Biology subjects

Suh, E.

Publications and source records attributed to Suh, E..

12 recordsLinked to original sources

bioRxiv2026

Patient-Derived Synovium-on-a-Chip Recapitulates Disease and Treatment Response and Permits Study of Resistance

Rheumatoid arthritis (RA) is a chronic inflammatory disease with substantial interpatient heterogeneity in synovial pathology and therapeutic response. Reliable methods to predict drug efficacy for a given patients remain a critical unmet need. We developed a vascularized, immunocompetent synovium-on-a-chip platform that integrates patient-derived fibroblast-like synoviocytes (FLS) with matched peripheral blood leukocytes to provide a physiological human model of RA. The platform reconstructed the lining-sublining synovial architecture, recapitulated key features of RA inflammation, and exhibited transcriptional profiles resembling those of patient synovial tissue. Across patients spanning low, mixed, and high inflammatory endotypes, stromal-vascular organization was associated with distinct immune cell positioning and activation patterns, and on-chip immune phenotypes correlated with histological joint inflammation scores. We then tested infliximab, tocilizumab, and tofacitinib in parallel and integrated cytokine secretion, extracellular matrix remodeling, immune cell survival and immune cell recruitment into a composite treatment response score. On-chip scores for clinically matched treatments correlated with clinical improvement measured by {Delta}DAS28-ESR (Pearson r = 0.844). To investigate the cellular basis of heterogeneous drug responses, single-cell RNA sequencing identified SFRP1 remodeling FLS that persisted under treatment and exhibited high inflammatory programs in poorly responding chips. Cell-cell communication analysis linked reduced FN1-CD44 signaling toward SFRP1 remodeling FLS to higher NF-{kappa}B activity and drug resistance. We tested the functional relevance of this finding in chips derived from an independent TNFi-nonresponsive patient, where fibronectin supplementation reduced IL-6 secretion and restored the composite treatment response. Together, these findings support patient-derived synovium-on-a-chip as a platform for individualized drug evaluation and identify ECM-mediated niche signaling as a potential therapeutic target for overcoming drug resistance in RA.

bioengineering↗

bioRxiv2025

Hologenomic structure of bacterial and fungal community composition in the West Nile virus vector Culex tarsalis

BackgroundMicrobiota play a crucial role in determining the ability for arthropod disease vectors to transmit pathogens. Microbial community structure can be heavily influenced by microbe-microbe interactions, host genetics and environmental factors. Here, we characterize the host population genetic structure, and bacterial and fungal communities in natural populations of the West Nile virus mosquito vector Culex tarsalis. Mosquitoes were collected and analyzed across the species range of the mosquito in the United States, where we used PoolRADSeq to quantify population genetic structure. Microbial community composition was characterized using bacterial 16S rRNA gene sequencing (V3-V4 region) and fungal ITS sequencing (ITS1 region). ResultsPoolRADSeq identified four broad genetic clusters of mosquito populations, which corresponded to previous clusters identified by microsatellite analysis and RADSeq on individual mosquitoes. Microbiome diversity grouped mosquito populations into three broad clusters, with each cluster distinctively represented by diagnostic abundant bacteria (Ralstonia, Pseudomonas, or Zymobacter/Providencia, respectively). Clustering for fungal taxa was less pronounced. Geographic distance between populations was positively correlated with microbiome community dissimilarity, and multiple environmental factors were significantly correlated with microbial species richness and diversity. ConclusionsThese results suggest that bacterial and fungal communities are geographically structured in Cx. tarsalis, interact with important environmental factors, and are partially correlated with host genetic structure. As microbiota can affect the ability for mosquitoes to transmit pathogens, understanding the factors underpinning microbiome variation across space and time has important implications for the spread of vector-borne pathogens such as WNV.

ecology↗

bioRxiv2025

Virome profiling of Culex tarsalis through small RNA-seq: A challenge of suboptimal samples

Viral infections in mosquitoes trigger the RNA interference (RNAi) pathway, a key antiviral defense mechanism that generates virus-derived small RNAs (vsRNAs). Given the natural enrichment of vsRNAs during infection and their stability, small RNA sequencing (sRNA-seq) has emerged as a powerful tool for virome characterization. Culex tarsalis is a widely distributed mosquito species in North America and is an important vector of West Nile virus (WNV). Previous studies have shown that co-infection with insect-specific viruses (ISVs) can modulate WNV replication in Cx. tarsalis, highlighting the importance of characterizing the virome of this species. Here, we investigated the virome of Cx. tarsalis populations across 5 states of the Midwestern United States using sRNA-seq. We analyzed samples from 17 geographic locations which were collected under suboptimal field conditions during the COVID-19 pandemic, presenting challenges related to sample integrity. Despite these challenges, sRNA-seq proved to be a reliable method for virome analysis. We identified seven viruses associated with Cx. tarsalis, along with their respective sRNA (siRNA and piRNA) profiles. These findings not only deepen our understanding of ISVs, but also demonstrate the utility of sRNA-seq in non-ideal situations, enabling the collection and analysis of samples under real-world surveillance scenarios.

microbiology↗

bioRxiv2024

Creating a biomedical knowledge base by addressing GPT inaccurate responses and benchmarking context

We created GNQA, a generative pre-trained transformer (GPT) knowledge base driven by a performant retrieval augmented generation (RAG) with a focus on aging, dementia, Alzheimers and diabetes. We uploaded a corpus of three thousand peer reviewed publications on these topics into the RAG. To address concerns about inaccurate responses and GPT hallucinations, we implemented a context provenance tracking mechanism that enables researchers to validate responses against the original material and to get references to the original papers. To assess the effectiveness of contextual information we collected evaluations and feedback from both domain expert users and citizen scientists on the relevance of GPT responses. A key innovation of our study is automated evaluation by way of a RAG assessment system (RAGAS). RAGAS combines human expert assessment with AI-driven evaluation to measure the effectiveness of RAG systems. When evaluating the responses to their questions, human respondents give a "thumbs-up" 76% of the time. Meanwhile, RAGAS scores 90% on answer relevance on questions posed by experts. And when GPT-generates questions, RAGAS scores 74% on answer relevance. With RAGAS we created a benchmark that can be used to continuously assess the performance of our knowledge base. Full GNQA functionality is embedded in the free GeneNetwork.org web service, an open-source system containing over 25 years of experimental data on model organisms and human. The code developed for this study is published under a free and open-source software license at https://git.genenetwork.org/gn-ai/tree/README.md.

scientific communication and education↗

bioRxiv2024

Stat3-mediated Atg7 expression enhances anti-tumor immunity in melanoma

Epigenetic modifications to DNA and chromatin control oncogenic and tumor suppressive mechanisms in melanoma. EZH2, the catalytic component of the Polycomb repressive complex 2 (PRC2), which mediates methylation of lysine 27 on histone 3 (H3K27me3), can regulate both melanoma initiation and progression. We previously found that mutant Ezh2Y641F interacts with the immune regulator Stat3 and together they affect anti-tumor immunity. However, given the numerous downstream targets and pathways affected by EZH2, many mechanisms that determine its oncogenic activity remain largely unexplored. Using genetically engineered mouse models we further investigated the role of pathways downstream of EZH2 in melanoma carcinogenesis and identified significant enrichment in several autophagy signatures, along with increased expression of autophagy regulators, such as Atg7. In this study, we investigated the effect of Atg7 on melanoma growth and tumor immunity within the context of an Ezh2Y641F epigenetic state. We found that expression of Atg7 is largely dependent on Stat3 expression and that deletion of Atg7 slows down melanoma cell growth in vivo, but not in vitro. Atg7 deletion also results in increased CD8+ T cells and reduced myelosuppressive cell infiltration in the tumor microenvironment, suggesting a strong immune system contribution in the role of Atg7 in melanoma progression. These findings highlight the complex interplay between genetic mutations, epigenetic regulators, and autophagy in shaping tumor immunity in melanoma.

cancer biology↗

bioRxiv2023

Temperature and transmission: novel estimates of the effects of temperature on the human malaria parasite, Plasmodium falciparum

Malaria transmission is strongly influenced by traits such as mosquito life expectancy, vector competence, and the Extrinsic Incubation Period (EIP, which is the development time of the parasite inside the mosquito). Even though these traits are known to be shaped by environmental temperature and there is considerable concern that climate change could increase disease risk in certain areas, surprisingly, these temperature dependencies are poorly characterized. Here, we use a mechanistic model fitted to novel experimental data to describe how Plasmodium falciparum infection of the African malaria vector, Anopheles gambiae, is modulated by temperature, including its influences on parasite establishment, conversion efficiency through parasite developmental stages, EIP and overall competence. We use these data, together with novel estimates of the survival of infected blood-fed mosquitoes, to explore the potential influence of temperature on transmission in four locations in Kenya, considering recent conditions and future climate change. Results provide insights into factors limiting transmission in cooler environments and indicate that increases in malaria transmission efficiency due to climate warming in areas like the Kenyan Highlands, might be less than previously predicted.

microbiology↗

bioRxiv2022

Glucocerebrosidase activity and lipid levels are related to protein pathologies in Parkinson's disease

Parkinsons disease (PD) and dementia with Lewy bodies (DLB) are progressive neurodegenerative diseases characterized by the accumulation of misfolded -synuclein in the form of Lewy pathology. While most cases are sporadic, there are rare genetic mutations that cause disease and more common variants that increase incidence of disease. The most prominent genetic mutations for PD and DLB are in the GBA1 and LRRK2 genes. GBA1 mutations are associated with decreased glucocerebrosidase activity and lysosomal accumulation of its lipid substrates, glucosylceramide and glucosylsphingosine. Previous studies have shown a link between this enzyme and lipids even in sporadic PD. However, it is unclear how the protein pathologies of disease are related to enzyme activity and glycosphingolipid levels. To address this gap in knowledge, we examined quantitative protein pathology, glucocerebrosidase activity and lipid substrates in parallel from 4 regions of 91 brains with no neurological disease, idiopathic, GBA1-linked, or LRRK2-linked PD and DLB. We find that several biomarkers are altered with respect to mutation and disease severity. We found mild association of glucocerebrosidase activity with disease, but a strong association of glucosylsphingosine with -synuclein pathology, irrespective of genetic mutation. This association suggests that Lewy pathology precipitates changes in lipid levels related to disease severity.

neuroscience↗

bioRxiv2020

Using a non-destructive sugar-feeding assay for sporozoite detection and estimating the extrinsic incubation period of Plasmodium falciparum in mosquito vectors

Despite its epidemiological importance, the time Plasmodium parasites take to achieve development in the vector mosquito (the extrinsic incubation period, EIP) remains poorly characterized. A novel non-destructive assay designed to estimate EIP in single mosquitoes, and more broadly to study Plasmodium - Anopheles vectors interactions, is presented. The assay uses small pieces of cotton wool soaked in sugar solution to collect malaria sporozoites from individual mosquitoes during sugar feeding to monitor infection status over time. This technique has been tested across four natural malaria mosquito species of Africa and Asia, six parasite isolates of Plasmodium falciparum, and across a range of temperatures relevant to malaria transmission in field conditions. We find that monitoring individual infectious mosquitoes is feasible, although due to the frequency of mosquito sugar feeding and inter-individual variation in infection intensity, there is inherent risk that this technique will result in some false negatives. The sensitivity rate ranged from 0.27 to 0.81 depending on mosquito species and on infection intensity in mosquitoes used to collect saliva. Using this non-destructive technique, the estimated median extrinsic incubation period of P. falciparum at 27{degrees}C was 11 to 14 days depending on mosquito species and parasite isolate. Long-term individual tracking also revealed that sporozoite transfer onto cotton wool can occur at least until day 40 post-infection. In addition to contributing to a better understanding of EIP and mosquito to human transmission with implications for improving epidemiological models, this technique also allows to link different transmission traits at the mosquito individual level. As one example, we found a significant relationship between EIP and mosquito lifespan, with short individual EIP associated with short mosquito lifespan. Correlations between mosquito/parasite traits often reveal trade-offs and constraints and have important implications for understanding the evolution of parasite transmission strategies.

molecular biology↗

bioRxiv2020

St. Jude Cloud a Pediatric Cancer Genomic Data Sharing Ecosystem

Effective data sharing is key to accelerating research that will improve the precision of diagnoses, efficacy of treatments and long-term survival of pediatric cancer and other childhood catastrophic diseases. We present St. Jude Cloud (https://www.stjude.cloud), a cloud-based data sharing ecosystem developed via collaboration between St. Jude Childrens Research Hospital, DNAnexus, and Microsoft, for accessing, analyzing and visualizing genomic data from >10,000 pediatric cancer patients, long-term survivors of pediatric cancer and >800 pediatric sickle cell patients. Harmonized genomic data totaling 1.25 petabyes on St. Jude Cloud include 12,104 whole genomes, 7,697 whole exomes and 2,202 transcriptomes, which are freely available to researchers worldwide. The resource is expanding rapidly with regular data uploads from St. Judes prospective clinical genomics programs, providing public access as soon as possible rather than holding data back until publication. Three interconnected apps within the St. Jude Cloud ecosystem--Genomics Platform, Pediatric Cancer Knowledgebase (PeCan) and Visualization Community--provide a unique experience for simultaneously performing advanced data analysis in the cloud and enhancing the pediatric cancer knowledgebase. We demonstrate the value of the St. Jude Cloud ecosystem through use cases that classify 48 pediatric cancer subtypes by gene expression profiling and map mutational signatures across 35 subtypes of pediatric cancer.

cancer biology↗

bioRxiv2019

ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data

Classification algorithms assign observations to groups based on patterns in data. The machine-learning community have developed myriad classification algorithms, which are employed in diverse life-science research domains. When applying such algorithms, researchers face the challenge of deciding which algorithm(s) to apply in a given research domain. Algorithm choice can affect classification accuracy dramatically, so it is crucial that researchers optimize these choices based on empirical evidence rather than hearsay or anecdotal experience. In benchmark studies, multiple algorithms are applied to multiple datasets, and the researcher examines overall trends. In addition, the researcher may evaluate multiple hyperparameter combinations for each algorithm and use feature selection to reduce data dimensionality. Although software implementations of classification algorithms are widely available, robust benchmark comparisons are difficult to perform when researchers wish to compare algorithms that span multiple software packages.\n\nProgramming interfaces, data formats, and evaluation procedures differ across software packages; and dependency conflicts may arise during installation. To address these challenges, we created ShinyLearner, an open-source project for integrating machine-learning packages into software containers. ShinyLearner provides a uniform interface for performing classification, irrespective of the library that implements each algorithm, thus facilitating benchmark comparisons. In addition, ShinyLearner enables researchers to optimize hyperparameters and select features via nested cross validation; it tracks all nested operations and generates output files that make these steps transparent. ShinyLearner includes a Web interface to help users more easily construct the commands necessary to perform benchmark comparisons. ShinyLearner is freely available at https://github.com/srp33/ShinyLearner.

bioinformatics↗

bioRxiv2019

Thermal ecology of malaria transmission and the potential impact of behavioural resistance

Insecticide-treated bed nets reduce malaria transmission by limiting contact between mosquito vectors and human hosts when mosquitoes feed during the night. However, malaria vectors can also feed in the early evening and in the morning when people are not protected. Here, we explored how timing of blood feeding interacts with environmental temperature to influence the capacity of Anopheles mosquitoes to transmit the human malaria parasite, Plasmodium falciparum. We found no effect of biting time itself on the proportion of mosquitoes that became infectious (vector competence) at constant temperature. However, when mosquitoes were maintained under more realistic fluctuating temperatures there was a significant increase in competence for mosquitoes feeding in the evening, and a significant reduction in competence for those feeding in the morning, relative to those feeding at midnight. These effects appear to be due to thermal sensitivity of malaria parasites during the initial stages of parasite development within the mosquito, and the fact that mosquitoes feeding in the evening experience cooling temperatures during the night, whereas mosquitoes feeding in the morning quickly experience warming temperatures that are inhibitory to parasite establishment. A transmission dynamics model illustrates that such differences in competence could have important implications for disease endemicity, the extent of transmission that persists in the presence of bed nets, and the epidemiological impact of behavioural resistance. These results indicate the interaction of temperature and feeding behaviour to be a major ecological determinant of the vectorial capacity of malaria mosquitoes.

ecology↗

bioRxiv2019

Exploring the lower thermal limits for transmission of human malaria, Plasmodium falciparum

The rate of malaria transmission is strongly determined by parasite development time in the mosquito, known as the extrinsic incubation period (EIP), since the quicker parasites develop, the greater the chance that the vector will survive long enough for the parasite to complete development and be transmitted. EIP is known to be temperature dependent but this relationship is surprisingly poorly characterized. There is a single degree-day model for EIP of Plasmodium falciparum that derives from a limited number of poorly controlled studies conducted almost a century ago. Here, we show that the established degree-day model greatly underestimates the rate of development of P. falciparum in both Anopheles stephensi and An. gambiae mosquitoes at temperatures in the range of 17-20{degrees}C. We also show that realistic daily temperature fluctuation further speeds parasite development. These novel results challenge one of the longest standing models in malaria biology and have potentially important implications for understanding the impacts of climate change.

ecology↗