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Usefulness of molecular biology tools in the operation and control of the anaerobic digestion process
Jean-Philippe Steyer
To cite this version:
Jean-Philippe Steyer. Usefulness of molecular biology tools in the operation and control of the anaer- obic digestion process. XIII Latin American Workshop and Symposium on Anaerobic Digestion, International Water Association (IWA). INT., Oct 2018, Medellin, Colombia. �hal-02785209�
Usefulness of Molecular Biology Tools in the Operation and Control
of the Anaerobic Digestion Process
Jean-Philippe Steyer
Laboratoire de Biotechnologie de l’Environnement, INRA Narbonne
Usefulness of Molecular Biology Tools
Microbial Resource Management towards Ecological Engineering ?
From « Who is present ? » « Who is doing what ? » « With whom ? »….
… to « why are they doing it together? »
Study and control of
electro-assisted fermentation in mixed cultures:
The role of engineering of microbial interactions
Javiera Toledo Alarcón PhD Candidate
28 / 09 / 2018
Supervisor: Nicolas Bernet Co-Supervisor: Eric Trably
Metabolic Pathways
H2 to release e- excess
𝐺𝑙𝑢𝑐𝑜𝑠𝑒 + 2𝐻2𝑂 → 𝟐𝑨𝒄𝒆𝒕𝒂𝒕𝒆 + 2𝐶𝑂2 + 𝟒𝑯𝟐
Acetate route
Butyrate route
𝐺𝑙𝑢𝑐𝑜𝑠𝑒 → 𝑩𝒖𝒕𝒚𝒓𝒂𝒕𝒆 + 2𝐶𝑂2 + 𝟐𝑯𝟐
Acetate + ethanol route
𝐺𝑙𝑢𝑐𝑜𝑠𝑒 + 𝐻2𝑂 → 𝑬𝒕𝒉𝒂𝒏𝒐𝒍 + 𝑨𝒄𝒆𝒕𝒂𝒕𝒆 + 2𝐶𝑂2 + 𝟐𝑯𝟐
Lactate route
𝐺𝑙𝑢𝑐𝑜𝑠𝑒 → 𝟐𝑳𝒂𝒄𝒕𝒂𝒕𝒆 + 𝐻+
“Novel process that consists of electrochemically controlling microbial metabolism with electrodes”
• Anodic EF: partial electron sink
• Voltage applied on working electrode
Electro-Fermentation
Anode Cathode
e- e-
Ox e- Red
e-
V
Electron sink Electron source
• Cathodic EF: additional electron source
• Microbial interaction between species and electrode surface
• Microbial interaction between species
Experimental methodology
Control
(n=5)
Electro-Fermentation
- 0.4 V vs SCE (n=2)
+ 0.4 V vs SCE (n=3)
+ 0.9 V vs SCE (n=3)
- 0.9 V vs SCE (n=2)
Glucose (5 g.l-1) & Other Nutrients: Starkey
pHinitial: 6.0 (MES Buffer)
Temperature: 37 °C
Operation: Batch x 20 h
Inoculum: HT anaerobic sludge sampled from a lab-scale AD treating sewage sludge
0,74
1,49
1,80 1,34 1,81
0,0 0,5 1,0 1,5 2,0
Control – 0.9 V – 0.4 V 0.4 V 0.9 V H 2 Yield (mol H2/mol Glucose)
(Anova, F=20.68, p=0.001)
2x
Small current High impact H2 production during Electro-Fermentation
(Not correlated with the voltage applied)
H
2production
0%
25%
50%
75%
100%
Control – 0.9 V – 0.4 V 0.4 V 0.9 V
%COD Balance
H2
Propionate Succinate Acetate Ethanol Butyrate Lactate
𝑮𝒍𝒖𝒄𝒐𝒔𝒆 → 𝟐𝑳𝒂𝒄𝒕𝒂𝒕𝒆 + 𝑯+
𝑮𝒍𝒖𝒄𝒐𝒔𝒆 + 𝟐𝑯𝟐𝑶 → 𝑬𝒕𝒉𝒂𝒏𝒐𝒍 + 𝑨𝒄𝒆𝒕𝒂𝒕𝒆+ 𝟐𝑪𝑶𝟐 + 𝟐𝑯𝟐 𝑮𝒍𝒖𝒄𝒐𝒔𝒆 → 𝑩𝒖𝒕𝒚𝒓𝒂𝒕𝒆 + 𝟐𝑪𝑶𝟐 + 𝟐𝑯𝟐
Metabolite distribution
Control: Lactate
EF:
Acetate Ethanol Butyrate
0%
25%
50%
75%
100%
Control - 0.9 V - 0.4 V 0.4 V 0.9 V
Family distribution (%)
Clostridiaceae Enterobacteriaceae Streptococcaceae Others (<4.0%)
Microbial community
Streptococcaceae
Enterobacteriaceae
Clostridiaceae
Analysis of Metabolic patterns &
microbial community
Streptococcaceae
Lactate
H2
Clostridiaceae Butyrate
Lactate H2
Enterobacteriaceae
Acetate Ethanol Succinate
Usefulness of Molecular Biology Tools
Could these tools help us
to optimize process performances?
Anaerobic digestion
SSCP fingerprint
Complex ecosystem – High diversity
Anaerobic digestion
Under specific operating conditions (pre-heating, low pH, short HRT) No biogas but bioH2 and biomolecules
Anaerobic digestion
One major species
Few minor species : roles ?
Ecological Engineering for biotic control
raw heated
raw heated
raw heated
Mix of all
In each reactor, same operating conditions (feed=glucose, HRT=10h, T=37°C, pH=5.5)
In steady state in each reactor (after several HRTs), only one major specie
(difference only in minor species)
BDA
Cæ Cæpth
Man Manpth
Mix BDApth
Relative Auondance of bacteria
Link between
structure and function of the ecosystem
Ecological Engineering for biotic control
Identical major bacteria,
so identical performance, isn’t it ?….
NO !!!
BDA
Cæ Cæpth
Man Manpth
Mix BDApth
Relative Auondance of bacteria
Biotic control of the metabolism
PERFORMANCES
To act on the structure of the ecosystem to influence the function
Ecological Engineering for biotic control
STABILITY
Clostridium sp. Desulfovibrio sp.
Study of the interactions : a model
Ecological Engineering for biotic control
+
H2 H2 =
= ?
[H2] x 2.5 ! And faster ! Change in metabolic flux
Ecological Engineering for biotic control
<< +
influences the metabolism of !!!
Clostridium sp. Desulfovibrio sp.
Aggregation of the two organisms
Study of the interactions : a model
Ecological Engineering for biotic control
+
H2 H2 =
In addition….
Ecological Engineering for biotic control
<< +
=
A physical contact is mandatory !
Ecological Engineering for biotic control
New microbial interactions !
Usefulness of Molecular Biology Tools
Is microbial diversity an advantage?
17 different inocula (from real digesters réels or natural environments)
Same complex substrate for all digesters
Same stable conditions for hundreds of days
Role of the inoculum and microbial diversity
25
occasional substrate addition as fed-batch
The 17 inocula : soil, compost, freshwater sediments, digestors...
Role of the inoculum and microbial diversity
Six months
Hypothesis: Divergence of ecosystem performance
26
weeks 1 – 3 weeks 10 – 12
moved up in rank moved down in rank
27
occasional substrate addition as fed-batch
feeding/withdrawing every two day
final substrate pulse(s) in batch, BMP-like
The 17 inocula : soil, compost, freshwater sediments, digestors...
Role of the inoculum and microbial diversity
three months Six months
28
Role of the inoculum and microbial diversity
From 17 continuous processes
to 256 batch reactors !
No substrate
The 17 ecosystems
alone
“Overyielding”
Role of the inoculum and microbial diversity
After mixing of the 17 ecosystems
+
Role of the inoculum and microbial diversity
syntrophic networks
with different community structures
Usefulness of Molecular Biology Tools
How to integrate all the information
in mathematical models?
Modeling of microbial ecosystems
Microbial diversity or functional distribution?
Modelling competition between multiple populations:
emergence of the
"redox tower of microbial metabolism"
Microbial diversity or functional distribution?
Growth rate formulation:
𝜇 = 𝜇
𝑚𝑎𝑥𝑒
𝜈𝑖𝑀𝐸𝑇 𝑉ℎ 𝐶 𝑖 𝑐𝑎𝑟𝑑 𝐶
𝑖=1
From µ = µ
max 𝑆𝐾𝑆+𝑆
to
𝜇
𝑚𝑎𝑥= 𝑘
𝐵𝑇
ℎ 𝑓 𝑇, ∆𝑆, 𝑘
𝐵, ℎ
𝑉
ℎ: harvest volume
𝐶
𝑖: concentration of chemical specie #i 𝜈
𝑖𝑀𝐸𝑇= 𝜈
𝑖𝐴𝑁+ 𝜆 𝐶, 𝑇 ∙ 𝜈
𝑖𝐶𝐴𝑇𝜆 𝐶, 𝑇 = ∆𝐺𝑎𝑛 𝐶, 𝑇 − ∆𝐺𝑑𝑖𝑠 𝑁𝑜𝐶𝐶𝑠, 𝛾𝐶𝑆
−∆𝐺𝑐𝑎𝑡 𝐶, 𝑇
with
Only tuning parameter !
Microbial diversity or functional distribution?
μmax, Vh
μmax, Vh
μmax, Vh
μmax, Vh μmax, Vh
μmax, Vh
μmax, Vh
μmax, Vh μmax, Vh
μmax, Vh μmax, Vh
Comparing with classical Monod equation
μmax, Vh
Usefulness of Molecular Biology Tools
Examples of remaining
open questions
Never forget Mother Nature !
Treated Pollution (kgCOD/m3 .j)
0 100
50
Min Max
70
220
400
?
Never forget Mother Nature !
0,1 1 10 100 1000 10000 100000 1000000 10000000
1 2 3 4 5 6 7
(3) (3)
(3)
(3) (3)
(3) (15)
(35)
(26)
(3) (3)
(2) (2)
(3)
(2)
(2)
(2)
(4)
Simpson microbial diversity index
Weight (g)
Never forget Mother Nature !
From the analysis of 190 digestive tracts
Plug-flow reactor CSTRs in serie
Continuous stirred tank reactor (CSTR) Batch reactor
Never forget Mother Nature !
Carnivorous
Herbivorous
Slowly Biodegradable Substrates
omnivores
Readily Biodegradable Substrates
enzymes
assimilation
(sugar, acetate, etc.)
80 % 20 %
30 % 50 % 20 %
20 % 10 % 70 % 0 %
Never forget Mother Nature !
In terms of volume
Hoazin The ‘herbivorous’ configuration
Cow
Kangaroo Lama
Never forget Mother Nature !
New opportunities for wastewater treatment ?
• Granules settle very well: Largely reduce size of settler (space and operation = $$)
• Phototrophs produce oxygen: reduced need for external oxygen supply (aeration = $$)
• When digested, phototrophic granules produces 30% more CH4 ($$)
traditional wastewater treatment
