Add Introduction to Metagenomics lecture notes

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+* Metagenomics applied to surveillance of pathogens and antimicrobial resistance
+** Week 1
+*** Introduction to Metagenomics
+
+In order to fight against antimicrobial resistance, we need to know where the pathogens and the transmisison routes are.
+
+Metagenomics allows us to identify individuals in a complex sample, using DNA sequences. It is a sequencing-based analysis of genomes contained in an environmental sample.
+
+We need to isolate the genomes of the microbes, the same applies to all microbial genomics techniques, which we'll compare to metagenomics:
+
+**** Microbial genomics
+***** 16S rRNA profiling
+We amplify the 16S ribosomal RNA obtaining as a result an idea of the taxonomic composition of the sample. The 16S analysis offers deep insight, such as presence of low abundance organisms.
+
+Metagenomics is a more generic approach, by randomly amplifying whole genomes we can learn more about the function.
+***** Whole Genome Sequencing (WGS)
+We isolate and cultivate specific microbes from a complex sample. We obtain taxonomic identity information and specific information such as virulence, antimicrobial resistance, etc.
+***** Single Cell Sequencing
+It has the same principles as the previous method and it's used when it's not possible to cultivate the microbe.
+**** Metagenomics project
+
+A metagenomics project involves many steps, we will group them in 2 categories:
+
+***** Laboratory steps
+1. DNA/RNA isolation: RNA is translated to cDNA
+2. Fragmentation: current next generation sequencing methods cannot sequence long fragments (exception: Nanopore sequencing)
+3. DNA sequencing: we obtain files with the sequence and quality information
+***** Data analysis
+- Reads: we analyze directly
+- Binning and assembly
+**** Current challenges
+
+Metagenomics still faces some challenges, mostly due to the sequencing process:
+
+- Sequencing data can belong to the tip of the iceberg (for complex samples)
+- Background DNA sequences can make up a considerable percentage of the data (e.g. host environment)
+- Lack of reference genomes due to novel organisms, although some methods exist to allow us to identify them
+- Low-quality reference genome (contaminant sequences -> false-positive)
+- Quantification of the pathogens is difficult due to the different genome sizes
+- Assembly of reads from different organisms (chimera formation)
+- Unknown function of novel proteins