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85 result(s) for "Burgio, Gaetan"
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Redefining mouse transgenesis with CRISPR/Cas9 genome editing technology
The generation of genetically modified alleles in mice using conventional transgenesis technologies is a long and inefficient process. A new study shows that the in situ delivery of CRISPR/Cas9 reagents into pregnant mice results in a high efficiency of editing, and enables the rapid generation of both simple and complex alleles.
Correction to: Redefining mouse transgenesis with CRISPR/Cas9 genome editing technology
In the recent Research Highlight [1], it has been highlighted that part b of Fig. 1 was incorrectly labelled as \"sgRNA + tracrRNA\" instead of \"sgRNA (crRNA + tracrRNA)\". An updated Figure 1, including also the amended figure legend has therefore been provided below.
Bacillus cereus non-haemolytic enterotoxin activates the NLRP3 inflammasome
Inflammasomes are important for host defence against pathogens and homeostasis with commensal microbes. Here, we show non-haemolytic enterotoxin (NHE) from the neglected human foodborne pathogen Bacillus cereus is an activator of the NLRP3 inflammasome and pyroptosis. NHE is a non-redundant toxin to haemolysin BL (HBL) despite having a similar mechanism of action. Via a putative transmembrane region, subunit C of NHE initiates binding to the plasma membrane, leading to the recruitment of subunit B and subunit A, thus forming a tripartite lytic pore that is permissive to efflux of potassium. NHE mediates killing of cells from multiple lineages and hosts, highlighting a versatile functional repertoire in different host species. These data indicate that NHE and HBL operate synergistically to induce inflammation and show that multiple virulence factors from the same pathogen with conserved function and mechanism of action can be exploited for sensing by a single inflammasome. The Bacillus haemolytic enterotoxin haemolysin BL has been shown to activate the NLRP3 inflammasome. Here the authors show that a non-haemolytic enterotoxin (NHE) from B. cereus can also activate the NLRP3 inflammasome with a similar mechanism of lytic pore formation.
Predicting CRISPR-Cas12a guide efficiency for targeting using machine learning
Genome editing through the development of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat)–Cas technology has revolutionized many fields in biology. Beyond Cas9 nucleases, Cas12a (formerly Cpf1) has emerged as a promising alternative to Cas9 for editing AT-rich genomes. Despite the promises, guide RNA efficiency prediction through computational tools search still lacks accuracy. Through a computational meta-analysis, here we report that Cas12a target and off-target cleavage behavior are a factor of nucleotide bias combined with nucleotide mismatches relative to the protospacer adjacent motif (PAM) site. These features helped to train a Random Forest machine learning model to improve the accuracy by at least 15% over existing algorithms to predict guide RNA efficiency for the Cas12a enzyme. Despite the progresses, our report underscores the need for more representative datasets and further benchmarking to reliably and accurately predict guide RNA efficiency and off-target effects for Cas12a enzymes.
Collateral damage and CRISPR genome editing
The simplicity and the versatility of clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR-Cas) systems have enabled the genetic modification of virtually every organism and offer immense therapeutic potential for the treatment of human disease. Although these systems may function efficiently within eukaryotic cells, there remain concerns about the accuracy of Cas endonuclease effectors and their use for precise gene editing. Recently, two independent reports investigating the editing accuracy of the CRISPR-Cas9 system were published by separate groups at the Wellcome Sanger Institute; our study-Iyer and colleagues [1]-defined the landscape of off-target mutations, whereas the other by Kosicki and colleagues [2] detailed the existence of on-target, potentially deleterious deletions. Although both studies found evidence of large on-target CRISPR-induced deletions, they reached seemingly very different conclusions.
Targeting the Cell Stress Response of Plasmodium falciparum to Overcome Artemisinin Resistance
Successful control of falciparum malaria depends greatly on treatment with artemisinin combination therapies. Thus, reports that resistance to artemisinins (ARTs) has emerged, and that the prevalence of this resistance is increasing, are alarming. ART resistance has recently been linked to mutations in the K13 propeller protein. We undertook a detailed kinetic analysis of the drug responses of K13 wild-type and mutant isolates of Plasmodium falciparum sourced from a region in Cambodia (Pailin). We demonstrate that ART treatment induces growth retardation and an accumulation of ubiquitinated proteins, indicative of a cellular stress response that engages the ubiquitin/proteasome system. We show that resistant parasites exhibit lower levels of ubiquitinated proteins and delayed onset of cell death, indicating an enhanced cell stress response. We found that the stress response can be targeted by inhibiting the proteasome. Accordingly, clinically used proteasome inhibitors strongly synergize ART activity against both sensitive and resistant parasites, including isogenic lines expressing mutant or wild-type K13. Synergy is also observed against Plasmodium berghei in vivo. We developed a detailed model of parasite responses that enables us to infer, for the first time, in vivo parasite clearance profiles from in vitro assessments of ART sensitivity. We provide evidence that the clinical marker of resistance (delayed parasite clearance) is an indirect measure of drug efficacy because of the persistence of unviable parasites with unchanged morphology in the circulation, and we suggest alternative approaches for the direct measurement of viability. Our model predicts that extending current three-day ART treatment courses to four days, or splitting the doses, will efficiently clear resistant parasite infections. This work provides a rationale for improving the detection of ART resistance in the field and for treatment strategies that can be employed in areas with ART resistance.
Differential activation of NLRP3 inflammasome by Acinetobacter baumannii strains
Acinetobacter baumannii is an emerging nosocomial, opportunistic pathogen with growing clinical significance globally. A . baumannii has an exceptional ability to rapidly develop drug resistance. It is frequently responsible for ventilator-associated pneumonia in clinical settings and inflammation resulting in severe sepsis. The inflammatory response is mediated by host pattern-recognition receptors and the inflammasomes. Inflammasome activation triggers inflammatory responses, including the secretion of the pro-inflammatory cytokines IL-1β and IL-18, the recruitment of innate immune effectors against A . baumannii infection, and the induction programmed cell death by pyroptosis. An important knowledge gap is how variation among clinical isolates affects the host’s innate response and activation of the inflammasome during A . baumannii infection. In this study, we compared nine A . baumannii strains, including clinical locally-acquired isolates, in their ability to induce activation of the inflammasome and programmed cell death in primary macrophages, epithelial lung cell line and mice. We found a variation in survival outcomes of mice and bacterial dissemination in organs among three commercially available A . baumannii strains, likely due to the differences in virulence between strains. Interestingly, we found variability among A . baumannii strains in activation of the NLRP3 inflammasome, non-canonical Caspase-11 pathway, plasmatic secretion of the pro-inflammatory cytokine IL-1β and programmed cell death. Our study highlights the importance of utilising multiple bacterial strains and clinical isolates with different virulence to investigate the innate immune response to A . baumannii infection.
Pathogen-selective killing by guanylate-binding proteins as a molecular mechanism leading to inflammasome signaling
Inflammasomes are cytosolic signaling complexes capable of sensing microbial ligands to trigger inflammation and cell death responses. Here, we show that guanylate-binding proteins (GBPs) mediate pathogen-selective inflammasome activation. We show that mouse GBP1 and GBP3 are specifically required for inflammasome activation during infection with the cytosolic bacterium Francisella novicida . We show that the selectivity of mouse GBP1 and GBP3 derives from a region within the N-terminal domain containing charged and hydrophobic amino acids, which binds to and facilitates direct killing of F. novicida and Neisseria meningitidis , but not other bacteria or mammalian cells. This pathogen-selective recognition by this region of mouse GBP1 and GBP3 leads to pathogen membrane rupture and release of intracellular content for inflammasome sensing. Our results imply that GBPs discriminate between pathogens, confer activation of innate immunity, and provide a host-inspired roadmap for the design of synthetic antimicrobial peptides that may be of use against emerging and re-emerging pathogens. Guanylate-binding proteins (GBP) have a function in inflammasome formation and pathogen defence. Here the authors show that these GBP proteins are able to kill certain bacteria and promote selective inflammasome activation and that this is mediated by specific GBP protein regions.
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 efficiency with known optimization factors being largely immutable in experiments. Here, we investigated the variable efficiency-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, different regions of the ssODN have variable influence, which reflects the underlying mechanism of the repair process. Our model improves HDR efficiency by 83% compared to traditionally chosen targets. Using our findings, 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-first-time – HDR-mediated nucleotide changes.