Proteomic analysis of nuclei dissected from fixed rat brain tissue using expression microdissection

Antibody-based nanotechnology

Antibodies are considered the hallmark of the adaptive immune system in that they mediate various key biological functions, such as direct neutralization and recruitment of effector immune cells to eliminate invading pathogens. Antibodies exhibit several unique properties, including high diversity (enabling binding to a wide range of targets), high specificity and structural integrity. These properties and the understanding that antibodies can be utilized in a wide range of applications have motivated the scientific community to develop new approaches for antibody repertoire analysis and rapid monoclonal antibody discovery. Today, antibodies are key modules in the pharmaceutical and diagnostic industries. By virtue of their high affinity and specificity to their targets and the availability of technologies to engineer different antibodies to a wide range of targets, antibodies have become the most promising natural biological molecules in a range of biotechnological applications, such as: highly specific and sensitive nanobiosensors for the diagnostics of different biomarkers; nanoparticle-based targeted drug delivery systems to certain cells or tissues; and nanomachines, which are nanoscale mechanical devices that enable energy conversion into precise mechanical motions in response to specific molecular inputs. In this review, we start by describing the unique properties of antibodies, how antibody diversity is generated, and the available technologies for antibody repertoire analysis and antibody discovery. Thereafter, we provide an overview of some antibody-based nanotechnologies and discuss novel and promising approaches for the application of antibodies in the nanotechnology field. Overall, we aim to bridge the knowledge gap between the nanotechnology and antibody engineering disciplines by demonstrating how technological advances in the antibody field can be leveraged to develop and/or enhance new technological approaches in the nanotechnology field.

Computer-Aided Laser Dissection: A Microdissection Workflow Leveraging Image Analysis Tools

Introduction

The development and application of new molecular diagnostic assays based on next-generation sequencing and proteomics require improved methodologies for procurement of target cells from histological sections. Laser microdissection can successfully isolate distinct cells from tissue specimens based on visual selection for many research and clinical applications. However, this can be a daunting task when a large number of cells are required for molecular analysis or when a sizeable number of specimens need to be evaluated.

Materials and Methods

To improve the efficiency of the cellular identification process, we describe a microdissection workflow that leverages recently developed and open source image analysis algorithms referred to as computer-aided laser dissection (CALD). CALD permits a computer algorithm to identify the cells of interest and drive the dissection process.

Results

We describe several "use cases" that demonstrate the integration of image analytic tools probabilistic pairwise Markov model, ImageJ, spatially invariant vector quantization (SIVQ), and eSeg onto the ThermoFisher Scientific ArcturusXT and Leica LMD7000 microdissection platforms.

Conclusions

The CALD methodology demonstrates the integration of image analysis tools with the microdissection workflow and shows the potential impact to clinical and life science applications.

Laser microdissection: A powerful tool for genomics at cell level

Laser microdissection (LM) has become widely democratized over the last fifteen years. Instruments have evolved to offer more powerful and efficient lasers as well as new options for sample collection and preparation. Technological evolutions have also focused on the post-microdissection analysis capabilities, opening up investigations in all disciplines of experimental and clinical biology, thanks to the advent of new high-throughput methods of genome analysis, including RNAseq and proteomics, now globally known as microgenomics, i.e. analysis of biomolecules at the cell level. In spite of the advances these rapidly developing methods have allowed, the workflow for sampling and collection by LM remains a critical step in insuring sample integrity in terms of histology (accurate cell identification) and biochemistry (reliable analyzes of biomolecules). In this review, we describe the sample processing as well as the strengths and limiting factors of LM applied to the specific selection of one or more cells of interest from a heterogeneous tissue. We will see how the latest developments in protocols and methods have made LM a powerful and sometimes essential tool for genomic and proteomic analyzes of tiny amounts of biomolecules extracted from few cells isolated from a complex tissue, in their physiological context, thus offering new opportunities for understanding fundamental physiological and/or patho-physiological processes.

Optimized expression-based microdissection of formalin-fixed lung cancer tissue

Analysis of specific DNA alterations in precision medicine of tumors is crucially important for molecular targeted treatments. Lung cancer is a prototypic example and one of the leading causes of cancer-related deaths worldwide. One major technical problem of detecting DNA alterations in tissue samples is cellular heterogeneity, that is, mixture of tumor and normal cells. Microdissection is an important tool to enrich tumor cells from heterogeneous tissue samples. However, conventional laser capture microdissection has several disadvantages like user-dependent selection of regions of interest (ROI), high costs for dissection systems and long processing times. ROI selection in expression-based microdissection (xMD) directly relies on cancer cell-specific immunostaining. Whole-slide irradiation leads to localized energy absorption at the sites of most intensive staining and melting of a membrane covering the slide, so that tumor cells can be isolated by removing the complete membrane. In this study, we optimized xMD of lung cancer tissue by enhancing staining intensity of tumor cell-specific immunostaining and processing of the stained samples. This optimized procedure did not alter DNA quality and resulted in enrichment of mutated EGFR DNA from lung adenocarcinoma specimens after xMD. We here also introduce a quality control protocol based on digital whole-slide scanning and image analysis before and after xMD to quantify selectivity and efficiency of the procedure. In summary, this study provides a workflow for xMD, adapted and tested for lung cancer tissue that can be used for lung tumor cell dissection before diagnostic or investigatory analyses.

Optimized Protocol for Quantitative Multiple Reaction Monitoring-Based Proteomic Analysis of Formalin-Fixed, Paraffin-Embedded Tissues

Despite a clinical, economic, and regulatory imperative to develop companion diagnostics, precious few new biomarkers have been successfully translated into clinical use, due in part to inadequate protein assay technologies to support large-scale testing of hundreds of candidate biomarkers in formalin-fixed paraffin-embedded (FFPE) tissues. Although the feasibility of using targeted, multiple reaction monitoring mass spectrometry (MRM-MS) for quantitative analyses of FFPE tissues has been demonstrated, protocols have not been systematically optimized for robust quantification across a large number of analytes, nor has the performance of peptide immuno-MRM been evaluated. To address this gap, we used a test battery approach coupled to MRM-MS with the addition of stable isotope-labeled standard peptides (targeting 512 analytes) to quantitatively evaluate the performance of three extraction protocols in combination with three trypsin digestion protocols (i.e., nine processes). A process based on RapiGest buffer extraction and urea-based digestion was identified to enable similar quantitation results from FFPE and frozen tissues. Using the optimized protocols for MRM-based analysis of FFPE tissues, median precision was 11.4% (across 249 analytes). There was excellent correlation between measurements made on matched FFPE and frozen tissues, both for direct MRM analysis (R(2) = 0.94) and immuno-MRM (R(2) = 0.89). The optimized process enables highly reproducible, multiplex, standardizable, quantitative MRM in archival tissue specimens.

High-Throughput Microdissection for Next-Generation Sequencing

Precision medicine promises to enhance patient treatment through the use of emerging molecular technologies, including genomics, transcriptomics, and proteomics. However, current tools in surgical pathology lack the capability to efficiently isolate specific cell populations in complex tissues/tumors, which can confound molecular results. Expression microdissection (xMD) is an immuno-based cell/subcellular isolation tool that procures targets of interest from a cytological or histological specimen. In this study, we demonstrate the accuracy and precision of xMD by rapidly isolating immunostained targets, including cytokeratin AE1/AE3, p53, and estrogen receptor (ER) positive cells and nuclei from tissue sections. Other targets procured included green fluorescent protein (GFP) expressing fibroblasts, in situ hybridization positive Epstein-Barr virus nuclei, and silver stained fungi. In order to assess the effect on molecular data, xMD was utilized to isolate specific targets from a mixed population of cells where the targets constituted only 5% of the sample. Target enrichment from this admixed cell population prior to next-generation sequencing (NGS) produced a minimum 13-fold increase in mutation allele frequency detection. These data suggest a role for xMD in a wide range of molecular pathology studies, as well as in the clinical workflow for samples where tumor cell enrichment is needed, or for those with a relative paucity of target cells.

Proteogenomics of the human hippocampus: The road ahead

The hippocampus is one of the most essential components of the human brain and plays an important role in learning and memory. The hippocampus has drawn great attention from scientists and clinicians due to its clinical importance in diseases such as Alzheimer's disease (AD), non-AD dementia, and epilepsy. Understanding the function of the hippocampus and related disease mechanisms requires comprehensive knowledge of the orchestration of the genome, epigenome, transcriptome, proteome, and post-translational modifications (PTMs) of proteins. The past decade has seen remarkable advances in the high-throughput sequencing techniques that are collectively called next generation sequencing (NGS). NGS enables the precise analysis of gene expression profiles in cells and tissues, allowing powerful and more feasible integration of expression data from the gene level to the protein level, even allowing "-omic" level assessment of PTMs. In addition, improved bioinformatics algorithms coupled with NGS technology are finally opening a new era for scientists to discover previously unidentified and elusive proteins. In the present review, we will focus mainly on the proteomics of the human hippocampus with an emphasis on the integrated analysis of genomics, epigenomics, transcriptomics, and proteomics. Finally, we will discuss our perspectives on the potential and future of proteomics in the field of hippocampal biology. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Applications of mass spectrometry for quantitative protein analysis in formalin-fixed paraffin-embedded tissues

Proteomic analysis of tissues has advanced in recent years as instruments and methodologies have evolved. The ability to retrieve peptides from formalin-fixed paraffin-embedded tissues followed by shotgun or targeted proteomic analysis is offering new opportunities in biomedical research. In particular, access to large collections of clinically annotated samples should enable the detailed analysis of pathologically relevant tissues in a manner previously considered unfeasible. In this paper, we review the current status of proteomic analysis of formalin-fixed paraffin-embedded tissues with a particular focus on targeted approaches and the potential for this technique to be used in clinical research and clinical diagnosis. We also discuss the limitations and perspectives of the technique, particularly with regard to application in clinical diagnosis and drug discovery.