Aptamers as biomarkers for neurological disorders. Proof of concept in transgenic mice

A novel hybrid approach to overcome defects of CE-SELEX and cell-SELEX in developing aptamers against aspartate β-hydroxylase

Background and purpose

Aptamers, a new category of molecular probes, are overthrowing antibodies in molecular diagnostics. However, there are serious problems with using aptamers for this application including poor or non-specific binding in vivo conditions. Systematic evolution of aptamers is achieved through various approaches including CE-SELEX and Cell-SELEX, each suffering its inevitable weaknesses. The shortcomings of negative selection and the lengthy procedure are Cell-SELEX's main problems, while CE-SELEX is deprived of native targets. Here, we introduced a kind of hybrid CE-Cell-SELEX, named CEC hybrid-SELEX, for addressing these limitations in creating aptamer probes detecting human aspartate β-hydroxylase (ASPH), which is a well-established tumor biomarker, in cancer diagnostic investigations.

Experimental approach

In our approach, the selected oligomer pool from the last cycle of CE-SELEX was sequenced and then subjected to 3 additional rounds of Cell-SELEX which provides native ASPH (CEC hybrid-SELEX). High-throughput sequencing was applied to achieve a comprehensive sight of the enriched pools. Further confirmatory investigations on oligomers with higher copy numbers were performed using flow cytometry.

Findings/Results

Three selected oligomers, AP-CEC 1, AP-CEC 2, and AP-CEC 3, showing Kd values of 43.09 nM, 34.85 nM, and 35.92 nM, respectively, were achieved based on the affinity assessment of the ASPH-expressing cells.

Conclusion and implications

Our research suggested that CEC hybrid-SELEX could help recognize which oligomers from CE-SELEX are more capable of binding native ASPH in vivo.

A reproducible approach for the use of aptamer libraries for the identification of Aptamarkers for brain amyloid deposition based on plasma analysis

An approach for the agnostic identification and validation of aptamers for the prediction of a medical state from plasma analysis is presented in application to a key risk factor for Alzheimer's disease. brain amyloid deposition. This method involved the use of a newly designed aptamer library with sixteen random nucleotides interspersed with fixed sequences called a Neomer library. The Neomer library approach enables the direct application of the same starting library on multiple plasma samples, without the requirement for pre-enrichment associated with the traditional approach. Eight aptamers were identified as a result of the selection process and screened across 390 plasma samples by qPCR assay. Results were analysed using multiple machine learning algorithms from the Scikit-learn package along with clinical variables including cognitive status, age and sex to create predictive models. An Extra Trees Classifier model provided the highest predictive power. The Neomer approach resulted in a sensitivity of 0.88. specificity of 0.76. and AUC of 0.79. The only clinical variables that were included in the model were age and sex. We conclude that the Neomer approach represents a clear improvement for the agnostic identification of aptamers (Aptamarkers) that bind to unknown biomarkers of a medical state.

Aptamer binding footprints discriminate α-synuclein fibrillar polymorphs from different synucleinopathies

Synucleinopathies, including dementia with Lewy bodies (DLB), Parkinson's disease (PD), and multiple system atrophy (MSA), are characterized by the presence of α-synuclein (α-syn) aggregates in the central nervous system. Recent evidence suggests that the heterogeneity of synucleinopathies may be partly explained by the fact that patients may have different α-syn fibrillar polymorphs with structural differences. In this study, we identify nuclease resistant 2'fluoro-pyrimidine RNA aptamers that can differentially bind to structurally distinct α-syn fibrillar polymorphs. Moreover, we introduce a method, AptaFOOT-Seq, designed to rapidly assess the affinity of a mixture of these aptamers for different α-SYN fibrillar polymorphs using next-generation sequencing. Our findings reveal that the binding behavior of aptamers can be very different when they are tested separately or in the presence of other aptamers. In this case, competition and cooperation can occur, providing a higher level of information, which can be exploited to obtain specific 'footprints' for different α-Syn fibrillar polymorphs. Notably, these footprints can distinguish polymorphs obtained from patients with PD, DLB or MSA. This result suggests that aptaFOOT-Seq could be used for the detection of misfolded or abnormal protein conformations to improve the diagnosis of synucleinopathies.

Differential RNA aptamer affinity profiling on plasma as a potential diagnostic tool for bladder cancer

The molecular composition of blood is a signature of human health, reflected in the thousands of blood biomarkers known for human diseases. However, establishing robust disease markers is challenging due to the diversity of individual samples. New sequencing methods have simplified biomarker discovery for circulating DNA and RNA while protein profiling is still laborious and costly. To harness the power of high-throughput sequencing to profile the protein content of a biological sample, we developed a method termed APTASHAPE that uses oligonucleotide aptamers to recognize proteins in complex biofluids. We selected a large pool of 2'Fluoro protected RNA sequences to recognize proteins in human plasma and identified a set of 33 cancer-specific aptamers. Differential enrichment of these aptamers after selection against 1 μl of plasma from individual patients allowed us to differentiate between healthy controls and bladder cancer-diagnosed patients (91% accuracy) and between early non-invasive tumors and late stage tumors (83% accuracy). Affinity purification and mass spectrometry of proteins bound to the predictive aptamers showed the main target proteins to be C4b-binding protein, Complement C3, Fibrinogen, Complement factor H and IgG. The APTASHAPE method thus provides a general, automated and highly sensitive platform for discovering potential new disease biomarkers.

Aptamer Applications in Neuroscience

Being the predominant cause of disability, neurological diseases have received much attention from the global health community. Over a billion people suffer from one of the following neurological disorders: dementia, epilepsy, stroke, migraine, meningitis, Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, Huntington's disease, prion disease, or brain tumors. The diagnosis and treatment options are limited for many of these diseases. Aptamers, being small and non-immunogenic nucleic acid molecules that are easy to chemically modify, offer potential diagnostic and theragnostic applications to meet these needs. This review covers pioneering studies in applying aptamers, which shows promise for future diagnostics and treatments of neurological disorders that pose increasingly dire worldwide health challenges.

Novel Approach to Overcome Defects of Cell-SELEX in Developing Aptamers against Aspartate β-Hydroxylase

Cell-based aptamer selection (Cell-SELEX) against predefined protein targets that benefits using the native form of the targets is the most promising approach to achieve aptamer probes capable of recognizing targets under both in vitro and in vivo conditions. The major disadvantages in Cell-SELEX are the imperfectness of the negative selection step and the lengthy procedure of selection. Here, we introduced the Counter-SELEX as part of our modified Cell-SELEX and implemented deep sequencing to overcome these shortcomings in developing aptamers against aspartate β-hydroxylase (ASPH) as a known tumor marker. In parallel with the conventional Cell-SELEX, five consecutive cycles of counter selection were accomplished using sequences bound to negative cells (the Counter-SELEX) to detect oligos that are not specific for ASPH. After high-throughput sequencing, the representative of each promising achieved family was subjected to further confirmatory analysis via flow cytometry, followed by the fluorescence immunostaining of histopathological sections. Implementing our innovative complementary method, annoying mis-selected sequences in Cell-SELEX enriched pools were effectively identified and removed. According to the affinity assay on the cells displaying ASPH, three aptamers, AP-Cell 1, AP-Cell 2, and AP-Cell 3, with K _d values of 47.51, 39.38, and 65.23 nM, respectively, were obtained, while AP-Cell 1 and 3 could then successfully spot ASPH displayed on the tissues. Our study showed that the Counter-SELEX could be considered as a complementary method for Cell-SELEX to overcome the imperfectness of the negative selection step. Moreover, high-throughput nucleotide sequencing could help to shorten the overall process.

Aptamarker prediction of brain amyloid-β status in cognitively normal individuals at risk for Alzheimer's disease

The traditional approach to biomarker discovery for any pathology has been through hypothesis-based research one candidate at a time. The objective of this study was to develop an agnostic approach for the simultaneous screening of plasma for consistent molecular differences between a group of individuals exhibiting a pathology and a group of healthy individuals. To achieve this, we focused on developing a predictive tool based on plasma for the amount of brain amyloid-β deposition as observed in PET scans. The accumulation of brain amyloid-β (Aβ) plaques is a key risk factor for the development of Alzheimer’s disease. A contrast was established between cognitively normal individuals above the age of 70 that differed for the amount of brain amyloid-β observed in PET scans (INSIGHT study group). Positive selection was performed against a pool of plasma from individuals with high brain amyloid and negative selection against a pool of plasma from individuals with low brain amyloid This enriched, selected library was then applied to plasma samples from 11 individuals with high levels of brain amyloid and 11 individuals with low levels of brain Aβ accumulation. Each of these individually selected libraries was then characterized by next generation sequencing, and the relative frequency of 10,000 aptamer sequences that were observed in each selection was screened for ability to explain variation in brain amyloid using sparse partial least squares discriminant analysis. From this analysis a subset of 44 aptamers was defined, and the individual aptamers were synthesized. This subset was applied to plasma samples from 70 cognitively normal individuals all above the age of 70 that differed for brain amyloid deposition. 54 individuals were used as a training set, and 15 as a test set. Three of the 15 individuals in the test set were mis-classified resulting in an overall accuracy of 80% with 86% sensitivity and 75% specificity. The aptamers included in the subset serve directly as biomarkers, thus we have named them Aptamarkers. There are two potential applications of these results: extending the predictive capacity of these aptamers across a broader range of individuals, and/or using the individual aptamers to identify targets through covariance analysis and reverse omics approaches. We are currently expanding applications of the Aptamarker platform to other diseases and target matrices.

Blood-based diagnostics of Alzheimer's disease

Introduction: This review is focused on the methods used for biomarker discovery for Alzheimer's disease (AD) in blood rather than on the nature of the biomarkers themselves. Areas covered: All biomarker discovery programs explicitly rely on contrasts in phenotype as a basis for defining differences. In this review, we explore the basis of contrasting choices as a function of the type of biomarker (genetic, protein, metabolite, non-coding RNA, or pathogenic epitope). We also provide an overview of the capacity to identify pathogenic epitopes with our new platform called Aptamarkers. It is suggested that a pre-existing hypothesis regarding the pathophysiology of the disease can act as a constraint to the development of biomarkers. Expert opinion: Limiting putative biomarkers to those that have a postulated role in the pathophysiology of disease imposes an unrealistic constraint on biomarker development. The understanding of Alzheimer's disease would be accelerated by agnostic, non-hypothesis-based biomarker discovery methods. There is a need for more complex contrasts and more complex mathematical models.

Recent Advances in Aptamer Discovery and Applications

Aptamers are short, single-stranded DNA, RNA, or synthetic XNA molecules that can be developed with high affinity and specificity to interact with any desired targets. They have been widely used in facilitating discoveries in basic research, ensuring food safety and monitoring the environment. Furthermore, aptamers play promising roles as clinical diagnostics and therapeutic agents. This review provides update on the recent advances in this rapidly progressing field of research with particular emphasis on generation of aptamers and their applications in biosensing, biotechnology and medicine. The limitations and future directions of aptamers in target specific delivery and real-time detection are also discussed.

Development of novel aptamers for low-density lipoprotein particle quantification

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Low-density lipoprotein cholesterol (LDL-C) is commonly used for CVD risk assessment; however, recent research has shown LDL particle (LDL-P) number to be a more sensitive indicator of CVD risk than both LDL-C and non-high-density lipoprotein cholesterol (HDL-C). Described herein are five single stranded DNA aptamers with dissociation constants in the low picomolar range specific to LDL-P and its subfractions. Furthermore, a set of antisense sequences have been developed and characterized that are capable of binding to the best aptamers and undergoing displacement by LDL-P for use in a simple, affordable diagnostic assay.