J R Soc Interface. 2025 Jan;22(222):20240404. doi: 10.1098/rsif.2024.0404. Epub 2025 Jan 30.

ABSTRACT

Bond graphs provide an energy-based methodology for modelling complex systems hierarchically; at the moment, the method allows biological systems with both chemical and electrical subsystems to be modelled. Herein, the bond graph approach is extended to include chemomechanical transduction thus extending the range of biological systems to be modelled. Actin filament polymerization and force generation is used as an example of chemomechanical transduction, and it is shown that the TF (transformer) bond graph component provides a practical, and conceptually simple, alternative to the Brownian ratchet approach of Peskin, Odell, Oster and Mogilner. Furthermore, it is shown that the bond graph approach leads to the same equation as the Brownian ratchet approach in the simplest case. The approach is illustrated by showing that flexibility and non-normal incidence can be modelled by simply adding additional bond graph components and that compliance leads to non-convexity of the force-velocity curve. Energy flows are fundamental to life; for this reason, the energy-based approach is utilized to investigate the power transmission by the actin filament and its corresponding efficiency. The bond graph model is fitted to experimental data by adjusting the model physical parameters.

PMID:39881657 | DOI:10.1098/rsif.2024.0404

Environ Toxicol Chem. 2025 Jan 28:vgaf028. doi: 10.1093/etojnl/vgaf028. Online ahead of print.

ABSTRACT

Given the need to reduce animal testing for environmental risk assessment, we aim to develop a fish invitrome, an alternative fish modular framework capable of predicting chemical toxicity in fish without the use of animals. The central module of the framework is the validated RTgill-W1 cell line assay that predicts fish acute toxicity of chemicals (Organization for Economic Cooperation and Development Test Guideline (OECD TG) 249). Expanding towards prediction of chronic toxicity, the fish invitrome includes two other well-advanced modules for chemical bioaccumulation/biotransformation and inhibition of fish growth. This framework is expected to continuously evolve with the development of modules that predict, for instance, neurotoxicity and reproductive toxicity. We envisage the fish invitrome framework to become part of the broader academic field of New Approach Methodologies (NAMs), where it will remain flexible and open to integration of new developments from research groups around the world. To accelerate the development and uptake of this framework, we strive for transdisciplinarity, integrating both natural and social sciences, along with broader stakeholder interactions. A stepwise socio-technical approach has been chosen, where mainstreaming the fish invitrome involves progressive adoption across various ecotoxicological contexts. The framework will be co-designed with stakeholders from academia, industry, and regulatory bodies. Rather than aiming for immediate regulatory acceptance, this approach aims to build trust and familiarity with fish cell line-based testing among stakeholders. By doing so, it encourages broader use of the framework in practical applications while gradually overcoming institutional, cultural, and technical barriers. Additionally, establishing a clear roadmap for mainstreaming the fish invitrome will help identify and address challenges to its uptake, ensuring a smoother transition to non-organismal testing methodologies.

PMID:39880375 | DOI:10.1093/etojnl/vgaf028

Biochim Biophys Acta Gen Subj. 2025 Jan 27:130768. doi: 10.1016/j.bbagen.2025.130768. Online ahead of print.

ABSTRACT

Apolipoprotein E (apoE) polymorphism is associated with different pathologies such as atherosclerosis and Alzheimer's disease. Knowledge of the three-dimensional structure of apoE and isoform-specific structural differences are prerequisites for the rational design of small molecule structure modulators that correct the detrimental effects of pathological isoforms. In this study, cross-linking mass spectrometry (XL-MS) targeting Asp, Glu and Lys residues was used to explore the intramolecular interactions in the E2, E3 and E4 isoforms of apoE. The resulting quantitative XL-MS data combined with molecular modeling revealed isoform-specific characteristics of the N- and C-terminal domain interfaces as well as the isoform-dependent dynamic equilibrium of these interfaces. Finally, the data identified a network of salt bridges formed by R61-R112-E109 residues in the N-terminal helical bundle as a modulator of the interaction with the C-terminal domain making this network a potential drug target.

PMID:39880049 | DOI:10.1016/j.bbagen.2025.130768

Curr Biol. 2025 Jan 23:S0960-9822(24)01707-X. doi: 10.1016/j.cub.2024.12.039. Online ahead of print.

ABSTRACT

Yeasts are a diverse group of unicellular fungi that have developed a wide array of phenotypes and traits over 400 million years of evolution. However, we still lack an understanding of the biological principles governing the range of cell morphologies, metabolic modes, and reproductive strategies yeasts display. In this study, we explored the relationship between cell morphology and metabolism in sixteen yeast strains across eleven species. We performed a quantitative analysis of the physiology and morphology of these strains and discovered a strong correlation between the glucose uptake rate (GUR) and the surface-area-to-volume ratio. 14C-glucose uptake experiments demonstrated that the GUR for a given strain is governed either by glucose transport capacity or glycolytic rate, indicating that it is rather the rate of glucose metabolism in general that correlates with cell morphology. Furthermore, perturbations in glucose metabolism influenced cell sizes, whereas manipulating cell size did not affect GUR, suggesting that glucose metabolism determines cell size rather than the reverse. Across the strains tested, we also found that the rate of glucose metabolism influenced ethanol production rate, biomass yield, and carbon dioxide transfer rate. Overall, our findings demonstrate that the rate of glucose metabolism is a key factor shaping yeast cell morphology and physiology, offering new insights into the fundamental principles of yeast biology.

PMID:39879976 | DOI:10.1016/j.cub.2024.12.039

Mar Pollut Bull. 2025 Jan 28;212:117615. doi: 10.1016/j.marpolbul.2025.117615. Online ahead of print.

ABSTRACT

The Strait of Sicily, a vital marine passage with diverse fauna, is seeing a steep rise in the planning of offshore wind farm projects. This study assesses the acoustic impact of these wind farms on local marine species. Underwater propagation was modeled for three proposed floating wind farms using JASCO's Marine Operations Noise Model (MONM), which integrates a parabolic equation method for frequencies from 10 to 800 Hz and a beam-tracing model for 1 to 25 kHz. Propagation losses were calculated in one-third octave bands for ten source locations selected to represent the variability in bathymetry, and considering sound speed profiles for February and August. Sound levels from floating turbines were used to estimate exceedance ranges to known acoustic thresholds for marine species. Modeling indicated that sound levels could exceed temporary threshold shift and, for some species, permanent threshold shift criteria within a few tens of meters, but only if animals were to remain for 24 h at such small distances from a turbine. Behavioral disturbance thresholds for marine mammals were exceeded up to 68 km from the wind farms' boundaries. The study emphasizes considering species-specific sensitivities and ecological contexts in environmental impact assessments, recommending mitigation measures, such as the strategic placement of the turbines and continuous monitoring, to minimize adverse effects on local marine fauna, including marine mammals and turtles.

PMID:39879849 | DOI:10.1016/j.marpolbul.2025.117615

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