Simple toxin identification using a
chemical ‘tongue’
Lucienne Otten and Matthew Gibson
Department of Chemistry, University of Warwick,
UK
l.c.otten@warwick.ac.uk
www.warwick.ac.uk/go/gibsongroup
Chemistry postgraduate symposium. 27th May 2015 University of Warwick Cholera toxin and Ricin
Enzymatic domain
Carbohydrate
binding domain
3-5 million cases a year
100-120,000 deaths
A dose the same size
as a couple of grains of
table salt can kill an
adult
Cholera infection and ricin poisoning
Severe cholera infection
Ricin poisoning through ingestion
•  Vomiting
•  Vomiting
•  Diarrhea
•  Diarrhea
•  Severe dehydration
•  Severe dehydration
•  Drop in blood pressure
•  Drop in blood pressure
•  Clinical shock
•  Clinical shock
•  Stomach cramps
•  Seizures
•  Death
•  Hematuria
•  Multiple organ failure
•  Death
CDC, WHO
Protein Carbohydrate interactions
Holgerrson et al. Immunol. Cell Biol. (2005)
Carbohydrate microarray: oligosaccharides
CTX
DBA
PNA
RCA
SBA
Specific
High-throughput
Simple
Various oligosaccharides
= £102,000 per g
Consortium for Functional Glycomics, CFG
0.1
Consortium for Functional Glycomics, CFG
Galb1-3GalNAca-Sp8
Galb1-2Galb-Sp8
Galb-Sp8
Various mono- and di-saccharides
Galb1-3GlcNAcb-Sp0
Galb1-3Galb-Sp8
= £1 per g
lb1-4(6P)GlcNAcb-Sp0
lb1-3(6S)GalNAcb-Sp8
Galb1-6Galb-Sp10
RCA
Galb1-4Galb-Sp10
Galb1-4Glcb-Sp8
Galb1-4Glcb-Sp0
Galb1-4GlcNacb-Sp23
PNA
Galb1-4GlcNAcb-Sp8
Galb1-4GlcNAcb-Sp0
Galb1-4(6S)Glcb-Sp8
DBA
Galb1-4(6S)Glcb-Sp0
Galb1-3GlcNAcb-Sp8
CTX
Galb1-3GalNAcb-sp8
Galb1-3GalNAca-Sp16
Galb1-3GalNAca-Sp14
Fluorescence (RFU)
Carbohydrate microarray: mono-/di-saccharides
SBA
10000
1000
CTx
Specific
DBA
High-throughput
PNA
Simple
RCA120
SBA
100
10
1
Linear Discriminant Analysis
Linear Discriminant 2
Linear Discriminant Analysis
Linear Discriminant 1
Carbohydrate surfaces
Otten, L., Gibson, M.I., R. Soc. Chem. Adv. (accepted)
Carbohydrate binding
Mannose
Galactose
Glucose
50% Gal: 50% Man
Fluorescence (RFU)
3000
2500
2000
1500
500
0
CTx
DBA
PNA
RCA120
SBA
Lectin
Otten, L., Gibson, M.I., R. Soc. Chem. Adv. (accepted)
LDA model
!
Otten, L., Gibson, M.I., R. Soc. Chem. Adv. (accepted)
Sample classification
Sample
Predicted Actual
U1
RCA120
RCA120
U2
PNA
PNA
U3
SBA
SBA
U4
DBA
DBA
U5
CTx
CTx
100% correct identification of ‘blind’
lectin samples
!
Otten, L., Gibson, M.I., R. Soc. Chem. Adv. (accepted)
Label free techniques
10
0
5
LD2
15
20
Otten, L. et al. J. Mater. Chem. B (2013)
-140
-120
-100
LD1
Richards, S-J., Otten, L. and Gibson, M.I., in preparation
Richards, S. et al., ACS Macro Letters (2014)
-80
-60
Other applications- Bacteria
AnAbioAc Discovery AnAmicrobial resistance deaths by 2050 Development of resistance Review on antimicrobial resistance, 2014
Protein Carbohydrate interactions
Bacteria Labelling
H
S
O
O
HN
N
NH
H
O
O
+
NH 2
R
O
S
H
N
HN
NH
H
O
R
O
R
Unpublished results
N
H
O
+
NH 2
S
H
N
HN
NH
O
O
H
OH
pH7-9
7
pH
H
O
R
Bacterial binding profiles
Unpublished results
LDA
Unpublished results
Conclusions and further work
Mannose
Galactose
Glucose
50% Gal: 50% Man
Fluorescence (RFU)
3000
2500
2000
1500
500
0
CTx
DBA
PNA
RCA120
SBA
Lectin
Conclusions:
•  Linear discriminant analysis has been shown to aid in the identification of
blind lectin samples
•  It has also shown to be applicable to identification of bacterial species
Future work:
•  Increase the number of bacterial species examined
•  Identification of Influenza A strains through differential carbohydrate binding
will also be analysed.
Acknowledgements
Matthew Gibson
Elizabeth Fullam
Sarah-Jane Richards
Lucienne Otten and Matthew Gibson
Department of Chemistry, University of Warwick,
UK
l.c.otten@warwick.ac.uk
www.warwick.ac.uk/go/gibsongroup
Chemistry Postgraduate Symposium. 27th May 2015 University of Warwick