Metaproteomics Studies Using The Galaxy-P Platform

PRATIK  JAGTAP    

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

AcknowledgementS

Minnesota  Supercompu0ng  Ins0tute  Ben  Lynch  Trevor  Wennblom  Tom  McGowan  Ge2ria  Onsongo  James  Johnson    Center  for  Mass  

Spectrometry  &  Proteomics  

LeeAnn  Higgins,    Todd  Markowski    

 

 

Ira  Cooke  La  Trobe  University,  Melbourne  ,  Australia  

Funding

2

Biochemistry,  Molecular  Biology  &  Biophysics  

TIM  GRIFFIN  Candace  Guerrero  Kevin  Murray  

Biologists  /  collaborators  

Brian  Sandri,  PhD  Alexa  Pragman,  MD  Chris  Wendt,  PhD    Somiah  Afiuni,  PhD  KrisEn  Boylan,  PhD  Marnie  Peterson,  PhD  Amy  Skubitz,  PhD  Kevin  Viken  Maneesh  Bhargava,  MD  Lauren  Cline,  PhD  Peter  Kennedy,  PhD  Joel  Rudney,  PhD  

Harald  Barsnes  &  Marc  Vaudel  University  of  Bergen,  Bergen,  Norway  

Bjoern  Gruening  University  of  Freiburg,    Freiburg,  Germany  

Lennart  Martens  VIB,  Ugent,  Belgium  

John  Chilton  Galaxy  Team  Penn  State  University  

Metaproteomics in Galaxy

• METAPROTEOMICS / MICROBIOMES

• GALAXY WORKFLOWS AS A SOLUTION

• EXAMPLE METAPROTEOMICS PROJECTS

• WHAT’S NEXT?

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

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. z.umn.edu/microbiomessi

Metaproteomics

1. Supporting interdisciplinary research to answer fundamental questions about microbiomes in diverse ecosystems. 2. Developing platform technologies that will generate insights and help share knowledge of microbiomes in diverse ecosystems and enhance access to microbiome data. 3. Expanding the microbiome workforce through citizen science, public engagement, and educational opportunities.

National Microbiome Initiative

Federal agency investment of more than $121 million in Fiscal Year (FY) 2016 and 2017.

Metaproteomics / Microbiome

Challenges •  Large metagenomic databases with

data from multiple organisms. Ø  False Discovery Rate estimation

strategies. Ø  Peptide sharing / Protein inference

across multiple organisms.

•  Interpretation of biological function.

•  Validation of the peptide identification.

- PSM Evaluation / Targeted proteomics of identified peptides.

•  Disparate tools and numerous processing steps.

Solution: Galaxy Platform

•  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.

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

Solution: Galaxy Platform

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

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

Solution: Galaxy Platform

Metaproteomic analysis using the Galaxy framework. Proteomics. (2015)

doi:10.1002/pmic.201500074. Unipept: Taxonomy MEGAN: Taxonomy + Functional analysis

Metaproteomics Projects Sucrose-induced dysbiosis in dental caries. Protein relative abundance patterns associated with sucrose-induced dysbiosis are conserved across taxonomically diverse oral microcosm biofilm models of dental caries Rudney et al., BMC Microbiome DOI: 10.1186/s40168-015-0136-z

•  Plaque microcosms were grown from carious lesions in 12 children •  Extensive inter-individual variation in dental plaque composition •  Paired design – microcosms grown in presence/absence of sucrose •  Sucrose induces acid production in dental caries (dysbiosis) Prof. Joel Rudney

School of Dentistry, UMN

16S rRNA Sucrose microcosms retained inter-individual taxonomic variation

Metaproteomics Projects Sucrose-induced dysbiosis in dental caries.

RAW data conversion Database generation Database Search 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.

•  2-D LC-MS/MS Metaproteome was analyzed for taxonomy and function •  Taxonomically-diverse sucrose-pulsed microcosms clustered more closely by function •  Function-based changes may be better indicators of dysbiosis

Rudney et al., BMC Microbiome DOI: 10.1186/s40168-015-0136-z

MEGAN5 Taxonomic Analysis SEED Functional Analysis

Metaproteomics Projects metaproteome of cervical vaginal fluid

Boylan et al. (2014) Clin Proteomics;11(1):30-45.

SCHEME FOR SAMPLE PREPARATION AND ANALYSIS •  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.

Metaproteomics Projects metaproteome of cervical vaginal fluid

Functional categorization •  267 peptides could be assigned to

99 InterPro2GO proteins, notably the Glyceraldehyde/Erythrose phosphate dehydrogenase family (15% of reads)

Taxonomic characterization • 27 genera (notably Lactobacillus, Gardnerella, and Acinetobacter) and 37 species (e.g. Gardnerella vaginalis, Lactobacillus iners) were identified from 419 microbial peptides from all the datasets.

MEGAN6 ANALYSIS

Metaproteomics Projects Lung Tissue Metaproteome

•  Lung cancer patient tumor samples were compared to healthy adjacent tissue and control tissue samples. Sixteen iTRAQ experiments were run to examine lung cancer biomarkers.

•  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

Chris Wendt Alexa Pragman Brian Sandri

Metaproteomics Projects Lung Tissue Metaproteome

Functional categorization •  336 peptides could be assigned to

132 InterPro2GO proteins, notably the ATPase, F1 complex (19% of reads)

MEGAN6 ANALYSIS Taxonomic characterization •  71 genera (notably Bacteroides,

Lactobacillus, and Mycobacterium ) and 84 species (e.g. Lactobacillus hilgardii) were identified from 729 microbial peptides from lung tissue datasets.

Metaproteomics Projects Broncheo-Alveolar Lavage Fluid Metaproteome

• Bronchoalveolar Lavage Fluid (BALF) is the proximate fluid to the site of injury in lung disease & is acquired through a bronchoscopy.

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

Bronchoscopy

Metaproteomics Projects Broncheo-Alveolar Lavage Fluid Metaproteome

MEGAN6 ANALYSIS Taxonomic characterization •  53 genera (notably Pyramidobacter,

Orbibacterium, Fusobacterium) and 71 species (e.g. Pyramidobacter piscolens) were identified from 776 microbial peptides, combining BALF from both the datasets.

Functional categorization •  232 peptides could be assigned to 107

InterPro2GO proteins, notably Triosephosphate isomerase, Thiazole biosynthesis ThiH, and DNA helicase, RecD-like.

Figure generated from UniPept Analysis: doi:10.1002/pmic.201400361

Metaproteomics Projects Ongoing Projects

Historical contingencies during fungal wood decay •  Research Question: As initial colonists of wood, does the presence of

fungal endophytes alter the rate and extent of wood decay? •  Hypotheses: Through priority effects, initial colonists of wood will alter

the composition and function of wood-decay communities •  Design:

•  Three healthy Betula papyrifera trees cut down at the Cloquet Forestry Center and segmented

•  In half of wood segments, initial colonists removed via wood sterilization by autoclaving

•  Wood returned to forest floor; samples collected at 7, 19 and 42 months

•  Test of hypothesis using metaproteomics: Investigate differences in fungal protein composition between sterilized and control wood treatments to understand whether the presence of endophytes has functional consequences for fungal wood decay

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 (WoodsHole). •  PSM Evaluation (UMN).

•  Quantitative Analysis. •  Interpretation and biological function analysis.

Galaxy @ ASMS z.umn.edu/gpatasms2016

z.umn.edu/galaxypreferences