Biology subjects

Marino, D.

Publications and source records attributed to Marino, D..

5 recordsLinked to original sources

bioRxiv2026

MYB28 and MYB29 transcription factors regulate iron homeostasis and iron-mobilizing coumarin biosynthesis in Arabidopsis thaliana

Iron (Fe) deficiency is a major constraint for plant growth and triggers extensive physiological and transcriptional reprogramming to maintain Fe homeostasis. Here, we identify the glucosinolate-associated transcription factors MYB28 and MYB29 as previously unrecognized regulators of Arabidopsis thaliana adaptation to Fe deficiency. Across various growth systems, loss of MYB28 increased sensitivity to Fe deficiency, whereas the myb28myb29 double mutant displayed stronger chlorosis, reduced root growth and impaired biomass accumulation, indicating cooperative but unequal functions of these transcription factors. Despite their enhanced Fe-deficiency phenotype, double mutant plants accumulated higher Fe levels in roots and exhibited stronger induction of canonical Fe-deficiency responses, suggesting impaired Fe utilization or distribution rather than defective Fe uptake. RNA-seq revealed extensive transcriptional reprogramming under Fe deficiency, with pronounced deregulation of genes involved in Fe homeostasis, redox processes and growth, particularly in the double mutant. Among these, SCOPOLETIN 8-HYDROXYLASE (S8H) emerged as a major target gene of MYB28. The expression of S8H was almost abolished in myb28 and myb28myb29 mutants, whereas expression of other coumarin biosynthetic genes remained largely unaffected. Promoter activation assays demonstrated that MYB28 activates the S8H promoter, and metabolic analyses showed accumulation of scopolin together with reduced fraxin levels in the mutants, consistent with impaired S8H activity. Collectively, our results identify MYB28 as a key regulator linking specialized metabolism to Fe homeostasis through control of coumarin biosynthesis, thereby expanding the biological functions of MYB28 and MYB29 transcription factors.

plant biology↗

bioRxiv2025

Biological nitrification inhibition (BNI) in wheat for climate adaptation in acidic and alkaline soils

Anthropogenic disturbances to nitrogen (N) cycling, particularly through agricultural N use, have intensified nitrous oxide (N2O) emissions. Developing wheat lines with biological nitrification inhibition (BNI) is a promising strategy to reduce such emissions. However, the effectiveness of BNI depends not only on plant characteristics, but also on how they interact with environmental factors such as soil pH and elevated atmospheric CO2 (eCO2). This study evaluated the response of a BNI-capable wheat line (Triticum aestivum cv. ROELFS) to eCO2 under contrasting soil pH during the 30 days following ammonium fertilization. Two wheat lines (ROELFS-Control and ROELFS-BNI) were grown under ambient (400 ppm) and elevated (800 ppm) CO2 in acidic (pH 5.3) and alkaline (pH 8.8) soils. N2O emissions, nitrifying and denitrifying microbial communities, and soil chemical properties were monitored to assess plant-soil-microbe interactions. ROELFS-BNI consistently reduced N2O emissions under all conditions by reducing archaeal (Nitrososphaeraceae) and bacterial nitrifiers (Nitrosomonadaceae, Nitrospiraceae) without major shifts in overall microbial composition, indicating high specificity of BNI exudates. Elevated CO2 effects on N2O emissions were pH-dependent. In acidic soil, eCO2 increased emissions in ROELFS-Control but not in ROELFS-BNI, likely due to the enrichment of complete denitrifiers (e.g. Rhodanobacteraceae). However, in alkaline soil, eCO2 reduced N2O emissions in both Control and BNI lines, especially the latter, which was associated with a higher abundance of N2O-reducing denitrifiers (e.g. Burkholderiaceae). This study highlights the potential of ROELFS-BNI wheat as a sustainable practice to mitigate N pollution adaptable to diverse soils and predicted CO2 atmospheric conditions.

plant biology↗

bioRxiv2025

Pan-cancer prediction of tumor immune activation and response to immune checkpoint blockade from tumor transcriptomics and histopathology

Accurately predicting which patients will respond to immune checkpoint blockade (ICB) remains a major challenge. Here, we present TIME_ACT, an unsupervised 66-gene transcriptomic signature of tumor immune activation derived from TCGA (The Cancer Genome Atlas) melanoma data. First, we demonstrate that TIME_ACT scores accurately identify tumors with activated immune microenvironments across different cancer types. Further, analysis of spatial features reveals that tumor microenvironment regions with dense lymphocyte infiltration near tumor cells have high TIME_ACT scores, successfully marking localized immune activation. Second, across 25 transcriptomic ICB cohorts encompassing nine cancer types, TIME_ACT achieves a mean AUC of 0.76 and a mean odds ratio of 5.77, significantly outperforming 30 established transcriptomic signatures and prediction methods for ICB response, including a recently developed foundation model for immunotherapy response prediction. Third, we show that TIME_ACT scores can be accurately inferred from routine tumor histopathology slides and that slide-inferred TIME_ACT scores predict ICB response across nine new independent patient cohorts spanning eight cancer types, achieving a mean AUC of 0.72 and a mean odds ratio of 4.99. These findings establish TIME_ACT as a robust, pan-cancer biomarker that enables accurate, low-cost, and clinically scalable prediction of ICB response from routine histopathology.

cancer biology↗

bioRxiv2022

DEGoldS: a workflow to assess the accuracy of differential expression analysis pipelines through gold-standard construction

RNA sequencing (RNA-seq) is a high throughput sequencing method that has become one the most employed tools in transcriptomics. The implementation of optimal bioinformatic analyses required in RNA-seq experiments may be complicated due to the large amounts of data generated by the sequencing platforms, along with the intrinsic nature of these data types. In the last years many programs and pipelines have been developed for differential expression (DE) analyses, but their effectiveness can be reduced when working with non-model species lacking public genomic resources. Moreover, there is not a universal recipe for all the experiments and datasets and the modification of standard RNA-seq bioinformatic pipelines through parameter tuning and the use of alternative software may have a strong impact in the outcome of DE analysis. Therefore, although the selection of the most accurate DE pipeline configuration and the evaluation of how these changes could affect the final DE results in RNA-seq experiments is mandatory to reduce bias, the lack of gold-standard datasets with known expression patterns hampers its implementation. In the present manuscript we present DEGoldS, a workflow consisting on sequential Bash and R scripts to construct gold-standards for simulation-based benchmarking of user selected pipelines for DE analysis and the computation of the accuracy of the pipelines. We validated the workflow with a case study consisting on real RNA-seq libraries of radiata pine, an important forest tree species with no publicly available reference genome. The results showed that slight pipeline modifications produced remarkable differences in the outcome of DE analysis.

bioinformatics↗

bioRxiv2021

The Actin Bundling Protein Fascin Promotes Lung Cancer Growth and Metastasis by Enhancing Glycolysis and PFKFB3 Expression

Fascin is a pro-metastasis actin bundling protein upregulated in essentially all the metastatic carcinoma. It is believed that fascin promotes cancer cell migration and invasion by facilitating membrane protrusions such as filopodia and invadopodia. Aerobic glycolysis is a key feature of cancer metabolism that provides critical intermediate metabolites for tumor growth and cell proliferation. Here we report that fascin increase glycolysis in lung cancer to promote tumor growth and metastasis. Fascin promotes glycolytic flux by increasing the expression and activities of phosphofructose kinase 1 and 2 (PFK1 and 2). The glycolytic function of fascin depends on activation of YAP1 through its canonical actin bundling activity. Fascin promotes the binding of YAP1 to a TEAD1/4 binding motif located 30 bp upstream of the PFKFB3 transcription start site to activate its transcription. Our interrogation of the TCGA database suggest that the fascin-YAP1-PFKFB3 circuit is likely conserved across different types of cancer. We further showed that the glycolytic function of fascin is essential for promotion of lung cancer growth and metastasis. Importantly, pharmacological inhibitors of fascin could be used to suppress the YAP1-PFKFB3 signaling and inhibit glycolysis in cancer cell lines, organoid cultures and xenograft metastasis models. Taken together, our data reveal an important glycolytic role of fascin in lung cancer metabolism, and suggest that pharmacological inhibitors of fascin could be used to reprogram cancer metabolism in lung cancer and potentially other cancer with fascin upregulation.

cancer biology↗