Asif, A. | bioRxiv Science

bioRxiv2020

An assessment of efficacy of Iodine complex (Renessans) against SARS-CoV-2 in non-human primates (Rhesus macaque)

Renessans is an iodine complex which has proven in vitro antiviral activity including Anti-SARS-CoV-2 activity. The present study was designed to determine its efficacy against SARS-CoV-2 in monkeys (Rhesus macaque). A total of 14 monkeys were divided into four groups: A) Prophylactic group (n=03), (B) Treatment group (n=03), (C) infection control group (n=04) and (D) negative control group (n=04) and were housed in BSL-3 Animal facility while group D was housed at another animal house. Group A was administered with Renessans @ 2.85 mg/7 kg from 5 days prior to the infection to 08 days post infections (DPI). Group B was administered with Renessans from 03-08 DPI @ 2.85 mg/7 kg. Group C was administered with WIF only. The infection @ 2 x 106 TCID of SARS-CoV-2 was given to all group monkeys through intranasal and oral route under anesthesia. Nasal swab samples (at different times) and fecal matter on daily basis were collected for the detection of SARS-CoV-2 through real-time quantitative PCR. Three monkeys (one from each of group A, B and C) were euthanized at 07 DPI to determine the gross pathological lesions and SARS-CoV-2 detection from internal tissues. Nasal swabs from all the monkeys from group A, B and C were positive for SARS-CoV-2 at 02 and 07 DPI (Day 05 of treatment). At 14 DPI, all (100%) nasal swabs from group A were negative for SARS-CoV-2 while 50% and 100% were positive from group B and C, respectively. At 21 DPI, monkeys from group B were negative and all in group C were still positive for SARS-CoV-2. Similarly, fecal matter of monkeys in group A and B was returned negative in significantly lesser time as compared to monkeys from infection control group. Based on these research findings it is concluded that the Renessans has in-vivo SARS-CoV-2 activity and may result in early clearance of SARS-CoV-2. Therefore, a clinical trial of the drug in COVID-19 patients may reveal its anti-COVID-19 potential.

microbiology↗

bioRxiv2019

Machine Learning Predicts New Anti-CRISPR Proteins

The increasing use of CRISPR-Cas9 in medicine, agriculture and synthetic biology has accelerated the drive to discover new CRISPR-Cas inhibitors as potential mechanisms of control for gene editing applications. Many such anti-CRISPRs have been found in mobile genetic elements that disable the CRISPR-Cas adaptive immune system. However, comparing all currently known anti-CRISPRs does not reveal a shared set of properties that can be used for facile bioinformatic identification of new anti-CRISPR families. Here, we describe AcRanker, a machine learning based method for identifying new potential anti-CRISPRs directly from proteomes using protein sequence information only. Using a training set of known anti-CRISPRs, we built a model based on XGBoost ranking and extensively benchmarked it through non-redundant cross-validation and external validation. We then applied AcRanker to predict candidate anti-CRISPRs from self-targeting bacterial genomes and discovered two previously unknown anti-CRISPRs: AcrllA16 (ML1) and AcrIIA17 (ML8). We show that AcrIIA16 strongly inhibits Streptococcus iniae Cas9 (SinCas9) and weakly inhibits Streptococcus pyogenes Cas9 (SpyCas9). We also show that AcrIIA17 inhibits both SpyCas9 and SauCas9 with low potency. The addition of AcRanker to the anti-CRISPR discovery toolkit allows researchers to directly rank potential anti-CRISPR candidate genes for increased speed in testing and validation of new anti-CRISPRs. A web server implementation for AcRanker is available online at http://acranker.pythonanywhere.com/.

biochemistry↗