Merge pull request #5237 from galaxyproject/create-pull-request/patch…

…-1723891399

[Google Form] New Recording Submission! Foodborne pathogen detection

topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md

@@ -1,50 +1,54 @@
 ---
 layout: tutorial_hands_on
-
-title: "Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne Edition"
+title: Pathogen detection from (direct Nanopore) sequencing data using Galaxy - Foodborne
+  Edition
 subtopic: metagenomics
 tags:
-    - microgalaxy
-    - Nanopore data analysis
-    - Pathogens detection
-    - Phylogenetic tree
-    - Heatmap
-    - cyoa
+- microgalaxy
+- Nanopore data analysis
+- Pathogens detection
+- Phylogenetic tree
+- Heatmap
+- cyoa
 level: Introductory
-zenodo_link: "https://zenodo.org/record/11222469"
+zenodo_link: https://zenodo.org/record/11222469
 questions:
-    - What are the preprocessing steps to prepare ONT sequencing data for further analysis?
-    - How to identify pathogens using sequencing data?
-    - How to track the found pathogens through all your samples datasets?
+- What are the preprocessing steps to prepare ONT sequencing data for further analysis?
+- How to identify pathogens using sequencing data?
+- How to track the found pathogens through all your samples datasets?
 objectives:
-    - 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
-time_estimation: "4h"
+- 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
+time_estimation: 4h
 contributions:
-   authorship:
-    - bebatut
-    - EngyNasr
-    - paulzierep
-   editing:
-    - hrhotz
-    - wm75
-   funding:
-    - gallantries
-    - eosc-life
+  authorship:
+  - bebatut
+  - EngyNasr
+  - paulzierep
+  editing:
+  - hrhotz
+  - wm75
+  funding:
+  - gallantries
+  - eosc-life
 redirect_from:
-    - /topics/metagenomics/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial
+- "/topics/metagenomics/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial"
 edam_ontology:
-- topic_3174 # Metagenomics
-- topic_3305 # Public health and epidemiology
-- topic_0637 # Taxonomy
-- topic_0196 # Sequence assembly
-- topic_0634 # Pathology
-- topic_0080 # Sequence analysis
-
+- topic_3174
+- topic_3305
+- topic_0637
+- topic_0196
+- topic_0634
+- topic_0080
 recordings:
 - youtube_id: gQHb_jkj-Z0
   date: '2023-05-01'
@@ -54,10 +58,21 @@ recordings:
   - EngyNasr
   captioners:
   - EngyNasr
+- youtube_id: rGP-BKYwUbc
+  length: 1H55M
+  galaxy_version: '24.1.2.dev0 '
+  date: '2024-08-16'
+  speakers:
+  - EngyNasr
+  captioners:
+  - EngyNasr
+  bot-timestamp: 1723837296
+
 
 ---
 
 
+
 Food contamination with pathogens is a major burden on our society. In the year 2019, foodborne pathogens caused 137 hospitalisations in Germany [(BVL 2019)](https://www.bvl.bund.de/SharedDocs/Berichte/10_BELA_lebensmittelbed_Krankheitsausbruechen_Dtl/Jahresbericht2019.pdf?__blob=publicationFile&v=4). Globally, they affect an estimated 600 million people a year and impact socioeconomic development at different levels. These outbreaks are mainly due to _Salmonella spp._ followed by _Campylobacter spp._ and Noroviruses, as studied by the [__Food safety - World Health Organization (WHO)__](https://www.who.int/publications/i/item/9789241565165).
 
 During the investigation of a foodborne outbreak, a microbiological analysis of the potentially responsible food vehicle is performed in order to detect the responsible pathogens and identify the contamination source. By default, the [__European Regulation (EC)__](https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2005:338:0001:0026:EN:PDF) follows ISO standards to detect bacterial pathogens in food: pathogens are detected and identified by **stepwise cultures** on selective media and/or **targeting specific genes with real-time PCRs**. The current gold standard is Pulsed-field Gel Electrophoresis (PFGE) or Multiple-Locus Variable Number Tandem Repeat Analysis (MLVA) to characterize the detected strains. These techniques have some disadvantages.