Biology subjects

Zeng, Y.

Publications and source records attributed to Zeng, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2023

A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge

Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional nearinfrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural selfregulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.

neuroscience↗

bioRxiv2023

MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis

Summarycell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) has emerged as a promising non-invasive technology to detect cancers and monitor treatments. Several bioinformatics tools are available for cfMeDIP-seq data analysis. However, an easy to implement and flexible pipeline, particularly, for large-scale cfMeDIP-seq profiling, is still lacking. Here we present the MEDIPIPE, which provides a one-stop solution for cfMeDIP-seq data quality control, methylation quantification and sample aggregation. The major advantages of MEDIPIPE are: 1) it is easy to implement and reproduce with automatically deployed execution environments; 2) it can handle different experimental settings with a single input configuration file; 3) it is computationally efficient for large-scale cfMeDIP-seq profiling data analysis and aggregation. Availability and implementationThis pipeline is an open-source software under the MIT license and it is freely available at https://github.com/yzeng-lol/MEDIPIPE. Contactyzeng@uhnresearch.ca or trevor.pugh@utoronto.ca or hansenhe@uhnresearch.ca Supplementary informationSupplementary data are appended.

bioinformatics↗

bioRxiv2023

Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy

Computational super-resolution (SR) methods, including conventional analytical algorithms and deep learning models, have substantially improved optical microscopy. Among them, supervised deep neural networks have demonstrated outstanding SR performance, however, demanding abundant high-quality training data, which are laborious and even impractical to acquire due to the high dynamics of living cells. Here, we develop zero-shot deconvolution networks (ZS-DeconvNet) that instantly enhance the resolution of microscope images by more than 1.5-fold over the diffraction limit with 10-fold lower fluorescence than ordinary SR imaging conditions in an unsupervised manner without the need for either ground truths or additional data acquisition. We demonstrate the versatile applicability of ZS-DeconvNet on multiple imaging modalities, including total internal reflection fluorescence microscopy, three-dimensional (3D) wide-field microscopy, confocal microscopy, lattice light-sheet microscopy, and multimodal structured illumination microscopy (SIM), which enables multi-color, long-term, super-resolution 2D/3D imaging of subcellular bioprocesses from mitotic single cells to multicellular embryos of mouse and C. elegans.

bioengineering↗

bioRxiv2023

Excess PrPC inhibits muscle cell differentiation via miRNA-enhanced liquid-liquid phase separation implicated in myopathy

The cellular prion protein (PrPC), a glycoprotein existing in membrane-bound and cytoplasmic forms, has functional importance in skeletal muscle, but the mechanism behind the phenomenon remains poorly understood. Here we report that PrPC is overexpressed and located in the cytoplasm of the skeletal muscle of six myopathy patients; cytoplasmic PrPC strongly inhibits skeletal muscle cell autophagy and blocks myoblast differentiation. PrPC selectively binds to a subset of miRNAs during myoblast differentiation, and the co-localization of PrPC with miR-214-3p was clearly observed in the skeletal muscle of six myopathy patients but not in that of four age-matched controls. We demonstrate that PrPC is overexpressed in skeletal muscle cells under pathological conditions and inhibits muscle cell differentiation via physically interacting with a subset of miRNAs to significantly inhibit autophagy-related protein 5-dependent autophagy, and selectively recruits these miRNAs into phase-separated condensates in living myoblasts, which in turn greatly enhances liquid-liquid phase separation (LLPS) of PrPC and results in the subsequent PrP aggregation and muscle bundle formation in myopathy patients characterized by incomplete muscle regeneration. Our findings show how excess PrPC can inhibit muscle cell differentiation via miRNA-enhanced LLPS implicated in myopathy.

biochemistry↗

bioRxiv2023

Who you gonna call? TMS-induced inhibition of the left premotor cortex acts as a Bayesian Ghost Buster by altering illusory social perception

Communicative actions from one person are used to predict another persons response. However, in some cases, these predictions can outweigh the processing of sensory information and lead to illusory social perception such as seeing two people interact, although only one is present (i.e., seeing a Bayesian ghost). We applied either inhibitory brain stimulation over the left premotor cortex (i.e., real TMS) or sham TMS. Then, participants indicated the presence or absence of a masked agent that followed a communicative or individual gesture of another agent. As expected, participants had more false alarms (i.e., Bayesian ghosts) in the communicative than individual condition in the sham TMS session and this difference between conditions vanished after real TMS. In contrast to our hypothesis, the number of false alarms increased (rather than decreased) after real TMS. These pre-registered findings confirm the significance of the premotor cortex for social action predictions and illusory social perception. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/526257v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1b5812corg.highwire.dtl.DTLVardef@1338411org.highwire.dtl.DTLVardef@123b84eorg.highwire.dtl.DTLVardef@192a4b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LISocial predictions can outweigh sensory information and lead to illusory perception C_LIO_LIPremotor cortex is linked to the illusory social perception of a Bayesian ghost C_LIO_LITMS over premotor cortex modulates how social predictions influence our perception C_LI

neuroscience↗

bioRxiv2023

Natural methylation epialleles correlate with gene expression in maize

DNA methylation (5-methylcytosine) represses transposon activity and contributes to inaccessible chromatin structure of repetitive DNA in plants. It is depleted from cis regulatory elements in and near genes but is present in some gene bodies, including exons. Methylation in exons solely in the CG context is called gene body methylation (gbM). Methylation in exons in both CG and non-CG contexts is called TE-like methylation (teM). Assigning functions to both forms of methylation in genes has proven to be challenging. Toward that end, we utilized recent genome assemblies, gene annotations, transcription data, and methylome data to quantify common patterns of gene methylation and their relations to gene expression in maize. To compare between genomes, we analyzed each data source relative to its own genome assembly rather than the easier but less accurate method of using one assembly as reference for all. We found that gbM genes exist in a continuum of CG methylation levels without a clear demarcation between unmethylated genes and gbM genes. Analysis of expression levels across diverse maize stocks and tissues revealed a weak but highly significant positive correlation between gbM and gene expression except in endosperm. gbM epialleles were associated with an approximately 3% increase in steady-state expression level relative to unmethylated epialleles. In contrast to gbM genes, which were conserved and were broadly expressed across tissues, we found that teM genes, which make up about 12% of genes, are mainly silent, are limited to specific maize stocks, and exhibit evidence of annotation errors. We used these data to flag all teM genes in the 26 NAM founder genome assemblies. While some teM genes are likely functional, these data suggest that the majority are not, and their inclusion can confound interpretation of whole-genome studies.

plant biology↗

bioRxiv2023

Phenome-wide analysis identifies parent-of-origin effects on the human methylome associated with changes in the rate of aging

Variation in the rate at which humans age may be rooted in early life events acting through genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions either enriched for genetically controlled imprinting effects (the typical type of POE) or atypical POE introduced by environmental effects associated with parents. This part of the methylome is heavily influenced by early life events, making it a potential route connecting early environmental exposures, the epigenome and the rate of aging. Here, we aim to test the association of POE-influenced methylation of CpG dinucleotides (POE-CpG sites) with early and later environmental exposures and subsequently with health-related phenotypes and adult aging phenotypes. We do this by performing phenome-wide association analyses of the POE-influenced methylome using a large family-based population cohort (GS:SFHS, Ndiscovery=5,087, Nreplication=4,450). At the single CpG level, 92 associations of POE-CpGs with phenotypic variation were identified and replicated. Most of the associations were contributed by POE-CpGs belonging to the atypical class and the most strongly enriched associations were with aging (DNAmTL acceleration), intelligence and parental (maternal) smoking exposure phenotypes. We further found that a proportion of the atypical-POE-CpGs formed co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased internal module connectivity (strength of methylation correlation across constituent CpGs) with age. Atypical POE-CpGs also displayed high levels of methylation heterogeneity and epigenetic drift (i.e. information loss with age) and a strong correlation with CpGs contained within epigenetic clocks. These results identified associations between the atypical-POE-influenced methylome and aging and provided new evidence for the "early development of origin" hypothesis for aging in humans.

genetics↗

bioRxiv2023

Single-cell transcriptional analysis of lamina propria lymphocytes in the jejunum reveals ILC-like cells in pigs

Pigs are the most suitable model to study various therapeutic strategies and drugs for human beings, while knowledge about tissue- and cell-type-specific transcriptomes and heterogeneity is poorly available. Here, we focused on the intestinal immunity of pigs. Through single-cell sequencing (scRNA-seq) and flow cytometry analysis of the types of immune cells in the jejunum of pigs, we found that innate lymphoid cells (ILCs) existed in the lamina propria lymphocytes (LPLs) of the jejunum. Then, through flow sorting of Live/Dead (L/D)-Lineage(LIN)-CD45+ cells and scRNA-seq, we found that ILCs in the porcine jejunum were mainly ILC3s, with a small number of ILC1s, ILC2s, and NK cells. Through a gene expression map, we found that ILCs coexpressed IL-7R, ID2, and other genes and differentially expressed RORC, GATA3, and other genes but did not express the CD3 gene. According to their gene expression profiles, ILC3s can be divided into four subgroups, and genes such as CXCL8, CXCL2, IL-22, IL-17, and NCR2 are differentially expressed. To further detect and identify ILC3s, we prepared RORC monoclonal antibodies and verified the classification of ILCs in the porcine jejunum subgroup and the expression of related hallmark genes at the protein level by flow cytometry. For systematically characterizing of ILCs in the porcine intestines, we combined our pig ILCs dataset with publicly available human and mice ILCs data and identified that the humans and pigs ILCs shared more common features than those mice ILCs in gene signatures and cell states. For the first time, our results showed in detail the gene expression of porcine jejunal ILCs, the subtype classification of ILCs, and the markers of various ILCs, which provides a basis for an in-depth exploration of porcine intestinal mucosal immunity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/522424v3_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@184fd80org.highwire.dtl.DTLVardef@1efc00org.highwire.dtl.DTLVardef@328a04org.highwire.dtl.DTLVardef@3296e_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

immunology↗

bioRxiv2022

Identifying B-cell epitopes using AlphaFold2 predicted structures and pretrained language model

MotivationIdentifying the B-cell epitopes is an essential step for guiding rational vaccine development and immunotherapies. Due to experimental approaches being expensive and time-consuming, many computational methods have been designed to assist B-cell epitope prediction. However, existing sequence-based methods have limited performance since they only use contextual features of the sequential neighbors while neglecting structural information. ResultsBased on the recent breakthrough of AlphaFold2 in protein structure prediction, we propose GraphBepi, a novel graph-based model for accurate B-cell epitope prediction. GraphBepi first generates the effective information sequence representations and protein structures from antigen sequences through the pretrained language model and AlphaFold2, respectively. GraphBepi then applies the edge-enhanced deep graph neural network (EGNN) to capture the spatial information from predicted protein structures and leverages the bidirectional long short-term memory neural networks (BiLSTM) to capture long-range dependencies from sequences. The low-dimensional representation learned by EGNN and BiLSTM is then combined to predict B-cell epitopes through a multilayer perceptron. Through comprehensive tests on the curated epitope dataset, GraphBepi was shown to outperform the state-of-the-art methods by more than 5.5% and 44.0% in terms of AUC and AUPR, respectively. We also provide the GraphBepi web server that is freely available at https://biomed.nscc-gz.cn/apps/GraphBepi. AvailabilityThe datasets, pre-computed features, source codes, and the pretrained model of GraphBepi are available at https://github.com/biomed-AI/GraphBepi. Contactyangyd25@mail.sysu.edu.cn or gaojz@nankai.edu.cn

bioinformatics↗

bioRxiv2022

The critical role of BTRC in hepatic steatosis as an ATGL E3 ligase

ObjectiveNon-alcoholic fatty liver disease (NAFLD), characterized by hepatic steatosis, is one of the most common causes of liver dysfunction. ATGL is closely related to hepatic steatosis as the speed-limited triacylglycerol lipase. Nevertheless, the expression and regulation of ATGL in NAFLD remain unclear. MethodsUsing immunohistochemistry and qRT-PCR to detect the expression of ATGL and BTRC in different models with hepatic steatosis. Co-IP evaluated the binding of ATGL and BTRC. Knockdown of BTRC employed by adenoviruses and then analyzed the ATGL expression, triglyceride levels, and lipid droplets accumulation. ResultsOur results revealed that ATGL protein level was decreased in animal and cellular models of hepatic steatosis and the liver tissues of cholangioma/hepatic carcinoma patients with hepatic steatosis, while the ATGL mRNA level had hardly changed; which means the decreased ATGL mainly degraded through the proteasome pathway. BTRC was identified as the E3 ligase for ATGL, up-regulated, and negatively correlated with ATGL level. Moreover, adenovirus-mediated knockdown of BTRC ameliorated hepatic steatosis via up-regulating ATGL level. ConclusionsOur study demonstrates a crucial role of elevated BTRC in hepatic steatosis through promoting ATGL proteasomal degradation as a new ATGL E3 ligase and suggests BTRC may serve as a potential therapeutic target for NAFLD. FundingThis study was supported by The National Natural Science Foundation of China (Grants 82070888, 82070882, 82100917, 81872165, 82273116, 82203661, 81901557 and 81902693); Key Project of Nature Science Foundation of Guangdong Province, China (Grant 2019B1515120077); National Key R&D Program of China (Grant 2018YFA0800403); Guangdong Special Support Program for Young Top Scientist (Grant 201629046); Guangdong Natural Science Fund (Grant 2019A1515011810, 2021A1515010434, 2022A1515012423 and 2022A1515012513); Key Sci-Tech Research Project of Guangzhou Municipality (Grants 202201010820) Fundamental Research Funds for the Central Universities (Grant 50000-31620106); China Postdoctoral Science Foundation (Grant 2021M703679, 2020M683110).

cell biology↗

bioRxiv2022

GSK-3484862 targets DNMT1 for degradation in cells

Maintenance of genomic methylation patterns at DNA replication forks by DNMT1 is the key to faithful mitotic inheritance. DNMT1 is often overexpressed in cancer cells and the DNA hypomethylating agents azacytidine and decitabine are currently used in the treatment of hematologic malignancies. However, the toxicity of these cytidine analogs and their ineffectiveness in treating solid tumors have limited wider clinical use. GSK-3484862 is a newly-developed, dicyanopyridine containing, non-nucleoside DNMT1-selective inhibitor with low cellular toxicity. Here, we show that GSK-3484862 targets DNMT1 for protein degradation in both cancer cell lines and murine embryonic stem cells (mESCs). DNMT1 depletion was rapid, taking effect within hours following GSK-3484862 treatment, leading to global hypomethylation. Inhibitor-induced DNMT1 degradation was proteasome-dependent, with no discernible loss of DNMT1 mRNA. In mESCs, GSK-3484862-induced Dnmt1 degradation requires Uhrf1, an accessory factor of Dnmt1 with E3 ubiquitin ligase activity. We also show that Dnmt1 depletion and DNA hypomethylation induced by the compound are reversible after its removal. Together, these results indicate that this DNMT1-selective degrader/inhibitor will be a valuable tool for dissecting both coordinated events linking DNA methylation to gene expression and identifying downstream effectors that ultimately regulate cellular response to altered DNA methylation patterns in a tissue/cell-specific manner. HighlightsO_LIGSK-3484862 targets DNMT1 for protein degradation in a wide-range of cancer cell lines, without a decrease in DNMT1 mRNA levels C_LIO_LIDNMT1 depletion leads to a >50% loss of global DNA methylation in cells within 2-days of treatment with GSK-3484862 C_LIO_LIGSK-3484862-induced DNMT1 degradation is proteasome-dependent C_LIO_LIIn mESCs, Uhrf1 is required for GSK-3484862 to induce Dnmt1 degradation C_LI

cancer biology↗

bioRxiv2022

Export of discarded splicing intermediates requires mRNA export factors and the nuclear basket

To promote fidelity in nuclear pre-mRNA splicing, the spliceosome rejects and discards suboptimal splicing substrates after they have engaged the spliceosome. Although nuclear quality control mechanisms have been proposed to retain immature mRNPs, evidence indicates that discarded splicing substrates, including lariat intermediates, do export to the cytoplasm, as indicated by their translation and degradation by cytoplasmic nucleases. However, the mechanism for exporting these species has remained unknown. By single molecule (sm) RNA FISH in budding yeast, we have directly observed the nuclear export of lariat intermediates. Further, by crosslinking, export reporter assays, and smRNA FISH, we have demonstrated that the export of lariat intermediates requires the general mRNA export receptor Mex67p and three of its mRNA export adapter proteins, Nab2p, Yra1p, and Nlp3, establishing that mRNAs and lariat intermediates share the same export machinery. Unexpectedly, the export of lariat intermediates, but not mRNA, requires an interaction between Nab2p and Mlp1p, a nuclear basket component implicated in retaining immature mRNPs, including unspliced pre-mRNA, in the nucleus of budding yeast. Finally, the export of lariat intermediates, like mRNA, relies on the E3 ubiquitin ligase Tom1p and its target sites in Yra1p. Overall, our data indicate that the nuclear basket can promote, rather than antagonize, the export of an immature mRNP. Further, our data imply that the export of discarded lariat intermediates requires both Mlp1p-dependent docking onto the nuclear basket and subsequent Tom1p-mediated undocking, a mechanism our data suggests functions in the export of mRNA also but in a manner obscured by redundant pathways.

cell biology↗

bioRxiv2022

Deciphering Spatial Domains by Integrating Histopathological Image and Transcriptomics via Contrastive Learning

Recent advances in spatial transcriptomics have enabled measurements of gene expression at cell/spot resolution meanwhile retaining both the spatial information and the histopathological images of the tissues. Deciphering the spatial domains of spots in the tissues is a vital step for various downstream tasks in spatial transcriptomics analysis. Existing methods have been developed for this purpose by combining gene expression and histopathological images to conquer noises in gene expression. However, current methods only use the histopathological images to construct spot relations without updating in the training stage, or simply concatenate the information from gene expression and images into one feature vector. Here, we propose a novel method ConGI to accurately decipher spatial domains by integrating gene expression and histopathological images, where the gene expression is adapted to image information through contrastive learning. We introduce three contrastive loss functions within and between modalities to learn the common semantic representations across all modalities while avoiding their meaningless modality-private noise information. The learned representations are then used for deciphering spatial domains through a clustering method. By comprehensive tests on tumor and normal spatial transcriptomics datasets, ConGI was shown to outperform existing methods in terms of spatial domain identification. More importantly, the learned representations from our model have also been used efficiently for various downstream tasks, including trajectory inference, clustering, and visualization.

bioinformatics↗

bioRxiv2022

Synthetic maize centromeres transmit chromosomes across generations

Centromeres are long, often repetitive regions of genomes that bind kinetochore proteins and ensure normal chromosome segregation. Engineering centromeres that function in vivo has proven to be difficult. Here we describe a LexA-CENH3 tethering approach that activates functional centromeres at maize synthetic repeat arrays containing LexO binding sites. The synthetic centromeres are sufficient to cause chromosome breakage and release of chromosome fragments that are passed through meiosis and into progeny. Several independent chromosomes were identified, each with newly created centromeres localized over the repeat arrays where they were directed. The new centromeres were self-sustaining and stably transmitted chromosomes to progeny in the absence of the LexA-CENH3 activator. Our results demonstrate the feasibility of using synthetic centromeres for karyotype engineering applications.

genetics↗

bioRxiv2022

A Meta-learning based Graph-Hierarchical Clustering Method for Single Cell RNA-Seq Data

Single cell sequencing techniques enable researchers view complex bio-tissues from a more precise perspective to identify cell types. However, more and more recent works have been done to find more detailed subtypes within already known cell types. Here, we present MeHi-SCC, a method which utilized meta-learning protocol and brought in multi scRNA-seq datasets information in order to assist graph-based hierarchical sub-clustering process. In result, MeHi-SCC outperformed current-prevailing scRNA clustering methods and successfully identified cell subtypes in two large scale cell atlas. Our codes and datasets are available online at https://github.com/biomed-AI/MeHi-SCC

bioinformatics↗

bioRxiv2022

Structural basis for intrinsic transcription termination

Efficient and accurate termination is required for gene transcription in all living organisms. Cellular RNA polymerases (RNAP) in both bacteria and eukaryotes can terminate their transcription through a factor-independent termination pathway (called intrinsic termination transcription in bacteria), in which RNAP recognizes terminator sequences, stops nucleotide addition, and releases nascent RNA spontaneously. Here we report a set of single-particle cryo-EM structures of E. coli transcription intrinsic termination complexes representing key intermediate states of the event. The structures show how RNAP pauses at terminator sequences, how the terminator RNA hairpin folds inside RNAP, and how RNAP rewinds the transcription bubble to release RNA and then DNA. These macromolecular snapshots define a structural mechanism for bacterial intrinsic termination and a pathway for RNA release and DNA collapse relevant for factor-independent termination by all RNA polymerases.

molecular biology↗

bioRxiv2022

Individual tree-based vs pixel-based approaches to mapping forest functional traits and diversity by remote sensing

Trait-based approaches, focusing on the functional characteristics of vascular plants in a community, have been increasingly used in plant ecology and biodiversity research. Compared with traditional field survey (which typically samples individual trees), remote sensing enables quantifying functional traits over large contiguous areas, but assigning trait values to biological units such as species and individuals is difficult with pixel-based approaches. We used a subtropical forest landscape in China to compare an approach based on LiDAR-delineated individual tree crowns (ITCs) with a pixel-based approach for assessing functional traits from remote sensing data. We compared trait distributions, trait-trait relationships and functional diversity metrics obtained by the two approaches at changing grain and extent. We found that morphological traits derived from airborne laser scanning showed more differences between ITC- and pixel-based approaches than physiological traits estimated by imaging spectroscopy data. Pixel sizes approximating average tree crowns yielded similar results as ITCs, but 95th quantile height and foliage height diversity tended to be overestimated and leaf area index underestimated relative to ITC-based values. With increasing pixel size, the differences to ITC- based trait values became larger and less trait variance was captured, indicating information loss. The consistency of ITC- and pixel-based functional richness measures also decreased with increasing pixel grain, and changed with the observed extent for functional diversity monitoring. We conclude that whereas ITC-based approaches in principle allow partitioning of variation between individuals, genotypes and species, at high resolution, pixel-based approaches come close to this and can be suitable for assessing ecosystem-scale trait variation by weighting individuals and species according to coverage.

ecology↗

bioRxiv2022

An Open Microfluidic Coculture Model of Fibroblasts and Eosinophils to Investigate Mechanisms of Airway Inflammation

Interactions between fibroblasts and immune cells play an important role in tissue inflammation. Previous studies have found that eosinophils activated with interleukin-3 (IL-3) degranulate on aggregated immunoglobulin G (IgG) and release mediators that activate fibroblasts in the lung. However, these studies were done with eosinophil-conditioned media that have the capacity to investigate only one-way signaling from eosinophils to fibroblasts. Here, we demonstrate a coculture model of primary normal human lung fibroblasts (HLFs) and human blood eosinophils from patients with allergy and asthma using an open microfluidic coculture device. In our device, the two types of cells can communicate via two-way soluble factor signaling in the shared media while being physically separated by a half wall. Initially, we assessed the level of eosinophil degranulation by their release of eosinophil-derived neurotoxin (EDN). Next, we analyzed the inflammation-associated genes and soluble factors using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and multiplex immunoassays, respectively. Our results suggest an induction of a proinflammatory fibroblast phenotype of HLFs following the coculture with degranulating eosinophils, validating our previous findings. Additionally, we present a new result that indicate potential impacts of activated HLFs back on eosinophils. This open microfluidic coculture platform provides unique opportunities to investigate the intercellular signaling between the two cell types and their roles in airway inflammation and remodeling.

cell biology↗