Reconstructing paleoenvironments using metagenomics

Rutger Vos

Outline

• About Naturalis Biodiversity Center

• NBC's facilities and expertises

Ancient DNA lab

Barcode lab

Informatics focus group

• Metagenomics and paleoecology

• Use case: The mammoth's last meal

• NGS@Naturalis

• Pipeline development

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Naturalis Biodiversity Center

• With 37 million specimens, NBC holds one of the largest natural history collections in the world

• More than just a museum, NBC is an expert center specializing in:

Species identification

Trait harvesting

Impact modeling

Ecological intensivation

6 February 2013Metagenomics approaches and data analysis

Ancient DNA lab

• The ancient-DNA facility is equipped for recovering DNA from plant and animal material from museum collections and fossils.

• It permits research that would otherwise not be possible, such as the study of ancient populations and museum material.

• The ancient-DNA lab provides an environment where the risk of contamination with contemporary DNA is minimal.

• The facility, a collaboration of IBL, the faculty of archeology and NBC, is unique in the Netherlands

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Barcode lab

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Informatics focus group

• Exploitation of HPC resources

• Dissemination of best practices

• In-house development of research-supporting tools:

NGS data processing

Clustering, BLASTing

Custom pipelines

Visualization

Image analysis

Niche modeling

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HPC infrastructure

• Dell T7500 and T7600 workstations

• Intel® Xeon® Processor (QuadCore, 2.40GHz) x 2

• 128Gb RAM

• TESLA/NVIDIA GPU

• RedHat/Ubuntu Linux

• Always looking for extra numbercrunching power, e.g. from NBIC Galaxy, CIPRES, BioPortal, etc.

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Paleoenvironments

• Reconstructing the paleoenvironment is useful for:

Understanding the dynamics of ecosystem change

Reconstructing pre-industrialization ecosystems

• Many public policy decision-makers have pointed to the importance of using palaeoecological studies as a basis for choices made in conservation ecology

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Metagenomics

• Taxonomic identification is one of the main challenges surrounding metagenomics, and one of NBC’s core strengths

• Conversely, a better understanding of the metagenome feeds back into our other research interests and expertises

• Consequently, a lot of research activity and ongoing capacity building

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Use case: the woolly mammoth's dietary metagenome

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The research programme• To test hypotheses about the structure of the ancient environment

of the woolly mammoth, i.e. productive, continuous grassland steppe or sparsely covered herb tundra

• Finding frozen mammoths with forensically identiable food, parasites, and microorganisms in their gastrointestinal tracts or feces has the potential of adding data to the extinction debate

• To integrate the findings from ancient DNA with those obtained from macro- and micro-fossils

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Lyuba

Cape BlossomYukagir

Permafrost-preserved mammoth remains

"Lyuba"

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• Discovered in May 2007

• One-month old mammoth calf

• Age: 41,910 ± 550 YBP

• Very well-nourished, milk-fed

The Yukagir mammoth

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• Male woolly mammal

• Discovered in 2002

• Very well preserved in the permafrost

• Age: 18,560 ± 50 YBP

• Head, front legs, parts of stomach and intestinal tract

• Last meal still preserved

The Cape Blossom mammoth dung

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• Produced during the cold season

• Found among a partial skeleton

• Exact site unknown

• Age: 12,300 YBP

DNA extraction and sequencing

• In all studies, macro-fossils (stems, leaves, seeds), micro-fossils (pollen) and ancient DNA were compared

• DNA was extracted in the ancient DNA facility using multiple extraction protocols

• Several commonly-used markers were amplified (trnL, rbcL, nrITS1)

• Sanger sequencing was done on an ABI 3730xl

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Data analysis

• Sequences were assembled using Sequencher

• Taxa were assigned using a combination of GenBank BLAST searches and phylogenetic inference

• BLAST hits were only accepted if they covered the full query sequence and differed by at most 1 nucleotide

• Phylogenetic placement was determined on the basis of bootstrap support (1000 replicates using paup*)

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Findings

• Ancient DNA could assign 7 ("Lyuba"), 12 ("dung") and 8 ("Yukagir") plant families, with several determinations down to genus level

• Molecules complemented and confirmed fossils

• Identified vegetation composition is generally supportive of a productive "mammoth steppe"

• Micro-fossils of specific dung fungi showed that mammoths appear, unlike elephants, to be habitually coprophagous

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Next generation applications

• The results of the mammoth research so far have been obtained using Sanger sequencing

• Similar, as yet unpublished, research is being undertaken with the newly acquired IonTorrent "sequencing by synthesis" platform

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Marcel Eurlings at Naturalis

IonTorrent chip generations

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IonTorrent data pre-processing workflow

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Filter out short reads

Splice out low phred scores

Split by primer

sequence

Split by adapter

sequence

FASTA for downstream analysis

Taxonomic identification pipeline

• Taxonomic identification of the contents of samples is a generic problem for which we have developed a re-usable pipeline

• It replicates some of the functionality of QIIME but integrates more conveniently in our HPC configuration

• Requirements:

Python 2.7 or 3.2

Biopython 1.58

NCBI-Blast-2.2.25+

Clustering programs, e.g. TGICL, Usearch, Octupus, cd-hit

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Pipeline steps

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Optional: tag FASTA for provenance retracing across files

Cluster sequences into OCTUs of at least 10 reads

Pick exemplar sequence (random, consensus or hybrid)

BLAST exemplar sequences (local or remote)

Optional: retrace provenance

Report

Pipeline extensions

• NBC frequently deals with samples that may contain materials from endangered species, for example:

Putative FSC wood

Traditional Chinese medicine

Incense

• We are therefore extending the taxonomic identification pipeline to check automatically whether any taxa from the sample are listed in CITES appendices

• This, however, poses additional challenges of taxonomic name reconciliation

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Other metagenomics work

• Phylogenies from metagenomic sequence data can grow to immense sizes

• For example, the GreenGenes 16S rRNA tree has ~400k tips

• We are developing novel algorithms for pruning these trees using (Google’s) MapReduce programming model

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Acknowledgements

• I am grateful to:

• Dr. Barbara Gravendeel for her input in developing this talk

• Youri Lammers for his great working in developing a well-documented taxonomic identification pipeline

• And to NBIC for giving me the opportunity to present this story

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Thank you for listening