Biology subjects

Arevalo, J.

Publications and source records attributed to Arevalo, J..

15 recordsLinked to original sources

bioRxiv2025

Alternate dyes for image-based profiling assays

BackgroundCell Painting, the leading image-based profiling assay, involves staining plated cells with six dyes that mark the different compartments in a cell. Such profiles can then be used to discover connections between samples (whether different cell lines, different genetic treatments, or different compound treatments) as well as to assess particular features impacted by each treatment. Researchers may wish to vary the standard dye panel to assess particular phenotypes, or image cells live while maintaining the ability to cluster profiles overall. MethodsIn this study, we evaluate the performance of dyes that can either replace or augment the traditional Cell Painting dyes or enable tracking live cell dynamics. We perturbed U2OS cells with 90 different compounds and subsequently stained them with either standard Cell Painting dyes (Revvity), or with MitoBrilliant (Tocris) replacing MitoTracker or Phenovue phalloidin 400LS (Revvity) replacing phalloidin. We also tested the live-cell compatible ChromaLive dye (Saguaro). ResultsAll dye sets effectively separated biological replicates of the same sample vs. negative controls (phenotypic activity), although separating from replicates of all other compounds (phenotypic distinctiveness) proved challenging for all dye sets. While individual dye substitutions within the standard Cell Painting panel had minimal impact on assay performance, the live cell dye exhibited distinct performance profiles across different compound classes compared to the standard panel, with later time points more distinct than earlier ones. DiscussionSubstituting MitoBrilliant or Phenovue phalloidin 400LS for standard mitochondrial or actin dyes minimally impacted Cell Painting assay performance. Phenovue phalloidin 400LS offers the advantage of isolating actin features from Golgi or plasma membrane while accommodating an additional 568nm dye. Live cell imaging, enabled by ChromaLive dye, provides real-time assessment of compound-induced morphological changes. Combining this with the standard Cell Painting assay significantly expands the feature space for enhanced cellular profiling. Our findings provide data-driven options for researchers selecting dye sets for image-based profiling.

cell biology↗

bioRxiv2024

Morphological map of under- and over-expression of genes in human cells

Cell Painting images offer valuable insights into a cells state and enable many biological applications, but publicly available arrayed datasets only include hundreds of genes perturbed. The JUMP (Joint Undertaking in Morphological Profiling) Cell Painting Consortium perturbed roughly 75% of the protein-coding genome in human U-2 OS cells, generating a rich resource of single-cell images and extracted features. These profiles capture the phenotypic impacts of perturbing 15,243 human genes, including overexpressing 12,609 genes (using open reading frames, ORFs) and knocking out 7,975 genes (using CRISPR-Cas9). We mitigated technical artifacts by rigorously evaluating data processing options and validated the datasets robustness and biological relevance. Analysis of phenotypic profiles revealed novel gene clusters and functional relationships, including those associated with mitochondrial function, cancer, and neural processes. The JUMP Cell Painting genetic dataset is a valuable resource for exploring gene relationships and uncovering novel functions.

bioinformatics↗

bioRxiv2024

Cell morphological representations of genes enhance prediction of drug targets

Identifying a chemicals mechanism of action on biological systems is critical for drug development. A compounds mechanism can sometimes be identified by matching its image-based morphological profile to a well-annotated library. We enhance this approach by incorporating gene representations, demonstrating improved classification performance compared to direct matching methods. These representations are generated using morphological profiles of cells with artificially altered gene expression. A transformer model is trained to classify gene-compound pairs as true or false interactions, using both gene and compound profiles. The model then ranks likely target genes for unseen compounds. The strategy performs well for compounds targeting known genes but has limited effectiveness for novel targets, likely due to the current dataset size. However, the performance increase over existing profile-matching methods is notable. Future work with expanded datasets may enhance predictive capabilities, potentially accelerating early-stage drug discovery by improving target identification for novel compounds.

bioinformatics↗

bioRxiv2024

Evolutionary genomics of a zoonotic parasite across the Neotropical Realm

The Neotropical realm, one of the most biodiverse regions on Earth, houses a broad range of zoonoses that pose serious public health threats. Protozoan parasites of the Leishmania (Viannia) braziliensis species complex cause zoonotic leishmaniasis in Latin America with clinical symptoms ranging from simple cutaneous to destructive, disfiguring mucosal lesions. We present the first comprehensive genome-wide continental study including 257 cultivated isolates representing most of the geographical distribution of this major human pathogen. The L. braziliensis species complex is genetically highly heterogeneous, consisting of divergent parasite groups that are associated with different environments and vary greatly in diversity. Apart from several small ecologically isolated groups with little diversity, our sampling identifies two major parasite groups, one associated with the Amazon and the other with the Atlantic Forest biomes. These groups show different recombination histories, as suggested by high levels of heterozygosity and effective population sizes in the Amazonian group in contrast to high levels of linkage and clonality in the Atlantic group. We argue that these differences are linked to strong eco-epidemiological differences between the two regions. In contrast to geographically focused studies, our study provides a broad understanding of the molecular epidemiology of zoonotic parasites circulating in tropical America.

evolutionary biology↗

bioRxiv2024

A versatile information retrieval framework for evaluating profile strength and similarity

In profiling assays, thousands of biological properties are measured across many samples, 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.

bioinformatics↗

bioRxiv2023

Capturing cell heterogeneity in representations of cell populations for image-based profiling using contrastive learning

Image-based cell profiling is a powerful tool that compares perturbed cell populations by measuring thousands of single-cell features and summarizing them into profiles. Typically a sample is represented by averaging across cells, but this fails to capture the heterogeneity within cell populations. We introduce CytoSummaryNet: a Deep Sets-based approach that improves mechanism of action prediction by 30-68% in mean average precision compared to average profiling on a public dataset. CytoSummaryNet uses self-supervised contrastive learning in a multiple-instance learning framework, providing an easier-to-apply method for aggregating single-cell feature data than previously published strategies. Interpretability analysis suggests that the model achieves this improvement by downweighting small mitotic cells or those with debris and prioritizing large uncrowded cells. The approach requires only perturbation labels for training, which are readily available in all cell profiling datasets. CytoSummaryNet offers a straightforward post-processing step for single-cell profiles that can significantly boost retrieval performance on image-based profiling datasets.

bioinformatics↗

bioRxiv2023

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.

bioinformatics↗

bioRxiv2023

Unveiling drug tolerant and persister-like cells in Leishmania braziliensis lines derived from patients with cutaneous leishmaniasis

IntroductionResistance against anti-Leishmania drugs (DR) has been studied for years, giving important insights into long-term adaptations of these parasites to drugs, through genetic modifications. However, microorganisms can also survive lethal drug exposure by entering into temporary quiescence, a phenomenon called drug tolerance (DT), which is rather unexplored in Leishmania. MethodsWe studied a panel of 9 Leishmania braziliensis strains highly susceptible to potassium antimonyl tartrate (PAT), exposed promastigotes to lethal PAT pressure and compared several cellular and molecular parameters distinguishing DT from DR. Results and discussionWe demonstrated in vitro that a variable proportion of cells remained viable, showing all the criteria of DT and not of DR: (i) signatures of quiescence, under drug pressure: reduced proliferation and significant decrease of rDNA transcription, (ii) reversibility of the phenotype: return to low IC50 after removal of drug pressure, (iii) absence of significant genetic differences between exposed and unexposed lineages of each strain and absence of reported markers of DR. We found different levels of quiescence and DT among the different L. braziliensis strains. We provide here a new in vitro model of drug-induced quiescence and DT in Leishmania. Research should be extended in vivo, but current model could be further exploited to support R&D, for instance, to guide screening of compounds able to overcome quiescence resilience of the parasite, hereby improving therapy of leishmaniasis.

microbiology↗

bioRxiv2023

Parasite hybridization promotes spreading of endosymbiotic viruses

Viruses are the most abundant biological entities on Earth and play a significant role in the evolution of many organisms and ecosystems. In pathogenic protozoa, the presence of endosymbiotic viruses has been linked to an increased risk of treatment failure and severe clinical outcome. Here, we studied the molecular epidemiology of the zoonotic disease cutaneous leishmaniasis in Peru and Bolivia through a joint evolutionary analysis of Leishmania braziliensis parasites and their endosymbiotic Leishmania RNA virus. We show that parasite populations circulate in isolated pockets of suitable habitat and are associated with single viral lineages that appear in low prevalence. In contrast, groups of hybrid parasites were geographically and ecologically dispersed, and commonly infected from a pool of genetically diverse viruses. Our results suggest that parasite hybridization, likely due to increased human migration and ecological perturbations, increased the frequency of endosymbiotic interactions known to play a key role in disease severity.

evolutionary biology↗

bioRxiv2023

JUMP Cell Painting dataset: morphological impact of 136,000 chemical and genetic perturbations

Image-based profiling has emerged as a powerful technology for various steps in basic biological and pharmaceutical discovery, but the community has lacked a large, public reference set of data from chemical and genetic perturbations. Here we present data generated by the Joint Undertaking for Morphological Profiling (JUMP)-Cell Painting Consortium, a collaboration between 10 pharmaceutical companies, six supporting technology companies, and two non-profit partners. When completed, the dataset will contain images and profiles from the Cell Painting assay for over 116,750 unique compounds, over-expression of 12,602 genes, and knockout of 7,975 genes using CRISPR-Cas9, all in human osteosarcoma cells (U2OS). The dataset is estimated to be 115 TB in size and capturing 1.6 billion cells and their single-cell profiles. File quality control and upload is underway and will be completed over the coming months at the Cell Painting Gallery: https://registry.opendata.aws/cellpainting-gallery. A portal to visualize a subset of the data is available at https://phenaid.ardigen.com/jumpcpexplorer/.

bioinformatics↗

bioRxiv2022

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

Identifying genetic and chemical perturbations with similar impacts on cell morphology can reveal compounds mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here, we create such a Resource dataset, CPJUMP1, where each perturbed gene is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same gene, and we find that identifying matches between chemical perturbations and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling, such as functional genomics and drug discovery.

bioinformatics↗

bioRxiv2021

Cell Painting predicts impact of lung cancer variants

Most variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding gene is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance (VUS) as impactful vs. neutral in an approach called expression-based variant-impact phenotyping (eVIP). We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cells image, we found that cell morphological profiling (cmVIP) can predict variants functional impact and, particularly at the single-cell level, reveals biological insights into variants which can be explored in our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene-specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.

cancer biology↗

bioRxiv2021

SorCS2 dynamically interacts with TrkB and GluN2B to control neurotransmission and Huntington's disease progression

BackgroundHuntingtons disease (HD) is a fatal neurodegenerative disorder characterized by progressive motor dysfunction and loss of medium spiny neurons (MSNs) in dorsal striatum. Brain-derived neurotrophic factor (BDNF) sustains functionality and integrity of MSNs, and thus reduced BDNF signaling is integral to the disease. Mutations in BDNF receptor SorCS2 were recently identified in HD patients. Our study investigates the role of SorCS2 in MSNs biology and in HD progression. MethodsWe derived a double transgenic line by crossbreeding SorCS2 deficient (KO) mice with the HD mouse model R6/1. Subsequently, we characterized the SorCS2 KO; R6/1 line by a set of behavioral and biochemical studies to evaluate phenotypes related to HD. Moreover, in combination with electrophysiology and super resolution microscopy techniques, we addressed the molecular mechanism by which SorCS2 controls synaptic activity in MSNs neurons. ResultsWe show that SorCS2 is expressed in MSNs with reduced levels in R6/1 HD model, and that SorCS2 deficiency exacerbates the disease progression in R6/1 mice. Furthermore, we find that SorCS2 binds TrkB and the NMDA receptor subunit GluN2B, which is required to control neurotransmission in corticostriatal synapses. While BDNF stimulates SorCS2-TrkB complex formation to enable TrkB signaling, it disengages SorCS2 from GluN2B, leading to enrichment of the subunit at postsynaptic densities. Consequently, long-term potentiation (LTP) is abolished in SorCS2 deficient mice, despite increased striatal TrkB and unaltered BDNF expression. However, the addition of exogenous BDNF rescues the phenotype. Finally, GluN2B, but not GluN2A, currents are also severely impaired in the SorCS2 KO mice. ConclusionsWe formulate a novel molecular mechanism by which SorCS2 acts as a molecular switch. SorCS2 targets TrkB and GluN2B into postsynaptic densities to enable BDNF signaling and NMDAR dependent neurotransmission in the dorsal striatum. Remarkably, the binding between SorCS2 and TrkB or GluN2B, respectively, is mutually exclusive and controlled by BDNF. This mechanism provides an explanation why deficient SorCS2 signaling severely aggravates HD progression in mice. Moreover, we provide evidence that this finding might represent a general mechanism of SorCS2 signaling found in other brain areas, thus increasing its relevance for other neurological and psychiatric impairments.

neuroscience↗

bioRxiv2019

Ecological divergence and hybridization of Neotropical Leishmania parasites

The tropical Andes is an important natural laboratory to understand speciation and diversification in many taxa. Here, we examined the evolutionary history of parasites of the Leishmania braziliensis species complex based on whole genome sequencing of 67 isolates from 47 localities in Peru. We firstly show the origin of near-clonal Andean Leishmania lineages that diverged from admixed Amazonian ancestors, accompanied by a significant reduction in genome diversity and large structural variations implicated in host-parasite interactions. Beside a clear dichotomy between Andean and Amazonian species, patterns of population structure were strongly associated with biogeographical origin. Molecular clock analyses and ecological niche modeling suggested that the history of diversification of the Andean lineages is limited to the Late Pleistocene and intimately associated with habitat contractions driven by climate change. These results support a wider model on trypanosomatid evolution where major parasite lineages emerge through ecological fitting. Second, genome-scale analyses provided evidence of meiotic recombination between Andean and Amazonian Leishmania species, resulting in full-genome hybrids. The mitochondrial genome of these hybrids consisted of homogeneous uniparental maxicircles, but minicircles originated from both parental species, leaving a mosaic ancestry of minicircle-encoded guide RNA genes. We further show that mitochondrial minicircles - but not maxicircles - show a similar evolutionary pattern as the nuclear genome, suggesting that biparental inheritance of minicircles is universal and may be important to alleviate maxicircle-nuclear incompatibilities. By comparing full nuclear and mitochondrial genome ancestries, our data expands our appreciation on the genetic consequences of diversification and hybridization in parasitic protozoa.

genomics↗

bioRxiv2019

Tracking of quiescence in Leishmania by quantifying the expression of GFP in the ribosomal DNA locus

Under stressful conditions some microorganisms adopt a reversible non or slow proliferative quiescent stage that allows their survival. Although quiescence has been described broadly in bacteria, this phenotype has been only recently discovered in Leishmania. In the present work we developed a biosensor of quiescence that allows to monitor the physiological stage of the parasite at population and single cell levels. We inserted a GFP gene into the ribosomal DNA locus and followed the expression of this reporter gene, driven by the ribosomal promotor (rGFP expression). We showed that rGFP expression decreased significantly and rapidly during the in vitro transition from extracellular promastigotes to intracellular amastigotes of L. mexicana an L. braziliensis and that the decrease in rGFP expression was coupled in vitro with a decrease in replication as measured by BrdU incorporation. Quiescence was not only observed in reference laboratory strains, but also among clinical isolates. We found that quiescence was reversible as the parasites could rapidly resume their metabolically active and proliferative stage when they were put back in an optimal environment for growth. We demonstrated for the first time in live cells that amastigotes are a heterogeneous population in which shallow and deep quiescent stages may coexist. Finally, we showed that rGFP expression could be monitored in vivo and that quiescent amastigotes could reside in tissues of animals with latent infections of L. braziliensis or L. mexicana. We propose rGFP expression as a simple parameter to define quiescent cells and further characterize them.\n\nIMPORTANCEQuiescence is a physiological diversification that allows pathogens to overcome chemotherapy without the development of drug resistance and to be invisible to the immune system of their host. Quiescent pathogens can cause latent infections and (re-) emerge in an unpredictable time during the lifetime of the individual. The phenomenon was recently described in Leishmania in which it could explain several clinical and sub-clinical features, like therapeutic failure, reactivation of the disease and asymptomatic infections. However, a simple biosensor of quiescence for Leishmania is not yet available. We show for the first time that the integration of GFP within the rDNA locus and the subsequent quantification of its expression can be used as a biosensor to distinguish quiescent subpopulations among live amastigotes. Moreover, we show quiescence is quickly reversible both in vivo and in vitro. We offer a tool that will allow the further molecular characterization of quiescent parasites.

microbiology↗