Laser-capture microdissection

Lactobacillus rhamnosus-derived extracellular vesicles influence calcium deposition in a model of breast cancer intraductal calcium stress

Extracellular calcium export by the breast ductal epithelium is crucial during lactation and plays a significant role in breast cancer progression. Intraductal calcium deposition is a hallmark of aggressive premalignant lesions. This study tested the hypothesis that microbiome-derived extracellular vesicles (EVs) influence calcium modulation in premalignant breast cancer lesions. Based on the analysis of plasma, serum, saliva, and tissue collected from breast cancer patients and controls (N = 150), Lactobacillus rhamnosus (Lr) was chosen as the model microbiota. In a BT-474 human breast cancer cell line monolayer culture under acute calcium stress, Lr EVs enhanced intracellular calcium intake. In a BT474 3D spheroid model under chronic calcium stress, Lr EVs increased extracellular calcium deposition and mRNA expression of calcium export channel plasma membrane calcium-transporting ATPase 2 (PMCA2) and stromal interaction molecule 1 (STIM1) in a dose-dependent manner. We propose that Lr EVs influence calcium regulation and mineral deposition, thereby affecting premalignant breast cancer progression.

Single-cell technology for cell-based drug delivery and pharmaceutical research

Leveraging the capacity to precisely manipulate and analyze individual cells, single-cell technology has rapidly become an indispensable tool in the advancement of cell-based drug delivery systems and innovative cell therapies. This technology offers powerful means to address cellular heterogeneity and significantly enhance therapeutic efficacy. Recent breakthroughs in techniques such as single-cell electroporation, mechanical perforation, and encapsulation, particularly when integrated with microfluidics and bioelectronics, have led to remarkable improvements in drug delivery efficiency, reductions in cytotoxicity, and more precise targeting of therapeutic effects. Moreover, single-cell analyses, including advanced sequencing and high-resolution sensing, offer profound insights into complex disease mechanisms, the development of drug resistance, and the intricate processes of stem cell differentiation. This review summarizes the most significant applications of these single-cell technologies, highlighting their impact on the landscape of modern biomedicine. Furthermore, it provides a forward-looking perspective on future research directions aimed at further optimizing drug delivery strategies and enhancing therapeutic outcomes in the treatment of various diseases.

Proteomic Insights into IgA Nephropathy: A Comprehensive Analysis of Differentially Expressed Proteins in the Kidney

IgA nephropathy represents a significant challenge in nephrology research, and an understanding of its underlying molecular mechanisms is crucial. In this study, we conducted a comprehensive proteomic investigation of IgA nephropathy utilizing microdissection techniques combined with data-independent acquisition technology. Our analysis focused on differentially expressed proteins in the glomeruli, interstitium, and tubules of the kidney. Functional enrichment analysis revealed distinct pathway enrichment patterns, with fatty acid synthesis predominating in the glomerulus and complement and coagulation pathways predominantly enriched in the tubules. These pathway enrichments suggest potential key contributors to the pathogenesis of IgA nephropathy. Furthermore, our study identified ATP1B1 and COX4I1 in the glomerulus and SLC22A13 in the tubules as promising diagnostic markers for the disease. Meanwhile, C4A and APEX1 proteins were identified as valuable biomarkers for assessing disease progression. This research could provide valuable insights into the proteomic alterations associated with IgA nephropathy and offer potential targets for further therapeutic exploration.

The EGFR Pathway as a Potential Therapeutic Target for Modulation of Radiation-induced Liver Injury

Radiation exposure can result in various complications influenced by factors such as dose, the amount of tissue exposed, and the type of tissue exposed. Radiation-induced liver injury (RILI) is a concern in cancer patients receiving thoracic and upper abdominal radiation, but it can also be a risk for civilians exposed to radiation in a nuclear event. RILI can lead to organ dysfunction or death; a deeper understanding of how radiation causes damage to normal tissue could pave the way for new treatments. In our study, we focused on the effects of radiation on the two main liver cell types: liver sinusoidal endothelial cells (LSECs) and hepatocytes. We exposed these cells to different doses of radiation (2, 4 or 8 Gy) as well as a sham irradiation (0 Gy) control. Proteins were extracted at 30 min, 6 h and 24 h postirradiation and analyzed using reverse phase protein array (RPPA). We observed changes to the Hepatic fibrosis signaling pathway, IL-8 signaling, and S100 family signaling pathways across multiple doses and time points in LSECs. In hepatocytes, radiation affected different pathways; we see changes in the Th1 and Th2 signaling pathways and the IL-10 signaling pathway. These pathways are critical in mediating the immune response, with Th1 being associated with pro-inflammatory responses and Th2 with anti-inflammatory responses. Hub proteins from protein-protein interaction (PPI) networks across all time points for both LSECs and hepatocytes highlighted EGFR as a top-ranked protein, indicating the potential role in mitigating radiation damage in liver cells. Herein, we showed alterations in protein expression after RILI using RPPA at early time points (hours to days) to determine potentially targetable molecular pathways. We further highlighted potential therapeutic protein markers, including EGFR, as an example of the potential utility of RPPA in target discovery.

Use of polyethylene glycol as an alternative to optimal cutting temperature medium in freeze sectioning for plant histochemical studies

Plant anatomical and histochemical studies are concerned with the structural organization of tissues as well as localization of various metabolites and enzyme activity inside cells and tissues. Traditionally, rotary microtomes are used for paraffin and resin-embedded samples which provide excellent preservation of tissue morphology but removes enzymes, lipid components, and various specialized metabolites. Freeze sectioning apparently remained unexplored in plant histology because of the presence of rigid cell walls and highly vacuolated cytoplasm in plant tissues. In this study, we have described a simple cryostat-based sectioning technique using polyethylene glycol (PEG) as embedding medium after glycerol infiltration that protects the plant tissues from freezing and thawing damage. We have also compared the suitability of inexpensive aqueous PEG solution as compared to commercially available optimal cutting temperature (OCT) medium and obtained identical microscopic images. Diverse plant organs from different genera were sectioned to check the application of this method in plant anatomical studies. In all the cases, cross sections were shown to be well preserved similar to paraffin-embedded plant tissues. In addition, histochemical analyses showed retention of metabolites and even enzymes in the tissues, which can make this method an alternate choice in cryo-microtomy replacing the expensive OCT medium.

Applications of spatial transcriptomics in studying spermatogenesis

Spermatogenesis is a complex differentiation process that is facilitated by a series of cellular and molecular events. High-throughput genomics approaches, such as single-cell RNA sequencing, have begun to enable the systematic characterization of these events. However, the loss of tissue context because of tissue disassociations in the single-cell isolation protocols limits our ability to understand the regulation of spermatogenesis and how defects in spermatogenesis lead to infertility. The recent advancement of spatial transcriptomics technologies enables the studying of the molecular signatures of various cell types and their interactions in the native tissue context. In this review, we discuss how spatial transcriptomics has been leveraged to identify spatially variable genes, characterize cellular neighborhood, delineate cell‒cell communications, and detect molecular changes under pathological conditions in the mammalian testis. We believe that spatial transcriptomics, along with other emerging spatially resolved omics assays, can be utilized to further our understanding of the underlying causes of male infertility, and to facilitate the development of new treatment approaches.

Acoustic ejection mass spectrometry: the potential for personalized medicine

INTRODUCTION

The emergence of personalized medicine (PM) has shifted the focus of healthcare from the traditional 'one-size-fits-all' approach to strategies tailored to individual patients, accounting for genetic, environmental, and lifestyle factors. Acoustic ejection mass spectrometry (AEMS) is a novel technology that offers a robust and scalable platform for high-throughput MS readout. AEMS achieves analytical speeds of one sample per second while maintaining high data quality, broad compound coverage, and minimal sample preparation, making it an invaluable tool for PM.

AREAS COVERED

This article explores the potential of AEMS in critical PM applications, including therapeutic drug monitoring (TDM), proteomics, metabolomics, and mass spectrometry imaging. AEMS simplifies conventional workflows by minimizing sample preparation, enhancing automation compatibility, and enabling direct analysis of complex biological matrices.

EXPERT OPINION

Integrating AEMS with orthogonal separation techniques such as differential mobility spectrometry (DMS) further addresses challenges in isomer discrimination, expanding the platform's analytical capabilities. Additionally, the development of high-throughput data processing tools could further enable AEMS to accelerate the development of personalized medicine.

Cutting-edge RNA technologies to advance the understanding of learning and memory

Following the recent emergence of RNA as a therapeutic tool, and coupled with an explosion in the development of new RNA technologies, it is rapidly becoming clear that the 21st century is the era of RNA. Neuroscience as a discipline has a long history of embracing new technology to advance the understanding of brain function, particularly in the context of learning and memory. In this short review, we highlight four broad categories of emerging RNA technologies, namely: imaging, isolation, identification and manipulation, and discuss their potential to advance the fundamental understanding of how RNA impacts experience-dependent plasticity, learning, and memory.

Integrating -Omic Technologies across Modality, Space, and Time to Decipher Remodeling in Cardiac Disease

PURPOSE OF REVIEW

Despite significant efforts to understand pathophysiological processes underlying cardiac diseases, the molecular causes for the most part remain unresolved. Rapid advancements in -omics technologies, and their application in cardiac research, offer new insight into cardiac remodeling in disease states. This review aims to provide an accessible overview of recent advances in omics approaches for studying cardiac remodeling, catering to readers without extensive prior expertise.

RECENT FINDINGS

We provide a methodologically focused overview of current methods for performing transcriptomics and proteomics, including their extensions for single-cell and spatial measurements. We discuss approaches to integrate data across modalities, resolutions and time. Key recent applications within the cardiac field are highlighted. Each -omics modality can provide insight, yet each existing experimental method has technical or conceptual limitations. Integrating data across multiple modalities can leverage strengths and mitigate weaknesses, ultimately enhancing our understanding of cardiac pathophysiology.

Navigating the landscape of plant proteomics

In plants, proteins are fundamental to virtually all biological processes, such as photosynthesis, signal transduction, metabolic regulation, and stress responses. Studying protein distribution, function, modifications, and interactions at the cellular and tissue levels is critical for unraveling the complexities of these biological pathways. Protein abundance and localization are highly dynamic and vary widely across the proteome, presenting a challenge for global protein quantification and analysis. Mass spectrometry-based proteomics approaches have proven to be powerful tools for addressing this complex issue. In this review, we summarize recent advancements in proteomics research and their applications in plant biology, with an emphasis on the current state and challenges of studying post-translational modifications, single-cell proteomics, and protein-protein interactions. Additionally, we discuss future prospects for plant proteomics, highlighting potential opportunities that proteomics technologies offer in advancing plant biology research.

Toward spatial glycomics and glycoproteomics: Innovations and applications

In this mini review, we provide an overview of the challenging field of spatial glycomics/glycoproteomics. Owing to their complexity, sophisticated analytical methods and innovative technologies are needed to advance this field. An agile development approach enables unraveling aberrant glycosylations, glycobiomarkers, and glycotargets for spatial imaging, diagnosis, and therapeutic purposes. We discuss glycopathology and tissue glycomic profiling using highly sensitive lectin-based analyses and introduce deep visual proteomics for glycomic/glycoproteomic sample preparation. Additionally, we highlight the importance of leveraging laser microdissection and artificial intelligence-driven visual software for cell-type assignment and automation techniques, which are crucial for advancing glycomics/glycoproteomics.

Robust collection and processing for label-free single voxel proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated wet collection of single microscale tissue voxels and Surfactant-assisted One-Pot voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of single voxels dissected by LCM to the tube cap and SOP voxel processing in the same collection cap. This method enables reproducible, label-free quantification of approximately 900 and 4600 proteins for single voxels at 20 µm × 20 µm × 10 µm (~1 cell region) and 200 µm × 200 µm × 10 µm (~100 cell region) from fresh frozen human spleen tissue, respectively. It can reveal spatially resolved protein signatures and region-specific signaling pathways. Furthermore, wcSOP-MS is demonstrated to be broadly applicable for OCT-embedded and FFPE human archived tissues as well as for small-scale 2D proteome mapping of tissues at high spatial resolutions. wcSOP-MS may pave the way for routine robust single voxel proteomics and spatial proteomics.

Dissection of Gene Expression at the Single-Cell Level: scRNA-seq

Sequencing approaches that allowed for a better resolution of the transcriptome have been a major goal in the transcriptomics field since the development of RNA-seq techniques. While RNA-seq provides gene expression data from one entire sample in bulk, single-cell analysis allows for a better characterization of gene expression associated to specific cell types. Single-cell RNA-seq (scRNA-seq) is a reliable technique to unravel transcriptomic features of the tissues of interest dissociated at a single-cell level. The main feature of the single-cell technique is its ability to generate barcoded individual cells that allow for tracking the origin of thousands to millions of transcripts and reveal new cell types associated to diseases and different cell types and states. In this chapter, we discuss how scRNA-seq has become the gold standard to deepen the understanding of the gene expression with single-cell resolution.

Methods for Selective Gene Expression Profiling in Single Tertiary Lymphoid Structure Using Laser Capture Microdissection

Tertiary lymphoid structures (TLS) are de novo lymphoid formations that are induced within tissues during inflammatory episodes. TLS have been reported at various anatomic sites and in many different contexts like cancer, infections, autoimmunity, graft rejection, and idiopathic diseases. These inducible, ectopic, and transient lymphoid structures exhibit the prototypical architecture found within secondary lymphoid organs (SLO) and have been increasingly recognized as a major driver of local adaptive immune reaction. As TLS emerge within tissues, the isolation in situ and the molecular characterization of these structures are challenging to perform. Laser capture microdissection (LCM) is a powerful tool to isolate selective structural components and cells from frozen or paraffin-embedded tissues. We and other groups previously applied LCM to decipher the molecular network within TLS and uncover their intrinsic connection with the local microenvironment. In this chapter, we describe a detailed LCM method for selecting and isolating TLS in situ to perform comprehensive downstream molecular analyses.

Spatial Proteomics towards cellular Resolution

INTRODUCTION

Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level.

AREAS COVERED

This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution.

EXPERT OPINION

The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. Achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

Exploring new frontiers in type 1 diabetes through advanced mass-spectrometry-based molecular measurements

Type 1 diabetes (T1D) is a devastating autoimmune disease for which advanced mass spectrometry (MS) methods are increasingly used to identify new biomarkers and better understand underlying mechanisms. For example, integration of MS analysis and machine learning has identified multimolecular biomarker panels. In mechanistic studies, MS has contributed to the discovery of neoepitopes, and pathways involved in disease development and identifying therapeutic targets. However, challenges remain in understanding the role of tissue microenvironments, spatial heterogeneity, and environmental factors in disease pathogenesis. Recent advancements in MS, such as ultra-fast ion-mobility separations, and single-cell and spatial omics, can play a central role in addressing these challenges. Here, we review recent advancements in MS-based molecular measurements and their role in understanding T1D.

Spatiotemporal metabolomic approaches to the cancer-immunity panorama: a methodological perspective

Metabolic reprogramming drives the development of an immunosuppressive tumor microenvironment (TME) through various pathways, contributing to cancer progression and reducing the effectiveness of anticancer immunotherapy. However, our understanding of the metabolic landscape within the tumor-immune context has been limited by conventional metabolic measurements, which have not provided comprehensive insights into the spatiotemporal heterogeneity of metabolism within TME. The emergence of single-cell, spatial, and in vivo metabolomic technologies has now enabled detailed and unbiased analysis, revealing unprecedented spatiotemporal heterogeneity that is particularly valuable in the field of cancer immunology. This review summarizes the methodologies of metabolomics and metabolic regulomics that can be applied to the study of cancer-immunity across single-cell, spatial, and in vivo dimensions, and systematically assesses their benefits and limitations.

A modified dual preparatory method for improved isolation of nucleic acids from laser microdissected fresh-frozen human cancer tissue specimens

A central theme in cancer research is to increase our understanding of the cancer tissue microenvironment, which is comprised of a complex and spatially heterogeneous ecosystem of malignant and non-malignant cells, both of which actively contribute to an intervening extracellular matrix. Laser microdissection (LMD) enables histology selective harvest of cellular subpopulations from the tissue microenvironment for their independent molecular investigation, such as by high-throughput DNA and RNA sequencing. Although enabling, LMD often requires a labor-intensive investment to harvest enough cells to achieve the necessary DNA and/or RNA input requirements for conventional next-generation sequencing workflows. To increase efficiencies, we sought to use a commonplace dual preparatory (DP) procedure to isolate DNA and RNA from the same LMD harvested tissue samples. While the yield of DNA from the DP protocol was satisfactory, the RNA yield from the LMD harvested tissue samples was significantly poorer compared to a dedicated RNA preparation procedure. We determined that this low yield of RNA was due to incomplete partitioning of RNA in this widely used DP protocol. Here, we describe a modified DP protocol that more equally partitions nucleic acids and results in significantly improved RNA yields from LMD-harvested cells.

Scoping Review: Methods and Applications of Spatial Transcriptomics in Tumor Research

Spatial transcriptomics (ST) examines gene expression within its spatial context on tissue, linking morphology and function. Advances in ST resolution and throughput have led to an increase in scientific interest, notably in cancer research. This scoping study reviews the challenges and practical applications of ST, summarizing current methods, trends, and data analysis techniques for ST in neoplasm research. We analyzed 41 articles published by the end of 2023 alongside public data repositories. The findings indicate cancer biology is an important focus of ST research, with a rising number of studies each year. Visium (10x Genomics, Pleasanton, CA, USA) is the leading ST platform, and SCTransform from Seurat R library is the preferred method for data normalization and integration. Many studies incorporate additional data types like single-cell sequencing and immunohistochemistry. Common ST applications include discovering the composition and function of tumor tissues in the context of their heterogeneity, characterizing the tumor microenvironment, or identifying interactions between cells, including spatial patterns of expression and co-occurrence. However, nearly half of the studies lacked comprehensive data processing protocols, hindering their reproducibility. By recommending greater transparency in sharing analysis methods and adapting single-cell analysis techniques with caution, this review aims to improve the reproducibility and reliability of future studies in cancer research.

Single-cell RNA sequencing in tuberculosis: Application and future perspectives

Tuberculosis (TB) has one of the highest mortality rates among infectious diseases worldwide. The immune response in the host after infection is proposed to contribute significantly to the progression of TB, but the specific mechanisms involved remain to be elucidated. Single-cell RNA sequencing (scRNA-seq) provides unbiased transcriptome sequencing of large quantities of individual cells, thereby defining biological comprehension of cellular heterogeneity and dynamic transcriptome state of cell populations in the field of immunology and is therefore increasingly applied to lung disease research. Here, we first briefly introduce the concept of scRNA-seq, followed by a summarization on the application of scRNA-seq to TB. Furthermore, we underscore the potential of scRNA-seq for clinical biomarker exploration, host-directed therapy, and precision therapy research in TB and discuss the bottlenecks that need to be overcome for the broad application of scRNA-seq to TB-related research.

Dielectrophoretic capture and electrochemical enzyme-linked immunosorbent assay of single melanoma cells at an array of interlocked spiral bipolar electrodes

Analysis of single cancer cells is critical to obtain accurate patient diagnosis and prognosis. In this work, we report the selective dielectrophoretic capture and electrochemical analysis of single melanoma cells at an array of interlocked spiral bipolar electrodes (iBPEs). Following dielectrophoretic capture, individual melanoma cells are hydrodynamically transferred into picoliter-scale chambers for subsequent analysis. The interlocked spiral end of the iBPE (the sensing pole) is utilized to read out an electrochemical enzyme-linked immunosorbent assay (eELISA), which quantifies the expression of a cell surface antigen, melanoma cell adhesion marker (MCAM). The opposite pole of each BPE is located in a fluidically isolated compartment containing reagents for electrogenerated chemiluminescence (ECL), such that luminescence reports iBPE current. In a preliminary device design, the ECL intensity was insufficient to detect MCAM expression on single cells. To achieve single-cell analysis, we decreased the gap size between the interlocked spirals tenfold (5.0 μm to 0.5 μm), thereby creating a more sensitive biosensor by enhanced redox cycling of the product of eELISA. This work is significant because it allows for the selective isolation and sensitive analysis of individual melanoma cells in a device amenable to point-of-care (POC) application by combining dielectrophoresis (DEP) with interdigitated bipolar electrodes (IDBPEs).

Genetic variation across and within individuals

Germline variation and somatic mutation are intricately connected and together shape human traits and disease risks. Germline variants are present from conception, but they vary between individuals and accumulate over generations. By contrast, somatic mutations accumulate throughout life in a mosaic manner within an individual due to intrinsic and extrinsic sources of mutations and selection pressures acting on cells. Recent advancements, such as improved detection methods and increased resources for association studies, have drastically expanded our ability to investigate germline and somatic genetic variation and compare underlying mutational processes. A better understanding of the similarities and differences in the types, rates and patterns of germline and somatic variants, as well as their interplay, will help elucidate the mechanisms underlying their distinct yet interlinked roles in human health and biology.

Deceptive learning in histopathology

AIMS

Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the extent to which the visual strategies learned by deep learning models in histopathological analysis are trustworthy or not has yet to be systematically analysed. Here, we systematically evaluate deep neural networks (DNNs) trained for histopathological analysis in order to understand if their learned strategies are trustworthy or deceptive.

METHODS AND RESULTS

We trained a variety of DNNs on a novel data set of 221 whole-slide images (WSIs) from lung adenocarcinoma patients, and evaluated their effectiveness at (1) molecular profiling of KRAS versus EGFR mutations, (2) determining the primary tissue of a tumour and (3) tumour detection. While DNNs achieved above-chance performance on molecular profiling, they did so by exploiting correlations between histological subtypes and mutations, and failed to generalise to a challenging test set obtained through laser capture microdissection (LCM). In contrast, DNNs learned robust and trustworthy strategies for determining the primary tissue of a tumour as well as detecting and localising tumours in tissue.

CONCLUSIONS

Our work demonstrates that DNNs hold immense promise for aiding pathologists in analysing tissue. However, they are also capable of achieving seemingly strong performance by learning deceptive strategies that leverage spurious correlations, and are ultimately unsuitable for research or clinical work. The framework we propose for model evaluation and interpretation is an important step towards developing reliable automated systems for histopathological analysis.

Laser axial scanning microdissection for high-efficiency dissection from uneven biological samples

Fast and efficient separation of target samples is crucial for the application of laser-assisted microdissection in the molecular biology research field. Herein, we developed a laser axial scanning microdissection (LASM) system with an 8.6 times extended depth of focus by using an electrically tunable lens. We showed that the ablation quality of silicon wafers at different depths became homogenous after using our system. More importantly, for those uneven biological tissue sections within a height difference of no more than 19.2 µm, we have demonstrated that the targets with a size of microns at arbitrary positions can be dissected efficiently without additional focusing and dissection operations. Besides, dissection experiments on various biological samples with different embedding methods, which were widely adopted in biological experiments, also have shown the feasibility of our system.

Humans vs. Fungi: An Overview of Fungal Pathogens against Humans

Human fungal diseases are infections caused by any fungus that invades human tissues, causing superficial, subcutaneous, or systemic diseases. Fungal infections that enter various human tissues and organs pose a significant threat to millions of individuals with weakened immune systems globally. Over recent decades, the reported cases of invasive fungal infections have increased substantially and research progress in this field has also been rapidly boosted. This review provides a comprehensive list of human fungal pathogens extracted from over 850 recent case reports, and a summary of the relevant disease conditions and their origins. Details of 281 human fungal pathogens belonging to 12 classes and 104 genera in the divisions ascomycota, basidiomycota, entomophthoromycota, and mucoromycota are listed. Among these, Aspergillus stands out as the genus with the greatest potential of infecting humans, comprising 16 species known to infect humans. Additionally, three other genera, Curvularia, Exophiala, and Trichophyton, are recognized as significant genera, each comprising 10 or more known human pathogenic species. A phylogenetic analysis based on partial sequences of the 28S nrRNA gene (LSU) of human fungal pathogens was performed to show their phylogenetic relationships and clarify their taxonomies. In addition, this review summarizes the recent advancements in fungal disease diagnosis and therapeutics.

Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection

BACKGROUND

Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors.

METHODS

We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers.

RESULTS

We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors.

CONCLUSIONS

This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.

Hematoxylin and Eosin Staining Helps Reduce Maternal Contamination in Short Tandem Repeat Genotyping for Hydatidiform Mole Diagnosis

Short tandem repeat (STR) genotyping provides parental origin information about aneuploidy pregnancy loss and has become the current gold standard for hydatidiform mole diagnosis. STR genotyping diagnostic support most commonly relies on formalin-fixed paraffin-embedded samples, but maternal contamination is one of the most common issues based on traditional unstained sections. To evaluate the influence of hematoxylin and eosin (H&E) staining on DNA quality and STR genotyping, DNA was isolated from unstained, deparaffinized hydrated, and H&E-stained tissue sections (i.e. 3 groups) from each of 6 formalin-fixed paraffin-embedded placentas. The macrodissected view field, DNA quality, and polymerase chain reaction amplification efficiency were compared among groups. STR genotyping analysis was performed in both the test cohort (n = 6) and the validation cohort (n = 149). H&E staining not only did not interfere with molecular DNA testing of formalin-fixed paraffin-embedded tissue but also had a clearer macrodissected field of vision. In the test cohort, H&E-stained sections were the only group that did not exhibit maternal miscellaneous peaks in STR genotyping results. In the validation cohort, 138 (92.62%) cases yielded satisfactory amplification results without maternal contamination. Thus, H&E staining helped to reduce maternal contamination in STR genotyping for hydatidiform mole diagnosis, suggesting that H&E-stained sections can be incorporated into the hydatidiform mole molecular diagnostic workflow.

LncRNA CARMN facilitates odontogenic differentiation of dental pulp cells by impairing EZH2

OBJECTIVE

This study aimed to reveal the potential role of CARMN in odontogenic differentiation of dental pulp cells (DPCs).

METHODS

Laser capture microdissection was used to detect Carmn in DPCs and odontoblasts in P0 mice. After manipulating CARMN expression in odontogenic differentiation induced hDPCs, the state of odontogenic differentiation was evaluated by ALP staining, ARS, and related marker expression in qRT-PCR and western blotting. The subcutaneous transplantation of HA/β-TCP loaded with hDPCs was performed to verify CARMN's role in promoting odontogenic differentiation in vivo. RNAplex and RIP were employed to reveal potential mechanism of CARMN in hDPCs.

RESULTS

CARMN expressed more abundantly in odontoblasts than DPCs in P0 mice. CARMN expression boosted during in vitro odontogenic differentiation of hDPCs. CARMN overexpression enhanced odontogenic differentiation of hDPCs in vitro, while inhibition impaired the process. CARMN overexpression in HA/β-TCP composites promoted more mineralized nodule formation in vivo. CARMN knockdown led to soared EZH2, while CARMN overexpression brought about EZH2 inhibition. CARMN functioned via direct interaction with EZH2.

CONCLUSIONS

The results uncovered CARMN as a modulator during the odontogenic differentiation of DPCs. CARMN promoted odontogenic differentiation of DPCs by impairing EZH2.

Precision isolation and cultivation of single cells by vortex and flat-top laser ejection

Single-cell isolation stands as a critical step in single-cell studies, and single-cell ejection technology based on laser induced forward transfer technology (LIFT) is considered one of the most promising methods in this regard for its ability of visible isolating single cell from complex samples. In this study, we improve the LIFT technology and introduce optical vortex laser-induced forward transfer (OV-LIFT) and flat-top laser-induced forward transfer (FT-LIFT) by utilizing spatial light modulator (SLM), aiming to enhance the precision of single-cell sorting and the cell's viability after ejection. Experimental results demonstrate that applying vortex and flat-top beams during the sorting and collection process enables precise retrieval of single cells within diameter ranges of 50 μm and 100 μm, respectively. The recovery rates of Saccharomyces cerevisiae and Escherichia coli DH5α single cell ejected by vortex beam are 89 and 78%, by flat-top beam are 85 and 57%. When employing Gaussian beam sorting, the receiving range extends to 400 μm, with cultivation success rates of S. cerevisiae and E. coli DH5α single cell are 48 and 19%, respectively. This marks the first application of different mode beams in the ejection and cultivation of single cells, providing a novel and effective approach for the precise isolation and improving the viability of single cells.

Multiomic-Based Molecular Landscape of FaDu Xenograft Tumors in Mice after a Combinatorial Treatment with Radiation and an HSP90 Inhibitor Identifies Adaptation-Induced Targets of Resistance and Therapeutic Intervention

Treatments involving radiation and chemotherapy alone or in combination have improved patient survival and quality of life. However, cancers frequently evade these therapies due to adaptation and tumor evolution. Given the complexity of predicting response based solely on the initial genetic profile of a patient, a predetermined treatment course may miss critical adaptation that can cause resistance or induce new targets for drug and immunotherapy. To address the timescale for these evasive mechanisms, using a mouse xenograft tumor model, we investigated the rapidity of gene expression (mRNA), molecular pathway, and phosphoproteome changes after radiation, an HSP90 inhibitor, or combination. Animals received radiation, drug, or combination treatment for 1 or 2 weeks and were then euthanized along with a time-matched untreated group for comparison. Changes in gene expression occur as early as 1 week after treatment initiation. Apoptosis and cell death pathways were activated in irradiated tumor samples. For the HSP90 inhibitor and combination treatment at weeks 1 and 2 compared with Control Day 1, gene-expression changes induced inhibition of pathways including invasion of cells, vasculogenesis, and viral infection among others. The combination group included both drug-alone and radiation-alone changes. Our data demonstrate the rapidity of gene expression and functional pathway changes in the evolving tumor as it responds to treatment. Discovering these phenotypic adaptations may help elucidate the challenges in using sustained treatment regimens and could also define evolving targets for therapeutic efficacy.

Prostate cancer research: tools, cell types, and molecular targets

Multiple cancer cell types are found in prostate tumors. They are either luminal-like adenocarcinoma or less luminal-like and more stem-like non-adenocarcinoma and small cell carcinoma. These types are lineage related through differentiation. Loss of cancer differentiation from luminal-like to stem-like is mediated by the activation of stem cell transcription factors (scTF) such as LIN28A, NANOG, POU5F1 and SOX2. scTF expression leads to down-regulation of β2-microglobulin (B2M). Thus, cancer cells can change from the scT F ˜ B 2 M hi phenotype of differentiated to that of scT F ˙ B 2 M lo of dedifferentiated in the disease course. In development, epithelial cell differentiation is induced by stromal signaling and cell contact. One of the stromal factors specific to prostate encodes proenkephalin (PENK). PENK can down-regulate scTF and up-regulate B2M in stem-like small cell carcinoma LuCaP 145.1 cells indicative of exit from the stem state and differentiation. In fact, prostate cancer cells can be made to undergo dedifferentiation or reprogramming by scTF transfection and then to differentiate by PENK transfection. Therapies need to be designed for treating the different cancer cell types. Extracellular anterior gradient 2 (eAGR2) is an adenocarcinoma antigen associated with cancer differentiation that can be targeted by antibodies to lyse tumor cells with immune system components. eAGR2 is specific to cancer as normal cells express only the intracellular form (iAGR2). For AGR2-negative stem-like cancer cells, factors like PENK that can target scTF could be effective in differentiation therapy.

Microfluidic platform for omics analysis on single cells with diverse morphology and size: A review

BACKGROUND

Microfluidic techniques have emerged as powerful tools in single-cell research, facilitating the exploration of omics information from individual cells. Cell morphology is crucial for gene expression and physiological processes. However, there is currently a lack of integrated analysis of morphology and single-cell omics information. A critical challenge remains: what platform technologies are the best option to decode omics data of cells that are complex in morphology and size?

RESULTS

This review highlights achievements in microfluidic-based single-cell omics and isolation of cells based on morphology, along with other cell sorting methods based on physical characteristics. Various microfluidic platforms for single-cell isolation are systematically presented, showcasing their diversity and adaptability. The discussion focuses on microfluidic devices tailored to the distinct single-cell isolation requirements in plants and animals, emphasizing the significance of considering cell morphology and cell size in optimizing single-cell omics strategies. Simultaneously, it explores the application of microfluidic single-cell sorting technologies to single-cell sequencing, aiming to effectively integrate information about cell shape and size.

SIGNIFICANCE AND NOVELTY

The novelty lies in presenting a comprehensive overview of recent accomplishments in microfluidic-based single-cell omics, emphasizing the integration of different microfluidic platforms and their implications for cell morphology-based isolation. By underscoring the pivotal role of the specialized morphology of different cells in single-cell research, this review provides robust support for delving deeper into the exploration of single-cell omics data.

Spatial MS multiomics on clinical prostate cancer tissues

Mass spectrometry (MS) and MS imaging (MSI) are used extensively for both the spatial and bulk characterization of samples in lipidomics and proteomics workflows. These datasets are typically generated independently due to different requirements for sample preparation. However, modern omics technologies now provide higher sample throughput and deeper molecular coverage, which, in combination with more sophisticated bioinformatic and statistical pipelines, make generating multiomics data from a single sample a reality. In this workflow, we use spatial lipidomics data generated by matrix-assisted laser desorption/ionization MSI (MALDI-MSI) on prostate cancer (PCa) radical prostatectomy cores to guide the definition of tumor and benign tissue regions for laser capture microdissection (LCM) and bottom-up proteomics all on the same sample and using the same mass spectrometer. Accurate region of interest (ROI) mapping was facilitated by the SCiLS region mapper software and dissected regions were analyzed using a dia-PASEF workflow. A total of 5525 unique protein groups were identified from all dissected regions. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), a lipid remodelling enzyme, was significantly enriched in the dissected regions of cancerous epithelium (CE) compared to benign epithelium (BE). The increased abundance of this protein was reflected in the lipidomics data with an increased ion intensity ratio for pairs of phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) in CE compared to BE.

Transcriptome profiling of microdissected cortex and medulla unravels functional regionalization in the European sea bass Dicentrarchus labrax thymus

The thymus is a sophisticated primary lymphoid organ in jawed vertebrates, but knowledge on teleost thymus remains scarce. In this study, for the first time in the European sea bass, laser capture microdissection was leveraged to collect two thymic regions based on histological features, namely the cortex and the medulla. The two regions were then processed by RNAseq and in-depth functional transcriptome analyses with the aim of revealing differential gene expression patterns and gene sets enrichments, ultimately unraveling unique microenvironments imperative for the development of functional T cells. The sea bass cortex emerged as a hub of T cell commitment, somatic recombination, chromatin remodeling, cell cycle regulation, and presentation of self antigens from autophagy-, proteasome- or proteases-processed proteins. The cortex therefore accommodated extensive thymocyte proliferation and differentiation up to the checkpoint of positive selection. The medulla instead appeared as the center stage in autoimmune regulation by negative selection and deletion of autoreactive T cells, central tolerance mechanisms and extracellular matrix organization. Region-specific canonical markers of T and non-T lineage cells as well as signals for migration to/from, and trafficking within, the thymus were identified, shedding light on the highly coordinated and exquisitely complex bi-directional interactions among thymocytes and stromal components. Markers ascribable to thymic nurse cells and poorly characterized post-aire mTEC populations were found in the cortex and medulla, respectively. An in-depth data mining also exposed previously un-annotated genomic resources with differential signatures. Overall, our findings contribute to a broader understanding of the relationship between regional organization and function in the European sea bass thymus, and provide essential insights into the molecular mechanisms underlying T-cell mediated adaptive immune responses in teleosts.

Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca2+ imaging and electrophysiology

I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.

Mass Spectrometry-Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

A Microdissection Protocol for Proteogenomic Analysis of Histological Sections to Advance Drug Development

Combining proteogenomics with laser capture microdissection (LCM) in cancer research offers a targeted way to explore the intricate interactions between tumor cells and the different microenvironment components. This is especially important for immuno-oncology (IO) research where improvements in the predictability of IO-based drugs are sorely needed, and depends on a better understanding of the spatial relationships involving the tumor, blood supply, and immune cell interactions, in the context of their associated microenvironments. LCM is used to isolate and obtain distinct histological cell types, which may be routinely performed on complex and heterogeneous solid tumor specimens. Once cells have been captured, nucleic acids and proteins may be extracted for in-depth multimodality molecular profiling assays. Optimizing the minute tissue quantities from LCM captured cells is challenging. Following the isolation of nucleic acids, RNA-seq may be performed for gene expression and DNA sequencing performed for the discovery and analysis of actionable mutations, copy number variation, methylation profiles, etc. However, there remains a need for highly sensitive proteomic methods targeting small-sized samples. A significant part of this protocol is an enhanced liquid chromatography mass spectrometry (LC-MS) analysis of micro-scale and/or nano-scale tissue sections. This is achieved with a silver-stained one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) approach developed for LC-MS analysis of fresh-frozen tissue specimens obtained via LCM. Included is a detailed in-gel digestion method adjusted and specifically designed to maximize the proteome coverage from amount-limited LCM samples to better facilitate in-depth molecular profiling. Described is a proteogenomic approach leveraged from microdissected fresh frozen tissue. The protocols may also be applicable to other types of specimens having limited nucleic acids, protein quantity, and/or sample volume.

Canine urothelial carcinoma: a pilot study of microRNA detection in formalin-fixed, paraffin-embedded tissue samples and in normal urine

We assessed the effects of fixation time in formalin and inclusion of surrounding tissue on microRNA (miRNA) cycle quantification (Cq) values in formalin-fixed, paraffin-embedded (FFPE) urothelial carcinoma (UC) tissue (n = 3), and the effect of conditions on miRNAs in urine from 1 healthy dog. MiRNAs were extracted using commercial kits and quantified using miRNA-specific fluorometry in normal bladder tissue scrolls, UC tissue cores, and bladder muscularis tissue cores from 4 FFPE bladder sections (3 UCs, 1 normal), plus 1 UC stored in formalin for 1, 8, 15, and 22 d before paraffin-embedding. Urine was collected from a healthy dog on 4 occasions; 1-mL aliquots were stored at 20, 4, -20, and -80°C for 4, 8, 24, and 48 h, and 1 and 2 wk. For both FFPE tissue and urine, we used reverse-transcription quantitative real-time PCR (RT-qPCR) to quantify miR-143, miR-152, miR-181a, miR-214, miR-1842, and RNU6B in each tissue or sample, using miR-39 as an exogenous control gene. The Cq values were compared with ANOVA and t-tests. The time of tissue-fixation in formalin did not alter miRNA Cq values; inclusion of the muscularis layer resulted in a statistically different miRNA Cq profile for miR-152, miR-181a, and RNU6B in bladder tissue. MiRNAs in acellular urine were stable for up to 2 wk regardless of the storage temperature. Our findings support using stored FFPE and urine samples for miRNA detection; we recommend measuring miRNA only in the tissue of interest in FFPE sections.

MicroRNA-126 in dogs with immune complex-mediated glomerulonephritis

BACKGROUND

Most proteinuric dogs with naturally occurring chronic kidney disease have amyloidosis (AMYL), glomerulosclerosis (GS), or immune complex-mediated glomerulonephritis (ICGN), each with different treatment and prognosis. A noninvasive and disease-specific biomarker is lacking.

HYPOTHESIS

We hypothesized that the expression pattern of biofluid microRNA (miRNAs and miRs) would correlate with disease progression and categorization.

ANIMALS

Archived serum and urine samples from 18 dogs with glomerular disease and 6 clinically healthy dogs; archived urine samples from 49 dogs with glomerular disease and 13 clinically healthy dogs.

METHODS

Retrospective study. Archived biofluid samples from adult dogs with biopsy-confirmed glomerular disease submitted to the International Veterinary Renal Pathology Service between 2008 and 2016 were selected. Serum and urinary miRNAs were isolated and profiled using RNA sequencing. Urinary miR-126, miR-21, miR-182, and miR-486 were quantified using quantitative reverse transcription PCR.

RESULTS

When comparing more advanced disease with earlier disease, no serum miRNAs were differentially expressed, but urinary miR-21 and miR-182 were 1.63 (95% CI: .86-3.1) and 1.45 (95% CI: .82-2.6) times higher in azotemic dogs, respectively (adjusted P < .05) and weakly correlated with tubulointerstitial fibrosis (miR-21: r = .32, P = .03; miR-182: r = .28, P = .05). Expression of urinary miR-126 was 10.5 (95% CI: 4.1-26.7), 28.9 (95% CI: 10.5-79.8), and 126.2 (95% CI: 44.7-356.3) times higher in dogs with ICGN compared with dogs with GS, AMYL, and healthy controls, respectively (P < .001).

CONCLUSIONS AND CLINICAL IMPORTANCE

The miR-126 could help identify dogs that might benefit from immunosuppressive therapy in the absence of a biopsy. MiR-21 and miR-182 are potential markers of disease severity and fibrosis.

Mapping the human brain proteome: opportunities, challenges, and clinical potential

INTRODUCTION

Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases.

AREAS COVERED

Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification.

EXPERT OPINION

Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.

Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial

Molecular subtyping of breast cancer is based mostly on HR/HER2 and gene expression-based immune, DNA repair deficiency, and luminal signatures. We extend this description via functional protein pathway activation mapping using pre-treatment, quantitative expression data from 139 proteins/phosphoproteins from 736 patients across 8 treatment arms of the I-SPY 2 Trial (ClinicalTrials.gov: NCT01042379). We identify predictive fit-for-purpose, mechanism-of-action-based signatures and individual predictive protein biomarker candidates by evaluating associations with pathologic complete response. Elevated levels of cyclin D1, estrogen receptor alpha, and androgen receptor S650 associate with non-response and are biomarkers for global resistance. We uncover protein/phosphoprotein-based signatures that can be utilized both for molecularly rationalized therapeutic selection and for response prediction. We introduce a dichotomous HER2 activation response predictive signature for stratifying triple-negative breast cancer patients to either HER2 or immune checkpoint therapy response as a model for how protein activation signatures provide a different lens to view the molecular landscape of breast cancer and synergize with transcriptomic-defined signatures.

How to explore what is hidden? A review of techniques for vascular tissue expression profile analysis

The evolution of plants to efficiently transport water and assimilates over long distances is a major evolutionary success that facilitated their growth and colonization of land. Vascular tissues, namely xylem and phloem, are characterized by high specialization, cell heterogeneity, and diverse cell components. During differentiation and maturation, these tissues undergo an irreversible sequence of events, leading to complete protoplast degradation in xylem or partial degradation in phloem, enabling their undisturbed conductive function. Due to the unique nature of vascular tissue, and the poorly understood processes involved in xylem and phloem development, studying the molecular basis of tissue differentiation is challenging. In this review, we focus on methods crucial for gene expression research in conductive tissues, emphasizing the importance of initial anatomical analysis and appropriate material selection. We trace the expansion of molecular techniques in vascular gene expression studies and discuss the application of single-cell RNA sequencing, a high-throughput technique that has revolutionized transcriptomic analysis. We explore how single-cell RNA sequencing will enhance our knowledge of gene expression in conductive tissues.

High-quality single-cell transcriptomics from ovarian histological sections during folliculogenesis

High-quality, straightforward single-cell RNA sequencing (RNA-seq) with spatial resolution remains challenging. Here, we developed DRaqL (direct RNA recovery and quenching for laser capture microdissection), an experimental approach for efficient cell lysis of tissue sections, directly applicable to cDNA amplification. Single-cell RNA-seq combined with DRaqL allowed transcriptomic profiling from alcohol-fixed sections with efficiency comparable with that of profiling from freshly dissociated cells, together with effective exon-exon junction profiling. The combination of DRaqL with protease treatment enabled robust and efficient single-cell transcriptome analysis from formalin-fixed tissue sections. Applying this method to mouse ovarian sections, we were able to predict the transcriptome of oocytes by their size and identified an anomaly in the size-transcriptome relationship relevant to growth retardation of oocytes, in addition to detecting oocyte-specific splice isoforms. Furthermore, we identified differentially expressed genes in granulosa cells in association with their proximity to the oocytes, suggesting distinct epigenetic regulations and cell-cycle activities governing the germ-soma relationship. Thus, DRaqL is a versatile, efficient approach for high-quality single-cell RNA-seq from tissue sections, thereby revealing histological heterogeneity in folliculogenic transcriptome.

Clonal expansion of intra-epithelial T cells in breast cancer revealed by spatial transcriptomics

The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of tumor microenvironment. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse and more clonal than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top 10 dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology

Voluntary striated muscles are characterized by a highly complex and dynamic proteome that efficiently adapts to changed physiological demands or alters considerably during pathophysiological dysfunction. The skeletal muscle proteome has been extensively studied in relation to myogenesis, fiber type specification, muscle transitions, the effects of physical exercise, disuse atrophy, neuromuscular disorders, muscle co-morbidities and sarcopenia of old age. Since muscle tissue accounts for approximately 40% of body mass in humans, alterations in the skeletal muscle proteome have considerable influence on whole-body physiology. This review outlines the main bioanalytical avenues taken in the proteomic characterization of skeletal muscle tissues, including top-down proteomics focusing on the characterization of intact proteoforms and their post-translational modifications, bottom-up proteomics, which is a peptide-centric method concerned with the large-scale detection of proteins in complex mixtures, and subproteomics that examines the protein composition of distinct subcellular fractions. Mass spectrometric studies over the last two decades have decisively improved our general cell biological understanding of protein diversity and the heterogeneous composition of individual myofibers in skeletal muscles. This detailed proteomic knowledge can now be integrated with findings from other omics-type methodologies to establish a systems biological view of skeletal muscle function.

Chromatin accessibility profiling of targeted cell populations with laser capture microdissection coupled to ATAC-seq

Spatially resolved omics technologies reveal context-dependent cellular regulatory networks in tissues of interest. Beyond transcriptome analysis, information on epigenetic traits and chromatin accessibility can provide further insights on gene regulation in health and disease. Nevertheless, compared to the enormous advancements in spatial transcriptomics technologies, the field of spatial epigenomics is much younger and still underexplored. In this study, we report laser capture microdissection coupled to ATAC-seq (LCM-ATAC-seq) applied to fresh frozen samples for the spatial characterization of chromatin accessibility. We first demonstrate the efficient use of LCM coupled to in situ tagmentation and evaluate its performance as a function of cell number, microdissected areas, and tissue type. Further, we demonstrate its use for the targeted chromatin accessibility analysis of discrete contiguous or scattered cell populations in tissues via single-nuclei capture based on immunostaining for specific cellular markers.

Single-cell analysis and spatial resolution of the gut microbiome

Over the past decade it has become clear that various aspects of host physiology, metabolism, and immunity are intimately associated with the microbiome and its interactions with the host. Specifically, the gut microbiome composition and function has been shown to play a critical role in the etiology of different intestinal and extra-intestinal diseases. While attempts to identify a common pattern of microbial dysbiosis linked with these diseases have failed, multiple studies show that bacterial communities in the gut are spatially organized and that disrupted spatial organization of the gut microbiome is often a common underlying feature of disease pathogenesis. As a result, focus over the last few years has shifted from analyzing the diversity of gut microbiome by sequencing of the entire microbial community, towards understanding the gut microbiome in spatial context. Defining the composition and spatial heterogeneity of the microbiome is critical to facilitate further understanding of the gut microbiome ecology. Development in single cell genomics approach has advanced our understanding of microbial community structure, however, limitations in approaches exist. Single cell genomics is a very powerful and rapidly growing field, primarily used to identify the genetic composition of microbes. A major challenge is to isolate single cells for genomic analyses. This review summarizes the different approaches to study microbial genomes at single-cell resolution. We will review new techniques for microbial single cell sequencing and summarize how these techniques can be applied broadly to answer many questions related to the microbiome composition and spatial heterogeneity. These methods can be used to fill the gaps in our understanding of microbial communities.

A Standardized and Reproducible Workflow for Membrane Glass Slides in Routine Histology and Spatial Proteomics

Defining the molecular phenotype of single cells in situ is key for understanding tissue architecture in health and disease. Advanced imaging platforms have recently been joined by spatial omics technologies, promising unparalleled insights into the molecular landscape of biological samples. Furthermore, high-precision laser microdissection (LMD) of tissue on membrane glass slides is a powerful method for spatial omics technologies and single-cell type spatial proteomics in particular. However, current histology protocols have not been compatible with glass membrane slides and LMD for automated staining platforms and routine histology procedures. This has prevented the combination of advanced staining procedures with LMD. In this study, we describe a novel method for handling glass membrane slides that enables automated eight-color multiplexed immunofluorescence staining and high-quality imaging followed by precise laser-guided extraction of single cells. The key advance is the glycerol-based modification of heat-induced epitope retrieval protocols, termed "G-HIER." We find that this altered antigen-retrieval solution prevents membrane distortion. Importantly, G-HIER is fully compatible with current antigen retrieval workflows and mass spectrometry-based proteomics and does not affect proteome depth or quality. To demonstrate the versatility of G-HIER for spatial proteomics, we apply the recently introduced deep visual proteomics technology to perform single-cell type analysis of adjacent suprabasal and basal keratinocytes of human skin. G-HIER overcomes previous incompatibility of standard and advanced staining protocols with membrane glass slides and enables robust integration with routine histology procedures, high-throughput multiplexed imaging, and sophisticated downstream spatial omics technologies.