Biology subjects

Jaramillo, S.

Publications and source records attributed to Jaramillo, S..

13 recordsLinked to original sources

bioRxiv2025

Genomic REWRITE of Immune Interfaces Reveals Heritable Epigenetic Memory in Human Stem Cells

Human leukocyte antigen (HLA) polymorphism underlies antigen presentation, immune recognition, and central tolerance, yet the complex, multigenic structure of native HLA loci has precluded systematic engineering in human pluripotent stem cells (hPSCs). Existing genome engineering demonstrations in hPSCs focus on smaller integrations or at ectopic sites, leaving scar-minimized rewriting of native human loci at >100 kb scale a major technical challenge. Here, we present REWRITE, a modular platform for scar-minimized genome writing that enables engineering of large human genomic loci exceeding 100 kb at their native chromosomal sites. Using REWRITE, we deleted 105 kb spanning the dispersed HLA class-I locus and installed either compact or full-length refactored synthetic HLA haplotypes. Both refactored architectures exhibited transient activity before re-acquiring the native inactive state; upon extended culture, engineered lines yielded global transcriptomes nearly indistinguishable from parental cells. The engineered loci were genomically stable, retained interferon-responsive HLA expression, and remained compatible with differentiation into endothelial-like and thymic epithelial-like cells. Together, these results establish REWRITE as a platform for locus-scale genome engineering in hPSCs and provides a system for studying HLA haplotype structure and function in an isogenic pluripotent cell background. One sentenceA practical platform for scar-minimized rewriting of native human loci exceeding 100 kb in hPSCs, demonstrated through synthetic refactoring of the class-I HLA region.

synthetic biology↗

bioRxiv2025

A multimodal approach for visualization and identification of electrophysiological cell types in vivo

Neurons of different types perform diverse computations and coordinate their activity during sensation, perception, and action. While electrophysiological recordings can measure the activity of many neurons simultaneously, identifying cell types during these experiments remains difficult. To identify cell types, we developed PhysMAP, a framework that weighs multiple electrophysiological modalities simultaneously to obtain interpretable multimodal representations. We apply PhysMAP to seven datasets and demonstrate that these multimodal representations are better aligned with known transcriptomically-defined cell types than any single modality alone. We then show that such alignment allows PhysMAP to better identify putative cell types in the absence of ground truth. We also demonstrate how annotated datasets can be used to infer multiple cell types simultaneously in unannotated datasets and show that the properties of inferred types are consistent with the known properties of these cell types. Finally, we provide a first-of-its-kind demonstration of how PhysMAP can help understand how multiple cell types interact to drive circuit dynamics. Collectively, these results demonstrate that multimodal representations from PhysMAP enable the study of multiple cell types simultaneously, thus providing insight into neural circuit dynamics.

neuroscience↗

bioRxiv2025

Modeling acquired TKI resistance and effective combination therapeutic strategies in murine RET+ lung adenocarcinoma

RET gene rearrangements yield oncogenic fusion proteins that drive a subset of lung adenocarcinomas (LUAD). The tyrosine kinase inhibitors (TKIs) selpercatinib and pralsetinib are approved therapies for RET+ lung cancers and have markedly improved clinical outcomes in these patients, but acquired resistance remains a hurdle to their durable management. Using a recently developed murine model of RET+ lung cancer driven by a Trim24-Ret fusion protein, two Trim24-Ret cell lines (TR.1 and TR.2) were established. Orthotopic lung tumors generated by transplantation of these cell lines initially respond to selpercatinib followed by prompt progression within [~]3 weeks of initiating TKI treatment. Cell lines derived from the selpercatinib-resistant TR.1 and TR.2 tumors exhibited in vitro sensitivity to MET and ERBB-targeted TKIs, indicating acquired bypass signaling through these receptor tyrosine kinases. Moreover, the selpercatinib-resistant TR.1 and TR.2 cell lines exhibited increased sensitivity to MEK and PTPN11 inhibitors relative to the parental cell lines, indicating a greater dependence on MAPK pathway signaling. The TKI-resistant cell lines showed no evidence for MET gene amplification, but exhibited varied induction of multiple genes that function within MET and ERBB2:ERBB4 interaction networks including ligands (HGF, NRG1), adaptors (GAB1) and co-receptors (NRP1). Consistent with an important role for MET signaling in driving acquired selpercatinib resistance, mice bearing orthotopic lung tumors derived from TR.1 or TR.2 cells that had progressed on selpercatinib treatment underwent significant re-shrinkage upon co-treatment with the MET inhibitor, crizotinib, although progression re-occurred. By contrast, upfront treatment with selpercatinib and crizotinib in orthotopic tumors yielded complete elimination of 78% of TR.1 tumors and a prolonged duration of response in TR.2 tumors. The findings highlight the failings inherent in treating acquired resistance mechanisms at progression and the potential therapeutic impact of predicting and targeting dominant mechanisms of resistance prior to or early after initiating oncogene-targeting TKI treatment in RTK-driven LUAD.

cancer biology↗

bioRxiv2024

The serotonergic psychedelic DOI impairs deviance detection in the auditory cortex

Psychedelics are known to induce profound perceptual distortions, yet the neural mechanisms underlying these effects, particularly within the auditory system, remain poorly understood. In this study, we investigated the effects of the psychedelic compound 2,5-Dimethoxy-4-iodoamphetamine (DOI), a serotonin 2A receptor agonist, on the activity of neurons in the auditory cortex of awake mice. We examined whether DOI administration alters sound-frequency tuning, variability in neural responses, and deviance detection (a neural process reflecting the balance between top-down and bottom-up processing). Our results show that while DOI does not alter the frequency selectivity of auditory cortical neurons in a consistent manner, it increases trial-by-trial variability in responses and consistently diminishes the neural distinction between expected (standard) and unexpected (oddball) stimuli. This reduction in deviance detection was primarily driven by a decrease in the response to oddball sounds, suggesting that DOI dampens the auditory cortexs sensitivity to unexpected events. These findings provide insights into how psychedelics disrupt sensory processing and shed light on the neural mechanisms underlying the altered perception of auditory stimuli observed in the psychedelic state. New & NoteworthyThe neural basis of perceptual distortions induced by psychedelics remains poorly understood. This study demonstrates that the serotonergic psychedelic DOI increases neural response variability and impairs deviance detection in the auditory cortex by reducing sensitivity to unexpected sounds. These findings provide new insights into how psychedelics disrupt sensory processing and alter the balance between bottom-up and top-down neural signaling, contributing to our understanding of altered perception in the psychedelic state.

neuroscience↗

bioRxiv2024

PhysMAP - interpretable in vivo neuronal cell type identification using multi-modal analysis of electrophysiological data

Cells of different types perform diverse computations and coordinate their activity during sensation, perception, and action. While electrophysiological approaches can measure the activity of many neurons simultaneously, assigning cell type labels to these neurons is an open problem. Here, we develop PhysMAP, a framework that weighs multiple electrophysiological modalities simultaneously in an unsupervised manner and obtain an interpretable representation that separates neurons by cell type. PhysMAP is superior to any single electrophysiological modality in identifying neuronal cell types such as excitatory pyramidal, PV+ interneurons, and SOM+ interneurons with high confidence in both juxtacellular and extracellular recordings and from multiple areas of the mouse brain. PhysMAP built on ground truth data can be used for classifying cell types in new and existing electrophysiological datasets, and thus facilitate simultaneous assessment of the coordinated dynamics of multiple neuronal cell types during behavior.

neuroscience↗

bioRxiv2023

Passive exposure to task-relevant stimuli enhances categorization learning

Learning to perform a perceptual decision task is generally achieved through sessions of effortful practice with feedback. Here, we investigated how passive exposure to task-relevant stimuli, which is relatively effortless and does not require feedback, influences active learning. First, we trained mice in a sound-categorization task with various schedules combining passive exposure and active training. Mice that received passive exposure exhibited faster learning, regardless of whether this exposure occurred entirely before active training or was interleaved between active sessions. We next trained neural-network models with different architectures and learning rules to perform the task. Networks that use the statistical properties of stimuli to enhance separability of the data via unsupervised learning during passive exposure provided the best account of the behavioral observations. We further found that, during interleaved schedules, there is an increased alignment between weight updates from passive exposure and active training, such that a few interleaved sessions can be as effective as schedules with long periods of passive exposure before active training, consistent with our behavioral observations. These results provide key insights for the design of efficient training schedules that combine active learning and passive exposure in both natural and artificial systems.

neuroscience↗

bioRxiv2023

Transitions between discrete performance states in auditory and visual tasks are predicted by arousal and uninstructed movements

During sensory-guided behavior, an animals decision-making dynamics unfold through sequences of distinct performance states, even while stimulus-reward contingencies remain static. Little is known about the factors that underlie these changes in task performance. We hypothesize that these decision-making dynamics can be predicted by externally observable measures, such as uninstructed movements and changes in arousal. Here, combining behavioral experiments in mice with computational modeling, we uncovered lawful relationships between transitions in strategic task performance states and an animals arousal and uninstructed movements. Using hidden Markov models applied to behavioral choices during sensory discrimination tasks, we found that animals fluctuate between minutes-long optimal, sub-optimal and disengaged performance states. Optimal state epochs were predicted by intermediate levels, and reduced variability, of pupil diameter, along with reduced variability in face movements and locomotion. Our results demonstrate that externally observable uninstructed behaviors can predict optimal performance states, and suggest mice regulate their arousal during optimal performance.

neuroscience↗

bioRxiv2022

Sound-evoked responses of distinct neuron classes from the tail of the striatum

Given its inputs from auditory structures and neuromodulatory systems, the posterior tail of the striatum is ideally positioned to influence behavioral responses to acoustic stimuli according to context and previous rewards. Results from previous studies indicate that neurons in this striatal region display selective responses to sounds. However, it is not clear whether different striatal cell classes code for distinct features of sounds, nor how different striatal output pathways may use acoustic information to guide behavior. Here we compared the sound-evoked responses of posterior striatal neurons that form the striatal direct pathway (and express the dopamine receptor D1) to the responses of neighboring neurons in naive mice. We achieved this via optogenetic photo-identification of D1-expressing neurons during extracellular electrophysiological recordings in awake head-fixed mice of both sexes. We found that the frequency tuning of sound-responsive direct-pathway striatal neurons is comparable to that of their sound-responsive neighbors. Moreover, we found that both populations encode amplitude modulated sounds in a similar fashion. These results suggest that different classes of neurons in the posterior striatum of naive animals have similar access to acoustic features conveyed by the auditory system even outside the context of an auditory task.

neuroscience↗

bioRxiv2021

Contributions of distinct auditory cortical inhibitory neuron types to the detection of sounds in background noise

The ability to separate background noise from relevant acoustic signals is essential for appropriate sound-driven behavior in natural environments. Examples of this separation are apparent in the auditory system, where neural responses to behaviorally relevant stimuli become increasingly noise-invariant along the ascending auditory pathway. However, the mechanisms that underlie this reduction in responses to background noise are not well understood. To address this gap in knowledge, we first evaluated the effects of auditory cortical inactivation on mice of both sexes trained to perform a simple auditory signal-in-noise detection task, and found that outputs from the auditory cortex are important for the detection of auditory stimuli in noisy environments. Next, we evaluated the contributions of the two most common cortical inhibitory cell types, parvalbumin-expressing (PV+) and somatostatin-expressing (SOM+) interneurons, to the perception of masked auditory stimuli. We found that inactivation of either PV+ or SOM+ cells resulted in a reduction in the ability of mice to determine the presence of auditory stimuli masked by noise. These results indicate that a disruption of auditory cortical network dynamics by either of these two types of inhibitory cells is sufficient to impair the ability to separate acoustic signals from noise. Significance StatementAppropriate behavior in a natural environment relies on the ability to separate background noise from relevant signals. We found that auditory cortical inhibitory neurons play a causal role in separating environmental noise from behaviorally relevant auditory signals. These results advance our understanding of the computations performed by the auditory system to decompose and analyze acoustic stimuli in the presence of noise.

neuroscience↗

bioRxiv2021

FXa cleaves the SARS-CoV-2 spike protein and blocks cell entry to protect against infection with inferior effects in B.1.1.7 variant

The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human natural defense mechanisms against SARS-CoV-2 are largely unknown. Serine proteases (SPs) including furin and TMPRSS2 cleave SARS-CoV-2 spike protein, facilitating viral entry. Here, we show that FXa, a SP for blood coagulation, is upregulated in COVID-19 patients compared to non-COVID-19 donors and exerts anti-viral activity. Mechanistically, FXa cleaves the SARS-CoV-2 spike protein, which prevents its binding to ACE2, and thus blocks viral entry. Furthermore, the variant B.1.1.7 with several mutations is dramatically resistant to the anti-viral effect of FXa compared to wild-type SARA-CoV-2 in vivo and in vitro. The anti-coagulant rivaroxaban directly inhibits FXa and facilitates viral entry, whereas the indirect inhibitor fondaparinux does not. In a lethal humanized hACE2 mouse model of SARS-CoV-2, FXa prolonged survival while combination with rivaroxaban but not fondaparinux abrogated this protection. These preclinical results identify a previously unknown SP function and associated anti-viral host defense mechanism and suggest caution in considering direct inhibitors for prevention or treatment of thrombotic complications in COVID-19 patients.

microbiology↗

bioRxiv2021

The K18-hACE2 Transgenic Mouse Model Recapitulates Non-Severe and Severe COVID-19 in Response to Infectious Dose of SARS-CoV-2 Virus

A comprehensive analysis and characterization of a SARS-CoV-2 infection model that mimics non-severe and severe COVID-19 in humans is warranted for understating the virus and developing preventive and therapeutic agents. Here, we characterized the K18-hACE2 mouse model expressing human (h)ACE2 in mice, controlled by the human keratin 18 (K18) promoter, in epithelia, including airway epithelial cells where SARS-CoV-2 infections typically start. We found that intranasal inoculation with higher viral doses (2x103 and 2x104 PFU) of SARS-CoV-2 caused lethality of all mice and severe damage of various organs, including lungs, liver, and kidney, while lower doses (2x101 and 2x102 PFU) led to less severe tissue damage and some mice recovered from the infection. In this humanized hACE2 mouse model, SARS-CoV-2 infection damaged multiple tissues, with a dose-dependent effect in most tissues. Similar damage was observed in biopsy samples from COVID-19 patients. Finally, the mice that recovered after infection with a low dose of virus also survived rechallenge with a high dose of virus. Compared to other existing models, the K18-hACE2 model seems to be the most sensitive COVID-19 model reported to date. Our work expands the information available about this model to include analysis of multiple infectious doses and various tissues with comparison to human biopsy samples from COVID-19 patients. In conclusion, the K18-hACE2 mouse model recapitulates both severe and non-severe COVID-19 in humans and can provide insight into disease progression and the efficacy of therapeutics for preventing or treating COVID-19. ImportanceThe pandemic of COVID-19 has reached 112,589,814 cases and caused 2,493,795 deaths worldwide as of February 23, 2021, has raised an urgent need for development of novel drugs and therapeutics to prevent the spread and pathogenesis of SARS-CoV-2. To achieve this goal, an animal model that recapitulates the features of human COVID-19 disease progress and pathogenesis is greatly needed. In this study, we have comprehensively characterized a mouse model of SARS-CoV-2 infection using K18-hACE2 transgenic mice. We infected the mice with low and high doses of SARS-CoV-2 virus to study the pathogenesis and survival in response to different infection patterns. Moreover, we compared the pathogenesis of the K18-hACE2 transgenic mice with that of the COVID-19 patients to show that this model could be a useful tool for the development of anti-viral drugs and therapeutics.

microbiology↗

bioRxiv2018

Response outcomes gate the impact of expectations on perceptual decisions

Perceptual decisions are not only determined by current sensory information but are also influenced by recent experience. Can the magnitude of expectation-based decision biases be flexibly modulated based on the outcome of previous decisions? We trained rats in several two-alternative forced choice auditory tasks, where the probability to repeat the previous stimulus category was varied in blocks of trials. All rats capitalized on the serial correlations of the stimulus sequence by consistently exploiting a transition bias: a tendency to repeat or alternate their previous response using an internal trial-by-trial estimate of the sequence repeating probability. Surprisingly, this expectation bias was null in trials immediately following an error. The internal estimate however was not reset and it became effective again causing a bias after the next correct response. This ability to rapidly activate and inactivate the bias was captured by a non-linear generative model of rat behavior, whereby a reward-driven modulatory signal gated the use of the latent estimate of the environment statistics on the current decision. These results demonstrate that rats use behavioral outcomes to flexibly modulate how expectations derived from the recent history influence their decisions.

neuroscience↗

bioRxiv2017

Stable representation of sounds in the posterior striatum during flexible auditory decisions

The neuronal pathways that link sounds to rewarded actions remain elusive. It is unclear whether neurons in the posterior tail of the dorsal striatum (which receive direct input from the auditory system) mediate action selection, as other striatal circuits do. Here, we examined the role of posterior striatal neurons in auditory decisions in mice. We found that, in contrast to the anterior dorsal striatum, activation of the posterior striatum did not elicit systematic movement. However, activation of posterior striatal neurons during sound presentation in an auditory discrimination task biased the animals choices, and transient inactivation of these neurons largely impaired sound discrimination. Moreover, the activity of these neurons reliably encoded stimulus features, but was only minimally influenced by the animals choices. Our results suggest that posterior striatal neurons play an essential role in auditory decisions, yet these neurons provide sensory information downstream rather than motor commands during well-learned sound-driven tasks.

neuroscience↗