PLoS One. 2025 Jun 3;20(6):e0324312. doi: 10.1371/journal.pone.0324312. eCollection 2025.

ABSTRACT

In the evolving landscape of technology, robots have emerged as social companions, prompting an investigation into social bonding between humans and robots. While human-animal interactions are well-studied, human-robot interactions (HRI) remain comparatively underexplored. Ethorobotics, a field of social robotic engineering based on ecology and ethology, suggests designing companion robots modeled on animal companions, which are simpler to emulate than humans. However, it is unclear whether these robots can match the social companionship provided by their original models. This study examined social bonding between humans and AIBOs, dog-inspired companion robots, compared to real dogs. Nineteen female participants engaged in 12 affiliative interactions with dogs and AIBOs across two counter-balanced, one-month bonding phases. Social bonding was assessed through urinary oxytocin (OXT) level change over an interaction, self-reported attachment using an adapted version of the Lexington Attachment to Pets Scale, and social companionship evaluations administering the Robot-Dog Questionnaire. To examine OXT level changes and self-reported attachment by comparing the two social companions, we conducted mixed-effects model analyses and planned follow-up comparisons. Frequency comparison, binary logistic regression, and thematic analysis were performed to analyze social companionship evaluations. Results revealed significant differences between dogs and AIBOs in fostering social bonds. OXT level change increased during interactions with dogs but decreased with AIBOs. Participants reported stronger attachment to dogs and rated them as better social companions. These findings highlight the current limitations of AIBOs in fostering social bonding immediately compared to dogs. Our study contributes to the growing HRI research by demonstrating an existing gap between AIBOs and dogs as social companions. It highlights the need for further investigation to understand the complexities of social bonding with companion robots, which is essential to implement successful applications for social robots in diverse domains such as the elderly and health care, education, and entertainment.

PMID:40460066 | DOI:10.1371/journal.pone.0324312

ACS Synth Biol. 2025 Jun 3. doi: 10.1021/acssynbio.4c00894. Online ahead of print.

ABSTRACT

Addressing the challenge of achieving a global circular bioeconomy requires efficient and robust bio-based processes operating at different scales. These processes should also be competitive replacements for the production of chemicals currently obtained from fossil resources, as well as for the production of new-to-nature compounds. To that end, genetic circuits can be used to control cellular behavior and are instrumental in developing efficient cell factories. Whole-cell biosensors harbor circuits that can be based on allosteric transcription factors (TFs) to detect and elicit a response depending on the target molecule concentrations. By modifying regulatory elements and testing various genetic components, the responsive behavior of genetic biosensors can be finely tuned and engineered. While previous models have described and characterized the behavior of naringenin biosensors, additional data and resources are required to predict their dynamic response and performance in different contexts, such as under various gene expression regulatory elements, media, carbon sources, or media supplements. Tuning these conditions is pivotal in optimizing biosensor design for applications operating in varying conditions, such as fermentation processes. In this study, we assembled a library of FdeR biosensors, characterized their performance under different conditions, and developed a mechanistic model to describe their dynamic behavior under reference conditions, which guided a machine learning-based predictive model that accounts for context-dependent dynamic parameters. Such a Design-Build-Test-Learn (DBTL) pipeline allowed us to determine optimal condition combinations for the desired biosensor specifications, both for automated screening and dynamic regulation. The findings of this work contribute to a deeper understanding of whole-cell biosensors and their potential for precise measurement, screening, and dynamic regulation of engineered production pathways for valuable molecules.

PMID:40460061 | DOI:10.1021/acssynbio.4c00894

ACS Nano. 2025 Jun 3. doi: 10.1021/acsnano.5c03590. Online ahead of print.

ABSTRACT

The safety of inorganic nanoparticles (NPs) remains a critical challenge for their clinical translation. To address this, we developed a machine learning (ML) framework that predicts NP toxicity both in vitro and in vivo, leveraging physicochemical properties and experimental conditions. A curated in vitro cytotoxicity dataset was used to train and validate binary classification models, with top-performing models undergoing explainability analysis to identify key determinants of toxicity and establish structure-toxicity relationships. External testing with diverse inorganic NPs validated the predictive accuracy of the framework for in vitro settings. To enable organ-specific toxicity predictions in vivo, we integrated a physiologically based pharmacokinetic (PBPK) model into the ML pipeline to quantify NP exposure across organs. Retraining the ML models with PBPK-derived exposure metrics yielded robust predictions of organ-specific nanotoxicity, further validating the framework. This PBPK-informed ML approach can thus serve as a potential alternative approach to streamline NP safety assessment, enabling the rational design of safer NPs and expediting their clinical translation.

PMID:40460056 | DOI:10.1021/acsnano.5c03590

PLoS Biol. 2025 Jun 3;23(6):e3003172. doi: 10.1371/journal.pbio.3003172. eCollection 2025 Jun.

ABSTRACT

Inhaled anesthetics were first introduced into clinical use in the 1840s. Molecular and transgenic animal studies indicate that inhaled anesthetics act through several ion channels, including γ-aminobutyric acid type A receptors (GABAARs) and two-pore domain K+ (K2P) channels, but other targets may mediate anesthetic effects. Mutations in the type 1 ryanodine receptor (RyR1), which is a calcium release channel on the endoplasmic reticulum membrane, are relevant to malignant hyperthermia, a condition that can be induced by inhaled anesthetics. However, it was previously uncertain whether inhaled anesthetics directly interact with RyR1. In our study, we demonstrated that isoflurane and other inhaled anesthetics activate wild-type RyR1. By employing systematic mutagenesis, we discovered that altering just one amino acid residue negates the response to isoflurane, thus helping us to pinpoint the potential binding site. Knock-in mice engineered to express a mutant form of RyR1 that is insensitive to isoflurane exhibited resistance to the loss of righting reflex (LORR) when exposed to isoflurane anesthesia. This observation suggests a connection between RyR1 activation and the anesthetic effects in vivo. Moreover, it was shown that RyR1 is involved in the neuronal response to isoflurane. Additionally, administering new RyR1 agonists, which share the same binding site as isoflurane, resulted in a sedation-like state in mice. We propose that isoflurane directly activates RyR1, and this activation is pertinent to its anesthetic/sedative effects.

PMID:40460053 | DOI:10.1371/journal.pbio.3003172

Bioinformatics. 2025 Jun 3:btaf326. doi: 10.1093/bioinformatics/btaf326. Online ahead of print.

ABSTRACT

MOTIVATION: Drug combination therapy is an effective strategy for cancer treatment, enhancing drug efficacy and reducing toxic side effects. However, in vitro drug screening experiments are time-consuming and expensive, necessitating the development of computational methods for drug synergy prediction. While current methods focus on molecular chemical structures, they often overlook the biological context, limiting their ability to capture complex drug synergies.

RESULTS: In this work, we propose MADSP, a novel method for anti-cancer drug synergy prediction that integrates target and pathway knowledge for a more comprehensive understanding of systems biology. MADSP first incorporates chemical structure, target, and pathway features of drugs, using a multi-head self-attention mechanism to learn a unified drug representation. It then integrates protein-protein interaction (PPI) data with omics data from cell lines, extracting a low-dimensional dense embedding of cell lines via an autoencoder. Finally, the synergy scores for drug combinations are predicted using a fully connected neural network. Experiments on benchmark datasets demonstrate that MADSP outperforms state-of-the-art methods. The ablation study reveals that multi-source information fusion and attention mechanisms significantly enhance model performance. The case study further illustrates the practical applicability of MADSP as a powerful tool for drug synergy prediction, offering potential for advancing cancer treatment strategies.

AVAILABILITY AND IMPLEMENTATION: MADSP is available at https://github.com/Hhyqi/MADSP.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:40460032 | DOI:10.1093/bioinformatics/btaf326

mBio. 2025 Jun 3:e0087225. doi: 10.1128/mbio.00872-25. Online ahead of print.

ABSTRACT

Proteases regulate important biological functions. Here, we present the structural and functional characterization of three previously uncharacterized aspartic proteases in Pseudomonas aeruginosa. We show that these proteases have structural hallmarks of retropepsin peptidases and play redundant roles for cell survival under hypoosmotic stress conditions. Consequently, we named them retropepsin-like osmotic stress tolerance peptidases (Rlo). Our research shows that while Rlo proteases are homologous to RimB, an aspartic peptidase involved in rhizosphere colonization and plant infection, they contain N-terminal signal peptides and perform distinct biological functions. Mutants lacking all three secreted Rlo peptidases show defects in antibiotic resistance, biofilm formation, and cell morphology. These defects are rescued by mutations in the inactive transglutaminase transmembrane protein RloB and the cytoplasmic ATP-grasp protein RloC, two previously uncharacterized genes in the same operon as one of the Rlo proteases. These studies identify Rlo proteases and rlo operon products as critical factors in clinically relevant processes, making them appealing targets for therapeutic strategies against Pseudomonas infections.IMPORTANCEBacterial infections have become harder to treat due to the ability of pathogens to adapt to different environments and the rise of antimicrobial resistance. This has led to longer illnesses, increased medical costs, and higher mortality rates. The opportunistic pathogen Pseudomonas aeruginosa is particularly problematic because of its inherent resistance to many antibiotics and its capacity to form biofilms, structures that allow bacteria to withstand hostile conditions. Our study uncovers a new class of retropepsin-like proteases in P. aeruginosa that are required for biofilm formation and bacterial survival under stress conditions, including antibiotic exposure. By identifying critical factors that determine bacterial fitness and adaptability, our research lays the foundation for developing new therapeutic strategies against bacterial infections.

PMID:40459290 | DOI:10.1128/mbio.00872-25

Elife. 2025 Jun 3;13:RP100071. doi: 10.7554/eLife.100071.

ABSTRACT

Targeted monotherapies for cancer often fail due to inherent or acquired drug resistance. By aiming at multiple targets simultaneously, drug combinations can produce synergistic interactions that increase drug effectiveness and reduce resistance. Computational models based on the integration of omics data have been used to identify synergistic combinations, but predicting drug synergy remains a challenge. Here, we introduce Drug synergy Interaction Prediction (DIPx), an algorithm for personalized prediction of drug synergy based on biologically motivated tumor- and drug-specific pathway activation scores (PASs). We trained and validated DIPx in the AstraZeneca-Sanger (AZS) DREAM Challenge human cell-line dataset using two separate test sets: Test Set 1 comprised the combinations already present in the training set, while Test Set 2 contained combinations absent from the training set, thus indicating the model's ability to handle novel combinations. The Spearman's correlation coefficients between predicted and observed drug synergy were 0.50 (95% CI: 0.47-0.53) in Test Set 1 and 0.26 (95% CI: 0.22-0.30) in Test Set 2, compared to 0.38 (95% CI: 0.34-0.42) and 0.18 (95% CI: 0.16-0.20), respectively, for the best performing method in the Challenge. We show evidence that higher synergy is associated with higher functional interaction between the drug targets, and this functional interaction information is captured by PAS. We illustrate the use of PAS to provide a potential biological explanation in terms of activated pathways that mediate the synergistic effects of combined drugs. In summary, DIPx can be a useful tool for personalized prediction of drug synergy and exploration of activated pathways related to the effects of combined drugs.

PMID:40459126 | DOI:10.7554/eLife.100071

New Phytol. 2025 Jun 3. doi: 10.1111/nph.70227. Online ahead of print.

ABSTRACT

Plant host cell-cycle hyperactivation is essential for nematode feeding site (NFS) ontogenesis, but the balanced mitotic and endoreplication cycles must occur for homeostasis. Alterations in core cell cycle gene expression are well known to disturb root-knot and cyst-NFS development. Herein, our investigation focused on the activity of E2FA and E2FB transcription factors in root-knot nematode-induced galls in Arabidopsis thaliana controlling both the mitotic and endocycles through the activation of S-phase cell cycle genes. The roles of the two plant E2F activators during cell cycle progression in galls were compared with syncytia induced by cyst nematodes. E2FA and E2FB transcripts were highly expressed in both galls and syncytia. Loss-of-function analysis revealed that the absence of E2FA and E2FB impaired feeding-site development, resulting in significantly reduced gall development and nematode reproduction. Transcript analysis of galls upon E2FA and E2FB loss-of-function compared with that of wild-type revealed differential expression of selected target genes operating during S phase. Although our results imply the functional interplay of E2FA and E2FB for gall development, we recognize that E2FA alone commands and sustains cell division as well as the endocycle in galls and syncytia, whereas E2FB is likely partaking in nematode-induced gall initiation.

PMID:40459000 | DOI:10.1111/nph.70227

Int J Cancer. 2025 Jun 3. doi: 10.1002/ijc.35499. Online ahead of print.

ABSTRACT

Recent studies show that the dysregulation of the transcription factor SOX10 is essential for the development and progression of melanoma. MicroRNAs (miRNAs) can regulate the expression of transcription factors at the post-transcriptional level. The interactions between SOX10 and its targeting miRNAs form network motifs such as feedforward and feedback loops. Such motifs can result in nonlinear dynamics in gene expression levels, therefore playing a crucial role in regulating tumor proliferation and metastasis as well as the tumor's responses to therapies. Here, we reviewed and discussed the intricate interplay between SOX10 and miRNAs in melanoma biology including melanogenesis, phenotype switch, and therapy resistance. Additionally, we investigated the gene regulatory interactions in melanoma, identifying crucial network motifs that involve SOX10, MITF, and miRNAs. We also analyzed the expression levels of the components within these motifs. From a control theory perspective, we explained how these dynamics are linked to the phenotypic plasticity of melanoma cells. In summary, we underscored the importance of employing a data-driven network biology approach to elucidate the complex regulatory mechanisms and identify driver network motifs within the melanoma network. This methodology facilitates a deeper understanding of the regulation of SOX10 and MITF by miRNAs in melanoma. The insight gained could potentially contribute to the development of miRNA-based treatments, thereby enhancing the clinical management of this malignancy.

PMID:40458894 | DOI:10.1002/ijc.35499

Front Pharmacol. 2025 May 19;16:1570158. doi: 10.3389/fphar.2025.1570158. eCollection 2025.

ABSTRACT

Protein glycosylation, particularly O-GlcNAcylation, is a critical post-translational modification (PTM) that regulates cardiac and vascular functions by modulating protein stability, localization, and interactions. Dysregulated glycosylation is generally believed as a key driver in the pathogenesis of cardiovascular diseases (CVDs), contributing to adverse cardiac remodeling, mitochondrial dysfunction, metabolic dysregulation, and vascular inflammation. This review highlights the mechanistic roles of glycosylation in CVD progression, including its regulation of cardiac remodeling, mitochondrial dysfunction, and vascular inflammation. This study explored the dual role of O-GlcNAcylation in acute protection and chronic injury, emphasizing its potential as a biomarker for early diagnosis and risk stratification. Therapeutic strategies targeting glycosylation pathways, particularly O-GlcNAc transferase (OGT), and O-GlcNAcase (OGA), hold promise for addressing myocardial ischemia-reperfusion injury, diabetic cardiomyopathy, and atherosclerosis. Advances in glycosylation profiling and interdisciplinary collaboration are essential to overcome challenges such as tissue specificity and off-target effects, advancing precision cardiovascular medicine.

PMID:40458788 | PMC:PMC12127152 | DOI:10.3389/fphar.2025.1570158

Biofilm. 2025 May 3;9:100284. doi: 10.1016/j.bioflm.2025.100284. eCollection 2025 Jun.

ABSTRACT

Synthetic communities (SynComs) are valuable tools for addressing microbial community assembly and function, towards their manipulation for clinical, biotechnological and agricultural applications. However, SynCom design is complicated since interactions between microbes cannot be predicted based on their individual properties. Here we aimed to assemble a functionally cohesive SynCom displaying high-order interactions, as a model to study the community-level beneficial functions of seed-endophytic bacteria from native maize landraces, including strains from the Bacilli class, and the Burkholderia and Pseudomonas genera. We developed a partial combinatorial, bottom-up strategy that was followed by the detection of complex colony architecture as an emergent property in co-cultures. Using this simplified approach, we tested less than 400 co-cultures from a pool of 27 strains, resulting in the assembly the Xilonen SynCom, which includes Bacillus pumilus NME155, Burkholderia contaminans XM7 and Pseudomonas sp. GW6. In this community, higher-order interactions result in complex colony architecture, which is considered a proxy of biofilm formation. Additionally, we generated protocols for absolute quantification of each member from a complex mixture. The Xilonen SynCom will serve as a model to study biofilm formation in community settings, and will aid in the study of the molecular and ecological basis mediating maize fertility.

PMID:40458266 | PMC:PMC12127623 | DOI:10.1016/j.bioflm.2025.100284

Mol Biol Evol. 2025 Jun 3:msaf127. doi: 10.1093/molbev/msaf127. Online ahead of print.

ABSTRACT

How viruses evolve largely depends on their hosts. To quantitatively characterize this dependence, we introduce Maximum Entropy Nucleotide Bias models (MENB) learned from single, di- and tri- nucleotide usage of viral sequences that infect a given host. We first use MENB to classify the viral family and the host of a virus from its genome, among four families of ssRNA viruses and three hosts. We show that both the viral family and the host leave a fingerprint in nucleotide motif usages that MENB models decode. Benchmarking our approach against state-of-the-art methods based on deep neural networks, such as VIDHOP, shows that MENB is rapid, interpretable and robust. Our approach is able to predict, with good accuracy, both the viral family and the host from a whole genomic sequence or a portion of it. MENB models also display promising out of sample generalization ability on viral sequences of new host taxa or new viral families. Our approach is also capable of identifying, within the limitations imposed by the three-host setting, intermediate hosts for well-known pathogenic strains of Influenza A subtypes and Human Coronavirus and recombinations and reassortments on specific genomic regions. Finally MENB models can be used to track the adaptation to the new host, to shed light on the more relevant selective pressures that acted on motif usage during this process and to design new sequences with altered nucleotide usage at fixed amino-acid content.

PMID:40458044 | DOI:10.1093/molbev/msaf127

Genome Med. 2025 Jun 2;17(1):65. doi: 10.1186/s13073-025-01486-w.

ABSTRACT

BACKGROUND: Human leukocyte antigen class II (HLA-II) genes are highly polymorphic affecting the specificity of human antibody responses, as presentation of processed antigen peptides by HLA-II on B cells is essential for T helper cell dependent affinity maturation and class switching. The combination of high-throughput immunoassays and genome-wide association studies has recently revealed strong associations between HLA-II variants and antibody responses against specific antigens. However, factors underlying these associations remain incompletely understood.

METHODS: Here, we have leveraged paired data sets of SNP arrays and functional antibody epitope repertoires against 344,000 peptide antigens in 1940 individuals to mine for key determinants linking genetics and antibody specificity.

RESULTS: We show that secreted proteins and antigens presented in small modules (i.e., viruses) are significantly more frequently associated with HLA-II alleles, than membrane bound or intracellular proteins. This data suggests a model in which antibody responses against separate antigen units composed of single or few proteins dominate HLA-II associations. In contrast, the presence of manifold intracellular or membrane proteins (peptides of which could be bound by different HLA-II alleles) on bacterial cells dilutes potential associations to antibody specificities.

CONCLUSIONS: Hence, genetic associations to antibody specificities are shaped by antigen intrinsic properties. Given the prominent role of HLA-II alleles in infection, autoimmune diseases, allergies, and cancer, our work provides a theoretical framework to study antigen/HLA-II risk factors in these disease settings and will fuel the design of improved immunogenetics screens.

PMID:40457459 | DOI:10.1186/s13073-025-01486-w

Nat Genet. 2025 Jun 2. doi: 10.1038/s41588-025-02198-y. Online ahead of print.

ABSTRACT

The completion of the Human Genome Project catalyzed the development of 'omics' technologies, enabling the detailed exploration of biological systems at an unprecedented molecular scale. Microfluidics has transformed the omics toolbox by facilitating large-scale, high-throughput and highly accurate measurements of DNA and RNA, driving the transition from bulk to single-cell analyses. This transition has ushered in a new era, moving beyond a gene- and protein-centric perspective toward a holistic understanding of cellular phenotypes. This emerging 'single-cell phenomics era' integrates diverse omics datasets with spatial, morphological and temporal phenotypes to provide a comprehensive perspective on cellular function. This Review highlights how microfluidics addressed key challenges in the transition to single-cell omics and explores how lessons learned from these efforts will propel the single-cell phenomics revolution. Furthermore, we discuss emerging opportunities in which integrative single-cell phenomics could serve as a foundation for transformative discoveries in biology.

PMID:40457076 | DOI:10.1038/s41588-025-02198-y

Nat Neurosci. 2025 Jun 2. doi: 10.1038/s41593-025-01952-z. Online ahead of print.

ABSTRACT

Aging is one of the most prominent risk factors for neurodegeneration, yet the molecular mechanisms underlying the deterioration of old neurons are mostly unknown. To efficiently study neurodegeneration in the context of aging, we transdifferentiated primary human fibroblasts from aged healthy donors directly into neurons, which retained their aging hallmarks, and we verified key findings in aged human and mouse brain tissue. Here we show that aged neurons are broadly depleted of RNA-binding proteins, especially spliceosome components. Intriguingly, splicing proteins-like the dementia- and ALS-associated protein TDP-43-mislocalize to the cytoplasm in aged neurons, which leads to widespread alternative splicing. Cytoplasmic spliceosome components are typically recruited to stress granules, but aged neurons suffer from chronic cellular stress that prevents this sequestration. We link chronic stress to the malfunctioning ubiquitylation machinery, poor HSP90α chaperone activity and the failure to respond to new stress events. Together, our data demonstrate that aging-linked deterioration of RNA biology is a key driver of poor resiliency in aged neurons.

PMID:40456907 | DOI:10.1038/s41593-025-01952-z

Nat Commun. 2025 Jun 2;16(1):5120. doi: 10.1038/s41467-025-60233-2.

ABSTRACT

Inflammatory bowel diseases (IBDs) are chronic disorders involving dysregulated immune responses. Despite the role of disrupted host-microbial interaction in the pathophysiology of IBD, the underlying metabolic principles are not fully understood. We densely profiled microbiome, transcriptome and metabolome signatures from longitudinal IBD cohorts before and after advanced drug therapy initiation and reconstructed metabolic models of the gut microbiome and the host intestine to study host-microbiome metabolic cross-talk in the context of inflammation. Here, we identified concomitant changes in metabolic activity across data layers involving NAD, amino acid, one-carbon and phospholipid metabolism. In particular on the host level, elevated tryptophan catabolism depleted circulating tryptophan, thereby impairing NAD biosynthesis. Reduced host transamination reactions disrupted nitrogen homeostasis and polyamine/glutathione metabolism. The suppressed one-carbon cycle in patient tissues altered phospholipid profiles due to limited choline availability. Simultaneously, microbiome metabolic shifts in NAD, amino acid and polyamine metabolism exacerbated these host metabolic imbalances. Leveraging host and microbe metabolic models, we predicted dietary interventions remodeling the microbiome to restore metabolic homeostasis, suggesting novel therapeutic strategies for IBD.

PMID:40456745 | DOI:10.1038/s41467-025-60233-2

Int J Cancer. 2025 Jun 2. doi: 10.1002/ijc.35490. Online ahead of print.

ABSTRACT

During cancer development and progression, many genetic alterations lead to the acquisition of novel features that confer selective advantage to cancer cells and that resemble developmental programs. SRY-box transcription factor 2 (SOX2) is one of the key pluripotency transcription factors, expressed during embryonic development and active in adult stem cells. In cancer, SOX2 is frequently dysregulated and associated with tumor stemness and poor patient survival. SOX2 expression is suppressed in differentiated cells by tumor suppressor proteins that form a transcriptional repressive complex. We previously identified some of these proteins and found that their absence combined with deficiency in Trp53 leads to maximal dysregulated expression of Sox2. Using cancer cell lines of different origin and with different p53 status, we show here that manipulating TP53 to restore or decrease its activity results in repression or induction of SOX2, respectively. Mechanistically, we observed that the regulation of SOX2 expression by TP53 is transcriptional and identified Trp53 bound to the promoter region and the Sox2 Regulatory Region 2 enhancer of Sox2. Forcing high levels of SOX2 in cancer cells leads to morphological changes that molecularly correspond to the acquisition of a more mesenchymal phenotype, correlating with an increased migratory capacity. Finally, the analysis of human breast cancer samples shows that this correlation between TP53 status, levels of expression of SOX2, and a more metastatic phenotype is also observed in cancer patients. Our results support the notion that lack of TP53 in tumor cells results in deregulated expression of developmental gene SOX2 with phenotypic consequences related to increased malignization.

PMID:40456627 | DOI:10.1002/ijc.35490

J Food Prot. 2025 May 31:100551. doi: 10.1016/j.jfp.2025.100551. Online ahead of print.

ABSTRACT

To enhance control of human pathogenic microorganisms in plant production systems, an EU COST Action (HUPLANTcontrol CA16110) was initiated, bringing together microbiologists in food, environmental and plant microbial ecology. This article summarizes the outcomes of multiple workshops and the four main lessons learned: (i) many terminologies need further explanation to facilitate multidisciplinary communication on the behavior of human pathogens from pre-harvest plant production to post-harvest food storage, (ii) the complexity of bacterial taxonomy pushes microbial hazard identification for greater resolution of characterisation (to subspecies, or even strain level) needing a multi-method approach, (iii) hazard characterisation should consider a range of factors to evaluate the weight of evidence for adverse health effects in humans, including strain pathogenicity, host susceptibility, and the impact of the plant, food, or human gut microbiome, (iv) a wide diversity of microorganisms in varying numbers and behaviours co-exist in the plant microbiome, including good (beneficial for plant or human health), bad (established human or plant pathogens) or ugly (causing spoilage or opportunistic disease). In conclusion, active listening in communication and a multi-perspective approach are the foundation for every successful conversation when plant science meets food safety.

PMID:40456365 | DOI:10.1016/j.jfp.2025.100551

J Biol Chem. 2025 May 31:110329. doi: 10.1016/j.jbc.2025.110329. Online ahead of print.

ABSTRACT

Cellular protein homeostasis relies on a complex network of protein synthesis, folding, sub-cellular localization, and degradation to sustain a functional proteome. Since, most of these processes are energy driven, proteostasis is inescapably afflicted by cellular metabolism. Proteostasis collapse and metabolic imbalance are both linked to aging and age-associated disorders, yet they have traditionally been studied as a separate phenomenon in the context of aging. In this study, we indicate that reduced proteostasis capacity is a result of a metabolic imbalance associated with age. We observed increased accumulation of L-serine and L-threonine in replicative old cells of S. cerevisiae, indicating an imbalance in amino acid metabolism with replicative aging. Replicating this metabolic imbalance in young cells through deletion of serine dependent transcriptional activator, CHA4, resulted in increased aggregation of endogenous proteins along with misfolding prone proteins Guk1-7ts-GFP and Luciferase-GFP in both young and old cells. Aggregate formation in the cha4Δ strain required a functional sensor of mitochondrial dysfunction and an activator of the retrograde signalling gene, RTG2. CHA4 and RTG2 exhibited genetic interaction and together regulated mitochondrial metabolism, replicative lifespan, and aggregate formation in young cells, connecting metabolic regulation with proteostasis and aging. Constitutive activation of retrograde signalling through overexpression of RTG2 or deletion of MKS-1, negative regulator of Rtg1-Rtg3 nuclear translocation, resulted in faster resolution of aggregates upon heat shock through RTG3 and was found to be independent of molecular chaperone upregulation.

PMID:40456447 | DOI:10.1016/j.jbc.2025.110329

PLoS Genet. 2025 Jun 2;21(6):e1011261. doi: 10.1371/journal.pgen.1011261. Online ahead of print.

ABSTRACT

The myometrium, the muscular layer of the uterus, undergoes crucial transitions during pregnancy, maintaining quiescence throughout gestation, and generating coordinated contractions during labor. Dysregulation of this transition can lead to premature labor with serious complications for the infant. Despite extensive gene expression data available for varying myometrial states, the molecular mechanisms governing the increase in contraction-associated gene expression at labor onset remain unclear. Transcription factors, such as JUND and progesterone receptor (PR), play essential roles in regulating transcription of select myometrial contraction-associated genes, however, a broader understanding of their involvement in transcriptional regulation at a genome-wide scale is lacking. This study examines changes in transcription and JUND binding within human myometrial tissue during the transition from quiescence (term-not-in labor/TNIL) to contractility (term labor/TL). Total RNA-sequencing reveals a global increase in primary transcript levels at TL, with AP-1/JUND binding motifs overrepresented in the promoters of upregulated transcripts. Interestingly, ChIP-seq analysis demonstrates higher JUND enrichment in TNIL compared to TL tissues, suggesting its role in preparing the myometrium for labor onset. Integration of JUND and PR ChIP-seq data identifies over 10,000 gene promoters bound by both factors at TNIL and TL, including genes involved in labor-driving processes. Additionally, the study uncovers elevated levels of enhancer RNAs (eRNAs) at intergenic JUND peaks in laboring myometrial tissues, and implicates additional transcription factors, such as NFKB and ETS, in the regulatory switch from quiescence to contractility. In summary, this research enhances our understanding of the myometrial molecular regulatory network during pregnancy and labor, shedding light on the roles of JUND and PR in gene expression regulation genome-wide. These findings open avenues for further exploration, potentially leading to improved interventions for preventing premature labor and the associated complications.

PMID:40455848 | DOI:10.1371/journal.pgen.1011261