Microbiology/Metabolomics Core

John Cronan and Jonathan Sweedler

Enzyme Function Initiative (EFI)Advisory Committee Meeting

November 30, 2011

Outline

• Experimental scope

• Infrastructure

• Targets

• YidA from E. coli (HAD)

• YghU, YfcF, and YfcG from E. coli (GST)

• RuBisCO-like protein from R. rubrum (ENO)

• Future Directions

Experimental Scope

Bochner, B.R. (2003) New technologies to assess genotype-phenotype relationships, Nature Rev. Genetics. 4, 309-314.

Phenomics Transcriptomics Metabolomics

Conditions for target expression

(We now do qRT-PCR on each gene of interest)

Verification of hypothesized enzyme-catalyzed reaction

and/or evidence from relevant pathway

Infrastructure

Personnel

• John Cronan (Microbiology)• Jonathan Sweedler

(Metabolomics)

• Brad Evans (Metabolomics)• McKay Wood (Micro/Meta)• Kyuil Cho (Metabolomics)• Ritesh Kumar (Micro)• Amy Jones (Micro)

Instrumentation

• Microbiology– Biolog Omnilog phenotype

microarray plate reader/incubator

– Growth curve-ometer, BioscreenC

– E. coli single gene KO collection (Keio collection)

• Metabolomics– 11 Tesla LTQ-FT LC-MS– High resolution QTOF LC-MS– Custom XCMS LCMS data

analysis platform for untargeted metabolomics

Targets from around the EFI

• AHS:– E. coli

• SsnA, Php, TatD, YahJ, YjjV, HyuA, YcdX, Ade

– B. halodurans• LisM-RP

• ENO:– E. coli

• GudX, RspA, YcjG, YfaW– B. cereus

• NSAAR– S. enterica

• ManD-RP– A. tumefaciens

• 1RVK, 2NQL, GlucDRP, Atu0270, Atu4120, Atu3139, Atu4196…

• GST:– E. coli

• YfcG, YghU, YqjG, YliJ, YfcF, YncG, YibF, YecN

• HAD:– E. coli

• YidA, YigB, YbjI, NagD– P. fluorescens

• 3M9L

• IS:– A. tumefaciens

• IspB– C. glutamicum

• gi# 19551716– B. fragilis

• gi# 53711383

HAD SF: YidA from E. coli

Courtesy of D. Dunaway-Mariano

YidAkcat = 2 s-1

KM = 250 μMkcat/KM = 8 x 103 M-1s-1

dgoRdgoKdgoAdgoDdgoT yidA

Toxic if concentration

builds in the cell!

YidA (HAD): no effect after addition of galactonate

glycerol +galactonate

succinate + galactonate

glucose +galactonate

YidA(HAD): long lag when cells are resuspended in galactonate

YidA KOlikely mutated during lag

YidA (HAD): LCMS results for KDGP

Validated with standard from Hua Huang in the DDM Lab

YidA from E. coli (HAD): Results and Conclusions

• Phenomics is difficult with HAD SF members, as many are promiscuous housekeeping phosphatases

• An abrupt shift from a relatively poor carbon source to galactonate as sole carbon source causes the YidA KO to display a growth lag– The “abruptness” may be important for quickly building

levels of the toxic metabolite, KDGP– Growth of YidA following the lag may be due to mutation

• Metabolomics efforts so far do not support the connection between YidA KO lag with elevated KDGP levels

GST SF in E. coli: a role in oxidative stress response?

YfcF and YfcG (GST): NO sensitivity in null mutants

GST SF in E. coli: secreted to the periplasm?

Modeling/docking by Backy Chen, Computation Core

GST SF in E. coli: protein localization via gene fusionyghU-phoA yqjG-phoAyfcG-phoA empty vector treA-phoA gapA-phoA

yghU-lacZ yqjG-lacZyfcG-lacZ empty vector treA-lacZ gapA-lacZ

Cyt

opla

smPe

ripla

sm

YghU (GST): protein localization via proteomics

YfcF(GST): culture labeling and metabolite extraction

YfcF (GST): differential labeling provides higher accuracy

Ions from WT Ions from mutant

YfcF (GST): contaminant peaks remain unlabeled

YfcF (GST): affect of nitric oxide on metabolites

GST SF: results and conclusions

• YfcF and YfcG are implicated in reduction of nitric oxide– NO sensitivity phenotype identified– YfcF metabolomics with cutting-edge labeling protocol

allows measurement of small changes in metabolites

• Cellular localization is an important aspect of enzyme function– YghU and YfcG appear to remain in the cytoplasm

RuBisCO-like protein, RLP, from R. rubrum (ENO)

Canonical methionine salvage pathway (e.g. B. subtilis)

Seemingly incomplete MSP (R. rubrum)

?RLP

Work with Tobias Erb, Gerlt Lab

RLP: evidence for novel fate of methionine sulfur

Work with Tobias Erb, Gerlt Lab (ENO)

RLP: whole cell untargeted metabolomics

Work with Tobias Erb, Gerlt Lab (ENO)

RLP: whole cell untargeted metabolomics

Work with Tobias Erb, Gerlt Lab (ENO)

Data Processing

Preprocessing(XCMS)

Data Quality Control

Data Normalization

Peak detection/alignment

Retention time correction

Noise filtering

Retention time filter Adducts/Salt filter Missing value

imputation

Time-wise, condition specific

Mean-, Z-value …

Peak Grouping Formula Prediction

Pathway Activity Profiling

Isotope Pattern Analysis Mass check Retention time check Intensity ratio check

Peak Grouping

Deisotoping

Formula modeling

Theoretical Isotope Pattern Modeling

Perturbation Exp.LC-MS Analysis

Primary Peaks Isotope pattern ≥ 20% intensity change Secondary Peaks Isotope pattern < 20% intensity change

Monoisotopic peaks

Primary peaks used first Round Robin Recursive Backtracking

First order Markov Forward Trellis

Bayesian Statistics Isotope pattern

comparison experimental v.s

theoretical

Heuristics Prior prob. for C, N, S 6 Golden rules

Top 3 hits

DB Search

Seed Metabolites

Pathway Analysis

Activity Profiling

Active Pathways

2ppm mass tolerance Top hits formula

Isotope pattern High intensity change Exist in current DB

Seed metabolites info. DB Hits mono. peaks Shared pathways detection

Sort detected peaks upon fold change

p-values by MSEA

Pathways: p < 0.05

Potential Target Peaks Highly up- or down-

regulated, but not yet annotated peaks

Further experiments are needed

MTRu-1P01

2

MTA08

16

MTR-1P04

8

0min

10m

in20

min

0min

10m

in20

min

Met

abol

ite in

tens

ity (

x 10

6 )

Control +MTA

met-salvagepathway

p-value= 1.2 x 10-3

Isoprenoidpathway

p-value= 0.048

Glutathionemetabolism

p-value= 7.3 x 10-4

Purinemetabolism

Butanoatemetabolism

DXP

CDP-MEP

c-MEPP

00.51.0

0 1 2

0 4 8

0min

10m

in20

min

0min

10m

in20

min

Met

abol

ite in

tens

ity (

x 10

6 )

Control +MTA

up-regulated pathway

down-regulated pathway

pathway showing no big difference

metabolite

p-value= 4.8 x 10-4

p-value= 0.02

RLP: whole cell untargeted metabolomics

Work with Tobias Erb, Gerlt Lab (ENO)

RuBisCO-like protein from R. rubrum

RLPCupin

Work with Tobias Erb, Gerlt Lab (ENO)

RuBisCO-like protein (ENO): Results and Conclusions

• Perfect starting point for Micro./Metabolomics Core– Collaboration with ENO bridging project– Phenotype was known– High profile project (Ashida, et.al. Science, 2003)

• Genome context and measured thiol release suggested novel fate of MTA– Key enzymes in known MSP missing from genome– Cell extracts mixed with MTA produced methanethiol

• LC-MS-based metabolomics uncovered connection between MTA feeding and isoprenoid biosynthesis– Untargeted metabolite profiling of R. rubrum uncovered:

• Predicted MTA degradation products• Unexpected isoprenoid biosynthesis intermediates

Taking advantage of existing samples…Noncovalent Protein: Ligand Interactions Measured by Native ESI-MS

(from test cases to EFI samples…)

Microbiology/Protein/Structure Core Collaboration

Future work will use the samples stored in the Protein / Structure Core

Micro./Metabolomics Core: future directions

• Application of Biolog and custom phenotype microarrays to null mutants of targets from additional organisms

• Transcriptional analysis coupled to growth condition screens to gain complementary evidence for when target genes are expressed

• Further improvements in XCMS software to better detect metabolites of low abundance

• Application of differential labeling and multiple chromatographies for each metabolomics experiment to increase accuracy

• Continued and increasing collaboration with the BPs and Cores