Biology subjects

Antonini, M.

Publications and source records attributed to Antonini, M..

3 recordsLinked to original sources

bioRxiv2026

DNA-MGC+: A versatile codec for reliable and resource-efficient data storage on synthetic DNA

The biochemical processes underlying DNA data storage, including synthesis, amplification, and sequencing, are inherently noisy. Consequently, base-level insertion, deletion, and substitution (IDS) errors, as well as sequence-level dropouts, occur and pose major challenges for reliable data retrieval. Here we introduce DNA-MGC+, a DNA storage codec designed to enable reliable and resource-efficient data retrieval under diverse operating conditions. We evaluate DNA-MGC+ across a wide range of in silico and in vitro settings, including experiments with both Illumina and Nanopore sequencing, and show that it consistently outperforms several representative codecs from the literature. In particular, DNA-MGC+ achieves simultaneous gains in sequencing depth requirements, read cost, decoding time, storage density, and error-correction capability under explicit reliability constraints. These gains persist and become more pronounced for larger files, with DNA-MGC+ remaining reliable and efficient well beyond the practical scalability limits of the benchmarked codecs. Notable performance results include reliable decoding under IDS error rates of up to 24% in synthetic scenarios, and reliable retrieval at sequencing depths below 3x with read costs below 3.5 nts/bit under electrochemical synthesis for both Illumina and Nanopore sequencing.

bioinformatics↗

bioRxiv2019

Screening of clustered regulatory elements reveals functional cooperating dependencies in Leukemia.

In the recent years, massively parallel sequencing approaches identified hundreds of mutated genes in cancer(1) providing an unprecedented amount of information about mechanisms of cancer cell maintenance and progression. However, while (it is widely accepted that) transformation processes result from oncogenic cooperation between deregulated genes and pathways, the functional characterization of candidate key players is mostly performed at the single gene level which is generally inadequate to identify these oncogene circuitries. In addition, studies aimed at depicting oncogenic cooperation involve the generation of challenging mouse models or the deployment of tedious screening pipelines. Genome wide mapping of epigenomic modifications on histone tails or binding of factors such as MED1 and BRD4 allowed identification of clusters of regulatory elements, also termed Super-Enhancers (SE)(2). Functional annotation of these regions revealed their high relevance during normal tissue development and cancer ontogeny(3). An interesting paradigm of the tumorigenic function of these SE regions comes from ETO2-GLIS2-driven acute megakaryoblastic leukemia (AMKL) in which the fusion protein ETO2-GLIS2 is sufficient to promote an aberrant transcriptional network by the rewiring of SE regions(4). We thus hypothesized that important regulatory regions could control simultaneously expression of genes cooperating in functional modules to promote cancer development. In an effort to identify such modules, we deployed a genome-wide CRISPRi-based screening approach and nominated SE regions that are functionally linked to leukemia maintenance. In particular, we pinpointed a novel SE region regulating the expression of both tyrosine kinases KIT and PDGFRA. Whereas the inhibition of each kinase alone affected modestly cancer cell growth, combined inhibition of both receptors synergizes to impair leukemia cell growth and survival. Our results demonstrate that genome-wide screening of regulatory DNA elements can identify co-regulated genes collaborating to promote cancer and could open new avenues to the concept of combined gene inhibition upon single hit targeting.

cancer biology↗

bioRxiv2018

Epidemiologal investigation of an Acinetobacter baumannii outbreak using Core Genome Multilocus Sequence Typing

Carbapenem-resistant (CR) Acinetobacter baumannii is a serious nosocomial pathogen able to cause a variety of serious, often life-threatening infections and outbreaks. We aimed to investigate the molecular epidemiology of clinical isolates of CR-A. baumannii from an outbreak occurred in the intensive care unit (ICU) of our hospital.\n\nFrom January to April 2017, 13 CR-A. baumannii isolates were collected at the \"L. Spallanzani\" hospital, Rome, Italy; typing was performed by repetitive extragenetic palindromic-based (rep)- PCR-based DiversiLab system and WGS data were used for in silico analysis of traditional MLST types, for identifying resistance genes and for core genome multi locus sequence typing (cgMLST) analysis. Epidemiological data were obtained from hospital records.\n\nStrains were cultured from 7 patients treated in the ICU of our hospital; all isolates showed a multi-drug resistant (MDR) profile, carrying the blaOXA-23 carbapenemase. Typing performed by rep-PCR and MLST showed that the isolates clustered into one group while the cgMLST approach, which uses 2690 gene targets to characterize the gene-by-gene allelic profile of A. baumannii, highlighted the presence of two cluster types. These results allowed us to identify two patients who entered the ICU already colonized by two different strains of CR-A. baumannii; we hypothesize that these two patients could be the source of two separate transmission chains.\n\nOur results show that whole-genome-DNA sequencing by cgMLST is a valuable tool, better suited for prompt epidemiological investigations than traditional typing methods because of its higher discriminatory ability in determining clonal relatedness.

molecular biology↗