Hurdle Approach to Simulate Corn Wet Milling Inactivation of Undesirable Microorganisms: A Pilot Scale Microbial Challenge Study Using Salmonella Surrogate Enterococcus faecium.

Corn wet milling (CWM) and corn starch flash drying processing conditions reduce undesirable microorganisms, such as Salmonella. Finished products are historically safe, with intrinsic properties such as low water activity inhibiting microbial growth. Corn processors could use quantified levels of reduction in this study of Salmonella surrogate Enterococcus faecium (E.

Machine learning for design of degenerate Cas13a crRNAs using lassa virus as a model of highly variable RNA target.

The design of minimum CRISPR RNA (crRNA) sets for detection of diverse RNA targets using sequence degeneracy has not been systematically addressed. We tested candidate degenerate Cas13a crRNA sets designed for detection of diverse RNA targets (Lassa virus). A decision tree machine learning (ML) algorithm (RuleFit) was applied to define the top attributes that determine the specificity of degenerate crRNAs to elicit collateral nuclease activity.

Prevalence of malaria resistance-associated mutations in circulating in 2017-2018, Bo, Sierra Leone.

Introduction: In spite of promising medical, sociological, and engineering strategies and interventions to reduce the burden of disease, malaria remains a source of significant morbidity and mortality, especially among children in sub-Saharan Africa. In particular, progress in the development and administration of chemotherapeutic agents is threatened by evolved resistance to most of the antimalarials currently in use, including artemisinins.

Methods: This study analyzed the prevalence of mutations associated with antimalarial resistance in from 95 clinical samples collected from individuals with clinically confirmed malaria at a hospital in Bo, Sierra Leone between May 2017 and December 2018.

Quantum Dot-Based Molecular Beacons for Quantitative Detection of Nucleic Acids with CRISPR/Cas(N) Nucleases.

Strategies utilizing the CRISPR/Cas nucleases Cas13 and Cas12 have shown great promise in the development of highly sensitive and rapid diagnostic assays for the detection of pathogenic nucleic acids. The most common approaches utilizing fluorophore-quencher molecular beacons require strand amplification strategies or highly sensitive optical setups to overcome the limitations of the readout. Here, we demonstrate a flexible strategy for assembling highly luminescent and colorimetric quantum dot-nucleic acid hairpin (QD-HP) molecular beacons for use in CRISPR/Cas diagnostics.

Large scale screening of CRISPR guide RNAs using an optimized high throughput robotics system.

All CRISPR/CAS systems utilize CRISPR guide RNAs (crRNAs), the design of which depend on the type of CAS protein, genetic target and the environment/matrix. While machine learning approaches have recently been developed to optimize some crRNA designs, candidate crRNAs must still be screened for efficacy under relevant conditions. Here, we demonstrate a high-throughput method to screen hundreds of candidate crRNAs for activation of Cas13a collateral RNA cleavage.