Protein-Protein Interactions in Candida albicans

A Current State of Proteomics in Adult and Pediatric Inflammatory Bowel Diseases: A Systematic Search and Review

Inflammatory bowel diseases (IBD) are systemic immune-mediated conditions with predilection for the gastrointestinal tract and include Crohn's disease and ulcerative colitis. Despite the advances in the fields of basic and applied research, the etiopathogenesis remains largely unknown. As a result, only one third of the patients achieve endoscopic remission. A substantial portion of the patients also develop severe clinical complications or neoplasia. The need for novel biomarkers that can enhance diagnostic accuracy, more precisely reflect disease activity, and predict a complicated disease course, thus, remains high. Genomic and transcriptomic studies contributed substantially to our understanding of the immunopathological pathways involved in disease initiation and progression. However, eventual genomic alterations do not necessarily translate into the final clinical picture. Proteomics may represent a missing link between the genome, transcriptome, and phenotypical presentation of the disease. Based on the analysis of a large spectrum of proteins in tissues, it seems to be a promising method for the identification of new biomarkers. This systematic search and review summarize the current state of proteomics in human IBD. It comments on the utility of proteomics in research, describes the basic proteomic techniques, and provides an up-to-date overview of available studies in both adult and pediatric IBD.

The effect of herbal medicine in innate immunity to Candida albicans

Candida albicans (C. albicans) is an opportunistic pathogenic fungus that often causes mucosal and systemic infections. Several pattern recognition receptors (PRRs), such as Toll-like receptors (TLRs) and C-type lectin receptors (CLRs), have been implicated in the host recognition of C. albicans. These PRRs recognize the pathogen-associated molecular patterns (PAMPs) of C. albicans to activate innate immune cells, thereby rapidly inducing various inflammatory responses by activating intracellular signaling cascades. Herbal medicine and its active components deserve priority development due to their low toxicity and high antibacterial, antiviral and antifungal activities. This review discussed the activities of herbal compounds against C. albicans and their related mechanisms, especially their regulatory role on innate immune cells such as neutrophils, macrophages, and dendritic cells (DCs) implicated in C. albicans infections. Our work aims to find new therapeutic drugs and targets to prevent and treat diseases caused by C. albicans infection with the mechanisms by which this fungus interacts with the innate immune response.

Effects of Natural Rheum tanguticum on the Cell Wall Integrity of Resistant Phytopathogenic Pectobacterium carotovorum subsp. Carotovorum

The abuse of agricultural antibiotics has led to the emergence of drug-resistant phytopathogens. Rifampicin and streptomycin and streptomycin resistance Pectobacterium carotovorum subsp. carotovorum (PccS1) was obtained from pathological plants in a previous experiment. Rheum tanguticum, derived from the Chinese plateau area, exhibits excellent antibacterial activity against PccS1, yet the action mode has not been fully understood. In present text, the cell wall integrity of the PccS1 was tested by the variation of the cellular proteins, SDS polyacrylamide gel electrophoresis (SDS-PAGE), scanning electron microscopy (SEM) and Fourier transform infrared spectrophotometer (FTIR) characteristics. Label-free quantitative proteomics was further used to identify the DEPs in the pathogen response to treatment with Rheum tanguticum Maxim. ex Balf. extract (abbreviated as RTMBE). Based on the bioinformatics analysis of these different expressed proteins (DEPs), RTMBE mainly inhibited some key protein expressions of beta-Lactam resistance, a two-component system and phosphotransferase system. Most of these membrane proteins were extraordinarily suppressed, which was also consistent with the morphological tests. In addition, from the downregulated flagellar motility related proteins, it was also speculated that RTMBE played an essential antibacterial role by affecting the swimming motility of the cells. The results indicated that Rheum tanguticum can be used to attenuate the virulence of the drug-resistant phytopathogenic bacteria.

Magnolol as a potent antifungal agent inhibits Candida albicans virulence factors via the PKC and Cek1 MAPK signaling pathways

Magnolol, a lignin compound extracted from Magnolia officinalis Cortex, has been found to have prominent antifungal effects against Candida albicans. However, the specific mechanism still remains unclear. Therefore, this study aimed to further explore the inhibition mechanism of magnolol against Candida albicans virulence factors and the related signaling pathways. By an XTT reduction assay, a hyphal formation assay, confocal laser scanning microscopy, transmission electron microscopy, a calcofluor white staining assay, and a cell wall β-glucan quantitative detection assay, we evaluated the inhibitory effects of magnolol against the adhesion, hyphal formation, biofilm viability, biofilm spatial structure, and cell wall ultrastructure of Candida albicans. Moreover, by RNA sequencing and qRT-PCR, we confirmed the effects of magnolol in inhibiting the gene expression of Candida albicans virulence factors and the related signaling pathways. The results revealed that the adhesion and hyphal formation of Candida albicans were inhibited significantly by magnolol. The viability and spatial structures of Candida albicans biofilms were further weakened. Candida albicans ultrastructure showed partial thinning of cell walls and even rupture, with cytoplasmic leakage. The cell wall intergrity and β-glucan content were also radically reduced. Moreover, magnolol caused significant inhibition of the expression of Candida albicans adhesion, invasion, hyphal formation, biofilm formation, β-1,3-glucan synthesis, and hydrolase secretion-related genes, including ALS1, ALS3, EFG1, EAP1, FKS1, FKS2, PLB2, and SAP2. Furthermore, the PKC pathway-related genes (RHO1, PKC1, BCK1, MKK2, MKC1) and Cek1 pathway-related genes (CDC42, CST20, STE11, HST7, CEK1) were also significantly downregulated, indicating that the inhibition of magnolol against Candida albicans virulence factors might be related to PKC and Cek1 MAPK signaling pathways. In conclusion, the findings of this study confirmed the inhibition mechanism of magnolol against Candida albicans virulence factors, which might be related to PKC and Cek1 MAPK pathways, thus laying the theoretical foundation for its clinical antifungal applications.

CXCR4 and TYROBP mediate the development of atrial fibrillation via inflammation

Atrial fibrillation (AF) is a rapid supraventricular arrhythmia. However, the pathogenesis of atrial fibrillation remains controversial. We obtained transcriptome expression profiles GSE41177, GSE115574 and GSE79768 from GEO database. WGCNA was performed, DEGs were screened, PPI network was constructed using STRING database. CTD database was used to identify the reference score of hub genes associated with cardiovascular diseases. Prediction of miRNAs of hub genes was performed by TargetScan. DIANA‐miRPath v3.0 was applied to make functional annotation of miRNA. The animal model of atrial fibrillation was constructed, RT‐PCR was used to verify the expression of hub genes. Immunofluorescence assay for THBS2 and VCAN was made to identify molecular. Design of BP neural network was made to explore the prediction relationship of CXCR4 and TYROBP on AF. The merged datasets contained 104 up‐regulated and 34 down‐regulated genes. GO and KEGG enrichment analysis results of DEGs showed they were mainly enriched in ‘regulation of release of sequestered calcium ion into cytosol’, ‘actin cytoskeleton organization’ and ‘focal adhesion’. The hub genes were CXCR4, SNAI2, S100A4, IGFBP3, CSNK2A1, CHGB, VCAN, APOE, C1QC and TYROBP, which were up‐regulated expression in the AF compared with control tissues. There was strong correlation among the CXCR4, TYROBP and AF based on the BP neural network. Through training, best training performance is 9.6474e‐05 at epoch 14, and the relativity was 0.99998. CXCR4 and TYROBP might be involved in the development of atrial fibrillation by affecting inflammation‐related signalling pathways and may serve as targets for early diagnosis and preventive treatment.

Fluorescent toys 'n' tools lighting the way in fungal research

Although largely overlooked compared to bacterial infections, fungal infections pose a significant threat to the health of humans and other organisms. Many pathogenic fungi, especially Candida species, are extremely versatile and flexible in adapting to various host niches and stressful situations. This leads to high pathogenicity and increasing resistance to existing drugs. Due to the high level of conservation between fungi and mammalian cells, it is hard to find fungus-specific drug targets for novel therapy development. In this respect, it is vital to understand how these fungi function on a molecular, cellular as well as organismal level. Fluorescence imaging allows for detailed analysis of molecular mechanisms, cellular structures and interactions on different levels. In this manuscript, we provide researchers with an elaborate and contemporary overview of fluorescence techniques that can be used to study fungal pathogens. We focus on the available fluorescent labelling techniques and guide our readers through the different relevant applications of fluorescent imaging, from subcellular events to multispecies interactions and diagnostics. As well as cautioning researchers for potential challenges and obstacles, we offer hands-on tips and tricks for efficient experimentation and share our expert-view on future developments and possible improvements.

Protein-Protein Interface Topology as a Predictor of Secondary Structure and Molecular Function Using Convolutional Deep Learning

To power the specific recognition and binding of protein partners into functional complexes, a wealth of information about the structure and function of the partners is necessarily encoded into the global shape of protein-protein interfaces and their local topological features. To identify whether this is the case, this study uses convolutional deep learning methods (typically leveraged for 2D image recognition) on 3D voxel representations of protein-protein interfaces colored by burial depth. A novel two-stage network fed with voxelizations of each interface at two distinct resolutions achieves balance between performance and computational cost. From the shape of the interfaces, the network tries to predict the presence of secondary structure motifs at the interface and the molecular function of the corresponding complex. Secondary structure and certain classes of function are found to be very well predicted, validating the hypothesis that interface shape is a conveyor of higher-level information. Interface patterns triggering the recognition of specific classes are also identified and described.

Identification of therapeutic targets and mechanisms of tumorigenesis in non-small cell lung cancer using multiple-microarray analysis

Lung cancer is the most commonly occurring cancer attributed to the leading cause of cancer-related deaths globally. Non-small cell lung cancer (NSCLC) comprises 85% to 90% of lung cancers. The survival rate of patients with advanced stage NSCLC is in months. Moreover, the underlying molecular mechanisms still remain to be understood.We used 2 sets of microarray data in combination with various bioinformatic approaches to identify the differentially expressed genes (DEGs) in NSCLC patients.We identified a total of 419 DEGs using the Limma package. Gene set enrichment analysis demonstrated that "Citrate cycle (TCA cycle)," "RNA degradation," and "Pyrimidine metabolism" pathways were significantly enriched in the NSCLC samples. Gene Ontology annotations of the 419 DEGs primarily comprised "glycosaminoglycan binding," "cargo receptor activity," and "organic acid binding." Kyoto Encyclopedia of Genes and Genomes analysis revealed that DEGs were enriched in pathways related to "Malaria," "Cell cycle," and "IL-17 signaling pathway." Protein protein interaction network analysis showed that the hub genes constituted of CDK1, CDC20, BUB1, BUB1B, TOP2A, CCNA2, KIF20A, CCNB1, KIF2C, and NUSAP1.Taken together, the identified hub genes and pathways will help understand NSCLC tumorigenesis and develop prognostic markers and therapeutic targets against NSCLC.

Tracking the functional meaning of the human oral-microbiome protein-protein interactions

The interactome - the network of protein-protein interactions (PPIs) within a cell or organism - is technically difficult to assess. Bioinformatic tools can, not only, identify potential PPIs that can be later experimentally validated, but also be used to assign functional meaning to PPIs. Saliva's potential as a non-invasive diagnostic fluid is currently being explored by several research groups. But, in order to fully attain its potential, it is necessary to achieve the full characterization of the mechanisms that take place within this ecosystem. The onset of omics technologies, and specifically of proteomics, delivered a huge set of data that is largely underexplored. Quantitative information relative to proteins within a given context (for example a given disease) can be used by computational algorithms to generate information regarding PPIs. These PPIs can be further analyzed concerning their functional meaning and used to identify potential biomarkers, therapeutic targets, defense and pathogenicity mechanisms. We describe a computational pipeline that can be used to identify and analyze PPIs between human and microbial proteins. The pipeline was tested within the scenario of human PPIs of systemic (Zika Virus infection) and of oral conditions (Periodontal disease) and also in the context of microbial interactions (Candida-Streptococcus) and showed to successfully predict functionally relevant PPIs. The pipeline can be applied to different scientific areas, such as pharmacological research, since a functional meaningful PPI network can provide insights on potential drug targets, and even new uses for existing drugs on the market.