Biology subjects

Yuan, H.

Publications and source records attributed to Yuan, H..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Estimation of Species Abundance Based on the Number of Segregating Sites using Environmental DNA (eDNA)

The advance of environmental DNA (eDNA) has enabled rapid and non-invasive species detection in aquatic environments. Although most studies focus on species detections, some recent studies explored the potential of using eDNA concentration to quantify species abundance. However, the differential individual DNA contribution to eDNA samples could easily obscure the concentration-species abundance relationship. We propose using the number of segregating sites as a proxy for estimating species abundance. Since segregating sites reflects the genetic diversity of the population, which is less sensitive to differential individual DNA contribution than eDNA concentration. We examined the relationship between the number of segregating sites and species abundance in silico, in vitro, and in situ using two brackish goby species, Acanthogobius hasta and Tridentiger bifasciatus. Analyses of the simulated data and in vitro data with DNA mixed from a known number of individuals showed a strong correlation between the number of segregating sites and species abundance (R2 > 0.9; P < 0.01). Results from the in situ experiment further validated the correlation (R2 = 0.70, P < 0.01), and such correlation was not affected by biotic factors, including body size and feeding behavior (P > 0.05). Results of the cross-validation test also showed that the number of segregating sites predicted species abundance with less bias and variability than the eDNA concentration. Overall, the number of segregating sites correlates stronger with species abundance and also provides a better estimate than eDNA concentration. This advancement can significantly enhance the quantitative capabilities of eDNA technology.

ecology↗

bioRxiv2024

O-GlcNAcylation of the intellectual disability protein DDX3X exerts proteostatic cell cycle control

O-GlcNAcylation is an evolutionary conserved post-translational modification implicated in neurodevelopment. Missense variants of O-GlcNAc transferase (OGT) are causal for the intellectual disability syndrome OGT Congenital Disorder of Glycosylation (OGT-CDG). The observation of microcephaly in OGT-CDG patients suggests that dysregulation of the cell cycle and aberrant neurogenesis may contribute to disease aetiology. Here, we identify Ser584 O-GlcNAcylation of DDX3X, a known intellectual disability and microcephaly associated protein, as a key regulator of G1/S-phase transition, inhibiting proteasome-dependent degradation of DDX3X. DDX3X levels are reduced in a mouse model of OGT-CDG, alongside the DDX3X-target gene and synaptogenic regulator cyclin E1. These data reveal how a single DDX3X O-GlcNAc site exerts control of the cell cycle and highlights dysregulation of DDX3X-dependent translation, and concomitant impairments in cortical neurogenesis, as a possible pathway disrupted in OGT-CDG.

cell biology↗

bioRxiv2024

Jianpi Jiedu Recipe inhibits proliferation through reactive oxygen species-induced incomplete autophagy and reduces PD-L1 expression in colon cancer

BackgroundJianpi Jiedu Recipe has been used to treat digestive tract tumors in China since ancient times, and its reliability has been proven by clinical research. Currently, the specific biological mechanism of JPJDR in treating tumors is unclear. MethodologyCCK-8 assay was used to detect cell viability. Clone formation assay and EdU assay were used to detect cell proliferation potential. DCFH-DA probe and JC-1 probe were used to detect total intracellular reactive oxygen species and mitochondrial membrane potential, respectively. Western blotting and immunofluorescence were used to detect protein expression level and subcellular localization of cells. RFP-GFP-LC3B reporter system was used to observe the type of autophagy in cells. Xenograft tumor model was used to study the therapeutic effect of JPJDR in vivo. ResultsJPJDR has a good inhibitory effect on various colorectal cancer cells and effectively reduces the proliferation ability of HT29 cells. After treatment with JPJDR, the amount of reactive oxygen species in HT29 cells increased significantly and the mitochondrial membrane potential decreased. JPJDR induced the accumulation of autophagosomes in HT29 cells and was shown to be incomplete autophagy. At the same time, JPJDR reduced the expression of PD-L1.Meanwhile, JPJDR can exert a good therapeutic effect in xenograft tumor mice. ConclusionJPJDR is a low-toxic and effective anti-tumor agent that can effectively treat colon cancer in vitro and in vivo. Its mechanism may be through inducing mitochondrial dysfunction and incomplete autophagy injury to inhibit the proliferation of colon cancer cells.

pharmacology and toxicology↗

bioRxiv2023

Insight into the gut virome in patients with multiple sclerosis

Multiple sclerosis (MS) is an autoimmune condition associated with dysbiosis in the bacterial element of microbiome, yet limited information exists regarding dysbiosis in the virome. In this study, we examined the virome in 20 relapsing-remitting MS (RRMS) patients and 22 healthy controls (HC). We extracted virus-like particles (VLP) genomic DNA through sequential filtration, followed by deep metagenomic sequencing approaches with and without multiple displacement amplification (MDA). We found significantly lower diversity in the gut virome of RRMS patients relative to HC, consistent across both sequencing methods. MDA method identified reduced relative abundance of Microviridae and Myoviridae bacteriophage, and eukaryotic virus such as Herpesviridae and Phycodnaviridae in RRMS patients compared to HC. Non-MDA methods showed reduction in relative abundance of Siphoviridae bacteriophage and eukaryotic viruses such as Ackermannviridae, Demerecviridae, Dicistroviridae, Herelleviridae, Mesnidovirineae in RRMS patients. Cluster analysis revealed that the whole virome family was dominated by Podoviridae and Siphoviridae clusters. Comparing dietary metadata between these clusters, RRMS patients in the Siphoviridae-dominated Cluster B showed significantly higher consumption of refined grains and salad dressings compared to those in the Podoviridae-dominated Cluster A. Correlation analysis between gut viruses and bacteria demonstrated that Siphoviridae exhibited positive correlations with many different bacterial genera. Conversely, Microviridae displayed negative correlations with many different bacterial genera. These findings underscore the alterations in viral diversity and taxonomic composition of the gut virome in RRMS patients. Our study represents the first step in understanding the gut virome in MS patients, providing a groundwork for future research on the role of the gut virome in the context of MS.

microbiology↗

bioRxiv2023

MdHY5 and MdHY5S form a transcription loop to regulate browning and phenolics synthesis in apple under purple light

Enzymatic browning significantly affects the appearance and quality of fresh-cut fruit. Light treatment can effectively inhibit fresh-cut apple browning via unknown molecular mechanisms. Here, we found that the application of purple LED light decreased the browning index of fresh-cut apple, delaying browning as compared to that of fresh-cut apple placed in the dark, and suggesting that purple LED light suppresses browning. In addition, the expression levels of MdHY5 and MdHY5S, important BASIC LEUCINE ZIPPER DOMAIN (bZIP) transcription factors that are involved in the light signaling pathway, were increased by purple LED light treatment. Silencing MdHY5 and MdHY5S in apple meant that purple LED light treatment no longer inhibited fresh-cut apple browning, the expression levels of the browning-related genes POLYPHENOL OXIDASE (MdPPO) and PEROXIDASE (MdPOD) increased, and the expression of the phenolic synthesis gene PHENYLALANINE AMMONIALYASE (MdPAL) decreased. Further study revealed that MdHY5 and MdHY5S bind to the MdPPO and MdPOD promoters, reducing their transcription. In contrast, MdHY5 and MdHY5S bind to the MdPAL promoter, enhancing transcription. Further research revealed that MdHY5 and MdHY5S also bind directly to each others promoters to form a positive transcriptional loop that activates their transcription. Our findings revealed that purple LED light inhibits browning and increases phenolics synthesis in fresh-cut apple by activating MdHY5 and MdHY5S. The results provide a theoretical basis upon which the new methods for improving the appearance and quality of fresh-cut apple can be based.

developmental biology↗

bioRxiv2023

Paternal genomic resources from the YanHuang cohort suggested a Weakly-Differentiated Multi-source Admixture model for the formation of Hans founding ancestral lineages

The large-scale human genome revolution and rapidly advanced statistical innovation have updated our understanding of the fine-scale and complex genetic structure, the entire landscape of genetic diversity and the evolutionary trajectories of spatiotemporally different ancients and ethnolinguistically diverse modern populations. Recent ancient DNA research provided a detailed and complex admixture picture of ancient Europeans but limited insights into East Asians as the few available genomes. Y-chromosome variations in the male-specific regions, served as molecular archaeological tool, have unique evolutionary features that can be utilized to reconstruct the origin and subsequent interaction of ancient East Asian paternal lineages. We launched the YanHuang cohort using our designed highest-resolution capture sequencing panel to explore the detailed evolutionary trajectory of the Han Chinese, one of the largest ethnic groups in the world. We reported one of the largest uniparental genomic resources and observed multiple founding paternal lineages dominant in ancient western Eurasian, Siberian and East Asian participating in the formation of the gene pool of the Han Chinese. We identified fine-scale paternal genetic structure correlated with different patterns of ancient population interaction and geographical mountain barriers (Qinling-Huaihe line and Nanling Mountains), suggesting isolation-enhanced and admixture-introduced genetic differentiation enhanced the complexity of the Han Chinese genomic diversity. We observed a strong direct correlation between the frequency of multiple founding lineages of the Han Chinese and the proportion of subsistence-related ancestry sources related to western pastoralists, Holocene Mongolian Plateau people and ancient East Asians, reflecting the ancient migration events contributed to our identified patterns of Chinese paternal genomic diversity. We finally provided one novel and the most plausible admixture-by-admixture model, the Weakly-Differentiated Multi-Source Admixture model, as the major genetic mechanism to illuminate our observed pattern of complex interactions of multiple ancestral sources and landscape of the Han Chinese paternal genetic diversity. Generally, we presented one large-scale uniparental genomic resource from the YanHuang cohort, portrayed one novel admixture formation model and presented the entire genomic landscape with multiple ancestral sources related to ancient herders, hunter-gatherers and farmers who participated in the ancestral formation of the Han Chinese.

evolutionary biology↗

bioRxiv2023

CONE: COntext-specific Network Embedding via Contextualized Graph Attention

Human gene interaction networks, commonly known as interactomes, encode genes functional relationships, which are invaluable knowledge for translational medical research and the mechanistic understanding of complex human diseases. Meanwhile, the advancement of network embedding techniques has inspired recent efforts to identify novel human disease-associated genes using canonical interac-tome embeddings. However, one pivotal challenge that persists stems from the fact that many complex diseases manifest in specific biological contexts, such as tissues or cell types, and many existing interactomes do not encapsulate such information. Here, we propose CONE3, a versatile approach to generate context-specific embeddings from a context-free interactome. The core component of CONE consists of a graph attention network with contextual conditioning, and it is trained in a noise contrastive fashion using contextualized interactome random walks localized around contextual genes. We demonstrate the strong performance of CONE embeddings in identifying disease-associated genes when using known associated biological contexts to the diseases. Furthermore, our approach offers insights into understanding the biological contexts associated with human diseases.

bioinformatics↗

bioRxiv2023

High-throughput and in-depth analysis of plasma proteome by UV-assisted protein digestion, 5-plex labeling and MS-based high abundance protein removal method

Human plasma contains various proteins, some of which reflect individuals physiological health state or predict diseases. Therefore, plasma analysis can provide a wealth of information on novel biomarkers for clinical diagnosis and prognosis. The use of mass spectrometry (MS) for high-throughput and in-depth quantitative proteomic analysis of plasma allows for highly specific and quantitative readout, but is challenging because of the high dynamic range of protein abundances. Here, we introduce a robust, high-throughput, and in-depth workflow for plasma proteome analysis based on UV-assisted rapid protein digestion, 5-plex dimethyl labeling, and MS-based high abundance protein removal. UV-assisted protein digestion could quantify the same protein numbers as traditional enzymatic hydrolysis and achieve a low miss-cleavage rate in only 20 minutes. And the MS-based high abundance protein removed 5-plex DIA method, which does not require extra protein depletion procedures, enables quantitative analysis of more than 600 proteins using an equivalent MS analysis time of 30 minutes per sample. The average relative error was 6.9%. We believe the method is beneficial for analyzing large numbers of trace-level clinical samples and broaden a vision for the discovery of low abundance protein markers.

biochemistry↗

bioRxiv2023

Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation

Sequence-based machine learning models trained on genome-scale biochemical assays improve our ability to interpret genetic variants by providing functional predictions describing their impact on the cis-regulatory code. Here, we introduce a new model, Borzoi, which learns to predict cell- and tissue-specific RNA-seq coverage from DNA sequence. Using statistics derived from Borzois predicted coverage, we isolate and accurately score variant effects across multiple layers of regulation, including transcription, splicing, and polyadenylation. Evaluated on QTLs, Borzoi is competitive with, and often outperforms, state-of-the-art models trained on individual regulatory functions. By applying attribution methods to the derived statistics, we extract cis-regulatory patterns driving RNA expression and post-transcriptional regulation in normal tissues. The wide availability of RNA-seq data across species, conditions, and assays profiling specific aspects of regulation emphasizes the potential of this approach to decipher the mapping from DNA sequence to regulatory function.

genomics↗

bioRxiv2023

Alternating Polarity as a Novel Strategy for Cultivating Electro-Methanogenic Microbial Communities Capable of Robust Biogas Production

Electro-methanogenic microbial communities can produce biogas with high efficiency. Extensive efforts have been made to cultivate these communities in engineered systems. Conventional cultivation strategies can select electrotrophic methanogens but not their electron-donating partners, resulting in communities that are sensitive to perturbations. Herein, we developed an alternating polarity strategy to simultaneously select both microbial populations. In two-chamber bioelectrochemical systems amended with activated carbon, the electrode potential was alternated between +0.8 V and -0.4 V vs. standard hydrogen electrode every three days. After eight alternating cycles, cultivated activated carbon was transferred into new bioreactors, and the enrichment procedure was repeated four times. Cumulative biogas production under alternating polarity increased from 45 L/L/kg-activated carbon after start-up to 125 L/L/kg after the 4th enrichment, significantly higher than that under intermittent cathode (-0.4 V/open circuit), continuous cathode (-0.4 V), and open circuit. The communities cultivated under alternating polarity were electroactive and structurally different from those cultivated under other conditions. One Methanobacterium population and two Geobacter populations were consistently abundant and active in the communities. Their 16S rRNA was upregulated by electrode potentials. Bayesian networks inferred close associations between these populations. The cultivation strategy can enhance biogas production, and the cultivated communities may serve as a model system for elucidating the mechanisms of extracellular electron uptake. SynopsisAn alternating polarity strategy was developed in this study to cultivate electro-methanogenic microbial communities. The cultivated communities can produce biogas more efficiently and help us understand the ecophysiology of the key microbial populations.

ecology↗

bioRxiv2023

Ancient farmer and steppe pastoralist-related founding lineages contributed to the complex landscape of episodes in the diversification of Chinese paternal lineages

Ancient DNA advances have reported the complex genetic history of Eurasians, but how the knowledge of ancient subsistence strategy shifts and population movements influenced the fine-scale paternal genetic structure in East Asia has not been assessed. Here, we reported one integrated Y-chromosome genomic database of 15,530 people, including 1753 ancient people and newly-reported 919 individuals genotyped using our recently-developed targeted sequencing YHSeqY3000 panel, to explore Chinese genomic diversity, population evolutionary tracts and their genetic formation mechanism. We identified four major ancient technological innovations and population movements that shaped the landscape of Chinese paternal lineages. First, the expansion of millet farmers and early East Asians from the Yellow River Basin carrying the major O2/D subclades promoted the formation of the Sino-Tibetan peoples major composition and accelerated the Tibetan Plateaus permanent occupation. Second, rice farmers dispersal from the Yangtze River Valley carrying O1 and some sublineages of O2 contributed significantly to Tai-Kadai, Austronesian, Hmong-Mien, Austroasiatic people and southern Han Chinese. Third, Siberian-related paternal lineages of Q and C originated and boomed from Neolithic hunter-gatherers from the Mongolian Plateau and the Amur River Basin and significantly influenced the gene pools of northern Chinese. Fourth, western Eurasian-derived J, G and R lineages initially spread with Yamnaya steppe pastoralists and other proto-Indo-European people and further widely dispersed via the trans-Eurasian cultural communication along the Eurasian Steppe and the ancient Silk Road, remaining genetic trajectories in northwestern Chinese. Our work provided comprehensive modern and ancient genetic evidence to illuminate the impact of population interaction from the ancient farmer or herder-based societies on the genetic diversity patterns of modern people, revised our understandings of ancestral sources of Chinese paternal lineages, underscored the scientific imperative of the large-scale genomic resources of dense spatiotemporal underrepresented sampling populations to understand human evolutionary history.

genetics↗

bioRxiv2023

Cross-regulation between proteome reallocation and metabolic flux redistribution governs bacterial growth transition kinetics

Bacteria need to adjust their metabolism and protein synthesis simultaneously to adapt to changing nutrient conditions. Its still a grand challenge to predict how cells coordinate such adaptation due to the cross-regulation between the metabolic fluxes and the protein synthesis. Here we developed a dynamic Constrained Allocation Flux Balance Analysis method (dCAFBA), which integrates flux-controlled proteome allocation and protein limited flux balance analysis. This framework can predict the redistribution dynamics of metabolic fluxes without requiring detailed enzyme parameters. We reveal that during nutrient up-shifts, the calculated metabolic fluxes change in agreement with experimental measurements of enzyme protein dynamics. During nutrient down-shifts, we uncover a switch of metabolic bottleneck from carbon uptake proteins to metabolic enzymes, which disrupts the coordination between metabolic flux and their enzyme abundance. Our method provides a quantitative framework to investigate cellular metabolism under varying environments and reveals insights into bacterial adaptation strategies.

systems biology↗

bioRxiv2023

Hybrid Modeling of Engineered Biological Systems through Coupling Data-Driven Calibration of Kinetic Parameters with Mechanistic Prediction of System Performance

Mechanistic models can provide predictive insight into the design and optimization of engineered biological systems, but the kinetic parameters in the models need to be frequently calibrated and uniquely identified. This limitation can be addressed by integrating mechanistic models with data-driven approaches, a strategy known as hybrid modeling. Herein, we developed a hybrid modeling strategy using bioelectrochemical systems as a platform system. The data-driven component of the model consisted of artificial neural networks (ANNs) that were trained by using mechanistically derived parameter values (e.g., the maximum specific growth rate {micro}max and the maximum substrate utilization rate kmax for the fermentative, electroactive, and methanogenic populations, and the mediator yield for electroactive microbes YM) as outputs to compute error signals. The hybrid model was built using 148 samples collected from 25 publications. After ten-fold cross-validation, the model was tested with another 28 samples. Internal resistance was accurately predicted with a relative root-mean-square error (RMSE) of 3.9%. Microbial kinetic parameters were also calibrated using the data-driven component. They were fed into the mechanistic component to predict system performance. The R2 between the predicted and observed organic removal and current production for systems fed with a simple substrate were 0.90 and 0.94, respectively, significantly higher than those obtained with a standalone data-driven model (0.51 and 0) and a standalone mechanistic model (0.07 and 0.15). The hybrid modeling strategy can potentially be applied to a variety of engineered biological systems for in silico system design and optimization. SYNOPSISA hybrid modeling strategy was developed to predict the performance of engineered biological systems without the need for laborious experiment-based parameter calibration.

microbiology↗

bioRxiv2023

Combination of Polymeric Micelle Formulation of TGFβ Receptor Inhibitors and Paclitaxel Produce Consistent Response Across Different Mouse Models of TNBC

Triple-negative breast cancer (TNBC) is notoriously difficult to treat due to the lack of targetable receptors and sometimes poor response to chemotherapy. The transforming growth factor-beta (TGF{beta}) family of proteins and their receptors (TGFR) are highly expressed in TNBC and implicated in chemotherapy-induced cancer stemness. Here we evaluated combination treatments using experimental TGFR inhibitors (TGF{beta}i), SB525334 (SB), and LY2109761 (LY) with Paclitaxel (PTX) chemotherapy. These TGF{beta}i target TGFR-I (SB) or both TGFR-I&II (LY). Due to the poor water solubility of these drugs, we incorporated each of them in poly(2-oxazoline) (POx) high-capacity polymeric micelles (SB-POx and LY-POx). We assessed their anti-cancer effect as single agents and in combination with micellar Paclitaxel (PTX-POx) using multiple immunocompetent TNBC mouse models that mimic human subtypes (4T1, T11-Apobec and T11-UV). While either TGF{beta}i or PTX showed a differential effect in each model as single agents, the combinations were consistently effective against all three models. Genetic profiling of the tumors revealed differences in the expression levels of genes associated with TGF{beta}, EMT, TLR-4, and Bcl2 signaling, alluding to the susceptibility to specific gene signatures to the treatment. Taken together, our study suggests that TGF{beta}i and PTX combination therapy using high-capacity POx micelle delivery provides a robust anti-tumor response in multiple TNBC subtype mouse models. Translational Impact StatementPaclitaxel is a widely used chemotherapy in breast cancer. However, response to single-agent chemotherapy is short-lived in a metastatic setting. This study shows the broad applicability of the therapeutic combination of TGF{beta} inhibitors with Paclitaxel across different TNBC subtypes.

cancer biology↗

bioRxiv2023

Mammalian Esophageal Stratified Tissue Homeostasis is Maintained Distinctively by the Epithelial Pluripotent p63+Sox2+ and p63-Sox2+ Cell Populations

Self-renewing, damage-repair and differentiation of mammalian stratified squamous epithelia are subject to tissue homeostasis, but the regulation mechanisms remain elusive. Here, we investigate the esophageal squamous epithelial tissue homeostasis in vitro and in vivo. We establish a rat esophageal organoid (rEO) in vitro system and show that the landscapes of rEO formation, development and maturation trajectories can mimic those of rat esophageal epithelia in vivo. Single-cell RNA sequencing (scRNA-seq), snap-shot immunostaining and functional analyses of stratified "matured" rEOs define that the epithelial pluripotent stem-cell determinants, p63 and Sox2, play crucial but distinctive roles for regulating mammalian esophageal tissue homeostasis. We identify two cell populations, p63+Sox2+ and p63-Sox2+, of which the p63+Sox2+ population presented at the basal layer is the cells of origin required for esophageal epithelial stemness maintenance and proliferation whereas the p63-Sox2+ population presented at the suprabasal layers is the cells of origin having a dual role for esophageal epithelial differentiation (differentiation-prone fate) and rapid tissue damage-repair responses (proliferation-prone fate). Given the fact that p63 and Sox2 are developmental lineage oncogenes and commonly overexpressed in ESCC tissues, p63-Sox2+ population could not be detected in organoids formed by esophageal squamous cell carcinoma (ESCC) cell lines. Taken together, these findings reveal that the tissue homeostasis is maintained distinctively by p63 and/or Sox2 dependent cell lineage populations required for the tissue renewing, damage-repair and protection of carcinogenesis in mammalian esophagi.

cell biology↗

bioRxiv2023

Identification of mobile element insertion from whole genome sequencing data using deep neural network model

Mobile element insertions (MEIs) are a major contributor to genome evolution and play an essential role in the regulation of gene expression, as well as being implicated in various human diseases. This study introduces DeepMEI, a tool based on a convolutional neural network model that transforms the MEI identification process into an image recognition problem and automatically learns complex and abstract representations of MEI features in whole genome sequencing data. DeepMEI outperformed existing tools in the benchmark dataset from the Genome in a Bottle consortium, with a precision of 0.90 and recall of 0.70. Moreover, factors such as sequencing depth, ME integrity, and genome mappability can affect MEI identification accuracy. Using DeepMEI, we reanalyzed 3,202 high-coverage whole-genome sequencing samples from the 1000 Genome Project (1kGP) phase 4 release, discovering 1.71-fold more non-reference MEIs, totaling 6,218,088, with 92.2% of the increase coming from rare MEIs (allele frequency <1%). This enhances our understanding of MEIs role in human disease and evolution. The DeepMEI tool and the updated 1kGP MEI dataset can be accessed at https://github.com/xuxif/DeepMEI.

bioinformatics↗

bioRxiv2023

Mis-spliced transcripts generate de novo proteins in TDP-43-related ALS/FTD

Functional loss of TDP-43, an RNA-binding protein genetically and pathologically linked to ALS and FTD, leads to inclusion of cryptic exons in hundreds of transcripts during disease. Cryptic exons can promote degradation of affected transcripts, deleteriously altering cellular function through loss-of-function mechanisms. However, the possibility of de novo protein synthesis from cryptic exon transcripts has not been explored. Here, we show that mRNA transcripts harboring cryptic exons generate de novo proteins both in TDP-43 deficient cellular models and in disease. Using coordinated transcriptomic and proteomic studies of TDP-43 depleted iPSC-derived neurons, we identified numerous peptides that mapped to cryptic exons. Cryptic exons identified in iPSC models were highly predictive of cryptic exons expressed in brains of patients with TDP-43 proteinopathy, including cryptic transcripts that generated de novo proteins. We discovered that inclusion of cryptic peptide sequences in proteins altered their interactions with other proteins, thereby likely altering their function. Finally, we showed that these de novo peptides were present in CSF from patients with ALS. The demonstration of cryptic exon translation suggests new mechanisms for ALS pathophysiology downstream of TDP-43 dysfunction and may provide a strategy for novel biomarker development. One Sentence SummaryLoss of TDP-43 function results in the expression of de novo proteins from mis-spliced mRNA transcripts.

neuroscience↗

bioRxiv2022

Small Molecule Screen Identifies Pyrimethamine as an Inhibitor of NRF2-driven Esophageal Hyperplasia

ObjectiveNRF2 is a master transcription factor that regulates the stress response. NRF2 is frequently mutated and activated in human esophageal squamous cell carcinoma (ESCC), which drives resistance to chemotherapy and radiation therapy. Therefore, a great need exists for NRF2 inhibitors for targeted therapy of NRF2high ESCC. DesignWe performed high-throughput screening of two compound libraries from which hit compounds were further validated in human ESCC cells and a genetically modified mouse model. The mechanism of action of one compound was explored by biochemical assays. ResultsUsing high-throughput screening of two small molecule compound libraries, we identified 11 hit compounds as potential NRF2 inhibitors with minimal cytotoxicity at specified concentrations. We then validated two of these compounds, pyrimethamine and mitoxantrone, by demonstrating their dose- and time-dependent inhibitory effects on the expression of NRF2 and its target genes in two NRF2Mut human ESCC cells (KYSE70 and KYSE180). RNAseq and qPCR confirmed the suppression of global NRF2 signaling by these two compounds. Mechanistically, pyrimethamine reduced NRF2 half-life by promoting NRF2 ubiquitination and degradation in KYSE70 and KYSE180 cells. Expression of an Nrf2E79Q allele in mouse esophageal epithelium (Sox2CreER;LSL-Nrf2E79Q/+) resulted in an NRF2high phenotype, which included squamous hyperplasia, hyperkeratinization, and hyperactive glycolysis. Treatment with pyrimethamine (30mg/kg/day, p.o.) suppressed the NRF2high esophageal phenotype with no observed toxicity. ConclusionWe have identified and validated pyrimethamine as an NRF2 inhibitor that may be rapidly tested in the clinic as a radiation and chemotherapy sensitizer for NRF2high ESCC. SummaryO_ST_ABSWhat is already known on this topic - summarise the state of scientific knowledge on this subject before you did your study and why this study needed to be doneC_ST_ABSO_LIMutational activation of the NRF2 transcription factor drives ESCC progression and therapeutic resistance. Targeted therapies to block NRF2 have not yet been realized, despite great needs. C_LI What this study adds - summarise what we now know as a result of this study that we did not know beforeO_LIA screen of >35,000 small molecules identified eleven potential NRF2 inhibitors. Pyrimethamine and mitoxantrone were validated to inhibit the expression of NRF2 and NQO1 in human ESCC cells in both dose- and time-dependent manners. C_LIO_LIPyrimethamine enhanced NRF2 protein ubiquitination and degradation, resulting a decreased half-life. C_LIO_LIA genetically modified mouse model was established to express the Nrf2E79Q mutant allele in the mouse esophageal epithelium upon tamoxifen induction. Pyrimethamine suppressed the NRF2high esophageal phenotype induced by the mutant allele. C_LI How this study might affect research, practice or policy - summarise the implications of this studyO_LIAs an FDA-approved drug, Pyrimethamine has the potential for immediate translation to a clinical trial on NRF2high ESCC in humans. C_LIO_LIFurther exploration of its mechanisms of action may lead to more potent NRF2 inhibitors for future use. C_LI

cancer biology↗