Biology subjects

Ramirez, J. A.

Publications and source records attributed to Ramirez, J. A..

3 recordsLinked to original sources

bioRxiv2023

Increased FAN1 expression by mRNA-LNP attenuates CAG repeat expansion in Huntington patients' iPSC-derived astrocytes

Expansion of repeat sequences within the human genome can lead to disease pathogenesis, such as Huntingtons Disease, primarily affecting the nervous system. Genome-wide association studies (GWAS) of age-at-onset in Huntingtons disease (HD) patients demonstrated DNA mismatch repair (MMR) genes are modifiers of somatic expansion and may be potential therapeutic targets for repeat expansion (RE) disorders. FAN1, a Fanconi anemia-associated nuclease, has been reported as an influencer of repeat expansion in the RE mouse models. Here, we show the first demonstration that FAN1 knock-out in HD patient-derived fibroblasts and results in increased CAG repeat length. We also develop a robust novel cell-based platform using stem cell technology to produce the HD patients iPSC-derived astrocytes (iAstro). This platform is a disease-relevant system and has a significantly wider assay window, making it more suitable to assess the effect of gene modulation on CAG repeats. A substantial and exponential increase in repeat instability was exhibited in this HD patients iPSC-derived astrocytes platform. Over-expression of FAN1 protein via FAN1 plasmid transfection in this platform reduced CAG repeat instability, suggesting that upregulation of FAN1 protein may have a potential protective effect in CAG repeat expansion for a therapeutic setting. We leveraged the mRNA-LNP modality to enhance FAN1 protein expression and revealed that codon-optimized FAN1 mRNA-LNP robustly prevented increased CAG repeat in HD patients iPSC-derived astrocytes platform. The data from these cell-based platforms highlight that FAN1 plays a protective role in attenuating expanded somatic HTT CAG repeats and shed light on new therapeutic directions against repeat expansion disorders.

neuroscience↗

bioRxiv2022

Host Age Structure Defines Interactions with Pathogens: Grandparent Effect under Collaboration and Virulent Mutualism under Competition

BackgroundSymbiotic relationships are ubiquitous in the biosphere. Inter-species symbiosis is impacted by intra-specific distinctions, in particular, those defined by the age structure of a population. Older individuals compete with younger individuals for resources despite being less likely to reproduce, diminishing the fitness of the population. Conversely, however, older individuals can support the reproduction of younger individuals, increasing the population fitness. Parasitic relationships are commonly age structured, typically, more adversely affecting older hosts. ResultsWe employ mathematical modeling to explore the differential effects of collaborative or competitive host age structures on host-parasite relationships. A classical epidemiological compartment model is constructed with three disease states: susceptible, infected, and recovered. Each of these three states is partitioned into two compartments representing young, potentially reproductive, and old, post-reproductive, hosts, yielding 6 compartments in total. In order to describe competition and collaboration between old and young compartments, we model the reproductive success to depend on the fraction of young individuals in the population. Collaborative populations with relatively greater numbers of post-reproductive hosts enjoy greater reproductive success whereas in purely competitive populations, increase of the post-reproductive subpopulation reduces reproductive success. However, in competitive populations, virulent pathogens preferentially targeting old individuals can increase the population fitness. ConclusionsWe demonstrate that, in collaborative host populations, pathogens strictly impacting older, post-reproductive individuals can reduce population fitness even more than pathogens that directly impact younger, potentially reproductive individuals. In purely competitive populations, the reverse is observed, and we demonstrate that endemic, virulent pathogens can oxymoronically form a mutualistic relationship with the host, increasing the fitness of the host population. Applications to endangered species conservation and invasive species containment are discussed.

evolutionary biology↗

bioRxiv2020

Discovery and Predictive Modeling of Urine Microbiome, Metabolite and Cytokine Biomarkers in Hospitalized Patients with Community Acquired Pneumonia

Pneumonia is the leading cause of infectious related death costing 12 billion dollars annually in the United States alone. Despite improvements in clinical care, total mortality remains around 4%, with inpatient mortality reaching 5-10%. For unknown reasons, mortality risk remains high even after hospital discharge and there is a need to identify those patients most at risk. Also of importance, clinical symptoms alone do not distinguish viral from bacterial infection which may delay appropriate treatment and may contribute to short-term and long-term mortality. Biomarkers have the potential to provide point of care diagnosis, identify high-risk patients, and increase our understanding of the biology of disease. However, there have been mixed results on the diagnostic performance of many of the analytes tested to date. Urine represents a largely untapped source for biomarker discovery and is highly accessible. To test this hypothesis, we collected urine from hospitalized patients with community-acquired pneumonia (CAP) and performed a comprehensive screen for urinary tract microbiota signatures, metabolite, and cytokine profiles. CAP patients were diagnosed with influenza or bacterial (S. aureus and S. pneumoniae) etiologies and compared with healthy volunteers. Microbiome signatures showed marked shifts in taxonomic levels in patients with bacterial etiology versus influenza and CAP versus normal. Predictive modeling of 291 microbial and metabolite values achieved a +90% accuracy with LASSO in predicting specific pneumonia etiology. This study demonstrates that urine from patients hospitalized with pneumonia may serve as a reliable and accessible sample to evaluate biomarkers that may diagnose etiology and predict clinical outcomes. Author SummaryUrine has been classically considered sterile since most microorganisms are not readily culturable under healthy circumstances. Further, many pneumonia patients are immediately placed on antibiotics rendering culture-based techniques useless. However, the advent of next generation sequencing has enabled unprecedented analysis of the microbial communities - living or detected as free DNA - found in many niches of the human body. Here, we describe a urine microbiome as well as metabolites and cytokines measured in patients newly admitted to the hospital diagnosed with influenza or bacterial (S. aureus and S. pneumoniae) infection pneumonia, compared with healthy controls. Using these parameters alone, we were able to achieve high success in predicting patient pneumonia. This study provides a proof of concept that urine samples, which are easily accessible in outpatient and inpatient settings, could provide additional diagnostic insights to patient infectious status and future risk factor for complication.

systems biology↗