Caveolae and Scaffold Detection from Single Molecule Localization Microscopy Data Using Deep Learning

Caveolae are plasma membrane invaginations whose formation requires caveolin-1 (Cav1), the adaptor protein polymerase I, and the transcript release factor (PTRF or CAVIN1). Caveolae have an important role in cell functioning, signaling, and disease. In the absence of CAVIN1/PTRF, Cav1 forms non-caveolar membrane domains called scaffolds. In this work, we train machine learning models to automatically distinguish between caveolae and scaffolds from single molecule localization microscopy (SMLM) data. We apply machine learning algorithms to discriminate biological structures from SMLM data. Our work is the first that is leveraging machine learning approaches (including deep learning models) to automatically identifying biological structures from SMLM data. In particular, we develop and compare three binary classification methods to identify whether or not a given 3D cluster of Cav1 proteins is a caveolae. The first uses a random forest classifier applied to 28 hand-crafted/designed features, the second uses a convolutional neural net (CNN) applied to a projection of the point clouds onto three planes, and the third uses a PointNet model, a recent development that can directly take point clouds as its input. We validate our methods on a dataset of super-resolution microscopy images of PC3 prostate cancer cells labeled for Cav1. Specifically, we have images from two cell populations: 10 PC3 and 10 CAVIN1/PTRF-transfected PC3 cells (PC3-PTRF cells) that form caveolae. We obtained a balanced set of 1714 different cellular structures. Our results show that both the random forest on hand-designed features and the deep learning approach achieve high accuracy in distinguishing the intrinsic features of the caveolae and non-caveolae biological structures. More specifically, both random forest and deep CNN classifiers achieve classification accuracy reaching 94% on our test set, while the PointNet model only reached 83% accuracy. We also discuss the pros and cons of the different approaches

Field Performance of Nine Soil Water Content Sensors on a Sandy Loam Soil in New Brunswick, Maritime Region, Canada

An in situ field test on nine commonly-used soil water sensors was carried out in a sandy loam soil located in the Potato Research Center, Fredericton, NB (Canada) using the gravimetric method as a reference. The results showed that among the tested sensors, regardless of installation depths and soil water regimes, CS615, Trase, and Troxler performed the best with the factory calibrations, with a relative root mean square error (RRMSE) of 15.78, 16.93, and 17.65%, and a r2 of 0.75, 0.77, and 0.65, respectively. TRIME, Moisture Point (MP917), and Gopher performed slightly worse with the factory calibrations, with a RRMSE of 45.76, 26.57, and 20.41%, and a r2 of 0.65, 0.72, and 0.78, respectively, while the Gypsum, WaterMark, and Netafim showed a frequent need for calibration in the application in this region

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Caveolin-1 and membrane domain regulation of focal adhesions and tumor cell migration

Caveolin-1 (Cav1), a key protein component of cell surface invagination caveolae and a major substrate of Src kinase, has been shown to be associated with cancer malignancy. Galectin-3 (Gal3), a galactose-specific lectin, forms oligomers and crosslinks N-glycans on cell surface to form the galectin lattice. Gal3 and Cav1 function together to regulate focal adhesion dynamics and tumor cell migration. In this thesis we hypothesize that the galectin lattice, Cav1 membrane domain organization (caveolae, Cav1 scaffolds) and Cav1 molecular motifs (tyrosine 14 phosphorylation (pY14), the caveolin scaffolding domain (CSD)) are all involved in Cav1 promotion of focal adhesion dynamics and tumor cell motility. Firstly, we found a synergistic expression of Cav1 and Gal3 in malignant thyroid cancer cells, which was required for focal adhesion kinase (FAK) stabilization in focal adhesions (a measure of focal adhesion dynamics), RhoA activation and cell migration. Co-overexpression of Cav1 and Gal3, but not either alone, in an anaplastic thyroid cancer cell line stabilized FAK within focal adhesions. Therefore, co-function of Cav1 and Gal3 is required to promote focal adhesion dynamics and cell migration in thyroid cancer. Next we found that overexpression of PTRF/cavin-1 in PC3 prostate cancer cells, and consequent formation of caveolae, decreased cell motility by destabilizing FAK in focal adhesions. The impaired focal adhesion stabilization of FAK in PTRF/cavin-1-expressing PC3 cells was rescued by exogenous Gal3 in a Cav1-dependent manner. Hence the alteration of Cav1 microdomains by PTRF/cavin-1 overexpression decreases cell motility through affecting focal adhesion dynamics, which is overridden by reinforced Cav1-Gal3/galectin lattice co-function. Finally, using Cav1-positive but tyrosine 14-phosphorylated Cav1 (pY14Cav1)-negative DU145 prostate cancer cells, various Cav1 Y14 and CSD mutants and a CSD mimicking/competing peptide, we found a CSD-dependent pY14Cav1 regulation of focal adhesion dynamics and cell motility. Vinculin, a mechano-sensor at focal adhesions that was previously shown to recruit and stabilize other focal adhesion components, preferentially bound pY14Cav1 and was stabilized in focal adhesions by pY14Cav1 in a CSD-dependent manner. Vinculin tension was induced by pY14Cav1 in a CSD-dependent manner. Therefore, a novel interplay between pY14 and the CSD of Cav1 regulates focal adhesion dynamics and tension favouring cell migration.Medicine, Faculty ofGraduat

Evaluating Impacts of Detailed Land Use and Management Inputs on the Accuracy and Resolution of SWAT Predictions in an Experimental Watershed

Land use and management practice inputs to the Soil and Water Assessment Tool (SWAT) are critical for evaluating the impact of land use change and best management practices on soil erosion and water quality in watersheds. We developed an algorithm in this study to maximize the usage of land use and management records during the setup of SWAT for a small experimental watershed in New Brunswick, Canada. In the algorithm, hydrologic response units (HRUs) were delineated based on field boundaries and associated with long-term field records. The SWAT model was further calibrated and validated with respect to water flow and sediment and nutrient (nitrate and soluble phosphorus) loadings at the watershed outlet. As a comparison, a baseline version of SWAT was also set up using the conventional way of HRU delineation with limited information on land use and management practices. These two versions of SWAT were compared with respect to input and output resolution and prediction accuracy of monthly and annual water flow and sediment and nutrient loadings. Results show that the SWAT set up with the new method had much higher accuracies in generating annual areas of crops, fertilizer application, tillage operation, flow diversion terraces (FDT), and grassed waterways in the watershed. Compared with the SWAT set up with the conventional method, the SWAT set up with the new method improved the accuracy of predicting monthly sediment loading due to a better representation of FDT in the watershed, and it also successfully estimated the spatial impact of FDT on soil erosion across the watershed. However, there was no definite increase in simulation accuracy in monthly water flow and nutrient loadings with high spatial and temporal management inputs, though monthly nutrient loading simulations were sensitive to management configuration. The annual examination also showed comparable simulation accuracy on water flow and nutrient loadings between the two models. These results indicate that SWAT, although set up with limited land use and management information, is able to provide comparable simulations of water quantity and quality at the watershed outlet, as long as the estimated land use and management practice data can reasonably represent the average land use and management condition of the watershed over the target simulation period.https://doi.org/10.3390/w1415235

Evaluating Impacts of Detailed Land Use and Management Inputs on the Accuracy and Resolution of SWAT Predictions in an Experimental Watershed

Land use and management practice inputs to the Soil and Water Assessment Tool (SWAT) are critical for evaluating the impact of land use change and best management practices on soil erosion and water quality in watersheds. We developed an algorithm in this study to maximize the usage of land use and management records during the setup of SWAT for a small experimental watershed in New Brunswick, Canada. In the algorithm, hydrologic response units (HRUs) were delineated based on field boundaries and associated with long-term field records. The SWAT model was further calibrated and validated with respect to water flow and sediment and nutrient (nitrate and soluble phosphorus) loadings at the watershed outlet. As a comparison, a baseline version of SWAT was also set up using the conventional way of HRU delineation with limited information on land use and management practices. These two versions of SWAT were compared with respect to input and output resolution and prediction accuracy of monthly and annual water flow and sediment and nutrient loadings. Results show that the SWAT set up with the new method had much higher accuracies in generating annual areas of crops, fertilizer application, tillage operation, flow diversion terraces (FDT), and grassed waterways in the watershed. Compared with the SWAT set up with the conventional method, the SWAT set up with the new method improved the accuracy of predicting monthly sediment loading due to a better representation of FDT in the watershed, and it also successfully estimated the spatial impact of FDT on soil erosion across the watershed. However, there was no definite increase in simulation accuracy in monthly water flow and nutrient loadings with high spatial and temporal management inputs, though monthly nutrient loading simulations were sensitive to management configuration. The annual examination also showed comparable simulation accuracy on water flow and nutrient loadings between the two models. These results indicate that SWAT, although set up with limited land use and management information, is able to provide comparable simulations of water quantity and quality at the watershed outlet, as long as the estimated land use and management practice data can reasonably represent the average land use and management condition of the watershed over the target simulation period

Galectin-3 Overrides PTRF/Cavin-1 Reduction of PC3 Prostate Cancer Cell Migration.

Expression of Caveolin-1 (Cav1), a key component of cell surface caveolae, is elevated in prostate cancer (PCa) and associated with PCa metastasis and a poor prognosis for PCa patients. Polymerase I and Transcript Release Factor (PTRF)/cavin-1 is a cytoplasmic protein required for Cav1-dependent formation of caveolae. Expression of PTRF reduces the motility of PC3 cells, a metastatic prostate cancer cell line that endogenously expresses abundant Cav1 but no PTRF and no caveolae, suggesting a role for non-caveolar Cav1 domains, or Cav1 scaffolds, in PCa cell migration. Tyrosine phosphorylated Cav1 (pCav1) functions in concert with Galectin-3 (Gal3) and the galectin lattice to stabilize focal adhesion kinase (FAK) within focal adhesions (FAs) and promote cancer cell motility. However, whether PTRF regulation of Cav1 function in PCa cell migration is related to Gal3 expression and functionality has yet to be determined. Here we show that PTRF expression in PC3 cells reduces FAK stabilization in focal adhesions and reduces cell motility without affecting pCav1 levels. Exogenous Gal3 stabilized FAK in focal adhesions of PTRF-expressing cells and restored cell motility of PTRF-expressing PC3 cells to levels of PC3 cells in a dose-dependent manner, with an optimal concentration of 2 µg/ml. Exogenous Gal3 stabilized FAK in focal adhesions of Gal3 knockdown PC3 cells but not in Cav1 knockdown PC3 cells. Cav1 knockdown also prevented Gal3 rescue of FA-associated FAK stabilization in PTRF-expressing PC3 cells. Our data support a role for PTRF/cavin-1, through caveolae formation, as an attenuator of the non-caveolar functionality of Cav1 in Gal3-Cav1 signalling and regulation of focal adhesion dynamics and cancer cell migration

Summarized working models of affecting Gal3-pCav1 function.

<p>Extracellular Gal3 and non-caveolar pCav1 each stabilizes FAK within FAs dependent on each other. Expression of PTRF disrupts this function through three possible ways: 1) by recruiting pCav1 away from non-caveolar Cav1 scaffolds and into caveolae; 2) by direct interaction with non-caveolar pCav1; 3) by affecting Gal3 secretion and thus extracellular Gal3 concentration. Through which pathway PTRF affects Gal3-pCav1 function on FA dynamics remains to be studied.</p

Exogenous Gal3 restores FAK stabilization in FAs of Gal3 knockdown cells.

<p>(A) Western blot shows the efficiency of Gal3 siRNA knockdown. (B) FRAP assay shows FA-associated FAK-GFP stability in PC3 cells transfected with no siRNA, scramble control siRNA (siCTL) or the siRNA against human Gal3 (siGal3), and subjected to 2 μg/ml Gal3-His treatment. The FAK-GFP intensity recovery curve graphs of one representative experiment and a bar graph of the FAK-GFP mobile fraction summarized from all experiments are shown. (n = 3; ***: p<0.001.)</p

Expression of PTRF does not affect pCav1 in PC3 cells.

<p>Western blot shows expression levels of GFP, GFP-PTRF, Cav1 and pCav1 in PC3 wild-type cells (PC3), PC3 cells stably transfected with GFP (PC3-GFP) and PC3 cells stably transfected with GFP-PTRF (PC3-GFP-PTRF). Western blot band intensity of Cav1 and pCav1 is quantified and normalized to that of β-actin and shows no significant difference of Cav1 expression or phosphorylation between PC3, PC3-GFP and PC3-GFP-PTRF cells. (n≥3; ***: p<0.001.)</p