Laser capture microdissection: from its principle to applications in research on neurodegeneration

Diverse genetic alteration dysregulates neuropeptide and intracellular signalling in the suprachiasmatic nuclei

In mammals, intrinsic 24 h or circadian rhythms are primarily generated by the suprachiasmatic nuclei (SCN). Rhythmic daily changes in the transcriptome and proteome of SCN cells are controlled by interlocking transcription-translation feedback loops (TTFLs) of core clock genes and their proteins. SCN cells function as autonomous circadian oscillators, which synchronize through intercellular neuropeptide signalling. Physiological and behavioural rhythms can be severely disrupted by genetic modification of a diverse range of genes and proteins in the SCN. With the advent of next generation sequencing, there is unprecedented information on the molecular profile of the SCN and how it is affected by genetically targeted alteration. However, whether the expression of some genes is more readily affected by genetic alteration of the SCN is unclear. Here, using publicly available datasets from recent RNA-seq assessments of the SCN from genetically altered and control mice, we evaluated whether there are commonalities in transcriptome dysregulation. This was completed for four different phases across the 24 h cycle and was augmented by Gene Ontology Molecular Function (GO:MF) and promoter analysis. Common differentially expressed genes (DEGs) and/or enriched GO:MF terms included signalling molecules, their receptors, and core clock components. Finally, examination of the JASPAR database indicated that E-box and CRE elements in the promoter regions of several commonly dysregulated genes. From this analysis, we identify differential expression of genes coding for molecules involved in SCN intra- and intercellular signalling as a potential cause of abnormal circadian rhythms.

Microbial Pathogenesis in the Era of Spatial Omics

The biology of a cell, whether it is a unicellular organism or part of a multicellular network, is influenced by cell type, temporal changes in cell state, and the cell's environment. Spatial cues play a critical role in the regulation of microbial pathogenesis strategies. Information about where the pathogen is-in a tissue or in proximity to a host cell-regulates gene expression and the compartmentalization of gene products in the microbe and the host. Our understanding of host and pathogen identity has bloomed with the accessibility of transcriptomics and proteomics techniques. A missing piece of the puzzle has been our ability to evaluate global transcript and protein expression in the context of the subcellular niche, primary cell, or native tissue environment during infection. This barrier is now lower with the advent of new spatial omics techniques to understand how location regulates cellular functions. This review will discuss how recent advances in spatial proteomics and transcriptomics approaches can address outstanding questions in microbial pathogenesis.

Neurotrauma investigation through spatial omics guided by mass spectrometry imaging: Target identification and clinical applications

Traumatic brain injury (TBI) represents one of the major public health concerns worldwide due to the increase in TBI incidence as a result of injuries from daily life accidents such as sports and motor vehicle transportation as well as military-related practices. This type of central nervous system trauma is known to predispose patients to several neurological disorders such as Parkinson's disease, Alzheimer's disease, chronic trauamatic encephalopathy, and age-related Dementia. Recently, several proteomic and lipidomic platforms have been applied on different TBI studies to investigate TBI-related mechanisms that have broadened our understanding of its distinct neuropathological complications. In this study, we provide an updated comprehensive overview of the current knowledge and novel perspectives of the spatially resolved microproteomics and microlipidomics approaches guided by mass spectrometry imaging used in TBI studies and its applications in the neurotrauma field. In this regard, we will discuss the use of the spatially resolved microproteomics and assess the different microproteomic sampling methods such as laser capture microdissection, parafilm assisted microdissection, and liquid microjunction extraction as accurate and precise techniques in the field of neuroproteomics. Additionally, we will highlight lipid profiling applications and their prospective potentials in characterizing molecular processes involved in the field of TBI. Specifically, we will discuss the phospholipid metabolism acting as a precursor for proinflammatory molecules such as eicosanoids. Finally, we will survey the current state of spatial neuroproteomics and microproteomics applications and present the various studies highlighting their findings in these fields.

Laser Capture Microdissection: A Gear for Pancreatic Cancer Research

The advancement in molecular techniques has been attributed to the quality and significance of cancer research. Pancreatic cancer (PC) is one of the rare cancers with aggressive behavior and a high mortality rate. The asymptomatic nature of the disease until its advanced stage has resulted in late diagnosis as well as poor prognosis. The heterogeneous character of PC has complicated cancer development and progression studies. The analysis of bulk tissues of the disease was insufficient to understand the disease, hence, the introduction of the single-cell separating technique aided researchers to decipher more about the specific cell population of tumors. This review gives an overview of the Laser Capture Microdissection (LCM) technique, one of the single-cell separation methods used in PC research.

The Dysregulation of MicroRNAs in the Development of Cervical Pre-Cancer—An Update

Globally in 2020, an estimated ~600,000 women were diagnosed with and 340,000 women died from cervical cancer. Compared to 2012, the number of cases increased by 7.5% and the number of deaths increased by 17%. MiRNAs are involved in multiple processes in the pathogenesis of cervical cancer. Dysregulation of miRNAs in the pre-stage of cervical cancer is the focus of this review. Here we summarize the dysregulated miRNAs in clinical samples from cervical pre-cancer patients and relate them to the early transformation process owing to human papillomavirus (HPV) infection in the cervical cells. When HPV infects the normal cervical cells, the DNA damage response is initiated with the involvement of HPV’s E1 and E2 proteins. Later, cell proliferation and cell death are affected by the E6 and E7 proteins. We find that the expressions of miRNAs in cervical pre-cancerous tissue revealed by different studies seldom agreed with each other. The discrepancy in sample types, samples’ HPV status, expression measurement, and methods for analysis contributed to the non-aligned results across studies. However, several miRNAs (miR-34a, miR-9, miR-21, miR-145, and miR-375) were found to be dysregulated across multiple studies. In addition, there are hints that the DNA damage response and cell growth response induced by HPV during the early transformation of the cervical cells are related to these miRNAs. Currently, no review articles analyse the relationship between the dysregulated miRNAs in cervical pre-cancerous tissue and their possible roles in the early processes involving HPV’s protein encoded by the early genes and DNA damage response during normal cell transformation. Our review provides insight on spotting miRNAs involved in the early pathogenic processes and pointing out their potential as biomarker targets of cervical pre-cancer.

Neuroproteomics of the Synapse: Subcellular Quantification of Protein Networks and Signaling Dynamics

One of the most fascinating features of the brain is its ability to adapt to its surroundings. Synaptic plasticity, the dynamic mechanism of functional and structural alterations in synaptic strength, is essential for brain functioning and underlies a variety of processes such as learning and memory. Although the molecular mechanisms underlying such rapid plasticity are not fully understood, a consensus exists on the important role of proteins. The study of these neuronal proteins using neuroproteomics has increased rapidly in the last decades, and advancements in MS-based proteomics have broadened our understanding of neuroplasticity exponentially. In this review, we discuss the trends in MS-based neuroproteomics for the study of synaptic protein-protein interactions and protein signaling dynamics, with a focus on sample types, different labeling and enrichment approaches, and data analysis and interpretation. We highlight studies from the last 5 years, with a focus on synapse structure, composition, functioning, or signaling and finally discuss some recent developments that could further advance the field of neuroproteomics.

Advancements in Cancer Stem Cell Isolation and Characterization

Occurrence of stem cells (CSCs) in cancer is well established in last two decades. These rare cells share several properties including presence of common surface markers, stem cell markers, chemo- and radio- resistance and are highly metastatic in nature; thus, considered as valuable prognostic and therapeutic targets in cancer. However, the studies related to CSCs pave number of issues due to rare cell population and difficulties in their isolation ascribed to common stem cell marker. Various techniques including flow cytometry, laser micro-dissection, fluorescent nanodiamonds and microfluidics are used for the isolation of these rare cells. In this review, we have included the advance strategies adopted for the isolation of CSCs using above mentioned techniques. Furthermore, CSCs are primarily found in the core of the solid tumors and their microenvironment plays an important role in maintenance, self-renewal, division and tumor development. Therefore, in vivo tracking and model development become obligatory for functional studies of CSCs. Fluorescence and bioluminescence tagging has been widely used for transplantation assay and lineage tracking experiments to improve our understanding towards CSCs behaviour in their niche. Techniques such as Magnetic resonance imaging (MRI) and Positron emission tomography (PET) have proved useful for tracking of endogenous CSCs which could be helpful in their identification in clinical settings.

Mapping Cellular Coordinates through Advances in Spatial Transcriptomics Technology

Complex cell-to-cell communication underlies the basic processes essential for homeostasis in the given tissue architecture. Obtaining quantitative gene-expression of cells in their native context has significantly advanced through single-cell RNA sequencing technologies along with mechanical and enzymatic tissue manipulation. This approach, however, is largely reliant on the physical dissociation of individual cells from the tissue, thus, resulting in a library with unaccounted positional information. To overcome this, positional information can be obtained by integrating imaging and positional barcoding. Collectively, spatial transcriptomics strategies provide tissue architecture-dependent as well as position-dependent cellular functions. This review discusses the current technologies for spatial transcriptomics ranging from the methods combining mechanical dissociation and single-cell RNA sequencing to computational spatial re-mapping.

De novo compartment deconvolution and weight estimation of tumor samples using DECODER

Tumors are mixtures of different compartments. While global gene expression analysis profiles the average expression of all compartments in a sample, identifying the specific contribution of each compartment remains a challenge. With the increasing recognition of the importance of non-neoplastic components, the ability to breakdown the gene expression contribution of each is critical. Here, we develop DECODER, an integrated framework which performs de novo deconvolution and single-sample compartment weight estimation. We use DECODER to deconvolve 33 TCGA tumor RNA-seq data sets and show that it may be applied to other data types including ATAC-seq. We demonstrate that it can be utilized to reproducibly estimate cellular compartment weights in pancreatic cancer that are clinically meaningful. Application of DECODER across cancer types advances the capability of identifying cellular compartments in an unknown sample and may have implications for identifying the tumor of origin for cancers of unknown primary.

Separating different cell compartments from bulk gene expression data can be challenging. Here the authors present DECODER, which can perform de novo deconvolutions on non-negative matrices including microarray, RNA-seq and ATAC-seq data sets.

Current Trends of Microfluidic Single-Cell Technologies

The investigation of human disease mechanisms is difficult due to the heterogeneity in gene expression and the physiological state of cells in a given population. In comparison to bulk cell measurements, single-cell measurement technologies can provide a better understanding of the interactions among molecules, organelles, cells, and the microenvironment, which can aid in the development of therapeutics and diagnostic tools. In recent years, single-cell technologies have become increasingly robust and accessible, although limitations exist. In this review, we describe the recent advances in single-cell technologies and their applications in single-cell manipulation, diagnosis, and therapeutics development.

An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors

By leveraging tumorgraft (patient-derived xenograft) RNA-sequencing data, we developed an empirical approach, DisHet, to dissect the tumor microenvironment (eTME). We found that 65% of previously defined immune signature genes are not abundantly expressed in renal cell carcinoma (RCC) and identified 610 novel immune/stromal transcripts. Using eTME, genomics, pathology, and medical record data involving >1,000 patients, we established an inflamed pan-RCC subtype (IS) enriched for regulatory T cells, natural killer cells, TH1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. IS is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. The IS subtype correlated with systemic manifestations of inflammation such as thrombocytosis and anemia, which are enigmatic predictors of poor prognosis. Furthermore, IS was a strong predictor of poor survival. Our analyses suggest that tumor cells drive the stromal immune response. These data provide a missing link between tumor cells, the TME, and systemic factors.Significance: We undertook a novel empirical approach to dissect the renal cell carcinoma TME by leveraging tumorgrafts. The dissection and downstream analyses uncovered missing links between tumor cells, the TME, systemic manifestations of inflammation, and poor prognosis. Cancer Discov; 8(9); 1142-55. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 1047.

Electrostatic Capture Following Laser Microdissection for the Preparation of Homogeneous Biological Specimens

There is an unmet need for researchers in life sciences and clinical pathology to obtain untainted target cells with very high accuracy, which are suitable for subsequent genome and protein analysis. In this paper, an electrostatic capture laser microdissection technology (ECM) is proposed and explained. Following microscopic identification and separation of target cells from the surrounding tissues using laser cutting, the ECM uses electrostatic forces to capture target cells. Validation experiments indicate that ECM can capture a wide assortment of contamination-free homogeneous samples, ranging from very tiny pieces of a few micrometers in diameter to large pieces with a surface area of over 40,000 µm2. Evidence is also provided indicating that uncontaminated homogeneous tissue materials collected by ECM are suitable for further DNA and RNA analysis. This suggests that ECM capture causes little or no identifiable damage to the collected tissues. This technique has significant advantages compared with existing traditional capture methods, such as very low risk of biological sample damage and the fact that it can be applied to both upright and inverted microscopy. The latter allows for separating target cells in tissue culture. ECM usage provides a cost-effective alternative to more traditional laser capture microdissection techniques.

Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock

Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN). Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies toward understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

Mitochondrial DNA typing of laser-captured single sperm cells to differentiate individuals in a mixed semen stain

The identification of individuals in a mixture of two semen samples usually involves an analysis of autosomal and Y chromosomal short tandem repeats (STR) which can exclude unrelated individuals but cannot achieve the purpose of individual identification. In sperm cells, there are multiple copies of mitochondrial DNAs (mtDNA) which exhibit genetic polymorphisms in different matrilineal-related individuals. Single-cell capture technology can be applied to obtain some single sperm cells in a mixed semen sample, then polymerase chain reaction can be employed to amplify the mtDNA hypervariable region I (HVR I) from each cell. By pooling the cells with the same HVR I sequence, we can obtain the sufficient nuclear DNA for STR typing.

Laser ablation sample transfer for localized LC-MS/MS proteomic analysis of tissue

We have developed a mid-infrared laser ablation sampling technique for nano-flow liquid chromatography coupled with tandem mass spectrometry proteomic profiling of discrete regions from biological samples. Laser ablation performed in transmission geometry was used to transfer material from 50-µm thick tissue sections mounted on a glass microscope slide to a capturing solvent. Captured samples were processed using filter-aided sample preparation and enzymatically digested to produce tryptic peptides for data-dependent analysis with an ion trap mass spectrometer. Comparison with ultraviolet laser capture microdissection from neighboring regions on the same tissue section revealed that infrared laser ablation transfer has higher reproducibility between samples from different consecutive sections. Both techniques allowed for proteomics investigation of different organelles without the addition of surfactants.