24 research outputs found
The Current State and Future of CRISPR-Cas9 gRNA Design Tools
Recent years have seen the development of computational tools to assist researchers in performing CRISPR-Cas9 experiment optimally. More specifically, these tools aim to maximize on-target activity (guide efficiency) while also minimizing potential off-target effects (guide specificity) by analyzing the features of the target site. Nonetheless, currently available tools cannot robustly predict experimental success as prediction accuracy depends on the approximations of the underlying model and how closely the experimental setup matches the data the model was trained on. Here, we present an overview of the available computational tools, their current limitations and future considerations. We discuss new trends around personalized health by taking genomic variants into account when predicting target sites as well as discussing other governing factors that can improve prediction accuracy
MicroRNA-22 Controls Aberrant Neurogenesis and Changes in Neuronal Morphology After Status Epilepticus
Prolonged seizures (status epilepticus, SE) may drive hippocampal dysfunction and epileptogenesis, at least partly, through an elevation in neurogenesis, dysregulation of migration and aberrant dendritic arborization of newly-formed neurons. MicroRNA-22 was recently found to protect against the development of epileptic foci, but the mechanisms remain incompletely understood. Here, we investigated the contribution of microRNA-22 to SE-induced aberrant adult neurogenesis. SE was induced by intraamygdala microinjection of kainic acid (KA) to model unilateral hippocampal neuropathology in mice. MicroRNA-22 expression was suppressed using specific oligonucleotide inhibitors (antagomir-22) and newly-formed neurons were visualized using the thymidine analog iodo-deoxyuridine (IdU) and a green fluorescent protein (GFP)-expressing retrovirus to visualize the dendritic tree and synaptic spines. Using this approach, we quantified differences in the rate of neurogenesis and migration, the structure of the apical dendritic tree and density and morphology of dendritic spines in newly-formed neurons.SE resulted in an increased rate of hippocampal neurogenesis, including within the undamaged contralateral dentate gyrus (DG). Newly-formed neurons underwent aberrant migration, both within the granule cell layer and into ectopic sites. Inhibition of microRNA-22 exacerbated these changes. The dendritic diameter and the density and average volume of dendritic spines were unaffected by SE, but these parameters were all elevated in mice in which microRNA-22 was suppressed. MicroRNA-22 inhibition also reduced the length and complexity of the dendritic tree, independently of SE. These data indicate that microRNA-22 is an important regulator of morphogenesis of newly-formed neurons in adults and plays a role in supressing aberrant neurogenesis associated with SE
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Single-cell multi-omics analysis of the immune response in COVID-19
Funder: Lister Institute of Preventive Medicine; doi: https://doi.org/10.13039/501100001255Funder: University College London, Birkbeck MRC Doctoral Training ProgrammeFunder: The Jikei University School of MedicineFunder: Action Medical Research (GN2779)Funder: NIHR Clinical Lectureship (CL-2017-01-004)Funder: NIHR (ACF-2018-01-004) and the BMA FoundationFunder: Chan Zuckerberg Initiative (grant 2017-174169) and from Wellcome (WT211276/Z/18/Z and Sanger core grant WT206194)Funder: UKRI Innovation/Rutherford Fund Fellowship allocated by the MRC and the UK Regenerative Medicine Platform (MR/5005579/1 to M.Z.N.). M.Z.N. and K.B.M. have been funded by the Rosetrees Trust (M944)Funder: Barbour FoundationFunder: ERC Consolidator and EU MRG-Grammar awardsFunder: Versus Arthritis Cure Challenge Research Grant (21777), and an NIHR Research Professorship (RP-2017-08-ST2-002)Funder: European Molecular Biology Laboratory (EMBL)Abstract: Analysis of human blood immune cells provides insights into the coordinated response to viral infections such as severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). We performed single-cell transcriptome, surface proteome and T and B lymphocyte antigen receptor analyses of over 780,000 peripheral blood mononuclear cells from a cross-sectional cohort of 130 patients with varying severities of COVID-19. We identified expansion of nonclassical monocytes expressing complement transcripts (CD16+C1QA/B/C+) that sequester platelets and were predicted to replenish the alveolar macrophage pool in COVID-19. Early, uncommitted CD34+ hematopoietic stem/progenitor cells were primed toward megakaryopoiesis, accompanied by expanded megakaryocyte-committed progenitors and increased platelet activation. Clonally expanded CD8+ T cells and an increased ratio of CD8+ effector T cells to effector memory T cells characterized severe disease, while circulating follicular helper T cells accompanied mild disease. We observed a relative loss of IgA2 in symptomatic disease despite an overall expansion of plasmablasts and plasma cells. Our study highlights the coordinated immune response that contributes to COVID-19 pathogenesis and reveals discrete cellular components that can be targeted for therapy
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Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study
Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat
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Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study
The original version of this article unfortunately contained a mistake
Severe Intraperitoneal Haemorrhage following Suprapubic Catheter Insertion in a Patient Treated with Iloprost
Suprapubic catheter (SPC) insertion is a common urological procedure, performed both in the elective and emergency settings. The authors present an unusual case of severe intraperitoneal bleeding following the insertion of an SPC under direct vision, where the use of prostacyclin analogue may have been a contributing factor
Unlocking HDR-mediated nucleotide editing by identifying high-efficiency target sites using machine learning
Editing individual nucleotides is a crucial component for validating genomic disease association. It
is currently hampered by CRISPR-Cas-mediated “base editing” being limited to certain nucleotide
changes, and only achievable within a small window around CRISPR-Cas target sites. The more versatile
alternative, HDR (homology directed repair), has a 3-fold lower efciency with known optimization
factors being largely immutable in experiments. Here, we investigated the variable efciency-governing
factors on a novel mouse dataset using machine learning. We found the sequence composition of the
single-stranded oligodeoxynucleotide (ssODN), i.e. the repair template, to be a governing factor.
Furthermore, diferent regions of the ssODN have variable infuence, which refects the underlying
mechanism of the repair process. Our model improves HDR efciency by 83% compared to traditionally
chosen targets. Using our fndings, we developed CUNE (Computational Universal Nucleotide Editor),
which enables users to identify and design the optimal targeting strategy using traditional base editing
or – for-the-frst-time–HDR-mediated nucleotide changes.This work was supported by the National Collaborative Research Infrastructure (NCRIS) via the
Australian Phenomics Network (APN). We thank Alex Whan and Daniel Layton for critical reading of the
document
Table_1_The Current State and Future of CRISPR-Cas9 gRNA Design Tools.DOCX
<p>Recent years have seen the development of computational tools to assist researchers in performing CRISPR-Cas9 experiment optimally. More specifically, these tools aim to maximize on-target activity (guide efficiency) while also minimizing potential off-target effects (guide specificity) by analyzing the features of the target site. Nonetheless, currently available tools cannot robustly predict experimental success as prediction accuracy depends on the approximations of the underlying model and how closely the experimental setup matches the data the model was trained on. Here, we present an overview of the available computational tools, their current limitations and future considerations. We discuss new trends around personalized health by taking genomic variants into account when predicting target sites as well as discussing other governing factors that can improve prediction accuracy.</p