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Targeted Quantitation of Insulin and Its Therapeutic Analogs for Research
Overview
Purpose:
To perform simultaneous qualitative and quantitative analyses of endogenous
insulin and/or therapeutic analogs at biological levels for research.
Methods:
We used a pan-anti insulin antibody in
Thermo Scientific™
Mass
Spectrometric Immunoassay (MSIA) D.A.R.T.’S
TM
pipette tips for highly-selective affinity
purification of all insulin analogs. Analogs were detected, verified, and quantified using
high-resolution, accurate-mass (HRAM) MS and MS/MS data from a
Thermo Scientific™ Q Exactive™ mass spectrometer.
Results:
We achieved a lower-limit-of-detection (LLOD) of 15 pM in plasma for all
variants used with linear regressions of 0.99 or better. Further, we demonstrate inter-
and intra-
day CV’s of < 3% and spike and recovery resulted in recoveries of 96–
100%.
Introduction
The measurement of insulin is a paramount metric in clinical research, therapeutic
research, forensic, and sports doping applications. Conventional insulin analytical
methods are plagued by the inability to differentiate endogenous insulin from exogenous
insulin analogs. The use of LC/MS can overcome this shortcoming
1
; however, the
LC/MS methods to date lack the analytical sensitivity demanded by the field. Therefore,
a highly selective sample interrogation workflow is required to address the complexity of
plasma samples and, ultimately, for accurate and sensitive LC/MS detection and
quantification. To meet these requirements, a MSIA research workflow was developed
for the high-throughput, analytically sensitive quantification of insulin and its analogs
from human donor plasma.
Methods
Sample Preparation
For spike and recovery studies, both neat and donor plasma samples containing a mix
of insulin and its analogs were prepared. Insulin was added at three different amounts
that spanned the dynamic range to the donor plasma. Up to four analogs were prepared
in a single sample. For the limit-of-detection and limit-of-quantification studies, 1.5 pM to
960 pM insulin was added to bovine serum albumin in phosphate buffered saline.
Additionally, either 0.05 nM of a heavy version of insulin or porcine insulin was added as
an internal reference standard to each well of 500 µL plasma.
Samples were then addressed for the first stage in the MSIA workflow. Targeted
selection was achieved using insulin MSIA Disposable Automated Research Tip’s
(D.A.R.T.’S) (Figure 1). The affinity purification step in the MSIA workflow was automated
by the Thermo Scientific™
Versette
™ automated liquid handler. Following extraction,
intact insulin analogs were eluted with 75 µL 70:30 water/acetonitrile with 0.2% formic
acid with 15 µg/mL ACTH 1-24. The final concentration was adjusted to 75:25
water/acetonitrile with 0.2% formic acid for LC/MS analysis.
Liquid Chromatography
A Thermo Scientific™ Dionex™ UltiMate™ 3000 RSLC system was used for all
experiments. 100 µL of each sample was separated on a 100 x 1 mm Thermo
Scientific™
ProSwift
™ column using a linear gradient (10–
50% in 10 min) comprised of
A) 0.1% formic acid in water and B) 0.1% formic acid in acetonitrile. The column was
heated to 50 ºC.
Mass Spectrometry
All data was acquired using a Q Exactive Orbitrap mass spectrometer operated in data-
dependent mode with dynamic exclusion enabled. Full scan MS data was acquired with
a resolution setting of 70,000 (at
m/z
200) and using a mass range of 800
–
2000 Da. A
targeted inclusion list was used to trigger MS/MS events and MS/MS was acquired with
a resolution setting of 17,500 (at
m/z
200).
Data Analysis
Thermo Scientific™ Pinpoint™ software version 1.3 was used to analyze all LC/MS
data. HRAM measurements were used for qualitative and quantitative measurement of
insulin and its analogs.
The three most abundant precursor charge states per analog and the six most abundant
isotopes per charge state provided qualitative validation for insulin and its analogs.
Qualitative scoring was based on mass error, precursor charge state distribution,
isotopic overlap, and corresponding LC elution peak profiles. Product ion data was used
for sequence verification.
FIGURE 1. Targeted se
its analogs are selecti
compounds. Lastly, th
which is ready for LC/
Results
FIGURE 2. HRAM MS
ion chromatograms fo
isotopic
m/z
values fro
from each isotope wer
Additionally, each ins
2a) comparative peak
well as 2b) isotopic di
Qualitative Validation
One of the primary limit
distinguish between end
insulin pan-
antibody in t
the
-chain that is cons
capture and detection of
region remains conserv
the MSIA workflow enab
ability to screen for uns
LC/MS detection using
insulin variants from the
precursor charge states
approach. Figure 3 sho
fragmentation patterns f
confirm the identity of in
2a
For quantification, a m
Amounts of each insuli
(AUC) values, normaliz
from standard curve dat