Page 80 - CRFTApplication Compendium_090613

2 Integrated Targeted Quantitation Method for Insulin and its Therapeutic Analogs
Overview
Purpose: Perform simultaneous qualitative measurements and quantitation on
endogenous insulin and/or therapeutic analogs at biological levels for research.
Methods: Incorporate pan-insulin Ab in the Thermo Scientific™ MSIA™ (Mass
Spectrometric Immunoassay) Tips for increased extraction efficiency of all insulin
variants that are detected, verified, and quantified using HR/AM MS and MS/MS data
on the Thermo Scientific™ Q Exactive™ mass spectrometer.
Results: Quantitation ranges reached 0.015 nM in plasma for all variants used in the
experiment with linear regressions of 0.99 or better. In addition, robust qual/quan
results were observed for multiple insulin variants spiked at different levels.
Introduction
The need to detect and quantify insulin and its therapeutic analogs has become
paramount for many different research assays 1. Insulin is typically present at sub
ng/mL in the presence of complex biological matrices requiring extraction/enrichment
protocols to be used prior to LC-MS detection and quantitation. In addition to
endogenous insulin quantification, variants are also used to stimulate the same
response and need to be quantified. Variants contain slight sequence variations to
effect bioavailability and are generally administered at sub ng/mL levels. To reduce
sample handling bias, a universal extraction method is required to facilitate
simultaneous insulin variant extraction for targeted quantitation. In addition, the LC-MS
detection method must be amenable to detection and quantification of known and
unknown variants.
Methods
Sample Preparation
All samples were prepared from a stock solution of plasma. To each well a 500 µL
aliquot of the plasma was added as well as 0.05 nM porcine insulin and used as an
internal standard. Three different sets of samples were prepared in the wells. The first
set had individual insulin variants spiked covering a range of 0.015 to 0.96 nM
increasing in 2-fold steps. The second set of samples had one insulin variant spiked
covering the same concentration range as that in sample set 1 except Humulin® S
was spiked in at a constant concentration of 0.06 nM. The last set of samples spiked
two different insulin variants over the expressed concentration range with Humulin S
spiked in at a constant concentration of 0.06 nM. Each sample was extracted using a
MSIA Thermo Scientific™ D.A.R.T. ™ (Disposable Automated Research Tips)
loaded with 3 µg of pan-insulin Ab in an automated method using the Thermo
Scientific™ Versette ™ Automated Liquid Handler2. Following insulin extraction,
washing, and elution into a new well, the samples were dried down and then
reconstituted in a 100 µL solution of 75:25:0.2% water/MeCN/formic acid with 15
mg/mL ACTH 1-24.
Liquid Chromatography (or more generically Separations)
An Thermo Scientific™ Dionex™ UltiMate™ 3000 RSLC system was used for all
experiments and 100 µL of each sample was separated on a 100 x 1 mm Thermo
Scientific™ ProSwift™ RP-4H 1 x 250 mm monolithic column using a linear gradient
(10-50% in 10 minutes) comprised of A) 0.1% formic acid in water and B) 0.1% formic
acid in MeCN. The column was heated to a temperature of 50 ºC.
Mass Spectrometry
All experiments were acquired using a Q Exactive mass spectrometer operated in
data-dependent/dynamic exclusion. A resolution setting of 70,000 (@ m/z 200) was
used for full scan MS and 17,500 for MS/MS events. Full scan MS data was acquired
using a mass range of 800-2000 Da and a targeted inclusion list was used to trigger all
data dependent events.
Data Analysis
All data was processed using Thermo Scientific™ Pinpoint™ 1.3 software. HR/AM
MS data extraction was used for quantitation. To provide additional levels of
qualitative analysis, the three most abundant precursor charge states per insulin
variant were used as well as the six most abundant isotopes per charge state. A mass
tolerance of ±5 ppm was used for all data extraction. Qualitative scoring was based on
mass error, precursor charge state distribution, and isotopic overlap as well as
corresponding LC elution peak profiles measured for each sample. Product ion data
was used for sequence verification. The measured AUC values for porcine insulin was
used as an internal standard for all samples.
Results
The protocol for targeted dete
sequence variants must have
selectivity of extraction and de
provide qualitative measurem
to normalize the entire method
data processing. Lastly, the p
reduce cost and complexity fo
Our workflow has been shown
cost internal standard in porci
sample analysis and data proc
extraction using the Ab coated
bind the insulin variants, wash
plate. Once the extraction wa
analysis. This process elimin
the detection/quantitative cap
FIGURE 1. Targeted extracti
to MSIA D.A.R.T tips. All sa
Following automated extrac
down prior to being reconst
FIGURE 2. Targeted data ext
on HR/AM MS data. Data fro
based on isotopic m/z value
AUC values from each isoto
In addition, qualitative analy
based on 2A) comparative p
factors) as well as 2b) isoto
2a
The subsequent LC-MS detec
distinguish insulin variants fro
states and isotopes. The data
multliple verification attributes
acquisition can also be used f
Decoupling the quantitative m
enables the method to probe
acquisition processing as new
region remains consistent. Fi
efficiency of the workflow acro