Peak identification. Chemometric analysis was performed using the MZMine 12.4 software package. Peaks were detected from the positive mode and processed.
Chemometric-Directed Bioexploration of Natural Products Joshua J. Kellogg1, Daniel A. Todd1, Joseph M. Egan1, Huzefa A. Raja1, Nicholas H. Oberlies1, Olav M. Kvalheim2, Nadja B. Cech1 1 Department
Results
Identification of Potent Antibacterial Altersetin
Bioassay-guided fractionation (BGF)
22
24
Sample
S. aureus growth inhibition (%)
F2
F2-1
0.00 ± 0.02%
F2-1 F2-2 F2-3
F2-2
0.00 ± 0.01%
F2-3
0.01 ± 0.02%
F2-4
0.30 ± 0.01%
F2-5
0.00 ± 0.05%
F2-6
0.10 ± 0.10%
Incorporating Orthogonality • Increasing rationality of discovery • Orthogonal techniques • Metabolomics gives high-throughput data on secondary metabolites [4] • Biological activity data promotes balanced selection of potential leads ! biochemometrics [5] • Enhanced selection of higher-priority candidates [6] • Multivariate analysis improves data-mining capabilities
Growth inhibition of wildtype S. aureus by fungal crude extract (CR), flash fractions (FX), and preparatory HPLC sub-fractions (F2-X) was assayed at 10 μg/mL (Tables, right).
F2-4
F2-7
F2-5
F2-8
0.05 ± 0.02%
F2-6
F2-9
99.5 ± 0.01%
F2-10
99.1 ± 0.01%
2
F2-10
4
6
8
10
12 14 Time (min)
16
18
20
22
Dereplication Comparison
24
Dereplication using S-plot (below) identified alternariol methyl ether and tenuazonic acid as principal bioactive components. However, subfractionation confirmed that altersetin was primarily responsible for observed bioactivity, as predicted by the Selectivity Ratio plot. 1.50
1.00
Selec1vity Ra1o
Correla1on
0.50
0.8 0.6 0.4 0.2 0 -
0.40
0.00
Rela&ve Abundance
Growth Inhibi1on of AH1199
0.60
+
CR
F1
F2
F3
F4
100 90 80 70 60 50 40 30 20 10 0 0
CR F1 F2 F3 F4 2
4
1044.3
768.2
718.7
701.2
619.3
542.6
491.1
450.2
422.1
401.6
388.1
371.0
357.2
342.1
326.1
307.1
274.0
250.1
232.0
210.5
177.1
Crude Extract
Fractions Selectivity Ratio Plot (Bioactivity) - Significance Threshold 1.738 (p=0.050) 1.28
1.04
Untargeted LC-MS
0.79
0.55
0.30
0.05
Bioassays
991,220108
649,4749069
556,3489863
516,3619486
371,204629
481,3207825
441,2949407
355,214535
397,2179195
-0.19
Chemometric Analysis Variables Predicted vs Measured,(3 Com p), RMSECV = 0.11
0.6
F15
0.5
0.4
Slope = 0.654 Interc. = 0.040 Bias = -0.000 R= 0.809 R2 = 0.654 Adj. Corr. = 0.624
F14
0.3
F08
F37
F16 F34 F31
F09
0.2
CR_m ed 0.1 F20 0
F22 F23 F36 F04 F29 F02 F03 F05 F10 F06F12 F11
F33
F07 F17 F38 F25 F26F28F27 F24 F13 F18
F21 F32 F30 F01
F35
F19 -0.1 -0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
Measured (Bioactivity)
Identified Peaks
Dereplication
Structural Identification
6
8
10 Time (min) 12 14
16
18
20
22
24
0.500
1.000
2-2
2-1
2-8 2-7
Variable Selec1vity Ra1o
CR
4
PLS scores
1000
500
0
2 3
4 1 CR
-500
-1000 -1000
-500
0
Comp. 1
500
1000
994.6
815.5
790.5
780.5
700.1
559.3
542.3
522.3
497.3
455.2
429.3
413.2
396.3
379.3
351.2
318.1
283.2
273.0
235.0
198.1
8 6 4 2 0
-1000
0
-500
Comp. 1
500
1000 100
F2
90 80
OH
30 20 10 0
2
4
400.2480512
6
8
10
12 14 Time (min)
16
18
20
22
O
24
CH 3 O
F2-7
70
273.0756112 198.112477
Tenuazonic acid
O
40
0
CH 3
H N
50
80
H 3C
60
90
293.1016218 379.3355459 259.059964 544.3625203
M/z [Da]
F2-3
70
100
1.500
400.2488
O
OH
HO
60 50 40
CH3
30 20 10 0
0
100 90 80 70
2
4
6
8
10
12 14 Time (min)
16
18
20
22
24
H3C
O
F2-9
O
60
H 3C
50
2.000
*104 2.500
Alternariol methyl O ether
CH 3
H N
OH
CH 3
OH
H
40 30 20 10 0
0
2
4
6
8
10
12
14
16
18
20
22
24
Time (min)
Discussion
H
CH 3
Alterse1n
! Biochemometric analysis integrated orthogonal datasets to improve rational exploration of natural products ! Employing the Selective Ratio allowed for enhanced predictive capabilities for determining active agents and dereplication of known bioactives compared against other ! More complex botanical samples and including multiple biological assays will refine the modeling technique and analytical potential of biochemometrics
Extracts and fractions were brought up to 1 mg/mL in methanol and injected onto an Acquity UPLC BEH C18 (1.7μm, 2.1 × 50 mm) column at a flow rate of 0.3 mL/min using the following binary gradient. Solvent A consisted of water with 0.1% formic acid and solvent B consisted of acetonitrile. The gradient initiated at an isocratic composition of 95:5 (A:B) for 1.0 min, increasing linearly to 10:90 (A:B), followed by an isocratic hold at 10:90 (A:B) from 8.0–9.0 min, gradient returned to starting conditions of 90:10 (A:B) from 9.0–9.1 min, and was held at this composition from 9.1–10 min. The mass spectrometer was operated in positive ionization mode over a scan range of 150–1500 with the following settings: capillary voltage set at 5 V, capillary temperature set at 300°C, tube lens offset set at 35 V, spray voltage set at 3.80 kV, sheath gas flow set at 35, and auxiliary gas flow set at 20. Each sample was injected five times, with an injection volume of 3 μL. The results were monitored using a photodiode array (PDA) detector at 200 to 600 nm.
Antibacterial Bioassay Putative bioactive structures
0.000
Covariance
UPLC-MS
Endophyte isolates
343,2124258
Endophytes were extracted in 80% aqueous methanol and shaken for 24 h. Post-filtration, the filtrate was partitioned against hexane to yield the crude extract. Solvents were removed via rotary evaporation. Active extracts were separated using normal-phase flash chromatography (CombiFlash RF system, 12 g silica gel column) at 18 mL/min with a 36 min hexane/CHCl3/MeOH gradient. Active fractions were subject to further separation using HPLC with a Gemini-NX 5 μm, 250 × 21.2 mm C18 column. Samples eluted using a binary solvent system of water with 0.1% formic acid (solvent A) and acetonitrile (solvent B) at a flow rate of 21 mL/min. Solvents at 50:50 (A:B) was held isocratically for 5 min, increased linearly to 100:0 over 15 min, held for 5 min, then decreased to initial conditions over 5 min.
Goldenseal
337,2003726
Extraction & Fractionation
-0.500
325,2060982
Fresh goldenseal (Hydrastis canadensis) plant material was washed and surface-sterilized by sequential immersion in 95% ethanol, sodium hypochlorite, and 70% ethanol. Plant segments were transferred under aseptic conditions onto 2% malt extract agar. Plates were sealed and incubated at room temperate in 12 h dark/light until emergent colonies were observed. Fungi were grown subsequently on 2% MEA, potato dextrose agar, 2% soy peptone, 2% dextrose, and 1% yeast extract.
2-3
0
100 90 80 70 60 50 40 30 20 10 0 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (min)
315,0808765
Fungal Isolation & Culture
307,1929864
Methods
293,2111836
Macrosphelide A
185,115854
O
245,1378193
O
CH 3
227,1286033
O
O
212,0747543
CH 3
161,0273694
O
Variable Selectivity Ratio
OH
83,02174322
HO
O
Predicted (Bioactivity)
CH3
The Selectivity Ratio plot (above) dereplicated the known antibacterial agent macrosphelide A ([M+H]+ 343.1315 Da, left) as the peak that most significantl y contributes to the antimicrobial activity of the fungal isolate.
2
-500
930.2031759 239.069809 473.2903646 607.1773885 630.2684326 596.1069336 356.1124471 371.2187195 324.2894592 1087.716146 638.1063131 604.6700439 665.612854 317.08019 665.1116079 604.1696574 458.1228434 365.2324197 437.2158508 387.213946 645.2326904 415.2335697 385.1756897 231.101359 442.31545 355.2837016 750.7178141 571.2285258 563.4203491 407.0592651 403.2843831 353.1019592 275.0909743 536.5870623 536.0858231 263.0912005 274.088926 448.1290766 211.1442337 385.2733443 544.1486206 247.0600739 217.0853691 315.6380615 425.2652486 750.2173258 349.2375556 250.1046753 360.1442057 275.0800507 197.128418 433.1635651 181.1334432 213.0907033 417.0134786 740.5224813 343.1514181 289.0703278 433.1949259 199.1327006 849.427887 319.0595551 489.2853495 295.1165187 229.0856883 339.3253784 723.4565531 561.1033325 570.0231157 500.3731435 235.0964088 321.1674093 321.1692444 257.0801863 237.5988693 329.2104492 370.2370199 336.1222805 468.2359924 357.3360931 436.210001 433.2444153 560.3579865 339.2895813 233.0809504 357.2996674 281.1021627 943.6051453 512.3730367 209.1285756 277.0705922 207.0651805 245.0804644 407.5607109 736.6073354 422.2292084 542.3467204 196.0976105 414.2630107 274.0890706 419.1755312 507.1654053 547.1567485 831.4793091 309.0966441 300.2895406 621.3115234 318.1122504 181.1224416 289.140096 310.0605927 380.2214661 401.2889659 315.0831299 420.1774089 413.1058451 1034.677246 441.2730153 444.1076609 394.3078827 401.2686259 416.242157 267.1591593 821.4690552 448.5958023 700.6513478 564.6186024 191.0702871 578.0875041 326.3052877 335.0908813 180.0728073 334.0843018 700.150238 564.1171625 201.1634796 687.4932454 271.0594584 428.0826041 312.2898661 302.3045603 355.2836304 245.1285278 598.0545654 586.3748779 227.1388855 317.0805969 403.2557882 338.0555514 417.2491252 298.2736511 526.352581 347.221166 286.6587474 398.2322775 438.2246958 228.1229553 332.185037 372.253006 4227.5677658 39.2309452 336.2896213 386.2323507 616.2819824 333.0748393 238.1068598 1236.674052 337.2347565 377.3201263 321.0599569 419.1755371 249.148468 560.1555481 428.1348826 275.0547985 398.2323761 279.2317932 317.2086283 414.2269461 392.2069804 361.198232 344.3156857 475.325765 184.5397664 210.1123556 317.0654806 459.3108673 331.2838257 386.3617065 210.5467873 277.0706685 330.2997803 293.9987842 405.1998494 799.4888179 208.0945969 377.3199209 395.3310445 384.3831406 412.2474365 318.2998734 291.0860901 456.2359416 216.0847524 404.2065803 215.0922718 558.3782857 312.3253906 328.2846883 420.2139282 556.3622538 411.2129873 446.1451752 428.2066701 197.1724972 395.3303281 194.153965 320.1465658 197.1727905 331.2838236 429.3357544 602.3681793 419.2211792 199.1880086 268.625234 247.0959702 435.2160034 216.084743 446.2167257 394.1779378 853.4585215 624.3505147 313.2736003 217.5545495 544.6515299 260.6272142 358.3311666 330.336577 584.3577677 411.3256531 331.0809428 393.3147278 228.0070942 188.0618159 298.1650391 215.0923805 311.1846924 176.5537453 215.0923328 481.2929321 416.2430155 194.1541697 198.1849326 351.0708618 416.2433044 491.300827 196.1697337 274.0890503 351.0411835 546.3510437 398.3993352 408.3238322 215.0924327 198.1846873 302.1750488 584.3939732 216.0848127 295.2265015 332.1851349 199.188036 375.3042717 427.3201714 510.3601176 328.3568039 277.2160645 438.2245178 218.1510913 393.3148152 409.3094177 409.3097432 391.2295252 335.3104858 359.2032445 413.2113342 541.3309123 321.3150024 297.241923 515.3168513 544.3371216 388.2120449 800.5072021 539.311971 446.2544963 360.1172078 326.3416585 199.1880468 446.6467285 278.0266724 382.2371806 339.6038666 263.2364883 314.3414201 215.0924816 404.3368327 783.5700684 216.08479 315.2313354 314.1740112 445.2563171 261.0646667 194.1538522 596.393988 463.2812264 214.0892563 426.4298655 354.2417501 364.2262268 196.1694412 452.2398783 468.4045054 542.3210754 382.2371063 215.0923702 198.185154 279.2316793 197.1726163 760.5104167 426.2631938 663.453654 261.0755964 441.2994385 197.1724167 351.2131653 281.2471008 478.2921753 610.4110718 782.5683424 283.2625427 349.2342784 454.2917201 480.3076096 804.5499268 786.4898885 430.3892415 198.1851061 432.2381862 432.2389526 398.2685038 295.2627869 288.1596052 256.2630615 539.814209 399.4010544 1564.127645 243.1162949 269.1019287 997.624054 404.2182007 301.1676941 467.2757009 280.1481476 550.3867798 188.0617269 279.6462911 485.2870636 949.6241557 366.3724185 798.5616048 280.6543325 784.5112915 460.2683907 281.1075338 520.3387553 338.3414819 515.8143806 291.0837606 336.3260411 339.3432655 518.3211093 675.6762196 522.3547533 356.3517487 780.5524597 498.3436584 415.2113304 758.5696513 308.6725566 1039.667196 354.2633158 372.3473083 437.1929517 400.3419088 1043.70109 341.3047516 524.3705716 784.5841014 762.9780782 359.3151245 199.9873962 496.3398041 468.3077494 740.5228678 647.3739217 836.5386454 335.1252394 796.5480143 786.599467 674.4393921 1011.143555 421.2321555 552.328654 251.0911102 354.032692 790.558492 182.9849558 274.0891622 342.3728333 554.3439433 296.3305442 991.669142 814.5569153 188.0616455 816.571696 235.168691 716.5213114 782.5666911 286.3105214 846.5466309 216.0847595 476.3941243 784.5839132 215.0923004 193.9893265 830.5526123 812.5417684 251.1637592 659.2860514 335.1055519 197.1726227 362.2078603 396.4198739 279.1589457 833.5182902 236.0710512 407.279007 294.31545 393.2885844 342.3360443 279.1586202 760.5103353 637.3047016 443.2405192 436.3420105 803.5406784 413.2652383 453.3183289 340.3577012 300.3256989 371.1829631 412.4150289 425.2868618 405.2636058 427.2454224 429.260671 389.2677917
-1.00 -1.000
Comp. 2
PLS analysis incorporating S. aureus inhibitory bioactivity (SA1199, above, left) with LC-MS (above, right) of the crude (CR) and f lash chromatography fractions (F1-F4) of Pyrenocheta sp. revealed a clustering of crude and F4 distinct from F1-F3 (right).
M/z [Da]
2-10
2-6
1
S-plot
-0.50
0.20
0.00
2-5 2-4
-1000
10
2-9
F2-8
1
15 objects: CR, F1-F4, F2-1 - F2-10
Selec&vity Ra&o
12
3
Dereplication of Macrosphelide A
0.80
422.2295
500
0.08 ± 0.06%
F2-9
! Both models highlighted altersetin (m/z 400.2488 Da) as a primary putative bioactive structure. 14
0
Selec&vity Ra&o
PLS
1000
• Multiple techniques exist for biomarker identification and prioritization • Selectivity Ratio (SR) [7] • Ratio of explained variance to residual variance • Combines predictive power with explanatory power • Accounts for variation in intensity that could mask covariance with dependent variable • Can also show variables that negatively vary with dependent variable (i.e. reduce bioactivity)
343.1315
! Active and inactive fractions separated into distinct groupings with no overlap.
F2-7
Marker Selection
1.00
472 independent variables: LC-MS marker ions 1 dependent variable: antibacterial bioactivity
930.2
20
784.5
18
663.4
16
A 4-component PLS model was constructed. Dividing the explained variance by residual variances yielded the Selectivity Ratio (SR) for each marker ion, with higher SR indicating stronger predictive correlation with bioactivity.
570.0
10 12 14 Time (min)
Partial-least squares scores plot (PLS) of the pre- and post-HPLC fractionation matrices (above and below, respectively).
536.5
8
M/z [Da]
473.2
6
1000
441.2
4
Comp. 1
500
426.4
2
0
412.4
F4
-500
180.0
Quantitative Chemometric Matrix
0
-1000 -1000
398.2
How to chose which peaks should be targeted?
F3
380.2
If not, is there sufficient material to isolate each minor peak?
356.1
20
0
338.3
18
F2
0.7 ± 0.01%
20
326.3
16
F4
-500
310.0
12 14 Time (min)
100 90 80 70 60 50 40 30 20 10 0
40
286.6
10
0.1 ± 0.02%
F1
4 1
274.0
8
F3
5 objects: CR + F1F4
2
239.0
6
99.8 ± 0.01%
0
215.0
0
F2
60
198.1
10
0.0 ± 0.03%
Selec&vity Ra&o
422.2295
176.5
30 20
F1
CR
3
Variable Selec&vity Ra&o
40
100.0 ± 1.10%
544.3623
80
Rela&ve Abundance
50
CR
400.2488
120
500
Rela&ve Abundance
Rela&ve Abundance
70 60
98.3 ± 0.41%
CR
Rela&ve Abundance
Is this peak responsible for observed bioactivity?
80
Pos Con
Rela&ve Abundance
100
Sample
100
Comp. 2
Alternaria daucifolii crude extract (CR) yielded 4 flash fractions (F1-F4). F2 showed highest growth inhibition of S. aureus, and was fractionated.
S. aureus growth inhibition (%)
Comp. 2
• Standard for natural product discovery [1] • Questions remain with complex, bioactive mixtures • BGF’s focus on dominant peaks • Issues of isolation [2] • Ascribing bioactivity [3] 90
PLS
1000
Rela&ve Abundance
Introduction
of Chemistry & Biochemistry, University of North Carolina Greensboro, Greensboro, NC, USA 2 Department of Chemistry, University of Bergen, Bergen, Norway
Two strains of S. aureus were employed, wild-type (SA1199) and
methicillin-resistant S. aureus (MRSA, AH1263). A single colony inoculum of S. aureus was grown to log phase in Müeller-Hinton broth and was adjusted to a final assay dilution of 1.0 × 105 cfu/mL based on at 600 nm (OD600). The negative control consisted of 2% DMSO in broth (vehicle), and the known antibacterial agent chloramphenicol served as positive control. Triplicate wells were prepared with all treatments and controls. Background absorbance was subtracted using wells containing samples without bacteria. OD600 was read after incubation for 20 h at 37 °C.
Biochemometric Analysis Peak identification Chemometric analysis was performed using the MZMine 12.4 software package. Peaks were detected from the positive mode and processed according to the parameters: 1–30 min retention time, 150–1000 Da mass range. Isotopic peaks were excluded from analysis, the intensity threshold (counts) was 1 × 107, and retention time window was 0.1 min. The spectra were aligned by retention time, and m/z data points were aligned using the Join Align function in MZMine, and gaps were back-filled postalignment. The data matrix was constructed setting m/z as the variables and consecutive samples as the objects, with each data point as the peak intensity.
Statistics Data was transformed by taking the 4th root to remove heteroscedastic noise. PCA and PLS-DA analyses on the data matrix were conducted
Acknowledgements The authors wish to thank Vincent Sica for assistance in collecting mass spectrometry profiles. This project is supported with funding from the National Center for Complimentary and Integrative Health (NCCIH, grant R01 AT006860).
References [1 ]Weller, M.G. (2012) A unifying review of bioassay-guided fractionation, effect-directed analysis, and related techniques. Sensors, 12, 9181-9209. [2] Prince, E.K. and Pohnert, G. (2010) Searching for signals in the noise: metabolomics in chemical ecology. Analytical and Bioanalytical Chemistry, 396, 193-197. [3] Qui, F., Cai, G., Jaki, B.U., Lankin, D.C., Franzblau, S.G., Pauli, G.F. (2013) Quantitative purity-activity relationships of natural products: the case of anti-tuberculosis active triterpenes from Oplopanax horridus. Journal of Natural Products, 76, 413-419. [4] Kurita, K.L., Linington, R.G. (2015) Connecting phenotype and chemotype: high-content discovery strategies for natural products research. Journal of Natural Products, 78, 587-596. [5] Martens, H., Bruun, S. W., Adt, I., Sockalingum, G.D., Kohler, A. (2006) Pre-processing in biochemometrics: correction for path-length and temperature effects of water in FTIR bio-spectroscopy by EMSC. Journal of Chemometrics, 20, 402-417. [6] Kulakowski, D.M., Wu, S.B., Balick, M.J., Kennelly, E.J. (2014) Merging bioactivity with liquid chromatographymass spectrometry-based chemometrics to identify minor immunomodulatory compounds from a Micronesian adaptogen, Phaleria nisidai. Journal of Chromatography A, 1364, 74-82. [7] Kvalheim, O.M., Chan, H., Benzie, I.F.F., Szeto, Y., Tzang, A.H., Mok, D.K., Chau, F. (2011) Chromatographic profiling and multivariate analysis for screening and quantifying the contributions from individual components to the bioactive signature in natural products. Chemometrics and Intelligent Laboratory Systems, 107, 98-105.
