<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kumar, Manoj</style></author><author><style face="normal" font="default" size="100%">Gulati, Sneha</style></author><author><style face="normal" font="default" size="100%">Ansari, Asgar H.</style></author><author><style face="normal" font="default" size="100%">Phutela, Rhythm</style></author><author><style face="normal" font="default" size="100%">Acharya, Sundaram</style></author><author><style face="normal" font="default" size="100%">Azhar, Mohd</style></author><author><style face="normal" font="default" size="100%">Murthy, Jayaram</style></author><author><style face="normal" font="default" size="100%">Kathpalia, Poorti</style></author><author><style face="normal" font="default" size="100%">Kanakan, Akshay</style></author><author><style face="normal" font="default" size="100%">Maurya, Ranjeet</style></author><author><style face="normal" font="default" size="100%">Vasudevan, Janani Srinivasa</style></author><author><style face="normal" font="default" size="100%">Aparna, S.</style></author><author><style face="normal" font="default" size="100%">Pandey, Rajesh</style></author><author><style face="normal" font="default" size="100%">Maiti, Souvik</style></author><author><style face="normal" font="default" size="100%">Chakraborty, Debojyoti</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">FnCas9-based CRISPR diagnostic for rapid and accurate detection of major SARS-CoV-2 variants on a paper strip</style></title><secondary-title><style face="normal" font="default" size="100%">eLife</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">e67130</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The COVID-19 pandemic originating in the Wuhan province of China in late 2019 has impacted global health, causing increased mortality among elderly patients and individuals with comorbid conditions. During the passage of the virus through affected populations, it has undergone mutations, some of which have recently been linked with increased viral load and prognostic complexities. Several of these variants are point mutations that are difficult to diagnose using the gold standard quantitative real-time PCR (qRT-PCR) method and necessitates widespread sequencing which is expensive, has long turn-around times, and requires high viral load for calling mutations accurately. Here, we repurpose the high specificity of Francisella novicida Cas9 (FnCas9) to identify mismatches in the target for developing a lateral flow assay that can be successfully adapted for the simultaneous detection of SARS-CoV-2 infection as well as for detecting point mutations in the sequence of the virus obtained from patient samples. We report the detection of the S gene mutation N501Y (present across multiple variant lineages of SARS-CoV-2) within an hour using lateral flow paper strip chemistry. The results were corroborated using deep sequencing on multiple wild-type (n = 37) and mutant (n = 22) virus infected patient samples with a sensitivity of 87% and specificity of 97%. The design principle can be rapidly adapted for other mutations (as shown also for E484K and T716I) highlighting the advantages of quick optimization and roll-out of CRISPR diagnostics (CRISPRDx) for disease surveillance even beyond COVID-19. This study was funded by Council for Scientific and Industrial Research, India.</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">8.140</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Azhar, Mohd</style></author><author><style face="normal" font="default" size="100%">Phutela, Rhythm</style></author><author><style face="normal" font="default" size="100%">Kumar, Manoj</style></author><author><style face="normal" font="default" size="100%">Ansari, Asgar Hussain</style></author><author><style face="normal" font="default" size="100%">Rauthan, Riya</style></author><author><style face="normal" font="default" size="100%">Gulati, Sneha</style></author><author><style face="normal" font="default" size="100%">Sharma, Namrata</style></author><author><style face="normal" font="default" size="100%">Sinha, Dipanjali</style></author><author><style face="normal" font="default" size="100%">Sharma, Saumya</style></author><author><style face="normal" font="default" size="100%">Singh, Sunaina</style></author><author><style face="normal" font="default" size="100%">Acharya, Sundaram</style></author><author><style face="normal" font="default" size="100%">Sarkar, Sajal</style></author><author><style face="normal" font="default" size="100%">Paul, Deepanjan</style></author><author><style face="normal" font="default" size="100%">Kathpalia, Poorti</style></author><author><style face="normal" font="default" size="100%">Aich, Meghali</style></author><author><style face="normal" font="default" size="100%">Sehgal, Paras</style></author><author><style face="normal" font="default" size="100%">Ranjan, Gyan</style></author><author><style face="normal" font="default" size="100%">Bhoyar, Rahul C.</style></author><author><style face="normal" font="default" size="100%">Singhal, Khushboo</style></author><author><style face="normal" font="default" size="100%">Lad, Harsha</style></author><author><style face="normal" font="default" size="100%">Patra, Pradeep Kumar</style></author><author><style face="normal" font="default" size="100%">Makharia, Govind</style></author><author><style face="normal" font="default" size="100%">Chandak, Giriraj Ratan</style></author><author><style face="normal" font="default" size="100%">Pesala, Bala</style></author><author><style face="normal" font="default" size="100%">Chakraborty, Debojyoti</style></author><author><style face="normal" font="default" size="100%">Maiti, Souvik</style></author><author><style face="normal" font="default" size="100%">Indian CoV2 Genomics Genetic Epide</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Rapid and accurate nucleobase detection using FnCas9 and its application in COVID-19 diagnosis</style></title><secondary-title><style face="normal" font="default" size="100%">Biosensors &amp; Bioelectronics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CRISPRDx</style></keyword><keyword><style  face="normal" font="default" size="100%">FELUDA</style></keyword><keyword><style  face="normal" font="default" size="100%">FnCas9</style></keyword><keyword><style  face="normal" font="default" size="100%">LFA</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV2</style></keyword><keyword><style  face="normal" font="default" size="100%">SNV detection</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUL </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">183</style></volume><pages><style face="normal" font="default" size="100%">113207</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Rapid detection of DNA/RNA pathogenic sequences or variants through point-of-care diagnostics is valuable for accelerated clinical prognosis, as witnessed during the recent COVID-19 outbreak. Traditional methods relying on qPCR or sequencing are tough to implement with limited resources, necessitating the development of accurate and robust alternative strategies. Here, we report FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that utilizes a direct Cas9 based enzymatic readout for detecting nucleobase and nucleotide sequences without transcleavage of reporter molecules. We also demonstrate that FELUDA is 100% accurate in detecting single nucleotide variants (SNVs), including heterozygous carriers, and present a simple web-tool JATAYU to aid end-users. FELUDA is semi-quantitative, can adapt to multiple signal detection platforms, and deploy for versatile applications such as molecular diagnosis during infectious disease outbreaks like COVID-19. Employing a lateral flow readout, FELUDA shows 100% sensitivity and 97% specificity across all ranges of viral loads in clinical samples within 1hr. In combination with RT-RPA and a smartphone application True Outcome Predicted via Strip Evaluation (TOPSE), we present a prototype for FELUDA for CoV-2 detection closer to home.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;10.257&lt;/p&gt;</style></custom4></record></records></xml>