Next-generation or High-throughput Sequencing

• Define next-generation sequencing (NGS) or high-throughput sequencing. Massively parallel sequencing by synthesis (non-Sanger-based).
  • Examples: Illumina MiSeq is “2nd generation,” Nanopore (https://nanoporetech.com/) is “3rd generation”  PacBio sequel (https://www.pacb.com/).

• Illumina: Sequencing by synthesis, building DNA model and cataloging sequence by fluorescence
  • General Steps/ Method
    • PCR desired gene (optional)
    • Tag PCR products with bar codes and tags
    • Both forward and reverse reads are obtained but forward usually has greater quality
      • This is “paired-end” sequencing. Illumina also does “single-read” which is only one direction. Paired-end allows for longer amplicons to be sequenced
    • Generate library based on DNA or PCR amplicons
      • Library in sequencing refers to a collection of DNA fragments that may be from a chromosome or genomes that have been sheared or digested to a certain size range.
    • Sequence on MiSeq
    • Analyze via software
  • Pitfalls/Limitations:
    • Read length
    • Read 2 has less quality (Q scores). See this for Illumina Q scores: https://www.illumina.com/documents/products/technotes/technote_Q-Scores.pdf
    • Storage and utilization of great amount of generated data
    • Expensive (run ~$2,000, reagents and barcodes $900, QIAGEN Smart control $100)’
  • Benefits/Advantages
    • Lots of reads
    • Can generate sequence data from multiple species in a given sample
    • Easy to use
    • Fast results
    • Barcoded library to separate pooled samples using bioinformatics as necessary
  • Previous methods
    • Capillary required individual bacteria to be grown and cultures, thus individually sequenced.
    • Sanger Sequencing: terminally tagged nucleotides
      • Required primers
  • We used “Phased primers” for QIAseq 16S/ITS (for higher diversity in samples)
    • Source: https://www.qiagen.com/us/products/next-generation-sequencing/qiaseq-16s-its-index-kits/#orderinginformation

• Nanopore: Still massively parallel, uses many pores to read each strand where each NT disrupts the ionic current and leaves a trace signature
  • Trace files: measures ionic disruptions to determine base present.
  • Read speed: 400bp/s
  • Sequence bins: add the sample to beads to fragment DNA then add adaptor (from Nanopore) that enables barcode identification to separate samples by compost pile.
  • General Steps/ Method
  • Pitfalls/Limitations:
    • Quality is less/ questionable (Q~ 11)
    • Storage and utilization of great amount of generated data
  • Benefits
    • Read length (longest 1mil bp)
    • Generates quickly across long strands
    • Completely mobile
    • Cheap(er) equipment ($900 flowcell and $500 reagents)
    • Shotgun sequencing
  • Compare/Contrast w/ Illumina
    • Similar:
      • Massively parallel
    • Different:
      • Measuring disruption in ionic current → get trace files → software determines what base pairs
      • Using a pore and stringing DNA through it
      • Data quality
• 16S has both highly conserved and variable regions. This allows a single primer set to be used to identify many different species based on genomic variations.

Metagenomics and Microbiomes

• Define metagenomics.
  • Study of genomic samples from a defined microbial community
    • Genes that are present in the sample (shotgun sequencing)
    • Amplicons (16S, ITS)
  • It could also be defined as the study of microbial genomics obtained directly from an environmental sample (eDNA) using sequencing approaches.

• • List two applications of metagenomics in health, industry, or medicine.

• Role of microbiome in humans: How do the communities of microbes affect our health?

• • Is there a correlation of lifestyle to gut microbiome?
  • Functional metagenomics for enzyme discovery
  • Finding the relationship between environmental data and metadata
  • Time-series analysis (reminds me of the composting article: https://www.sciencedirect.com/science/article/pii/S1369527415000478)

“Dirt is Good” by Jack Gilbert and Rob Knight

Microbes probably associated with certain auto-immune diseases based on variations and commonalities with/between households

American Gut Study

• Objective: Establish relationships (correlation/associations) between bacteria with body and lifestyle, diseases, interactions, diet, etc.
• Observational Study via Survey and Sample collection
• Crowdsource for the American public (e.g., hospitals, public spaces, ) to have access to microbiome within themselves.

Microbiome: the community of microbial genomes that live on/within organisms. ALT: Collection of genomes…

Microbiota: Depending on the author, interchangeable with the microbiome

Agriculture is just beginning research into the effect of microbes on plant development. The potential to identify microbes that assist with drought tolerance, heat stress, defense, and nutrient acquisition could be used to improve production as extreme weather becomes more prevalent.

Applications in the industry:

Biofuel industry for example, is always looking at a consortium of organisms that can generate methane, ethanol, or other compounds. Using metagenomics we can assess those microbes and characterize that microbial community.

Food industry, for instance, is looking at microbes performing fermentation and how to characterize or manipulate that community to improve their products.

Three major findings from ARTICLE 1:

Principal Antunes et al. 2016. Microbial community structure and dynamics in thermophilic composting viewed through metagenomics and metatranscriptomics. Scientific Reports. 6. Article number: 38915.

1. The abundance of different organisms changed over time
2. The potential identification of a new bacteria
3. The workflow/method in paper 1 may be useful for our lab work or future projects.

Approaches used in the paper:

An introduction and workflow of metagenomics from an online workshop: https://youtu.be/LUS62N7tSUU