big data: mass spectral studies on the …...big data: mass spectral studies on the human skin...
TRANSCRIPT
BIG DATA: MASS SPECTRAL STUDIES ON
THE HUMAN SKIN SURFACE FOR MALARIA
VECTOR CONTROL APPLICATIONS
Madelien Wooding
Yvette Naudé
Egmont Rohwer
Department of Chemistry1
September 2019
BACKGROUND
2
NH3
CO2
CO2
NH2
OH
HO
OH
O
HO
O
To chemically profile the human skin surface
with the aim of identifying compounds
which can be used in integrated malaria
vector control strategies
Chemical profile of the human skin surface
Volatolome
Contact chemical compounds
GCxGC-TOFMSVOCs
Semi-volatile organic compounds
PDMS loop
(ankle vs wrist)
TD directly in GC inlet liner
Control
Method blank
UPLC-HRMS
Semi-volatile organic compounds
Non-volatile (larger molecules)
PDMS loop
(ankle vs wrist)
Back extraction
Control
Method blank
PROJECT OVERVIEW
3
IMSAdd unique feature for
compound identification
SKIN SAMPLING METHODS
Cotton pads – back extracted [1]
Dynamic headspace adsorption onto various polymers [1]
Solid phase microextraction (SPME) [1]
Glass beads – back extracted [2]
Silicone sheets – thermal desorption [3]
Worn nylon stockings & T-shirts [4]
Body chamber [5]
Air entrainment [6]
PDMS anklets and bracelets – Alex Roodt
41. Dormont, L., J.-M. Bessière, and A. Cohuet, Human skin volatiles: a review. Journal of chemical ecology, 2013. 39(5): p. 569-578.
2. Qiu YT, Smallegange RC, Hoppe S, van Loon JJ a, Bakker E-J, Takken W. Behavioural and electrophysiological responses of the malaria mosquito Anopheles gambiae Giles sensu stricto (Diptera: Culicidae) to human skin emanations. Med Vet Entomol. 2004;18(4):429–38. Riazanskaia
S, Blackburn G, Harker M, Taylor D, Thomas CLP. The analytical utility of thermally desorbed polydimethylsilicone membranes for in-vivo sampling of volatile organic compounds in and on human skin. Analyst . 2008;133(8):1020.
4, Takken, W. and B.G. Knols, Odor-mediated behavior of Afrotropical malaria mosquitoes. Annual review of entomology, 1999. 44(1): p. 131-157.5. Mochalski, P., et al., Monitoring of selected skin-and breath-borne volatile organic compounds emitted from the human body using gas chromatography ion mobility spectrometry (GC-IMS). Journal of Chromatography B, 2018. 1076: p. 29-34.
6. Robinson, A., et al., Plasmodium-associated changes in human odor attract mosquitoes. Proceedings of the National Academy of Sciences, 2018. 115(18): p. E4209-E4218.
Air entrainment [6]
EXPERIMENTAL
Single subject, multiple day (n=5) sampling events
Mosquito biting preference [7]
5 day study
Anklets & Bracelets
X 3 biological repeats
5
7, Braack, L., et al., Biting behaviour of African malaria vectors: 1. where do the main vector species bite on the human body? Parasites & vectors, 2015. 8(1): p. 76.
S i
C H 3
H 3 C
C H 3
O S i O
C H 3
C H 3
S i
C H 3
C H 3
C H 3n
EXTRACTION OF HUMAN SKIN COMPOUNDS FOR LC
6
Open loops
Sonicate
15 min
10 ml Isopropanol
+ internal standard
RT
Close loopsWipe skin with 70% isopropanol
prior to sampling
Sample skin surface
1 hourStore loops in foil at 4°C
Thermal desorb each loop
directly in GC inlet liner
Back extract
MeOH:ACN
1:1
200 µl
Sonicate 15min at RT
Remove loop
Place vial with glass insert in LC autosampler
5 µl injection
Volatiles
GC
Non- volatiles
LC
Ankle
Wrists
RESULTS
HUMAN SKIN SURFACE CHEMICAL PROFILE
LCMS
7
GCMS
IMS: Wrist Day 1 Positive mode IMS: Ankles Day 1 Positive mode GCxGC: Wrist Day 1 GCxGC: Ankles Day 1
BIG DATA DILEMMA
8
GCXGC-TOFMS DATA PROCESSING
9
200 400 600 800 1000 1200 1400 1600
0
500
1000
1500
2000
2500
3000
Time (s)
3267 104 150 196
272 376 596
660
734
896
1039
1334
1480
1665
1925
2048
2432
2558
2721
30223131
33253490
3626
3811
39164098
4456 4640
4955
5083
5215
LECO Stat compare Software
Fisher Ratio
Similarity ≥ 80%
RI ± 35
Excel
VLOOKUP/ SUMIFS
1D RT ± 3sec
2D RT ± 0,3sec
Normalised, IS
Multivariate
Statistics
JMP
ANKLE VS WRIST (M=29), PCA SCORE PLOT
10JMP Pro 14
Reporting compounds with similarity >800
Tentatively identified
NIST14 library
-40
-20
0
20
40
Sample
20180626A Day1 MW Wrist a
20180626B Day1 MW Wrist b
20180626C Day1 MW Wrist c
20180626D Day1 MW Ankles a
20180626F Day1 MW Ankles c
20180627A Day2 MW Wrists a
20180627B Day2 MW Wrists b
20180627C Day2 MW Wrists c
20180627D Day2 MW Ankles a
20180627E Day2 MW Ankles b
20180627F Day2 MW Ankles c
20180628A Day3 MW Wrists a
20180628B Day3 MW Wrists b
20180628C Day3 MW Wrists c
20180628D Day3 MW Ankles a
20180628E Day3 MW Ankles b
20180702 Day3 MW Ankles c
20180702B Day4 MW Wrists a
20180702C Day4 MW Wrists b
20180702D Day4 MW Wrists c
20180702E Day4 MW Ankles a
20180702F Day4 MW Ankles b
20180702G Day4 MW Ankles c
20180703A Day5 MW Wrists a
20180703B Day5 MW Wrists b
20180703c Day5 MW Wrists c
20180703D Day5 MW Ankles a
20180703E Day5 MW Ankles b
20180703F Day5 MW Ankles c
20180704A Method blank a
20180704B Method blank b
20180704C Method blank c
-40 -20 0 20 40
Component 1 (6,76 %)
Ankle
Wrist
Method
Blank
11
UPLC-IMS-HDMS DATA PROCESSING
12
Data acquired: MassLynx
Data processed: UNIFI
Mass error: 20ppm
RT ± 0,2min
Drift time ± 0,5mseconds
Normalise, IS
Multivariate Statistics
EZinfo
Marker table
ANKLE VS WRIST (M=30), PCA SCORE PLOT
13-900
-800
-700
-600
-500
-400
-300
-200
-100
0
100
200
300
400
500
600
700
800
900
-1000 0 1000
t[2
]
t[1]
Single subject, multiple (n=5) sampling eventsESI+
Ankle (15 observations)Major Mix, QCMethod BlankPooled SamplesWrist (15 observations)
Major Mix2_pMajor Mix3_pMajor Mix4_pMajor Mix_p
Method Blanka_pMethod Blankb_p
Method Blankc_p
MW_A_Day1a_p
MW_A_Day1b_p
MW_A_Day1c_p
MW_W_Day1a_p
MW_W_Day1b_p
MW_W_Day1c_pPooled Samples2_p
Pooled Samples3_pPooled Samples_p
MW_A_Day2a_p
MW_A_Day2b_p
MW_A_Day2c_p
MW_W_Day2a_p
MW_W_Day2b_p
MW_W_Day2c_p
MW_A_Day3a_p
MW_A_Day3b_p
MW_A_Day3c_pMW_W_Day3a_p
MW_W_Day3b_p
MW_W_Day3c_pMW_A_Day4a_p
MW_A_Day4b_p
MW_A_Day4c_p
MW_W_Day4a_p
MW_W_Day4b_p
MW_W_Day4c_p
MW_A_Day5a_p
MW_A_Day5b_p
MW_A_Day5c_p
MW_W_Day5a_p
MW_W_Day5b_p
MW_W_Day5c_p
EZinfo 2 - Marker table ankle vs wrist named p2 (M3: PCA-X) - 2019-09-12 09:24:46 (UTC+2)
OPLS-DA
14
-1200
-1000
-800
-600
-400
-200
0
200
400
600
800
1000
-600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600
t[2]O
t[1]P
Single subject, multiple day (n=5) sampling events
Ankle vs Wrist ESI+
Ankle
WristMW_A_Day1a_p
MW_A_Day1b_p
MW_A_Day1c_p
MW_W_Day1a_p
MW_W_Day1b_pMW_W_Day1c_p
MW_A_Day2a_p
MW_A_Day2b_p
MW_A_Day2c_p
MW_W_Day2a_p
MW_W_Day2b_p
MW_W_Day2c_p
MW_A_Day3a_p
MW_A_Day3b_pMW_A_Day3c_p
MW_W_Day3a_p
MW_W_Day3b_p
MW_W_Day3c_p
MW_A_Day4a_p
MW_A_Day4b_p
MW_A_Day4c_p
MW_W_Day4a_pMW_W_Day4b_pMW_W_Day4c_p
MW_A_Day5a_p
MW_A_Day5b_p
MW_A_Day5c_p
MW_W_Day5a_p
MW_W_Day5b_p
MW_W_Day5c_p
EZinfo 2 - MarkerTable_Ankle vs Wrist_p (M3: OPLS-DA) - 2019-09-11 09:37:09 (UTC+2)
S-PLOT
15
Wrist
Ankle
16
17
MARKERS
LC RESULTS
18
Progenesis QI v2.3
q-value ≤ 0.05
p-value ≤ 0.05
O
N
N,N-Diethylbenzeneacetamide
OH
O
OIsolinderanolide
H
H
H
H
H
HO
Abs
Campestanol
Ankle Wrist
O
O
O
P
O
OH
HO
DHAP
MARKERS
LC RESULTS
ID Class of
compound
Adduct Ret.
Time
(min)
m/z (Da) Collision
Cross
Section
(Å2)
Formula Mass Error
(ppm)
Isotope
Similarity
Fragments
(Peak m/z)Database Marker
CampestanolErgosterols and
derivativesM+Na 14.66 425.3764 216.715 C28H50O -3.19 90.86 - HMDB* Wrist
Isolinderanolide Tetrahydrofurans M+NH4 13.00 354.2992 202.09 C21H36O3 2.61 83.98 1 (312.2902) HMDB Ankle
Olomoucine 6-alkylaminopurines M+H 10.08 299.1615 175.489 C15H18N6O 0.098 88.01 - HMDB Ankle
N,N-
DiethylbenzeneacetamidePhenylacetamides M+H 6.59 192.1377 144.382 C12H17NO -2.87 95.86
2 (119.0488,
91.0570)HMDB Ankle
DHAP(18:0e)O-alkylglycerone
phosphatesM+H 7.38 423.2880 216.247 C21H43O6P 2.33 89.59 - HMDB Wrist
2-(Ethylamino)-4,5-
dihydroxybenzamide2-aminobenzamides M+NH4 6.59 214.1196 158.547 C9H12N2O3 4.90 96.07 - HMDB Ankle
2-Tetradecanone Ketones M+NH4 8.08 230.2469 178.356 C14H28O -4.21 92.60 - HMDB Wrist
19
* HMDB: Human Metabolome Database Version 4 created 10 July 2019
MARKERS SEPARATED BY DRIFT TIME
LC RESULTS
ID Class of
compound
Adduct Ret.
Time
(min)
m/z (Da) Collision
Cross
Section
(Å2)
Formula Mass Error
(ppm)
Isotope
Similarity
Fragments
(Peak m/z)Database
3β-Acetoxy-19α-hydroxy-
12-urseneTriterpenoids M+Na 11.21 507.3811
236.849
(Wrists)
210.679
(Ankle)
C32H52O3 0.41 79.34 - HMDB*
20
* HMDB: Human Metabolome Database Version 4 created 10 July 2019
O
HO
O
MULTIPLE SUBJECTS (N=20), SINGLE SAMPLING EVENT
GCxGC-TOFMS
Ankles and wrist
X2 biological
repeats
Ankles (m=39)
Wrists (m=40)
79 observations
21
UPLC-IMS-qTOFMS
Ankles and wrist
X3 biological repeats
Ankles (m=60)
Wrists (m=60)
120 observations
240 injections (ESI+ & ESI-)
22
Name
001Aa
001Ab
001Wa
001Wb
002Aa
002Ab
002Wa
002Wb
003Aa
003Ab
003Wa
003Wb
004Aa
004Ab
004Wa
004Wb
005Ab
005Wa
005Wb
006Aa
006Ab
006Wa
006Wb
007Aa
007Ab
007Wa
007Wb
008Aa
008Ab
008Wa
008Wb
009Aa
009Ab
009Wa
009Wb
010Aa
010Ab
010Wa
010Wb
011Aa
011Ab
011Wa
011Wb
012Aa
012Ab
012Wa
012Wb
013Aa
013Ab
013Wa
013Wb
014Aa
014Ab
014Wa
014Wb
015Aa
015Ab
015Wa
015Wb
016Aa
016Ab
016Wa
016Wb
017Aa
017Ab
017Wa
017Wb
018Aa
018Ab
018Wa
018Wb
019Aa
019Ab
019Wa
019Wb
020Aa
020Ab
020Wa
020Wb
Method Blank a
Method Blank b
Co
mp
on
en
t 2
(9,7
9 %
)
Ankles (m=39)
Wrists (m=40)
GCxGC
Ankles vs Wrists
20 Subjects, single sampling event
Component 1 (16,2 %)
23-10
-5
0
5
10Name
001Aa
001Ab
002Aa
002Ab
003Aa
003Ab
005Ab
008Aa
008Ab
009Aa
009Ab
010Aa
010Ab
011Aa
011Ab
012Aa
012Ab
013Aa
013Ab
014Aa
014Ab
015Aa
015Ab
017Aa
017Ab
018Aa
018Ab
019Aa
019Ab
Method Blank a
Method Blank b
-10 -5 0 5 10
Component 1 (14,5 %)
0
1
2
3
4
5
6
1 2 3 4 5
(5%); 1
(25%); 5 (25%); 5
(15%); 3
(30%); 6
1 = Not attractive
5 = Highly attractive
How attractive do you consider yourself to be
for mosquitoes?
(n = 20)
24
-10
-5
0
5
10
Oleic Acid
Ethanol, 2-(2-ethoxyethoxy)-
Nonane, 2,2,4,4,6,8,8-heptamethyl-
Octanal
2-Butoxyethyl acetate
n-Hexadecanoic acid
(2,3,5,6-Tetrafluorophenyl)methyl 3-(2,2-dichlorovinyl)-2,2-dimethyl-cyclopropane-1-carboxylate
Octadecanoic acid, 2,3-dihydroxypropyl ester
Butyrolactone
Benzaldehyde, 4-methyl-
4-Cyanocyclohexene
2,6-Diisopropylnaphthalene
Ethanol, 2-(dodecyloxy)-
Octane, 1,1'-oxybis-
1,3,5,7-Cyclooctatetraene
Benzenemethanol, à,à-dimethyl-
Isopropyl palmitate
Hexadecane, 2,6,10,14-tetramethyl-
Naphthalene, 5-ethyl-1,2,3,4-tetrahydro-
Sorbic Acid
Pentadecane, 2-methyl-
Benzenebutanoic acid, ç-oxo-, ethyl ester
1,2-Benzenedicarboxylic acid, bis(2-methylpropyl) ester
Pentadecanoic acid
Benzonitrile, 3,5-dimethyl-
Acetic acid, octyl ester
Hexadecane, 3-methyl-
Tetradecanoic acid
1-Heptanol, 6-methyl-
1-Octanol
Dodecanoic acid
Tridecanoic acid
Geraniol
9,12-Octadecadienoic acid (Z,Z)-
Phenanthrene
Name
001Aa
001Ab
002Aa
002Ab
003Aa
003Ab
005Ab
008Aa
008Ab
009Aa
009Ab
010Aa
010Ab
011Aa
011Ab
012Aa
012Ab
013Aa
013Ab
014Aa
014Ab
015Aa
015Ab
017Aa
017Ab
018Aa
018Ab
019Aa
019Ab
Method Blank a
Method Blank b
-10 -5 0 5 10
Component 1 (14,5 %)
25-8
-6
-4
-2
0
2
4
6
8Sample
001Wa
001Wb
003Wa
003Wb
004Wa
004Wb
005Wa
005Wb
006Wa
006Wb
007Wa
007Wb
008Wa
008Wb
009Wa
009Wb
011Wa
011Wb
013Wa
013Wb
014Wa
014Wb
015Wa
015Wb
017Wa
017Wb
018Wa
018Wb
020Wa
020Wb
Method blank a
Method blank b
-8 -6 -4 -2 0 2 4 6 8
Component 1 (27,5 %)
No 20
GCxGC
Wrists
-8
-6
-4
-2
0
2
4
6
8
Benzene, (1-ethyldecyl)-
Benzene, undecyl-
3-Butylisobenzofuran-1(3H)-one
Acetic acid, (3-methylbutoxy)-, 2-propenyl ester
1,2-Cyclohexanedicarboxylic acid, diethyl ester
Triethyl citrate
Naphthalene, 2,6-dimethyl-
Propoxur
Dodecyl acrylate
Phenanthrene
-8 -6 -4 -2 0 2 4 6 8
Component 1 (27,5 %)
3
Feet, ankles and legs
55%
Face and neck
5%
Hands, wrists and
arms
15%
I get bitten all over my
body
25%
Which part of your body gets bitten most by mosquitoes?
(n = 20)
26
0
2
4
6
8
10
12
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
CO
UN
T
NO
RM
ALI
SED
MEA
N P
EAK
AR
EA
COUMPOUNS DETECTED
Would you say that when outdoors you are the person who preferentially gets bitten by mosquitoes?
Yes
No
Count (yes, n=10)
Count (no, n=10)
27
-800
-700
-600
-500
-400
-300
-200
-100
0
100
200
300
400
500
600
-300 -200 -100 0 100 200 300
t[2
]O
t[1]P
UPLC-ESI+
Ankles vs Wrist
(m=120)
AnklesWrists
EZinfo 2 - MarkerTable_Skin RWS_p (M3: OPLS-DA) - 2019-09-11 10:43:55 (UTC+2)
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
-0.2 -0.1 -0.0 0.1
p(c
orr
)[1
]P (
Co
rre
latio
n)
p[1]P (Loadings)
S-Plot (Wrists = -1, Ankles = 1)
299.11043_5.530_3.54
192.14076_6.333_2.66
304.30064_9.222_4.40
365.13552_9.941_3.76
399.25075_10.063_4.70
421.23185_10.089_4.70332.33108_10.312_4.74
301.14103_10.355_3.46
149.02306_10.358_1.88437.20961_10.369_3.76
383.32032_10.371_4.42 383.20660_10.374_4.52
284.33159_10.441_4.48
531.35063_10.725_5.70
227.19983_10.742_2.95
487.32398_10.743_5.39443.29743_10.750_5.11
326.37865_10.758_4.89
429.31812_11.330_4.63385.29201_11.385_4.37
341.26627_11.418_4.06
340.28385_11.485_3.93
487.36016_11.810_4.93
398.23517_11.863_4.96
311.16587_11.993_3.59
477.22486_12.058_4.44
278.21276_12.119_3.91161.06024_12.155_2.07
256.26287_12.165_3.51
EZinfo 2 - MarkerTable_Skin RWS_p (M4: OPLS-DA) - 2019-09-11 10:50:36 (UTC+2)
-800
-700
-600
-500
-400
-300
-200
-100
0
100
200
300
400
500
600
-400 -300 -200 -100 0 100 200 300 400
t[2
]O
t[1]P
UPLC-ESI+
1-24-5
001_Aa_p001_Ab_p
001_Ac_p
002_Aa_p002_Ab_p
002_Ac_p
003_Aa_p
003_Ab_p
003_Ac_p
005_Aa_p
005_Ab_p
005_Ac_p
008_Aa_p008_Ab_p
008_Ac_p
009_Aa_p
009_Ab_p009_Ac_p
010_Aa_p
010_Ab_p
010_Ac_p
011_Aa_p
011_Ab_p
011_Ac_p
012_Aa_p 012_Ab_p012_Ac_p
013_Aa_p013_Ab_p013_Ac_p
014_Aa_p014_Ab_p014_Ac_p
015_Aa_p015_Ab_p
015_Ac_p
017_Aa_p017_Ab_p
017_Ac_p
018_Aa_p018_Ab_p018_Ac_p
019_Aa_p019_Ab_p
019_Ac_p
EZinfo 2 - Marker table Skin RWS named p scale (M4: OPLS-DA) - 2019-09-12 11:49:37 (UTC+2)
28
0
2000
4000
6000
8000
10000
Attractive Not attractive
Variable Averages 192.22142_6.331_2.70192.14076_6.333_2.66214.12023_6.333_3.25229.08758_8.612_2.71399.25075_10.063_4.70301.14103_10.355_3.46227.19983_10.742_2.95326.37865_10.758_4.89385.29201_11.385_4.37614.48346_11.621_6.48531.38650_11.784_3.42487.36016_11.810_4.93443.33340_11.839_2.99399.30682_11.859_2.82149.02462_11.863_1.93398.23517_11.863_4.96278.21276_12.119_3.91161.06024_12.155_2.07
EZinfo 2 - Marker table Skin RWS named p scale (M4: OPLS-DA) - 2019-09-12 11:52:55 (UTC+2)
0
1
2
3
4
5
6
1 2 3 4 5
(5%); 1
(25%); 5 (25%); 5
(15%); 3
(30%); 6
1 = Not attractive
5 = Highly attractive
How attractive do you consider yourself to be
for mosquitoes?
(n = 20)
29-700
-600
-500
-400
-300
-200
-100
0
100
200
300
400
-700 -600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600 700
t[2
]O
t[1]P
UPLC ESI+Ankles
Feet, ankles and legs
Hands, wrist and arms
EZinfo 2 - Marker table Skin RWS named p body parts ankles2 (M4: OPLS-DA) - 2019-09-12 12:07:08 (UTC+2)
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Ave
rage
Resp
onse
Markers
Feet, ankles and legs
55%
Face and neck
5%
Hands, wrists and
arms
15%
I get bitten all over my
body
25%
Which part of your body gets bitten most by mosquitoes?
(n = 20)
30
CONCLUSION & FUTURE WORK
Data integrity
Good chromatography (mass spec or UV detector)
Mass accuracy
Additional features: 2D GC or ion mobility
Collaboration with data scientist/ statisticians
Develop tools
Tentatively identify lead compound for vector control strategies
Differences between skin areas sampled
Differences between attractive vs not-attractive groups31
ACKNOWLEDGEMENTS
I would like to thank the following people for their support with the project:
Dr Hubert Mandery for financial support in his private capacity
Prof Leo Braack, UP ISMC
David Masemula (UP) for assembling the PDMS loops
Microsep, Tyren & Caryn
L’Oréal-UNESCO For Women in Science Sub-Saharan African Programme
32
Ethics approval: EC171109-159
33
"For Africa to move forward, you've really got to get rid of malaria."
— Bill Gates
THANK YOU!
QUESTIONS?