Protein Bioinformatics Databases and Resources

Value of Bioinformatics Models for Predicting Translational Control of Angiogenesis

Angiogenesis, the formation of new blood vessels, is a fundamental biological process with implications for both physiological functions and pathological conditions. While the transcriptional regulation of angiogenesis, mediated by factors such as HIF-1α (hypoxia-inducible factor 1-alpha) and VEGF (vascular endothelial growth factor), is well-characterized, the translational regulation of this process remains underexplored. Bioinformatics has emerged as an indispensable tool for advancing our understanding of translational regulation, offering predictive models that leverage large data sets to guide research and optimize experimental approaches. However, a significant gap persists between bioinformatics experts and other researchers, limiting the accessibility and utility of these tools in the broader scientific community. To address this divide, user-friendly bioinformatics platforms are being developed to democratize access to predictive analytics and empower researchers across disciplines. Translational control, compared with transcriptional control, offers a more energy-efficient mechanism that facilitates rapid cellular responses to environmental changes. Furthermore, transcriptional regulators themselves are often subject to translational control, emphasizing the interconnected nature of these regulatory layers. Investigating translational regulation requires advanced, accessible bioinformatics tools to analyze RNA structures, interacting micro-RNAs, long noncoding RNAs, and RBPs (RNA-binding proteins). Predictive platforms such as RNA structure, human internal ribosome entry site Atlas, and RBPSuite enable the study of RNA motifs and RNA-protein interactions, shedding light on these critical regulatory mechanisms. This review highlights the transformative role of bioinformatics using widely accessible user-friendly tools with a Web-browser interface to elucidate translational regulation in angiogenesis. The bioinformatics tools discussed extend beyond angiogenesis, with applications in diverse fields, including clinical care. By integrating predictive models and experimental insights, researchers can streamline hypothesis generation, reduce experimental costs, and find novel translational regulators. By bridging the bioinformatics knowledge gap, this review aims to empower researchers worldwide to adopt bioinformatics tools in their work, fostering innovation and accelerating scientific discovery.

Quercetin alleviates ulcerative colitis through inhibiting CXCL8-CXCR1/2 axis: a network and transcriptome analysis

Introduction

Ulcerative colitis (UC) is a chronic inflammatory condition of the intestinal tract in which mucosal healing is a crucial measure of therapeutic efficacy. Quercetin, a flavonoid prevalent in various foods and traditional Chinese medicines, exhibits notable pharmacological properties, including antioxidant and anti-inflammatory activities. Consequently, it warrants investigation to determine its potential therapeutic effects on UC. The objective of this study was to investigate the effects and underlying mechanisms of quercetin in a murine model of UC.

Methods

A comprehensive approach integrating network predictions with transcriptomic analyses was employed to identify the potential targets and enriched pathways associated with quercetin in UC. Subsequently, the effects of quercetin on pathological morphology, inflammatory mediators, and mucosal barrier-associated proteins, as well as the identified potential targets and enriched pathways, were systematically investigated in a murine model of dextran sulfate sodium (DSS)-induced UC.

Results

Network analyses identified CXCL8 and its receptors, CXCR1 and CXCR2, as primary target genes for therapeutic intervention in UC. Further validation through transcriptomic analysis and immunofluorescence staining demonstrated significant upregulation of the CXCL8-CXCR1/2 axis in the intestinal tissues of patients with UC. Experimental investigations in animal models have shown that quercetin markedly alleviates DSS-induced symptoms in mice. This effect includes the restoration of colonic crypt architecture, normalization of goblet cell structure and density, reduction of inflammatory cell infiltration, and decreased concentrations of inflammatory mediators. Quercetin enhanced the expression of tight junction (TJ) proteins, including ZO-1, MUC2 (Mucin 2), and occludin, thereby preserving the integrity of the intestinal mucosal barrier. Additionally, it significantly diminished the levels of IL-17A, NF-κB, CXCL8, CXCR1, and CXCR2 in the colonic tissues of mice with UC.

Discussion

The ameliorative effects of quercetin on colon tissue damage in DSS-induced UC mice were significant, possibly due to its ability to inhibit the CXCL8-CXCR1/2 signaling axis. These findings provide a solid foundation for the clinical application and pharmaceutical advancement of quercetin.

TRAIP enhances progression of tongue squamous cell carcinoma through EMT and Wnt/β-catenin signaling by interacting with DDX39A

BACKGROUND

Tongue squamous cell carcinoma (TSCC) is one of the most common malignant tumors with high mortality and poor prognosis. Its incidence rate is increasing gradually. Tumor necrosis factor receptor-associated factor interacting protein (TRAIP), as a factor related to several tumors, reveals that its gene expression is different between normal tissue and primary tumor of head and neck squamous cell carcinoma using bioinformatics analysis.

METHOD

In our study, TCGA database, immunohistochemistry, proliferation assay, colony formation, wound healing assay, Transwell, cell cycle analysis and tumor xenografts model were used to determine the expression and functions of TRAIP in TSCC.

RESULT

We found that TRAIP may promote the proliferation, migration and invasion of TSCC. Furthermore, the results of bioinformatics analysis, mass spectrometry and co-immunoprecipitation suggested that DDX39A may be a TRAIP interacting protein. DDX39A has been proven to be an oncogene in several tumors, which may have an important effect on cell proliferation and metastasis in multiple tumors. In addition, the high expression of DDX39A implies the poor prognosis of patients. Our study demonstrated that TRAIP probably interact with DDX39A to regulate cell progression through epithelial-mesenchymal transition and Wnt/β-catenin pathway. In addition, we show that the necessary domain of DDX39A for the interaction between DDX39A and TRAIP region.

CONCLUSION

These results indicate that TRAIP is important in occurrence and development of TSCC and is expected to become the new promising therapeutic target.

Study on the mechanism of action of Saposhnikovia divaricata and its key phytochemical on rheumatoid arthritis based on network pharmacology and bioinformatics

ETHNOPHARMACOLOGICAL RELEVANCE

Saposhnikovia divaricata (Turcz.) Schischk (SD; called "fangfeng" in China) has been widely used in the clinical treatment of rheumatoid arthritis (RA) and has shown well therapeutic effects, but the specific mechanisms of action of its bioactive phytochemicals remain unclear.

AIM OF THE STUDY

This study aimed to investigate the molecular biological mechanism of SD in treating RA through a pharmacology-based strategy. The SD-specific core ingredient Prangenidin was screened for further in-depth study.

MATERIALS AND METHODS

The bioactive phytochemicals of SD and potential targets for the treatment of RA were screened by network pharmacology, and phytochemicals-related parameters such as pharmacology, and toxicology were evaluated. The protein interaction network was established to screen the core targets, and the correlation between the core targets and RA was further validated by bioinformatics strategy. Finally, molecular docking of core components and corresponding targets was performed. The in vitro experiments were performed to elucidate the regulation of Prangenidin on MH7A cells and on the PI3K/AKT pathway, and the in vivo therapeutic effect of Prangenidin was validated in collagen-induced arthritis (CIA) mice.

RESULTS

A total of 18 bioactive phytochemicals and 66 potential target genes intersecting with the screened RA disease target genes were identified from SD. Finally, core ingredients such as wogonin, beta-sitosterol, 5-O-Methylvisamminol, and prangenidin and core targets such as PTGS2, RELA, and AKT1 were obtained. The underlying mechanism of SD in treating RA might be achieved by regulating pathways such as PI3K/AKT, IL-17 pathway, apoptosis, and multiple biological processes to exert anti-inflammatory and immunomodulatory effects. Molecular docking confirmed that all core ingredients and key targets had great docking activity. Prangenidin inhibited viability, migration, and invasion, and induced apoptosis in MH7A cells. Prangenidin also reduced the production of IL-1β, IL-6, IL-8, MMP-1, and MMP-3. Molecular analysis showed that Prangenidin exerts its regulatory effect on MH7A cells by inhibiting PI3K/AKT pathway. Treatment with Prangenidin ameliorated synovial inflammation in the joints of mice with CIA.

CONCLUSION

Our findings provide insights into the therapeutic effects of SD on RA, successfully predicting the effective ingredients and potential targets, which could suggest a novel theoretical basis for further exploration of its molecular mechanisms. It also revealed that Prangenidin inhibited viability, migration, invasion, cytokine, and MMPs expression, and induced apoptosis in RA FLSs via the PI3K/AKT pathway.

Meloidogyne enterolobii MeMSP1 effector targets the glutathione-S-transferase phi GSTF family in Arabidopsis to manipulate host metabolism and promote nematode parasitism

Meloidogyne enterolobii is an emerging root-knot nematode species that overcomes most of the nematode resistance genes in crops. Nematode effector proteins secreted in planta are key elements in the molecular dialogue of parasitism. Here, we show the MeMSP1 effector is secreted into giant cells and promotes M. enterolobii parasitism. Using co-immunoprecipitation and bimolecular fluorescent complementation assays, we identified glutathione-S-transferase phi GSTFs as host targets of the MeMSP1 effector. This protein family plays important roles in plant responses to abiotic and biotic stresses. We demonstrate that MeMSP1 interacts with all Arabidopsis GSTF. Moreover, we confirmed that the N-terminal region of AtGSTF9 is critical for its interaction, and atgstf9 mutant lines are more susceptible to root-knot nematode infection. Combined transcriptome and metabolome analyses showed that MeMSP1 affects the metabolic pathways of Arabidopsis thaliana, resulting in the accumulation of amino acids, nucleic acids, and their metabolites, and organic acids and the downregulation of flavonoids. Our study has shed light on a novel effector mechanism that targets plant metabolism, reducing the production of plant defence-related compounds while favouring the accumulation of metabolites beneficial to the nematode, and thereby promoting parasitism.

Serum proteomics analysis for differentiation among Mycobacterium tuberculosis infection categories

Inhalation of Mycobacterium tuberculosis (Mtb) bacilli can lead to a range of TB categories including early clearance (EC), latent TB infection (LTBI) and active TB (ATB). There are few biomarkers available to differentiate among these TB categories: effective new biomarkers are badly needed. Here, we analyzed the serum proteins from 26 ATB cases, 20 LTBI cases, 34 EC cases and 38 healthy controls (HC) using label-free LC-MS/MS. The results were analyzed using MaxQuant software and matched to three different bacterial proteomics databases, including Mtb, Mycobacterium spp. and normal lung flora. PCA of protein candidates using the three proteomics databases revealed 44.5% differentiation power to differentiate among four TB categories. There were 289 proteins that showed potential for distinguishing between each pair of groups among TB categories. There were 50 candidate protein markers specifically found in ATB and LTBI but not in HC and EC groups. Decision trees using the top five candidate biomarkers (A0A1A2RWZ9, A0A1A3FMY8, A0A1A3KIY2, A0A5C7MJH5 and A0A1X0XYR3) had 92.31% accuracy to differentiate among TB categories and the accuracy was increased to 100% when using 10 candidate biomarkers. Our study shows that proteins expressed from Mycobacterium spp. have the potential to be used to differentiate among TB categories.

StandEnA: a customizable workflow for standardized annotation and generating a presence-absence matrix of proteins

Motivation

Several genome annotation tools standardize annotation outputs for comparability. During standardization, these tools do not allow user-friendly customization of annotation databases; limiting their flexibility and applicability in downstream analysis.

Results

StandEnA is a user-friendly command-line tool for Linux that facilitates the generation of custom databases by retrieving protein sequences from multiple databases. Directed by a user-defined list of standard names, StandEnA retrieves synonyms to search for corresponding sequences in a set of public databases. Custom databases are used in prokaryotic genome annotation to generate standardized presence-absence matrices and reference files containing standard database identifiers. To showcase StandEnA, we applied it to six metagenome-assembled genomes to analyze three different pathways.

Availability and implementation

StandEnA is an open-source software available at https://github.com/mdsufz/StandEnA.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Ovule Transcriptome Analysis Discloses Deregulation of Genes and Pathways in Sexual and Apomictic Limonium Species (Plumbaginaceae)

The genus Limonium Mill. (sea lavenders) includes species with sexual and apomixis reproductive strategies, although the genes involved in these processes are unknown. To explore the mechanisms beyond these reproduction modes, transcriptome profiling of sexual, male sterile, and facultative apomictic species was carried out using ovules from different developmental stages. In total, 15,166 unigenes were found to be differentially expressed with apomictic vs. sexual reproduction, of which 4275 were uniquely annotated using an Arabidopsis thaliana database, with different regulations according to each stage and/or species compared. Gene ontology (GO) enrichment analysis indicated that genes related to tubulin, actin, the ubiquitin degradation process, reactive oxygen species scavenging, hormone signaling such as the ethylene signaling pathway and gibberellic acid-dependent signal, and transcription factors were found among differentially expressed genes (DEGs) between apomictic and sexual plants. We found that 24% of uniquely annotated DEGs were likely to be implicated in flower development, male sterility, pollen formation, pollen-stigma interactions, and pollen tube formation. The present study identifies candidate genes that are highly associated with distinct reproductive modes and sheds light on the molecular mechanisms of apomixis expression in Limonium sp.

IFIH1 was predicted as a key biomarker in primary Sjögren's syndrome based on transcriptome analysis and experimental verification in patients and mice

OBJECTIVES

To investigate the novel key genes and biological processes that may lead to primary Sjögren' s syndrome (pSS).

METHODS

We downloaded datasets about peripheral blood samples of pSS patients and healthy controls (GSE51092, GSE84844, and GSE66795) from Gene Expression Omnibus database. The weighted co-expression network analysis and differential expression analysis first were implemented. After that, protein-protein network interaction and Support Vector Machines were applied in the meantime to take intersection for key genes. Moreover, we conducted immune cell infiltration analysis to explore the relationship between the gene expression and concentration of immune cells in peripheral blood. Lastly, the expression of key genes was verified in pSS patients and murine models by reverse-transcription polymerase chain reaction. Meanwhile, correlation analysis of gene expression and disease activity was also performed.

RESULTS

Only 1 key gene, interferon induced with helicase c domain 1 (IFIH1), was identified to be both significantly up-regulated and important for the diagnosis of pSS. The increased expression of IFIH1 in peripheral blood was confirmed in data sets, patients and non-obese diabetic (NOD) mice. Its expression was correlated with disease activity in patients as well. In addition, the IFIH1 expression was also increased in spleen and salivary glands infiltrated with lymphocytes in NOD mice. Furthermore, immune cell infiltration analysis showed that the expression of IFIH1 was positively correlated with the proportion of memory B cells and activated dendritic cells, and negatively correlated with the proportion of macrophage M0.

CONCLUSIONS

Here, bioinformatics analyses and experimental assays were performed to provide a new insight for understanding of pSS. IFIH1 may be a new diagnostic marker or therapeutic target for pSS.

Roadmap to the study of gene and protein phylogeny and evolution-A practical guide

Developments in sequencing technologies and the sequencing of an ever-increasing number of genomes have revolutionised studies of biodiversity and organismal evolution. This accumulation of data has been paralleled by the creation of numerous public biological databases through which the scientific community can mine the sequences and annotations of genomes, transcriptomes, and proteomes of multiple species. However, to find the appropriate databases and bioinformatic tools for respective inquiries and aims can be challenging. Here, we present a compilation of DNA and protein databases, as well as bioinformatic tools for phylogenetic reconstruction and a wide range of studies on molecular evolution. We provide a protocol for information extraction from biological databases and simple phylogenetic reconstruction using probabilistic and distance methods, facilitating the study of biodiversity and evolution at the molecular level for the broad scientific community.

Overexpression of Water-Responsive Genes Promoted by Elevated CO2 Reduces ROS and Enhances Drought Tolerance in Coffea Species

Drought is a major constraint to plant growth and productivity worldwide and will aggravate as water availability becomes scarcer. Although elevated air [CO₂] might mitigate some of these effects in plants, the mechanisms underlying the involved responses are poorly understood in woody economically important crops such as Coffea. This study analyzed transcriptome changes in Coffea canephora cv. CL153 and C. arabica cv. Icatu exposed to moderate (MWD) or severe water deficits (SWD) and grown under ambient (aCO₂) or elevated (eCO₂) air [CO₂]. We found that changes in expression levels and regulatory pathways were barely affected by MWD, while the SWD condition led to a down-regulation of most differentially expressed genes (DEGs). eCO₂ attenuated the impacts of drought in the transcripts of both genotypes but mostly in Icatu, in agreement with physiological and metabolic studies. A predominance of protective and reactive oxygen species (ROS)-scavenging-related genes, directly or indirectly associated with ABA signaling pathways, was found in Coffea responses, including genes involved in water deprivation and desiccation, such as protein phosphatases in Icatu, and aspartic proteases and dehydrins in CL153, whose expression was validated by qRT-PCR. The existence of a complex post-transcriptional regulatory mechanism appears to occur in Coffea explaining some apparent discrepancies between transcriptomic, proteomic, and physiological data in these genotypes.

Molecular Mimicry between Respiratory Syncytial Virus F Antigen and the Human Proteome

This study examined respiratory syncytial virus (RSV) F glycoprotein (gp) antigen for molecular mimicry with the human proteome. It was found that the viral antigen presents an impressive number of pentapeptides (namely, 525 out of 570) in common with the human proteome, with viral sequences widely and repeatedly distributed among 3,762 human proteins implicated in crucial fundamental cellular functions. The data can have implications for anti-RSV vaccines. Indeed, the high level of molecular mimicry can lead to cross-reactivity and autoimmunity, and invites to follow safer vaccinal protocols based on pentapeptide sequences uniquely present in the viral antigen.

Critical review of conformational B-cell epitope prediction methods

Accurate in silico prediction of conformational B-cell epitopes would lead to major improvements in disease diagnostics, drug design and vaccine development. A variety of computational methods, mainly based on machine learning approaches, have been developed in the last decades to tackle this challenging problem. Here, we rigorously benchmarked nine state-of-the-art conformational B-cell epitope prediction webservers, including generic and antibody-specific methods, on a dataset of over 250 antibody-antigen structures. The results of our assessment and statistical analyses show that all the methods achieve very low performances, and some do not perform better than randomly generated patches of surface residues. In addition, we also found that commonly used consensus strategies that combine the results from multiple webservers are at best only marginally better than random. Finally, we applied all the predictors to the SARS-CoV-2 spike protein as an independent case study, and showed that they perform poorly in general, which largely recapitulates our benchmarking conclusions. We hope that these results will lead to greater caution when using these tools until the biases and issues that limit current methods have been addressed, promote the use of state-of-the-art evaluation methodologies in future publications and suggest new strategies to improve the performance of conformational B-cell epitope prediction methods.

Assessment of potassium ion channel during electric signalling in biofilm formation of Acinetobacter baumannii for finding antibiofilm molecule

Acinetobacter baumannii is an opportunistic ESKAPE pathogen which causes nosocomial infections and can produce biofilms that act as resistant determinants. The role of quorum sensing (chemical signaling) in biofilm establishment has already been studied extensively, but the existence of electrochemical signaling during biofilm formation by A. baumannii has not yet been investigated. The current study evaluated the presence of electrical signaling, types of ion channels involved, and their role in biofilm formation using spectroscopic and microbiological methods. The findings suggest that the potassium ion channel has a significant role in the electrical signaling during the biofilm formation by A. baumannii. Further, in-silico screening, molecular mechanics, and molecular dynamic simulation studies identify a potential lead, ZINC12496555(a specific inhibitor), which targets the potassium ion channel protein of A. baumannii. Mutational analysis of the interacting residues showed alterations in the unfolding rate of this protein after the selected mutation, which shows its role in the stability of this protein. It was also observed that identified lead has high antibiofilm activity, no human off-targets, and non-cytotoxicity to cell lines. Thus, identified lead against the potassium channel of A baumannii may be used as an effective therapeutic for the treatment of A. baumannii infections after further experimental validation.

The First Snake Venom KTS/Disintegrins-Integrin Interactions Using Bioinformatics Approaches

Snake venom contains a number of active molecules that have been shown to possess high anti-tumor activities; disintegrins are an excellent example among these. Their ability to interact and bind with integrins suggests that they could be very valuable molecules for the development of new cancer therapeutic approaches. However, in the absence of a clear Lysine-Threonine-Serine (KTS) Disintegrins Integrin interaction model, the exact compound features behind it are still unknown. In this study, we investigated the structural characteristics of three KTS-disintegrins and the interaction mechanisms with the α1β1 integrin receptor using in silico bioinformatics approaches. Normal mode analysis showed that the flexibility of the KTSR motif and the C-terminal region play a key role and influence the KTS-Disintegrin-integrin interaction. Protein-protein docking also suggested that the interaction involving the KTSR motif is highly dependent on the residue following K21, S23 and R24. These findings contribute to a better understanding of the KTS-Disintegrin-Integrin structural differences and their interactions with α1β1 receptors, which could improve the selection process of the best active molecules for antitumor therapies.

Bioinformatics in Plant Breeding and Research on Disease Resistance

In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance.

Salt Stress Tolerance in Casuarina glauca: Insights from the Branchlets Transcriptome

Climate change and the accelerated rate of population growth are imposing a progressive degradation of natural ecosystems worldwide. In this context, the use of pioneer trees represents a powerful approach to reverse the situation. Among others, N₂-fixing actinorhizal trees constitute important elements of plant communities and have been successfully used in land reclamation at a global scale. In this study, we have analyzed the transcriptome of the photosynthetic organs of Casuarina glauca (branchlets) to unravel the molecular mechanisms underlying salt stress tolerance. For that, C. glauca plants supplied either with chemical nitrogen (KNO₃⁺) or nodulated by Frankia (NOD⁺) were exposed to a gradient of salt concentrations (200, 400, and 600 mM NaCl) and RNA-Seq was performed. An average of ca. 25 million clean reads was obtained for each group of plants, corresponding to 86,202 unigenes. The patterns of differentially expressed genes (DEGs) clearly separate two groups: (i) control- and 200 mM NaCl-treated plants, and (ii) 400 and 600 mM NaCl-treated plants. Additionally, although the number of total transcripts was relatively high in both plant groups, the percentage of significant DEGs was very low, ranging from 6 (200 mM NaCl/NOD⁺) to 314 (600 mM NaCl/KNO₃⁺), mostly involving down-regulation. The vast majority of up-regulated genes was related to regulatory processes, reinforcing the hypothesis that some ecotypes of C. glauca have a strong stress-responsive system with an extensive set of constitutive defense mechanisms, complemented by a tight mechanism of transcriptional and post-transcriptional regulation. The results suggest that the robustness of the stress response system in C. glauca is regulated by a limited number of genes that tightly regulate detoxification and protein/enzyme stability, highlighting the complexity of the molecular interactions leading to salinity tolerance in this species.

Data Mining and Network Pharmacology Analysis of Kidney-Tonifying Herbs on the Treatment of Renal Osteodystrophy Based on the Theory of "Kidney Governing Bones" in Traditional Chinese Medicine

Background

Renal osteodystrophy (ROD) secondary to chronic kidney disease is closely associated with osteoporosis and fractures. Based on the theory of “kidney governing bones” in traditional Chinese medicine (TCM), treating bone diseases from the perspective of the kidney has become a basic principle of treating ROD. However, there are many kidney-tonifying herbs and their mechanisms of treating ROD are not clear. Therefore, our study intends to use data mining and network pharmacology to study the commonly used kidney-tonifying herbs, as well as their active ingredients and mechanisms of treating ROD.

Methods

We established a clinical ROD database by searching PubMed, CNKI, and other databases and screened out a core herbal combination of treating ROD. Furthermore, by using databases such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and GeneCards, we obtained active ingredients and targets of the core herbal combination and ROD targets. The STRING website and Cytoscape software were then used to obtain information on key active ingredients and key targets. Finally, we conducted GO and KEGG analyses using the Metascape website and molecular docking using the AutoDock Vina software.

Results

Our study eventually included 58 prescriptions and 116 herbs of treating ROD. Through data mining, we found that yin-yang-huo, du-zhong, and bu-gu-zhi (YDB) constituted a core herbal combination to treat ROD. Network pharmacology showed that YDB mainly acted on targets such as estrogen receptor alpha through active ingredients such as quercetin by mitogen-activated protein kinase and other signaling pathways.

Conclusion

Many ingredients, targets, and pathways are involved in the treatment of YDB for ROD. Specifically, the flavonoids contained in YDB have great potential for ROD treatment.

Molecular evolutionary analysis of the SHI/STY gene family in land plants: A focus on the Brassica species

The plant-specific SHORT INTERNODES/STYLISH (SHI/STY) proteins belong to a family of transcription factors that are involved in the formation and development of early lateral roots. However, the molecular evolution of this family is rarely reported. Here, a total of 195 SHI/STY genes were identified in 21 terrestrial plants, and the Brassica species is the focus of our research. Their physicochemical properties, chromosome location and duplication, motif distribution, exon-intron structures, genetic evolution, and expression patterns were systematically analyzed. These genes are divided into four clades (Clade 1/2/3/4) based on phylogenetic analysis. Motif distribution and gene structure are similar in each clade. SHI/STY proteins are localized in the nucleus by the prediction of subcellular localization. Collinearity analysis indicates that the SHI/STYs are relatively conserved in evolution. Whole-genome duplication is the main factor for their expansion. SHI/STYs have undergone intense purifying selection, but several positive selection sites are also identified. Most promoters of SHI/STY genes contain different types of cis-elements, such as light, stress, and hormone-responsive elements, suggesting that they may be involved in many biological processes. Protein-protein interaction predicted some important SHI/STY interacting proteins, such as LPAT4, MBOATs, PPR, and UBQ3. In addition, the RNA-seq and qRT-PCR analysis were studied in detail in rape. As a result, SHI/STYs are highly expressed in root and bud, and can be affected by Sclerotinia sclerotiorum, drought, cold, and heat stresses. Moreover, quantitative real-time PCR (qRT-PCR) analyses indicates that expression levels of BnSHI/STYs are significantly altered in different treatments (cold, salt, drought, IAA, auxin; ABA, abscisic acid; 6-BA, cytokinin). It provides a new understanding of the evolution and expansion of the SHI/STY family in land plants and lays a foundation for further research on their functions.

Potential of Mitochondrial Ribosomal Genes as Cancer Biomarkers Demonstrated by Bioinformatics Results

Next-generation sequencing and bioinformatics analyses have clearly revealed the roles of mitochondrial ribosomal genes in cancer development. Mitochondrial ribosomes are composed of three RNA components encoded by mitochondrial DNA and 82 specific protein components encoded by nuclear DNA. They synthesize mitochondrial inner membrane oxidative phosphorylation (OXPHOS)-related proteins and participate in various biological activities via the regulation of energy metabolism and apoptosis. Mitochondrial ribosomal genes are strongly associated with clinical features such as prognosis and foci metastasis in patients with cancer. Accordingly, mitochondrial ribosomes have become an important focus of cancer research. We review recent advances in bioinformatics research that have explored the link between mitochondrial ribosomes and cancer, with a focus on the potential of mitochondrial ribosomal genes as biomarkers in cancer.

Relating SARS-CoV-2 variants using cellular automata imaging

We classify the main variants of the SARS-CoV-2 virus representing a given biological sequence coded as a symbolic digital sequence and by its evolution by a cellular automata with a properly chosen rule. The spike protein, common to all variants of the SARS-CoV-2 virus, is then by the picture of the cellular automaton evolution yielding a visible representation of important features of the protein. We use information theory Hamming distance between different stages of the evolution of the cellular automaton for seven variants relative to the original Wuhan/China virus. We show that our approach allows to classify and group variants with common ancestors and same mutations. Although being a simpler method, it can be used as an alternative for building phylogenetic trees.

Metagenomic-Metabolomic Mining of Kinema, a Naturally Fermented Soybean Food of the Eastern Himalayas

Kinema is a popular sticky fermented soybean food of the Eastern Himalayan regions of North East India, east Nepal, and south Bhutan. We hypothesized that some dominant bacteria in kinema may contribute to the formation of targeted and non-targeted metabolites for health benefits; hence, we studied the microbiome-metabolite mining of kinema. A total of 1,394,094,912 bp with an average of 464,698,304 ± 120,720,392 bp was generated from kinema metagenome, which resulted in the identification of 47 phyla, 331 families, 709 genera, and 1,560 species. Bacteria (97.78%) were the most abundant domain with the remaining domains of viruses, eukaryote, and archaea. Firmicutes (93.36%) was the most abundant phylum with 280 species of Bacillus, among which Bacillus subtilis was the most dominant species in kinema followed by B. glycinifermentans, B. cereus, B. licheniformis, B. thermoamylovorans, B. coagulans, B. circulans, B. paralicheniformis, and Brevibacillus borstelensis. Predictive metabolic pathways revealed the abundance of genes associated with metabolism (60.66%), resulting in 216 sub-pathways. A total of 361 metabolites were identified by metabolomic analysis (liquid chromatography-mass spectrophotometry, LC-MS). The presence of metabolites, such as chrysin, swainsonine, and 3-hydroxy-L-kynurenine (anticancer activity) and benzimidazole (antimicrobial, anticancer, and anti-HIV activities), and compounds with immunomodulatory effects in kinema supports its therapeutic potential. The correlation between the abundant species of Bacillus and primary and secondary metabolites was constructed with a bivariate result. This study proves that Bacillus spp. contribute to the formation of many targeted and untargeted metabolites in kinema for health-promoting benefits.

DBHR: a collection of databases relevant to human research

BACKGROUND

The achievement of the human genome project provides a basis for the systematic study of the human genome from evolutionary history to disease-specific medicine. With the explosive growth of biological data, a growing number of biological databases are being established to support human-related research.

OBJECTIVE

The main objective of our study is to store, organize and share data in a structured and searchable manner. In short, we have planned the future development of new features in the database research area.

MATERIALS & METHODS

In total, we collected and integrated 680 human databases from scientific published work. Multiple options are presented for accessing the data, while original links and short descriptions are also presented for each database.

RESULTS & DISCUSSION

We have provided the latest collection of human research databases on a single platform with six categories: DNA database, RNA database, protein database, expression database, pathway database and disease database.

CONCLUSION

Taken together, our database will be useful for further human research study and will be modified over time. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://habdsk.org/database.php.

Computational analyses of mechanism of action (MoA): data, methods and integration

The elucidation of a compound's Mechanism of Action (MoA) is a challenging task in the drug discovery process, but it is important in order to rationalise phenotypic findings and to anticipate potential side-effects. Bioinformatic approaches, advances in machine learning techniques and the increasing deposition of high-throughput data in public databases have significantly contributed to recent advances in the field, but it is not straightforward to decide which data and methods are most suitable to use in a given case. In this review, we focus on these methods and data and their applications in generating MoA hypotheses for subsequent experimental validation. We discuss compound-specific data such as -omics, cell morphology and bioactivity data, as well as commonly used supplementary prior knowledge such as network and pathway data, and provide information on databases where this data can be accessed. In terms of methodologies, we discuss both well-established methods (connectivity mapping, pathway enrichment) as well as more developing methods (neural networks and multi-omics integration). Finally, we review case studies where the MoA of a compound was successfully suggested from computational analysis by incorporating multiple data modalities and/or methodologies. Our aim for this review is to provide researchers with insights into the benefits and drawbacks of both the data and methods in terms of level of understanding, biases and interpretation - and to highlight future avenues of investigation which we foresee will improve the field of MoA elucidation, including greater public access to -omics data and methodologies which are capable of data integration.

Inhibiting effect of miR-29 on proliferation and migration of uterine leiomyoma via the STAT3 signaling pathway

Aim: Uterine leiomyoma is the most common benign tumor of female genitalia, and the incidence is rising gradually. This study explores the mechanism of miR-29 and STAT3 signaling pathways on uterine leiomyoma.

Methods: GSE64763 and GSE5244 datasets were downloaded. Enrichment analyses were performed in GSE64763. PPI network was constructed, and the significant module was identified. Uterine leiomyoma cell lines were divided into NC, miR-29 mimic, anti-NC, and miR-29 inhibitor groups. Plate clone formation and Transwell assays detected the proliferation, invasion, and migration of cells. The expression levels of STAT3, proliferation, EMT, invasion-associated proteins were determined by Western blotting.

Results: Differently expressed genes were mainly enriched in positive regulation of cell migration and gene expression, cell proliferation. Through GSEA, JAK-STAT is a significantly correlated enrichment pathway. A Venn diagram was drawn to identify the common miRNA (miR-29-3p). miR-29 inhibitors promoted protein expression of STAT-3, Cyclin D1, and c-Myc compared with the anti-NC control (P < 0.01), and miR-29 inhibitors promoted cell proliferation in uterine leiomyoma cells (P < 0.05). Furthermore, miR-29 inhibitors promoted the protein expression of MMP-2 and MMP-9 (P < 0.01), and EMT promoting proteins N-cadherin, snail, vimentin, and Transwell assay showed that miR-29 inhibitors promoted cell migration in uterine leiomyoma (P < 0.01).

Conclusions: High expression of miR-29 could inhibit cell proliferation, invasion, and metastasis in uterine leiomyoma, which might be related to the inhibition of the STAT3 signaling pathway, and could provide a novel target for the treatment of uterine leiomyoma.

E3 ligases: a potential multi-drug target for different types of cancers and neurological disorders

Ubiquitylation is a posttranslational modification of proteins that is necessary for a variety of cellular processes. E1 ubiquitin activating enzyme, E2 ubiquitin conjugating enzyme, and E3 ubiquitin ligase are all involved in transferring ubiquitin to the target substrate to regulate cellular function. The objective of this review is to provide an overview of different aspects of E3 ubiquitin ligases that can lead to major biological system failure in several deadly diseases. The first part of this review covers the important characteristics of E3 ubiquitin ligases and their classification based on structural domains. Further, the authors provide some online resources that help researchers explore the data relevant to the enzyme. The following section delves into the involvement of E3 ubiquitin ligases in various diseases and biological processes, including different types of cancer and neurological disorders.

Enhancing the Discovery of Functional Post-Translational Modification Sites with Machine Learning Models - Development, Validation, and Interpretation

Protein posttranslational modifications (PTMs) are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof, the number of functionals PTMs in the eukaryotic proteome is currently underestimated. Furthermore, not all PTMs are functionally equivalent. Computational approaches that can confidently recommend PTMs of probable function can improve the heuristics of PTM investigation and alleviate these problems. To address this need, we developed SAPH-ire: a multifeature heuristic neural network model that takes community wisdom into account by recommending experimental PTMs similar to those which have previously been established as having regulatory impact. Here, we describe the principle behind the SAPH-ire model, how it is developed, how we evaluate its performance, and important caveats to consider when building and interpreting such models. Finally, we discus current limitations of functional PTM prediction models and highlight potential mechanisms for their improvement.

In vitro and in silico analysis reveals antifungal activity and potential targets of curcumin on Paracoccidioides spp

The search for new compounds with activity against Paracoccidioides, etiologic agents of Paracoccidioidomycosis (PCM), is extremely necessary due to the current scenario of the available therapeutic arsenal. Treatment is restricted to three classes of antifungals with side effects. Curcumin is a polyphenol with antifungal effects that is extracted from Curcuma longa. The present work aimed to evaluate the activity of curcumin in different species of Paracoccidioides and to evaluate the potential molecular targets of curcumin using computational strategies. In addition, interactions with classic antifungals used in the treatment of PCM were evaluated. Curcumin inhibits the growth of Paracoccidioides spp. exerting a fungicidal effect. The combination of curcumin with amphotericin B, co-trimoxazole, and itraconazole showed a synergistic or additive interaction. Molecular targets as superoxide dismutase, catalase, and isocitrate lyase were proposed based on in silico approaches. Curcumin affects the fungal plasma membrane and increases the production of reactive oxygen species. Therefore, curcumin is a good alternative for the treatment of PCM.

Genome-scale protein interaction network construction and topology analysis of functional hypothetical proteins in Helicobacter pylori divulges novel therapeutic targets

The emergence and spread of multi-drug resistance among Helicobacter pylori (H. pylori) strain raise more stakes for genetic research for discovering new drugs. The quantity of uncharacterized hypothetical proteins in the genome may provide an opportunity to explore their property and promulgation could act as a platform for designing the drugs, making them an intriguing genetic target. In this context, the present study aims to identify the key hypothetical proteins (HPs) and their biological regulatory processes in H. pylori. This investigation could provide a foundation to establish the molecular connectivity among the pathways using topological analysis of the protein interaction networks (PINs). The giant network derived from the extended network has 374 nodes connected via 925 edges. A total of 43 proteins with high betweenness centrality (BC), 54 proteins with a large degree, and 23 proteins with high BC and large degrees have been identified. HP 1479, HP 0056, HP 1481, HP 1021, HP 0043, HP 1019, gmd, flgA, HP 0472, HP 1486, HP 1478, and HP 1473 are categorized as hub nodes because they have a higher number of direct connections and are potentially more important in understanding HP's molecular interactions. The pathway enrichment analysis of the network clusters revealed significant involvement of HPs in pathways such as flagellar assembly, bacterial chemotaxis and lipopolysaccharide biosynthesis. This comprehensive computational study revealed HP's functional role and its druggability characteristics, which could be useful in the development of drugs to combat H. pylori infections.

Exposure to an Environmental Mixture of Polycyclic Aromatic Hydrocarbons Induces Hepatic Cytochrome P450 Enzymes in Mice

Cytochrome P450 enzymes (CYPs) play an important role in bioactivating or detoxifying polycyclic aromatic hydrocarbons (PAHs), common environmental contaminants. While it is widely accepted that exposure to PAHs induces CYPs, effectively increasing rates of xenobiotic metabolism, dose- and time-response patterns of CYP induction are not well-known. In order to better understand dose- and time-response relationships of individual CYPs following induction, we exposed B6129SF1/J mice to single or repeated doses (2-180 μmol/kg/d) of benzo[a]pyrene (BaP) or Supermix-10, a mixture of the top 10 most abundant PAHs found at the Portland Harbor Superfund Site. In hepatic microsomes from exposed mice, we measured amounts of active CYPs using activity-based protein profiling and total CYP expression using global proteomics. We observed rapid Cyp1a1 induction after 6 h at the lowest PAH exposures and broad induction of many CYPs after 3 daily PAH doses at 72 h following the first dose. Using samples displaying Cyp1a1 induction, we observed significantly higher metabolic affinity for BaP metabolism (K_m reduced 3-fold), 3-fold higher intrinsic clearance, but no changes to the V_max. Mice dosed with the highest PAH exposures exhibited 1.7-5-fold higher intrinsic clearance rates for BaP compared to controls and higher V_max values indicating greater amounts of enzymes capable of metabolizing BaP. This study demonstrates exposure to PAHs found at superfund sites induces enzymes in dose- and time-dependent patterns in mice. Accounting for specific changes in enzyme profiles, relative rates of PAH bioactivation and detoxification, and resulting risk will help translate internal dosimetry of animal models to humans and improve risk assessments of PAHs at superfund sites.

Peptidomics and proteogenomics: background, challenges and future needs

INTRODUCTION

With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development.

AREAS COVERED

Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date.

EXPERT OPINION

This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.

Trends and Applications of Omics Technologies to Functional Characterisation of Enzymes and Protein Metabolites Produced by Fungi

Identifying and adopting industrial applications for proteins and enzymes derived from fungi strains have been at the focal point of several studies in recent times. To facilitate such studies, it is necessary that advancements and innovation in mycological and molecular characterisation are concomitant. This review aims to provide a detailed overview of the necessary steps employed in both qualitative and quantitative research using the omics technologies that are pertinent to fungi characterisation. This stems from the understanding that data provided from the functional characterisation of fungi and their metabolites is important towards the techno-economic feasibility of large-scale production of biological products. The review further describes how the functional gaps left by genomics, internal transcribe spacer (ITS) regions are addressed by transcriptomics and the various techniques and platforms utilised, including quantitive reverse transcription polymerase chain reaction (RT-qPCR), hybridisation techniques, and RNA-seq, and the insights such data provide on the effect of environmental changes on fungal enzyme production from an expressional standpoint. The review also offers information on the many available bioinformatics tools of analysis necessary for the analysis of the overwhelming data synonymous with the omics approach to fungal characterisation.

Evolution of Toll, Spatzle and MyD88 in insects: the problem of the Diptera bias

BACKGROUND

Arthropoda, the most numerous and diverse metazoan phylum, has species in many habitats where they encounter various microorganisms and, as a result, mechanisms for pathogen recognition and elimination have evolved. The Toll pathway, involved in the innate immune system, was first described as part of the developmental pathway for dorsal-ventral differentiation in Drosophila. Its later discovery in vertebrates suggested that this system was extremely conserved. However, there is variation in presence/absence, copy number and sequence divergence in various genes along the pathway. As most studies have only focused on Diptera, for a comprehensive and accurate homology-based approach it is important to understand gene function in a number of different species and, in a group as diverse as insects, the use of species belonging to different taxonomic groups is essential.

RESULTS

We evaluated the diversity of Toll pathway gene families in 39 Arthropod genomes, encompassing 13 different Insect Orders. Through computational methods, we shed some light into the evolution and functional annotation of protein families involved in the Toll pathway innate immune response. Our data indicates that: 1) intracellular proteins of the Toll pathway show mostly species-specific expansions; 2) the different Toll subfamilies seem to have distinct evolutionary backgrounds; 3) patterns of gene expansion observed in the Toll phylogenetic tree indicate that homology based methods of functional inference might not be accurate for some subfamilies; 4) Spatzle subfamilies are highly divergent and also pose a problem for homology based inference; 5) Spatzle subfamilies should not be analyzed together in the same phylogenetic framework; 6) network analyses seem to be a good first step in inferring functional groups in these cases. We specifically show that understanding Drosophila's Toll functions might not indicate the same function in other species.

CONCLUSIONS

Our results show the importance of using species representing the different orders to better understand insect gene content, origin and evolution. More specifically, in intracellular Toll pathway gene families the presence of orthologues has important implications for homology based functional inference. Also, the different evolutionary backgrounds of Toll gene subfamilies should be taken into consideration when functional studies are performed, especially for TOLL9, TOLL, TOLL2_7, and the new TOLL10 clade. The presence of Diptera specific clades or the ones lacking Diptera species show the importance of overcoming the Diptera bias when performing functional characterization of Toll pathways.

Sex-linked gene expression and the emergence of hermaphrodites in Carica papaya

PREMISE

One evolutionary path from hermaphroditism to dioecy is via a gynodioecious intermediate. The evolution of dioecy may also coincide with the formation of sex chromosomes that possess sex-determining loci that are physically linked in a region of suppressed recombination. Dioecious papaya (Carica papaya) has an XY chromosome system, where the presence of a Y chromosome determines maleness. However, in cultivation, papaya is gynodioecious, due to the conversion of the male Y chromosome to a hermaphroditic Y^h chromosome during its domestication.

METHODS

We investigated gene expression linked to the X, Y, and Y^h chromosomes at different floral developmental stages to identify differentially expressed genes that may be involved in the sexual transition of males to hermaphrodites.

RESULTS

We identified 309 sex-biased genes found on the sex chromosomes, most of which are found in the pseudoautosomal regions. Female (XX) expression in the sex-determining region was almost double that of X-linked expression in males (XY) and hermaphrodites (XY^h ), which rules out dosage compensation for most sex-linked genes; although, an analysis of hemizygous X-linked loci found evidence of partial dosage compensation. Furthermore, we identified a candidate gene associated with sex determination and the transition to hermaphroditism, a homolog of the MADS-box protein SHORT VEGETATIVE PHASE.

CONCLUSIONS

We identified a pattern of partial dosage compensation for hemizygous genes located in the papaya sex-determining region. Furthermore, we propose that loss-of-expression of the Y-linked SHORT VEGETATIVE PHASE homolog facilitated the transition from males to hermaphrodites in papaya.

An overview of graph databases and their applications in the biomedical domain

Over the past couple of decades, the explosion of densely interconnected data has stimulated the research, development and adoption of graph database technologies. From early graph models to more recent native graph databases, the landscape of implementations has evolved to cover enterprise-ready requirements. Because of the interconnected nature of its data, the biomedical domain has been one of the early adopters of graph databases, enabling more natural representation models and better data integration workflows, exploration and analysis facilities. In this work, we survey the literature to explore the evolution, performance and how the most recent graph database solutions are applied in the biomedical domain, compiling a great variety of use cases. With this evidence, we conclude that the available graph database management systems are fit to support data-intensive, integrative applications, targeted at both basic research and exploratory tasks closer to the clinic.

Analysis of aqueous humor total antioxidant capacity and its correlation with corneal endothelial health

Corneal endothelial decompensation is a serious condition that frequently requires treatment via corneal transplantation which contributes to a global shortage in donor corneas. Therefore, the purpose of this study was to analyze the influence of aqueous humor total antioxidant capacity (TAC) on corneal endothelial health. There is an urgent need for discovering protective factors to combat corneal endothelial cell (CEC) loss. For methods, we developed a cupric ion-based TAC (CuTAC) assay to analyze TAC level in a small volume of aqueous humor, that is, 10 μL per test, and examined the influences of ascorbic acid (AA) and antioxidant proteins on aqueous humor TAC. To broaden the investigation, we conducted a case-control study with patients classified into two groups, an insufficient endothelial cell density (ECD < 2100 cells/mm2) group, and a control group. These groups were formed based on baseline ECD values and were used to evaluate the influence of aqueous humor TAC and AA on overall corneal endothelial health. A CuTAC assay was used to accurately measure aqueous humor TAC without the need for sample dilution. After analyzing a total of 164 human aqueous humor samples, we found that AA was the major contributor to aqueous humor TAC (73.2%). In addition, TAC and AA levels in the IECD and control groups were both found to be significantly different (1.168 vs. 1.592 mM, p = 0.009 and 0.856 vs. 1.178 mM, p = 0.016). TAC and AA were considered independent protective factors against IECD with adjusted odds ratios of 0.02 (p = 0.017) and 0.023 (p = 0.033), respectively. In conclusion, aqueous humor TAC and AA contribute to the maintenance of sufficient corneal ECD, and our CuTAC assay can be a useful tool for analyzing TAC using only a small aqueous humor sample volume.

Reverse vaccinology and subtractive genomics approaches for identifying common therapeutics against Mycobacterium leprae and Mycobacterium lepromatosis

BACKGROUND

Mycobacterium leprae and Mycobacterium lepromatosis are gram-positive bacterial pathogens and the causative agents of leprosy in humans across the world. The elimination of leprosy cannot be achieved by multidrug therapy alone, and highlights the need for new tools and drugs to prevent the emergence of new resistant strains.

METHODS

In this study, our contribution includes the prediction of vaccine targets and new putative drugs against leprosy, using reverse vaccinology and subtractive genomics. Six strains of Mycobacterium leprae and Mycobacterium lepromatosis (4 and 2 strains, respectively) were used for comparison taking Mycobacterium leprae strain TN as the reference genome. Briefly, we used a combined reverse vaccinology and subtractive genomics approach.

RESULTS

As a result, we identified 12 common putative antigenic proteins as vaccine targets and three common drug targets against Mycobacterium leprae and Mycobacterium lepromatosis. Furthermore, the docking analysis using 28 natural compounds with three drug targets was done.

CONCLUSIONS

The bis-naphthoquinone compound Diospyrin (CID 308140) obtained from indigenous plant Diospyros spp. showed the most favored binding affinity against predicted drug targets, which can be a candidate therapeutic target in the future against leprosy.

Protein phylogenetics with mass spectrometry. A comparison of methods

Advances in protein mass spectrometry have provided the ability to identify and sequence proteins with unprecedented speed, sensitivity and accuracy. These benefits now offer advantages for studies of protein evolution and phylogeny avoiding the need to generate and align DNA sequences which can prove time consuming, costly and difficult in the case of large genomes and for highly diverse organisms. The methods of phylogenetic analysis using protein mass spectrometry can be classified into three categories: (1) de novo protein sequencing followed by multiple sequence alignment for classical phylogenetic reconstruction, (2) direct phylogenetic reconstruction using expressed protein mass profiles exploited in microbial biotyping applications, and (3) the construction of trees using proteolytic peptide mass map or fingerprint data. This review describes the three approaches together with the relevant tools and algorithms required to implement them. It also compares each of these alternative protein based methods alongside conventional gene sequence based phylogenetics.

Transcriptional host-pathogen responses of Pseudogymnoascus destructans and three species of bats with white-nose syndrome

Understanding how context (e.g., host species, environmental conditions) drives disease susceptibility is an essential goal of disease ecology. We hypothesized that in bat white-nose syndrome (WNS), species-specific host-pathogen interactions may partly explain varying disease outcomes among host species. We characterized bat and pathogen transcriptomes in paired samples of lesion-positive and lesion-negative wing tissue from bats infected with Pseudogymnoascus destructans in three parallel experiments. The first two experiments analyzed samples collected from the susceptible Nearctic Myotis lucifugus and the less-susceptible Nearctic Eptesicus fuscus, following experimental infection and hibernation in captivity under controlled conditions. The third experiment applied the same analyses to paired samples from infected, free-ranging Myotis myotis, a less susceptible, Palearctic species, following natural infection and hibernation (n = 8 sample pairs/species). Gene expression by P. destructans was similar among the three host species despite varying environmental conditions among the three experiments and was similar within each host species between saprophytic contexts (superficial growth on wings) and pathogenic contexts (growth in lesions on the same wings). In contrast, we observed qualitative variation in host response: M. lucifugus and M. myotis exhibited systemic responses to infection, while E. fuscus up-regulated a remarkably localized response. Our results suggest potential phylogenetic determinants of response to WNS and can inform further studies of context-dependent host-pathogen interactions.

Comparative Genomics of Pathogenic Clavibacter michiganensis subsp. michiganensis Strains from Chile Reveals Potential Virulence Features for Tomato Plants

The genus Clavibacter has been associated largely with plant diseases. The aims of this study were to characterize the genomes and the virulence factors of Chilean C. michiganensis subsp. michiganensis strains VL527, MSF322 and OP3, and to define their phylogenomic positions within the species, Clavibacter michiganensis. VL527 and MSF322 genomes possess 3,396,632 and 3,399,199 bp, respectively, with a pCM2-like plasmid in strain VL527, with pCM1- and pCM2-like plasmids in strain MSF322. OP3 genome is composed of a chromosome and three plasmids (including pCM1- and pCM2-like plasmids) of 3,466,104 bp. Genomic analyses confirmed the phylogenetic relationships of the Chilean strains among C.michiganensis subsp. michiganensis and showed their low genomic diversity. Different virulence levels in tomato plants were observable. Phylogenetic analyses of the virulence factors revealed that the pelA1 gene (chp/tomA region)—that grouped Chilean strains in three distinct clusters—and proteases and hydrolases encoding genes, exclusive for each of the Chilean strains, may be involved in these observed virulence levels. Based on genomic similarity (ANIm) analyses, a proposal to combine and reclassify C. michiganensis subsp. phaseoli and subsp. chilensis at the species level, as C. phaseoli sp. nov., as well as to reclassify C. michiganensis subsp. californiensis as the species C. californiensis sp. nov. may be justified.

Binding Mode Exploration of B1 Receptor Antagonists' by the Use of Molecular Dynamics and Docking Simulation-How Different Target Engagement Can Determine Different Biological Effects

The kinin B1 receptor plays a critical role in the chronic phase of pain and inflammation. The development of B1 antagonists peaked in recent years but almost all promising molecules failed in clinical trials. Little is known about these molecules' mechanisms of action and additional information will be necessary to exploit the potential of the B1 receptor. With the aim of contributing to the available knowledge of the pharmacology of B1 receptors, we designed and characterized a novel class of allosteric non-peptidic inhibitors with peculiar binding characteristics. Here, we report the binding mode analysis and pharmacological characterization of a new allosteric B1 antagonist, DFL20656. We analyzed the binding of DFL20656 by single point mutagenesis and radioligand binding assays and we further characterized its pharmacology in terms of IC₅₀, B1 receptor internalization and in vivo activity in comparison with different known B1 antagonists. We highlighted how different binding modes of DFL20656 and a Merck compound (compound 14) within the same molecular pocket can affect the biological and pharmacological properties of B1 inhibitors. DFL20656, by its peculiar binding mode, involving tight interactions with N114, efficiently induced B1 receptor internalization and evoked a long-lasting effect in an in vivo model of neuropathic pain. The pharmacological characterization of different B1 antagonists highlighted the effects of their binding modes on activity, receptor occupancy and internalization. Our results suggest that part of the failure of most B1 inhibitors could be ascribed to a lack of knowledge about target function and engagement.

Protein acetylation and deacetylation: An important regulatory modification in gene transcription (Review)

Cells primarily rely on proteins to perform the majority of their physiological functions, and the function of proteins is regulated by post-translational modifications (PTMs). The acetylation of proteins is a dynamic and highly specific PTM, which has an important influence on the functions of proteins, such as gene transcription and signal transduction. The acetylation of proteins is primarily dependent on lysine acetyltransferases and lysine deacetylases. In recent years, due to the widespread use of mass spectrometry and the emergence of new technologies, such as protein chips, studies on protein acetylation have been further developed. Compared with histone acetylation, acetylation of non-histone proteins has gradually become the focus of research due to its important regulatory mechanisms and wide range of applications. The discovery of specific protein acetylation sites using bioinformatic tools can greatly aid the understanding of the underlying mechanisms of protein acetylation involved in related physiological and pathological processes.

Reclassification of the Taxonomic Framework of Orders Cellvibrionales, Oceanospirillales, Pseudomonadales, and Alteromonadales in Class Gammaproteobacteria through Phylogenomic Tree Analysis

Orders Oceanospirillales and Pseudomonadales play important roles in various ecosystems as the keystone taxa of microbiomes. However, the two orders present a close evolutionary relationship, which might have caused taxonomic misinterpretation and resulted in an incorrect understanding of their evolutionary history. In this study, first, we used the 16S rRNA gene sequences of 2,049 species of Gammaproteobacteria to build a phylogenetic tree, which demonstrated that reports regarding the evolutionary relationship of orders Cellvibrionales, Oceanospirillales, and Pseudomonadales based on a single conserved gene with a poor resolution have been conflicting; in particular, the major families Moraxellaceae and Pseudomonadaceae of order Pseudomonadales were separated from orders Cellvibrionales and Oceanospirillales Subsequently, we constructed the bac120 trees of all representative reference genomes of class Gammaproteobacteria based on 120 ubiquitous single-copy proteins from bacteria and a phylogenomic tree based on the 119 core genes of 257 reference genomes obtained from orders Cellvibrionales, Oceanospirillales, and Pseudomonadales to cross validate and infer their intrinsic evolutionary relationships. These results indicated that two novel orders, Moraxellales ord. nov. and Kangiellales ord. nov., and three novel families, Marinobacteraceae fam. nov., Perlucidibacaceae fam. nov., and Zooshikellaceae fam. nov., should be proposed. Additionally, orders Cellvibrionales and Oceanospirillales were merged into the order Pseudomonadales except for families Moraxellaceae and Kangiellaceae in class Gammaproteobacteria, which currently includes 18 families. Our work sheds some light on the evolutionary history of class Gammaproteobacteria, which could facilitate the detection and taxonomic analysis of natural communities.IMPORTANCE The orders Cellvibrionales, Oceanospirillales, and Pseudomonadales, as three major orders of the largest bacterial class, Gammaproteobacteria, play important roles in various ecosystems as the keystone taxa of microbiomes, but their evolutionary relationship is currently polyphyletic and chaotic. Here, we constructed a bac120 tree and core-genome tree and calculated the amino acid identity (AAI) value to explore their intrinsic evolutionary history. In this study, we proposed two novel orders and three novel families. This evolution study vastly reconstructed the taxonomic framework of class Gammaproteobacteria and could provide a more distinct perspective on global distribution and evolutionary patterns of these environmental microorganisms.

Comparative analysis of genome-wide DNA methylation in Neurospora

DNA methylation is an epigenetic mark that plays an important role in genetic regulation in eukaryotes. Major progress has been made in dissecting the molecular pathways that regulate DNA methylation. Yet, little is known about DNA methylation variation over evolutionary time. Here we present an investigation of the variation of DNA methylation and transposable element (TE) content in species of the filamentous ascomycetes Neurospora. We generated genome-wide DNA methylation data at single-base resolution, together with genomic TE content and gene expression data, of 10 individuals representing five closely related Neurospora species. We found that the methylation levels were low (ranging from 1.3% to 2.5%) and varied among the genomes in a species-specific way. Furthermore, we found that the TEs over 400 bp long were targeted by DNA methylation, and in all genomes, high methylation correlated with low GC, confirming a conserved link between DNA methylation and Repeat Induced Point (RIP) mutations in this group of fungi. Both TE content and DNA methylation pattern showed phylogenetic signal, and the species with the highest TE load (N. crassa) also exhibited the highest methylation level per TE. Our results suggest that DNA methylation is an evolvable trait and indicate that the genomes of Neurospora are shaped by an evolutionary arms race between TEs and host defence.