Transcriptional regulatory networks in the mouse hippocampus

Magister Scientiae - MScNeurological diseases are socially disabling and often mortal. To efficiently combat these diseases, a deep understanding of involved cellular processes, gene functions and anatomy is required. However, differential regulation of genes across anatomy is not sufficiently well understood. This study utilized large-scale gene expression data to define the regulatory networks of genes expressing in the hippocampus to which multiple disease pathologies may be associated. Specific aims were: ident i fy key regulatory transcription factors (TFs) responsible for observed gene expression patterns, reconstruct transcription regulatory networks, and prioritize likely TFs responsible for anatomically restricted gene expression. Most of the analysis was restricted to the CA3 sub-region of Ammon’s horn within the hippocampus. We identified 155 core genes expressing throughout the CA3 sub-region and predicted corresponding TF binding site (TFBS) distributions. Our analysis shows plausible transcription regulatory networks for twelve clusters of co-expressed genes. We demonstrate the validity of the predictions by re-clustering genes based on TFBS distributions and found that genes tend to be correctly assigned to groups of previously identified co-expressing genes with sensitivity of 67.74% and positive predictive value of 100%. Taken together, this study represents one of the first to merge anatomical architecture, expression profiles and transcription regulatory potential on such a large scale in hippocampal sub-anatomy.South Afric

Nutrient sensing modulates malaria parasite virulence

The lifestyle of intracellular pathogens, such as malaria parasites, is intimately connected to that of their host, primarily for nutrient supply. Nutrients act not only as primary sources of energy but also as regulators of gene expression, metabolism and growth, through various signalling networks that enable cells to sense and adapt to varying environmental conditions. Canonical nutrient-sensing pathways are presumed to be absent from the causative agent of malaria, Plasmodium, thus raising the question of whether these parasites can sense and cope with fluctuations in host nutrient levels. Here we show that Plasmodium blood-stage parasites actively respond to host dietary calorie alterations through rearrangement of their transcriptome accompanied by substantial adjustment of their multiplication rate. A kinome analysis combined with chemical and genetic approaches identified KIN as a critical regulator that mediates sensing of nutrients and controls a transcriptional response to the host nutritional status. KIN shares homology with SNF1/AMPKα, and yeast complementation studies suggest that it is part of a functionally conserved cellular energy-sensing pathway. Overall, these findings reveal a key parasite nutrient-sensing mechanism that is critical for modulating parasite replication and virulence

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Multi-messenger Observations of a Binary Neutron Star Merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ∼ 1.7 {{s}} with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of {40}-8+8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 {M}ȯ . An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ∼ 40 {{Mpc}}) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ∼10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ∼ 9 and ∼ 16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta.</p

Genome editing in the human malaria parasite Plasmodium falciparum using the CRISPR-Cas9 system

International audienceGenome manipulation in the malaria parasite Plasmodium falciparum remains largely intractable and improved genomic tools are needed to further understand pathogenesis and drug resistance. We demonstrated the CRISPR-Cas9 system for use in P. falciparum by disrupting chromosomal loci and generating marker-free, single-nucleotide substitutions with high efficiency. Additionally, an artemisinin-resistant strain was generated by introducing a previously implicated polymorphism, thus illustrating the value of efficient genome editing in malaria research

Flexible guide-RNA design for CRISPR applications using Protospacer Workbench

International audienceno abstrac

Development of a machine learning model for early prediction of plasma leakage in suspected dengue patients.

BackgroundAt least a third of dengue patients develop plasma leakage with increased risk of life-threatening complications. Predicting plasma leakage using laboratory parameters obtained in early infection as means of triaging patients for hospital admission is important for resource-limited settings.MethodsA Sri Lankan cohort including 4,768 instances of clinical data from N = 877 patients (60.3% patients with confirmed dengue infection) recorded in the first 96 hours of fever was considered. After excluding incomplete instances, the dataset was randomly split into a development and a test set with 374 (70%) and 172 (30%) patients, respectively. From the development set, five most informative features were selected using the minimum description length (MDL) algorithm. Random forest and light gradient boosting machine (LightGBM) were used to develop a classification model using the development set based on nested cross validation. An ensemble of the learners via average stacking was used as the final model to predict plasma leakage.ResultsLymphocyte count, haemoglobin, haematocrit, age, and aspartate aminotransferase were the most informative features to predict plasma leakage. The final model achieved the area under the receiver operating characteristics curve, AUC = 0.80 with positive predictive value, PPV = 76.9%, negative predictive value, NPV = 72.5%, specificity = 87.9%, and sensitivity = 54.8% on the test set.ConclusionThe early predictors of plasma leakage identified in this study are similar to those identified in several prior studies that used non-machine learning based methods. However, our observations strengthen the evidence base for these predictors by showing their relevance even when individual data points, missing data and non-linear associations were considered. Testing the model on different populations using these low-cost observations would identify further strengths and limitations of the presented model

First efficient CRISPR-Cas9-mediated genome editing in Leishmania parasites

Protozoan pathogens that cause leishmaniasis in humans are relatively refractory to genetic manipulation. In this work, we implemented the CRISPR‐Cas9 system in Leishmania parasites and demonstrated its efficient use for genome editing. The Cas9 endonuclease was expressed under the control of the Dihydrofolate Reductase‐Thymidylate Synthase (DHFR‐TS) promoter and the single guide RNA was produced under the control of the U6snRNA promoter and terminator. As a proof of concept, we chose to knockout a tandemly repeated gene family, the paraflagellar rod‐2 locus. We were able to obtain null mutants in a single round of transfection. In addition, we confirmed the absence of off‐target editions by whole genome sequencing of two independent clones. Our work demonstrates that CRISPR‐Cas9‐mediated gene knockout represents a major improvement in comparison with existing methods. Beyond gene knockout, this genome editing tool opens avenues for a multitude of functional studies to speed up research on leishmaniasis

Pre-Transplant Prediction of Acute Graft-versus-Host Disease Using the Gut Microbiome

Gut microbiota is thought to influence host responses to allogeneic hematopoietic stem cell transplantation (aHSCT). Recent evidence points to this post-transplant for acute graft-versus-host disease (aGvHD). We asked whether any such association might be found pre-transplant and conducted a metagenome-wide association study (MWAS) to explore. Microbial abundance profiles were estimated using ensembles of Kaiju, Kraken2, and DeepMicrobes calls followed by dimensionality reduction. The area under the curve (AUC) was used to evaluate classification of the samples (aGvHD vs. none) using an elastic net to test the relevance of metagenomic data. Clinical data included the underlying disease (leukemia vs. other hematological malignancies), recipient age, and sex. Among 172 aHSCT patients of whom 42 developed aGVHD post transplantation, a total of 181 pre-transplant tool samples were analyzed. The top performing model predicting risk of aGVHD included a reduced species profile (AUC = 0.672). Beta diversity (37% in Jaccard&rsquo;s Nestedness by mean fold change, p &lt; 0.05) was lower in those developing aGvHD. Ten bacterial species including Prevotella and Eggerthella genera were consistently found to associate with aGvHD in indicator species analysis, as well as relief and impurity-based algorithms. The findings support the hypothesis on potential associations between gut microbiota and aGvHD based on a data-driven approach to MWAS. This highlights the need and relevance of routine stool collection for the discovery of novel biomarkers