A versatile information retrieval framework for evaluating profile strength and similarity.

In profiling assays, thousands of biological properties are measured in a single test, yielding biological discoveries by capturing the state of a cell population, often at the single-cell level. However, for profiling datasets, it has been challenging to evaluate the phenotypic activity of a sample and the phenotypic consistency among samples, due to profiles' high dimensionality, heterogeneous nature, and non-linear properties. Existing methods leave researchers uncertain where to draw boundaries between meaningful biological response and technical noise. Here, we developed a statistical framework that uses the well-established mean average precision (mAP) as a single, data-driven metric to bridge this gap. We validated the mAP framework against established metrics through simulations and real-world data applications, revealing its ability to capture subtle and meaningful biological differences in cell state. Specifically, we used mAP to assess both phenotypic activity for a given perturbation (or a sample) as well as consistency within groups of perturbations (or samples) across diverse high-dimensional datasets. We evaluated the framework on different profile types (image, protein, and mRNA profiles), perturbation types (CRISPR gene editing, gene overexpression, and small molecules), and profile resolutions (single-cell and bulk). Our open-source software allows this framework to be applied to identify interesting biological phenomena and promising therapeutics from large-scale profiling data.

Reproducible image-based profiling with Pycytominer.

Technological advances in high-throughput microscopy have facilitated the acquisition of cell images at a rapid pace, and data pipelines can now extract and process thousands of image-based features from microscopy images. These features represent valuable single-cell phenotypes that contain information about cell state and biological processes. The use of these features for biological discovery is known as image-based or morphological profiling. However, these raw features need processing before use and image-based profiling lacks scalable and reproducible open-source software. Inconsistent processing across studies makes it difficult to compare datasets and processing steps, further delaying the development of optimal pipelines, methods, and analyses. To address these issues, we present Pycytominer, an open-source software package with a vibrant community that establishes an image-based profiling standard. Pycytominer has a simple, user-friendly Application Programming Interface (API) that implements image-based profiling functions for processing high-dimensional morphological features extracted from microscopy images of cells. Establishing Pycytominer as a standard image-based profiling toolkit ensures consistent data processing pipelines with data provenance, therefore minimizing potential inconsistencies and enabling researchers to confidently derive accurate conclusions and discover novel insights from their data, thus driving progress in our field.

Drug screens of NGLY1 deficiency in worm and fly models reveal catecholamine, NRF2 and anti-inflammatory-pathway activation as potential clinical approaches.

N-glycanase 1 (NGLY1) deficiency is an ultra-rare and complex monogenic glycosylation disorder that affects fewer than 40 patients globally. NGLY1 deficiency has been studied in model organisms such as yeast, worms, flies and mice. Proteasomal and mitochondrial homeostasis gene networks are controlled by the evolutionarily conserved transcriptional regulator NRF1, whose activity requires deglycosylation by NGLY1. Hypersensitivity to the proteasome inhibitor bortezomib is a common phenotype observed in whole-animal and cellular models of NGLY1 deficiency. Here, we describe unbiased phenotypic drug screens to identify FDA-approved drugs that are generally recognized as safe natural products, and novel chemical entities, that rescue growth and development of NGLY1-deficient worm and fly larvae treated with a toxic dose of bortezomib. We used image-based larval size and number assays for use in screens of a 2560-member drug-repurposing library and a 20,240-member lead-discovery library. A total of 91 validated hit compounds from primary invertebrate screens were tested in a human cell line in an NRF2 activity assay. NRF2 is a transcriptional regulator that regulates cellular redox homeostasis, and it can compensate for loss of NRF1. Plant-based polyphenols make up the largest class of hit compounds and NRF2 inducers. Catecholamines and catecholamine receptor activators make up the second largest class of hits. Steroidal and non-steroidal anti-inflammatory drugs make up the third largest class. Only one compound was active in all assays and species: the atypical antipsychotic and dopamine receptor agonist aripiprazole. Worm and fly models of NGLY1 deficiency validate therapeutic rationales for activation of NRF2 and anti-inflammatory pathways based on results in mice and human cell models, and suggest a novel therapeutic rationale for boosting catecholamine levels and/or signaling in the brain.

Repurposing the aldose reductase inhibitor and diabetic neuropathy drug epalrestat for the congenital disorder of glycosylation PMM2-CDG.

Phosphomannomutase 2 deficiency, or PMM2-CDG, is the most common congenital disorder of glycosylation and affects over 1000 patients globally. There are no approved drugs that treat the symptoms or root cause of PMM2-CDG. To identify clinically actionable compounds that boost human PMM2 enzyme function, we performed a multispecies drug repurposing screen using a novel worm model of PMM2-CDG, followed by PMM2 enzyme functional studies in PMM2-CDG patient fibroblasts. Drug repurposing candidates from this study, and drug repurposing candidates from a previously published study using yeast models of PMM2-CDG, were tested for their effect on human PMM2 enzyme activity in PMM2-CDG fibroblasts. Of the 20 repurposing candidates discovered in the worm-based phenotypic screen, 12 were plant-based polyphenols. Insights from structure-activity relationships revealed epalrestat, the only antidiabetic aldose reductase inhibitor approved for use in humans, as a first-in-class PMM2 enzyme activator. Epalrestat increased PMM2 enzymatic activity in four PMM2-CDG patient fibroblast lines with genotypes R141H/F119L, R141H/E139K, R141H/N216I and R141H/F183S. PMM2 enzyme activity gains ranged from 30% to 400% over baseline, depending on genotype. Pharmacological inhibition of aldose reductase by epalrestat may shunt glucose from the polyol pathway to glucose-1,6-bisphosphate, which is an endogenous stabilizer and coactivator of PMM2 homodimerization. Epalrestat is a safe, oral and brain penetrant drug that was approved 27 years ago in Japan to treat diabetic neuropathy in geriatric populations. We demonstrate that epalrestat is the first small molecule activator of PMM2 enzyme activity with the potential to treat peripheral neuropathy and correct the underlying enzyme deficiency in a majority of pediatric and adult PMM2-CDG patients.