Working with Bacterial Genomes

About the course  |  Intended audience  |  Prerequisites  |  Content details

About the course

Bacterial genomics has become an essential approach for studying microbial diversity, evolution, epidemiology, and antimicrobial resistance. This course provides a practical introduction to analysing bacterial genomes, primarily using Illumina-sequenced samples.

Participants will learn how to select appropriate analysis strategies based on the genomic diversity of different bacterial species and will gain hands-on experience using both de novo assembly and reference-based mapping approaches to reconstruct bacterial genomes. The course covers standardised workflows for genome assembly and annotation, together with approaches for assessing the quality of assembled genomes.

Participants will also learn methods for bacterial typing, including MLST, cgMLST, and PopPUNK, and will construct phylogenetic trees using whole genome and core genome alignments. The course further covers methods for estimating time-scaled phylogenies and detecting antimicrobial resistance genes using a range of species-specific and general-purpose tools.

Examples throughout the course are drawn from Mycobacterium tuberculosis, Staphylococcus aureus, and Streptococcus pneumoniae, providing participants with practical experience that can be applied across a range of bacterial species.

By the end of the course, participants should be able to conduct bacterial genomics analyses from raw sequencing data through to phylogenetic interpretation and antimicrobial resistance profiling.

Teaching is primarily hands-on, with short presentations and demonstrations introducing the concepts and methods needed to analyse bacterial genomic data.

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Intended audience

This course is suitable for:

• biologists interested in microbiology and prokaryotic genomics
• researchers interested in antimicrobial resistance and pathogen surveillance
• participants who want practical experience with bacterial genomics analysis workflows
• researchers seeking to apply genomic approaches to the study of bacterial evolution and epidemiology

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Prerequisites

Participants should have:

• a basic understanding of high-throughput sequencing technologies
• a working knowledge of the UNIX command line
• a working knowledge of R

The following experience is recommended:

• a basic knowledge of phylogenetic inference methods
• running analyses on High Performance Computing (HPC) clusters

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Content details

The course covers the following topics:

• Introduction to bacterial genomics workflows
  Introduces the principles of bacterial genomics analysis and discusses how to select appropriate workflows based on the genomic diversity of different bacterial species.
• Quality control of sequencing data
  Covers quality assessment of raw sequencing data using the avantonder/bacQC pipeline and introduces approaches for evaluating sequencing data prior to downstream analyses.
• Genome assembly and annotation
  Introduces both de novo assembly and reference-based mapping approaches for reconstructing bacterial genomes. Participants will use standardised workflows for genome assembly, annotation, and quality assessment using the avantonder/assembleBAC pipeline.
• Whole genome and core genome alignments
  Covers approaches for generating whole genome multiple sequence alignments using nf-core/bactmap and core genome alignments using Panaroo.
• Recombination detection
  Introduces methods for identifying and removing recombinant regions from bacterial genome alignments using Gubbins.
• Phylogenetic analysis
  Covers the construction of maximum likelihood phylogenetic trees using IQ-TREE and demonstrates how phylogenetic methods can be used to investigate evolutionary relationships between isolates.
• Time-scaled phylogenetic inference
  Introduces methods for estimating time-scaled phylogenies using TreeTime and demonstrates how temporal information can be incorporated into phylogenetic analyses.
• Bacterial typing and genomic epidemiology
  Covers approaches for bacterial typing using MLST, cgMLST, and PopPUNK and demonstrates how these methods can be used for genomic epidemiology and strain surveillance.
• Antimicrobial resistance analysis
  Introduces methods for detecting antimicrobial resistance genes using species-specific tools such as TB-Profiler, online resources such as Pathogenwatch, and the nf-core/funcscan pipeline.

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