Meiotic transcriptional reprogramming mediated by cell-cell communications in humans and mice revealed by scATAC-seq and scRNA-seq.

Meiosis is a highly complex process significantly influenced by transcriptional regulation. However, studies on the mechanisms that govern transcriptomic changes during meiosis, especially in prophase I, are limited. Here, we performed single-cell ATAC-seq of human testis tissues and observed reprogramming during the transition from zygotene to pachytene spermatocytes. This event, conserved in mice, involved the deactivation of genes associated with meiosis after reprogramming and the activation of those related to spermatogenesis before their functional onset. Furthermore, we identified 282 transcriptional regulators (TRs) that underwent activation or deactivation subsequent to this process. Evidence suggested that physical contact signals from Sertoli cells may regulate these TRs in spermatocytes, while secreted ENHO signals may alter metabolic patterns in these cells. Our results further indicated that defective transcriptional reprogramming may be associated with non-obstructive azoospermia (NOA). This study revealed the importance of both physical contact and secreted signals between Sertoli cells and germ cells in meiotic progression.

Systematic mapping of TF-mediated cell fate changes by a pooled induction coupled with scRNA-seq and multi-omics approaches.

Transcriptional regulation controls cellular functions through interactions between transcription factors (TFs) and their chromosomal targets. However, understanding the fate conversion potential of multiple TFs in an inducible manner remains limited. Here, we introduce iTF-seq as a method for identifying individual TFs that can alter cell fate toward specific lineages at a single-cell level. iTF-seq enables time course monitoring of transcriptome changes, and with biotinylated individual TFs, it provides a multi-omics approach to understanding the mechanisms behind TF-mediated cell fate changes. Our iTF-seq study in mouse embryonic stem cells identified multiple TFs that trigger rapid transcriptome changes indicative of differentiation within a day of induction. Moreover, cells expressing these potent TFs often show a slower cell cycle and increased cell death. Further analysis using bioChIP-seq revealed that GCM1 and OTX2 act as pioneer factors and activators by increasing gene accessibility and activating the expression of lineage specification genes during cell fate conversion. iTF-seq has utility in both mapping cell fate conversion and understanding cell fate conversion mechanisms.

Detection of a 7SL RNA-derived small non-coding RNA using Molecular Beacons in vitro and in cells.

Small non-coding RNAs (sncRNA) are involved in many steps of the gene expression cascade and regulate processing and expression of mRNAs by the formation of ribonucleoprotein complexes (RNP) such as the RNA-induced silencing complex (RISC). By analyzing small RNA Seq data sets, we identified a sncRNA annotated as piR-hsa-1254, which is likely derived from the 3'-end of 7SL RNA2 (RN7SL2), herein referred to as snc7SL RNA. The 7SL RNA is an abundant long non-coding RNA polymerase III transcript and serves as structural component of the cytoplasmic signal recognition particle (SRP). To evaluate a potential functional role of snc7SL RNA, we aimed to define its cellular localization by live cell imaging. Therefore, a Molecular Beacon (MB)-based method was established to compare the subcellular localization of snc7SL RNA with its precursor 7SL RNA. We designed and characterized several MBs in vitro and tested those by live cell fluorescence microscopy. Using a multiplex approach, we show that 7SL RNA localizes mainly to the endoplasmic reticulum (ER), as expected for the SRP, whereas snc7SL RNA predominately localizes to the nucleus. This finding suggests a fundamentally different function of 7SL RNA and its derivate snc7SL RNA.

IL-33/ST2 Activation Is involved in Ro60-Regulated Photosensitivity in Cutaneous Lupus Erythematosus.

Interleukin- (IL-) 33 contributes to various inflammatory processes. IL-33/ST2 activation participates in systemic lupus erythematous via binding to the receptor of Suppression of Tumorigenicity 2 protein (ST2). However, whether IL-33/ST2 interferes with the nosogenesis of cutaneous lupus erythematosus (CLE) has not been reported so far. Herein, we proposed to disclose the impacts on IL-33/ST2 activation and Ro60 on CLE and their potential implications in the photosensitization of CLE cells. IL-33, ST2, and Ro60 in CLE patients' skin lesions were detected. Murine keratinocytes stimulated with or without IL-33 were irradiated by ultraviolet B (UVB), and the levels of Ro60 and inflammation markers were determined. Keratinocytes were cocultured with J774.2 macrophages and stimulated with IL-33 for analysis of chemostasis. The results identified that IL-33, ST2, and downstream inflammation markers were significantly upregulated in CLE lesions with Ro60 overexpression. Additionally, IL-33 treatment promoted the upregulation of Ro60 induced by UVB treatment in murine keratinocytes. Moreover, IL-33 stimulates keratinocytes to induce macrophage migration via enhancing the generation of the chemokine (C-C motif) ligands 17 and 22. Meanwhile, the silencing of ST2 or nuclear factor-kappa B (NF-κB) suppression abolished IL-33-induced upregulation of Ro60 in keratinocytes. Similarly, the inhibition of SOX17 expression was followed by downregulation of Ro60 in keratinocytes following IL-33 stimulation. In addition, UVB irradiation upregulated SOX17 in keratinocytes. Conclusively, the IL-33/ST2 axis interferes with Ro60-regulated photosensitization via activating the NF-κB- and PI3K/Akt- and SOX17-related pathways.

Hobit confers tissue-dependent programs to type 1 innate lymphoid cells.

Identification of type 1 innate lymphoid cells (ILC1s) has been problematic. The transcription factor Hobit encoded by Zfp683 has been proposed as a major driver of ILC1 programs. Using Zfp683 reporter mice, we showed that correlation of Hobit expression with ILC1s is tissue- and context-dependent. In liver and intestinal mucosa, Zfp683 expression correlated well with ILC1s; in salivary glands, Zfp683 was coexpressed with the natural killer (NK) master transcription factors Eomes and TCF1 in a unique cell population, which we call ILC1-like NK cells; during viral infection, Zfp683 was induced in conventional NK cells of spleen and liver. The impact of Zfp683 deletion on ILC1s and NK cells was also multifaceted, including a marked decrease in granzyme- and interferon-gamma (IFNγ)-producing ILC1s in the liver, slightly fewer ILC1s and more Eomes+ TCF1+ ILC1-like NK cells in salivary glands, and only reduced production of granzyme B by ILC1 in the intestinal mucosa. NK cell-mediated control of viral infection was unaffected. We conclude that Hobit has two major impacts on ILC1s: It sustains liver ILC1 numbers, while promoting ILC1 functional maturation in other tissues by controlling TCF1, Eomes, and granzyme expression.

Inhibition of estrogen signaling in myeloid cells increases tumor immunity in melanoma.

Immune checkpoint blockade (ICB) therapies have significantly prolonged patient survival across multiple tumor types, particularly in melanoma. Interestingly, sex-specific differences in response to ICB have been observed, with males receiving a greater benefit from ICB than females, although the mechanism or mechanisms underlying this difference are unknown. Mining published transcriptomic data sets, we determined that the response to ICBs is influenced by the functionality of intratumoral macrophages. This puts into context our observation that estrogens (E2) working through the estrogen receptor α (ERα) stimulated melanoma growth in murine models by skewing macrophage polarization toward an immune-suppressive state that promoted CD8+ T cell dysfunction and exhaustion and ICB resistance. This activity was not evident in mice harboring macrophage-specific depletion of ERα, confirming a direct role for estrogen signaling within myeloid cells in establishing an immunosuppressed state. Inhibition of ERα using fulvestrant, a selective estrogen receptor downregulator (SERD), decreased tumor growth, stimulated adaptive immunity, and increased the antitumor efficacy of ICBs. Further, a gene signature that determines ER activity in macrophages predicted survival in patients with melanoma treated with ICB. These results highlight the importance of E2/ER signaling as a regulator of intratumoral macrophage polarization, an activity that can be therapeutically targeted to reverse immune suppression and increase ICB efficacy.

The small RNA mascRNA differentially regulates TLR-induced proinflammatory and antiviral responses.

MALAT1-associated small cytoplasmic RNA (mascRNA) is a highly conserved transfer RNA-like (tRNA-like) noncoding RNA whose function remains largely unknown. We show here that this small RNA molecule played a role in the stringent control of TLR-mediated innate immune responses. mascRNA inhibited activation of NF-κB and mitogen-activated protein kinase (MAPK) signaling and the production of inflammatory cytokines in macrophages stimulated with LPS, a TLR4 ligand. Furthermore, exogenous mascRNA alleviated LPS-induced lung inflammation. However, mascRNA potentiated the phosphorylation of IRF3 and STAT1 and the transcription of IFN-related genes in response to the TLR3 ligand poly(I:C) both in vitro and in vivo. Mechanistically, mascRNA was found to enhance K48-linked ubiquitination and proteasomal degradation of TRAF6, thereby negatively regulating TLR-mediated MyD88-dependent proinflammatory signaling while positively regulating TRIF-dependent IFN signaling. Additionally, heterogeneous nuclear ribonucleoprotein H (hnRNP H) and hnRNP F were found to interact with mascRNA, promote its degradation, and contribute to the fine-tuning of TLR-triggered immune responses. Taken together, our data identify a dual role of mascRNA in both negative and positive regulation of innate immune responses.

scRNA sequencing uncovers a TCF4-dependent transcription factor network regulating commissure development in mouse.

Transcription factor 4 (TCF4) is a crucial regulator of neurodevelopment and has been linked to the pathogenesis of autism, intellectual disability and schizophrenia. As a class I bHLH transcription factor (TF), it is assumed that TCF4 exerts its neurodevelopmental functions through dimerization with proneural class II bHLH TFs. Here, we aim to identify TF partners of TCF4 in the control of interhemispheric connectivity formation. Using a new bioinformatic strategy integrating TF expression levels and regulon activities from single cell RNA-sequencing data, we find evidence that TCF4 interacts with non-bHLH TFs and modulates their transcriptional activity in Satb2+ intercortical projection neurons. Notably, this network comprises regulators linked to the pathogenesis of neurodevelopmental disorders, e.g. FOXG1, SOX11 and BRG1. In support of the functional interaction of TCF4 with non-bHLH TFs, we find that TCF4 and SOX11 biochemically interact and cooperatively control commissure formation in vivo, and regulate the transcription of genes implicated in this process. In addition to identifying new candidate interactors of TCF4 in neurodevelopment, this study illustrates how scRNA-Seq data can be leveraged to predict TF networks in neurodevelopmental processes.

Archaeal SRP RNA and SRP19 facilitate the assembly of SRP54-FtsY targeting complex.

The signal recognition particle (SRP) plays an essential role in protein translocation across biological membranes. Stable complexation of two GTPases in the signal recognition particle (SRP) and its receptor (SR) control the delivery of nascent polypeptide to the membrane translocon. In archaea, protein targeting is mediated by the SRP54/SRP19/7S RNA ribonucleoprotein complex (SRP) and the FtsY protein (SR). In the present study, using fluorescence resonance energy transfer (FRET), we demonstrate that archaeal 7S RNA stabilizes the SRP54·FtsY targeting complex (TC). Moreover, we show that archaeal SRP19 further assists 7S RNA in stabilizing the targeting complex (TC). These results suggest that archaeal 7S RNA and SRP19 modulate the conformation of the targeting complex and thereby reinforce TC to execute protein translocation via concomitant GTP hydrolysis.

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility using scRNA-Seq and scATAC-Seq.

Powerful next generation sequencing techniques offer robust and comprehensive analysis to investigate how retinal gene regulatory networks function during development and in disease states. Single-cell RNA sequencing allows us to comprehensively profile gene expression changes observed in retinal development and disease at a cellular level, while single-cell ATAC-Seq allows analysis of chromatin accessibility and transcription factor binding to be profiled at similar resolution. Here the use of these techniques in the developing retina is described, and MULTI-Seq is demonstrated, where individual samples are labeled with a modified oligonucleotide-lipid complex, enabling researchers to both increase the scope of individual experiments and substantially reduce costs.

scRNA-seq of ovarian follicle granulosa cells from different fertility goats reveals distinct expression patterns.

The new technology of high-throughput single-cell RNA sequencing (10 × scRNA-seq) was developed recently with many advantages. However, it was not commonly used in farm animal research. There are few reports for the gene expression of goat ovarian follicle granulosa cells (GCs) during different developmental stages. In the current investigation, the gene expression of follicle GCs at different stages from two populations of Ji'ning grey goats: high litter size (HL; ≥3/L; 2 L) and low litter size (LL; ≤2 /L; 2 L) were analysed by scRNA-seq. Many GC marker genes were identified, and the pseudo-time showed that GCs developed during the time course which reflected the follicular development and differentiation trajectory. Moreover, the gene expression difference between the two populations HL versus LL was very clear at different developmental stages. Many marker genes differentially expressed at different developmental stages. ASIP and ASPN were found to be highly expressed in the early stage of GCs, INHA, INHBA, MFGE8 and HSD17B1 were identified to be highly expressed in the growing stage of GCs, while IGFBP2, IGFBP5 and CYP11A1 were found to be highly expressed in late stage. These marker genes could be used as reference genes of goat follicle GC development. This investigation for the first time discovered the gene expression patterns in goat follicle GCs in high- or low-fertility populations (based on litter size) by scRNA-seq which may be useful for uncovering the oocyte development potential.

Preprocessing choices affect RNA velocity results for droplet scRNA-seq data.

Experimental single-cell approaches are becoming widely used for many purposes, including investigation of the dynamic behaviour of developing biological systems. Consequently, a large number of computational methods for extracting dynamic information from such data have been developed. One example is RNA velocity analysis, in which spliced and unspliced RNA abundances are jointly modeled in order to infer a 'direction of change' and thereby a future state for each cell in the gene expression space. Naturally, the accuracy and interpretability of the inferred RNA velocities depend crucially on the correctness of the estimated abundances. Here, we systematically compare five widely used quantification tools, in total yielding thirteen different quantification approaches, in terms of their estimates of spliced and unspliced RNA abundances in five experimental droplet scRNA-seq data sets. We show that there are substantial differences between the quantifications obtained from different tools, and identify typical genes for which such discrepancies are observed. We further show that these abundance differences propagate to the downstream analysis, and can have a large effect on estimated velocities as well as the biological interpretation. Our results highlight that abundance quantification is a crucial aspect of the RNA velocity analysis workflow, and that both the definition of the genomic features of interest and the quantification algorithm itself require careful consideration.

Insights from the Applications of Single-Cell Transcriptomic Analysis in Germ Cell Development and Reproductive Medicine.

Mechanistic understanding of germ cell formation at a genome-scale level can aid in developing novel therapeutic strategies for infertility. Germ cell formation is a complex process that is regulated by various mechanisms, including epigenetic regulation, germ cell-specific gene transcription, and meiosis. Gonads contain a limited number of germ cells at various stages of differentiation. Hence, genome-scale analysis of germ cells at the single-cell level is challenging. Conventional genome-scale approaches cannot delineate the landscape of genomic, transcriptomic, and epigenomic diversity or heterogeneity in the differentiating germ cells of gonads. Recent advances in single-cell genomic techniques along with single-cell isolation methods, such as microfluidics and fluorescence-activated cell sorting, have helped elucidate the mechanisms underlying germ cell development and reproductive disorders in humans. In this review, the history of single-cell transcriptomic analysis and their technical advantages over the conventional methods have been discussed. Additionally, recent applications of single-cell transcriptomic analysis for analyzing germ cells have been summarized.

Are dropout imputation methods for scRNA-seq effective for scHi-C data?

The prevalence of dropout events is a serious problem for single-cell Hi-C (scHiC) data due to insufficient sequencing depth and data coverage, which brings difficulties in downstream studies such as clustering and structural analysis. Complicating things further is the fact that dropouts are confounded with structural zeros due to underlying properties, leading to observed zeros being a mixture of both types of events. Although a great deal of progress has been made in imputing dropout events for single cell RNA-sequencing (RNA-seq) data, little has been done in identifying structural zeros and imputing dropouts for scHiC data. In this paper, we adapted several methods from the single-cell RNA-seq literature for inference on observed zeros in scHiC data and evaluated their effectiveness. Through an extensive simulation study and real data analysis, we have shown that a couple of the adapted single-cell RNA-seq algorithms can be powerful for correctly identifying structural zeros and accurately imputing dropout values. Downstream analysis using the imputed values showed considerable improvement for clustering cells of the same types together over clustering results before imputation.

PresRAT: a server for identification of bacterial small-RNA sequences and their targets with probable binding region.

Bacterial small-RNA (sRNA) sequences are functional RNAs, which play an important role in regulating the expression of a diverse class of genes. It is thus critical to identify such sRNA sequences and their probable mRNA targets. Here, we discuss new procedures to identify and characterize sRNA and their targets via the introduction of an integrated online platform 'PresRAT'. PresRAT uses the primary and secondary structural attributes of sRNA sequences to predict sRNA from a given sequence or bacterial genome. PresRAT also finds probable target mRNAs of sRNA sequences from a given bacterial chromosome and further concentrates on the identification of the probable sRNA-mRNA binding regions. Using PresRAT, we have identified a total of 66,209 potential sRNA sequences from 292 bacterial genomes and 2247 potential targets from 13 bacterial genomes. We have also implemented a protocol to build and refine 3D models of sRNA and sRNA-mRNA duplex regions and generated 3D models of 50 known sRNAs and 81 sRNA-mRNA duplexes using this platform. Along with the server part, PresRAT also contains a database section, which enlists the predicted sRNA sequences, sRNA targets, and their corresponding 3D models with structural dynamics information.

Tfh Cells in Health and Immunity: Potential Targets for Systems Biology Approaches to Vaccination.

T follicular helper (Tfh) cells are a specialised subset of CD4+ T cells that play a significant role in the adaptive immune response, providing critical help to B cells within the germinal centres (GC) of secondary lymphoid organs. The B cell receptors of GC B cells undergo multiple rounds of somatic hypermutation and affinity maturation within the GC response, a process dependent on cognate interactions with Tfh cells. B cells that receive sufficient help from Tfh cells form antibody-producing long-lived plasma and memory B cells that provide the basis of decades of effective and efficient protection and are considered the gold standard in correlates of protection post-vaccination. However, the T cell response to vaccination has been understudied, and over the last 10 years, exponential improvements in the technological underpinnings of sampling techniques, experimental and analytical tools have allowed multidisciplinary characterisation of the role of T cells and the immune system as a whole. Of particular interest to the field of vaccinology are GCs and Tfh cells, representing a unique target for improving immunisation strategies. Here, we discuss recent insights into the unique journey of Tfh cells from thymus to lymph node during differentiation and their role in the production of high-quality antibody responses as well as their journey back to the periphery as a population of memory cells. Further, we explore their function in health and disease and the power of next-generation sequencing techniques to uncover their potential as modulators of vaccine-induced immunity.

Functional Pro-metastatic Heterogeneity Revealed by Spiked-scRNAseq Is Shaped by Cancer Cell Interactions and Restricted by VSIG1.

How cells with metastatic potential, or pro-metastatic states, arise within heterogeneous primary tumors remains unclear. Here, we have used one index primary colon cancer to develop spiked-scRNAseq to link omics-defined single-cell clusters with cell behavior. Using spiked-scRNAseq we uncover cell populations with differential metastatic potential in which pro-metastatic states are correlated with the expression of signaling and vesicle-trafficking genes. Analyzing such heterogeneity, we define an anti-metastatic, non-cell-autonomous interaction originating from non-/low-metastatic cells, and identify membrane VSIG1 as a critical mediator of this interaction. VSIG1 acts to restrict the development of pro-metastatic states autonomously and non-cell autonomously, in part by inhibiting YAP/TAZ-TEAD signaling. As VSIG1 re-expression is able to reduce metastatic behavior from multiple colon cancer cell types, the regulation of VSIG1 or its effectors opens new interventional opportunities. In general, we propose that crosstalk between cancer cells, including the action of VSIG1, dynamically defines the degree of pro-metastatic intra-tumoral heterogeneity.

SARS-CoV-2 Disrupts Splicing, Translation, and Protein Trafficking to Suppress Host Defenses.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recently identified coronavirus that causes the respiratory disease known as coronavirus disease 2019 (COVID-19). Despite the urgent need, we still do not fully understand the molecular basis of SARS-CoV-2 pathogenesis. Here, we comprehensively define the interactions between SARS-CoV-2 proteins and human RNAs. NSP16 binds to the mRNA recognition domains of the U1 and U2 splicing RNAs and acts to suppress global mRNA splicing upon SARS-CoV-2 infection. NSP1 binds to 18S ribosomal RNA in the mRNA entry channel of the ribosome and leads to global inhibition of mRNA translation upon infection. Finally, NSP8 and NSP9 bind to the 7SL RNA in the signal recognition particle and interfere with protein trafficking to the cell membrane upon infection. Disruption of each of these essential cellular functions acts to suppress the interferon response to viral infection. Our results uncover a multipronged strategy utilized by SARS-CoV-2 to antagonize essential cellular processes to suppress host defenses.

Tumor-on-a-chip platform to interrogate the role of macrophages in tumor progression.

Tumor-infiltrating leukocytes, in particular macrophages, play an important role in tumor behavior and clinical outcome. The spectrum of macrophage subtypes ranges from antitumor 'M1'-type to protumor 'M2'-type macrophages. Tumor-associated macrophages (TAMs) typically display phenotypic features of both M1 and M2, and the population distribution is thought to be dynamic and evolves as the tumor progresses. However, our understanding of how TAMs impact the tumor microenvironment remains limited by the lack of appropriate 3D in vitro models that can capture cell-cell dynamics at high spatial and temporal resolution. Using our recently developed microphysiological 'tumor-on-a-chip' (TOC) device, we present here our findings on the impact of defined macrophage subsets on tumor behavior. The TOC device design contains three adjacent and connected chambers in which both the upper and lower chambers are loaded with tumor cells, whereas the central chamber contains a dynamic, perfused, living microvascular network. Introduction of human pancreatic or colorectal cancer cells together with M1-polarized macrophages significantly inhibited tumor growth and tumor-induced angiogenesis. Protein analysis and antibody-based neutralization studies confirmed that these effects were mediated through production of C-X-C motif chemokines (CXCL9), CXCL10 and CXCL11. By contrast, M2-macrophages mediated increased tumor cell migration into the vascularized chamber and did not inhibit tumor growth or angiogenesis. In fact, single-cell RNA sequencing showed that M2 macrophages further segregated endothelial cells into two distinct subsets, corresponding to static cells in vessels versus active cells involved in angiogenesis. The impact of M2 macrophages was mediated mostly by production of matrix metalloproteinase 7 and angiopoietin 2. In summary, our data demonstrate the utility of the TOC device to mechanistically probe biological questions in a 3D in vitro microenvironment.

Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancer.

Cell function and activity are regulated through integration of signaling, epigenetic, transcriptional, and metabolic pathways. Here, we introduce INs-seq, an integrated technology for massively parallel recording of single-cell RNA sequencing (scRNA-seq) and intracellular protein activity. We demonstrate the broad utility of INs-seq for discovering new immune subsets by profiling different intracellular signatures of immune signaling, transcription factor combinations, and metabolic activity. Comprehensive mapping of Arginase 1-expressing cells within tumor models, a metabolic immune signature of suppressive activity, discovers novel Arg1+ Trem2+ regulatory myeloid (Mreg) cells and identifies markers, metabolic activity, and pathways associated with these cells. Genetic ablation of Trem2 in mice inhibits accumulation of intra-tumoral Mreg cells, leading to a marked decrease in dysfunctional CD8+ T cells and reduced tumor growth. This study establishes INs-seq as a broadly applicable technology for elucidating integrated transcriptional and intra-cellular maps and identifies the molecular signature of myeloid suppressive cells in tumors.