Charting human development using a multi-endodermal organ atlas and organoid models.

Organs are composed of diverse cell types that traverse transient states during organogenesis. To interrogate this diversity during human development, we generate a single-cell transcriptome atlas from multiple developing endodermal organs of the respiratory and gastrointestinal tract. We illuminate cell states, transcription factors, and organ-specific epithelial stem cell and mesenchyme interactions across lineages. We implement the atlas as a high-dimensional search space to benchmark human pluripotent stem cell (hPSC)-derived intestinal organoids (HIOs) under multiple culture conditions. We show that HIOs recapitulate reference cell states and use HIOs to reconstruct the molecular dynamics of intestinal epithelium and mesenchyme emergence. We show that the mesenchyme-derived niche cue NRG1 enhances intestinal stem cell maturation in vitro and that the homeobox transcription factor CDX2 is required for regionalization of intestinal epithelium and mesenchyme in humans. This work combines cell atlases and organoid technologies to understand how human organ development is orchestrated.

VisuStatR: visualizing motility and morphology statistics on images in R.

MOTIVATION: Live-cell microscopy has become an essential tool for analyzing dynamic processes in various biological applications. Thereby, high-throughput and automated tracking analyses allow the simultaneous evaluation of large numbers of objects. However, to critically assess the influence of individual objects on calculated summary statistics, and to detect heterogeneous dynamics or possible artifacts, such as misclassified or -tracked objects, a direct mapping of gained statistical information onto the actual image data would be necessary. RESULTS: We present VisuStatR as a platform independent software package that allows the direct visualization of time-resolved summary statistics of morphological characteristics or motility dynamics onto raw images. The software contains several display modes to compare user-defined summary statistics and the underlying image data in various levels of detail. AVAILABILITY AND IMPLEMENTATION: VisuStatR is a free and open-source R-package, containing a user-friendly graphical-user interface and is available via GitHub at https://github.com/grrchrr/VisuStatR/ under the MIT+ license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multimodal spatiotemporal phenotyping of human retinal organoid development.

Organoids generated from human pluripotent stem cells provide experimental systems to study development and disease, but quantitative measurements across different spatial scales and molecular modalities are lacking. In this study, we generated multiplexed protein maps over a retinal organoid time course and primary adult human retinal tissue. We developed a toolkit to visualize progenitor and neuron location, the spatial arrangements of extracellular and subcellular components and global patterning in each organoid and primary tissue. In addition, we generated a single-cell transcriptome and chromatin accessibility timecourse dataset and inferred a gene regulatory network underlying organoid development. We integrated genomic data with spatially segmented nuclei into a multimodal atlas to explore organoid patterning and retinal ganglion cell (RGC) spatial neighborhoods, highlighting pathways involved in RGC cell death and showing that mosaic genetic perturbations in retinal organoids provide insight into cell fate regulation.

A framework for automated time-resolved analysis of cell colony growth after irradiation.

Understanding dose-dependent survival of irradiated cells is a pivotal goal in radiotherapy and radiobiology. To this end, the clonogenic assay is the standard in vitro method, classifying colonies into either clonogenic or non-clonogenic based on a size threshold at a fixed time. Here we developed a methodological framework for the automated analysis of time course live-cell image data to examine in detail the growth dynamics of large numbers of colonies that occur during such an experiment. We developed a segmentation procedure that exploits the characteristic composition of phase-contrast images to identify individual colonies. Colony tracking allowed us to characterize colony growth dynamics as a function of dose by extracting essential information: (a) colony size distributions across time; (b) fractions of differential growth behavior; and (c) distributions of colony growth rates across all tested doses. We analyzed three data sets from two cell lines (H3122 and RENCA) and made consistent observations in line with already published results: (i) colony growth rates are normally distributed with a large variance; (ii) with increasing dose, the fraction of exponentially growing colonies decreases, whereas the fraction of delayed abortive colonies increases; as a novel finding, we observed that (iii) mean exponential growth rates decrease linearly with increasing dose across the tested range (0-10 Gy). The presented method is a powerful tool to examine live colony growth on a large scale and will help to deepen our understanding of the dynamic, stochastic processes underlying the radiation response in vitro.

Development of Helicobacter pylori Whole-Proteome Arrays and Identification of Serologic Biomarkers for Noncardia Gastric Cancer in the MCC-Spain Study.

BACKGROUND: Helicobacter pylori (H. pylori) is a bacterial carcinogen and the leading risk factor for noncardia gastric cancer (NCGC). Detecting antibodies against specific H. pylori proteins in peripheral blood can be applied to characterize infection and determine disease associations. Most studies analyzing the association between H. pylori infection and gastric cancer have focused on previously identified antigens, predominantly the virulence factor cytotoxin-associated gene A (CagA). Selecting antigens in an unbiased approach may, however, allow the identification of novel biomarkers. METHODS: Using a combination of multiple spotting technique and cell-free, on-chip protein expression, we displayed the H. pylori genome (strain 26695) on high-density microarrays. Immunogenic proteins were identified by serum pool incubations and henceforth analyzed in individual samples. To test its applicability, we used sera from a multicase-control (MCC)-Spain study. Serologic responses between NCGC cases and controls were assessed by conditional logistic regression estimating ORs and 95% confidence intervals. RESULTS: We successfully expressed 93% of the 1,440 H. pylori open reading frames in situ. Of these, 231 (17%) were found to be immunogenic. By comparing 58 NCGC cases with 58 matched controls, we confirmed a higher seroprevalence of CagA among cases (66%) than controls (31%). We further identified a potential novel marker, the Helicobacter outer membrane protein A (HopA). CONCLUSIONS: In this study, we provide evidence that our H. pylori whole-proteome microarray offers a platform for unbiased de novo identification of serologic biomarkers. IMPACT: Given its versatile workflow, antibody responses against other H. pylori strains and possible associations with diverse H. pylori-related outcomes can be systematically analyzed.

Structures of GapR reveal a central channel which could accommodate B-DNA.

GapR is a nucleoid-associated protein required for the cell cycle of Caulobacter cresentus. We have determined new crystal structures of GapR to high resolution. As in a recently published structure, a GapR monomer folds into one long N-terminal α helix and two shorter α helices, and assembles into a tetrameric ring with a closed, positively charged, central channel. In contrast to the conclusions drawn from the published structures, we observe that the central channel of the tetramer presented here could freely accommodate B-DNA. Mutation of six conserved lysine residues lining the cavity and electrophoretic mobility gel shift experiments confirmed their role in DNA binding and the channel as the site of DNA binding. Although present in our crystals, DNA could not be observed in the electron density maps, suggesting that DNA binding is non-specific, which could be important for tetramer-ring translocation along the chromosome. In conjunction with previous GapR structures we propose a model for DNA binding and translocation that explains key published observations on GapR and its biological functions.

Chlamydia trachomatis Whole-Proteome Microarray Analysis of The Netherlands Chlamydia Cohort Study.

Chlamydia trachomatis (Ct) whole-proteome microarrays were utilized to identify antibody patterns associated with infection; pelvic inflammatory disease (PID), tubal factor infertility, chronic pelvic pain (CPP) and ectopic pregnancy in a subsample of the Netherlands Chlamydia cohort study. Serum pools were analyzed on whole-proteome arrays. The 121 most reactive antigens identified during whole-proteome arrays were selected for further analysis with minimized microarrays that allowed for single sera analysis. From the 232 single sera; 145 (62.5%) serum samples were reactive for at least one antigen. To discriminate between positive and negative serum samples; we created a panel of in total 18 antigens which identified 96% of all microarray positive samples. Antigens CT_858; CT_813 and CT_142 were most reactive. Comparison of antibody reactivity's among women with and without Ct related sequelae revealed that the reactivity of CT_813 and CT_142 was less common among women with PID compared to women without (29.0% versus 58.6%, p = 0.005 and 25.8% versus 50.6%, p = 0.017 respectively). CT_858 was less common among CPP cases compared to controls (33.3% versus 58.6; p = 0.028). Using a whole-proteome array to select antigens for minimized arrays allows for the identification of novel informative antigens as general infection markers or disease associated antigens.

Post-treatment human papillomavirus antibody kinetics in cervical cancer patients.

Antibodies to the E6 and E7 oncoproteins of high-risk human papillomavirus (HPV) types are strongly associated with HPV-driven cancer, while antibodies against the capsid protein L1 are considered cumulative exposure markers. To test the hypothesis that L1 antibody levels are stable over time, whereas E6 and E7 levels undergo decay after cervical cancer (CxCa) treatment, we performed multiplex serology for HPV16 and 18 antigens E6, E7 and L1 in a post-treatment study of 184 patients with invasive CxCa that were characterized with a median follow-up time of 725 days, and 2-12 sera per patient. Antibody titers significantly decreased within the first six months for HPV16 E6 and E7 but not L1, and stabilized for the following 12 months on a high level, with few patients showing seroreversion. Of 67 patients seropositive for HPV16 E6 at diagnosis, 28 (41.8%) showed a decrease in antibody titers of at least 50% within the first 18 months. Similarly, of 50 HPV16 E7 seropositives, 33 (66.0%) showed decreasing antibody levels, whereas antibody decay was less frequent for HPV16 L1 (12 of 47, 25.5%). Using a power-law mathematical model to characterize antibody decay kinetics, the mean (±s.e.) durations to a 50% reduction in antibody titers within individual patients were estimated to be 56.9 (±26.1) and 56.3 (±19.0) days for HPV16 E6 and E7, respectively. In summary, HPV16 E6 and E7 antibodies undergo a slow but significant decrease in antibody titers within the first 6-18 months following CxCa treatment. However, larger studies are needed to confirm the utility of serology for prediction of disease progression and time to relapse based on antibody decay kinetics. This article is part of the theme issue 'Silent cancer agents: multi-disciplinary modelling of human DNA oncoviruses'.