scholarly journals 993. A CRISPR-Powered Universal Infectious Disease Assay

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S587-S588
Author(s):  
Keith Brown

Abstract Background The COVID-19 pandemic has brought awareness to the dangers of emerging pathogens to global human health and welfare. Sensitivity and flexibility are important features for methods used to detect emerging pathogens. While PCR testing is rapid and sensitive, a significant advantage next generation sequencing (NGS) approaches have over PCR-based analyses is the ability to detect previously undiscovered pathogens while also providing genomic information that can detect SARS-CoV-2 genome sequence, identify source of co-infection, and the host transcriptional response in a single workflow. The critical component enabling this approach is Jumpcode CRISPRclean technology which removes abundant human and bacterial ribosomal RNA sequences from NGS libraries. CRISPRclean workflow easily integrates into next generation sequencing projects Schematic of the Jumpcode CRISPRclean protocol Methods CRISPRclean was applied to contrived infected tissue samples including human lung RNA spiked with serially diluted amounts of SARS-CoV-2 RNA and bacterial RNA. NEB RNA libraries were prepared and treated with CRISPRclean protocol, then sequenced on Illumina instruments. Data analysis was performed using Jumpcode proprietary software to measure alignment and depletion rates, the Silva database for rRNA read alignment, and Kraken2 and CosmosID pipelines for k-mer based metagenomic investigation. Fold enrichment of SARS-CoV-2 reads after CRISPRclean depletion of libraries prepared from contrived samples. CRISPRclean treatment of the fully contrived samples increases the fraction of reads that map to the SARS-CoV-2 genome by an average of ~10-fold Results CRISPRclean treatment of the contrived samples increases ~10 fold of reads that map to the SARS-CoV-2 genome. For the 60 viral copies of SARS-CoV-2 sample, the number of reads mapping to the SARSCoV-2 genome increases from ~10,000 reads to ~70,000 reads. A similar increase in reads occurs for S. aureus. The percentage of SARS-CoV-2 genome covered at 1X and 10X also increases. Similar results were achieved even after downsampling the datasets to 5M reads. There is a ~4-fold increase in bacterial species detection in these stool samples after CRISPRclean treatment. Percentage of SARS-CoV-2 genome covered at 1X and 10X increases as a result of rRNA depletion. Coverage of the SARS-CoV-2 genome at 50 million reads. Number of reads aligning to the S. aureus and SARS-CoV-2 genomes increases after CRISPRclean depletion. For the sample containing 0.0001% SARS-CoV-2, (60 viral copies), the number of reads mapping to the SARS-CoV-2 genome increases from ~10,000 reads to ~70,000 reads. CosmosID Shotgun Metagenomics Analysis heat map showing read alignments to viral genomes. The yellow color indicates high read counts. The CosmosID shotgun metagenomic analysis software was used to analyze the sequencing data, classify the sequences and generate the heat map. Conclusion Metatranscriptomics powered by CRISPR-mediated rRNA depletion offers a robust methodology to acquire viral genomic data, microbiome composition, co-infection information, and the transcriptional status of the host immune response in a single workflow. This sequencing-based approach can be available on the first day of the next viral outbreak and should be considered as a first-line test for novel zoonotic virus detection. Bacterial species composition of patient stool samples before and after CRISPRclean depletion. ~4-fold increase in bacterial species detection in these stool samples after CRISPRclean treatment. Sequencing data downsampled to 20 million reads. Disclosures Keith Brown, n/a, Jumpcode Genomics (Board Member, Employee, Shareholder)

Author(s):  
Anne Krogh Nøhr ◽  
Kristian Hanghøj ◽  
Genis Garcia Erill ◽  
Zilong Li ◽  
Ida Moltke ◽  
...  

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Panagiotis Moulos

Abstract Background The relentless continuing emergence of new genomic sequencing protocols and the resulting generation of ever larger datasets continue to challenge the meaningful summarization and visualization of the underlying signal generated to answer important qualitative and quantitative biological questions. As a result, the need for novel software able to reliably produce quick, comprehensive, and easily repeatable genomic signal visualizations in a user-friendly manner is rapidly re-emerging. Results recoup is a Bioconductor package for quick, flexible, versatile, and accurate visualization of genomic coverage profiles generated from Next Generation Sequencing data. Coupled with a database of precalculated genomic regions for multiple organisms, recoup offers processing mechanisms for quick, efficient, and multi-level data interrogation with minimal effort, while at the same time creating publication-quality visualizations. Special focus is given on plot reusability, reproducibility, and real-time exploration and formatting options, operations rarely supported in similar visualization tools in a profound way. recoup was assessed using several qualitative user metrics and found to balance the tradeoff between important package features, including speed, visualization quality, overall friendliness, and the reusability of the results with minimal additional calculations. Conclusion While some existing solutions for the comprehensive visualization of NGS data signal offer satisfying results, they are often compromised regarding issues such as effortless tracking of processing and preparation steps under a common computational environment, visualization quality and user friendliness. recoup is a unique package presenting a balanced tradeoff for a combination of assessment criteria while remaining fast and friendly.


2011 ◽  
Vol 9 (6) ◽  
pp. 238-244 ◽  
Author(s):  
Tongwu Zhang ◽  
Yingfeng Luo ◽  
Kan Liu ◽  
Linlin Pan ◽  
Bing Zhang ◽  
...  

AIDS ◽  
2011 ◽  
Vol 25 (16) ◽  
pp. 2019-2026 ◽  
Author(s):  
Art F.Y. Poon ◽  
Rachel A. McGovern ◽  
Theresa Mo ◽  
David J.H.F. Knapp ◽  
Bluma Brenner ◽  
...  

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