Search Results (692)

We present LazyNet, a compact one-step neural-ODE model for single-cell CRISPR activation/interference (A/I) that operates directly on two-snapshot (“pre → post”) measurements and yields parameters with clear mechanistic meaning. The core log–linear–exp residual block exactly represents multiplicative effects, so synergistic multi-locus responses appear as explicit components rather than opaque composites. On a 53k-cell × 18k-gene neuronal Perturb-seq matrix, a three-replica LazyNet ensemble trained under a matched 1 h budget achieved strong threshold-free ranking and competitive error (genome-wide r ≈ 0.67) while running on CPUs. For comparison, we instantiated transformer (scGPT-style) and state-space (RetNet/CellFM-style) architectures from random initialization and trained them from scratch on the same dataset and within the same 1 h cap on a GPU platform, without any large-scale pretraining or external data. Under these strictly controlled, low-data conditions, LazyNet matched or exceeded their predictive performance while using far fewer parameters and resources. A T-cell screen included only for generalization showed the same ranking advantage under the identical evaluation pipeline. Beyond prediction, LazyNet exposes directed, local elasticities; averaging Jacobians across replicas produces a consensus interaction matrix from which compact subgraphs are extracted and evaluated at the module level. The resulting networks show coherent enrichment against authoritative resources (large-scale co-expression and curated functional associations) and concordance with orthogonal GPX4-knockout proteomes, recovering known ferroptosis regulators and nominating testable links in a lysosomal–mitochondrial–immune module. These results position LazyNet as a practical option for from-scratch, low-data CRISPR A/I studies where large-scale pretraining of foundation models is not feasible. Full article

Root rot disease severely threatens tropical fruit production, leading to plant mortality and reduced yields; however, the mechanisms of host defense responses and pathogen infection remain poorly understood. In this study, Fusarium acutatum was isolated from diseased Annona squamosa roots and identified through morphological features and ITS phylogeny (99.8% identity). Infection triggered a marked activation of antioxidant defenses, with elevated POD, SOD, PAL, PPO, and CAT activities. Transcriptomic and TMT-based quantitative proteomic analyses identified 23,791 and 74,403 differentially expressed genes (DEGs) and 367 and 609 differentially expressed proteins (DEPs) in root at 5 and 10 days post inoculation, respectively, relative to the control. These DEGs and DEPs were consistently enriched in pathways involving redox regulation, protein synthesis and processing, ubiquitin-mediated proteolysis, phenylpropanoid and flavonoid metabolism, cell wall remodeling, plant–pathogen interaction and MAPK signaling. Integrated transcriptomic–proteomic correlation analysis showed clear positive associations between key defense-related genes and proteins, suggesting that phenylpropanoid metabolism and reactive oxygen species (ROS) scavenging play central roles in resistance. Key genes such as CHI2, CHS, and CYP were strongly induced and validated by qPCR, supporting coordinated activation of the defense systems. Furthermore, F. acutatum exhibited upregulation of 50 pathogenic-related proteins, including 4 cell wall-degrading enzymes (e.g., CBH1, pectate lyase), 5 metabolic regulation or signal transduction enzymes (e.g., gabD, TPI, and ENO) and 3 potential effectors, suggesting coordinated pathogen strategies for host colonization. Collectively, this study provides comprehensive multi-omics insight into the molecular mechanisms underlying A. squamosa defense against F. acutatum and offers candidate targets supported by omics evidence, serving as a theoretical reference for the management of root rot. Full article

Proteomes are typically analyzed at the level of individual proteins or protein families. In this study, we introduce a bottom-up approach that treats proteomes as holistic entities by examining the properties of k-mers within entire proteomes and protein groups. We performed a comprehensive analysis of short amino acid k-mer (k = 1, 2, 3) distributions across all proteins in a given proteome. Using 86 bacterial proteomes representing 18 clades, we evaluated whether k-mer frequencies characterize uniquely the analyzed organisms. Remarkably, in a post hoc analysis, we found that the k-mer frequency vector unambiguously coevolves with the entire proteome—a pattern not observed even within specific protein groups, such as conserved ribosomal proteins or more variable nucleotide-binding proteins. This finding holds regardless of the k-mer calculation parameters or the distance metrics employed. Our results show that even a simple analysis based on tripeptide frequencies can precisely position proteomes within the k-mer space. Moreover, relationships derived from k-mer comparisons highly correlate with evolutionary relationships derived from phylogenetic trees, reaching up to 99% match with reference classification of the proteomes within major bacterial clades. These findings establish k-mer-based proteomic analysis as an additional robust and powerful feature for characterizing evolutionary relationships, opening new pathways in phylogenetics and evolutionary genomics. Full article

Grain weight, a highly heritable yield component, is a primary breeding target for enhancing wheat productivity. Unraveling the molecular dynamics underlying grain development is essential for identifying key regulators controlling this trait. In this study, we employed an integrated multi-omics approach to analyze transcriptomic and proteomic profiles in developing grains using pairwise near-isogenic lines with contrasting grain weight across four grain developmental stages. Our analysis revealed that early grain development, particularly at 7 days post-anthesis, serves as a critical window during which differential regulation of genes and proteins involved in carbohydrate biosynthesis and metabolic pathways establishes the final grain weight. By combining weighted gene co-expression network analysis (WGCNA) and K-means clustering, we identified a grain weight-associated module and pinpointed four high-confidence candidate genes. Among these, TaYAK1-2D, which encodes a YAK family protein kinase, was functionally validated as a positive regulator of grain weight through mutational analysis. Sequence analysis revealed two major natural haplotypes of TaYAK1-2D, with TaYAK1-2D-Hap2 being significantly associated with higher grain weight across multiple environments. Our findings not only delineate a crucial metabolic window governing grain weight but also provide both a novel genetic target and a practical haplotype marker for molecular breeding aimed at yield improvement in wheat. Full article

Objective: Airway hyperresponsiveness (AHR) is a hallmark feature of asthma; however, its precise molecular mechanisms remain incompletely defined. In this study, we investigated protein expression in airway smooth muscle that may contribute to AHR, using an experimental model of ovalbumin-induced allergic asthma. Methods: Guinea pigs were sensitized and challenged with ovalbumin. Airway responsiveness to histamine was assessed, and proteomic analysis of the tracheal tissue was conducted using electrophoresis followed by MALDI/TOF-TOF mass spectrometry. Specific protein bands corresponding to the myosin phosphatase target subunit 1 (MYPT1) were analyzed, and regulatory subunit of glycogen-targeted phosphatase 1 (RG1) was further evaluated through immunohistochemistry. Results: MYPT1, previously associated with AHR, was not detected in the proteomic analysis. Interestingly, an RG1 peptide was identified. Immunohistochemistry showed a differential expression pattern was observed for the RG1 and Rho-associated protein kinase 2 (ROCK2), both of which were significantly upregulated in airway smooth muscle and positively correlated with the degree of AHR. Moreover, a significant positive correlation was observed between RG1 and ROCK2 expression levels. MYPT1 and its phosphorylated forms (Thr⁶⁹⁶ and Thr⁸⁵⁰), along with ROCK1 immunostaining, did not differ from controls. Conclusions: These findings suggest that RG1, along with ROCK2, may play an important role in airway hyperresponsiveness characteristic of asthma. Full article

Background: Patients with EGFR-mutated non-small cell lung cancer (NSCLC) respond well to EGFR tyrosine kinase inhibitors (TKIs), but current EGFR mutation profiling relies on invasive tumor biopsies. Developing less invasive approaches, particularly proteomic evaluation of circulating tumor cells (CTCs) for EGFR mutation profiling, remains crucial. Methods: A flow cytometry method for detecting EGFR^L858R-bearing CTCs was established by spiking NCI-H1975 cells into blood from cancer-naive donors. The method was then applied to blood samples from 21 NSCLC patients and 10 cancer-naive donors. Results: The gating strategy was defined by CD45⁻CK-7/8⁺CK-14/15/16/19⁻EpCAM⁺vimentin⁺EGFR^L858R, with a cut-off value of 5 cells/mL. The method yielded positive results in all seven patients with the EGFR^L858R mutation and negative results in all ten cancer-naive donors. Compared to the PCR-based reference method, the approach showed 100% positive and 71% negative agreement. Crucially, our in-house method detected EGFR^L858R-bearing CTCs in three patients initially identified as EGFR wild-type and one patient with a different EGFR mutation. The remaining samples were concordant with PCR. Notably, two patients with these discordant results received EGFR-TKIs and experienced partial responses. Conclusions: This study introduces a feasible, less invasive proteomic approach for binarily detecting EGFR mutations in CTCs, offering a novel means for patient identification. Full article

Background: Rabies is among the oldest known zoonotic viral diseases and is caused by members of the Lyssavirus genus. The prototype species, Lyssavirus rabies, effectively evades the host immune response, allowing the infection to progress unnoticed until the onset of clinical signs. At this stage, the disease is irreversible and invariably fatal, with definitive diagnosis possible only post-mortem. Given the advances in modern proteomics, this study aimed to identify potential protein biomarkers for antemortem diagnosis of rabies in dogs, which are the principal reservoir hosts of the rabies virus. Methods: Two hundred and thirty-one samples (brain tissues (BT), cerebrospinal fluids (CSF), and serum (SR) samples) were collected from apparently healthy dogs brought for slaughter for human consumption in South-East and North-Central Nigeria. All the BT were subjected to a direct fluorescent antibody test to confirm the presence of lyssavirus antigen, and 8.7% (n = 20) were positive. Protein extraction, quantification, reduction, and alkylation were followed by on-bead (HILIC) cleanup and tryptic digestion. The resulting peptides from each sample were injected into the Evosep One LC system, coupled to the timsTOF HT MS, using the standard dia-PASEF short gradient data acquisition method. Data was processed using Spectronaut^TM (v19). An unpaired t-test was performed to compare identified protein groups (proteins and their isoforms) between the rabies-infected and uninfected BT, CSF, and SR samples. Results: The study yielded 54 significantly differentially abundant proteins for the BT group, 299 for the CSF group, and 280 for the SR group. Forty-five overlapping differentially abundant proteins were identified between CSF and SR, one between BT and CSF, and two between BT and SR; none were found that overlapped all three groups. Within the BT group, 33 proteins showed increased abundance, while 21 showed decreased abundance in the rabies-positive samples. In the CSF group, 159 proteins had increased abundance and 140 had decreased abundance in the rabies-positive samples. For the SR group, 215 proteins showed increased abundance, and 65 showed decreased abundance in the rabies-positive samples. Functional enrichment analysis revealed that pathways associated with CSF, spinocerebellar ataxia, and neurodegeneration were among the significant findings. Conclusion: This study identified canonical proteins in CSF and SR that serve as candidate biomarkers for rabies infection, offering insights into neuronal dysfunction and potential tools for early diagnosis. Full article

Rare genetic ocular diseases represent a heterogeneous group of disorders that significantly impair visual function and quality of life. Despite their clinical relevance, many of these conditions remain insufficiently characterized due to complex molecular mechanisms and diagnostic limitations. Recent advances in molecular diagnostics, particularly Next-Generation Sequencing (NGS), have enabled comprehensive and accurate identification of pathogenic variants, offering novel insights into genotype–phenotype correlations and supporting precision medicine approaches. In parallel, the use of alternative biological matrices such as tear fluid has emerged as a promising non-invasive strategy for biomarker discovery and disease monitoring. Tear-based omics, including proteomics and transcriptomics, have identified diagnostic signatures and pathogenic mediators such as non-coding RNAs, microRNAs, and tRNA-derived fragments (tRFs). Among these, tRF-1001 has shown potential both as a biomarker and therapeutic target in ocular neovascular conditions through its modulation of angiogenic pathways. The objective of this review is to show the integration of two rapidly advancing yet frequently isolated fields: next-generation sequencing-based genomics and tear-fluid molecular profiling, positioning them as complementary foundations of precision ophthalmology for rare inherited retinal and optic nerve disorders. Previous reviews have mainly concentrated on either genetic diagnosis or ocular surface biomarkers separately; however, we have introduced a convergent model wherein genomic data furnish diagnostic and prognostic clarity, while tear-omics deliver dynamic, minimally invasive assessments of disease activity, treatment efficacy, and persistent neurovascular stress. By explicitly connecting these two aspects, we have delineated how multi-matrix, multi-omics approaches can expedite early diagnosis, facilitate personalized longitudinal monitoring, and direct focused treatment interventions in rare ocular genetic illnesses. Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, underscoring the urgent need for reliable biomarkers and therapeutic targets. To address this need, we focused on UDP-glucose pyrophosphorylase 2 (UGP2). Although UGP2 has been implicated in tumorigenesis across multiple cancers, its precise role and clinical significance in CRC remain poorly understood. This study aimed to comprehensively characterize UGP2 in CRC through an integrated approach encompassing proteomic screening, bioinformatics analysis, and experimental validation. We identified UGP2 as a significantly downregulated tumor-suppressive factor in CRC. Specifically, UGP2 expression was significantly downregulated in CRC tissues compared with that in normal controls and exhibited strong correlations with aggressive clinicopathological features, including lymphatic invasion, perineural invasion, and colon polyp history, and patient age. It also demonstrated high diagnostic accuracy in CRC, with an area under the receiver operating characteristic curve (AUC) of 0.990. Reduced UGP2 levels were associated with poorer overall survival and disease-specific survival. Hypermethylation of the UGP2 promoter correlated with a favorable prognosis in patients with CRC. UGP2 expression positively correlated with immune cell infiltration within the tumor microenvironment. Functionally, UGP2 knockdown increased CRC cell proliferation and migration while suppressing apoptosis. Conversely, its overexpression yielded the opposite effects, confirming UGP2’s role in constraining malignant phenotypes. Collectively, these findings establish UGP2 as a key CRC tumor suppressor whose downregulation drives malignant progression and predicts adverse clinical outcomes, suggesting its potential as a dual-purpose diagnostic and prognostic biomarker. Full article

Background: Chili pepper (Capsicum annuum L.), a globally cultivated and ancient domesticated crop, carries considerable significance in agriculture. While radiation-induced mutagenesis has found application in this crop, the mutagenic efficacy and molecular-level impacts of 7Li ion beam radiation remain poorly elucidated. Methods: We irradiated pepper with a beam of 7Li ions to create a mutant, which showed good economic traits, and phenotypic and physio-biochemical characterization were combined with proteomic and metabolomic profiling to delineate the mutagenic mechanisms. Quantitative real-time PCR (qRT-PCR) was further utilized to assess the biological impact and underlying response pathways. We used this to evaluate the biological impact and the reaction mechanisms behind it. Results: 7Li beam radiation positively influenced morphology and physiological traits, notably chlorophyll and anthocyanin content. Leveraging proteomic profiling detected 6082 proteins, including 355 differential proteins (139 upregulated, 216 downregulated), enriched in 4 KEGG pathways. Based on GO and KEGG network analysis, 250 metabolites were quantified, with 120 being differentially abundant (112 upregulated, 8 downregulated), enriched in 9 metabolic pathways. Furthermore, qRT-PCR results revealed that differentially expressed genes were consistent with the corresponding metabolomic data. Joint analysis revealed the coordinated enrichment of differential metabolites and proteins in pathways related to amino acid and carbohydrate metabolism. These findings suggest that these active pathways in pepper are related to its response to ion beam radiation. Overall, this study is a valuable resource for subsequent genomic research on peppers and 7Li ion beam radiation research. Full article

Background: The positive identification of a source of tissue as human plays an important role in various contexts. It is particularly important for investigations concerning tissue and organ trafficking, since unequivocal confirmation is required for legal proceedings involving such cases. While deoxyribonucleic (DNA) methods are considered the gold standard for tissue identification, issues such as degraded DNA or the presence of chemical preservatives can hinder performance and positive identification using DNA techniques. Objectives: The aim of this study was to develop a simple method for presumptive identification of human tissue using standard bottom-up proteomics data. Methods: We identified proteins isolated from human kidney, lung and spleen tissues by bottom-up proteomics and database search using Proteome Discoverer and Sequest HT algorithms. The list of identified proteins was sorted based on liquid chromatography (LC)–mass spectrometry (MS) data metrics such as the number of unique peptides used to identify each protein and the % sequence coverage of an identified protein to determine if any parameter would cluster proteins annotated as human in a distinct category. We found that eliminating proteins identified with fewer than two unique peptides and those with less than 5% sequence coverage resulted in a final list where at least half of the remaining proteins are annotated as human. We applied this data filtration process to blinded LC–MS/MS data from 26 previous experiments to assess accuracy. Results: Using bottom-up proteomics data and the filtration rules established, we identified tissue samples (n = 10), including kidney, spleen, lung, formalin-fixed paraffin-embedded uterus, frozen breast tissue, dry blood and dry saliva as human, and tissue (n = 16) from rat, mouse, bovine, and sheep as non-human, resulting in 100% sensitivity and specificity. Conclusions: The results demonstrate that the list of identified proteins following a standard bottom-up proteomics experiment could be filtered and potentially used as a fast and simple method for presumptive human tissue identification. Full article

Single-cell sequencing (scRNA-seq) has emerged as a pivotal technology for deciphering the complex cellular heterogeneity and tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC), positioning it as a critical tool for informing novel therapeutic strategies. This review explores how scRNA-seq reveals diverse cellular subpopulations and their functional roles within the PDAC TME, including malignant epithelial cells with transitional phenotypes, heterogeneous cancer-associated fibroblasts (CAFs), functionally distinct immune cells such as tumor-associated neutrophils (TANs) and macrophages (TAMs), and actively participating neural components like Schwann cells. These cellular constituents form specialized functional units that drive tumor progression, immune evasion, neural invasion, and therapy resistance through metabolic reprogramming, immunosuppressive signaling, and cellular plasticity. The review further examines technological advances in single-cell sequencing from 2023 to 2025, focusing on sample preprocessing innovations, multi-omics integration (combining transcriptomics with epigenomics and proteomics), spatial resolution enhancements, and customized computational tools that address PDAC-specific challenges. Clinically, single-cell sequencing enables precise cellular subtyping, identification of novel biomarkers, and development of personalized therapeutic approaches, including combination therapies targeting specific cellular subpopulations and their interactions. Despite these advances, significant challenges remain in standardizing clinical applications such as liquid biopsy for early detection and tumor microenvironment assessment for diagnostic staging, validating biomarkers like CLIC4, GAS2L1, Cytokeratins, Vimentin and N-cadherin in circulating tumor cells, and comprehensively integrating multi-omics data. Future research focusing on both technology refinement and biological validation will be essential for translating single-cell insights into improved diagnostic and therapeutic outcomes for pancreatic cancer. Full article

Background/Objectives: Urothelial carcinoma of the bladder (UCC) is a leading cause of cancer-related death globally. Given that urine is in direct contact with the tumor, it represents a highly valuable source for non-invasive molecular analysis. Methods: This study utilized liquid biopsies from 41 UCC patients and 27 non-cancerous hematuria controls to identify novel diagnostic and prognostic biomarkers via proteomic and transcriptomic analysis. Results: Urine proved to be a reliable source, yielding a mean tumor cell fraction of 0.605 (95% CI: 0.505–0.705). We identified 11 genes with concurrent alteration at both the urinary protein and mRNA levels. Notably, four upregulated markers, CYTB, C1QC, SBP1, and ANXA4, demonstrated strong diagnostic potential, with AUC values greater than 0.70. CYTB and ANXA4 were detectable even in early-stage UCC (stages Cis, I, and II). Furthermore, we identified two proteins, CATC and SPB10, that were markedly upregulated in recurrent UCC and correlated with poor overall survival, positioning them as potential prognostic markers for recurrence risk. Conclusions: This study confirms the utility of urine as a reliable medium for detecting UCC tumor cells, offering promising markers for both early-stage diagnosis and predicting NMIBC recurrence. Full article

Background/Objectives Plant lectins have emerged as potential antifungal molecules, where the carbohydrate recognition domain (CRD) is possibly the main mode of action of these proteins. Previously, we saw that the lectin extracted from the seeds of Dioclea violacea (DVL) has anti-candida activity against Candida krusei cells by acting to inhibit ergosterol biosynthesis, cell wall deformation, and deregulation of the redox system. Methods We have now confirmed this anti-candida activity by proteomic analysis, with the expression of proteins that show us how C. krusei cells respond to this treatment. Results A total of 395 proteins were identified: 142 proteins exclusively found in untreated C. krusei cells and 245 proteins exclusive to DVL-treated cells. Eight proteins were detected in both conditions. Six displayed positive accumulation (fold change > 1.5), one exhibited negative accumulation (fold change < 0.5). We observed the expression of proteins related to cell wall remodeling; alteration of energy metabolism, suggesting a metabolic adaptation to stress; oxidative stress was responded to through the expression of proteins with antioxidant action, in addition to identifying multidrug transport proteins that are often involved in the process of antifungal resistance and sterol transport to the membrane. Conclusions Our results show the complexity of adaptive responses of C. krusei cells to treatment with DVL, elucidating new mechanisms of resistance and paving the way for the development of more effective and innovative antifungal therapies. Full article

Parageobacillus thermoglucosidasius is a thermophilic Gram-positive that is emerging as a platform for bioproduction. However, one potential limitation of P. thermoglucosidasius is its natural tendency to sporulate. As a non-model organism, the complex regulatory system that governs sporulation in P. thermoglucosidasius remains poorly characterised. To advance current understanding, this study presents a comparative characterisation and proteomic analysis of the P. thermoglucosidasius wildtype strain alongside four early-stage sporulation-inhibited variants. To inhibit sporulation, the genes spo0A, spo0B, spo0F, and sigF were targeted for deletion, as based on their crucial regulatory roles in the sporulation pathway of Bacillus subtilis. Microscopic analysis indicated that the Δspo0A, Δspo0F, and ΔsigF strains were sporulation-suppressed while the Δspo0B strain sporulated at low levels. Proteomics data were obtained from four different growth stages and the resulting expression profiles were compared. Consistent with the regulatory network of B. subtilis, the Δspo0A, Δspo0B, and Δspo0F strains exhibited largely inactive sporulation pathways, while the ΔsigF strain retained some early regulatory functions. Additionally, two co-expression modules comprising approximately 300 genes were identified and linked to the P. thermoglucosidasius sporulation pathway. Overall, these results expand the understanding of the sporulation network of P. thermoglucosidasius and provide a foundation for future engineering of non-sporulating variants. Full article