Elevated temperature alters bacterial community from mutualism to antagonism with Skeletonema costatum: insights into the role of a novel species, Tamlana sp. MS1.

Skeletonema costatum, a cosmopolitan diatom primarily inhabiting coastal ecosystems, exhibits a typically close yet variable relationship with heterotrophic bacteria. The increasing temperature of surface seawater is expected to substantially affect the viability and ecological dynamics of S. costatum, potentially altering its relationship with bacteria. However, it remains unclear to what extent the elevated temperature could change these relationships. Here, the relationship between axenic S. costatum and natural seawater bacteria underwent a dramatic shift from mutualism to antagonism as the co-culture temperature increased from 20°C to 25°C. The co-occurrence network indicated significantly increased complexity of interaction between S. costatum and bacteria community after temperature elevation, especially with Flavobacteriaceae, implying their potential role in eliminating S. costatum under higher temperatures. Additionally, a Flavobacteriaceae isolate, namely MS1 identified as Tamlana genus, was isolated from the co-culture system at 25°C. MS1 had a remarkable ability to eliminate S. costatum, with the mortality rate at 25°C steadily rising from 30.2% at 48 h to 92.4% at 120 h. However, it promoted algal growth to some extent at 20°C. These results demonstrated that increased temperature promotes MS1 shifts from mutualism to antagonism with S. costatum. According to the comparative genomics analysis, changes in the lifestyle of MS1 were attributed to the increased gliding motility and attachment of MS1 under elevated temperature, enabling it to exert an algicidal effect through direct contact with alga. This investigation provided an advanced understanding of interactions between phytoplankton and bacteria in future warming oceanic ecosystems. IMPORTANCE: Ocean warming profoundly influences the growth and metabolism of phytoplankton and bacteria, thereby significantly reshaping their interactions. Previous studies have shown that warming can change bacterial lifestyle from mutualism to antagonism with phytoplankton, but the underlying mechanism remains unclear. In this study, we found that high temperature promotes Tamlana sp. MS1 adhesion to Skeletonema costatum, leading to algal lysis through direct contact, demonstrating a transition in lifestyle from mutualism to antagonism with increasing temperature. Furthermore, the gliding motility of MS1 appears to be pivotal in mediating the transition of its lifestyle. These findings not only advance our understanding of the phytoplankton-bacteria relationship under ocean warming but also offer valuable insights for predicting the impact of warming on phytoplankton carbon sequestration.

Methyl-CpG-Binding Domain Protein 3 Promotes Seizures by Recruiting Methyltransferase DNMT1 to Enhance TREM2 Methylation.

Epilepsy represents a hazardous neurological disorder, underpinned by a pathophysiological process that is yet to be fully understood. Here, we aimed to elucidate the effect of methyl-CpG-binding domain protein 3 (MBD3) on hippocampal neuronal damage in epileptic mice by targeting the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway. The expression of MBD3 was determined by Western blot in a hippocampal neuronal culture (HNC) epileptic model established using the low Mg2+ECF culture method. The interaction between MBD3 and DNA methyltransferase 1 (DNMT1) was determined via co-immunoprecipitation and mass spectrometry analysis. Bisulfite modification and sequencing was performed to evaluate the degree of methylation of triggering receptor expressed on myeloid cells 2 (TREM2). The viability and apoptosis of hippocampal neurons were detected by CCK-8 and TUNEL assays, respectively. Finally, the effect of MBD3 was verified in vivo. MBD3 was highly expressed in the HNC model of epilepsy, with its interaction with DNMT1 found to promote the hypermethylation of TREM2 at site cg25748868. Additionally, decreased TREM2 and inhibited PI3K/Akt pathway was observed in the HNC epileptic model. Simultaneous inhibition of MBD3 and DNMT1 decreased the methylation level at cg25748868, up-regulated TREM2 expression, and activated the PI3K/Akt pathway, thereby arresting neuronal damage. Inhibition of MBD3 reduced the level of epileptic seizures, down-regulated cg25748868 methylation, activated TREM2-mediated signaling pathways, and alleviated hippocampal neuronal damage in the acute seizure mouse models. The present study unveiled that MBD3 and DNMT1 synergistically enhanced hypermethylation of cg25748868 in TREM2, and promoted the onset of epilepsy via inhibition of the PI3K/Akt pathway.

Molecular and Clinical Characterization of UBE2S in Glioma as a Biomarker for Poor Prognosis and Resistance to Chemo-Radiotherapy.

Glioblastoma is the most common and lethal brain cancer globally. Clinically, this cancer has heterogenous molecular and clinical characteristics. Studies have shown that UBE2S is highly expressed in many cancers. But its expression profile in glioma, and the correlation with clinical outcomes is unknown. RNA sequencing data of glioma samples was downloaded from the Chinese Glioma Genome Atlas and The Cancer Genome Atlas. A total of 114 cases of glioma tissue samples (WHO grades II-IV) were used to conduct protein expression assays. The molecular and biological characteristics of UBE2S, and its prognostic value were analyzed. The results showed that high UBE2S expression was associated with a higher grade of glioma and PTEN mutations. In addition, UBE2S affected the degree of malignancy of glioma and the development of chemo-radiotherapy resistance. It was also found to be an independent predictor of worse survival of LGG patients. Furthermore, we identified five UBE2S ubiquitination sites and found that UBE2S was associated with Akt phosphorylation in malignant glioblastoma. The results also revealed that UBE2S expression was negatively correlated with 1p19q loss and IDH1 mutation; positively correlated with epidermal growth factor receptor amplification and PTEN mutation. This study demonstrates that UBE2S expression strongly correlates with glioma malignancy and resistance to chemo-radiotherapy. It is also a crucial biomarker of poor prognosis.

Expression Profile Analysis Identifies a Novel Seven Immune-Related Gene Signature to Improve Prognosis Prediction of Glioblastoma.

Glioblastoma multiform (GBM) is a malignant central nervous system cancer with dismal prognosis despite conventional therapies. Scientists have great interest in using immunotherapy for treating GBM because it has shown remarkable potential in many solid tumors, including melanoma, non-small cell lung cancer, and renal cell carcinoma. The gene expression patterns, clinical data of GBM individuals from the Cancer Genome Atlas database (TCGA), and immune-related genes (IRGs) from ImmPort were used to identify differentially expressed IRGs through the Wilcoxon rank-sum test. The association between each IRG and overall survival (OS) of patients was investigated by the univariate Cox regression analysis. LASSO Cox regression assessment was conducted to explore the prognostic potential of the IRGs of GBM and construct a risk score formula. A Kaplan-Meier curve was created to estimate the prognostic role of IRGs. The efficiency of the model was examined according to the area under the receiver operating characteristic (ROC) curve. The TCGA internal dataset and two GEO external datasets were used for model verification. We evaluated IRG expression in GBM and generated a risk model to estimate the prognosis of GBM individuals with seven optimal prognostic expressed IRGs. A landscape of 22 types of tumor-infiltrating immune cells (TIICs) in glioblastoma was identified, and we investigated the link between the seven IRGs and the immune checkpoints. Furthermore, there was a correlation between the IRGs and the infiltration level in GBM. Our data suggested that the seven IRGs identified in this study are not only significant prognostic predictors in GBM patients but can also be utilized to investigate the developmental mechanisms of GBM and in the design of personalized treatments for them.

Assessment of kitchen emissions using a backpropagation neural network model based on urinary hydroxy polycyclic aromatic hydrocarbons.

Kitchen emissions are mixed indoor air pollutants with adverse health effects, but the large-scale assessment is limited by costly equipment and survey methods. This study aimed to discuss the application of backpropagation (BP) neural network models in the assessment of kitchen emissions based on the exposure marker. A total of 3686 participants were recruited for the kitchen survey, and their sleep quality was measured by the Pittsburgh sleep quality index (PSQI). After excluding the confounders, 365 participants were selected to assess their urinary hydroxy polycyclic aromatic hydrocarbons (OH-PAHs) concentrations by ultra-high-performance liquid chromatography/tandem mass spectrometry. Two BP neural network models were then set up using the survey and detection data from the 365 participants and used to predict the total urinary OH-PAHs concentrations of all participants. The total urinary OH-PAHs and 1-hydroxy-naphthalene (1-OHNap) concentrations were significantly higher among the 365 participants with poor sleep quality (global PSQI score > 5; P < 0.05). Results from internal and external validation showed that our model has high credibility (model 2). Further, the participants with higher predicted total urinary OH-PAHs concentrations were associated with the global PSQI score of >5 (odds ratio (OR) = 1.284, 95% confidence interval (CI) = 1.082-1.525 for participants with predicted total urinary OH-PAHs concentrations of over 1.897 µg/mmol creatinine in model 1, and OR = 1.467, 95% CI = 1.240-1.735 for participants with predicted total urinary OH-PAHs concentrations of over 2.253 µg/mmol creatinine in model 2) after adjusting for the confounders. Findings suggest that the BP neural network model is suitable for assessing kitchen emissions, and the urinary OH-PAHs concentrations can be taken as the model outlay.