Embracing Complexity and Diversity: Discovery Metaproteomics of Multiple Microbiomes

using the Galaxy Framework

PRATIK  JAGTAP    

Center  for  Mass  Spectrometry  and  Proteomics,  St.  Paul,  MN  Department  of  Biochemistry,  Molecular  Biology  and  Biophysics,  Minneapolis,  MN  

64th ASMS Annual Conference San Antonio, TX 6th June 2016

AcknowledgementS

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Metaproteomics in Galaxy

• MICROBIOMES / METAPROTEOMICS

• GALAXY WORKFLOWS AS A SOLUTION

• EXAMPLE METAPROTEOMICS PROJECTS

• WHAT’S NEXT?

Microbiome

•  Microbiome (all the genes from microbes residing within the host) can be considered a counterpart to the human genome (all of the host genes).

•  Metagenomics: identifies species present within complex community (16S rRNA and Whole Genome Sequencing).

http://draxe.com/microbiome/

Bond and Wilmes 2015 “Through the application of metaproteomics to different microbial consortia over the past decade, we have learnt much about key functional traits in the various environmental settings where they occur.” Proteomics. doi:10.1002/pmic.201500183.

Metaproteomics Bond and Wilmes 2004 “The large-scale characterization of the entire protein complement of environmental microbiota at a given point in time” Environ. Microbiol. 6, 911–920.

Metaproteomics

Challenges

•  Large metagenomic databases with data from multiple organisms. Peptide sharing / Protein inference across multiple organisms.

•  Interpretation of biological function.

•  Validation of the peptide identification.

•  Disparate tools and multiple processing steps. Proteomics. doi: 10.1002/pmic.201500183.

Solution: Galaxy Platform

Goecks J et al Genome Biol. 2010;11(8):R86.

•  A web-based bioinformatics data analysis platform. •  Software accessibility and usability. •  Share-ability of tools, workflows and histories. •  Reproducibility and ability to test and compare results after

using multiple parameters. •  Ability to assimilate disparate software into integrated

workflows.

Solution: Galaxy Platform

For example, Protein Database Downloader downloads UniProt protein FASTA databases of various organisms.

WEDNESDAY, 6/8 5:45-7:00 PM, ROOM 305 WORKSHOP 14: GALAXY FOR PROTEOMICS DATA

ANALYSIS: AN INTERACTIVE DEMONSTRATION

Software tools can be used in a sequential manner to generate analytical workflows that can be reused, shared and creatively modified.

Solution: Galaxy Platform

Metaproteomic analysis using the Galaxy framework. Proteomics. (2015) doi:10.1002/pmic.201500074.

•  Plaque microcosms were grown from carious lesions in 12 children •  Extensive inter-individual variation in dental plaque composition

Metaproteomics Projects Sucrose-induced dysbiosis in dental caries. Rudney et al., BMC Microbiome DOI: 10.1186/s40168-015-0136-z

NS: Absence of sucrose WS: Presence of sucrose P: Plaque samples

•  Paired design – microcosms grown in presence/absence of sucrose •  Sucrose induces acid production in dental caries (dysbiosis) •  16S rRNA sucrose microcosms retained inter-individual taxonomic variation

RAW data conversion Database generation Database Search against Human Oral Microbiome Database (HOMD) Convert microbial peptide lists to FASTA format BLAST-P Analysis (30K to 60K peptides) MEGAN Analysis

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Metaproteomics Projects Sucrose-induced dysbiosis in dental caries. Rudney et al., BMC Microbiome DOI: 10.1186/s40168-015-0136-z

SEED Functional Analysis

Metaproteomics Projects Sucrose-induced dysbiosis in dental caries.

•  2-D LC-MS/MS Metaproteome was analyzed for taxonomy and function. Rudney et al., BMC Microbiome DOI: 10.1186/s40168-015-0136-z

MEGAN5 Taxonomic Analysis

NS: Absence of sucrose WS: Presence of sucrose

•  Taxonomically-diverse sucrose-pulsed microcosms clustered more closely by function. Function-based changes may be better indicators of dysbiosis

Metaproteomics Projects Sucrose-induced dysbiosis in dental caries.

Samples grown with sucrose

Samples not exposed to sucrose

•  Statistical analysis identified proteins that were expressed at a higher abundance in presence of sugar.

•  Selected reaction monitoring (SRM) was used to quantify conserved peptides from three enzymes whose abundance increased in sucrose-induced dysbiosis: NADP-specific glutamate dehydrogenase (EC 1.4.1.4) ; Ketol-acid reductoisomerase (EC 1.1.1.86) ; L-lactate dehydrogenase (EC 1.1.1.27).

Metaproteomics Projects Ongoing Projects

MEGAN Analysis

729 Microbial Peptides 71 genera. 84 species Function: 336 peptides

assigned to 132 InterPro2GO proteins

•  LUNG TISSUE MICROBIOME: Lung cancer patient tumor samples were compared to healthy adjacent tissue and control tissue samples.

•  Complementary 16S rRNA microbiota sequencing was also performed on these samples. Along with many human peptides, several bacteria peptides and 16S rRNA sequences were identified

Wendt Lab

MEGAN Analysis

776 Microbial Peptides 53 genera. 71 species Function: 232 peptides

assigned to 107 InterPro2GO proteins

• BRONCHOALVEOLAR LAVAGE FLUID

(BALF) MICROBIOME: Microbiome of fluid proximate to the site of lung injury – acquired by using a bronchoscopy procedure – was analyzed.

•  BALF from subjects with Acute Respiratory Disease (ARDS) patients and lung injury after Hematopoietic Stem Cell Transplant (HSCT) were analyzed.

Bhargava Lab

Metaproteomics Projects Ongoing Projects

•  MICROBIOME OF HUMAN CERVICAL-VAGINAL FLUID was analyzed after collecting samples using residual Pap test fixatives from a pool of 40 normal samples and 5 individual women with normal cytology.

•  Understanding the nature of the microorganisms and the functional role of the expressed proteins is an important step to develop diagnostic tools for gynecological conditions and malignancies.

MEGAN Analysis

1190 Microbial Peptides 30 genera. 42 species Function: 939 peptides

assigned to 137 InterPro2GO proteins

Skubitz Lab

•  METAPROTEOMICS OF FUNGAL WOOD DECAY: Investigate how fungal communities alter the decomposition and function of forest wood.

•  Experimental treatments: sterilized wood compared to non-sterilized control

•  Three-pronged approach to characterize influence of fungal communities on wood rot: metagenomics for taxonomy; metaproteomics for functional analysis & determine rate of wood decay.

Kennedy Lab

What’s Next? New Tools and Ideas

•  Taxonomy data derived protein FASTA database •  MetaProteomeAnalyzer (Rapp Lab – VIB, Belgium)

•  ComPIL (Comprehensive Protein Identification Library) and BlazMass (Fast and sensitive search engine) – Wolan Lab (Scripps).

•  MetaTRYP – Saito Lab (Woods Hole Institute). •  PSM Evaluation (UMN).

•  Quantitative Analysis. •  Interpretation and biological function analysis.

Galaxy @ ASMS z.umn.edu/gpatasms2016

z.umn.edu/galaxypreferences