In silico designed RNA aptamer against epithelial cell adhesion molecule for cancer cell imaging.

Aptamers are short, single-stranded oligonucleotides that bind to their targets with high affinity and specificity. Usually, aptamers are selected experimentally using SELEX approach. Here, we describe a computational approach for selection of aptamers for proteins, which involves generation of a virtual library of sequences, modeling of their 3D-structures and selection of perspective aptamers through docking, molecular dynamics simulation, binding free energy calculations and finally estimating the experimental affinity. Using this method, a 15-mer RNA aptamer was designed for epithelial cell adhesion molecule. Flow cytometry and fluorescence microscopy results reviled that RNA1 aptamer interacts specifically with human cancer cells that express EpCAM, but not with the EpCAM negative cells. The binding affinity of the RNA1 aptamer to MCF-7 and MDA-MB-231 is approximately 21.8 and 96.9 nM respectively. This novel RNA aptamer will help in the future development of targeted therapeutics and molecular imaging.

Research-based flow cytometry assays for pathogenic assessment in the human B-cell biology of gene variants revealed in the diagnosis of inborn errors of immunity: a Bruton's tyrosine kinase case-study.

Introduction: Inborn errors of immunity (IEI) are an expanding group of rare diseases whose field has been boosted by next-generation sequencing (NGS), revealing several new entities, accelerating routine diagnoses, expanding the number of atypical presentations and generating uncertainties regarding the pathogenic relevance of several novel variants. Methods: Research laboratories that diagnose and provide support for IEI require accurate, reproducible and sustainable phenotypic, cellular and molecular functional assays to explore the pathogenic consequences of human leukocyte gene variants and contribute to their assessment. We have implemented a set of advanced flow cytometry-based assays to better dissect human B-cell biology in a translational research laboratory. We illustrate the utility of these techniques for the in-depth characterization of a novel (c.1685G>A, p.R562Q) de novo gene variant predicted as probably pathogenic but with no previous insights into the protein and cellular effects, located in the tyrosine kinase domain of the Bruton's tyrosine kinase (BTK) gene, in an apparently healthy 14-year-old male patient referred to our clinic for an incidental finding of low immunoglobulin (Ig) M levels with no history of recurrent infections. Results and discussion: A phenotypic analysis of bone marrow (BM) revealed a slightly high percentage of pre-B-I subset in BM, with no blockage at this stage, as typically observed in classical X-linked agammaglobulinemia (XLA) patients. The phenotypic analysis in peripheral blood also revealed reduced absolute numbers of B cells, all pre-germinal center maturation stages, together with reduced but detectable numbers of different memory and plasma cell isotypes. The R562Q variant allows Btk expression and normal activation of anti-IgM-induced phosphorylation of Y551 but diminished autophosphorylation at Y223 after anti IgM and CXCL12 stimulation. Lastly, we explored the potential impact of the variant protein for downstream Btk signaling in B cells. Within the canonical nuclear factor kappa B (NF-κB) activation pathway, normal IκBα degradation occurs after CD40L stimulation in patient and control cells. In contrast, disturbed IκBα degradation and reduced calcium ion (Ca2+) influx occurs on anti-IgM stimulation in the patient's B cells, suggesting an enzymatic impairment of the mutated tyrosine kinase domain.

An optimized procedure for quantitative analysis of mitophagy with the mtKeima system using flow cytometry.

Mitophagy is the process by which mitochondria are selectively targeted and removed via autophagic machinery to maintain mitochondrial homeostasis in the cell. Recently, flow cytometry-based assays that utilize the fluorescent mtKeima reporter system have allowed for quantitative assessment of mitophagy at a single-cell level. However, clear guidelines for appropriate flow cytometry workflow and downstream analysis are lacking and studies using flow cytometry in mtKeima-expressing cells often display incorrect and arbitrary binary mitophagic or nonmitophagic cutoffs that prevent proper quantitative analyses. In this paper we propose a novel method of mtKeima data analysis that preserves subtle differences present within flow cytometry data in a manner that ensures reproducibility.