The distinct cell physiology of Bradyrhizobium at the population and cellular level.

The α-Proteobacteria belonging to Bradyrhizobium genus are microorganisms of extreme slow growth. Despite their extended use as inoculants in soybean production, their physiology remains poorly characterized. In this work, we produced quantitative data on four different isolates: B. diazoefficens USDA110, B. diazoefficiens USDA122, B. japonicum E109 and B. japonicum USDA6 which are representative of specific genomic profiles. Notably, we found conserved physiological traits conserved in all the studied isolates: (i) the lag and initial exponential growth phases display cell aggregation; (ii) the increase in specific nutrient concentration such as yeast extract and gluconate hinders growth; (iii) cell size does not correlate with culture age; and (iv) cell cycle presents polar growth. Meanwhile, fitness, cell size and in vitro growth widely vary across isolates correlating to ribosomal RNA operon number. In summary, this study provides novel empirical data that enriches the comprehension of the Bradyrhizobium (slow) growth dynamics and cell cycle.

Cell4D: a general purpose spatial stochastic simulator for cellular pathways.

BACKGROUND: With the generation of vast compendia of biological datasets, the challenge is how best to interpret 'omics data alongside biochemical and other small-scale experiments to gain meaningful biological insights. Key to this challenge are computational methods that enable domain-users to generate novel hypotheses that can be used to guide future experiments. Of particular interest are flexible modeling platforms, capable of simulating a diverse range of biological systems with low barriers of adoption to those with limited computational expertise. RESULTS: We introduce Cell4D, a spatial-temporal modeling platform combining a robust simulation engine with integrated graphics visualization, a model design editor, and an underlying XML data model capable of capturing a variety of cellular functions. Cell4D provides an interactive visualization mode, allowing intuitive feedback on model behavior and exploration of novel hypotheses, together with a non-graphics mode, compatible with high performance cloud compute solutions, to facilitate generation of statistical data. To demonstrate the flexibility and effectiveness of Cell4D, we investigate the dynamics of CEACAM1 localization in T-cell activation. We confirm the importance of Ca2+ microdomains in activating calmodulin and highlight a key role of activated calmodulin on the surface expression of CEACAM1. We further show how lymphocyte-specific protein tyrosine kinase can help regulate this cell surface expression and exploit spatial modeling features of Cell4D to test the hypothesis that lipid rafts regulate clustering of CEACAM1 to promote trans-binding to neighbouring cells. CONCLUSIONS: Through demonstrating its ability to test and generate hypotheses, Cell4D represents an effective tool to help integrate knowledge across diverse, large and small-scale datasets.

Cell sorting by active forces in a phase-field model of cell monolayers.

Cell sorting, the segregation of cells with different properties into distinct domains, is a key phenomenon in biological processes such as embryogenesis. We use a phase-field model of a confluent cell layer to study the role of activity in cell sorting. We find that a mixture of cells with extensile or contractile dipolar activity, and which are identical apart from their activity, quickly sort into small, elongated patches which then grow slowly in time. We interpret the sorting as driven by the different diffusivity of the extensile and contractile cells, mirroring the ordering of Brownian particles connected to different hot and cold thermostats. We check that the free energy is not changed by either partial or complete sorting, thus confirming that activity can be responsible for the ordering even in the absence of thermodynamic mechanisms.

Targeted Metabolomics on Rare Primary Cells.

Cellular function critically depends on metabolism, and the function of the underlying metabolic networks can be studied by measuring small molecule intermediates. However, obtaining accurate and reliable measurements of cellular metabolism, particularly in rare cell types like hematopoietic stem cells, has traditionally required pooling cells from multiple animals. A protocol now enables researchers to measure metabolites in rare cell types using only one mouse per sample while generating multiple replicates for more abundant cell types. This reduces the number of animals that are required for a given project. The protocol presented here involves several key differences over traditional metabolomics protocols, such as using 5 g/L NaCl as a sheath fluid, sorting directly into acetonitrile, and utilizing targeted quantification with rigorous use of internal standards, allowing for more accurate and comprehensive measurements of cellular metabolism. Despite the time required for the isolation of single cells, fluorescent staining, and sorting, the protocol can preserve differences among cell types and drug treatments to a large extent.

Potential therapeutic strategy for cancer: Multi-dimensional cross-talk between circRNAs and parental genes.

In many ways, circular RNAs (circRNAs) have been demonstrated to be crucial in the onset and advancement of cancer throughout the last ten years and have become a new focus of intense research in the field of RNAs. Accumulating studies have demonstrated that circRNAs can regulate parental gene expression via a variety of biological pathways. Furthermore, research into the complex interactions between circRNAs and their parental genes will shed light on their biological roles and open up new avenues for circRNAs' potential clinical translational uses. However, to date, multi-dimensional cross-talk between circRNAs and parental genes have not been systematically elucidated. Particularly intriguing is circRNA's exploration of tumor targeting, and potential therapeutic uses based on the parental gene regulation perspective. Here, we discuss their biogenesis, take a fresh look at the molecular mechanisms through which circRNAs control the expression of their parental genes in cancer. We further highlight We further highlight the latest circRNA clinical translational applications, including prognostic diagnostic markers, cancer vaccines, gDNA, and so on. Demonstrating the potential benefits and future applications of circRNA therapy.

Recording physiological history of cells with chemical labeling.

Recordings of the physiological history of cells provide insights into biological processes, yet obtaining such recordings is a challenge. To address this, we introduce a method to record transient cellular events for later analysis. We designed proteins that become labeled in the presence of both a specific cellular activity and a fluorescent substrate. The recording period is set by the presence of the substrate, whereas the cellular activity controls the degree of the labeling. The use of distinguishable substrates enabled the recording of successive periods of activity. We recorded protein-protein interactions, G protein-coupled receptor activation, and increases in intracellular calcium. Recordings of elevated calcium levels allowed selections of cells from heterogeneous populations for transcriptomic analysis and tracking of neuronal activities in flies and zebrafish.

Aneuploidy-induced cellular behaviors: Insights from Drosophila.

A balanced gene complement is crucial for proper cell function. Aneuploidy, the condition of having an imbalanced chromosome set, alters the stoichiometry of gene copy numbers and protein complexes and has dramatic consequences at the cellular and organismal levels. In humans, aneuploidy is associated with different pathological conditions including cancer, microcephaly, mental retardation, miscarriages, and aging. Over the last century, Drosophila has provided a valuable system for studying the consequences of systemic aneuploidies. More recently, it has contributed to the identification and molecular dissection of aneuploidy-induced cellular behaviors and their impact at the tissue and organismal levels. In this perspective, we review this active field of research, first by comparing knowledge from yeast, mouse, and human cells, then by highlighting the contributions of Drosophila. The aim of these discussions was to further our understanding of the functional interplay between aneuploidy, cell physiology, and tissue homeostasis in human development and disease.

Mechanism and cellular function of direct membrane binding by the ESCRT and ERES-associated Ca2+-sensor ALG-2.

Apoptosis linked Gene-2 (ALG-2) is a multifunctional intracellular Ca2+ sensor and the archetypal member of the penta-EF hand protein family. ALG-2 functions in the repair of damage to both the plasma and lysosome membranes and in COPII-dependent budding at endoplasmic reticulum exit sites (ERES). In the presence of Ca2+, ALG-2 binds to ESCRT-I and ALIX in membrane repair and to SEC31A at ERES. ALG-2 also binds directly to acidic membranes in the presence of Ca2+ by a combination of electrostatic and hydrophobic interactions. By combining giant unilamellar vesicle-based experiments and molecular dynamics simulations, we show that charge-reversed mutants of ALG-2 at these locations disrupt membrane recruitment. ALG-2 membrane binding mutants have reduced or abrogated ERES localization in response to Thapsigargin-induced Ca2+ release but still localize to lysosomes following lysosomal Ca2+ release. In vitro reconstitution shows that the ALG-2 membrane-binding defect can be rescued by binding to ESCRT-I. These data thus reveal the nature of direct Ca2+-dependent membrane binding and its interplay with Ca2+-dependent protein binding in the cellular functions of ALG-2.

Depalmitoylation and cell physiology: APT1 as a mediator of metabolic signals.

More than half of the global population is obese or overweight, especially in Western countries, and this excess adiposity disrupts normal physiology to cause chronic diseases. Diabetes, an adiposity-associated epidemic disease, affects >500 million people, and cases are projected to exceed 1 billion before 2050. Lipid excess can impact physiology through the posttranslational modification of proteins, including the reversible process of S-palmitoylation. Dynamic palmitoylation cycling requires the S-acylation of proteins by acyltransferases and the depalmitoylation of these proteins mediated in part by acyl-protein thioesterases (APTs) such as APT1. Emerging evidence points to tissue-specific roles for the depalmitoylase APT1 in maintaining homeostasis in the vasculature, pancreatic islets, and liver. These recent findings raise the possibility that APT1 substrates can be therapeutically targeted to treat the complications of metabolic diseases.

Simple visualization of submicroscopic protein clusters with a phase-separation-based fluorescent reporter.

Protein clustering plays numerous roles in cell physiology and disease. However, protein oligomers can be difficult to detect because they are often too small to appear as puncta in conventional fluorescence microscopy. Here, we describe a fluorescent reporter strategy that detects protein clusters with high sensitivity called CluMPS (clusters magnified by phase separation). A CluMPS reporter detects and visually amplifies even small clusters of a binding partner, generating large, quantifiable fluorescence condensates. We use computational modeling and optogenetic clustering to demonstrate that CluMPS can detect small oligomers and behaves rationally according to key system parameters. CluMPS detected small aggregates of pathological proteins where the corresponding GFP fusions appeared diffuse. CluMPS also detected and tracked clusters of unmodified and tagged endogenous proteins, and orthogonal CluMPS probes could be multiplexed in cells. CluMPS provides a powerful yet straightforward approach to observe higher-order protein assembly in its native cellular context. A record of this paper's transparent peer review process is included in the supplemental information.

Kinetic Modeling of Hepatic Metabolism and Simulation of Treatment Effects.

Mathematical modeling is a promising strategy to fill the experimentally unapproachable knowledge gaps about the relative contribution of various molecular processes to cellular metabolic function. To this end, we developed detailed kinetic models of the central metabolism of different cell types, comprising multiple metabolic functionalities. We used the model to simulate metabolic changes in several cell types under different experimental settings in health and disease. In this way, we show that it is possible to decipher and characterize the relative influence of various metabolic pathways and enzymes to overall metabolic performance and phenotype.Quantitative Systems Metabolism (QSM™) allows quantitative assessment of metabolic functionality and metabolic profiling based on proteomic data. Here, we describe the technique, namely, molecular resolved kinetic modeling, underlying QSM™. We explain the necessary steps for the generation of cell-specific models to functionally interpret proteomic data and point out some unresolved challenges and open questions.

Cross-talk between Helicobacter pylori and gastric cancer: a scientometric analysis.

Background: Helicobacter pylori (HP) is considered a leading risk factor for gastric cancer (GC). The aim of this article is to conduct bibliometric and visual analysis to assess scientific output, identify highly cited papers, summarize current knowledge, and explore recent hotspots and trends in HP/GC research. Methods: A bibliographic search was conducted on October 24, 2023, to retrieve relevant studies on HP/GC research between 2003 and 2022. The search terms were attached to HP and GC. The main data were from the Web of Science Core Collection (WoSCC). Data visualization was performed using Biblioshiny, VOSviewer, and Microsoft Excel. Results: In HP/GC research, 1970 papers were retrieved. The total number of papers (Np) in HP/GC was growing from 2003 to 2022. China and Japan were in the leading position and made the most contributions to HP/GC. Vanderbilt University and the US Department of Veterans Affairs had the highest Np. The most productive authors were Peek Jr Richard M. and Piazuelo M Blanca. Helicobacter received the most Np, while Gastroenterology had the most total citations (TC). High-cited publications and keyword clustering were used to identify the current status and trends in HP/GC research, while historical citation analysis provided insight into the evolution of HP/GC research. The hot topics included the effect of HP on gastric tumorigenesis and progression, the pathogenesis of HP-induced GC (HP factors), and the mechanisms by which HP affects GC (host factors). Research in the coming years could focus on topics such as autophagy, gut microbiota, immunotherapy, exosomes, epithelial-mesenchymal transition (EMT), and gamma-glutamyl transpeptidase (GGT). Conclusion: This study evaluated the global scientific output in HP/GC research and its quantitative characteristics, identified the essential works, and collected information on the current status, main focuses and emerging trends in HP/GC research to provide academics with guidance for future paths.

Postnatal Exposure to the Endocrine Disruptor Dichlorodiphenyltrichloroethane Affects Adrenomedullary Chromaffin Cell Physiology and Alters the Balance of Mechanisms Underlying Cell Renewal.

Dichlorodiphenyltrichloroethane (DDT) is a wide-spread systemic pollutant with endocrine disrupting properties. Prenatal exposure to low doses of DDT has been shown to affect adrenal medulla growth and function. The role of postnatal exposure to DDT in developmental disorders remains unclear. The aim of the present investigation is to assess growth parameters and the expression of factors mediating the function and renewal of chromaffin cells in the adult adrenal medulla of male Wistar rats exposed to the endocrine disruptor o,p'-DDT since birth until sexual maturation. The DDT-exposed rats exhibited normal growth of the adrenal medulla but significantly decreased tyrosine hydroxylase production by chromaffin cells during postnatal period. Unlike the control, the exposed rats showed enhanced proliferation and reduced expression of nuclear ß-catenin, transcription factor Oct4, and ligand of Sonic hedgehog after termination of the adrenal growth period. No expression of pluripotency marker Sox2 and absence of Ascl 1-positive progenitors were found in the adrenal medulla during postnatal ontogeny of the exposed and the control rats. The present findings indicate that an increase in proliferative activity and inhibition of the formation of reserve for chromaffin cell renewal, two main mechanisms for cell maintenance in adrenal medulla, in the adult DDT-exposed rats may reflect a compensatory reaction aimed at the restoration of catecholamine production levels. The increased proliferation of chromaffin cells in adults suggests excessive growth of the adrenal medulla. Thus, postnatal exposure to DDT alters cell physiology and increases the risk of functional insufficiency and hyperplasia of the adrenal medulla.

Proteomics: Unraveling the Cross Talk Between Innate Immunity and Disease Pathophysiology, Diagnostics, and Treatment Options.

Inflammation is crucial in diseases, and proteins play a key role in the interplay between innate immunity and pathology. This review explores how proteomics helps understanding this relationship, focusing on diagnosis and treatment. We explore the dynamic innate response and the significance of proteomic techniques in deciphering the complex network of proteins involved in prevalent diseases, including infections, cancer, autoimmune and neurodegenerative disorders. Proteomics identifies key proteins in host-pathogen interactions, shedding light on infection mechanisms and inflammation. These discoveries hold promise for diagnostic tools, therapies, and vaccines. In cancer research, proteomics reveals innate signatures associated with tumor development, immune evasion, and therapeutic response. Additionally, proteomic analysis has unveiled autoantigens and dysregulation of the innate immune system in autoimmunity, offering opportunities for early diagnosis, disease monitoring, and new therapeutic targets. Moreover, proteomic analysis has identified altered protein expression patterns in neurodegenerative diseases like Alzheimer's and Parkinson's, providing insights into potential therapeutic strategies. Proteomics of the innate immune system provides a comprehensive understanding of disease mechanisms, identifies biomarkers, and enables effective interventions in various diseases. Despite still in its early stages, this approach holds great promise to revolutionize innate immunity research and significantly improve patient outcomes across a wide range of diseases.

A data-driven approach for timescale decomposition of biochemical reaction networks.

Understanding the dynamics of biological systems in evolving environments is a challenge due to their scale and complexity. Here, we present a computational framework for the timescale decomposition of biochemical reaction networks to distill essential patterns from their intricate dynamics. This approach identifies timescale hierarchies, concentration pools, and coherent structures from time-series data, providing a system-level description of reaction networks at physiologically important timescales. We apply this technique to kinetic models of hypothetical and biological pathways, validating it by reproducing analytically characterized or previously known concentration pools of these pathways. Moreover, by analyzing the timescale hierarchy of the glycolytic pathway, we elucidate the connections between the stoichiometric and dissipative structures of reaction networks and the temporal organization of coherent structures. Specifically, we show that glycolysis is a cofactor-driven pathway, the slowest dynamics of which are described by a balance between high-energy phosphate bond and redox trafficking. Overall, this approach provides more biologically interpretable characterizations of network dynamics than large-scale kinetic models, thus facilitating model reduction and personalized medicine applications. IMPORTANCE Complex interactions within interconnected biochemical reaction networks enable cellular responses to a wide range of unpredictable environmental perturbations. Understanding how biological functions arise from these intricate interactions has been a long-standing problem in biology. Here, we introduce a computational approach to dissect complex biological systems' dynamics in evolving environments. This approach characterizes the timescale hierarchies of complex reaction networks, offering a system-level understanding at physiologically relevant timescales. Analyzing various hypothetical and biological pathways, we show how stoichiometric properties shape the way energy is dissipated throughout reaction networks. Notably, we establish that glycolysis operates as a cofactor-driven pathway, where the slowest dynamics are governed by a balance between high-energy phosphate bonds and redox trafficking. This approach enhances our understanding of network dynamics and facilitates the development of reduced-order kinetic models with biologically interpretable components.

Intraocular liver spheroids for non-invasive high-resolution in vivo monitoring of liver cell function.

Longitudinal monitoring of liver function in vivo is hindered by the lack of high-resolution non-invasive imaging techniques. Using the anterior chamber of the mouse eye as a transplantation site, we have established a platform for longitudinal in vivo imaging of liver spheroids at cellular resolution. Transplanted liver spheroids engraft on the iris, become vascularized and innervated, retain hepatocyte-specific and liver-like features and can be studied by in vivo confocal microscopy. Employing fluorescent probes administered intravenously or spheroids formed from reporter mice, we showcase the potential use of this platform for monitoring hepatocyte cell cycle activity, bile secretion and lipoprotein uptake. Moreover, we show that hepatic lipid accumulation during diet-induced hepatosteatosis is mirrored in intraocular in vivo grafts. Here, we show a new technology which provides a crucial and unique tool to study liver physiology and disease progression in pre-clinical and basic research.

[Progress and prospects of liquid-liquid phase separation in developmental diseases].

Membrane-bound organelles as well as membrane-free compartments exist in eukaryotic cells, which divide the nucleus and cytoplasm into distinct subregions and allow specific biochemical reactions to occur. The physiological mechanisms of membrane-bound organelles have been extensively characterized, but the formation and function of membrane-free compartments have not been thoroughly studied. Over the past decade, significant progress had been made in the studies about the role of liquid-liquid phase separation (LLPS) in the formation of membrane-free organelles. LLPS which serves as an aggregated separation mechanism for cellular biochemical reactions, is associated with a variety of physiological processes such as signal transduction and gene transcriptional regulation; while aberrant LLPS may contribute to the occurrence of developmental diseases. The present review investigates the role of LLPS as a mechanism of aggregation and segregation of cellular biochemical responses. The mechanisms of LLPS development and recent advances in the relationships between aberrant LLPS and developmental diseases are forward discussed, as well as how these advances may aid in the development of LLPS-based therapies.

Ketone bodies in cell physiology and cancer.

Ketogenic diets (KDs), fasting, or prolonged physical activity elevate serum ketone bodies (KBs) levels, providing an alternative fuel source for the brain and other organs. However, KBs play pleiotropic roles that go beyond their role in energy production. KBs can act as signaling metabolites, influence gene expression, proteins' posttranslational modifications (PTMs), inflammation, and oxidative stress. Here, we explore the impact of KBs on mammalian cell physiology, including aging and tissue regeneration. We also concentrate on KBs and cancer, given the extensive evidence that dietary approaches inducing ketosis, including fasting-mimicking diets (FMDs) and KDs, can prevent cancer and affect tumor progression.

CCDC88B interacts with RASAL3 and ARHGEF2 and regulates dendritic cell function in neuroinflammation and colitis.

CCDC88B is a risk factor for several chronic inflammatory diseases in humans and its inactivation causes a migratory defect in DCs in mice. CCDC88B belongs to a family of cytoskeleton-associated scaffold proteins that feature protein:protein interaction domains. Here, we identified the Rho/Rac Guanine Nucleotide Exchange Factor 2 (ARHGEF2) and the RAS Protein Activator Like 3 (RASAL3) as CCDC88B physical and functional interactors. Mice defective in Arhgef2 or Rasal3 show dampened neuroinflammation, and display altered cellular response and susceptibility to colitis; ARHGEF2 maps to a human Chromosome 1 locus associated with susceptibility to IBD. Arhgef2 and Rasal3 mutant DCs show altered migration and motility in vitro, causing either reduced (Arhgef2) or enhanced (Rasal3) migratory properties. The CCDC88B/RASAL3/ARHGEF2 complex appears to regulate DCs migration by modulating activation of RHOA, with ARHGEF2 and RASAL3 acting in opposite regulatory fashions, providing a molecular mechanism for the involvement of these proteins in DCs immune functions.

The future is on the way: ß cell function preservation for type 1 diabetes.

This phase 3 trial of PROTECT confirms the beneficial effects of teplizumab (anti-CD3 treatment) in type 1 diabetes and expands the indications from diabetes prevention (stage 2) to early treatment (stage 3). More efforts are needed to confirm the effects in the general population, with a higher dose, and with repeated dosing.