Extracting histones for the specific purpose of label-free MS

Extracting histones from cells is the first step in studies that aim to characterize histones and their post-translational modifications (hPTMs) with MS. In the last decade, label-free quantification is more frequently being used for MS-based histone characterization. However, many histone extraction protocols were not specifically designed for label-free MS. While label-free quantification has its advantages, it is also very susceptible to technical variation. Here, we adjust an established histone extraction protocol according to general label-free MS guidelines with a specific focus on minimizing sample handling. These protocols are first evaluated using SDS-PAGE. Hereafter, a selection of extraction protocols was used in a complete histone workflow for label-free MS. All protocols display nearly identical relative quantification of hPTMs. We thus show that, depending on the cell type under investigation and at the cost of some additional contaminating proteins, minimizing sample handling can be done during histone isolation. This allows analyzing bigger sample batches, leads to reduced technical variation and minimizes the chance of in vitro alterations to the hPTM snapshot. Overall, these results allow researchers to determine the best protocol depending on the resources and goal of their specific study. Data are available via ProteomeXchange with identifier PXD002885

Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy.

Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single-cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label-free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K-562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells-a critical step toward label-free single cancer cell dormancy research. The result suggests a droplet-based noninvasive and label-free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry

Semiconductor Electronic Label-Free Assay for Predictive Toxicology.

While animal experimentations have spearheaded numerous breakthroughs in biomedicine, they also have spawned many logistical concerns in providing toxicity screening for copious new materials. Their prioritization is premised on performing cellular-level screening in vitro. Among the screening assays, secretomic assay with high sensitivity, analytical throughput, and simplicity is of prime importance. Here, we build on the over 3-decade-long progress on transistor biosensing and develop the holistic assay platform and procedure called semiconductor electronic label-free assay (SELFA). We demonstrate that SELFA, which incorporates an amplifying nanowire field-effect transistor biosensor, is able to offer superior sensitivity, similar selectivity, and shorter turnaround time compared to standard enzyme-linked immunosorbent assay (ELISA). We deploy SELFA secretomics to predict the inflammatory potential of eleven engineered nanomaterials in vitro, and validate the results with confocal microscopy in vitro and confirmatory animal experiment in vivo. This work provides a foundation for high-sensitivity label-free assay utility in predictive toxicology

RIBAR and xRIBAR: methods for reproducible relative MS/MS-based label-free protein quantification

Mass spectrometry-driven proteomics is increasingly relying on quantitative analyses for biological discoveries. As a result, different methods and algorithms have been developed to perform relative or absolute quantification based on mass spectrometry data. One of the most popular quantification methods are the so-called label-free approaches, which require no special sample processing, and can even be applied retroactively to existing data sets. Of these label-free methods, the MS/MS-based approaches are most often applied, mainly because of their inherent simplicity as compared to MS-based methods. The main application of these approaches is the determination of relative protein amounts between different samples, expressed as protein ratios. However, as we demonstrate here, there are some issues with the reproducibility across replicates of these protein ratio sets obtained from the various, MS/MS-based label-free methods, indicating that the existing methods are not optimally robust. We therefore present two new Methods (called RIBAR and xRIBAR) that use the available MS/MS data more effectively, achieving increased robustness. Both the accuracy and the precision of our novel methods are analyzed and compared to the existing methods to illustrate the increased robustness of our new methods over existing ones

Serial optical coherence microscopy for label-free volumetric histopathology

The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories. However, slide-based microscopic pathology is not suitable for visualizing the large-scale tissue and native 3D organ structure due to its sampling limitation and shallow imaging depth. Here, we demonstrate serial optical coherence microscopy (SOCM) technique that offers label-free, high-throughput, and large-volume imaging of ex vivo mouse organs. A 3D histopathology of whole mouse brain and kidney including blood vessel structure is reconstructed by deep tissue optical imaging in serial sectioning techniques. Our results demonstrate that SOCM has unique advantages as it can visualize both native 3D structures and quantitative regional volume without introduction of any contrast agents

High-resolution Imaging of nanoparticles in wide-field interferometric scattering microscopy

Single particle interferometric scattering microscopy has demonstrated great capability in label-free imaging of sub-wavelength dielectric nanoparticles (r<25 nm); however, it suffers from diffraction-limited resolution. Here, we demonstrate ~2-fold improvement in lateral resolution upon asymmetric illumination.Published versio

Label-free enrichment of adrenal cortical progenitor cells using inertial microfluidics.

Passive and label-free isolation of viable target cells based on intrinsic biophysical cellular properties would allow for cost savings in applications where molecular biomarkers are known as well as potentially enable the separation of cells with little-to-no known molecular biomarkers. We have demonstrated the purification of adrenal cortical progenitor cells from digestions of murine adrenal glands utilizing hydrodynamic inertial lift forces that single cells and multicellular clusters differentially experience as they flow through a microchannel. Fluorescence staining, along with gene expression measurements, confirmed that populations of cells collected in different outlets were distinct from one another. Furthermore, primary murine cells processed through the device remained highly viable and could be cultured for 10 days in vitro. The proposed target cell isolation technique can provide a practical means to collect significant quantities of viable intact cells required to translate stem cell biology to regenerative medicine in a simple label-free manner