Metabolic modelling of a
bacterial/animal symbiosis
Sandy Macdonald and Gavin Thomas
Department of Biology
University of York
Angela Douglas
Department of Entomology
Cornell University
USA
Outline
• The Buchnera / aphid symbiosis
• The Buchnera genome
• Construction and analysis of the Buchnera
metabolic model
Many insects have obligate bacterial symbionts
Aphid symbionts
• Buchnera sp. APS – Acyrthosiphon pisum
• Buchnera sp. SG - Schizaphis graminum
• Buchnera sp. BP - Baizongia pistacea
Ant symbionts
• Blochmannia floridanus
• Blochmannia pennsylvanicus
Tsetse fly symbionts
• Wigglesworthia glossinidia brevipalpis
Aphids – phloem sap feeding pests
The pea
aphid,
Acyrthosiphon
pisum.
• About 5000 different species
• Major crop pests.
• Restricted diet of phloem sap.
• All contain a primary symbiont and often a secondary symbiont.
Buchnera aphidicola sp. APS is the primary
symbiont of the pea aphid
• The bacteria are located in specialised insect cells
called bacteriocytes in their body cavity.
• They are surrounded by an aphid-derived
bacteriocycte membrane.
• TEM of bacteriocyte cytoplasm,
showing coccoid Buchnera.
• The Buchnera are unculturable
• Vertically transmitted to aphid
offspring via the ovary.
• The function of the symbiosis is nutritional.
• Phloem sap poor in essential amino acids (histidine, isoleucine, leucine,
lysine, methionine, phenylalanine, threonine, tryptophan and valine).
• These are known to be provided by the symbiont.
The Buchnera APS genome
• Small - 0.64 Mb
• 607 genes (569 protein coding genes)
• AT rich - 73 % AT
• Almost 90% of the genes have known
functions in E. coli K-12.
• Virtually no transcription regulation.
• No IS or phage elements
• Genome reannotated in BuchneraBASE.
The genome sequences of primary insect symbionts reveal
clear descent from an ancestral -proteobacterium
Ancestor ~3.5 Mb
200 My ago…
Free-living
Gene loss and
gene gain
E. coli K-12
4.2 Mb
Intracellular
Gene loss
only
Buchnera sp. APS
0.6 Mb
The Buchnera genome has undergone reductive evolution by a
series of deletion and inactivations of existing genes
• Initial large deletions removed large regions of the genome.
• Followed by smaller deletions and gene inactivation.
• Genomes are still relatively co-linear (syntenic).
The genome supports the proposed symbiotic function
Understanding the symbiosis
Exploiting E. coli to rapidly
produce a high quality metabolic
reconstruction of Buchnera APS
The iJR904 metabolic model of E. coli K-12
Metabolic model which contains the reactions catalysed by 904 gene products from
E. coli.
Central
metabolism
• Built from biochemical/genetics
literature for E. coli
• High quality reconstruction
• Contains 931 unique biochemical
reactions
• Mass and charge balanced
• e.g.
[c]h2o + sl26da --> 26dap-LL + succ
[c]26dap-LL <==> 26dap-M
[c]26dap-M + h --> co2 + lys-L
Construction of the metabolic network
Method
• Map all orthologues between APS and K-12.
• Manually assign reaction codes for APS gene
products.
• Store all relationships in BuchneraBASE.
www.buchnera.org
Construction of the metabolic network (2)
Removing isolated reactions
During the reductive evolution, some pathways are in
the process of being lost and still have remnants left.
APS has a number of isolated enzymes, e.g. SerC,
which were included in the original mapping.
Construction of the metabolic network (3)
Missing reactions
Some pathways for EAAs are not complete from the in silico reconstructions, but
are known to function in vivo. Infer promiscuous enzymes to fill these gaps.
Full gene complement for synthesis of 4 EAAs (histidine, tryptophan,
threonine and lysine), as well as the non-essentials arginine, cysteine and
glycine.
Also very short of transporters. Many have been inferred.
Carbon-skeleton based manual visualisation of iGT196
196 gene products
240 compounds (39% of iJR904)
263 reactions (27% of iJR904)
35% of reactions for EAA
biosynthesis.
Key
Red hexagon – high flux precursor
Red circle – low flux precursor
Grey triangle – inferred reaction
Blue square - EAA
Blue circle – biomass component
Thomas et al., (2009) BMC Systems Biology 3:24.
Understanding the symbiosis
Analysis of the reconstruction
using constraint-based modelling
(flux balance analysis)
Flux balance analysis
Exchange
Intracellular
Biomass
Exchange
The steady-state
assumption states that for
each metabolite the sum
of the fluxes producing
that metabolite is equal to
the sum of the fluxes
consuming that
metabolite.
Running FBA with the Buchnera model
FBA is essentially an optimisation problem solved using linear programming, i.e. it
finds the optimal route of fluxes through the network to get the desired output (the
objective function).
Used reduced version of the ‘biomass’ reaction of E. coli as the objective function.
(0000050) ACP + (0000050) fmnh2 + (0000050) pnto-R + (0000050) gthrd + (0000050) thmpp + (0000050) sheme +
(0000050) btn + (0000050) hemeO + (0203000) gtp + (0126000) ctp + (0136000) utp + (0027600) murein5p5p[p] + (0025400)
dctp + (0176000) phe-L + (0241000) thr-L + (0054000) trp-L + (0326000) lys-L + (0146000) met-L + (0428000) leu-L +
(0090000) his-L + (0276000) ile-L + (0281000) arg-L + (0087000) cys-L + (0582000) gly + (0402000) val-L + (0007000) spmd +
(0000010) fad + (0025400) dgtp + (0024700) dttp + (0024700) datp + (45731800) atp + (0001000) amp + (0002150) nad +
(0000050) nadh + (0000130) nadp + (0000400) nadph + (0000006) coa + (0000050) accoa + (0000003) succoa + (0730200)
pi + (0730200) ppi
To make this a ‘symbiotic’ model the biomass reaction modified to include the
exported EAA component.
An estimate of EAA export was obtained empirically using the pea aphid-Buchnera
symbiosis reared on chemically defined diets. It varied among the amino acids, from
22% (histidine and tryptophan) to 50% (threonine) of the amount synthesised.
Model required significant tweaking to get it to function – had to build iteratively.
The Buchnera metabolic network is highly constrained
The primary constraint that is used to assess the output of the network are the
uptake fluxes - 5 main precursors used by the network.
Optimal growth flux (5.21) is unusually only
reached by essentially a single ‘solution’, i.e. a
single distribution of internal fluxes, as judged by
flux variability analysis.
A number of ‘dead end’ metabolites are produced in significant quantities in the 5.21 model by Buchnera
• Adenine
by product of spermidine biosynthesis
• 5-methylribose
by product of spermidine biosynthesis
• S-ribosylhomocysteine
by product of cysteine biosynthesis
• Succinate
by product of lysine biosynthesis
The Buchnera metabolic network is fragile
Dogma is that biological networks
have evolved to be robust, i.e. tolerant
of some disruption.
• Deleted individual genes in silico and
measured resulting growth flux.
• E. coli iJR904 serves as a control.
• Deletion of 84% of the genes in
iGT196 led to a >99% decrease in
growth flux (19% for iJR904).
• Similar results using linear
minimisation of metabolic adjustment
(linearMOMA).
Can the aphid control the metabolic function of its
symbiont?
Designed a qualitative experiment to demonstrate the principle that the
aphid could manipulate the metabolic output of the bacterium just by
changing the inputs.
If this network is
‘always on’ then this
is a plausible way to
control the
symbiosis.
Possibly at the level
of transporter activity
in the bacteriocyte
membrane.