SweepCluster: A SNP clustering tool for detecting gene-specific sweeps in prokaryotes.

BACKGROUND: The gene-specific sweep is a selection process where an advantageous mutation along with the nearby neutral sites in a gene region increases the frequency in the population. It has been demonstrated to play important roles in ecological differentiation or phenotypic divergence in microbial populations. Therefore, identifying gene-specific sweeps in microorganisms will not only provide insights into the evolutionary mechanisms, but also unravel potential genetic markers associated with biological phenotypes. However, current methods were mainly developed for detecting selective sweeps in eukaryotic data of sparse genotypes and are not readily applicable to prokaryotic data. Furthermore, some challenges have not been sufficiently addressed by the methods, such as the low spatial resolution of sweep regions and lack of consideration of the spatial distribution of mutations. RESULTS: We proposed a novel gene-centric and spatial-aware approach for identifying gene-specific sweeps in prokaryotes and implemented it in a python tool SweepCluster. Our method searches for gene regions with a high level of spatial clustering of pre-selected polymorphisms in genotype datasets assuming a null distribution model of neutral selection. The pre-selection of polymorphisms is based on their genetic signatures, such as elevated population subdivision, excessive linkage disequilibrium, or significant phenotype association. Performance evaluation using simulation data showed that the sensitivity and specificity of the clustering algorithm in SweepCluster is above 90%. The application of SweepCluster in two real datasets from the bacteria Streptococcus pyogenes and Streptococcus suis showed that the impact of pre-selection was dramatic and significantly reduced the uninformative signals. We validated our method using the genotype data from Vibrio cyclitrophicus, the only available dataset of gene-specific sweeps in bacteria, and obtained a concordance rate of 78%. We noted that the concordance rate could be underestimated due to distinct reference genomes and clustering strategies. The application to the human genotype datasets showed that SweepCluster is also applicable to eukaryotic data and is able to recover 80% of a catalog of known sweep regions. CONCLUSION: SweepCluster is applicable to a broad category of datasets. It will be valuable for detecting gene-specific sweeps in diverse genotypic data and provide novel insights on adaptive evolution.

Resveratrol ameliorated endothelial injury of thoracic aorta in diabetic mice and Gly-LDL-induced HUVECs through inhibiting TLR4/HIF-1α.

To explore the effects of resveratrol on the levels of inflammatory cytokines and Toll-like receptor-4/ hypoxia-inducible transcription factors-1α (TLR4/HIF-1α) signalling pathway in diabetes mellitus. C57BL/6 mice received intraperitoneal injection of streptozocin for constructing diabetic mice models. Human umbilical vein endothelial cells (HUVECs) were treated with 50 µg/mL Gly-LDL for inducing injury models. 10, 100 and 1000 mmol/L resveratrol were obtained and added into each group. Haematoxylin-eosin (H&E) staining was used for histological evaluation. CCK8 assay was performed for determination of cell viability, and Transwell assay was implemented for detecting cell migration ability. Cell apoptosis was analysed using flow cytometry. The content of inflammatory factors including interleukin-6 (IL-6), tumour necrosis factor-α (TNF-α), vascular adhesion molecule-1 (VCAM-1) and vascular endothelial growth factor (VEGF) were measured by ELISA. GST pull-down assay was employed for determining interactions between TLR4 and HIF-1α. The protein expression of TLR4 and HIF-1α was detected using Western blotting and immunohistochemistry, while relative mRNA expression was measured by RT-qRCR. Resveratrol could reduce bodyweight and ameliorate endothelial injury of thoracic aorta in diabetic mice. Both in vivo and in vitro results revealed that the level of IL-6, TNF-α, VCAM-1 and VEGF was significantly down-regulated after being treated with resveratrol. Resveratrol inhibited the increase of MDA and ROS and increased the level of SOD in diabetic mice. Western blotting, IHC and RT-qPCR results showed that the levels of TLR4 and HIF-1α were significantly down-regulated in resveratrol group. Overexpression of TLR4 or HIF-1α could reverse the effect of resveratrol. GST pull-down elucidated that there might be a close interaction between TLR4 and HIF-1α. Resveratrol ameliorated endothelial injury of thoracic aorta in diabetic mice and Gly-LDL-induced HUVECs through inhibiting TLR4/HIF-1α signalling pathway.

deepAMPNet: a novel antimicrobial peptide predictor employing AlphaFold2 predicted structures and a bi-directional long short-term memory protein language model.

Background: Global public health is seriously threatened by the escalating issue of antimicrobial resistance (AMR). Antimicrobial peptides (AMPs), pivotal components of the innate immune system, have emerged as a potent solution to AMR due to their therapeutic potential. Employing computational methodologies for the prompt recognition of these antimicrobial peptides indeed unlocks fresh perspectives, thereby potentially revolutionizing antimicrobial drug development. Methods: In this study, we have developed a model named as deepAMPNet. This model, which leverages graph neural networks, excels at the swift identification of AMPs. It employs structures of antimicrobial peptides predicted by AlphaFold2, encodes residue-level features through a bi-directional long short-term memory (Bi-LSTM) protein language model, and constructs adjacency matrices anchored on amino acids' contact maps. Results: In a comparative study with other state-of-the-art AMP predictors on two external independent test datasets, deepAMPNet outperformed in accuracy. Furthermore, in terms of commonly accepted evaluation matrices such as AUC, Mcc, sensitivity, and specificity, deepAMPNet achieved the highest or highly comparable performances against other predictors. Conclusion: deepAMPNet interweaves both structural and sequence information of AMPs, stands as a high-performance identification model that propels the evolution and design in antimicrobial peptide pharmaceuticals. The data and code utilized in this study can be accessed at https://github.com/Iseeu233/deepAMPNet.

The Pan-Genomic Analysis of Corynebacterium striatum Revealed its Genetic Characteristics as an Emerging Multidrug-Resistant Pathogen.

Corynebacterium striatum is a Gram-positive bacterium that is straight or slightly curved and non-spore-forming. Although it was originally believed to be a part of the normal microbiome of human skin, a growing number of studies have identified it as a cause of various chronic diseases, bacteremia, and respiratory infections. However, despite its increasing importance as a pathogen, the genetic characteristics of the pathogen population, such as genomic characteristics and differences, the types of resistance genes and virulence factors carried by the pathogen and their distribution in the population are poorly understood. To address these knowledge gaps, we conducted a pan-genomic analysis of 314 strains of C. striatum isolated from various tissues and geographic locations. Our analysis revealed that C. striatum has an open pan-genome, comprising 5692 gene families, including 1845 core gene families, 2362 accessory gene families, and 1485 unique gene families. We also found that C. striatum exhibits a high degree of diversity across different sources, but strains isolated from skin tissue are more conserved. Furthermore, we identified 53 drug resistance genes and 42 virulence factors by comparing the strains to the drug resistance gene database (CARD) and the pathogen virulence factor database (VFDB), respectively. We found that these genes and factors are widely distributed among C. striatum, with 77.7% of strains carrying 2 or more resistance genes and displaying primary resistance to aminoglycosides, tetracyclines, lincomycin, macrolides, and streptomycin. The virulence factors are primarily associated with pathogen survival within the host, iron uptake, pili, and early biofilm formation. In summary, our study provides insights into the population diversity, resistance genes, and virulence factors ofC. striatum from different sources. Our findings could inform future research and clinical practices in the diagnosis, prevention, and treatment of C. striatum-associated diseases.

Fibroblast growth factor 18 alleviates stress-induced pathological cardiac hypertrophy in male mice.

Fibroblast growth factor-18 (FGF18) has diverse organ development and damage repair roles. However, its role in cardiac homeostasis following hypertrophic stimulation remains unknown. Here we investigate the regulation and function of the FGF18 in pressure overload (PO)-induced pathological cardiac hypertrophy. FGF18 heterozygous (Fgf18+/-) and inducible cardiomyocyte-specific FGF18 knockout (Fgf18-CKO) male mice exposed to transverse aortic constriction (TAC) demonstrate exacerbated pathological cardiac hypertrophy with increased oxidative stress, cardiomyocyte death, fibrosis, and dysfunction. In contrast, cardiac-specific overexpression of FGF18 alleviates hypertrophy, decreased oxidative stress, attenuates cardiomyocyte apoptosis, and ameliorates fibrosis and cardiac function. Tyrosine-protein kinase FYN (FYN), the downstream factor of FGF18, was identified by bioinformatics analysis, LC-MS/MS and experiment validation. Mechanistic studies indicate that FGF18/FGFR3 promote FYN activity and expression and negatively regulate NADPH oxidase 4 (NOX4), thereby inhibiting reactive oxygen species (ROS) generation and alleviating pathological cardiac hypertrophy. This study uncovered the previously unknown cardioprotective effect of FGF18 mediated by the maintenance of redox homeostasis through the FYN/NOX4 signaling axis in male mice, suggesting a promising therapeutic target for the treatment of cardiac hypertrophy.

C1q tumor necrosis factor-related protein 4 is associated with coronary artery disease in patients with type 2 diabetes.

AIMS/INTRODUCTION: To evaluate the correlation of circulating C1q tumor necrosis factor-related protein 4 (CTRP4) with coronary artery disease (CAD) in type 2 diabetes mellitus patients. METHODS: A total of 240 individuals with type 2 diabetes mellitus were enrolled in our center between January 2020 and December 2020. They were assigned into two groups, including the CAD and non-CAD groups, based on coronary angiography or computed tomography angiography findings. Serum CTRP4 levels were detected by an enzyme-linked immunosorbent assay kit. The association of CTRP4 with CAD was determined by logistic regression analysis. The predictive value of CTRP4 for CAD was calculated by receiver operating characteristic curve analysis. RESULTS: Median serum CTRP4 amounts were markedly elevated in the CAD group in comparison with the non-CAD group (10.37 vs 3.75 ng/mL, P < 0.01). Binary logistic regression showed that CTRP4 was associated with CAD and even the amount of coronary artery lesions (P < 0.05). In receiver operating characteristic curve analysis, the area under the receiver operating characteristic curve was greater for CTRP4 compared with HbA1c or CRP (0.87 vs 0.74, 0.87 vs 0.80, P < 0.01). The area under the curve for CTRP4 and glycated hemoglobin in combination was larger than that obtained for CTRP4 combined with CRP (0.91 vs 0.87, P < 0.01). According to the maximum Youden index criteria, the optimal cut-off of CTRP4 was 5.42 ng/mL, which yielded a sensitivity of 84.4% and a specificity of 76.7% in predicting CAD in type 2 diabetes mellitus patients. CONCLUSIONS: Serum CTRP4 levels are positively correlated with CAD occurrence and severity. Combining CTRP4 and glycated hemoglobin has a better predictive value for CAD in type 2 diabetes mellitus patients.

The global research of bladder cancer immunotherapy from 2012 to 2021: A bibliometric analysis.

Intravesical instillation of Bacillus Calmette-Guérin has been used as an immunotherapy to treat superficial bladder cancer for almost half a century. In recent years, the approval of several monoclonal antibody treatments has transformed the treatment landscape for patients with muscle-invasive or metastatic uroepithelial carcinoma. The purpose of this study was to conduct a thorough review of immunotherapy in bladder cancer through a bibliometric approach. Publications related to bladder cancer immunotherapy were obtained from the Web of Science Core Collection on July 1st, 2022. We conducted a bibliometric analysis of literature information using CiteSpace IV, VOSviewer, and Scimago Graphica, including co-authorship or co-citation of authors, countries/regions, journals, references, and keyword co-occurrence. There was a total of 2,352 papers included, with the most contributions coming from the United States, China, and Italy. The United States had the highest H-index value and was the leading country in this field. Meanwhile, the number of publications in China was steadily growing. The top three productive researchers were Kamat AM, Necchi A, and Shariat SF, with Powles T as the top co-cited author. Most papers were published by the University of Texas System. The majority of papers in this field were published in Urologic Oncology Seminars and Original Investigations and European Urology was the most influential journal with the highest H-index. The tumor microenvironment and complete molecular characterization may still be the frontier in this research area, allowing us to obtain a better understanding of the pathogenesis and clinical prognosis of bladder cancer. More research are conducted to identify clinically meaningful biomarkers that may provide opportunities for the personalization of bladder cancer therapy. This study provides clinicians and researchers with an overview and helpful guidance on how to choose the research direction and management of bladder cancer immunotherapy.

The genetic variation landscape of African swine fever virus reveals frequent positive selection and adaptive flexibility.

African swine fever virus (ASFV) is a lethal disease agent that causes high mortality in swine population and devastating loss in swine industries. The development of efficacious vaccines has been hindered by the gap in knowledge concerning genetic variation of ASFV and the genetic factors involved in host adaptation and virus-host interactions. In this study, we performed a meta-genetic study of ASFV aiming to profile the variation landscape and identify genetic factors with signatures of positive selection and relevance to host adaptation. Our data reveal a high level of genetic variability of ASFV shaped by both diversifying selection and selective sweep. The selection signatures are widely distributed across the genome with the diversifying selection falling within 29 genes and selection sweep within 25 genes, highlighting strong signals of adaptive evolution of ASFV. Further examination of the sequence properties reveals the link of the selection signatures with virus-host interactions and adaptive flexibility. Specifically, we discovered a site at 157th of the key antigen protein EP402R under diversifying selection, which is located in the cytotoxic T-cell epitope related to the low level of cross-reaction in T-cell response. Importantly, two multigene families MGF360 and MGF505, the host range factors of ASFV, exhibit divergent selection among the paralogous members, conferring sequence pools for genetic diversification and adaptive capability. By integrating the genes with selection signatures into a unified framework of interactions between ASFV and hosts, we showed that the genes are involved in multiple processes of host immune interaction and virus life cycles, and may play crucial roles in circumventing host defence systems and enhancing adaptive fitness. Our findings will allow enhanced understanding of genetic basis of rapid spreading and adaptation of ASFV among the hosts.

Resveratrol improves Gly-LDL-induced vascular endothelial cell apoptosis, inflammatory factor secretion and oxidative stress by regulating miR-142-3p and regulating SPRED2-mediated autophagy.

BACKGROUND: Resveratrol improves cell apoptosis and tissue damage induced by high glucose, but the specific mechanism is unknown. METHODS: This is a basic research. We performed cell transfection, real-time fluorescence quantitative PCR (qPCR), flow cytometry, immunofluorescence, western blot, enzyme linked immunosorbent assay (ELISA) and cell viability assay to analyze cell viability, cell cycle, cellular oxidative stress, intracellular inflammatory factors and autophagy activities in vitro. Meanwhile, dual luciferase reporter assay was conducted to explore the influence of miR-142-3p and sprouty-related EVH1 domain 2 (SPRED 2) on human glycated low-density lipoprotein (Gly-LDL)-induced vascular endothelial cell apoptosis, inflammatory factor secretion and oxidative stress. RESULTS: Resveratrol inhibited the expression of miR-142-3p in human umbilical vein endothelial cells (HUVECs) induced by Gly-LDL in a dose-dependent manner, and the overexpression of miR-142-3p reverses the effect of resveratrol on the proliferation, apoptosis, secretion of inflammatory factors, oxidative stress, and autophagy. The dual-luciferase report analysis found a negative regulatory relationship between miR-142-3p and SPRED2. Inhibition of SPRED2 reversed the effects of resveratrol on Gly-LDL-induced HUVECs proliferation, apoptosis, inflammatory factor secretion and oxidative stress, and reversed the effects of resveratrol on Gly-LDL-induced HUVECs autophagy. CONCLUSION: miR-142-3p promotes the development of diabetes by inhibiting SPRED2-mediated autophagy, including inducing cell apoptosis, aggravating cellular oxidative stress and secretion of inflammatory factors, and resveratrol improves this effect.