CyTOF: An Emerging Technology for Single-Cell Proteomics in the Mouse

A review of single-cell transcriptomics and epigenomics studies in maternal and child health

Single-cell sequencing technologies enhance our understanding of cellular dynamics throughout pregnancy. We outlined the workflow of single-cell sequencing techniques and reviewed single-cell studies in maternal and child health. We conducted a literature review of single cell studies on maternal and child health using PubMed. We summarized the findings from 16 single-cell atlases of the human and mammalian placenta across gestational stages and 31 single-cell studies on maternal exposures and complications including infection, obesity, diet, gestational diabetes, pre-eclampsia, environmental exposure and preterm birth. Single-cell studies provides insights on novel cell types in placenta and cell type-specific marks associated with maternal exposures and complications.

Integrating the analysis of human biopsies using post-translational modifications proteomics

Proteome diversities and their biological functions are significantly amplified by post-translational modifications (PTMs) of proteins. Shotgun proteomics, which does not typically survey PTMs, provides an incomplete picture of the complexity of human biopsies in health and disease. Recent advances in mass spectrometry-based proteomic techniques that enrich and study PTMs are helping to uncover molecular detail from the cellular level to system-wide functions, including how the microbiome impacts human diseases. Protein heterogeneity and disease complexity are challenging factors that make it difficult to characterize and treat disease. The search for clinical biomarkers to characterize disease mechanisms and complexity related to patient diagnoses and treatment has proven challenging. Knowledge of PTMs is fundamentally lacking. Characterization of complex human samples that clarify the role of PTMs and the microbiome in human diseases will result in new discoveries. This review highlights the key role of proteomic techniques used to characterize unknown biological functions of PTMs derived from complex human biopsies. Through the integration of diverse methods used to profile PTMs, this review explores the genetic regulation of proteoforms, cells of origin expressing specific proteins, and several bioactive PTMs and their subsequent analyses by liquid chromatography and tandem mass spectrometry.

The impacts of active and self-supervised learning on efficient annotation of single-cell expression data

A crucial step in the analysis of single-cell data is annotating cells to cell types and states. While a myriad of approaches has been proposed, manual labeling of cells to create training datasets remains tedious and time-consuming. In the field of machine learning, active and self-supervised learning methods have been proposed to improve the performance of a classifier while reducing both annotation time and label budget. However, the benefits of such strategies for single-cell annotation have yet to be evaluated in realistic settings. Here, we perform a comprehensive benchmarking of active and self-supervised labeling strategies across a range of single-cell technologies and cell type annotation algorithms. We quantify the benefits of active learning and self-supervised strategies in the presence of cell type imbalance and variable similarity. We introduce adaptive reweighting, a heuristic procedure tailored to single-cell data-including a marker-aware version-that shows competitive performance with existing approaches. In addition, we demonstrate that having prior knowledge of cell type markers improves annotation accuracy. Finally, we summarize our findings into a set of recommendations for those implementing cell type annotation procedures or platforms. An R package implementing the heuristic approaches introduced in this work may be found at https://github.com/camlab-bioml/leader .

Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases

Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.

The spatiotemporal heterogeneity of the biophysical microenvironment during hematopoietic stem cell development: from embryo to adult

Hematopoietic stem cells (HSCs) with the ability to self-renew and differentiate are responsible for maintaining the supply of all types of blood cells. The complex and delicate microenvironment surrounding HSCs is called the HSC niche and can provide physical, chemical, and biological stimuli to regulate the survival, maintenance, proliferation, and differentiation of HSCs. Currently, the exploration of the biophysical regulation of HSCs remains in its infancy. There is evidence that HSCs are susceptible to biophysical stimuli, suggesting that the construction of engineered niche biophysical microenvironments is a promising way to regulate the fate of HSCs in vitro and ultimately contribute to clinical applications. In this review, we introduced the spatiotemporal heterogeneous biophysical microenvironment during HSC development, homeostasis, and malignancy. Furthermore, we illustrated how these biophysical cues contribute to HSC behaviors, as well as the possible mechanotransduction mechanisms from the extracellular microenvironment into cells. Comprehending the important functions of these biophysical regulatory factors will provide novel approaches to resolve clinical problems.

Omics approaches for the assessment of biological responses to nanoparticles

Nanotechnology has enabled the development of innovative therapeutics, diagnostics, and drug delivery systems. Nanoparticles (NPs) can influence gene expression, protein synthesis, cell cycle, metabolism, and other subcellular processes. While conventional methods have limitations in characterizing responses to NPs, omics approaches can analyze complete sets of molecular entities that change upon exposure to NPs. This review discusses key omics approaches, namely transcriptomics, proteomics, metabolomics, lipidomics and multi-omics, applied to the assessment of biological responses to NPs. Fundamental concepts and analytical methods used for each approach are presented, as well as good practices for omics experiments. Bioinformatics tools are essential to analyze, interpret and visualize large omics data, and to correlate observations in different molecular layers. The authors envision that conducting interdisciplinary multi-omics analyses in future nanomedicine studies will reveal integrated cell responses to NPs at different omics levels, and the incorporation of omics into the evaluation of targeted delivery, efficacy, and safety will improve the development of nanomedicine therapies.

Role of Innate Immunity in Allergic Contact Dermatitis: An Update

Our understanding of allergic contact dermatitis mechanisms has progressed over the past decade. Innate immune cells that are involved in the pathogenesis of allergic contact dermatitis include Langerhans cells, dermal dendritic cells, macrophages, mast cells, innate lymphoid cells (ILCs), neutrophils, eosinophils, and basophils. ILCs can be subcategorized as group 1 (natural killer cells; ILC1) in association with Th1, group 2 (ILC2) in association with Th2, and group 3 (lymphoid tissue-inducer cells; ILC3) in association with Th17. Pattern recognition receptors (PRRs) including toll-like receptors (TLRs) and nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) in innate immune cells recognize damage-associated molecular patterns (DAMPs) and cascade the signal to produce several cytokines and chemokines including tumor necrosis factor (TNF)-α, interferon (IFN)-α, IFN-γ, interleukin (IL)-1β, IL-4, IL-6, IL-12, IL-13, IL-17, IL-18, and IL-23. Here we discuss the recent findings showing the roles of the innate immune system in allergic contact dermatitis during the sensitization and elicitation phases.

Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing

The ability to map a proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotype. In contrast to nucleic acid sequencing, in vitro protein amplification is impossible and no single cell proteomic workflow has been established as gold standard yet. Advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies, and intelligent data analysis algorithms have resulted in major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, it is commonly accepted that highest possible sensitivity, robustness, and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free SCP is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances in label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or combinations of methods for their specific applications. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.

Spatial Multiplexed Protein Profiling of Cardiac Ischemia-Reperfusion Injury

BACKGROUND

Reperfusion therapy is critical to myocardial salvage in the event of a myocardial infarction but is complicated by ischemia-reperfusion injury (IRI). Limited understanding of the spatial organization of cardiac cells, which governs cellular interaction and function, has hindered the search for targeted interventions minimizing the deleterious effects of IRI.

METHODS

We used imaging mass cytometry to characterize the spatial distribution and dynamics of cell phenotypes and communities in the mouse left ventricle following IRI. Heart sections were collected from 12 cardiac segments (basal, mid-cavity, apical, and apex of the anterior, lateral, and inferior wall) and 8 time points (before ischemia [I-0H], and postreperfusion [R-0H, R-2H, R-6H, R-12H, R-1D, R-3D, R-7D]), and stained with 29 metal-isotope-tagged antibodies. Cell community analysis was performed on reconstructed images, and the most disease-relevant cell type and target protein were selected for intervention of IRI.

RESULTS

We obtained a total of 251 multiplexed images, and identified 197 063 single cells, which were grouped into 23 distinct cell communities based on the structure of cellular neighborhoods. The cellular architecture was heterogeneous throughout the ventricular wall and exhibited swift changes following IRI. Analysis of proteins with posttranslational modifications in single cells unveiled 13 posttranslational modification intensity clusters and highlighted increased H3K9me3 (tri-methylated lysine 9 of histone H3) as a key regulatory response in endothelial cells during the middle stage of IRI. Erasing H3K9 methylation, by silencing its methyltransferase Suv39h1 or overexpressing its demethylase Kdm4d in isolated endothelial cells, attenuated cardiac dysfunction and pathological remodeling following IRI. in vitro, H3K9me3 binding significantly increased at endothelial cell function-related genes upon hypoxia, suppressing tube formation, which was rescued by inhibiting H3K9me3.

CONCLUSIONS

We mapped the spatiotemporal heterogeneity of cellular phenotypes in the adult heart upon IRI, and uncovered H3K9me3 in endothelial cells as a potential therapeutic target for alleviating pathological remodeling of the heart following myocardial IRI.

Meningeal immunity and neurological diseases: new approaches, new insights

The meninges, membranes surrounding the central nervous system (CNS) boundary, harbor a diverse array of immunocompetent immune cells, and therefore, serve as an immunologically active site. Meningeal immunity has emerged as a key factor in modulating proper brain function and social behavior, performing constant immune surveillance of the CNS, and participating in several neurological diseases. However, it remains to be determined how meningeal immunity contributes to CNS physiology and pathophysiology. With the advances in single-cell omics, new approaches, such as single-cell technologies, unveiled the details of cellular and molecular mechanisms underlying meningeal immunity in CNS homeostasis and dysfunction. These new findings contradict some previous dogmas and shed new light on new possible therapeutic targets. In this review, we focus on the complicated multi-components, powerful meningeal immunosurveillance capability, and its crucial involvement in physiological and neuropathological conditions, as recently revealed by single-cell technologies.

Advances in Mass Spectrometry-Based Single Cell Analysis

Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.

Dormant cancer cells: programmed quiescence, senescence, or both?

Metastasis is the overwhelming driver of cancer mortality, accounting for the majority of cancer deaths. Many patients present with metastatic relapse years after eradication of the primary lesion. Disseminated cancer cells can undergo a durable proliferative arrest and lie dormant in secondary tissues before reentering the cell cycle to seed these lethal relapses. This process of cancer cell dormancy remains poorly understood, largely due to difficulties in studying these dormant cells. In the face of these challenges, the application of knowledge from the cellular senescence and quiescence fields may help to guide future thinking on the study of dormant cancer cells. Both senescence and quiescence are common programs of proliferative arrest that are integral to tissue development and homeostasis. Despite phenotypic differences, these two states also share common characteristics, and both likely play a role in cancer dormancy and delayed metastatic relapse. Understanding the cell biology behind these states, their overlaps and unique characteristics is critical to our future understanding of dormant cancer cells, as these cells likely employ some of the same molecular programs to promote survival and dissemination. In this review, we highlight the biology underlying these non-proliferative states, relate this knowledge to what we currently know about dormant cancer cells, and discuss implications for future work toward targeting these elusive metastatic seeds.

Achieving a Deeper Understanding of Drug Metabolism and Responses Using Single-Cell Technologies

Recent advancements in single-cell technologies have enabled detection of RNA, proteins, metabolites, and xenobiotics in individual cells, and the application of these technologies has the potential to transform pharmacological research. Single-cell data has already resulted in the development of human and model species cell atlases, identifying different cell types within a tissue, further facilitating the characterization of tumor heterogeneity, and providing insight into treatment resistance. Research discussed in this review demonstrates that distinct cell populations express drug metabolizing enzymes to different extents, indicating there may be variability in drug metabolism not only between organs, but within tissue types. Additionally, we put forth the concept that single-cell analyses can be used to expose underlying variability in cellular response to drugs, providing a unique examination of drug efficacy, toxicity, and metabolism. We will outline several of these techniques: single-cell RNA-sequencing and mass cytometry to characterize and distinguish different cell types, single-cell proteomics to quantify drug metabolizing enzymes and characterize cellular responses to drug, capillary electrophoresis-ultrasensitive laser-induced fluorescence detection and single-probe single-cell mass spectrometry for detection of drugs, and others. Emerging single-cell technologies such as these can comprehensively characterize heterogeneity in both cell-type-specific drug metabolism and response to treatment, enhancing progress toward personalized and precision medicine. SIGNIFICANCE STATEMENT: Recent technological advances have enabled the analysis of gene expression and protein levels in single cells. These types of analyses are important to investigating mechanisms that cannot be elucidated on a bulk level, primarily due to the variability of cell populations within biological systems. Here, we summarize cell-type-specific drug metabolism and how pharmacologists can utilize single-cell approaches to obtain a comprehensive understanding of drug metabolism and cellular heterogeneity in response to drugs.

Present and future challenges for the investigation of transgenerational epigenetic inheritance

Epigenetic pathways are essential in different biological processes and in phenotype-environment interactions in response to different stressors and they can induce phenotypic plasticity. They encompass several processes that are mitotically and, in some cases, meiotically heritable, so they can be transferred to subsequent generations via the germline. Transgenerational Epigenetic Inheritance (TEI) describes the phenomenon that phenotypic traits, such as changes in fertility, metabolic function, or behavior, induced by environmental factors (e.g., parental care, pathogens, pollutants, climate change), can be transferred to offspring generations via epigenetic mechanisms. Investigations on TEI contribute to deciphering the role of epigenetic mechanisms in adaptation, adversity, and evolution. However, molecular mechanisms underlying the transmission of epigenetic changes between generations, and the downstream chain of events leading to persistent phenotypic changes, remain unclear. Therefore, inter-, (transmission of information between parental and offspring generation via direct exposure) and transgenerational (transmission of information through several generations with disappearance of the triggering factor) consequences of epigenetic modifications remain major issues in the field of modern biology. In this article, we review and describe the major gaps and issues still encountered in the TEI field: the general challenges faced in epigenetic research; deciphering the key epigenetic mechanisms in inheritance processes; identifying the relevant drivers for TEI and implement a collaborative and multi-disciplinary approach to study TEI. Finally, we provide suggestions on how to overcome these challenges and ultimately be able to identify the specific contribution of epigenetics in transgenerational inheritance and use the correct tools for environmental science investigation and biomarkers identification.

A companion to the preclinical common data elements for proteomics, lipidomics, and metabolomics data in rodent epilepsy models. A report of the TASK3-WG4 omics working group of the ILAE/AES joint translational TASK force

The International League Against Epilepsy/American Epilepsy Society (ILAE/AES) Joint Translational Task Force established the TASK3 working groups to create common data elements (CDEs) for various preclinical epilepsy research disciplines. This is the second in a two-part series of omics papers, with the other including genomics, transcriptomics, and epigenomics. The aim of the CDEs was to improve the standardization of experimental designs across a range of epilepsy research-related methods. We have generated CDE tables with key parameters and case report forms (CRFs) containing the essential contents of the study protocols for proteomics, lipidomics, and metabolomics of samples from rodent models and people with epilepsy. We discuss the important elements that need to be considered for the proteomics, lipidomics, and metabolomics methodologies, providing a rationale for the parameters that should be documented.

S-Glutathionylation-Controlled Apoptosis of Lung Epithelial Cells; Potential Implications for Lung Fibrosis

Glutathione (GSH), a major antioxidant in mammalian cells, regulates several vital cellular processes, such as nutrient metabolism, protein synthesis, and immune responses. In addition to its role in antioxidant defense, GSH controls biological processes through its conjugation to reactive protein cysteines in a post-translational modification known as protein S-glutathionylation (PSSG). PSSG has recently been implicated in the pathogenesis of multiple diseases including idiopathic pulmonary fibrosis (IPF). Hallmarks of IPF include repeated injury to the alveolar epithelium with aberrant tissue repair, epithelial cell apoptosis and fibroblast resistance to apoptosis, and the accumulation of extracellular matrix and distortion of normal lung architecture. Several studies have linked oxidative stress and PSSG to the development and progression of IPF. Additionally, it has been suggested that the loss of epithelial cell homeostasis and increased apoptosis, accompanied by the release of various metabolites, creates a vicious cycle that aggravates disease progression. In this short review, we highlight some recent studies that link PSSG to epithelial cell apoptosis and highlight the potential implication of metabolites secreted by apoptotic cells.

Tumor vessel co-option: The past & the future

Tumor vessel co-option (VCO) is a non-angiogenic vascularization mechanism that is a possible cause of resistance to anti-angiogenic therapy (AAT). Multiple tumors are hypothesized to primarily rely on growth factor signaling-induced sprouting angiogenesis, which is often inhibited during AAT. During VCO however, tumors invade healthy tissues by hijacking pre-existing blood vessels of the host organ to secure their blood and nutrient supply. Although VCO has been described in the context of AAT resistance, the molecular mechanisms underlying this process and the profile and characteristics of co-opted vascular cell types (endothelial cells (ECs) and pericytes) remain poorly understood, resulting in the lack of therapeutic strategies to inhibit VCO (and to overcome AAT resistance). In the past few years, novel next-generation technologies (such as single-cell RNA sequencing) have emerged and revolutionized the way of analyzing and understanding cancer biology. While most studies utilizing single-cell RNA sequencing with focus on cancer vascularization have centered around ECs during sprouting angiogenesis, we propose that this and other novel technologies can be used in future investigations to shed light on tumor EC biology during VCO. In this review, we summarize the molecular mechanisms driving VCO known to date and introduce the models used to study this phenomenon to date. We highlight VCO studies that recently emerged using sequencing approaches and propose how these and other novel state-of-the-art methods can be used in the future to further explore ECs and other cell types in the VCO process and to identify potential vulnerabilities in tumors relying on VCO. A better understanding of VCO by using novel approaches could provide new answers to the many open questions, and thus pave the way to develop new strategies to control and target tumor vascularization.

Advances in LC-MS/MS usher in the era of single-cell proteomics

As a new realm of single-cell studies becomes more accessible, innovative developments in one well-established technique are driving the field towards full-coverage proteomic profiles of single cells.

Novel Techniques and Future Perspective for Investigating Critical-Size Bone Defects

A critical-size bone defect is a challenging clinical problem in which a gap between bone ends will not heal and will become a nonunion. The current treatment is to harvest and transplant an autologous bone graft to facilitate bone bridging. To develop less invasive but equally effective treatment options, one needs to first have a comprehensive understanding of the bone healing process. Therefore, it is imperative to leverage the most advanced technologies to elucidate the fundamental concepts of the bone healing process and develop innovative therapeutic strategies to bridge the nonunion gap. In this review, we first discuss the current animal models to study critical-size bone defects. Then, we focus on four novel analytic techniques and discuss their strengths and limitations. These four technologies are mass cytometry (CyTOF) for enhanced cellular analysis, imaging mass cytometry (IMC) for enhanced tissue special imaging, single-cell RNA sequencing (scRNA-seq) for detailed transcriptome analysis, and Luminex assays for comprehensive protein secretome analysis. With this new understanding of the healing of critical-size bone defects, novel methods of diagnosis and treatment will emerge.

Recent progress of proteomic analysis on spermatogenesis

Testis, the only organ responsible for generating sperm, is by far the organ with the largest variety of proteins and tissue-specific proteins in humans. In testis, spermatogenesis is a multi-step complex process well-accepted that protein and mRNA are decoupled in certain stages of spermatogenesis. With the fast development of mass spectrometry-based proteomics, it is possible to systemically study protein abundances and modifications in testis and sperm to help us understand the molecular mechanisms of spermatogenesis. This review provides an overview of the recent progress of proteomics analysis on spermatogenesis, including protein expression and multiple PTMs, such as phosphorylation, glycosylation, ubiquitylation, and acetylation.

Recent progress in cytometric technologies and their applications in ecotoxicology and environmental risk assessment

Environmental toxicology focuses on identifying and predicting impact of potentially toxic anthropogenic chemicals on biosphere at various levels of biological organization. Presently there is a significant drive to gain deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity. Most notable is increased focus on elucidation of cellular-response networks, interactomes, and greater implementation of cell-based biotests using high-throughput procedures, while at the same time decreasing the reliance on standard animal models used in ecotoxicity testing. This is aimed at discovery and interpretation of molecular pathways of ecotoxicity at large scale. In this regard, the applications of cytometry are perhaps one of the most fundamental prospective analytical tools for the next generation and high-throughput ecotoxicology research. The diversity of this modern technology spans flow, laser-scanning, imaging, and more recently, Raman as well as mass cytometry. The cornerstone advantages of cytometry include the possibility of multi-parameter measurements, gating and rapid analysis. Cytometry overcomes, thus, limitations of traditional bulk techniques such as spectrophotometry or gel-based techniques that average the results from pooled cell populations or small model organisms. Novel technologies such as cell imaging in flow, laser scanning cytometry, as well as mass cytometry provide innovative and tremendously powerful capabilities to analyze cells, tissues as well as to perform in situ analysis of small model organisms. In this review, we outline cytometry as a tremendously diverse field that is still vastly underutilized and often largely unknown in environmental sciences. The main motivation of this work is to highlight the potential and wide-reaching applications of cytometry in ecotoxicology, guide environmental scientists in the technological aspects as well as popularize its broader adoption in environmental risk assessment.

Dynamic Interactions of Transcription Factors and Enhancer Reprogramming in Cancer Progression

While improved tumor treatment has significantly reduced the overall mortality rates, invasive progression including recurrence, therapy resistance and metastasis contributes to the majority of deaths caused by cancer. Enhancers are essential distal DNA regulatory elements that control temporal- or spatial-specific gene expression patterns during development and other biological processes. Genome-wide sequencing has revealed frequent alterations of enhancers in cancers and reprogramming of distal enhancers has emerged as one of the important features for tumors. In this review, we will discuss tumor progression-associated enhancer dynamics, its transcription factor (TF) drivers and how enhancer reprogramming modulates gene expression during cancer invasive progression. Additionally, we will explore recent advancements in contemporary technology including single-cell sequencing, spatial transcriptomics and CUT&RUN, which have permitted integrated studies of enhancer reprogramming in vivo. Given the essential roles of enhancer dynamics and its drivers in controlling cancer progression and treatment outcome, understanding these changes will be paramount in mitigating invasive events and discovering novel therapeutic targets.