Sci Rep. 2024 Dec 18;14(1):30541. doi: 10.1038/s41598-024-80498-9.

ABSTRACT

When infected with SARS-CoV-2, Syrian hamsters (Mesocricetus auratus) develop moderate disease severity presenting key features of human COVID-19. We here develop a biomathematical model of the disease course by translating known biological mechanisms of virus-host interactions and immune responses into ordinary differential equations. We explicitly describe the dynamics of virus population, affected alveolar epithelial cells, and involved relevant immune cells comprising for example CD4+ T cells, CD8+ T cells, macrophages, natural killer cells and B cells. We also describe the humoral response dynamics of neutralising antibodies and major regulatory cytokines including CCL8 and CXCL10. The model is developed and parametrized based on experimental data collected at days 2, 3, 5, and 14 post infection. Pulmonary cell composition and their transcriptional profiles were obtained by lung single-cell RNA (scRNA) sequencing analysis. Parametrization of the model resulted in a good agreement of model and data. The model can be used to predict, for example, the time course of the virus population, immune cell dynamics, antibody production and regeneration of alveolar cells for different therapy scenarios or after multiple-infection events. We aim to translate this model to the human situation in the future.

PMID:39695178 | DOI:10.1038/s41598-024-80498-9

Brain Res. 2024 Dec 16:149403. doi: 10.1016/j.brainres.2024.149403. Online ahead of print.

ABSTRACT

BACKGROUND: Epilepsy affects nearly 50 million people worldwide. Previous studies have indicated the neuroprotective effects of statin on several neuropathological conditions. However, it is very much unknown whether fluvastatin was able to alter the seizure types related to neuronal excitability and progression mediated by NMDA receptor activation, and the mechanisms involved in these actions are not completely understood so far. Our study evaluated the effects of fluvastatin on the NMDA-induced seizure, BKCa channels activity, NMDA receptor activation opens BKCa current, sodium channel current, NMDA receptor-mediated current, and hyperexcitable neuronal activity associated with activation of NMDA receptor.

METHODS: The effects of fluvastatin on seizure thresholds induced by NMDA were monitored in mice. The cell-attached and whole-cell patch-clamp recordings were applied to evaluate the ionic currents and action potentials of rCN or SHSY5Y neuroblastoma cells.

RESULTS: The results of our study have demonstrated that fluvastatin did increase the NMDA-induced seizure threshold and suppressed the frequency of action potentials induced by NMDA. Notably, our findings provide the evidence that fluvastatin exhibits inhibitory effects on NMDA receptor-mediated current, BKCa channels currents, NMDA receptor activation opens BKCa current, and sodium channel currents in rCN and SHSY5Y neuroblastoma cells.

CONCLUSION: Our findings suggested that fluvastatin may protect against seizure types related to neuronal excitability and NMDA receptor activation by inhibiting NMDA-mediated action potentials, NMDA receptor-mediated currents, BKCa channels, and sodium channels.

PMID:39694167 | DOI:10.1016/j.brainres.2024.149403

J Pharmacol Toxicol Methods. 2024 Dec 17;131:107571. doi: 10.1016/j.vascn.2024.107571. Online ahead of print.

ABSTRACT

Immunotoxins are genetically engineered recombinant proteins consisting of a targeting moiety, such as an antibody, and a cytotoxic toxin moiety of microbial origin. Pseudomonas exotoxin A and diphtheria toxin (DT) have been abundantly used in immunotoxins, with the latter applied as the toxin moiety of the FDA-approved drug Denileukin diftitox (ONTAK®). However, the use of immunotoxins provokes an adverse immune response in the host body against the toxin moiety, limiting their efficacy. In silico approaches have received increasing attention in protein engineering. In this study, the epitopes responsible for immunogenicity were identified through multiple platforms. By subtracting conserved and ligand-binding residues, K33, T111, and E112 were identified as common epitopes across all platforms. Substitution analysis evaluated alternative residues regarding their impact on protein stability, considering 19 different amino acid substitutions. Among the mutants explored, the T111A-E112G mutant exhibited the most destabilizing substitution for DT, thereby reducing immunogenicity. Finally, a 3D model of the mutant was generated and verified. The model was then docked with its native ligand NADH, and the complex's molecular behavior was simulated using molecular dynamics.

PMID:39693813 | DOI:10.1016/j.vascn.2024.107571

NPJ Genom Med. 2024 Dec 18;9(1):65. doi: 10.1038/s41525-024-00456-2.

ABSTRACT

Whole genome sequencing has transformed rare disease research; however, 50-80% of rare disease patients remain undiagnosed after such testing. Regular reanalysis can identify new diagnoses, especially in newly discovered disease-gene associations, but efficient tools are required to support clinical interpretation. Exomiser, a phenotype-driven variant prioritisation tool, fulfils this role; within the 100,000 Genomes Project (100kGP), diagnoses were identified after reanalysis in 463 (2%) of 24,015 unsolved patients after previous analysis for variants in known disease genes. However, extensive manual interpretation was required. This led us to develop a reanalysis strategy to efficiently reveal candidates from recent disease gene discoveries or newly designated pathogenic/likely pathogenic variants. Optimal settings to highlight new candidates from Exomiser reanalysis were identified with high recall (82%) and precision (88%) when including Exomiser's automated ACMG/AMP classifier, which correctly converted 92% of variants from unknown significance to pathogenic/likely pathogenic. In conclusion, Exomiser efficiently reinterprets previously unsolved cases.

PMID:39695184 | DOI:10.1038/s41525-024-00456-2

Hematol Oncol Clin North Am. 2024 Dec 17:S0889-8588(24)00148-5. doi: 10.1016/j.hoc.2024.11.003. Online ahead of print.

ABSTRACT

Gene expression signatures (GES) are a powerful tool in oncology used for classification, prognostication, and therapeutic response prediction of malignancies. In this article, we review the disease site guidelines by the National Comprehensive Cancer Network that use GES for treatment planning and clinical use. We identified 4 cancer types for which treatment decisions are frequently influenced by GES. Future developments in the field of GES are likely to include expanded data sources to personalize radiation therapy dosing and predict response to immunotherapy. Ongoing challenges in GES may be addressed to ensure that all patients with cancer benefit from precision oncology.

PMID:39694780 | DOI:10.1016/j.hoc.2024.11.003

Cell Mol Gastroenterol Hepatol. 2024 Dec 16:101442. doi: 10.1016/j.jcmgh.2024.101442. Online ahead of print.

NO ABSTRACT

PMID:39694413 | DOI:10.1016/j.jcmgh.2024.101442

Cell. 2024 Dec 12:S0092-8674(24)01324-2. doi: 10.1016/j.cell.2024.11.007. Online ahead of print.

ABSTRACT

Long-term durable remission in patients with B cell malignancies following chimeric antigen receptor (CAR)-T cell immunotherapy remains unsatisfactory, often due to antigen escape. Malignant B cell transformation and oncogenic growth relies on efficient ATP synthesis, although the underlying mechanisms remain unclear. Here, we report that YTHDF2 facilitates energy supply and antigen escape in B cell malignancies, and its overexpression alone is sufficient to cause B cell transformation and tumorigenesis. Mechanistically, YTHDF2 functions as a dual reader where it stabilizes mRNAs as a 5-methylcytosine (m5C) reader via recruiting PABPC1, thereby enhancing their expression and ATP synthesis. Concomitantly, YTHDF2 also promotes immune evasion by destabilizing other mRNAs as an N6-methyladenosine (m6A) reader. Small-molecule-mediated targeting of YTHDF2 suppresses aggressive B cell malignancies and sensitizes them to CAR-T cell therapy.

PMID:39694037 | DOI:10.1016/j.cell.2024.11.007

Gigascience. 2024 Jan 2;13:giae100. doi: 10.1093/gigascience/giae100.

ABSTRACT

Amyotrophic lateral sclerosis (ALS) is the most common motor neuron disease, which still lacks effective disease-modifying therapies. Similar to other neurodegenerative disorders, such as Alzheimer and Parkinson disease, ALS pathology is presumed to propagate over time, originating from the motor cortex and spreading to other cortical regions. Exploring early disease stages is crucial to understand the causative molecular changes underlying the pathology. For this, we sampled human postmortem prefrontal cortex (PFC) tissue from Brodmann area 6, an area that exhibits only moderate pathology at the time of death, and performed a multiomic analysis of 51 patients with sporadic ALS and 50 control subjects. To compare sporadic disease to genetic ALS, we additionally analyzed PFC tissue from 4 transgenic ALS mouse models (C9orf72-, SOD1-, TDP-43-, and FUS-ALS) using the same methods. This multiomic data resource includes transcriptome, small RNAome, and proteome data from female and male samples, aimed at elucidating early and sex-specific ALS mechanisms, biomarkers, and drug targets.

PMID:39693632 | DOI:10.1093/gigascience/giae100

PLoS Pathog. 2024 Dec 18;20(12):e1012788. doi: 10.1371/journal.ppat.1012788. Online ahead of print.

ABSTRACT

Transmission of the malaria parasite Plasmodium to mosquitoes necessitates gamete egress from red blood cells to allow zygote formation and ookinete motility to enable penetration of the midgut epithelium. Both processes are dependent on the secretion of proteins from distinct sets of specialized vesicles. Inhibiting some of these proteins has shown potential for blocking parasite transmission to the mosquito. To identify new transmission blocking vaccine candidates, we aimed to define the microneme content from ookinetes of the rodent model organism Plasmodium berghei using APEX2-mediated rapid proximity-dependent biotinylation. Besides known proteins of ookinete micronemes, this identified over 50 novel candidates and sharpened the list of a previous survey based on subcellular fractionation. Functional analysis of a first candidate uncovered a dual role for this membrane protein in male gametogenesis and ookinete midgut traversal. Mutation of a putative trafficking motif in the C-terminus affected ookinete to oocyst transition but not gamete formation. This suggests the existence of distinct functional and transport requirements for Plasmodium proteins in different parasite stages.

PMID:39693377 | DOI:10.1371/journal.ppat.1012788

Genetics. 2024 Dec 18:iyae167. doi: 10.1093/genetics/iyae167. Online ahead of print.

ABSTRACT

Reliable methods for detecting and analyzing gene expression are necessary tools for understanding development and investigating biological responses to genetic and environmental perturbation. With its fully sequenced genome, invariant cell lineage, transparent body, wiring diagram, detailed anatomy, and wide array of genetic tools, Caenorhabditis elegans is an exceptionally useful model organism for linking gene expression to cellular phenotypes. The development of new techniques in recent years has greatly expanded our ability to detect gene expression at high resolution. Here, we provide an overview of gene expression methods for C. elegans, including techniques for detecting transcripts and proteins in situ, bulk RNA sequencing of whole worms and specific tissues and cells, single-cell RNA sequencing, and high-throughput proteomics. We discuss important considerations for choosing among these techniques and provide an overview of publicly available online resources for gene expression data.

PMID:39693264 | DOI:10.1093/genetics/iyae167

Elife. 2024 Dec 18;13:e92718. doi: 10.7554/eLife.92718.

ABSTRACT

Diverse antibody repertoires spanning multiple lymphoid organs (i.e., bone marrow, spleen, lymph nodes) form the foundation of protective humoral immunity. Changes in their composition across lymphoid organs are a consequence of B-cell selection and migration events leading to a highly dynamic and unique physiological landscape of antibody repertoires upon antigenic challenge (e.g., vaccination). However, to what extent B cells encoding identical or similar antibody sequences (clones) are distributed across multiple lymphoid organs and how this is shaped by the strength of a humoral response remains largely unexplored. Here, we performed an in-depth systems analysis of antibody repertoires across multiple distinct lymphoid organs of immunized mice and discovered that organ-specific antibody repertoire features (i.e., germline V-gene usage and clonal expansion profiles) equilibrated upon a strong humoral response (multiple immunizations and high serum titers). This resulted in a surprisingly high degree of repertoire consolidation, characterized by highly connected and overlapping B-cell clones across multiple lymphoid organs. Finally, we revealed distinct physiological axes indicating clonal migrations and showed that antibody repertoire consolidation directly correlated with antigen specificity. Our study uncovered how a strong humoral response resulted in a more uniform but redundant physiological landscape of antibody repertoires, indicating that increases in antibody serum titers were a result of synergistic contributions from antigen-specific B-cell clones distributed across multiple lymphoid organs. Our findings provide valuable insights for the assessment and design of vaccine strategies.

PMID:39693231 | DOI:10.7554/eLife.92718

Int J Cancer. 2024 Dec 18. doi: 10.1002/ijc.35295. Online ahead of print.

ABSTRACT

Animal models of N-butyl-N-(4-hydroxy butyl) nitrosamine (BBN)-induced urothelial carcinoma (UC), particularly bladder cancer (BC), have long been established. However, the rare incidence of BBN-induced upper urinary tract UC (UTUC), which originates from the same urothelium as BC, remains elusive. The scarcity of animal models of UTUC has made it challenging to study the biology of UTUC. To address this problem, we tried to establish a novel mouse model of UTUC by treating multiple mice strains and sexes with BBN. The molecular consistency between the UTUC mouse model and human UTUC was confirmed using multi-omics analyses, including whole-exome, whole-transcriptome, and spatial transcriptome sequencing. 16S ribosomal RNA metagenome sequencing, metabolome analysis, and dietary interventions were employed to assess changes in the gut microbiome, metabolome, and carcinogenesis of UTUC. Of all treated mice, only female BALB/c mice developed UTUC over BC. Multi-omics analyses confirmed that the UTUC model reflected the molecular characteristics and heterogeneity of human UTUC with poor prognosis. Furthermore, the model exhibited increased Tnf-related inflammatory gene expression in the upper urinary tract and a low relative abundance of Parabacteroides distasonis in the gut. Dietary intervention, mainly without alanine, led to P. distasonis upregulation and successfully prevented UTUC, as well as suppressed Tnf-related inflammatory gene expression in the upper urinary tract despite the exposure to BBN. This is the first report to demonstrate a higher incidence of UTUC than BC in a non-engineered mouse model using BBN. Overall, this model could serve as a useful tool for comprehensively investigating UTUC in future studies.

PMID:39693209 | DOI:10.1002/ijc.35295

Genomics Proteomics Bioinformatics. 2024 Dec 18:qzae089. doi: 10.1093/gpbjnl/qzae089. Online ahead of print.

NO ABSTRACT

PMID:39693115 | DOI:10.1093/gpbjnl/qzae089

J Membr Biol. 2024 Dec 18. doi: 10.1007/s00232-024-00330-3. Online ahead of print.

ABSTRACT

Plants are attacked by various pathogens that secrete a variety of effectors to damage host cells and facilitate infection. One of the largest and so far understudied microbial protein families of effectors is necrosis- and ethylene-inducing peptide-1-like proteins (NLPs), which are involved in important plant diseases. Many NLPs act as cytolytic toxins that cause cell death and tissue necrosis by disrupting the plant's plasma membrane. Their mechanism of action is unique and leads to the formation of small, transient membrane ruptures. Here, we capture the interaction of the cytotoxic model NLP from the oomycete Pythium aphanidermatum, NLPPya, with plant cell-mimicking membranes of giant unilamellar vesicles (GUVs) and tobacco protoplasts using confocal fluorescence microscopy. We show that the permeabilization of GUVs by NLPPya is concentration- and time-dependent, confirm the small size of the pores by observing the inability of NLPPya monomers to pass through them, image the morphological changes of GUVs at higher concentrations of NLPPya and confirm its oligomerization on the membrane of GUVs. In addition, NLPPya bound to plasma membranes of protoplasts, which showed varying responses. Our results provide new insights into the interaction of NLPPya with model lipid membranes containing plant-derived sphingolipids.

PMID:39692881 | DOI:10.1007/s00232-024-00330-3

Front Toxicol. 2024 Dec 3;6:1452974. doi: 10.3389/ftox.2024.1452974. eCollection 2024.

ABSTRACT

INTRODUCTION: In 2015, the FDA released a Drug Safety Communication regarding a possible link between opioid exposure during early pregnancy and an increased risk of fetal neural tube defects (NTDs). At the time, the indications for opioid use during pregnancy were not changed due to incomplete maternal toxicity data and limitations in human and animal studies. To assess these knowledge gaps, largescale animal studies are ongoing; however, state-of-the-art technologies have emerged as promising tools to assess otherwise non-standard endpoints. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) is a dynamic approach capable of generating 2D ion images to visualize the distribution of an analyte of interest across a tissue section.

METHODS: Given the importance of lipid metabolism and neurotransmitters in the developing central nervous system, this study incorporates MALDI MSI to assess lipid distributions across mouse gestational day (GD) 18 fetuses, with and without observable NTDs following maternal exposure on GD 8 to morphine (400 mg/kg BW) or the NTD positive control valproic acid (VPA) (500 mg/kg BW).

RESULTS: Analysis of whole-body mouse fetuses revealed differential lipid distributions localized mainly in the brain and spinal cord, which included several phosphatidylcholine (PC) species such as PCs 34:1, 34:0, and 36:2 localized to the cortex or hippocampus and lyso PC 16:0 across all brain regions. Overall, differential lipids increased in with maternal morphine and VPA exposure. Neurotransmitter distributions across the brain using FMP-10 derivatizing agent were also assessed, revealing morphine-specific changes.

DISCUSSION: The observed differential glycerophospholipid distributions in relation to treatment and NTD development in mouse fetuses provide potential targets for further investigation of molecular mechanisms of opioid-related developmental effects. Overall, these findings support the feasibility of incorporating MALDI MSI to assess non-standard endpoints of opioid exposure during gestation.

PMID:39691158 | PMC:PMC11651024 | DOI:10.3389/ftox.2024.1452974

Phys Rev E. 2024 Nov;110(5-1):054405. doi: 10.1103/PhysRevE.110.054405.

ABSTRACT

Buckling instabilities driven by tissue growth underpin key developmental events such as the folding of the brain. Tissue growth is disordered due to cell-to-cell variability, but the effects of this variability on buckling are unknown. Here, we analyze what is perhaps the simplest setup of this problem: the buckling of an elastic rod with fixed ends driven by spatially varying, yet highly symmetric growth. Combining analytical calculations for simple growth fields and numerical sampling of random growth fields, we show that variability can increase as well as decrease the growth threshold for buckling, even when growth variability does not cause any residual stresses. For random growth, we find numerically that the shift of the buckling threshold correlates with spatial moments of the growth field. Our results imply that biological systems can either trigger or avoid buckling by exploiting the spatial arrangement of growth variability.

PMID:39690582 | DOI:10.1103/PhysRevE.110.054405

Nat Protoc. 2024 Dec 17. doi: 10.1038/s41596-024-01095-8. Online ahead of print.

ABSTRACT

Antibody-based research applications are critical for biological discovery. Yet there are no industry standards for comparing the performance of antibodies in various applications. We describe a knockout cell line-based antibody characterization platform, developed and approved jointly by industry and academic researchers, that enables the systematic comparison of antibody performance in western blot, immunoprecipitation and immunofluorescence. The scalable protocols, which require minimal technological resources, consist of (1) the identification of appropriate cell lines for antibody characterization studies, (2) development/contribution of isogenic knockout controls, and (3) a series of antibody characterization procedures focused on the most common applications of antibodies in research. We provide examples of expected outcomes to guide antibody users in evaluating antibody performance. Central to our approach is advocating for transparent and open data sharing, enabling a community effort to identify specific antibodies for all human proteins. Mid-level graduate students with training in biochemistry and prior experience in cell culture and microscopy can complete the protocols for a specific protein within 1 month while working part-time on this effort. Antibody characterization is needed to meet standards for resource validation and data reproducibility, which are increasingly required by journals and funding agencies.

PMID:39690206 | DOI:10.1038/s41596-024-01095-8

Nat Biomed Eng. 2024 Dec 17. doi: 10.1038/s41551-024-01290-8. Online ahead of print.

ABSTRACT

Clinical and biological information in large datasets of gene expression across cancers could be tapped with unsupervised deep learning. However, difficulties associated with biological interpretability and methodological robustness have made this impractical. Here we describe an unsupervised deep-learning framework for the generation of low-dimensional latent spaces for gene-expression data from 50,211 transcriptomes across 18 human cancers. The framework, which we named DeepProfile, outperformed dimensionality-reduction methods with respect to biological interpretability and allowed us to unveil that genes that are universally important in defining latent spaces across cancer types control immune cell activation, whereas cancer-type-specific genes and pathways define molecular disease subtypes. By linking latent variables in DeepProfile to secondary characteristics of tumours, we discovered that mutation burden is closely associated with the expression of cell-cycle-related genes, and that the activity of biological pathways for DNA-mismatch repair and MHC class II antigen presentation are consistently associated with patient survival. We also found that tumour-associated macrophages are a source of survival-correlated MHC class II transcripts. Unsupervised learning can facilitate the discovery of biological insight from gene-expression data.

PMID:39690287 | DOI:10.1038/s41551-024-01290-8

Proc Biol Sci. 2024 Dec;291(2037):20241970. doi: 10.1098/rspb.2024.1970. Epub 2024 Dec 18.

ABSTRACT

Closely related host species share similar symbionts, but the effects of host genetic admixture and environmental conditions on these communities remain largely unknown. We investigated the influence of host genetic admixture and environmental factors on the intestinal prokaryotic and eukaryotic communities (fungi, parasites) of two house mouse subspecies (Mus musculus domesticus and M. m. musculus) and their hybrids in two settings: (i) wild-caught mice from the European hybrid zone and (ii) wild-derived inbred mice in a controlled laboratory environment before and during a community perturbation (infection). In wild-caught mice, environmental factors strongly predicted the overall microbiome composition. Subspecies' genetic distance significantly influenced the overall microbiome composition, and each component (bacteria, parasites and fungi). While hybridization had a weak effect, it significantly impacted fungal composition. We observed similar patterns in wild-derived mice, where genetic distances and hybridization influenced microbiome composition, with fungi being more stable to infection-induced perturbations than other microbiome components. Subspecies' genetic distance has a stronger and consistent effect across microbiome components than differences in expected heterozygosity among hybrids, suggesting that host divergence and host filtering play a key role in microbiome divergence, influenced by environmental factors. Our findings offer new insights into the eco-evolutionary processes shaping host-microbiome interactions.

PMID:39689880 | DOI:10.1098/rspb.2024.1970

Cell Syst. 2024 Dec 14:S2405-4712(24)00366-1. doi: 10.1016/j.cels.2024.12.002. Online ahead of print.

ABSTRACT

Single-cell CRISPR screens link genetic perturbations to transcriptional states, but high-throughput methods connecting these induced changes to their regulatory foundations are limited. Here, we introduce Multiome Perturb-seq, extending single-cell CRISPR screens to simultaneously measure perturbation-induced changes in gene expression and chromatin accessibility. We apply Multiome Perturb-seq in a CRISPRi screen of 13 chromatin remodelers in human RPE-1 cells, achieving efficient assignment of sgRNA identities to single nuclei via an improved method for capturing barcode transcripts from nuclear RNA. We organize expression and accessibility measurements into coherent programs describing the integrated effects of perturbations on cell state, finding that ARID1A and SUZ12 knockdowns induce programs enriched for developmental features. Modeling of perturbation-induced heterogeneity connects accessibility changes to changes in gene expression, highlighting the value of multimodal profiling. Overall, our method provides a scalable and simply implemented system to dissect the regulatory logic underpinning cell state. A record of this paper's transparent peer review process is included in the supplemental information.

PMID:39689711 | DOI:10.1016/j.cels.2024.12.002