SEP 07, 2022 9:00 AM PDT

Panel Presentation: Antimicrobial Resistance (AMR) Summit: Identifying Antimicrobial Resistance from Sample to Insight

Sponsored by: QIAGEN


Antimicrobial resistance (AMR) detection and surveillance is a high priority in healthcare and environmental settings for the safety of both patients and the general public. However, working with samples used for this type of monitoring, such as stool or wastewater, can be challenging, from the sample preparation to the sequencing to the bioinformatics.

You will learn about:

Nucleic acid extraction from various sample types

The importance of inhibitor removal during sample preparation

Sequencing workflows for AMR

Benefits of using hybrid capture versus shotgun sequencing

How to generate ShortBRED AMR marker abundance tables

How to associate and compare different metadata, such as sample type (stool, wastewater, etc.)

AMR alpha and beta diversity across sample types and how to determine the depth of coverage

Talk 1: Sample preparation

Some of the most interesting sample types for healthcare and environmental monitoring, such as stool or wastewater, are the most problematic sources for extracting nucleic acids. Nucleic acid extraction kits that deliver high yields and remove inhibitory substances are essential for workflows aimed at gaining insight from these sample types. We will discuss techniques and technologies for optimizing sample extraction from inhibitory samples.

Talk 2: Sequencing workflows

Cities employ NGS-based wastewater analysis to identify not only SARS-CoV-2 variants but also other viral and bacterial targets as early alert systems of community health. We will discuss an optimized hybrid capture-based NGS workflow for detection, sequencing and characterization of AMR gene targets using a variety of sample types.

Talk 3: Bioinformatics analysis and interpretation

Bioinformatics analysis is the last crucial step in sequencing experiments, including AMR hybrid capture panels. This talk will discuss key principles behind the data analysis, followed by a demonstration of a typical analysis journey from FASTQ files to insight.

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