Tumor cell differentiation by label-free fluorescence microscopy

Identification of resident progenitors labeled with Top2a responsible for proximal tubular regeneration in ischemia reperfusion-induced acute kidney injury

BACKGROUND

Acute kidney injury is a common fatal disease with complex etiology and limited treatment methods. Proximal tubules (PTs) are the most vulnerable segment. Not only in injured kidneys but also in normal kidneys, shedding of PTs often happens. However, the source cells and mechanism of their regeneration remain unclear.

METHODS

ScRNA and snRNA sequencing data of acute injured or normal kidney were downloaded from GEO database to identify the candidate biomarker of progenitor of proximal tubules. SLICE algorithm and CytoTRACE analyses were employed to evaluate the stemness of progenitors. Then the repairing trajectory was constructed through pseudotime analyses. SCENIC algorithm was used to detect cell-type-specific regulon. With spatial transcriptome data, the location of progenitors was simulated. Neonatal/ adult/ aged mice and preconditioning AKI mice model and deconvolution of 2 RNA-seq data were employed for validation.

RESULTS

Through cluster identification, PT cluster expressed Top2a specifically was identified to increase significantly during AKI. With relatively strong stemness, the Top2a-labeled PT cluster tended to be the origin of the repairing trajectory. Moreover, the cluster was regulated by Pbx3-based regulon and possessed great segmental heterogeneity. Changes of Top2a between neonatal and aged mice and among AKI models validated the progenitor role of Top2a-labeled cluster.

CONCLUSIONS

Our study provided transcriptomic evidence that resident proximal tubular progenitors labeled with Top2a participated in regeneration. Considering the segmental heterogeneity, we find that there is a group of reserve progenitor cells in each tubular segment. When AKI occurs, the reserve progenitors of each tubular segment proliferate and replenish first, and PT-progenitors, a cluster with no obvious PT markers replenish each subpopulation of the reserve cells.

Lasers in Live Cell Microscopy

Due to their unique properties—coherent radiation, diffraction limited focusing, low spectral bandwidth and in many cases short light pulses—lasers play an increasing role in live cell microscopy. Lasers are indispensable tools in 3D microscopy, e.g., confocal, light sheet or total internal reflection microscopy, as well as in super-resolution microscopy using wide-field or confocal methods. Further techniques, e.g., spectral imaging or fluorescence lifetime imaging (FLIM) often depend on the well-defined spectral or temporal properties of lasers. Furthermore, laser microbeams are used increasingly for optical tweezers or micromanipulation of cells. Three exemplary laser applications in live cell biology are outlined. They include fluorescence diagnosis, in particular in combination with Förster Resonance Energy Transfer (FRET), photodynamic therapy as well as laser-assisted optoporation, and demonstrate the potential of lasers in cell biology and—more generally—in biomedicine.

Förster resonance energy transfer-what can we learn and how can we use it?

The present manuscript gives a short overview on Förster Resonance Energy Transfer (FRET) of molecular interactions in the nanometre range. First, its principle is described and a short historical overview is given. Subsequently some principal methods and applications of FRET sensing and imaging are described (with some emphasis on fluorescence lifetime imaging, FLIM), and finally two innovative FRET techniques are presented in more detail. Applications are focused on measurements of living cells.

Elastic and inelastic light scattering spectroscopy and its possible use for label-free brain tumor typing

This paper presents an approach for label-free brain tumor tissue typing. For this application, our dual modality microspectroscopy system combines inelastic Raman scattering spectroscopy and Mie elastic light scattering spectroscopy. The system enables marker-free biomedical diagnostics and records both the chemical and morphologic changes of tissues on a cellular and subcellular level. The system setup is described and the suitability for measuring morphologic features is investigated. Graphical Abstract Bimodal approach for label-free brain tumor typing. Elastic and inelastic light scattering spectra are collected laterally resolved in one measurement setup. The spectra are investigated by multivariate data analysis for assigning the tissues to specific WHO grades according to their malignancy.

NAD(P)H and Flavin Autofluorescence Correlation with ATP in Rat Livers with Different Metabolic Steady-State Conditions

The monitoring of NAD(P)H and flavin autofluorescence (AF) is at the basis of numerous investigations on energy metabolism. Nevertheless, the ability of these AF biomarkers to accurately represent the energy currency, ATP, is poorly explored. Here, we focused on the AF/ATP correlation in lean and fatty livers with different steady-state metabolic conditions, achieved after organ isolation, preservation and recovery, in a likely dependence on both liver intrinsic metabolic features and externally induced perturbations. Within these eventual, various conditions, a significant correlation was detected between liver NAD(P)H and flavin AF, measured via fiber-optic probe, and biochemical ATP data, strengthening AF as biomarker of energy metabolism in steady-state conditions for wide-ranging experimental and diagnostic applications.

SLICE: determining cell differentiation and lineage based on single cell entropy

A complex organ contains a variety of cell types, each with its own distinct lineage and function. Understanding the lineage and differentiation state of each cell is fundamentally important for the ultimate delineation of organ formation and function. We developed SLICE, a novel algorithm that utilizes single-cell RNA-seq (scRNA-seq) to quantitatively measure cellular differentiation states based on single cell entropy and predict cell differentiation lineages via the construction of entropy directed cell trajectories. We validated our approach using three independent data sets with known lineage and developmental time information from both Homo sapiens and Mus musculus. SLICE successfully measured the differentiation states of single cells and reconstructed cell differentiation trajectories that have been previously experimentally validated. We then applied SLICE to scRNA-seq of embryonic mouse lung at E16.5 to identify lung mesenchymal cell lineage relationships that currently remain poorly defined. A two-branched differentiation pathway of five fibroblastic subtypes was predicted using SLICE. The present study demonstrated the general applicability and high predictive accuracy of SLICE in determining cellular differentiation states and reconstructing cell differentiation lineages in scRNA-seq analysis.