Module: Microbial Analysis

This lecture briefly introduces 16S sequencing, a popular technique used for taxonomic profiling of microbial communities.

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This lecture briefly introduces 16S sequencing, a popular technique used for taxonomic profiling of microbial communities.

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• Analyze of 16S rRNA sequencing data using the mothur toolsuite in Galaxy
• Using a mock community to assess the error rate of your sequencing experiment
• Visualize sample diversity using Krona and Phinch

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• Explain what taxonomic assignment is
• Explain how taxonomic assignment works
• Apply Kraken and MetaPhlAn to assign taxonomic labels
• Apply Krona and Pavian to visualize results of assignment and understand the output
• Identify taxonomic classification tool that fits best depending on their data

This video will show you the full process of sequencing a bacterial genome using the Oxford Nanopore MinION sequencer.

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Nanopore Sequencing has many applications in a clinical setting. In this lecture, Astrid Heikema discusses how her group at the Erasmus Medical Center uses Nanopore for sequencing of bacterial Genomes.

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This tutorial will guide you through the process of assembling your Nanopore-sequenced bacterial samples and determining the presence of antibiotic resistance genes.

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• Perform Quality control on your reads
• Assemble a genome with Minimap2/Miniasm/Racon
• Determine the structure of the genome(s)
• Scan for antimicrobial resistance genes with Staramr

In this tutorial, we will be presenting a series of Galaxy workflows whose main goals are 1) to agnostically detect pathogens (What exactly is this pathogen and what virulence factors does it carry?) from data extracted directly (without prior cultivation) from a potentially contaminated sample (e.g. food like chicken, beef, etc.) and sequenced using Nanopore, and 2) to compare different samples to trace the possible source of contamination

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• Check quality reports generated by FastQC and NanoPlot for metagenomics Nanopore data
• Preprocess the sequencing data to remove adapters, poor quality base content and host/contaminating reads
• Perform taxonomy profiling indicating and visualizing up to species level in the samples
• Identify pathogens based on the found virulence factor gene products via assembly, identify strains and indicate all antimicrobial resistance genes in samples
• Identify pathogens via SNP calling and build the consensus gemone of the samples
• Relate all samples' pathogenic genes for tracking pathogens via phylogenetic trees and heatmaps

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• Inspect metagenomics data
• Run metagenomics tools
• Identify yeast species contained in a sequenced beer sample using DNA
• Visualize the microbiome community of a beer sample

In this tutorial, we will learn how to run metagenomic assembly tool and evaluate the quality of the generated assemblies. To do that, we will use data from the study: Temporal shotgun metagenomic dissection of the coffee fermentation ecosystem. For an in-depth analysis of the structure and functions of the coffee microbiome, a temporal shotgun metagenomic study (six time points) was performed. The six samples have been sequenced with Illumina MiSeq utilizing whole genome sequencing.

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• Describe what an assembly is
• Describe what de-replication is
• Explain the difference between co-assembly and individual assembly
• Explain the difference between reads, contigs and scaffolds
• Explain how tools based on De Bruijn graph work
• Apply appropriate tools for analyzing the quality of metagenomic data
• Construct and apply simple assembly pipelines on short read data
• Apply appropriate tools for analyzing the quality of metagenomic assembly
• Evaluate the Quality of the Assembly with Quast, Bowtie2, and CoverM-Genome

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. According to the WHO, in 2018 there were 10.0 million new cases of TB worldwide and 1.4 million deaths due to the disease, making TB the world’s most deadly infectious disease.

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Variation in the genome of M. tuberculosis (Mtb) is associated with changes in phenotype, for example drug resistance and virulence. It is also useful for outbreak investigation as the single nucleotide polymorphisms (SNPs) in a sample can be used to build a phylogeny.

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• How should we filter those variants
• How can we predict drug resistance from those variants
• How do we annotate those variants

Metatranscriptomics analysis examines how the microbiome responds to the environment by studying the taxonomic composition and functional analysis of genes expressed by the microbiome, using microbial community RNASeq data and subsequent metatranscriptomics workflows. This workshop will introduce researchers to the basic concepts and tools from the ASaiM-MT workflow. ASaiM-MT provides a curated collection of tools to explore and visualize taxonomic and functional information from metatranscriptomic sequences.

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In this tutorial, the basic workflow for metaproteomics is described, which includes database search, seeking taxonomy information and functional analysis. Related metaproteomics and functional microbiome tools and GTN tutorials are also mentioned in this tutorial.

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• A taxonomy and functional analysis of metaproteomic mass spectrometry data.