Symbiosis between Dendrobium catenatum protocorms and Serendipita indica involves the plant hypoxia response pathway.

Mycorrhizae are ubiquitous symbioses established between fungi and plant roots. Orchids, in particular, require compatible mycorrhizal fungi for seed germination and protocorm development. Unlike arbuscular mycorrhizal fungi, which have wide host ranges, orchid mycorrhizal fungi are often highly specific to their host orchids. However, the molecular mechanism of orchid mycorrhizal symbiosis is largely unknown compared to that of arbuscular mycorrhizal and rhizobial symbiosis. Here, we report that an endophytic Sebacinales fungus, Serendipita indica, promotes seed germination and the development of protocorms into plantlets in several epiphytic Epidendroideae orchid species (6 species in 2 genera), including Dendrobium catenatum, a critically endangered orchid with high medicinal value. Although plant-pathogen interaction and high meristematic activity can induce the hypoxic response in plants, it has been unclear whether interactions with beneficial fungi, especially mycorrhizal ones, also involve the hypoxic response. By studying the symbiotic relationship between D. catenatum and S. indica, we determined that hypoxia-responsive genes, such as those encoding alcohol dehydrogenase (ADH), are highly induced in symbiotic D. catenatum protocorms. In situ hybridization assay indicated that the ADH gene is predominantly expressed in the basal mycorrhizal region of symbiotic protocorms. Additionally, the ADH inhibitors puerarin and 4-methylpyrazole both decreased S. indica colonization in D. catenatum protocorms. Thus, our study reveals that S. indica is widely compatible with orchids and that ADH and its related hypoxia-responsive pathway are involved in establishing successful symbiotic relationships in germinating orchids.

Valproic acid exposure decreases neurogenic potential of outer radial glia in human brain organoids.

Valproic acid (VPA) exposure during pregnancy leads to a higher risk of autism spectrum disorder (ASD) susceptibility in offspring. Human dorsal forebrain organoids were used to recapitulate course of cortical neurogenesis in the developing human brain. Combining morphological characterization with massive parallel RNA sequencing (RNA-seq) on organoids to analyze the pathogenic effects caused by VPA exposure and critical signaling pathway. We found that VPA exposure in organoids caused a reduction in the size and impairment in the proliferation and expansion of neural progenitor cells (NPCs) in a dose-dependent manner. VPA exposure typically decreased the production of outer radial glia-like cells (oRGs), a subtype of NPCs contributing to mammalian neocortical expansion and delayed their fate toward upper-layer neurons. Transcriptomics analysis revealed that VPA exposure influenced ASD risk gene expression in organoids, which markedly overlapped with irregulated genes in brains or organoids originating from ASD patients. We also identified that VPA-mediated Wnt/ß-catenin signaling pathway activation is essential for sustaining cortical neurogenesis and oRGs output. Taken together, our study establishes the use of dorsal forebrain organoids as an effective platform for modeling VPA-induced teratogenic pathways involved in the cortical neurogenesis and oRGs output, which might contribute to ASD pathogenesis in the developing brain.

Transcriptome of pituitary function changes in rat model of high altitude cerebral edema.

High altitude cerebral edema (HACE) is a serious subtype of acute mountain sickness (AMS). Studies have suggested that increased expression of corticotropin releasing hormone receptor 1 (CRFR1) in pituitary is related to the development of HACE, but no study has revealed the molecular landscape of pituitary function changes in this process. Rat model of HACE was established by simulating the high-altitude hypobaric hypoxia environment. Then RNA-sequencing was performed of rat pituitary gland (PG) in HACE and non-HACE groups. The function annotations, enrichment analysis, protein-protein interaction (PPI) network, chromosome location and drug repositioning of differentially expressed genes (DEGs) were explored based on the transcriptomic data. And we found pituitary secretion function was disordered in HACE, which was partly due to activated inflammation and oxidative stress. In addition, we identified potential biomarkers for early recognition of pituitary dysfunction and potential protective drugs for pituitary function in HACE.

MSPJ: Discovering potential biomarkers in small gene expression datasets via ensemble learning.

In transcriptomics, differentially expressed genes (DEGs) provide fine-grained phenotypic resolution for comparisons between groups and insights into molecular mechanisms underlying the pathogenesis of complex diseases or phenotypes. The robust detection of DEGs from large datasets is well-established. However, owing to various limitations (e.g., the low availability of samples for some diseases or limited research funding), small sample size is frequently used in experiments. Therefore, methods to screen reliable and stable features are urgently needed for analyses with limited sample size. In this study, MSPJ, a new machine learning approach for identifying DEGs was proposed to mitigate the reduced power and improve the stability of DEG identification in small gene expression datasets. This ensemble learning-based method consists of three algorithms: an improved multiple random sampling with meta-analysis, SVM-RFE (support vector machines-recursive feature elimination), and permutation test. MSPJ was compared with ten classical methods by 94 simulated datasets and large-scale benchmarking with 165 real datasets. The results showed that, among these methods MSPJ had the best performance in most small gene expression datasets, especially those with sample size below 30. In summary, the MSPJ method enables effective feature selection for robust DEG identification in small transcriptome datasets and is expected to expand research on the molecular mechanisms underlying complex diseases or phenotypes.

Drp1-Mediated Mitochondrial Metabolic Dysfunction Inhibits the Tumor Growth of Pituitary Adenomas.

Metabolic changes have been suggested to be a hallmark of tumors and are closely associated with tumorigenesis. In a previous study, we demonstrated the role of lactate dehydrogenase in regulating abnormal glucose metabolism in pituitary adenomas (PA). As the key organelle of oxidative phosphorylation (OXPHOS), mitochondria play a vital role in the energy supply for tumor cells. However, few attempts have been made to elucidate mitochondrial metabolic homeostasis in PA. Dynamin-related protein 1 (Drp1) is a member of the dynamin superfamily of GTPases, which mediates mitochondrial fission. This study is aimed at investigating whether Drp1 affects the progression of PA through abnormal mitochondrial metabolism. We analyzed the expression of dynamin-related protein 1 (Drp1) in 20 surgical PA samples. The effects of Drp1 on PA growth were assessed in vitro and in xenograft models. We found an upregulation of Drp1 in PA samples with a low proliferation index. Knockdown or inhibition of Drp1 enhanced the proliferation of PA cell lines in vitro, while overexpression of Drp1 could reversed such effects. Mechanistically, overexpressed Drp1 damaged mitochondria by overproduction of reactive oxygen species (ROS), which induced mitochondrial OXPHOS inhibition and decline of ATP production. The energy deficiency inhibited proliferation of PA cells. In addition, overexpressed Drp1 promoted cytochrome c release from damaged mitochondria into the cytoplasm and then activated the downstream caspase apoptotic cascade reaction, which induced apoptosis of PA cells. Moreover, the decreased ATP production induced by Drp1 overexpressing activated the AMPK cellular energy stress sensor and enhanced autophagy through the AMPK-ULK1 pathway, which might play a protective role in PA growth. Furthermore, overexpression of Drp1 repressed PA growth in vivo. Our data indicates that Drp1-mediated mitochondrial metabolic dysfunction inhibits PA growth by affecting cell proliferation, apoptosis, and autophagy. Selectively targeting mitochondrial metabolic homeostasis stands out as a promising antineoplastic strategy for PA therapy.

Female mice lacking ERß display excitatory/inhibitory synaptic imbalance to drive the pathogenesis of temporal lobe epilepsy.

Epilepsy is a highly prevalent and drug-refractory neurological disorder characterized by spontaneous recurrent seizures. Estrogen is identified to be proconvulsant and lowers the seizure threshold of female epilepsy. Estrogen receptor ß (ERß) has been proposed to mediate neuroprotection in epilepsy, although the underlying mechanism remains unknown. Rationale: In this study, we investigated the role of ERß in the epileptogenesis of female temporal lobe epilepsy (TLE). Methods: Immunohistochemistry, immunofluorescence, western blots, Golgi staining, 1H MRS and whole-cell patch-clamp were used to evaluate ERß expression, pathological changes, and synaptic excitation /inhibition (E/I) balance in female TLE patients and ovariectomized (OVX) chronic epileptic mice. Electroencephalogram (EEG) recordings were recorded to evaluate the epileptic susceptibility in OVX WT and ERß-/- mice. And high-throughput RNA-sequence was performed to identify differential expression genes (DEGs) which can elucidate the potential mechanism of ERß regulating the seizure susceptibility. Results: ERß expression was decreased in the brains of female TLE patients and OVX chronic epileptic mice. ERß deletion enhanced seizure susceptibility and exacerbated the imbalance of synaptic E/I in hippocampal CA1 area of OVX epileptic mice. In line with these observations, RNA-sequence data further identified glutamine ligase (GLUL) as the target of ERß involved in regulating synaptic E/I in CA1. Furthermore, ERß agonist WAY-200070 markedly suppressed epileptic phenotypes and normalized GLUL expression in CA1 region of kainic acid (KA) induced OVX chronic epileptic model. Conclusions: Our data provide novel insight into the pathogenesis of female TLE, and indicate ERß provides a new therapeutic strategy for female TLE patients.

Systematic Identification of Housekeeping Genes Possibly Used as References in Caenorhabditis elegans by Large-Scale Data Integration.

For accurate gene expression quantification, normalization of gene expression data against reliable reference genes is required. It is known that the expression levels of commonly used reference genes vary considerably under different experimental conditions, and therefore, their use for data normalization is limited. In this study, an unbiased identification of reference genes in Caenorhabditis elegans was performed based on 145 microarray datasets (2296 gene array samples) covering different developmental stages, different tissues, drug treatments, lifestyle, and various stresses. As a result, thirteen housekeeping genes (rps-23, rps-26, rps-27, rps-16, rps-2, rps-4, rps-17, rpl-24.1, rpl-27, rpl-33, rpl-36, rpl-35, and rpl-15) with enhanced stability were comprehensively identified by using six popular normalization algorithms and RankAggreg method. Functional enrichment analysis revealed that these genes were significantly overrepresented in GO terms or KEGG pathways related to ribosomes. Validation analysis using recently published datasets revealed that the expressions of newly identified candidate reference genes were more stable than the commonly used reference genes. Based on the results, we recommended using rpl-33 and rps-26 as the optimal reference genes for microarray and rps-2 and rps-4 for RNA-sequencing data validation. More importantly, the most stable rps-23 should be a promising reference gene for both data types. This study, for the first time, successfully displays a large-scale microarray data driven genome-wide identification of stable reference genes for normalizing gene expression data and provides a potential guideline on the selection of universal internal reference genes in C. elegans, for quantitative gene expression analysis.

Identification of Transcriptional Metabolic Dysregulation in Subtypes of Pituitary Adenoma by Integrated Bioinformatics Analysis.

BACKGROUND: Pituitary adenoma (PA) is a prevalent intracranial tumor. Metabolites differ between pituitary tumor and healthy tissues or among different tumor subtypes. However, the transcriptional changes in metabolic enzymes, which are usually seemed as targets for metabolic therapy, remain unidentified. METHODS: Using microarray data for 160 samples from the Gene Expression Omnibus database, across the four most common tumor subtypes, we present the integrated identification of differentially expressed genes (DEGs) between tumors and controls. RESULTS: Subtype-specific DEGs revealed 1081 prolactin tumor-specific DEGs, 437 nonfunctioning tumor-specific DEGs, and 217 common DEGs among the four subtypes. Functional enrichment showed that a lot of biological functions related to metabolism had changed. Twenty-one prolactin and twenty-three nonfunctioning tumor-specific metabolic-related DEGs are mainly involved in fatty acid and nucleotide metabolism, redox reaction, and gluconeogenesis. Eighteen metabolic-related DEGs enriched in the metabolism of xenobiotics by the cytochrome P450 pathway, sulfur metabolism, retinoid metabolism, and glucose homeostasis were abnormal in all subtypes of PA. CONCLUSION: Based on a comprehensive bioinformatics analysis of the available PA-related transcriptomics data, we identified specific DEGs related to metabolism, and some of them might be new attractive therapeutic targets. Especially, PDK4 and PCK1 might be new attractive biomarkers and therapeutic targets.