Quantitative analysis of small molecules in biological samples. Jeevan Prasain, Ph.D. Department of Pharmacology & Toxicology, UAB.

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Quantitative analysis of small molecules in biological samples 100 Jeevan Prasain, Ph.D. Department of Pharmacology & Toxicology, UAB % 0 300 500 700 900 1100 1300 1500 1700 m/z Class Overview Introduction to method validation and LC- MS/MS analysis Quantitative analysis of puerarin, and phytoestrogens in biological samples by LC-MS/MS 1

Validation All of the procedures that demonstrate that a particular method used for quantitative measurement of analytes in a given biological matrix, Such as blood, plasma, serum, or urine, is reliable and reproducible for the intended use http://www.fda.gov/downloads/drugs/guidances/ucm070107.pdf Untargeted metabolomics and method validation No guidelines for validating analytical part in untargeted metabolomics. Unbiased differential, comprehensive analysis of metabolites in a biological sample. Reproducibility in chromatographic as well as MS performance Comparison should be valid and the change in signals should be related to the concentration- i.e. precisely measured. Quality control samples, spiking with unnatural internal standard to monitor reproducibility Statistical analysis- similarity/differences between and within samples. Naz et al., J Chrom A., 2014. 2

Bio-analytical works Sample preparation Chromatographic separation MS ionization/detection Assay development, validation Quantitative analysis Challenges in quantitative analysis of analytes Low concentrations of metabolites in a complex matrix Number of samples (eg.10-1000)/study Wide dynamic concentration range (pico to microgram/ml) 3

Sample preparation is a crucial step in removing the interfering compounds from biological matrix Sample preparation Liquid-liquid Extraction LLE Protein Precipitation PP Solid phase Extraction SPE The method of choice will be determined by the sample matrix and the concentration of compounds In samples Choice of Good Internal Standards A stable isotopically labeled IS is preferable. Is not found in the original sample In the absence of stable isotopically labeled internal std, the structure of the internal standard needs to be similar to the analyte and co-elute with the analyte. Should not react chemically with the analyte. 4

Problems encountered in LC-MS analysis Matrix effect on Ion suppression? The presence of endogenous substances from matrix, i.e., organic or inorganic molecules present in the sample and that are retained in the final extract Exogenous substances, i.e., molecules not present in the sample but coming from various external sources during the sample preparation LC-MS analysis HPLC Isocratic Gradient Reversed-nonpolar stationary, polar mobile Normal- polar stationary, nonpolar mobile HILIC- hydrophilic interaction Common column- 100-200 mm long and 3-4.6 mm diameter Smaller diameter offers better separation and sensitivity 5

Points to be considered in LC-MS analysis Choice of ionization mode - ESI vs. APCI +ve/-ve modes Choice of eluting solvent - methanol vs. acetonitrile Evaluation of spectral quality - what to look for in a good quality spectra Molecular ion recognition Choice of solvent Common organic solvents- Methanol and acetonitrile, water alone is poor solvent for ESI Acetonitrile vs methanol- acetonitrile (expensive), water/methanol creates more pressure than water/acetonitrile Elution strength- usually acetonitrile> methanol Methanol provide a more stable spray and better sensitivity than acetonitrile in negative ion mode. 6

APCI is less prone to than ESI to the effects of ion suppression King et al. J. Am Soc Mass Spectrom 2000 Eliminating matrix effects 1. Preparing more cleaner samples. 2. Concentrating analyte of interest 3. Improve analytical system performance % matrix effects = [Response post-extracted spiked sample -1] x100 response non-extracted neat samples 7

Carry over - a big problem Previously injected sample which appears upon subsequent analyses due to physico-chemical property of the sample, analysis system or both. 8.5e4 4.10 Intensity, cps 4.15 100 ng/ml of Chlorhexidine 4.22 4.28 4.38 1 3 5 8 10 12 14 1771 4.10 Intensity, cps 0 MeOH blank injection 4.41 3.93 4.93 3.86 6.01 6.31 10.67 13.43 13.32 1 3 5 7 9 11 13 15 Analytical method validation Should demonstrate specificity, linearity, recovery, accuracy, precision Lower limit of quantification, detection Stability (freeze/thaw) Robustness & ruggedness Matrix effects 8

Method validation.. Specificity is established by the lack of interference peaks at the retention time for the internal standard and the analyte. Accuracy is determined by comparing the calculated concentration using calibration curves to known concentration. The LLQ is defined as the smallest amount of the analyte that could be measured in a sample with sufficient precision (%CV) and accuracy (within 20% for both parameters) and is chosen as the lowest concentration on the calibration curve. Linearity It indicates the relationship between changed concentrations and proportional response R2> 0.95, with at least 5 concentration levels 9

Standard curve non-linearity is possible due to detector saturation, dimer/multimer formation, and or ESI droplet saturation at higher concentration Non-linear due to detector saturation Source: Bakhtiar & Majumdar. Journal of Pharmacological and Toxicological Methods, 2007 Precision.. The closeness of agreement between a series of measurements obtained from multiple samples of the homogenous sample.- Repeatability %CV 10

Robustness Ability to remain unaffected by small but deliberate variations in the LC-MS/MS method parameters- such as ph in a mobile phase, composition of solvents, different lots of column, flow rates etc. Ruggedness Indicates degree of reproducibility of test results under a variety of conditions such as different labs, instruments and reagents etc. 11

Recovery Recovery is a ratio of the detector response of an analyte from an extracted sample to the detector response of the analyte in post extracted sample (spiked sample) %RE = response extracted sample x100 response post extracted spiked sample LC/MS/MS Method for Puerarin Column: Waters X-Terra C18 with guard, 2.1 x 100 mm, 3.5 micron Mobile Phase A: 10% MeCN + 10 mm NH4OAc Mobile Phase B: 70% MeCN + 10mM NH4OAc Gradient: 0 minutes = 100% A 6 minutes = 100% B 7 minutes = 100% A 10 minutes = Stop Injection Volume: 20 ul Flow Rate: 0.2 ml/min split flow Mass Spectrometer: Negative Electrospray Mass Transitions: 415/267 (Puerarin) 415/295 (Puerarin) 269/149 (apigenin, IS) 12

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Relative Intensity (%) Ion chromatograms of a rat serum spiked sample (0.01 M of puerarin) vs. blank serum 100 50 Blank Spiked with 0.01 M 0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 Time (min) Average serum concentration of puerarin versus time after Oral administration of 50 mg/kg puerarin Average serum conc. UM 4.50 4.00 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00 0 30 60 90 120 150 180 210 240 270 Time points (min) Prasain et al. (unpublished results) 14

MRM chromatogram showing separation of 11 phytoestrogens using a 2 min run time Prasain et al., 2010 15

Specificity of the assay - no peaks from matrix 1.6e5 Intensity, cps (A) 0.0 0.1 0.4 0.7 1.0 1.3 1.6 1.9 2.7e5 Intensity, cps (B) IS IS 0.0 0.1 0.5 0.9 1.3 1.7 1.9 Time, min Calibration range and lower limit of Quantification (LLOQ) of analytes 16

Precision and accuracy of quality control samples Comparison of precision intra-day and inter-day 17

Conclusions The sensitive & accurate analysis of biological samples remains a significant challenge. Although SPE and PPT can be HTS, LLE where extensive clean up is required, is less prone to matrix effects. Column temperature, LC column particles, gradient and run time can influence chromatographic separation. Method of validation is always performed with spiked matrix same as the biological sample following the validation criteria. 18