J Invest Dermatol. 2025 Apr 9:S0022-202X(25)00401-4. doi: 10.1016/j.jid.2025.03.033. Online ahead of print.

ABSTRACT

T cells and structural cells coordinate appropriate inflammatory responses and restoration of barrier integrity following insult. Dysfunctional T cells precipitate skin pathology occurring alongside altered structural cell frequencies and transcriptional states, but to what extent different T cells promote disease-associated changes remains unclear. We show that functionally diverse circulating and skin-resident CD4+CLA+ T cell populations promote distinct transcriptional outcomes in human keratinocytes and fibroblasts associated with inflamed or healthy tissue. We identify Th17 cell-induced genes in keratinocytes that are enriched in psoriasis patient skin and normalized by anti-IL-17 therapy. We also describe a CD103+ skin-resident T cell-induced transcriptional module enriched in healthy controls that is diminished during psoriasis and scleroderma and show that CD103+ T cell frequencies are altered during disease. Interrogating clinical data using immune-dependent transcriptional signatures defines the T cell subsets and genes distinguishing inflamed from healthy skin and allows investigation of heterogeneous patient responses to biologic therapy.

PMID:40216155 | DOI:10.1016/j.jid.2025.03.033

Int J Biol Macromol. 2025 Apr 9:143040. doi: 10.1016/j.ijbiomac.2025.143040. Online ahead of print.

ABSTRACT

Poly-3-hydroxyalkanoate (PHA) and polyacrylamide (PAM) are potentially copolymerized into a novel hybrid material with distinctive characteristics but scarcely explored. In this study, the copolymerization of semicrystalline and amorphous forms of PHA, designated as scPHA and amPHA, with PAM utilizing ultrasonication and hydrogen peroxide as the initiator under defined conditions were investigated. The effect of varying acrylamide amounts on the yield and properties of graft copolymers (PHA-g-MA) were characterized by molecular weight changes, thermal and spectroscopic properties. Grafting scPHA and amPHA with PAM influenced their initial molecular weights (Mw). Specifically, scPHA's Mw decreased from 140 × 103 to ~130 × 103 g mol-1, while amPHA's Mw increased from 62 × 103 to ~68 × 103 g mol-1. Additionally, scPHA and amPHA copolymers showed an increase in thermal decomposition temperature (Td) from 240 °C to 265 °C and 275 °C to 285 °C, respectively. The presence of an amide functional group in the copolymers was authenticated by a Raman peak at 1100 cm-1. Both scPHA and amPHA graft copolymers exhibited unique contrast to their neat counterpart. The scPHA-g-PAMs showed strong crystalline characteristics, evidenced by elevated glass transition and melting temperatures, alterations in crystalline planes and surface morphologies, and a decrease in dielectric constant values. Conversely, amPHA-g-PAMs showed pronounced amorphous characteristics, substantiated by a lowered glass transition and melting temperatures, altered surface morphologies, and increased dielectric constant values. The observations made are attributed to distinct chain packing characteristics between both graft copolymers, which are the consequence of the PHA alkyl side chains length. The biological PHA graft copolymers may offer a diverse array of applications such composite for tissue engineering and biosensor development.

PMID:40216121 | DOI:10.1016/j.ijbiomac.2025.143040

Cancer Cell. 2025 Apr 7:S1535-6108(25)00126-6. doi: 10.1016/j.ccell.2025.03.025. Online ahead of print.

ABSTRACT

Brain metastases (BrMs) remain a major clinical and therapeutic challenge in patients with metastatic cancers. However, advances in our understanding of BrM have been hampered by the constrained sample size and resolution of BrM profiling studies. Here, we perform integrative single-cell RNA sequencing analysis on 108 BrM samples and 111 primary tumor (PTs) samples to investigate the characteristics and remodeling of cell states and composition across cancer lineages and subsets. Recurring and enriched features of malignant cells are increased chromosomal instability, marked proliferative and angiogenic hallmarks, and adoption of a neural-like BrM-associated metaprogram. Immunosuppressive myeloid and stromal subsets dominate the BrM tumor microenvironment, which are associated with poor prognosis and resistance to immunotherapy. Furthermore, five distinct BrM ecotypes are identified, correlating with specific histopathological patterns and clinical characteristics. This work defines hallmarks of BrM biology across cancer types and suggests that shared dependencies may exist, which may be exploited clinically.

PMID:40215980 | DOI:10.1016/j.ccell.2025.03.025

Cancer Cell. 2025 Apr 7:S1535-6108(25)00132-1. doi: 10.1016/j.ccell.2025.03.031. Online ahead of print.

ABSTRACT

Cuproptosis is a recently identified form of copper-dependent cell death. Here, we reveal that radiotherapy (RT) induces cuproptosis in cancer cells, independent of apoptosis and ferroptosis, and depletes lipoylated proteins and iron-sulfur (Fe-S) cluster proteins-both hallmarks of cuproptosis-in patient tumors. Mechanistically, RT elevates mitochondrial copper levels by upregulating copper transporter 1 (CTR1) and depleting mitochondrial glutathione, a copper chelator, thereby triggering cuproptosis. Integrated analyses of RNA sequencing (RNA-seq) from radioresistant esophageal cancer cells and single-cell RNA-seq from esophageal tumors of patients unresponsive to RT link radioresistance to the downregulation of BTB and CNC homology 1 (BACH1). This downregulation de-represses the expression of copper-sequestering metallothionein (MT) 1E/X, thereby mitigating cuproptosis and contributing to radioresistance. Copper ionophore treatment sensitizes radioresistant cancer cells and cell line- and patient-derived xenografts to RT by potentiating cuproptosis. Our findings unveil a link between RT and cuproptosis and inform a therapeutic strategy to overcome tumor radioresistance by targeting cuproptosis.

PMID:40215978 | DOI:10.1016/j.ccell.2025.03.031

Cell Rep Methods. 2025 Apr 7:101022. doi: 10.1016/j.crmeth.2025.101022. Online ahead of print.

ABSTRACT

Understanding the interplay among clinical variables-such as demographics, symptoms, and laboratory results-and their relationships with disease outcomes is critical for advancing diagnostics and understanding mechanisms in complex diseases. Existing methods fail to capture indirect or directional relationships, while existing Bayesian network learning methods are computationally expensive and only infer general associations without focusing on disease outcomes. Here we introduce random walk- and genetic algorithm-based network inference (RAMEN), a method for Bayesian network inference that uses absorbing random walks to prioritize outcome-relevant variables and a genetic algorithm for efficient network refinement. Applied to COVID-19 (Biobanque québécoise de la COVID-19), intensive care unit (ICU) septicemia (MIMIC-III), and COPD (CanCOLD) datasets, RAMEN reconstructs networks linking clinical markers to disease outcomes, such as elevated lactate levels in ICU patients. RAMEN demonstrates advantages in computational efficiency and scalability compared to existing methods. By modeling outcome-specific relationships, RAMEN provides a robust tool for uncovering critical disease mechanisms, advancing diagnostics, and enabling personalized treatment strategies.

PMID:40215965 | DOI:10.1016/j.crmeth.2025.101022

Cell. 2025 Apr 4:S0092-8674(25)00289-2. doi: 10.1016/j.cell.2025.03.016. Online ahead of print.

ABSTRACT

Diverse microbes utilize redox shuttles to exchange electrons with their environment through mediated extracellular electron transfer (EET), supporting anaerobic survival. Although mediated EET has been leveraged for bioelectrocatalysis for decades, fundamental questions remain about how these redox shuttles are reduced within cells and their role in cellular bioenergetics. Here, we integrate genome editing, electrochemistry, and systems biology to investigate the mechanism and bioenergetics of mediated EET in Escherichia coli, elusive for over two decades. In the absence of alternative electron sinks, the redox cycling of 2-hydroxy-1,4-naphthoquinone (HNQ) via the cytoplasmic nitroreductases NfsB and NfsA enables E. coli respiration on an extracellular electrode. E. coli also exhibits rapid genetic adaptation in the outer membrane porin OmpC, enhancing HNQ-mediated EET levels coupled to growth. This work demonstrates that E. coli can grow independently of classic electron transport chains and fermentation, unveiling a potentially widespread new type of anaerobic energy metabolism.

PMID:40215961 | DOI:10.1016/j.cell.2025.03.016

EBioMedicine. 2025 Apr 10;115:105688. doi: 10.1016/j.ebiom.2025.105688. Online ahead of print.

ABSTRACT

BACKGROUND: Endometriosis is a chronic inflammatory condition characterised by pain and infertility. We conducted a prospective study to elucidate the pathophysiological mechanisms underlying endometriosis development.

METHODS: We examined the association between 1305 proteins measured by SomaScan proteomics and risk of endometriosis diagnosis in prospectively collected plasma from 200 laparoscopically-confirmed endometriosis cases and 200 risk-set sampling matched controls within the Nurses' Health Study II (NHSII) cohort. Using conditional logistic regression, we calculated odds ratios (OR) and 95% confidence intervals (CI) per one standard deviation increase in protein levels and area under the curve (AUC) to assess the multi-protein model in discriminating cases from controls. Analytical validation for three proteins was performed using immunoassays. Ingenuity Pathway Analysis and STRING analyses identified biological pathways and protein interactions.

FINDINGS: Blood samples from cases were collected up to 9 years before diagnosis (median = 4 years). Among 61 individual proteins nominally significantly associated with risk of endometriosis diagnosis compared to controls, endometriosis cases had higher plasma levels of S100A9 (OR = 1.52, 95%CI = 1.19-1.94), ICAM2 (OR = 1.47, 95%CI = 1.17-1.85), HIST1H3A (OR = 1.42, 95%CI = 1.31-1.78), TOP1 (OR = 1.95, 95%CI = 1.24-3.06), CD5L (OR = 1.23, 95%CI = 1.00-1.51) and lower levels of IGFBP1 (OR = 0.70, 95%CI = 0.52-0.94). We further evaluated three of the proteins in an independent set of 103 matched case-control pairs within the NHSII cohort. Pathway analyses revealed upregulation of multiple immune-related pathways in blood samples collected years before endometriosis diagnosis.

INTERPRETATION: In this prospective analysis using aptamer-based proteomics, we identified multiple proteins and biological pathways related to innate immune response upregulated years before endometriosis surgical diagnosis, suggesting the role of immune dysregulation in endometriosis development.

FUNDING: This study was supported by the Department of Defence, the 2017 Boston Center for Endometriosis Trainee Award. Investigators were supported by Aspira Women's Health and NIH which were not directly related to this project.

PMID:40215752 | DOI:10.1016/j.ebiom.2025.105688

Phys Rev Lett. 2025 Mar 28;134(12):128401. doi: 10.1103/PhysRevLett.134.128401.

ABSTRACT

The spatial organization of DNA involves DNA loop extrusion and the formation of protein-DNA condensates. While the significance of each process is increasingly recognized, their interplay remains unexplored. Using molecular dynamics simulation and theory we investigate this interplay. Our findings reveal that loop extrusion can enhance the dynamics of condensation and promotes coalescence and ripening of condensates. Further, the DNA loop enables condensate formation under DNA tension and position condensates. The concurrent presence of loop extrusion and condensate formation results in the formation of distinct domains similar to TADs, an outcome not achieved by either process alone.

PMID:40215530 | DOI:10.1103/PhysRevLett.134.128401

Plant Biotechnol J. 2025 Apr 11. doi: 10.1111/pbi.70054. Online ahead of print.

NO ABSTRACT

PMID:40214971 | DOI:10.1111/pbi.70054

Cells. 2025 Apr 4;14(7):548. doi: 10.3390/cells14070548.

ABSTRACT

Extracellular vesicles (EVs) have been explored as promising vehicles for drug delivery. One of the most valuable features of EVs is their ability to cross physiological barriers, particularly the blood-brain barrier (BBB). This significantly enhances the development of EV-based drug delivery systems for the treatment of CNS disorders. The present review focuses on the factors and techniques that contribute to the successful delivery of EV-based therapeutics to the brain. Here, we discuss the major methods of brain targeting which includes the utilization of different administration routes, capitalizing on the biological origins of EVs, and the modification of EVs through the addition of specific ligands on to the surface of EVs. Finally, we discuss the current challenges in large-scale EV production and drug loading while highlighting future perspectives regarding the application of EV-based therapeutics for brain delivery.

PMID:40214500 | DOI:10.3390/cells14070548

Front Bioeng Biotechnol. 2025 Mar 27;13:1527084. doi: 10.3389/fbioe.2025.1527084. eCollection 2025.

ABSTRACT

INTRODUCTION: Genetically enhanced microorganisms have wide applications in different fields and the increasing availability of omics data has enabled the development of genome-scale metabolic models (GEMs), which are essential tools in synthetic biology. Bartonella quintana str. Toulouse, a facultative intracellular parasite, presents a small genome and the ability to grow in axenic culture, making it a potential candidate for genome reduction and synthetic biology applications. This study aims to reconstruct and analyze the metabolic network of B. quintana to optimize its growth conditions for laboratory use.

METHODS: A metabolic reconstruction of B. quintana was performed using genome annotation tools (RAST and ModelSEED), followed by refinement using multiple databases (KEGG, BioCyc, BRENDA). Flux Balance Analysis (FBA) was conducted to optimize biomass production, and in-silico knockouts were performed to evaluate growth yield under different media conditions. Additionally, experimental validation was carried out by testing modified culture media and performing proteomic analyses to identify metabolic adaptations.

RESULTS: FBA simulations identified key metabolic requirements, including 2-oxoglutarate as a crucial compound for optimal growth. In-silico knockouts of transport genes revealed their essentiality in nutrient uptake. Experimental validation confirmed the role of 2-oxoglutarate and other nutrients in improving bacterial growth, though unexpected decreases in viability were observed under certain supplemented conditions. Proteomic analysis highlighted differential expression of proteins associated with cell wall integrity and metabolic regulation.

DISCUSSION: This study represents a step toward developing B. quintana as a viable chassis for synthetic biology applications. The reconstructed metabolic model provides a comprehensive understanding of B. quintana's metabolic capabilities, identifying essential pathways and growth limitations. While metabolic predictions align with experimental results in key aspects, further refinements are needed to enhance model accuracy and optimize growth conditions.

PMID:40213639 | PMC:PMC11983613 | DOI:10.3389/fbioe.2025.1527084

Comput Struct Biotechnol J. 2025 Mar 19;27:1204-1214. doi: 10.1016/j.csbj.2025.03.011. eCollection 2025.

ABSTRACT

Non-invasive force inference based on imaging data has significantly advanced our understanding of the mechanical cues driving morphogenesis. In 2D studies of confluent tissues, these methods allow for the computation of forces acting on cells by analyzing their geometrical features. Here, we present a novel approach for 3D force and energy inference in curved epithelia. Specifically, we focus on tubular epithelia, which form the foundation of many vital organs, including the lungs, kidneys, and vasculature. Our technique analyzes the average mechanical behavior of cells along their apico-basal axis and is based on an optimal parametrization of a vertex model aimed at obtaining effective tissue parameters. We apply our method to in silico data to investigate the mechanical consequences of different 3D cellular packing scenarios. Our results reveal that in squamous epithelia, prismatic cellular shapes are mechanically stable. However, in cubic/columnar tubes, prismatic shapes are incompatible with the adhesion required to maintain tissue integrity. In conclusion, this study indicates that in cubic/columnar epithelia, stability can only be achieved if cells undergo apico-basal intercalations and adopt an alternative shape: the scutoid.

PMID:40213271 | PMC:PMC11982039 | DOI:10.1016/j.csbj.2025.03.011

NPJ Metab Health Dis. 2025;3(1):13. doi: 10.1038/s44324-025-00056-3. Epub 2025 Apr 8.

ABSTRACT

Consumption of ultra-processed foods (UPFs) increases overall caloric intake and is associated with obesity, cardiovascular disease, and brain pathology. There is scant evidence as to why UPF consumption leads to increased caloric intake and whether the negative health consequences are due to adiposity or characteristics of UPFs. Using the UK Biobank sample, we probed the associations between UPF consumption, adiposity, metabolism, and brain structure. Our analysis reveals that high UPF intake is linked to adverse adiposity and metabolic profiles, alongside cellularity changes in feeding-related subcortical brain areas. These are partially mediated by dyslipidemia, systemic inflammation and body mass index, suggesting that UPFs exert effects on the brain beyond just contributing to obesity. This dysregulation of the network of subcortical feeding-related brain structures may create a self-reinforcing cycle of increased UPF consumption.

PMID:40213086 | PMC:PMC11978510 | DOI:10.1038/s44324-025-00056-3

iScience. 2025 Mar 12;28(4):112097. doi: 10.1016/j.isci.2025.112097. eCollection 2025 Apr 18.

ABSTRACT

Innate defensive behaviors are essential for survival, allowing animals to appropriately respond to predatory threats. The anterior hypothalamic nucleus (AHN), a key region in the medial hypothalamic defense system, contains both GABAergic and glutamatergic neurons, reflecting a sophisticated balance between inhibitory and excitatory signaling. However, the specific behavioral functions of these neuronal populations have not been systemically examined. Here, we utilized fiber photometry and optogenetic stimulation to investigate the roles of AHN GABAergic, glutamatergic, and CaMKIIa+ neuronal activities in mediating innate defensive behaviors. Our results indicate that AHN GABAergic neurons mediate anxiety-associated investigatory behaviors, while AHN glutamatergic neurons drive escape and freezing responses. The AHN CaMKIIa+ neurons, which exhibit significant heterogeneity, suggest a more nuanced role, potentially balancing escape and freezing responses. Our study provides a foundation for future investigations into the neural circuits underlying innate defensive behaviors and its dysregulation in neuropsychiatric conditions including PTSD and panic disorder.

PMID:40212593 | PMC:PMC11985144 | DOI:10.1016/j.isci.2025.112097

Front Artif Intell. 2025 Mar 19;8:1528562. doi: 10.3389/frai.2025.1528562. eCollection 2025.

ABSTRACT

INTRODUCTION: The biomedical literature is the go-to source of information regarding relationships between biological entities, including genes, diseases, cell types, and drugs, but the rapid pace of publication makes an exhaustive manual exploration impossible. In order to efficiently explore an up-to-date repository of millions of abstracts, we constructed an efficient and modular natural language processing pipeline and applied it to the entire PubMed abstract corpora.

METHODS: We developed SciLinker using open-source libraries and pre-trained named entity recognition models to identify human genes, diseases, cell types and drugs, normalizing these biological entities to the Unified Medical Language System (UMLS). We implemented a scoring schema to quantify the statistical significance of entity co-occurrences and applied a fine-tuned PubMedBERT model for gene-disease relationship extraction.

RESULTS: We identified and analyzed over 30 million association sentences, including more than 11 million gene-disease co-occurrence sentences, revealing more than 1.25 million unique gene-disease associations. We demonstrate SciLinker's ability to extract specific gene-disease relationships using osteoporosis as a case study. We show how such an analysis benefits target identification as clinically validated targets are enriched in SciLinker-derived disease-associated genes. Moreover, this co-occurrence data can be used to construct disease-specific networks, providing insights into significant relationships among biological entities from scientific literature.

CONCLUSION: SciLinker represents a novel text mining approach that extracts and quantifies associations between biomedical entities through co-occurrence analysis and relationship extraction from PubMed abstracts. Its modular design enables expansion to additional entities and text corpora, making it a versatile tool for transforming unstructured biomedical data into actionable insights for drug discovery.

PMID:40212086 | PMC:PMC11983328 | DOI:10.3389/frai.2025.1528562

Small Sci. 2024 Jul 8;4(9):2400084. doi: 10.1002/smsc.202400084. eCollection 2024 Sep.

ABSTRACT

Mesoporous silica nanoparticles (MSNs) have emerged as promising drug carriers that can facilitate targeted anticancer drug delivery, but efficiency studies relying on active targeting mechanisms remain elusive. This study implements in vitro 3D cocultures, so-called microtissues, to model a physiologically relevant tumor microenvironment (TME) to examine the impact of surface-modified MSNs without targeting ligands on the internalization, cargo delivery, and cargo release in tumor cells and cancer-associated fibroblasts. Among these, acetylated MSNs most effectively localized in tumor cells in a 3D setting containing collagen, while other MSNs did so to a lesser degree, most likely due to remaining trapped in the extracellular matrix of the TME. Confocal imaging of hydrophobic model drug-loaded MSNs demonstrated effective cargo release predominantly in tumor cells, both in 2D and 3D cocultures. MSN-mediated delivery of an anticancer drug in the microtissues exhibited a significant reduction in tumor organoid size and enhanced the tumor-specific cytotoxic effects of a γ-secretase inhibitor, compared to the highly hydrophobic drug in free form. This inherent targeting potential suggests reduced off-target effects and increased drug efficacy, showcasing the promise of surface modification of MSNs as a means of direct cell-specific targeting and delivery for precise and successful targeted drug delivery.

PMID:40212075 | PMC:PMC11935100 | DOI:10.1002/smsc.202400084

Bioessays. 2025 Apr 10:e202400175. doi: 10.1002/bies.202400175. Online ahead of print.

ABSTRACT

The assembly of Cullin3-based RING E3 ubiquitin ligase (CRL3) complexes is orchestrated in two consecutive steps: the formation of the dimeric BTB domain core and the recruitment of CUL3-RBX1 subunits. Each step is tightly regulated to ensure the formation of complete and functional dimeric CRL3s. The first assembly step is regulated by two mechanisms: "co-co assembly" and proteasome-dependent degradation of aberrant heterodimers. The second step is facilitated by a conserved CUL3 N-terminal assembly (NA) motif. The CUL3 NA motif contributes to the assembly of CRL3s in two aspects: interacting with both BTB domain-containing protein protomers to facilitate complete dimeric assembly, and enhancing the stability of CRL3s by overcoming the tensions generated by conformational entropy during ubiquitin transfer. Given that all Cullin proteins contain N-terminal extensions, we postulate that these extensions, similar to the CUL3 NA motif-contributed assembly, play an important role in the functional regulation of CRLs and thus warrant further investigation.

PMID:40211562 | DOI:10.1002/bies.202400175

Thyroid Res. 2025 Apr 11;18(1):15. doi: 10.1186/s13044-025-00230-1.

ABSTRACT

BACKGROUND: Papillary thyroid cancer (PTC) is the most prevalent follicular cell-derived subtype of thyroid cancer. A systems biology approach to PTC can elucidate the mechanism by which molecular components work and interact with one another to decipher a panoramic view of the pathophysiology.

METHODOLOGY: PTC associated genes and transcriptomic data were retrieved from DisGeNET and Gene Expression Omnibus database respectively. Published proteomic and metabolomic datasets in PTC from EMBL-EBI were used. Gene Ontology and pathway analyses were performed with SNPs, differentially expressed genes (DEGs), proteins, and metabolites linked to PTC. The effect of a nucleotide substitution on a protein's function was investigated. Additionally, significant transcription factors (TFs) and kinases were identified. An integrated strategy was used to analyse the multi-omics data to determine the key deregulated pathways in PTC carcinogenesis.

RESULTS: Pathways linked to carbohydrate, protein, and lipid metabolism, along with the immune response, signaling, apoptosis, gene expression, epithelial-mesenchymal transition (EMT), and disease onset, were identified as significant for the clinical and functional aspects of PTC. Glyoxylate and dicarboxylate metabolism and citrate cycle were the most common pathways among the PTC omics datasets. Commonality analysis deciphered five TFs and fifty-seven kinases crucial for PTC genesis and progression. Core deregulated pathways, TFs, and kinases modulate critical biological processes like proliferation, angiogenesis, immune infiltration, invasion, autophagy, EMT, and metastasis in PTC.

CONCLUSION: Identified dysregulated pathways, TFs and kinases are critical in PTC and may help in systems level understanding and device specific experiments, biomarkers, and drug targets for better management of PTC.

PMID:40211357 | DOI:10.1186/s13044-025-00230-1

J Transl Med. 2025 Apr 10;23(1):425. doi: 10.1186/s12967-025-06446-x.

ABSTRACT

Systems biology is a holistic approach to biological sciences that combines experimental and computational strategies, aimed at integrating information from different scales of biological processes to unravel pathophysiological mechanisms and behaviours. In this scenario, high-throughput technologies have been playing a major role in providing huge amounts of omics data, whose integration would offer unprecedented possibilities in gaining insights on diseases and identifying potential biomarkers. In the present review, we focus on strategies that have been applied in literature to integrate genomics, transcriptomics, proteomics, and metabolomics in the year range 2018-2024. Integration approaches were divided into three main categories: statistical-based approaches, multivariate methods, and machine learning/artificial intelligence techniques. Among them, statistical approaches (mainly based on correlation) were the ones with a slightly higher prevalence, followed by multivariate approaches, and machine learning techniques. Integrating multiple biological layers has shown great potential in uncovering molecular mechanisms, identifying putative biomarkers, and aid classification, most of the time resulting in better performances when compared to single omics analyses. However, significant challenges remain. The high-throughput nature of omics platforms introduces issues such as variable data quality, missing values, collinearity, and dimensionality. These challenges further increase when combining multiple omics datasets, as the complexity and heterogeneity of the data increase with integration. We report different strategies that have been found in literature to cope with these challenges, but some open issues still remain and should be addressed to disclose the full potential of omics integration.

PMID:40211300 | DOI:10.1186/s12967-025-06446-x

BMC Genomics. 2025 Apr 10;26(1):359. doi: 10.1186/s12864-025-11545-6.

ABSTRACT

BACKGROUND: This study assessed the long-term metabolic effects of prenatal nutrition in Nelore bulls through an integrated analysis of metabolome and microbiome data to elucidate the interconnected host-microbe metabolic pathways. To this end, a total of 126 cows were assigned to three supplementation strategies during pregnancy: NP (control)- only mineral supplementation; PP- protein-energy supplementation during the last trimester; and FP- protein-energy supplementation throughout pregnancy. At the end of the finishing phase, blood, fecal, and ruminal fluid samples were collected from 63 male offspring. The plasma underwent targeted metabolomics analysis, and fecal and ruminal fluid samples were used to perform 16 S rRNA gene sequencing. Metabolite and ASV (amplicon sequence variant) co-abundance networks were constructed for each treatment using the weighted gene correlation network analysis (WGCNA) framework. Significant modules (p ≤ 0.1) were selected for over-representation analyses to assess the metabolic pathways underlying the metabolome (MetaboAnalyst 6.0) and the microbiome (MicrobiomeProfiler). To explore the metabolome-metagenome interplay, correlation analyses between host metabolome and microbiome were performed. Additionally, a holistic integration of metabolic pathways was performed (MicrobiomeAnalyst 2.0).

RESULTS: A total of one and two metabolite modules associated with the NP and FP were identified, respectively. Regarding fecal microbiome, three, one, and two modules for the NP, PP, and FP were identified, respectively. The rumen microbiome demonstrated two modules correlated with each of the groups under study. Metabolite and microbiome enrichment analyses revealed the main metabolic pathways associated with lipid and protein metabolism, and regulatory mechanisms. The correlation analyses performed between the host metabolome and fecal ASVs revealed 13 and 12 significant correlations for NP and FP, respectively. Regarding the rumen, 16 and 17 significant correlations were found for NP and FP, respectively. The NP holistic analysis was mainly associated with amino acid and methane metabolism. Glycerophospholipid and polyunsaturated fatty acid metabolism were over-represented in the FP group.

CONCLUSIONS: Prenatal nutrition significantly affected the plasma metabolome, fecal microbiome, and ruminal fluid microbiome of Nelore bulls, providing insights into key pathways in protein, lipid, and methane metabolism. These findings offer novel discoveries about the molecular mechanisms underlying the effects of prenatal nutrition.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:40211121 | DOI:10.1186/s12864-025-11545-6