Instrument design and optimization of interferometric reflectance imaging sensors for in vitro diagnostics

Thesis (Ph.D.)--Boston UniversityIn the field of drug discovery and disease diagnostics, protein microarrays have generated much enthusiasm for their high-throughput monitoring of biomarkers; however, this technology has yet to translate from research laboratories to commercialization. The hindrance is the considerable uncertainty and skepticism regarding data obtained. The disparity in results from different laboratories performing identical tests is attributed to a lack of assay quality control. Unlike DNA microarrays, protein microarrays have a higher level of bioreceptor immobilization variability and non-specific binding because of the more complex molecular structure and broader physiochemical properties. Traditional assay detection modalities, such as fluorescence microscopy and surface plasmon resonance, are unable to overcome both of these sources of variation. This dissertation describes the hardware and software design and biological validation of three complementary platforms that overcome bioreceptor variability and non-specific binding for diagnostics. In order to quantify the bioreceptor quality, a label-free, nondestructive, low cost, and high-throughput interferometric sensor has been developed as a quality control tool. The quality control tool was combined with a wide-field fluorescence imaging system to improve fluorescence experimental repeatability. Lastly, a novel high-throughput and label-free platform for quality control and specific protein microarray detection is described. This platform overcomes the additional complexities and time required with labeled assays by discriminating between specific and nonspecific detection by including sizing of individual binding events. Protein microarrays may one day emerge as routine clinical laboratory tests; however, it is important that the proper quality control procedures are in place to minimize erroneous results. These platforms provide reliable and repeatable protein microarray measurements for new advancements in disease diagnostics with the potential for drug discovery

Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor (IRIS)

The sensitive measurement of biomolecular interactions has use in many fields and industries such as basic biology and microbiology, environmental/agricultural/biodefense monitoring, nanobiotechnology, and more. For diagnostic applications, monitoring (detecting) the presence, absence, or abnormal expression of targeted proteomic or genomic biomarkers found in patient samples can be used to determine treatment approaches or therapy efficacy. In the research arena, information on molecular affinities and specificities are useful for fully characterizing the systems under investigation

Adenosine A2A receptors: localization and function

Adenosine is an endogenous purine nucleoside present in all mammalian tissues, that originates from the breakdown of ATP. By binding to its four receptor subtypes (A1, A2A, A2B, and A3), adenosine regulates several important physiological functions at both the central and peripheral levels. Therefore, ligands for the different adenosine receptors are attracting increasing attention as new potential drugs to be used in the treatment of several diseases. This chapter is aimed at providing an overview of adenosine metabolism, adenosine receptors localization and their signal transduction pathways. Particular attention will be paid to the biochemistry and pharmacology of A2A receptors, since antagonists of these receptors have emerged as promising new drugs for the treatment of Parkinson's disease. The interactions of A2A receptors with other nonadenosinergic receptors, and the effects of the pharmacological manipulation of A2A receptors on different body organs will be discussed, together with the usefulness of A2A receptor antagonists for the treatment of Parkinson's disease and the potential adverse effects of these drugs

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

The cellular localization of adenosine receptors in rat neostriatum

Using quantitative autoradiography of ligand binding sites combined with lesions of specific neuronal pathways, the cellular locations of A1 and A2 adenosine receptors, as well as a third binding site for the adenosine receptor ligand, [3H]N-ethylcarboxamidoadenosine, and a nucleoside transporter were investigated in rat neostriatum. Intrastriatal kainic acid administration resulted in the loss of 50% of A1 adenosine receptors and virtually abolished ligand binding to A2 receptors. A small reduction in [3H]cyclohexyladenosine binding to striatal A1 receptors was found after lesioning the corticostriatal input. A2 receptor sites were unaffected by this treatment. Destruction of dopaminergic neurons using 6-hydroxydopamine or the raphestriatal serotoninergic input using 5,7-dihydroxytryptamine affected neither A1, nor A2 binding sites. These results indicate the localization of both A1 and A2 adenosine receptors on neurons intrinsic to the neostriatum and probably postsynaptic to the dopaminergic input. In addition, a binding site for [3H]N-ethylcarboxamidoadenosine which is not affected by the adenosine receptor agonist, R-phenylisopropyladenosine, was also partly abolished after kainic acid injection. In contrast, no significant change in the binding of the nucleoside transporter ligand, [3H]nitrobenzylthioinosine, was observed after any lesions, indicating the widespread association of this site with various cell types. © 1989

A High-Throughput Method to Examine Protein-Nucleotide Interactions Identifies Targets of the Bacterial Transcriptional Regulatory Protein Fur

<div><p>The <u>F</u>erric <u>u</u>ptake <u>r</u>egulatory protein (Fur) is a transcriptional regulatory protein that functions to control gene transcription in response to iron in a number of pathogenic bacteria. In this study, we applied a label-free, quantitative and high-throughput analysis method, <u>I</u>nterferometric <u>R</u>eflectance <u>I</u>maging <u>S</u>ensor (IRIS), to rapidly characterize Fur-DNA interactions <i>in vitro</i> with predicted Fur binding sequences in the genome of <i>Neisseria gonorrhoeae</i>, the causative agent of the sexually transmitted disease gonorrhea. IRIS can easily be applied to examine multiple protein-protein, protein-nucleotide and nucleotide-nucleotide complexes simultaneously and demonstrated here that seventy percent of the predicted Fur boxes in promoter regions of iron-induced genes bound to Fur <i>in vitro</i> with a range of affinities as observed using this microarray screening technology. Combining binding data with mRNA expression levels in a gonococcal <i>fur</i> mutant strain allowed us to identify five new gonococcal genes under Fur-mediated direct regulation.</p></div

Fur binding to the predicted Fur boxes. (A) Cold competition assay for the specificity of Fur binding to the predicted Fur boxes.

<p>³²P-labeled ∼50 bp dsDNAs were analyzed after incubation with Fur and unlabeled dsDNA probes (cold probes). Two types of cold competitor probes were used: <i>fur</i>, which contains a Fur box, and <i>rmp</i>, which does not bind to Fur. When the unlabeled probes <i>fur</i> compete out binding of labeled probes, but the unlabeled <i>rmp</i> cannot, the binding of Fur to the predicted Fur box was considered specific. Lane 1, free ³²P-labeled DNA; Lane 2 through Lane 10 contained gonococcal Fur. For the <i>fur</i> and NGO0073 Fur box, Fur protein was added at a concentration of 100 nM and for the NGO0101 Fur box, 400 nM of Fur protein was added. The fold excess of the cold probes was increased from Lane 3 to Lane 6 and Lane 7 to Lane 10 ranging from 50 fold, 500 fold to 1000 fold (indicated by the triangles). <b>(B) Fur binding affinities determined by EMSA.</b> The ³²P labeled dsDNA probes were incubated with a gradient of concentrations of purified gonococcal Fur protein (Lane 1 to Lane 10, 0 nM, 5 nM, 25 nM, 50 nM, 100 nM, 200 nM, 400 nM, 600 nM, 800 nM and 1000 nM, respectively). Arrows indicate the shift of Fur-bound probes. The apparent binding affinities (K_D) were calculated using GraphPad Prism and were represented as mean ± standard error. The gene designations of <i>N. gonorrhoeae</i> F62 were assigned according to their homologues in <i>N. gonorrhoeae</i> FA1090.</p

Identification of Fur binding to predicted Fur boxes by label-free IRIS screening.

<p>A set of ∼50 bp dsDNA probes containing the predicted Fur box in the middle of the probes were designed for IRIS screening (<b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096832#pone.0096832.s006" target="_blank">Table S4</a></b>). Each dsDNA probe was immobilized on a chip to produce a spot with a diameter of approximately 100 µm. Three concentrations of Fur protein, 200 nM (red bars), 400 nM (blue bars) and 800 nM (orange bars), were incubated with the individually prepared arrays (in addition to a 0 nM control incubation (black bars) and the binding of Fur protein to dsDNA spots was measured. A mass increase for each spot was represented as a differential spot height (DSH). The known Fur boxes in <i>fur</i>, <i>norB</i> and <i>nspA</i> promoter regions were used as positive controls, and the <i>aniA</i> promoter region was used as negative control in this IRIS assay. (<b>A</b>) Differential spot height for each dsDNA probe after incubation with 0 nM, 200 nM, 400 nM and 800 nM Fur protein, respectively. (<b>B</b>) The number of Fur dimers bound per dsDNA molecule of each probe as calculated from initial and post-incubation mass density measurements. The gene designations of <i>N. gonorrhoeae</i> F62 were assigned according to their homologues in <i>N. gonorrhoeae</i> FA1090.</p

Transcriptional regulation patterns of genes determined by quantitative real-time PCR.

<p>The RNA samples were purified from cultures of the wild-type (WT) and <i>fur</i> mutant and <i>fur</i> complemented strains under iron-replete (+Fe, grey bars) or iron-deplete (-Fe, white bars) conditions 1 h after addition of 100 µM iron or 150 µM desferal. The mRNA levels of <i>fbpA</i> and <i>norB</i>, genes that were repressed and activated by iron-bound Fur respectively, were used as controls for iron and Fur regulation in <i>N. gonorrhoeae</i>. The mRNA levels observed for the five conditions (WT strain under −Fe conditions, <i>fur</i> mutant strain under +Fe and −Fe conditions, and <i>fur</i> complemented strain under +Fe and −Fe conditions) were compared to the value of WT strain under +Fe conditions. The final results were represented as mean ± standard deviation. A * indicates significantly different compared to the mRNA level of WT+Fe. A ** indicates significantly different compared to the mRNA level of WT-Fe. The gene designations of <i>N. gonorrhoeae</i> F62 were assigned according to their homologues in <i>N. gonorrhoeae</i> FA1090.</p