Stem Cell Res. 2025 Jan 15;83:103660. doi: 10.1016/j.scr.2025.103660. Online ahead of print.

ABSTRACT

NHD/PLOSL is an orphan disease characterized by progressive presenile dementia associated with recurrent fractures due to polycystic bone lesions. In this study, we generated the human induced pluripotent stem cell (hiPSC) line BIHi292-A from a 30-year-old women diagnosed with NHD/PLOSL, carrying two compound heterozygous frameshift mutations [c.313del (p.Ala105fs) and c.199del (p.His67fs)] in the TREM2 (triggering receptor expressed on myeloid cells 2) gene. BIHi292-A hiPSCs are karyotypically normal, express typical markers for the undifferentiated state and have pluripotent differentiation potential. BIHi292-A cells will provide a valuable tool for investigating pathogenic mechanisms of NHD/PLOSL and TREM2-related research questions.

PMID:39879812 | DOI:10.1016/j.scr.2025.103660

Brief Bioinform. 2024 Nov 22;26(1):bbaf039. doi: 10.1093/bib/bbaf039.

ABSTRACT

Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks. We validated our method effectiveness through a comparative study using a simulated dataset and RNA-Seq data from The Cancer Genome Atlas breast cancer dataset. Our method was benchmarked against traditional techniques (ORA, FCS), shallow machine learning models (logistic regression, support vector machine), and deep learning approaches (DeepHisCom, PASNet). The results demonstrate that GPNet outperforms these methods in low-SNR, large-sample datasets, where it remains robust and reliable, significantly reducing both Type I error and improving power. This makes our method well suited for pathway analysis in large, multi-center studies. The code can be found at https://github.com/haolu123/GPNet_pathway">https://github.com/haolu123/GPNet_pathway.

PMID:39879387 | DOI:10.1093/bib/bbaf039

PLoS One. 2025 Jan 29;20(1):e0314288. doi: 10.1371/journal.pone.0314288. eCollection 2025.

ABSTRACT

BACKGROUND: Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data. Because of the variability in how phenotypic data was collected by the various BD studies over the years, homogenizing this subphenotypic data is a challenging task, and so is replication. An alternative methodology, taken here, is to set aside the intricacies of subphenotype and allow the genetic data itself to determine which subjects define a homogeneous genetic subgroup (termed 'bicluster' below).

RESULTS: In this paper, we leverage recent advances in heterogeneity analysis to look for genetically-driven subgroups (i.e., biclusters) within the broad phenotype of Bipolar Disorder. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN) within the Psychiatric Genomics Consortium (PGC). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This disease-specific genetic pattern (i.e., 'genetic subgroup') replicates across the remaining data-sets collected by the PGC containing 5781/8289, 3581/7591, and 6825/9752 cases/controls, respectively. This genetic subgroup (discovered without using any BD subtype information) was more prevalent in Bipolar type-I than in Bipolar type-II.

CONCLUSIONS: Our methodology has successfully identified a replicable homogeneous genetic subgroup of bipolar disorder. This subgroup may represent a collection of correlated genetic risk-factors for BDI. By investigating the subgroup's bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve risk prediction. This improvement is particularly notable when using only a relatively small subset of the available SNPs, implying improved SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity.

PMID:39879180 | DOI:10.1371/journal.pone.0314288

J Biol Rhythms. 2025 Jan 29:7487304241310923. doi: 10.1177/07487304241310923. Online ahead of print.

ABSTRACT

The nature of biological research is changing, driven by the emergence of big data, and new computational models to parse out the information therein. Traditional methods remain the core of biological research but are increasingly either augmented or sometimes replaced by emerging data science tools. This presents a profound opportunity for those circadian researchers interested in incorporating big data and related analyses into their plans. Here, we discuss the emergence of novel sources of big data that could be used to gain real-world insights into circadian biology. We further discuss technical considerations for the biologist interested in including data science approaches in their research. We conversely discuss the biological considerations for data scientists so that they can more easily identify the nuggets of biological rhythms insight that might too easily be lost through application of standard data science approaches done without an appreciation of the way biological rhythms shape the variance of complex data objects. Our hope is that this review will make bridging disciplines in both directions (biology to computational and vice versa) easier. There has never been such rapid growth of cheap, accessible, real-world research opportunities in biology as now; collaborations between biological experts and skilled data scientists have the potential to mine out new insights with transformative impact.

PMID:39878301 | DOI:10.1177/07487304241310923

Front Plant Sci. 2025 Jan 14;15:1525729. doi: 10.3389/fpls.2024.1525729. eCollection 2024.

ABSTRACT

The formation of the female germline is the fundamental process in most flowering plants' sexual reproduction. In Arabidopsis, only one somatic cell obtains the female germline fate, and this process is regulated by different pathways. Megaspore mother cell (MMC) is the first female germline, and understanding MMC development is essential for comprehending the complex mechanisms of plant reproduction processes. Recently, more advanced technologies such as whole-mount single-molecule fluorescence in situ hybridization (smFISH), laser-assisted microdissection (LCM), chromatin immunoprecipitation/sequencing, and CRISPR gene editing have provided opportunities to reveal the mechanism of female germline development at different stages. Single-cell transcriptome/spatial transcriptomics analysis helps to investigate complex cellular systems at the single-cell level, reflecting the biological complexity of different cell types. In this review, we highlight recent progress that facilitates the development of the female germline to explore the roles of crucial gene regulatory networks, epigenetic pathways, cell-cycle regulators, and phytohormones in this process. This review discusses three key phases in female germline development and provides the possibility of distinct pathways restricting germline development in the future.

PMID:39877734 | PMC:PMC11773337 | DOI:10.3389/fpls.2024.1525729

Heliyon. 2025 Jan 10;11(2):e41610. doi: 10.1016/j.heliyon.2024.e41610. eCollection 2025 Jan 30.

ABSTRACT

BACKGROUND: Normothermic machine perfusion (NMP) provides a platform for kidney quality assessment. Donation after circulatory death (DCD) donor kidneys are associated with great ischemic injury and high intrarenal resistance (IRR). This experimental study aims to investigate the impact of different perfusion pressures on marginal kidney function and injury during NMP.

METHODS: Twenty-seven slaughterhouse porcine kidneys were retrieved and subjected to 60 min of warm ischemia time to mimic DCD condition. These kidneys were randomized into 75 mmHg (subphysiological, n = 9), 95 mmHg (physiological, n = 9), and 115 mmHg NMP (high physiological, n = 9). Renal function and injury were assessed during NMP.

RESULTS: Three groups showed comparable IRR, with the 115 mmHg group exhibiting the highest blood flow. The 95 mmHg group [0.48 (0.36-1.15) ml/min/100g] and 115 mmHg group [0.93 (0.45-1.41) ml/min/100g] showed significantly higher creatinine clearance compared to the 75 mmHg group [0.16 (0.08-0.37) ml/min/100g] during the first hour of NMP (p = 0.049, p = 0.009, respectively). The 115 mmHg group exhibited significantly higher oxygen consumption compared to the 75 mmHg group at 30 min of NMP [1.37 (1.05-1.92) versus 0.72 (0.61-0.82) mlO2/min/100g, p = 0.009]. Perfusate neutrophil gelatinase-associated lipocalin (NGAL) levels were consistently lowest in the 95 mmHg group and highest in the 75 mmHg group. Aspartate aminotransferase (AST) levels of the 115 mmHg group were significantly higher than the 75 mmHg group.

CONCLUSIONS: For kidneys with high IRR, both 95 mmHg and 115 mmHg perfusion pressures enable an early improvement in renal hemodynamics and function compared to 75 mmHg during NMP, while a high physiological perfusion can cause additional injury.

PMID:39877618 | PMC:PMC11773052 | DOI:10.1016/j.heliyon.2024.e41610

Res Sq [Preprint]. 2025 Jan 17:rs.3.rs-5629379. doi: 10.21203/rs.3.rs-5629379/v1.

ABSTRACT

Antigen processing and presentation via major histocompatibility complex (MHC) molecules are central to immune surveillance. Yet, quantifying the dynamic activity of MHC class I and II antigen presentation remains a critical challenge, particularly in diseases like cancer, infection and autoimmunity where these pathways are often disrupted. Current methods fall short in providing precise, sample-specific insights into antigen presentation, limiting our understanding of immune evasion and therapeutic responses. Here, we present PSAA (PINN-empowered Systems Biology Analysis of Antigen Presentation Activity), which is designed to estimate sample-wise MHC class I and class II antigen presentation activity using bulk, single-cell, and spatially resolved transcriptomics or proteomics data. By reconstructing MHC pathways and employing pathway flux estimation, PSAA offers a detailed, stepwise quantification of MHC pathway activity, enabling predictions of gene-specific impacts and their downstream effects on immune interactions. Benchmarked across diverse omics datasets and experimental validations, PSAA demonstrates a robust prediction accuracy and utility across various disease contexts. In conclusion, PSAA and its downstream functions provide a comprehensive framework for analyzing the dynamics of MHC antigen presentation using omics data. By linking antigen presentation to immune cell activity and clinical outcomes, PSAA both elucidates key mechanisms driving disease progression and uncovers potential therapeutic targets.

PMID:39877095 | PMC:PMC11774464 | DOI:10.21203/rs.3.rs-5629379/v1

Nucleic Acids Res. 2025 Jan 24;53(3):gkaf001. doi: 10.1093/nar/gkaf001.

ABSTRACT

Cell fate determination at the chromatin level is not fully comprehended. Here, we report that c-JUN acts on chromatin loci to limit mesoderm cell fate specification as cells exit pluripotency. Although c-JUN is widely expressed across various cell types in early embryogenesis, it is not essential for maintaining pluripotency. Instead, it functions as a repressor to constrain mesoderm development while having a negligible impact on ectoderm differentiation. c-JUN interacts with MBD3-NuRD complex, which helps maintain chromatin in a low accessibility state at mesoderm-related genes during the differentiation of human pluripotent stem cells into mesoderm. Furthermore, c-JUN specifically inhibits the activation of key mesoderm factors, such as EOMES and GATA4. Knocking out c-JUN or inhibiting it with a JNK inhibitor can alleviate this suppression, promoting mesoderm cell differentiation. Consistently, knockdown of MBD3 enhances mesoderm generation, whereas MBD3 overexpression impedes it. Overexpressing c-JUN redirects differentiation toward a fibroblast-like lineage. Collectively, our findings suggest that c-JUN acts as a chromatin regulator to restrict the mesoderm cell fate.

PMID:39876710 | DOI:10.1093/nar/gkaf001

Protein Sci. 2025 Feb;34(2):e5163. doi: 10.1002/pro.5163.

ABSTRACT

Amyloid fibril formation of α-synuclein (αSN) is a hallmark of synucleinopathies. Although the previous studies have provided numerous insights into the molecular basis of αSN amyloid formation, it remains unclear how αSN self-assembles into amyloid fibrils in vivo. Here, we show that αSN amyloid formation is accelerated in the presence of two macromolecular crowders, polyethylene glycol (PEG) (MW: ~10,000) and dextran (DEX) (MW: ~500,000), with a maximum at approximately 7% (w/v) PEG and 7% (w/v) DEX. Under these conditions, the two crowders induce a two-phase separation of upper PEG and lower DEX phases with a small number of liquid droplets of DEX and PEG in PEG and DEX phases, respectively. Fluorescence microscope images revealed that the interfaces of DEX droplets in the upper PEG phase are the major sites of amyloid formation. We consider that the depletion interactions working in micro phase-segregated state with DEX and PEG systems causes αSN condensation at the interface between solute PEG and DEX droplets, resulting in accelerated amyloid formation. Ultrasonication further accelerated the amyloid formation in both DEX and PEG phases, confirming the droplet-dependent amyloid formation. Similar PEG/DEX-dependent accelerated amyloid formation was observed for amyloid β peptide. In contrast, amyloid formation of β2-microglobulin or hen egg white lysozyme with a native fold was suppressed in the PEG/DEX mixtures, suggesting that the depletion interactions work adversely depending on whether the protein is unfolded or folded.

PMID:39876094 | DOI:10.1002/pro.5163

Virol J. 2025 Jan 28;22(1):19. doi: 10.1186/s12985-025-02636-7.

ABSTRACT

Infection with Influenza A virus (IAV) induces severe inflammatory responses and lung injury, contributing significantly to mortality and morbidity rates. Alterations in the microbial composition of the lungs and intestinal tract resulting from infection could influence disease progression and treatment outcomes. Xiyanping (XYP) injection has demonstrated efficacy in clinical treatment across various viral infections. However, its specific effects and mechanisms against IAV remain unclear. In this study, we established an IAV infection mice model, and utilized 16 S rRNA sequencing, RNA sequencing, protein chips, and molecular docking, to investigate the mechanisms of XYP injection on altering pulmonary and gut microbiota, and identifying its target sites. We revealed that XYP injection significantly reduced mortality, weight loss, lung viral titers, and lung pathology in IAV-infected mice. XYP injection down-regulated the activity of malondialdehyde, and the levels of interleukin (IL)-1β, IL-5, IL-6, tumor necrosis factor-α, IL-18, IL-15, granulocyte colony-stimulating factor, IL-9, chemokine (C-C motif) ligand-5, and C-X-C motif chemokine ligand 5, while up-regulated the activities of glutathione peroxidase reactive and superoxide dismutase, and the level of interferon-γ. The diversity of the pulmonary and gut microbiota was altered slightly after XYP injection. The linear discriminant analysis of the gut microbes revealed a higher proportion of potentially beneficial bacteria, including Akkermansia, Parabacteroides goldsteinii, Defluviitaleaceae, Oscillospirales, and Eubacterium_coprostanoligenes_group characterized the XYP group. Peritoneal macrophage RNA sequencing highlighted Serpinb2 as the most significantly regulated gene by XYP injection, along with consistent changes in multiple downstream Th2 structure genes. KEGG pathway analysis indicated significant modifications in genes associated with influenza A, mitogen-activated protein kinase signaling, nuclear factor kappa-B signaling, and apoptosis following XYP injection. Finally, human protein chips and molecular docking were carried out to confirm the binding of the main component of XYP injection, andrographolide, with SERPINB2/PAI-2 protein. Overall, our study provides valuable insights into the therapeutic potential of XYP injection in treating influenza, highlighting its multifaceted effects on host microbiota and immune responses, and pinpointing SerpinB2/PAI-2 as the target for XYP injection in exerting anti-inflammatory and antiviral therapeutic mechanisms.

PMID:39875956 | DOI:10.1186/s12985-025-02636-7

BMC Mol Cell Biol. 2025 Jan 28;26(1):7. doi: 10.1186/s12860-025-00532-0.

ABSTRACT

This paper describes a method for determining the cytotoxicity of chemical compounds based on the detection of fluorescent proteins-in this case, green fluorescent protein (GFP) and red fluorescent protein (RFP), which are released into the medium from dead cells. This method is similar in principle to the lactate dehydrogenase test (LDH test), but it does not require a reaction with a chromogenic substrate. This method also makes it possible to independently determine the viability of different lines when used in cocultures. Experiments were performed on a classical monolayer, spheroids and 3D cultures in alginate hydrogel. Capecitabine was used as a model cytotoxic agent. We included liver cells (Huh7) in a coculture model and determined changes in the cytotoxicity levels of capecitabine against NCI-H1299 cells. The experimental part also found that there were differences in sensitivity to capecitabine depending on the type of 3D cultures used.

PMID:39875861 | DOI:10.1186/s12860-025-00532-0

EMBO J. 2025 Jan 28. doi: 10.1038/s44318-025-00368-6. Online ahead of print.

ABSTRACT

Na+-K+-Cl- cotransporters functions as an anion importers, regulating trans-epithelial chloride secretion, cell volume, and renal salt reabsorption. Loop diuretics, including furosemide, bumetanide, and torsemide, antagonize both NKCC1 and NKCC2, and are first-line medicines for the treatment of edema and hypertension. NKCC1 activation by the molecular crowding sensing WNK kinases is critical if cells are to combat shrinkage during hypertonic stress; however, how phosphorylation accelerates NKCC1 ion transport remains unclear. Here, we present co-structures of phospho-activated NKCC1 bound with furosemide, bumetanide, or torsemide showing that furosemide and bumetanide utilize a carboxyl group to coordinate and co-occlude a K+, whereas torsemide encroaches and expels the K+ from the site. We also found that an amino-terminal segment of NKCC1, once phosphorylated, interacts with the carboxyl-terminal domain, and together, they engage with intracellular ion exit and appear to be poised to facilitate rapid ion translocation. Together, these findings enhance our understanding of NKCC-mediated epithelial ion transport and the molecular mechanisms of its inhibition by loop diuretics.

PMID:39875725 | DOI:10.1038/s44318-025-00368-6

Nat Biotechnol. 2025 Jan 28. doi: 10.1038/s41587-024-02524-5. Online ahead of print.

ABSTRACT

Understanding a small molecule's mode of action (MoA) is essential to guide the selection, optimization and clinical development of lead compounds. In this study, we used high-throughput non-targeted metabolomics to profile changes in 2,269 putative metabolites induced by 1,520 drugs in A549 lung cancer cells. Although only 26% of the drugs inhibited cell growth, 86% caused intracellular metabolic changes, which were largely conserved in two additional cancer cell lines. By testing more than 3.4 million drug-metabolite dependencies, we generated a lookup table of drug interference with metabolism, enabling high-throughput characterization of compounds across drug therapeutic classes in a single-pass screen. The identified metabolic changes revealed previously unknown effects of drugs, expanding their MoA annotations and potential therapeutic applications. We confirmed metabolome-based predictions for four new glucocorticoid receptor agonists, two unconventional 3-hydroxy-3-methylglutaryl-CoA (HMGCR) inhibitors and two dihydroorotate dehydrogenase (DHODH) inhibitors. Furthermore, we demonstrated that metabolome profiling complements other phenotypic and molecular profiling technologies, opening opportunities to increase the efficiency, scale and accuracy of preclinical drug discovery.

PMID:39875672 | DOI:10.1038/s41587-024-02524-5

World J Microbiol Biotechnol. 2025 Jan 29;41(2):53. doi: 10.1007/s11274-025-04260-7.

ABSTRACT

The photoautotrophic nature of cyanobacteria, coupled with their fast growth and relative ease of genetic manipulation, makes these microorganisms very promising factories for the sustainable production of bio-products from atmospheric carbon dioxide. However, both in nature and in cultivation, cyanobacteria go through different abiotic stresses such as high light (HL) stress, heavy metal stress, nutrient limitation, heat stress, salt stress, oxidative stress, and alcohol stress. In recent years, significant improvement has been made in identifying the stress-responsive genes and the linked pathways in cyanobacteria and developing genome editing tools for their manipulation. Metabolic pathways play an important role in stress tolerance; their modification is also a very promising approach to adapting to stress conditions. Several synthetic as well as systems biology approaches have been developed to identify and manipulate genes regulating cellular responses under different stresses. In this review, we summarize the impact of different stresses on metabolic processes, the small RNAs, genes and heat shock proteins (HSPs) involved, changes in the metabolome and their adaptive mechanisms. The developing knowledge of the adaptive behaviour of cyanobacteria may also be utilised to develop better stress-responsive strains for various applications.

PMID:39875631 | DOI:10.1007/s11274-025-04260-7

Commun Biol. 2025 Jan 28;8(1):131. doi: 10.1038/s42003-025-07586-y.

ABSTRACT

Rapid structural analysis of purified proteins and their complexes has become increasingly common thanks to key methodological advances in cryo-electron microscopy (cryo-EM) and associated data processing software packages. In contrast, analogous structural analysis in cells via cryo-electron tomography (cryo-ET) remains challenging due to critical technical bottlenecks, including low-throughput sample preparation and imaging, and laborious data processing methods. Here, we describe a rapid in situ cryo-ET sample preparation and data analysis workflow that results in the routine determination of sub-nm resolution ribosomal structures. We apply this workflow to E. coli, producing a 5.8 Å structure of the 70S ribosome from cells in less than 10 days and facilitating the discovery of a minor population of 100S-like disomes. We envision our approach to be widely applicable to related bacterial samples.

PMID:39875527 | DOI:10.1038/s42003-025-07586-y

Sci Rep. 2025 Jan 28;15(1):3549. doi: 10.1038/s41598-025-86242-1.

ABSTRACT

SARS-CoV-2 is a viral infection, best studied in the context of epithelial cell infection. Epithelial cells, when infected with SARS-CoV-2 express the viral S-protein, which causes host cells to fuse together into large multi-nucleated cells known as syncytia. Because SARS-CoV-2 infections also frequently present with cardiovascular phenotypes, we sought to understand if S-protein expression would also result in syncytia formation in endothelial cells. S-protein expression in endothelial cells was sufficient to induce the formation of multi-nucleated cells, with an average of 10% of all cells forming syncytia with an average of 6 nuclei per syncytia after 72 h of S-protein expression. Formation of syncytia was associated with the formation of gaps between cells, suggesting the potential for syncytia formation to compromise barrier function. Inhibition of myosin light chain kinase (MLCK), but not Rho-associated protein kinase, inhibited the formation of syncytia, suggesting a role for MLCK in syncytia formation. Further supporting the role of cellular contractility in syncytia formation, we also observed a reduction in the occurrence of syncytia for endothelial cells grown on substrates with reduced stiffness. Because endothelial cells are exposed to physiological forces due to blood flow, we examined the effects of cyclic biaxial stretch and fluid shear stress. While biaxial stretch did not affect syncytia formation, endothelial cells exposed to fluid shear stress were more resistant to syncytia formation. Finally, we observed that endothelial cells are suitable host cells for SARS-CoV-2 viral infection and replication, and that viral infection also causes syncytia formation. Our studies indicate that endothelial cells, in addition to epithelial cells, should also be considered a target for SARS-CoV-2 infection and a driver of COVID-19-associated pathology.

PMID:39875448 | DOI:10.1038/s41598-025-86242-1

NPJ Syst Biol Appl. 2025 Jan 28;11(1):12. doi: 10.1038/s41540-025-00494-1.

ABSTRACT

Cancer-associated fibroblasts (CAFs) play a key role in metabolic reprogramming and are well-established contributors to drug resistance in colorectal cancer (CRC). To exploit this metabolic crosstalk, we integrated a systems biology approach that identified key metabolic targets in a data-driven method and validated them experimentally. This process involved a novel machine learning-based method to computationally screen, in a high-throughput manner, the effects of enzyme perturbations predicted by a computational model of CRC metabolism. This approach reveals the network-wide effects of metabolic perturbations. Our results highlighted hexokinase (HK) as a crucial target, which subsequently became our focus for experimental validation using patient-derived tumor organoids (PDTOs). Through metabolic imaging and viability assays, we found that PDTOs cultured in CAF-conditioned media exhibited increased sensitivity to HK inhibition, confirming the model predictions. Our approach emphasizes the critical role of integrating computational and experimental techniques in exploring and exploiting CRC-CAF crosstalk.

PMID:39875420 | DOI:10.1038/s41540-025-00494-1

Nat Commun. 2025 Jan 28;16(1):1113. doi: 10.1038/s41467-025-56251-9.

ABSTRACT

Complete blood count indices and their ratios are associated with adverse clinical outcomes for many acute illnesses, but the mechanisms generating these associations are not fully understood. Recent identification of a consistent pattern of white blood cell and platelet count co-regulation during acute inflammatory recovery provides a potentially unifying explanation. Here we show that the platelet-to-white-cell ratio, which was selected based on this conserved recovery pattern, is more strongly associated with mortality than other blood count markers and ratios in four important illnesses involving acute inflammation: COVID-19, acute heart failure, myocardial infarction, and stroke. Patients recovering well from these acute illnesses tend to follow a joint white cell and platelet trajectory that can be reduced to this one-dimensional ratio. The platelet-to-white-cell ratio's association with prognosis is consistent with recently identified inflammatory dynamics and may provide a convenient and interpretable summary of patient inflammatory state.

PMID:39875373 | DOI:10.1038/s41467-025-56251-9

Cell Rep Methods. 2025 Jan 27;5(1):100963. doi: 10.1016/j.crmeth.2024.100963.

ABSTRACT

Identifying key regulators of important genes in non-model crop species is challenging due to limited multi-omics resources. To address this, we introduce the network-enabled gene discovery pipeline NEEDLE, a user-friendly tool that systematically generates coexpression gene network modules, measures gene connectivity, and establishes network hierarchy to pinpoint key transcriptional regulators from dynamic transcriptome datasets. After validating its accuracy with two independent datasets, we applied NEEDLE to identify transcription factors (TFs) regulating the expression of cellulose synthase-like F6 (CSLF6), a crucial cell wall biosynthetic gene, in Brachypodium and sorghum. Our analyses uncover regulators of CSLF6 and also shed light on the evolutionary conservation or divergence of gene regulatory elements among grass species. These results highlight NEEDLE's capability to provide biologically relevant TF predictions and demonstrate its value for non-model plant species with dynamic transcriptome datasets.

PMID:39874949 | DOI:10.1016/j.crmeth.2024.100963

J Proteome Res. 2025 Jan 28. doi: 10.1021/acs.jproteome.4c01109. Online ahead of print.

ABSTRACT

The E3 ubiquitin ligase neural precursor cell-expressed developmentally down-regulated 4 (NEDD4) is involved in various cancer signaling pathways, including PTEN/AKT. However, its role in promoting gastric cancer (GC) progression is unclear. This study was conducted to elucidate the role of NEDD4 in GC progression. We found that the inhibition of NEDD4 expression significantly reduced the migratory and proliferative abilities of GC cells, with minimal impact on the PTEN expression or p-AKT activation, suggesting that NEDD4 may exert its GC-promoting effects through alternative pathways. To gain novel insights into the role of NEDD4 in GC, we performed a comprehensive proteomic analysis to search for proteins with altered expression levels following NEDD4 gene knockdown, identifying a total of 3916 proteins. Pathway analysis of differentially expressed proteins (DEPs) indicated the potential involvement of NEDD4 in cancer-related metabolic pathways. Furthermore, the protein-protein interaction network of the DEPs revealed enriched core modules, highlighting key cellular processes and signaling pathways regulated by NEDD4 in GC. Additionally, we identified proteins whose expression was altered by NEDD4 inhibition, some of which were associated with poor prognosis in GC. These findings suggest that these proteins may act as downstream effectors that contribute to NEDD4-mediated GC progression.

PMID:39874481 | DOI:10.1021/acs.jproteome.4c01109