Biology subjects

Correa, S.

Publications and source records attributed to Correa, S..

14 recordsLinked to original sources

bioRxiv2026

Endocrine-Adapted Pituitary Macrophages Regulate Gonadotropin Secretion through CXCL5-CXCR2-MAPK Signaling

Chronic inflammation disrupts hormonal balance in the Hypothalamic-Pituitary-Gonadal (HPG) axis, contributing to reproductive disorders. While immune cells in the hypothalamus and ovaries have been extensively studied, their impact on the pituitary remains largely unexplored. Our research identifies pituitary macrophages (PitMacs) as the dominant pituitary immune cell population with a role in regulating reproductive gonadotropin secretion both in vitro and in vivo. Using a targeted AAV-based depletion strategy, we demonstrate that a reduction of PitMacs decreases serum gonadotropins, luteinizing hormone (LH) and follicle-stimulating hormone (FSH), in female mice. PitMacs are transcriptomically distinct from other tissue-resident macrophages and harbor a unique translational program that reflects the pituitarys endocrine identity, including active translation of growth hormone (Gh) and prolactin (Prl). Cytokine profiling identified CXCL5 and IFN-{gamma} as key PitMac-derived mediators of gonadotropin regulation. Mechanistically, CXCL5 signals through CXCR2 to activate the MAPK pathway, converging with Gonadotropin-Releasing Hormone (GnRH) signaling in a time-dependent manner to regulate LH secretion and GnRH receptor surface expression. These findings establish PitMacs as essential endocrine-immune integrators, opening new avenues for understanding inflammation-driven reproductive disorders. One Sentence SummaryPituitary macrophages are unique hormone-producing immune cells that regulate hormone secretion via cytokine signaling.

immunology↗

bioRxiv2026

Supramolecular hydrogel viscoelasticity regulates in situ tertiary lymphoid neogenesis

Tertiary lymphoid structures (TLSs) are organized three-dimensional immune niches associated with improved antitumor immunity, which has galvanized efforts to induce them artificially using biomaterials. However, these strategies have largely focused on soluble cue delivery, leaving the role of scaffold physical properties poorly understood. Here, we developed injectable, liposome-crosslinked supramolecular hydrogels spanning soft and stiff formulations to determine how scaffold mechanical properties regulate in situ tertiary lymphoid neogenesis. The formulations differed in their viscoelastic properties while maintaining broadly comparable release of ovalbumin and LIGHT. Soft hydrogels underwent distributed cellular infiltration and material replacement, transitioning from an early myeloid-rich response to vascularized, lymphoid-dominant tissues containing B-cell-rich aggregates adjacent to T-cell regions, with B-cell organization peaking at day 14. Single-cell RNA sequencing revealed that transient interferon-associated neutrophil and macrophage states in the early niche preceded the emergence of TLS-associated transcriptional programs across lymphoid and myeloid populations. In contrast, stiff hydrogels resisted infiltration and perpetuated a niche dominated by activated myeloid cells with limited lymphoid organization. Prophylactically implanted soft hydrogels improved early melanoma control relative to stiff hydrogels under checkpoint blockade, and a single soft-hydrogel implantation restrained tumor growth even without checkpoint blockade. Together, these findings establish scaffold mechanics and remodeling as active regulators of engineered immune-tissue organization and provide design principles for directing the development of local TLS-like niches.

bioengineering↗

bioRxiv2025

Modular Noncovalent Functionalization of Electrospun Piezoelectric Scaffolds with Bioactive Nanocarriers

Electrospun scaffolds offer a promising platform for immune-instructive materials, but stable and modular functionalization with bioactive signals remains a technical challenge. Here, we develop a surface coating strategy for electrospun scaffolds that consist of poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE), a piezoelectric polymer, using electrostatic adsorption of charged nanoparticles. We show that under certain conditions, these piezoelectric scaffolds are suitable substrates for electrostatic self-assembly, and that the density of nanoparticle coatings can be tuned by adjusting buffer pH, ionic strength, and nanoparticle concentration. This approach enables robust and uniform coating of both polymeric nanoparticles and soft nanocarriers such as liposomes, without requiring covalent surface modification. Liposome-coated scaffolds are cytocompatible with adherent epithelial and suspension immune cells and support lipid exchange at the cell-material interface. Using a supramolecular tethering strategy, we use liposome coatings to present interleukin-15 (IL-15) from the scaffold surface and demonstrate localized, sustained cytokine signaling. Together, these findings establish a modular approach for post-fabrication, noncovalent scaffold functionalization with bioactive nanocarriers, offering new opportunities for tissue and immune engineering.

bioengineering↗

bioRxiv2025

Range-wide responses to an extreme heat event in Mimulus cardinalis

PremiseExtreme events are an understudied aspect of ongoing anthropogenic climate change that could play a disproportionate role in the threat that rapid environmental shifts pose to natural populations. MethodsWe used a short-term heatwave treatment in controlled growth chamber environments to study evolutionary responses in Mimulus cardinalis populations to a recent repeated extreme heat event. Individuals from before (ancestors) and after (descendants) this extreme heat event were resurrected from seeds harvested from six populations across the range of M. cardinalis, and their physiological, performance, and functional responses (stomatal conductance, leaf temperature difference, photosystem II efficiency, relative growth rate, specific leaf area, and leaf dry matter content) to the heatwave treatment were assessed. Key ResultsOur results allow for two main conclusions: 1) plants responded favorably to the heatwave treatment in terms of their overall performance and the magnitude of response was generally greatest among trailing-edge populations, and 2) despite some evidence of divergent evolutionary responses among regions to the recent natural extreme heat event, we did not find adaptive evolution that affected how M. cardinalis populations responded to the heatwave treatment. ConclusionsThese results demonstrate that many M. cardinalis populations may be residing in natural environments that are below their optimum average temperature, indicating that M. cardinalis populations could exhibit resiliency to future warming. However, limited evolutionary responses in M. cardinalis to the recent extreme heatwave could still indicate that there is potential for future vulnerability to extreme climate events of increased intensity, frequency, and duration in the future.

evolutionary biology↗

bioRxiv2024

Evaluating plant growth-defence trade-offs by modelling the interaction between primary and secondary metabolism

Understanding the molecular mechanisms behind plant response to stress can enhance breeding strategies and help us design crop varieties with improved stress tolerance, yield and quality. To investigate resource redistribution from growth-to defence-related processes in an essential tuber crop, potato, here we generate a large-scale compartmentalised genome-scale metabolic model, Potato-GEM. Apart from a large-scale reconstruction of primary metabolism, the model includes the full known potato secondary metabolism, spanning over 600 reactions that facilitate the biosynthesis of 182 distinct potato secondary metabolites. Constraint-based modelling identifies that the activation of the largest amount of secondary (defence) pathways occurs at a decrease of the relative growth rate of potato leaf, due to the costs incurred by defence. We then obtain transcriptomics data from experiments exposing potato leaves to two biotic stress scenarios, a herbivore and a viral pathogen, and apply it as constraints to produce condition-specific models. We show that these models recapitulate experimentally observed decreases in relative growth rates under treatment, enabling us to pinpoint the metabolic rewiring underlying growth-defence trade-offs. Potato-GEM thus presents a useful resource to study and broaden our understanding of potato and general plant defence responses under stress conditions.

systems biology↗

bioRxiv2022

An automated BIDS-App for brain segmentation of human fetal functional MRI data

Fetal functional magnetic resonance imaging (fMRI) offers critical insight into the developing brain and could aid in predicting developmental outcomes. As the fetal brain is surrounded by heterogeneous tissue, it is not possible to use adult- or child-based segmentation toolboxes. Manually-segmented masks can be used to extract the fetal brain; however, this comes at significant time costs. Here, we present a new BIDS App for masking fetal fMRI, funcmasker-flex, that overcomes these issues with a robust 3D convolutional neural network (U-net) architecture implemented in an extensible and transparent Snakemake workflow. Open-access fetal fMRI data with manual brain masks from 159 fetuses (1103 total volumes) were used for training and testing the U-net model. We also tested generalizability of the model using 82 locally acquired functional scans from 19 fetuses, which included over 2300 manually segmented volumes. Dice metrics were used to compare performance of funcmasker-flex to the ground truth manually segmented volumes, and segmentations were consistently robust (all Dice metrics [≥]0.74). The tool is freely available and can be applied to any BIDS dataset containing fetal bold sequences. funcmasker-flex reduces the need for manual segmentation, even when applied to novel fetal functional datasets, resulting in significant time-cost savings for performing fetal fMRI analysis.

neuroscience↗

bioRxiv2021

Delivery of CAR-T Cells in a Transient Injectable Stimulatory Hydrogel Niche Improves Treatment of Solid Tumors

Adoptive cell therapy (ACT) has proven to be highly effective in treating blood cancers such as B cell malignancies, but traditional approaches to ACT are poorly effective in treating the multifarious solid tumors observed clinically. Locoregional cell delivery methods have shown promising results in treating solid tumors compared to standard intravenous delivery methods, but the approaches that have been described to date have several critical drawbacks ranging from complex manufacturing and poor modularity to challenging adminstration. In this work, we develop a simple-to-implement self-assembled and injectable hydrogel material for the controlled co-delivery of CAR-T cells and stimulatory cytokines that improves treatment of solid tumors. We evaluate a range of hydrogel formulations to optimize the creation of a transient inflammatory niche that affords sustained exposure of CAR-T cells and cytokines. This facile approach yields increased CAR-T cell expansion, induces a more tumor-reactive CAR-T phenotype, and improves efficacy in treating solid tumors in mice.

bioengineering↗

bioRxiv2021

Injectable Liposome Based Supramolecular Hydrogels for the Programmable Release of Multiple Protein Drugs

Directing and manipulating biological functions is at the heart of next-generation biomedical initiatives such as tissue and immuno-engineering. Yet, the ambitious goal of engineering complex biological networks requires the ability to precisely perturb specific signaling pathways at distinct times and places. Using lipid nanotechnology and the principles of supramolecular self-assembly, we have developed an injectable liposomal nanocomposite hydrogel platform to precisely control drug presentation through programing of the co-release of multiple protein drugs. These liposomal hydrogels exhibited robust shear-thinning and self-healing behaviors enabling facile injectability for local drug delivery applications. By integrating modular lipid nanotechnology into this hydrogel platform, we introduced multiple mechanisms of protein release based on liposome surface chemistry. When injected into immuno-competent mice, these liposomal hydrogels exhibited formulation-dependent rates of dissolution and excellent biocompatibility. To fully validate the utility of this system for multi-protein delivery, we demonstrated the synchronized, sustained, and localized release of IgG antibody and IL-12 cytokine in vivo, despite the significant size differences between these two proteins. Overall, these liposomal nanocomposite hydrogels are a highly modular platform technology with the ability the mediate orthogonal modes of protein release and the potential to precisely coordinate biological cues both in vitro and in vivo.

bioengineering↗

bioRxiv2021

Real-time monitoring of drug pharmacokinetics within tumor tissue in live animals

The efficacy and safety of a chemotherapy regimen fundamentally depends on its pharmacokinetics. This is currently measured based on blood samples, but the abnormal vasculature and physiological heterogeneity of the tumor microenvironment can produce radically different drug pharmacokinetics relative to the systemic circulation. We have developed an implantable microelectrode array sensor that can collect such tissue-based pharmacokinetic data by simultaneously measuring intratumoral pharmacokinetics from multiple sites. We employ gold nanoporous microelectrodes that maintain robust sensor performance even after repeated tissue implantation and extended exposure to the tumor microenvironment. We demonstrate continuous in vivo monitoring of concentrations of the chemotherapy drug doxorubicin at multiple tumor sites in a rodent model, and demonstrate clear differences in pharmacokinetics relative to the circulation that could meaningfully affect drug efficacy and safety. This platform could prove valuable for preclinical in vivo characterization of cancer therapeutics, and may offer a foundation for future clinical applications.

bioengineering↗

bioRxiv2021

Deep learning model for the prediction and classification of protein toxins across all domains of life

Toxins are widely produced by different organisms to disrupt the physiology of other organisms, and support their own existence. Their study is useful to understand protein evolution, environmental adaptation and survival competition. In-silico predictions of toxic proteins can support empirical frameworks, and help in the safety measurements needed for various industrial related processes. Some in-silico methods are slow, hard to implement or lack taxa representation in their training datasets. Here we present a deep learning model to classify protein toxins, through the use of Convolutional Neural Networks (ConvTOX). ConvTOX is able to accurately identify toxic proteins across the domains of life, with accuracies over 80% for animal and plant toxins, and over 50% for bacterial toxins. Moreover, ConvTOX is able to generalize the identification of differences among toxin types, such as neurotoxins and myotoxins, and to accurately identify structural similarities between different protein toxins. ConvTOX overcomes limitations from previous models by being able to predict toxin proteins from across all domains of life, and by not being limited to only short toxin peptides. Limitations are still clear in terms of lower accuracies for specific phylogenetic groups (such as bacterial toxins), but still this works presents itself as a one step forward for the universal use, classification and study of toxic proteins.

synthetic biology↗

bioRxiv2021

Injectable Nanoparticle-Based Hydrogels Enable the Safe and Effective Deployment of Immunostimulatory CD40 Agonist Antibodies

When properly deployed, the immune system can eliminate deadly pathogens, eradicate metastatic cancers, and provide long-lasting protection from diverse diseases. Unfortunately, realizing these remarkable capabilities is inherently risky as disruption to immune homeostasis can elicit dangerous complications or autoimmune disorders. While current research is continuously expanding the arsenal of potent immunotherapeutics, there is a technological gap when it comes to controlling when, where, and how long these drugs act on the body. Here, we explore the ability of a slow-releasing injectable hydrogel depot to reduce the problematic dose-limiting toxicities of immunostimulatory CD40 agonist (CD40a) while maintaining their potent anti-cancer efficacy. We leverage a previously described polymer-nanoparticle (PNP) hydrogel system that exhibits shear-thinning and yield-stress properties that we hypothesized would improve locoregional delivery of the CD40a immunotherapy. Using PET imaging, we demonstrate that prolonged hydrogel-based delivery redistributes CD40a exposure to the tumor and the tumor draining lymph node (TdLN), thereby reducing weight loss, hepatotoxicity, and cytokine storm associated with standard treatment. Moreover, CD40a-loaded hydrogels mediate improved local cytokine induction in the TdLN and improve treatment efficacy in the B16F10 melanoma model. PNP hydrogels, therefore, represent a facile, drug-agnostic method to ameliorate immune-related adverse effects and explore locoregional delivery of immunostimulatory drugs.

bioengineering↗

bioRxiv2021

Consistent Tumorigenesis with Self-Assembled Hydrogels Enables High-powered Murine Cancer Studies

Preclinical cancer research is heavily dependent on allograft and xenograft models, but current approaches to tumor inoculation yield inconsistent tumor formation and growth, ultimately wasting valuable resources (e.g., animals, time, and money) and limiting experimental progress. Here we demonstrate a method for tumor inoculation using self-assembled hydrogels to reliably generate tumors with low variance in growth. The observed reduction in model variance enables smaller animal cohorts, improved effect observation and higher powered studies.

bioengineering↗

bioRxiv2020

Deep learning enables the design of functional de novo antimicrobial proteins

Protein sequences are highly dimensional and present one of the main problems for the optimization and study of sequence-structure relations. The intrinsic degeneration of protein sequences is hard to follow, but the continued discovery of new protein structures has shown that there is convergence in terms of the possible folds that proteins can adopt, such that proteins with sequence identities lower than 30% may still fold into similar structures. Given that proteins share a set of conserved structural motifs, machine-learning algorithms can play an essential role in the study of sequence-structure relations. Deep-learning neural networks are becoming an important tool in the development of new techniques, such as protein modeling and design, and they continue to gain power as new algorithms are developed and as increasing amounts of data are released every day. Here, we trained a deep-learning model based on previous recurrent neural networks to design analog protein structures using representations learning based on the evolutionary and structural information of proteins. We test the capabilities of this model by creating de novo variants of an antifungal peptide, with sequence identities of 50% or lower relative to the wild-type (WT) peptide. We show by in silico approximations, such as molecular dynamics, that the new variants and the WT peptide can successfully bind to a chitin surface with comparable relative binding energies. These results are supported by in vitro assays, where the de novo designed peptides showed antifungal activity that equaled or exceeded the WT peptide.

bioengineering↗

bioRxiv2018

Estrogen Signaling in Arcuate Kiss1 Neurons Suppresses a Sex-Dependent Circuit That Promotes Dense Strong Bones in Female Mice

Central estrogen signaling coordinates energy expenditure, reproduction, and in concert with peripheral estrogen impacts skeletal homeostasis in female rodents. Here, we ablate estrogen receptor alpha (ER) in the medial basal hypothalamus and find a robust bone phenotype only in female mice that results in exceptionally strong trabecular and cortical bones, whose density surpasses other reported mouse models. Stereotaxic guided deletion of ER in the arcuate nucleus increases bone mass in both intact and estrogen-depleted females, confirming the central role of estrogen signaling in this sex-dependent bone phenotype. Loss of ER activity in kisspeptin (Kiss1)-expressing cells is sufficient to recapitulate the bone phenotype, identifying Kiss1 neurons as a critical node in this powerful neuroskeletal circuit. We propose that this newly identified female brain-to-bone pathway exists as a homeostatic regulator to divert calcium and energy stores from bone building when energetic demands are high. Our work reveals a previously unknown target for the treatment of age-related bone disease.

physiology↗