skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Recent Advances in Nanomaterial-Based Aptasensors in Medical Diagnosis and Therapy
Rapid and accurate diagnosis of various biomarkers associated with medical conditions including early detection of viruses and bacteria with highly sensitive biosensors is currently a research priority. Aptamer is a chemically derived recognition molecule capable of detecting and binding small molecules with high specificity and its fast preparation time, cost effectiveness, ease of modification, stability at high temperature and pH are some of the advantages it has over traditional detection methods such as High Performance Liquid Chromatography (HPLC), Enzyme-linked Immunosorbent Assay (ELISA), Polymerase Chain Reaction (PCR). Higher sensitivity and selectivity can further be achieved via coupling of aptamers with nanomaterials and these conjugates called “aptasensors” are receiving greater attention in early diagnosis and therapy. This review will highlight the selection protocol of aptamers based on Traditional Systematic Evolution of Ligands by EXponential enrichment (SELEX) and the various types of modified SELEX. We further identify both the advantages and drawbacks associated with the modified version of SELEX. Furthermore, we describe the current advances in aptasensor development and the quality of signal types, which are dependent on surface area and other specific properties of the selected nanomaterials, are also reviewed.  more » « less
Award ID(s):
2032601 2032582
PAR ID:
10290364
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Nanomaterials
Volume:
11
Issue:
4
ISSN:
2079-4991
Page Range / eLocation ID:
932
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Staphylococcus aureusis a major foodborne bacterial pathogen. Early detection ofS. aureusis crucial to prevent infections and ensure food quality. The iron‐regulated surface determinant protein A (IsdA) ofS. aureusis a unique surface protein necessary for sourcing vital iron from host cells for the survival and colonization of the bacteria. The function, structure, and location of the IsdA protein make it an important protein for biosensing applications relating to the pathogen. Here, we report an in‐silico approach to develop and validate high‐affinity binding aptamers for the IsdA protein detection using custom‐designed in‐silico tools and single‐molecule Fluorescence Resonance Energy Transfer (smFRET) measurements. We utilized in‐silico oligonucleotide screening methods and metadynamics‐based methods to generate 10 aptamer candidates and characterized them based on the Dissociation Free Energy (DFE) of the IsdA‐aptamer complexes. Three of the aptamer candidates were shortlisted for smFRET experimental analysis of binding properties. Limits of detection in the low picomolar range were observed for the aptamers, and the results correlated well with the DFE calculations, indicating the potential of the in‐silico approach to support aptamer discovery. This study showcases a computational SELEX method in combination with single‐molecule binding studies deciphering effective aptamers againstS. aureus IsdA, protein. The established approach demonstrates the ability to expedite aptamer discovery that has the potential to cut costs and predict binding efficacy. The application can be extended to designing aptamers for various protein targets, enhancing molecular recognition, and facilitating the development of high‐affinity aptamers for multiple uses. 
    more » « less
  2. Antibodies are important biomolecules that are often designed to recognize target antigens. However, they are expensive to produce and their relatively large size prevents their transport across lipid membranes. An alternative to antibodies is aptamers, short ([Formula: see text] bp) oligonucleotides (and amino acid sequences) with specific secondary and tertiary structures that govern their affinity to specific target molecules. Aptamers are typically generated via solid phase oligonucleotide synthesis before selection and amplification through Systematic Evolution of Ligands by EXponential enrichment (SELEX), a process based on competitive binding that enriches the population of certain strands while removing unwanted sequences, yielding aptamers with high specificity and affinity to a target molecule. Mathematical analyses of SELEX have been formulated in the mass action limit, which assumes large system sizes and/or high aptamer and target molecule concentrations. In this paper, we develop a fully discrete stochastic model of SELEX. While converging to a mass-action model in the large system-size limit, our stochastic model allows us to study statistical quantities when the system size is small, such as the probability of losing the best-binding aptamer during each round of selection. Specifically, we find that optimal SELEX protocols in the stochastic model differ from those predicted by a deterministic model. 
    more » « less
  3. Abstract Aptamers are short oligonucleotides isolated in vitro from randomized libraries that can bind to specific molecules with high affinity, and offer a number of advantages relative to antibodies as biorecognition elements in biosensors. However, it remains difficult and labor‐intensive to develop aptamer‐based sensors for small‐molecule detection. Here, we review the challenges and advances in the isolation and characterization of small‐molecule‐binding DNA aptamers and their use in sensors. First, we discuss in vitro methodologies for the isolation of aptamers, and provide guidance on selecting the appropriate strategy for generating aptamers with optimal binding properties for a given application. We next examine techniques for characterizing aptamer–target binding and structure. Afterwards, we discuss various small‐molecule sensing platforms based on original or engineered aptamers, and their detection applications. Finally, we conclude with a general workflow to develop aptamer‐based small‐molecule sensors for real‐world applications. 
    more » « less
  4. The fast, accurate detection of biomolecules, ranging from nucleic acids and small molecules to proteins and cellular secretions, plays an essential role in various biomedical applications. These include disease diagnostics and prognostics, environmental monitoring, public health, and food safety. Aptamer recognition (DNA or RNA) has gained extensive attention for biomolecular detection due to its high selectivity, affinity, reproducibility, and robustness. Concurrently, biosensing with nanoparticles has been widely used for its high carrier capacity, stability and feasibility of incorporating optical and catalytic activity, and enhanced diffusivity. Biosensors based on aptamers and nanoparticles utilize the combination of their advantages and have become a promising technology for detecting of a wide variety of biomolecules with high sensitivity, reliability, specificity, and detection speed. Via various sensing mechanisms, target biomolecules have been quantified in terms of optical (e.g., colorimetric and fluorometric), magnetic, and electrical signals. In this review, we summarize the recent advances in and compare different aptamer–nanoparticle-based biosensors by nanoparticle types and detection mechanisms. We also share our views on the highlights and challenges of the different nanoparticle-aptamer-based biosensors. 
    more » « less
  5. Li, Jinyan (Ed.)
    Selection protocols such as SELEX, where molecules are selected over multiple rounds for their ability to bind to a target of interest, are popular methods for obtaining binders for diagnostic and therapeutic purposes. We show that Restricted Boltzmann Machines (RBMs), an unsupervised two-layer neural network architecture, can successfully be trained on sequence ensembles from single rounds of SELEX experiments for thrombin aptamers. RBMs assign scores to sequences that can be directly related to their fitnesses estimated through experimental enrichment ratios. Hence, RBMs trained from sequence data at a given round can be used to predict the effects of selection at later rounds. Moreover, the parameters of the trained RBMs are interpretable and identify functional features contributing most to sequence fitness. To exploit the generative capabilities of RBMs, we introduce two different training protocols: one taking into account sequence counts, capable of identifying the few best binders, and another based on unique sequences only, generating more diverse binders. We then use RBMs model to generate novel aptamers with putative disruptive mutations or good binding properties, and validate the generated sequences with gel shift assay experiments. Finally, we compare the RBM’s performance with different supervised learning approaches that include random forests and several deep neural network architectures. 
    more » « less