A cis-regulatory module underlies retinal ganglion cell genesis and axonogenesis.

Atoh7 is transiently expressed in retinal progenitor cells (RPCs) and is required for retinal ganglion cell (RGC) differentiation. In humans, a deletion in a distal non-coding regulatory region upstream of ATOH7 is associated with optic nerve atrophy and blindness. Here, we functionally interrogate the significance of the Atoh7 regulatory landscape to retinogenesis in mice. Deletion of the Atoh7 enhancer structure leads to RGC deficiency, optic nerve hypoplasia, and retinal blood vascular abnormalities, phenocopying inactivation of Atoh7. Further, loss of the Atoh7 remote enhancer impacts ipsilaterally projecting RGCs and disrupts proper axonal projections to the visual thalamus. Deletion of the Atoh7 remote enhancer is also associated with the dysregulation of axonogenesis genes, including the derepression of the axon repulsive cue Robo3. Our data provide insights into how Atoh7 enhancer elements function to promote RGC development and optic nerve formation and highlight a key role of Atoh7 in the transcriptional control of axon guidance molecules.

Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression.

Spatial transcriptomics technologies have shed light on the complexities of tissue structures by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods, especially those utilized in platforms like Visium, often relinquish spatial details owing to intrinsic resolution limitations. In response, we introduce TransformerST, an innovative, unsupervised model anchored in the Transformer architecture, which operates independently of references, thereby ensuring cost-efficiency by circumventing the need for single-cell RNA sequencing. TransformerST not only elevates Visium data from a multicellular level to a single-cell granularity but also showcases adaptability across diverse spatial transcriptomics platforms. By employing a vision transformer-based encoder, it discerns latent image-gene expression co-representations and is further enhanced by spatial correlations, derived from an adaptive graph Transformer module. The sophisticated cross-scale graph network, utilized in super-resolution, significantly boosts the model's accuracy, unveiling complex structure-functional relationships within histology images. Empirical evaluations validate its adeptness in revealing tissue subtleties at the single-cell scale. Crucially, TransformerST adeptly navigates through image-gene co-representation, maximizing the synergistic utility of gene expression and histology images, thereby emerging as a pioneering tool in spatial transcriptomics. It not only enhances resolution to a single-cell level but also introduces a novel approach that optimally utilizes histology images alongside gene expression, providing a refined lens for investigating spatial transcriptomics.

Nasal epithelial gene expression and total IgE in children and adolescents with asthma.

BACKGROUND: Little is known about nasal epithelial gene expression and total IgE in youth. OBJECTIVE: We aimed to identify genes whose nasal epithelial expression differs by total IgE in youth, and group them into modules that could be mapped to airway epithelial cell types. METHODS: We conducted a transcriptome-wide association study of total IgE in 469 Puerto Ricans aged 9 to 20 years who participated in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study, separately in all subjects and in those with asthma. We then attempted to replicate top findings for each analysis using data from 3 cohorts. Genes with a Benjamini-Hochberg-adjusted P value of less than .05 in the Epigenetic Variation and Childhood Asthma in Puerto Ricans study and a P value of less than .05 in the same direction of association in 1 or more replication cohort were considered differentially expressed genes (DEGs). DEGs for total IgE in subjects with asthma were further dissected into gene modules using coexpression analysis, and such modules were mapped to specific cell types in airway epithelia using public single-cell RNA-sequencing data. RESULTS: A higher number of DEGs for total IgE were identified in subjects with asthma (n = 1179 DEGs) than in all subjects (n = 631 DEGs). In subjects with asthma, DEGs were mapped to 11 gene modules. The top module for positive correlation with total IgE was mapped to myoepithelial and mucus secretory cells in lower airway epithelia and was regulated by IL-4, IL5, IL-13, and IL-33. Within this module, hub genes included CDH26, FETUB, NTRK2, CCBL1, CST1, and CST2. Furthermore, an enrichment analysis showed overrepresentation of genes in signaling pathways for synaptogenesis, IL-13, and ferroptosis, supporting interactions between interleukin- and acetylcholine-induced responses. CONCLUSIONS: Our findings for nasal epithelial gene expression support neuroimmune coregulation of total IgE in youth with asthma.

Methyl-TWAS: A powerful method for in silico transcriptome-wide association studies (TWAS) using long-range DNA methylation.

In silico transcriptome-wide association studies (TWAS) are commonly used to test whether expression of specific genes is linked to a complex trait. However, genotype-based in silico TWAS such as PrediXcan, exhibit low prediction accuracy for a majority of genes because genotypic data lack tissue- and disease-specificity and are not affected by the environment. Because methylation is tissue-specific and, like gene expression, can be modified by environment or disease status, methylation should predict gene expression with more accuracy than SNPs. Therefore, we propose Methyl-TWAS, the first approach that utilizes long-range methylation markers to impute gene expression for in silico TWAS through penalized regression. Methyl-TWAS 1) predicts epigenetically regulated/associated expression (eGReX), which incorporates tissue-specific expression and both genetically- (GReX) and environmentally-regulated expression to identify differentially expressed genes (DEGs) that could not be identified by genotype-based methods; and 2) incorporates both cis- and trans- CpGs, including various regulatory regions to identify DEGs that would be missed using cis- methylation only. Methyl-TWAS outperforms PrediXcan and two other methods in imputing gene expression in the nasal epithelium, particularly for immunity-related genes and DEGs in atopic asthma. Methyl-TWAS identified 3,681 (85.2%) of the 4,316 DEGs identified in a previous TWAS of atopic asthma using measured expression, while PrediXcan could not identify any gene. Methyl-TWAS also outperforms PrediXcan for expression imputation as well as in silico TWAS in white blood cells. Methyl-TWAS is a valuable tool for in silico TWAS, leveraging a growing body of publicly available genome-wide DNA methylation data for a variety of human tissues.

Targeting Bcl-xL is a potential therapeutic strategy for extranodal NK/T cell lymphoma.

Extranodal natural killer/T cell lymphoma, nasal type (ENKTL) is an aggressive lymphoid malignancy with a poor prognosis and lacks standard treatment. Targeted therapies are urgently needed. Here we systematically investigated the druggable mechanisms through chemogenomic screening and identified that Bcl-xL-specific BH3 mimetics effectively induced ENKTL cell apoptosis. Notably, the specific accumulation of Bcl-xL, but not other Bcl-2 family members, was verified in ENKTL cell lines and patient tissues. Furthermore, Bcl-xL high expression was shown to be closely associated with worse patient survival. The critical role of Bcl-xL in ENKTL cell survival was demonstrated utilizing selective inhibitors, genetic silencing, and a specific degrader. Additionally, the IL2-JAK1/3-STAT5 signaling was implicated in Bcl-xL dysregulation. In vivo, Bcl-xL inhibition reduced tumor burden, increased apoptosis, and prolonged survival in ENKTL cell line xenograft and patient-derived xenograft models. Our study indicates Bcl-xL as a promising therapeutic target for ENKTL, warranting monitoring in ongoing clinical trials by targeting Bcl-xL.

Cis- and trans-eQTM analysis reveals novel epigenetic and transcriptomic immune markers of atopic asthma in airway epithelium.

BACKGROUND: Expression quantitative trait methylation (eQTM) analyses uncover associations between DNA methylation markers and gene expression. Most eQTM analyses of complex diseases have focused on cis-eQTM pairs (within 1 megabase). OBJECTIVES: This study sought to identify cis- and trans-methylation markers associated with gene expression in airway epithelium from youth with and without atopic asthma. METHODS: In this study, the investigators conducted both cis- and trans-eQTM analyses in nasal (airway) epithelial samples from 158 Puerto Rican youth with atopic asthma and 100 control subjects without atopy or asthma. The investigators then attempted to replicate their findings in nasal epithelial samples from 2 studies of children, while also examining whether their results in nasal epithelium overlap with those from an eQTM analysis in white blood cells from the Puerto Rican subjects. RESULTS: This study identified 9,108 cis-eQTM pairs and 2,131,500 trans-eQTM pairs. Trans-associations were significantly enriched for transcription factor and microRNA target genes. Furthermore, significant cytosine-phosphate-guanine sites (CpGs) were differentially methylated in atopic asthma and significant genes were enriched for genes differentially expressed in atopic asthma. In this study, 50.7% to 62.6% of cis- and trans-eQTM pairs identified in Puerto Rican youth were replicated in 2 smaller cohorts at false discovery rate-adjusted P < .1. Replicated genes in the trans-eQTM analysis included biologically plausible asthma-susceptibility genes (eg, HDC, NLRP3, ITGAE, CDH26, and CST1) and are enriched in immune pathways. CONCLUSIONS: Studying both cis- and trans-epigenetic regulation of airway epithelial gene expression can identify potential causal and regulatory pathways or networks for childhood asthma. Trans-eQTM CpGs may regulate gene expression in airway epithelium through effects on transcription factor and microRNA target genes.

Nasal DNA methylation at three CpG sites predicts childhood allergic disease.

Childhood allergic diseases, including asthma, rhinitis and eczema, are prevalent conditions that share strong genetic and environmental components. Diagnosis relies on clinical history and measurements of allergen-specific IgE. We hypothesize that a multi-omics model could accurately diagnose childhood allergic disease. We show that nasal DNA methylation has the strongest predictive power to diagnose childhood allergy, surpassing blood DNA methylation, genetic risk scores, and environmental factors. DNA methylation at only three nasal CpG sites classifies allergic disease in Dutch children aged 16 years well, with an area under the curve (AUC) of 0.86. This is replicated in Puerto Rican children aged 9-20 years (AUC 0.82). DNA methylation at these CpGs additionally detects allergic multimorbidity and symptomatic IgE sensitization. Using nasal single-cell RNA-sequencing data, these three CpGs associate with influx of T cells and macrophages that contribute to allergic inflammation. Our study suggests the potential of methylation-based allergy diagnosis.

Anti-C5a antibody vilobelimab treatment and the effect on biomarkers of inflammation and coagulation in patients with severe COVID-19: a substudy of the phase 2 PANAMO trial.

We recently reported in the phase 3 PANAMO trial that selectively blocking complement 5a (C5a) with vilobelimab led to improved survival in critically ill COVID-19 patients. C5a is an important contributor to the innate immune system and can also activate the coagulation system. High C5a levels have been reported in severely ill COVID-19 patients and correlate with disease severity and mortality. Previously, we assessed the potential benefit and safety of vilobelimab in severe COVID-19 patients. In the current substudy of the phase 2 PANAMO trial, we aim to explore the effects of vilobelimab on various biomarkers of inflammation and coagulation. Between March 31 and April 24, 2020, 17 patients with severe COVID-19 pneumonia were enrolled in an exploratory, open-label, randomised phase 2 trial. Blood markers of complement, endothelial activation, epithelial barrier disruption, inflammation, neutrophil activation, neutrophil extracellular trap (NET) formation and coagulopathy were measured using enzyme-linked immunosorbent assay (ELISA) or utilizing the Luminex platform. During the first 15 days after inclusion, change in biomarker concentrations between the two groups were modelled with linear mixed-effects models with spatial splines and compared. Eight patients were randomized to vilobelimab treatment plus best supportive care (BSC) and nine patients were randomized to BSC only. A significant decrease over time was seen in the vilobelimab plus BSC group for C5a compared to the BSC only group (p < 0.001). ADAMTS13 levels decreased over time in the BSC only group compared to the vilobelimab plus BSC group (p < 0.01) and interleukin-8 (IL-8) levels were statistically more suppressed in the vilobelimab plus BSC group compared to the BSC group (p = 0.03). Our preliminary results show that C5a inhibition decreases the inflammatory response and hypercoagulability, which likely explains the beneficial effect of vilobelimab in severe COVID-19 patients. Validation of these results in a larger sample size is warranted.

The PROTAC selectively degrading Bcl-xL represents a novel Hedgehog pathway inhibitor with capacity of combating resistance to Smoothened inhibitors while sparing bone growth.

Rationale: Primary and acquired resistance to Smoothened (Smo) inhibitors largely hampered their clinical efficacy. Given the important functions of hedgehog (Hh) pathway in bone formation and development, the permanent defects in bone growth caused by Smo inhibitors further restrict the use of Smo inhibitors for pediatric tumor patients. Anti-apoptotic Bcl-2 proteins regulate Hh activity by engaging a Bcl-2 homology (BH) domain sequence found in suppressor of fused (Sufu). In this study, we tested the effect of SIAIS361034, a Proteolysis Targeting Chimera (PROTAC) specifically targeting B-cell lymphoma extra large (Bcl-xL) to the celeblon (CRBN) E3 ligase for degradation, on combating the resistance and reducing the toxicity of bone growth caused by Hh inhibition. Methods: Fluorescence polarization, homogeneous time-resolved fluorescence (HTRF) assay, immunoblot, and immunoprecipitation (IP) were used to evaluate whether SIAIS361034 is an appropriate Bcl-xL PROTAC. Dual luciferase reporter assay, real-time quantitative PCR (RT-qPCR), depilatory model, and SmoA1 model were established to assess the effect of SIAIS361034 on the activity of Hh signaling pathway and its ability to overcome drug resistance in vitro and in vivo. Molecular mechanisms of SIAIS361034 for inhibiting Hh activity were demonstrated by dual luciferase reporter assay, immunoblot, and immunofluorescence staining. PET-CT and histopathology of bone tissues were used to assess the effects of SIAIS361034 on bone growth. Results: We observed that SIAIS361034 efficiently and selectively inhibits the activity of the Hh pathway in vitro and in vivo, by interrupting Bcl-xL/Sufu interaction, therefore, promoting the interaction of Sufu with Gli1. Moreover, SIAIS361034 possesses the ability of combating resistance to current Smo inhibitors caused by Smo mutations and Gli2 amplification and remarkably inhibits the growth of SmoA1 tumors in vivo. In contrast to von Hippel-Lindau (VHL) E3 ligase, our result further reveals little detectable expression of CRBN in two types of cells critical for bone development, human articular chondrocytes and human fetal osteoblastic cells. Moreover, treatment with SIAIS361034 results in no impairment on the bone growth of young mice, accompanying no alteration of the expression of Bcl-xL and Gli1 proteins. Conclusion: Our findings demonstrate that selectively targeting Bcl-xL by PROTAC is a promising strategy for combating resistance to Smo inhibitors without causing on-target drug toxicities of bone growth.

SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics.

The recent advance of single cell sequencing (scRNA-seq) technology such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) allows researchers to quantify cell surface protein abundance and RNA expression simultaneously at single cell resolution. Although CITE-seq and other similar technologies have gained enormous popularity, novel methods for analyzing this type of single cell multi-omics data are in urgent need. A limited number of available tools utilize data-driven approach, which may undermine the biological importance of surface protein data. In this study, we developed SECANT, a biology-guided SEmi-supervised method for Clustering, classification, and ANnoTation of single-cell multi-omics. SECANT is used to analyze CITE-seq data, or jointly analyze CITE-seq and scRNA-seq data. The novelties of SECANT include (1) using confident cell type label identified from surface protein data as guidance for cell clustering, (2) providing general annotation of confident cell types for each cell cluster, (3) utilizing cells with uncertain or missing cell type label to increase performance, and (4) accurate prediction of confident cell types for scRNA-seq data. Besides, as a model-based approach, SECANT can quantify the uncertainty of the results through easily interpretable posterior probability, and our framework can be potentially extended to handle other types of multi-omics data. We successfully demonstrated the validity and advantages of SECANT via simulation studies and analysis of public and in-house datasets from multiple tissues. We believe this new method will be complementary to existing tools for characterizing novel cell types and make new biological discoveries using single-cell multi-omics data.

Integrative analysis of spatial transcriptome with single-cell transcriptome and single-cell epigenome in mouse lungs after immunization.

Understanding lung immunity requires an unbiased profiling of tissue-resident T cells at their precise anatomical locations within the lung, but such information has not been characterized in the immunized mouse model. In this pilot study, using 10x Genomics Chromium and Visium platform, we performed an integrative analysis of spatial transcriptome with single-cell RNA-seq and single-cell ATAC-seq on lung cells from mice after immunization using a well-established Klebsiella pneumoniae infection model. We built an optimized deconvolution pipeline to accurately decipher specific cell-type compositions by anatomic location. We discovered that combining scATAC-seq and scRNA-seq data may provide more robust cell-type identification, especially for lineage-specific T helper cells. Combining all three modalities, we observed a dynamic change in the location of T helper cells as well as their corresponding chemokines. In summary, our proof-of-principle study demonstrated the power and potential of single-cell multi-omics analysis to uncover spatial- and cell-type-dependent mechanisms of lung immunity.

Comprehensive benchmarking of CITE-seq versus DOGMA-seq single cell multimodal omics.

The recently developed method TEA-seq and similar DOGMA-seq single cell trimodal omics assays provide unprecedented opportunities for understanding cell biology, but independent evaluation is lacking. We explore the utility of DOGMA-seq compared to the bimodal CITE-seq assay in activated and stimulated human peripheral blood T cells. We find that single cell trimodal omics measurements after digitonin (DIG) permeabilization were generally better than after an alternative "low-loss lysis" (LLL) permeabilization condition. Next, we find that DOGMA-seq with optimized DIG permeabilization and its ATAC library provides more information, although its mRNA and cell surface protein libraries have slightly inferior quality, compared to CITE-seq.

Differential gene expression in nasal airway epithelium from overweight or obese youth with asthma.

BACKGROUND: The mechanisms underlying the known link between overweight/obesity and childhood asthma are unclear. We aimed to identify differentially expressed genes and pathways associated with obesity-related asthma through a transcriptomic analysis of nasal airway epithelium. METHODS: We compared the whole transcriptome in nasal airway epithelium of youth with overweight or obesity and asthma with that of youth of normal weight and asthma, using RNA sequencing data from a cohort of 235 Puerto Ricans aged 9-20 years (EVA-PR) and an independent cohort of 66 children aged 6-16 years in Pittsburgh (VDKA). Differential expression analysis adjusting for age, sex, sequencing plate number, and sample sorting protocol, and the first five principal components were performed independently in each cohort. Results from the two cohorts were combined in a transcriptome-wide meta-analysis. Gene enrichment and network analyses were performed on top genes. RESULTS: In the meta-analysis, 29 genes were associated with obesity-related asthma at an FDR-adjusted p <.05, including pro-inflammatory genes known to be differentially expressed in adipose tissue of obese subjects (e.g., CXCL11, CXCL10, and CXCL9) and several novel genes. Functional enrichment analyses showed that pathways for interferon signaling, and innate and adaptive immune responses were down-regulated in overweight/obese youth with asthma, while pathways related to ciliary structure or function were up-regulated. Upstream regulatory analysis predicted significant inhibition of the IRF7 pathway. Network analyses identified "hub" genes like GBP5 and SOCS1. CONCLUSION: Our transcriptome-wide analysis of nasal airway epithelium identified biologically plausible genes and pathways for obesity-related asthma in youth.

ChromInst: A single cell sequencing technique to accomplish pre-implantation comprehensive chromosomal screening overnight.

Next Generation Sequencing (NGS) is a powerful tool getting into the field of clinical examination. Its preliminary application in pre-implantation comprehensive chromosomal screening (PCCS) of assisted reproduction (test-tube baby) has shown encouraging outcomes that improves the success rate of in vitro fertilization. However, the conventional NGS library construction is time consuming. In addition with the whole genome amplification (WGA) procedure in prior, makes the single cell NGS assay hardly be accomplished within an adequately short turnover time in supporting fresh embryo implantation. In this work, we established a concise single cell sequencing protocol, ChromInst, in which the single cell WGA and NGS library construction were integrated into a two-step PCR procedure of ~ 2.5hours reaction time. We then validated the feasibility of ChromInst for overnight PCCS assay by examining 14 voluntary donated embryo biopsy samples in a single sequencing run of Miseq with merely 13M reads production. The good compatibility of ChromInst with the restriction of Illumina sequencing technique along with the good library yield uniformity resulted superior data usage efficiency and reads distribution evenness that ensures precisely distinguish of 6 normal embryos from 8 abnormal one with variable chromosomal aneuploidy. The superior succinctness and effectiveness of this protocol permits its utilization in other time limited single cell NGS applications.

A genome-wide study of DNA methylation in white blood cells and asthma in Latino children and youth.

Latinos are heavily affected with childhood asthma. Little is known about epigenetic mechanisms of asthma in Latino youth. We conducted a meta-analysis of two epigenome-wide association studies (EWAS) of asthma, using DNA from white blood cells (WBCs) from 1,136 Latino children and youth aged 6 to 20 years. Genes near the top CpG sites in this EWAS were examined in a pathway enrichment analysis, and we then assessed whether our results replicated those from publicly available data from three independent EWAS conducted in non-Latino populations. We found that DNA methylation profiles differed between subjects with and without asthma. After adjustment for covariates and multiple testing, two CpGs were differentially methylated at a false discovery rate (FDR)-adjusted P < 0.1, and 193 CpG sites were differentially methylated at FDR-adjusted P < 0.2. The two top CpGs are near genes relevant to inflammatory signalling, including CAMK1D (Calcium/Calmodulin Dependent Protein Kinase ID) and TIGIT (T Cell Immunoreceptor With Ig And ITIM Domains). Moreover, 25 genomic regions were differentially methylated between subjects with and without asthma, at Sidák-corrected P < 0.10. An enrichment analysis then identified the TGF-beta pathway as most relevant to asthma in our analysis, and we replicated some of the top signals from publicly available EWAS datasets in non-Hispanic populations. In conclusion, we have identified novel epigenetic markers of asthma in WBCs from Latino children and youth, while also replicating previous results from studies conducted in non-Latinos.

GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing.

Identifying and removing multiplets are essential to improving the scalability and the reliability of single cell RNA sequencing (scRNA-seq). Multiplets create artificial cell types in the dataset. We propose a Gaussian mixture model-based multiplet identification method, GMM-Demux. GMM-Demux accurately identifies and removes multiplets through sample barcoding, including cell hashing and MULTI-seq. GMM-Demux uses a droplet formation model to authenticate putative cell types discovered from a scRNA-seq dataset. We generate two in-house cell-hashing datasets and compared GMM-Demux against three state-of-the-art sample barcoding classifiers. We show that GMM-Demux is stable and highly accurate and recognizes 9 multiplet-induced fake cell types in a PBMC dataset.

Expression Quantitative Trait Methylation Analysis Reveals Methylomic Associations With Gene Expression in Childhood Asthma.

BACKGROUND: Nasal (airway) epithelial methylation profiles have been associated with asthma, but the effects of such profiles on expression of distant cis-genes are largely unknown. RESEARCH QUESTION: To identify genes whose expression is associated with proximal and distal CpG probes (within 1 Mb), and to assess whether and how such genes are differentially expressed in atopic asthma. STUDY DESIGN AND METHODS: Genome-wide expression quantitative trait methylation (eQTM) analysis in nasal epithelium from Puerto Rican subjects (aged 9-20 years) with (n = 219) and without (n = 236) asthma. After the eQTM analysis, a Gene Ontology Enrichment analysis was conducted for the top 500 eQTM genes, and mediation analyses were performed to identify paths from DNA methylation to atopic asthma through gene expression. Asthma was defined as physician-diagnosed asthma and wheeze in the previous year, and atopy was defined as at least one positive IgE to allergens. Atopic asthma was defined as the presence of both atopy and asthma. RESULTS: We identified 16,867 significant methylation-gene expression pairs (false-discovery rate-adjusted P < .01) in nasal epithelium from study participants. Most eQTM methylation probes were distant (average distance, ∼378 kb) from their target genes, and also more likely to be located in enhancer regions of their target genes in lung tissue than control probes. The top 500 eQTM genes were enriched in pathways for immune processes and epithelial integrity and were more likely to have been previously identified as differentially expressed in atopic asthma. In a mediation analysis, we identified 5,934 paths through which methylation markers could affect atopic asthma through gene expression in nasal epithelium. INTERPRETATION: Previous epigenome-wide association studies of asthma have estimated the effects of DNA methylation markers on expression of nearby genes in airway epithelium. Our findings suggest that distant epigenetic regulation of gene expression in airway epithelium plays a role in atopic asthma.

BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data.

Droplet-based single cell transcriptome sequencing (scRNA-seq) technology, largely represented by the 10× Genomics Chromium system, is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. Despite the rapid advances in technologies, novel statistical methods and computational tools for analyzing multi-modal CITE-Seq data are lacking. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data. Through simulation studies and analysis of public and in-house real data sets, we successfully demonstrated the validity and advantages of this method in fully utilizing both types of data to accurately identify cell clusters. In addition, as a probabilistic model-based approach, BREM-SC is able to quantify the clustering uncertainty for each single cell. This new method will greatly facilitate researchers to jointly study transcriptome and surface proteins at the single cell level to make new biological discoveries, particularly in the area of immunology.

Cryptic indole hydroxylation by a non-canonical terpenoid cyclase parallels bacterial xenobiotic detoxification.

Terpenoid natural products comprise a wide range of molecular architectures that typically result from C-C bond formations catalysed by classical type I/II terpene cyclases. However, the molecular diversity of biologically active terpenoids is substantially increased by fully unrelated, non-canonical terpenoid cyclases. Their evolutionary origin has remained enigmatic. Here we report the in vitro reconstitution of an unusual flavin-dependent bacterial indoloterpenoid cyclase, XiaF, together with a designated flavoenzyme-reductase (XiaP) that mediates a key step in xiamycin biosynthesis. The crystal structure of XiaF with bound FADH2 (at 2.4 Å resolution) and phylogenetic analyses reveal that XiaF is, surprisingly, most closely related to xenobiotic-degrading enzymes. Biotransformation assays show that XiaF is a designated indole hydroxylase that can be used for the production of indigo and indirubin. We unveil a cryptic hydroxylation step that sets the basis for terpenoid cyclization and suggest that the cyclase has evolved from xenobiotics detoxification enzymes.