Cell Rep Methods. 2025 Jun 27:101088. doi: 10.1016/j.crmeth.2025.101088. Online ahead of print.

ABSTRACT

Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is a potent addition to single-cell RNA sequencing (scRNA-seq). This method enriches transcriptomic insights by incorporating information about the cell surface phenotype through the application of oligonucleotide-tagged monoclonal antibodies. Similar to observations in flow cytometry, the CITE-seq signal (antibody-derived tag [ADT]) contains technical noise originating from ambient antibodies within the reaction compartment, non-specific binding, and/or imperfect titration. To denoise ADT data provided through CITE-seq experiments, we present ThresholdR, an R-based automated tool, to reliably and systematically find the threshold that separates the signal from the noise for each antibody. We assess the performance of ThresholdR across different datasets and platforms and benchmark it against two alternative methods, DSB (denoised and scaled by background) and CellBender. We show that ThresholdR remedies the high false negative rates of DSB and CellBender. We propose that denoising with ThresholdR can improve cell-type annotation and improve downstream analyses.

PMID:40633544 | DOI:10.1016/j.crmeth.2025.101088

Cell Rep Methods. 2025 Jun 28:101090. doi: 10.1016/j.crmeth.2025.101090. Online ahead of print.

ABSTRACT

Zebrafish has become a preeminent model for developmental biology research, largely due to the ease of transgenesis. Despite widespread usage of transgenic lines, mapping of transgene insertion sites is rare, which raises complications involving potential local chromatin influences on transgene expression, off-target effects, and issues with allelic variation. To address these shortcomings, we introduce TransTag, a simple and efficient method utilizing Tn5 transposase-mediated tagmentation, for the streamlined identification of Tol2-based transgene insertion sites in zebrafish. TransTag is straightforward to perform and can identify insertion sites without the need for the alignment of raw sequencing data. We also provide a detailed protocol for TransTag, a step-by-step guide for data analysis, and a user-friendly Shiny app, making transgene mapping achievable at a low cost for researchers without programming expertise. Altogether, TransTag emerges as a valuable tool to enhance the precision and utility of transgenesis studies by providing essential chromosome-specific information on transgene locations.

PMID:40633543 | DOI:10.1016/j.crmeth.2025.101090

Semin Cell Dev Biol. 2025 Jul 8;173:103628. doi: 10.1016/j.semcdb.2025.103628. Online ahead of print.

ABSTRACT

Collective cell migration is a key tissue shaping process fundamental to development, wound healing and cancer invasion. The sensing, integration, transduction and propagation of guidance signals and the resulting generation of collective cell responses during collective cell migration can occur at several different length scales from molecular to cellular to supracellular. Furthermore, we have become aware that the cell-environment relationship during migration is bi-directional, where cells not only receive guidance cues from the environment, but also dynamically remodel the environment via their migratory behaviours. Such complex interplay of internal (i.e. intracellular) and external (i.e. cell-cell and cell-environment) interactions makes predicting the emergent output behaviours of cell groups challenging. Here, we propose a framework that combines interdisciplinary experimental and theoretical approaches to bridge the gap between molecular-level mechanisms and tissue-level phenomena during collective cell migration in complex environments. We will review recent works on both in vitro and in vivo migratory models that successfully employ some of these approaches to identify general principles explaining the input-output relationships of robustly tuneable migratory systems. By integrating in vitro with in vivo observations, we will develop more comprehensive models of how collective cell migration is orchestrated in living organisms, which will also pave the way for more effective applications in tissue engineering and disease therapeutics in the future.

PMID:40633502 | DOI:10.1016/j.semcdb.2025.103628

Plant J. 2025 Jul;123(1):e70337. doi: 10.1111/tpj.70337.

ABSTRACT

Abscisic acid (ABA) mediates stress responses and growth regulation in plants, but the roles of ABA-responsive transcription factors (TFs) in Populus development remain poorly characterized. Here, we identified an ABA-upregulated TF and investigated its function through overexpression in transgenic poplar. The PtrMYBH is upregulated during ABA treatment, and its overexpression in transgenic poplar leads to leaf malformations, including reduced size and curling, with severity correlating with PtrMYBH-overexpression levels in three independent transgenic lines. PtrMYBH regulates stomatal growth and development, resulting in decreased stomatal length and aperture, along with distinct leaf structural abnormalities. Additionally, PtrMYBH affects root development, with overexpressing lines showing an increase in adventitious root number but shorter lengths, alongside morphological changes in the root elongation zone. Furthermore, morphological changes are observed in the shoot apical meristem (SAM) and stem-differentiating xylem (SDX) of PtrMYBH-overexpressing poplar. RNA-seq analyses reveal PtrMYBH's influence on the expression of genes related to cellular proliferation in the SAM and developmental pathways in the SDX. Finally, in PtrMYBH-overexpressing lines, ABA treatment results in leaf tip damage, earlier leaf drop, and stunted growth, highlighting its critical role in the ABA response. These findings lay a foundation for further exploration of TFs like PtrMYBH to regulate growth in Populus species.

PMID:40632924 | DOI:10.1111/tpj.70337

ACS Sens. 2025 Jul 9. doi: 10.1021/acssensors.5c01035. Online ahead of print.

ABSTRACT

The highly prevalent single nucleotide polymorphism (SNP, rs671) of the aldehyde dehydrogenase (ALDH2) gene in Asian populations instigates various human pathologies and thus accentuates the urgent need for effective diagnostic tools. In this study, we present an ultrasensitive biosensing method by a combination of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a with the fiber optic nanogold-linked sorbent assay (FONLISA) for precise SNP identification. This method leverages the sequence-specific recognition capability of the CRISPR/Cas system and the ultrahigh sensitivity via the dual signal enhancement mechanisms by integrating the trans-cleavage mechanism of Cas12a to amplify the signal from an activity reporter and the subsequent waveguide-enhanced nanoplasmonic absorption by a signaling reporter. In this method, Cas12a targets a double-stranded DNA from the ALDH2 SNP and then activates the degradation of the activity reporter, a free biotin-labeled single-stranded DNA probe (ssDNAb), by trans-cleavage. An unhybridized complementary single-stranded DNA probe (ssDNAc) labeled with a gold nanoparticle (AuNP) as the signaling reporter (AuNP@ssDNAc) is subsequently released and captured by the immobilized ssDNAb on the fiber core surface, resulting in a detectable nanoplasmonic absorption signal. The method also utilized an indispensable nanoplasmonic signal generator, carboxymethyl dextran-coated AuNP, to improve the preparation and bioconjugation processes. The CRISPR-FONLISA system demonstrates the ability to analyze the ALDH2 rs671 SNP from double-stranded DNA with a limit of detection of 71 aM. Furthermore, both cell lines and unamplified DNA extracted from blood samples were conducted to verify the system accuracy for ALDH2 rs671 SNP detection.

PMID:40632881 | DOI:10.1021/acssensors.5c01035

Brief Bioinform. 2025 Jul 2;26(4):bbaf314. doi: 10.1093/bib/bbaf314.

ABSTRACT

A fundamental principle of immunotherapy is that T cells are capable of detecting tumor epitopes presented on cancer cell surfaces. Immunopeptidomic strategies empowered by liquid chromatography-tandem mass spectrometry have transformed tumor epitopes identification and provided novel insights into tumor immunology. It enables in-depth profiling of major histocompatibility complex (MHC) presented ligands, thereby offering valuable perspectives on the molecular dialog among tumor and T cells. Here, we developed an immune-ligand identification and analysis pipeline from large-scale immunopeptidomics data. Through an extensive collection and processing of 5821 immunopeptidomic samples, which amounted to 305.7 million MS2 spectra, we identified 24 380 595 peptide-spectrum matches from these samples and further detected a total of 1 017 731 unique MHC immune ligands. These ligands were deconvolved and classified to specific HLA alleles. In total, we detected 582 852 HLA-I peptides and 434 879 HLA-II peptides that can bind to 292 HLA alleles, thereby greatly expanding the cancer immunopeptidome. Additionally, we identified and annotated 372 720 tumor-associated post-translational modification (PTM) peptides, revealing the comprehensive landscape of PTM antigens. All ligands and annotations were aggregated into Ligand.MHC Atlas, a comprehensive repository dedicated to tumor-derived HLA-presented ligands across 26 major human cancers (54 subtypes). Overall, our study uniquely integrates batch-effect correction, leverages the optimized software with novel deconvolution approach for immunopeptidomics analysis and ligand identification, and provides a public web portal with a comprehensive HLA ligand repository. Ligand.MHC Atlas functions as an invaluable resource, offering crucial understandings into immunology investigations. It will accelerate the advancement of cancer vaccines and immunotherapies. Ligand.MHC Atlas is available at http://modinfor.com/Ligand.MHC-Atlas/.

PMID:40632497 | DOI:10.1093/bib/bbaf314

Birth Defects Res. 2025 Jul;117(7):e2499. doi: 10.1002/bdr2.2499.

ABSTRACT

BACKGROUND: Orofacial clefts (OFCs) are the most common craniofacial birth defects, affecting 1 in 700 births, and have a strong genetic basis with a high recurrence risk within families.

AIMS: While many of the previous studies have associated common, noncoding genetic loci with OFCs, previous studies on de novo variants (DNVs) in OFC cases have focused on coding variants that could have a functional impact on protein structure, and the contribution of noncoding DNVs to the formation of OFCs has largely been ignored and is not well understood.

MATERIALS AND METHODS: We reanalyzed an existing dataset of DNVs from 1409 trios with OFCs that had undergone targeted sequencing of known OFC-associated loci. We then annotated these DNVs with information from datasets of predicted epigenetic function during human craniofacial development.

RESULTS: Of the 66 DNVs called in the targeted regions in this study, 17 (25.7%) were within a predicted enhancer or promoter region. Two DNVs fell within the same enhancer region (hs1617), which is more than expected by chance (p = 0.0017). The sequence changes caused by these hs1617 DNVs are predicted to create binding sites not seen in the reference sequence for transcription factors PAX6 and ZBTB7A and to disrupt binding sites for STAT1 and STAT3.

DISCUSSION: The hs1617 enhancer region is within the same topologically associated domain as HHAT, SERTAD4, and IRF6, all of which are involved in craniofacial development. All three genes are highly expressed in human neural crest cells. Knockout mice for Hhat and Irf6 have abnormal embryonic development including a cleft palate, and variants in and around IRF6 are associated with nonsyndromic and syndromic forms of OFCs in humans.

CONCLUSION: Taken together, this suggests that noncoding DNVs contribute to the genetic architecture of OFCs, with an excess of DNVs in OFC trios in enhancer regions near known OFC-associated genes. Overall, this adds to our understanding of the genetic mechanisms that underlie OFC formation.

PMID:40631876 | DOI:10.1002/bdr2.2499

Epigenet Rep. 2025;3(1):1-10. doi: 10.1080/28361512.2025.2508883. Epub 2025 May 30.

ABSTRACT

Extracellular vesicle and particle microRNAs (EVP miRNA) in milk have the capacity to facilitate maternal-infant communication in the postpartum period and are hypothesized to play important roles in child development. Maternal diet quality has been linked to milk macronutrient composition, microbiota profiles, as well as various child health outcomes. The aim of this study was to assess the association between maternal diet quality and milk EVP miRNA. In a pilot study of 54 participants from a larger birth cohort study, diet quality was measure by the Alternative Healthy Eating Index 2010 (AHEI-2010) during the second trimester of pregnancy and 798 EVP miRNA were profiled in mature milk samples (collected approximately six weeks postpartum) using the NanoString nCounter platform. In covariate-adjusted models, AHEI-2010 was positively associated (Q < 0.05) with levels of miR-1283, miR-520h, and mir-570-3p in milk EVPs. Predicted target genes of these diet-associated miRNA are enriched in pathways related to lactation and mammary development (PI3 kinase signaling and Wnt signaling pathways) and milk protein and fat synthesis (PI3 kinase signaling). Further research is needed to investigate whether these diet-associated miRNA influence lactation, human milk quality, and child growth and development.

PMID:40631350 | PMC:PMC12234000 | DOI:10.1080/28361512.2025.2508883

Kidney Int Rep. 2025 Apr 1;10(6):1806-1818. doi: 10.1016/j.ekir.2025.03.048. eCollection 2025 Jun.

ABSTRACT

INTRODUCTION: Molecular classifiers are a promising tool to refine the diagnosis of antibody-mediated rejection (ABMR) and T-cell-mediated rejection (TCMR) after kidney transplantation. Despite this potential, the integration of molecular classifiers in transplant clinics has been slow, in part because of the complexity of current assays and lack of a consensus platform. Herein, we aimed to develop and validate sparse molecular classifiers for ABMR and TCMR using allograft tissue.

METHODS: In a discovery cohort of 224 kidney transplant biopsies, lasso regression was applied on microarray gene expression data to derive a molecular classifier for ABMR and TCMR, respectively.

RESULTS: A 2-gene classifier for ABMR (PLA1A, GNLY) and a 2-gene classifier for TCMR (IL12RB1, ARPC1B) were identified. External validation (n = 403 biopsies) demonstrated preserved diagnostic accuracy for ABMR (area under the receiver operating characteristic curve [ROC-AUC]: 0.80, 95% confidence interval [CI]: 0.75-0.85) and TCMR (ROC-AUC: 0.83, 95% CI: 0.77-0.89), with the possibility to discriminate between pure and mixed rejection phenotypes. Complementary to their diagnostic potential, the molecular classifiers associated with accelerated graft loss in a second validation cohort (n = 282 biopsies) and identified allografts at risk for failure with histological lesions that did not reach the Banff thresholds for rejection. The computational approach was further validated using the Banff Human Organ Transplant (B-HOT) gene panel in 2 independent biopsy cohorts that were analyzed on the Nanostring nCounter platform (n = 66 and n = 80, respectively).

CONCLUSION: Rigid variable selection strategies can yield sparse molecular classifiers for allograft rejection phenotypes with preserved accuracy and prognostic value across different molecular diagnostic platforms, which may facilitate their interpretation and clinical implementation.

PMID:40630324 | PMC:PMC12231026 | DOI:10.1016/j.ekir.2025.03.048

Front Pharmacol. 2025 Jun 24;16:1642311. doi: 10.3389/fphar.2025.1642311. eCollection 2025.

NO ABSTRACT

PMID:40630135 | PMC:PMC12234477 | DOI:10.3389/fphar.2025.1642311

Ann Bot. 2025 Jul 9:mcaf145. doi: 10.1093/aob/mcaf145. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Photosynthesis is central to plant function, yet it has been repeatedly lost or diminished in parasitic angiosperm lineages. This variation raises questions about how photosynthetic function is retained, modified, or repurposed in the evolutionary context of parasitism. Cuscuta species, as a model system for studying parasitism, exhibit varying degrees of plastid functionality and photosynthetic ability, based on genomic and ultrastructure studies. However, few direct physiological studies exist, and none that span multiple developmental stages of autotrophic, mixotrophic, and non-photosynthetic species in a phylogenetic framework.

METHODS: To address this gap, we paired photosynthetic activity measurements from Imaging-PAM fluorometry with quantitative analysis of chlorophylls and carotenoids from multiple developmental stages in fourteen Cuscuta species, representing the phylogenetic breadth of the genus, and a closely related autotrophic species. Multivariate data were analyzed using nonparametric hypothesis tests, and comparative phylogenetic patterns were explored through Bayesian model testing.

KEY RESULTS: Photosynthetic activity, chlorophyll and carotenoid content were highest in meristematic regions (e.g., shoot tips and developing seeds) and lowest in older stems or haustoria. Neoxanthin, a carotenoid typically highly conserved in plants, appears to have been lost once in Cuscuta and subsequently re-gained in certain lineages. Complex relationships between photosynthetic activity and lutein epoxide concentration suggest differing roles in developmental stages with high and low energetic needs.

CONCLUSIONS: These findings provide substantial evidence that photosynthesis in Cuscuta is not vestigial but rather modulated based on developmental stage and across phylogenetic history, revealing a dynamic interplay between parasitism and photosynthetic function.

PMID:40629517 | DOI:10.1093/aob/mcaf145

Genome Biol. 2025 Jul 9;26(1):180. doi: 10.1186/s13059-025-03611-9.

ABSTRACT

BACKGROUND: Epigenetic reprogramming shapes immune memory in both innate (trained immunity) and adaptive immune cells following Bacillus Calmette-Guérin (BCG) vaccination. However, the role of dynamic DNA methylation changes in post-vaccination immune responses remains unclear.

RESULTS: We established a cohort of 284 healthy Dutch individuals, profiling genome-wide DNA methylation and cytokine responses to ex vivo stimulation at baseline, 14 days, and 90 days post-BCG vaccination. We identified distinct patterns of DNA methylation alternations in the short- and long-term following BCG vaccination. Moreover, we established that baseline DNA methylation profiles exert influence on the change in interferon-γ (IFN-γ) production upon heterologous (Staphylococcus aureus) stimulation before and after BCG vaccination. Specifically, we identified the regulation of kisspeptin as a novel pathway implicated in the modulation of IFN-γ production, and this finding has been substantiated through experimental validation. We also observed associations between BCG-induced DNA methylation changes and increased IFN-γ and interleukin-1 β (IL-1β) production upon S. aureus stimulation. Interestingly, by integrating with genetic, epigenetic, and cytokine response data from the same individuals, mediation analysis demonstrated that most of the identified DNA methylation changes played a mediating role between genetic variants and cytokine responses; for example, the changes of cg21375332 near SLC12 A3 gene mediated the regulation of genetic variants on IFN-γ changes after BCG vaccination. Sex-specific effects were observed in DNA methylation and cytokine responses, highlighting the importance of considering sex in immune studies.

CONCLUSIONS: These findings provide deeper insights into immune response mechanisms, crucial for developing effective epigenetic-based medical interventions for personalized medicine.

PMID:40629459 | DOI:10.1186/s13059-025-03611-9

Nat Commun. 2025 Jul 8;16(1):6281. doi: 10.1038/s41467-025-60231-4.

ABSTRACT

Rapidly evolving viral pathogens such as SARS-CoV-2 continuously accumulate amino acid changes, some of which affect transmissibility, virulence or improve the virus' ability to escape host immunity. Since the beginning of the SARS-CoV-2 pandemic, multiple lineages with concerning phenotypic alterations, so-called Variants of Concern (VOCs), have emerged and risen to predominance. To optimize public health management and ensure the continued efficacy of vaccines, the early detection of such variants is essential. Therefore, large-scale viral genomic surveillance programs have been initiated worldwide, with data being deposited in public repositories in a timely manner. However, technologies for their continuous interpretation are lacking. Here, we describe the CoVerage system ( www.sarscoverage.org ) for viral genomic surveillance, which continuously predicts and characterizes emerging potential Variants of Interest (pVOIs) from country-wise lineage frequency dynamics, together with their antigenic and evolutionary alterations utilizing the GISAID viral genome resource. In a comprehensive assessment of VOIs, VUMs, and VOCs, we demonstrate how CoVerage can be used to swiftly identify and characterize such variants, with a lead time of almost three months relative to their WHO designation. CoVerage can facilitate the timely identification and assessment of future SARS-CoV-2 variants relevant for public health.

PMID:40628697 | DOI:10.1038/s41467-025-60231-4

Cell Genom. 2025 Jul 1:100927. doi: 10.1016/j.xgen.2025.100927. Online ahead of print.

ABSTRACT

The determination of long non-coding RNA (lncRNA) function is a major challenge in RNA biology with applications to basic, translational, and medical research. We developed BigHorn to computationally infer lncRNA-DNA interactions that mediate transcription and chromatin-remodeling factor activity. Its accurate inference enabled the identification of lncRNAs that coordinately regulate both the transcriptional and post-transcriptional processing of their targets. These lncRNAs may act as molecular chaperones, regulating the stability and translation of mRNAs they helped transcribe, leading to tightly coupled expression profiles. Our analysis suggests that lncRNAs regulate cancer genes across tumor contexts, thus propagating the effects of non-coding alterations to effectively dysregulate cancer programs. As a proof of principle, we studied the regulation of DICER1, a cancer gene that plays a key role in microRNA biogenesis, by the lncRNA ZFAS1. We showed that ZFAS1 helps activate DICER1 transcription and block its mRNA degradation to phenomimic DICER1 and regulate its target microRNAs.

PMID:40628267 | DOI:10.1016/j.xgen.2025.100927

Cell Chem Biol. 2025 Jul 2:S2451-9456(25)00198-9. doi: 10.1016/j.chembiol.2025.06.003. Online ahead of print.

ABSTRACT

Kinase inhibitors are potent therapeutics, but most essential Plasmodium kinases remain unexploited as antimalarial targets. We identified compound 12, a type II kinase inhibitor based on aminopyridine and 2,6-benzimidazole scaffolds, as a lead compound with nanomolar potency, fast action, and in vivo activity in the Plasmodium berghei rodent malaria model. Three-hybrid luciferase fragment complementation, enzymatic studies, and cellular thermal shift assays implicated Plasmodium protein kinase 6 (PfPK6) as the target. However, conditional knockdown of PfPK6 did not alter 12 potency, suggesting complex mechanisms of action. In vitro selection for compound 12 resistance revealed mutations in three transporters: multidrug-resistance protein 1, chloroquine resistance transporter and V-type ATPase, indicating a digestive vacuole site of action. Compound 12 inhibited β-hematin and hemozoin formation while increasing free heme levels, suggesting antimalarial activity via blockade of heme detoxification. Our studies repurpose a safe human kinase inhibitor as a potent, fast-acting antimalarial with established in vivo efficacy.

PMID:40628257 | DOI:10.1016/j.chembiol.2025.06.003

J Pharm Biomed Anal. 2025 Jul 4;265:117046. doi: 10.1016/j.jpba.2025.117046. Online ahead of print.

ABSTRACT

Suicidal behavior is highly variable regarding severity of ideation and lethality, which may be reflected in central and systemic proteomic modifications. This study aimed to identify the proteomic profile by mass spectrometry analysis, pathways, and biological processes underlying suicidal behavior. We systematically reviewed three databases, including studies of postmortem brain tissue of suicide completers, and analyzed serum from individuals hospitalized after recent suicide attempts. The Biological General Repository for Interaction Datasets (BioGRID) was used to verify interactions between identified proteins, followed by functional enrichment analysis to determine the main biological processes and pathways. Over 700 differentially expressed proteins (DEP) were found in the postmortem brain of suicide victims, while 36 DEP were identified in the serum of individuals with suicide attempts. Four common DEPs (serum amyloid P-component, beta-2-glycoprotein 1, hemoglobin subunit beta, and S100 calcium-binding protein A9) were found in both tissues. Biological processes and pathways indicated disturbance on cytoskeletal organization, energy metabolism, complement cascade, and coagulation as key mechanisms associated with suicidal behavior. Despite preliminary findings, our work provides molecular insights into the biological underpinnings of suicidal behavior and contributes to the identification of promising candidate targets for suicide risk, an urgent and still largely unmet need in psychiatric research. Nevertheless, analytical validation using complementary molecular techniques in larger, independent samples is essential to confirm their reproducibility and quantification accuracy.

PMID:40628118 | DOI:10.1016/j.jpba.2025.117046

Curr Opin Biotechnol. 2025 Jul 7;94:103335. doi: 10.1016/j.copbio.2025.103335. Online ahead of print.

ABSTRACT

Algae are a sustainable, nutrient-rich resource with growing potential in food biotechnology. Their ability to thrive in diverse environments makes them a promising alternative to conventional crops. Rich in proteins, essential fatty acids, and bioactive compounds, algae support the development of functional foods, including plant-based meat and seafood alternatives. Advances in synthetic biology and fermentation have enhanced algal nutrient profiles and enabled novel applications. Algae-derived polysaccharides, such as alginate, fucoidan, laminarin, and porphyran, exhibit prebiotic effects by modulating the gut microbiota and promoting SCFA production. Enzymatic hydrolysis efficiently produces bioactive oligosaccharides, while engineered microbial systems support scalable production. Algae also enable synbiotic food development by serving as both prebiotic substrates and probiotic carriers.

PMID:40628054 | DOI:10.1016/j.copbio.2025.103335

ACS Nano. 2025 Jul 8. doi: 10.1021/acsnano.5c04309. Online ahead of print.

ABSTRACT

The frequent global outbreaks of viral infectious diseases have significantly heightened the urgent demand for molecular testing at home. However, the labor-intensive sample preparation and nucleic acid amplification steps, along with the complexity and bulkiness of detection equipment, have limited the large-scale application of molecular testing at home. Here, we propose artificial intelligence-enhanced hand-driven microfluidic system (MACRO) based on RPA and CRISPR technologies for home diagnosis of multiple types of infectious diseases. Leveraging a multidimensional space hourglass structure design, precise spatiotemporal control of fluids can be achieved simply by flipping the chip. Through dual chemical reactions, the system eliminates the need for nucleic acid extraction and purification, simplifying sample preparation and obviating the reliance on heating equipment. The MACRO achieves attomolar sensitivity within 60 min from sample input to result, and 100% specificity for 27 HPV subtypes. Clinical validation using 140 cervical swab specimens demonstrated 98.57% accuracy with 100% specificity. Further, we validated MACRO through multiplex detection of three clinically critical respiratory pathogens (SARS-CoV-2, Influenza A, and Influenza B) in 70 samples, achieving 100% diagnostic concordance. To circumvent subjective errors and enable real-time data collection, we further developed a mobile health platform based on the YoLov8 image recognition algorithm to ensure rapid and precise result output. With the performance of cost-effectiveness ($1.34 per target), and independence from instrument support, MACRO provides a comprehensive solution for molecular testing at home, offering significant implications for enhancing early warning systems for major epidemics and improving public health emergency response capabilities.

PMID:40627810 | DOI:10.1021/acsnano.5c04309

Int Immunol. 2025 Jul 8:dxaf037. doi: 10.1093/intimm/dxaf037. Online ahead of print.

ABSTRACT

Three-prime repair exonuclease 1 (TREX1) is the major 3' to 5' DNA exonuclease in mammals and plays an essential role in preserving immune homeostasis by controlling cytosolic DNA sensing. By degrading excess self and foreign DNA, TREX1 limits aberrant activation of the cGAS-STING pathway and downstream type I interferon responses. Loss-of-function mutations in TREX1 underlie a spectrum of interferon-driven autoimmune and autoinflammatory syndromes, demonstrating its role as a key regulator of immune tolerance. Beyond autoimmunity, recent discoveries have uncovered critical roles for TREX1 in shaping tumor immunogenicity and modulating antiviral defense through regulation of DNA-sensing pathways. In this review, we summarize current insights into the evolutionary origin, structural mechanisms, and functional repertoire of TREX1 in innate immunity. We further discuss how dysregulation of TREX1 contributes to disease and highlight emerging strategies to therapeutically modulate TREX1 activity in cancer and interferonopathies.

PMID:40627703 | DOI:10.1093/intimm/dxaf037

Brief Bioinform. 2025 Jul 2;26(4):bbaf286. doi: 10.1093/bib/bbaf286.

ABSTRACT

Employing machine learning (ML) models to accelerate experimentation and uncover biological mechanisms has been a rising tendency in genetic engineering. However, effectively collecting data to enhance model accuracy and improve design remains challenging, especially when data quality is poor and validation resources are limited. Active learning (AL) addresses this by iteratively identifying promising candidates, thereby reducing experimental efforts while improving model performance. This review highlights how AL can assist scientists throughout the design-build-test-learn cycle, explore its various practical implementations, and discuss its potential through the integration of cross-domain expertise. In the age of genetic engineering revolutionized by data-driven ML models, AL presents an iterative framework that significantly enhances the functionalities of biomolecules and uncovers their intrinsic mechanisms, all while minimizing expenses and efforts.

PMID:40627682 | DOI:10.1093/bib/bbaf286