Direct electrical quantification of glucose and asparagine from bodily fluids using nanopores

Galenkamp, Nicole Stéphanie; Soskine, Misha; Hermans, Jos; Wloka, Carsten; Maglia, Giovanni

doi:10.1038/s41467-018-06534-1

Cited by 119 publications

(161 citation statements)

References 34 publications

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“…Alternatively, it may be that other read strategies (e.g. nanopores [39,40]) would provide higher sensitivity than MS, but the protocol demonstrated here has ample room to increase capacity by several orders of magnitude.…”

Section: Discussionmentioning

confidence: 99%

Encoding Information in Synthetic Metabolomes

Kennedy

Arcadia

Geiser

et al. 2019

Preprint

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Biomolecular information systems o↵er numerous potential advantages over conventional semiconductor technologies. Downstream from DNA, the metabolome is an informationrich molecular system with diverse chemical dimensions which could be harnessed for information storage and processing. As a proof of principle of postgenomic data storage, here we demonstrate a workflow for representing abstract data in synthetic metabolomes. Our approach leverages robotic liquid handling for writing digital information into chemical mixtures, and mass spectrometry for extracting the data. We present several kilobytescale image datasets stored in synthetic metabolomes, which are decoded with accuracy exceeding 98-99% using multi-mass logistic regression. Cumulatively, >100,000 bits of digital image data was written into metabolomes. These early demonstrations provide insight into the benefits and limitations of postgenomic chemical information systems.

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Section: Discussionmentioning

confidence: 99%

Encoding Information in Synthetic Metabolomes

Kennedy

Arcadia

Geiser

et al. 2019

Preprint

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“…Detailed knowlegde of the ionic environment can be valuable to experimentalists who seek to trap and study single enzymes with ClyA. 30,97,100 Moreover, it gives insight into the origin of the ion current rectification, ion selectivity and the electro-osmotic flow. We evaluated the densities of both Na We also observed a stark difference between their sensitivities to the applied bias voltage, particularly at low salt concentrations ( Fig.…”

Section: Ion Concentration Distributionmentioning

confidence: 99%

“…Hence, it strongly influences the capture and translocation of biomolecules including nucleic acids, 36,47,122 peptides, 28,123,124 and proteins. 25,27,30,[96][97][98][99]125 Because the drag exerted by the EOF depends primarily on the size and shape of the biomolecule of interest and not on its charge, 125 it can be harnassed to capture molecules even against the electric field. 25 The EOF is a consequence of interaction between the fixed charges on the nanopore walls and mobile charges in the electrolyte.…”

Section: Transport Of Water Through Clyamentioning

confidence: 99%

“…[1][2][3][4][5][6] One of the primary driving forces behind this research is the development of nanopores as label-free, stochastic sensors at the ultimate analytical limit (i.e., single molecule). 7-10 Such detectors have applications ranging from the analysis of biopolymers such as DNA [11][12][13][14][15][16][17][18] or proteins, [19][20][21][22][23] to the detection and quantification of biomarkers, [24][25][26][27][28][29][30] to the fundamental study of chemical or enzymatic reactions at the single molecular level. 22,[31][32][33][34] Nanopores are typically operated in the resistive-pulse mode, where the fluctuations of their ionic conductance are monitored over time.…”

Section: Introductionmentioning

confidence: 99%

“…and the solvent in terms of density, viscosity92 and relative permittivity 93 . To validate our new framework, we applied it directly to a 2D-axisymmetric model of Cytolysin A (ClyA), a large protein nanopore that typically contains 12 subunits 95 or more96 and has been extensively used in experimental studies of both proteins27,30,[96][97][98][99][100] and DNA 17,101. .…”

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confidence: 99%

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Modeling of Ion and Water Transport in the Biological Nanopore ClyA

Willems

Ruić

Lucas

et al. 2020

Preprint

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In recent years, the protein nanopore cytolysin A (ClyA) has become a valuable tool for the detection, characterization and quantification of biomarkers, proteins and nucleic acids at the single-molecule level. Despite this extensive experimental utilization, a comprehensive computational study of ion and water transport through ClyA is currently lacking. Such a study yields a wealth of information on the electrolytic conditions inside the pore and on the scale the electrophoretic forces that drive molecular transport. To this end we have built a computationally efficient continuum model of ClyA which, together with an extended version of Poison-Nernst-Planck-Navier-Stokes (ePNP-NS) equations, faithfully reproduces its ionic conductance over a wide range of salt concentrations. These ePNP-NS equations aim to tackle the shortcomings of the traditional PNP-NS models by self-consistently taking into account the influence of both the ionic strength and the nanoscopic scale of the pore on all relevant electrolyte properties. In this study, we give both a detailed description of our ePNP-NS 1 model and apply it to the ClyA nanopore. This enabled us to gain a deeper insight into the influence of ionic strength and applied voltage on the ionic conductance through ClyA and a plethora of quantities difficult to assess experimentally. The latter includes the cation and anion concentrations inside the pore, the shape of the electrostatic potential landscape and the magnitude of the electro-osmotic flow. Our work shows that continuum models of biological nanopores-if the appropriate corrections are applied-can make both qualitatively and quantitatively meaningful predictions that could be valuable tool to aid in both the design and interpretation of nanopore experiments.

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Automated Electrical Quantification of Vitamin B1 in a Bodily Fluid using an Engineered Nanopore Sensor

et al. 2021

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The ability to measure the concentration of metabolites in biological samples is important, both in the clinic and for home diagnostics. Here we present a nanopore‐based biosensor and automated data analysis for quantification of thiamine in urine in less than a minute, without the need for recalibration. For this we use the Cytolysin A nanopore and equip it with an engineered periplasmic thiamine binding protein (TbpA). To allow fast measurements we tuned the affinity of TbpA for thiamine by redesigning the π‐π stacking interactions between the thiazole group of thiamine and TbpA. This substitution resulted furthermore in a marked difference between unbound and bound state, allowing the reliable discrimination of thiamine from its two phosphorylated forms by residual current only. Using an array of nanopores, this will allow the quantification within seconds, paving the way for next‐generation single‐molecule metabolite detection systems.

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Direct electrical quantification of glucose and asparagine from bodily fluids using nanopores

Cited by 119 publications

References 34 publications

Encoding Information in Synthetic Metabolomes

Encoding Information in Synthetic Metabolomes

Modeling of Ion and Water Transport in the Biological Nanopore ClyA

Automated Electrical Quantification of Vitamin B1 in a Bodily Fluid using an Engineered Nanopore Sensor

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