Metabarcoding

Sample Collection of Swabs

  1. Select sites for sampling according to your experimental hypothesis and design
  2. Record surrounding environment (i.e., sources of human influence, temperature, etc.). Take the exact coordinates using your phone’s compass and record them in a database.
  3. Swab from 4 spots within a 1m2 at the chosen sites.
    • Note, if swabbing from smaller sites, such as shoes or doors, you should use just one or two swabs and try to cover as much of the surface as possible. Take note of this.
  4. Wear gloves and take precautions to avoid contaminating the site or the swabs from your skin or hair, etc.
  5. Dip a sterile swab into sterile swab solution
  6. Swab an area the size of your palm
  7. Place swab into a sterile and labeled 1.5 ml centrifuge tube and cut the stick
  8. Add 0.5 ml of swab solution to the 1.5 ml tube the swabs and vortex for 1 minute to release samples from swab
  9. Follow solid sample protocol below to extract DNA

DNA isolation

DNA from environmental samples can be performed using filtration of water to capture microbes and sample environmental DNA (eDNA). Water filtration can be performed using 0.45μm filters in general as filters tend to clog. Serial filtration through 0.45μm and 0.22 μm may also be performed. Solid samples such as soil , sand, or swabs may be analyzed similar to filters using a bead beating protocol.

Water Filtration Protocol

Protocol with DNeasy PowerWater Kit (Cat. No. / ID: 14900-100-NF)  and Pall Water filters 0.22 μm (VWR:28143-542) or 0.45 μm (VWR: 55095-060)

  1. 250-500ml water samples filtered through 0.45 μm filters (>250ml)
  2. Filter stored in 50ml conical tubes in -20°C
  3. PowerWater DNA Extraction as directed
  4. Store 100μl eluent with filter columns in -20°C

Solid Sample Protocol

Protocol with ZymoBIOMICS DNA Microprep Kit (D4301)

  1. Place swab tip or sample into bead beating tube
  2. Follow protocol as directed
  3. Store eluent with filter columns at -20°C

16S PCR Reaction

Modified 16S protocol from the Earth Microbiome Project.
PCR reaction mixture
Reagent
Volume
PCR-grade water
10.5 µL
PCR master mix (2x)
12.5 µL
Indexed Primers (should have enough of each indexed primer set for two reactions in case you need to repeat some).
1 µL
Template DNA
1 µL
Total reaction volume
25.0 µL
Temperature
Time, 96-well
Time, 384-well
Repeat
94 °C
3 min
3 min
Hold
94 °C
45 s
60 s
35x
50 °C 60 s 60 s
72 °C
90 s
105 s
72 °C
10 min
10 min
Hold
4 °C
Hold

12S Fish Metabarcoding

eDNA protocol for filtered water to detect fish.

PCR reaction mixture
Reagent
Volume
PCR-grade water
6.5 µL
PCR master mix (2x)
12.5 µL
Indexed Primers (should have enough of each indexed primer set for two reactions in case you need to repeat some)
1.0 µL
Template DNA (fish DNA is much less abundant than microbes)
5 µL
Total reaction volume
25.0 µL
12S PCR program uses a lot of cycles to increase signal, which will make things even less quantitative than with fewer cycles.
Temperature
Time, 96-well
Time, 384-well
Repeat
95 °C
3 min
3 min
Hold
95 °C
20 s
30 s
40x
52 °C
20 s
30 s
72 °C
20 s
30 s
72 °C
5 min
5 min
Hold
4 °C
Hold

Metabarcoding Analysis

Metabarcoding utilizes high throughput sequencing that produces FASTQ files. These files contain numerous reads that also contain the sequence quality information for each read. The use of a data analysis pipeline assists in cleaning up poor quality reads, demultiplexing the parallel sequencing reactions and providing statistics of defined taxonomic units. One highly robust pipeline used is the Quantitative Insights Into Microbial Ecology (QIIME). A useful tutorial for QIIME2 to demonstrate its complexity can be seen at https://docs.qiime2.org/2022.2/tutorials/moving-pictures/.

To facilitate analysis, Students will be using a web-based interface for QIIME2 through the DNAsubway.

Feature Identification of Amplicons

PCR amplicons of metabarcoding DNA samples are identified through the use of high-throughput sequencing (typically Illumina). The sequences undergo a series of steps which include quality cut-offs. Areas of low quality are trimmed from the ends of sequences so that analysis can occur. Although these sequences are from the same gene region, they contain variations that make them identifiable as distinct taxa. These differences are called Amplified Sequence Variations (ASVs). An algorithm like DADA2 may be employed in the analysis pipeline to group similar sequences into clusters of representative sequences as “features“, in the computer science lingo . In the former language, these features would be referred to as Operational Taxonomic Units (OTUs). With QIIME2, the identified features are later given proper taxonomic identification through querying properly curated databases such as SILVA (16S/18S and 23S/28S), UNITE (fungal ITS) or PLANiTS (plant ITS).

References

  • Bolyen, E., Rideout, J.R., Dillon, M.R. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37, 852–857 (2019). https://doi.org/10.1038/s41587-019-0209-9
  • Caporaso JG, Lauber CL, Costello EK, Berg-Lyons D, Gonzalez A, Stombaugh J, Knights D, Gajer P, Ravel J, Fierer N, Gordon JI, Knight R. Moving pictures of the human microbiome. Genome Biol. 2011;12(5):R50. doi: 10.1186/gb-2011-12-5-r50. PMID: 21624126; PMCID: PMC3271711.
  • Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016 Jul;13(7):581-3. doi: 10.1038/nmeth.3869. Epub 2016 May 23. PMID: 27214047; PMCID: PMC4927377.