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PubMed2026

Enhanced Production of Recombinant Thermophilic Xylanase X11P in Ogataea polymorpha via In-Silico Signal Peptide Discovery and Fed-Batch Fermentation.

Efficient secretion of heterologous proteins is essential for advancing yeast-based bioprocesses, yet signal peptide (SP) optimization in the thermotolerant methylotrophic yeast Ogataea polymorpha remains limited. This study integrates in-silico SP discovery, experimental validation, and bioprocess engineering to enhance secretion of the thermophilic xylanase X11P under sucrose-inducible expression. Genome-wide screening of 5184 O. polymorpha proteins using SignalP, Phobius, DeepLoc, WoLF PSORT, and ProP identified 11 high-confidence SP candidates. Comparative analysis with Komagataella phaffii endogenous proteins guided selection of seven SPs for experimental evaluation. Among these, the novel O. polymorpha α-mating factor-like peptide FUN_005010 exhibited strong secretion-promoting activity, with its prepro-sequence yielding the highest extracellular xylanase levels and outperforming the classical Saccharomyces cerevisiae α-MF. To evaluate industrial applicability, sucrose-based fermentation strategies were systematically optimized in a 5-L bioreactor. Controlled sucrose feeding and balanced C/N ratios were found to be critical for maximizing maltase (MAL) promoter-driven expression. A stepwise increasing sucrose feed combined with induction at 30°C enabled X11P titers up to 770 U/mL, representing a 15-fold improvement over shake-flask cultures. This work demonstrates that the combination of SP evaluation and optimized sucrose-inducible fed-batch operation significantly enhances X11P production in O. polymorpha. The identified FUN_005010-prepro SP and the refined process framework provide valuable tools for developing O. polymorpha as a high-performance industrial expression platform.

Fermentation↗

PubMed2025

Genomic mapping of diabetic kidney disease biomarkers and identification of potential inhibitors through virtual screening.

BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus, marked by a multifactorial pathogenesis and the absence of sensitive diagnostic biomarkers. Identifying novel molecular targets and therapeutic options is essential to improve early diagnosis and treatment outcomes. METHODS: To uncover potential biomarkers and therapeutic candidates, we performed an integrated genomic analysis using microarray and RNA-seq datasets from the Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) databases. Differentially expressed genes (DEGs) were identified and subjected to protein-protein interaction (PPI) network analysis. Key genes were further explored through virtual screening of an FDA-approved compound library using molecular docking techniques. Drug-likeness was assessed via Lipinski's rule of five. RESULTS: A total of 40 DEGs were identified, among which ISCU (downregulated; involved in iron-sulfur cluster biogenesis) and AP1S2 (upregulated; associated with vesicular trafficking) emerged as potential biomarkers. PPI analysis revealed their involvement in critical DKD-related pathways, such as extracellular matrix remodeling and oxidative stress. Virtual screening identified six FDA-approved compounds with high binding affinity (≤-7.96 kcal/mol) to ISCU, notably ZINC000001576020, all of which complied with Lipinski's rule. CONCLUSIONS: This in-silico study nominates ISCU and AP1S2 as candidate diagnostic biomarkers for DKD and identifies computationally prioritized inhibitors targeting ISCU. These findings require experimental validation but provide a molecular framework for precision diagnosis and therapeutic development. These findings offer new molecular insights that could inform precision diagnosis and personalized treatment strategies for diabetic kidney disease.

Diabetic Nephropathies↗

PubMed2006

Building a European biomedical grid on cancer: the ACGT Integrated Project.

This paper presents the needs and requirements that led to the formation of the ACGT (Advancing Clinico Genomic Trials) integrated project, its vision and methodological approaches of the project. The ultimate objective of the ACGT project is the development of a European biomedical grid for cancer research, based on the principles of open access and open source, enhanced by a set of interoperable tools and services which will facilitate the seamless and secure access to and analysis of multi-level clinico-genomic data, enriched with high-performing knowledge discovery operations and services. By doing so, it is expected that the influence of genetic variation in oncogenesis will be revealed, the molecular classification of cancer and the development of individualised therapies will be promoted, and finally the in-silico tumour growth and therapy response will be realistically and reliably modelled. Its main design decisions and results at its current stage of development are presented.

Biomedical Research↗

PubMed2026

The gonadal matrisome and its correlation with sex change in the ricefield eel Monopterus albus.

The matrisome is a comprehensive list of genes in the genome of an organism, which encodes proteins constituting or interacting with the extracellular matrix (ECM). The gonadal ECM is important for folliculogenesis and spermatogenesis. This study characterized the composition of the matrisome and the expression of matrisome genes in the gonad of ricefield eel, a protogynous sex-changing teleost, during sex change. A total of 838 matrisome genes were identified in the genome of ricefield eel through an in-silico orthology-based approach, of which 482, 443, 429, and 570 matrisome genes were shown to be expressed in the gonads of female (F), early intersexual (EI), mid-intersexual (MI), and late intersexual (LI) fish, respectively. Differentially expressed matrisome genes (DEMGs) were observed across all the sexual stages as well as in each category of ECM components. Analysis of DEMGs in the comparison between EI and F revealed dramatic upregulation of adam8a, mmp9, and s100a11 while downregulation of col4a5, col15a1b, clec3ba, f13a1, and ccl44, which were further confirmed by qPCR analysis. Together, these findings revealed significant changes in the expression of many matrisome genes, particularly three regulator genes, adam8a, mmp9 and f13a1, as female ricefield eels initiate sex change, suggesting that gonadal tissues undergo dramatic remodeling involving the regression of ovarian tissues and the development of testicular tissues to facilitate this process. These data provide valuable resources for further unraveling the roles of matrisome genes in gonadal development of ricefield eel and other vertebrates.

Animals↗

PubMed2026

Comparative in silico analysis of Apis mellifera immune responses to Varroa destructor and Tropilaelaps mercedesae: Common and mite-specific molecular signatures.

Parasitic mites Varroa destructor and Tropilaelaps mercedesae represent major threats to global honey bee (Apis mellifera) health and productivity, yet comparative molecular insights into host responses remain limited. To address this, we systematically compiled published studies (2015-2025) reporting genes associated with honey bee interactions with V. destructor (11 studies, 87 genes), T. mercedesae (4 studies, 35 genes), and hygienic behavior (6 studies, 44 genes). Gene identifiers were harmonized to the Amel_HAv3.1 genome assembly, yielding three non-redundant sets: 64 Varroa-associated, 34 Tropilaelaps-associated, and 44 hygienic behavior-associated genes. Venn analysis identified 10 overlapping genes (including A0A088A8D5, A0A088ADL8, ABAE_APIME, Def1, Def2, Gapdh, HYTA_APIME, Imd, LOC726783, and Vg), suggesting conserved defense mechanisms, while 41 and 24 genes were uniquely associated with Varroa and Tropilaelaps, respectively. Enrichment analyses revealed Varroa-responsive genes were enriched in immune processes, chitin catabolism, and signaling pathways (Toll/Imd, MAPK, Wnt). Tropilaelaps-associated genes were enriched for antibacterial defense and stress response, with Toll/Imd signaling as the sole significantly enriched pathway. Overlapping genes reinforced core innate immunity activation. Protein-protein interaction network centrality analysis identified key hub genes: Def1, HYTA_APIME, ABAE_APIME, PPO, Imd, PGRP-LC, Vg for Varroa; and ACPH1_APIME, MRJP1, Vg, LOC726783 for Tropilaelaps. Results demonstrate that, despite differences in mite biology, honey bees show a conserved immune response against both parasites, centered on antibacterial defense, humoral immunity, and activation of the Toll/Imd pathway. Although limited by the in-silico nature and research asymmetries reflecting Tropilaelaps' emergence, this curated resource establishes a comprehensive framework for elucidating shared and distinct molecular defense mechanisms. Ultimately, this approach prioritizes diagnostic markers and candidate genes for functional validation and breeding strategies to enhance colony resilience against mite‑driven disease globally.

Animals↗

PubMedDate not supplied

Generalized fragment-substructure based property prediction method.

The need for fast and accurate predictors of pharmaceutically important properties has been increasing due to pressure from high-throughput screening, in-silico screening, and the need to more rapidly identify potential pharmacokinetic issues before drugs advance to the more expensive clinical development stages. A novel method for making predictive models based on decomposing 2D structure into component structural fragments is used to model logP, water solubility, and melting point. The fragment orientation of the method facilitates understanding of how molecules might be altered to improve the desired properties. The 2D structure-based descriptor is computed by analysis of the target molecules with a substructure searching algorithm and a set of fragments selected for chemical and pharmaceutical relevance. These are combined with partial least squares to create predictive models. The correlation coefficients achieved are 0.86 for logP (SE = 0.68), 0.73 for logS (SE = 0.89), and 0.64 (SE = 48.9 degrees) for melting point over diverse data sets of 11,447, 2427, and 5598 molecules, respectively. The models were verified via test sets of compounds not included in the training set.

Journal Article↗

PubMedDate not supplied

Computational modeling of oligonucleotide positional densities for human promoter prediction.

OBJECTIVE: The gene promoter region controls transcriptional initiation of a gene, which is the most important step in gene regulation. In-silico detection of promoter region in genomic sequences has a number of applications in gene discovery and understanding gene expression regulation. However, computational prediction of eukaryotic poly-II promoters has remained a difficult task. This paper introduces a novel statistical technique for detecting promoter regions in long genomic sequences. METHOD: A number of existing techniques analyze the occurrence frequencies of oligonucleotides in promoter sequences as compared to other genomic regions. In contrast, the present work studies the positional densities of oligonucleotides in promoter sequences. The analysis does not require any non-promoter sequence dataset or any model of the background oligonucleotide content of the genome. The statistical model learnt from a dataset of promoter sequences automatically recognizes a number of transcription factor binding sites simultaneously with their occurrence positions relative to the transcription start site. Based on this model, a continuous naïve Bayes classifier is developed for the detection of human promoters and transcription start sites in genomic sequences. RESULTS: The present study extends the scope of statistical models in general promoter modeling and prediction. Promoter sequence features learnt by the model correlate well with known biological facts. Results of human transcription start site prediction compare favorably with existing 2nd generation promoter prediction tools.

Base Sequence↗

PubMed2006

In-silico prediction and observations of nuclear matrix attachment.

The nuclear matrix is a functionally adaptive structural framework interior to the nuclear envelope. The nature and function of this nuclear organizer remains the subject of widespread discussion in the epigenetic literature. To draw this discussion together with a view to suggest a way forward we summarize the biochemical evidence for the modalities of DNA-matrix binding alongside the in-silico predictions. Concordance is exhibited at various, but not all levels. On the one hand, both the reiteration and sequence similarity of some elements of Matrix Attachment Regions suggest conservation. On the other hand, in-silico predictions suggest additional unique components. In bringing together biological and sequence evidence we conclude that binding may be hierarchical in nature, reflective of a biological role in replicating, transcribing and potentiating chromatin. Nuclear matrix binding may well be more complex than the widely accepted simple loop model.

Algorithms↗

PubMed2026

Exploring the Role of HSD17B2 in Colorectal Cancer Through Bioinformatic Analysis: Preliminary Insights for Prognostic Evaluation.

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer-related mortality worldwide. Although screening has reduced CRC in older adults, cases in younger individuals are rising, highlighting the need for early biomarkers. Emerging research highlights the role of estrogen metabolism in CRC progression, with enzymes such as hydroxysteroid (17-beta) dehydrogenase (HSD17B) being increasingly implicated. In this study, we performed a bioinformatics analysis using publicly available datasets, including The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) cohort and two independent Gene Expression Omnibus (GEO) cohorts (GSE40967 and GSE41258), to investigate the role of HSD17B enzymes in CRC. Our results suggest that HSD17B2 is frequently downregulated in precancerous lesions and early-stage CRC, which may contribute to elevated estradiol levels and a tumor-promoting microenvironment. In advanced stages, higher HSD17B2 expression levels are associated with poorer survival outcomes in retrospective cohorts. Other HSD17B enzymes also exhibit significant expression changes, further complicating the hormonal landscape of CRC. In addition, estrone, traditionally considered a weaker estrogen, emerges as a potential driver of CRC progression. Our in-silico analyses indicate that HSD17B2 and HSD17B11 warrant further investigation as candidate biomarkers for distinguishing CRC from benign and precancerous conditions, with the combination showing strong discriminatory power in Receiver Operating Characteristic (ROC) analyses. Overall, these findings highlight the potential role of estrogen metabolism in CRC and suggest that HSD17B enzymes may hold value as candidate prognostic and diagnostic indicators, though their clinical utility remains hypothetical at this stage. Experimental and clinical validation is strictly required to confirm these in silico observations and to clarify their mechanisms in CRC.

Humans↗

PubMed2026

Artificial intelligence in molecular diagnostics for pandemic preparedness.

INTRODUCTION: Molecular diagnostics focusing on the detection and analysis of nucleic acids are indispensable tools for early pathogen identification, transmission monitoring, and genomic surveillance during pandemics. Recent technological advances have broadened the diagnostic landscape, incorporating PCR-based methods, isothermal amplification, high-CRISPR-based amplification detection, and sequencing. Despite their diagnostic potential, widespread implementation remains limited by high validation costs, time and logistical constraints, the need for specialized professional knowledge, and a lack of adaptability in resource-limited settings. Artificial intelligence (AI) is increasingly recognized as a promising but challenging approach, offering tools that streamline assay development, automate data interpretation, and optimize real-time diagnostic performance. AREAS COVERED: This review introduces recently published AI tools with potential to enhance the in-silico design validation process of oligonucleotides for molecular assays. These cover tools for initial assay design and optimization to validation and continuous assay updates. The limitations, including concerns regarding data accuracy, the lack of transparency in data processing ('black box' models), and unresolved licensing and regulatory issues, are highlighted for each tool and as expert opinion. EXPERT OPINION: Collectively, these challenges currently confine most AI-based approaches to research settings and prevent their routine implementation in clinical molecular diagnostics. Their widespread adoption depends on addressing remaining technical, regulatory, and practical challenges.

Humans↗

PubMed2026

Metabolic-cell-death gene trio predicts survival and cuproptosis sensitivity in colorectal cancer.

BACKGROUND: Metabolic cell death (MCD) modulates colorectal cancer (CRC) progression, yet its prognostic value remains unexplored. We aimed to build an MCD-centred gene signature for outcome prediction and precision therapy. METHODS: Transcriptomes of 1,174 CRC patients were integrated. Weighted gene co-expression network analysis, differential expressions and least absolute shrinkage and selection operator (LASSO) + random survival forest were successively applied to derive a three-gene (CDKN2A/MPC1/AHCY) risk model. Functional, immune-infiltration, drug-sensitivity and genomic analyses were performed, followed by validation in fresh clinical specimens and cell lines. RESULTS: Integrative metabolic-death transcriptomics identified CDKN2A, MPC1 and AHCY as the hub drivers of CRC. Their three-gene signature robustly stratified patients into high- and low-risk subsets [3-year area under the curve (AUC) 0.83-0.85, P<0.001]. High-risk tumors were enriched for extracellular matrix (ECM)-receptor-interaction pathways, displayed abundant myeloid-derived suppressor cell (MDSC) infiltration and were more vulnerable to AZD8186, AZ960 and JAK inhibitors. Guided by these in-silico findings, we functionally confirmed that CDKN2A silencing markedly repressed proliferation, invasion and migration of SW480/HCT116 cells and potentiated cuproptosis via up-regulation of lipoylated DLAT/DLST and CTR1. CONCLUSIONS: We report the first MCD-derived prognostic platform for CRC that simultaneously predicts survival and therapeutic response. Targeting CDKN2A-enhanced cuproptosis represents a promising metabolic-precision strategy for high-risk patients.

Colorectal cancer (CRC)↗

PubMed2006

Similarity and differences in the Lactobacillus acidophilus group identified by polyphasic analysis and comparative genomics.

A set of lactobacilli were investigated by polyphasic analysis. Multilocus sequence analysis, DNA typing, microarray analysis, and in silico whole-genome alignments provided a remarkably consistent pattern of similarity within the Lactobacillus acidophilus complex. On microarray analysis, 17 and 5% of the genes from Lactobacillus johnsonii strain NCC533 represented variable and strain-specific genes, respectively, when tested against four independent isolates of L. johnsonii. When projected on the NCC533 genome map, about 10 large clusters of variable genes were identified, and they were enriched around the terminus of replication. A quarter of the variable genes and two-thirds of the strain-specific genes were associated with mobile DNA. Signatures for horizontal gene transfer and modular evolution were found in prophages and in DNA from the exopolysaccharide biosynthesis cluster. On microarray hybridizations, Lactobacillus gasseri strains showed a shift to significantly lower fluorescence intensities than the L. johnsonii test strains, and only genes encoding very conserved cellular functions from L. acidophilus hybridized to the L. johnsonii array. In-silico comparative genomics showed extensive protein sequence similarity and genome synteny of L. johnsonii with L. gasseri, L. acidophilus, and Lactobacillus delbrueckii; moderate synteny with Lactobacillus casei; and scattered X-type sharing of protein sequence identity with the other sequenced lactobacilli. The observation of a stepwise decrease in similarity between the members of the L. acidophilus group suggests a strong element of vertical evolution in a natural phylogenetic group. Modern whole-genome-based techniques are thus a useful adjunct to the clarification of taxonomical relationships in problematic bacterial groups.

Genetic Variation↗

PubMed2026

Genomic and computational analysis of variants in telomere regulatory genes in subjects with bone marrow failure.

Telomere Biology Disorders (TBDs) are a genetically heterogeneous and often under-recognized cause of Bone Marrow Failure Syndromes (BMFS), driven by defective telomere maintenance and progressive telomere attrition. We performed an integrated genomic, telomeric and computational analysis in 118 subjects presenting clinical features of BMFS to delineate the contribution of Telomere Regulatory Genes (TRGs) variants to disease pathogenesis. Whole exome sequencing (WES) identified pathogenic (18.18%), likely pathogenic (27.27%) and rare variants of uncertain significance (54.54%) in 27 subjects (22.9%) across five TRGs: RTEL1, TERT, TINF2, NOP10, and WRAP53. Telomere Length (TL) assessment revealed significant telomere shortening in TRG variant-positive subjects compared with age-matched controls, with the most profound attrition observed in individuals harboring de novo TINF2 gene variants. RTEL1 emerged as the most frequently affected gene, with recurrent clustering of variants within its C-terminal regulatory region. A familial NOP10 variant, Asp12His, segregated with cutaneous pigmentation and hematological abnormalities consistent with the established role of NOP10 in dyskeratosis congenita, further broadening the known mutational spectrum of the gene. Structure-guided in-silico analyses predicted that both novel and recurrent variants disrupt protein stability, telomerase assembly or trafficking and shelterin complex integrity. Reduced TERT expression and a significant inverse correlation between telomere length and clinical severity further underscored the functional impact of TRG defects. Collectively, this study provides the first comprehensive characterization of TRG variants in the Indian BMFS cohort and highlights the utility of integrating genomic sequencing, telomere length measurement and computational modeling to improve diagnostic precision, variant interpretation and clinical stratification in TBDs.

Journal Article↗

PubMed2004

The PDB-Preview database: a repository of in-silico models of 'on-hold' PDB entries.

UNLABELLED: The PDB-Preview database is a dynamic web repository of in-silico predicted three-dimensional (3D) models of experimentally determined structures that are deposited into the PDB but are not yet publicly released, and are kept 'on-hold'. The PDB-Preview database is automatically generated on a weekly basis by the bioinfo.pl meta-server, which uses top-of-the-line fold-recognition methods. The PDB-Preview provides biologists with preliminary fold assignments well before the experimentally determined 3D structures are released. AVAILABILITY: http://bioinfo.pl/PDB-Preview/.

Computer Simulation↗

PubMed2006

Characterization of an interleukin-15 like (IL-15L) gene from zebrafish (Danio rerio).

In fish, interleukin (IL)-2, IL-21 and IL-15 genes have recently been identified by in-silico cloning. Fish IL-15 gene is similar to counterparts from mammals and other vertebrates. A zebrafish genomic database-search initiated to find IL-2 and IL-21 genes from zebrafish (Danio rerio) led to the identification of an IL-15 like gene (IL-15L). This gene was cloned by prediction and the transcripts were subsequently cloned by PCR. The predicted translation yielded a 162 amino acid protein with a 42 amino acid-long signal peptide. This protein shared identities of 28.4% to 31.5% with other mammalian and vertebrate IL-2, IL-15 and IL-21 genes. The gene occupies 7.7 kb of the genomic DNA and the coding region spans into four exons and is interrupted by three introns, which is similar to the genomic structure of IL-2 gene. The chromosomal synteny and phylogenetic analyses support our view that this IL-15L gene is specific to teleosts. Furthermore, two alternatively spliced forms have been identified with differential exon usage translating for proteins of 108 and 120 amino acids in length. The analysis of the alternative splicing suggests it may play an important role in regulating the function of this novel gene. Analyses by RT-PCR and in situ hybridization show gene expression in lymphoid tissues like intestine, gills, spleen, pancreas and kidney suggestive of a role in immunity of fish.

Alternative Splicing↗

PubMed2002

Generation and mapping of AFLP, SSRs and SNPs in Lycopersicon esculentum.

Amplified Fragment Length Polymorphism (AFLP), Simple Sequence Repeat (SSR) and Single Nucleotide Polymorphism (SNP), were applied to the tomato genome for assessment of polymorphism and for mapping. The polymorphism of AFLP was studied in twenty-one commercial tomato (L. esculentum) varieties. Four AFLP primer combinations produced 298 clear bands; an average of 75 bands per combination. SSR markers were generated from two sources: (1) size-selected genomic libraries screened with (AT)n, (CT)n, (GT)n, (ATT)n and (CTT)n probes. (2) GeneBank database. Primers were designed for 114 loci and used for genotyping 13 tomato varieties and three Lycopersicon species. Eighteen markers were used to evaluate the polymorphism among the commercial cultivars and were found to be a useful tool for cultivar identification. In-silico comparison of DNA sequences (ESTs and genes) of L. pennellii and L. esculentum, yielded 312 SNPs. Ten L. pennelli genomic fragments were sequenced and the comparison with L. esculentum yielded 22 SNPs. Another 19 SNPs were discovered by sequencing and comparing L. pennellii genomic DNA to L. esculentum DNA fragments containing SSRs. The average SNP frequency was found to be one in a few tens of base pairs. A total of 52 microsatellites, 159 polymorphic AFLP markers and six SNPs were mapped using the Introgression Lines generated by [1]. Map location and markers' distribution are presented.

Alleles↗

PubMed2005

Nonrandom distribution and frequencies of genomic and EST-derived microsatellite markers in rice, wheat, and barley.

BACKGROUND: Earlier comparative maps between the genomes of rice (Oryza sativa L.), barley (Hordeum vulgare L.) and wheat (Triticum aestivum L.) were linkage maps based on cDNA-RFLP markers. The low number of polymorphic RFLP markers has limited the development of dense genetic maps in wheat and the number of available anchor points in comparative maps. Higher density comparative maps using PCR-based anchor markers are necessary to better estimate the conservation of colinearity among cereal genomes. The purposes of this study were to characterize the proportion of transcribed DNA sequences containing simple sequence repeats (SSR or microsatellites) by length and motif for wheat, barley and rice and to determine in-silico rice genome locations for primer sets developed for wheat and barley Expressed Sequence Tags. RESULTS: The proportions of SSR types (di-, tri-, tetra-, and penta-nucleotide repeats) and motifs varied with the length of the SSRs within and among the three species, with trinucleotide SSRs being the most frequent. Distributions of genomic microsatellites (gSSRs), EST-derived microsatellites (EST-SSRs), and transcribed regions in the contiguous sequence of rice chromosome 1 were highly correlated. More than 13,000 primer pairs were developed for use by the cereal research community as potential markers in wheat, barley and rice. CONCLUSION: Trinucleotide SSRs were the most common type in each of the species; however, the relative proportions of SSR types and motifs differed among rice, wheat, and barley. Genomic microsatellites were found to be primarily located in gene-rich regions of the rice genome. Microsatellite markers derived from the use of non-redundant EST-SSRs are an economic and efficient alternative to RFLP for comparative mapping in cereals.

Amino Acid Motifs↗

PubMed2026

In-Silico and Functional Characterization of EcdLp, an ABC Transporter of Aspergillus nidulans NRRL11440.

Echinocandin B (ECB) biosynthesis in Aspergillus nidulans is primarily governed by multiple genes located within the biosynthetic echinocandin (ecd) gene cluster. The contributory functions of many genes, including transcription factors and tailoring enzymes of the ecd gene cluster, have been previously studied. The present study focused on determining the role of transporter proteins, EcdLp, EcdCp, and EcdDp, in ECB efflux using in silico and biochemical approaches. The molecular docking analysis revealed that ECB relatively showed higher binding affinity for EcdLp than the other co-clustered MFS transporters EcdCp and EcdDp, suggesting a preferred substrate of EcdLp. These results were further confirmed by heterologous integration of the ecdL gene in the ABC transporters-deficient Saccharomyces cerevisiae AD1-8u⁻, confirming active efflux. However, the binding of ECB in EcdLp is distinct from the R6G binding, overlapping the promiscuous site of farnesol, resulting in inhibition of R6G efflux in a dose-dependent manner. In conclusion, these results decipher the ECB binding and efflux mechanism and unveil the evolutionarily specialized architecture of EcdLp that permits targeted metabolite export in addition to environmental responsiveness, and lay the groundwork for optimizing ECB production via transporter engineering.

Aspergillus nidulans↗