How Saliva Interferes with Colorimetric Gold Nanoparticle Aptasensors: Understanding and Mitigating Surface Interactions.

Colorimetric gold-nanoparticle-based biosensors are an attractive platform for the detection of small-molecule analytes. Taking advantage of the adsorption of DNA aptamer probes on AuNPs, these sensors can be simple, rapid, sensitive, selective, and cost-effective. These properties are important for rapid detection of drugs like methamphetamine in biological matrices. Saliva is a highly desirable matrix for development of diagnostic tests because saliva sampling is minimally invasive and drug levels relate to recent use rather than accumulation from historical use. However, saliva is a complex fluid that presents a multitude of challenges when applying colorimetric aggregation assays. Here, we show that the contents of saliva interfere with the sensor in two main ways: (i) suppressing color change signals due to proteins nonspecifically adsorbing to nanoparticles and (ii) blocking aggregation and generating false signals due to specific electrolytes that induce aggregation. With this knowledge, we examine strategies to mitigate these effects, including sample collection and pretreatment procedures. These measures ultimately result in a sensor that can detect methamphetamine spiked into saliva samples and suggest immense promise for the feasibility of these platforms for on-site diagnostic applications.

Localisation of clozapine during experimental autoimmune encephalomyelitis and its impact on dopamine and its receptors.

Multiple sclerosis is a disease characterised by axonal demyelination in the central nervous system (CNS). The atypical antipsychotic drug clozapine attenuates experimental autoimmune encephalomyelitis (EAE), a mouse model used to study multiple sclerosis, but the precise mechanism is unknown and could include both peripheral and CNS-mediated effects. To better understand where clozapine exerts its protective effects, we investigated the tissue distribution and localisation of clozapine using matrix-assisted laser desorption ionization imaging mass spectrometry and liquid chromatography-mass spectrometry. We found that clozapine was detectable in the brain and enriched in specific brain regions (cortex, thalamus and olfactory bulb), but the distribution was not altered by EAE. Furthermore, although not altered in other organs, clozapine levels were significantly elevated in serum during EAE. Because clozapine antagonises dopamine receptors, we analysed dopamine levels in serum and brain as well as dopamine receptor expression on brain-resident and infiltrating immune cells. While neither clozapine nor EAE significantly affected dopamine levels, we observed a significant downregulation of dopamine receptors 1 and 5 and up-regulation of dopamine receptor 2 on microglia and CD4+-infiltrating T cells during EAE. Together these findings provide insight into how neuroinflammation, as modelled by EAE, alters the distribution and downstream effects of clozapine.

Proteins Annexin A2 and PSA in Prostate Cancer Biopsies Do Not Predict Biochemical Failure.

BACKGROUND/AIM: We previously reported the use of mass spectrometry and western blotting to identify proteins from tumour regions of formalin-fixed paraffin-embedded biopsies from 16 men who presented with apparently localized prostate cancer, and found that annexin A2 (ANXA2) appeared to be a better predictor of subsequent biochemical failure than prostate-specific antigen (PSA). MATERIALS AND METHODS: In this follow-up study, ANXA2 and PSA were measured using western blotting of proteins extracted from biopsies from 37 men from a subsequent prostate cancer trial. RESULTS: No significant differences in ANXA2 and PSA levels were observed between men with and without biochemical failure. The statistical effect sizes were small, d=0.116 for ANXA2, and 0.266 for PSA. CONCLUSION: ANXA2 and PSA proteins measured from biopsy tumour regions are unlikely to be good biomarkers for prediction of the clinical outcome of prostate cancer presenting with apparently localized disease.

Proteins from formalin-fixed paraffin-embedded prostate cancer sections that predict the risk of metastatic disease.

BACKGROUND: Prostate cancer is the most frequently diagnosed cancer in men and the third leading cause of cancer related deaths among men living in developed countries. Biomarkers that predict disease outcome at the time of initial diagnosis would substantially aid disease management. RESULTS: Proteins extracted from formalin-fixed paraffin-embedded tissue were identified using nanoflow liquid chromatography-MALDI MS/MS or after separation by one- or two-dimensional electrophoresis. The proteomics data have been deposited to the ProteomeXchange with identifier PXD000963. A list of potential biomarker candidates, based on proposed associations with prostate cancer, was derived from the 320 identified proteins. Candidate biomarkers were then examined by multiplexed Western blotting of archival specimens from men with premetastatic disease and subsequent disease outcome data. Annexin A2 provided the best prediction of risk of metastatic disease (log-rank Chi squared p = 0. 025). A tumor/control tissue >2-fold relative abundance increase predicted early biochemical failure, while <2-fold change predicted late or no biochemical failure. CONCLUSIONS: This study confirms the potential for use of archival FFPE specimens in the search for prognostic biomarkers for prostate cancer and suggests that annexin A2 abundance in diagnostic biopsies is predictive for metastatic potential. Protein profiling each cancer may lead to an overall reduction in mortality from metastatic prostate cancer as well as reduced treatment associated morbidity.