fluxomics quantifying metabolic phenotypes · alexander braun [email protected]...

Fluxomics – Quantifying Metabolic Phenotypes

Alexander Braun

Environmental Isotope Chemistry Institute of Groundwater Ecology

„The central dogma of

one gene, one protein, one function

died in the last years.“ (Cascante & Marin 2008)

What is Fluxomics?

„What can happen?“

„What appears to be happening?“

„What makes it happen?“

„What could have happened?“

(Dettmer et al. 2006)

What is Fluxomics?

„What did happen and how did it happen?“

„What can happen?“

„What appears to be happening?“

„What makes it happen?“

„What could have happened?“


What is Fluxomics?

… the „traffic of metabolites“

The entity of intracellular fluxes that comprise the

ultimate endpoint of the regulated interplay of

genome, transcriptome, proteome and

metabolome.

The science of the fluxome is called

FLUXOMICS.

What is Fluxomics?


(Zamboni 2009)

(Niklas et al. 2010)

FLUXOME

„qualitative snapshots of the metabolic state of a cell“

indicators for metabolic phenotype

(Winter & Krömer 2013)

? gap


What is Fluxomics?

FLUXOME

(Chubukov 2013)

The Proteome-To-Phenotype Gap

(Tang 2008)

Fluxomics: metabolic endpoint = high scientific output?


𝑣 = 𝑓(𝐸, 𝑘, 𝑆, 𝑃, 𝐼)

Principles of Fluxomics

enzymek

S

I

P v

v: metabolic flux

E: enzyme concentration

k: kinetic parameters of the enzyme

S: substrate(s) concentration

P: product(s) concentration

I : effector molecule(s) concentration


𝑣 = 𝑓(𝐸, 𝑘, 𝑆, 𝑃, 𝐼)


k: in vitro ≠ in vivo

v must be quantified indirectly

Proteomics Metabolomics

Enzyme kinetics (in vitro!)

v: metabolic flux

E: enzyme concentration

k: kinetic parameters of the enzyme

S: substrate(s) concentration

P: product(s) concentration

I : effector molecule(s) concentration

Glcin

PEPin

Lacin Pyrin

Alain

Glcex

Directly measurable:

• intracellular metabolites and

their stable isotope label,

e.g. Glc, Lac, Ala


Not directly measurable:

• intracellular fluxes,

e.g. Glc -> PEP

Glcin

PEPin

Lacin Pyrin

Alain

Glcex


Stable Isotopes as Tracer:

(Niedenführ 2015)

Fluxomics

Complexity (experimental & modelling)

Example 1

(Niedenführ 2015)

Fluxomics


(Zhang et al. 2014)

Example 1: Isotope profiling

(Zhang et al. 2014)

healthy cell


(Zhang et al. 2014)

cancer cell



Conclusions:

-probably the easiest way to determine metabolic fluxes

(label->sample->data analysis[yes or no])

allows to prove metabolic connections / disconnections,

e.g. induced by cancer / diabetes

Isotope profiles can be used as indicators for metabolic disorders and/or

environmental conditions

Example 1

(Niedenführ 2015)

Fluxomics


Example 2

Glcin

PEPin

Lacin Pyrin

Alain

Glcex

Alaex Lacex

Directly measurable:

• intracellular metabolites and

their stable isotope label,

e.g. Glc, Lac, Ala

• extracellular fluxes,

e.g. Glc, Lac, Ala

Example 2: 13C Metabolic Flux Analysis

Not directly measurable:

• intracellular fluxes,

e.g. Glc -> PEP

Metabolic steady state

constant growth rate,

O2 consumpition,

CO2 production,

organic intake &

output rates

Isotopic steady state

constant isotope

signatures of

metabolites over time

Metabolic network model


Atom transitions

(Zamboni 2011)

„metabolic

phenotype“


(Zamboni 2011)


„Flux map“


Conclusions:

-“sophisticated“ experiments

-only for „known networks“

-extensive(!) modelling is necessary (CPU time: days-weeks)

Absolute flux information

- Metabolic fluxes are the ultimate metabolic endpoint

- Stable Isotopes allow determination of fluxes

- Different approaches for different levels of flux information

(in principle: the more input, the more output)

For further ideas / suggestions / cooperations, please contact

Alexander Braun

[email protected]

Overarching Conclusions


Example 1

(Niedenführ 2015)

Fluxomics:

Example 3

Example 2

Example 3: Kinetic Flux Profiling

liver muscle

C & N

input

10 20 100 200 1000

Half-life (h)

urin

efe

ces

liver

kidn

ey, s

plee

n

hear

t

mus

cle

brai

nlu

ngpl

asm

a

amin

oac

idsin

mus

cle

cow (Bos taurus)rat (Rattus rattus)

milk

fat

milk

case

in

milk

lact

ose

who

lem

ilk

fece

sha

irC & N residence time (h)

-48 -24 0 24 48 72 96-31

-30

-29

-28

-27

-26

Time after isotopic switch (h)

Iso

top

icco

mp

ositio

n(0

/ 00)


• Metabolic and isotopic steady state

• Time resolved sampling

• (simple) modelling

grey: diet

black: liver


Conclusions:

-metabolic & isotopic steady states are necessary

-(simple) modelling is necessary

time-resolved sampling allows kinetic flux information (e.g. half-lifes)

Sampling

Compound specific

(Metabolomics)

Bulk tissues

Organisms

(time resolved?)

Isotope Tracer

C, N, S, O, H….

Molecules

Isotopomes

Data analysis

No modelling

Exponential decay

Isotopomer modelling

….


The Metabolome-To-Phenotype Gap

fluxomics quantifying metabolic phenotypes · alexander braun [email protected]...

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