34 research outputs found
INVESTIGATING THE MECHANISM OF BACTERIAL CELL DIVISION WITH SUPERRESOLUTION MICROSCOPY
The molecular mechanisms that drive bacterial cytokinesis are attractive antibiotic targets that remain poorly understood. The machinery that performs cytokinesis in bacteria has been termed the 'divisome' (see Chapter 1 for description). The most widely-conserved divisome protein, FtsZ, is an essential tubulin homolog that polymerizes into protofilaments in a nucleotide-dependent manner. These protofilaments assemble at midcell to form the ‘Z-ring’, which has been the prevailing candidate for constrictive force generation during cell division. However, it has been difficult to experimentally test proposed Z-ring force generation models in vivo due to the small size of bacteria (< 1 μm diameter for E. coli) compared to the diffraction-limited resolution of light (~ 0.3 μm).
In this work, quantitative superresolution and time-lapse microscopy were applied to examine whether Z-ring structure and function indeed play limiting roles in driving E. coli cell constriction (Chapter 2). Surprisingly, these studies revealed that the rate of septum closure during constriction is robust to substantial changes in many Z-ring properties, including the GTPase activity of FtsZ, molecular density of the Z-ring, the timing of Z-ring disassembly, and the absence of Z-ring assembly regulators. Further investigation revealed that septum closure rate is instead highly coupled to the rate of cell wall growth and elongation, and can be modulated by coordination with chromosome segregation. Taken together, these results challenge the Z-ring centric view of constriction force generation, and suggest that cell wall synthesis and chromosome segregation likely drive the rate and progress of cell constriction in bacteria.
These investigations were made possible by advancements in quantitative superresolution microscopy techniques (see Chapter 3 for overview). One major obstacle encountered during the course of this work, and shared by those utilizing localization-based superresolution microscopy techniques, was the overestimation of molecule numbers caused by fluorophore photoblinking. Thus, Chapter 4 describes a systematic characterization of the effects of photoblinking on the accurate construction and analysis of superresolution images. These characterizations enabled the development of a simple method to identify the optimal clustering thresholds and an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions
Hybrid endoscopic thymectomy : combined transesophageal and transthoracic approach in a survival porcine model with cadaver assessment
BACKGROUND:
Video-assisted thoracoscopic surgery thymectomy has been used in the treatment of Myastenia Gravis and thymomas (coexisting or not). In natural orifice transluminal endoscopic surgery, new approaches to the thorax are emerging as alternatives to the classic transthoracic endoscopic surgery. The aim of this study was to assess the feasibility and reliability of hybrid endoscopic thymectomy (HET) using a combined transthoracic and transesophageal approach.
METHODS:
Twelve consecutive in vivo experiments were undertaken in the porcine model (4 acute and 8 survival). The same procedure was assessed in a human cadaver afterward. For HET, an 11-mm trocar was inserted in the 2nd intercostal space in the left anterior axillary line. A 0° 10-mm thoracoscope with a 5-mm working channel was introduced. Transesophageal access was created through a submucosal tunnel using a flexible gastroscope with a single working channel introduced through the mouth. Using both flexible (gastroscope) and rigid (thoracoscope) instruments, the mediastinum was opened; the thymus was dissected, and the vessels were ligated using electrocautery alone.
RESULTS:
Submucosal tunnel creation and esophagotomy were performed safely without incidents in all animals. Complete thymectomy was achieved in all experiments. All animals in the survival group lived for 14 days. Thoracoscopic and postmortem examination revealed pleural adhesions on site of the surgical procedure with no signs of infection. Histological analysis of the proximal third of the esophagus revealed complete cicatrization of both mucosal defect and myotomy site. In the human cadaver, we were able to replicate all the procedure even though we were not able to identify the thymus.
CONCLUSIONS:
Hybrid endoscopic thymectomy is feasible and reliable. HET could be regarded as a possible alternative to classic thoracoscopic approach for patients requiring thymectomy.This project was funded by the FCT Grants project PTDC/SAU-OSM/105578/2008
In Vivo Structure of the E. coli FtsZ-ring Revealed by Photoactivated Localization Microscopy (PALM)
The FtsZ protein, a tubulin-like GTPase, plays a pivotal role in prokaryotic cell division. In vivo it localizes to the midcell and assembles into a ring-like structure-the Z-ring. The Z-ring serves as an essential scaffold to recruit all other division proteins and generates contractile force for cytokinesis, but its supramolecular structure remains unknown. Electron microscopy (EM) has been unsuccessful in detecting the Z-ring due to the dense cytoplasm of bacterial cells, and conventional fluorescence light microscopy (FLM) has only provided images with limited spatial resolution (200–300 nm) due to the diffraction of light. Hence, given the small sizes of bacteria cells, identifying the in vivo structure of the Z-ring presents a substantial challenge. Here, we used photoactivated localization microscopy (PALM), a single molecule-based super-resolution imaging technique, to characterize the in vivo structure of the Z-ring in E. coli. We achieved a spatial resolution of ∼35 nm and discovered that in addition to the expected ring-like conformation, the Z-ring of E. coli adopts a novel compressed helical conformation with variable helical length and pitch. We measured the thickness of the Z-ring to be ∼110 nm and the packing density of FtsZ molecules inside the Z-ring to be greater than what is expected for a single-layered flat ribbon configuration. Our results strongly suggest that the Z-ring is composed of a loose bundle of FtsZ protofilaments that randomly overlap with each other in both longitudinal and radial directions of the cell. Our results provide significant insight into the spatial organization of the Z-ring and open the door for further investigations of structure-function relationships and cell cycle-dependent regulation of the Z-ring
31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two
Background
The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd.
Methods
We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background.
Results
First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001).
Conclusions
In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival
INVESTIGATING THE MECHANISM OF BACTERIAL CELL DIVISION WITH SUPERRESOLUTION MICROSCOPY
The molecular mechanisms that drive bacterial cytokinesis are attractive antibiotic targets that remain poorly understood. The machinery that performs cytokinesis in bacteria has been termed the 'divisome' (see Chapter 1 for description). The most widely-conserved divisome protein, FtsZ, is an essential tubulin homolog that polymerizes into protofilaments in a nucleotide-dependent manner. These protofilaments assemble at midcell to form the ‘Z-ring’, which has been the prevailing candidate for constrictive force generation during cell division. However, it has been difficult to experimentally test proposed Z-ring force generation models in vivo due to the small size of bacteria (< 1 μm diameter for E. coli) compared to the diffraction-limited resolution of light (~ 0.3 μm).
In this work, quantitative superresolution and time-lapse microscopy were applied to examine whether Z-ring structure and function indeed play limiting roles in driving E. coli cell constriction (Chapter 2). Surprisingly, these studies revealed that the rate of septum closure during constriction is robust to substantial changes in many Z-ring properties, including the GTPase activity of FtsZ, molecular density of the Z-ring, the timing of Z-ring disassembly, and the absence of Z-ring assembly regulators. Further investigation revealed that septum closure rate is instead highly coupled to the rate of cell wall growth and elongation, and can be modulated by coordination with chromosome segregation. Taken together, these results challenge the Z-ring centric view of constriction force generation, and suggest that cell wall synthesis and chromosome segregation likely drive the rate and progress of cell constriction in bacteria.
These investigations were made possible by advancements in quantitative superresolution microscopy techniques (see Chapter 3 for overview). One major obstacle encountered during the course of this work, and shared by those utilizing localization-based superresolution microscopy techniques, was the overestimation of molecule numbers caused by fluorophore photoblinking. Thus, Chapter 4 describes a systematic characterization of the effects of photoblinking on the accurate construction and analysis of superresolution images. These characterizations enabled the development of a simple method to identify the optimal clustering thresholds and an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions
Accurate Construction of Photoactivated Localization Microscopy (PALM) Images for Quantitative Measurements
<div><p>Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (<em>t<sub>Thresh</sub></em> and <em>d<sub>Thresh</sub></em>) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems.</p> </div
Quantitative measurements of a simulated cluster dataset.
<p>(A) Representative cluster diameter measurement for a reference image with no repeat localizations. Each cluster is identified by eye, and then fit to a two-dimensional, symmetrical Gaussian distribution (blue mesh). The cluster diameter is measured as the FWHM, calculated as 2.35*σ, where σ is the fitted Gaussian standard deviation. The average FWHM of these four clusters is 74±1 nm. (B) Cluster diameter values (average of four clusters) calculated from images generated by applying different threshold pairs to the same simulated dataset. The measured diameters decrease with increasing threshold values, similarly to the Z-ring width measurement. (C) The fraction of molecules located in clusters (<i>f<sub>cluster</sub></i>) is most similar to that measured in the reference image (0.47) for low values of both <i>d<sub>Thresh</sub></i> and <i>t<sub>Thresh</sub></i>. (D) As with the Z-ring simulation, fractional difference between each reconstructed image and the number of molecules in the reference image (<i>N<sub>ref</sub></i>  = 1212) is lowest along two intersecting valleys. (E) The Jaccard index peak position for the cluster simulation is similar to that in the Z-ring simulation where identical kinetic parameters were used (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051725#pone-0051725-g005" target="_blank">Figure 5B</a>). This simulated dataset was generated using the following parameters: N<sub>total</sub>  = 2000 (50% in clusters),  = 200, FWHM<sub>cluster</sub>  = 50 nm, σ  = 15 nm, blink>  = 2, <τ<sub>off</sub>>  = 1 frame, <τ<sub>on</sub>>  = 1 frame, <τ<sup>0</sup><sub>act</sub>>  = 5 frames (1 frame  = 50 ms).</p