Br J Pharmacol. 2024 May 19. doi: 10.1111/bph.16390. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: The canonical Kir6.2/SUR2A ventricular KATP channel is highly ATP-sensitive and remains closed under normal physiological conditions. These channels activate only when prolonged metabolic compromise causes significant ATP depletion and then shortens the action potential to reduce contractile activity. Pharmacological activation of KATP channels is cardioprotective, but physiologically, it is difficult to understand how these channels protect the heart if they only open under extreme metabolic stress. The presence of a second KATP channel population could help explain this. Here, we characterise the biophysical and pharmacological behaviours of a constitutively active Kir6.1-containing KATP channel in ventricular cardiomyocytes.

EXPERIMENTAL APPROACH: Patch-clamp recordings from rat ventricular myocytes in combination with well-defined pharmacological modulators was used to characterise these newly identified K+ channels. Action potential recording, calcium (Fluo-4) fluorescence measurements and video edge detection of contractile function were used to assess functional consequences of channel modulation.

KEY RESULTS: Our data show a ventricular K+ conductance whose biophysical characteristics and response to pharmacological modulation were consistent with Kir6.1-containing channels. These Kir6.1-containing channels lack the ATP-sensitivity of the canonical channels and are constitutively active.

CONCLUSION AND IMPLICATIONS: We conclude there are two functionally distinct populations of ventricular KATP channels: constitutively active Kir6.1-containing channels that play an important role in fine-tuning the action potential and Kir6.2/SUR2A channels that activate with prolonged ischaemia to impart late-stage protection against catastrophic ATP depletion. Further research is required to determine whether Kir6.1 is an overlooked target in Comprehensive in vitro Proarrhythmia Assay (CiPA) cardiac safety screens.

PMID:38763521 | DOI:10.1111/bph.16390

Curr Opin Immunol. 2024 May 18;87:102425. doi: 10.1016/j.coi.2024.102425. Online ahead of print.

ABSTRACT

Interferons (IFNs) are an integral component of the host innate immune response during viral infection. Recent advances in the study of type I and III IFNs suggest that though both types counteract viral infection, type III IFNs act predominantly at epithelial barrier sites, while type I IFNs drive systemic responses. The dynamics and specific roles of type I versus III IFNs have been studied in the context of infection by a variety of enteric pathogens, including reovirus, rotavirus, norovirus, astrovirus, and intestinal severe acute respiratory syndrome coronavirus 2, revealing shared patterns of regulatory influence. An important role for the gut microbiota, including the virome, in regulating homeostasis and priming of intestinal IFN responses has also recently emerged.

PMID:38763032 | DOI:10.1016/j.coi.2024.102425

Phytomedicine. 2024 May 15;130:155746. doi: 10.1016/j.phymed.2024.155746. Online ahead of print.

ABSTRACT

BACKGROUND: Triple-negative breast cancer (TNBC) is a category of breast cancer characterized with high molecular heterogeneity. Owing to the lack of effective therapeutic strategies, patients with TNBC have a poor prognosis. Paris saponin VII (PSⅦ), a steroidal saponin extracted from the rhizome of Trichillium tschonoskii Maxim, exhibits excellent anti-cancer activity in a variety of solid tumors. However, the role and potential mechanism of PSⅦ against TNBC remain unexplored.

PURPOSE: This study aimed to elucidate the therapeutic effects of PSⅦ against TNBC and explore the potential mechanism of action.

METHODS: We combined the analysis of public single-cell sequencing data with weighted gene co-expression network analysis (WGCNA) to identity differentially expressed genes (DEGs) that distinguished malignant and normal epithelial cells in TNBC. Subsequently, the biological features of DEGs in TNBC were evaluated. Gene set enrichment analysis (GSEA) was used to define potential pathways associated with the DEGs. The pharmacological activity of PSⅦ for TNBC was evidenced via in vitro and in vivo experiments, and molecular docking, molecular dynamics (MD), surface plasmon resonance (SPR) assay and western blotting were employed to confirm the relative mechanisms.

RESULTS: Single-cell sequencing and WGCNA revealed STMN1 as a pivotal biomarker of TNBC. STMN1 overexpression in TNBC was associated with poor patient prognosis. GSEA revealed a significant accumulation of STMN1 within the MAPK signaling pathway. Furthermore, In vitro experiments showed that PSⅦ showed significantly suppressive actions on the proliferation, migration and invasion abilities for TNBC cells, while inducing apoptosis. Molecular docking, MD analysis and SPR assay indicated a robust interaction between PSⅦ and the MEK protein. Western blotting revealed that PSⅦ may inhibit tumor progression by suppressing the phosphorylation of MEK1/2 and the downstream phosphorylation of ERK1/2 and STMN1. Intraperitoneal injection of PSⅦ (10 mg/kg) notably reduced tumor growth by 71.26 % in a 4T1 xenograft model.

CONCLUSION: In our study, the systems biology method was used to identify potential therapeutic targets for TNBC. In vitro and in vivo experiments demonstrated PSⅦ suppresses cancer progression by targeting the MEK/ERK/STMN1 signaling axis. For the first time, the inhibition of STMN1 phosphorylation has been indicated as a possible mechanism for the anticancer effects of PSⅦ. These results emphasize the potential value of PSⅦ as a promising anti-cancer drug candidate for further development in the field of TNBC therapeutics.

PMID:38763012 | DOI:10.1016/j.phymed.2024.155746

Biophys J. 2024 May 17:S0006-3495(24)00329-1. doi: 10.1016/j.bpj.2024.05.015. Online ahead of print.

ABSTRACT

Cells employ many large macromolecular machines for the execution and regulation of processes that are vital for cell and organismal viability. Interestingly, cells cannot synthesize these machines as functioning units. Instead, cells synthesize the molecular parts that must then assemble into the functional complex. Many important machines, including chaperones like GroEL and proteases like the proteasome, are comprised protein rings that are stacked on top of one another. While there is some experimental data regarding how stacked-ring complexes like the proteasome self-assemble, a comprehensive understanding of the dynamics of stacked ring assembly is currently lacking. Here, we developed a mathematical model of stacked trimer assembly, and performed an analysis of the assembly of the stacked homomeric trimer, which is the simplest stacked ring architecture. We found that stacked rings are particularly susceptible to a form of kinetic trapping that we term "deadlock," in which the system gets stuck in a state where there are many large intermediates that are not the fully-assembled structure, but that cannot productively react. When interaction affinities are uniformly strong, deadlock severely limits assembly yield. We thus predicted that stacked rings would avoid situations where all interfaces in the structure have high affinity. Analysis of available crystal structures indicated that indeed the majority - if not all - of stacked trimers do not contain uniformly strong interactions. Finally, to better understand the origins of deadlock, we developed a formal pathway analysis and showed that, when all the binding affinities are strong, many of the possible pathways are utilized. In contrast, optimal assembly strategies utilize only a small number of pathways. Our work suggests that deadlock is a critical factor influencing the evolution of macromolecular machines and provides general principles for understanding the self-assembly efficiency of existing machines.

PMID:38762753 | DOI:10.1016/j.bpj.2024.05.015

J Lipid Res. 2024 May 16:100564. doi: 10.1016/j.jlr.2024.100564. Online ahead of print.

ABSTRACT

Metabolic programming underpins inflammatory processes of immune cells. In the context of chronic liver disease, liver macrophage activation and response to hepatocellular damage is dependent on profound metabolic changes. Here, we sought to identify the role of an important metabolic regulator, AMP-activated protein kinase (AMPK), specifically within myeloid cells during the progression of non-alcoholic steatohepatitis (NASH) and whether treatment with metformin, a first line therapy for diabetes and activator of AMPK could stem disease progression. Male and female Prkaa1fl/fl/Prkaa2fl/fl (Flox) control and Flox-LysM-Cre+ (MacKO) mice were fed a low-fat control or a choline-deficient, amino acid defined 45% Kcal high fat diet (CDAHFD) for 8 weeks, where metformin was introduced in the drinking water (50 or 250 mg/kg/day) for the last 4 weeks. Hepatic steatosis and fibrosis were dramatically increased in response to CDAHFD-feeding compared to low-fat control. While myeloid AMPK signaling had no effect on markers of hepatic steatosis or circulating markers, fibrosis as measured by total liver collagen was significantly elevated in livers from MacKO mice, independent of sex. Although treatment with 50 mg/kg/day metformin had no effect on any parameter, intervention with 250 mg/kg/day metformin completely ameliorated hepatic steatosis and fibrosis in both male and female mice. While the protective effect of metformin was associated with lower final body weight, decrease expression of lipogenic and Col1a1 transcripts, it was independent of myeloid AMPK signaling. These results suggest that endogenous AMPK signaling in myeloid cells, both liver-resident and infiltrating, acts to restrict fibrogenesis during CDAHFD-induced NASH progression but is not the mechanism by which metformin improves markers of NASH.

PMID:38762124 | DOI:10.1016/j.jlr.2024.100564

Cell Rep Methods. 2024 May 14:100781. doi: 10.1016/j.crmeth.2024.100781. Online ahead of print.

ABSTRACT

We present an innovative strategy for integrating whole-genome-wide multi-omics data, which facilitates adaptive amalgamation by leveraging hidden layer features derived from high-dimensional omics data through a multi-task encoder. Empirical evaluations on eight benchmark cancer datasets substantiated that our proposed framework outstripped the comparative algorithms in cancer subtyping, delivering superior subtyping outcomes. Building upon these subtyping results, we establish a robust pipeline for identifying whole-genome-wide biomarkers, unearthing 195 significant biomarkers. Furthermore, we conduct an exhaustive analysis to assess the importance of each omic and non-coding region features at the whole-genome-wide level during cancer subtyping. Our investigation shows that both omics and non-coding region features substantially impact cancer development and survival prognosis. This study emphasizes the potential and practical implications of integrating genome-wide data in cancer research, demonstrating the potency of comprehensive genomic characterization. Additionally, our findings offer insightful perspectives for multi-omics analysis employing deep learning methodologies.

PMID:38761803 | DOI:10.1016/j.crmeth.2024.100781

Cell Rep Med. 2024 May 15:101577. doi: 10.1016/j.xcrm.2024.101577. Online ahead of print.

ABSTRACT

Descendants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant now account for almost all SARS-CoV-2 infections. The Omicron variant and its sublineages have spike glycoproteins that are highly diverged from the pandemic founder and first-generation vaccine strain, resulting in significant evasion from monoclonal antibody therapeutics and vaccines. Understanding how commonly elicited antibodies can broaden to cross-neutralize escape variants is crucial. We isolate IGHV3-53, using "public" monoclonal antibodies (mAbs) from an individual 7 months post infection with the ancestral virus and identify antibodies that exhibit potent and broad cross-neutralization, extending to the BA.1, BA.2, and BA.4/BA.5 sublineages of Omicron. Deep mutational scanning reveals these mAbs' high resistance to viral escape. Structural analysis via cryoelectron microscopy of a representative broadly neutralizing antibody, CAB-A17, in complex with the Omicron BA.1 spike highlights the structural underpinnings of this broad neutralization. By reintroducing somatic hypermutations into a germline-reverted CAB-A17, we delineate the role of affinity maturation in the development of cross-neutralization by a public class of antibodies.

PMID:38761799 | DOI:10.1016/j.xcrm.2024.101577

Plant Foods Hum Nutr. 2024 May 18. doi: 10.1007/s11130-024-01190-x. Online ahead of print.

ABSTRACT

High voltage electrostatic field processing (HVEF) is a food preservation procedure frequently used to produce healthy minimally processed fruits and vegetables (F&V) as it reduces the growth of microorganisms and activates or inhibits various enzymes, thus retarding their natural ripening while preserving and even enhancing native nutritional quality and sensory characteristics. HVEF is one of the various nonthermal processing technology (NTPT) regarded as abiotic stress that can activate the antioxidant system of F&V and can also inhibith spoilage enzymes as, polyphenol oxidase (PPO), lipoxygenase (LOX), pectin methylesterase (PME), polygalacturonase (PG), cellulase (Cel), β-xylosidase, xyloglucan and endotransglycosylase/hydrolase, bringing positive effect on hardness, firmness, colour attributes, electric conductivity, antioxidant compounds, microstructure and decreasing electrolyte leakage (EL), malondialdehyde (MDA) contents and browning degree. This technique can also increase the contents of fructose, glucose, and sucrose and decrease the production of CO2 and H2O2. Additionally, it has been reported that HVEF could be used with other treatments, such as modified atmosphere packaging (MAP) and acidic electrolyzed water (AEW) treatment, to enhance its effects. Future works should deepen on elucidating the activation of the antioxidant systems by applying HVEF of critical enzymes related to the synthesis pathways of phenolic compounds (PC) and carotenoids (Car). Holistic approaches to the effects of HVEF on metabolism based on systems biology also need to be studied by considering the overall biochemical, physical, and process engineering related aspects of this technique.

PMID:38761282 | DOI:10.1007/s11130-024-01190-x

Scand J Med Sci Sports. 2024 May;34(5):e14651. doi: 10.1111/sms.14651.

ABSTRACT

There is some, albeit inconsistent, evidence supporting sex differences in preschoolers' motor competence (MC), with these observations not uniform when analyzed by age, and cultural groups. Thus, this study examined sex differences across ages in 3- to 5-year-old children's MC. A cross-country pooled sample of 6241 children aged 3-5 years (49.6% girls) was assessed for MC using the Test of Gross Motor Development-2nd/3rd edition, and children were categorized into groups of age in months. Multiple linear regression models and predictive margins were calculated to explore how sex and age in months affect scores of MC (i.e., locomotor and ball skills), with adjustments for country and BMI. The Chow's Test was used to test for the presence of a structural break in the data. Significant differences in favor of girls were seen at 57-59 and 66-68 months of age for locomotor skills; boys performed better in ball skills in all age periods, except for 42-44 and 45-47 months of age. The higher marginal effects were observed for the period between 45-47 and 48-50 months for locomotor skills (F = 30.21; and F = 25.90 for girls and boys, respectively), and ball skills (F = 19.01; and F = 42.11 for girls and boys, respectively). A significantly positive break point was seen at 45-47 months, highlighting the age interval where children's MC drastically improved. The identification of this breakpoint provides an evidence-based metric for when we might expect MC to rapidly increase, and an indicator of early delay when change does not occur at that age.

PMID:38760918 | DOI:10.1111/sms.14651

Phytomedicine. 2024 May 3;130:155710. doi: 10.1016/j.phymed.2024.155710. Online ahead of print.

ABSTRACT

BACKGROUND: Sepsis, a life-threatening condition resulting from uncontrolled host responses to infection, poses a global health challenge with limited therapeutic options. Due to high heterogeneity, sepsis lacks specific therapeutic drugs. Additionally, there remains a significant gap in the clinical management of sepsis regarding personalized and precise medicine.

PURPOSE: This review critically examines the scientific landscape surrounding natural products in sepsis and sepsis-mediated inflammation, highlighting their clinical potential.

METHODS: Following the PRISMA guidelines, we retrieved articles from PubMed to explore potential natural products with therapeutic effects in sepsis-mediated inflammation.

RESULTS: 434 relevant in vitro and in vivo studies were identified and screened. Ultimately, 55 studies were obtained as the supporting resources for the present review. We divided the 55 natural products into three categories: those influencing the synthesis of inflammatory factors, those affecting surface receptors and modulatory factors, and those influencing signaling pathways and the inflammatory cascade.

CONCLUSION: Natural products' potential as game-changers in sepsis-mediated inflammation management lies in their ability to modulate hallmarks in sepsis, including inflammation, immunity, and coagulopathy, which provides new therapeutic avenues that are readily accessible and capable of undergoing rapid clinical validation and deployment, offering a gift from nature to humanity. Innovative techniques like bioinformatics, metabolomics, and systems biology offer promising solutions to overcome these obstacles and facilitate the development of natural product-based therapeutics, holding promise for personalized and precise sepsis management and improving patient outcomes. However, standardization, bioavailability, and safety challenges arise during experimental validation and clinical trials of natural products.

PMID:38759311 | DOI:10.1016/j.phymed.2024.155710

BMC Plant Biol. 2024 May 17;24(1):415. doi: 10.1186/s12870-024-05119-z.

ABSTRACT

Globe artichoke (Cynara cardunculus var. scolymus; 2n = 2x = 34) is a food crop consumed for its immature flower heads. Traditionally, globe artichoke varietal types are vegetatively propagated. However, seed propagation makes it possible to treat the crop as annual, increasing field uniformity and reducing farmers costs, as well as pathogens diffusion. Despite globe artichoke's significant agricultural value and the critical role of heterosis in the development of superior varieties, the production of hybrids remains challenging without a reliable system for large-scale industrial seed production. Male sterility (MS) presents a promising avenue for overcoming these challenges by simplifying the hybridization process and enabling cost-effective seed production. However, within the Cynara genus, genic male sterility has been linked to three recessive loci in globe artichoke, with no definitive genetic mechanism elucidated to date. A 250 offsprings F2 population, derived from a cross between a MS globe artichoke and a male fertile (MF) cultivated cardoon (C. cardunculus var. altilis) and fitting a monogenic segregation model (3:1), was analyzed through BSA-seq, aiming at the identification of genomic regions/genes affecting male sterility. Four QTL regions were identified on chromosomes 4, 12, and 14. By analyzing the sequence around the highest pick on chromosome 14, a cytochrome P450 (CYP703A2) was identified, carrying a deleterious substitution (R/Q) fixed in the male sterile parent. A single dCAPS marker was developed around this SNP, allowing the discrimination between MS and MF genotypes within the population, suitable for applications in plant breeding programs. A 3D model of the protein was generated by homology modeling, revealing that the mutated amino acid is part of a highly conserved motif crucial for protein folding.

PMID:38760683 | DOI:10.1186/s12870-024-05119-z

Nat Med. 2024 May 17. doi: 10.1038/s41591-024-03066-8. Online ahead of print.

NO ABSTRACT

PMID:38760590 | DOI:10.1038/s41591-024-03066-8

Nat Med. 2024 May 17. doi: 10.1038/s41591-024-02969-w. Online ahead of print.

ABSTRACT

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes.

PMID:38760585 | DOI:10.1038/s41591-024-02969-w

NPJ Syst Biol Appl. 2024 May 17;10(1):53. doi: 10.1038/s41540-024-00378-w.

ABSTRACT

Breast cancer is one of the prevailing cancers globally, with a high mortality rate. Metastatic breast cancer (MBC) is an advanced stage of cancer, characterised by a highly nonlinear, heterogeneous process involving numerous singling pathways and regulatory interactions. Epithelial-mesenchymal transition (EMT) emerges as a key mechanism exploited by cancer cells. Transforming Growth Factor-β (TGFβ)-dependent signalling is attributed to promote EMT in advanced stages of breast cancer. A comprehensive regulatory map of TGFβ induced EMT was developed through an extensive literature survey. The network assembled comprises of 312 distinct species (proteins, genes, RNAs, complexes), and 426 reactions (state transitions, nuclear translocations, complex associations, and dissociations). The map was developed by following Systems Biology Graphical Notation (SBGN) using Cell Designer and made publicly available using MINERVA ( http://35.174.227.105:8080/minerva/?id=Metastatic_Breast_Cancer_1 ). While the complete molecular mechanism of MBC is still not known, the map captures the elaborate signalling interplay of TGFβ induced EMT-promoting MBC. Subsequently, the disease map assembled was translated into a Boolean model utilising CaSQ and analysed using Cell Collective. Simulations of these have captured the known experimental outcomes of TGFβ induced EMT in MBC. Hub regulators of the assembled map were identified, and their transcriptome-based analysis confirmed their role in cancer metastasis. Elaborate analysis of this map may help in gaining additional insights into the development and progression of metastatic breast cancer.

PMID:38760412 | DOI:10.1038/s41540-024-00378-w

J Leukoc Biol. 2024 May 17:qiae104. doi: 10.1093/jleuko/qiae104. Online ahead of print.

ABSTRACT

Alternative splicing (AS) participates in tumor development and tumor microenvironment formation. However, the landscape of immune infiltrating AS events (IIASE) in pan-cancer and mechanisms of AS in lung adenocarcinoma (LUAD) have not been comprehensively characterized. We systematically profiled the IIASE landscape of pan-cancer using data from The Cancer Genome Atlas (TCGA), analyzing both commonalities and specific characteristics among different cancer types. We found that AS events tend to occur specifically in one cancer type rather than in multiple cancer types. AS events were used to classify 512 LUAD samples into two subtypes by unsupervised clustering: aberrant splicing subtype (ABS) and immune infiltrating subtype (IIS). The two subtypes showed significant differences in clinicopathology, prognosis, transcriptomics, genomics and immune microenvironment. We constructed a classification signature comprising 10 genes involved in 14 AS events using Logistic regression. The robustness of the signature was validated in three independent datasets using survival analysis. To explore AS mechanisms in LUAD, we constructed subtype-specific co-expression networks using Pearson correlation analysis. AS event of AKT3 regulated by splicing factor ENOX1 was associated with poor prognosis in LUAD. Overall, we outline AS events associated with immune infiltration in pan-cancer and this study provides insights into AS mechanisms in LUAD patient classification.

PMID:38758950 | DOI:10.1093/jleuko/qiae104

J Comput Biol. 2024 May 17. doi: 10.1089/cmb.2024.0520. Online ahead of print.

ABSTRACT

Information on the structure of molecules, retrieved via biochemical databases, plays a pivotal role in various disciplines, including metabolomics, systems biology, and drug discovery. No such database can be complete and it is often necessary to incorporate data from several sources. However, the molecular structure for a given compound is not necessarily consistent between databases. This article presents StructRecon, a novel tool for resolving unique molecular structures from database identifiers. Currently, identifiers from BiGG, ChEBI, Escherichia coli Metabolome Database (ECMDB), MetaNetX, and PubChem are supported. StructRecon traverses the cross-links between entries in different databases to construct what we call identifier graphs. The goal of these graphs is to offer a more complete view of the total information available on a given compound across all the supported databases. To reconcile discrepancies met during the traversal of the databases, we develop an extensible model for molecular structure supporting multiple independent levels of detail, which allows standardization of the structure to be applied iteratively. In some cases, our standardization approach results in multiple candidate structures for a given compound, in which case a random walk-based algorithm is used to select the most likely structure among incompatible alternatives. As a case study, we applied StructRecon to the EColiCore2 model. We found at least one structure for 98.66% of its compounds, which is more than twice as many as possible when using the databases in more standard ways not considering the complex network of cross-database references captured by our identifier graphs. StructRecon is open-source and modular, which enables support for more databases in the future.

PMID:38758924 | DOI:10.1089/cmb.2024.0520

Sci Immunol. 2024 May 17;9(95):eadi5374. doi: 10.1126/sciimmunol.adi5374. Epub 2024 May 17.

ABSTRACT

The gut microbiota and tumor-associated macrophages (TAMs) affect tumor responses to anti-programmed cell death protein 1 (PD-1) immune checkpoint blockade. Reprogramming TAM by either blocking or deleting the macrophage receptor triggering receptor on myeloid cells 2 (TREM2) attenuates tumor growth, and lack of functional TREM2 enhances tumor elimination by anti-PD-1. Here, we found that anti-PD-1 treatment combined with TREM2 deficiency in mice induces proinflammatory programs in intestinal macrophages and a concomitant expansion of Ruminococcus gnavus in the gut microbiota. Gavage of wild-type mice with R. gnavus enhanced anti-PD-1-mediated tumor elimination, recapitulating the effect occurring in the absence of TREM2. A proinflammatory intestinal environment coincided with expansion, increased circulation, and migration of TNF-producing CD4+ T cells to the tumor bed. Thus, TREM2 remotely controls anti-PD-1 immune checkpoint blockade through modulation of the intestinal immune environment and microbiota, with R. gnavus emerging as a potential probiotic agent for increasing responsiveness to anti-PD-1.

PMID:38758808 | DOI:10.1126/sciimmunol.adi5374

IEEE/ACM Trans Comput Biol Bioinform. 2024 May 17;PP. doi: 10.1109/TCBB.2024.3402220. Online ahead of print.

ABSTRACT

The complexity, scale, and uncertainty in regulatory networks (e.g., gene regulatory networks and microbial networks) regularly pose a huge uncertainty in their models. These uncertainties often cannot be entirely reduced using limited and costly data acquired from the normal condition of systems. Meanwhile, regulatory networks often suffer from the non-identifiability issue, which refers to scenarios where the true underlying network model cannot be clearly distinguished from other possible models. Perturbation or excitation is a well-known process in systems biology for acquiring targeted data to reveal the complex underlying mechanisms of regulatory networks and overcome the non-identifiability issue. We consider a general class of Boolean network models for capturing the activation and inactivation of components and their complex interactions. Assuming partial available knowledge about the interactions between components of the networks, this paper formulates the inference process through the maximum aposteriori (MAP) criterion. We develop a Bayesian lookahead policy that systematically perturbs regulatory networks to maximize the performance of MAP inference under the perturbed data. This is achieved by optimally formulating the perturbation process in a reinforcement learning context and deriving a scalable deep reinforcement learning perturbation policy to compute near-optimal Bayesian policy. The proposed method learns the perturbation policy through planning without the need for any real data. The high performance of the proposed approach is demonstrated by comprehensive numerical experiments using the well-known mammalian cell cycle and gut microbial community networks.

PMID:38758625 | DOI:10.1109/TCBB.2024.3402220

Bull Math Biol. 2024 May 17;86(7):75. doi: 10.1007/s11538-024-01297-x.

ABSTRACT

The landscape of computational modeling in cancer systems biology is diverse, offering a spectrum of models and frameworks, each with its own trade-offs and advantages. Ideally, models are meant to be useful in refining hypotheses, to sharpen experimental procedures and, in the longer run, even for applications in personalized medicine. One of the greatest challenges is to balance model realism and detail with experimental data to eventually produce useful data-driven models. We contribute to this quest by developing a transparent, highly parsimonious, first principle in silico model of a growing avascular tumor. We initially formulate the physiological considerations and the specific model within a stochastic cell-based framework. We next formulate a corresponding mean-field model using partial differential equations which is amenable to mathematical analysis. Despite a few notable differences between the two models, we are in this way able to successfully detail the impact of all parameters in the stability of the growth process and on the eventual tumor fate of the stochastic model. This facilitates the deduction of Bayesian priors for a given situation, but also provides important insights into the underlying mechanism of tumor growth and progression. Although the resulting model framework is relatively simple and transparent, it can still reproduce the full range of known emergent behavior. We identify a novel model instability arising from nutrient starvation and we also discuss additional insight concerning possible model additions and the effects of those. Thanks to the framework's flexibility, such additions can be readily included whenever the relevant data become available.

PMID:38758501 | DOI:10.1007/s11538-024-01297-x

New Phytol. 2024 May 17. doi: 10.1111/nph.19815. Online ahead of print.

ABSTRACT

Recent advancements in our understanding of cell membrane dynamics have shed light on the importance of plasma membrane (PM) nanodomains in plant cell signaling. Nevertheless, many aspects of membrane nanodomains, including their regulatory mechanisms and biological functions, remain enigmatic. To address this knowledge gap, our review article proposes a novel perspective wherein signaling pathways target endoplasmic reticulum (ER)-based lipid metabolism to exert control over the formation and function of membrane nanodomains. Subsequently, these nanodomains reciprocate by influencing the localization and activity of signaling molecules at the PM. We place a specific emphasis on ER-based enzymatic reactions, given the ER's central role in membrane lipid biosynthesis and its capacity to directly impact PM lipid composition, particularly with regard to saturation levels - an essential determinant of nanodomain properties. The interplay among cell signaling, glycerolipid metabolism, and PM nanodomain may create feedforward/feedback loops that fine-tune cellular responses to developmental and environmental cues.

PMID:38757654 | DOI:10.1111/nph.19815