Repurposing of the enhancer-promoter communication underlies the compensation of Mesp2 by Mesp1

Organisms are inherently equipped with buffering systems against genetic perturbations. Genetic compensation, the compensatory response by upregulating another gene or genes, is one such buffering mechanism. Recently, a well-conserved compensatory mechanism was proposed: transcriptional adaptation of homologs under the nonsense-mediated mRNA decay pathways. However, this model cannot explain the onset of all compensatory events. We report a novel genetic compensation mechanism operating over the Mesp gene locus. Mesp1 and Mesp2 are paralogs located adjacently in the genome. Mesp2 loss is partially rescued by Mesp1 upregulation in the presomitic mesoderm (PSM). Using a cultured PSM induction system, we reproduced the compensatory response in vitro and found that the Mesp2-enhancer is required to promote Mesp1. We revealed that the Mesp2-enhancer directly interacts with the Mesp1 promoter, thereby upregulating Mesp1 expression upon the loss of Mesp2. Of note, this interaction is established by genomic arrangement upon PSM development independently of Mesp2 disruption. We propose that the repurposing of this established enhancer-promoter communication is the mechanism underlying this compensatory response for the upregulation of the adjacent gene.

Systematic identification of ACE2 expression modulators reveals cardiomyopathy as a risk factor for mortality in COVID-19 patients

Background Angiotensin-converting enzyme 2 (ACE2) is the cell-entry receptor for SARS-CoV-2. It plays critical roles in both the transmission and the pathogenesis of COVID-19. Comprehensive profiling of ACE2 expression patterns could reveal risk factors of severe COVID-19 illness. While the expression of ACE2 in healthy human tissues has been well characterized, it is not known which diseases and drugs might be associated with ACE2 expression. Results We develop GENEVA (GENe Expression Variance Analysis), a semi-automated framework for exploring massive amounts of RNA-seq datasets. We apply GENEVA to 286,650 publicly available RNA-seq samples to identify any previously studied experimental conditions that could be directly or indirectly associated with ACE2 expression. We identify multiple drugs, genetic perturbations, and diseases that are associated with the expression of ACE2, including cardiomyopathy, HNF1A overexpression, and drug treatments with RAD140 and itraconazole. Our joint analysis of seven datasets confirms ACE2 upregulation in all cardiomyopathy categories. Using electronic health records data from 3936 COVID-19 patients, we demonstrate that patients with pre-existing cardiomyopathy have an increased mortality risk than age-matched patients with other cardiovascular conditions. GENEVA is applicable to any genes of interest and is freely accessible at http://genevatool.org. Conclusions This study identifies multiple diseases and drugs that are associated with the expression of ACE2. The effect of these conditions should be carefully studied in COVID-19 patients. In particular, our analysis identifies cardiomyopathy patients as a high-risk group, with increased ACE2 expression in the heart and increased mortality after SARS-COV-2 infection.

A kinase translocation reporter reveals real-time dynamics of ERK activity in Drosophila

Extracellular Signal-Regulated Kinase (ERK) lies downstream of a core signalling cascade that controls all aspects of development and adult homeostasis. Recent developments have led to new tools to image and manipulate the pathway. However, visualising ERK activity in vivo with high temporal resolution remains a challenge in Drosophila. We adapted a kinase translocation reporter (KTR) for use in Drosophila, which shuttles out of the nucleus when phosphorylated by ERK. We show that ERK-KTR faithfully reports endogenous ERK signalling activity in developing and adult tissues, and that it responds to genetic perturbations upstream of ERK. Using ERK-KTR in time-lapse imaging, we made two novel observations: firstly, sustained hyperactivation of ERK by expression of dominant-active Epidermal Growth Factor Receptor raised the overall level but did not alter the kinetics of ERK activity; secondly, heterogeneity in ERK activity in retinal basal glia correlated with the direction of migration of individual cells. Our results show that KTR technology can be applied in Drosophila to monitor ERK activity in real-time and suggest that this modular tool can be further adapted to study other kinases.

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

We present a new, carefully designed and well-annotated dataset of images and image-based profiles of cells that have been treated with chemical compounds and genetic perturbations. Each gene that is perturbed is a known target of at least two compounds in the dataset. The dataset can thus serve as a benchmark to evaluate methods for predicting similarities between compounds and between genes and compounds, measuring the effect size of a perturbation, and more generally, learning effective representations for measuring cellular state from microscopy images. Advancements in these applications can accelerate the development of new medicines.

A Foliar Pigment-Based Bioassay for Interrogating Chloroplast Signalling Reveals that Chlorophyll Biosynthesis Requires Carotenoid Isomerisation.

Background: Plastid-derived metabolites can signal control over nuclear gene expression, chloroplast biogenesis, and chlorophyll biosynthesis. Norflurazon (NFZ) inhibition of carotenoid biosynthesis in seedlings can elicit a protoporphyrin retrograde signal that controls chlorophyll and chloroplast biogenesis. Recent evidence reveals that plastid development can be regulated by carotenoid cleavage products called apocarotenoids. The key steps in carotenoid biosynthesis and catabolism that generate apocarotenoid signalling metabolites in foliar tissues remains to be elucidated. Here, we established an Arabidopsis foliar pigment-based bioassay using detached rosettes to differentiate plastid signalling processes in young expanding leaves containing dividing cells with active chloroplast biogenesis, from fully expanded leaves containing mature chloroplasts. Results: We demonstrate that environmental (extended darkness and cold exposure) as well as chemical (norflurazon; NFZ) inhibition of carotenoid biosynthesis can reduce chlorophyll levels in young, but not older leaves following a 24 h of rosette treatment. Mutants that disrupted xanthophyll accumulation, phytohormone biosynthesis (abscisic acid and strigolactone), or enzymatic carotenoid cleavage, did not alter chlorophyll levels in young or old leaves. Perturbations in acyclic cis-carotene biosynthesis revealed that disruption of CAROTENOID ISOMERASE (CRTISO), but not ZETA-CAROTENE ISOMERASE (Z-ISO) activity, reduced chlorophyll levels in young but not older leaves of plants growing under a long photoperiod. NFZ-induced inhibition of PHYTOENE DESATURASE (PDS) activity triggered phytoene accumulation more so in younger relative to older leaves from both WT and the crtiso mutant, indicating a continued substrate supply from the methylerythritol 4-phosphate (MEP) pathway for carotenogenesis. NFZ treatment of WT and crtiso mutant rosettes reveal similar, additive, and opposite effects on individual pigment accumulation.Conclusion: The Arabidopsis foliar pigment-based bioassay was used to differentiate signalling events elicited by environmental, chemical, genetic, and combinations thereof, that control chlorophyll biosynthesis. Genetic perturbations that impaired xanthophyll biosynthesis and/or carotenoid catabolism did not affect chlorophyll biosynthesis. The lack of CAROTENOID ISOMERISATION generated a signal that rate-limited chlorophyll accumulation, but not phytoene biosynthesis in young Arabidopsis leaves exposed to a long photoperiod. Findings generated using this new foliar pigment bioassay implicate that carotenoid isomerisation and NFZ elicit different signalling pathways to control chlorophyll homeostasis in young emerging leaves.

Visualizing pyrazinamide action by live single cell imaging of phagosome acidification and Mycobacterium tuberculosis pH homeostasis

Mycobacterium tuberculosis (Mtb) segregates within multiple subcellular niches with different biochemical and biophysical properties that, upon treatment, may impact antibiotic distribution, accumulation, and efficacy. However, it remains unclear whether fluctuating intracellular microenvironments alter mycobacterial homeostasis and contribute to antibiotic enrichment and efficacy. Here, we describe a live dual-imaging approach to monitor host subcellular acidification and Mtb intrabacterial pH. By combining this approach with pharmacological and genetic perturbations, we show that Mtb can maintain its intracellular pH independently of the surrounding pH in human macrophages. Importantly, unlike bedaquiline (BDQ), isoniazid (INH) or rifampicin (RIF), the drug pyrazinamide (PZA) displays antibacterial efficacy by acting as protonophore which disrupts intrabacterial pH homeostasis in cellulo. By using Mtb mutants, we confirmed that intracellular acidification is a prerequisite for PZA efficacy in cellulo. We anticipate this imaging approach will be useful to identify host cellular environments that affect antibiotic efficacy against intracellular pathogens.

The good, the bad, and the ugly: Evolutionary and pathological aspects of gene dosage alterations

Diploid organisms contain a maternal and a paternal genome complement that is thought to provide robustness and allow developmental progression despite genetic perturbations that occur in heterozygosity. However, changes affecting gene dosage from the chromosome down to the individual gene level possess a significant pathological potential and can lead to developmental disorders (DDs). This indicates that expression from a balanced gene complement is highly relevant for proper cellular and organismal function in eukaryotes. Paradoxically, gene and whole chromosome duplications are a principal driver of evolution, while heteromorphic sex chromosomes (XY and ZW) are naturally occurring aneuploidies important for sex determination. Here, we provide an overview of the biology of gene dosage at the crossroads between evolutionary benefit and pathogenicity during disease. We describe the buffering mechanisms and cellular responses to alterations, which could provide a common ground for the understanding of DDs caused by copy number alterations.

Genetic perturbation enhances functional heterogeneity in alkaline phosphatase

Enzymes inherently exhibit molecule-to-molecule heterogeneity in catalytic activity or function, which underlies the acquisition of new functions in evolutionary processes. However, correlations between the functional heterogeneity of an enzyme and its multi-functionality or promiscuity remain elusive. In addition, the modulation of functional heterogeneity upon genetic perturbation is currently unexplored. Here, we quantitatively analyzed functional heterogeneity in the wild-type and 69 single-point mutants of Escherichia coli alkaline phosphatase (AP) by employing single-molecule assay with a femtoliter reactor array device. Most mutant enzymes exhibited higher functional heterogeneity than the wild-type enzyme, irrespective of catalytic activity. These results indicated that the wild-type AP minimizes functional heterogeneity, and single-point mutations can significantly expand the span of functional heterogeneity in AP. Moreover, we identified a clear correlation between functional heterogeneity and promiscuous activities. These findings suggest that enzymes can acquire greater functional heterogeneity following marginal genetic perturbations that concomitantly promote catalytic promiscuity.

A deep learning framework for quantitative analysis of actin microridges

Microridges are evolutionarily conserved actin-rich protrusions present on the apical surface of the squamous epithelial cells. In zebrafish epidermal cells, microridges form self-evolving patterns due to the underlying actomyosin network dynamics. However, their morphological and dynamic characteristics have remained poorly understood owing to lack of automated segmentation methods. We achieved ~97% pixel-level accuracy with the deep learning microridge segmentation strategy enabling quantitative insights into their bio-physical-mechanical characteristics. From the segmented images, we estimated an effective microridge persistence length as ~0.61μm. We discovered the presence of mechanical fluctuations and found relatively greater stresses stored within patterns of yolk than flank, indicating distinct regulation of their actomyosin networks. Furthermore, spontaneous formations and positional fluctuations of actin clusters within microridge influenced pattern rearrangements over short length/time-scales. Our framework allows large-scale spatiotemporal analysis of microridges during epithelial development and probing of their responses to chemical and genetic perturbations to unravel the underlying patterning mechanisms.

Label-free prediction of Cell Painting from brightfield images

Cell Painting is a high-content image-based assay which can reveal rich cellular morphology and is applied in drug discovery to predict bioactivity, assess toxicity and understand diverse mechanisms of action of chemical and genetic perturbations. In this study, we investigate label-free Cell Painting by predicting the five fluorescent Cell Painting channels from paired brightfield z-stacks using deep learning models. We train and validate the models with a dataset representing 1000s of pan-assay interference compounds sampled from 17 unique batches. The model predictions are evaluated using a test set from two additional batches, treated with compounds comprised from a publicly available phenotypic set. In addition to pixel-level evaluation, we process the label-free Cell Painting images with a segmentation-based feature-extraction pipeline to understand whether the generated images are useful in downstream analysis. The mean Pearson correlation coefficient (PCC) of the images across all five channels is 0.84. Without actually incorporating these features into the model training we achieved a mean correlation of 0.45 from the features extracted from the images. Additionally we identified 30 features which correlated greater than 0.8 to the ground truth. Toxicity analysis on the label-free Cell Painting resulted a sensitivity of 62.5% and specificity of 99.3% on images from unseen batches. Additionally, we provide a breakdown of the feature profiles by channel and feature type to understand the potential and limitation of the approach in morphological profiling. Our findings demonstrate that label-free Cell Painting has potential above the improved visualization of cellular components, and it can be used for downstream analysis. The findings also suggest that label-free Cell Painting could allow for repurposing the imaging channels for other non-generic fluorescent stains of more targeted biological interest, thus increasing the information content of the assay.