Sequence-specific antimicrobials using efficiently delivered RNA-guided nucleases

Current antibiotics tend to be broad spectrum, leading to indiscriminate killing of commensal bacteria and accelerated evolution of drug resistance. Here, we use CRISPR-Cas technology to create antimicrobials whose spectrum of activity is chosen by design. RNA-guided nucleases (RGNs) targeting specific DNA sequences are delivered efficiently to microbial populations using bacteriophage or bacteria carrying plasmids transmissible by conjugation. The DNA targets of RGNs can be undesirable genes or polymorphisms, including antibiotic resistance and virulence determinants in carbapenem-resistant Enterobacteriaceae and enterohemorrhagic Escherichia coli. Delivery of RGNs significantly improves survival in a Galleria mellonella infection model. We also show that RGNs enable modulation of complex bacterial populations by selective knockdown of targeted strains based on genetic signatures. RGNs constitute a class of highly discriminatory, customizable antimicrobials that enact selective pressure at the DNA level to reduce the prevalence of undesired genes, minimize off-target effects and enable programmable remodeling of microbiota.National Institutes of Health (U.S.) (New Innovator Award 1DP2OD008435)National Centers for Systems Biology (U.S.) (Grant 1P50GM098792)United States. Defense Threat Reduction Agency (HDTRA1-14-1-0007)Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies (W911NF13D0001)National Institute of General Medical Sciences (U.S.) (Interdepartmental Biotechnology Training Program 5T32 GM008334)Fonds de la recherche en sante du Quebec (Master's Training Award

The genome of the yellow potato cyst nematode, Globodera rostochiensis, reveals insights into the basis of parasitism and virulence

BACKGROUND: The yellow potato cyst nematode, Globodera rostochiensis, is a devastating plant pathogen of global economic importance. This biotrophic parasite secretes effectors from pharyngeal glands, some of which were acquired by horizontal gene transfer, to manipulate host processes and promote parasitism. G. rostochiensis is classified into pathotypes with different plant resistance-breaking phenotypes. RESULTS: We generate a high quality genome assembly for G. rostochiensis pathotype Ro1, identify putative effectors and horizontal gene transfer events, map gene expression through the life cycle focusing on key parasitic transitions and sequence the genomes of eight populations including four additional pathotypes to identify variation. Horizontal gene transfer contributes 3.5 % of the predicted genes, of which approximately 8.5 % are deployed as effectors. Over one-third of all effector genes are clustered in 21 putative ‘effector islands’ in the genome. We identify a dorsal gland promoter element motif (termed DOG Box) present upstream in representatives from 26 out of 28 dorsal gland effector families, and predict a putative effector superset associated with this motif. We validate gland cell expression in two novel genes by in situ hybridisation and catalogue dorsal gland promoter element-containing effectors from available cyst nematode genomes. Comparison of effector diversity between pathotypes highlights correlation with plant resistance-breaking. CONCLUSIONS: These G. rostochiensis genome resources will facilitate major advances in understanding nematode plant-parasitism. Dorsal gland promoter element-containing effectors are at the front line of the evolutionary arms race between plant and parasite and the ability to predict gland cell expression a priori promises rapid advances in understanding their roles and mechanisms of action.SE-vdA is supported by BBSRC grant BB/M014207/1. Sequencing was funded by BBSRC grant BB/F000642/1 to the University of Leeds and grant BB/F00334X/1 to the Wellcome Trust Sanger Institute). DRL was supported by a fellowship from The James Hutton Institute and the School of Biological Sciences, University of Edinburgh. GK was supported by a BBSRC PhD studentship. The James Hutton Institute receives funding from the Scottish Government. JAC and NEH are supported by the Wellcome Trust through its core funding of the Wellcome Trust Sanger Institute (grant 098051). This work was also supported by funding from the Canadian Safety and Security Program, project number CRTI09_462RD

Nanotechnology intervention of the microbiome for cancer therapy

The microbiome is emerging as a key player and driver of cancer. Traditional modalities to manipulate the microbiome (for example, antibiotics, probiotics and microbiota transplants) have been shown to improve efficacy of cancer therapies in some cases, but issues such as collateral damage to the commensal microbiota and consistency of these approaches motivates efforts towards developing new technologies specifically designed for the microbiome–cancer interface. Considering the success of nanotechnology in transforming cancer diagnostics and treatment, nanotechnologies capable of manipulating interactions that occur across microscopic and molecular length scales in the microbiome and the tumour microenvironment have the potential to provide innovative strategies for cancer treatment. As such, opportunities at the intersection of nanotechnology, the microbiome and cancer are massive. In this Review, we highlight key opportunistic areas for applying nanotechnologies towards manipulating the microbiome for the treatment of cancer, give an overview of seminal work and discuss future challenges and our perspective on this emerging area

Transcriptomic particularities among species of globodera

Globodera spp. are major plant parasitic nematodes affecting Solanaceous plants including potato, tomato, eggplant and tobacco. Each species secretes specialized proteins called effectors to outwit plant defenses, allowing them to have a unique host range

Genetic structure of golden nematode populations from Québec, Canada, with the use of new microsatellite markers

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Genetic structure and evolution of potato cyst nematodes populations

To understand the mechanisms leading to the breakdown of plant resistance by potato cyst nematodes (PCN; Globodera rostochiensis and G. pallida), an understanding of the genetic structure and variation in populations and the processes that govern their evolution is required

Effect of iron and nitrogen on the development of Helminthosporium solani and potato silver scurf

Silver scurf is a surface blemish disease of potato (Solanum tuberosum L.) tubers caused by Helminthosporium solani Durieu & Mont. Silver scurf is becoming a disease of high economic impact. In this study, the effect of different iron (FeSO 4, FeCl 2) and nitrogen (NaNO 2, NaNO 3, NH 4Cl, NH 4NO 3) salts on H. solani conidial germination and on potato silver scurf development was evaluated. The results show that iron and nitrogen salts affect in vitro germination of H. solani conidia. Conidia were particularly sensitive to FeSO 4 and FeCl 2. These salts completely inhibited conidial germination and were shown to be toxic at a concentration of 0.9 mM. Among the nitrogen salts tested, conidia were most affected by NaNO 2 and NH 4Cl, which almost completely inhibited their germination at a concentration of 169.7 mM. NaNO 2 was also toxic to conidia. Among the salts tested, only FeSO 4, FeCl 2 and NaNO 2 reduced the development of silver scurf. Comparison of the effect of the different tested salts leads to the conclusion that ions Fe ++ and NO 2 - have toxic effects on the conidia and repressive effects on silver scurf development while NO 3 - and NH 4 + have no toxic effect on conidia and no repressive effect on silver scurf development

PIPE4: Fast PPI Predictor for Comprehensive Inter- and Cross-Species Interactomes

The need for larger-scale and increasingly complex protein-protein interaction (PPI) prediction tasks demands that state-of-the-art predictors be highly efficient and adapted to inter- and cross-species predictions. Furthermore, the ability to generate comprehensive interactomes has enabled the appraisal of each PPI in the context of all predictions leading to further improvements in classification performance in the face of extreme class imbalance using the Reciprocal Perspective (RP) framework. We here describe the PIPE4 algorithm. Adaptation of the PIPE3/MP-PIPE sequence preprocessing step led to upwards of 50x speedup and the new Similarity Weighted Score appropriately normalizes for window frequency when applied to any inter- and cross-species prediction schemas. Comprehensive interactomes for three prediction schemas are generated: (1) cross-species predictions, where Arabidopsis thaliana is used as a proxy to predict the comprehensive Glycine max interactome, (2) inter-species predictions between Homo sapiens-HIV1, and (3) a combined schema involving both cross- and inter-species predictions, where both Arabidopsis thaliana and Caenorhabditis elegans are used as proxy species to predict the interactome between Glycine max (the soybean legume) and Heterodera glycines (the soybean cyst nematode). Comparing PIPE4 with the state-of-the-art resulted in improved performance, indicative that it should be the method of choice for complex PPI prediction schemas