Find New Genomic Insights into Antimicrobial Resistance

Author:

Winnie Ridderberg

Find New Genomic Insights into Antimicrobial Resistance

Find resistance through surveillance and source tracing with two new tools: PointFinder and ShortBRED

Winnie Ridderberg, PhD, Senior Scientist, Microbial Genomics

The emergence and spread of antimicrobial resistant (AMR) bacteria and resistance mechanisms pose a global challenge to public health, and careful surveillance and source tracing is crucial. To help contribute to fight against AMR, we have launched a new version of CLC Microbial Genomics Module (4.0) for CLC Genomics Workbench 12.

The New CLC Microbial Genomics Module

The new CLC Microbial Genomics Module (version 4.0) extends your capability for analyzing microbial genomics data. You can detect and predict antimicrobial resistance in genomic data from isolates and microbiome samples. You will get access to a suite of new tools for binning and functional annotation of assembled contigs, a new AMR profiling tool based on ShortBRED[1] suited for unassembled microbiome data, a new pipeline for assembling and annotating metagenomics samples, and an implementation of DIAMOND for gene annotation that has been shown to be significantly faster than BLAST without loss of accuracy. These new features come in addition to the exciting new improvements to CLC Genomics Workbench 12.

Below, we introduce you to two useful tools: PointFinder, used to detect chromosomal point mutations in bacterial genomes, and ShortBRED, used to detect and quantify the presence of antibiotic resistance genes directly from unassembled metagenomics data.

Find Resistance with PointFinder

PointFinder is a new tool that enables the detection of chromosomal point mutations in bacterial genomes (both finished references and draft assemblies). Its successful use was first published by Zanakri et.al. [2]. As PointFinder gained popularity and its usefulness was encouraging, we decided to implement the PointFinder tool within the latest release of CLC Microbial Genomics Module. With the new CLC tool, Find Resistance with PointFinder, you will be able to detect known resistance mediating mutations positioned in drug targets. The tool relies on the PointFinder database of known resistance causing mutations in common bacterial pathogens, available for download directly within the software. You will also be able to directly link your results to known classes of antimicrobials via ARO classes and EMBL-EBI ontology.

Find Resistance with ShortBRED

ShortBRED is a tool used for detecting and quantifying the presence of antibiotic resistance genes directly from unassembled metagenomics data. ShortBRED is based on the approach taken by Kaminski et.al. (2015) in the popular ShortBRED pipeline, and works by running DIAMOND against a database of well characterized peptide markers for antimicrobial resistance. The tool reports the abundance of these markers in your shotgun data, and groups them by antibiotic class. The CLC tool Find Resistance with ShortBRED is now also part of CLC Microbial Module 4.0. The peptide marker database is based on ARG-ANNOT [3] and can be downloaded directly from the module.

These are only two of the many other new features we have included in the latest Microbial Genomics Module. We will sharing with you over the coming months insights into their use and their importance in surveillance and source tracing of antimicrobial resistant bacteria and resistance mechanisms.

We invite you to download a 14-day free trial of CLC Genomics Workbench 12 and Microbial Genomics Module.

 

References

  1. Kaminski J, Gibson MK, Franzosa EA, Segata N, Dantas G, Huttenhower C. High-Specificity Targeted Functional Profiling in Microbial Communities with ShortBRED (2015). PLoS Computational Biology 11 (12), e1004557.
  2. Zankari E, Allesøe R, Joensen KG, Cavaco LM, Lund O, Aarestrup FM (2017). PointFinder: A Novel Web Tool for WGS-Based Detection of Antimicrobial Resistance Associated with Chromosomal Point Mutations in Bacterial Pathogens. J Antimicrobial Chemotherapy 72 (10), 2764–68.
  3. Gupta SK, Padmanabhan BR, Diene SM, Lopez-Rojas R, Kempf M, Landraud L, Rolain JM. ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob Agents Chemother. 2014;58(1):212-20.