Metagenomics and cloud_computing_london_january_2014_era7_bioinformatics

A New Era in Diagnostic Microbiology Pathogen Genomics. Whole Genome Sequencing
15 January 2014. The Royal College of Pathologists.

A New Cloud Computing System for Massive
Analysis of Reads from Metagenomics Samples

http://ohnosequences.com
www.era7bioinformatics.com

The Royal College of Pathologists
15 January 2014

A New Cloud Computing System for Massive Analysis of Reads from
Metagenomics Samples

- A bit of context:

- The metagenomics bioinformatics challenge:

• What is Era7

• High computational cost

• What is Oh no sequences! Research group

• Bining for reducing computation

• Research lines / Research projects

• Reducing reference database

- Clonal cultures versus Metagenomics
- Microbiome

- MG7

- Microbiome in health and disease

• Cloud computing

- Metagenomics in a clinical sample

• MG7 algorithms and pipeline

- 16S and shotgun metagenomics

• Lowest Common Ancestor assignment

- Metagenomics for detection of viruses

• MG7 uses Graph databases

- Metagenomics for detection of bacteria

• MG7 uses NCBI taxonomy tree

MG7 for metagenomics analysis

15 January 2014

A bit of context



15 January 2014

What is Era7 Bioinformatics



15 January 2014

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Research driven SME
Open Source
Cloud Computing
Next Generation Sequencing



15 January 2014

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Bacterial Genomics projects
Comparative Genomics
Metagenomics
Microbiome
RNA-seq (and Dual RNA-seq)
Cancer Genomics
Big Data management and integration



15 January 2014

What is Era7 Oh no sequences!



15 January 2014

A New Cloud Computing System for Massive Analysis of Reads from
Metagenomics Samples
Research Lines:

Software Research Ptojects
• BG7

• Algorithms for assembly

• Bio4j

• Methods for bacterial genome annotation

• Nextmicro

• New Cloud Computing Architectures

• Statika

• Graph Databases for Biological data

• Nispero

• Comparative genomics and bacterial evolution
• Genome Plasticity
• Big Data integration and visualization
• Host Immune System and infection

• MG7
(All of them are Open Source
AGPLv3 projects)

MG7 for metagenomics analysis

15 January 2014

Traditional microbial genome sequencing
relies upon clonal cultures,
but the new era of genomics is facing a new
challenge: the metagenomics analysis



15 January 2014

Microbiome analysis is possible by
metagenomics approaches.
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Health and Disease
Therapeutic Interventions
Transplant
Immune system



15 January 2014

Microbiome in Health and Disease
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Inflamatory Bowel Disease
Diabetes
Obesity
Cardiovascular Disease
Colon Cancer



15 January 2014

Modifying the Microbiome
• Prebiotics
• Probiotics
• Microbiome Transplant (Clostridium Difficile)



15 January 2014

For bacteria, it should be reminded that only
a small fraction of the phylogenetic diversity
of Bacteria and Archaea is represented by
cultivated organisms



15 January 2014

Metagenomics has the potential to
revolutionize pathogen detection in public
health laboratories by allowing the

simultaneous detection of all microorganisms
in a clinical sample



15 January 2014

Metagenomic analysis after PCR amplification
of different gene regions

Shotgun Metagenomics



15 January 2014

Metagenomic analysis after PCR amplification
of different gene regions:
• 16S rRNA
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Gyrase
Ribosomal proteins
Elongation Fctors
RNA Polymerase
……….

16S metagenomics tells us about microbial diversity and
relative abundance of species and taxa


15 January 2014

Shotgun Metagenomics
Shotgun metagenomics is a much more massive approach
able to inform about the functional profile of the different genes
present in the sample and even to obtain assembled genomes
if the sample is not very complex



15 January 2014

Thechnology
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454 in the past

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illumina today (approaches overlaping paired reads)

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Preprocessing steps very important



15 January 2014

For viruses:
Unbiased high-throughput sequencing approach is useful for
directly detecting pathogenic viruses without advance genetic
information.
The use of metagenomics for virus discovery in clinical
samples has opened new opportunities for understanding the
aetiology of unexplained illness



15 January 2014

For Bacteria:
Metagenomics will probably serve to identify new pathogens,
and new infections caused by consortiums.
In chronic infections metagenomics will give us information
about the relevance of biofilms and other bacterial
organizations that would be important in such infections..
Microbiome analysis has been one of the most important
applications of metagenomics.


15 January 2014

For Bacteria:
As an example, metagenomics for Mycobacterium infections
have demonstrated undetected, plural, strains in the same
patient



15 January 2014

The Bioinformatics challenge
Metagenomics has a high computational cost

1. One approach is to reduce the need of computation
2. The other is to be more efficient



15 January 2014


1. Reducing the computation
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Binning (clustering) the reads 16S and Shotgun.

Operational Taxonomic Units (OTUs) in 16S



15 January 2014


1. Reducing the computation
•

Reducing the size of the reference database: It
is frequent to use only the complete bacterial
genomes Shotgun



15 January 2014


2. The other is to be more efficient:


MG7


15 January 2014

Cloud computing can solve the problem of massive data
analysis providing scalable, real time, on demand computing
for metagenomics data analysis.
However, Cloud Computing infrastructure is not easy to
manage and publicly available software solutions would be
needed to extend the use of cloud for the analysis of huge
metagenomics data sets.


15 January 2014

MG7
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Based in Cloud Computing (AWS)
Parallel computation
Each read is compared with the complete database:
• No binning, all the reads
• All the known sequences (nt database) for shotgun
NCBI taxonomy
Graph database for analyzing the assignment results



15 January 2014

MG7
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EC2
S3
SQS
SNS
……



15 January 2014

MG7
Based in Cloud Computing (AWS) parallel computation
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A Cloud Master machine creates tasks and set Qeues
A set (hundreds, it could be thousands) of Cloud
instances (usually micro cloud EC2 instances) are
launched
After the parallel computation, results are modeled in a
graph database. This allows to further analysis



15 January 2014

https://github.com/pablopareja/MG7/wiki



15 January 2014

https://github.com/pablopareja/MG7/wiki


Data Model for the Graph DatabaseNeo4j


15 January 2014

MG7
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Storage , another challenge. AWS Cloud is very useful:
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S3 for inmediate access

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Glacier for archiving .



15 January 2014

MG7
Each read is compared with the complete database:
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Direct Assignment Best Blast Hit It can be done by:
• E value
• Depending on similarity % and length of the hit

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Lowest Common Ancestor



15 January 2014

MG7
First step:

We start from a set of nodes with an
arbitrary length – 4 in this sample,
which are spread through the
taxonomy tree



15 January 2014

MG7
Second step:
We fetch then the first node from the
set and calculate its whole ancestor list
to the main root of the taxonomy.



15 January 2014

MG7
Third step:
Now that we have the list, we take the
second node of the set and check if it’s
contained in it, if not, we keep going up
through its ancestors until we find a
marked node. Once it has been found,
we get rid of the previous elements in the
list (if any) so that they are not taken into
account for the next iterations in the
algorithm.


15 January 2014

MG7
Fourth step:
We keep going trough our node set,
and node C also removes some
elements of the list…



15 January 2014

MG7
Fifth step:
Finally we reach the last node of our
set, but no element is removed from
our list as a result.



15 January 2014

MG7
Here we have our lowest common
ancestor!



15 January 2014

MG7
All the known sequences (nt database) for shotgun
Nt database is the largest nucleotide database.
It contains nucleotide sequences from all the organisms.
This is important to detect:

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Unexpected organism
Contamination



15 January 2014

MG7
NCBI taxonomy
This Taxonomy is probably the best and most
comprehensive
A Graph Database is very appropriate to model a
Taxonomy tree



Thanks
for your attention!

Marina Manrique
Eduardo Pareja-Tobes
Pablo Pareja-Tobes
Raquel Tobes
Eduardo Pareja

epareja@era7.com


Metagenomics and cloud_computing_london_january_2014_era7_bioinformatics

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Metagenomics and cloud_computing_london_january_2014_era7_bioinformatics