Biology subjects

Patalano, S.

Publications and source records attributed to Patalano, S..

7 recordsLinked to original sources

bioRxiv2026

ArthroVerse: mapping protein family diversity across arthropod-associated microbiomes

Metagenomic studies of arthropod-associated microbiomes have generated vast amounts of sequence data, yet the functional and structural organization of these proteins remains largely unexplored. Here, we present ArthroVerse, the first comprehensive database of protein families derived from arthropod-associated metagenomes. Non-redundant protein families were generated after rigorous filtering, deduplication, and clustering. The protein families were further annotated with microbial taxonomy, host associations, protein structural information, and Carbohydrate-active enzymes (CAZyme) predictions. The resulting dataset integrates both metagenomic and reference genome-derived proteins, enabling systematic exploration of functional diversity, evolutionary relationships, and host-microbe interactions in insect microbiomes. ArthroVerse provides a valuable resource for the study of microbial ecology and arthropod physiology, offering unprecedented insight into the protein landscape of insect-associated microbial communities.

bioinformatics↗

bioRxiv2026

Agroforestry transition increases insect diversity and reorganizes soil function in a Mediterranean orchard

Agricultural intensification has reduced biodiversity and weakened ecosystem functions essential for sustainable crop production. Agroforestry has been proposed as a regenerative strategy to restore these functions through vegetation diversification, yet its ecological effects at the farm scale remain insufficiently documented, particularly in Mediterranean perennial systems. Here, adaptive field monitoring and soil shotgun metagenomics were combined to investigate ecological responses across a 10-year agroforestry transition gradient in a Mediterranean citrus and olive farm. Mature agroforestry plots supported higher insect richness and functional diversity while maintaining stable pollinator communities. Plant-insect interaction analyses suggested that potential pest activity was largely associated with spontaneous and supportive vegetation rather than crops. In contrast, soil communities showed limited changes in overall richness but substantial compositional and functional restructuring, including enrichment of the arbuscular mycorrhizal fungus Rhizophagus and proteins with nutrient-cycling functions in advanced plots. Together, these findings suggest that agroforestry transition can promote functional diversification above and below ground and highlight the value of farmer-led regenerative transitions coupled with integrative ecological monitoring for the development of more resilient agricultural systems.

ecology↗

bioRxiv2026

Intragenic Transcription from Defective HIV Proviruses Triggers Interferon Responses in Myeloid Cells

The persistent HIV-1 reservoir includes a subset of cells harboring transcriptionally repressed latent HIV-1 that contributes to rebound upon antiretroviral treatment (ART) interruption. However, the majority of the reservoir consists of defective proviral genomes with mutations that prevent production of HIV -1 virions. People with HIV (PWH), even with suppression of viremia, demonstrate comorbidities of the central nervous system, heart, gut, and general aging-associated inflammation. Previously, we identified a transcriptionally active element within the envelope gene (env) of HIV-1 which mediates the expression of aberrant HIV-1 RNAs. We hypothesize that spurious expression of defective proviruses contributes to the general inflammation that drives these comorbidities. We observed correlations between levels of pro-inflammatory cytokines in serum of PWH and levels of HIV-1 transcripts from this intragenic promoter. To investigate the impact of defective proviruses, we employed CRISPR-Cas9 to render the 5 Long Terminal Repeat (LTR), which acts as the enhancer and promoter for proviral transcription, non-functional. HIV-1 infected cells harboring this deletion produce significantly higher levels of IP-10 in vitro in both monocytic cell lines and primary monocyte-derived macrophages. Transcripts generated from the env promoter, include a 5 cap and polyA tail and the induction of IP-10 expression was dependent on the cytosolic innate immune sensing pathway components MDA5 and MAVS. We propose that defective HIV proviruses contribute to chronic inflammation in PWH via an MDA5-dependent induction of type I interferon pathways. ImportancePeople with HIV-1 are at higher risk of developing age-associated comorbidities and immune exhaustion even when receiving antiviral treatments and having no detectable viremia. Transcription and translation have been documented from latent and defective proviruses, but their impact on inflammation associated with chronic HIV-1 infection remains poorly understood. The significance of this work is in identifying a role for defective HIV-1 proviruses and correlating their transcription in triggering a type I interferon response. These results highlight the importance of the persistent defective HIV-1 proviruses and understanding their impact on driving chronic inflammation to inform future strategies to assure people with HIV-1 healthy living and aging.

microbiology↗

bioRxiv2023

Integrated omics analysis unveils a DNA damage response to neurogenic injury

Spinal cord injury (SCI) evokes profound bladder dysfunction. Current treatments are limited by a lack of molecular data to inform novel therapeutic avenues. Previously, we showed systemic inosine treatment improved bladder function following SCI in rats. Here, we applied multi-omics analysis to explore molecular alterations in the bladder and their sensitivity to inosine following SCI. Canonical pathways regulated by SCI included those associated with protein synthesis, neuroplasticity, wound healing, and neurotransmitter degradation. Upstream regulator analysis identified MYC as a key regulator, whereas causal network analysis predicted multiple regulators of DNA damage response signaling following injury, including PARP-1. Staining for both DNA damage ({gamma}H2AX) and PARP activity (poly-ADP-ribose) markers in the bladder was increased following SCI, and attenuated in inosine-treated tissues. Proteomics analysis suggested that SCI induced changes in protein synthesis-, neuroplasticity-, and oxidative stress-associated pathways, a subset of which were shown in transcriptomics data to be inosine-sensitive. These findings provide novel insights into the molecular landscape of the bladder following SCI, and highlight a potential role for PARP inhibition to treat neurogenic bladder dysfunction. Synopsis O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/571015v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@7c3e79org.highwire.dtl.DTLVardef@e998f5org.highwire.dtl.DTLVardef@38fd4aorg.highwire.dtl.DTLVardef@17d3aba_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIEmployed a multi-omics approach, integrating both transcriptomic and proteomic analyses, to investigate the molecular response in a rat model of spinal cord injury (SCI) and the therapeutic effect of inosine. C_LIO_LIDiscovered multiple regulators of the DNA damage response, including PARP-1, using causal network analysis. C_LIO_LIObserved decreased markers of DNA damage and PARP activity in inosine-treated tissues, indicating the therapeutic potential of inosine in neurogenic dysfunction. C_LIO_LIIdentified significant alterations in molecular pathways associated with protein synthesis, neuroplasticity, wound healing, and neurotransmitter degradation after SCI, and their modulation by inosine, highlighting its neuroprotective effects beyond DNA damage repair. C_LI

cell biology↗

bioRxiv2023

A Bayesian Noisy Logic Model for Inference of Transcription Factor Activity from Single Cell and Bulk Transcriptomic Data

The advent of high-throughput sequencing has made it possible to measure the expression of genes at relatively low cost. However, direct measurement of regulatory mechanisms, such as Transcription Factor (TF) activity is still not readily feasible in a high-throughput manner. Consequently, there is a need for computational approaches that can reliably estimate regulator activity from observable gene expression data. In this work, we present a noisy Boolean logic Bayesian model for TF activity inference from differential gene expression data and causal graphs. Our approach provides a flexible framework to incorporate biologically motivated TF-gene regulation logic models. Using simulations and controlled over-expression experiments in cell cultures, we demonstrate that our method can accurately identify TF activity. Moreover, we apply our method to bulk and single cell transcriptomics measurements to investigate transcriptional regulation of fibroblast phenotypic plasticity. Finally, to facilitate usage, we provide user-friendly software packages and a web-interface to query TF activity from user input differential gene expression data: https://umbibio.math.umb.edu/nlbayes/. Author SummaryNextGen RNA sequencing (RNA-Seq) has enabled simultaneous measurement of the expression level of all genes. Measurements can be done at the population level or single-cell resolution. However, direct measurement of regulatory mechanisms, such as Transcription Factor (TF) activity, is still not possible in a high-throughput manner. As such, there is a need for computational models to infer regulator activity from gene expression data. In this work, we introduce a Bayesian methodology that utilizes prior biological knowledge on bio-molecular interactions in conjunction with readily available gene expression measurements to estimate TF activity. The Bayesian model naturally incorporates biologically motivated combinatorial TF-gene interaction logic models and accounts for noise in gene expression data as well as prior knowledge. The method is accompanied by efficiently implemented R and Python software packages as well as a user-friendly web-based interface that allows users to upload their gene expression data and run queries on a TF-gene interaction network to identify and rank putative transcriptional regulators. This tool can be used for a wide range of applications, such as identification of TFs downstream of signaling events and environmental or molecular perturbations, the aberration in TF activity in diseases, and other studies with case-control gene expression data.

bioinformatics↗

bioRxiv2021

Bee foraging preferences, microbiota and pathogens revealed by direct shotgun metagenomics of honey

Honeybees (Apis mellifera) continue to succumb to human and environmental pressures despite their crucial role in providing essential ecosystem services. Owing to their foraging and honey production activities, honeybees form complex relationships with species across all domains, such as plants, viruses, bacteria (symbiotic and pathogenic), and other hive pests, making honey a valuable biomonitoring tool for assessing their ecological niche. Thus, the application of honey shotgun metagenomics (SM) has paved the way for a detailed description of the species honeybees interact with, in order to better assess the multiple factors governing their health. Here, we describe the implementation of optimized honey DNA extraction methodology coupled to direct shotgun metagenomics (Direct-SM) analysis, and to a computationally optimised and validated pipeline for taxonomic classification of species detected in honey. By comparing honey collected across 3 harvesting seasons in a stable apiary, we show that Direct-SM can describe the variability of sampled plant species, revealing honeybee behavioural adaptation. In addition, we reveal that Direct-SM can non-invasively capture the diversity of species comprising the core and non-core bacterial communities of the gut microbiome. Finally, we show that this methodology is applicable for the monitoring of pathogens and particularly for the biomonitoring varroa infestation. These results suggest that Direct-SM can accurately and comprehensively describe honeybee ecological niches and can be deployed to assess bee health in the field.

ecology↗

bioRxiv2020

Specialisation and plasticity in a primitively social insect

Biological systems not only have the remarkable capacity to build and maintain complex spatio-temporal structures in noisy environments, they can also rapidly break up and rebuild such structures. How such systems can simultaneously achieve both robust specialisation and plasticity is poorly understood. Here we use primitive societies of Polistes wasps as a model system where we experimentally perturb the social structure by removing the queen and follow the re-establishment of the social steady state over time. We combine a unique experimental strategy correlating time-resolved measurements across vastly different scales with a theoretical approach. We show that Polistes integrates antagonistic processes on multiple scales to distinguish between extrinsic and intrinsic perturbations and thereby achieve both robust specialisation and rapid plasticity. The long-term stability of the social structure relies on dynamic DNA methylation which controls transcriptional noise. Such dynamics provide a general principle of how both specialization and plasticity can be achieved in biological systems. One Sentence SummaryA primitive social insect simultaneously achieves specialisation and plasticity by integrating antagonistic dynamics on different scales. HighlightsO_LIWe employ a unique experimental approach correlating dynamics of societies, individuals, and epigenetic gene regulation C_LIO_LIA social insect simultaneously achieves specialisation and plasticity by integrating antagonistic processes on different spatial scales C_LIO_LIRegulation of population-level noise by DNA methylation ensures long-term stability of phenotypic specialisation C_LI

biophysics↗