SEARCH · bioRxiv Science

Results for “Molecular Biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68Linked to original sources

bioRxiv2025

Medium-chain fatty acids mitigate endoplasmic reticulum stress in yeast cells

Upon endoplasmic reticulum (ER) stress, eukaryotic cells commonly trigger cytoprotective transcriptome changes, namely the unfolded protein response (UPR). In yeast Saccharomyces cerevisiae, the UPR is mediated by the transcription factor Hac1, which is induced in response to ER stress. Since Hac1 controls hundreds of genes, the biological phenomena that result from UPR are not yet fully understood. Here, we show that cells carrying a mutation to constitutively express Hac1 abundantly contained C10:0 and C12:0 fatty acids, known as medium-chain fatty acids (MCFs). UPR induction by some ER stress stimuli was attenuated by externally supplied MCFs in cells in which fatty acid elongation was genetically or pharmacologically halted. The cell survival assay also indicated the mitigation of ER stress by the MCFs. Moreover, we demonstrated that MCFs leads to the diffusion of a mutant transmembrane protein aggregated in the ER. We propose that, as a biologically beneficial outcome of UPR, MCFs are produced to change the properties of the ER membrane, such as fluidity, in ER-stressed yeast cells.

molecular biology↗

bioRxiv2018

Comparative RNAi Screens in Isogenic Human Stem Cells Reveal SMARCA4 as a Differential Regulator

Large-scale RNAi screens are a powerful approach to identify functions of genes in a cell-type specific manner. For model organisms, genetically identical (isogenic) cells from different cell-types are readily available, making comparative studies meaningful. For humans, however, screening isogenic cells is not straightforward. Here, we show that RNAi screens are possible in genetically identical human stem cells, employing induced pluripotent stem cell as intermediates. The screens revealed SMARCA4 (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A member 4) as a stemness regulator, while balancing differentiation distinctively for each cell type. SMARCA4 knockdown in hematopoietic stem progenitor cells (HSPC) caused impaired self-renewal in-vitro and in-vivo with skewed myeloid differentiation; whereas in neural stem cells (NSC), it impaired selfrenewal while biasing differentiation towards neural lineage, through combinatorial SWI/SNF subunit assembly. Our findings pose a powerful approach for deciphering human stem cell biology and attribute distinct roles to SMARCA4 in stem cell maintenance.

molecular biology↗

bioRxiv2020

Analysis of new nosological models from disease similarities using clustering

While classical disease nosology is based on phenotypical characteristics, the increasing availability of biological and molecular data is providing new understanding of diseases and their underlying relationships, that could lead to a more comprehensive paradigm for modern medicine. In the present work, similarities between diseases are used to study the generation of new possible disease nosologic models that include both phenotypical and biological information. To this aim, disease similarity is measured in terms of disease feature vectors, that stood for genes, proteins, metabolic pathways and PPIs in the case of biological similarity, and for symptoms in the case of phenotypical similarity. An improvement in similarity computation is proposed, considering weighted instead of Booleans feature vectors. Unsupervised learning methods were applied to these data, specifically, density-based DBSCAN clustering algorithm. As evaluation metric silhouette coefficient was chosen, even though the number of clusters and the number of outliers were also considered. As a results validation, a comparison with randomly distributed data was performed. Results suggest that weighted biological similarities based on proteins, and computed according to cosine index, may provide a good starting point to rearrange disease taxonomy and nosology.

bioinformatics↗

bioRxiv2021

New loci and neuronal pathways for resilience to heat stress in animals

Climate change and resilience to warming climates have implications for humans, livestock, and wildlife. The genetic mechanisms that confer thermotolerance to mammals are still not well characterized. We used dairy cows as a model to study heat tolerance because they are lactating, and therefore often prone to thermal stress. The data comprised almost 0.5 million milk records (milk, fat, and proteins) of 29,107 Australian Holsteins, each having around 15 million imputed sequence variants. Dairy animals often reduce their milk production when temperature and humidity rise; thus, the phenotypes used to measure an individuals heat tolerance were defined as the rate of milk production decline (slope traits) with a rising temperature-humidity index. With these slope traits, we performed a genome-wide association study (GWAS) using different approaches, including conditional analyses, to correct for the relationship between heat tolerance and level of milk production. The results revealed multiple novel loci for heat tolerance, including 61 potential functional variants at sites highly conserved across vertebrate species. Moreover, it was interesting that specific candidate variants and genes are related to the neuronal system (ITPR1, ITPR2, and GRIA4) and neuroactive ligand-receptor interaction functions for heat tolerance (NPFFR2, CALCR, and GHR), providing a novel insight that can help to develop genetic and management approaches to combat heat stress. Author summaryWhile understanding the genetic basis of heat tolerance is crucial in the context of global warmings effect on humans, livestock, and wildlife, the specific genetic variants and biological features that confer thermotolerance in animals are still not well characterized. The ability to tolerate heat varies across individuals, with substantial genetic control of this complex trait. Dairy cattle are excellent model in which to find genes associated with individual variations in heat tolerance since they significantly suffer from heat stress due to the metabolic heat of lactation. By genome-wide association studies of more than 29,000 cows with 15 million sequence variants and controlled phenotype measurements, we identify many new loci associated with heat tolerance. The biological functions of these loci are linked to the neuronal system and neuroactive ligand-receptor interaction functions. Also, several putative causal mutations for heat tolerance are at genomic sites that are otherwise evolutionarily conserved across 100 vertebrate species. Overall, our findings provide new insight into the molecular and biological basis of heat tolerance that can help to develop genetic and management approaches to combat heat stress.

genomics↗

bioRxiv2026

A Wolbachia pipientis protein confers resistance to virus infection in Drosophila melanogaster

The intracellular bacterium Wolbachia pipientis alters the biology of its arthropod hosts in many ways, and can increase resistance to RNA viruses in both Drosophila and mosquitoes. Wolbachia-induced pathogen blocking has generated much interest because of its potential to restrict insect vector transmission of human diseases caused by RNA viruses. However, the molecular mechanisms by which Wolbachia affects host viral resistance are still mostly elusive. We used dilp2-3,5 mutant Drosophila, which are long-lived, but only in the presence of Wolbachia, to show that the presence of Wolbachia also increased the resistance of the mutant flies to infection with Drosophila C virus (DCV), relative both to mutants lacking Wolbachia and to wild type flies with and without Wolbachia. The insulin mutant flies had higher Wolbachia titres than wild type flies. By RNA-seq analysis of the Wolbachia transcriptome, we identified Wolbachia genes that were more strongly expressed in dilp2-3,5 mutant flies. Ankyrin-domain-containing proteins were among the most strongly up-regulated and they are predicted to be secreted effector proteins. To address their effect on host physiology, we generated 4 transgenic fly lines each with inducible expression of a different genes encoding ankyrin-domain-containing proteins. Expression of 3 of these did not cause obvious effects, but expression of WD0754 at high levels severely shortened fly survival. Interestingly, however, chronic low-level induction of WD0754 increased the resistance of the flies to DCV infection. Proteomics analysis showed a robust, tissue-specific, anti-viral response upon WD0754 induction, and identified the NFkB-like IMD pathway as a potential mediator of the antiviral activity of WD0754. Consistently, WD0754 expression activated Relish, a key downstream transcriptional mediator of IMD signalling, while loss-of Relish blocked the antiviral effect of WD0754. In summary, we identified a Wolbachia-derived ankyrin domain containing protein that modulates host immunity through the IMD pathway.

molecular biology↗

bioRxiv2019

In vivo mRNA structure regulates miRNA cleavage in Arabidopsis

MicroRNA (miRNA)-mediated cleavage is involved in numerous essential cellular pathways. miRNAs recognize target RNAs via sequence complementarity. In addition to complementarity, in vitro and in silico studies have suggested that RNA structure may influence the accessibility of mRNAs to miRNA-Induced Silencing Complexes (miRISCs), thereby affecting RNA silencing. However, the regulatory mechanism of mRNA structure in miRNA cleavage remains elusive. Here, we investigated the role of in vivo RNA secondary structure in miRNA cleavage by developing the new CAP-STRUCTURE-seq method to capture the intact mRNA structurome in Arabidopsis thaliana. This approach revealed that miRNA target sites were not structurally accessible for miRISC binding prior to cleavage in vivo. Instead, the unfolding of the target site structure is the primary determinant for miRISC activity in vivo. Notably, we found that the single-strandedness of the two nucleotides immediately downstream of the target site, named Target Adjacent structure Motif (TAM), can promote miRNA cleavage but not miRNA binding, thus decoupling target site binding from cleavage. Our findings demonstrate that mRNA structure in vivo can regulate miRNA cleavage, providing evidence of mRNA structure-dependent regulation of biological processes.

molecular biology↗

bioRxiv2021

OperonSEQer: A set of machine-learning algorithms with threshold voting for detection of operon pairs using short-read RNA-sequencing data

Operon prediction in prokaryotes is critical not only for understanding the regulation of endogenous gene expression, but also for exogenous targeting of genes using newly developed tools such as CRISPR-based gene modulation. A number of methods have used transcriptomics data to predict operons, based on the premise that contiguous genes in an operon will be expressed at similar levels. While promising results have been observed using these methods, most of them do not address uncertainty caused by technical variability between experiments, which is especially relevant when the amount of data available is small. In addition, many existing methods do not provide the flexibility to determine whether the stringency with which genes should be evaluated for being in an operon pair. We present OperonSEQer, a set of machine learning algorithms that uses the statistic and p-value from a non-parametric analysis of variance test (Kruskal-Wallis) to determine the likelihood that two adjacent genes are expressed from the same RNA molecule. We implement a voting system to allow users to choose the stringency of operon calls depending on whether your priority is high coverage of operons or high accuracy of the calls. In addition, we provide the code so that users can retrain the algorithm and re-establish hyperparameters based on any data they choose, allowing for this method to be expanded on as additional data is generated and incorporated. We show that our approach detects operon pairs that are missed by current methods by comparing our predictions to publicly available long-read sequencing data. OperonSEQer therefore improves on existing methods in terms of accuracy, flexibility and adaptability. Author SummaryBacteria and archaea, single-cell organisms collectively known as prokaryotes, live in all imaginable environments and comprise the majority of living organisms on this planet. Prokaryotes play a critical role in the homeostasis of multicellular organisms (such as animals and plants) and ecosystems. In addition, bacteria can be pathogenic, and cause a variety of diseases in these same hosts and ecosystems. In short, understanding the biology and molecular functions of bacteria and archaea and devising mechanisms to engineer and optimize their properties are critical scientific endeavors with significant implications in healthcare, agriculture, manufacturing and climate science among others. One major molecular difference between unicellular and multicellular organisms is the way the express genes - rather than making individual RNA molecules like multicellular organisms, prokaryotes express genes in long contiguous RNA molecules known as operons, which are subsequently processed. Understanding which genes exist within operons is critical for elucidating basic biology and for engineering organisms. In this work, we use a combination of statistical and machine learning-based methods to use next-generation sequencing data to predict operon structure across a range of prokaryotes. Our method provides a easily implemented, robust, accurate and flexible way to determine operon structure in an organism-agnosic manner using readily-available data.

bioinformatics↗

bioRxiv2024

Technical and biological variations in the purification of extrachromosomal circular DNA (eccDNA) and the finding of more eccDNA in the plasma of lung adenocarcinoma patients compared with healthy donors

Human plasma DNA originates from all tissues and organs, holding the potential as a versatile marker for diseases such as cancer, as fragments of cancer-specific alleles can be found circulating in the blood. While linear DNA has been studied intensely as a liquid biomarker, the role of circular circulating DNA in cancer is more unknown due, in part, to a lack of comprehensive testing methods. Our developed method profiles extrachromosomal circular DNA (eccDNA) in plasma, integrating Solid-Phase Reversible Immobilization (SPRI) bead purification, the removal of linear DNA and mitochondrial DNA, and DNA sequencing. As an initial assessment, we examined the method, biological variations, and technical variations using plasma samples from four patients with lung adenocarcinoma and four healthy and physically fit individuals. Despite the small sample group, we observed a significant eccDNA increase in cancer patients in two independent laboratories and that eccDNA covered up to 0.4 % of the genome/mL plasma. We found a subset of eccDNA from recurrent genes present in cancer samples but not in every control. In conclusion, our data reflect the large variation found in eccDNA sequence content and show that the variability observed among replicates in eccDNA stems from a biological source and can cause inconclusive findings for biomarkers. This suggests the need to explore other biological markers, such as epigenetic features on eccDNA.

molecular biology↗

bioRxiv2024

Epigenetic silencing and blockade of latency reversal by an HIV-1 encoded antisense transcript

The mechanisms that regulate human immunodeficiency virus 1 (HIV-1) latency are not fully elucidated. We reported that an HIV-1 antisense transcript (AST) induces epigenetic modifications at the HIV-1 promoter causing a closed chromatin state that suppresses viral transcription. Here we show that ectopic expression of AST in CD4+ T-cells from people with HIV-1 under antiretroviral therapy blocks latency reversal in response to pharmacologic and T-cell receptor stimulation, enforcing transcriptional silencing. We define structural domains and sequence motifs of AST contributing to its latency-promoting functions. Finally, we report an unbiased proteomics screen of AST interactors that revealed an array of previously known and potential new HIV-1-suppressive factors. Our studies identify AST as a first-in-class biological molecule capable of enforcing HIV-1 latency and with actionable curative potential.

molecular biology↗

bioRxiv2025

RNA-triggered fluorescence controlled by RNA switches for real-time RNA expression tracking in living plants

Real-time visualization of RNA dynamics across spatial scales in living plants is desirable yet remains challenging, hindered by the absence of imaging tools that simultaneously offer high sensitivity and deployability in whole living plants. Here, we engineered a modular, RNA-triggered fluorescence (RTF) reporter system de novo for spatiotemporal imaging of RNA from cellular to whole-plant scales in vivo. This system integrates three functional modules: a target-specific allosteric RNA switch, a degradable adapter for background suppression, and a fluorescent reporter. All components are stably expressed from a single vector and assemble in vivo, enabling uniform deployment throughout entire plants. The modified RTF (RTFst) achieves single-molecule sensitivity (signal-to-noise ratio >60) for dynamic tracking of developmentally regulated, tissue-specific, circadian, and stress-responsive mRNAs. Crucially, it enables the first direct, real-time observation of graft-transmissible mRNA trafficking across tissue scales and cross-kingdom transfer of the aphid-secreted long non-coding RNA Ya1 to plant cells. RTF establishes a versatile platform for studying gene regulation, signaling, and transcript mobility in plants, with broad applicability in synthetic biology and crop improvement.

molecular biology↗

bioRxiv2025

A modular toolbox for in cellulo screening of small molecule inhibitors targeting chromatin reader domains

The dysregulation of bromodomain proteins, a family of "reader" proteins that recognize the critical post-translational modification of acylation, is implicated in diseases like cancer, making them important therapeutic targets. However, the development of specific small-molecule inhibitors is hindered by the lack of robust, high-throughput cellular assays to measure target engagement and off-target binding in living cells. To address this gap, we developed a modular platform of cell lines that stably express synthetic chromatin reader constructs, termed Acyl-eCRs, containing various bromodomains fused to eGFP. We demonstrate that these Acyl-eCRs recapitulate the same response to bromodomain inhibitors and PROTACs as endogenous proteins, allowing for the quantitative assessment of drug effects. We introduce two complementary flow cytometry-based assays to evaluate inhibitor-target engagement: a competitive binding assay leveraging PROTAC-induced degradation, and a nuclear retention assay that directly measures the displacement of bromodomains from chromatin. Our approach circumvents the need for laborious protein purification and in vitro characterization, providing a scalable and physiologically relevant method for assessing inhibitor potency and specificity. This platform represents a versatile tool for chemical biology, enabling the functional evaluation of chromatin-targeting drugs in a native cellular context.

molecular biology↗

bioRxiv2026

Integrated transcriptomics and proteomics define the TRP channel hierarchy in mouse cortex

Transient receptor potential (TRP) channels are evolutionarily conserved polymodal cation channels that mediate diverse sensory functions across the animal kingdom. Although TRP channels play key roles in peripheral sensation, their expression and functional relevance in the cerebral cortex remain poorly defined. Here, we integrate long- and short-read transcriptomics, targeted qPCR and membrane-aware proteomics to quantify TRP family members in adult mouse cortex. Across transcriptomic platforms, cortical TRP expression is dominated by TRPML, TRPC, and TRPM subfamilies, with lower representation of TRPP/TRPV, whereas Trpa1 and Trpv1 lie near empirical detection thresholds. Our proteomic workflow yields reproducible protein-level evidence for a subset of cortical TRPs, including TRPV2, TRPC4, TRPM3, TRPM7 and TRPP2, consistent with transcript rank order, while TRPA1/TRPV1 do not meet replicate-level protein-group detection criteria under 1% FDR control. Together, these multi-platform measurements establish a quantitative reference for cortical TRP biology and a framework for profiling low-abundance ion channels in complex brain tissue.

molecular biology↗

bioRxiv2026

Beyond codon optimality: codon pairs regulate mRNA stability dependent on translation

The coding sequence of an mRNA directs its own decay, yet how codons, codon context, and amino acids collectively regulate mRNA stability remains poorly understood. Here we use a massively parallel reporter assay to decode this regulatory layer in zebrafish embryos. We find that codon pairs and amino acid pairs regulate mRNA stability beyond the level of individual codons. This regulation depends on the identity and order of neighboring codons and their encoded amino acids in a translation-dependent manner. The relative contributions of codon and amino acid combinations to mRNA stability can be quantified using machine learning. We further found that endogenous mRNAs are regulated by codon pairs, thereby governing developmental gene regulation and biological function. This codon context-dependent decay requires deadenylation and decapping by Cnot7 and Dcp2, with Upf1 acting on long non-optimal ORFs. Together, our results redefine codon optimality as a context-dependent, pair-level code with implications for RNA biology and therapeutic mRNA design.

molecular biology↗

bioRxiv2021

Natural and after colon washing fecal samples: the two sides of the coin for investigating the human gut microbiome

To date there are several studies focusing on the importance of gut microbiome for human health, however the selection of a universal sampling matrix representative of the microbial biodiversity associated to the gastrointestinal (GI) tract, still represents a challenge. Here we present a study in which, through a deep metabarcoding analysis of the 16S rRNA gene, we compared two sampling matrices, feces (F) and colonic lavage liquid (LL), in order to evaluate their accuracy to represent the complexity of the human gut microbiome. A training set of 37 volunteers was attained and paired F and LL samples were collected from each subject. A preliminary absolute quantification of total 16S rDNA, performed by droplet digital PCR (ddPCR), confirmed that sequencing and taxonomic analysis were performed on same total bacterial abundance obtained from the two sampling methods. The taxonomic analysis of paired samples revealed that, although specific taxa were predominantly or exclusively observed in LL samples, as well as other taxa were detectable only or were predominant in stool, the microbiomes of the paired samples F and LL in the same subject hold overlapping taxonomic composition. Moreover, LL samples revealed a higher biodiversity than stool at all taxonomic ranks, as demonstrated by the Shannon Index and the Inverse Simpsons Index. We also found greater inter-individual variability than intra-individual variability in both sample matrices. Finally, functional differences were unveiled in the gut microbiome detected in the F and LL samples. A significant overrepresentation of 22 and 13 metabolic pathways, mainly occurring in Firmicutes and Proteobacteria, was observed in gut microbiota detected in feces and LL samples, respectively. This suggests that LL samples may allow for the detection of microbes adhering to the intestinal mucosal surface as members of the resident flora that are not easily detectable in stool, most likely representative of a diet-influenced transient microbiota. This first comparative study on feces and LL samples for the study of the human gut microbiome demonstrates that the use of both types of sample matrices may represent a possible choice to obtain a more complete view of the human gut microbiota in response to different biological and clinical questions.

molecular biology↗

bioRxiv2021

Regulating expression of mistranslating tRNAs by readthrough RNA polymerase II transcription

Transfer RNA (tRNA) variants that alter the genetic code increase protein diversity and have many applications in synthetic biology. Since the tRNA variants can cause a loss of proteostasis, regulating their expression is necessary to achieve high levels of novel protein. Mechanisms to positively regulate transcription with exogenous activator proteins like those often used to regulate RNA polymerase II (RNAP II) transcribed genes are not applicable to tRNAs as their expression by RNA polymerase III requires elements internal to the tRNA. Here, we show that tRNA expression is repressed by overlapping transcription from an adjacent RNAP II promoter. Regulating the expression of the RNAP II promoter allows inverse regulation of the tRNA. Placing either Gal4 or TetR-VP16 activated promoters downstream of a mistranslating tRNASer variant that mis-incorporates serine at proline codons in Saccharomyces cerevisiae allows mistranslation at a level not otherwise possible because of the toxicity of the unregulated tRNA. Using this inducible tRNA system, we explore the proteotoxic effects of mistranslation on yeast cells. High levels of mistranslation cause cells to arrest in G1 phase. These cells are impermeable to propidium iodide, yet growth is not restored upon repressing tRNA expression. High levels of mistranslation increase cell size and alter cell morphology. This regulatable tRNA expression system can be applied to study how native tRNAs and tRNA variants affect the proteome and other biological processes. Variations of this inducible tRNA system should be applicable to other eukaryotic cell types.

molecular biology↗

bioRxiv2022

Deep-SMOLM: Deep Learning Resolves the 3D Orientations and 2D Positions of Overlapping Single Molecules with Optimal Nanoscale Resolution

Dipole-spread function (DSF) engineering reshapes the images of a microscope to maximize the sensitivity of measuring the 3D orientations of dipole-like emitters. However, severe Poisson shot noise, overlapping images, and simultaneously fitting high-dimensional information-both orientation and position-greatly complicates image analysis in single-molecule orientation-localization microscopy (SMOLM). Here, we report a deep-learning based estimator, termed Deep-SMOLM, that archives superior 3D orientation and 2D position measurement precision within 3% of the theoretical limit (3.8{whitebullet} orientation, 0.32 sr wobble angle, and 8.5 nm lateral position using 1000 detected photons). Deep-SMOLM also achieves state-of-art estimation performance on overlapping images of emitters, e.g., a 0.95 Jaccard index for emitters separated by 139 nm, corresponding to a 43% image overlap. Deep-SMOLM accurately and precisely reconstructs 5D information of both simulated biological fibers and experimental amyloid fibrils from images containing highly overlapped DSFs, at a speed [~]10 times faster than iterative estimators.

molecular biology↗

bioRxiv2022

Expression and Splicing Mediate Distinct Biological Signals

BackgroundThrough alternative splicing, most human genes produce multiple isoforms in a cell-, tissue-, and disease-specific manner. Numerous studies show that alternative splicing is essential for development, diseases and their treatments. Despite these important examples, the extent and biological relevance of splicing are currently unknown. ResultsTo solve this problem, we developed pairedGSEA and used it to profile transcriptional changes in 100 representative RNA-seq datasets. Our systematic analysis demonstrates that changes in splicing, on average, contribute to 48.1% of the biological signal in expression analyses. Gene-set enrichment analysis furthermore indicates that expression and splicing both convey shared and distinct biological signals. ConclusionThese findings establish alternative splicing as a major regulator of the human condition and suggest that most contemporary RNA-seq studies likely miss out on critical biological insights. We anticipate our results will contribute to the transition from a gene-centric to an isoform-centric research paradigm.

molecular biology↗

bioRxiv2022

Recombinant Human Proteoglycan 4 (rhPRG4) Downregulates TNFα-Stimulated NFκB Activity and FAT10 Expression in Human Corneal Epithelial Cells

Dry Eye Disease (DED) is a complex pathology affecting millions of people with significant impact on quality of life. Corneal inflammation, including via the NF{kappa}B pathway, plays a key etiological role in DED. Recombinant human proteoglycan 4 (rhPRG4) has been shown to be a clinically effective treatment for DED that has anti-inflammatory effects in corneal epithelial cells, but the underlying mechanism is still not understood. Our goal was to understand if rhPRG4 affects TNF-stimulated inflammatory activity in corneal epithelial cells. We treated hTERT-immortalized corneal epithelial (hTCEpi) cells {+/-}TNF {+/-}rhPRG4 and performed Western blotting on cell lysate and RNA sequencing. Bioinformatics analysis revealed that rhPRG4 had a significant effect on TNF-mediated inflammation with potential effects on matricellular homeostasis. rhPRG4 reduced activation of key inflammatory pathways and decreased expression of transcripts for key inflammatory cytokines, interferons, interleu-kins, and transcription factors. TNF treatment significantly increased phosphorylation and nuclear translocation of p65, and rhPRG4 significantly reduced both these effects. RNA sequencing identified FAT10, which has not been studied in the context of DED, as a key pro-inflammatory transcript increased by TNF and decreased by rhPRG4. These results were confirmed at the protein level. In summary, rhPRG4 is able to downregulate NF{kappa}B activity in hTCEpi cells, suggesting a potential biological mechanism by which it may act as a therapeutic for DED.

molecular biology↗