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

Front Cell Infect Microbiol. 2025 Jul 9;15:1539240. doi: 10.3389/fcimb.2025.1539240. eCollection 2025.

ABSTRACT

Tuberculosis (TB) remains a major global health threat, with the urgent need for rapid and accurate diagnostic methods to improve control and treatment outcomes. This study evaluates the performance of MassARRAY technology for detecting Mycobacterium tuberculosis (MTB) and identifying drug resistance, compared to traditional culture methods and Xpert MTB/RIF. From July 2021 to February 2024, bronchoalveolar lavage fluid (BALF) samples from 289 suspected pulmonary tuberculosis patients at Henan Provincial Chest Hospital, China, were tested using MassARRAY, Xpert MTB/RIF, and conventional culturing techniques. The performance of each method was assessed for MTB detection, and the ability of MassARRAY to identify drug resistance was compared with standard drug susceptibility testing (DST). MassARRAY demonstrated a sensitivity of 96.5% and a specificity of 34.6% for MTB detection, outperforming the Xpert MTB/RIF assay in sensitivity (94.7%) but showing lower specificity. In detecting rifampicin resistance, MassARRAY achieved concordance rates of 83.93% with Xpert MTB/RIF and 72.73% with DST. Furthermore, MassARRAY successfully identified key genetic mutations associated with drug resistance, such as rpoB 531 for rifampicin and katG 315 for isoniazid. MassARRAY demonstrated high concordance with DST for several drugs, including isoniazid, kanamycin, and streptomycin, but exhibited limitations in detecting resistance to pyrazinamide, clofazimine, cycloserine, and linezolid. Overall, MassARRAY provides a rapid, cost-effective, and high-throughput diagnostic platform for MTB and drug resistance, particularly for first-line anti-tuberculosis drugs. While limitations in specificity and resistance detection for certain second-line drugs exist, its ability to rapidly provide comprehensive resistance profiles makes it a valuable tool for TB management.

PMID:40703669 | PMC:PMC12283603 | DOI:10.3389/fcimb.2025.1539240

Evol Appl. 2025 Jul 23;18(7):e70138. doi: 10.1111/eva.70138. eCollection 2025 Jul.

ABSTRACT

Maternally transmitted symbionts such as Wolbachia spread within host populations by mediating reproductive phenotypes. Cytoplasmic incompatibility (CI) is a reproductive phenotype that interferes with embryonal development when infected males fertilize uninfected females. Wolbachia-based pest control relies on strong CI to suppress or replace pest populations. Host genetic background determines CI strength, and host suppressors that cause weak CI threaten the efficacy of Wolbachia-based pest control programs. In haplodiploids, CI embryos either die (Female Mortality, FM-CI) or develop into uninfected males (Male Development, MD-CI). The reciprocal spread of host suppressors and infection, as well as the interaction with the two CI outcomes in haplodiploids, remains poorly understood. The contribution of sex allocation distortion (Sd), an independent Wolbachia-mediated reproductive phenotype that causes a female-biased sex ratio, to infection persistence in haplodiploids is also poorly understood, especially with imperfect maternal transmission. To address these issues, we developed individual-based simulations and validated this computational tool by tracking Wolbachia spread in experimental Tetranychus urticae populations and by contrasting infection dynamics with deterministic mathematical models. Within ⁓14 host generations, we found that deterministic models inflate infection frequencies relative to simulations by ⁓8.1% and overestimate the driving potential of CI, particularly under low initial infection frequencies. Compared to MD-CI, we show that FM-CI strongly extends infection persistence when nuclear suppressors are segregating in the population. We also quantify how maternal transmission modulates the reciprocal spread of suppressors and infection. Upon loss of CI, we show that hypomorphic expression of Sd (~5%) is sufficient for a stable persistence of infection. We derive a mathematical expression that approximates the stable polymorphic infection frequencies that can be maintained by Sd. Collectively, our results advance our understanding of how symbiosis with CI-inducing Wolbachia and haplodiploid hosts might evolve and inform CI-based pest control programs of potential future risks.

PMID:40703634 | PMC:PMC12284905 | DOI:10.1111/eva.70138

Front Immunol. 2025 Jul 9;16:1596113. doi: 10.3389/fimmu.2025.1596113. eCollection 2025.

ABSTRACT

Hemophagocytic lymphohistiocytosis (HLH) and macrophage activation syndrome (MAS) are life-threatening hyperinflammatory conditions. Primary HLH is caused by genetic mutations associated with defective cytotoxicity, while secondary HLH is triggered by various factors, including infection-associated HLH (IAHS), rheumatic diseases-associated HLH (MAS), or malignancy-associated HLH (M-HLH). We retrospectively reviewed the medical records of patients younger than 20 years of age with physician-diagnosed HLH or MAS between January 2005 and July 2022 in a large medical center in Taiwan. Seven patients were prospectively enrolled since Jan 2019. Clinical and laboratory features, treatments rendered, and outcomes of patients with HLH/MAS were analyzed. Fifty-two patients with HLH/MAS were included in this study and classified as follows: 21 (40.4%) with IAHS, 20 (38.5%) with MAS, 5 (9.6%) with M-HLH, 4 (7.7%) with primary HLH, and 2 (3.8%) with unclassified HLH (U-HLH). The median age of diagnosis for all patients was 9.04 years, while it ranged between 5.12 (for primary HLH) to 16.03 (for M-HLH) years. Two-year probabilities of survival of each group of HLH/MAS were 100%, 85.7%, 65.63%, 25%, and 20% for patients with U-HLH, IAHS, MAS, primary HLH, and M-HLH, respectively (log-rank, P =0.0018). The five-year probability of survival was 65.63% for patients with MAS. M-HLH and ICU admission were significantly associated with mortality. Infections and rheumatic diseases are the main triggers or conditions associated with pediatric HLH/MAS, whereas malignancy is an important etiology among adolescents.

PMID:40703525 | PMC:PMC12284797 | DOI:10.3389/fimmu.2025.1596113

iScience. 2025 Jun 28;28(8):113031. doi: 10.1016/j.isci.2025.113031. eCollection 2025 Aug 15.

ABSTRACT

For cancer patients, metastasis is a life-threatening event limiting therapeutic options. Molecularly, the metastatic phenotype can be conferred by mitochondrial reactive oxygen species (mtROS) generated upon metabolic stress. Mitochondrial damage can also trigger mtROS production, which is particularly well illustrated for anthracyclines. Here, we tested in mouse models of murine and human breast cancer whether this type of chemotherapy can trigger metastasis. We report that subcytotoxic doses of doxorubicin mimicking the clinical situation in poorly perfused tumor areas sequential trigger mtROS production, activate TGFβ pathway effector Pyk2, and increase cancer cell migration and invasion. Fortunately, the metastatic switch was incompletely induced, and doxorubicin did not promote breast cancer metastasis in immunocompetent mice. Yet, MitoTEMPO fully prevented metastatic dissemination and did not interfere with doxorubicin cytotoxicity, making it attractive to combine anthracyclines with mitochondria-targeted antioxidants.

PMID:40703453 | PMC:PMC12283550 | DOI:10.1016/j.isci.2025.113031

iScience. 2025 Jun 28;28(8):113038. doi: 10.1016/j.isci.2025.113038. eCollection 2025 Aug 15.

ABSTRACT

Preterm infants are frequently administered antibiotics to prevent infections, yet their impact on the developing gut microbiota and metabolome remains complex and clinically significant. To systematically assess these effects, we analyzed longitudinal stool samples from 54 extremely- and very-low-birthweight infants by integrating clinical data, 16S rRNA-based microbiome profiling, targeted metabolomics, and community-scale metabolic modeling. Antibiotic exposure disrupted microbial diversity, depleted beneficial taxa, and altered metabolites such as short-chain fatty acids (SCFAs) and bile acids. Class-specific antibiotic effects were observed, with cephalosporins promoting Staphylococcus dominance and potentially reducing bile acid diversity. Necrotizing enterocolitis (NEC) samples showed SCFAs depletion and enrichment of antibiotic-resistant genera. In silico models further identified microbial contributors to SCFAs production and recapitulated metabolite trends. These findings demonstrate how antibiotic regimens can perturb the neonatal gut ecosystem and highlight the need for precision antibiotic stewardship to preserve microbiome-derived metabolic functions and reduce disease risk in preterm infants.

PMID:40703452 | PMC:PMC12283561 | DOI:10.1016/j.isci.2025.113038

Front Microbiol. 2025 Jul 9;16:1582121. doi: 10.3389/fmicb.2025.1582121. eCollection 2025.

ABSTRACT

INTRODUCTION: Elizabethkingia miricola is a gram-negative bacterium that causes life-threatening infections in vulnerable populations. Unlike other species in the Elizabethkingia genus, E. miricola also leads to meningitis-like diseases in aquatic invertebrates such as frogs, raising concerns about its zoonotic transmission potential. Management of its infection is complicated by unclear transmission pathways and multi-drug resistance.

METHODS: In this study, we analyzed three clinical strains (E. miricola Mich-1, Mich-2, and Mich-3) isolated from patients in Michigan using morphology observations, biochemical tests, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-ToF/MS), and genome sequencing.

RESULTS: Average Nucleotide Identity (ANI) analysis revealed that the Michigan strains were nearly identical and shared 96.52% identity with the type strain E. miricola DSM 14571, confirming their classification as E. miricola. Comprehensive comparative genomic analyses were conducted across 28 strains, including human isolates and strains from invertebrates like frogs. The strains exhibited open pan-genome characteristics. Mich-1 shared 3,199 genes (83.2%) with human isolates but fewer genes with frog-derived isolates (ranging from 3,319 to 3,375). This phylogenetic analysis highlights regional variation and the global diversity of E. miricola isolates, revealing connections between clinical and environmental strains. Antibiotic susceptibility testing revealed that the three clinical strains were resistant to 13 out of 16 tested drugs, with susceptibility only to trimethoprim/sulfamethoxazole and ciprofloxacin. The strains carried five β-lactamase-encoding genes (BlaB-10, BlaB-39, CME-1, CME-2, and GOB-25), conferring resistance to penams, cephalosporins, and carbapenems. Several virulence-associated genes were conserved across clinical and frog isolates. These genes contribute to stress adaptation, adherence, and immune modulation.

DISCUSSION: This study underscores the evolutionary adaptability of E. miricola genomes, highlighting their capacity to acquire genetic traits that enable survival in diverse niches. This adaptability facilitates the emergence of more resistant and virulent strains, posing significant threats to both human and animal health.

PMID:40703244 | PMC:PMC12283610 | DOI:10.3389/fmicb.2025.1582121