Biology subjects

Cuevas, M.

Publications and source records attributed to Cuevas, M..

6 recordsLinked to original sources

bioRxiv2026

S3-enriched kidney proximal nephrons from stem cells facilitate tubular injury modelling

Chronic kidney disease (CKD) is a major global health challenge affecting >840 million people, with rising prevalence driven by common conditions including diabetes, hypertension, obesity, and drug toxicity. The proximal tubule (PT) is central to kidney function yet is highly injury-prone, particularly within the S3 segment which plays key roles in drug clearance and CKD pathology. Despite decades of in vitro PT model development, achieving accurate functional and structural segmentation of the PT with distinct PT sub-cell types has remained challenging. Here, we report an enrichment of S3-like cells within PT-enhanced kidney organoids (PT-EKO) that confers segment-specific functionality and injury susceptibility. This advanced platform facilitated physiologically relevant modelling of hyperglycaemia-induced damage, including rapid detection of injury biomarker Kidney Injury Molecule-1 (KIM-1). Integrating with both static and organ-on-chip culture systems, the translational potential of S3-enriched PT-EKO was underscored by its amenability to scale-up via cryopreservation of day 13 progenitors with retained differentiation capacity. PT-EKO applications were further broadened as an expandable high-yield source of isolatable PT cells, retaining PT characteristics across multiple passages and cryopreservation. Together, these findings present a high-fidelity platform for modelling tubular injury and advancing translational applications including CKD drug development, cell-specific nephrotoxicity testing and cellular therapies. SIGNIFICANCE STATEMENTAdvancing stem cell-based proximal nephron models, here we identify proximal tubule-enhanced kidney organoids (PT-EKO) as an enriched source of the nephrons most injury-prone cell type; S3 proximal tubule cells. This advanced platform provides physiologically-relevant modelling of tubular injury and a scalable source of high-quality PT cells, paving the way for more accurate modelling, screening, and cellular therapy applications.

bioengineering↗

bioRxiv2021

PySeq2500: An open source toolkit for repurposing HiSeq 2500 sequencing systems as versatile fluidics and imaging platforms.

Fluorescence microscopy is a key method in the life sciences. State of the art -omics methods combine fluorescence microscopy with complex protocols to visualize tens to thousands of features in each of millions of pixels across samples. These -omics methods require precise control of temperature, reagent application, and image acquisition parameters during iterative chemistry and imaging cycles conducted over the course of days or weeks. Automated execution of such methods enables robust and reproducible data generation. However, few commercial solutions exist for temperature controlled, fluidics coupled fluorescence imaging, and implementation of bespoke instrumentation requires specialized engineering expertise. Here we present PySeq2500, an open source Python code base and flow cell design that converts the Illumina HiSeq 2500 instrument into an open platform for programmable applications. Customizable PySeq2500 protocols enable experimental designs involving simultaneous 4-channel image acquisition, temperature control, reagent exchange, stable positioning, and sample integrity over extended experiments. To demonstrate accessible automation of complex, multi-day workflows, we use the PySeq2500 system for unattended execution of iterative indirect immunofluorescence imaging (4i). Our automated 4i method uses off-the-shelf antibodies over multiple cycles of staining, imaging, and antibody elution to build highly multiplexed maps of cell types and pathological features in mouse and postmortem human spinal cord sections. As demonstrated here, PySeq2500 enables non-specialists to develop and implement state of the art fluidics coupled imaging methods in a widely available benchtop system.

genomics↗

bioRxiv2020

Cell-type specific gene expression profiling in heterogeneous in vitro cultures using epitope-tagged RPL22

Genetic and genomic studies of brain disease increasingly demonstrate disease-associated interactions between the cell types of the brain. Increasingly complex and more physiologically relevant human induced pluripotent stem cell (hiPSC)-based models better explore the molecular mechanisms underlying disease, but also challenge our ability to resolve cell-type specific perturbations. Here we report an extension of the RiboTag system, first developed to achieve cell-type restricted expression of epitope-tagged ribosomal protein (RPL22) in mouse tissue, to a variety of in vitro applications, including immortalized cell lines, primary mouse astrocytes, and hiPSC-derived neurons. RiboTag expression enables efficient depletion of off-target RNA in mixed species primary co-cultures and in hiPSC-derived neural progenitor cells, motor neurons, and GABAergic neurons. Nonetheless, depletion efficiency varies across independent experimental replicates. The challenges and potential of implementing RiboTags in complex in vitro cultures are discussed.

molecular biology↗

bioRxiv2019

Splotch: Robust estimation of aligned spatial temporal gene expression data.

Spatial genomics technologies enable new approaches to study how cells interact and function in intact multicellular environments but present a host of technical and computational challenges. Here we describe Splotch, a novel computational framework for the analysis of spatially resolved transcriptomics data. Splotch aligns transcriptomics data from multiple tissue sections and timepoints to generate improved posterior estimates of gene expression. We demonstrate alignment of a large corpus of single-cell RNA-seq data into an automatically generated spatial-temporal coordinate and study optimal design for spatial transcriptomics experiments.

bioinformatics↗

bioRxiv2018

A Rap1 binding site and lipid-dependent helix in talin F1 domain cooperate in integrin activation

Rap1 GTPases bind effectors, such as RIAM, to enable talin1 to induce integrin activation. In addition, Rap1 binds directly to the talin1 F0 domain (F0); however, this interaction makes a negligible contribution to integrin activation in CHO cells or platelets. Here, we show that talin1 F1 domain contains a previously undetected Rap1 binding site of similar affinity to that in F0. A structure-guided point mutant (R118E) in F1, which blocks Rap1 binding, abolishes the capacity of Rap1 to potentiate talin1-induced integrin activation. The capacity of F1 to mediate Rap1-dependent integrin activation depends on a unique loop in F1 that transforms into an amphipathic helix upon binding to membrane lipids. Basic membrane-facing residues of this helix are critical as charge reversal mutations led to dramatic suppression of talin1-dependent activation. Thus, a novel Rap1 binding site and a lipid-dependent amphipathic helix in talin1 F1 cooperate to enable a direct Rap1-talin1 interaction to cause integrin activation.\n\nSummaryThis work reveals that Rap1 GTPases bind directly to talin1 F1 domain and by cooperating with a unique lipid-dependent amphipathic helix in the F1 domain effects talin1-mediated integrin activation.

cell biology↗

bioRxiv2018

Spatiotemporal Dynamics of Molecular Pathology in Amyotrophic Lateral Sclerosis

Paralysis occurring in amyotrophic lateral sclerosis (ALS) results from denervation of skeletal muscle as a consequence of motor neuron degeneration. Interactions between motor neurons and glia contribute to motor neuron loss, but the spatiotemporal ordering of molecular events that drive these processes in intact spinal tissue remains poorly understood. Here, we use spatial transcriptomics to obtain gene expression measurements of mouse spinal cords over the course of disease, as well as of postmortem tissue from ALS patients, to characterize the underlying molecular mechanisms in ALS. We identify novel pathway dynamics, regional differences between microglia and astrocyte populations at early time-points, and discern perturbations in several transcriptional pathways shared between murine models of ALS and human postmortem spinal cords.\n\nOne Sentence SummaryAnalysis of the ALS spinal cord using Spatial Transcriptomics reveals spatiotemporal dynamics of disease driven gene regulation.

neuroscience↗