Single-cell screening of multiple biophysical properties in leukemia diagnosis from peripheral blood by pure light scattering

Abstract Histology and histopathology are based on the morphometric observations of quiescent cells. Their diagnostic potential could largely benefit from a simultaneous screening of intrinsic biophysical properties at single-cell level. For such a purpose, we analyzed light scattering signatures of individual mononuclear blood cells in microfluidic flow. In particular, we extracted a set of biophysical properties including morphometric (dimension, shape and nucleus-to-cytosol ratio) and optical (optical density) ones to clearly discriminate different cell types and stages. By considering distinctive ranges of biophysical properties along with the obtained relative cell frequencies, we can identify unique cell classes corresponding to specific clinical conditions (p < 0.01). Based on such a straightforward approach, we are able to discriminate T-, B-lymphocytes, monocytes and beyond that first results on different stages of lymphoid and myeloid leukemia cells are presented. This work shows that the simultaneous screening of only three biophysical properties enables a clear distinction between pathological and physiological mononuclear blood stream cells. We believe our approach could represent a useful tool for a label-free analysis of biophysical single-cell signatures

Supramolecular spectrally encoded microgels with double strand probes for absolute and direct miRNA fluorescence detection at high sensitivity

We present novel microgels as a particle-based suspension array for direct and absolute microRNA (miRNA) detection. The microgels feature a flexible molecular architecture, antifouling properties, and enhanced sensitivity with a large dynamic range of detection. Specifically, they possess a core-shell molecular architecture with two different fluorescent dyes for multiplex spectral analyses and are endowed with a fluorescent probe for miRNA detection. Encoding and detection fluorescence signals are distinguishable by nonoverlapping emission spectra. Tunable fluorescence probe conjugation and emission confinement on single microgels allow for ultrasensitive miRNA detection. Indeed, the suspension array has high selectivity and sensitivity with absolute quantification, a detection limit of 10(-15) M, a dynamic range from 10(-9) to 10(-15) M, and higher accuracy than qRT-PCR. The antifouling properties of the microgels also permit the direct measurement of miRNAs in serum, without sample pretreatment or target amplification. A multiplexed assay has been tested for a set of miRNAs chosen as cancer biomarkers

Hydrogel Microparticles for Fluorescence Detection of miRNA in Mix-Read Bioassay

Herein we describe the development of a mix-read bioassay based on a three-dimensional (3D) poly ethylene glycol-(PEG)-hydrogel microparticles for the detection of oligonucleotides in complex media. The key steps of hydrogels synthesis and molecular recognition in a 3D polymer network are elucidated. The design of the DNA probes and their density in polymer network were opportunely optimized. Furthermore, the diffusion into the polymer was tuned adjusting the polymer concentration and consequently the characteristic mesh size. Upon parameters optimization, 3D-PEG-hydrogels were synthetized in a microfluidic system and provided with fluorescent probe. Target detection occurred by double strand displacement assay associated to fluorescence depletion within the hydrogel microparticle. Proposed 3D-PEG-hydrogel microparticles were designed for miR-143-3p detection. Results showed 3D-hydrogel microparticles with working range comprise between 10-6-10-12 M, had limit of detection of 30 pM and good specificity. Moreover, due to the anti-fouling properties of PEG-hydrogel, the target detection occurred in human serum with performance comparable to that in buffer. Due to the approach versatility, such design could be easily adapted to other short oligonucleotides detection

Single cell classification of macrophage subtypes by label-free cell signatures and machine learning

Pro-inflammatory (M1) and anti-inflammatory (M2) macrophage phenotypes play a fundamental role in the immune response. The interplay and consequently the classification between these two functional subtypes is significant for many therapeutic applications. Albeit, a fast classification of macrophage phenotypes is challenging. For instance, image-based classification systems need cell staining and coloration, which is usually time- and cost-consuming, such as multiple cell surface markers, transcription factors and cytokine profiles are needed. A simple alternative would be to identify such cell types by using single-cell, label-free and high throughput light scattering pattern analyses combined with a straightforward machine learning-based classification. Here, we compared different machine learning algorithms to classify distinct macrophage phenotypes based on their optical signature obtained from an ad hoc developed wide-angle static light scattering apparatus. As the main result, we were able to identify unpolarized macrophages from M1- and M2-polarized phenotypes and distinguished them from naive monocytes with an average accuracy above 85%. Therefore, we suggest that optical single-cell signatures within a lab-on-a-chip approach along with machine learning could be used as a fast, affordable, non-invasive macrophage phenotyping tool to supersede resource-intensive cell labelling

Turn-on fluorescence detection of protein by molecularly imprinted hydrogels based on supramolecular assembly of peptide multi-functional blocks

Supramolecular in-cavity target–peptide complex for self-reporting imprinted polymers

Optical signature of erythrocytes by light scattering in microfluidic flows

A camera-based light scattering approach coupled with a viscoelasticity-induced cell migration technique has been used to characterize the morphological properties of erythrocytes in microfluidic flows. We have obtained the light scattering profiles (LSPs) of individual living cells in microfluidic flows over a wide angular range and matched them with scattering simulations to characterize their morphological properties. The viscoelasticity-induced 3D cell alignment in microfluidic flows has been investigated by bright-field and holographic microscopy tracking, where the latter technique has been used to obtain precise cell alignment profiles in-flow. Such information allows variable cell probability control in microfluidic flows at very low viscoelastic polymer concentrations, obtaining cell measurements that are almost physiological. Our results confirm the possibility of precise, label-free analysis of individual living erythrocytes in microfluidic flows