Biology subjects

Sanseverino, W.

Publications and source records attributed to Sanseverino, W..

4 recordsLinked to original sources

bioRxiv2025

ARABIDOPSIS Bsister and SEEDSTICK MADS-box transcription factors modulate maternal nutrient flow for seed development in Arabidopsis

Successful seed development in angiosperms depends on the coordinated transport and allocation of sugars from maternal tissues to the developing embryo and endosperm. In Arabidopsis thaliana, ovules function as carbohydrate sink organs, accumulating starch in both gametophytic and sporophytic domains prior to fertilization. This stored starch is later mobilized to support early embryogenesis. Despite extensive knowledge of starch metabolism in photosynthetic tissues, the regulatory mechanisms governing sugar transport in reproductive organs remain poorly understood. Recent studies have identified fertilization-dependent changes in nutrient flow, including callose-mediated modulation of symplastic transport at the phloem unloading site. However, the molecular players orchestrating these transitions are largely unknown. Here, we show that the MIKC MADS domain transcription factors ABS/TT16 and STK play critical roles in regulating maternal nutrient flow during ovule maturation and seed development. We dissect their functional redundancy using omics and genetic approaches, underscoring the importance of different ovule tissues in coordinating sugar transport pathways for post-fertilization development. Our findings reveal a previously underappreciated layer of genetic control over nutrient allocation in reproductive tissues and provide new insights into the metabolic reprogramming required for successful seed formation.

plant biology↗

bioRxiv2020

A NEW BIOINFORMATIC TOOL TO INTERPRET METAGENOMICS /METATRANSCRIPTOMICS RESULTS BASED ON THE GEOMETRY OF THE CLUSTERING NETWORK AND ITS DIFFERENTIALLY GENE ONTOLOGIES (GANGO)

High-throughput experimental techniques, such as metagenomics or metatranscriptomics, produce large amounts of data, which interpretation and conversion into understandable knowledge can be challenging and out of reach. We present GANGO, a new algorithm based on the ecological concept of consortium (groups biologically connected) and by using clustering network analysis, gene ontologies and powerful hypothesis test allows the identification and interpretation of complex ecological networks, allowing the identification of the relationship between taxa/genes, the number of groups, their relations and their functionalities using the annotated genes of an organism in a database (e.g. UniProt or Ensembl). Three examples of the use of GANGO are shown: a simulated mixture of fungi and bacteria, alterations in soil fungi communities after a diesel-oil spill and genomic changes in Saccharomyces cerevisae due to abiotic stress.

bioinformatics↗

bioRxiv2019

GAIA: an integrated metagenomics suite

Identifying the biological diversity of a microbial population is of fundamental importance due to its implications in industrial processes, environmental studies and clinical applications. Today, there is still an outstanding need to develop new, easy-to-use bioinformatics tools to analyze both amplicon and shotgun metagenomics, including both prokaryotic and eukaryotic organisms, with the highest accuracy and the lowest running time. With the aim of overcoming this need, we introduce GAIA, an online software solution that has been designed to provide users with the maximum information whether it be 16S, 18S, ITS, or shotgun analysis. GAIA is able to obtain a comprehensive and detailed overview at any taxonomic level of microbiomes of different origins: human (e.g. stomach or skin), agricultural and environmental (e.g. land, water or organic waste). By using recently published benchmark datasets from shotgun and 16S experiments we compared GAIA against several available pipelines. Our results show that for shotgun metagenomics, GAIA obtained the highest F-measures at species level above all tested pipelines (CLARK, Kraken, LMAT, BlastMegan, DiamondMegan and NBC). For 16S metagenomics, GAIA also obtained excellent F-measures comparable to QIIME at family level. The overall objective of GAIA is to provide both the academic and industrial sectors with an integrated metagenomics suite that will allow to perform metagenomics data analysis easily, quickly and affordably with the highest accuracy.

bioinformatics↗

bioRxiv2018

Reduction of LOXL2-mediated H3K4 oxidation increases chromatin accessibility and promotes chemosensitivity of triple-negative breast cancer cells

Oxidation of H3 at lysine 4 (H3K4ox) by lysyl oxidase-like 2 (LOXL2) generates an H3 modification with an unknown physiological function. We find that LOXL2 and H3K4ox are higher in triple-negative breast cancer (TNBC) cell lines and patient-derived xenographs (PDXs) than those from other breast cancer subtypes. ChIP-seq revealed that H3K4ox is located primarily in heterochromatin, where it is involved in chromatin compaction. Knocking down LOXL2 reduces H3K4ox levels and causes chromatin decompaction, resulting in a sustained activation of the DNA damage response (DDR) and increased susceptibility to anticancer agents. This critical role that LOXL2 and oxidized H3 play in chromatin compaction and DDR suggests that functionally targeting LOXL2 could be a way to sensitize TNBC cells to conventional therapy.

cancer biology↗