An electrochemical aptasensor is a compact analytical device where the bioreceptor (aptamer) is coupled to a transducer surface to convert a biological interaction into a measurable signal (current) that can be easily processed, recorded and displayed. Since the discovery of the Systematic Evolution of Ligands by Enrichment (SELEX) methodology, the selection of aptamers and their application as bioreceptors has become a promising tool in the design of electrochemical aptasensors. Aptamers present several advantages that highlight their usefulness as bioreceptors such as chemical stability, cost effectiveness and ease of modification towards detection and immobilization at different transducer surfaces. In this review, a special emphasis is given to the potential use of electrochemical aptasensors for the detection of protein disease biomarkers using voltammetry techniques. Methods for the immobilization of aptamers onto electrode surfaces are discussed, as well as different electrochemical strategies that can be used for the design of aptasensors.

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Electrochemical aptasensors may be used to detect protein biomarkers related to tumor activity. Osteopontin (OPN), a protein present in several body fluids, has been suggested as a potential biomarker since its overexpression seems to be associated with breast cancer progression and metastasis. In this work, a simple and label-free voltammetric aptasensor for the detection of OPN, using an RNA aptamer previously reported to have affinity for human OPN as the molecular recognition element, and the ferro/ ferricyanide solution as a redox probe, was developed. The RNA aptamer was synthetized and immobilized in a working microelectrode gold surface (diameter of 0.8 mm) of a screen-printed strip with a silver pseudo-reference electrode and a gold counter electrode. The electrochemical behavior of the electrode surface after each preparation step of the aptasensor was studied using cyclic voltammetry and square wave voltammetry. The resulting voltammetric aptasensor was used to detect OPN in standard solutions. Cyclic voltammetry results showed that the aptasensor has reasonable detection and quantification limits (3.7 70.6 nM and 11 7 2 nM, respectively). Indeed, the detection limit falls within the osteopontin levels reported in the literature for patients with metastatic breast cancer. Moreover, the aptasensor is able to selectively detect the target protein in the presence of other interfering proteins, except for thrombin. Considering the overall results, a possible application of the aptasensor for cancer prognosis may be foreseen in a near future.

In the present study, three different methods were used to identify yeast isolated from Trás-os-Montes, Portuguese honey. A total of 24 isolates were identified using a partial sequence of the 26S rRNA gene (rDNA), restriction patterns generated from the region spanning the internal transcribed spacers (ITS1 and ITS2) of the 5.8S rRNA gene and the API 20C AUX kit. Nine different yeast species were identified representing six different genera. Among the isolated honey samples, Rhodotorula mucilaginosa, Candida magnoliae and Zygosaccharomyces mellis were the predominant species. Partial sequence of the 26S rDNA yielded the best results in terms of correct identification, followed by-5.8S-ITS analysis. The commercial identification kit API 20C AUX was able to correctly identify only 58% of the isolates. Two new 5.8S-ITS profiles were described, corresponding to Trichosporon mucoides and Candida sorbosivorans. RESUMENEn este estudio, se han utilizado tres métodos para identificar levaduras aisladas de la miel de Trás-os-Montes, Portugal. Se han identificado un total de 24 aislados usando una secuencia parcial del gen rRNA 26S (rDNA), los patrones de restricción generados de la región de los espaciadores transcritos internos (ITS1 e ITS2) del gen rRNA 5.8S (rDNA) y el kit API 20C AUX. Fueron identificadas nueve especies distintas de levaduras que representan seis géneros distintos. Entre las muestras aisladas de la miel, Rhodotorula mucilaginosa, Candida magnoliae y Zygosaccharomyces mellis eran las especies predominantes. La secuencia parcial del rDNA 26S rindió los mejores resultados para la correcta identificación, seguida por el análisis del 5.8S-ITS. El kit comercial de identificación API 20C AUX. sólo identificó correctamente el 58% de los aislados. Se describen dos perfiles nuevos de 5.8S-ITS, correspondiendo a Trichosporon mucoides y Candida sorbosivorans.

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