Molecular techniques for Dicistrovirus detection without RNA extraction and purification

Dicistroviridae is a new family of small, nonenveloped, and +ssRNA viruses pathogenic to both beneficial arthropods and insect pests as well. Triatoma virus (TrV), a dicistrovirus, is a pathogen of Triatoma infestans (Hemiptera: Reduviidae), one of the main vectors of Chagas disease. In this work, we report a single-step method to identify TrV, a dicistrovirus, isolated from fecal samples of triatomines.The identification method proved to be quite sensitive, even without the extraction and purification of RNA virus.Fil: Querido, Jailson F. B.. Universidade Nova de Lisboa; PortugalFil: Agirre, Jon. Universidad del Pais Vasco; EspañaFil: Marti, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata; ArgentinaFil: Guerin, Diego M. A.. Universidad del Pais Vasco; EspañaFil: Silva, Marcelo Sousa . Universidade Nova de Lisboa; Portuga

Keras R-CNN: library for cell detection in biological images using deep neural networks

Background: A common yet still manual task in basic biology research, high-throughput drug screening and digital pathology is identifying the number, location, and type of individual cells in images. Object detection methods can be useful for identifying individual cells as well as their phenotype in one step. State-of-the-art deep learning for object detection is poised to improve the accuracy and efficiency of biological image analysis. Results: We created Keras R-CNN to bring leading computational research to the everyday practice of bioimage analysts. Keras R-CNN implements deep learning object detection techniques using Keras and Tensorflow (https://github.com/broadinstitute/keras-rcnn). We demonstrate the command line tool’s simplified Application Programming Interface on two important biological problems, nucleus detection and malaria stage classification, and show its potential for identifying and classifying a large number of cells. For malaria stage classification, we compare results with expert human annotators and find comparable performance. Conclusions: Keras R-CNN is a Python package that performs automated cell identification for both brightfield and fluorescence images and can process large image sets. Both the package and image datasets are freely available on GitHub and the Broad Bioimage Benchmark Collection

Challenges and guidelines toward 4D nucleome data and model standards

Due to recent advances in experimental and theoretical approaches, the dynamic three-dimensional organization (3D) of the nucleus has become a very active area of research in life sciences. We now understand that the linear genome is folded in ways that may modulate how genes are expressed during the basic functioning of cells. Importantly, it is now possible to build 3D models of how the genome folds within the nucleus and changes over time (4D). Because genome folding influences its function, this opens exciting new possibilities to broaden our understanding of the mechanisms that determine cell fate. However, the rapid evolution of methods and the increasing complexity of data can result in ambiguity and reproducibility challenges, which may hamper the progress of this field. Here, we describe such challenges ahead and provide guidelines to think about strategies for shared standardized validation of experimental 4D nucleome data sets and models

Bone Marrow Is a Major Parasite Reservoir in Plasmodium vivax Infection

ABSTRACT Plasmodium vivax causes heavy burdens of disease across malarious regions worldwide. Mature P. vivax asexual and transmissive gametocyte stages occur in the blood circulation, and it is often assumed that accumulation/sequestration in tissues is not an important phase in their development. Here, we present a systematic study of P. vivax stage distributions in infected tissues of nonhuman primate (NHP) malaria models as well as in blood from human infections. In a comparative analysis of the transcriptomes of P. vivax and Plasmodium falciparum blood-stage parasites, we found a conserved cascade of stage-specific gene expression despite the greatly different gametocyte maturity times of these two species. Using this knowledge, we validated a set of conserved asexual- and gametocyte-stage markers both by quantitative real-time PCR and by antibody assays of peripheral blood samples from infected patients and NHP (Aotus sp.). Histological analyses of P. vivax parasites in organs of 13 infected NHP (Aotus and Saimiri species) demonstrated a major fraction of immature gametocytes in the parenchyma of the bone marrow, while asexual schizont forms were enriched to a somewhat lesser extent in this region of the bone marrow as well as in sinusoids of the liver. These findings suggest that the bone marrow is an important reservoir for gametocyte development and proliferation of malaria parasites

Publisher Correction: LifeTime and improving European healthcare through cell-based interceptive medicine.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03287-8.</jats:p