Cancer diagnosis with DNA molecular computation

Noninvasive Multiplexed Analysis of Bladder Cancer-Derived Urine Exosomes via Janus Magnetic Microspheres

Bladder cancer greatly endangers human health, and its early diagnosis is of vital importance. Exosomes, which contain proteins and nucleic acids related to their source cells, are expected to be an emerging biomarker for bladder cancer detection. Here, we propose a novel system for multiplexed analysis of bladder cancer-derived urine exosomes based on Janus magnetic microspheres as barcoded microcarriers. The microcarriers are constructed by droplet-templated coassembly of colloidal silica nanoparticles and magnetic nanoparticles under a magnetic field. The microcarriers possess one hemisphere with structural color and the other hemisphere with magneto-responsiveness. Benefiting from the unique structure, these Janus microcarriers could serve as barcodes and could move controllably in a sample solution, thus realizing the multiplex detection of exosomes with high sensitivity. Notably, the present platform is noninvasive since a urine specimen, as an ideal source of bladder cancer-derived exosomes, is employed as the sample solution. This feature, together with the good sensitivity, specificity, low sample consumption, and easy operation, indicates the great potential of the platform for bladder cancer diagnosis in clinical applications.

An automated DNA computing platform for rapid etiological diagnostics

Rapid and accurate classification of the etiology for acute respiratory illness not only helps establish timely therapeutic plans but also prevents inappropriate use of antibiotics. Host gene expression patterns in peripheral blood can discriminate bacterial from viral causes of acute respiratory infection (ARI) but suffer from long turnaround time, as well as high cost resulting from the measurement methods of microarrays and next-generation sequencing. Here, we developed an automated DNA computing-based platform that can implement an in silico trained classification model at the molecular level with seven different mRNA expression patterns for accurate diagnosis of ARI etiology in 4 hours. By integrating sample loading, marker amplification, classifier implementation, and results reporting into one platform, we obtained a diagnostic accuracy of 87% in 80 clinical samples without the aid of computer and laboratory technicians. This platform creates opportunities toward an accurate, rapid, low-cost, and automated diagnosis of disease etiology in emergency departments or point-of-care clinics.

Pattern Recognition of microRNA Expression in Body Fluids Using Nanopore Decoding at Subfemtomolar Concentrations

This paper describes a method for detecting microRNA (miRNA) expression patterns using the nanopore-based DNA computing technology. miRNAs have shown promise as markers for cancer diagnosis due to their cancer type specificity, and therefore simple strategies for miRNA pattern recognition are required. We propose a system for pattern recognition of five types of miRNAs overexpressed in bile duct cancer (BDC). The information of miRNAs from BDC is encoded in diagnostic DNAs (dgDNAs) and decoded electrically by nanopore analysis. With this system, we succeeded in the label-free detection of miRNA expression patterns from the plasma of BDC patients. Moreover, our dgDNA-miRNA complexes can be detected at subfemtomolar concentrations, which is a significant improvement compared to previously reported limits of detection (∼10^-12 M) for similar analytical platforms. Nanopore decoding of dgDNA-encoded information represents a promising tool for simple and early cancer diagnosis.

Recent advances in aptamer-based targeted drug delivery systems for cancer therapy

The past decade has become an important strategy in precision medicine for the targeted therapy of many diseases, expecially various types of cancer. As a promising targeted element, nucleic acid aptamers are single-stranded functional oligonucleotides which have specific abilities to bind with various target molecules ranging from small molecules to entire organisms. They are often named ‘chemical antibody’ and have aroused extensive interest in diverse clinical studies on account of their advantages, such as considerable biostability, versatile chemical modification, low immunogenicity and quick tissue penetration. Thus, aptamer-embedded drug delivery systems offer an unprecedented opportunity in bioanalysis and biomedicine. In this short review, we endeavor to discuss the recent advances in aptamer-based targeted drug delivery platforms for cancer therapy. Some perspectives on the advantages, challenges and opportunities are also presented.

Nonlinear manipulation and analysis of large DNA datasets

Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a type of biased competition is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, a biased competition method for nonlinear manipulation and analysis of mixtures of DNA sequences was developed. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among a myriad of different DNA sequences was carried out to reduce the information entropy. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiments with DNA-encoded chemical libraries against protein targets.

Multiply Guaranteed and Successively Amplified Activation of a Catalytic DNA Machine for Highly Efficient Intracellular Imaging of MicroRNA

DNA amplification machines show great promise for intracellular imaging, yet are always constrained by off-site machinery activation or signal leakage, originating from the inherent thermodynamically driven hybridization between machinery substrates. Herein, an entropy-driven catalytic DNA amplification machine is integrated with the on-site amplified substrate exposure procedure to realize the high-contrast in vivo imaging of microRNA (miRNA). The key machinery substrate (fuel strands) is initially split into substrate subunits that are respectively grafted into an auxiliary DNA polymerization amplification accessory for eliminating the undesired signal leakage. Meanwhile, in target cells, the auxiliary polymerization accessory can be motivated by cell-specific mRNA for successively restoring their intact machine-propelling functions for guaranteeing the on-site amplified imaging of miRNA with high specificity. This intelligent on-site multiply guaranteed machinery can improve the specificity of catalytic DNA machines for discriminating different cell types and, thus, can provide a remarkable prospect in biomedical diagnosis.

DNA circuits compatible encoder and demultiplexer based on a single biomolecular platform with DNA strands as outputs

A series of multiple logic circuits based on a single biomolecular platform is constructed to perform nonarithmetic and arithmetic functions, including 4-to-2 encoder, 1-to-2 demultiplexer, 1-to-4 demultiplexer, and multi-input OR gate. The encoder to a DNA circuit is the equivalent of a sensory receptor to a reflex arc. They all function to encode information from outside the pathway (DNA circuit or reflex arc) into a form that subsequent pathways can recognize and utilize. Current molecular encoders are based on optical or electrical signals as outputs, while DNA circuits are based on DNA strands as transmission signals. The output of existing encoders cannot be recognized by subsequent DNA circuits. It is the first time the DNA-based encoder with DNA strands as outputs can be truly applied to the DNA circuit, enabling the application of DNA circuits in non-binary biological environments. Another novel feature of the designed system is that the developed nanodevices all have a simple structure, low leakage and low crosstalk, which allows them to implement higher-level encoders and demultiplexers easily. Our work is based on the idea of complex functionality in a simple form, which will also provide a new route for developing advanced molecular logic circuits.

Programmable Analysis of MicroRNAs by Thermus thermophilus Argonaute-Assisted Exponential Isothermal Amplification for Multiplex Detection (TEAM)

The simultaneous analysis of the levels of multiple microRNAs (miRNAs) is critical to the early diagnosis of cancer. However, this analysis is challenging because of the low concentrations of miRNAs and their high sequence homology. Here, we report a general and programmable diagnostic strategy for miRNA analysis: Thermus thermophilus Argonaute (TtAgo)-assisted exponential isothermal amplification for multiplex detection (TEAM). This system combines exponential isothermal amplification (EXPAR), for target amplification, with programmable TtAgo cleavage, for the generation of the reporting signal. The TEAM assay achieved attomolar sensitivity with a rapid turnaround time (30-35 min). Because of the single-nucleotide precision of TtAgo, the system demonstrated robust multiplex capability in the simultaneous detection of four miRNA targets and the classification of let-7 family members. The TEAM assay was superior in differentiating colorectal cancer patients from healthy individuals relative to the conventional EXPAR and reverse transcription polymerase chain reaction (RT-PCR) methods. This tunable and scalable approach is a powerful nucleic acid analysis tool that holds promise in scientific and clinical applications.

Trojan Horse Delivery of Spherical Nucleic Acid Probes into the Cytoplasm for High-Fidelity Imaging of MicroRNAs

We report a Trojan horse strategy to efficiently deliver the spherical nucleic acid probes (namely, nanoflares) into the cytoplasm for microRNA (miRNA) imaging with high fidelity, breaking through the cytoplasmic transport dilemma of RNA probes in living cells. The nanoflare is encapsulated into a "Trojan horse" consisting of zwitterionic choline phosphates (CPs) and acid-degradable crosslinkers; the former effectively promotes cell uptake and the latter triggers instantaneous liberation of the nanoflare probes from the lysosome to the cytoplasm. The exposed nanoflares in the cytoplasm can be lightened up by the target miRNAs specifically. Compared with the conventional nanoflares as well as the improved ones in previous reports, the "Trojan horse" nanoflares avoid nuclease degradation and thiol displacement during the delivery process, providing unprecedentedly high accuracy for intracellular miRNA imaging.

Recent Advances in DNA Nanotechnology for Plasmonic Biosensor Construction

Since 2010, DNA nanotechnology has advanced rapidly, helping overcome limitations in the use of DNA solely as genetic material. DNA nanotechnology has thus helped develop a new method for the construction of biosensors. Among bioprobe materials for biosensors, nucleic acids have shown several advantages. First, it has a complementary sequence for hybridizing the target gene. Second, DNA has various functionalities, such as DNAzymes, DNA junctions or aptamers, because of its unique folded structures with specific sequences. Third, functional groups, such as thiols, amines, or other fluorophores, can easily be introduced into DNA at the 5′ or 3′ end. Finally, DNA can easily be tailored by making junctions or origami structures; these unique structures extend the DNA arm and create a multi-functional bioprobe. Meanwhile, nanomaterials have also been used to advance plasmonic biosensor technologies. Nanomaterials provide various biosensing platforms with high sensitivity and selectivity. Several plasmonic biosensor types have been fabricated, such as surface plasmons, and Raman-based or metal-enhanced biosensors. Introducing DNA nanotechnology to plasmonic biosensors has brought in sight new horizons in the fields of biosensors and nanobiotechnology. This review discusses the recent progress of DNA nanotechnology-based plasmonic biosensors.

DNA Logic Circuits for Cancer Theranostics

Cancer diagnosis and therapeutics (theranostics) based on the tumor microenvironment (TME) and biomarkers has been an emerging approach for precision medicine. DNA nanotechnology dynamically controls the self-assembly of DNA molecules at the nanometer scale to construct intelligent DNA chemical reaction systems. The DNA logic circuit is a particularly emerging approach for computing within the DNA chemical systems. DNA logic circuits can sensitively respond to tumor-specific markers and the TME through logic operations and signal amplification, to generate detectable signals or to release anti-cancer agents. In this review, the fundamental concepts of DNA logic circuits are clarified, the basic modules in the circuit are summarized, and how this advanced nano-assembly circuit responds to tumor-related molecules, how to perform logic operations, to realize signal amplification, and selectively release drugs through discussing over 30 application examples, are demonstrated. This review shows that DNA logic circuits have powerful logic judgment and signal amplification functions in improving the specificity and sensitivity of cancer diagnosis and making cancer treatment controllable. In the future, researchers are expected to overcome the existing shortcomings of DNA logic circuits and design smarter DNA devices with better biocompatibility and stability, which will further promote the development of cancer theranostics.

DNA Input Classification by a Riboregulator-Based Cell-Free Perceptron

The ability to recognize molecular patterns is essential for the continued survival of biological organisms, allowing them to sense and respond to their immediate environment. The design of synthetic gene-based classifiers has been explored previously; however, prior strategies have focused primarily on DNA strand-displacement reactions. Here, we present a synthetic in vitro transcription and translation (TXTL)-based perceptron consisting of a weighted sum operation (WSO) coupled to a downstream thresholding function. We demonstrate the application of toehold switch riboregulators to construct a TXTL-based WSO circuit that converts DNA inputs into a GFP output, the concentration of which correlates to the input pattern and the corresponding weights. We exploit the modular nature of the WSO circuit by changing the output protein to the Escherichia coli σ28-factor, facilitating the coupling of the WSO output to a downstream reporter network. The subsequent introduction of a σ28 inhibitor enabled thresholding of the WSO output such that the expression of the downstream reporter protein occurs only when the produced σ28 exceeds this threshold. In this manner, we demonstrate a genetically implemented perceptron capable of binary classification, i.e., the expression of a single output protein only when the desired minimum number of inputs is exceeded.

Single-Molecule Resettable DNA Computing via Magnetic Tweezers

DNA-based Boolean logic computing has emerged as a leading technique in biosensing, diagnosis, and therapeutics. Due to the development of the biological and chemical methods, especially the toehold-mediated DNA strand displacement (TMSD) reaction, different logic gates as well as circuits can be performed. However, most of these methods have been conducted at the bulk level, which may lead to missing information and be less controllable. Herein, we engineered single-molecule DNA computing controlled by stretching forces using magnetic tweezers. By tracking the real-time signals of the DNA extension, the output can be determined at a single base-pair resolution. A kinetics-controllable TMSD reaction was realized in the range of a ∼19-fold change of the reaction rate by different stretching forces. OR, AND, and NOT gates were also achieved. In addition, resettable DNA computing using force stretching cycles has been further exemplified. Overall, such a real-time, label-free, and force-controlled single-molecule DNA computing system provided new insight into molecular computing.

Logical Analysis of Multiple Single-Nucleotide-Polymorphisms with Programmable DNA Molecular Computation for Clinical Diagnostics

Analyzing complex single-nucleotide-polymorphism (SNP) combinations in the genome is important for research and clinical applications, given that different SNP combinations can generate different phenotypic consequences. Recent works have shown that DNA-based molecular computing is powerful for simultaneously sensing and analyzing complex molecular information. Here, we designed a switching circuit-based DNA computational scheme that can integrate the sensing of multiple SNPs and simultaneously perform logical analysis of the detected SNP information to directly report clinical outcomes. As a demonstration, we successfully achieved automatic and accurate identification of 21 different blood group genotypes from 83 clinical blood samples with 100 % accuracy compared to sequencing data in a more rapid manner (3 hours). Our method enables a new mode of automatic and logical sensing and analyzing subtle molecular information for clinical diagnosis, as well as guiding personalized medication.

Cotranscriptionally encoded RNA strand displacement circuits

Engineered molecular circuits that process information in biological systems could address emerging human health and biomanufacturing needs. However, such circuits can be difficult to rationally design and scale. DNA-based strand displacement reactions have demonstrated the largest and most computationally powerful molecular circuits to date but are limited in biological systems due to the difficulty in genetically encoding components. Here, we develop scalable cotranscriptionally encoded RNA strand displacement (ctRSD) circuits that are rationally programmed via base pairing interactions. ctRSD circuits address the limitations of DNA-based strand displacement circuits by isothermally producing circuit components via transcription. We demonstrate circuit programmability in vitro by implementing logic and amplification elements, as well as multilayer cascades. Furthermore, we show that circuit kinetics are accurately predicted by a simple model of coupled transcription and strand displacement, enabling model-driven design. We envision ctRSD circuits will enable the rational design of powerful molecular circuits that operate in biological systems, including living cells.

Nucleic Acid Nanotechnology for Diagnostics and Therapeutics in Acute Kidney Injury

Acute kidney injury (AKI) has impacted a heavy burden on global healthcare system with a high morbidity and mortality in both hospitalized and critically ill patients. However, there are still some shortcomings in clinical approaches for the disease to date, appealing for an earlier recognition and specific intervention to improve long-term outcomes. In the past decades, owing to the predictable base-pairing rule and highly modifiable characteristics, nucleic acids have already become significant biomaterials for nanostructure and nanodevice fabrication, which is known as nucleic acid nanotechnology. In particular, its excellent programmability and biocompatibility have further promoted its intersection with medical challenges. Lately, there have been an influx of research connecting nucleic acid nanotechnology with the clinical needs for renal diseases, especially AKI. In this review, we begin with the diagnostics of AKI based on nucleic acid nanotechnology with a highlight on aptamer- and probe-functionalized detection. Then, recently developed nanoscale nucleic acid therapeutics towards AKI will be fully elucidated. Furthermore, the strengths and limitations will be summarized, envisioning a wiser and wider application of nucleic acid nanotechnology in the future of AKI.

A high-integrated DNA biocomputing platform for MicroRNA sensing in living cells

DNA logic computing has captured increasing interest due to its ability to assemble programmable DNA computing elements for disease diagnosis, gene regulation, and targeted therapy. In this work, we developed an aptamer-equipped high-integrated DNA biocomputing platform (HIDBP-A) with a dual-recognition function that enabled cancer cell targeting. Dual microRNAs were the input signals and can perform AND logic operations. Compared to the free DNA biocomputing platform (FDBP), the integration of all computing elements into the same DNA tetrahedron greatly improved logic computing speed and efficiency owing to the confinement effect reflected by the high local concentration of computing elements. As a proof of concept, the utilization of microRNA as the input signal was beneficial for improving the scalability and flexibility of the sequence design of the logic nano-platform. Given that the different microRNAs were over-expressed in cancer cells, this new HIDBP-A has great promise in accurate diagnosis and logic-controlled disease treatment.

Long-Lasting and Responsive DNA/Enzyme-Based Programs in Serum-Supplemented Extracellular Media

DNA molecular programs are emerging as promising pharmaceutical approaches due to their versatility for biomolecular sensing and actuation. However, the implementation of DNA programs has been mainly limited to serum-deprived in vitro assays due to the fast deterioration of the DNA reaction networks by the nucleases present in the serum. Here, we show that DNA/enzyme programs are functional in serum for 24 h but are later disrupted by nucleases that give rise to parasitic amplification. To overcome this, we implement three-letter code networks that suppress autocatalytic parasites while still conserving the functionality of DNA/enzyme programs for at least 3 days in the presence of 10% serum. In addition, we define a new buffer that further increases the biocompatibility and conserves responsiveness to changes in molecular composition across time. Finally, we demonstrate how serum-supplemented extracellular DNA molecular programs remain responsive to molecular inputs in the presence of living cells, having responses 6-fold faster than the cellular division rate, and are sustainable for at least three cellular divisions. This demonstrates the possibility of implementing in situ biomolecular characterization tools for serum-demanding in vitro models. We foresee that the coupling of chemical reactivity to our DNA programs by aptamers or oligonucleotide conjugations will allow the implementation of extracellular synthetic biology tools, which will offer new biomolecular pharmaceutical approaches and the emergence of complex and autonomous in vitro models.

Rapid Nucleic Acid Reaction Circuits for Point-Of-Care Diseases Diagnosis

An urgent need exists for a rapid, cost-effective, facile, and reliable nucleic acid assay for mass screening to control and prevent the spread of emerging pandemic diseases. This urgent need is not fully met by current diagnostic tools. In this review, we summarize the current state-of-the-art research in novel nucleic acid amplification and detection that could be applied to point-of-care (POC) diagnosis and mass screening of diseases. The critical technological breakthroughs will be discussed for their advantages and disadvantages. Finally, we will discuss the future challenges of developing nucleic acid-based POC diagnosis.

A panel of three serum microRNA can be used as potential diagnostic biomarkers for nasopharyngeal carcinoma

BACKGROUND

Nasopharyngeal carcinoma is cancer with unique epidemiological characteristics, showing obvious ethnicity, gender, and geographical prevalence. More and more evidence shows that microRNAs are stable in serum and are specific to different tumor types. Therefore, miRNA is a new non-invasive biomarker for cancer detection.

METHODS

The experiment is divided into three stages, namely, the screening stage, the training stage, and the verification stage. We took 54 patients with nasopharyngeal carcinoma and 108 healthy controls as the research objects. We use the receiver-operating characteristic (ROC) curve and area under the ROC curve (AUC) to evaluate the diagnostic value of miRNA. Finally, a three-miRNA panel with high diagnostic efficiency was constructed. In addition, we conducted biological information analysis of these miRNAs to explore their functions.

RESULTS

In NPC patients, the expression of five serum miRNAs (miR-29c-3p, miR-143-5p, miR-150-5p, miR-145-3p, and miR-205-5p) is significantly dysregulated. Among them, the diagnostic value of these three miRNAs (miR-29c-3p, AUC = 0.702; miR-143-5p, AUC = 0.733; and miR-205-5p, AUC = 787) is more prominent. The diagnostic panel constructed by them has a higher diagnostic value (AUC = 0.902). Through the analysis of the TCGA data set, the target gene of the three-miRNA panel may be KLF7, NRG1, SH3BGRL2, and SYNPO2.

CONCLUSION

The three-miRNA panel (miR-29c-3p, miR-143-5p, and miR-205-5p) may become a novel non-invasive biological marker for nasopharyngeal cancer screening.

Multitarget Reaction Programmable Automatic Diagnosis and Treatment Logic Device

Accurate diagnosis and precise and effective treatment are currently the two magic weapons for dealing with cancer. However, a single marker is often associated with multiple cellular events, which is not conducive to accurate diagnosis, and overly mild treatment methods often make the treatment effect unsatisfactory. In this paper, we construct a Au/Pd octopus nanoparticle-DNA nanomachine (Au/Pd ONP-DNA nanomachine) as a fully automatic diagnosis and treatment logic system. In this system, multiple DNA components are targeting detection units, Au/Pd ONPs act as carriers, and Au/Pd ONPs with an 808 nm laser is the treatment unit. In order to achieve the purpose of precise treatment, we will detect two secondary markers under the premise of detecting one major tumor marker. When all of the designated targets are detected (the logic system input is (1, 1, 1), and the output is (1, 1)), the 808 nm laser can be programmed to automatically radiate tumors and perform photothermal therapy and photodynamic therapy. In vivo and in vitro experiments show that this logic system not only can accurately identify tumor cells but also has considerable therapeutic effects.

Nucleic acid-based molecular computation heads towards cellular applications

Nucleic acids, with the advantages of programmability and biocompatibility, have been widely used to design different kinds of novel biocomputing devices. Recently, nucleic acid-based molecular computing has shown promise in making the leap from the test tube to the cell. Such molecular computing can perform logic analysis within the confines of the cellular milieu with programmable modulation of biological functions at the molecular level. In this review, we summarize the development of nucleic acid-based biocomputing devices that are rationally designed and chemically synthesized, highlighting the ability of nucleic acid-based molecular computing to achieve cellular applications in sensing, imaging, biomedicine, and bioengineering. Then we discuss the future challenges and opportunities for cellular and in vivo applications. We expect this review to inspire innovative work on constructing nucleic acid-based biocomputing to achieve the goal of precisely rewiring, even reconstructing cellular signal networks in a prescribed way.

DNA Nanodevices: from Mechanical Motions to Biomedical Applications

Inspired by molecular machines in nature, artificial nanodevices have been designed to realize various biomedical functions. Self-assembled deoxyribonucleic acid (DNA) nanostructures that feature designed geometries, excellent spatial accuracy, nanoscale addressability and marked biocompatibility provide an attractive candidate for constructing dynamic nanodevices with biomarker-targeting and stimuli-responsiveness for biomedical applications. Here, a summary of typical construction strategies of DNA nanodevices and their operating mechanisms are presented. We also introduced recent advances in employing DNA nanodevices as platforms for biosensing and intelligent drug delivery. Finally, the broad prospects and main challenges of the DNA nanodevices in biomedical applications are discussed.

Development of Synthetic DNA Circuit and Networks for Molecular Information Processing

Deoxyribonucleic acid (DNA), a genetic material, encodes all living information and living characteristics, e.g., in cell, DNA signaling circuits control the transcription activities of specific genes. In recent years, various DNA circuits have been developed to implement a wide range of signaling and for regulating gene network functions. In particular, a synthetic DNA circuit, with a programmable design and easy construction, has become a crucial method through which to simulate and regulate DNA signaling networks. Importantly, the construction of a hierarchical DNA circuit provides a useful tool for regulating gene networks and for processing molecular information. Moreover, via their robust and modular properties, DNA circuits can amplify weak signals and establish programmable cascade systems, which are particularly suitable for the applications of biosensing and detecting. Furthermore, a biological enzyme can also be used to provide diverse circuit regulation elements. Currently, studies regarding the mechanisms and applications of synthetic DNA circuit are important for the establishment of more advanced artificial gene regulation systems and intelligent molecular sensing tools. We therefore summarize recent relevant research progress, contributing to the development of nanotechnology-based synthetic DNA circuits. By summarizing the current highlights and the development of synthetic DNA circuits, this paper provides additional insights for future DNA circuit development and provides a foundation for the construction of more advanced DNA circuits.

Microfluidic Systems for Cancer Diagnosis and Applications

Microfluidic devices have led to novel biological advances through the improvement of micro systems that can mimic and measure. Microsystems easily handle sub-microliter volumes, obviously with guidance presumably through laminated fluid flows. Microfluidic systems have production methods that do not need expert engineering, away from a centralized laboratory, and can implement basic and point of care analysis, and this has attracted attention to their widespread dissemination and adaptation to specific biological issues. The general use of microfluidic tools in clinical settings can be seen in pregnancy tests and diabetic control, but recently microfluidic platforms have become a key novel technology for cancer diagnostics. Cancer is a heterogeneous group of diseases that needs a multimodal paradigm to diagnose, manage, and treat. Using advanced technologies can enable this, providing better diagnosis and treatment for cancer patients. Microfluidic tools have evolved as a promising tool in the field of cancer such as detection of a single cancer cell, liquid biopsy, drug screening modeling angiogenesis, and metastasis detection. This review summarizes the need for the low-abundant blood and serum cancer diagnosis with microfluidic tools and the progress that has been followed to develop integrated microfluidic platforms for this application in the last few years.

Activating a DNA Nanomachine via Computation across Cancer Cell Membranes for Precise Therapy of Solid Tumors

Taking advantage of cancer cells' endogenous characters, the responsive activation of DNA nanomachines has achieved great success in tumor therapy. Combining with extra stimuli such as external light irradiation provided spatiotemporal control of DNA nanomachine activation. However, specific activation at the cellular level is still challenging considering the macroscopic-scale exposure area of usual light sources. DNA logic gates located at the cell membrane contributed to cellular specificity, but the free diffusion of input DNA strands during the operation process would impair efficiency and result in side effects to circumjacent normal cells in solid tumors. Here we design a transmembrane DNA logical computation strategy to activate a DNA nanomachine only in cancer cells from a complex solid tumor microenvironment. The DNA nanomachine multishell UCNPs-DNA is prepared by modifying DNA strands on upconversion nanoparticles. LA-apt, a DNA strand anchoring to a cancer cell membrane overexpressed receptor, and intracellular miRNA-21 served as inputs 1 and 2, respectively. Hybridization with input 1 at the cell membrane not only exposes the miRNA-21 recognition region at the DNA nanomachine, but also delivers it into cancer cells. The cascade hybridization with intracellular input 2 completes the "AND" gate operation and releases a DNA strand L2 as output. L2 acts as the trigger to operate the DNA nanomachine and correspondingly activates the photosensitizer Rose Bengal for reactive oxygen species generation. Through the "AND" gate operation of the DNA nanomachine across the cancer cell membrane, highly precise therapy only to cancer cells is achieved in a complex solid tumor microenvironment, which could become a promising modality for precise therapy of solid tumors.

miR-552 promotes the proliferation and metastasis of cervical cancer cells through targeting MUC15 pathway

Accumulating evidence shows that microRNAs (miRNAs) play key roles in tumorigenesis, progression, recurrence and drug resistance of malignant tumors. The tumor-promoting role of miR-552 has been evidenced in multiple tumors. Yet, the relevance of miR-552 in cervical cancer remains undetermined. This study aimed to investigate the role of miR-552 in cervical cancer proliferation and metastasis. Herein, we for first found that miR-552 expression was upregulated in cervical cancer tissues compared with their normal controls. Functional assays revealed that miR-552 promoted the proliferation and metastasis of cervical cancer cells. Mechanically, bioinformatics and luciferase reporter analysis identified MUC15 as a direct target of miR-552. Reduced MUC15 expression was detected in cervical cancer, and MUC15 overexpression exhibited a tumor-suppressive effect. MUC15 restoration partially abolished the discrepancy of growth and metastasis capacity between miR-552 overexpression cervical cancer cells and control cells. Taken together, these data demonstrate that miR-552 acts as a potential oncogene miRNA in cervical cancer, which exerts its function through targeting MUC15.

Obtaining Precise Molecular Information via DNA Nanotechnology

Precise characterization of biomolecular information such as molecular structures or intermolecular interactions provides essential mechanistic insights into the understanding of biochemical processes. As the resolution of imaging-based measurement techniques improves, so does the quantity of molecular information obtained using these methodologies. DNA (deoxyribonucleic acid) molecule have been used to build a variety of structures and dynamic devices on the nanoscale over the past 20 years, which has provided an accessible platform to manipulate molecules and resolve molecular information with unprecedented precision. In this review, we summarize recent progress related to obtaining precise molecular information using DNA nanotechnology. After a brief introduction to the development and features of structural and dynamic DNA nanotechnology, we outline some of the promising applications of DNA nanotechnology in structural biochemistry and in molecular biophysics. In particular, we highlight the use of DNA nanotechnology in determination of protein structures, protein-protein interactions, and molecular force.

DNA Balance for Native Characterization of Chemically Modified DNA

Chemical modification is a powerful approach to expand the chemical diversity and functionality of natural DNA. However, when chemically modified oligonucleotides are employed in DNA-based reactions or structures, it becomes quite difficult to predict, understand, and control their kinetics and thermodynamics. To address this challenge, we introduce a rationally designed DNA balance capable of measuring critical thermodynamic and kinetic properties of chemically modified DNA in their native environment. Our DNA balance is operated using the principle of toehold-exchange, where a panel of weight probes were designed by tuning the lengths of forward and reverse toeholds. Once placed on the DNA balance, the chemical modification will be interrogated using the weight probes to determine changes in both Gibbs free energy and hybridization rate constant. Using cyclic-azobenzene (cAB)-modified DNA as a model system, we demonstrated that our DNA balance could not only measure stable chemical modifications, but also solve more challenging issues where unstable chemical modifications and transient isomerization reactions were involved. We anticipate that our DNA balance will find wide uses for measuring important thermodynamic and kinetic parameters for DNA carrying various chemical modifications, as well as for probing transient chemical changes in DNA.

A copper-free and enzyme-free click chemistry-mediated single quantum dot nanosensor for accurate detection of microRNAs in cancer cells and tissues

MicroRNAs (miRNAs) play key roles in the post-transcriptional regulation of genes, and their aberrant expression may disturb the normal gene regulation network to induce various diseases, and thus accurate detection of miRNAs is essential to early clinical diagnosis. Herein, we develop for the first time a single-quantum dot (QD)-based Förster resonance energy transfer (FRET) nanosensor to accurately detect miRNAs based on copper-free and enzyme-free cycling click chemistry-mediated tricyclic ligase chain reaction (LCR) amplification. We design four DNA probes namely DNA probes 1-4, with DNA probes 1 and 3 being modified with azide (N3) and DNA probes 2 and 4 being modified with dibenzocyclooctyne (DBCO). When target miRNA is present, DNA probes 1 and 2 can proceed via copper-free and enzyme-free click chemistry to generate the probes 1-2 ligation product. Subsequently, DNA probes 3 and 4 can hybridize with the probes 1-2 ligation product to generate the probes 3-4 ligation product. Both the probes 1-2 ligation product and probes 3-4 ligation product can act as the templates to initiate cycling click chemistry-mediated tricyclic LCR amplification whose products can be easily measured by the single-QD-based FRET nanosensor. This assay does not involve any enzymatic reverse transcription, copper catalyst, and ligase enzyme, and it exhibits excellent selectivity, high sensitivity, and the capability of differentiating even single-base mismatches. Moreover, this nanosensor can accurately quantify miRNA-155 even at the single-cell level, and it can distinguish the miRNA-155 expression in tissues of healthy persons and nonsmall cell lung cancer (NSCLC) patients.

Molecular-level similarity search brings computing to DNA data storage

As global demand for digital storage capacity grows, storage technologies based on synthetic DNA have emerged as a dense and durable alternative to traditional media. Existing approaches leverage robust error correcting codes and precise molecular mechanisms to reliably retrieve specific files from large databases. Typically, files are retrieved using a pre-specified key, analogous to a filename. However, these approaches lack the ability to perform more complex computations over the stored data, such as similarity search: e.g., finding images that look similar to an image of interest without prior knowledge of their file names. Here we demonstrate a technique for executing similarity search over a DNA-based database of 1.6 million images. Queries are implemented as hybridization probes, and a key step in our approach was to learn an image-to-sequence encoding ensuring that queries preferentially bind to targets representing visually similar images. Experimental results show that our molecular implementation performs comparably to state-of-the-art in silico algorithms for similarity search.

Storage technology based on DNA is emerging as an information dense and durable medium. Here the authors use machine learning-based encoding and hybridization probes to execute similarity searches in a DNA database.

AI in Measurement Science

Measurement of biological systems containing biomolecules and bioparticles is a key task in the fields of analytical chemistry, biology, and medicine. Driven by the complex nature of biological systems and unprecedented amounts of measurement data, artificial intelligence (AI) in measurement science has rapidly advanced from the use of silicon-based machine learning (ML) for data mining to the development of molecular computing with improved sensitivity and accuracy. This review presents an overview of fundamental ML methodologies and discusses their applications in disease diagnostics, biomarker discovery, and imaging analysis. We next provide the working principles of molecular computing using logic gates and arithmetical devices, which can be employed for in situ detection, computation, and signal transduction for biological systems. This review concludes by summarizing the strengths and limitations of AI-involved biological measurement in fundamental and applied research.

Aptamer-Programmed DNA Nanodevices for Advanced, Targeted Cancer Theranostics

DNA has been demonstrated to be a versatile material for construction at the nanoscale. DNA nanodevices are highly programmable and allow functionalization with multiple entities such as imaging modalities (fluorophores), targeting entities (aptamers), drug conjugation (chemical linkers), and triggered release (photoresponsive molecules). These features enhance the use of DNA nanodevices in biological applications, catalyzing the rapid growth of this domain of research. In this review, we focus on recent progress in the development and use of aptamer-functionalized DNA nanodevices as theranostic agents, their characterization, applications as delivery platforms, and advantages. We provide a brief background on the development of aptamers and DNA nanodevices in biomedical applications, and we present specific applications of these entities in cancer diagnosis and therapeutics. We conclude with a perspective on the challenges and possible solutions for the clinical translation of aptamer-functionalized DNA nanodevices in the domain of cancer therapeutics.

Machine Learning Protocols in Early Cancer Detection Based on Liquid Biopsy: A Survey

With the advances of liquid biopsy technology, there is increasing evidence that body fluid such as blood, urine, and saliva could harbor the potential biomarkers associated with tumor origin. Traditional correlation analysis methods are no longer sufficient to capture the high-resolution complex relationships between biomarkers and cancer subtype heterogeneity. To address the challenge, researchers proposed machine learning techniques with liquid biopsy data to explore the essence of tumor origin together. In this survey, we review the machine learning protocols and provide corresponding code demos for the approaches mentioned. We discuss algorithmic principles and frameworks extensively developed to reveal cancer mechanisms and consider the future prospects in biomarker exploration and cancer diagnostics.

The Construction of DNA Logic Gates Restricted to Certain Live Cells Based on the Structure Programmability and Aptamer-Cell Affinity of G-Quadruplexes

DNA computation is considered a fascinating alternative to silicon-based computers; it has evoked substantial attention and made rapid advances. Besides realizing versatile functions, implementing spatiotemporal control of logic operations, especially at the cellular level, is also of great significance to the development of DNA computation. However, developing simple and efficient methods to restrict DNA logic gates performing in live cells is still a challenge. In this work, a series of DNA logic gates was designed by taking full advantage of the diversity and programmability of the G-quadruplex (G4) structure. More importantly, by further using the high affinity and specific endocytosis of cells to aptamer G4, an INHIBIT logic gate has been realized whose operational site is precisely restricted to specific live cells. The design strategy might have great potential in the field of molecular computation and smart bio-applications.

DNA strand displacement reactions to accomplish a two-degree-of-freedom PID controller and its application in subtraction gate

Synthesis control circuits can be used to effectively control biochemical molecule processes. In the controller design based on chemical reaction networks (CRNs), generally only the tracking set-point is considered. However, the influence of disturbances, which are frequently encountered in biochemical systems, is often neglected, thus weakening the control effect of the system. In this article, tracking set-point input and suppressing disturbance input are considered in the control effect. Firstly, CRNs are adopted to construct a two-degree-of-freedom PID controller by combining a one-degree-of-freedom PID controller with a feedforward controller for the first time. Then, CRN expressions of the two input functions (step function and ramp function) used as input signals are defined. Furthermore, the two-degree-of-freedom PID controller is founded by DNA strand displacement (DSD) reaction networks, because DNA is an ideal engineering material to constitute molecular devices based on CRNs. The overshoot of the two-degree-of-freedom PID control system is significantly reduced compared to the one-degree-of-freedom PID control system. Finally, a leak reaction is treated as an extraneous disturbance input to a subtraction gate. The influence of external disturbance is solved by the two-degree-of-freedom PID controller. It is worth noting that the two-degree-of-freedom subtraction gate control system better restrains the impact of a disturbance input (leak reaction).

Structure sampling for computational estimation of localized DNA interaction rates

Molecular circuits implemented using molecular components tethered to a DNA tile nanostructure have certain advantages over solution-phase circuits. Tethering components in close proximity increases the speed of reactions by reducing diffusion and improves scalability by enabling reuse of identical DNA sequences at different locations in the circuit. These systems show great potential for practical applications including delivery of diagnostic and therapeutic molecular circuits to cells. When modeling such systems, molecular geometry plays an important role in determining whether the two species interact and at what rate. In this paper, we present an automated method for estimating reaction rates in tethered molecular circuits that takes the geometry of the tethered species into account. We probabilistically generate samples of structure distributions based on simple biophysical models and use these to estimate important parameters for kinetic models. This work provides a basis for subsequent enhanced modeling and design tools for localized molecular circuits.

A fluorescent microarray platform based on catalytic hairpin assembly for MicroRNAs detection

The DNA microarray has distinctive advantages of high-throughput and less complicated operations, but tends to have a relatively low sensitivity. Catalytic hairpin assembly (CHA) is one of the most promising enzyme-free, isothermal DNA circuit for high efficient signal amplification. Here, a microarray-based catalytic hairpin assembly (mi-CHA) biosensing method has been developed to detect various miRNAs in a single test simultaneously. The target miRNA can trigger conformational transformations of hairpin-structured DNA probes on the chip surface and lead to the specific signal amplification. A significant advantage of this approach is that each duplex produced by the solid-phase CHA will be immobilized on the certain location of the chip and release fluorescent signal via the universal domain, eliminating the requirement of different fluorophores. This method has manifested a high detection sensitivity of human cancer-associated miRNAs (miR-21 and miR-155) down to 1.33 fM and promised a high specificity to distinguish single-base mismatches. Furthermore, the practicability of this method was demonstrated by analyzing target miRNAs in human serum and cancer cells. The experimental results suggest that the proposed method has high-throughput analytical potential and could be applied to many other clinical diagnosis.

Biocomputing Based on DNA Strand Displacement Reactions

The high sequence specificity and precise base complementary pairing principle of DNA provides a rich orthogonal molecular library for molecular programming, making it one of the most promising materials for developing bio-compatible intelligence. In recent years, DNA has been extensively studied and applied in the field of biological computing. Among them, the toehold-mediated strand displacement reaction (SDR) with properties including enzyme free, flexible design and precise control, have been extensively used to construct biological computing circuits. This review provides a systemic overview of SDR design principles and the applications. Strategies for designing DNA-only, enzymes-assisted, other molecules-involved and external stimuli-controlled SDRs are described. The recently realized computing functions and the application of DNA computing in other fields are introduced. Finally, the advantages and challenges of SDR-based computing are discussed.

Breast Cancer Case Identification Based on Deep Learning and Bioinformatics Analysis

Mastering the molecular mechanism of breast cancer (BC) can provide an in-depth understanding of BC pathology. This study explored existing technologies for diagnosing BC, such as mammography, ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) and summarized the disadvantages of the existing cancer diagnosis. The purpose of this article is to use gene expression profiles of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to classify BC samples and normal samples. The method proposed in this article triumphs over some of the shortcomings of traditional diagnostic methods and can conduct BC diagnosis more rapidly with high sensitivity and have no radiation. This study first selected the genes most relevant to cancer through weighted gene co-expression network analysis (WGCNA) and differential expression analysis (DEA). Then it used the protein-protein interaction (PPI) network to screen 23 hub genes. Finally, it used the support vector machine (SVM), decision tree (DT), Bayesian network (BN), artificial neural network (ANN), convolutional neural network CNN-LeNet and CNN-AlexNet to process the expression levels of 23 hub genes. For gene expression profiles, the ANN model has the best performance in the classification of cancer samples. The ten-time average accuracy is 97.36% (±0.34%), the F1 value is 0.8535 (±0.0260), the sensitivity is 98.32% (±0.32%), the specificity is 89.59% (±3.53%) and the AUC is 0.99. In summary, this method effectively classifies cancer samples and normal samples and provides reasonable new ideas for the early diagnosis of cancer in the future.

Aligner-Mediated Cleavage-Based Isothermal Amplification for SARS-CoV-2 RNA Detection

Rapid detection of SARS-CoV-2 RNA is critical for reducing the global transmission of COVID-19. Here, we report a simple and versatile assay for detection of SARS-CoV-2 RNA based on aligner-mediated cleavage-based strand displacement amplification (AMC-SDA). The entire amplification procedure takes less than 25 min without professional instruments or requirement of specific target sequences and can reach a limit of detection of attomolar RNA concentration. Using pseudovirus as mimicry of clinical SARS-CoV-2 positive samples, we achieved a diagnostic accuracy of 100% in 10 simulated samples (five positive and five negative). We anticipate that our method will provide a universal platform for rapid and accurate detection of emerging infectious diseases.

Recombinase Polymerase Amplification Coupled with a Photosensitization Colorimetric Assay for Fast Salmonella spp. Testing

Salmonella spp. is one of the most serious foodborne pathogens causing millions of infection cases annually, especially in resource-limited areas. The standard culture method (2-3 days) and current nucleic acid amplification-based testing are not suitable for on-site testing in rural areas with heavy Salmonella spp. burden. Here, we developed a colorimetric recombinase polymerase amplification (RPA) method for fast and sensitive Salmonella spp. testing in 1 h. Specifically, the invA gene from the genomic DNA of Salmonella spp. was amplified isothermally to produce double-stranded DNA (dsDNA) amplicons, which were directly quantified by a photosensitization colorimetric assay. The proposed method offered the lowest detectable concentration of 5 × 10³ colony-forming units/mL (cfu/mL), which is much lower than that of ELISA (10⁵-10⁷ cfu/mL). The detectable limit could be further pushed down to 3 cfu/mL upon coupling with bacteria pre-enrichment for 6 h. Analysis of synthetic milk samples confirmed the high precision (90%) and specificity (95%) of the method for Salmonella spp. testing. Moreover, use of a DNA releaser could further simplify the whole testing operation. Because RPA features low-temperature amplification (25-42 °C) without the need for specific instruments and the dsDNA-based photosensitization colorimetric assay served as a simple and facile readout for RPA, our method thus allows fast and low-cost Salmonella spp. testing in food samples.