Genetic Engineering of Bacteriophages Against Infectious Diseases

Bacteriophages (phages) are the most abundant and widely distributed organisms on Earth, constituting a virtually unlimited resource to explore the development of biomedical therapies. The therapeutic use of phages to treat bacterial infections (“phage therapy”) was conceived by Felix d’Herelle nearly a century ago. However, its power has been realized only recently, largely due to the emergence of multi-antibiotic resistant bacterial pathogens. Progress in technologies, such as high-throughput sequencing, genome editing, and synthetic biology, further opened doors to explore this vast treasure trove. Here, we review some of the emerging themes on the use of phages against infectious diseases. In addition to phage therapy, phages have also been developed as vaccine platforms to deliver antigens as part of virus-like nanoparticles that can stimulate immune responses and prevent pathogen infections. Phage engineering promises to generate phage variants with unique properties for prophylactic and therapeutic applications. These approaches have created momentum to accelerate basic as well as translational phage research and potential development of therapeutics in the near future

Comparing Evapotranspiration from Eddy Covariance Measurements, Water Budgets, Remote Sensing, and Land Surface Models over Canada

This study compares six evapotranspiration ET products for Canada’s landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of data quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November–February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation

Artificial intelligence-based non-invasive tumor segmentation, grade stratification and prognosis prediction for clear-cell renal-cell carcinoma

Due to the complicated histopathological characteristics of clear-cell renal-cell carcinoma (ccRCC), non-invasive prognosis before operative treatment is crucial in selecting the appropriate treatment. A total of 126 345 computerized tomography (CT) images from four independent patient cohorts were included for analysis in this study. We propose a V Bottleneck multi-resolution and focus-organ network (VB-MrFo-Net) using a cascade framework for deep learning analysis. The VB-MrFo-Net achieved better performance than VB-Net in tumor segmentation, with a Dice score of 0.87. The nuclear-grade prediction model performed best in the logistic regression classifier, with area under curve values from 0.782 to 0.746. Survival analysis revealed that our prediction model could significantly distinguish patients with high survival risk, with a hazard ratio (HR) of 2.49 [95% confidence interval (CI): 1.13-5.45, P = 0.023] in the General cohort. Excellent performance had also been verified in the Cancer Genome Atlas cohort, the Clinical Proteomic Tumor Analysis Consortium cohort, and the Kidney Tumor Segmentation Challenge cohort, with HRs of 2.77 (95%CI: 1.58-4.84, P = 0.0019), 3.83 (95%CI: 1.22-11.96, P = 0.029), and 2.80 (95%CI: 1.05-7.47, P = 0.025), respectively. In conclusion, we propose a novel VB-MrFo-Net for the renal tumor segmentation and automatic diagnosis of ccRCC. The risk stratification model could accurately distinguish patients with high tumor grade and high survival risk based on non-invasive CT images before surgical treatments, which could provide practical advice for deciding treatment options.</p

Resolving power of diffraction imaging with an objective: a numerical study

Diffraction imaging in the far-field can detect 3D morphological features of an object for its coherent nature. We describe methods for accurate calculation and analysis of diffraction images of scatterers of single and double spheres by an imaging unit based on microscope objective at non-conjugate positions. A quantitative study of the calculated diffraction imaging in spectral domain has been performed to assess the resolving power of diffraction imaging. It has been shown numerically that with coherent illumination of 532 nm in wavelength the imaging unit can resolve single spheres of 2 μm or larger in diameters and double spheres separated by less than 300 nm between their centers.ECU Open Access Publishing Fun

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus

Coherent light scattering presents complex spatial patterns that depend on morphological and molecular features of biological cells. We present a numerical approach to establish realistic optical cell models for generating virtual cells and accurate simulation of diffraction images that are comparable to measured data of prostate cells. With a contourlet transform algorithm, it has been shown that the simulated images and extracted parameters can be used to distinguish virtual cells of different nuclear volumes and refractive indices against the orientation variation. These results demonstrate significance of the new approach for development of rapid cell assay methods through diffraction imaging.ECU Open Access Publishing Support Fun

Single-cell profiling reveals distinct immune response landscapes in tuberculous pleural effusion and non-TPE

BackgroundTuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb) and remains a major health threat worldwide. However, a detailed understanding of the immune cells and inflammatory mediators in Mtb-infected tissues is still lacking. Tuberculous pleural effusion (TPE), which is characterized by an influx of immune cells to the pleural space, is thus a suitable platform for dissecting complex tissue responses to Mtb infection.MethodsWe employed singe-cell RNA sequencing to 10 pleural fluid (PF) samples from 6 patients with TPE and 4 non-TPEs including 2 samples from patients with TSPE (transudative pleural effusion) and 2 samples with MPE (malignant pleural effusion).ResultCompared to TSPE and MPE, TPE displayed obvious difference in the abundance of major cell types (e.g., NK, CD4+T, Macrophages), which showed notable associations with disease type. Further analyses revealed that the CD4 lymphocyte population in TPE favored a Th1 and Th17 response. Tumor necrosis factors (TNF)-, and XIAP related factor 1 (XAF1)-pathways induced T cell apoptosis in patients with TPE. Immune exhaustion in NK cells was an important feature in TPE. Myeloid cells in TPE displayed stronger functional capacity for phagocytosis, antigen presentation and IFN-γ response, than TSPE and MPE. Systemic elevation of inflammatory response genes and pro-inflammatory cytokines were mainly driven by macrophages in patients with TPE.ConclusionWe provide a tissue immune landscape of PF immune cells, and revealed a distinct local immune response in TPE and non-TPE (TSPE and MPE). These findings will improve our understanding of local TB immunopathogenesis and provide potential targets for TB therapy

Structural and functional studies of birnavirus RNA polymerases---Insights into the protein-priming mechanism and the evolution of RNA viruses

The first crystal structure of a birnavirus polymerase, IBDV VP1, has been determined at 2.5 A resolution by multiple isomorphous replacement and anomalous scattering (MIR-AS). The VP1 structure reveals several highly unusual features. By adopting a novel topology in the polymerase palm subdomain, VP1 is able to bring several functional motifs into spatial proximity to form a complete polymerase active site, despite the permutaion of sequence. By modeling initiation and elongation complexes onto the VP1 structure, important structural features are demonstrated and insights into the functions of the birnavirus self-guanylylation and protein-primed RNA synthesis are presented. Both self-guanylylation and nucleotide polymerization activities of VP1 are explored using various biochemical approaches; and based on the combination these findings and site-directed mutagenesis, speculations about the mechanisms of the self-guanylylation active site and the unusual polymerase active site are presented. Moreover, the VP1 structure lends further support for the evolutionary relationship between dsRNA and +ssRNA viruses. Progress in crystallographic and functional studies on other birnavirus polymerases and various functional complexes are also provided for the future direction of further investigation on the structural basis of the protein-priming mechanism by birnavirus VP1