Cytoscape stringApp 2.0: Analysis and Visualization of Heterogeneous Biological Networks

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

Interrogation of RNA-protein interaction dynamics in bacterial growth

Characterising RNA-protein interaction dynamics is fundamental to understand how bacteria respond to their environment. In this study, we have analysed the dynamics of 91% of the Escherichia coli expressed proteome and the RNA-interaction properties of 271 RNA-binding proteins (RBPs) at different growth phases. We find that 68% of RBPs differentially bind RNA across growth phases and characterise 17 previously unannotated proteins as bacterial RBPs including YfiF, a ncRNA-binding protein. While these new RBPs are mostly present in Proteobacteria, two of them are orthologs of human mitochondrial proteins associated with rare metabolic disorders. Moreover, we reveal novel RBP functions for proteins such as the chaperone HtpG, a new stationary phase tRNA-binding protein. For the first time, the dynamics of the bacterial RBPome have been interrogated, showcasing how this approach can reveal the function of uncharacterised proteins and identify critical RNA-protein interactions for cell growth which could inform new antimicrobial therapies.

The RBPome of influenza A virus NP-mRNA reveals a role for TDP-43 in viral replication

Genome-wide approaches have significantly advanced our knowledge of the repertoire of RNA-binding proteins (RBPs) that associate with cellular polyadenylated mRNAs within eukaryotic cells. Recent studies focusing on the RBP interactomes of viral mRNAs, notably SARS-Cov-2, have revealed both similarities and differences between the RBP profiles of viral and cellular mRNAs. However, the RBPome of influenza virus mRNAs remains unexplored. Herein, we identify RBPs that associate with the viral mRNA encoding the nucleoprotein (NP) of an influenza A virus. Focusing on TDP-43, we show that it binds several influenza mRNAs beyond the NP-mRNA, and that its depletion results in lower levels of viral mRNAs and proteins within infected cells, and a decreased yield of infectious viral particles. We provide evidence that the viral polymerase recruits TDP-43 onto viral mRNAs through a direct interaction with the disordered C-terminal domain of TDP-43. Notably, other RBPs found to be associated with influenza virus mRNAs also interact with the viral polymerase, which points to a role of the polymerase in orchestrating the assembly of viral messenger ribonucleoproteins.

OPA1 mutation affects autophagy and triggers senescence in autosomal dominant optic atrophy plus fibroblasts

In several cases of mitochondrial diseases, the underlying genetic and bioenergetic causes of reduced oxidative phosphorylation (OxPhos) in mitochondrial dysfunction are well understood. However, there is still limited knowledge about the specific cellular outcomes and factors involved for each gene and mutation, which contributes to the lack of effective treatments for these disorders. This study focused on fibroblasts from a patient with Autosomal Dominant Optic Atrophy (ADOA) plus syndrome harboring a mutation in the Optic Atrophy 1 (OPA1) gene. By combining functional and transcriptomic approaches, we investigated the mitochondrial function and identified cellular phenotypes associated with the disease. Our findings revealed that fibroblasts with the OPA1 mutation exhibited a disrupted mitochondrial network and function, leading to altered mitochondrial dynamics and reduced autophagic response. Additionally, we observed a premature senescence phenotype in these cells, suggesting a previously unexplored role of the OPA1 gene in inducing senescence in ADOA plus patients. This study provides novel insights into the mechanisms underlying mitochondrial dysfunction in ADOA plus and highlights the potential importance of senescence in disease progression.

Transcriptomic analysis reveals sex-specific patterns in the hippocampus in Alzheimer's disease

Background

The hippocampus, vital for memory and learning, is among the first brain regions affected in Alzheimer's Disease (AD) and exhibits adult neurogenesis. Women face twice the risk of developing AD compare to men, making it crucial to understand sex differences in hippocampal function for comprehending AD susceptibility.

Methods

We conducted a comprehensive analysis of bulk mRNA postmortem samples from the whole hippocampus (GSE48350, GSE5281) and its CA1 and CA3 subfields (GSE29378). Our aim was to perform a comparative molecular signatures analysis, investigating sex-specific differences and similarities in the hippocampus and its subfields in AD. This involved comparing the gene expression profiles among: (a) male controls (M-controls) vs. female controls (F-controls), (b) females with AD (F-AD) vs. F-controls, (c) males with AD (M-AD) vs. M-controls, and (d) M-AD vs. F-AD. Furthermore, we identified AD susceptibility genes interacting with key targets of menopause hormone replacement drugs, specifically the ESR1 and ESR2 genes, along with GPER1.

Results

The hippocampal analysis revealed contrasting patterns between M-AD vs. M-controls and F-AD vs. F-controls, as well as M-controls vs. F-controls. Notably, BACE1, a key enzyme linked to amyloid-beta production in AD pathology, was found to be upregulated in M-controls compared to F-controls in both CA1 and CA3 hippocampal subfields. In M-AD vs. M-controls, the GABAergic synapse was downregulated, and the Estrogen signaling pathway was upregulated in both subfields, unlike in F-AD vs. F-controls. Analysis of the whole hippocampus also revealed upregulation of the GABAergic synapse in F-AD vs. F-controls. While direct comparison of M-AD vs. F-AD, revealed a small upregulation of the ESR1 gene in the CA1 subfield of males. Conversely, F-AD vs. F-controls exhibited downregulation of the Dopaminergic synapse in both subfields, while the Calcium signaling pathway showed mixed regulation, being upregulated in CA1 but downregulated in CA3, unlike in M-AD vs. M-controls. The upregulated Estrogen signaling pathway in M-AD, suggests a compensatory response to neurodegenerative specifically in males with AD. Our results also identified potential susceptibility genes interacting with ESR1 and ESR2, including MAPK1, IGF1, AKT1, TP53 and CD44.

Conclusion

These findings underscore the importance of sex-specific disease mechanisms in AD pathogenesis. Region-specific analysis offers a more detailed examination of localized changes in the hippocampus, enabling to capture sex-specific molecular patterns in AD susceptibility and progression.

Studying the O-GlcNAcome of human placentas using banked tissue samples

O-GlcNAcylation is a dynamic modulator of signaling pathways, equal in magnitude to the widely studied phosphorylation. With the rapid development of tools for its detection at the single protein level, the O-GlcNAc modification rapidly emerged as a novel diagnostic and therapeutic target in human diseases. Yet, mapping the human O-GlcNAcome in various tissues is essential for generating relevant biomarkers. In this study, we used human banked tissue as a sample source to identify O-GlcNAcylated protein targets relevant to human diseases. Using human term placentas, we propose (1) a method to clean frozen banked tissue of blood proteins; (2) an optimized protocol for the enrichment of O-GlcNAcylated proteins using immunoaffinity purification; and (3) a bioinformatic workflow to identify the most promising O-GlcNAc targets. As a proof-of-concept, we used 45 mg of banked placental samples from two pregnancies to generate intracellular protein extracts depleted of blood protein. Then, antibody-based O-GlcNAc enrichment on denatured samples yielded over 2000 unique HexNAc PSMs and 900 unique sites using 300 μg of protein lysate. Due to efficient sample cleanup, we also captured 82 HexNAc proteins with high placental expression. Finally, we provide a bioinformatic tool (CytOVS) to sort the HexNAc proteins based on their cellular localization and extract the most promising O-GlcNAc targets to explore further. To conclude, we provide a simple 3-step workflow to generate a manageable list of O-GlcNAc proteins from human tissue and improve our understanding of O-GlcNAcylation's role in health and diseases.

Nonlinear DNA methylation trajectories in aging male mice

Although DNA methylation data yields highly accurate age predictors, little is known about the dynamics of this quintessential epigenomic biomarker during lifespan. To narrow the gap, we investigate the methylation trajectories of male mouse colon at five different time points of aging. Our study indicates the existence of sudden hypermethylation events at specific stages of life. Precisely, we identify two epigenomic switches during early-to-midlife (3-9 months) and mid-to-late-life (15-24 months) transitions, separating the rodents' life into three stages. These nonlinear methylation dynamics predominantly affect genes associated with the nervous system and enrich in bivalently marked chromatin regions. Based on groups of nonlinearly modified loci, we construct a clock-like classifier STageR (STage of aging estimatoR) that accurately predicts murine epigenetic stage. We demonstrate the universality of our clock in an independent mouse cohort and with publicly available datasets.

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies.

METHODS

This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications.

RESULTS

We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets.

CONCLUSIONS

Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.

Identifying Candidate Polyphenols Beneficial for Oxidative Liver Injury through Multiscale Network Analysis

Oxidative stress, a driver of liver pathology, remains a challenge in clinical management, necessitating innovative approaches. In this research, we delved into the therapeutic potential of polyphenols for oxidative liver injury using a multiscale network analysis framework. From the Phenol-Explorer database, we curated a list of polyphenols along with their corresponding PubChem IDs. Verified target information was then collated from multiple databases. We subsequently measured the propagative effects of these compounds and prioritized a ranking based on their correlation scores for oxidative liver injury. This result underwent evaluation to discern its effectiveness in differentiating between known and unknown polyphenols, demonstrating superior performance over chance level in distinguishing these compounds. We found that lariciresinol and isopimpinellin yielded high correlation scores in relation to oxidative liver injury without reported evidence. By analyzing the impact on a multiscale network, we found that lariciresinol and isopimpinellin were predicted to offer beneficial effects on the disease by directly acting on targets such as CASP3, NR1I2, and CYP3A4 or by modulating biological functions related to the apoptotic process and oxidative stress. This study not only corroborates the efficacy of identified polyphenols in liver health but also opens avenues for future investigations into their mechanistic actions.

Mitochondrial and Nuclear DNA Variants in Amyotrophic Lateral Sclerosis: Enrichment in the Mitochondrial Control Region and Sirtuin Pathway Genes in Spinal Cord Tissue

Amyotrophic Lateral Sclerosis (ALS) is a progressive disease with prevalent mitochondrial dysfunctions affecting both upper and lower motor neurons in the motor cortex, brainstem, and spinal cord. Despite mitochondria having their own genome (mtDNA), in humans, most mitochondrial genes are encoded by the nuclear genome (nDNA). Our study aimed to simultaneously screen for nDNA and mtDNA genomes to assess for specific variant enrichment in ALS compared to control tissues. Here, we analysed whole exome (WES) and whole genome (WGS) sequencing data from spinal cord tissues, respectively, of 6 and 12 human donors. A total of 31,257 and 301,241 variants in nuclear-encoded mitochondrial genes were identified from WES and WGS, respectively, while mtDNA reads accounted for 73 and 332 variants. Despite technical differences, both datasets consistently revealed a specific enrichment of variants in the mitochondrial Control Region (CR) and in several of these genes directly associated with mitochondrial dynamics or with Sirtuin pathway genes within ALS tissues. Overall, our data support the hypothesis of a variant burden in specific genes, highlighting potential actionable targets for therapeutic interventions in ALS.

Genome-wide analysis of the KNOX gene family in Moso bamboo: insights into their role in promoting the rapid shoot growth

BACKGROUND

KNOTTED1-like homeobox (KNOX) genes, plant-specific homologous box transcription factors (TFs), play a central role in regulating plant growth, development, organ formation, and response to biotic and abiotic stresses. However, a comprehensive genome-wide identification of the KNOX genes in Moso bamboo (Phyllostachys edulis), the fastest growing plant, has not yet been conducted, and the specific biological functions of this family remain unknown.

RESULTS

The expression profiles of 24 KNOX genes, divided into two subfamilies, were determined by integrating Moso bamboo genome and its transcriptional data. The KNOX gene promoters were found to contain several light and stress-related cis-acting elements. Synteny analysis revealed stronger similarity with rice KNOX genes than with Arabidopsis KNOX genes. Additionally, several conserved structural domains and motifs were identified in the KNOX proteins. The expansion of the KNOX gene family was primarily regulated by tandem duplications. Furthermore, the KNOX genes were responsive to naphthaleneacetic acid (NAA) and gibberellin (GA) hormones, exhibiting distinct temporal expression patterns in four different organs of Moso bamboo. Short Time-series Expression Miner (STEM) analysis and quantitative real-time PCR (qRT-PCR) assays demonstrated that PeKNOX genes may play a role in promoting rapid shoot growth. Additionally, Gene Ontology (GO) and Protein-Protein Interaction (PPI) network enrichment analyses revealed several functional annotations for PeKNOXs. By regulating downstream target genes, PeKNOXs are involved in the synthesis of AUX /IAA, ultimately affecting cell division and elongation.

CONCLUSIONS

In the present study, we identified and characterized a total of 24 KNOX genes in Moso bamboo and investigated their physiological properties and conserved structural domains. To understand their functional roles, we conducted an analysis of gene expression profiles using STEM and RNA-seq data. This analysis successfully revealed regulatory networks of the KNOX genes, involving both upstream and downstream genes. Furthermore, the KNOX genes are involved in the AUX/IAA metabolic pathway, which accelerates shoot growth by influencing downstream target genes. These results provide a theoretical foundation for studying the molecular mechanisms underlying the rapid growth and establish the groundwork for future research into the functions and transcriptional regulatory networks of the KNOX gene family.

SERBP1 interacts with PARP1 and is present in PARylation-dependent protein complexes regulating splicing, cell division, and ribosome biogenesis

RNA binding proteins (RBPs) containing intrinsically disordered regions (IDRs) are present in diverse molecular complexes where they function as dynamic regulators. Their characteristics promote liquid-liquid phase separation (LLPS) and the formation of membraneless organelles such as stress granules and nucleoli. IDR-RBPs are particularly relevant in the nervous system and their dysfunction is associated with neurodegenerative diseases and brain tumor development. SERBP1 is a unique member of this group, being mostly disordered and lacking canonical RNA-binding domains. Using a proteomics approach followed by functional analysis, we defined SERBP1's interactome. We uncovered novel SERBP1 roles in splicing, cell division, and ribosomal biogenesis and showed its participation in pathological stress granules and Tau aggregates in Alzheimer's disease brains. SERBP1 preferentially interacts with other G-quadruplex (G4) binders, implicated in different stages of gene expression, suggesting that G4 binding is a critical component of SERBP1 function in different settings. Similarly, we identified important associations between SERBP1 and PARP1/polyADP-ribosylation (PARylation). SERBP1 interacts with PARP1 and its associated factors and influences PARylation. Moreover, protein complexes in which SERBP1 participates contain mostly PARylated proteins and PAR binders. Based on these results, we propose a feedback regulatory model in which SERBP1 influences PARP1 function and PARylation, while PARylation modulates SERBP1 functions and participation in regulatory complexes.

Overview of the Knowledge Management Center for Illuminating the Druggable Genome

The Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) project aims to aggregate, update, and articulate protein-centric data knowledge for the entire human proteome, with emphasis on the understudied proteins from the three IDG protein families. KMC collates and analyzes data from over 70 resources to compile the Target Central Resource Database (TCRD), which is the web-based informatics platform (Pharos). These data include experimental, computational, and text-mined information on protein structures, compound interactions, and disease and phenotype associations. Based on this knowledge, proteins are classified into different Target Development Levels (TDLs) for identification of understudied targets. Additional work by the KMC focuses on enriching target knowledge and producing DrugCentral and other data visualization tools for expanding investigation of understudied targets.

Biomimetic biphasic microsphere preparation based on the thermodynamic incompatibility of glycosaminoglycan with gelatin methacrylate for hair regeneration

Hair follicle (HF) tissue engineering is promising for hair loss treatment especially for androgenetic alopecia. Physiologically, the initiation of HF morphogenesis relies on the interactions between hair germ mesenchymal and epithelial layers. To simulate this intricate process, in this study, a co-flowing microfluidic-assisted technology was developed to produce dual aqueous microdroplets capturing growth factors and double-layer cells for subsequent use in hair regeneration. Microspheres, called G/HAD, were generated using glycosaminoglycan-based photo-crosslinkable biological macromolecule (HAD) shells and gelatin methacrylate (GelMA) cores to enclose mesenchymal cells (MSCs) and mouse epidermal cells (EPCs). The findings indicated that the glycosaminoglycan-based HAD shells display thermodynamic incompatibility with GelMA cores, resulting in the aqueous phase separation of G/HAD cell spheres. These G/HAD microspheres exhibited favorable characteristics, including sustained growth factor release and wet adhesion properties. After transplantation into the dorsal skin of BALB/c nude mice, G/HAD cell microspheres efficiently induced the regeneration of HFs. This approach enables the mass production of approximately 250 dual-layer microspheres per minute. Thus, this dual-layer microsphere fabrication method holds great potential in improving current hair regeneration techniques and can also be combined with other tissue engineering techniques for various regenerative purposes.

Trypanosoma cruzi interaction with host tissues modulate the composition of large extracellular vesicles

Trypanosoma cruzi is the protozoan that causes Chagas disease (CD), an endemic parasitosis in Latin America distributed around the globe. If CD is not treated in acute phase, the parasite remains silent for years in the host's tissues in a chronic form, which may progress to cardiac, digestive or neurological manifestations. Recently, studies indicated that the gastrointestinal tract represents an important reservoir for T. cruzi in the chronic phase. During interaction T. cruzi and host cells release extracellular vesicles (EVs) that modulates the immune system and infection, but the dynamics of secretion of host and parasite molecules through these EVs is not understood. Now, we used two cell lines: mouse myoblast cell line C2C12, and human intestinal epithelial cell line Caco-2to simulate the environments found by the parasite in the host. We isolated large EVs (LEVs) from the interaction of T. cruzi CL Brener and Dm28c/C2C12 and Caco-2 cells upon 2 and 24 h of infection. Our data showed that at two hours there is a strong cellular response mediated by EVs, both in the number, variety and enrichment/targeting of proteins found in LEVs for diverse functions. Qualitative and quantitative analysis showed that proteins exported in LEVs of C2C12 and Caco-2 have different patterns. We found a predominance of host proteins at early infection. The parasite-host cell interaction induces a switch in the functionality of proteins carried by LEVs and a heterogeneous response depending on the tissues analyzed. Protein-protein interaction analysis showed that cytoplasmic and mitochondrial homologues of the same parasite protein, tryparedoxin peroxidase, were differentially packaged in LEVs, also impacting the interacting molecule of this protein in the host. These data provide new evidence that the interaction with T. cruzi leads to a rapid tissue response through the release of LEVs, reflecting the enrichment of some proteins that could modulate the infection environment.

Oral infectivity through carnivorism in murine model of Trypanosoma cruzi infection

Introduction

Oral transmission of T. cruzi is probably the most frequent transmission mechanism in wild animals. This observation led to the hypothesis that consuming raw or undercooked meat from animals infected with T. cruzi may be responsible for transmitting the infection. Therefore, the general objective of this study was to investigate host-pathogen interactions between the parasite and gastric mucosa and the role of meat consumption from infected animals in the oral transmission of T. cruzi.

Methods

Cell infectivity assays were performed on AGS cells in the presence or absence of mucin, and the roles of pepsin and acidic pH were determined. Moreover, groups of five female Balb/c mice were fed with muscle tissue obtained from mice in the acute phase of infection by the clone H510 C8C3hvir of T. cruzi, and the infection of the fed mice was monitored by a parasitemia curve. Similarly, we assessed the infective capacity of T. cruzi trypomastigotes and amastigotes by infecting groups of five mice Balb/c females, which were infected orally using a nasogastric probe, and the infection was monitored by a parasitemia curve. Finally, different trypomastigote and amastigote inoculums were used to determine their infective capacities. Adhesion assays of T. cruzi proteins to AGS stomach cells were performed, and the adhered proteins were detected by western blotting using monoclonal or polyclonal antibodies and by LC-MS/MS and bioinformatics analysis.

Results

Trypomastigote migration in the presence of mucin was reduced by approximately 30%, whereas in the presence of mucin and pepsin at pH 3.5, only a small proportion of parasites were able to migrate (∼6%). Similarly, the ability of TCTs to infect AGS cells in the presence of mucin is reduced by approximately 20%. In all cases, 60-100% of the animals were fed meat from mice infected in the acute phase or infected with trypomastigotes or amastigotes developed high parasitemia, and 80% died around day 40 post-infection. The adhesion assay showed that cruzipain is a molecule of trypomastigotes and amastigotes that binds to AGS cells. LC-MS/MS and bioinformatics analysis, also confirmed that transialidase, cysteine proteinases, and gp63 may be involved in TCTs attachment or invasion of human stomach cells because they can potentially interact with different proteins in the human stomach mucosa. In addition, several human gastric mucins have cysteine protease cleavage sites.

Discussion

Then, under our experimental conditions, consuming meat from infected animals in the acute phase allows the T. cruzi infection. Similarly, trypomastigotes and amastigotes could infect mice when administered orally, whereas cysteinyl proteinases and trans-sialidase appear to be relevant molecules in this infective process.

Transomics2cytoscape: an automated software for interpretable 2.5-dimensional visualization of trans-omic networks

Biochemical network visualization is one of the essential technologies for mechanistic interpretation of omics data. In particular, recent advances in multi-omics measurement and analysis require the development of visualization methods that encompass multiple omics data. Visualization in 2.5 dimension (2.5D visualization), which is an isometric view of stacked X-Y planes, is a convenient way to interpret multi-omics/trans-omics data in the context of the conventional layouts of biochemical networks drawn on each of the stacked omics layers. However, 2.5D visualization of trans-omics networks is a state-of-the-art method that primarily relies on time-consuming human efforts involving manual drawing. Here, we present an R Bioconductor package 'transomics2cytoscape' for automated visualization of 2.5D trans-omics networks. We confirmed that transomics2cytoscape could be used for rapid visualization of trans-omics networks presented in published papers within a few minutes. Transomics2cytoscape allows for frequent update/redrawing of trans-omics networks in line with the progress in multi-omics/trans-omics data analysis, thereby enabling network-based interpretation of multi-omics data at each research step. The transomics2cytoscape source code is available at https://github.com/ecell/transomics2cytoscape .

Computational resources and chemoinformatics for translational health research

The integration of computational resources and chemoinformatics has revolutionized translational health research. It has offered a powerful set of tools for accelerating drug discovery. This chapter overviews the computational resources and chemoinformatics methods used in translational health research. The resources and methods can be used to analyze large datasets, identify potential drug candidates, predict drug-target interactions, and optimize treatment regimens. These resources have the potential to transform the drug discovery process and foster personalized medicine research. We discuss insights into their various applications in translational health and emphasize the need for addressing challenges, promoting collaboration, and advancing the field to fully realize the potential of these tools in transforming healthcare.

Network pharmacology, molecular simulation, and binding free energy calculation-based investigation of Neosetophomone B revealed key targets for the treatment of cancer

In the current study, Neosetophomone B (NSP-B) was investigated for its anti-cancerous potential using network pharmacology, quantum polarized ligand docking, molecular simulation, and binding free energy calculation. Using SwissTarget prediction, and Superpred, the molecular targets for NSP-B were predicted while cancer-associated genes were obtained from DisGeNet. Among the total predicted proteins, only 25 were reported to overlap with the disease-associated genes. A protein-protein interaction network was constructed by using Cytoscape and STRING databases. MCODE was used to detect the densely connected subnetworks which revealed three sub-clusters. Cytohubba predicted four targets, i.e., fibroblast growth factor , FGF20, FGF22, and FGF23 as hub genes. Molecular docking of NSP-B based on a quantum-polarized docking approach with FGF6, FGF20, FGF22, and FGF23 revealed stronger interactions with the key hotspot residues. Moreover, molecular simulation revealed a stable dynamic behavior, good structural packing, and residues' flexibility of each complex. Hydrogen bonding in each complex was also observed to be above the minimum. In addition, the binding free energy was calculated using the MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) and MM/PBSA (Molecular Mechanics/Poisson-Boltzmann Surface Area) approaches. The total binding free energy calculated using the MM/GBSA approach revealed values of -36.85 kcal/mol for the FGF6-NSP-B complex, -43.87 kcal/mol for the FGF20-NSP-B complex, and -37.42 kcal/mol for the FGF22-NSP-B complex, and -41.91 kcal/mol for the FGF23-NSP-B complex. The total binding free energy calculated using the MM/PBSA approach showed values of -30.05 kcal/mol for the FGF6-NSP-B complex, -39.62 kcal/mol for the FGF20-NSP-B complex, -34.89 kcal/mol for the FGF22-NSP-B complex, and -37.18 kcal/mol for the FGF23-NSP-B complex. These findings underscore the promising potential of NSP-B against FGF6, FGF20, FGF22, and FGF23, which are reported to be essential for cancer signaling. These results significantly bolster the potential of NSP-B as a promising candidate for cancer therapy.

Comprehensive analyses of mitophagy-related genes and mitophagy-related lncRNAs for patients with ovarian cancer

BACKGROUND

Both mitophagy and long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC). We sought to explore the characteristics of mitophagy-related gene (MRG) and mitophagy-related lncRNAs (MRL) to facilitate treatment and prognosis of OC.

METHODS

The processed data were extracted from public databases (TCGA, GTEx, GEO and GeneCards). The highly synergistic lncRNA modules and MRLs were identified using weighted gene co-expression network analysis. Using LASSO Cox regression analysis, the MRL-model was first established based on TCGA and then validated with four external GEO datasets. The independent prognostic value of the MRL-model was evaluated by Multivariate Cox regression analysis. Characteristics of functional pathways, somatic mutations, immunity features, and anti-tumor therapy related to the MRL-model were evaluated using abundant algorithms, such as GSEA, ssGSEA, GSVA, maftools, CIBERSORT, xCELL, MCPcounter, ESTIMATE, TIDE, pRRophetic and so on.

RESULTS

We found 52 differentially expressed MRGs and 22 prognostic MRGs in OC. Enrichment analysis revealed that MRGs were involved in mitophagy. Nine prognostic MRLs were identified and eight optimal MRLs combinations were screened to establish the MRL-model. The MRL-model stratified patients into high- and low-risk groups and remained a prognostic factor (P < 0.05) with independent value (P < 0.05) in TCGA and GEO. We observed that OC patients in the high-risk group also had the unfavorable survival in consideration of clinicopathological parameters. The Nomogram was plotted to make the prediction results more intuitive and readable. The two risk groups were enriched in discrepant functional pathways (such as Wnt signaling pathway) and immunity features. Besides, patients in the low-risk group may be more sensitive to immunotherapy (P = 0.01). Several chemotherapeutic drugs (Paclitaxel, Veliparib, Rucaparib, Axitinib, Linsitinib, Saracatinib, Motesanib, Ponatinib, Imatinib and so on) were found with variant sensitivity between the two risk groups. The established ceRNA network indicated the underlying mechanisms of MRLs.

CONCLUSIONS

Our study revealed the roles of MRLs and MRL-model in expression, prognosis, chemotherapy, immunotherapy, and molecular mechanism of OC. Our findings were able to stratify OC patients with high risk, unfavorable prognosis and variant treatment sensitivity, thus improving clinical outcomes for OC patients.

Potential Mechanisms Underlying the Therapeutic Roles of Gancao fuzi Decoction in Cold-dampness Obstruction Syndrome-type Knee Osteoarthritis

BACKGROUND

The key active components and potential molecular mechanism of Gancao Fuzi decoction (GFD) in the treatment of cold-dampness obstruction-type knee osteoarthritis (KOA) remain unclear.

OBJECTIVES

To explore the mechanism of GFD in the treatment of cold-dampness obstruction syndrome-type KOA by network pharmacology.

METHODS

The potential active components and targets of the four herbs in GFD (Fuzi, Guizhi, Baizhu, and Gancao) were screened using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The targets of KOA were obtained with the Comparative Toxicogenomics Database (CTD), the GeneCards database, and the DisGeNET database, and the common targets of the drugs and disease were ultimately obtained. Cytoscape (v.3.7.1) was used to draw the active component-target network, and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) (v.11.0) database was used to construct the protein interaction network. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for the Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the intersecting targets.

RESULTS

A total of 102 potential active components and 208 targets of GFD in the treatment of cold-dampness obstruction syndrome-type KOA were screened. GFD treatment was found to be closely related to many inflammatory signalling pathways in the treatment of KOA.

CONCLUSION

The effect of GFD on cold-dampness obstruction syndrome-type KOA is mediated by multicomponent, multitarget, and multichannel mechanisms, which provides the basis for further experimental study of its pharmacodynamic material basis and mechanism.

Anti-inflammation is an important way that Qingre-Huazhuo-Jiangsuan recipe treats acute gouty arthritis

Background: Acute gouty arthritis (AGA) significantly impairs patients' quality of life. Currently, existing therapeutic agents exhibit definite efficacy but also lead to serious adverse reactions. Therefore, it is essential to develop highly efficient therapeutic agents with minimal adverse reactions, especially within traditional Chinese medicine (TCM). Additionally, food polyphenols have shown potential in treating various inflammatory diseases. The Qingre-Huazhuo-Jiangsuan-Recipe (QHJR), a modification of Si-Miao-San (SMS), has emerged as a TCM remedy for AGA with no reported side effects. Recent research has also highlighted a strong genetic link to gout. Methods: The TCM System Pharmacology (TCMSP) database was used to collect the main chemical components of QHJR and AGA-related targets for predicting the metabolites in QHJR. HPLC-Q-Orbitrap-MS was employed to identify the ingredients of QHJR. The collected metabolites were then used to construct a Drugs-Targets Network in Cytoscape software, ranked based on their "Degree" of significance. Differentially expressed genes (DEGs) were screened in the Gene Expression Omnibus (GEO) database using GEO2R online analysis. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. The DEGs were utilized to construct a Protein-Protein Interaction (PPI) Network via the STRING database. In vivo experimental validation was conducted using colchicine, QHJR, rapamycin (RAPA), and 3-methyladenine (3-MA) as controls to observe QHJR's efficacy in AGA. Synovial tissues from rats were collected, and qRT-PCR and Western blot assays were employed to investigate Ampk-related factors (Ampk, mTOR, ULK1), autophagy-related factors (Atg5, Atg7, LC3, p62), and inflammatory-related factors (NLRP3). ELISA assays were performed to measure inflammatory-related factor levels (IL-6, IL-1β, TNF-α), and H&E staining was used to examine tissue histology. Results: Network analysis screened out a total of 94 metabolites in QHJR for AGA. HPLC-Q-Orbitrap-MS analysis identified 27 of these metabolites. Notably, five metabolites (Neochlorogenic acid, Caffeic acid, Berberine, Isoliquiritigenin, Formononetin) were not associated with any individual herbal component of QHJR in TCMSP database, while six metabolites (quercetin, luteolin, formononetin, naringenin, taxifolin, diosgenin) overlapped with the predicted results from the previous network analysis. Further network analysis highlighted key components, such as Caffeic acid, cis-resveratrol, Apigenin, and Isoliquiritigenin. Other studies have found that their treatment of AGA is achieved through reducing inflammation, consistent with this study, laying the foundation for the mechanism study of QHJR against AGA. PPI analysis identified TNF, IL-6, and IL-1β as hub genes. GO and KEGG analyses indicated that anti-inflammation was a key mechanism in AGA treatment. All methods demonstrated that inflammatory expression increased in the Model group but was reversed by QHJR. Additionally, autophagy-related expression increased following QHJR treatment. The study suggested that AMPKα and p-AMPKα1 proteins were insensitive to 3 MA and RAPA, implying that AMPK may not activate autophagy directly but through ULK1 and mTOR. Conclusion: In conclusion, this study confirms the effectiveness of QHJR, a modified formulation of SMS (a classic traditional Chinese medicine prescription for treating gout), against AGA. QHJR, as a TCM formula, offers advantages such as minimal safety concerns and potential long-term use. The study suggests that the mechanism by which QHJR treats AGA may involve the activation of the AMPK/mTOR/ULK1 pathway, thereby regulating autophagy levels, reducing inflammation, and alleviating AGA. These findings provide new therapeutic approaches and ideas for the clinical treatment of AGA.

Flame (v2.0): advanced integration and interpretation of functional enrichment results from multiple sources

Functional enrichment is the process of identifying implicated functional terms from a given input list of genes or proteins. In this article, we present Flame (v2.0), a web tool which offers a combinatorial approach through merging and visualizing results from widely used functional enrichment applications while also allowing various flexible input options. In this version, Flame utilizes the aGOtool, g: Profiler, WebGestalt, and Enrichr pipelines and presents their outputs separately or in combination following a visual analytics approach. For intuitive representations and easier interpretation, it uses interactive plots such as parameterizable networks, heatmaps, barcharts, and scatter plots. Users can also: (i) handle multiple protein/gene lists and analyse union and intersection sets simultaneously through interactive UpSet plots, (ii) automatically extract genes and proteins from free text through text-mining and Named Entity Recognition (NER) techniques, (iii) upload single nucleotide polymorphisms (SNPs) and extract their relative genes, or (iv) analyse multiple lists of differentially expressed proteins/genes after selecting them interactively from a parameterizable volcano plot. Compared to the previous version of 197 supported organisms, Flame (v2.0) currently allows enrichment for 14 436 organisms.

AVAILABILITY AND IMPLEMENTATION

Web Application: http://flame.pavlopouloslab.info. Code: https://github.com/PavlopoulosLab/Flame. Docker: https://hub.docker.com/r/pavlopouloslab/flame.

Functional Landscape of African Swine Fever Virus-Host and Virus-Virus Protein Interactions

Viral replication fully relies on the host cell machinery, and physical interactions between viral and host proteins mediate key steps of the viral life cycle. Therefore, identifying virus-host protein-protein interactions (PPIs) provides insights into the molecular mechanisms governing virus infection and is crucial for designing novel antiviral strategies. In the case of the African swine fever virus (ASFV), a large DNA virus that causes a deadly panzootic disease in pigs, the limited understanding of host and viral targets hinders the development of effective vaccines and treatments. This review summarizes the current knowledge of virus-host and virus-virus PPIs by collecting and analyzing studies of individual viral proteins. We have compiled a dataset of experimentally determined host and virus protein targets, the molecular mechanisms involved, and the biological functions of the identified virus-host and virus-virus protein interactions during infection. Ultimately, this work provides a comprehensive and systematic overview of ASFV interactome, identifies knowledge gaps, and proposes future research directions.

Arena3Dweb: interactive 3D visualization of multilayered networks supporting multiple directional information channels, clustering analysis and application integration

Arena3D^web is an interactive web tool that visualizes multi-layered networks in 3D space. In this update, Arena3D^web supports directed networks as well as up to nine different types of connections between pairs of nodes with the use of Bézier curves. It comes with different color schemes (light/gray/dark mode), custom channel coloring, four node clustering algorithms which one can run on-the-fly, visualization in VR mode and predefined layer layouts (zig-zag, star and cube). This update also includes enhanced navigation controls (mouse orbit controls, layer dragging and layer/node selection), while its newly developed API allows integration with external applications as well as saving and loading of sessions in JSON format. Finally, a dedicated Cytoscape app has been developed, through which users can automatically send their 2D networks from Cytoscape to Arena3D^web for 3D multi-layer visualization. Arena3D^web is accessible at http://arena3d.pavlopouloslab.info or http://arena3d.org.

In vivo Protein Footprinting Reveals the Dynamic Conformational Changes of Proteome of Multiple Tissues in Progressing Alzheimer's Disease

Numerous studies have investigated changes in protein expression at the system level using proteomic mass spectrometry, but only recently have studies explored the structure of proteins at the proteome level. We developed covalent protein painting (CPP), a protein footprinting method that quantitatively labels exposed lysine, and have now extended the method to whole intact animals to measure surface accessibility as a surrogate of in vivo protein conformations. We investigated how protein structure and protein expression change as Alzheimer's disease (AD) progresses by conducting in vivo whole animal labeling of AD mice. This allowed us to analyze broadly protein accessibility in various organs over the course of AD. We observed that structural changes of proteins related to 'energy generation,' 'carbon metabolism,' and 'metal ion homeostasis' preceded expression changes in the brain. We found that proteins in certain pathways undergoing structural changes were significantly co-regulated in the brain, kidney, muscle, and spleen.

Genome-Wide Analysis of the KLF Gene Family in Chicken: Characterization and Expression Profile

The kruppel-like factor (KLF) gene family is a group of transcription factors containing highly conserved zinc-finger motifs, which play a crucial role in cell proliferation and differentiation. Chicken has been widely used as a model animal for analyzing gene function, however, little is known about the function of the KLF gene family in chickens. In this study, we performed genome-wide studies of chicken KLF genes and analyzed their biological and expression characteristics. We identified 13 KLF genes from chickens. Our phylogenetic, motif, and conserved domain analyses indicate that the KLF gene family has remained conserved through evolution. Synteny analysis showed the collinear relationship among KLFs, which indicated that they had related biomolecular functions. Interaction network analysis revealed that KLFs worked with 20 genes in biological processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that KLF2 was involved in Apelin and Forkhead Box O (FOXO) signaling pathways. Moreover, qPCR showed that 13 KLF genes were expressed in the nine selected tissues and displayed various gene expression patterns in chickens. RNA-seq showed that KLF3 and KLF10 genes were differentially expressed in the normal and high-fat diet fed groups, and KLF4, KLF5, KLF6, KLF7, KLF9, KLF12, and KLF13 genes were differentially expressed between undifferentiated and differentiated chicken preadipocytes. Besides, RNA-seq also showed that KLF genes displayed different expression patterns in muscle at 11 and 16 embryonic days old, and in 1-day-old chickens. These results indicated that the KLF genes were involved in the development of muscle and fat in chickens. Our findings provide some valuable reference points for the subsequent study of the function of KLF genes.

Analysis of the Genetic Relationship between Atherosclerosis and Non-Alcoholic Fatty Liver Disease through Biological Interaction Networks

Non-alcoholic fatty liver disease (NAFLD) seems to have some molecular links with atherosclerosis (ATH); however, the molecular pathways which connect both pathologies remain unexplored to date. The identification of common factors is of great interest to explore some therapeutic strategies to improve the outcomes for those affected patients. Differentially expressed genes (DEGs) for NAFLD and ATH were extracted from the GSE89632 and GSE100927 datasets, and common up- and downregulated DEGs were identified. Subsequently, a protein-protein interaction (PPI) network based on the common DEGs was performed. Functional modules were identified, and the hub genes were extracted. Then, a Gene Ontology (GO) and pathway analysis of common DEGs was performed. DEGs analysis in NAFLD and ATH showed 21 genes that were regulated similarly in both pathologies. The common DEGs with high centrality scores were ADAMTS1 and CEBPA which appeared to be down- and up-regulated in both disorders, respectively. For the analysis of functional modules, two modules were identified. The first one was oriented to post-translational protein modification, where ADAMTS1 and ADAMTS4 were identified, and the second one mainly related to the immune response, where CSF3 was identified. These factors could be key proteins with an important role in the NAFLD/ATH axis.

Identifying NFKB1, STAT3, and CDKN1A as Baicalein's Potential Hub Targets in Parkinson's Disease-related α-synuclein-mediated Pathways by Integrated Bioinformatics Strategies

BACKGROUND

The overexpression, accumulation, and cell-to-cell transmission of α-synuclein leads to the deterioration of Parkinson's disease (PD). Previous studies suggest that Baicalein (BAI) can bind to α-synuclein and inhibit α-synuclein aggregation and secretion. However, it is still unclear whether BAI can intervene with the pathogenic molecules in α-synuclein-mediated PD pathways beyond directly targeting α-synuclein per se.

METHODS

This study aimed to systematically investigate BAI's potential targets in PD-related A53T mutant α-synuclein-mediated pathways by integrating data mining, network pharmacological analysis, and molecular docking simulation techniques.

RESULTS

The results suggest that BAI may target genes that are dysregulated in synaptic transmission, vesicle trafficking, gene transcription, protein binding, extracellular matrix formation, and kinase activity in α-synucleinmediated pathways. NFKB1, STAT3, and CDKN1A are BAI's potential hub targets in these pathways.

CONCLUSION

Our findings highlight BAI's potentiality to modulate α-synuclein-mediated pathways beyond directly targeting α-synuclein per se.