Full-Community Metabarcoding: An Ecosystem Map

CBIOMES Annual Meeting 2022

Jesse McNichol (he/him) : PhD, Biological Oceanography

Postdoctoral Scholar, University of Southern California

Comprehensive (primers target all cellular life)
Sensitive with deep sequencing
Specific with "denoising" algorithms

Microbe art: @claudia_traboni

Full-Community Metabarcoding: The Promise

Full-Community Metabarcoding: The Challenges

✓

Biases exist, but are consistent & correctable
Extraction bias for complex marine mixtures unknown, needs validation (BioGEOSCAPES)

1. Led in silico method optimization

Universal primers for barcoding work almost* perfectly across global oceans

2. Developed collaborations and generated data

Global metagenomes

Over 800 globally-distributed barcode samples allow model-data intercomparison

Craig Carlson, UCSB

Full-Community Metabarcoding: Progress

Microbe art: @claudia_traboni

p16S

e16S

18S

Comprehensive community data from single PCR assay:
- p(rokaryotic)16S
- e(ukaryotic)16S
- Eukaryotic 18S

Full-Community Metabarcoding: Applications

Microbe art: @claudia_traboni

18S

p16S

e16S

Comprehensive community data from single PCR assay:
- p(rokaryotic)16S
- e(ukaryotic)16S
- Eukaryotic 18S

Full-Community Metabarcoding: Applications

Craig Carlson, Elisa Halewood, UCSB

Fraction of 18S amplicon sequences

16S

plastid 16S

18S

Jan-Feb 2005

Feb-Mar 2006

With deep sequencing, good coverage for all 3 domains

Full-Community Metabarcoding: Applications

Taxa-specific activity

Full-Community Metabarcoding: An Ecosystem Map

"eDNA"

Full-Community Metabarcoding: Synergies

Research questions

An in silico global phytoplankton model (DARWIN project, MIT)

How robust are model predictions?
What is the function of microbial "black box"?
Can models and data help predict consequences of climate change?

How well do imaging-based methods (flow cytometry, imaging flow cytobot) align with 3-domain metabarcoding?

Advantages:

Simple but impactful
Simons CMAP database makes possible
Extend by mining global distribution data

Kalmbach et al. (2017), arXiv:1703.07309v1

Example research project #1

Example research project #2

How can we infer changes in microbial community composition change across decadal time-scales using barcoding data from different regions of SSU rRNA?

Advantages:

"Rosetta stone" allows intercomparisons, FISH probe design from barcodes
Address previously impossible questions
"Data science" experience for student/postdoc

Dueholm et al. (2020) mBio, e01557-20

Database of full-length 16S rRNA

Taxonomy (CARD/HCR-FISH) / transcription (FISH-TAMB)
Respiration, cell viability (RSG); Polyphosphate content (DAPI)

Automatic cell-sorting + environmental databases = taxon-specific activity or genetic potential measurements

Many uses for sorted cells:

Taxon-specific isotope uptake
Mini-metagenomes with few cells
Cell isolation for cultivation

Pjevac et al (2019) 10.1111/1462-2920.14739

Multiple sorting axes now possible

Microscale cell sorting enabled by new databases

Applications "at sea"

"Rosetta stone" => FISH probes:
- Cell enrichment for mini-metagenomes
- Visualize predicted symbioses / other ecological interactions
- Measure cell-specific traits such as biovolume
Attempt cultivation of "microbial dark matter":
- Flow cytometry with "live stains"
- Enrichment experiments

Intercalibration, intercomparison
Methods development
Interdisciplinary by nature
Lots of room for young scientists to make major contributions

BioGeoSCAPES

Motivated by goal of understanding the Earth System

We anticipate that as trait-based biogeography continues to evolve, micro- and macroorganisms will be studied in concert, establishing a science that is informed by and relevant to all domains of life.” -Green, Bohannan, and Whitaker, Science (2008)

Ecosystem-centered research

Sebastián & Gasol (2019), 10.1098/rstb.2019.0083 ; McNichol et al (2018) 10.1073/pnas.1804351115 ; Zehr (2015) 10.1126/science.aac9752; Bramucci et al (2021) 10.1038/s43705-021-00079-z