Biology subjects

Merola, F.

Publications and source records attributed to Merola, F..

4 recordsLinked to original sources

bioRxiv2021

Stain-free nucleus identification in holographic learning flow cyto-tomography

Quantitative Phase Imaging (QPI) has gained popularity because it can avoid the staining step, which in some cases is difficult or impossible. However, QPI does not provide the well-known specificity to various parts of the cell (e.g., organelles, membrane). Here we show a novel computational segmentation method based on statistical inference that bridges the gap between the specificity of Fluorescence Microscopy (FM) and the label-free property of QPI techniques to identify the cell nucleus. We demonstrate application to stain-free cells reconstructed through the holographic learning and in flow cyto-tomography modality. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus-like regions can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal FM data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting the three-dimensional (3D) intracellular specificity directly from the phase-contrast data in a typical flow cytometry configuration.

bioengineering↗

bioRxiv2021

Tracking-based rolling angles recovery method for holographic tomography of flowing cells

Holographic Tomography (HT) is an emerging label-free technique for microscopic bioimaging applications, that allows reconstructing the three-dimensional (3D) refractive index (RI) distribution of biological specimens. Recently, an in-flow HT technique has been proposed in which multiple digital holograms are recorded at different viewing angles around the sample while it flows and rotates within a microfluidic channel. However, unlike conventional HT methods, there is no a priori information about cell 3D orientations, that are instead requested to perform any tomographic algorithm. Here we investigate a tracking-based rolling angles recovery method, showing robustness against the samples features. It is based on a phase images similarity metric recently demonstrated, that exploits the local contrast phase measurements to recognize a full cell rotation within the microfluidic channel. Hence, the orientations of the flowing cells are retrieved from their positions, which are in turn computed through the 3D holographic tracking. The performances of the rolling angles recovery method have been assessed both numerically, by simulating a 3D cell phantom, and experimentally, by reconstructing the 3D RI tomograms of two cancer cells. Both the numerical and the experimental analysis have been performed at different spatial resolutions. This rolling angles recovery method, not depending on the cell shapes, the RI contents, and the optical experimental conditions, could pave the way to the study of circulating tumor cells (CTCs) in the challenging tool of liquid biopsy.

bioengineering↗

bioRxiv2021

tdLanYFP, a yellow, bright, photostable and pH insensitive fluorescent protein for live cell imaging and FRET-based sensing strategies

Yellow fluorescent proteins (YFP) are widely used as optical reporters in Forster Resonance Energy Transfer (FRET) based biosensors. Although great improvements have been done, the sensitivity of the biosensors is still limited by the low photostability and the poor fluorescence performances of YFPs at acidic pHs. Here, we characterize the yellow fluorescent protein, tdLanYFP, derived from the tetrameric protein from the cephalochordate B. lanceolatum, LanYFP. With a quantum yield of 0.92 and an extinction coefficient of 133 000 mol-1.L.cm-1, it is, to our knowledge, the brightest dimeric fluorescent protein available. Contrasting with EYFP and its derivatives, tdLanYFP has a very high photostability in vitro and in live cells. As a consequence, tdLanYFP allows imaging of cellular structures with sub-diffraction resolution using STED nanoscopy and is compatible with the use of spectro-microscopies in single molecule regimes. Its very low pK1/2 of 3.9 makes tdLanYFP an excellent tag even at acidic pHs. Finally, we show that tdLanYFP is valuable FRET partner either as donor or acceptor in different biosensing modalities. Altogether, these assets make tdLanYFP a very attractive yellow fluorescent protein for long-term or single-molecule live cell imaging including FRET experiments at acidic pH.

biophysics↗

bioRxiv2019

Optimised FRET pairs and quantification approaches to detect the activation of Aurora kinase A at mitosis

Genetically-encoded Forsters Resonance Energy Transfer (FRET) biosensors are indispensable tools to sense the spatiotemporal dynamics of signal transduction pathways. Investigating the crosstalk between different signalling pathways is becoming increasingly important to follow cell development and fate programs. To this end, FRET biosensors must be optimised to monitor multiple biochemical activities simultaneously and in single cells. In addition, their sensitivity must be increased to follow their activation even when the abundance of the biosensor is low. We describe here the development of a second generation of Aurora kinase A/AURKA biosensors. First, we adapt the original AURKA biosensor -GFP-AURKA-mCherry- to multiplex FRET by using dark acceptors as ShadowG or ShadowY. Then, we use the novel superYFP acceptor protein to measure FRET by 2-colour Fluorescence Cross-Correlation Spectroscopy, in cytosolic regions where the abundance of AURKA is extremely low and undetectable with the original AURKA biosensor. These results pave the way to the use of FRET biosensors to follow AURKA activation in conjunction with substrate-based activity biosensors. In addition, they open up the possibility of tracking the activation of small pools of AURKA and its interaction with novel substrates, which would otherwise remain undetectable with classical biochemical approaches.

cell biology↗