Mol Cell Proteomics. 2025 Jul 22:101038. doi: 10.1016/j.mcpro.2025.101038. Online ahead of print.

ABSTRACT

African swine fever virus (ASFV) causes a lethal disease in pigs and represents a significant threat to the global pork industry due to the lack of effective vaccines or treatments. Despite intensive research, many ASFV proteins remain uncharacterized. This study aimed to elucidate the functions of two ASFV proteins, pMGF360-21R and pA151R, through comprehensive analysis of their interactions with host proteins. Using affinity purification-mass spectrometry and yeast two-hybrid screening approaches, we identified the host protein barrier-to-autointegration factor 1 (BANF1) as a key interactor of both viral proteins. Biochemical and colocalization assays confirmed these interactions and demonstrated that MGF360-21R and A151R expression leads to cytoplasmic relocation of BANF1. Functionally, BANF1 silencing significantly reduced ASFV replication, indicating its proviral role. Given BANF1's established function in regulating the cGAS/STING-dependent type I interferon (IFN-I) response, we postulated that A151R and MGF360-21R could inhibit this pathway. Using different strategies, we showed that both A151R and MGF360-21R did indeed inhibit IFN-I induction. Generation of ASFV deficient of A151R or MGF360-21R showed that both mutant viruses enhanced the host IFN response in primary porcine macrophages compared to wild-type virus. However, their capacity to inhibit this pathway could occur through mechanisms independent of BANF1. Proteomic analysis of BANF1 interactors during ASFV infection highlighted potentially roles in chromatin remodeling, nuclear transport, and innate immune response pathways. Altogether, our data provide new insights into ASFV-host interactions, identifying BANF1 as an important new host factor required for replication and uncovering novel functions for A151R and MGF360-21R.

PMID:40707000 | DOI:10.1016/j.mcpro.2025.101038

Toxicol Lett. 2025 Jul 22:S0378-4274(25)01552-8. doi: 10.1016/j.toxlet.2025.07.1415. Online ahead of print.

ABSTRACT

Endosulfan, an organochlorine pesticide, is implicated in human cardiovascular diseases. Protein-tyrosine phosphatase 4A3 (PTP4A3) has been identified to play a critical role in endothelial cell migration when exposure to endosulfan. In the present study, we aim to explore the epigenetic mechanism by which endosulfan upregulates PTP4A3 expression to enhance cell migration in human umbilical vein endothelial cells (HUVECs). Bioinformatics analysis showed that there were complementary sequences in the 3'-UTR of PTP4A3 and lncRNA KCNQ1OT1 to the seed regions of miR-140-5p. Dual luciferase reporter assay confirmed that miR-140-5p had potential binding capacity to PTP4A3 and KCNQ1OT1. Endosulfan upregulated PTP4A3 and KCNQ1OT1, but downregulated miR-140-5p expression, promoting cell migration through the activation of MAPK/ERK and PI3K/AKT pathways in HUVECs, which were inhibited by miR-140-5p overexpression or KCNQ1OT1 silencing Anti-Ago2 RNA immunoprecipitation experiments confirmed the binding interaction between miR-140-5p and KCNQ1OT1. Transfection of miR-140-5p mimics downregulated PTP4A3 and KCNQ1OT1, while si-KCNQ1OT1 downregulated PTP4A3 and upregulated miR-140-5p in HUVECs. Either miR-140-5p mimic or si-KCNQ1OT1 attenuated cell migration and influenced MAPK/ERK and PI3K/AKT signaling pathways in HUVECs, which were counteracted by co-transfection with pEGFP-PTP4A3 or anti-miR-140-5p. We observed the upregulation of PTP4A3 and KCNQ1OT1, as well as the downregulation of miR-140-5p in the aorta of the ApoE-/- atherosclerotic mice. These findings suggest the involvement of KCNQ1OT1/miR-140-5p/PTP4A3 axis in endosulfan-induced cell migration, providing new insights into the epigenetic mechanisms of endothelial dysfunction in cardiovascular diseases when exposure to endosulfan.

PMID:40706910 | DOI:10.1016/j.toxlet.2025.07.1415

Adv Drug Deliv Rev. 2025 Jul 22:115658. doi: 10.1016/j.addr.2025.115658. Online ahead of print.

ABSTRACT

Carbon-based nanomaterials (CBMs) and their polymeric composites have garnered widespread interest in treating neurotrauma and neurodegenerative diseases, where restoring damaged central and peripheral nervous systems remains a persistent clinical challenge. These materials provide exceptional electrical conductivity, mechanical robustness, and tunable nanoscale architectures conducive to guiding neuronal growth, synaptic connectivity, and targeted biomolecule delivery. In this review, we explore the rationale, recent advances, and translational potential of CBM scaffolds in promoting neuronal survival, neurite outgrowth, and functional maturity across various experimental models. We detail key fabrication strategies, including electrospinning, phase inversion, 3D bioprinting, and pyrolysis that enable precise control over scaffolds' structural and mechanical properties while facilitating the incorporation of neurotrophic factors, genes, and therapeutic drugs. Emerging in vivo findings suggest that CBM nanocomposites promote regenerative outcomes in peripheral nerve injuries at levels comparable to, or exceeding conventional autografts, underscoring their promise as off-the-shelf solutions. Nonetheless, concerns persist regarding large-scale manufacturing, cytotoxicity, and meeting regulatory standards for clinical use. By highlighting cutting-edge innovations and remaining bottlenecks, this review aims to guide future research endeavors in harnessing CBM scaffolds for safe and effective neural tissue repair.

PMID:40706866 | DOI:10.1016/j.addr.2025.115658

Bioresour Technol. 2025 Jul 22:133030. doi: 10.1016/j.biortech.2025.133030. Online ahead of print.

ABSTRACT

Free fatty acids (FFA) serve as versatile precursors for biofuels and oleochemicals, and their microbial production offers a renewable alternative to petrochemical processes. Escherichia coli has been extensively engineered for high-titer FFA production and currently serves as the benchmark chassis, achieving titers exceeding 35 g L-1 through advanced metabolic and systems biology approaches. In contrast, Pseudomonas putida KT2440 has recently gained attention due to its innate stress tolerance, redox flexibility, and broad substrate utilization, though reported FFA titers remain modest (∼0.67 g L-1). P. putida KT2440 exhibits innate tolerance to FFA toxicity, attributed to its surplus NADPH supply and robust membrane composition. This review provides a side-by-side comparison of the two hosts with respect to fatty acid biosynthetic pathways, redox metabolism, native tolerance mechanisms, and substrate scope. We summarize key metabolic engineering strategies used to enhance FFA production and examine recent advances in genetic toolkits and regulatory rewiring that have accelerated strain development in both organisms. While E. coli remains the leading host in terms of performance, P. putida offers distinct advantages for next-generation biomanufacturing. This comparative review outlines the key opportunities and challenges in FFA biosynthesis and offers a framework to guide future strain engineering for sustainable production.

PMID:40706765 | DOI:10.1016/j.biortech.2025.133030

J Microbiol Methods. 2025 Jul 22:107201. doi: 10.1016/j.mimet.2025.107201. Online ahead of print.

ABSTRACT

Nitrification inhibitors are valuable in mitigating nitrogen (N) losses from agricultural fertilizers, enhancing fertilizer use efficiency, and minimizing their environmental and climatic impacts. Currently, the portfolio of approved inhibitors is limited, creating a strong demand for new alternatives. Traditional nitrification inhibition assays rely on large soil systems, batch cultures, or, at best, microbial cultures in deep-well 96-well plates, none of which are suited for high-throughput screening. Here, we present a highly robust method that enables rapid and efficient screening of thousands of molecules on the soil-borne ammonia-oxidizing bacteria Nitrosomonas europaea and Nitrosospira multiformis. Our assay utilizes 384-well plates for both screening and read-out, requiring only 50 μl of culture per sample and low amounts of compound. The assay also allows for further characterization of nitrification inhibitors and differentiation between those targeting the ammonia monooxygenase (AMO) and hydroxylamine oxidoreductase (HAO) pathways. Finally, we applied the assay to test several oxazolidine variants and discovered goitrin as a novel biological nitrification inhibitor (BNI). Overall, this assay offers promising tools for the rapid identification of novel nitrification inhibitors, contributing to sustainable agriculture.

PMID:40706639 | DOI:10.1016/j.mimet.2025.107201

Nucleic Acids Res. 2025 Jul 19;53(14):gkaf670. doi: 10.1093/nar/gkaf670.

ABSTRACT

The 3D organization of the genome-in particular, which two regions of DNA are in contact with each other-plays a role in regulating gene expression. Several factors influence genome 3D organization. Nucleosomes (where ∼100 base pairs of DNA wrap around histone proteins) bend, twist, and compactify chromosomal DNA, altering its polymer mechanics. How much does the positioning of nucleosomes between gene loci influence contacts between those gene loci? And to what extent are polymer mechanics responsible for this? To address this question, we combine a stochastic polymer mechanics model of chromosomal DNA including twists and wrapping induced by nucleosomes with two data-driven pipelines. The first estimates nucleosome positioning from ATAC-seq data in regions of high accessibility. Most of the genome is low accessibility, so we combine this with a novel image analysis method that estimates the distribution of nucleosome spacing from electron microscopy data. There are no fit parameters in the biophysical model. We apply this method to IL-6, IL-15, CXCL9, and CXCL10, inflammatory marker genes in macrophages, before and after inflammatory stimulation, and compare the predictions with contacts measured by conformation capture experiments (4C-seq). We find that within a 500-kb genomic region, polymer mechanics with nucleosomes can explain 71% of close contacts. These results suggest that, while genome contacts on 100 kb scales are multifactorial, they may be amenable to mechanistic, physical explanation. Our work also highlights the role of nucleosomes, not just at the loci of interest, but between them, and not just the total number of nucleosomes, but their specific placement. The method generalizes to other genes, and can be used to address whether a contact is under active regulation by the cell (e.g. a macrophage during inflammatory stimulation).

PMID:40705928 | DOI:10.1093/nar/gkaf670

Science. 2025 Jul 24:eadx3800. doi: 10.1126/science.adx3800. Online ahead of print.

ABSTRACT

Charting the spatiotemporal dynamics of cell fate determination in development and disease is a long-standing objective in biology. Here we present the design, development, and extensive validation of PEtracer, a prime editing-based, evolving lineage tracing technology compatible with both single-cell sequencing and multimodal imaging methodologies to jointly profile cell state and lineage in dissociated cells or while preserving cellular context in tissues with high spatial resolution. Using PEtracer coupled with MERFISH spatial transcriptomic profiling in a syngeneic mouse model of tumor metastasis, we reconstruct the growth of individually-seeded tumors in vivo and uncover distinct modules of cell-intrinsic and cell-extrinsic factors that coordinate tumor growth. More generally, PEtracer enables systematic characterization of cell state and lineage relationships in intact tissues over biologically-relevant temporal and spatial scales.

PMID:40705858 | DOI:10.1126/science.adx3800

PLoS Pathog. 2025 Jul 24;21(7):e1013341. doi: 10.1371/journal.ppat.1013341. Online ahead of print.

ABSTRACT

Glycoproteins in the viral envelope of human cytomegalovirus (HCMV) orchestrate virion tethering, receptor recognition and fusion with cellular membranes. The glycoprotein gB acts as fusion protein. The gHgL complexes gHgLgO and gHgLpUL(128,130,131A) define the HCMV cell tropism. Studies with HCMV lacking gO had indicated that gHgLgO, independently of binding to its cellular receptor PDGFRα plays an important second role in infection. Here, we identified a gO mutation which abolished virus particle infectivity by preventing the interaction of gHgLgO with host cell heparan sulfate proteoglycans (HSPGs). We could not only show that gHgLgO - HSPG interactions are a genuine second role of gHgLgO, but also that gHgLgO is a main player in determining the infectivity of HCMV virus particles. This challenges long-accepted textbook knowledge on the role of gB and gMgN complexes in virion tethering. Additionally, it adds the gHgLgO complex to the antigens of interest for future HCMV vaccines or treatments.

PMID:40705828 | DOI:10.1371/journal.ppat.1013341

STAR Protoc. 2025 Jul 22;6(3):103968. doi: 10.1016/j.xpro.2025.103968. Online ahead of print.

ABSTRACT

Intrinsically disordered regions (IDRs) of proteins leverage their structural flexibility to play important roles in numerous cellular processes including molecular recognition. Many IDRs interact with DNA, and characterizing these interactions is crucial for understanding their biological impact. Here, we present a protocol for the in vitro detection of IDR-DNA interactions using an electrophoretic mobility shift assay. We describe a radioactive-free procedure using long DNA substrates and define steps for data analysis. Altogether, this protocol facilitates reproducible and sensitive quantification of IDR-DNA interactions. For complete details on the use and execution of this protocol, please refer to Pastic et al.1.

PMID:40705594 | DOI:10.1016/j.xpro.2025.103968

Biometrics. 2025 Jul 3;81(3):ujaf089. doi: 10.1093/biomtc/ujaf089.

ABSTRACT

Directed acyclic graphical models with additive noises are essential in nonlinear causal discovery and have numerous applications in various domains, such as social science and systems biology. Most such models further assume that structural causal functions are additive to ensure causal identifiability and computational feasibility, which may be too restrictive in the presence of causal interactions. Some methods consider general nonlinear causal functions represented by, for example, Gaussian processes and neural networks, to accommodate interactions. However, they are either computationally intensive or lack interpretability. We propose a highly interpretable and computationally feasible approach using trees to incorporate interactions in nonlinear causal discovery, termed tree-based additive noise models. The nature of the tree construction leads to piecewise constant causal functions, making existing causal identifiability results of additive noise models with continuous and smooth causal functions inapplicable. Therefore, we provide new conditions under which the proposed model is identifiable. We develop a recursive algorithm for source node identification and a score-based ordering search algorithm. Through extensive simulations, we demonstrate the utility of the proposed model and algorithms benchmarking against existing additive noise models, especially when there are strong causal interactions. Our method is applied to infer a protein-protein interaction network for breast cancer, where proteins may form protein complexes to perform their functions.

PMID:40705488 | DOI:10.1093/biomtc/ujaf089

Proc Natl Acad Sci U S A. 2025 Jul 29;122(30):e2505704122. doi: 10.1073/pnas.2505704122. Epub 2025 Jul 24.

ABSTRACT

While somatic variants are well-characterized drivers of tumor evolution, their influence on cellular fitness in nonmalignant contexts remains understudied. We identified a mosaic synonymous variant (m.7076A > G) in the mitochondrial DNA (mtDNA)-encoded cytochrome c-oxidase subunit 1 (MT-CO1, p.Gly391=), present at homoplasmy in 47% of immune cells from a healthy donor. Single-cell multiomics revealed strong, lineage-specific selection against the m.7076G allele in CD8+ effector memory T cells, but not other T cell subsets, mirroring patterns of purifying selection of pathogenic mtDNA alleles. The limited anticodon diversity of mitochondrial tRNAs forces m.7076G translation to rely on wobble pairing, unlike the Watson-Crick-Franklin pairing used for m.7076A. Mitochondrial ribosome profiling confirmed stalled translation of the m.7076G allele. Functional analyses demonstrated that the elevated translational and metabolic demands of short-lived effector T cells (SLECs) amplify dependence on MT-CO1, driving this selective pressure. These findings suggest that synonymous variants can alter codon syntax, impacting mitochondrial physiology in a cell type-specific manner.

PMID:40705423 | DOI:10.1073/pnas.2505704122

Probiotics Antimicrob Proteins. 2025 Jul 24. doi: 10.1007/s12602-025-10634-y. Online ahead of print.

ABSTRACT

Saccharomyces cerevisiae var. boulardii (Sb) is a S. cerevisiae (Sc) strain that has been widely used in the treatment of gastrointestinal diseases due to its unique probiotic properties. The key genomic differences that distinguish Sb from Sc include the tetrasomy of chromosome XII, the absence of intact transposon-yeast (Ty) elements, and variations in the copy number of specific genes. These genomic variations may contribute to enhanced thermotolerance, increased acid resistance, and elevated acetate production, collectively supporting its probiotic functions. The probiotic mechanisms of Sb are mediated through luminal actions, mucosal actions, and trophic effects. Its luminal activity involves neutralizing pathogen toxins via the secretion of proteins and inhibiting pathogen growth through the production of short-chain fatty acids (SCFAs). Additionally, Sb modulates gut microbiota composition by fostering symbiotic relationships, thereby increasing the abundance of beneficial microbes and SCFA levels to promote gut health. The mucosal action of Sb promotes anti-inflammatory responses by regulating the nuclear factor kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) pathways. Meanwhile, its trophic effects, driven by polyamine production, enhance the function of intestinal epithelial cells. Recent findings further suggest that Sb may serve as a potential adjuvant therapy for brain disorders by modulating the gut-brain axis (GBA) to attenuate neuroinflammation. With continued multidisciplinary research, Sb is well-positioned to advance the biotherapeutic landscape. This review aims to synthesize recent advances in the genetics and probiotic mechanisms of Sb, with particular emphasis on its modulatory effects on the GBA.

PMID:40705231 | DOI:10.1007/s12602-025-10634-y

Acc Chem Res. 2025 Jul 24. doi: 10.1021/acs.accounts.5c00225. Online ahead of print.

ABSTRACT

ConspectusSmall molecules that induce proximity between proteins have transformed our ability to manipulate and study cellular processes. Beyond this, proximity-inducing small molecules and biologics are now a clinical reality with increasing reach over different targets and disease indications, benefiting from our rapidly expanding abilities to exploit diverse biochemical mechanisms and being powered by emerging design principles. Targeted protein degradation has become a predominant proximity-dependent therapeutic mechanism. We contend that there are many yet-unexplored pharmacologically useful mechanisms that can be triggered by chemically induced protein interactions. We discuss the general principles of proximity pharmacology and highlight two areas we believe are ripe for innovation.

PMID:40705033 | DOI:10.1021/acs.accounts.5c00225

Microbiol Spectr. 2025 Jul 24:e0044225. doi: 10.1128/spectrum.00442-25. Online ahead of print.

ABSTRACT

Coccidioidomycosis, or Valley fever, is an emerging respiratory disease caused by soil-dwelling fungi of the Coccidioides genus that is expected to spread from the southwest into the central U.S. by 2050. While 60% of infections are asymptomatic, the other 40% of patients experience a range of symptoms, from self-limiting pneumonia to life-threatening disseminated disease. The immunological events that underlie the progression to severe disease remain underdefined. Here, we probed the early immune response to Coccidioides using a high dose of an attenuated strain of Coccidioides posadasii in a mouse model of infection coupled with single-cell RNA sequencing. At 24 h post-infection, robust immune infiltration is detected in the lung, marked by high levels of inflammatory PD-L1+ neutrophils and fungal-contact-dependent pro-fibrotic Spp1+ macrophages. These findings elucidate the early dynamics of the host response to Coccidioides and provide a deeper understanding of host-pathogen interactions in the lung.IMPORTANCEBy examining early immune dynamics in the lungs, we uncover critical insights into how myeloid cells, particularly neutrophils and macrophages, are recruited and differentiated during Coccidioides infection. The discovery of specific immune cell subsets, such as PD-L1+ neutrophils and Spp1+ macrophages, which are associated with inflammation and fibrosis, highlights potential targets for therapeutic intervention. These findings provide a deeper understanding of the host-pathogen interactions that occur during Coccidioides infection, offering valuable directions for developing more effective treatments and preventive strategies against this increasingly prevalent disease.

PMID:40704794 | DOI:10.1128/spectrum.00442-25

mBio. 2025 Jul 24:e0141125. doi: 10.1128/mbio.01411-25. Online ahead of print.

ABSTRACT

Microbial communities are often studied by measuring gene expression (mRNA levels), but translating these data into functional insights is challenging because mRNA abundance does not always predict protein levels. Here, we present a strategy to bridge this gap by deriving gene-specific RNA-to-protein conversion factors that improve the prediction of protein abundance from transcriptomic data. Using paired mRNA-protein data sets from seven bacteria and one archaeon, we identified orthologous genes where mRNA levels poorly predicted protein abundance, yet each gene's protein-to-RNA ratio was consistent across these diverse organisms. Applying the resulting conversion factors to mRNA levels dramatically improved protein abundance predictions, even when the conversion factors were obtained from distantly related species. Remarkably, conversion factors derived from bacteria also enhanced protein prediction in an archaeon, demonstrating the robustness of this approach. This cross-domain framework enables more accurate functional inference in microbiomes without requiring organism-specific proteomic data, offering a powerful new tool for microbial ecology, systems biology, and functional genomics.

IMPORTANCE: Deciphering the biology of natural microbial communities is limited by the lack of functional data. While transcriptomics enables gene expression profiling, mRNA levels often fail to predict protein abundance, the primary indicator of microbial function. Prior studies addressed this by calculating RNA-to-protein (RTP) conversion factors using conserved protein-to-RNA (ptr) ratios across bacterial strains, but their cross-species and cross-domain utility remained unknown. We generated comprehensive transcriptomic and proteomic data sets from seven bacteria and one archaeon spanning diverse metabolisms and ecological niches. We identified orthologous genes with conserved ptr ratios, enabling the discovery of RTP conversion factors that significantly improved protein prediction from mRNA, even between distant species and domains. This reveals previously unrecognized conservation in ptr ratios across domains and eliminates the need for paired proteomic data in many cases. Our approach offers a broadly applicable framework to enhance functional prediction in microbiomes using only transcriptomic data.

PMID:40704792 | DOI:10.1128/mbio.01411-25

Clin Transplant. 2025 Aug;39(8):e70225. doi: 10.1111/ctr.70225.

NO ABSTRACT

PMID:40704553 | DOI:10.1111/ctr.70225

JHEP Rep. 2025 May 30;7(8):101465. doi: 10.1016/j.jhepr.2025.101465. eCollection 2025 Aug.

ABSTRACT

BACKGROUND & AIMS: Liver regeneration is essential for recovery following injury, but this process can be impaired by factors such as sex, age, metabolic disorders, fibrosis, and immunosuppressive therapies. We aimed to identify key transcriptomic, proteomic, and serum biomarkers of regeneration in mouse models under these diverse conditions using systems biology and machine learning approaches.

METHODS: Six mouse models, each undergoing 75% hepatectomy, were used to study regeneration across distinct clinical contexts: young males and females, aged mice, stage 2 fibrosis, steatosis, and tacrolimus exposure. A novel contrastive deep learning framework with triplet loss was developed to map regenerative trajectories and identify genes associated with regenerative efficiency.

RESULTS: Despite achieving ≥75% liver mass restoration by day 7, regeneration was significantly delayed in aged, steatotic, and fibrotic models, as indicated by reduced Ki-67 staining on day 2 (p <0.0001 for all). Interestingly, fibrotic livers exhibited reduced collagen deposition and partial regression to stage 1 fibrosis post-hepatectomy. Transcriptomic and proteomic analyses revealed consistent downregulation of cell cycle genes in impaired regeneration. The deep learning model integrating clinical and transcriptomic data predicted regenerative outcomes with 87.9% accuracy. SHAP (SHapley Additive exPlanations) highlighted six key predictive genes: Wee1, Rbl1, Gnl3, Mdm2, Cdk2, and Ccne2. Proteomic validation and human SPLiT-seq (split-pool ligation-based transcriptome sequencing) data further supported their relevance across species.

CONCLUSIONS: This study identifies conserved cell cycle regulators underlying efficient liver regeneration and provides a predictive framework for evaluating regenerative capacity. The integration of deep learning and multi-omics profiling provides a promising approach to better understand liver regeneration and may help guide therapeutic strategies, especially in complex clinical settings.

IMPACT AND IMPLICATIONS: The aim of this study was to identify key transcriptomic, proteomic, and serum biomarkers of regeneration in mouse models under diverse conditions, using systems biology and machine learning approaches. Key molecular drivers of liver regeneration across diverse clinical conditions were identified using innovative deep learning and multi-omics approaches. By identifying conserved cell cycle genes predictive of regenerative outcomes, this study offers a powerful framework to assess and potentially enhance liver recovery in older patients, those with fibrosis or steatosis, and/or those under immunosuppression.

PMID:40704068 | PMC:PMC12284365 | DOI:10.1016/j.jhepr.2025.101465

Regen Ther. 2025 Jul 17;30:403-414. doi: 10.1016/j.reth.2025.07.001. eCollection 2025 Dec.

ABSTRACT

Stem-cell derived therapies are an essential pillar in the field of regenerative medicine, utilising stem cell self-renewal and multipotent or pluripotent differentiation capabilities to give rise to functional, specialised cells to repair and restore tissue function. Haematopoietic cell therapies have been pivotal to the development of the regenerative medicine field and continue to hold significant promise enabled by recent technical innovation in cell culture approaches that have expanded their therapeutic potential. The development of novel cell culture protocols that allow for the standardised ex vivo expansion of haematopoietic stem cells (HSCs) has facilitated the exploration of umbilical cord blood allogeneic HSC transplantation. Directed differentiation protocols of HSCs, embryonic stem cells and induced pluripotent stem cells, to selectively produce a desired haematopoietic cell type in a donor-independent manner, has broadened the scope for haematopoietic cell-based regenerative therapy. Furthermore, the integration of genome modification or gene editing with these protocols have allowed for corrective autologous HSC transplantation as well as the ability to confer haematopoietic cells with enhanced or novel therapeutic functions. Despite this, realising large-scale clinical translation remains challenging. Current efforts aim to move towards chemically defined culture systems, improving the efficiency and reproducibility of lineage-specific differentiation with an emphasis on compatibility with genome modification and gene-editing protocols for the scalable production of high-quality, efficacious and safe cellular therapies. In this review, we summarise the key milestones and technical advancements in the field in addition to the outstanding questions to be addressed.

PMID:40704043 | PMC:PMC12284713 | DOI:10.1016/j.reth.2025.07.001

Front Vet Sci. 2025 Jul 9;12:1635202. doi: 10.3389/fvets.2025.1635202. eCollection 2025.

ABSTRACT

Hair follicle development and cycling are governed by intricate genetic and molecular networks, with microRNAs (miRNAs) playing essential roles as post-transcriptional regulators. In cashmere goats, valued for their fine fiber, miRNAs have emerged as key modulators influencing hair follicle morphogenesis, regeneration, and fiber traits such as fineness and pigmentation. This review highlights recent discoveries in miRNA-mediated regulation of hair follicles, focusing on their dynamic expression patterns and cell-specific functions in keratinocytes, dermal papilla cells, and follicular stem cells. Key miRNAs, including miR-31, miR-22, and miR-214, are explored for their effects on follicle growth, hair shaft formation, and pigment regulation. We discuss advances in single-cell RNA sequencing and spatial transcriptomics, revealing new insights into cellular heterogeneity and lineage specification. Integrative multi-omics approaches, combining transcriptomics, proteomics, and epigenomics uncover complex regulatory networks in which miRNAs interact with other non-coding RNAs and signaling pathways. Artificial Intelligence (AI) -driven analytics enhance the discovery of biomarkers and therapeutic targets, offering precision strategies for clinical and livestock applications. miRNA profiling now informs breeding strategies to improve cashmere fiber quality and is a minimally invasive diagnostic tool for hair disorders. We outline future directions, including improved miRNA delivery methods, systems biology integration, and AI-powered multi-omics approaches to deepen our understanding of hair follicle biology and facilitate practical applications in medicine and agriculture.

PMID:40703926 | PMC:PMC12283300 | DOI:10.3389/fvets.2025.1635202

Front Cell Infect Microbiol. 2025 Jul 9;15:1554760. doi: 10.3389/fcimb.2025.1554760. eCollection 2025.

ABSTRACT

INTRODUCTION: Viruses exploit host kinases to phosphorylate their proteins, enabling viral replication and interference with host-cell functions. Understanding phosphorylation in SARS-CoV-2 proteins necessitates identifying viral phosphoproteins, their phosphosites, and the host kinase-viral protein interactions critical for evading host antiviral responses.

METHODS: Employing the protein kinase substrate sequence-preference motifs derived by Poll B G. et. al., 2024, we performed kinase-substrate phosphomotif pattern analysis on the SARS-CoV-2 proteome. We identified major host kinases by analyzing SARS-CoV-2 perturbed phosphoproteomes from various studies and cell systems. These kinases were subjected to interactome analysis and literature-based validation for the impact of kinase inhibitors on infection. Further, conservation of viral phosphosites across SARS CoV-2 variants were also assessed.

RESULTS: The human kinome-substrate phosphomotif analysis predicted 49 kinases capable of phosphorylating 639 phosphosites across 33 SARS-CoV-2 proteins. From these, 24 kinases were also perturbed in SARS-CoV-2-infected phosphoproteomes. Literature review identified seven kinases, including MAP2K1, whose inhibition may reduce viral replication. MAP2K1 was found to target key viral phosphosites, including N protein (S206, T198) and ORF9b (S50), conserved across SARS-CoV-2 variants. Docking analysis showed MAP2K1 forms stronger, closer interactions with N protein compared to SRPK1, highlighting MAP2K1 as a potential host kinase for therapeutic targeting in SARS-CoV-2 infection.

DISCUSSION AND CONCLUSIONS: This study presents a framework for predicting human kinases of specific SARS-CoV-2 protein phosphosites by integrating kinase specificity, virus-host interactions, and post-translational modifications. MAP2K1 was identified as a key host kinase, showing stronger interactions than SRPK1, and is proposed as an antiviral drug target for repurposing in SARS-CoV-2 infections.

PMID:40703672 | PMC:PMC12283625 | DOI:10.3389/fcimb.2025.1554760