Multiplexed bulk and single-cell RNA-seq hybrid enables cost-efficient disease modeling with chimeric organoids.

Disease modeling with isogenic Induced Pluripotent Stem Cell (iPSC)-differentiated organoids serves as a powerful technique for studying disease mechanisms. Multiplexed coculture is crucial to mitigate batch effects when studying the genetic effects of disease-causing variants in differentiated iPSCs or organoids, and demultiplexing at the single-cell level can be conveniently achieved by assessing natural genetic barcodes. Here, to enable cost-efficient time-series experimental designs via multiplexed bulk and single-cell RNA-seq of hybrids, we introduce a computational method in our Vireo Suite, Vireo-bulk, to effectively deconvolve pooled bulk RNA-seq data by genotype reference, and thereby quantify donor abundance over the course of differentiation and identify differentially expressed genes among donors. Furthermore, with multiplexed scRNA-seq and bulk RNA-seq, we demonstrate the usefulness and necessity of a pooled design to reveal donor iPSC line heterogeneity during macrophage cell differentiation and to model rare WT1 mutation-driven kidney disease with chimeric organoids. Our work provides an experimental and analytic pipeline for dissecting disease mechanisms with chimeric organoids.

Optimization of seeding density of OP9 cells to improve hematopoietic differentiation efficiency.

BACKGROUND: OP9 mouse stromal cell line has been widely used to induce differentiation of human embryonic stem cells (hESCs) into hematopoietic stem/progenitor cells (HSPCs). However, the whole co-culture procedure usually needs 14-18 days, including preparing OP9 cells at least 4 days. Therefore, the inefficient differentiation system is not appreciated. We aimed to optimize the culture conditions to improve differentiation efficiency. METHODS: In the experimental group, we set six different densities of OP9 cells and just cultured them for 24 h before co-culture, and in the control group, OP9 cells were cultured for 4 days to reach an overgrown state before co-culture. Then we compared the hematopoietic differentiation efficiency among them. RESULTS: OP9 cells were randomly assigned into two groups. In the experimental group, six different plated numbers of OP9 cells were cultured for 1 day before co-culture with hESCs. In contrast, in the control group, OP9 cells were cultured for 4 days at a total number of 3.1 × 104 cells/cm2 in a 6-well plate to reach an overgrown state before co-culture. Hematopoietic differentiation was evaluated with CD34 immunostaining, and compared between these two groups. We could not influence the differentiation efficiency of OP9 cells with a total number of 10.4 × 104 cells/cm2 in a 6-well plate which was cultured just for 1 day, followed by co-culture with hESCs. It reached the same differentiation efficiency 5 days earlier than the control group. CONCLUSION: The peak of CD34 + cells appeared 2 days earlier compared to the control group. A total number of 1.0 × 106 cells in a 6-well plate for OP9 cells was appropriate to have high differentiation efficiency.

MetaQuad: shared informative variants discovery in metagenomic samples.

Motivation: Strain-level analysis of metagenomic data has garnered significant interest in recent years. Microbial single nucleotide polymorphisms (SNPs) are genomic variants that can reflect strain-level differences within a microbial species. The diversity and emergence of SNPs in microbial genomes may reveal evolutionary history and environmental adaptation in microbial populations. However, efficient discovery of shared polymorphic variants in a large collection metagenomic samples remains a computational challenge. Results: MetaQuad utilizes a density-based clustering technique to effectively distinguish between shared variants and non-polymorphic sites using shotgun metagenomic data. Empirical comparisons with other state-of-the-art methods show that MetaQuad significantly reduces the number of false positive SNPs without greatly affecting the true positive rate. We used MetaQuad to identify antibiotic-associated variants in patients who underwent Helicobacter pylori eradication therapy. MetaQuad detected 7591 variants across 529 antibiotic resistance genes. The nucleotide diversity of some genes is increased 6 weeks after antibiotic treatment, potentially indicating the role of these genes in specific antibiotic treatments. Availability and implementation: MetaQuad is an open-source Python package available via https://github.com/holab-hku/MetaQuad.

Accurate top protein variant discovery via low-N pick-and-validate machine learning.

A strategy to obtain the greatest number of best-performing variants with least amount of experimental effort over the vast combinatorial mutational landscape would have enormous utility in boosting resource producibility for protein engineering. Toward this goal, we present a simple and effective machine learning-based strategy that outperforms other state-of-the-art methods. Our strategy integrates zero-shot prediction and multi-round sampling to direct active learning via experimenting with only a few predicted top variants. We find that four rounds of low-N pick-and-validate sampling of 12 variants for machine learning yielded the best accuracy of up to 92.6% in selecting the true top 1% variants in combinatorial mutant libraries, whereas two rounds of 24 variants can also be used. We demonstrate our strategy in successfully discovering high-performance protein variants from diverse families including the CRISPR-based genome editors, supporting its generalizable application for solving protein engineering tasks. A record of this paper's transparent peer review process is included in the supplemental information.

Effect of Cyclosporine A on Th1/Th2 Cytokine Production by Decidual Stromal Cells Mediated by Trophoblast-derived Galectin-9.

This study aimed to investigate the effect of cyclosporine A (CsA) on secretion of Th1 and Th2 cytokines by decidual stromal cells (DSCs) mediated by galectin (Gal)-9.HTR8/SVneo cells and primary trophoblasts were used for in vitro studies. Gal-9 expression was measured using quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay, CsA was used to regulate Gal-9 expression in trophoblasts. DSCs were treated with trophoblast supernatant and changes in Th1 and Th2 cytokine levels were analyzed. Changes in DSC levels of the T-cell immunoglobulin mucin receptor 3 (TIM-3) levels in DSCs after treatment with Gal-9 were assessed. Western blotting and ERK and AKT inhibitors were used to assess the involvement of the corresponding signaling pathways. Gal-9 was expressed by both primary trophoblasts and HTR8/SVneo cells. CsA treatment increased Gal-9 secretion by trophoblasts, which in turn increased IL-6 (Th2 cytokine) and decreased TNF-α and IFN-γ (Th1 cytokines) secretion in DSCs. Upon downregulation of trophoblast Gal-9 secretion, DSCs secreted lower levels of Th2 cytokines and higher levels of Th1 cytokines, and the effect was reversed by addition of CsA. TIM-3 expression changed in parallel with Gal-9 secretion. CsA treatment upregulated expression of Gal-9 in trophoblasts, promoted secretion of Th2 cytokines, and inhibited secretion of Th1 cytokines via ERK signaling.

Expression profiling of cerebrospinal fluid identifies dysregulated antiviral mechanisms in multiple sclerosis.

Despite the overwhelming evidence that multiple sclerosis is an autoimmune disease, relatively little is known about the precise nature of the immune dysregulation underlying the development of the disease. Reasoning that the CSF from patients might be enriched for cells relevant in pathogenesis, we have completed a high-resolution single-cell analysis of 96 732 CSF cells collected from 33 patients with multiple sclerosis (n = 48 675) and 48 patients with other neurological diseases (n = 48 057). Completing comprehensive cell type annotation, we identified a rare population of CD8+ T cells, characterized by the upregulation of inhibitory receptors, increased in patients with multiple sclerosis. Applying a Multi-Omics Factor Analysis to these single-cell data further revealed that activity in pathways responsible for controlling inflammatory and type 1 interferon responses are altered in multiple sclerosis in both T cells and myeloid cells. We also undertook a systematic search for expression quantitative trait loci in the CSF cells. Of particular interest were two expression quantitative trait loci in CD8+ T cells that were fine mapped to multiple sclerosis susceptibility variants in the viral control genes ZC3HAV1 (rs10271373) and IFITM2 (rs1059091). Further analysis suggests that these associations likely reflect genetic effects on RNA splicing and cell-type specific gene expression respectively. Collectively, our study suggests that alterations in viral control mechanisms might be important in the development of multiple sclerosis.

PD-L1 regulates inflammatory programs of macrophages from human pluripotent stem cells.

Programmed death ligand 1 (PD-L1) serves as a pivotal immune checkpoint in both the innate and adaptive immune systems. PD-L1 is expressed in macrophages in response to IFNγ. We examined whether PD-L1 might regulate macrophage development. We established PD-L1 KO (CD274 -/- ) human pluripotent stem cells and differentiated them into macrophages and observed a 60% reduction in CD11B+CD45+ macrophages in CD274 -/- ; this was orthogonally verified, with the PD-L1 inhibitor BMS-1166 reducing macrophages to the same fold. Single-cell RNA sequencing further confirmed the down-regulation of the macrophage-defining transcription factors SPI1 and MAFB Furthermore, CD274 -/- macrophages reduced the level of inflammatory signals such as NF-κB and TNF, and chemokine secretion of the CXCL and CCL families. Anti-inflammatory TGF-ß was up-regulated. Finally, we identified that CD274 -/- macrophages significantly down-regulated interferon-stimulated genes despite the presence of IFNγ in the differentiation media. These data suggest that PD-L1 regulates inflammatory programs of macrophages from human pluripotent stem cells.

The Effect of the cAMP Signaling Pathway on HTR8/SV-Neo Cell Line Proliferation, Invasion, and Migration After Treatment with Forskolin.

Pre-eclampsia (PE) is thought to be related to placental dysfunction, particularly poor extravillous trophoblast (EVT) invasion and migration abilities. However, the pathogenic mechanism is not fully understood. This article describes the impact of the cyclic adenosine monophosphate(cAMP) signaling pathway on EVT behavior, focusing on EVT proliferation, invasion, and migration. Here, we used the HTR8/SV-neo cell line to study human EVT function in vitro. HTR8/SV-neo cells were treated with different concentrations of forskolin (cAMP pathway-specific agonist) to alter intracellular cAMP levels, and dimethyl sulfoxide (DMSO) was used as the control. First, a cAMP assay was performed to measure the cAMP concentration in HTR8/SV-neo cells treated with different forskolin concentrations, and cell proliferation was assessed by constructing cell growth curves and assessing colony formation. Cell invasion and migration were observed by Transwell experiments, and intracellular epithelial-mesenchymal transition (EMT) marker expression was evaluated by quantitative real-time polymerase chain reaction (qPCR) and Western blotting (WB). According to our research, the intracellular cAMP levels in HTR8/SV-neo cells were increased in a dose-dependent manner, and HTR8/SV-neo cell proliferation, invasion and migration were significantly enhanced. The expression of EMT and angiogenesis markers was upregulated. Additionally, with the increase in intracellular cAMP levels, the phosphorylation of intracellular mitogen-activated protein kinase (MAPK) signaling pathway components was significantly increased. These results suggested that the cAMP signaling pathway promoted the phosphorylation of MAPK signaling components, thus enhancing EVT functions, including proliferation, invasion, and migration, and to a certain extent, providing a novel direction for the treatment of PE patients.

CsA promotes trophoblast invasion accompanied by changes in leukaemic inhibitory factor and fibroblast growth factor in peri-implantation blastocysts.

During the early stages of human pregnancy, successful implantation of embryonic trophoblast cells into the endometrium depends on good communication between trophoblast cells and the endometrium. Abnormal trophoblast cell function can cause embryo implantation failure. In this study, we added cyclosporine A (CsA) to the culture medium to observe the effect of CsA on embryonic trophoblast cells and the related mechanism. We observed that CsA promoted the migration and invasion of embryonic trophoblast cells. CsA promoted the expression of leukaemic inhibitory factor (LIF) and fibroblast growth factor (FGF). In addition, CsA promoted the secretion and volume increase in vesicles in the CsA-treated group compared with the control group. Therefore, CsA may promote the adhesion and invasion of trophoblast cells through LIF and FGF and promote the vesicle dynamic process, which is conducive to embryo implantation.

CamoTSS: analysis of alternative transcription start sites for cellular phenotypes and regulatory patterns from 5' scRNA-seq data.

Five-prime single-cell RNA-seq (scRNA-seq) has been widely employed to profile cellular transcriptomes, however, its power of analysing transcription start sites (TSS) has not been fully utilised. Here, we present a computational method suite, CamoTSS, to precisely identify TSS and quantify its expression by leveraging the cDNA on read 1, which enables effective detection of alternative TSS usage. With various experimental data sets, we have demonstrated that CamoTSS can accurately identify TSS and the detected alternative TSS usages showed strong specificity in different biological processes, including cell types across human organs, the development of human thymus, and cancer conditions. As evidenced in nasopharyngeal cancer, alternative TSS usage can also reveal regulatory patterns including systematic TSS dysregulations.

Discovery of regulatory motifs in 5' untranslated regions using interpretable multi-task learning models.

The sequence in the 5' untranslated regions (UTRs) is known to affect mRNA translation rates. However, the underlying regulatory grammar remains elusive. Here, we propose MTtrans, a multi-task translation rate predictor capable of learning common sequence patterns from datasets across various experimental techniques. The core premise is that common motifs are more likely to be genuinely involved in translation control. MTtrans outperforms existing methods in both accuracy and the ability to capture transferable motifs across species, highlighting its strength in identifying evolutionarily conserved sequence motifs. Our independent fluorescence-activated cell sorting coupled with deep sequencing (FACS-seq) experiment validates the impact of most motifs identified by MTtrans. Additionally, we introduce "GRU-rewiring," a technique to interpret the hidden states of the recurrent units. Gated recurrent unit (GRU)-rewiring allows us to identify regulatory element-enriched positions and examine the local effects of 5' UTR mutations. MTtrans is a powerful tool for deciphering the translation regulatory motifs.

SpatialDM for rapid identification of spatially co-expressed ligand-receptor and revealing cell-cell communication patterns.

Cell-cell communication is a key aspect of dissecting the complex cellular microenvironment. Existing single-cell and spatial transcriptomics-based methods primarily focus on identifying cell-type pairs for a specific interaction, while less attention has been paid to the prioritisation of interaction features or the identification of interaction spots in the spatial context. Here, we introduce SpatialDM, a statistical model and toolbox leveraging a bivariant Moran's statistic to detect spatially co-expressed ligand and receptor pairs, their local interacting spots (single-spot resolution), and communication patterns. By deriving an analytical null distribution, this method is scalable to millions of spots and shows accurate and robust performance in various simulations. On multiple datasets including melanoma, Ventricular-Subventricular Zone, and intestine, SpatialDM reveals promising communication patterns and identifies differential interactions between conditions, hence enabling the discovery of context-specific cell cooperation and signalling.

DCATS: differential composition analysis for flexible single-cell experimental designs.

Differential composition analysis - the identification of cell types that have statistically significant changes in abundance between multiple experimental conditions - is one of the most common tasks in single cell omic data analysis. However, it remains challenging to perform differential composition analysis in the presence of flexible experimental designs and uncertainty in cell type assignment. Here, we introduce a statistical model and an open source R package, DCATS, for differential composition analysis based on a beta-binomial regression framework that addresses these challenges. Our empirical evaluation shows that DCATS consistently maintains high sensitivity and specificity compared to state-of-the-art methods.

Comparison of recombinant human FSH biosimilar QL1012 with Gonal-f® for ovarian stimulation: a phase-three trial.

RESEARCH QUESTION: Are QL1012 and Gonal-f® equivalent in women undergoing ovarian stimulation for assisted reproductive technology (ART)? DESIGN: This multicentre, randomized, assessor-blinded, phase-three trial was conducted at 13 centres in China. Eligible patients were infertile women; age 20-39 years; body mass index 18-30 kg/m2; regular menstrual cycles; and indication for ART. After successful pituitary downregulation, patients were randomly assigned (1:1) to receive QL1012 or Gonal-f®, stratified by age (initial dose of 75-150 IU for women younger than 30 years, 150-225 IU for women aged 30-34 years and 225-300 IU for women aged ≥35 years, subcutaneously, once daily). The primary end point was the number of oocytes retrieved. RESULTS: Between October 2018, and June 2019, 341 patients were included in the per-protocol set. The mean numbers of oocytes retrieved were 14.7 ± 7.0 in the QL1012 group (n = 169) and 13.4 ± 6.1 in the Gonal-f® group (n = 172). Adjusted by analysis of covariance model, the least-squares mean difference was 1.3 oocytes (95% CI -0.1 to 2.7; P = 0.0650), within the pre-defined equivalence margins of ±3.0. Similar results were observed in the full analysis set. Additionally, no statistical differences were found in secondary end points except oestradiol concentration (median 3948.0 pg/ml versus 3545.3 pg/ml; P = 0.0015). Ovarian hyperstimulation syndrome (12.4% versus 13.1 %) and other adverse events were similar between the two groups. CONCLUSIONS: Therapeutic equivalence and similar safety profiles were demonstrated between QL1012 and Gonal-f® in women undergoing ovarian stimulation for ART.

Cyclosporin A Promotes Invasion and Migration of Extravillous Trophoblast Cells Derived from Human-Induced Pluripotent Stem Cells and Human Embryonic Stem Cells.

Extravillous trophoblast (EVT) cells play an essential role in the maternal-fetal interaction. Although abnormal development and function of EVT cells, including impaired migration and invasion capability, are believed to be etiologically linked to severe pregnancy disorders including pre-eclampsia, the associated molecular mechanisms are not clear due to the lack of an appropriate cell model in vitro. Cyclosporin A (CsA) is a macrolide immunosuppressant and also used in clinic to improve pregnancy outcomes. However, whether CsA has any effects on the function of EVT cells has not been well investigated. In this study, we induced differentiation of human-induced pluripotent stem cells (hiPSCs) and human embryonic stem cells (hESCs) into EVT cells (hiPSC-EVT and hESC-EVT cells, respectively) by Y27632, neuregulin-1 (NRG1), A83-01, and matrigel, and collected these derived EVT cells by flow cytometry for sorting cells positive for double human leukocyte antigen-G (HLA-G) and Cytokeratin7 (KRT7), both of which are EVT markers. We then investigated the effects of CsA on the invasion and migration of these derived EVT cells. We found that the hiPSC-EVT and hESC-EVT cells expressed high levels of the EVT markers such as KRT7, integrin alpha 5 (ITGA5), and HLA-G but low levels of OCT4, a stem cell marker, and that CsA significantly promoted the invasion and migration of hiPSC-EVT and hESC-EVT cells compared with HTR-8/SVneo cells. These results represent a possible cell model for studying the function of EVT cells and mechanism of pregnancy-related disorders associated with EVT. In addition, CsA may be used to treat pregnancy complications in clinic associated with deficient EVT function.

Chronic type I interferon signaling promotes lipid-peroxidation-driven terminal CD8+ T cell exhaustion and curtails anti-PD-1 efficacy.

Identifying signals that govern the differentiation of tumor-infiltrating CD8+ T cells (CD8+ TILs) toward exhaustion can improve current therapeutic approaches for cancer. Here, we show that type I interferons (IFN-Is) act as environmental cues, enhancing terminal CD8+ T cell exhaustion in tumors. We find enrichment of IFN-I-stimulated genes (ISGs) within exhausted CD8+ T cells (Tex cells) in patients across various cancer types, with heightened ISG levels correlating with poor response to immune checkpoint blockade (ICB) therapy. In preclinical models, CD8+ TILs devoid of IFN-I signaling develop less exhaustion features, provide better tumor control, and show greater response to ICB-mediated rejuvenation. Mechanistically, chronic IFN-I stimulation perturbs lipid metabolism and redox balance in Tex cells, leading to aberrant lipid accumulation and elevated oxidative stress. Collectively, these defects promote lipid peroxidation, which potentiates metabolic and functional exhaustion of Tex cells. Thus, cell-intrinsic IFN-I signaling regulates the extent of CD8+ TIL exhaustion and has important implications for immunotherapy.

UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference.

The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model violation or lack of temporal regularization. Here, we present UniTVelo, a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. Uniquely, it also supports the inference of a unified latent time across the transcriptome. With ten datasets, we demonstrate that UniTVelo returns the expected trajectory in different biological systems, including hematopoietic differentiation and those even with weak kinetics or complex branches.