(109b) Competitive Protein-Based Fluorescent Biosensor for Glucose Detection in Exhaled Breath Condensate | AIChE

(109b) Competitive Protein-Based Fluorescent Biosensor for Glucose Detection in Exhaled Breath Condensate

Authors 

Tankasala, D. - Presenter, Purdue University
Ejendal, K., Purdue University
Kinzer-Ursem, T. L., Purdue University
Linnes, J., Purdue University

justify">Despite recent advances in the development of non-invasive glucose biosensors,
reliable measurement of glucose presence at very low concentrations in certain
non-invasive fluids is highly desired. The current gold standard for glucose
measurements involve electrochemical sensors to detect glucose oxidase (GOx);
however, the high dissociation constant of the GOx enzyme prevents it from
being able to distinguish sub-micromolar concentration changes of glucose. As
alternative non-invasive fluids, such as exhaled breath condensate, are being
examined for glucose detection, there is a greater need for a highly sensitive
biosensor that can detect and resolve changes in sub-micromolar glucose
concentrations.  Based on this need, we have developed a fluorescent biosensor using
the E. coli glucose binding protein (GBP) as a molecular recognition
element. GBP is an attractive alternative because the protein has a higher affinity
for glucose (KD = 0.35 µM) compared to that of GOx (KD =
20 mM).

justify">In this work, we selectively label GBP co-translationally in the E.
coli
recombinant expression system using a chemoenzymatic tagging method.
In this method, GBP is labeled with an azide functionality at the N-terminus,
which allows for rapid bio-orthogonal conjugation to surfaces using
azide-alkyne cycloaddition – a common click chemistry technique. As
proof-of-concept, we have demonstrated selective labeling of the GBP to both an
alkyne- and dibenzocyclooctyne (DBCO)-labeled fluorophore, TAMRA, directly from
E. coli cell lysate using copper-mediated and copper-free click
chemistry, respectively. Due to their high photostability, large Stoke’s
shifts, and low pH and temperature dependence, we use CdSe/ZnS quantum dots
(QDs) functionalized with DBCO as a fluorescent nanomaterial for bio-orthogonal
conjugation to azide-labeled GBP directly from cell lysate[1].
Copper-free click chemistry is employed to avoid irreversible quenching of QDs
by copper (Cu2+)[2].

justify">While GBP binds to both glucose and galactose, it has a higher
affinity for glucose (KD = 0.35 µM) over galactose (KD =
1.4 µM)[3];
thus, galactose can be harnessed as a competitive binding molecule in a
fluorescent assay. Förster resonance energy transfer (FRET) is a common method
used in fluorescence-based detection, in which the distance between the donor
and acceptor molecules determines the rate of energy transfer. The transfer of
energy leads to a reduction in the donor’s fluorescence intensity and an
increase in the acceptor’s emission intensity, provided there is close
proximity and good spectral overlap between the two molecules.

justify">Here, FRET is utilized to detect the presence of glucose based on the
distance between the donor molecule (QD) and an acceptor molecule designed to
quench the QD emission. A quencher molecule was designed using a
galactose-analog covalently bound to a black-hole quencher (BHQ2) fluorophore
that has overlapping emission spectra with the QD. When samples containing
glucose are introduced to the QD-BHQ2 system, the galactose-quencher is
displaced by the glucose and the fluorescence of the glucose-bound GBP-QD
increases proportionally to the concentration of glucose (Fig. 1).

justify">A computational model simulating galactose binding to GBP, the
introduction of glucose, and the resultant competition of galactose and glucose
binding to GBP has been developed using parameters determined by Miller et al.
(Fig. 2)[4].
This model indicates that upon the introduction of glucose to galactose-bound
GBP, the system arrives at equilibrium within 10 seconds and can provide a
linear response over a range of glucose concentrations. As a conservative
estimate, at a high galactose concentration (10 µM), a low concentration of
glucose (1 µM) can displace over 60% of the galactose-bound GBP. At this level,
we would expect at least a 230% increase in fluorescent signal.

justify">This presentation will discuss our work in selectively conjugating the
GBP protein onto highly-photostable quantum dots using copper-free click
chemistry. Subsequently, we will present the characterization of competitive
fluorescent quenching when interfaced with a galactose-quencher on this quantum
dot system through fluorescence response curves. To demonstrate specificity of
our system to glucose detection at low concentrations, the fluorescence
response curves will be compared to those generated with the sensor titrated
with galactose, fructose, and other non-specific monosaccharides. Together,
this work will enable the detection of low concentrations of glucose such as
those found in non-invasive sample matrices such as exhaled breath.

margin-left:32.0pt;margin-bottom:.0001pt;text-indent:-32.0pt;line-height:normal;
text-autospace:none">[1]         N. Tajarrod, M. K. Rofouei, M.
Masteri-Farahani, and R. Zadmard, “A quantum dot-based fluorescence sensor for
sensitive and enzymeless detection of creatinine,” Anal. Methods, vol.
8, no. 30, pp. 5911–5920, 2016.

margin-left:32.0pt;margin-bottom:.0001pt;text-indent:-32.0pt;line-height:normal;
text-autospace:none">[2]         V. R. Mann, A. S. Powers, D. C. Tilley, J. T.
Sack, and B. E. Cohen, “Azide–Alkyne Click Conjugation on Quantum Dots by
Selective Copper Coordination,” ACS Nano, vol. 12, no. 5, pp. 4469–4477,
May 2018.

margin-left:32.0pt;margin-bottom:.0001pt;text-indent:-32.0pt;line-height:normal;
text-autospace:none">[3]         A. V Fonin, O. V Stepanenko, O. I. Povarova,
C. A. Volova, E. M. Philippova, G. S. Bublikov, I. M. Kuznetsova, A. P.
Demchenko, and K. K. Turoverov, “Spectral characteristics of the mutant form
GGBP/H152C of D-glucose/D-galactose-binding protein labeled with fluorescent
dye BADAN: influence of external factors,” PeerJ, vol. 2, p. e275, Nov.
2014.

margin-left:32.0pt;margin-bottom:.0001pt;text-indent:-32.0pt;line-height:normal;
text-autospace:none">[4]         D. W. Miller and K. A. Dill, “Ligand binding
to proteins: the binding landscape model,” Protein Sci., vol. 6, no. 10,
pp. 2166–2179, Oct. 1997.

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