Biology subjects

Desiro, D.

Publications and source records attributed to Desiro, D..

5 recordsLinked to original sources

bioRxiv2026

Bridging disciplines towards wastewater-based surveillance of antimicrobial resistance: frequency, local dynamics, and genomic characteristics of carbapenemase-producing Klebsiella pneumoniae

The World Health Organization (WHO) has designated carbapenemase-producing Klebsiella pneumoniae (CP-KP) as a critical priority pathogen due to its increasing importance for human health. As wastewater-based surveillance (WBS) is discussed as a complementary tool for classical systems regarding hazard forecasting and early-warning, we designed a "wet-lab to genomics" workflow to target CP-KP in raw influent wastewater samples to support method development processes across different scientific disciplines. The CP-KP screening workflow was set up based on membrane filtration, selective chromogenic media for selective cultivation and the modified carbapenem inactivation method (mCIM) for confirming carbapenemase-production using 33 samples from four different wastewater treatment plants in North-Eastern Germany. All samples tested positive for CP-KP, with concentrations ranging between 102 and 104 colony-forming units (cfu) per 100 ml across the sample set. As a result, 320 isolates belonged to the Klebsiella, Enterobacter, Citrobacter (KEC)- group, with the majority being identified as KP (n= 297; 93%), including n= 253 (79%) verified CP-KP. Genotypic characterization of CP-KP by PCR revealed the predominance of blaOXA-48-related genes (n= 83) among isolates from all WWTPs. As quality parameters, colony counts for viable Escherichia coli (EC) were employed as a proxy for valid wastewater samples and extended-spectrum beta-lactamase-producing E. coli (ESBL-EC) as indicator for AMR, with cfu/100 ml ranges from 10 to 10 and 102 to 10, respectively. To verify the screening outcome, a subset of 58 CP-KP from two WWTPs were subjected to whole genome sequencing (WGS). As a result, eight different sequence types (STs), i.e., ST147 and ST273 (both: clonal group 147), ST258, ST35, ST15, ST37, ST307, and ST485 were identified. These include clinically relevant STs clustering closest with fecal isolates from Germany when compared with Pathogenwatch-database entries. Moreover, WGS data enabled the identification of antibiotic resistance genes (ARGs), and the detection of closely related isolates within the WWTP dataset.

microbiology↗

bioRxiv2025

Phosphorylation enables allosteric control of a viral condensate

In many viruses, intrinsically disordered proteins (IDPs) drive the formation of replicative organelles essential for viral production. In species A rotaviruses, the disordered protein NSP5 forms condensates in cells via liquid-liquid phase separation (LLPS). Yet the sequence diversity of NSP5 raises the question of whether condensate formation is conserved across all strains and if distinct variants employ alternative mechanisms for nucleating phase separation. Using a machine learning approach, we demonstrate that NSP5 variants differ significantly in their propensity to phase-separate. We engineered a variant incorporating amino acid signatures from strains with low LLPS tendency, which failed to phase separate in vitro yet supported the formation of replicative condensates in recombinant viruses in cells. Low-tendency LLPS strains require phosphorylation of NSP5 to nucleate phase separation, whereas high-tendency strains do not, suggesting distinct nucleation mechanisms. Furthermore, hydrogen-deuterium exchange mass spectrometry revealed a phosphorylation-driven allosteric switch between binding sites on the high-propensity variant. These findings establish that phosphorylation plays a context-dependent role in the formation of replicative organelles across diverse rotaviruses.

biophysics↗

bioRxiv2021

Principles of RNA recruitment to viral ribonucleoprotein condensates in a segmented dsRNA virus

Rotaviruses transcribe eleven distinct protein-coding RNAs that must be stoichiometrically co-packaged prior to their replication to make an infectious virion. During infection, rotavirus transcripts accumulate in cytoplasmic ribonucleoprotein (RNP) condensates, termed viroplasms. Understanding the mechanisms of viroplasm assembly and RNA enrichment within is crucial to gaining greater insight into their function and stoichiometric assortment of individual transcripts. We analysed the subcellular distribution of individual RV transcripts and viroplasm transcriptome by combining multiplexed DNA-barcoded single-molecule RNA FISH of infected cells. Using DNA-PAINT microscopy, we provide evidence of the early onset of viral transcript oligomerisation that occurs prior to the formation of viroplasms. We demonstrate that viral sequences lacking the conserved terminal regions fail to undergo enrichment in rotavirus RNP condensates. We show that individual viral transcripts exhibit variable propensities to partition into viroplasms, irrespective of their absolute numbers in cells, suggesting a selective RNA enrichment mechanism distinct from other known cellular RNP granules. We suggest that rotavirus replication factories represent unique RNP condensates enriched in eleven types of cognate transcripts that may facilitate the assembly of a multi-segmented RNA genome.

biochemistry↗

bioRxiv2019

A comprehensive annotation and differential expression analysis of short and long non-coding RNAs in 16 bat genomes

Although bats are increasingly becoming the focus of scientific studies due to their unique properties, these exceptional animals are still among the least studied mammals. Assembly quality and completeness of bat genomes vary a lot and especially non-coding RNA (ncRNA) annotations are incomplete or simply missing. Accordingly, standard bioinformatics pipelines for gene expression analysis often ignore ncRNAs such as microRNAs or long antisense RNAs. The main cause of this problem is the use of incomplete genome annotations. We present a complete screening for ncRNAs within 16 bat genomes. NcRNAs affect a remarkable variety of vital biological functions, including gene expression regulation, RNA processing, RNA interference and, as recently described, regulatory processes in viral infections. Within all investigated bat assemblies we annotated 667 ncRNA families including 162 snoRNAs and 193 miRNAs as well as rRNAs, tRNAs, several snRNAs and IncRNAs, and other structural ncRNA elements. We validated our ncRNA candidates by six RNA-Seq data sets and show significant expression patterns that have never been described before in a bat species on such a large scale. Our annotations will be usable as a resource (Electronic Supplement) for deeper studying of bat evolution, ncRNAs repertoire, gene expression and regulation, ecology, and important host-virus interactions. Supplementary informationis available at rna.uni-jena.de/supplements/bats, the Open Science Framework (doi.org/10.17605/OSF.IO/4CMDN), and GitHub (github.com/rnajena/bats_ncrna).

bioinformatics↗

bioRxiv2018

SilentMutations (SIM): a tool for analyzing long-range RNA-RNA interactions in viral genomes and structural RNAs

BackgroundA single nucleotide change in the coding region can alter the amino acid sequence of a protein. In consequence, natural or artificial sequence changes in viral RNAs may have various effects not only on protein stability, function and structure but also on viral replication.\n\nIn recent decades, several tools have been developed to predict the effect of mutations in structured RNAs such as viral genomes or non-coding RNAs. Some tools use multiple point mutations and also take coding regions into account. However, none of these tools was designed to specifically simulate the effect of mutations on viral long-range interactions.\n\nResultsHere, we developed SilentMutations (SIM), an easy-to-use tool to analyze the effect of multiple point mutations on the secondary structures of two interacting viral RNAs. The tool can simulate disruptive and compensatory mutants of two interacting single-stranded RNAs. This allows a fast and accurate assessment of key regions potentially involved in functional long-range RNA-RNA interactions and will eventually help virologists and RNA-experts to design appropriate experiments.\n\nSIM only requires two interacting single-stranded RNA regions as input. The output is a plain text file containing the most promising mutants and a graphical representation of all interactions.\n\nConclusionWe applied our tool on two experimentally validated influenza A virus and hepatitis C virus interactions and we were able to predict potential double mutants for in vitro validation experiments.\n\nAvailabilityThe source code and documentation of SIM are freely available at github.com/desiro/silentMutations.

bioinformatics↗