Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.ImportanceTo fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available

Unraveling the mechanisms of NK cell dysfunction in aging and Alzheimer’s disease: insights from GWAS and single-cell transcriptomics

BackgroundAging is an important factor in the development of Alzheimer’s disease (AD). The senescent cells can be recognized and removed by NK cells. However, NK cell function is gradually inactivated with age. Therefore, this study used senescence as an entry point to investigate how NK cells affect AD.MethodsThe study validated the correlation between cognition and aging through a prospective cohort of the National Health and Nutrition Examination Survey database. A cellular trajectory analysis of the aging population was performed using single-cell nuclear transcriptome sequencing data from patients with AD and different ages. The genome-wide association study (GWAS) cohort of AD patients was used as the outcome event, and the expression quantitative trait locus was used as an instrumental variable. Causal associations between genes and AD were analyzed by bidirectional Mendelian randomization (MR) and co-localization. Finally, clinical cohorts were constructed to validate the expression of key genes.ResultsA correlation between cognition and aging was demonstrated using 2,171 older adults over 60 years of age. Gene regulation analysis revealed that most of the highly active transcription factors were concentrated in the NK cell subpopulation of AD. NK cell trajectories were constructed for different age populations. MR and co-localization analyses revealed that CHD6 may be one of the factors influencing AD.ConclusionWe explored different levels of AD and aging from population cohorts, single-cell data, and GWAS cohorts and found that there may be some correlations of NK cells between aging and AD. It also provides some basis for potential causation

Nonparametric Interaction Selection

cancelled due to Covid 1

Machine learning and experimental validation identified autophagy signature in hepatic fibrosis

BackgroundThe molecular mechanisms of hepatic fibrosis (HF), closely related to autophagy, remain unclear. This study aimed to investigate autophagy characteristics in HF.MethodsGene expression profiles (GSE6764, GSE49541 and GSE84044) were downloaded, normalized, and merged. Autophagy-related differentially expressed genes (ARDEGs) were determined using the limma R package and the Wilcoxon rank sum test and then analyzed by GO, KEGG, GSEA and GSVA. The infiltration of immune cells, molecular subtypes and immune types of healthy control (HC) and HF were analyzed. Machine learning was carried out with two methods, by which, core genes were obtained. Models of liver fibrosis in vivo and in vitro were constructed to verify the expression of core genes and corresponding immune cells.ResultsA total of 69 ARDEGs were identified. Series functional cluster analysis showed that ARDEGs were significantly enriched in autophagy and immunity. Activated CD4 T cells, CD56bright natural killer cells, CD56dim natural killer cells, eosinophils, macrophages, mast cells, neutrophils, and type 17 T helper (Th17) cells showed significant differences in infiltration between HC and HF groups. Among ARDEGs, three core genes were identified, that were ATG5, RB1CC1, and PARK2. Considerable changes in the infiltration of immune cells were observed at different expression levels of the three core genes, among which the expression of RB1CC1 was significantly associated with the infiltration of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. In the mouse liver fibrosis experiment, ATG5, RB1CC1, and PARK2 were at higher levels in HF group than those in HC group. Compared with HC group, HF group showed low positive area in F4/80, IL-17 and CD56, indicating decreased expression of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. Meanwhile, knocking down RB1CC1 was found to inhibit the activation of hepatic stellate cells and alleviate liver fibrosis.ConclusionATG5, RB1CC1, and PARK2 are promising autophagy-related therapeutic biomarkers for HF. This is the first study to identify RB1CC1 in HF, which may promote the progression of liver fibrosis by regulating macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell

Right hepatectomy by the anterior method with liver hanging versus conventional approach for large hepatocellular carcinomas

Background: The aim was to compare short-term results of right hepatectomy using the anterior approach (AA) and liver hangingmanoeuvre with the conventional approach (CA) for large hepatocellular carcinoma (HCC). Methods: This was a retrospective review of 71 consecutive patients with HCC at least 5 cm in diameter who underwent curative right hepatectomy using either the AA with the liver hanging manoeuvre (33) or the CA (38) between January 2004 and December 2008. Clinical data, operative results and survival outcomes were analysed. Results: The groups had similar clinical, laboratory and pathological parameters. The AA group had larger tumours than the CA group (P = 0·039), but comparable grade and stage distribution. The operative results were similar except for an increased blood transfusion requirement with the conventional procedure (P = 0·001). The AA group had a lower recurrence rate (P = 0·003) and better disease-free survival (DFS) (P = 0·001) than theCA group, but overall survival rates were not significantly different (P = 0·091). Presence of tumour encapsulation, absence of tumour microvascular invasion and AA were predictive of DFS, whereas tumour stage was the only independent predictor of overall survival. Conclusion: The AA right hepatectomy with liver hanging manoeuvre for large HCC is associated with reduced blood transfusion requirement and lower recurrence rates in the short term

The preparation and properties of photocatalytic composites based on palygorskite/molybdenum disulfide

The pollution problem resulting from advancements in science and technology is increasingly severe, particularly concerning organic pollution. Photocatalytic technology is considered one of the most effective methods for treating organic pollution due to its cost-effectiveness, simplicity of operation, high efficiency, and versatility. In this study, palygorskite was purified and extracted using techniques such as ultrasonication, high-speed stirring, centrifugation, and others. Molybdenum disulfide (MoS2) was synthesized in situ on the palygorskite surface through hydrothermal synthesis, resulting in palygorskite/MoS2 nanocomposites. The structure and apparent morphology of the palygorskite/MoS2 composites were analyzed using characterization methods such as transmission electron microscopy, x-ray diffraction, Fourier transform infrared spectroscopy, and others. MoS2 interacted with the hydroxyl groups on the palygorskite surface through amino groups, leading to the dispersion of MoS2 nanosheets on the palygorskite surface, forming a unique nanoflower structure. To assess the photocatalytic degradation performance of palygorskite/MoS2 composites, Rhodamine B was employed as the target pollutant. Under conditions of a pH of 6, a reaction time of 170 min, and a solution concentration of 1500 mg/l, palygorskite/MoS2 composites achieved a Rhodamine B removal amount of 371.73 mg/g. Notably, these composites facilitated the degradation of Rhodamine B into intermediate chain-broken products. The findings of this study hold significant implications for the advancement of clay mineral-based photocatalytic composites and the effective removal of organic pollutants

Antiangiogenesis Efficacy of Ethanol Extract from Amomum tsaoko in Ovarian Cancer through Inducing ER Stress to Suppress p-STAT3/NF-kB/IL-6 and VEGF Loop

Natural plants are considered as a huge treasure for anticancer. Amomum tsaoko, a plant of Zingiberaceae, is used widely as a food and traditional medicine in East Asia. In previous studies, Amomum tsaoko has antitumor effect on liver cancer cells, but the mechanism is not clear. Here, we demonstrated that ethanol extract from Amomum tsaoko (At-EE) could inhibit ovarian cancer and decrease angiogenesis in vivo. At-EE did not influence vascular endothelial cells directly, but decreased IL-6 and VEGF secreted by ovarian cancer cells to inhibit angiogenesis through inhibition of p-STAT3 and NF-kB activation. In addition, we demonstrated that p-STAT3 and NF-kB could adjust each other and IL-6 and VEGF also mediate p-STAT3 and NF-kB too, which created a loop. In addition, At-EE interrupted p-STAT3/NF-kB/IL-6 and VEGF loop through induced ER stress. These results reveal that p-STAT3/NF-kB/IL-6 and VEGF is a cascade amplification loop in ovarian cancer for angiogenesis, and induced ER stress can interrupt it. Taken together, this work explored the anticancer activities of Amomum tsaoko, which could be a potential therapeutic candidate in the treatment of ovarian cancer

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is usually limited by sampling size. Sequence conservation-based methods are further confounded by structural constraints and multifunctionality of proteins. Here we present a method that can systematically identify and annotate functional residues of a given protein. We used a high-throughput functional profiling platform to identify essential residues. Coupling it with homologous-structure comparison, we were able to annotate multiple functions of proteins. We demonstrated the method with the PB1 protein of influenza A virus and identified novel functional residues in addition to its canonical function as an RNA-dependent RNA polymerase. Not limited to virology, this method is generally applicable to other proteins that can be functionally selected and about which homologous-structure information is available

DataSheet_2_Machine learning and experimental validation identified autophagy signature in hepatic fibrosis.docx

BackgroundThe molecular mechanisms of hepatic fibrosis (HF), closely related to autophagy, remain unclear. This study aimed to investigate autophagy characteristics in HF.MethodsGene expression profiles (GSE6764, GSE49541 and GSE84044) were downloaded, normalized, and merged. Autophagy-related differentially expressed genes (ARDEGs) were determined using the limma R package and the Wilcoxon rank sum test and then analyzed by GO, KEGG, GSEA and GSVA. The infiltration of immune cells, molecular subtypes and immune types of healthy control (HC) and HF were analyzed. Machine learning was carried out with two methods, by which, core genes were obtained. Models of liver fibrosis in vivo and in vitro were constructed to verify the expression of core genes and corresponding immune cells.ResultsA total of 69 ARDEGs were identified. Series functional cluster analysis showed that ARDEGs were significantly enriched in autophagy and immunity. Activated CD4 T cells, CD56bright natural killer cells, CD56dim natural killer cells, eosinophils, macrophages, mast cells, neutrophils, and type 17 T helper (Th17) cells showed significant differences in infiltration between HC and HF groups. Among ARDEGs, three core genes were identified, that were ATG5, RB1CC1, and PARK2. Considerable changes in the infiltration of immune cells were observed at different expression levels of the three core genes, among which the expression of RB1CC1 was significantly associated with the infiltration of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. In the mouse liver fibrosis experiment, ATG5, RB1CC1, and PARK2 were at higher levels in HF group than those in HC group. Compared with HC group, HF group showed low positive area in F4/80, IL-17 and CD56, indicating decreased expression of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. Meanwhile, knocking down RB1CC1 was found to inhibit the activation of hepatic stellate cells and alleviate liver fibrosis.ConclusionATG5, RB1CC1, and PARK2 are promising autophagy-related therapeutic biomarkers for HF. This is the first study to identify RB1CC1 in HF, which may promote the progression of liver fibrosis by regulating macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell.</p