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Measurements for dynamic modelling. Stefan Hohmann Cell and Molecular Biology Göteborg (Gothenburg) University, Sweden [email protected] [email protected] (from June 1) Field of research: Experimental biology, signal transduction, cell regulation.

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Measurements for dynamic modelling
Measurements for dynamic modelling

Stefan Hohmann

Cell and Molecular Biology

Göteborg (Gothenburg) University, Sweden

[email protected]

[email protected] (from June 1)

Field of research:

Experimental biology, signal transduction, cell regulation.

Employing budding yeast as experimental model.

Collaborations for measurements and modelling.

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Systems biology
Systems Biology

Top-down or data-driven

Networks from large-scale data

Bottom-up or model-driven

Dynamic modelling – simulating processes over time

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Data relevant for dynamic modelling
Data relevant for dynamic modelling

  • Physico-chemical properties of system components

  • Concentrations (molecules per cell) of components

  • Rates of changes of these concentrations

  • Rates of changes of interaction of the components

  • Velocity of movements or diffusion rates

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Ec funds several projects on dynamic modelling
EC funds several projects on dynamic modelling

  • QUASI – yeast MAPK signalling

  • AMPKIN – AMP-activated protein kinase signalling

  • COSBICS – JAK-STAT and MAPK signalling

  • RIBOSYS – yeast RNA metabolism

  • YSBN – Coordinating yeast systems biology

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Quantifying signal transduction
Quantifying signal transduction

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Quasi consortium
QUASI consortium

  • Gothenburg (biology: S Hohmann, P Sunnerhagen; chemistry: M Grøtli) Sweden

  • Barcelona (biology: F Posas) Spain

  • Vienna (biology: G Ammerer) Austria

  • Zürich (biology: M Peter) Switzerland

  • Berlin (theoretical physics: E Klipp) Germany


Types of measurements
Types of measurements

  • Rate of changes of phospho-MAPK

  • Certain other phospho-proteins

  • Rate of changes of mRNA of reporter genes

  • Levels and rate of change and transport of glycerol

  • Rate of change of certain protein-protein interactions

  • Population profiling using reporter-XFP and FACS

  • Hog1 MAPK nuclear shuttling


Types of perturbations
Types of perturbations

  • Genetic changes in pathways

  • Genetic changes in responses (osmoregulation)

  • Specific kinase inhibitors

  • Changes in experimental conditions


Integration of signalling, gene expression,

metabolism, transport and biophysical changes

Edda Klipp

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Questions addressed by quasi
Questions addressed by QUASI

  • Feedback control mechanisms in pheromone and high-osmolarity signalling MAPK pathways

  • Control of cell cycle by MAPK pathways

  • Control of a eukaryotic osmolyte system

  • Regulation of gene expression by Hog1 MAPK

  • Integration of converging branches of signalling pathway (HOG branches)

  • Pathway crosstalk

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Issues raised by quasi
Issues raised by QUASI

  • Linking different processes: signalling, gene expression, cell cycle, metabolism

  • Monitoring intermediates of signalling pathways (phospho-proteins)

  • Genetic perturbation – knock-out versus specific inhibitor

  • Cell-to-cell variations to interpret response profiles

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Systems biology of amp activated protein kinase

AMPKIN

Systems Biology of AMP-activated protein kinase

AMPK is the cellular energy regulator in eukaryotes and a possible target for drugs towards diabetes type II

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Ampkin consortium

AMPKIN

AMPKIN consortium

  • Gothenburg (biology: S Hohmann; physics: M Goksör) Sweden

  • Lyngby (bio-engineering: J Nielsen) Denmark

  • Rostock (computer science: O Wolkenhauer) Germany

  • London (biology: D Carling) UK

  • Arexis/Biovitrum (drug company – leaving project) Sweden


Types of measurements1

AMPKIN

Types of measurements

  • Glycolytic flux and rates of changes of metabolite levels

  • Rates of changes of phospho-AMPK

  • Rates of changes of phosphorylated forms of certain target proteins

  • Activity of target enzymes

  • Absolute levels and rates of changes for many pathway components

  • Rates of changes of mRNA levels for reporter genes

  • Population proflies using reporter-XFP and FACS

  • Nuclear shuttling of Mig1


Types of perturbations1

AMPKIN

Types of perturbations

  • Genetic changes in pathways

  • Genetic changes in metabolism

  • Specific kinase inhibitors

  • Changes in experimental conditions


Questions addressed by ampkin

AMPKIN

Questions addressed by AMPKIN

  • Comparative modelling of yeast and mammalian pathways

  • Integration of metabolism and signalling

  • Mechanisms controlling pathway activity

  • Signalling via kinases or phosphatases

  • Contributions of parallel pathways

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Issues raised by ampkin

AMPKIN

Issues raised by AMPKIN

  • Defining treatments for activating/deactivating the pathway

  • Sample preparation

  • Genetic perturbation – knock-out versus specific inhibitor

  • Cell-to-cell variations to interpret response profiles

CMB - Cell and Molecular Biology - Group Stefan Hohmann


CMB - Cell and Molecular Biology - Group Stefan Hohmann


Quantitative data for dynamic modelling
Quantitative data for dynamic modelling

  • Not commonly generated in high-throughput

  • Dedicated to very specific questions or modelling

  • Connected data sets – various measurements from same sample/culture/experiment

  • Reporting schemes/guidelines/standards and repositories

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Protein properties
Protein properties

  • Only for few metabolic enzymes

  • Generated in vitro with purified protein

  • Rarely known in vivo

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Numbers and concentrations
Numbers and concentrations

  • Readily possible for many metabolites

  • Possible for RNAs

  • Possible for proteins – but yeast data set needs to be re-checked very carefully

  • Protein modifications – specific antibodies or MS

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Single cell analyses
Single cell analyses

  • Cell-to-cell variation: interpretation of profiles obtained from cell extracts

  • Monitoring events in real time

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Single cell measurements

100

80

60

percent response

fraction of cells

40

20

0

0

10

20

30

40

50

60

time (min)

Single cell measurements

wild type

percent response

mutant

time (min)

Do all cells in the population show a

graded response?

Do different fractions of cells show an

all/nothing response at different times?

Do all mutant cells respond to max 50%?

Do only 50% of the mutant cells respondbut with 100% amplitude?

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Population profiling
Population profiling

  • Using promoter-XFP reporter systems

  • FACS analysis

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Monitoring signalling in real time
Monitoring signalling in real time

  • Suitable experimental setup, e.g. microfluidics

  • Monitoring protein movement associated with signalling (e.g. nuclear-cytosolic shuttling)

  • Monitoring transient protein-protein interactions using FRET

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Ec call for system approach to eukaryotic unicellular organism biology
EC call for ”system approach to eukaryotic unicellular organism biology”

  • Integration of different cellular modules (cell cycle, signalling, metabolism)

  • Integration population – cell – network - module

  • Large dynamic models

  • Operating procedures

  • Measurement tools (esp proteomics, single cells)

  • Modelling tools (esp linking different models)

  • Understanding biology: how external and internal signals control cell grwoth and proliferation

CMB - Cell and Molecular Biology - Group Stefan Hohmann


Some conclusions
Some conclusions organism biology”

  • Measurements for dynamic modelling are commonly small-scale and highly dedicated

  • Data collection is model-driven

  • Data should be reported in conjunction with the model

  • Measurements are often technically challenging

  • Quantitative measurements are being developed

  • Life cell imaging and single cell analyses methods are important

CMB - Cell and Molecular Biology - Group Stefan Hohmann


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