A Targeted Multi-omic Analysis Approach Measures Protein Expression and Low-Abundance Transcripts on the Single-Cell Level

Single-cell transcriptomics reveals the alteration of immune cell profile in peripheral blood of Henoch-Schonlein purpura

Henoch-Schönlein purpura (HSP) is an autoimmune vasculitis affecting multiple organs, and the understanding of circulating immune cell types and their states associated with disease subtypes of HSP remains incomplete. Here, we performed a comprehensive assessment of peripheral blood mononuclear cells of healthy donors and HSP patients, using both single-cell RNA sequencing and multiparameter flow cytometry. We revealed that HSP patients exhibited broad immune activation, evidenced by increased proportions of Effector memory CD8+ T, CD14+ monocytes, Tfh, Th2, Th17, Plasma, and B cells and decreased proportions of Naïve CD4+ T, Treg, Th1, and NK cells. Notably, we identified that cytotoxic effector T cell subsets were enriched in skin and renal type of HSP, whereas Plasma, B, and Tfh cells were expanded in joint and abdominal type of HSP. In conclusion, our findings highlight the dynamic nature of immune responses throughout the progression of HSP with different clinical manifestations.

Spatially Resolved Single-Cell Transcriptome Analysis of Mycosis Fungoides Reveals Distinct Biomarkers GNLY and FYB1 Compared With Psoriasis and Chronic Spongiotic Dermatitis

Early mycosis fungoides (MF) and inflammatory dermatoses including psoriasis and chronic spongiotic dermatitis are often difficult to differentiate. We explored diagnostic markers differentiating MF from psoriasis and chronic spongiotic dermatitis via spatially resolved single-cell transcriptome analysis. Single-cell transcriptomics of intraepidermal T cells of MF patches, psoriasis, and chronic spongiotic dermatitis were analyzed using CosMx spatial molecular imager utilizing surface markers, including CD3 and CD4. An immunohistochemical study with potential markers was performed to verify clinical utility. Compared with psoriasis and chronic spongiotic dermatitis, 41 upregulated differentially expressed genes (DEGs) in MF were associated with the T-cell receptor (TCR) signaling pathway and apoptosis regulation. Protein-protein interaction network analysis of these DEGs revealed a main cluster associated with TCR signaling. Pathway enrichment analysis showed that apoptosis, Th17 cell differentiation, and TCR signaling pathways were enriched in MF. GNLY and FYB1, DEGs with the highest fold-change values, were selected as potential diagnostic biomarkers for MF. For immunohistochemistry, biopsy specimens from 150 patients diagnosed with patch MF with CD4+ immunophenotype (n = 56), psoriasis (n = 48), and chronic eczema (n = 46) were included. The sensitivity and specificity of granulysin (GNLY) for distinguishing MF and psoriasis/chronic spongiotic dermatitis were 67.9% and 93.6%, respectively. For FYN-binding protein 1 (FYB1), those values were 73.2% and 69.2%, respectively. The area under the receiver operating characteristic curve values of GNLY and FYB1 were 0.86 and 0.79, respectively. In conclusion, granulysin and FYB1 can be promising diagnostic biomarkers for differentiating early-stage MF from psoriasis and chronic spongiotic dermatitis.

Unraveling plant-microbe symbioses using single-cell and spatial transcriptomics

Plant-microbe symbioses require intense interaction and genetic coordination to successfully establish in specific cell types of the host and symbiont. Traditional RNA-seq methodologies lack the cellular resolution to fully capture these complexities, but single-cell and spatial transcriptomics (ST) are now allowing scientists to probe symbiotic interactions at an unprecedented level of detail. Here, we discuss the advantages that novel spatial and single-cell transcriptomic technologies provide in studying plant-microbe endosymbioses and highlight key recent studies. Finally, we consider the remaining limitations of applying these approaches to symbiosis research, which are mainly related to the simultaneous capture of both plant and microbial transcripts within the same cells.

CRISPR/Cas9-mediated suppression of A4GALT rescues endothelial cell dysfunction in a fabry disease vasculopathy model derived from human induced pluripotent stem cells

BACKGROUND AND AIMS

The objective of this study was to investigate the efficacy of CRISPR/Cas9-mediated A4GALT suppression in rescuing endothelial dysfunction in Fabry disease (FD) endothelial cells (FD-ECs) derived from human induced pluripotent stem cells (hiPSCs).

METHODS

We differentiated hiPSCs (WT (wild-type), WTC-11), GLA-mutant hiPSCs (GLA-KO, CMC-Fb-002), and CRISPR/Cas9-mediated A4GALT-KO hiPSCs (GLA/A4GALT-KO, Fb-002-A4GALT-KO) into ECs and compared FD phenotypes and endothelial dysfunction. We also analyzed the effect of A4GALT suppression on reactive oxygen species (ROS) formation and transcriptome profiles through RNA sequencing.

RESULTS

GLA-mutant hiPSC-ECs (GLA-KO and CMC-Fb-002) showed downregulated expression of EC markers and significantly reduced α-GalA expression with increased Gb-3 deposition and intra-lysosomal inclusion bodies. However, CRISPR/Cas9-mediated A4GALT suppression in GLA/A4GALT-KO and Fb-002-A4GALT-KO hiPSC-ECs increased expression levels of EC markers and rescued these FD phenotypes. GLA-mutant hiPSC-ECs failed to form tube-like structure in tube formation assays, showing significantly decreased migration of cells into the scratched wound area. In contrast, A4GALT suppression improved tube formation and cell migration capacity. Western blot analysis revealed that MAPK and AKT phosphorylation levels were downregulated while SOD and catalase were upregulated in GLA-KO hiPSC-ECs. However, suppression of A4GALT restored these protein alterations. RNA sequencing analysis demonstrated significant transcriptome changes in GLA-mutant EC, especially in angiogenesis, cell death, and cellular response to oxidative stress. However, these were effectively restored in GLA/A4GALT-KO hiPSC-ECs.

CONCLUSIONS

CRISPR/Cas9-mediated A4GALT suppression rescued FD phenotype and endothelial dysfunction in GLA-mutant hiPSC-ECs, presenting a potential therapeutic approach for FD-vasculopathy.

Single cell multi-omic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients

Introduction

Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing.

Methods

To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omics approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls.

Results

We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC.

Discussion

Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.

Stress-free single-cell transcriptomic profiling and functional genomics of murine eosinophils

Eosinophils are a class of granulocytes with pleiotropic functions in homeostasis and various human diseases. Nevertheless, they are absent from conventional single-cell RNA sequencing atlases owing to technical difficulties preventing their transcriptomic interrogation. Consequently, eosinophil heterogeneity and the gene regulatory networks underpinning their diverse functions remain poorly understood. We have developed a stress-free protocol for single-cell RNA capture from murine tissue-resident eosinophils, which revealed distinct intestinal subsets and their roles in colitis. Here we describe in detail how to enrich eosinophils from multiple tissues of residence and how to capture high-quality single-cell transcriptomes by preventing transcript degradation. By combining magnetic eosinophil enrichment with microwell-based single-cell RNA capture (BD Rhapsody), our approach minimizes shear stress and processing time. Moreover, we report how to perform genome-wide CRISPR pooled genetic screening in ex vivo-conditioned bone marrow-derived eosinophils to functionally probe pathways required for their differentiation and intestinal maturation. These protocols can be performed by any researcher with basic skills in molecular biology and flow cytometry, and can be adapted to investigate other granulocytes, such as neutrophils and mast cells, thereby offering potential insights into their roles in both homeostasis and disease pathogenesis. Single-cell transcriptomics of eosinophils can be performed in 2-3 d, while functional genomics assays may require up to 1 month.

Beyond single cells: microfluidics empowering multiomics analysis

Single-cell multiomics technologies empower simultaneous measurement of multiple types of molecules within individual cells, providing a more profound comprehension compared with the analysis of discrete molecular layers from different cells. Microfluidic technology, on the other hand, has emerged as a pivotal facilitator for high-throughput single-cell analysis, offering precise control and manipulation of individual cells. The primary focus of this review encompasses an appraisal of cutting-edge microfluidic platforms employed in the realm of single-cell multiomics analysis. Furthermore, it discusses technological advancements in various single-cell omics such as genomics, transcriptomics, epigenomics, and proteomics, with their perspective applications. Finally, it provides future prospects of these integrated single-cell multiomics methodologies, shedding light on the possibilities for future biological research.

Enhancing the efficacy of vaccinia-based oncolytic virotherapy by inhibiting CXCR2-mediated MDSC trafficking

Oncolytic virotherapy is an innovative approach for cancer treatment. However, recruitment of myeloid-derived suppressor cells (MDSCs) into the tumor microenvironment (TME) after oncolysis-mediated local inflammation leads to tumor resistance to the therapy. Using the murine malignant mesothelioma model, we demonstrated that the in situ vaccinia virotherapy recruited primarily polymorphonuclear MDSCs (PMN-MDSCs) into the TME, where they exhibited strong suppression of cytotoxic T lymphocytes in a reactive oxygen species-dependent way. Single-cell RNA sequencing analysis confirmed the suppressive profile of PMN-MDSCs at the transcriptomic level and identified CXCR2 as a therapeutic target expressed on PMN-MDSCs. Abrogating PMN-MDSC trafficking by CXCR2-specific small molecule inhibitor during the vaccinia virotherapy exhibited enhanced antitumor efficacy in 3 syngeneic cancer models, through increasing CD8+/MDSC ratios in the TME, activating cytotoxic T lymphocytes, and skewing suppressive TME into an antitumor environment. Our results warrant clinical development of CXCR2 inhibitor in combination with oncolytic virotherapy.

Dynamics of Whole Transcriptome Analysis (WTA) and Surface markers expression (AbSeq) in Immune Cells of COVID-19 Patients and Recovered captured through Single Cell Genomics

Introduction

Single-cell multi-omics studies, such as multidimensional transcriptomics (whole transcriptomic analysis, WTA), and surface marker analysis (antibody sequencing, AbSeq), have turned out to be valuable techniques that offer inaccessible possibilities for single-cell profiling of mRNA, lncRNA, and proteins.

Methods

We used this technique to understand the dynamics of mRNA and protein-level differences in healthy, COVID-19-infected and recovered individuals using peripheral blood mononuclear cells (PBMCs). Our results demonstrate that compared to mRNA expression, protein abundance is a better indicator of the disease state.

Results

We demonstrate that compared to mRNA expression, protein abundance is a better indicator of the disease state. We observed high levels of cell identity and regulatory markers, CD3E, CD4, CD8A, CD5, CD7, GITR, and KLRB1 in healthy individuals, whereas markers related to cell activation, CD38, CD28, CD69, CD62L, CD14, and CD16 elevated in the SARS-CoV-2 infected patients at both WTA and AbSeq levels. Curiously, in recovered individuals, there was a high expression of cytokine and chemokine receptors (CCR5, CCR7, CCR4, CXCR3, and PTGRD2). We also observed variations in the expression of markers within cell populations under different states.

Discussion

Furthermore, our study emphasizes the significance of employing an oligo-based method (AbSeq) that can help in diagnosis, prognosis, and protection from disease/s by identifying cell surface markers that are unique to different cell types or states. It also allows simultaneous study of a vast array of markers, surpassing the constraints of techniques like FACS to query the vast repertoire of proteins.

Co-staining with Fluorescent Antibodies and Antibody-Derived Tags for Cell Sorting Prior to CITE-Seq

The paired detection of the transcriptome and proteome at single-cell resolution provides exquisite insight to immune mechanisms in health and disease. Here, we describe a detailed protocol wherein we combine cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq), a technique utilizing antibody-derived tags (ADTs) to profile mRNA and proteins simultaneously via sequencing, with fluorescence-activated cell sorting to enrich cell populations. Our protocol provides step-by-step guidance on co-staining cells with both fluorescent antibodies and ADTs simultaneously, instructions on cell sorting and an overview of the single-cell capture workflow using the BD Rhapsody™ system. This method is useful for in-depth single-cell characterization on sorted rare cell populations.

Comparative muscle transcriptome of Mali and Hampshire breeds of pigs: a preliminary study

Muscle development is an important priority of pig breeding programs. There is a considerable variation in muscularity between the breeds, but the regulation mechanisms of genes underlying myogenesis are still unclear. Transcriptome data from two breeds of pigs with divergent muscularity (Mali and Hampshire) were integrated with histology, immunofluorescence and meat yield to identify differences in myogenesis during the early growth phase. The muscle transcriptomics analysis revealed 17,721 common, 1413 and 1115 unique transcripts to Hampshire and Mali, respectively. This study identified 908 differentially expressed genes (p < 0.05; log2FC > ±1) in the muscle samples, of which 550 were upregulated and 358 were downregulated in Hampshire pigs, indicating differences in physiological process related to muscle function and development. Expression of genes related to myoblast fusion (MYMK), skeletal muscle satellite cell proliferation (ANGPT1, CDON) and growth factors (HGF, IGF1, IGF2) were higher in Hampshire than Mali, even though transcript levels of several other myogenesis-related genes (MYF6, MYOG, MSTN) were similar. The number of fibers per fascicle and the expression of myogenic marker proteins (MYOD1, MYOG and PAX7) were more in Hampshire as compared to Mali breed of pig, supporting results of transcriptome studies. The results suggest that differences in muscularity between breeds could be related to the regulation of myoblast fusion and myogenic activities. The present study will help to identify genes that could be explored for their utility in the selection of animals with different muscularities.

Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma

Multi-omics profiling by CITE-seq bridges the RNA-protein gap in single-cell analysis but has been largely applied to liquid biopsies. Applying CITE-seq to clinically relevant solid biopsies to characterize healthy tissue and the tumor microenvironment is an essential next step in single-cell translational studies. In this study, gating of cell populations based on their transcriptome signatures for use in cell type-specific ridge plots allowed identification of positive antibody signals and setting of manual thresholds. Next, we compare five skin dissociation protocols by taking into account dissociation efficiency, captured cell type heterogeneity and recovered surface proteome. To assess the effect of enzymatic digestion on transcriptome and epitope expression in immune cell populations, we analyze peripheral blood mononuclear cells (PBMCs) with and without dissociation. To further assess the RNA-protein gap, RNA-protein we perform codetection and correlation analyses on thresholded protein values. Finally, in a proof-of-concept study, using protein abundance analysis on selected surface markers in a cohort of healthy skin, primary, and metastatic melanoma we identify CD56 surface marker expression on metastatic melanoma cells, which was further confirmed by multiplex immunohistochemistry. This work provides practical guidelines for processing and analysis of clinically relevant solid tissue biopsies for biomarker discovery.

Isoformic PD-1-mediated immunosuppression underlies resistance to PD-1 blockade in hepatocellular carcinoma patients

OBJECTIVE

Immune checkpoint blockade (ICB) has improved cancer treatment, yet why most hepatocellular carcinoma (HCC) patients are resistant to PD-1 ICB remains elusive. Here, we elucidated the role of a programmed cell death protein 1 (PD-1) isoform, Δ42PD-1, in HCC progression and resistance to nivolumab ICB.

DESIGN

We investigated 74 HCC patients in three cohorts, including 41 untreated, 28 treated with nivolumab and 5 treated with pembrolizumab. Peripheral blood mononuclear cells from blood samples and tumour infiltrating lymphocytes from tumour tissues were isolated for immunophenotyping. The functional significance of Δ42PD-1 was explored by single-cell RNA sequencing analysis and validated by functional and mechanistic studies. The immunotherapeutic efficacy of Δ42PD-1 monoclonal antibody was determined in HCC humanised mouse models.

RESULTS

We found distinct T cell subsets, which did not express PD-1 but expressed its isoform Δ42PD-1, accounting for up to 71% of cytotoxic T lymphocytes in untreated HCC patients. Δ42PD-1+ T cells were tumour-infiltrating and correlated positively with HCC severity. Moreover, they were more exhausted than PD-1+ T cells by single T cell and functional analysis. HCC patients treated with anti-PD-1 ICB showed effective PD-1 blockade but increased frequencies of Δ42PD-1+ T cells over time especially in patients with progressive disease. Tumour-infiltrated Δ42PD-1+ T cells likely sustained HCC through toll-like receptors-4-signalling for tumourigenesis. Anti-Δ42PD-1 antibody, but not nivolumab, inhibited tumour growth in three murine HCC models.

CONCLUSION

Our findings not only revealed a mechanism underlying resistance to PD-1 ICB but also identified anti-Δ42PD-1 antibody for HCC immunotherapy.

Proteogenomic and V(D)J Analysis of Human Decidual T Cells Highlights Unique Transcriptional Programming and Clonal Distribution

Immunological tolerance toward the semiallogeneic fetus is one of many maternal adaptations required for a successful pregnancy. T cells are major players of the adaptive immune system and balance tolerance and protection at the maternal-fetal interface; however, their repertoire and subset programming are still poorly understood. Using emerging single-cell RNA sequencing technologies, we simultaneously obtained transcript, limited protein, and receptor repertoire at the single-cell level, from decidual and matched maternal peripheral human T cells. The decidua maintains a tissue-specific distribution of T cell subsets compared with the periphery. We find that decidual T cells maintain a unique transcriptome programming, characterized by restraint of inflammatory pathways by overexpression of negative regulators (DUSP, TNFAIP3, ZFP36) and expression of PD-1, CTLA-4, TIGIT, and LAG3 in some CD8 clusters. Finally, analyzing TCR clonotypes demonstrated decreased diversity in specific decidual T cell populations. Overall, our data demonstrate the power of multiomics analysis in revealing regulation of fetal-maternal immune coexistence.

Single-cell protein expression profiling resolves circulating and resident memory T cell diversity across tissues and infection contexts

Memory CD8⁺ T cells can be broadly divided into circulating (T_CIRCM) and tissue-resident memory T (T_RM) populations. Despite well-defined migratory and transcriptional differences, the phenotypic and functional delineation of T_CIRCM and T_RM cells, particularly across tissues, remains elusive. Here, we utilized an antibody screening platform and machine learning prediction pipeline (InfinityFlow) to profile >200 proteins in T_CIRCM and T_RM cells in solid organs and barrier locations. High-dimensional analyses revealed unappreciated heterogeneity within T_CIRCM and T_RM cell lineages across nine different organs after either local or systemic murine infection models. Additionally, we demonstrated the relative effectiveness of strategies allowing for the selective ablation of T_CIRCM or T_RM populations across organs and identified CD55, KLRG1, CXCR6, and CD38 as stable markers for characterizing memory T cell function during inflammation. Together, these data and analytical framework provide an in-depth resource for memory T cell classification in both steady-state and inflammatory conditions.

Ultra High-plex Spatial Proteogenomic Investigation of Giant Cell Glioblastoma Multiforme Immune Infiltrates Reveals Distinct Protein and RNA Expression Profiles

A deeper understanding of complex biological processes, including tumor development and immune response, requires ultra high-plex, spatial interrogation of multiple "omes". Here we present the development and implementation of a novel spatial proteogenomic (SPG) assay on the GeoMx Digital Spatial Profiler platform with next-generation sequencing readout that enables ultra high-plex digital quantitation of proteins (>100-plex) and RNA (whole transcriptome, >18,000-plex) from a single formalin-fixed paraffin-embedded (FFPE) sample. This study highlighted the high concordance, R > 0.85 and <15% change in sensitivity between the SPG assay and the single-analyte assays on various cell lines and tissues from human and mouse. Furthermore, we demonstrate that the SPG assay was reproducible across multiple users. When used in conjunction with advanced cellular neighborhood segmentation, distinct immune or tumor RNA and protein targets were spatially resolved within individual cell subpopulations in human colorectal cancer and non-small cell lung cancer. We used the SPG assay to interrogate 23 different glioblastoma multiforme (GBM) samples across four pathologies. The study revealed distinct clustering of both RNA and protein based on pathology and anatomic location. The in-depth investigation of giant cell glioblastoma multiforme (gcGBM) revealed distinct protein and RNA expression profiles compared with that of the more common GBM. More importantly, the use of spatial proteogenomics allowed simultaneous interrogation of critical protein posttranslational modifications alongside whole transcriptomic profiles within the same distinct cellular neighborhoods.

Significance

We describe ultra high-plex spatial proteogenomics; profiling whole transcriptome and high-plex proteomics on a single FFPE tissue section with spatial resolution. Investigation of gcGBM versus GBM revealed distinct protein and RNA expression profiles.

Discovery of cellular and genetic signatures of immune tolerance in kidney transplant recipients through single cell RNA sequencing analysis

The objective of this study was to uncover distinct cellular and genetic signatures of transplant operational tolerance (TOT) in kidney transplant recipients (KTRs) through single cell RNA sequencing (scRNA-seq) using peripheral blood mononuclear cells (PBMCs). PBMCs were isolated from 12 KTRs, including those with TOT (TOT, n = 4), stable allograft function on maintenance immunosuppression (STA, n = 4) and biopsy-proven allograft rejection (BPAR, n = 4). ScRNA-seq of PBMCs was analyzed using 20 cell surface marker antibody sequencing to annotate clusters and 399 immune response panel to identify gene expression. Differences in cellular distribution and gene expression were compared among the three groups. Heatmap hierarchical clustering showed that overall cellular distribution pattern was distinct in TOT in comparison with those in the other two groups, with the proportion of B cells being higher in TOT, attributed to immature B cell fraction (TOT vs. STA vs. BPAR: 4.61% vs. 1.27% vs. 2.53%, p = 0.01). Transcript analysis of B cells revealed that genes involved in allo-immune pathway were downregulated in TOT. In T cell subset analysis, the proportion of naïve T cells and regulatory T cells (Tregs) was increased. In transcript analysis, genes associated with inflammation were decreased, while expression levels of CCR6 in Tregs were increased in TOT. Proportions of NKT and NK cells were increased in TOT than in the other two groups. This study showed that TOT has distinct cellular and genetic signatures such as increases of immature B cells, naïve T cells and Tregs and high expression levels of CCR6 in Tregs.

Quantifying stimulus-response specificity to probe the functional state of macrophages

Immune sentinel macrophages initiate responses to pathogens via hundreds of immune response genes. Each immune threat demands a tailored response, suggesting that the capacity for stimulus-specific gene expression is a key functional hallmark of healthy macrophages. To quantify this property, termed "stimulus-response specificity" (SRS), we developed a single-cell experimental workflow and analytical approaches based on information theory and machine learning. We found that the response specificity of macrophages is driven by combinations of specific immune genes that show low cell-to-cell heterogeneity and are targets of separate signaling pathways. The "response specificity profile," a systematic comparison of multiple stimulus-response distributions, was distinctly altered by polarizing cytokines, and it enabled an assessment of the functional state of macrophages. Indeed, the response specificity profile of peritoneal macrophages from old and obese mice showed characteristic differences, suggesting that SRS may be a basis for measuring the functional state of innate immune cells. A record of this paper's transparent peer review process is included in the supplemental information.

Single-cell RNA-Seq analysis of diabetic wound macrophages in STZ-induced mice

The crucial role of macrophages in the healing of chronic diabetic wounds is widely known, but previous in vitro classification and marker genes of macrophages may not be fully applicable to cells in the microenvironment of chronic wounds. The heterogeneity of macrophages was studied and classified at the single-cell level in a chronic wound model. We performed single-cell sequencing of CD45 + immune cells within the wound edge and obtained 17 clusters of cells, including 4 clusters of macrophages. One of these clusters is a previously undescribed population of macrophages possessing osteoclast gene expression, for which analysis of differential genes revealed possible functions. We also analysed the differences in gene expression between groups of macrophages in the control and diabetic wound groups at different sampling times. We described the differentiation profile of mononuclear macrophages, which has provided an important reference for the study of immune-related mechanisms in diabetic chronic wounds.

Single-cell genomics in AML: extending the frontiers of AML research

The era of genomic medicine has allowed acute myeloid leukemia (AML) researchers to improve disease characterization, optimize risk-stratification systems, and develop new treatments. Although there has been significant progress, AML remains a lethal cancer because of its remarkably complex and plastic cellular architecture. This degree of heterogeneity continues to pose a major challenge, because it limits the ability to identify and therefore eradicate the cells responsible for leukemogenesis and treatment failure. In recent years, the field of single-cell genomics has led to unprecedented strides in the ability to characterize cellular heterogeneity, and it holds promise for the study of AML. In this review, we highlight advancements in single-cell technologies, outline important shortcomings in our understanding of AML biology and clinical management, and discuss how single-cell genomics can address these shortcomings as well as provide unique opportunities in basic and translational AML research.

Targeted multi-omic analysis of human skin tissue identifies alterations of conventional and unconventional T cells associated with burn injury

Burn injuries are a leading cause of unintentional injury, associated with a dysfunctional immune response and an increased risk of infections. Despite this, little is known about the role of T cells in human burn injury. In this study, we compared the activation and function of conventional T cells and unconventional T cell subsets in skin tissue from acute burn (within 7 days from initial injury), late phase burn (beyond 7 days from initial injury), and non-burn patients. We compared T cell functionality by a combination of flow cytometry and a multi-omic single-cell approach with targeted transcriptomics and protein expression. We found a significantly lower proportion of CD8+ T cells in burn skin compared to non-burn skin, with CD4+ T cells making up the bulk of the T cell population. Both conventional and unconventional burn tissue T cells show significantly higher IFN-γ and TNF-α levels after stimulation than non-burn skin T cells. In sorted T cells, clustering showed that burn tissue had significantly higher expression of homing receptors CCR7, S1PR1, and SELL compared to non-burn skin. In unconventional T cells, including mucosal-associated invariant T (MAIT) and γδ T cells, we see significantly higher expression of cytotoxic molecules GZMB, PRF1, and GZMK. Multi-omics analysis of conventional T cells suggests a shift from tissue-resident T cells in non-burn tissue to a circulating T cell phenotype in burn tissue. In conclusion, by examining skin tissue from burn patients, our results suggest that T cells in burn tissue have a pro-inflammatory rather than a homeostatic tissue-resident phenotype, and that unconventional T cells have a higher cytotoxic capacity. Our findings have the potential to inform the development of novel treatment strategies for burns.

The transcription factor IRF2 drives interferon-mediated CD8+ T cell exhaustion to restrict anti-tumor immunity

Type I and II interferons (IFNs) stimulate pro-inflammatory programs that are critical for immune activation, but also induce immune-suppressive feedback circuits that impede control of cancer growth. Here, we sought to determine how these opposing programs are differentially induced. We demonstrated that the transcription factor interferon regulatory factor 2 (IRF2) was expressed by many immune cells in the tumor in response to sustained IFN signaling. CD8+ T cell-specific deletion of IRF2 prevented acquisition of the T cell exhaustion program within the tumor and instead enabled sustained effector functions that promoted long-term tumor control and increased responsiveness to immune checkpoint and adoptive cell therapies. The long-term tumor control by IRF2-deficient CD8+ T cells required continuous integration of both IFN-I and IFN-II signals. Thus, IRF2 is a foundational feedback molecule that redirects IFN signals to suppress T cell responses and represents a potential target to enhance cancer control.

Review: Challenges and perspectives in applying single nuclei RNA-seq technology in plant biology

Plant single-cell RNA-seq technology quantifies the abundance of plant transcripts at a single-cell resolution. Deciphering the transcriptomes of each plant cell, their regulation during plant cell development, and their response to environmental stresses will support the functional study of genes, the establishment of precise transcriptional programs, the prediction of more accurate gene regulatory networks, and, in the long term, the design of de novo gene pathways to enhance selected crop traits. In this review, we will discuss the opportunities, challenges, and problems, and share tentative solutions associated with the generation and analysis of plant single-cell transcriptomes. We will discuss the benefit and limitations of using plant protoplasts vs. nuclei to conduct single-cell RNA-seq experiments on various plant species and organs, the functional annotation of plant cell types based on their transcriptomic profile, the characterization of the dynamic regulation of the plant genes during cell development or in response to environmental stress, the need to characterize and integrate additional layers of -omics datasets to capture new molecular modalities at the single-cell level and reveal their causalities, the deposition and access to single-cell datasets, and the accessibility of this technology to plant scientists.

Innate immune imprints in SARS-CoV-2 Omicron variant infection convalescents

SARS-CoV-2 Omicron variant infection generally gives rise to asymptomatic to moderate COVID-19 in vaccinated people. The immune cells can be reprogrammed or "imprinted" by vaccination and infections to generate protective immunity against subsequent challenges. Considering the immune imprint in Omicron infection is unclear, here we delineate the innate immune landscape of human Omicron infection via single-cell RNA sequencing, surface proteome profiling, and plasma cytokine quantification. We found that monocyte responses predominated in immune imprints of Omicron convalescents, with IL-1β-associated and interferon (IFN)-responsive signatures with mild and moderate symptoms, respectively. Low-density neutrophils increased and exhibited IL-1β-associated and IFN-responsive signatures similarly. Mild convalescents had increased blood IL-1β, CCL4, IL-9 levels and PI3⁺ neutrophils, indicating a bias to IL-1β responsiveness, while moderate convalescents had increased blood CXCL10 and IFN-responsive monocytes, suggesting durative IFN responses. Therefore, IL-1β- or IFN-responsiveness of myeloid cells may indicate the disease severity of Omicron infection and mediate post-COVID conditions.

Integrative insights and clinical applications of single-cell sequencing in cancer immunotherapy

Recently, immunotherapy has gained increasing popularity in oncology. Several immunotherapies obtained remarkable clinical effects, but the efficacy varied, and only subsets of cancer patients benefited. Breaking the constraints and improving immunotherapy efficacy is extremely important in precision medicine. Whereas traditional sequencing approaches mask the characteristics of individual cells, single-cell sequencing provides multiple dimensions of cellular characterization at the single-cell level, including genomic, transcriptomic, epigenomic, proteomic, and multi-omics. Hence, the complexity of the tumor microenvironment, the universality of tumor heterogeneity, cell composition and cell-cell interactions, cell lineage tracking, and tumor drug resistance mechanisms are revealed in-depth. However, the clinical transformation of single-cell technology is not to the point of in-depth study, especially in the application of immunotherapy. The newly discovered vital cells and tremendous biomarkers facilitate the development of more efficient individualized therapeutic regimens to guide clinical treatment and predict prognosis. This review provided an overview of the progress in distinct single-cell sequencing methods and emerging strategies. For perspective, the expanding utility of combining single-cell sequencing and other technologies was discussed.

A guide to systems-level immunomics

The immune system is highly complex and distributed throughout an organism, with hundreds to thousands of cell states existing in parallel with diverse molecular pathways interacting in a highly dynamic and coordinated fashion. Although the characterization of individual genes and molecules is of the utmost importance for understanding immune-system function, high-throughput, high-resolution omics technologies combined with sophisticated computational modeling and machine-learning approaches are creating opportunities to complement standard immunological methods with new insights into immune-system dynamics. Like systems immunology itself, immunology researchers must take advantage of these technologies and form their own diverse networks, connecting with researchers from other disciplines. This Review is an introduction and 'how-to guide' for immunologists with no particular experience in the field of omics but with the intention to learn about and apply these systems-level approaches, and for immunologists who want to make the most of interdisciplinary networks.

Combined protein and transcript single-cell RNA sequencing in human peripheral blood mononuclear cells

BACKGROUND

Cryopreserved peripheral blood mononuclear cells (PBMCs) are frequently collected and provide disease- and treatment-relevant data in clinical studies. Here, we developed combined protein (40 antibodies) and transcript single-cell (sc)RNA sequencing (scRNA-seq) in PBMCs.

RESULTS

Among 31 participants in the Women's Interagency HIV Study (WIHS), we sequenced 41,611 cells. Using Boolean gating followed by Seurat UMAPs (tool for visualizing high-dimensional data) and Louvain clustering, we identified 50 subsets among CD4+ T, CD8+ T, B, NK cells, and monocytes. This resolution was superior to flow cytometry, mass cytometry, or scRNA-seq without antibodies. Combined protein and transcript scRNA-seq allowed for the assessment of disease-related changes in transcriptomes and cell type proportions. As a proof-of-concept, we showed such differences between healthy and matched individuals living with HIV with and without cardiovascular disease.

CONCLUSIONS

In conclusion, combined protein and transcript scRNA sequencing is a suitable and powerful method for clinical investigations using PBMCs.

Quantifying the phenotypic information in mRNA abundance

Quantifying the dependency between mRNA abundance and downstream cellular phenotypes is a fundamental open problem in biology. Advances in multimodal single-cell measurement technologies provide an opportunity to apply new computational frameworks to dissect the contribution of individual genes and gene combinations to a given phenotype. Using an information theory approach, we analyzed multimodal data of the expression of 83 genes in the Ca2+ signaling network and the dynamic Ca2+ response in the same cell. We found that the overall expression levels of these 83 genes explain approximately 60% of Ca2+ signal entropy. The average contribution of each single gene was 17%, revealing a large degree of redundancy between genes. Using different heuristics, we estimated the dependency between the size of a gene set and its information content, revealing that on average, a set of 53 genes contains 54% of the information about Ca2+ signaling. Our results provide the first direct quantification of information content about complex cellular phenotype that exists in mRNA abundance measurements.

Frontiers in single cell analysis: multimodal technologies and their clinical perspectives

Single cell multimodal analysis is at the frontier of single cell research: it defines the roles and functions of distinct cell types through simultaneous analysis to provide unprecedented insight into cellular processes. Current single cell approaches are rapidly moving toward multimodal characterizations. It replaces one-dimensional single cell analysis, for example by allowing for simultaneous measurement of transcription and post-transcriptional regulation, epigenetic modifications and/or surface protein expression. By providing deeper insights into single cell processes, multimodal single cell analyses paves the way to new understandings in various cellular processes such as cell fate decisions, physiological heterogeneity or genotype-phenotype linkages. At the forefront of this, microfluidics is key for high-throughput single cell analysis. Here, we present an overview of the recent multimodal microfluidic platforms having a potential in biomedical research, with a specific focus on their potential clinical applications.

CD39 pathway inhibits Th1 cell function in tuberculosis

The role of CD39 pathway in Th1 cell function in tuberculosis (TB) is rarely elucidated. The present study aims to investigate the modulating mechanism of CD39 pathway during Mycobacterium tuberculosis (MTB) infection. CD39 expression was examined on host immune cells among patients with TB. The relationship between CD39 expression and Th1 cell function was analysed. Patients with TB displayed dramatically higher CD39 expression on Th1 cells than healthy controls, and a significantly increased expression of surface markers, including activation, exhaustion and apoptosis markers, were noted in CD39⁺ Th1 cells in comparison with CD39⁻ Th1 cells. Conversely, CD39 expression on Th1 cells was associated with diminished number of polyfunctional cells producing Th1‐type cytokines, and CD39⁺ Th1 cells showed obviously lower proliferation potential. Notably, tetramer analysis demonstrated a predominant CD39 expression on TB‐specific CD4⁺ cells, which was associated with higher apoptosis and lower cytokine‐producing ability. Transcriptome sequencing identified 27 genes that were differentially expressed between CD39⁺ and CD39⁻ Th1 cells, such as IL32, DUSP4 and RGS1. Inhibition of CD39 pathway could enhance the activation, proliferation and cytokine‐producing ability of Th1 cells. Furthermore, there was a significantly negative correlation between CD39 expression on Th1 cells and nutritional status indicators such as lymphocyte count and albumin levels, and we observed a significant decline in CD39 expression on Th1 cells after anti‐TB treatment. CD39 is predominantly expressed on TB‐specific Th1 cells and correlated with their exhausted function, which suggests that CD39 could serve as a prominent target for TB therapy.

Extricating human tumour immune alterations from tissue inflammation

Immunotherapies have achieved remarkable successes in the treatment of cancer, but major challenges remain1,2. An inherent weakness of current treatment approaches is that therapeutically targeted pathways are not restricted to tumours, but are also found in other tissue microenvironments, complicating treatment3,4. Despite great efforts to define inflammatory processes in the tumour microenvironment, the understanding of tumour-unique immune alterations is limited by a knowledge gap regarding the immune cell populations in inflamed human tissues. Here, in an effort to identify such tumour-enriched immune alterations, we used complementary single-cell analysis approaches to interrogate the immune infiltrate in human head and neck squamous cell carcinomas and site-matched non-malignant, inflamed tissues. Our analysis revealed a large overlap in the composition and phenotype of immune cells in tumour and inflamed tissues. Computational analysis identified tumour-enriched immune cell interactions, one of which yields a large population of regulatory T (Treg) cells that is highly enriched in the tumour and uniquely identified among all haematopoietically-derived cells in blood and tissue by co-expression of ICOS and IL-1 receptor type 1 (IL1R1). We provide evidence that these intratumoural IL1R1+ Treg cells had responded to antigen recently and demonstrate that they are clonally expanded with superior suppressive function compared with IL1R1- Treg cells. In addition to identifying extensive immunological congruence between inflamed tissues and tumours as well as tumour-specific changes with direct disease relevance, our work also provides a blueprint for extricating disease-specific changes from general inflammation-associated patterns.

The Intriguing Landscape of Single-Cell Protein Analysis

Profiling protein expression at single-cell resolution is essential for fundamental biological research (such as cell differentiation and tumor microenvironmental examination) and clinical precision medicine where only a limited number of primary cells are permitted. With the recent advances in engineering, chemistry, and biology, single-cell protein analysis methods are developed rapidly, which enable high-throughput and multiplexed protein measurements in thousands of individual cells. In combination with single cell RNA sequencing and mass spectrometry, single-cell multi-omics analysis can simultaneously measure multiple modalities including mRNAs, proteins, and metabolites in single cells, and obtain a more comprehensive exploration of cellular signaling processes, such as DNA modifications, chromatin accessibility, protein abundance, and gene perturbation. Here, the recent progress and applications of single-cell protein analysis technologies in the last decade are summarized. Current limitations, challenges, and possible future directions in this field are also discussed.

Inflammatory blockade prevents injury to the developing pulmonary gas exchange surface in preterm primates

Perinatal inflammatory stress is associated with early life morbidity and lifelong consequences for pulmonary health. Chorioamnionitis, an inflammatory condition affecting the placenta and fluid surrounding the developing fetus, affects 25 to 40% of preterm births. Severe chorioamnionitis with preterm birth is associated with significantly increased risk of pulmonary disease and secondary infections in childhood, suggesting that fetal inflammation may markedly alter the development of the lung. Here, we used intra-amniotic lipopolysaccharide (LPS) challenge to induce experimental chorioamnionitis in a prenatal rhesus macaque (Macaca mulatta) model that mirrors structural and temporal aspects of human lung development. Inflammatory injury directly disrupted the developing gas exchange surface of the primate lung, with extensive damage to alveolar structure, particularly the close association and coordinated differentiation of alveolar type 1 pneumocytes and specialized alveolar capillary endothelium. Single-cell RNA sequencing analysis defined a multicellular alveolar signaling niche driving alveologenesis that was extensively disrupted by perinatal inflammation, leading to a loss of gas exchange surface and alveolar simplification, with notable resemblance to chronic lung disease in newborns. Blockade of the inflammatory cytokines interleukin-1β and tumor necrosis factor-α ameliorated LPS-induced inflammatory lung injury by blunting stromal responses to inflammation and modulating innate immune activation in myeloid cells, restoring structural integrity and key signaling networks in the developing alveolus. These data provide new insight into the pathophysiology of developmental lung injury and suggest that modulating inflammation is a promising therapeutic approach to prevent fetal consequences of chorioamnionitis.

Single-Cell Antibody Sequencing in Atherosclerosis Research

The transcriptomic information obtained by single cell RNA sequencing (scRNA-seq) can be supplemented by information on the cell surface phenotype by using oligonucleotide-tagged monoclonal antibodies (scAb-Seq). This is of particular importance in immune cells, where the correlation between mRNA and cell surface expression is very weak. scAb-Seq is facilitated by the availability of commercial antibodies and antibody mixes. Now panels of up to 200 antibodies are available for human and mouse cells. Proteins are detected by antibodies conjugated to a tripartite DNA sequence that contains a primer for amplification and sequencing, a unique oligonucleotide that acts as an antibody barcode and a poly(dA) sequence, simultaneously detecting extension of antibody-specific DNA sequences and cDNAs in the same poly(dT)-primed reaction. For each cell, surface protein expression is captured and sequenced along with the cell's transcriptome. Here, we list the steps needed to produce antibody sequencing data from tissue or blood cells.

Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach

The wealth of high-throughput data has opened up new opportunities to analyze and describe biological processes at higher resolution, ultimately leading to a significant acceleration of scientific output using high-throughput data from the different omics layers and the generation of databases to store and report raw datasets. The great variability among the techniques and the heterogeneous methodologies used to produce this data have placed meta-analysis methods as one of the approaches of choice to correlate the resultant large-scale datasets from different research groups. Through multi-study meta-analyses, it is possible to generate results with greater statistical power compared to individual analyses. Gene signatures, biomarkers and pathways that provide new insights of a phenotype of interest have been identified by the analysis of large-scale datasets in several fields of science. However, despite all the efforts, a standardized regulation to report large-scale data and to identify the molecular targets and signaling networks is still lacking. Integrative analyses have also been introduced as complementation and augmentation for meta-analysis methodologies to generate novel hypotheses. Currently, there is no universal method established and the different methods available follow different purposes. Herein we describe a new unifying, scalable and straightforward methodology to meta-analyze different omics outputs, but also to integrate the significant outcomes into novel pathways describing biological processes of interest. The significance of using proper molecular identifiers is highlighted as well as the potential to further correlate molecules from different regulatory levels. To show the methodology’s potential, a set of transcriptomic datasets are meta-analyzed as an example.

Towards Tabula Gallus

The Tabula Gallus is a proposed project that aims to create a map of every cell type in the chicken body and chick embryos. Chickens (Gallus gallus) are one of the most recognized model animals that recapitulate the development and physiology of mammals. The Tabula Gallus will generate a compendium of single-cell transcriptome data from Gallus gallus, characterize each cell type, and provide tools for the study of the biology of this species, similar to other ongoing cell atlas projects (Tabula Muris and Tabula Sapiens/Human Cell Atlas for mice and humans, respectively). The Tabula Gallus will potentially become an international collaboration between many researchers. This project will be useful for the basic scientific study of Gallus gallus and other birds (e.g., cell biology, molecular biology, developmental biology, neuroscience, physiology, oncology, virology, behavior, ecology, and evolution). It will eventually be beneficial for a better understanding of human health and diseases.

Antibody-Oligonucleotide Conjugation Using a SPAAC Copper-Free Method Compatible with 10× Genomics' Single-Cell RNA-Seq

Recent advances in multimodal approaches toward single-cell analyses present valuable data points that can complement standard flow cytometry data. In particular, the overlay of cell-surface proteome data with gene expression analysis presents a necessary advancement, particularly in the field of immunology. Here we describe a copper-free click chemistry method for the generation of antibody-oligonucleotide complexes and present the steps for its employment in the context of the 10× genomics droplet-based single-cell RNA-seq workflow, providing a method for coupling proteomic and transcriptomic analyses in an efficient and cost-effect manner.

Combined Measurement of RNA and Protein Expression on a Single-Cell Level

Single-cell RNA sequencing (sc-RNAseq) has become a critical approach for the analysis of immune cell function and heterogeneity. So far, the immune cell isolation, based on surface marker expression predicted by the RNA expression profiles, is often limited by the poor correlation between transcript and protein expression patterns. To overcome these difficulties, novel single-cell multi-omic approaches based on the combined analysis of transcript and surface protein expression have been developed. One of the major benefits of these technologies is the possibility to use a high number of antibodies conjugated with oligonucleotide (AbOs) for the surface marker detection, thus overcoming the limit of using few surface markers as occurs in flow cytometry. Here we describe the BD Rhapsody single-cell analysis system protocol for 3' mRNA whole transcriptome analysis (WTA), combined with AbO- and Sample Tag library preparation.

Acquisition of murine splenic myeloid cells for protein and gene expression profiling by advanced flow cytometry and CITE-seq

Here, we outline detailed protocols to isolate and profile murine splenic dendritic cells (DCs) through advanced flow cytometry of the myeloid compartment and single-cell transcriptomic profiling with integrated cell surface protein expression through CITE-seq. This protocol provides a general transferrable road map for different tissues and species.

For complete details on the use and execution of this protocol, please refer to Lukowski et al. (2021).

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Protocol to obtain integrated single-cell gene and protein expression data

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Optimized flow cytometry panel for confident delineation of six main myeloid lineages

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Gating strategy identifies large cell state heterogeneity within each lineage

Co-staining human PBMCs with fluorescent antibodies and antibody-oligonucleotide conjugates for cell sorting prior to single-cell CITE-Seq

The dual interrogation of the transcriptome and proteome with single-cell resolution provides exquisite insights into immune mechanisms in health and disease. Here, we describe a cutting-edge protocol wherein we combine Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq), a technique utilizing antibody-oligonucleotide conjugates (AOCs), with fluorescence-activated cell sorting to enrich rare cell populations. Our protocol incorporates co-staining of cells with both fluorescent antibodies and AOCs simultaneously for subsequent input into the cell sorting and CITE-Seq pipeline.

For complete details on the use and execution of this protocol, please refer to Mair et al. (2020).

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Flow cytometry analysis to evaluate signals from cells at co-staining

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Step-by-step protocol for co-staining cells with fluorescent antibodies and AOCs

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Strategy to choose clones for the same protein marker with two antibodies

Monitoring CAR T cell generation with a CD8-targeted lentiviral vector by single-cell transcriptomics

Quantifying gene expression in individual cells can substantially improve our understanding about complex genetically engineered cell products such as chimeric antigen receptor (CAR) T cells. Here we designed a single-cell RNA sequencing (scRNA-seq) approach to monitor the delivery of a CD19-CAR gene via lentiviral vectors (LVs), i.e., the conventional vesicular stomatitis virus (VSV)-LV and the CD8-targeted CD8-LV. LV-exposed human donor peripheral blood mononuclear cells (PBMCs) were evaluated for a panel of 400 immune response-related genes including LV-specific probes. The resulting data revealed a trimodal expression for the CAR and CD8A, demanding a careful distribution-based identification of CAR T cells and CD8+ lymphocytes in scRNA-seq analysis. The fraction of T cells expressing high CAR levels was in concordance with flow cytometry results. More than 97% of the cells hit by CD8-LV expressed the CD8A gene. Remarkably, the majority of the potential off-target cells were in fact on-target cells, resulting in a target cell selectivity of more than 99%. Beyond that, differential gene expression analysis revealed the upregulation of restriction factors in CAR-negative cells, thus explaining their protection from CAR gene transfer. In summary, we provide a workflow and subsetting approach for scRNA-seq enabling reliable distinction between transduced and untransduced cells during CAR T cell generation.

High-throughput and high-dimensional single-cell analysis of antigen-specific CD8+ T cells

Although critical to T cell function, antigen specificity is often omitted in high-throughput multiomics-based T cell profiling due to technical challenges. We describe a high-dimensional, tetramer-associated T cell antigen receptor (TCR) sequencing (TetTCR-SeqHD) method to simultaneously profile cognate antigen specificities, TCR sequences, targeted gene expression and surface-protein expression from tens of thousands of single cells. Using human polyclonal CD8+ T cells with known antigen specificity and TCR sequences, we demonstrate over 98% precision for detecting the correct antigen specificity. We also evaluate gene expression and phenotypic differences among antigen-specific CD8+ T cells and characterize phenotype signatures of influenza- and Epstein-Barr virus-specific CD8+ T cells that are unique to their pathogen targets. Moreover, with the high-throughput capacity of profiling hundreds of antigens simultaneously, we apply TetTCR-SeqHD to identify antigens that preferentially enrich cognate CD8+ T cells in patients with type 1 diabetes compared to healthy controls and discover a TCR that cross-reacts with diabetes-related and microbiome antigens. TetTCR-SeqHD is a powerful approach for profiling T cell responses in humans and mice.

Application of Domain- and Genotype-Specific Models to Infer Post-Transcriptional Regulation of Segmentation Gene Expression in Drosophila

Unlike transcriptional regulation, the post-transcriptional mechanisms underlying zygotic segmentation gene expression in early Drosophila embryo have been insufficiently investigated. Condition-specific post-transcriptional regulation plays an important role in the development of many organisms. Our recent study revealed the domain- and genotype-specific differences between mRNA and the protein expression of Drosophila hb, gt, and eve genes in cleavage cycle 14A. Here, we use this dataset and the dynamic mathematical model to recapitulate protein expression from the corresponding mRNA patterns. The condition-specific nonuniformity in parameter values is further interpreted in terms of possible post-transcriptional modifications. For hb expression in wild-type embryos, our results predict the position-specific differences in protein production. The protein synthesis rate parameter is significantly higher in hb anterior domain compared to the posterior domain. The parameter sets describing Gt protein dynamics in wild-type embryos and Kr mutants are genotype-specific. The spatial discrepancy between gt mRNA and protein posterior expression in Kr mutants is well reproduced by the whole axis model, thus rejecting the involvement of post-transcriptional mechanisms. Our models fail to describe the full dynamics of eve expression, presumably due to its complex shape and the variable time delays between mRNA and protein patterns, which likely require a more complex model. Overall, our modeling approach enables the prediction of regulatory scenarios underlying the condition-specific differences between mRNA and protein expression in early embryo.

Inhibition of MET Signaling with Ficlatuzumab in Combination with Chemotherapy in Refractory AML: Clinical Outcomes and High-Dimensional Analysis

Acute myeloid leukemia patients refractory to induction therapy or relapsed within one year have poor outcomes. Autocrine production of hepatocyte growth factor by myeloid blasts drives leukemogenesis in pre-clinical models. A phase Ib trial evaluated ficlatuzumab, a first-in-class anti-HGF antibody, in combination with cytarabine in this high-risk population. Dose-limiting toxicities were not observed, and 20 mg/kg was established as the recommended phase II dose. The most frequent treatment-related adverse event was febrile neutropenia. Among 17 evaluable patients, the overall response rate was 53%, all complete remissions. Phospho-proteomic mass cytometry showed potent on-target suppression of p-MET after ficlatuzumab treatment and that attenuation of p-S6 was associated with clinical response. Multiplexed single cell RNA sequencing using prospectively acquired patient specimens identified interferon response genes as adverse predictive factors. The ficlatuzumab and cytarabine combination is well-tolerated with favorable efficacy. High-dimensional analyses at single-cell resolution represent promising approaches for identifying biomarkers of response and mechanisms of resistance in prospective clinical studies.

A subset of Kupffer cells regulates metabolism through the expression of CD36

Tissue macrophages are immune cells whose phenotypes and functions are dictated by origin and niches. However, tissues are complex environments, and macrophage heterogeneity within the same organ has been overlooked so far. Here, we used high-dimensional approaches to characterize macrophage populations in the murine liver. We identified two distinct populations among embryonically derived Kupffer cells (KCs) sharing a core signature while differentially expressing numerous genes and proteins: a major CD206^loESAM^- population (KC1) and a minor CD206^hiESAM⁺ population (KC2). KC2 expressed genes involved in metabolic processes, including fatty acid metabolism both in steady-state and in diet-induced obesity and hepatic steatosis. Functional characterization by depletion of KC2 or targeted silencing of the fatty acid transporter Cd36 highlighted a crucial contribution of KC2 in the liver oxidative stress associated with obesity. In summary, our study reveals that KCs are more heterogeneous than anticipated, notably describing a subpopulation wired with metabolic functions.

Single cell multiomic analysis of T cell exhaustion in vitro

T-cell activation is a key step in the amplification of an immune response. Over the course of an immune response, cells may be chronically stimulated, with some proportion becoming exhausted; an enormous number of molecules are involved in this process. There remain a number of questions about the process, namely: 1) what degree of heterogeneity and plasticity do T-cells exhibit during stimulation? 2) how many unique cell states define chronic stimulation? and 3) what markers discriminate activated from exhausted cells? We addressed these questions by performing single-cell multiomic analysis to simultaneously measure expression of 38 proteins and 399 genes in human T cells expanded in vitro. This approach allowed us to study - with unprecedented depth - how T cells change over the course of chronic stimulation. Comprehensive immunophenotypic and transcriptomic analysis at day 0 enabled a refined characterization of T-cell maturational states and the identification of a donor-specific subset of terminally differentiated T-cells that would have been otherwise overlooked using canonical cell classification schema. As expected, activation downregulated naïve-cell markers and upregulated effector molecules, proliferation regulators, co-inhibitory and co-stimulatory receptors. Our deep kinetic analysis further revealed clusters of proteins and genes identifying unique states of activation, defined by markers temporarily expressed upon 3 days of stimulation (PD-1, CD69, LTA), markers constitutively expressed throughout chronic activation (CD25, GITR, LGALS1), and markers uniquely up-regulated upon 14 days of stimulation (CD39, ENTPD1, TNFDF10); expression of these markers could be associated with the emergence of short-lived cell types. Notably, different ratios of cells expressing activation or exhaustion markers were measured at each time point. These data reveal the high heterogeneity and plasticity of chronically stimulated T cells. Our study demonstrates the power of a single-cell multiomic approach to comprehensively characterize T-cells and to precisely monitor changes in differentiation, activation, and exhaustion signatures during cell stimulation.

Interfacing Biomaterials with Synthetic T Cell Immunity

The clinical success of cancer immunotherapy is providing exciting opportunities for the development of new methods to detect and treat cancer more effectively. A new generation of biomaterials is being developed to interface with molecular and cellular features of immunity and ultimately shape or control anti-tumor responses. Recent advances that are supporting the advancement of engineered T cells are focused here. This class of cancer therapy has the potential to cure disease in subsets of patients, yet there remain challenges such as the need to improve response rates and safety while lowering costs to expand their use. To provide a focused overview, recent strategies in three areas of biomaterials research are highlighted: low-cost cell manufacturing to broaden patient access, noninvasive diagnostics for predictive monitoring of immune responses, and strategies for in vivo control that enhance anti-tumor immunity. These research efforts shed light on some of the challenges associated with T cell immunotherapy and how engineered biomaterials that interface with synthetic immunity are gaining traction to solve these challenges.

Bifidobacteria-mediated immune system imprinting early in life

Immune-microbe interactions early in life influence the risk of allergies, asthma, and other inflammatory diseases. Breastfeeding guides healthier immune-microbe relationships by providing nutrients to specialized microbes that in turn benefit the host's immune system. Such bacteria have co-evolved with humans but are now increasingly rare in modern societies. Here we show that a lack of bifidobacteria, and in particular depletion of genes required for human milk oligosaccharide (HMO) utilization from the metagenome, is associated with systemic inflammation and immune dysregulation early in life. In breastfed infants given Bifidobacterium infantis EVC001, which expresses all HMO-utilization genes, intestinal T helper 2 (Th2) and Th17 cytokines were silenced and interferon β (IFNβ) was induced. Fecal water from EVC001-supplemented infants contains abundant indolelactate and B. infantis-derived indole-3-lactic acid (ILA) upregulated immunoregulatory galectin-1 in Th2 and Th17 cells during polarization, providing a functional link between beneficial microbes and immunoregulation during the first months of life.

Cellular Tropism of SARS-CoV-2 across Human Tissues and Age-related Expression of ACE2 and TMPRSS2 in Immune-inflammatory Stromal Cells

Recently, emerging evidence has indicated that COVID-19 represents a major threat to older populations, but the underlying mechanisms remain unclear. The pathogen causing COVID-19 is acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 infection depends on the key entry factors, angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). Recognizing the importance of ACE2 and TMPRSS2 for the cellular tropism of SARS-CoV-2, we analyzed and presented the landscape of cell-type identities for ACE2⁺ TMPRSS2⁺ cells across different human tissues and the age-related alterations in ACE2 and TMPRSS2 expression across different cell types. Additionally, most of the post-acute COVID-19 sequelae could attribute to the ACE2-expressing organ systems. Therefore, these SARS-CoV-2 tropism data should be an essential resource for guiding clinical treatment and pathological studies, which should draw attention toward the prioritization of COVID-19 research in the future. Notably, we discovered the age-related expression of ACE2 and TMPRSS2 in the immune-inflammatory stromal cells, implying the potential interplay between COVID-19, stromal cells, and aging. In this study, we developed a novel and practical analysis framework for mapping the cellular tropism of SARS-CoV-2. This approach was built to aid the identification of viral-specific cell types and age-related alterations of viral tropism, highlighting the power of single-cell RNA sequencing (scRNA-seq) to address viral pathogenesis systematically. With the rapid accumulation of scRNA-seq data and the continuously increasing insight into viral entry factors, we anticipate that this scRNA-seq-based approach will attract broader interest in the virus research communities.

Improving oligo-conjugated antibody signal in multimodal single-cell analysis

Simultaneous measurement of surface proteins and gene expression within single cells using oligo-conjugated antibodies offers high-resolution snapshots of complex cell populations. Signal from oligo-conjugated antibodies is quantified by high-throughput sequencing and is highly scalable and sensitive. We investigated the response of oligo-conjugated antibodies towards four variables: concentration, staining volume, cell number at staining, and tissue. We find that staining with recommended antibody concentrations causes unnecessarily high background and amount of antibody used can be drastically reduced without loss of biological information. Reducing staining volume only affects antibodies targeting abundant epitopes used at low concentrations and is counteracted by reducing cell numbers. Adjusting concentrations increases signal, lowers background, and reduces costs. Background signal can account for a major fraction of total sequencing and is primarily derived from antibodies used at high concentrations. This study provides new insight into titration response and background of oligo-conjugated antibodies and offers concrete guidelines to improve such panels.