetitive imaging (SERI). For single-plane super-resolution microscopy, we demonstrate that, after multiple rounds of labeling and imaging, the signal density is increased. Using the same approach of repetitive imaging, washing and re-labeling, we demonstrate whole-cell 3D super-resolution imaging compensated for photobleaching above or below the imaging plane. This proof-of-principle study demonstrates that repetitive labeling of histidine-tagged proteins provides a versatile solution to break the ‘labeling barrier’ and to bypass photobleaching in multi-plane, whole-cell 3D experiments