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Engineering Biology throughMolecular Microbial Ecology
Russell Davenport
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Global challengesUN Millenium Development Goals 2.6 billion without improved sanitation
WHO/Unicef, 2010
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Global challenges
Rockstrm et al., 2009 Nature
Anthropocene
Ecologicalfootprint has beenexceeded
Affect air, land andwater
21st Century of theenvironment or
biology
Living beyond our planetary boundaries
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Double burden and emerging hazards
Lvovsky, 2001
World Bank, 2003
Traditional hazards: water-borne diseases from inadequate water supply & sanitation
Modern hazards: exposure to agro-industrial chemicals
Dual jeopardy risks to health
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Emerging hazards chemical exposure
Personal care and domestic
hygiene products, pesticides,
pharmaceuticals and plastics
Mitigation:
Manufacturing source chemical regulation (e.g. REACH)
Engineered intervention of emissions wastewater regulation
(e.g. Integrated Pollution Prevention & Control; IPPC and
Water Framework Directive; WFD)
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Environmental engineering
Provide appropriate water and
wastewater treatment
governance and technologies
Protection of human health and
the environment through theregulation of chemicals
World Bank, 1992
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Empiricism and opportunism
1910
1891
1914
..practices do not represent the zenithof scientific treatment, nor are theythe product of a logical
and rational and design process.
Feachem et al., 1983
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- 4 M tonnes total CO2 (0.5% total UK) emissions- 1.5% of UK electricity
Economic and Environmental Costs
Organic carbon, N, P
Waste sludge
(WAS)
Return Activated Sludge
(RAS)
CO2 emissions
CO2 emissions
Treated
effluent
to sludge
treatmentO2
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Empirical wastewater treatment
Sometimes result in failure
Unpredictable and inexplicable Situation bound
Proximity to failure unknown
Adequate theories and models
Aggregate behaviour
Poorly calibrated
Over design Over aeration
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Why theory? How difficult can it be?
Stars in the our galaxy : Stars in the universe :
Measures of complexity
Bacteria in a STW : Bacteria in the world :
1030
1021
1018
1011
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Causey Arch, Built 1725
Severan Bridge, Turkey ~200 AD
The limits of empiricism
Roman design: unchanged since 179 BC
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A new era
New molecular based tools based on
evolutionary principles
Novel (ecological) theories
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Evolutionary tree of life
Woeses tree (1977) based on rRNA gene sequence
comparisons
Tree dominated by microbial forms
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Revolution in microbial ecology
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The basic molecular tool box
Clone, screen &sequence
DNA extraction
Amplification
Community analysis
RNA sequence determination
Fingerprint gel
Sample
Fix cells
Fluorescence in situHybridisation (FISH)
Probe/primer design
Abundance Diversity
Quantitative real-time PCR
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Measure diversity and abundance
Microbial ecology
Understanding the problems
0
10
20
30
40
50
60
70
Time
BacterialNumbers
Identification and quantification is central inachieving population dynamics
- Empirical monitoring (reactive management)
- (Ecological) theory (predictive management)
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Challenges facing biological treatment
Nitrification Foaming
Phosphorus removal
Bulking Denitrification
Removal of micropollutants including Endocrine
Disrupting Compounds (EDC)
Nutrient removal Solids separation
BOD removal
N- Fixation
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Nitrification
3 step process involving 2 distinct groups of bacteria
Ammonia oxidation (autotrophic AOB)
NH3 + O2 + 2H+ + 2e- NH2OH + H2O
Nitrite oxidation(nitrite-oxidizing bacteria)
NH2OH + H2O NO2- + 5H+ + 4e-
NO2- + H2O NO3
- + 2H+ + 2e-
Rate limiting step
NH4
NO2
-
NO3-
N2
N- Fixation
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Quantitative analysis of AOB
AOB occur in microcolonies
in activated sludge flocs
Can contain thousands of
individual cells
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R2= 0.8704
012345678
0 2 4 6 8 10Microcolony radius (microns)
Cell No.4/3
3
R2 = 0.87
n = 80
Quantitative analysis of AOB
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On the basis of this theoretical model the proportion of AOB
to total biomass can be predicted from ammonia removal
Values from cultured AOB are used to provide yield and
growth rate
Xv
Ammoniaxbnit
Ynitx
Xv
Xnit
**1
XAOB
YAOB
bAOB
* x
Integrating microbial data and processmodels
I i i bi l d d
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Good fit between theoreticalpredictions and measurement
Betaproteobacterial AOB
responsible for observed
nitrification
Deviations from theoretical
predictions suggest
Novel AOB Failing nitrification
Model not universal
XAOB/Xv predicted (%)
X
AOB
/Xvmeasu
red(%)
Regression
95% CI
8
4
0
0 1 2 3 4 5 6 7
y = 0.94x 1.42
Integrating microbial data and processmodels
Coskunuret al.,AEM, 2005
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Data useful for resource management?
Can high biomass
plants be made to work
harder?
Can such data permit
more intelligent balance
between process
performance and
process cost?456789
0.01 0.1 1 10 100
logAOBcells/ml
Cell-specific ammonia
oxidation rate fmol/cell/h
Coskunuret al.,AEM, 2005
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Cell Specific Ammonia Oxidation Rate (fmol/cell/hr)
LogAOBcells/m
l
10.01.00.1
1.0E+09
1.0E+08
1.0E+07
Stability
Failing
Irregular
Stable
23
22
21
20
1918
17
16
15
14
13
12
11
10
98
7
6
54
3
2
1
Quantifying AOB in relation to failure
Pickering et al., submitted Environ. Sci. Tchnol. (under review)Pickering, 2008
P A i i
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Dissolved
oxygen
(mg l-1)
Ammoniacal
nitrogen
(mg l-1)
1. Influent
2. Anoxic zone
3. Mechanical aeration
4. Mechanical aeration5. Diffuse aeration
6. Diffuse aeration
7. Diffuse aeration
8. Secondary effluent
9. Return Activated Sludge
Sutton-in-Ashfield
TotonNitrosomonas europaeaNCIMB 11850T
1. Influent
2. Anoxic zone
3. Mechanical aeration
4. Mechanical aeration
5. Diffuse aeration
6. Diffuse aeration7. Diffuse aeration
8. Secondary effluent
9. Return Activated Sludge
Sutton-in-Ashfield
Toton
Nitrosomonas europaeaNCIMB 11850T
Wanlip
DNA
Wanlip
RNA
Presence versus Activity
Milneret al., 2008, Water Research
P A i i
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1. Influent
2. Anoxic zone
3. Mechanical aeration
4. Mechanical aeration5. Diffuse aeration
6. Diffuse aeration
7. Diffuse aeration
8. Secondary effluent
9. Return Activated Sludge
Sutton-in-Ashfield
TotonNitrosomonas europaeaNCIMB 11850T
1. Influent
2. Anoxic zone
3. Mechanical aeration
4. Mechanical aeration
5. Diffuse aeration
6. Diffuse aeration7. Diffuse aeration
8. Secondary effluent
9. Return Activated Sludge
Sutton-in-Ashfield
Toton
Nitrosomonas europaeaNCIMB 11850T
Wanlip
DNA
Wanlip
RNA
Presence versus Activity
AOB
abundance
( 107 ml-1)
Ammoniacal
nitrogen
(mg l-1)
Nitrosomonas europaea-like organism
Milneret al., 2008 Water Research
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Are AOB mixotrophic?
Y= (MtMt0)/ (St St0)
Observed yield
Assumptions: All ammonia is consumed by AOB with little used for maintenance,no heterotrophic assimilation
26 mg mg-1ammonia removed
0.03 - 0.34 mg mg-1ammonia removed
C k h bi k h d ?
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Can we make the biomass work harder?
Bellucci et al., 2011 Appl. Environ. Microbiol.
43373125191371
100
80
60
40
20
0
Time (days)
ConcentrationasN(mg/
L)
RH4
43373125191371
100
80
60
40
20
0
Time (days)
ConcentrationasN(mg/
L)
RH3
43373125191371
100
80
60
40
20
0
Time (days)
Concentrationa
sN(mg/L)
RL2
43373125191371
100
80
60
40
20
0
Time (days)
Concentrationa
sN(mg/L)
RL1
0.25 mg l-1 0.5 mg l-1
3.4 mg l-1 3.0 mg l-1
NH3
NO2-
NO3-
RHsRLs
2.5
2.0
1.5
1.0
0.5
0.0
Treatments
Yield(VSSaob/NH4+
-Nremoved)
M di i i d d
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All biological communities are characterised by a species abundance
distribution
Area under the curve is the total number of taxa, ST i.e. total (alpha)diversity or species richness
00 5 10 15 20 25
Log2 Bacterial abundance (arbitrary units)
Numberofspecies(S)
ST
Intermediate abundance
Rare
speciesCommon
species
Most diversity is undetected
M di i i d d
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0
5001000
1500
2000
2500
30003500
4000
4500
5000
0 5 10 15 20 25
log2 species abundance (arbitrary units)
Numberofspeciespresentata
givenabundance
Even cloning and sequencing efforts will only sample the
far right hand end of the species curve
Most diversity is undetected
N i i
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Next generation sequencing Generates orders of magnitude greater sequencing depth (i.e. number
of sequences) than conventional Sanger-sequencing of clones Clone-sequencing: 100 clones reads is a big library takes
approx. 2 days from PCR
Parallel sequencing: up to 1,000,000 reads takes hours to days
0
5001000150020002500
30003500400045005000
0 5 10 15 20 25
log2 species abundance (arbitrary units)
Numberofspec
iespresentat
agivenab
undance
N t ti i
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An explosion of data
Key tools and theories stillbeing developed
Genbank growth nowexceeding Moores law
Economist 2009
Next generation sequencing
N t ti i
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Next generation sequencing ABI SOLiD (~50 100 bp)
Illumina Solexa and Hi-Seq genome analyser(~75 150 bp)
Roche 454 pyrosequencing (~400 1000 bp)
Ion Torrent (~100 200 bp)
Pyrosequencing
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Pyrosequencing
PCR using fusion primers (so-called tags)
Generates PCR amplicons with A and B adaptor tags
One fragment binds to one bead Emulsified in oil to give microreactors with reagents
for PCR (emPCR)
Multiple copies made of single fragment
Pyrosequencing
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Initially each bead has a single DNA molecule attached
Pyrosequencing
Pyrosequencing
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Sequencing by synthesis as nucleotides are flowed across plate in turn
Incorporated bases emit light with intensity proportional to homopolymer
length n
Pyrosequencing
Pyrosequencing
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Flowgrams are translated into sequences (by rounding to integers)
Can cause noise which can be removed (Quince et al., 2009, Nature Methods)
Pyrosequencing
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Beware of sequencing error!
Quince et al., Nat.Meths 2009, BMC Bioinf. 2011
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Species diversity in activated sludge
30,000 sequencesfrom UK AS plants Sequencing noise
removed
1000s of species in ASplants!
Just to sequence 90%
of diversity in 0.25 mlrequires 2-8 MILLION
sequences 0
1000
2000
3000
4000
5000
6000
7000
8000
Lognormal InverseGaussian
Derby Wanlip
NumberofSpe
cies
Davenport et al., unpublished
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Thanks!