Magnetic sensing technology for molecular analyses

Abstract

Magnetic biosensors, based on nanomaterials and miniature electronics, have emerged as a powerful diagnostic platform. Benefiting from the inherently negligible magnetic background of biological objects, magnetic detection is highly selective even in complex biological media. The sensing thus requires minimal sample purification and yet achieves a high signal-to-background contrast. Moreover, magnetic sensors are also well-suited for miniaturization to match the size of biological targets, which enables sensitive detection of rare cells and small amounts of molecular markers. We herein summarize recent advances in magnetic sensing technologies, with an emphasis on clinical applications in point-of-care settings. Key components of sensors, including magnetic nanomaterials, labeling strategies and magnetometry, are reviewed.

Figure 1. Different types of MNPs developed for magnetic sensing

(a) Metal-doped ferrite MNPs. The top row shows transmission electron micrograph (TEM) images of 12-nm sized MnFe₂O₄, Fe₃O₄, CoFe₂O₄ and NiFe₂O₄ MNPs. Scale bar, 50 nm. The middle row lists the mass magnetization values of the corresponding MNPs. The bottom row is schematics of spin alignments of magnetic ions in spinel structure. MnFe₂O₄ exhibits high magnetization due to the high spin quantum number (5/2) of Mn²⁺. (b) Size-dependent magnetization of Fe₃O₄ MNPs. As the particle size increases, the relative amount of canted spins decreases, which results in the increase of net magnetization. (c) Effect of particle shape on its magnetic property. Cubic MNPs have higher saturation magnetization than spherical particles, since the cubic geometry allows more spins to be aligned in the same direction of applied magnetic fields. (d) Fe/Fe₃O₄ core/shell MNPs. These particle have a hybrid structure, and assume higher magnetization than ferrite particles. (e) TEM image of multicore MNPs (left) and magnetization of MNP clusters (right). Clustering MNPs can significantly increase the net magnetic moment of overall particles.^, (Reproduced with permission from ref. . Copyright 2007 Nature Publishing Group. Reproduced with permission from ref. . Copyright 2011 American Chemical Society. Reproduced with permission from ref. . Copyright 2012 American Chemical Society. Reproduced with permission from ref. , and . Copyright 2011, 2007, 2008 John Wiley and Sons, Inc.)

Figure 2. Molecular targeting and labeling strategies

(a) Clustering assay. In the presence of binding targets, multivalent MNPs aggregate by crossing-linking. Such changes in the organizational state of MNPs can be measured by NMR relaxometry or Brownian relaxation measurements, without the need for additional washing steps. (b) Sandwich labeling. By functionalizing a solid substrate with affinity ligands, small molecular targets can be effectively enriched against a complex biological background. Secondary MNP labeling after the initial capture further brings MNPs close to the sensor surface. (c) Direct labeling. For large biological entities, such as mammalian cells, the whole target can be labelled with affinity ligands and subsequently with MNPs. (d) Magnetic amplification. By grafting multiple layers of MNPs onto a target, through the sequential applications of MNPs modified with orthogonal binding partners, magnetic signal can be amplified to detect rare molecular targets. (Adopted with permission from ref. and . Copyright 2002, 2010 Nature Publishing Group. Reproduced with permission from ref. . Copyright 2011 John Wiley and Sons, Inc.)

Figure 3. NMR-based magnetic detection

(a) Assay principle. Samples containing magnetically-labeled biological objects display faster relaxation of proton NMR signal. (b) A new miniaturized NMR (μNMR) system was developed for point-of-care operations. The system features automatic system tuning and user-friendly interface. (c) Schematic of the magnet assembly and the NMR probe. The microcoil is embedded in a polymer (polydimethylsiloxane/PDMS) block with the entire coil-bore accessible, and a thin-walled tube is used for sample-loading. (d) The NMR electronics is designed for standalone operation and high programability. (e) A multifunctional fluidic cartridge was developed for bacterial detection. The device integrates polymerase-chain-reaction (PCR) chambers, torque-assisted valves, mixing channels and a microcoil. Bacterial samples, PCR reagents, microbeads, and MNPs are loaded onto the chip. After on-chip PCR, magnetic labeling of the microbeads takes place along the mixing channel. The magnetically-labeled beads are then purified and concentrated into the μNMR probe (microcoil) by the membrane filter. (f) The fluidic device in (e) was used to detect Mycobacterium tuberculosis (MTB) in clinical sputum specimens. Compared with samples collected from MTB-positive patients, samples collected from MTB/HIV-positive patients showed higher bacterial burden. Data is represented as mean ± s.d. from triplicate measurements. Reproduced with permission from ref. . Copyright 2011 RSC Publishing. Reproduced with permission from ref. . Copyright 2013 Nature Publishing Group.)

Figure 4. Multiplexed Brownian detection of differently sized MNPs

(a) The alternating current (AC) magnetic susceptibility is measured using a quadrature detector. The signals both in-phase and 90 degree out-of-phase with respect to the AC current source are measured, which correspond to the real and imaginary component of the magnetic susceptibility, respectively. PLL, phase-locked loop. (b) The out-of-phase (imaginary) component of the susceptibility has its maximum when the excitation frequency is close to the Brownian relaxation time of the particle. The peak position shifts for differently sized particles, enabling 25 nm core (red) and 50 nm core (blue) MNPs to be measured simultaneously (green). (Reproduced with permission from ref. . Copyright 2011 IOP Publishing Ltd.)

Figure 5. Giant magnetoresistance (GMR) detection of biomarkers

(a) GMR sensors consist of alternating layers of ferromagnetic and non-magnetic materials. The magnetization of a reference layer is pinned and the magnetization of a free layer is able to change with an applied field. The presence of MNP in close proximity to the sensor creates a local field which changes the magnetization of the free layer. H_ext, external magnetic field. (b) As the magnetization of the free layer changes under varying external magnetic fields, the overall electrical resistance of a GMR sensor changes as well. (c) An array of 256 GMR sensors (top) and its interface chip (bottom). The GMR sensor is mounted on a disposable test stick; the interface chip is on the reader stick. This approach has been applied to detect soluble proteins in clinical samples. A sandwich assay is used to bind MNPs close to the GMR sensor surface. CMOS, complementary metal-oxide-semiconductor. (Reproduced with permission from ref. . Copyright 2013 IEEE.)

Figure 6. Integrated Hall sensor for magnetic bead detection

(a) Die photograph of an integrated Hall sensor integrate circuit (IC). The chip contains 10240 Hall-effect sensors, evaluation electronics, and electromagnets for polarizing field generation. (b) Cross section of a single Hall sensing element. A pair of metal wires on both sides of the Hall-effect sensor are used to generate the polarizing field to magnetize the bead. (c) Magnetic beads are detected via relaxation measurement. The polarization magnetic field is applied to magnetic beads. Subsequently, the field is turned off, and the remnant decaying magnetic field from the bead is measured. The measurement is free from the large offset coming from the polarizing field. (d) Magnetic beads (2.8 μm) were detected in the entire sensing area (0.64 mm²). The sensitivity was down to 0.1% coverage of the sensing area. (Reproduced with permission from ref. and . Copyright 2012, 2013 IEEE.)

Figure 7. MicroHall (μHall) sensor for single cell detection

(a) Each cell, targeted with MNPs, generates magnetic fields that are detected by the μHall sensor. The Hall voltage (V_H) is proportional to the MNP counts. B₀, external magnetic field. (b) The sensing area has a 2 × 4 array of μHall elements. The dotted lines indicate the location of fluidic channel. The sensors are arranged into an overlapping array across the fluidic channel width. (c) The μHall system accurately measured the expression levels of epithelial cell adhesion molecule (EpCAM) in different cell lines; the inset shows the same measurements by flow cytometry. (d) Clinical applications of the μHall system. Circulating tumor cells (CTCs) in patient blood samples (n = 20) were detected using either the μHall system (top) or the clinical gold-standard system, CellSearch (bottom). The μHall enumerated a higher number of CTCs across all patient samples. (Reproduced with permission from ref. . Copyright 2012 American Association for the Advancement of Science AAAS.)

Figure 8. Diamond-based magnetic sensing

(a) Structure of the nitrogen (N) and vacancy (V) inside a diamond lattice. C, carbon. (b) Energy state diagram. The NV center has a spin-triplet ground state (³A₂) with a 2.87 GHz zero-field splitting between the m_s = 0 and m_s = ±1 spin states. Optical excitation (532 nm) pumps spins to the excited state (³E), which leads to the emission of a photon (638–800 nm). The m_s = 0 spin state has a stronger fluorescence than the m_s = ±1 states. When an external field (B₀) is applied, the m_s = ±1 states split by 2γB₀, where γ is the gyromagnetic ratio of the NV electronic spin. This field (B₀) can thus be measured by monitoring the fluorescence emission, while applying a continuous microwave. When the applied microwave frequency is on resonance with either of the m_s = ±1 state transitions from m_s = 0, the fluorescence rate decreases. (c) Detection of magnetotactic bacteria with a NV-diamond sensor. Top and bottom left images are from optical and scanning electron microscopy (SEM), respectively. Measured magnetic field projections along the x axis (B_x), y axis (B_y) and z axis (B_z) within the same field-of-view are shown in the top row. The bottom row shows simulated magnetic field projections, assuming that magnetic nanoparticle locations match those in the SEM image. (Reproduced with permission from ref. and . Copyright 2012, 2013 Nature Publishing Group.)