Telling metabolic stories to explore metabolomics data: a case study

Telling metabolic stories to explore metabolomics data
a case study on the yeast response to cadmium exposure
Paulo Vieira Milreu
Tecsinapse + Applied Research
Current Project
•
•
•
Green Synthesis of MNPs (NanoBioTec)
Metabolic networks
•
•
Stories, precursors, chemical organisations
GOV
2005
2006
Synthesis
2007
2008
2009
2010
2011
2012
2013
INOVATEC
Sistema de Inovação TecSinapse
2014 2015
Luciano Paulino da Silva
Cinthia Bonatto
Ivy Reis
Pedro Fonseca
Base Operacional em Nanotecnologia para
Simulação e Análise de Informação
Biomolecules
Nucleation
and Growth
Reducing Agents
Metal
Nanoparticle
Cínthia Bonatto
Makarov V. V. et al. “Green” Nanotechnologies:
Synthesis of Metal Nanoparticles Using
Plants. Acta naturae, 2014, 6.1: 35.
Silva, L. P. et al. Green Synthesis of Metal Nanoparticles by Plants: Current Trends and Challenges. In: Basiuk, V. A., Basiuk, E. V. (Eds.). Green Processes for
Nanotechnology: From Inorganic to Bioinspired Nanomaterials. Springer, 2015.
Absorbance UV/Vis
Zeta potential
Hydrodynamic size
Polydispersivity
Electrical Conductivity
Chemical properties → pH, composition
Microscopies (AFM/TEM) → size and shape
Surface Plasmon Resonance
Fluorescence
Mass Spectrometry
Fourier Transform InfraRed Spectroscopy
Raman Spectroscopy
5.00 um
10.00 x 10.00 um
67.46
[nm]
0.00
Toxicity tests on
Nematodes;
Gram positive and gram negative bacteria;
Yeast;
Fungus;
Cínthia Bonatto
Plants → in vivo and in vitro;
Eukaryotic cells → blood, cancer and connective cells.
Insect larvaes
•
•
•
•
•
•
Nanopigments
Nanosensors
Food industry (functional surfaces)
Water desalination
Water depollution (nanofilters)
...
Silva, L. P. et al. Green Synthesis of Metal Nanoparticles by Plants: Current Trends and Challenges. In: Basiuk, V. A., Basiuk, E. V. (Eds.). Green Processes for
Nanotechnology: From Inorganic to Bioinspired Nanomaterials. Springer, 2015.
•
•
•
What are the possible pathways explaining
differences of concentration of metabolites
under two conditions?
What are the possible inputs a metabolic
network needs to produce a specific target
metabolite?
How can one identify sets of metabolites that
are stable in time?
What are the possible pathways explaining differences of
concentration of metabolites under two conditions?
•
•
Metabolic Stories
What are the possible inputs a metabolic network needs to
produce a specific target metabolite?
•
•
Precursor Sets
How can one identify sets of metabolites that are stable in time?
•
•
Chemical Organisations
Metabolic network of the yeast - graph representation with 1336 nodes and 2865 arcs
Metabolic story = (compound) graph
Metabolites whose concentration changed =
subset of nodes (black nodes)
•
•
•
•
Remaining nodes are called white nodes.
Properties: maximal directed acyclic
subgraph (DAG) containing only black nodes
as source/targets
•
Acyclicity: define a flow of matter by assigning a role
(source/target/intermediate) in each story to the black nodes
•
Maximality: gets as many alternative paths as possible
Given a metabolic network and some black
nodes, is it easy to find a story?
In order to answer that... A step back:
•
•
Pitch
•
•
Is almost a story. It lacks only the maximality condition.
Formally:
Idea: explore random initial pitches
New problem: how to find random pitches!?
•
Proof:
•
Algorithm to enumerate all stories: inspect all
orderings of the nodes, compute each
individual pitch and complete it into a story.
•
Problem: inneficient (exponential)
1) Eliminate white dead ends
2) Simplify bottlenecks
2) Simplify bottlenecks
3) Eliminate self-loops
•
•
•
List of 24 metabolites whose
concentration significantly
changed under cádmium
exposure (Madalinski et al – 2008)
Current knowledge:
metathione binds to
cádmium in order to expelled
it from the cell
First experiment: try only
the metabolites involved in
the known pathway
Toy example with 5 nodes
and a score of 2.68
•
•
•
List of 24 metabolites whose
concentration significantly
changed under cádmium
exposure (Madalinski et al – 2008)
Current knowledge:
metathione binds to
cádmium in order to expelled
it from the cell
Second experiment: try all
metabolites identified in
the metabolomics
experiment
•
What are the precursors necessary to produce some target metabolites?
•
Input: target metabolites and some potential precursors (seeds)
•
Solutions: {E;G}, {E; F}, {G; I}, {G; J}, {F; I}, {F; J}
A definition that includes cycles:
•
Studying the dialog between a host and its two endosymbionts
•
Host: Glassy winged-sharpshooter (Homalodisca coagulata)
•
Symbionts: Sulcia muelleri and Baumannia cicadellinicola
•
Studying the dialog
between a host and its two
endosymbionts
•
Studying the dialog
between a host and its two
endosymbionts
Pitufo could deal with limited size networks
(~500 reactions)
New algorithms:
•
•
•
Traversing the network without building the
replacement tree
• Modifying the network while traversing it adding
shortcuts to save work
Paulo V. Milreu
E-mail: [email protected]
Telefone: (19) 99541-7007