Da Huang

Bio: Da Huang is an academic researcher from London Centre for Nanotechnology. The author has contributed to research in topics: Recombinase Polymerase Amplification & Dipstick. The author has an hindex of 2, co-authored 3 publications receiving 39 citations.

Spin-enhanced nanodiamond biosensing for ultrasensitive diagnostics.

Abstract: The quantum spin properties of nitrogen-vacancy defects in diamond enable diverse applications in quantum computing and communications1. However, fluorescent nanodiamonds also have attractive properties for in vitro biosensing, including brightness2, low cost3 and selective manipulation of their emission4. Nanoparticle-based biosensors are essential for the early detection of disease, but they often lack the required sensitivity. Here we investigate fluorescent nanodiamonds as an ultrasensitive label for in vitro diagnostics, using a microwave field to modulate emission intensity5 and frequency-domain analysis6 to separate the signal from background autofluorescence7, which typically limits sensitivity. Focusing on the widely used, low-cost lateral flow format as an exemplar, we achieve a detection limit of 8.2 × 10−19 molar for a biotin–avidin model, 105 times more sensitive than that obtained using gold nanoparticles. Single-copy detection of HIV-1 RNA can be achieved with the addition of a 10-minute isothermal amplification step, and is further demonstrated using a clinical plasma sample with an extraction step. This ultrasensitive quantum diagnostics platform is applicable to numerous diagnostic test formats and diseases, and has the potential to transform early diagnosis of disease for the benefit of patients and populations. Lateral-flow in vitro diagnostic assays based on fluorescent nanodiamonds, in which microwave-based spin manipulation is used to increase sensitivity, are demonstrated using the biotin–avidin model and by the single-copy detection of HIV-1 RNA.

Clinical Validation of a Rapid Variant-Proof RT-RPA Assay for the Detection of SARS-CoV-2

Abstract: The COVID-19 pandemic has unveiled a pressing need to expand the diagnostic landscape to permit high-volume testing in peak demand. Rapid nucleic acid testing based on isothermal amplification is a viable alternative to real-time reverse transcription polymerase chain reaction (RT-PCR) and can help close this gap. With the emergence of SARS-CoV-2 variants of concern, clinical validation of rapid molecular tests needs to demonstrate their ability to detect known variants, an essential requirement for a robust pan-SARS-CoV-2 assay. To date, there has been no clinical validation of reverse transcription recombinase polymerase amplification (RT-RPA) assays for SARS-CoV-2 variants. We performed a clinical validation of a one-pot multi-gene RT-RPA assay with the E and RdRP genes of SARS-CoV-2 as targets. The assay was validated with 91 nasopharyngeal samples, with a full range of viral loads, collected at University College London Hospitals. Moreover, the assay was tested with previously sequenced clinical samples, including eleven lineages of SARS-CoV-2. The rapid (20 min) RT-RPA assay showed high sensitivity and specificity, equal to 96% and 97%, respectively, compared to gold standard real-time RT-PCR. The assay did not show cross-reactivity with the panel of respiratory pathogens tested. We also report on a semi-quantitative analysis of the RT-RPA results with correlation to viral load equivalents. Furthermore, the assay could detect all eleven SARS-CoV-2 lineages tested, including four variants of concern (Alpha, Beta, Delta, and Omicron). This variant-proof SARS-CoV-2 assay offers a significantly faster and simpler alternative to RT-PCR, delivering sensitive and specific results with clinical samples.

Lateral flow test engineering and lessons learned from COVID-19

Abstract: The acceptability and feasibility of large-scale testing with lateral flow tests (LFTs) for clinical and public health purposes has been demonstrated during the COVID-19 pandemic. LFTs can detect analytes in a variety of samples, providing a rapid read-out, which allows self-testing and decentralized diagnosis. In this Review, we examine the changing LFT landscape with a focus on lessons learned from COVID-19. We discuss the implications of LFTs for decentralized testing of infectious diseases, including diseases of epidemic potential, the ‘silent pandemic’ of antimicrobial resistance, and other acute and chronic infections. Bioengineering approaches will play a key part in increasing the sensitivity and specificity of LFTs, improving sample preparation, incorporating nucleic acid amplification and detection, and enabling multiplexing, digital connection and green manufacturing, with the aim of creating the next generation of high-accuracy, easy-to-use, affordable and digitally connected LFTs. We conclude with recommendations, including the building of a global network of LFT research and development hubs to facilitate and strengthen future diagnostic resilience. The feasibility of large-scale testing with lateral flow tests has been demonstrated in the COVID-19 pandemic. This Review examines lessons learned from the COVID-19 pandemic to inform the design and bioengineering of next-generation lateral flow tests to strengthen future diagnostic resilience.

Harnessing recombinase polymerase amplification for rapid detection of SARS-CoV-2 in resource-limited settings

Abstract: The COVID-19 pandemic has challenged testing capacity worldwide. The mass testing needed to stop the spread of the virus requires new molecular diagnostic tests that are faster and with reduced equipment requirement, but as sensitive as the current gold standard protocols based on polymerase chain reaction. We developed a fast (25-35 minutes) molecular test using reverse transcription recombinase polymerase amplification for simultaneous detection of two conserved regions of the virus, targeting the E and RdRP genes. The diagnostic platform offers two complementary detection methods: real-time fluorescence or visual dipstick. The analytical sensitivity of the test by real-time fluorescence was 9.5 (95% CI: 7.0-18) RNA copies per reaction for the E gene and 17 (95% CI: 11-93) RNA copies per reaction for the RdRP gene. The analytical sensitivity for the dipstick readout was 130 (95% CI: 82-500) RNA copies per reaction. The assay showed high specificity with both detection methods when tested against common seasonal coronaviruses, SARS-CoV and MERS-CoV model samples. The dipstick readout demonstrated potential for point-of-care testing, with simple or equipment-free incubation methods and a user-friendly prototype smartphone application was proposed with data capture and connectivity. This ultrasensitive molecular test offers valuable advantages with a swift time-to-result and it requires minimal laboratory equipment compared to current gold standard assays. These features render this diagnostic platform more suitable for decentralised molecular testing.

Mass production and dynamic imaging of fluorescent nanodiamonds

Abstract: Fluorescent nanodiamond is a new nanomaterial that possesses several useful properties, including good biocompatibility1, excellent photostability1,2 and facile surface functionalizability2,3. Moreover, when excited by a laser, defect centres within the nanodiamond emit photons that are capable of penetrating tissue, making them well suited for biological imaging applications1,2,4. Here, we show that bright fluorescent nanodiamonds can be produced in large quantities by irradiating synthetic diamond nanocrystallites with helium ions. The fluorescence is sufficiently bright and stable to allow three-dimensional tracking of a single particle within the cell by means of either one- or two-photon-excited fluorescence microscopy. The excellent photophysical characteristics are maintained for particles as small as 25 nm, suggesting that fluorescent nanodiamond is an ideal probe for long-term tracking and imaging in vivo, with good temporal and spatial resolution.

Ultrasensitive and Highly Specific Lateral Flow Assays for Point-of-Care Diagnosis.

Abstract: Lateral flow assays (LFAs) are paper-based point-of-care (POC) diagnostic tools that are widely used because of their low cost, ease of use, and rapid format. Unfortunately, traditional commercial LFAs have significantly poorer sensitivities (μM) and specificities than standard laboratory tests (enzyme-linked immunosorbent assay, ELISA: pM-fM; polymerase chain reaction, PCR: aM), thus limiting their impact in disease control. In this Perspective, we review the evolving efforts to increase the sensitivity and specificity of LFAs. Recent work to improve the sensitivity through assay improvement includes optimization of the assay kinetics and signal amplification by either reader systems or additional reagents. Together, these efforts have produced LFAs with ELISA-level sensitivities (pM-fM). In addition, sample preamplification can be applied to both nucleic acids (direct amplification) and other analytes (indirect amplification) prior to LFA testing, which can lead to PCR-level (aM) sensitivity. However, these amplification strategies also increase the detection time and assay complexity, which inhibits the large-scale POC use of LFAs. Perspectives to achieve future rapid (<30 min), ultrasensitive (PCR-level), and "sample-to-answer" POC diagnostics are also provided. In the case of LFA specificity, recent research efforts have focused on high-affinity molecules and assay optimization to reduce nonspecific binding. Furthermore, novel highly specific molecules, such as CRISPR/Cas systems, can be integrated into diagnosis with LFAs to produce not only ultrasensitive but also highly specific POC diagnostics. In summary, with continuing improvements, LFAs may soon offer performance at the POC that is competitive with laboratory techniques while retaining a rapid format.

Point-of-care COVID-19 diagnostics powered by lateral flow assay.

Abstract: Since its first discovery in December 2019, the global coronavirus disease 2019 (COVID-19) pandemic caused by the novel coronavirus (SARS-CoV-2) has been posing a serious threat to human life and health. Diagnostic testing is critical for the control and management of the COVID-19 pandemic. In particular, diagnostic testing at the point of care (POC) has been widely accepted as part of the post restriction COVID-19 control strategy. Lateral flow assay (LFA) is a popular POC diagnostic platform that plays an important role in controlling the COVID-19 pandemic in industrialized countries and resource-limited settings. Numerous pioneering studies on the design and development of diverse LFA-based diagnostic technologies for the rapid diagnosis of COVID-19 have been done and reported by researchers. Hundreds of LFA-based diagnostic prototypes have sprung up, some of which have been developed into commercial test kits for the rapid diagnosis of COVID-19. In this review, we summarize the crucial role of rapid diagnostic tests using LFA in targeting SARS-CoV-2-specific RNA, antibodies, antigens, and whole virus. Then, we discuss the design principle and working mechanisms of these available LFA methods, emphasizing their clinical diagnostic efficiency. Ultimately, we elaborate the challenges of current LFA diagnostics for COVID-19 and highlight the need for continuous improvement in rapid diagnostic tests.

Machine learning and computation-enabled intelligent sensor design

Abstract: Over the past several decades the dramatic increase in the availability of computational resources, coupled with the maturation of machine learning, has profoundly impacted sensor technology. In this Perspective, we discuss computational sensing with a focus on intelligent sensor system design. By leveraging inverse design and machine learning techniques, data acquisition hardware can be fundamentally redesigned to ‘lock-in’ to the optimal sensing data with respect to a user-defined cost function or design constraint. We envision a new generation of computational sensing systems that reduce the data burden while also improving sensing capabilities, enabling low-cost and compact sensor implementations engineered through iterative analysis of data-driven sensing outcomes. We believe that the methodologies discussed in this Perspective will permeate the design phase of sensing hardware, and thereby will fundamentally change and challenge traditional, intuition-driven sensor and readout designs in favour of application-targeted and perhaps highly non-intuitive implementations. Such computational sensors enabled by machine learning can therefore foster new and widely distributed applications that will benefit from ‘big data’ analytics and the internet of things to create powerful sensing networks, impacting various fields, including for example, biomedical diagnostics, environmental sensing and global health, among others. Traditional sensing techniques apply computational analysis at the output of the sensor hardware to separate signal from noise. A new, more holistic and potentially more powerful approach proposed in this Perspective is designing intelligent sensor systems that ‘lock-in’ to optimal sensing of data, making use of machine leaning strategies.

Toward Quantitative Bio-sensing with Nitrogen-Vacancy Center in Diamond.

Abstract: The long-dreamed-of capability of monitoring the molecular machinery in living systems has not been realized yet, mainly due to the technical limitations of current sensing technologies. However, recently emerging quantum sensors are showing great promise for molecular detection and imaging. One of such sensing qubits is the nitrogen-vacancy (NV) center, a photoluminescent impurity in a diamond lattice with unique room-temperature optical and spin properties. This atomic-sized quantum emitter has the ability to quantitatively measure nanoscale electromagnetic fields via optical means at ambient conditions. Moreover, the unlimited photostability of NV centers, combined with the excellent diamond biocompatibility and the possibility of diamond nanoparticles internalization into the living cells, makes NV-based sensors one of the most promising and versatile platforms for various life-science applications. In this review, we will summarize the latest developments of NV-based quantum sensing with a focus on biomedical applications, including measurements of magnetic biomaterials, intracellular temperature, localized physiological species, action potentials, and electronic and nuclear spins. We will also outline the main unresolved challenges and provide future perspectives of many promising aspects of NV-based bio-sensing.