Gabriele Sales

Previous studies in monozygotic twins discordant for body mass index (BMI) revealed that individuals with obesity exhibit elevated expression of the immune receptor CD300e in white adipose tissue (WAT). Notably, CD300e levels decreased following weight loss, implicating its involvement in adipose tissue remodeling and metabolic regulation. To elucidate the functional role of CD300e, we employed a Cd300e knockout ( Cd300e−/− ) mouse model subjected to a high-fat diet (HFD). Our findings demonstrate that CD300e deficiency exacerbates obesity-associated metabolic dysfunction, including increased weight gain, adipocyte hypertrophy, hepatic steatosis, and impaired glucose and insulin sensitivity. Adipose tissue macrophages (ATMs) lacking CD300e displayed reduced lipid and glucose uptake, alongside diminished mitochondrial respiration—a phenotype consistent with a broader metabolic impairment, as evidenced by proteomic profiling. These metabolic deficits were genotype-dependent and persisted after 16 weeks of HFD. Concurrently, adipocytes from Cd300e−/− mice exhibited enhanced lipogenesis and attenuated lipolysis. Remarkably, the impaired metabolic fitness exhibited by Cd300e−/− mouse macrophages was recapitulated in human cells upon gene silencing. Collectively, these results establish CD300e as essential for ATM metabolic activation, positioning it as a key regulator of adipose tissue homeostasis and a critical mediator of obesity-induced metabolic dysfunction. Given its pivotal role, CD300e emerges as a promising therapeutic target for modulating adipose tissue function and improving metabolic health in obesity.

Summary: Heatwaves are increasing in frequency and intensity and may alter competitive interactions between native and non-indigenous plant species. We compared the responses of the native Sporobolus maritimus and the non-indigenous Sporobolus anglicus to a simulated 5-day heatwave using an integrative approach combining morphological, physiological, biochemical, transcriptomic, and metabolomic analyses. S. maritimus showed reduced survival, greater physiological damage, and no recovery, indicating high sensitivity to heat stress. Conversely, S. anglicus exhibited a rapid and coordinated response, limited damage to the photosynthetic apparatus, and full recovery after stress. These results highlight the greater resilience of S. anglicus and suggest a potential decline of the native species in the Venetian salt marshes under increasing heat stress. Graphical We investigated the effects of heatwaves on a native and NIS Sporobolus species from the Venice Lagoon using an integrative, multi-level approach during a simulated 5-day heatwave and recovery phase. The native species showed reduced survival, pronounced physiological damage, and no recovery, indicating high sensitivity to heat stress. Conversely, the NIS exhibited a rapid response, limited impairment of the photosynthetic apparatus, and full recovery. These findings indicate greater resilience of the NIS and suggest a potential decline of the native species in the Venice Lagoon under increasing heat stress. Image created with BioRender ( www.biorender.com ).

Plant proteomes contain evolutionarily conserved peptides with poorly conserved primary sequences, often hindering their identification and classification into families. Homology-based approaches and conventional annotation pipelines frequently fail to detect these family members, particularly in poorly characterized, but agronomically relevant plant species. CLE peptides (CLAVATA3/EMBRYO SURROUNDING REGION–related peptides) constitute a large and evolutionarily conserved family of plant signaling molecules, yet their characterization remains incomplete. Beyond a limited number of well-studied members, a substantial number of CLE peptides remain uncharacterized due to functional redundancy and the intrinsic features of CLE genes, which encode short pre-propeptides with only a small 12-residue conserved motif. Here, we present a novel framework leveraging state-of-the-art Protein Language Models (pLMs) to discover CLE peptides directly from 13 plant proteomes. By coupling sequence embeddings trained on large evolutionary datasets (ESM2 and ProtT5) with supervised machine learning, our dual-model approach captures deep semantic features of the CLE family that are missed by traditional alignment methods. The pipeline demonstrated robust generalization, achieving high classification accuracy (98.9-99.4%) on a held-out set of CLE peptides not used during training. Consequently, we identified a set of high-confidence, previously unannotated CLE candidates prioritized through a stringent consensus-based filtering strategy. This work demonstrates how AI-driven proteome analysis can overcome the limitations of homology-based methods and provides a scalable strategy for uncovering previously unidentified peptide-mediated signaling molecules across plant lineages. Highlight: Leveraging Protein Language Models, our AI framework uncovers “hidden” signaling peptides missed by standard tools, revealing the elusive diversity of CLE regulators across plant proteomes.

The increasing size of single-cell RNA sequencing (scRNA-seq) datasets poses major computational challenges. This work benchmarks the scalability, efficiency, and accuracy of five widely used analysis frameworks (Seurat, OSCA, scrapper, Scanpy, and rapids singlecell), focusing on the impact of algorithmic and infrastructural choices on performance. We performed a systematic comparison of these workflows using representative datasets, including a 1.3 million and a 4.2 million cell dataset for scalability and four smaller datasets (BE1, sc_mixology, cord blood CITE-seq and Hao) with ground truth labels to assess clustering accuracy. Principal Component Analysis (PCA) was used as a paradigmatic step to evaluate the computational performance of six SVD algorithms (exact, ARPACK, IRLBA, randomized, Jacobi, and incremental PCA) across multiple data representations (dense, sparse, HDF5) and hardware configurations (CPU vs GPU). All methods showed high concordance in PCA results, with negligible loss of accuracy in truncated approaches. GPU-based computation using rapids singlecell provided a 15 × speed-up over the best CPU methods, with moderate memory usage. On CPU, ARPACK and IRLBA were the most efficient for sparse matrices, while randomized SVD performed best for HDF5-backed data. Among full pipelines, rapids singlecell was the fastest, whereas OSCA and scrapper achieved the highest clustering accuracy (ARI up to 0.97) in datasets with known cell identities. Performance differences were largely driven by the choice of highly variable genes (HVGs) and PCA implementation. The study highlights that scalability in scRNA-seq analysis depends critically on both algorithmic and infrastructural factors. GPU acceleration and optimized BLAS/LAPACK configurations markedly enhance performance, while Bioconductor-based pipelines remain robust in accuracy. The provided benchmarks offer practical guidelines for efficient and reliable analysis of large-scale single-cell datasets.

Acartia tonsa is a calanoid copepod with a cosmopolitan distribution. Its ecological relevance makes it a useful bioindicator organism for assessing the toxicity of various compounds. However, transcriptomic assemblies of A. tonsa using long-read technologies have not yet been described. The use of long-read sequencing technologies in transcriptomics allows the study of alternative splicing, structural variations and alternative polyadenylation sites. In this study, we present a de novo transcriptome of A. tonsa adult copepods exposed to different neonicotinoids obtained from Nanopore sequences. This transcriptome (261,560 total transcripts, with 31,291 representative sequences) exhibits 88.3% completeness and an N50 of 2,580 bases, showing better results than previous assemblies of the same organism. We also performed a full annotation by sequence homology (NR database), domain identification (InterProScan) and functional classification (Gene Ontology); 54.3% of representative transcripts were annotated in at least one database. Our transcriptome represents a solid baseline for further transcriptomic studies on A. tonsa and, specifically, its response to currently used pesticides.

DNA recovered from herbarium specimens represents a vital asset in botanical research, playing a pivotal role in unravelling the evolution, diversity, and ecological dynamics of plants. Despite its importance, challenges such as fragmented DNA and insufficient sequencing yields render molecular data retrieval a high-risk and costly endeavour involving the use of non-replaceable herbarium specimens. Here, we propose a framework based on Artificial Intelligence (AI) to forecast the success of genomic DNA extraction suitable for sequencing from herbarium samples. Our model integrates morphological characteristics and sample colour derived from scanned herbarium images, metadata including sample age and locality, and DNA quantity measurements of samples. We train a deep learning algorithm with ca. 2,000 specimens that have been digitized and sequenced in the framework of the Plant and Fungal Trees of Life (PAFTOL) Project, spanning from year 1832 to the present. As training datasets increase with ongoing digitization and genomic sequencing efforts, our AI predictive model can support researchers in selecting the herbarium samples with the highest likelihood of yielding high-quality genomic DNA from amongst a vast array of globally distributed candidate specimens. Our approach enhances the contribution of herbarium-derived DNA in large-scale studies and facilitates the utilisation of historical collections for a deeper understanding of plant evolution and ecology, with implications for conservation.

The complement system is a pivotal component of innate immunity, extensively studied in vertebrates but also present in invertebrates. This study explores the existence of a terminal complement pathway in the tunicate Botryllus schlosseri, aiming to understand the evolutionary integration of innate and adaptive immunity. Through transcriptome analysis, we identified a novel transcript, BsITCCP, encoding a protein with both MACPF and LDLa domains—a structure resembling that of vertebrate C9 but with a simpler organization. Phylogenetic reconstruction positions BsITCCP between invertebrate perforins and vertebrate terminal complement proteins, suggesting an evolutionary link. Localization studies confirmed that bsitccp is transcribed in cytotoxic morula cells (MCs), which are also responsible for producing other complement components like BsC3, BsMBL, BsMASP, and BsBf. Functional assays demonstrated that bsitccp transcription is upregulated in response to nonself challenges and is dependent on BsC3 activity; inhibition of BsC3 led to a significant reduction in BsITCCP expression. Electron microscopy revealed that MCs form contact with perforated yeast cells, indicating a possible mechanism of cell lysis similar to the immunological synapse observed in vertebrates. These findings suggest that a C3-governed lytic complement pathway exists in B. schlosseri, challenging the assumption that a C5 ortholog is necessary for such a pathway. This work enhances our understanding of the evolution of the complement system and suggests that invertebrates possess a terminal complement complex capable of mediating cell lysis, regulated by C3. Future studies will focus on confirming the pore-forming ability of BsITCCP and its role in the immunological synapse.

Duchenne muscular dystrophy (DMD) is one of the most frequent and severe childhood muscle diseases. Its pathophysiology is multifaceted and still incompletely understood, but we and others have previously shown that oxidative stress plays an important role. In particular, we have demonstrated that inhibition of mitochondrial monoamine oxidases could improve some functional and biohumoral markers of the pathology. In the present study we report the use of dystrophic mdx mice to evaluate the efficacy of a dual monoamine oxidase B (MAO-B)/semicarbazide-sensitive amine oxidase (SSAO) inhibitor, PXS-5131, in reducing inflammation and fibrosis and improving muscle function. We found that a one-month treatment starting at three months of age was able to decrease reactive oxygen species (ROS) production, fibrosis, and inflammatory infiltrate in the tibialis anterior (TA) and diaphragm muscles. Importantly, we also observed a marked improvement in the capacity of the gastrocnemius muscle to maintain its force when challenged with eccentric contractions. Upon performing a bulk RNA-seq analysis, PXS-5131 treatment affected the expression of genes involved in inflammatory processes and tissue remodeling. We also studied the effect of prolonged treatment in older dystrophic mice, and found that a three-month administration of PXS-5131 was able to greatly reduce the progression of fibrosis not only in the diaphragm but also in the heart. Taken together, these results suggest that PXS-5131 is an effective inhibitor of fibrosis and inflammation in dystrophic muscles, a finding that could open a new therapeutic avenue for DMD patients.

Salpa thompsoni is an important grazer in the Southern Ocean and most abundant in the Antarctic Polar Front (APF) region. During recent decades, their distribution expanded southwards. However, it is unclear whether salps can maintain their populations in the high Antarctic regions throughout the year owing to a poor understanding of their physiological responses to changing environmental conditions. We examined gene expression signatures of salps collected in two geographically close regions south of the APF that differed in water mass composition and productivity. The observed differences in the expression of genes related to reproductive, cellular and metabolic processes reflect variations in water temperature and food supply between the two regions studied here. Our study contributes to a better understanding of the physiological responses of S. thompsoni to changing environmental conditions, and how the species may adapt to a changing environment through potential geographical population shifts under future climate change scenarios.