Evaluating batch correction methods for image-based cell profiling.

High-throughput image-based profiling platforms are powerful technologies capable of collecting data from billions of cells exposed to thousands of perturbations in a time- and cost-effective manner. Therefore, image-based profiling data has been increasingly used for diverse biological applications, such as predicting drug mechanism of action or gene function. However, batch effects severely limit community-wide efforts to integrate and interpret image-based profiling data collected across different laboratories and equipment. To address this problem, we benchmark ten high-performing single-cell RNA sequencing (scRNA-seq) batch correction techniques, representing diverse approaches, using a newly released Cell Painting dataset, JUMP. We focus on five scenarios with varying complexity, ranging from batches prepared in a single lab over time to batches imaged using different microscopes in multiple labs. We find that Harmony and Seurat RPCA are noteworthy, consistently ranking among the top three methods for all tested scenarios while maintaining computational efficiency. Our proposed framework, benchmark, and metrics can be used to assess new batch correction methods in the future. This work paves the way for improvements that enable the community to make the best use of public Cell Painting data for scientific discovery.

Evaluating batch correction methods for image-based cell profiling.

High-throughput image-based profiling platforms are powerful technologies capable of collecting data from billions of cells exposed to thousands of perturbations in a time- and cost-effective manner. Therefore, image-based profiling data has been increasingly used for diverse biological applications, such as predicting drug mechanism of action or gene function. However, batch effects pose severe limitations to community-wide efforts to integrate and interpret image-based profiling data collected across different laboratories and equipment. To address this problem, we benchmarked seven high-performing scRNA-seq batch correction techniques, representing diverse approaches, using a newly released Cell Painting dataset, the largest publicly accessible image-based dataset. We focused on five different scenarios with varying complexity, and we found that Harmony, a mixture-model based method, consistently outperformed the other tested methods. Our proposed framework, benchmark, and metrics can additionally be used to assess new batch correction methods in the future. Overall, this work paves the way for improvements that allow the community to make best use of public Cell Painting data for scientific discovery.

Transferable Immunoglobulin A-Coated Odoribacter splanchnicus in Responders to Fecal Microbiota Transplantation for Ulcerative Colitis Limits Colonic Inflammation.

BACKGROUND & AIMS: Fecal microbiota transplantation (FMT) is an emerging treatment modality for ulcerative colitis (UC). Several randomized controlled trials have shown efficacy for FMT in the treatment of UC, but a better understanding of the transferable microbiota and their immune impact is needed to develop more efficient microbiome-based therapies for UC. METHODS: Metagenomic analysis and strain tracking was performed on 60 donor and recipient samples receiving FMT for active UC. Sorting and sequencing of immunoglobulin (Ig) A-coated microbiota (called IgA-seq) was used to define immune-reactive microbiota. Colonization of germ-free or genetically engineered mice with patient-derived strains was performed to determine the mechanism of microbial impact on intestinal immunity. RESULTS: Metagenomic analysis defined a core set of donor-derived transferable bacterial strains in UC subjects achieving clinical response, which predicted response in an independent trial of FMT for UC. IgA-seq of FMT recipient samples and gnotobiotic mice colonized with donor microbiota identified Odoribacter splanchnicus as a transferable strain shaping mucosal immunity, which correlated with clinical response and the induction of mucosal regulatory T cells. Colonization of mice with O splanchnicus led to an increase in Foxp3+/RORγt+ regulatory T cells, induction of interleukin (IL) 10, and production of short chain fatty acids, all of which were required for O splanchnicus to limit colitis in mouse models. CONCLUSIONS: This work provides the first evidence of transferable, donor-derived strains that correlate with clinical response to FMT in UC and reveals O splanchnicus as a key component promoting both metabolic and immune cell protection from colitis. These mechanistic features will help enable strategies to enhance the efficacy of microbial therapy for UC. Clinicaltrials.gov ID NCT02516384.

A Bronchoscope Localization Method Using an Augmented Reality Co-Display of Real Bronchoscopy Images with a Virtual 3D Bronchial Tree Model.

In recent years, Image-Guide Navigation Systems (IGNS) have become an important tool for various surgical operations. In the preparations for planning a surgical path, verifying the location of a lesion, etc., it is an essential tool; in operations such as bronchoscopy, which is the procedure for the inspection and retrieval of diagnostic samples for lung-related surgeries, it is even more so. The IGNS for bronchoscopy uses 2D-based images from a flexible bronchoscope to navigate through the bronchial airways in order to reach the targeted location. In this procedure, the accurate localization of the scope becomes very important, because incorrect information could potentially cause a surgeon to mistakenly direct the scope down the wrong passage. It would be a great aid for the surgeon to be able to visualize the bronchoscope images alongside the current location of the bronchoscope. For this purpose, in this paper, we propose a novel registration method to match real bronchoscopy images with virtual bronchoscope images from a 3D bronchial tree model built using computed tomography (CT) image stacks in order to obtain the current 3D position of the bronchoscope in the airways. This method is a combination of a novel position-tracking method using the current frames from the bronchoscope and the verification of the position of the real bronchoscope image against an image extracted from the 3D model using an adaptive-network-based fuzzy inference system (ANFIS)-based image matching method. Experimental results show that the proposed method performs better than the other methods used in the comparison.

Retrospective analysis of model-based predictivity of human pharmacokinetics for anti-IL-36R monoclonal antibody MAB92 using a rat anti-mouse IL-36R monoclonal antibody and RNA expression data (FANTOM5).

Accurate prediction of the human pharmacokinetics (PK) of a candidate monoclonal antibody from nonclinical data is critical to maximize the success of clinical trials. However, for monoclonal antibodies exhibiting nonlinear clearance due to target-mediated drug disposition, PK predictions are particularly challenging. That challenge is further compounded for molecules lacking cross-reactivity in a nonhuman primate, in which case a surrogate antibody selective for the target in rodent may be required. For these cases, prediction of human PK must account for any interspecies differences in binding kinetics, target expression, target turnover, and potentially epitope. We present here a model-based method for predicting the human PK of MAB92 (also known as BI 655130), a humanized IgG1 κ monoclonal antibody directed against human IL-36R. Preclinical PK was generated in the mouse with a chimeric rat anti-mouse IgG2a surrogate antibody cross-reactive against mouse IL-36R. Target-specific parameters such as antibody binding affinity (KD), internalization rate of the drug target complex (kint), target degradation rate (kdeg), and target abundance (R0) were integrated into the model. Two different methods of assigning human R0 were evaluated: the first assumed comparable expression between human and mouse and the second used high-resolution mRNA transcriptome data (FANTOM5) as a surrogate for expression. Utilizing the mouse R0 to predict human PK, AUC0-∞ was substantially underpredicted for nonsaturating doses; however, after correcting for differences in RNA transcriptome between species, AUC0-∞ was predicted largely within 1.5-fold of observations in first-in-human studies, demonstrating the validity of the modeling approach. Our results suggest that semi-mechanistic models incorporating RNA transcriptome data and target-specific parameters may improve the predictivity of first-in-human PK.

Generation and functional characterization of anti-human and anti-mouse IL-36R antagonist monoclonal antibodies.

Deficiency of interleukin (IL)-36 receptor antagonist (DITRA) syndrome is a rare autosomal recessive disease caused by mutations in IL36RN. IL-36R is a cell surface receptor and a member of the IL1R family that is involved in inflammatory responses triggered in skin and other epithelial tissues. Accumulating evidence suggests that IL-36R signaling may play a role in the pathogenesis of psoriasis. Therapeutic intervention of IL-36R signaling offers an innovative treatment paradigm for targeting epithelial cell-mediated inflammatory diseases such as the life-threatening psoriasis variant called generalized pustular psoriasis (GPP). We report the discovery and characterization of MAB92, a potent, high affinity anti-human IL-36 receptor antagonistic antibody that blocks human IL-36 ligand (α, ß and γ)-mediated signaling. In vitro treatment with MAB92 directly inhibits human IL-36R-mediated signaling and inflammatory cytokine production in primary human keratinocytes and dermal fibroblasts. MAB92 shows exquisite species specificity toward human IL-36R and does not cross react to murine IL-36R. To enable in vivo pharmacology studies, we developed a mouse cross-reactive antibody, MAB04, which exhibits overlapping binding and pharmacological activity as MAB92. Epitope mapping indicates that MAB92 and MAB04 bind primarily to domain-2 of the human and mouse IL-36R proteins, respectively. Treatment with MAB04 abrogates imiquimod and IL-36-mediated skin inflammation in the mouse, further supporting an important role for IL-36R signaling in epithelial cell-mediated inflammation.

Signal Transduction and Intracellular Trafficking by the Interleukin 36 Receptor.

Improper signaling of the IL-36 receptor (IL-36R), a member of the IL-1 receptor family, has been associated with various inflammation-associated diseases. However, the requirements for IL-36R signal transduction remain poorly characterized. This work seeks to define the requirements for IL-36R signaling and intracellular trafficking. In the absence of cognate agonists, IL-36R was endocytosed and recycled to the plasma membrane. In the presence of IL-36, IL-36R increased accumulation in LAMP1+ lysosomes. Endocytosis predominantly used a clathrin-mediated pathway, and the accumulation of the IL-36R in lysosomes did not result in increased receptor turnover. The ubiquitin-binding Tollip protein contributed to IL-36R signaling and increased the accumulation of both subunits of the IL-36R.

Small-molecule ghrelin receptor antagonists improve glucose tolerance, suppress appetite, and promote weight loss.

Ghrelin, through action on its receptor, GH secretagogue receptor type 1a (GHS-R1a), exerts a variety of metabolic functions including stimulation of appetite and weight gain and suppression of insulin secretion. In the present study, we examined the effects of novel small-molecule GHS-R1a antagonists on insulin secretion, glucose tolerance, and weight loss. Ghrelin dose-dependently suppressed insulin secretion from dispersed rat islets. This effect was fully blocked by a GHS-R1a antagonist. Consistent with this observation, a single oral dose of a GHS-R1a antagonist improved glucose homeostasis in an ip glucose tolerance test in rat. Improvement in glucose tolerance was attributed to increased insulin secretion. Daily oral administration of a GHS-R1a antagonist to diet-induced obese mice led to reduced food intake and weight loss (up to 15%) due to selective loss of fat mass. Pair-feeding experiments indicated that weight loss was largely a consequence of reduced food intake. The impact of a GHS-R1a antagonist on gastric emptying was also examined. Although the GHS-R1a antagonist modestly delayed gastric emptying at the highest dose tested (10 mg/kg), delayed gastric emptying does not appear to be a requirement for weight loss because lower doses produced weight loss without an effect on gastric emptying. Consistent with the hypothesis that ghrelin regulates feeding centrally, the anorexigenic effects of potent GHS-R1a antagonists in mice appeared to correspond with their brain exposure. These observations demonstrate that GHS-R1a antagonists have the potential to improve the diabetic condition by promoting glucose-dependent insulin secretion and promoting weight loss.

Optimization of imidazole amide derivatives as cannabinoid-1 receptor antagonists for the treatment of obesity.

Several imidazole-based cyclohexyl amides were identified as potent CB-1 antagonists, but they exhibited poor oral exposure in rodents. Incorporation of a hydroxyl moiety on the cyclohexyl ring provided a dramatic improvement in oral exposure, together with a ca. 10-fold decrease in potency. Further optimization provided the imidazole 2-hydroxy-cyclohexyl amide 45, which exhibited hCB-1 K(i)=3.7nM, and caused significant appetite suppression and robust, dose-dependent reduction of body weight gain in industry-standard rat models.

Constrained analogs of CB-1 antagonists: 1,5,6,7-Tetrahydro-4H-pyrrolo[3,2-c]pyridine-4-one derivatives.

A series of pyrrolopyridinones was designed and synthesized as constrained analogs of the pyrazole CB-1 antagonist rimonabant. Certain examples exhibited very potent hCB-1 receptor binding affinity and functional antagonism with Ki and Kb values below 10 nM, and with high selectivity for CB-1 over CB-2 (>100-fold). A representative analog was established to cause significant appetite suppression and reduction in body weight gain in industry-standard rat models used to develop new therapeutics for obesity.