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Gao, J.

Publications and source records attributed to Gao, J..

At least 145 records · Page 8Linked to original sources

Adeno-to-squamous transition drives resistance to KRAS inhibition in LKB1 mutant lung cancer

KRASG12C inhibitors including adagrasib and sortorasib have shown clinical promise in targeting KRASG12C-mutated lung cancers, however, most patients eventually develop drug resistance. In lung adenocarcinoma patients with co-occurring KRASG12C and STK11/LKB1 mutations, we found a high squamous gene signature at baseline significantly correlated with poor adagrasib response. Through integrative studies of Lkb1-deficient KRASG12Cand KrasG12D lung cancer mouse models and/or organoids treated with KRAS inhibitors, we found tumor cells invoked a lineage plasticity program: adeno-to-squamous transition (AST) that mediated resistance to KRAS inhibition. Transcriptomic and epigenomic analyses revealed {Delta}Np63 drives AST and modulates response to KRAS inhibition. We identified an intermediate high-plasticity cell state with distinct gene expression program marked by Krt6a upregulation. Notably, higher KRT6A expression at baseline correlated with shorter overall survival in KRAS-mutant patients receiving adagrasib. These data support the role of AST in KRAS inhibitor resistance and provide predictive biomarker for KRAS-targeted therapies in lung cancer.

cancer biology↗

Oxytocin alleviated colitis and colitis-associated colorectal tumorigenesis by targeting fucosylated MUC2

Colon cancer is commonly regarded as hormone-independent. However, there have been reports suggesting the involvement of sex hormones in colon cancer development. Nevertheless, the role of hormones from the hypothalamus-hypophysis axis in colitis-associated colorectal cancer (CAC) remains uncertain. In this study, we observed a significant reduction in the expression of the oxytocin receptor (OXTR) in colon samples from both colitis and CAC patients. To investigate further, we generated mice with an intestinal epithelium cell (IEC)-specific knockout of OXTR. These mice exhibited markedly increased susceptibility to dextran sulfate sodium (DSS)-induced colitis and DSS/Azoxymethane (AOM)-induced CAC compared to wild-type mice. Our findings indicate that OXTR depletion impaired the inner mucus of the colon epithelium. Mechanistically, oxytocin was found to regulate MUC2 maturation through B3GNT7-mediated fucosylation. Interestingly, we observed a positive correlation between B3GNT7 expression and OXTR expression in human colitis and CAC colon samples. Moreover, the administration of oxytocin significantly alleviated tumor burden. Hence, our study unveils oxytocins promising potential as an affordable and effective therapeutic intervention for individuals affected by colitis and CAC.

physiology↗

Targeting adipocyte ESRRA promotes osteogenesis and vascular formation in adipocyte-rich bone marrow

Ectopic bone marrow adipocytes (BMAds) accumulation occurring under diverse pathophysiological conditions leads to bone deterioration. Estrogen-related receptor (ESRRA) is a key regulator responding to metabolic stress. Here, we show that adipocyte-specific ESRRA deficiency rescues osteogenesis and vascular formation in adipocyte-rich bone marrow due to estrogen deficiency or obesity. Mechanistically, adipocyte ESRRA interferes with E2/ESR1 signaling resulting in transcriptional repression of secreted phosphoprotein 1 (Spp1); and positively modulates Leptin expression by binding to its promoter. ESRRA abrogation results in enhanced SPP1 and decreased LEPTIN secretion from both visceral adipocytes and BMAds, concertedly dictating bone marrow stromal stem cell fate commitment and restoring type H vessel formation, constituting a feed-forward loop for bone formation. Pharmacological inhibition of ESRRA protects obese mice against bone loss and high marrow adiposity. Thus, our findings highlight a therapeutic approach via targeting adipocyte ESRRA to preserve bone formation especially in detrimental adipocyte-rich bone milieu. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/552932v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1132da3org.highwire.dtl.DTLVardef@19342aorg.highwire.dtl.DTLVardef@afe8d7org.highwire.dtl.DTLVardef@dfb1f9_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

ProjectSVR: Mapping single-cell RNA-seq data to reference atlases by supported vector regression

The rapid accumulation of public single-cell RNA-seq (scRNA-seq) data and advances in integration algorithms make it possible to build the organ and body-scale cell atlases after overcoming the batch effect originating from different studies, donors, and sequence platforms. However, projecting the query cells onto the carefully constructed reference atlas to rapidly interpret cell states remains challenging. Here, we present ProjectSVR (https://github.com/jarninggau/ProjectSVR), a machine learning-based algorithm for mapping the query cells onto well-constructed reference embeddings. We demonstrate the effectiveness of ProjectSVR in multiple case studies of different tissue and experimental design, including (1) interpreting the decidual immune microenvironment from recurrent pregnancy loss (RPL) patients, (2) resolving the tumor-infiltrated T cell states from patients receiving anti-PD1 treatment, (3) mapping the genetic-perturbed mouse germ cells to integrated mouse testicular cell atlas (mTCA) for inferring their arrested developmental stage, and (4) evaluating in vitro induced meiosis by via mapping the induced germ cells onto mTCA. Taken together, our results show that ProjectSVR is a useful tool for reference mapping and make the scRNA-seq data analysis more convenient when well-annotated atlases emerge.

bioinformatics↗

Functional analysis of cyclic diguanylate-modulating proteins in Vibrio fischeri

As bacterial symbionts transition from a motile free-living state to a sessile biofilm state, they must coordinate behavior changes suitable to each lifestyle. Cyclic diguanylate (c-di-GMP) is an intracellular signaling molecule that can regulate this transition, and it is synthesized by diguanylate cyclase (DGC) enzymes and degraded by phosphodiesterase (PDE) enzymes. Generally, c-di-GMP inhibits motility and promotes biofilm formation. While c-di-GMP and the enzymes that contribute to its metabolism have been well-studied in pathogens, considerably less focus has been placed on c-di-GMP regulation in beneficial symbionts. Vibrio fischeri is the sole beneficial symbiont of the Hawaiian bobtail squid (Euprymna scolopes) light organ, and the bacterium requires both motility and biofilm formation to efficiently colonize. C-di-GMP regulates swimming motility and cellulose exopolysaccharide production in V. fischeri. The genome encodes 50 DGCs and PDEs, and while a few of these proteins have been characterized, the majority have not undergone comprehensive characterization. In this study, we use protein overexpression to systematically characterize the functional potential of all 50 V. fischeri proteins. All 28 predicted DGCs and 14 predicted PDEs displayed at least one phenotype consistent with their predicted function, and a majority of each displayed multiple phenotypes. Finally, active site mutant analysis of proteins with the potential for both DGC and PDE activities revealed potential activities for these proteins. This work presents a systems-level functional analysis of a family of signaling proteins in a tractable animal symbiont and will inform future efforts to characterize the roles of individual proteins during lifestyle transitions. IMPORTANCEC-di-GMP is a critical second messenger that mediates bacterial behaviors, and V. fischeri colonization of its Hawaiian bobtail squid host presents a tractable model in which to interrogate the role of c-di-GMP during animal colonization. This work provides systems-level characterization of the 50 proteins predicted to modulate c-di-GMP levels. By combining multiple assays, we generated a rich understanding of which proteins have the capacity to influence c-di-GMP levels and behaviors. Our functional approach yielded insights into how proteins with domains to both synthesize and degrade c-di-GMP may impact bacterial behaviors. Finally, we integrated published data to provide a broader picture of each of the 50 proteins analyzed. This study will inform future work to define specific pathways by which c-di-GMP regulates symbiotic behaviors and transitions.

microbiology↗

Combination EZH2 inhibition and retinoic acid treatment promotes differentiation and apoptosis in rhabdomyosarcoma cells

Rhabdomyosarcomas (RMS) are predominantly pediatric sarcomas thought to originate from muscle precursor cells due to impaired myogenic differentiation. Despite intensive treatment, 5-year survival for patients with advanced disease remains low (<30%), highlighting a need for novel therapies to improve outcomes. Differentiation therapeutics are agents that induce differentiation of cancer cells from malignant to benign. The histone methyltransferase, Enhancer of Zeste Homolog 2 (EZH2) suppresses normal skeletal muscle differentiation and is highly expressed in RMS tumors. We demonstrate combining EZH2 inhibition with the differentiating agent retinoic acid (RA) is more effective at reducing cell proliferation in RMS cell lines than single agents alone. In PAX3 -FOXO1 positive RMS cells this is due to an RA-driven induction of the interferon pathway resulting in apoptosis. In fusion negative RMS, combination therapy led to an EZH2i-driven upregulation of myogenic signaling resulting in differentiation. These results provide insight into the mechanism that drives the anti-cancer effect of the EZH2/RA single agent and combination treatment and indicate that the reduction of EZH2 activity combined with the induction of RA signalling represents a potential novel therapeutic strategy to treat both subtypes of RMS. HighlightsO_LIEZH2 expression is upregulated fusion positive (FPRMS) and fusion negative (FNRMS) rhabdomyosarcomas C_LIO_LIEZH2 inhibition combined with retinoic acid treatment was investigated RMS cell models. C_LIO_LICombination treatment reduced cell proliferation and tumor spheroid volume. C_LIO_LICombination treatment in FPRMS resulted in apoptosis in FPRMS via interferon signaling. C_LIO_LIConversely, combination treatment in fusion negative RMS resulted in myogenic differentiation. C_LI

cancer biology↗

Neuropathy target esterase activity predicts retinopathy among PNPLA6 disorders

Biallelic pathogenic variants in the PNPLA6 gene cause a broad spectrum of disorders leading to gait disturbance, visual impairment, anterior hypopituitarism, and hair anomalies. PNPLA6 encodes Neuropathy target esterase (NTE), yet the role of NTE dysfunction on affected tissues in the large spectrum of associated disease remains unclear. We present a clinical meta-analysis of a novel cohort of 23 new patients along with 95 reported individuals with PNPLA6 variants that implicate missense variants as a driver of disease pathogenesis. Measuring esterase activity of 46 disease-associated and 20 common variants observed across PNPLA6-associated clinical diagnoses unambiguously reclassified 10 variants as likely pathogenic and 36 variants as pathogenic, establishing a robust functional assay for classifying PNPLA6 variants of unknown significance. Estimating the overall NTE activity of affected individuals revealed a striking inverse relationship between NTE activity and the presence of retinopathy and endocrinopathy. This phenomenon was recaptured in vivo in an allelic mouse series, where a similar NTE threshold for retinopathy exists. Thus, PNPLA6 disorders, previously considered allelic, are a continuous spectrum of pleiotropic phenotypes defined by an NTE genotype:activity:phenotype relationship. This relationship and the generation of a preclinical animal model pave the way for therapeutic trials, using NTE as a biomarker.

neuroscience↗

Haplotype-resolve genome assembly and resequencing provide insights into the origin and domestication of modern rose

Modern rose (Rosa hybrida) is a recently formed interspecific hybrid and has become one of the most important and widely cultivated ornamentals. Here, we report the haplotype-resolved chromosome-scale genome assembly of the tetraploid R. hybrida Samantha and a genome variation map of 233 Rosa accessions involving various wild species, and old and modern cultivars. The two subgenomes of Samantha show no significant global bias in gene loss but substantial expression bias, and homoeologous exchanges are frequently observed between subgenomes. Population genomic and genomic composition analyses reveal the contributions of wild Rosa species to modern roses, and highlight that R. odorata and its derived cultivars contribute more to modern roses than R. chinensis Old Blush. Furthermore, selective sweeps during modern rose breeding associated with major agronomic traits, including continuous flowering, floral organ identity, flower senescence, and disease resistance, are identified. This study provides insights into the genetic basis of modern rose origin and breeding history, and offers unprecedented genomic resources for rose improvement.

genomics↗

Convergent mutations in phage virion assembly proteins enable evasion of Type I CBASS immunity

CBASS is an anti-phage defense system that protects bacteria from phage infection and is evolutionarily related to human cGAS-STING immunity. cGAS-STING signaling is initiated by viral DNA but the stage of phage replication which activates bacterial CBASS remains unclear. Here we define the specificity of Type I CBASS immunity using a comprehensive analysis of 975 operon-phage pairings and show that Type I CBASS operons composed of distinct CD-NTases, and Cap effectors exhibit striking patterns of defense against dsDNA phages across five diverse viral families. We demonstrate that escaper phages evade CBASS immunity by acquiring mutations in structural genes encoding the prohead protease, capsid, and tail fiber proteins. Acquired CBASS resistance is highly operon-specific and typically does not affect overall fitness. However, we observe that some resistance mutations drastically alter phage infection kinetics. Our results define late-stage virus assembly as a critical determinant of CBASS immune activation and evasion by phages.

microbiology↗

Automatic Auditory Streaming Restores Missing Temporal Modulations in Echoic Speech

Human listeners can reliably recognize speech in adverse listening environments, and previous studies have identified that reliable neural encoding of slow temporal modulations in speech is essential for speech recognition. Recent behavioral studies demonstrate that long-delay echoes, which are rare in physical environments but common during online conferencing, can eliminate critical temporal modulations. These echoes, however, barely affect speech intelligibility, and here we investigate the underlying neural mechanisms. MEG experiments demonstrate that cortical activity can effectively track the temporal modulations eliminated by an echo, which cannot be explained by basic neural adaptation mechanisms such as synaptic depression, gain control, and adaptive filtering. Instead, the cortical response to echoic speech is better explained by a model that segregates speech from its echo than a model that encodes echoic speech as a whole. The speech segregation effect is observed even when attention is diverted, but disappears when speech segregation cues in the spectro-temporal fine structure are degraded. Altogether, these results strongly suggest that the auditory system can automatically segregate speech and its echo and encode them as two auditory streams, providing a potential neural basis for reliable speech recognition in echoic environments.

neuroscience↗

Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing

BackgroundDominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena played a major role in quantitative genetics. However, today most genome-wide association studies (GWAS) assume alleles act additively. MethodsWe systematically investigated both dominance - here representing any non-additive effect - and additivity across 574 physiological and gene expression traits in three mammalian models: a Pig F2 Intercross, a Rat Heterogeneous Stock and a Mouse Heterogeneous Stock. ResultsIn all species, and across all physiological traits, dominance accounts for about one quarter of the heritable variance. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable assuming additivity, we identified 154, 64 and 62 novel dominance QTLs in pigs, rats and mice respectively, that were undetectable as additive QTLs. Similarly, even though most cis-acting eQTLs are additive, we observed a large fraction of dominance variance in gene expression, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, in HS rat transcriptomes, thousands of eQTLs associate with alternate transcripts and exhibit complex additive and dominant architectures, suggesting a mechanism for dominance. ConclusionsAlthough heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality.

genetics↗

Automatic sleep staging by a hybrid model based on deep 1D-ResNet-SE and LSTM with single-channel raw EEG signals

Sleep staging is crucial in assessing sleep quality and diagnosing sleep disorders. Recent advances in deep learning methods with electroencephalogram (EEG) signals have shown remarkable success in automatic sleep staging. However, the use of deeper neural networks may lead to the issues of gradient disappearance and explosion, while the non-stationary nature and low signal-to-noise ratio of EEG signals can negatively impact feature representation. To overcome these challenges, we proposed a novel lightweight sequence-to-sequence deep learning model, 1D-ResNet-SE-LSTM, to classify sleep stages into five classes using single-channel raw EEG signals. Our proposed model consists of two main components: a one-dimensional residual convolutional neural network with a squeeze-and-excitation module to extract and reweight features from EEG signals, and a long short-term memory network to capture the transition rules among sleep stages. In addition, we applied the weighted cross-entropy loss function to alleviate the class imbalance problem. We evaluated the performance of our model on two publicly available datasets, Sleep-EDF Expanded and ISRUC-Sleep, and obtained an overall accuracy rate of 86.39% and 81.97%, respectively, along with corresponding macro average F1-scores of 81.95% and 79.94%. Our model outperforms existing sleep staging models, particularly for the N1 stage, where it achieves F1-scores of 59.00% and 55.53%. The kappa coefficient is 0.812 and 0.766 for the Sleep-EDF Expanded and ISRUC-Sleep datasets, respectively, indicating strong agreement with certified sleep experts. We also investigated the effect of different weight coefficient combinations and sequence lengths of EEG epochs used as input to the model on its performance. Furthermore, the ablation study was conducted to evaluate the contribution of each component to the models performance.

neuroscience↗

Modernizing the original influenza vaccine to enhance protective antibody responses against neuraminidase antigens

Most seasonal influenza vaccines are produced using hemagglutinin (HA) surface antigens from inactivated virions. However, virions are thought to be a suboptimal source for the less abundant NA surface antigen, which is also protective against severe disease. Here, we demonstrate that inactivated influenza virions are compatible with two modern approaches for improving protective NA antibody responses. Using a DBA/2J mouse model, we confirmed that the strong infection-induced NA inhibitory (NAI) antibody responses are only achieved by high dose immunizations of inactivated virions, likely due to low viral NA content. Based on this observation, we first produced virions with higher NA content by using reverse genetics to exchange the viral internal gene segments. Single immunizations with these inactivated virions enhanced NAI antibody responses, improved NA-based protection from a lethal viral challenge and allowed the development of natural immunity to the heterotypic challenge virus HA. Second, we combined inactivated virions with recombinant NA proteins. These mixtures increased NA-based protection following viral challenge and elicited stronger NA antibody responses than either component alone, especially when the NAs were homologous. Together, these results indicate that viral- and protein-based vaccines can be combined in a single syringe to improve protective antibody responses to influenza antigens.

microbiology↗

Exponential increase in QTL detection with increased sample size.

Power analyses are often used to determine the number of animals required for a genome wide association analysis (GWAS). These analyses are typically intended to estimate the sample size needed for at least one locus to exceed a genome-wide significance threshold. A related question that is less commonly considered is the number of significant loci that will be discovered with a given sample size. We used simulations based on a real dataset that consisted of 3,173 male and female adult N/NIH heterogeneous stock (HS) rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in sub-samples of the full dataset. The sub-sampling analysis was conducted for four traits with low (0.15 {+/-} 0.03), medium (0.31 {+/-} 0.03 and 0.36 {+/-} 0.03) and high (0.46 {+/-} 0.03) SNP-based heritabilities. For each trait, we sub-sampled the data 100 times at different sample sizes (500, 1,000, 1,500, 2,000, and 2,500). We observed an exponential increase in the number of significant loci with larger sample sizes. Our results are consistent with similar observations in human GWAS and imply that future rodent GWAS should use sample sizes that are significantly larger than those needed to obtain a single significant result.

genetics↗

Bioengineering of a Lactococcus lactis subsp. lactis strain enhances nisin production and bioactivity.

Lactococcus lactis subsp. lactis is a food bacterium that has been utilized for decades in food fermentation and the development of high-value industrial goods. Among these, nisin is produced by several strains of L. lactis subsp. lactis plays a crucial role as a food bio-preservative. The relative expression of the gene cluster involved in nisin production was evaluated using qPCR analysis. Additionally, a series of re-transformations of the strain introducing multi copies of the nisA and nisRK genes involved in nisin biosynthesis were developed. The simultaneous expression of nisA and nisZ genes was used to potentiate the effective inhibition of foodborne pathogens. Further, qPCR analysis revealed a low expression of the nisA and nisRK genes in wild-type L. lactis subsp. lactis. After several re-transformations of the strain with the nisA and nisRK genes, a high expression of these genes was obtained, contributing to improved nisin production. Also, the co-expression of nisA and nisZ genes results in highly efficient antimicrobial activity. Hence, this study would supply an approach to enhancing nisin production during industrial processes and antimicrobial activity.

microbiology↗

Automated quantitative trait locus analysis (AutoQTL)

BackgroundQuantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complex decisions related to analysis of complex traits and generate diverse solutions to describe relationships that exist in genetic data. ResultsUsing a dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model while also providing evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions from simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL. ConclusionsThis proof-of-concept illustrates that automated machine learning techniques can be applied to genetic data and has the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection strategies.

genetics↗

Arginine limitation causes a directed DNA sequence evolution response in colorectal cancer cells

Utilization of specific codons varies significantly across organisms. Cancer represents a model for understanding DNA sequence evolution and could reveal causal factors underlying codon evolution. We found that across human cancer, arginine codons are frequently mutated to other codons. Moreover, arginine restriction--a feature of tumor microenvironments--is sufficient to induce arginine codon-switching mutations in human colon cancer cells. Such DNA codon switching events encode mutant proteins with arginine residue substitutions. Mechanistically, arginine limitation caused rapid reduction of arginine transfer RNAs and the stalling of ribosomes over arginine codons. Such selective pressure against arginine codon translation induced a proteomic shift towards low arginine codon containing genes, including specific amino acid transporters, and caused mutational evolution away from arginine codons--reducing translational bottlenecks that occurred during arginine starvation. Thus, environmental availability of a specific amino acid can influence DNA sequence evolution away from its cognate codons and generate altered proteins.

cancer biology↗

The application of Nicotiana benthamiana as a Transient Expression Host to Clone the Coding Sequences of Plant Genes

Coding sequences (CDS) are commonly used for transient gene expression, in yeast two-hybrid screening, to verify protein interactions and in prokaryotic gene expression studies. CDS are most commonly obtained using complementary DNA (cDNA) derived from messenger RNA (mRNA) extracted from plant tissues and generated by reverse transcription. However, some CDS are difficult to acquire through this process as they are expressed at extremely low levels or have specific spatial and/or temporal expression patterns in vivo. These challenges require the development of alternative CDS cloning technologies. In this study, we found that the genomic intron-containing gene coding sequences (gDNA) from Arabidopsis thaliana, Oryza sativa, Brassica napus, and Glycine max can be correctly transcribed and spliced into mRNA in Nicotiana benthamiana. In contrast, gDNAs from Triticum aestivum and Sorghum bicolor did not function correctly. In transient expression experiments, the target DNA sequence is driven by a constitutive promoter. Theoretically, a sufficient amount of mRNA can be extracted from the N. benthamiana leaves, making it conducive to the cloning of CDS target genes. Our data demonstrate that N. benthamiana can be used as an effective host for the cloning CDS of plant genes.

molecular biology↗