The role and mechanism of PDZ binding kinase in hypobaric and hypoxic acute lung injury.

Background: Acute lung injury (ALI) caused by hypobaric hypoxia (HH) is frequently observed in high-altitude areas, and it is one of the leading causes of death in high-altitude-related diseases due to its rapid onset and progression. However, the pathogenesis of HH-related ALI (HHALI) remains unclear, and effective treatment approaches are currently lacking. Methods: A new mouse model of HHALI developed by our laboratory was used as the study subject (Chinese patent No. ZL 2021 1 1517241 X). Real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the messenger RNA (mRNA) expression levels of PDZ-binding kinase (PBK), sirtuin 1 (SIRT1), and PTEN-induced kinase 1 (PINK1) in mouse lung tissue. Hematoxylin and eosin staining was used to observe the main types of damage and damaged cells in lung tissue, and the lung injury score was used for quantification. The wet-dry (W/D) ratio was used to measure lung water content. Enzyme-linked immunosorbent assay was used to detect changes in inflammatory factors and oxidative stress markers in the lungs. Western blotting verified the expression of various mitochondrial autophagy-related proteins. The 5,5',6,6'-tetrachloro-1,1',3,3'-tetraethylbenzimi-dazoylcarbocyanine iodide (JC-1) method was used determined the health status of mitochondria based on changes in mitochondrial membrane potential. Transmission electron microscopy was used to directly observe the morphology of mitochondria. Multicolor immunofluorescence was used to observe the levels of mitochondrial autophagy markers. Other signaling pathways and molecular mechanisms that may play a role in epithelial cells were analyzed via through RNA sequencing. Results: Low pressure and hypoxia caused pathological changes in mouse lung tissue, mainly ALI, leading to increased levels of inflammatory factors and intensified oxidative stress response in the lungs. Overexpression of PBK was found to alleviate HHALI, and activation of the p53 protein was shown to abrogate this therapeutic effect, while activation of SIRT1 protein reactivated this therapeutic effect. The therapeutic effect of PBK on HHALI is achieved via the activation of mitochondrial autophagy. Finally, RNA sequencing demonstrated that besides mitochondrial autophagy, PBK also exerts other functions in HHALI. Conclusions: Overexpression of PBK inhibits the expression of p53 and activates SIRT1-PINK1 axis mediated mitochondrial autophagy to alleviate HHALI.

Opportunities and challenges for deep learning in cell dynamics research.

The growth of artificial intelligence (AI) has led to an increase in the adoption of computer vision and deep learning (DL) techniques for the evaluation of microscopy images and movies. This adoption has not only addressed hurdles in quantitative analysis of dynamic cell biological processes but has also started to support advances in drug development, precision medicine, and genome-phenome mapping. We survey existing AI-based techniques and tools, as well as open-source datasets, with a specific focus on the computational tasks of segmentation, classification, and tracking of cellular and subcellular structures and dynamics. We summarise long-standing challenges in microscopy video analysis from a computational perspective and review emerging research frontiers and innovative applications for DL-guided automation in cell dynamics research.

RVE2, a new regulatory factor in jasmonic acid pathway, orchestrates resistance to Verticillium wilt.

Verticillium dahliae, one of the most destructive fungal pathogens of several crops, challenges the sustainability of cotton productivity worldwide because very few widely-cultivated Upland cotton varieties are resistant to Verticillium wilt (VW). Here, we report that REVEILLE2 (RVE2), the Myb-like transcription factor, confers the novel function in resistance to VW by regulating the jasmonic acid (JA) pathway in cotton. RVE2 expression was essentially required for the activation of JA-mediated disease-resistance response. RVE2 physically interacted with TPL/TPRs and disturbed JAZ proteins to recruit TPL and TPR1 in NINJA-dependent manner, which regulated JA response by relieving inhibited-MYC2 activity. The MYC2 then bound to RVE2 promoter for the activation of its transcription, forming feedback loop. Interestingly, a unique truncated RVE2 widely existing in D-subgenome (GhRVE2D) of natural Upland cotton represses the ability of the MYC2 to activate GhRVE2A promoter but not GausRVE2 or GbRVE2. The result could partially explain why Gossypium barbadense popularly shows higher resistance than Gossypium hirsutum. Furthermore, disturbing the JA-signalling pathway resulted into the loss of RVE2-mediated disease-resistance in various plants (Arabidopsis, tobacco and cotton). RVE2 overexpression significantly enhanced the resistance to VW. Collectively, we conclude that RVE2, a new regulatory factor, plays a pivotal role in fine-tuning JA-signalling, which would improve our understanding the mechanisms underlying the resistance to VW.

CAVIN2/SDPR Functioned as a Tumor Suppressor in Lung Adenocarcinoma from Systematic Analysis of Caveolae-Related Genes and Experimental Validation.

Background: Caveolae-Related Genes include caveolins and cavins, which are the main component of the fossa and, play important roles in a variety of physiological and pathological processes. Although increasing evidence indicated that caveolins (CAVs) and cavins (CAVINs) are involved in carcinogenesis and progression, their clinical significance and biological function in lung cancer are still limited. Methods: We investigated the expression of CAVs and CAVINs at transcriptional levels using Oncomine and Gene Expression Profiling Interactive Analysis. The protein and mRNA expression levels of CAVs and CAVINs were determined by the human protein atlas website and our surgically resected samples, respectively. The clinical value of prognostic prediction based on the expression of CAVs and CAVINs was also assessed. cBioPortal, GeneMANIA and STRING were used to analyze the molecular characteristics of CAVs and CAVINs in lung adenocarcinoma (LUAD) comprehensively. Finally, we investigated the effect of CAVIN2/SDPR (serum deprivation protein response) on LUAD cells with biological experiments in vitro. Results: The expression of CAV1/2 and CAVIN1/2/3 were significantly downregulated in LUAD and lung squamous cell carcinoma (LUSC). The patients with high expression of CAV1, CAV2, CAV3, CAVIN1 and CAVIN2/SDPR were tightly correlated with a better prognosis in LUAD, while no statistical significances in LUSC. Further, our results found that CAVIN2/SDPR can be identified as a prognostic biomarker independent of other CAVINs in patients with LUAD. Mechanically, the overexpression of CAVIN2/SDPR inhibited cell proliferation and migration owing to the cell apoptosis induction and cell cycle arrest at S phase in LUAD cells. Conclusions: CAVIN2/SDPR functioned as a tumor suppressor, and was able to serve as prognostic biomarkers in precision medicine of LUAD. Mechanically, overexpression of CAVIN2/SDPR inhibited cell proliferation by inducing cell apoptosis and S phase arrest in LUAD cells.

PAX5-miR-142 feedback loop promotes breast cancer proliferation by regulating DNMT1 and ZEB1.

BACKGROUND: Breast cancer is one of the most common malignancies occurred in female around the globe. Recent studies have revealed the crucial characters of miRNA and genes, as well as the essential roles of epigenetic regulation in breast cancer initiation and progression. In our previous study, miR-142-3p was identified as a tumor suppressor and led to G2/M arrest through targeting CDC25C. However, the specific mechanism is still uncertain. METHODS: We identified PAX5 as the upstream regulator of miR-142-5p/3p through ALGGEN website and verified by series of assays in vitro and in vivo. The expression of PAX5 in breast cancer was detected by qRT-PCR and western blot. Besides, bioinformatics analysis and BSP sequencing were performed to analyze the methylation of PAX5 promoter region. Finally, the binding sites of miR-142 on DNMT1 and ZEB1 were predicted by JASPAR, and proved by luciferase reporter assay, ChIP analysis and co-IP. RESULTS: PAX5 functioned as a tumor suppressor by positive regulation of miR-142-5p/3p both in vitro and in vivo. The expression of PAX5 was regulated by the methylation of its promoter region induced by DNMT1 and ZEB1. In addition, miR-142-5p/3p could regulate the expression of DNMT1 and ZEB1 through binding with their 3'UTR region, respectively. CONCLUSION: In summary, PAX5-miR-142-DNMT1/ZEB1 constructed a negative feedback loop to regulate the progression of breast cancer, which provided emerging strategies for breast cancer therapy.

Characterization of cuproptosis-related lncRNA landscape for predicting the prognosis and aiding immunotherapy in lung adenocarcinoma patients.

Cuproptosis is a newly discovered mechanism of regulated cell death, which serves as a novel target for cancer therapy. Long non-coding RNAs (lncRNAs) play an important role in the initiation and progression of cancer cells; however, the relationship between cuproptosis and lncRNAs in tumorigenesis and cancer treatment has not been well established in lung adenocarcinoma (LUAD). Thus, it is important to clarify and characterize the cuproptosis-related lncRNA landscape in LUAD. In this study, cuproptosis-related lncRNAs was screened by Pearson correlation analysis. Then, univariate, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression were conducted to identify 6 cuproptosis-related lncRNAs (AC090541.1, AC009226.1, NIFK-AS1, AC027097.2, AC026355.2, and AC106028.2) which were used to construct a cuproptosis-related lncRNA signature (CRLS). Multi-dimensional assessments including Kaplan-Meier analysis, receiver operating characteristics (ROC) curves, and principal component analysis (PCA) verified that the CRLS could reliably predict the prognosis and survival of LUAD patients. We further compared the immune cell infiltration, somatic mutation landscape, and functional enrichment pathways between the high and low CRLS groups. Patients with low CRLS scores had prolonged survival and were sensitive to immunotherapy, whereas patients with high CRLS scores might benefit better from chemotherapy. We further analyzed the individualized immunotherapeutic strategies and the candidate compounds for the potential clinical treatment. Moreover, the expression level of these 6 lncRNAs was examined experimentally in vitro by using quantitative real-time polymerase chain reaction (RT-qPCR). Additionally, one of the significantly differentially expressed lncRNAs, NIFK-AS1, was confirmed to suppress the proliferation and migration of LUAD by Cell Counting Kit-8 Assays (CCK-8), wound healing assay, and colony formation assays. Taken together, we established a CRLS that might be a promising tool for predicting the prognosis, guiding individualized treatment, and serving as a promising therapeutic target for patients with LUAD.

Deep learning techniques and mathematical modeling allow 3D analysis of mitotic spindle dynamics.

Time-lapse microscopy movies have transformed the study of subcellular dynamics. However, manual analysis of movies can introduce bias and variability, obscuring important insights. While automation can overcome such limitations, spatial and temporal discontinuities in time-lapse movies render methods such as 3D object segmentation and tracking difficult. Here, we present SpinX, a framework for reconstructing gaps between successive image frames by combining deep learning and mathematical object modeling. By incorporating expert feedback through selective annotations, SpinX identifies subcellular structures, despite confounding neighbor-cell information, non-uniform illumination, and variable fluorophore marker intensities. The automation and continuity introduced here allows the precise 3D tracking and analysis of spindle movements with respect to the cell cortex for the first time. We demonstrate the utility of SpinX using distinct spindle markers, cell lines, microscopes, and drug treatments. In summary, SpinX provides an exciting opportunity to study spindle dynamics in a sophisticated way, creating a framework for step changes in studies using time-lapse microscopy.

CMTM7 inhibits breast cancer progression by regulating Wnt/ß-catenin signaling.

BACKGROUND: Breast cancer is the major cause of death in females globally. Chemokine-like factor like MARVEL transmembrane domain containing 7 (CMTM7) is reported as a tumor suppressor and is involved in epidermal growth factor receptor degradation and PI3K/AKT signaling in previous studies. However, other molecular mechanisms of CMTM7 remain unclear. METHODS: The expression level of CMTM7 in breast cancer cells and tissues was detected by qRT-PCR and western blot, and the methylation of CMTM7 promoter was detected by BSP sequencing. The effect of CMTM7 was verified both in vitro and in vivo, including MTT, colony formation, EdU assay, transwell assay and wound healing assay. The interaction between CMTM7 and CTNNA1 was investigated by co-IP assay. The regulation of miR-182-5p on CMTM7 and TCF3 on miR-182-5p was detected by luciferase reporter assay and ChIP analysis. RESULTS: This study detected the hypermethylation levels of the CMTM7 promoter region in breast cancer tissues and cell lines. CMTM7 was performed as a tumor suppressor both in vitro and in vivo. Furthermore, CMTM7 was a direct miR-182-5p target. Besides, we found that CMTM7 could interact with Catenin Alpha 1 (CTNNA1) and regulate Wnt/ß-catenin signaling. Finally, transcription factor 3 (TCF3) can regulate miR-182-5p. We identified a feedback loop with the composition of miR-182-5p, CMTM7, CTNNA1, CTNNB1 (ß-catenin), and TCF3, which play essential roles in breast cancer progression. CONCLUSION: These findings reveal the emerging character of CMTM7 in Wnt/ß-catenin signaling and bring new sights of gene interaction. CMTM7 and other elements in the feedback loop may serve as emerging targets for breast cancer therapy.

TIP41L, a putative candidate gene conferring both seed size and boll weight, was fine-mapped in an introgression line of Gossypium hirsutum-Gossypium arboreum.

QTLs for yield-related traits in tetraploid cotton have been widely mapped, but QTLs introduced from diploid species into tetraploid cotton background remain uninvolved. Here, a stable introgression line with the traits of small boll and seed on Chr. A12, IL197 derived from Gossypium hirsutum (2n = AADD = 52) × Gossypium arboreum (2n = AA = 26), was employed to construct the F2 and F3 secondary populations for fine-mapping QTLs of yield-related traits. QTL analysis showed eight QTLs were detected for three traits, boll weight (BW), seed index (SI, one-hundred-seed weight in g), and lint percentage, with 3.94-28.13 % of the phenotypic variance explained. Of them, a stable major QTL, q(BW + SI)-A12-1 controlling both BW and SI and covering the shortest region in Chr. A12, was further narrowed into a 60.09 kb-interval through substitution mapping. Finally, five candidate genes were detected in the interval. The qRT-PCR analysis revealed only TIP41-like family protein (TIP41L) kept up-regulated expression and significantly lower in TM-1 than that in IL197 from -1 DPA to 15 DPA during cotton boll rapid developmental stage. Therefore, TIP41L gene is speculated as the most likely candidate gene. Comparative analysis with the other four allotetraploid species showed TIP41L gene was probably diverged after the formation of allotetraploid cotton, which may be selected and swept during domestication of modern upland cotton because small boll and seed are detrimental to fibre yield of cotton. This research would lay a solid foundation for further elucidating the molecular mechanism of cotton boll and seed development.

HS3ST3A1 and CAPN8 Serve as Immune-Related Biomarkers for Predicting the Prognosis in Thyroid Cancer.

Background: Thyroid cancer (TC) tends to be a common malignancy worldwide and results in various outcomes due to its different subtypes. The tumor microenvironment (TME) was demonstrated to play crucial roles in various malignancies, including thyroid cancer. This study combined the ESTIMATE and CIBERSORT algorithms, identified four TME-related genes, and evaluated their correlation with clinical characteristics. These findings revealed the malignant performance of TME in TC, and the TME-related DEGs might serve as prognostic biomarkers, which can be utilized for the prediction of immunotherapy effects in patients with TC. Methods: The clinical and gene expression profiles of TC patients were collected from the TCGA dataset. The ESTIMATE algorithm was utilized to estimate stromal and immune scores and predict the level of stromal and immune cell infiltration. The differential expressed genes related to TME were filtered by the "limma" package in R, and the PPI network was constructed by a string website. KEGG pathway and GO analyses were performed to investigate the biological progression and molecular functions of TME-related DEGs. Then, univariate Cox regression analysis was employed to screen four genes correlated with clinical characteristics. GSEA was conducted to assess their roles in the TME of TC. To further investigate the association between TME-related genes and tumor-infiltrating immune cells (TIICs), the CIBERSORT algorithm was performed. Finally, the malignancy behaviors of the two genes were verified by RT-qPCR, IHC, MTT, colony formation, and transwell assays. Results: Four TME-related DEGs, LRRN4CL, HS3ST3A1, PCOLCE2, and CAPN8, were identified and were significantly predictive of poor overall survival. KEGG and GO pathway analysis established that the TME-related DEGs were involved in immune responses and pathways in cancer. Furthermore, the malignancy behaviors of HS3ST3A1 and CAPN8 were verified by cellular functional experiments. These results revealed that the TME-related genes HS3ST3A1 and CAPN8 were able to serve as predictors of prognosis in patients with TC. Conclusion: HS3ST3A1 and CAPN8 may serve as valuable prognostic biomarkers and TME indicators, which can be utilized for the prediction of immunotherapy effects and provide novel treatment strategies for patients with TC.

Genome-Wide Introgression and Quantitative Trait Locus Mapping Reveals the Potential of Asian Cotton (Gossypium arboreum) in Improving Upland Cotton (Gossypium hirsutum).

Gossypium arboreum (2n=2x=26, A2), the putative progenitor of the At-subgenome of Gossypium hirsutum (2n=4x=52, AD), is a repository of genes of interesting that have been eliminated during evolution/domestication of G. hirsutum. However, its valuable genes remain untapped so far due to species isolation. Here, using a synthetic amphiploid (AADDA2A2) previously reported, we developed a set of 289 G. arboreum chromosome segment introgression lines (ILs) in G. hirsutum by expanding the backcrossing population and through precise marker-assisted selection (MAS) although complex chromosomal structural variations existed between parents which severely hindered introgression. Our results showed the total coverage length of introgressed segments was 1,116.29 Mb, representing 78.48% of the At-subgenome in the G. hirsutum background, with an average segment-length of 8.69 Mb. A total of 81 co- quantitative trait loci (QTLs) for yield and fiber quality were identified by both the RSTEP-ADD-based QTL mapping and the genome-wide association study (GWAS) analysis, with 1.01-24.78% of the phenotypic variance explained. Most QTLs for boll traits showed negative additive effects, but G. arboreum still has the potential to improve boll-number traits in G. hirsutum. Most QTLs for fiber quality showed negative additive effects, implying these QTLs were domesticated in G. hirsutum compared with G. arboreum and, a small quantity of fiber quality QTLs showing positive additive effects, conversely; however, indicates that G. arboreum has the underlying genes of enhancing fiber quality of G. hirsutum. This study provides new insights into the breeding genetic potential of G. arboreum, lays the foundation for further mining favorable genes of interest, and provides guidance for inter-ploidy gene transference from relatives into cultivated crops.

Fine-mapping and candidate gene analysis of qFS-Chr. D02, a QTL for fibre strength introgressed from a semi-wild cotton into Gossypium hirsutum.

Fibre strength (FS) is an important quality attribute in the modern textile industry, which is genetically controlled by quantitative trait loci (QTLs). Fine-mapping stable QTLs for FS to identify candidate genes would be valuable for uncovering the genetic basis of fibre quality traits in cotton. Here, a single segment introgression line, IL-D2-2, from the cross of (TM-1×TX-1046) reported in our previous studies, was found to have significantly improved FS compared with the recurrent parent TM-1. To fine-map the QTLs of the FS, we further crossed IL-D2-2 with its recurrent parent TM-1 to produce F2 and F2:3 populations. QTL analysis and substitution mapping showed qFS-Chr. D02 was anchored into a 550.66 kb-interval between two markers, INTR1027 and JESPR-231. This interval contained 67 genes, among which 27 genes related to cell-wall synthesis were selected to conduct qRT-PCR. The results revealed seven genes were expressed significantly differently during the fibre secondary-wall-thickening stage (10-25 days post-anthesis), three being upregulated and four downregulated in IL-D2-2. Both GH_D02G2269 (UDP-glucosyl transferase 84B1) and GH_D02G2289 (unknown function (DUF869)) with nonsynonymous SNPs in IL-D2-2 had significantly downregulated expression, suggesting they were candidates for qFS-Chr. D02. This research provides information about marker-assisted selection for cotton fibre strength improvement.