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A contextual activity score (CAS) for inferring ADAR-associated transcriptional activity across RNA-seq, single-cell, and spatial transcriptomics.

BACKGROUND AND OBJECTIVE: Adenosine-to-inosine RNA editing, catalyzed by Adenosine Deaminases Acting on RNA (ADARs), is a widespread modification involved in neural function, immune regulation, and cancer. The Alu Editing Index (AEI) is the standard metric to estimate ADAR activity but requires raw sequencing reads and is poorly suited for single-cell and spatial transcriptomic data. This study aimed to develop an alternative framework for inferring ADAR-associated transcriptional activity from gene expression data across diverse transcriptomic technologies. METHODS: We developed the Contextual Activity Score (CAS), a framework based on transcriptional signatures from ADAR perturbation experiments. Context-specific signatures were generated for human neurons, mouse neurons, and cancer models to infer ADAR1 and ADAR2 activity. CAS was computed from normalized gene expression matrices using regulon-based enrichment analysis. Performance was evaluated by comparing with the Alu Editing Index across bulk RNA sequencing datasets, simulated sequencing depths, and library preparation protocols. RESULTS: CAS showed strong concordance with the Alu Editing Index across multiple datasets, while remaining robust to reduced sequencing depth and different library protocols. Unlike the Alu Editing Index, CAS can be applied to single-cell and spatial transcriptomic data and enables the independent assessment of ADAR2 activity. In cancer and neuronal contexts, CAS captured biologically meaningful variations in ADAR-associated transcriptional activity at sample, cell-type, and spatial levels. CONCLUSION: CAS provides a scalable approach applicable across multiple RNA-seq protocols for estimating ADAR-associated transcriptional activity using gene expression data. This method, implemented in an open-source R package for broad adoption, expands the ability to study ADAR-associated transcriptional activity across transcriptomic modalities where direct editing quantification is challenging, such as single-cell and spatial transcriptomics.

Adenosine Deaminase

Comparative transcriptome analysis provides insights into dorso-ventral color pattern formation of Holothuria edulis.

Animal body color patterns are highly diverse and play critical roles in camouflage, intraspecific communication, and environmental adaptation. Holothuria edulis, an important echinoderm inhabiting tropical waters, exhibits a typical dorsoventral dichromatism. This unique body color difference represents a key phenotypic trait for its habitat adaptation; however, the core differential genes regulating this trait remain to be elucidated. In this study, comparative transcriptome sequencing was performed on the dorsal and ventral body wall tissues of H. edulis, leading to the identification of a number of differentially expressed genes (DEGs), followed by GO functional annotation and KEGG pathway enrichment analysis. GO enrichment analysis indicated that the DEGs were significantly enriched in functional categories such as extracellular region, peptidase inhibitor activity, and tetrapyrrole binding. KEGG pathway analysis further revealed significant enrichment of protein digestion and absorption, the TNF signaling pathway, and cholesterol metabolism. Notably, the pigmentation-related gene FMO2 was highly expressed in the dorsal body wall tissue, whereas cyp1a1, ZIC1, Slc7a11, WNT-1, and ADAMTS20 were highly expressed in the ventral body wall tissue. This study identified DEGs and enriched pathways associated with dorsoventral body color differences in H. edulis, providing new insights into the molecular regulatory mechanisms underlying body color pattern formation. From the perspective of aquaculture applications, body color is one of the important traits affecting the quality and market value of sea cucumber products. Elucidating the molecular mechanisms of body color variation can provide a scientific basis for molecular marker-assisted breeding of superior sea cucumber variety.

Animals

Identification and functional analysis of MeJA-responsive bHLH family genes in Taraxacum kok-saghyz.

Taraxacum kok-saghyz (T. kok-saghyz) is considered a highly promising alternative source of natural rubber (NR), as its roots synthesize high-molecular-weight NR comparable to that produced by Hevea brasiliensis. The basic helix-loop-helix (bHLH) family of transcription factors (TFs) plays crucial roles in plant organogenesis, hormonal signal transduction, and the regulation of secondary metabolism. This study aimed to systematically identify TkbHLH family members and to elucidate their potential functions in responding to methyl jasmonate (MeJA) and regulating root development. Based on the T. kok-saghyz genome, 172 TkbHLH members were identified and phylogenetically classified into 16 subfamilies. Among these, 37 genes were selected due to their significant induction by MeJA. Sequence analysis confirmed all encoded proteins contain the conserved bHLH domain. Subcellular localization verified nuclear localization of five core TkbHLH proteins. Interactions were shown by yeast two-hybrid and bimolecular fluorescence complementation, revealing these proteins form homodimers and heterodimers. Notably, a specific interaction was detected between TkbHLH162 and TkHMGS1, a key enzyme in the mevalonate (MVA) pathway, suggesting a potential molecular link between JA signaling and the rubber biosynthesis precursor pathway. Functional characterization via overexpression assays showed that selected TkbHLH genes significantly either promoted or inhibited root elongation. In summary, this study presents the first systematic characterization of the bHLH TF family in T. kok-saghyz, elucidating its involvement in JA signal response, protein interaction networks, and root development regulation. These findings provide a crucial foundation for further investigation into the molecular mechanisms by which TkbHLH TFs influence root morphogenesis and NR biosynthesis in T. kok-saghyz.

Taraxacum kok-saghyz (T. kok-saghyz)

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans

Endocrine-disrupting chemical-induced gene networks confer coronary heart disease risk revealed by causal inference and single-cell analyses.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4&#x202f;>&#x202f;0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.

Humans

An overview of the use of proteomics and peptidomics to characterize alternative protein foods.

The global protein transition is accelerating the development of alternative protein foods, mainly derived from plants, insects, algae, fungi, and cellular agriculture. Ensuring the authenticity, safety, and nutritional adequacy of these emerging protein matrices requires molecular-level characterization beyond traditional compositional analyses. Proteomics and peptidomics have emerged as transformative analytical platforms capable of decoding the molecular signatures that define protein origin, structural integrity, digestibility, functionality, and health potential. The review comprehensively examines the application of proteomics, and peptidomics for profiling alternative protein foods. Further, the source authentication strategies based on species-specific protein and peptide biomarkers, detection of adulteration in complex matrices, and allergenicity assessment is discussed. Special attention is also given to nutritional proteomics with protein digestibility, gastrointestinal peptide release, and identification of bioactive sequences. SIGNIFICANCE: The importance of this review is that proteomics and peptidomics are becoming central in the management of the fast-growing environment of alternative protein foods, such as plant-based, insect, algal, fungal, and cultured meat products. It provides an explanation of the application of mass spectrometry-based processes to decode molecular signatures defining the origin of proteins, their structural integrity, digestibility, allergenicity, and bioactive properties, and thus directly contribute to safety, nutritional analysis, and authenticity of the product. Presentation of the article includes the integration of the knowledge of traditional muscle foods with alternative systems of proteins, where validated protein and peptide biomarkers are used in authentication, fraud detection, and allergy risk assessment in a wide variety of matrices. It also indicates the role of nutritional proteomics and peptidomics in informing the formulation strategy to promote digestibility and release of health-promoting peptides. In general, this review will guide scientists, the food industry, and regulatory bodies to use modern proteomic technologies in quality assurance, and decision-making, for the advancementof sustainable protein-based foods.

Proteomics

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans

Emergence of Babesia naoakii infection in Indonesian domestic cattle, a new host record in water buffaloes, and characterization of complete mitochondrial protein-coding genes.

Babesia (B.) naoakii, previously referred to as Babesia sp. Mymensingh, is a recently characterized tick-borne haemoprotozoan parasite of cattle. In Indonesia, we first reported its presence in 2022 from clinically affected cattle in Central Java. To investigate the wider epidemiology of this neglected ruminant-associated Babesia species, we surveyed apparently healthy cattle (Bos indicus) and water buffaloes (Bubalus bubalis) across three districts of Java, Indonesia. A PCR assay targeting the B. naoakii-specific apical membrane antigen 1 (ama1) gene detected the parasite occurrence in 34.39% of assessed cattle (87/253; 95% CI: 28.80-40.44%) and 30.77% of water buffaloes (12/39; 95% CI: 18.47-46.52%). These results represent the first record of B. naoakii infection in water buffaloes in the country and confirm that the parasite circulates in subclinically infected bovine hosts. To characterise this apicomplexan parasite further at the molecular level, we assembled in full length the three mitochondrial protein-coding genes (PCGs): cytochrome c oxidase subunits 1 (cox1) and 3 (cox3), as well as cytochrome b (cytb). These genes were reconstructed by next-generation sequencing of blood DNA collected during the acute haemolytic-phase of B. naoakii infection, from calves that subsequently succumbed to the disease in the endemic area. Phylogenetic analyses of the concatenated amino-acid sequences of cox1, cox3, and cytb placed the Indonesian isolates within a well-supported monophyletic clade, distinct from all previously characterised ruminant-associated Babesia species and sister to the Babesia bigemina/Babesia ovata lineage. This placement confirmed species identity and reinforced the genetic distinctiveness of B. naoakii in Indonesia. Notably, although B. naoakii circulates in peripheral blood and mirrors the diagnostic behaviour of the mild pathogen B. bigemina, its clinical impact more closely resembles that of the severe pathogenic B. bovis, particularly in young animals. This diagnostic-clinical discordance highlights the need for B. naoakii-specific molecular surveillance and species-level differentiation in regions of co-endemicity. Given the high prevalence in subclinically B. naoakii-infected adults, the documented severity of babesiosis in calves, and the potential for substantial economic losses, broader epidemiological investigations and species-specific control measures for B. naoakii are urgently performed. The same holds true for future epizootiological investigations of underdiagnosed B. naoakii-infections possibly circulating in Indonesian endemic ruminant bovids such as the banteng (Bos javanicus), the lowland anoa (Bubalus depressicornis) and the tamaraw (Bubalus mindorensis).

Animals

Nanopore-based epigenomic profiling reveals the absence of widespread CpG methylation in the African swine fever virus genome.

DNA methylation is a critical epigenetic mechanism implicated in regulating replication and transcription in DNA viruses. However, the epigenetic landscape of African swine fever virus (ASFV), a large double-stranded DNA virus infecting pigs, remains controversial. Here, we systematically profiled the DNA methylome of the first ASFV strain isolated in Hong Kong (HK_NT_202103) using Oxford Nanopore Technologies (ONT) R10.4.1 sequencing. We employed a paired design: native whole-genome sequencing (WGS) against a methylation-free whole-genome amplification (WGA) control. Using conservative thresholds, we found no evidence of 5-methylcytosine (5mC), especially typical CpG methylation, across the viral genome. Importantly, clear CpG methylation signals were successfully detected in the host genome from WGS data, confirming the functionality of the workflow to detect 5mC at CG sites. While widespread 5mC seems absent, a small number of putative N6-methyladenine (6mA) loci were identified. A specific 6mA candidate exhibited raw ionic current disruptions and gene-level intersection with another ASFV isolate (CAS19-01/2019), although it lacked single-base consensus across different methylation callers or between the two isolates. Although our biological findings are restricted to a single isolate under specific experimental conditions, this study introduces a novel, highly rigorous ONT framework for viral epigenomics research. Furthermore, the absence of ASFV CpG methylation indicates that host CpG-depletion remains a viable strategy for viral metagenomic enrichment. Ultimately, our work offers a critical methodological baseline for ASFV surveillance and highlights the necessity of targeted experimental validation for rare viral modifications.

African Swine Fever Virus

Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV&#xa0;>&#xa0;100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation

Transcriptome analysis of the pectoral fin degeneration in half-smooth tongue sole (Cynoglossus semilaevis).

Appendage degeneration is a notable morphological feature of some teleosts with specialized benthic lifestyles. The half-smooth tongue sole (Cynoglossus semilaevis) undergoes severe pectoral fin regression during metamorphosis. However, the molecular basis underlying rapid pectoral fin degeneration remains unclear. Here, we performed time-series transcriptome sequencing on pectoral fins at pre-metamorphosis, metamorphosis peak and post-metamorphosis to characterize the molecular changes associated with pectoral fin degeneration. Transcriptional dynamics and functional enrichment showed that no significant enrichment of classical apoptosis-related transcriptional pathways was detected during pectoral fin degeneration. Instead, sustained downregulation of twist1b, identified as a transcriptomic candidate, together with significant upregulation of ssh1, coupled with enrichment of lysosome and ubiquitin-proteasome system (UPS) pathways, suggested enhanced tissue remodeling during pectoral fin degeneration. Temporal expression clustering revealed heterochronic misalignment in the developmental gene expression: upstream initiator tbx5 was upregulated at early metamorphosis, while downstream maintenance signal fgf10 decreased synchronously. Distal patterning gene hoxd12a exhibited premature expression and rapid decay, losing sustained late-phase expression. Moreover, transient elevation of gli3 during metamorphosis may contribute to restricted distal fin growth. We conclude that pectoral fin degeneration in C. semilaevis is associated with heterochronic disruption of developmental signaling and extensive tissue remodeling. This study provides transcriptomic insights into pectoral fin degeneration in tongue soles and establishes a basis for future functional studies of appendage reduction in teleosts.

Animals

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans

Genomic characterization and pathogenicity of ruminant Listeria monocytogenes isolates in a murine oral infection model.

Listeria monocytogenes is a major foodborne pathogen; its ruminant isolates display zoonotic characteristics, causing similar clinical signs in humans, including abortion and encephalitis. However, data on whole genome sequencing and pathogenicity of ruminant L. monocytogenes isolates remain sparse. This study aimed to analyze the genotypic characteristics of L. monocytogenes isolates from ruminants with listeriosis. Furthermore, we assessed the in vivo pathogenicity of four ruminant L. monocytogenes isolates, characterized via whole-genome sequencing-based genetic clustering, in orogastrically inoculated mice. The isolate LM18 (serotype 1/2b, ST224, SL6178) had the lowest lethal dose compared to the other three isolates including previous hypervirulence type (serotype 4b, ST1, SL1) and caused secondary bacteremia in lungs, with sustained bacterial loads in the spleen and liver. Genomic (listeria pathogenicity island -1 and -3) and virulence gene (actA and llsX) mutation analyses associated with virulence suggested from well-recognized studies could not elucidate the virulence of the isolates. SSI-1, which only exists in the isolate LM18 (serotype 1/2b, ST224, SL6178), may help L. monocytogenes survive in the gastrointestinal environment, thereby affecting its virulence. Further research should investigate the role of SSI-1 in the pathogenicity of L. monocytogenes. Moreover, additional studies utilizing larger datasets of ruminant isolates are required to validate our genotypic characterization and to obtain a comprehensive picture of further genotypic differences crucial for L. monocytogenes pathogenicity.

Animals

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP&#xa0;+&#xa0;AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics

Measurable Residual Disease and the Unresolved Biology of Leukemic Stem Cells.

Measurable residual disease (MRD) testing has transformed the management of hematologic cancers by enabling detection of residual malignant cells after therapy. Current approaches rely on qPCR and next-generation sequencing to monitor leukemia-associated somatic mutations, while multiparameter flow cytometry identifies aberrant leukemic immunophenotypes. Although these methods provide valuable prognostic and therapeutic information, MRD negativity remains an imperfect surrogate for cure. Most MRD platforms evaluate CD45+, rapidly dividing leukemic populations and fail to detect quiescent cells that may survive cytotoxic therapies which efficiently target proliferating hematopoietic cells. Relapse frequently occurs despite deep molecular remission, suggesting persistence of rare leukemic stem cells (LSCs) that are intrinsically resistant to chemotherapy and targeted therapies. The paradox of relapse despite molecular remission could be explained by the presence of very small embryonic-like stem cells (VSELs) which are pluripotent, quiescent stem cells sitting at the top of cellular hierarchy in multiple adult tissues including bone marrow. A pluripotent VSEL divides through asymmetrical cell division to give rise to two cells of different sizes and fates, smaller cell is to self-renew while the bigger is lineage-restricted and tissue-committed progenitor which undergoes extensive epigenetic changes, divides rapidly and undergoes clonal expansion before further differentiation. Dysfunctions of VSELs initiate both solid and hematologic cancers. Based on this view, somatic mutations monitored during MRD assessment possibly represent downstream consequences of clonal expansion rather than the initiating drivers of disease persistence. Thus, exclusive monitoring of somatic mutations and CD45&#x2009;+&#x2009;leukemic populations possibly overlook rare, small-sized, CD45- VSELs that contribute to therapeutic resistance and relapse.

Humans

Comparative transcriptomic analysis of the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress.

To investigate the differences in molecular responses between the gills and hepatopancreas of freshwater-cultured Litopenaeus vannamei under chronic nitrite stress, a 30-day chronic stress experiment was conducted with a control group and a stress group. Transcriptomic analysis of the gills and hepatopancreas was performed using Illumina sequencing; differentially expressed genes (DEGs) were identified, and GO, KEGG, GSEA, PPI, and RT-qPCR validation were carried out. The results showed that 196 DEGs (161 up-regulated and 35 down-regulated) were identified in the gills, and 287 DEGs (199 up-regulated and 88 down-regulated) in the hepatopancreas, with only 18 DEGs shared between the two tissues. DEGs in the gills were enriched in oxidoreductase activity, glycerophospholipid metabolism, and tyrosine metabolism; DEGs in the hepatopancreas were enriched in lipid transporter activity, phagosome, ECM-receptor interaction, and riboflavin metabolism. GSEA revealed significant suppression of the mTOR pathway in the gills and the Polycomb complex pathway in the hepatopancreas. PPI network analysis identified hub genes P5CS and eEF2 in the gills, and PER, TUBB1, SHMT, and TUBB4B in the hepatopancreas. RT-qPCR validation was consistent with the RNA-seq results (R2&#xa0;=&#xa0;0.764). This study indicates that, under chronic nitrite stress, the gill response is centered on redox regulation and inhibition of growth metabolism, whereas the hepatopancreas response primarily involves lipid transport, cytoskeletal remodeling, and phagosome activation. The two tissues synergistically adapt through fundamental biosynthetic and motor protein pathways. This research provides molecular evidence for deciphering the nitrite tolerance mechanisms in freshwater-cultured shrimp.

Animals

ChIP-seq profiling identifies diapause-regulated H3K27me3 targets in the fat body of Culex pipiens.

Culex pipiens, a principal vector of significant arboviruses, survives winter through diapause, a hormonally controlled inactive phase that enhances endurance under severe cold circumstances. Recent data suggests that epigenetic processes, namely histone post-translational modifications (hPTMs), play a crucial role in regulating seasonal dormancy. Prior studies from our laboratory indicated a decrease in the methylation of Histone 3 (H3K27me3) in diapausing fat body tissue, associated with elevated expression of the histone demethylase UTX. Nonetheless, the precise genomic areas impacted by these chromatin alterations remained unidentified. We used chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) to delineate the genome-wide distribution of H3K27me3 across fat body chromatin in diapausing (D) and non-diapausing (ND) female Cx. pipiens. Notably, the higher signal at transcription start sites (TSSs) reflects localized redistribution rather than a global decrease, as diapausing fat bodies retain less H3K27me3 overall but concentrate it at promoters. To investigate the functional significance of these chromatin alterations, we confirmed a number of target loci via ChIP-qPCR and assessed gene expression with qRT-PCR. We identified many critical genes that were markedly increased in diapausing mosquitoes, exhibiting an inverse relation to H3K27me3 enrichment. Our data demonstrates different H3K27me3 chromatin landscapes between diapausing and non-diapausing Cx. pipiens, corroborating a hypothesis of selective, locus-specific repression in the non-diapause state and its targeted removal during diapause to permit activation of dormancy-associated genes. These results suggest that chromatin remodeling is a core driver of the diapause switch.

Animals

Comparative genomic epidemiology of food- and patient-derived diarrheagenic Escherichia coli from sentinel surveillance in Southeast China.

Diarrheagenic Escherichia coli (DEC) remains an important foodborne pathogen, yet long-term comparative genomic surveillance data jointly characterizing food-derived and patient-derived isolates remain limited. This surveillance-based comparative study integrated antimicrobial susceptibility testing and whole-genome sequencing to characterize diarrheagenic Escherichia coli isolates recovered from food and patient sources in Lishui, Southeast China, during 2018-2025, with emphasis on occurrence, resistance profiles, genomic backgrounds, and plasmid replicon-associated features. Antimicrobial susceptibility testing was performed for 258 selected isolates, and whole-genome sequencing was conducted for a curated analytical subset of 204 isolates. The sequenced subset was used for diversity-oriented comparative genomic analysis rather than for unbiased prevalence estimation of the entire DEC collection. EAEC predominated in both sources, although food-associated occurrence was heterogeneous across categories, with the highest recovery rate observed in raw meat. Patient-derived isolates showed a broader overall resistance burden, whereas food-derived isolates retained substantial resistance to tetracycline, chloramphenicol, and florfenicol. Phylogenetic analysis showed partial overlap in genomic backgrounds between food-derived and patient-derived isolates, while representative resistance determinants displayed both broadly distributed and lineage-enriched patterns. Replicon-based plasmid profiling identified 42 plasmid types, including 12 detected in both sources, with IncF-related replicons predominating among these shared profiles. Several food-derived isolates carried multiple plasmid replicon types that were also observed in patient-derived isolates. Overall, food-derived and patient-derived DEC showed partial overlap in genomic backgrounds, resistance determinants, and replicon-defined plasmid profiles within this surveillance setting, while retaining source-associated heterogeneity. These findings should be interpreted as surveillance-based comparative evidence rather than as evidence of direct source attribution or transmission.

Humans