bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.01.23.634476

Drug-Resistance Biomarkers in Leishmania infantum through Nanopore-Based Detection of Aneuploidy and Gene Copy Number Variations with LeishGenApp

Abstract

BackgroundDrug-resistant strains of Leishmania infantum challenge the effectiveness of treatments for clinical leishmaniosis and may lead to more frequent relapses. Copy number variation (CNV) at specific genetic loci is associated with drug resistance and virulence, but information about its prevalence in endemic regions is limited. This study examines the drug resistance and virulence status of Leishmania strains in human and canine isolates from the Mediterranean region. MethodsForty-eight Leishmania infantum isolates were whole-genome sequenced with nanopore long reads, followed by de novo assembly. We analyzed chromosomal aneuploidies and gene copy number variation in loci linked to drug resistance and virulence in Leishmania, alongside the genomic structure and rearrangements responsible for these variations. ResultsComplete genomes were de novo assembled for 35 L. infantum isolates (22 from dogs and 13 from humans), revealing significant chromosomal variability. We assessed copy number variation for 22 potential biomarkers: 15 genes related to drug resistance to first-line drugs (METK for allopurinol; LdSMT for amphotericin B; AQP1 and H-locus for antimonials; LdMT, LdRos3, and MSL for miltefosine; PPM for paramomycin) and seven genes related to virulence (lipophosphoglycan and proteophosphoglycan biosynthesis, and the Lack protein). Drug-resistance biomarkers were identified in 80% of the isolates. Canine strains primarily showed resistance to allopurinol and antimonials, while human isolates exhibited a broader resistance spectrum, especially to antimonials and paromomycin. The co-occurrence of resistance biomarkers was common, especially for allopurinol and antimonial resistance. Distinct mechanisms underlie the observed copy number variations. Virulence-associated genes were less variable among isolates. ConclusionsThe prevalence of drug-resistance biomarkers in Leishmania infantum strains from the Mediterranean region, as revealed by this study, underscores the critical need for routine resistance surveillance in managing clinical leishmaniosis. These findings not only inform current clinical practice but also pave the way for more effective management strategies in the future.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Carrasco Martin, M., Marti-Carreras, J., Gomez Ponce, M., Alcover, M. M., Roura, X., Ferrer, L., Baneth, G., Bruno, F., Chicharro, C., Cordeiro-da-Silva, A., Cristovao, J., Di Muccio, T., Maia, C., Moreno, J., Priego, A., Roca-Gerones, X., Santarem, N., Vila Soriano, A., Vitale, F., Yasur-Landau, D., Francino, O.. 2025-01-25. Drug-Resistance Biomarkers in Leishmania infantum through Nanopore-Based Detection of Aneuploidy and Gene Copy Number Variations with LeishGenApp. https://doi.org/10.1101/2025.01.23.634476

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Utilizing single-cell data for per-cell type eQTL mapping in the human pancreas

Aims/hypothesis The human pancreas is a central organ for metabolic regulation that is comprised of diverse cell types that uniquely contribute to its function. Previous studies have performed expression quantitative trail loci (eQTL) discovery in either whole pancreas or in pancreatic islets, but due to differences between pancreatic cell types, this approach does not reveal cell type-specific effects. In this study, we sought to either implicate the cell type of action for known eQTLs or identify new eQTLs that may have been masked in bulk studies by performing eQTL discovery in individual pancreatic cell types. Methods We clustered 153,018 single-cell RNA sequencing (scRNA-seq) data from 71 pancreatic islet donors from the Human Pancreas Analysis Program (HPAP). We performed eQTL discovery in six pancreatic cell types using this resource directly. We further utilized this single cell resource as a reference to deconvolute bulk pancreatic RNA sequencing data from 305 Genotype Tissue Expression (GTEx) project donors and performed eQTL discovery in four pancreatic cell types. Finally, we performed fine-mapping and co-localization of pancreatic cell type eQTLs with metabolic GWAS to connect our findings to metabolic disease risk. Results From analyzing 71 individuals with single cell profiles, we identified 112 unique eGenes across six pancreatic cell types, 99 of which had been identified previously and 13 unique to this study. From the deconvoluted eQTLs, we identified 3,134 unique eGenes across four pancreatic cell types, 116 of which were unique to our study. Fine-mapping and co-localization of eQTLs with metabolic GWAS yielded key leads that warrant further investigation, such as the association of rs2168101 with LMO1 expression in alpha cells. Conclusions/interpretation We identified new signals that were previously not found in bulk pancreatic eQTL studies and potential cell type of action for several signals that were identified previously. Although there are limitations to the power, and therefore, discoverability of this study, it provides insights into how individual pancreatic cells differently contribute to metabolic disease.

genetics↗

MOD-scTWAS: Leveraging gene co-expression for single-cell transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) provide an effective framework for identifying genes associated with complex traits. Population-scale single-cell transcriptomic data enable genetically regulated expression (GReX) prediction and TWAS analyses at cell-type resolution, but the predictive performance of existing single-cell TWAS methods remains limited. Here, we develop MOD-scTWAS, a module-based method that jointly models GReX for genes within co-expression modules to borrow information across genes. Starting from a generative model for single-cell gene expression, MOD-scTWAS accounts for the heteroscedasticity and cross-gene correlation of individual-level pseudobulk expression in joint GReX prediction. In cross-validation analyses of the OneK1K dataset, MOD-scTWAS achieved higher mean GReX prediction accuracy than scTWAS across all 14 cell types and increased the number of imputable genes. When applied to TWAS analyses of UK Biobank quantitative hematological traits, MOD-scTWAS identified more significant cell type-gene-trait associations than scTWAS. These results demonstrate the potential of leveraging gene co-expression through joint modeling to improve cell-type-specific GReX prediction and TWAS discovery.

genetics↗

Generation of a transgenic cephalopod

Coleoid cephalopods (cuttlefish, octopus, and squid) are marine mollusks with elaborate nervous systems that support a diverse repertoire of complex behaviors. These include the neural control of the color, pattern, and texture of the skin, facilitating both adaptive camouflage and innate patterning that may reflect internal state. The development of transgenic cephalopods expressing fluorescent proteins, optogenetic actuators, and reporters of neural activity would contribute a new and important technology to cephalopod biology. The generation of transgenic cephalopods, however, has remained a major challenge. Here, we report the development of stable transgenic dwarf cuttlefish (Ascarosepion bandense) expressing ubiquitous nuclear-localized mScarlet, a red fluorescent protein. We evaluated multiple strategies for transgenesis, and established cuttlefish lines using both CRISPR and the transposons Sleeping Beauty and Minos. The stable expression of transgenes enabled live imaging of cell dynamics during embryonic development. The Minos transposon emerged as the most efficient transgenesis strategy and is adaptable to promoters and transgenes of choice. These strategies now enable the generation of diverse genetic tools for mechanistic studies of cephalopod biology.

genetics↗