{"title":"Mapping the evolutionary and translational landscape of antibiotic resistance genes in Elizabethkingia anopheles.","authors":"Ujwal Dahal, Anu Bansal, Bhumandeep Kour, Mukti Ram Aryal, Archana Gautam","doi":"10.1007/s00438-026-02394-3","DOIUrl":"https://doi.org/10.1007/s00438-026-02394-3","url":null,"abstract":"","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147444373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-11DOI: 10.1007/s00438-026-02378-3
Flavia Thiebaut, Maria Clara Urquiaga, Paula Machado de Araújo, Aislan de Carvalho Vivarini, Clicia Grativol
Legumes are essential components of global cropping systems due to their nutritional value and contribution to sustainable agriculture. Among the regulatory molecules, small RNAs (sRNAs), particularly microRNAs (miRNAs), play crucial roles in plant development and in responses to biotic and abiotic stresses. miRNAs regulate genes involved in diverse developmental processes, including nodule formation, which is fundamental for the nitrogen-fixing symbiosis that characterizes legumes. Functional studies have demonstrated that miRNAs are key modulators of plant defense, contributing to resistance against pathogens and environmental challenges. Moreover, miRNAs also participate in cross-kingdom communication, such as plant-bacteria interactions, influencing symbiotic efficiency. Advances in molecular biology have enabled the manipulation of miRNAs and their targets for crop improvement. Current approaches include the design of artificial miRNAs (amiRNA), modulation of miRNA expression through miRNA-encoded peptides, genome editing of non-coding genes using CRISPR/Cas9, and the application of RNA interference (RNAi) technology. Together, these strategies highlight the potential of miRNA-based tools in plant biotechnology. A deeper understanding of the molecular mechanisms governing miRNA-mediated gene silencing will provide powerful resources for optimizing legume productivity and resilience within sustainable agricultural systems.
{"title":"Small but big player: the important role of microRNAs in legume crops.","authors":"Flavia Thiebaut, Maria Clara Urquiaga, Paula Machado de Araújo, Aislan de Carvalho Vivarini, Clicia Grativol","doi":"10.1007/s00438-026-02378-3","DOIUrl":"10.1007/s00438-026-02378-3","url":null,"abstract":"<p><p>Legumes are essential components of global cropping systems due to their nutritional value and contribution to sustainable agriculture. Among the regulatory molecules, small RNAs (sRNAs), particularly microRNAs (miRNAs), play crucial roles in plant development and in responses to biotic and abiotic stresses. miRNAs regulate genes involved in diverse developmental processes, including nodule formation, which is fundamental for the nitrogen-fixing symbiosis that characterizes legumes. Functional studies have demonstrated that miRNAs are key modulators of plant defense, contributing to resistance against pathogens and environmental challenges. Moreover, miRNAs also participate in cross-kingdom communication, such as plant-bacteria interactions, influencing symbiotic efficiency. Advances in molecular biology have enabled the manipulation of miRNAs and their targets for crop improvement. Current approaches include the design of artificial miRNAs (amiRNA), modulation of miRNA expression through miRNA-encoded peptides, genome editing of non-coding genes using CRISPR/Cas9, and the application of RNA interference (RNAi) technology. Together, these strategies highlight the potential of miRNA-based tools in plant biotechnology. A deeper understanding of the molecular mechanisms governing miRNA-mediated gene silencing will provide powerful resources for optimizing legume productivity and resilience within sustainable agricultural systems.</p>","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12979330/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-10DOI: 10.1007/s00438-026-02386-3
Yupeng Liu, Han Zhang, Rui Hu, Hui Zhang, Xiaochen Zhang
{"title":"Multi-task molecular representation learning based on soft prompting of the important subgraph.","authors":"Yupeng Liu, Han Zhang, Rui Hu, Hui Zhang, Xiaochen Zhang","doi":"10.1007/s00438-026-02386-3","DOIUrl":"https://doi.org/10.1007/s00438-026-02386-3","url":null,"abstract":"","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-10DOI: 10.1007/s00438-026-02365-8
Necati Kaan Kutlu, Hüseyin Güner, Gökhan Karakülah
{"title":"TEffectBayes: a nextflow pipeline for exploring the potential effect of transposable elements in gene regulatory network with multi-omic Bayesian network model.","authors":"Necati Kaan Kutlu, Hüseyin Güner, Gökhan Karakülah","doi":"10.1007/s00438-026-02365-8","DOIUrl":"https://doi.org/10.1007/s00438-026-02365-8","url":null,"abstract":"","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-10DOI: 10.1007/s00438-026-02384-5
Saeid Sadeghi Ghazi Chaki, Maryam Abdulrahman Najim, Lina A Hassan, Saleh A S AlAbdulhadi, Zahraa Abbas Al-Khafaji, M K Sharma, Ahmed Shihab Ahmed, Ali Batool Ahmed, Malik Bader Alazzam, Mohammad Sholeh
<p><p>Staphylococcus aureus is increasingly resistant to β-lactam antibiotics, making non-β-lactam cell-wall-targeting drugs crucial alternatives. Growing resistance to these agents highlights the need to identify genomic factors influencing susceptibility. Machine learning can integrate genomic and phenotypic data to predict minimum inhibitory concentrations (MICs) and uncover resistance mechanisms across time and regions. We obtained 112,360 S. aureus genomes from NCBI GenBank (March 2024), applying quality filters and standardizing metadata. Resistance genes and mutations were identified using AMRFinderPlus and CARD, focusing on glycopeptide, lipopeptide, bacitracin, and fosfomycin resistance. MICs for five antibiotics were compiled, standardized, and log₂-transformed for analysis. Allelic profiles for seven housekeeping genes were assigned using PubMLST's BIGSdb and MLST CLI v2.19.0. Temporal and geographic resistance trends were modeled using logistic regression and statistical tests. Machine learning models (Random Forest, XGBoost, Elastic Net, Partial Least Squares (PLS)) predicted MICs from genomic features, with performance assessed via cross-validation. Statistical analyses and visualizations were performed in R, with all data and scripts provided for reproducibility. We analyzed 111,350 S. aureus genomes from 137 countries, with 78% from clinical sources, 10% from environmental, veterinary, or food-related origins, and some from animals. Glycopeptide MICs were low across all sources: vancomycin (0.96 µg/mL) and teicoplanin (0.52 µg/mL), while daptomycin showed more variability (0.44 µg/mL). Fosfomycin resistance genes, particularly fosB, were detected in 65.3% of genomes overall, with significantly higher prevalence in clinical isolates (32.5%) compared to environmental (2.1%), food (4.0%), and animal sources (7.5%). Bacitracin resistance genes (bcrAB) were detected in 6.2% of clinical isolates versus 1.3% environmental and 2.8% animal sources. However, phenotypic MIC data were severely limited (fosfomycin n = 1, bacitracin n = 1), precluding validation of genotype-phenotype correlations and limiting epidemiological interpretation to genetic prevalence alone. Resistance to glycopeptides and lipopeptides remained rare (< 0.1%). Fosfomycin resistance protein B (fosB) resistance increased by 0.20% annually, especially in clinical and animal sources, while other mutations like glpT_V213I and murA_D278E declined. Geographic trends showed fosB resistance exceeded 50% in North America, Europe, and South America, with MurA_G257D most prevalent in the Middle East. Machine learning models showed moderate predictive performance for daptomycin MICs (R² = 0.49), with mprF mutations as key predictors, but demonstrated poor accuracy for glycopeptides (vancomycin R² = 0.05; teicoplanin R² = -0.13) due to extremely limited MIC variability in the dataset. Fosfomycin and bacitracin models could not be trained due to insufficient phenotypic data (n = 1 ea
{"title":"Staphylococcus aureus resistance to non-β-lactam antibiotics: global genomic epidemiology and machine learning feasibility assessment.","authors":"Saeid Sadeghi Ghazi Chaki, Maryam Abdulrahman Najim, Lina A Hassan, Saleh A S AlAbdulhadi, Zahraa Abbas Al-Khafaji, M K Sharma, Ahmed Shihab Ahmed, Ali Batool Ahmed, Malik Bader Alazzam, Mohammad Sholeh","doi":"10.1007/s00438-026-02384-5","DOIUrl":"https://doi.org/10.1007/s00438-026-02384-5","url":null,"abstract":"<p><p>Staphylococcus aureus is increasingly resistant to β-lactam antibiotics, making non-β-lactam cell-wall-targeting drugs crucial alternatives. Growing resistance to these agents highlights the need to identify genomic factors influencing susceptibility. Machine learning can integrate genomic and phenotypic data to predict minimum inhibitory concentrations (MICs) and uncover resistance mechanisms across time and regions. We obtained 112,360 S. aureus genomes from NCBI GenBank (March 2024), applying quality filters and standardizing metadata. Resistance genes and mutations were identified using AMRFinderPlus and CARD, focusing on glycopeptide, lipopeptide, bacitracin, and fosfomycin resistance. MICs for five antibiotics were compiled, standardized, and log₂-transformed for analysis. Allelic profiles for seven housekeeping genes were assigned using PubMLST's BIGSdb and MLST CLI v2.19.0. Temporal and geographic resistance trends were modeled using logistic regression and statistical tests. Machine learning models (Random Forest, XGBoost, Elastic Net, Partial Least Squares (PLS)) predicted MICs from genomic features, with performance assessed via cross-validation. Statistical analyses and visualizations were performed in R, with all data and scripts provided for reproducibility. We analyzed 111,350 S. aureus genomes from 137 countries, with 78% from clinical sources, 10% from environmental, veterinary, or food-related origins, and some from animals. Glycopeptide MICs were low across all sources: vancomycin (0.96 µg/mL) and teicoplanin (0.52 µg/mL), while daptomycin showed more variability (0.44 µg/mL). Fosfomycin resistance genes, particularly fosB, were detected in 65.3% of genomes overall, with significantly higher prevalence in clinical isolates (32.5%) compared to environmental (2.1%), food (4.0%), and animal sources (7.5%). Bacitracin resistance genes (bcrAB) were detected in 6.2% of clinical isolates versus 1.3% environmental and 2.8% animal sources. However, phenotypic MIC data were severely limited (fosfomycin n = 1, bacitracin n = 1), precluding validation of genotype-phenotype correlations and limiting epidemiological interpretation to genetic prevalence alone. Resistance to glycopeptides and lipopeptides remained rare (< 0.1%). Fosfomycin resistance protein B (fosB) resistance increased by 0.20% annually, especially in clinical and animal sources, while other mutations like glpT_V213I and murA_D278E declined. Geographic trends showed fosB resistance exceeded 50% in North America, Europe, and South America, with MurA_G257D most prevalent in the Middle East. Machine learning models showed moderate predictive performance for daptomycin MICs (R² = 0.49), with mprF mutations as key predictors, but demonstrated poor accuracy for glycopeptides (vancomycin R² = 0.05; teicoplanin R² = -0.13) due to extremely limited MIC variability in the dataset. Fosfomycin and bacitracin models could not be trained due to insufficient phenotypic data (n = 1 ea","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-10DOI: 10.1007/s00438-026-02385-4
Xu Lu, Yan Xu, Jiaxin Liu, Jian Chen
Diabetic foot ulcers (DFU) are a severe complication of diabetes. Although dysregulated M2 macrophage polarization is recognized as a key driver of chronic inflammation in DFU, the molecular checkpoints that can be therapeutically targeted to restore M2 bias remain poorly defined. Here, we aimed to determine whether the RNA-binding protein TAF15 acts as a post-transcriptional stabilizer of the M2-promoting CEBPB/APOE/PTX3 axis, thereby accelerating DFU healing. First, we confirmed that APOE positively regulates PTX3, which supports M2 polarization and the proliferation and migration of HDF. CEBPB transcriptionally activated APOE and promoted M2 macrophage polarization. TAF15 stabilized CEBPB mRNA and affected HDF cell proliferation and migration by promoting M2 macrophage polarization. Additionally, TAF15 overexpression partially counteracted the disruption of M2 macrophage polarization caused by APOE silencing and facilitated DFU wound healing. Collectively, our findings establish TAF15-driven stabilization of CEBPB mRNA as a target point that sequentially activates APOE/PTX3 signaling to enforce M2 polarization and accelerate DFU closure. This study provides a preclinical rationale for the development of TAF15-targeted oligonucleotides or small-molecule strategies to reprogram wound macrophages and improve DFU outcomes in patients with diabetes.
{"title":"TAF15 promotes the healing of diabetic foot ulcers by mediating the transcriptional activation of APOE through CEBPB to regulate PTX3.","authors":"Xu Lu, Yan Xu, Jiaxin Liu, Jian Chen","doi":"10.1007/s00438-026-02385-4","DOIUrl":"https://doi.org/10.1007/s00438-026-02385-4","url":null,"abstract":"<p><p>Diabetic foot ulcers (DFU) are a severe complication of diabetes. Although dysregulated M2 macrophage polarization is recognized as a key driver of chronic inflammation in DFU, the molecular checkpoints that can be therapeutically targeted to restore M2 bias remain poorly defined. Here, we aimed to determine whether the RNA-binding protein TAF15 acts as a post-transcriptional stabilizer of the M2-promoting CEBPB/APOE/PTX3 axis, thereby accelerating DFU healing. First, we confirmed that APOE positively regulates PTX3, which supports M2 polarization and the proliferation and migration of HDF. CEBPB transcriptionally activated APOE and promoted M2 macrophage polarization. TAF15 stabilized CEBPB mRNA and affected HDF cell proliferation and migration by promoting M2 macrophage polarization. Additionally, TAF15 overexpression partially counteracted the disruption of M2 macrophage polarization caused by APOE silencing and facilitated DFU wound healing. Collectively, our findings establish TAF15-driven stabilization of CEBPB mRNA as a target point that sequentially activates APOE/PTX3 signaling to enforce M2 polarization and accelerate DFU closure. This study provides a preclinical rationale for the development of TAF15-targeted oligonucleotides or small-molecule strategies to reprogram wound macrophages and improve DFU outcomes in patients with diabetes.</p>","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The molecular details of endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) and their functional significance in combating environmental stress in crop species remain inadequately elucidated. Tomato (Solanum lycopersicum) is an important crop, sensitive to temperature, and serves as a model crop plant for studying these pathways. To establish a tomato UPR transcriptome profile, we performed RNA sequencing (RNA-seq) analysis of tomato seedlings under tunicamycin (Tm)-induced ER stress. The 339 differentially expressed genes encompassed traditional ER stress markers, ER-associated degradation elements, transcription factors, and novel candidate genes. Our functional analysis of key UPR genes, viz., SlIRE1A, SlIRE1B, SlbZIP60, and SlbZIP28, using Virus-Induced Gene Silencing (VIGS) revealed differential requirements for SlIRE1A and SlIRE1B in the Tm-induced upregulation of downstream genes. Additionally, we found that the expression of most of the downstream genes we analyzed was equally dependent on both the IRE1 and bZIP28 pathways. The expression analysis of several of these genes under environmental stress conditions indicated that their expression patterns did not align with those observed during ER stress. Furthermore, our analysis of VIGS plants subjected to heat stress revealed that the regulation of reactive oxygen species (ROS) levels in tomato depends on the IRE1-bZIP60 pathway. Overall, this study provides a comprehensive analysis of UPR pathways in tomato and offers essential molecular insights for developing resilient tomato cultivars that can withstand adverse environmental conditions.
{"title":"Transcriptome analysis coupled with virus induced gene silencing delineates the unfolded protein response of tomato.","authors":"Ankita Rana, Navpreet Kaur, Ajay Kumar Pandey, Pramod Kaitheri Kandoth","doi":"10.1007/s00438-026-02400-8","DOIUrl":"https://doi.org/10.1007/s00438-026-02400-8","url":null,"abstract":"<p><p>The molecular details of endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) and their functional significance in combating environmental stress in crop species remain inadequately elucidated. Tomato (Solanum lycopersicum) is an important crop, sensitive to temperature, and serves as a model crop plant for studying these pathways. To establish a tomato UPR transcriptome profile, we performed RNA sequencing (RNA-seq) analysis of tomato seedlings under tunicamycin (Tm)-induced ER stress. The 339 differentially expressed genes encompassed traditional ER stress markers, ER-associated degradation elements, transcription factors, and novel candidate genes. Our functional analysis of key UPR genes, viz., SlIRE1A, SlIRE1B, SlbZIP60, and SlbZIP28, using Virus-Induced Gene Silencing (VIGS) revealed differential requirements for SlIRE1A and SlIRE1B in the Tm-induced upregulation of downstream genes. Additionally, we found that the expression of most of the downstream genes we analyzed was equally dependent on both the IRE1 and bZIP28 pathways. The expression analysis of several of these genes under environmental stress conditions indicated that their expression patterns did not align with those observed during ER stress. Furthermore, our analysis of VIGS plants subjected to heat stress revealed that the regulation of reactive oxygen species (ROS) levels in tomato depends on the IRE1-bZIP60 pathway. Overall, this study provides a comprehensive analysis of UPR pathways in tomato and offers essential molecular insights for developing resilient tomato cultivars that can withstand adverse environmental conditions.</p>","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Common fungal extracellular membrane (CFEM) domain-containing proteins are small cysteine-rich proteins exclusive to fungi. They are shown to contribute to fungal virulence by promoting appressorium development and suppressing plant immune response. This study aimed to investigate the role of CFEM-domain-containing proteins in fungal antagonism and beneficial fungus-plant interactions using the mycoparasitic fungus Clonostachys rosea IK726, a biocontrol agent against several fungal pathogens. Gene expression analysis of 21 C. rosea IK726 CFEM-encoding genes during in vitro interactions with fungal hosts Botrytis cinerea and Rhizoctonia solani showed that their expression patterns depend on the host and interaction stage. CFEM10, predicted to have antimicrobial activity, was expressed in Escherichia coli and purified. An in vitro assay using purified CFEM10 protein revealed its antimicrobial activity against E. coli and Saccharomyces cerevisiae. Functional analysis of CFEM10 using gene deletion strains showed a significant difference (P = 0.01) in conidial production between the WT and Δcfem10 strains. However, no significant difference was found in fungal antagonisms against B. cinerea, Fusarium graminearum or R. solani, root colonization ability and biocontrol of fusarium foot and root rot between the WT and Δcfem10 strains. Similarly, transient expression of cfem10 in tobacco leaves failed to suppress hypersensitive response (HR) induced by Avr4/Cf4 complex. In summary, our results demonstrated the antimicrobial activity of CFEM10 and its involvement in fungal conidiation. Functional analysis of several CFEM-domain-containing proteins is needed to comprehensively evaluate their roles in fungal antagonism and beneficial interactions with plant hosts.
{"title":"Functional characterization of a CFEM domain-containing protein in the mycoparasitic fungus Clonostachys rosea reveals antimicrobial activity and a role in conidiation.","authors":"Isaak Iliopoulos, Anastasios Samaras, Susmita Sigdel, Linnéa Forslund, Magnus Karlsson, Georgios Tzelepis, Mukesh Dubey","doi":"10.1007/s00438-026-02390-7","DOIUrl":"10.1007/s00438-026-02390-7","url":null,"abstract":"<p><p>Common fungal extracellular membrane (CFEM) domain-containing proteins are small cysteine-rich proteins exclusive to fungi. They are shown to contribute to fungal virulence by promoting appressorium development and suppressing plant immune response. This study aimed to investigate the role of CFEM-domain-containing proteins in fungal antagonism and beneficial fungus-plant interactions using the mycoparasitic fungus Clonostachys rosea IK726, a biocontrol agent against several fungal pathogens. Gene expression analysis of 21 C. rosea IK726 CFEM-encoding genes during in vitro interactions with fungal hosts Botrytis cinerea and Rhizoctonia solani showed that their expression patterns depend on the host and interaction stage. CFEM10, predicted to have antimicrobial activity, was expressed in Escherichia coli and purified. An in vitro assay using purified CFEM10 protein revealed its antimicrobial activity against E. coli and Saccharomyces cerevisiae. Functional analysis of CFEM10 using gene deletion strains showed a significant difference (P = 0.01) in conidial production between the WT and Δcfem10 strains. However, no significant difference was found in fungal antagonisms against B. cinerea, Fusarium graminearum or R. solani, root colonization ability and biocontrol of fusarium foot and root rot between the WT and Δcfem10 strains. Similarly, transient expression of cfem10 in tobacco leaves failed to suppress hypersensitive response (HR) induced by Avr4/Cf4 complex. In summary, our results demonstrated the antimicrobial activity of CFEM10 and its involvement in fungal conidiation. Functional analysis of several CFEM-domain-containing proteins is needed to comprehensively evaluate their roles in fungal antagonism and beneficial interactions with plant hosts.</p>","PeriodicalId":18816,"journal":{"name":"Molecular Genetics and Genomics","volume":"301 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12975806/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147434285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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