| Literature DB >> 30291230 |
Nicole Stéphanie Galenkamp1, Misha Soskine1, Jos Hermans2, Carsten Wloka1, Giovanni Maglia3.
Abstract
Crucial steps in the miniaturisation of biosensors are the conversion of a biological signal into an electrical current as well as the direct sampling of bodily fluids. Here we show that protein sensors in combination with a nanopore, acting as an electrical transducer, can accurately quantify metabolites in real time directly from nanoliter amounts of blood and other bodily fluids. Incorporation of the nanopore into portable electronic devices will allow developing sensitive, continuous, and non-invasive sensors for metabolites for point-of-care and home diagnostics.Entities:
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Year: 2018 PMID: 30291230 PMCID: PMC6173770 DOI: 10.1038/s41467-018-06534-1
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919
Fig. 1Nanopore glucose sensor for biological samples. a Cut-through of a surface depiction of a ClyA nanopore (grey) inserted into a lipid bilayer (yellow) containing a glucose-binding protein (GBP) created with the VMD software. GBP residues are coloured by the software according to their type. On the right are cartoon representations of GBP proteins in the open, ligand-free state and closed, liganded state. Right from the cartoon is a typical output signal (current trace) showing the entry of GBP proteins inside the nanopore. IB is the blocked pore current signal and IO the open pore current signal. b Effect of increasing concentrations of glucose added to the trans solution to the signal induced by GBP proteins internalised into a ClyA nanopore at −90 mV. On the left are shown current traces, on the right all-point histograms of ~50 s of a current trace. c Dependency of the opening and closing rates, measured as the inverse of dwell times (top) and the fraction of the closed state (bottom) on the concentration of glucose in the trans solution. The lines in the top graph are linear fits and the line in the graph below indicates the fitting to a Hill function. The solution used for the electrical recordings contained 150 mM NaCl and 15 mM Tris-HCl set at pH 7.5. Current traces were collected applying a Bessel low-pass filter with a 2 kHz cutoff and sampled at 10 kHz at room temperature (25 °C). A post-acquisition Gaussian filter of 200 Hz was applied. Error bars represent the standard deviation between independent experiments (N = 3)
Comparison of different methods measuring the concentrations of glucose and asparagine in different biological samples
| Glucose | Asparagine | |||||
|---|---|---|---|---|---|---|
| Nanopore | Sampled volume | Commercial assay | Nanopore | Sampled volume | LC assay | |
| Sweat | 105 ± 9 µM | 2 µL | 105 ± 7 µM | 94.6 ± 5.0 µM | 5 µL | 90.9 ± 4.1 µM |
| Urine | 368 ± 7.5 µM | 200 nL | 381 ± 6 µM | 35.4 ± 2.8 µM | 4 µL | 89.7 ± 3.6 µM |
| Saliva | 5.71 ± 0.48 µM | 15 µL | 10.4 ± 7.9 µM | 1.36 ± 0.22 µM | 30 µL | ND |
| Blood sample 1 | 5.09 ± 0.88 mM | 10 nL | 5.3 mM | 10.2 ± 0.2 µMa | 5–15 µL | 6.7 ± 0.2 µMa |
| Blood sample 2 | 4.91 mM | 10 nL | 4.9 mM | |||
| Blood sample 3 | 4.21 mM | 10 nL | 4.4 mM | |||
The concentration of glucose was measured using a glucose (HK) assay kit (Sigma-Aldrich) except for blood samples, where an Accu-Chek® Aviva (Roche) system was used. Since the latter system did not provide an error in the measurement, three different blood samples were tested. The concentration of asparagine was measured using a HPLC assay coupled with fluorescence detection. Sweat and urine were directly sampled, while the proteins in saliva and serum were precipitated with 8% trichloroaceticacid prior the HPLC measurements. The concentration of asparagine in saliva was too low to be measured with the HPLC assay
aSince a pre-purification step was required for LC sampling, serum instead of blood was used for the quantification of asparagine. Error is SD
Fig. 2Binding constants for asparagine binding to SBD1. a Current traces and all-point current histograms showing the binding of asparagine to SBD1 (120 nM, cis) inside a ClyA nanopore. Asparagine was added to the trans solution and the voltage was set to −90 mV. b Dependency of the opening and closing rates (calculated from the inverse of the dwell times) on the concentration of asparagine in the trans solution. The black and blue lines are linear fits. c Dependency of the percentage of the closed configuration on the concentration of asparagine in the trans solution. The blue line indicates fitting to a Hill function with the Hill coefficient set to one. The solution used for the electrical recording contained 150 mM NaCl, 15 mM Tris-HCl, pH 7.5. Current traces were collected applying a Bessel low-pass filter with a 2 kHz cutoff and sampled at 10 kHz at room temperature (25 °C). A post-acquisition Gaussian filter of 200 Hz was applied. Error bars represent the standard deviation between independent experiments (N = 3)
Fig. 3Multiplexed detection of glucose and asparagine from sweat. Schematic representation (above) and current blockades with its all-point current histogram (below) of two consecutive events showing the entry of SBD1 and GBP into a ClyA nanopore, respectively, under −90 mV applied transmembrane potential. The trans solution contained 5 µL of sweat constituting a 100-fold dilution. The solution used for the electrical recordings contained 150 mM NaCl and 15 mM Tris-HCl set to pH 7.5. Current traces were collected applying a Bessel low-pass filter with a 2 kHz cutoff and sampled at 10 kHz at room temperature (25 °C). A post-acquisition Gaussian filter of 200 Hz was applied