Genes In Genome Research Articles

Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistant Acinetobacter baumannii from whole genome sequencing and gene expression

ABSTRACT Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the challenge still exists to predict fully minimum inhibitory concentrations (MICs) and antimicrobial susceptibility phenotypes based on WGS data. This study aimed to establish an artificial intelligence-based computational approach in predicting antimicrobial susceptibilities of multidrug-resistant Acinetobacter baumannii from WGS and gene expression data. Antimicrobial susceptibility testing (AST) was performed using the broth microdilution method for 10 antimicrobial agents. In silico multilocus sequence typing (MLST), antimicrobial resistance genes, and phylogeny based on cgSNP and cgMLST strategies were analyzed. High-throughput qPCR was performed to measure the expression level of antimicrobial resistance (AMR) genes. Most isolates exhibited a high level of resistance to most of the tested antimicrobial agents, with the majority belonging to the IC2/CC92 lineage. Phylogenetic analysis revealed undetected transmission events or local outbreaks. The percentage agreements between AMR phenotype and genotype ranged from 70.08% to 89.96%, with the coefficient of agreement (κ) extending from 0.025 and 0.881. The prediction of AST employed by deep neural network models achieved an accuracy of up to 98.64% on the testing data set. Additionally, several linear regression models demonstrated high prediction accuracy, reaching up to 86.15% within an error range of one gradient, indicating a linear relationship between certain gene expressions and the corresponding antimicrobial MICs. In conclusion, neural network-based predictions could be used as a tool for the surveillance of antimicrobial resistance in multidrug-resistant A. baumannii .

Assembly, Annotation, and Comparative Analysis of Mitochondrial Genomes in Trichoderma

Trichoderma is a widely studied ascomycete fungal genus, including more than 400 species. However, genetic information on Trichoderma is limited, with most species reporting only DNA barcodes. Mitochondria possess their own distinct DNA that plays a pivotal role in molecular function and evolution. Here, we report 42 novel mitochondrial genomes (mitogenomes) combined with 18 published mitogenomes of Trichoderma. These circular mitogenomes exhibit sizes of 26,276–94,608 bp, typically comprising 15 core protein-coding genes (PCGs), 2 rRNAs, and 16–30 tRNAs; however, the number of endonucleases and hypothetical proteins encoded in the introns of PCGs increases with genome size enlargement. According to the result of phylogenetic analysis of the whole mitogenome, these strains diverged into six distinct evolutionary branches, supported by the phylogeny based on 2830 single-copy nuclear genes. Comparative analysis revealed that dynamic Trichoderma mitogenomes exhibited variations in genome size, gene number, GC content, tRNA copy, and intron across different branches. We identified three mutation hotspots near the regions encoding nad3, cox2, and nad5 that caused major changes in the mitogenomes. Evolutionary analysis revealed that atp9, cob, nad4L, nad5, and rps3 have been influenced by positive selection during evolution. This study provides a valuable resource for exploring the important roles of the genetic and evolutionary dynamics of Trichoderma mitogenome in the adaptive evolution of biocontrol fungi.

ANGI-14. DRUGGABLE GENOME CRISPR SCREEN IN 3D HYDROGEL DEVICES REVEALS TARGETABLE KINASES AND PHOSPHATASES IMPLICATED IN CYTOSKELETAL REORGANIZATION IN INVADING GBM CELLS

Abstract The invasive nature of glioblastoma cells into adjacent brain tissues is a key factor in its unfavorable prognosis. To decipher the mechanisms driving glioblastoma invasion, we developed microdissectable biomimetic 3D hydrogel invasion devices containing hyaluronic acid hydrogels decorated with integrin-binding peptides (RGD) and crosslinked with protease-cleavable crosslinkers. The ability to disassemble these devices and interrogate cells in the core vs. invasive fraction allows for high throughput screens. We thus performed a screen in GBM43 cells expressing CRISPR/Cas9 and a 13,250 gRNA library targeting the 2550 genes in the druggable human genome. Of seven initial hits from this screen, only two could be validated by single gene CRISPR and use of a drug to target the hit - ACP1 (also known as LMW-PTP) and Aurora Kinase B (AURKB). Integration of ChIP-seq and RNA-seq revealed no plausible transcriptional targets of ACP1 and AURKB that could drive invasion. Proximity labeling with the TurboID system identified CTTN (cortactin), an actin binding protein whose phosphorylation is integral to the formation of lamellipodia and invadopodia, as phosphorylated by AURKB and Ephrin A2 (EPHA2), whose dephosphorylation controls cell morphology, adhesion, migration and invasion by modifying the organization of the actin cytoskeleton and influencing the activities of integrins and intercellular adhesion molecules, as dephosphorylated by ACP1. These findings underscore the delicate balance between kinase and phosphatase activities in regulating the actin cytoskeleton broadly and at the cell’s front or “leading edge,” offering new therapeutic targets to disrupt the invasion that is a hallmark of glioblastoma.

BIOM-25. MOLECULAR PROFILING PREDICTS EARLY AND LATE PROGRESSION IN GLIOBLASTOMA

Abstract Patients with glioblastoma experience a wide variation in response to standard treatment, with nearly 30% experiencing tumour progression during treatment, and nearly 6% surviving more than 5 years. To date, there are few non-invasive clinical biomarkers to predict response to first – line treatment. Chemical exchange saturation transfer (CEST) MRI may have the potential to fill this gap. CEST MRI is sensitive to treatment-induced changes and changes in tumor metabolism. Our team has obtained CEST data for patients before, during and after the end of standard chemoradiation treatment, and found that CEST provides markers of early response and can identify early, standard and late progressors before treatment initiation. In this study, we aimed to establish molecular profiles of early, standard and late progressors with IDH wild-type glioblastoma. Patients (n=180) with primary, IDH wild-type glioblastoma were imaged with CEST-MRI at multiple time points throughout standard chemoradiation treatment. DNA and RNA were co-extracted from matched normal and tumour pairs and processed for whole genome sequencing, enzymatic methyl-seq and gene expression analysis using Nanostring. Clinical variables such as age, extent of resection, sex, ECOG status and MGMT promoter methylated were also collected. A survival analysis was conducted using the Kaplan-Meier method with log-rank tests. Univariate and multi-variate hazard ratios for clinical variables were calculated by fitting Cox Proportional Hazards Models. Early progressors reported a median progression-free survival (PFS) of 142 days compared to 832 days in late progressors (p<0.0001). Early progressors also harbored distinct and statistically significant differences in gene expression and genomic alterations, namely in DNA damage repair, glucose transport and arginine metabolism pathways. A gene signature was prognostic of PFS and overall survival. Collectively, this data has the potential to serve as a radiogenomic biomarker to assess treatment response before or within early phases of treatment and allow for individual tailoring of the treatment plan.

Gene expression-based modeling of overall survival in Black or African American patients with lung adenocarcinoma

IntroductionLung cancer is a leading cause of cancer-related deaths worldwide. Black/African American (B/AA) populations, in particular, exhibit the highest incidence and mortality rates of lung adenocarcinoma (LUAD) in the United States.MethodsThis study aims to explore gene expression patterns linked to LUAD in B/AA and case-matched white patients, with the goal of developing predictive models for prognosis. Leveraging RNA sequencing data from The Cancer Genome Atlas (TCGA) database, genes and pathways associated with overall survival (OS) were identified.ResultsThe OS-associated genes in B/AA patients were distinct from those in white patients, showing predominant enrichment in immune-related pathways. Furthermore, mRNA co-expression network analysis revealed that OS-associated genes in B/AA patients had higher levels of interaction with various pathways, including those related to immunity, cell-ECM interaction, and specific intracellular signaling pathways. Notably, a potential B/AA-specific biomarker, C9orf64, demonstrated significant correlations with genes involved in immune response. Unsupervised machine learning algorithms stratified B/AA patients into groups with distinct survival outcomes, while supervised algorithms demonstrated a higher accuracy in predicting survival for B/AA LUAD patients compared to white patients.DiscussionIn total, this study explored OS-associated genes and pathways specific for B/AA LUAD patients. Further validation and clinical application of these findings are warranted to address disparities and improve outcomes in diverse patient populations.

BindCompare: A Novel Integrated Protein-Nucleic Acid Binding Analysis Platform

Abstract Summary Advanced genomic technologies have generated thousands of protein-nucleic acid binding datasets that have the potential to identify testable gene regulatory network (GRNs) models governed by combinatorial associations between factors. Transcription factors (TFs) and RNA binding proteins (RBPs) are nucleic-acid binding proteins regulating gene expression and are key drivers of GRN function. However, the combinatorial mechanisms by which the interactions between specific TFs and RBPs regulate gene expression remain largely unknown. To identify possible combinations of TFs and RBPs that may function together, developing a tool that compares and contrasts the interactions of multiple TFs and RBPs with nucleic acids to identify their common and unique targets is necessary. Therefore, we introduce BindCompare, a user-friendly tool that can be run locally to predict new combinatorial relationships between TFs and RBPs. BindCompare can analyze data from any organism with known annotated genome information and outputs files with detailed genomic locations and gene information for targets for downstream analysis. Overall, BindCompare is a new tool that identifies TFs and RBPs that co-bind to the same DNA and/or RNA loci, generating testable hypotheses about their combinatorial regulation of target genes. Availability and Implementation BindCompare is an open-source package that is available on the Python Packaging Index (PyPI, https://pypi.org/project/bindcompare/) with the source code available on GitHub (https://github.com/pranavmahabs/bindcompare). Complete documentation for the package can be found at both links. Supplementary information Supplementary data are available at Bioinformatics online.

Bioinformatic Multi-Strategy Profiling of Congenital Heart Defects for Molecular Mechanism Recognition

Congenital heart defects (CHDs) rank among the most common birth defects, presenting diverse phenotypes. Genetic and environmental factors are critical in molding the process of cardiogenesis. However, these factors’ interactions are not fully comprehended. Hence, this study aimed to identify and characterize differentially expressed genes involved in CHD development through bioinformatics pipelines. We analyzed experimental datasets available in genomic databases, using transcriptome, gene enrichment, and systems biology strategies. Network analysis based on genetic and phenotypic ontologies revealed that EP300, CALM3, and EGFR genes facilitate rapid information flow, while NOTCH1, TNNI3, and SMAD4 genes are significant mediators within the network. Differential gene expression (DGE) analysis identified 2513 genes across three study types, (1) Tetralogy of Fallot (ToF); (2) Hypoplastic Left Heart Syndrome (HLHS); and (3) Trisomy 21/CHD, with LYVE1, PLA2G2A, and SDR42E1 genes found in three of the six studies. Interaction networks between genes from ontology searches and the DGE analysis were evaluated, revealing interactions in ToF and HLHS groups, but none in Trisomy 21/CHD. Through enrichment analysis, we identified immune response and energy generation as some of the relevant ontologies. This integrative approach revealed genes not previously associated with CHD, along with their interactions and underlying biological processes.

Evolutionary dynamics and functional characterization of proximal duplicated sorbitol-6-phosphate dehydrogenase genes in Rosaceae

Sorbitol is a critical photosynthate and storage substance in the Rosaceae family. Sorbitol 6-phosphate dehydrogenase (S6PDH) functions as the pivotal rate-limiting enzyme in sorbitol synthesis. The origin and functional diversification of S6PDH in Rosaceae remain unclear, largely due to the complicated interplay of gene duplications. Here, we investigated the synteny relationships among all identified S6PDH genes in representative genomes within the Rosaceae family. By integrating phylogenetic analyses, we elucidated the lineage-specific expansion and syntenic conservation of S6PDH across diverse Rosaceae plant lineages. We found that S6PDH can be traced back to a pair of proximal duplicated genes of the common ancestor of the Rosaceae, and the further amplification of S6PDH in the Maleae primarily relies on WGD events in their lineages. In Rosaceae species, multiple copies of the S6PDH gene are preliminarily divided into two main clades (Clade 1 and Clade 2) based on sequence similarity. These clades have evolved to acquire different functional directions. In Clade 1, lineage-specific transposition events in the Amygdaloideae have led to changes in gene expression patterns and promoted lineage evolution. This is mainly characterized by a decrease in enzymatic activity and transcriptional expression in the leaves, but also includes specific functional diversification, such as sustained post-harvest fruit expression and enhanced expression under biotic stress in certain tissues. In contrast, S6PDH in the Rosoideae and Dryadoideae has not undergone additional duplications beyond early proximal duplication. The loss of exons and variations in exon length might the key factor leading to reduced enzymatic activity in the Clade 2 proximal gene pairs. Collectively, our findings illuminate the dynamic nature of S6PDH evolution and reveal the intricate interplay between duplication, transposition, and functional diversification. This work not only contributes valuable insights into the genetic mechanisms underlying sorbitol metabolism but also establish a crucial foundation for future investigations aimed at comprehensively characterizing the variations of sorbitol metabolism across different subfamilies within the Rosaceae family.

Whole Genome Sequencing and Comparative Genomic Analysis of Pseudomonas aeruginosa SF416, a Potential Broad-Spectrum Biocontrol Agent Against Xanthomonas oryzae pv. oryzae

Rice is one of the most important staple crops worldwide. However, the bacterial blight of rice caused by Xanthomonas oryzae pv. oryzae (Xoo) poses a major threat to the production of rice. In this study, we isolated and identified the strain Pseudomonas aeruginosa SF416, which exhibited significant antagonistic activity against Xoo, from a soil sample collected in a winter wheat field in Shannanzhalang County, Tibet, China. The bacterial solution (BS) and cell-free supernatant (CFS) of SF416 had significant prevention effects for the bacterial blight of rice, with an efficacy of 45.1% and 34.18%, respectively, while they exhibited a slightly lower therapeutic efficiency of 31.64% and 25.09%. The genomic analysis showed that P. aeruginosa SF416 contains genes involved in cell motility, colonization, cold and hot shock proteins, antibiotic resistance, and plant growth promotion. SF416 also harbors two sets of phenazine-1-carboxylic acid (PCA) synthesis gene clusters, phz1 (phzA1-G1) and phz2 (phzA2-G2), and other phenozine product-synthesis--related genes phzS, phzM, and phzH, as well as genes in the SF416 genome that share high similarity with the ones in the genomes of P. aeruginosa M18, suggesting that the two sets of PCA synthesis gene clusters are responsible for the antagonistic effect of SF416 against Xoo. A comparative antiSMASH analysis revealed that P. aeruginosa SF416 contains 17 gene clusters related to secondary metabolite synthesis, 7 of which, encoding for pyochelin, azetidomonamide A/B, L-2-amino-4-methoxy-trans-3-butenoic acid, hydrogen cyanide, pyocyanine, pseudopaline, and bicyclomycin, are conserved in strains of P. aeruginosa. Moreover, SF416 can produce protease and siderophores and display a broad-spectrum antagonistic activity against various major plant pathogenic bacteria and fungi. The results suggest that P. aeruginosa SF416 could be a potential candidate agent for the bacterial blight of rice.

Identifying colorectal cancer subtypes and establishing a prognostic model using metabolic plasticity and ferroptosis genes

Metabolic plasticity and ferroptosis are essential for colorectal cancer (CRC) progression. The effects and prognostic value of metabolic plasticity- and ferroptosis-related genes (MPFRGs) in CRC remain unclear. We established a prognostic model for CRC patients by identifying important genes in metabolic plasticity and ferroptosis. Data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus; MPFRG data were obtained from GeneCards and FerrDb. We performed functional (to explore differences between the two metabolic subtypes) and single-sample gene set (to assess the immune environment) enrichment analyses. Immunophenotype, tumor immunological dysfunction, and exclusion scores were assessed to determine patient immune responses. A least absolute shrinkage and selection operator-Cox regression model comprising 10 significant differentially expressed genes of metabolic plasticity and ferroptosis (MPFDEGs) was constructed using TCGA training cohort and validated using the GSE17536 and GSE39582 datasets. We established a nomogram comprising metabolic plasticity- and ferroptosis-based signatures, revealing the clinical application and potential molecular mechanisms underlying the role of MPFRGs in CRC. Our model (developed based on 10 MPFDEGs) is efficient for calculating the overall survival of CRC patients. Our findings provide new strategies for the clinical management and individualized treatment of these patients.

SYNERGISTIC POTENTIAL OF NIGELLA SATIVA L. AND TRIGONELLA FOENUM-GRAECUM: INTEGRATED NETWORK PHARMACOLOGY FOR DIABETIC WOUND HEALING

Objective: Diabetes Mellitus (DM) is a metabolic disorder marked by elevated blood glucose levels, and one of the issues linked to DM involves the development of Diabetic Wounds (DW). DW is susceptible to infection and develops into chronic wounds if not treated properly. This study aimed to investigate the network pharmacology of N. sativa L. and T. foenum-graecum, emphasizing on their potential as DW treatment candidates. Methods: Various databases were used in this study, including PubChem, Dr. Duke's phytochemistry and Ethnobotany, and KNApSAcK Family. Swiss Target Prediction and Way2Drug PASS Online were utilized for biological activity and protein target prediction. The DW pathway's protein-protein interactions were examined with the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene Cards, and STRING databases. STRING was used to predict the metabolite's action. The relationship between metabolites and target proteins was predicted using STITCH, and Cytoscape was used to visualize the network. Result: The results showed that ten active ingredients (five active ingredients in N. sativa L. and five active ingredients in T. foenoem-graecum) contributed to DW healing by affecting Tumor Necrosis Factor (TNF), Interleukin-1beta (IL1B), JUN, Caspase 3 (CASP3), Interleukin-6 (IL-6), Alpha Kinase Threonine-1 (AKT1), Vascular Endothelial Growth Factor-A (VEGFA), and Mitogen-Activated Protein Kinase 3 (MAPK3) genes. Furthermore, the ten active ingredients correlated with twenty-eight intracellular proteins, resulting in a mechanism involving eight DW signalling pathways. Conclusion: Based on network pharmacology analysis, we determine that N. sativa L. and T. foenoem-graecum combination can potentially treat DW.

Phased T2T genome assemblies facilitate the mining of disease-resistance genes in Vitis davidii

Abstract Grape is an important fruit crop, and its production faces significant threat from diseases, resulting in substantial economic loss. Wild grape relatives are valuable resources for the restoration of disease-resistance loci. However, available resistance loci in wild grape genomes remain largely unexplored. In this study, we assembled two phased genomes, including a high resistant Chinese wild grape, Vitis davidii Föex, and a susceptible cultivar, V. vinifera L. cv. “Manicure Finger”. We detected a total of 36,688 structural variations (SVs), with the genes associated with heterozygous SVs showing an enrichment in allele-specific expression (ASE). Furthermore, we identified eight subgroups of R genes and found that 74.2% of R genes overlap with transposable elements (TEs). Among R genes, NBS-type genes exhibit higher expression profiles in the wild grape genome compared with those in the grape cultivar. Additionally, five specific NBS-type R gene clusters were identified in the wild grape genome that are absent in the cultivar. Through genetic mapping, we identified four quantitative trait loci (QTLs) associated with grape white rot resistance based on the Vitis davidii genome, within which six NBS-type R genes exhibit differential expression between wild and cultivated grapes. Overall, our study revealed the landscape of resistance genes in grape genomes, providing valuable genetic resources for further breeding programs.

Genome-Wide Characterization of Class III Peroxidases and Their Expression Profile During Mycorrhizal Symbiosis and Phosphorus Deprivation in Lettuce (Lactuca sativa L.)

Lettuce cultivation requires high fertilizer inputs, which impact the environment and costs. Arbuscular mycorrhizal symbiosis (AMS) can reduce fertilizer use, enhance plant nutrition (especially phosphorus), and promote healthier plants. Class III peroxidases (PRXs) play crucial roles in various physiological processes and stress responses. However, their role in AMS and phosphorous (P) deficiency is still unclear. Our study identified 91 PRX genes in the lettuce genome (LsPRXs) and clustered them into eight subfamilies based on phylogenetic relationships. Evolutionary analysis indicated that tandem duplication was the main driver for LsPRX gene family expansion. Synteny analysis showed orthologous relationships of the PRX gene family between lettuce and potato, Arabidopsis, and maize, identifying 39, 28, and 3 shared PRXs, respectively. Transcriptomic data revealed that most LsPRX genes were more expressed in roots than in leaves and differentially expressed LsPRXs were found in response to AMS and P supply. Notably, 15% of LsPRX genes were differentially expressed in roots during mycorrhization. Gene expression network analysis highly correlated five LsPRXs (LsPRX17, LsPRX23, LsPRX24, LsPRX64, and LsPRX79) with genes involved in cell wall remodeling and reorganization during mycorrhization. Our results provide insights into the evolutionary history and functional roles of PRX genes in lettuce and identify candidate gene targets that may enhance the bio-stimulant effects of AMS and help to cope with P deficiency.

Asymmetric genome merging leads to gene expression novelty through nucleo-cytoplasmic disruptions and transcriptomic shock in Chlamydomonas triploids.

Genome merging is a common phenomenon causing a wide range of consequences on phenotype, adaptation, and gene expression, yet its broader implications are not well-understood. Two consequences of genome merging on gene expression remain particularly poorly understood: dosage effects and evolution of expression. We employed Chlamydomonas reinhardtii as a model to investigate the effects of asymmetric genome merging by crossing a diploid with a haploid strain to create a novel triploid line. Five independent clonal lineages derived from this triploid line were evolved for 425 asexual generations in a laboratory natural selection experiment. Utilizing fitness assays, flow cytometry, and RNA-Seq, we assessed the immediate consequences of genome merging and subsequent evolution. Our findings reveal substantial alterations in genome size, gene expression, protein homeostasis, and cytonuclear stoichiometry. Gene expression exhibited expression-level dominance and transgressivity (i.e. expression level higher or lower than either parent). Ongoing expression-level dominance and a pattern of 'functional dominance' from the haploid parent was observed. Despite major genomic and nucleo-cytoplasmic disruptions, enhanced fitness was detected in the triploid strain. By comparing gene expression across generations, our results indicate that proteostasis restoration is a critical component of rapid adaptation following genome merging in Chlamydomonas reinhardtii and possibly other systems.

Assembly and comparative analysis of the multichromosomal mitochondrial genome of globally endangered seagrass Halophila beccarii

BackgroundHalophila beccarii is one of the oldest two generations of seagrass plants and one of the 10 species of seagrass currently at risk of extinction worldwide. Therefore, how to effectively protect the H. beccarii resources from extinction is a huge challenge. Molecular biology research can provide a scientific basis for species conservation. So far, there has been no detailed analysis of the mitochondrial genome of the genus Halophila.ResultsThe mitochondrial genome of H. beccarii was assembled into 28 circular chromosomes, ranging in length from 41,738 bp to 104,744 bp, with a total length of 1,964,072 bp and a GC content of 46.71%. It contains 39 genes, including 26 protein coding genes, 10 tRNA genes, and 3 rRNA genes. Repeat sequence analysis and prediction of RNA editing sites revealed a total of 850 dispersed repeats, 1,205 simple repeats, 61 tandem repeats, and 120 RNA editing sites. Analysis of codon usage indicates that codons ending in A/U are preferred. Gene migration between the mitochondrial genome and the chloroplast genome was observed through homologous fragment detection. In addition, Ka/Ks analysis showed that most protein coding genes in the mitochondrial genome experienced negative selection, while only the nad3 gene experienced potential positive selection in most Alismatales. Nucleotide polymorphism analysis revealed variations in each gene, with rpl10 being the most significant. In addition, comparative analysis shows that the GC content is conserved, but there are significant differences in the size and structure of mitochondrial genomes among different species of Alismatales. The phylogenetic analysis based on the mitochondrial genome reflects the exact evolutionary and taxonomic status of H. beccarii.ConclusionIn this study, we sequenced and annotated the mitochondrial genome of H. beccarii, and compared it with the mitochondrial genomes of other plants in Alismatales. Our findings enrich the mitogenome database of seagrass plants and highlight the potential for mitochondrial genes to help decipher plant evolutionary history.

Comprehensive Analysis and Verification of the Prognostic Significance of Cuproptosis-Related Genes in Colon Adenocarcinoma

Colon adenocarcinoma (COAD) is a frequently occurring and lethal cancer. Cuproptosis is an emerging type of cell death, and the underlying pathways involved in this process in COAD remain poorly understood. Transcriptomic and clinical data for COAD patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We investigated alterations in DNA and chromatin of cuproptosis-related genes (CRGs) in COAD. In order to identify predictive differentially expressed genes (DEGs) and various molecular subtypes, we used consensus cluster analysis. Through univariate, multivariate, and Lasso Cox regression analyses, four CRGs were identified. A risk prognostic model for cuproptosis characteristics was constructed based on four CRGs. This study also examined the association between the risk score and the tumor microenvironment (TME), the immune landscape, and drug sensitivity. We distinguished two unique molecular subtypes using consensus clustering analysis. We discovered that the clinical characteristics, prognosis, and TME cell infiltration characteristics of patients with multilayer CRG subtypes were all connected. The internal and external evaluations of the predicted accuracy of the prognostic model built using data derived from a cuproptosis risk score were completed at the same time. A nomogram and a clinical pathological analysis make it more useful in the field of medicine. A significant rise in immunosuppressive cells was observed in the high cuproptosis risk score group, with a correlation identified between the cuproptosis risk score and immune cell infiltration. Despite generally poor prognoses, the patients with a high cuproptosis risk but low tumor mutation burden (TMB), cancer stem cell (CSC) index, or microsatellite instability (MSI) may still benefit from immunotherapy. Furthermore, the cuproptosis risk score positively correlated with immune checkpoint gene expression. Analyzing the potential sensitivity to medications could aid in the development of clinical chemotherapy regimens and decision-making. CRGs are the subject of our in-depth study, which exposed an array of regulatory mechanisms impacting TME. In addition, we performed additional data mining into clinical features, prognosis effectiveness, and possible treatment medications. COAD’s molecular pathways will be better understood, leading to more precise treatment options.

Systematic identification and expression profiling of calmodulin-binding transcription activator genes reveal insights into their functional diversity against pathogens in sugarcane

The calmodulin-binding transcription activator (CAMTA) proteins in plants play significant roles in signal-transduction, activation of regulatory networks, and defense response against environmental stressors. In this study we systematically identified a total 17 CAMTA genes (named as SsnpCAMTAs) in Saccharum spontaneum Np-X genome. Moreover, SsnpCAMTAs exhibited diverse physio-chemical and gene structural attributes. Notably, eight SsnpCAMTA gene pairs displayed segmental duplication events, while CAMTA genes from S. spontaneum Np-X and Arabidopsis thaliana shared homology relationship. In-vitro interaction networking showed that SsnpCAMTA1 and SsnpCAMTA2 were the core protein which interacted with each other as well as with other four different proteins (SsnpCAMTA5/7/13/17). To check functional variability, the expression profiles of SsnpCAMTAs were quantified in transcriptomic and proteomic datasets triggered by Xanthomonas albilineans (Xa) and Acidovorax avenae subsp. avenae (Aaa). The temporal expression of SsnpCAMTA4/5 was ranged between 1.7–3.5 folds in sugarcane cultivars triggered by Xa infection. Most of the SsnpCAMTAs exhibited irregular expression profile in sugarcane cultivars triggered by Aaa infection. Additionally, transcript expression profiles of eight candidate genes SsnpCAMTA1/2/5/7/8/12/13/17 were determined by RT-qPCR assay in sugarcane cultivars Zhongtang3 (resistant to smut) and ROC22 (susceptible to smut) under Sporisorium scitamineum pathogen infection. Interestingly, the transcript expression of SsnpCAMTA5 was upregulated from 1.4 to 10.8 folds as compared to control in both cultivars, while SsnpCAMTA8 was downregulated in both cultivars. Overall, our results provide valuable candidate gene resources for the development of disease-resistant sugarcane cultivars in the face of current climate change scenarios.

Unlocking the role of novel primary/di-amine oxidases in crop improvement: Tissue specificity leads to specific roles connected to abiotic stress, hormone responses and sensing nitrogen

Genetic improvements of solanaceous crops for quality and stress responsive traits are needed because of the central role vegetables and fruits have in providing nutrients to human diets. Copper amine oxidase (CuAO) encoding genes involved in metabolism of primary/di-amine nitrogenous compounds, play a role in balancing internal nitrogen (N) pools especially when external N supply fluctuates during growth, development and environmental stresses. In the present study, we investigated the occurrence, molecular evolution and possible role(s) of these unknown genes in tomato crops. Multiple genome-wide bioinformatics approaches led to the identification of eight bona fide CuAO genes (SlCuAO1–SlCuAO8) in the tomato genome with gene numbers like those in Arabidopsis and rice indicating their conserved functional relevance with a tandemly duplicated SlCuAO6-SlCuAO7 pair at chr.9. A conserved intron-exon size and phase distribution for SlCuAO2, 3, 4 pairs are similar to a recently identified single duckweed SpCuAO1 orthologue gene indicating its evolutionary conservation. Synteny analysis showed their closest association to Arabidopsis and but not with rice. Transcriptome data indicated that gene expression for about six genes (SlCuAO1, 2, 3, 4, 6, 7) is root specific, fruit specific for SlCuAO5 and flower specific for SlCuAO8 thus indicating amine oxidation is variable across tissues with a prominance in the root tissue. The majority of CuAO genes are negatively regulated by methyl jasmonate. Positive regulation, however, involves CuAO3/8. Transcript analysis of the ethylene-deficient transgenic lines indicated that ethylene is required for activation of SlCuAO4. CuAO4 and CuAO5 exhibited most significant tissues-independent gene expression responses across various nitrogen regimes. Drought, heat and N stress identified CuAO5 as an overlapping highly expressed gene that corroborates with putrescine accumulation for free and conjugated forms with an opposite abundance of bound forms. Taken together our study highlights new insights into the roles of copper amine oxidation genes and identifies CuAO5 as a multiple stress induced gene that can be used in genetic improvement programs for combining heat, drought and nitrogen use efficiency related traits.

Deciphering the oncogenic potential of ADAM9 in hepatocellular carcinoma through bioinformatics and experimental approaches

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. This study investigates the role and mechanisms of ADAM9 as a biomarker and potential therapeutic target in HCC. Utilizing RNA-sequencing data and clinicopathological characteristics from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we conducted survival and meta-analyses, functional enrichment, and immune infiltration studies. Additionally, we evaluated the effects of ADAM9 silencing on HCC cell proliferation, migration, and invasion through in vitro experiments. Our results demonstrate that high ADAM9 expression is associated with poor prognosis and increased immune infiltration in HCC patients. Furthermore, ADAM9 knockdown significantly inhibited tumor cell proliferation and migration. These findings indicate that ADAM9 is a promising prognostic biomarker and potential therapeutic target in HCC. In conclusion, ADAM9 could offer avenues for developing strategies to inhibit tumor progression and improve patient outcomes.

Genome-wide analyses of Ariadne family genes reveal their involvement in abiotic stress responses in apple

E3 ligases are essential for ubiquitination and play a role in regulating various aspects of eukaryotic life. Ariadne (ARI) proteins, a subfamily of RBR (RING-between-RING) proteins, have been recognized as a new class of RING-finger E3 ligases. Recent research has shed light on their potential involvement in plants’ responses to abiotic stress. However, comprehensive studies on ARI genes in apple (Malus domestica) are still lacking. This study identified ten MdARI genes in the apple genome, and examined intraspecific and interspecific collinearity to explore the evolutionary relationships of ARI family members. Phylogenetic analyses classified MdARIs into two subfamilies (A and B), and by integrating gene structure, conserved motifs, and sequence comparison results, subfamily B was further divided into two subgroups (I and II). Tissue expression analyses revealed varied expression patterns of MdARI genes in different tissues, and subcellular localization showed that MdARI1-1, MdARI1-2, and MdARI9-1 were located in the nucleus, while the other seven MdARIs were distributed throughout the cell. Analyses of promoter cis-elements and expression patterns under cold, salt, and drought treatments indicated the involvement of MdARIs in abiotic stress responses. Several proteins crucial to the plant stress response were predicted to be potential MdARIs-interacting proteins based on the protein interaction network. Additionally, the interaction between UBC11 (E2) and MdARI7-2 was confirmed by a yeast two-hybrid (Y2H) experiment, suggesting that MdARI7-2 may function as an E3. These findings will greatly benefit future research on the role and mechanisms of ARI proteins in apple stress response.