ATF7-Dependent Epigenetic Changes Are Required for the Intergenerational Effect of a Paternal Low-Protein Diet.

Paternal dietary conditions may contribute to metabolic disorders in offspring. We have analyzed the role of the stress-dependent epigenetic regulator cyclic AMP-dependent transcription factor 7 (ATF7) in paternal low-protein diet (pLPD)-induced gene expression changes in mouse liver. Atf7+/- mutations cause an offspring phenotype similar to that caused by pLPD, and the effect of pLPD almost vanished when paternal Atf7+/- mice were used. ATF7 binds to the promoter regions of ∼2,300 genes, including cholesterol biosynthesis-related and tRNA genes in testicular germ cells (TGCs). LPD induces ATF7 phosphorylation by p38 via reactive oxygen species (ROS) in TGCs. This leads to the release of ATF7 and a decrease in histone H3K9 dimethylation (H3K9me2) on its target genes. These epigenetic changes are maintained and induce expression of some tRNA fragments in spermatozoa. These results indicate that LPD-induced and ATF7-dependent epigenetic changes in TGCs play an important role in paternal diet-induced metabolic reprograming in offspring.

Enhanced transcriptional heterogeneity mediated by NF-κB super-enhancers.

The transcription factor NF-κB, which plays an important role in cell fate determination, is involved in the activation of super-enhancers (SEs). However, the biological functions of the NF-κB SEs in gene control are not fully elucidated. We investigated the characteristics of NF-κB-mediated SE activity using fluorescence imaging of RelA, single-cell transcriptome and chromatin accessibility analyses in anti-IgM-stimulated B cells. The formation of cell stimulation-induced nuclear RelA foci was abolished in the presence of hexanediol, suggesting an underlying process of liquid-liquid phase separation. The gained SEs induced a switch-like expression and enhanced cell-to-cell variability in transcriptional response. These properties were correlated with the number of gained cis-regulatory interactions, while switch-like gene induction was associated with the number of NF-κB binding sites in SE. Our study suggests that NF-κB SEs have an important role in the transcriptional regulation of B cells possibly through liquid condensate formation consisting of macromolecular interactions.

ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomes.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) analysis reveals heterogeneity and dynamic cell transitions. However, conventional gene-based analyses require intensive manual curation to interpret biological implications of computational results. Hence, a theory for efficiently annotating individual cells remains warranted. RESULTS: We present ASURAT, a computational tool for simultaneously performing unsupervised clustering and functional annotation of disease, cell type, biological process and signaling pathway activity for single-cell transcriptomic data, using a correlation graph decomposition for genes in database-derived functional terms. We validated the usability and clustering performance of ASURAT using scRNA-seq datasets for human peripheral blood mononuclear cells, which required fewer manual curations than existing methods. Moreover, we applied ASURAT to scRNA-seq and spatial transcriptome datasets for human small cell lung cancer and pancreatic ductal adenocarcinoma, respectively, identifying previously overlooked subpopulations and differentially expressed genes. ASURAT is a powerful tool for dissecting cell subpopulations and improving biological interpretability of complex and noisy transcriptomic data. AVAILABILITY AND IMPLEMENTATION: ASURAT is published on Bioconductor (https://doi.org/10.18129/B9.bioc.ASURAT). The codes for analyzing data in this article are available at Github (https://github.com/keita-iida/ASURATBI) and figshare (https://doi.org/10.6084/m9.figshare.19200254.v4). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Systems approaches to investigate the role of NF-κB signaling in aging.

The nuclear factor-κB (NF-κB) signaling pathway is one of the most well-studied pathways related to inflammation, and its involvement in aging has attracted considerable attention. As aging is a complex phenomenon and is the result of a multi-step process, the involvement of the NF-κB pathway in aging remains unclear. To elucidate the role of NF-κB in the regulation of aging, different systems biology approaches have been employed. A multi-omics data-driven approach can be used to interpret and clarify unknown mechanisms but cannot generate mechanistic regulatory structures alone. In contrast, combining this approach with a mathematical modeling approach can identify the mechanistics of the phenomena of interest. The development of single-cell technologies has also helped clarify the heterogeneity of the NF-κB response and underlying mechanisms. Here, we review advances in the understanding of the regulation of aging by NF-κB by focusing on omics approaches, single-cell analysis, and mathematical modeling of the NF-κB network.

Postnatal liver functional maturation requires Cnot complex-mediated decay of mRNAs encoding cell cycle and immature liver genes.

Liver development involves dramatic gene expression changes mediated by transcriptional and post-transcriptional control. Here, we show that the Cnot deadenylase complex plays a crucial role in liver functional maturation. The Cnot3 gene encodes an essential subunit of the Cnot complex. Mice lacking Cnot3 in liver have reduced body and liver masses, and they display anemia and severe liver damage. Histological analyses indicate that Cnot3-deficient (Cnot3-/- ) hepatocytes are irregular in size and morphology, resulting in formation of abnormal sinusoids. We observe hepatocyte death, increased abundance of mitotic and mononucleate hepatocytes, and inflammation. Cnot3-/- livers show increased expression of immune response-related, cell cycle-regulating and immature liver genes, while many genes relevant to liver functions, such as oxidation-reduction, lipid metabolism and mitochondrial function, decrease, indicating impaired liver functional maturation. Highly expressed mRNAs possess elongated poly(A) tails and are stabilized in Cnot3-/- livers, concomitant with an increase of the proteins they encode. In contrast, transcription of liver function-related mRNAs was lower in Cnot3-/- livers. We detect efficient suppression of Cnot3 protein postnatally, demonstrating the crucial contribution of mRNA decay to postnatal liver functional maturation.

CD4 memory T cells develop and acquire functional competence by sequential cognate interactions and stepwise gene regulation.

Memory CD4(+) T cells promote protective humoral immunity; however, how memory T cells acquire this activity remains unclear. This study demonstrates that CD4(+) T cells develop into antigen-specific memory T cells that can promote the terminal differentiation of memory B cells far more effectively than their naive T-cell counterparts. Memory T cell development requires the transcription factor B-cell lymphoma 6 (Bcl6), which is known to direct T-follicular helper (Tfh) cell differentiation. However, unlike Tfh cells, memory T cell development did not require germinal center B cells. Curiously, memory T cells that develop in the absence of cognate B cells cannot promote memory B-cell recall responses and this defect was accompanied by down-regulation of genes associated with homeostasis and activation and up-regulation of genes inhibitory for T-cell responses. Although memory T cells display phenotypic and genetic signatures distinct from Tfh cells, both had in common the expression of a group of genes associated with metabolic pathways. This gene expression profile was not shared to any great extent with naive T cells and was not influenced by the absence of cognate B cells during memory T cell development. These results suggest that memory T cell development is programmed by stepwise expression of gatekeeper genes through serial interactions with different types of antigen-presenting cells, first licensing the memory lineage pathway and subsequently facilitating the functional development of memory T cells. Finally, we identified Gdpd3 as a candidate genetic marker for memory T cells.

Obesity resistance and increased hepatic expression of catabolism-related mRNAs in Cnot3+/- mice.

Obesity is a life-threatening factor and is often associated with dysregulation of gene expression. Here, we show that the CNOT3 subunit of the CCR4-NOT deadenylase complex is critical to metabolic regulation. Cnot3(+/-) mice are lean with hepatic and adipose tissues containing reduced levels of lipids, and show increased metabolic rates and enhanced glucose tolerance. Cnot3(+/-) mice remain lean and sensitive to insulin even on a high-fat diet. Furthermore, introduction of Cnot3 haplodeficiency in ob/ob mice ameliorated the obese phenotype. Hepatic expression of most mRNAs is not altered in Cnot3(+/-) vis-à-vis wild-type mice. However, the levels of specific mRNAs, such as those coding for energy metabolism-related PDK4 and IGFBP1, are increased in Cnot3(+/-) hepatocytes, having poly(A) tails that are longer than those seen in control cells. We provide evidence that CNOT3 is involved in recruitment of the CCR4-NOT deadenylase to the 3' end of specific mRNAs. Finally, as CNOT3 levels in the liver and white adipose tissues decrease upon fasting, we propose that CNOT3 responds to feeding conditions to regulate deadenylation-specific mRNAs and energy metabolism.

Determination of the Clostridium perfringens-binding site on fibronectin.

The extracellular matrix protein fibronectin (Fn) is known to bind to the surface of Clostridium perfringens cells. Fn is a disulfide-linked homodimer protein, with each Fn polypeptide consisting of three types of repeating modules: 12 type I, 2 type II, and 15-17 type III modules. To determine the epitope on Fn recognized by C. perfringens cells, anti-Fn monoclonal antibodies (mAbs) and various Fn fragments (III2-10, rIII2-4, rIII5-7, rIII8, rIII9, rIII10) were employed. Although two C. perfringens-derived Fn-binding proteins, FbpA and FbpB, have been reported, they appear not to be the bacterium's surface Fn receptor. Moreover, both FbpA and FbpB were found to bind to C. perfringens cells. To avoid confusion, a mutant C. perfringens lacking both the fbpA and fbpB genes (MW5) was prepared using an in-frame deletion system. MW5 cells bound Fn on their surface, suggesting the presence of a putative Fn receptor(s) on C. perfringens cells. Of several anti-Fn mAbs, both HB39 and MO inhibited the binding of Fn to MW5 cells. HB39 reacted strongly with III2-10 and rIII9, and weakly with rIII2-4, rIII10 and rIII5-7 in Western blotting analysis. Binding of HB39 to Fn was inhibited in the presence of either rIII9 or rIII10, but not in the presence of rIII2-4, rIII5-7, or rIII8. Binding of Fn to MW5 cells was strongly inhibited by both III2-10 and rIII9, marginally inhibited by rIII2-4, but not affected by rIII5-7, rIII8, or rIII10. Significant binding of MW5 cells to immobilized rIII9 and rIII10 as well as immobilized III2-10 was observed. The region of Fn recognized by C. perfringens was thus mapped to the region encompassed by III9 and III10.

Both mutated and unmutated memory B cells accumulate mutations in the course of the secondary response and develop a new antibody repertoire optimally adapted to the secondary stimulus.

High-affinity memory B cells are preferentially selected during secondary responses and rapidly differentiate into antibody-producing cells. However, it remains unknown whether only high-affinity, mutated memory B cells simply expand to dominate the secondary response or if in fact memory B cells with a diverse VH repertoire, including those with no mutations, accumulate somatic mutations to create a new repertoire through the process of affinity maturation. In this report, we took a new approach to address this question by analyzing the VH gene repertoire of IgG1(+) memory B cells before and after antigen re-exposure in a host unable to generate IgG(+) B cells. We show here that both mutated and unmutated IgG1(+) memory B cells respond to secondary challenge and expand while accumulating somatic mutations in their VH genes in a stepwise manner. Both types of memory cells subsequently established a VH gene repertoire dominated by two major clonotypes, which are distinct from the original repertoire before antigen re-exposure. In addition, heavily mutated memory B cells were excluded from the secondary repertoire. Thus, both mutated and unmutated IgG1(+) memory cells equally contribute to establish a new antibody repertoire through a dynamic process of mutation and selection, becoming optimally adapted to the recall challenge.

Identifying Key Regulatory Genes in Drug Resistance Acquisition: Modeling Pseudotime Trajectories of Breast Cancer Single-Cell Transcriptome.

Single-cell RNA-sequencing (scRNA-seq) technology has provided significant insights into cancer drug resistance at the single-cell level. However, understanding dynamic cell transitions at the molecular systems level remains limited, requiring a systems biology approach. We present an approach that combines mathematical modeling with a pseudotime analysis using time-series scRNA-seq data obtained from the breast cancer cell line MCF-7 treated with tamoxifen. Our single-cell analysis identified five distinct subpopulations, including tamoxifen-sensitive and -resistant groups. Using a single-gene mathematical model, we discovered approximately 560-680 genes out of 6000 exhibiting multistable expression states in each subpopulation, including key estrogen-receptor-positive breast cancer cell survival genes, such as RPS6KB1. A bifurcation analysis elucidated their regulatory mechanisms, and we mapped these genes into a molecular network associated with cell survival and metastasis-related pathways. Our modeling approach comprehensively identifies key regulatory genes for drug resistance acquisition, enhancing our understanding of potential drug targets in breast cancer.

Positive and negative feedback regulation of the TGF-ß1 explains two equilibrium states in skin aging.

During aging, skin homeostasis is essential for maintaining appearance, as well as biological defense of the human body. In this study, we identified thrombospondin-1 (THBS1) and fibromodulin (FMOD) as positive and negative regulators, respectively, of the TGF-ß1-SMAD4 axis in human skin aging, based on in vitro and in vivo omics analyses and mathematical modeling. Using transcriptomic and epigenetic analyses of senescent dermal fibroblasts, TGF-ß1 was identified as the key upstream regulator. Bifurcation analysis revealed a binary high-/low-TGF-ß1 switch, with THBS1 as the main controller. Computational simulation of the TGF-ß1 signaling pathway indicated that THBS1 expression was sensitively regulated, whereas FMOD was regulated robustly. Results of sensitivity analysis and validation showed that inhibition of SMAD4 complex formation was a promising method to control THBS1 production and senescence. Therefore, this study demonstrated the potential of combining data-driven target discovery with mathematical approaches to determine the mechanisms underlying skin aging.

Extending BioMASS to construct mathematical models from external knowledge.

Motivation: Mechanistic modeling based on ordinary differential equations has led to numerous findings in systems biology by integrating prior knowledge and experimental data. However, the manual curation of knowledge necessary when constructing models poses a bottleneck. As the speed of knowledge accumulation continues to grow, there is a demand for a scalable means of constructing executable models. Results: We previously introduced BioMASS-an open-source, Python-based framework-to construct, simulate, and analyze mechanistic models of signaling networks. With one of its features, Text2Model, BioMASS allows users to define models in a natural language-like format, thereby facilitating the construction of large-scale models. We demonstrate that Text2Model can serve as a tool for integrating external knowledge for mathematical modeling by generating Text2Model files from a pathway database or through the use of a large language model, and simulating its dynamics through BioMASS. Our findings reveal the tool's capabilities to encourage exploration from prior knowledge and pave the way for a fully data-driven approach to constructing mathematical models. Availability and implementation: The code and documentation for BioMASS are available at https://github.com/biomass-dev/biomass and https://biomass-core.readthedocs.io, respectively. The code used in this article are available at https://github.com/okadalabipr/text2model-from-knowledge.

Preliminary External Validation Results of the Artificial Intelligence-Based Headache Diagnostic Model: A Multicenter Prospective Observational Study.

The misdiagnosis of headache disorders is a serious issue, and AI-based headache model diagnoses with external validation are scarce. We previously developed an artificial intelligence (AI)-based headache diagnosis model using a database of 4000 patients' questionnaires in a headache-specializing clinic and herein performed external validation prospectively. The validation cohort of 59 headache patients was prospectively collected from August 2023 to February 2024 at our or collaborating multicenter institutions. The ground truth was specialists' diagnoses based on the initial questionnaire and at least a one-month headache diary after the initial consultation. The diagnostic performance of the AI model was evaluated. The mean age was 42.55 ± 12.74 years, and 51/59 (86.67%) of the patients were female. No missing values were reported. Of the 59 patients, 56 (89.83%) had migraines or medication-overuse headaches, and 3 (5.08%) had tension-type headaches. No one had trigeminal autonomic cephalalgias or other headaches. The models' overall accuracy and kappa for the ground truth were 94.92% and 0.65 (95%CI 0.21-1.00), respectively. The sensitivity, specificity, precision, and F values for migraines were 98.21%, 66.67%, 98.21%, and 98.21%, respectively. There was disagreement between the AI diagnosis and the ground truth by headache specialists in two patients. This is the first external validation of the AI headache diagnosis model. Further data collection and external validation are required to strengthen and improve its performance in real-world settings.

Quantitative Imaging Analysis of NF-κB for Mathematical Modeling Applications.

Mathematical models can integrate different types of experimental datasets, reconstitute biological systems in silico, and identify previously unknown molecular mechanisms. Over the past decade, mathematical models have been developed based on quantitative observations, such as live-cell imaging and biochemical assays. However, it is difficult to directly integrate next-generation sequencing (NGS) data. Although highly dimensional, NGS data mostly only provides a "snapshot" of cellular states. Nevertheless, the development of various methods for NGS analysis has led to much more accurate predictions of transcription factor activity and has revealed various concepts regarding transcriptional regulation. Therefore, fluorescence live-cell imaging of transcription factors can help alleviate the limitations in NGS data by supplementing temporal information, linking NGS to mathematical modeling. This chapter introduces an analytical method for quantifying dynamics of nuclear factor kappaB (NF-κB) which forms aggregates in the nucleus. The method may also be applicable to other transcription factors regulated in a similar fashion.

The Mediator subunit MED12 promotes formation of HSF1 condensates on heat shock response element arrays in heat-shocked cells.

Upon heat shock, activated heat shock transcription factor 1 (HSF1) binds to the heat shock response elements (HSEs) in the promoters of mammalian heat shock protein (HSP)-encoding genes and recruits the preinitiation complex and coactivators, including Mediator. These transcriptional regulators may be concentrated in phase-separated condensates around the promoters, but they are too minute to be characterized in detail. We herein established HSF1-/- mouse embryonic fibroblasts harbouring HSP72-derived multiple HSE arrays and visualized the condensates of fluorescent protein-tagged HSF1 with liquid-like properties upon heat shock. Using this experimental system, we demonstrate that endogenous MED12, a subunit of Mediator, is concentrated in artificial HSF1 condensates upon heat shock. Furthermore, the knockdown of MED12 markedly reduces the size of condensates, suggesting an important role for MED12 in HSF1 condensate formation.

Early Effect of Calcitonin Gene-related Peptide Monoclonal Antibodies in Migraine with Medication Overuse: A Single-center Retrospective Study.

Objective Calcitonin gene-related peptide (CGRP)-(receptor) monoclonal antibody (mAb) has been reported to reduce the frequency of medication overuse in patients with migraine. The present study investigated whether or not CGRP-mAb treatment shows early effectiveness for medication overuse headache (MOH) in Japan. Methods We retrospectively reviewed 34 patients with MOH who received preventive treatment with CGRP-mAb from June 2021 to October 2022. The International Classification of Headache Disorders, 3rd edition was used to diagnose MOH. This study was conducted at the Department of Neurology, Saitama Medical University. Patients were recruited from this specialized headache outpatient center. Results In total, 69 patients with migraine had newly introduced CGRP-mAb, and 34 patients had MOH (49.3%). The mean±standard deviation patient age was 44±15.5 years old. The study population included 24 women (70.6%). The types of CGRP-mAb used were galcanezumab in 16 patients (47.0%), fremanezumab in 10 (29.4%), and erenumab in 8 (23.5%). The mean disease duration was 19.6±13.1 years. The types of migraine diagnosis were chronic migraine in 28 patients (82.4%) and migraine with aura in 11 patients (32.4%). The mean number of headache days in the month before administration of CGRP-mAb was 22±7.7 days; 1 month after administration, the MHD was 16.9±9.1 days. The change in MHD was -5.7 days (22.7%), indicating significant improvement (p<0.05). Conclusion CGRP-mAb has been suggested as a preventive treatment for patients with MOH. Further investigation of the long-term efficacy of CGRP-mAb for MOH is needed.

A Combination of Conformation-Specific RAF Inhibitors Overcome Drug Resistance Brought about by RAF Overexpression.

Cancer cells often adapt to targeted therapies, yet the molecular mechanisms underlying adaptive resistance remain only partially understood. Here, we explore a mechanism of RAS/RAF/MEK/ERK (MAPK) pathway reactivation through the upregulation of RAF isoform (RAFs) abundance. Using computational modeling and in vitro experiments, we show that the upregulation of RAFs changes the concentration range of paradoxical pathway activation upon treatment with conformation-specific RAF inhibitors. Additionally, our data indicate that the signaling output upon loss or downregulation of one RAF isoform can be compensated by overexpression of other RAF isoforms. We furthermore demonstrate that, while single RAF inhibitors cannot efficiently inhibit ERK reactivation caused by RAF overexpression, a combination of two structurally distinct RAF inhibitors synergizes to robustly suppress pathway reactivation.

Distinct but interchangeable subpopulations of colorectal cancer cells with different growth fates and drug sensitivity.

Dynamic changes in cell properties lead to intratumor heterogeneity; however, the mechanisms of nongenetic cellular plasticity remain elusive. When the fate of each cell from colorectal cancer organoids was tracked through a clonogenic growth assay, the cells showed a wide range of growth ability even within the clonal organoids, consisting of distinct subpopulations; the cells generating large spheroids and the cells generating small spheroids. The cells from the small spheroids generated only small spheroids (S-pattern), while the cells from the large spheroids generated both small and large spheroids (D-pattern), both of which were tumorigenic. Transition from the S-pattern to the D-pattern occurred by various extrinsic triggers, in which Notch signaling and Musashi-1 played a key role. The S-pattern spheroids were resistant to chemotherapy and transited to the D-pattern upon drug treatment through Notch signaling. As the transition is linked to the drug resistance, it can be a therapeutic target.

Systems biology of protein network.

The development of comprehensive measurement technology for biomolecules and the development of computer hardware and algorithms, enhanced by human genome research, have greatly contributed to the advancement of predictive biology. However, to make that happen, it was essential to have a common concept of sharing data in a standard format. In this article, I would like to briefly review how such concepts were developed in Japan for the foundation of today's biological sciences.

Encoding and decoding NF-κB nuclear dynamics.

The NF-κB signaling pathway is crucial for cellular responses to environmental factors. Several studies have tried to decipher the mechanism of cells utilizing this pathway for information transfer and accurately encoding extracellular information that is translated into unique transcriptional programs. This fine-tuned encoding is possible owing to the complex regulatory mechanisms in the NF-κB pathway and is relayed through the nuclear dynamics of the NF-κB transcription factor. The "message" is then decoded through transcriptional and post-transcriptional regulation leading to stimulus-dependent phenotypes. Here, we reviewed recent advances on how different environmental stimuli are encoded and decoded by cells to produce distinct transcriptional responses and the important analytical techniques used in NF-κB research.