Search

Lignocellulosic materials from municipal solid waste emerge as attractive resources for anaerobic digestion biorefinery. To increase the knowledge required for establishing efficient bioprocesses, dynamics of batch fermentation by the cellulolytic bacterium Ruminiclostridium cellulolyticum were compared using three cellulosic materials, paper handkerchief, cotton discs and Whatman filter paper. Fermentation of paper handkerchief occurred the fastest and resulted in a specific metabolic profile: it resulted in the lowest acetate-to-lactate and acetate-to-ethanol ratios. By shotgun proteomic analyses of paper handkerchief and Whatman paper incubations, 151 proteins with significantly different levels were detected, including 20 of the 65 cellulosomal components, 8 non-cellulosomal CAZymes and 44 distinct extracytoplasmic proteins. Consistent with the specific metabolic profile observed, many enzymes from the central carbon catabolic pathways had higher levels in paper handkerchief incubations. Among the quantified CAZymes and cellulosomal components, 10 endoglucanases mainly from the GH9 families and 7 other cellulosomal subunits had lower levels in paper handkerchief incubations. An in-depth characterization of the materials used showed that the lower levels of endoglucanases in paper handkerchief incubations could hypothetically result from its lower crystallinity index (50%) and degree of polymerization (970). By contrast, the higher hemicellulose rate in paper handkerchief (13.87%) did not result in the enhanced expression of enzyme with xylanase as primary activity, including enzymes from the “xyl-doc” cluster. It suggests the absence, in this material, of molecular structures that specifically lead to xylanase induction. The integrated approach developed in this work shows that subtle differences among cellulosic materials regarding chemical and structural characteristics have significant effects on expressed bacterial functions, in particular the cellulolysis machinery, resulting in different metabolic patterns and degradation dynamics. [ABSTRACT FROM AUTHOR]

Cell shape plays a fundamental role in many biological processes, including adhesion, migration, division and development, but it is not clear which shape model best predicts three-dimensional cell shape in structured environments. Here, we compare different modelling approaches with experimental data. The shapes of single mesenchymal cells cultured in custom-made 3D scaffolds were compared by a Fourier method with surfaces that minimize area under the given adhesion and volume constraints. For the minimized surface model, we found marked differences to the experimentally observed cell shapes, which necessitated the use of more advanced shape models. We used different variants of the cellular Potts model, which effectively includes both surface and bulk contributions. The simulations revealed that the Hamiltonian with linear area energy outperformed the elastic area constraint in accurately modelling the 3D shapes of cells in structured environments. Explicit modelling the nucleus did not improve the accuracy of the simulated cell shapes. Overall, our work identifies effective methods for accurately modelling cellular shapes in complex environments. Author summary: Cell shape and forces have emerged as important determinants of cell function and thus their prediction is essential to describe and control the behaviour of cells in complex environments. While there exist well-established models for the two-dimensional shape of cells on flat substrates, it is less clear how cell shape should be modeled in three dimensions. Different from the philosophy of the vertex model often used for epithelial sheets, we find that models based only on cortical tension as a constant geometrical surface tension are not sufficient to describe the shape of single cells in 3D. Therefore, we employ different variants of the cellular Potts model, where either a target area is prescribed by an elastic constraint or the area energy is described with a linear surface tension. By comparing the simulated shapes to experimental images of cells in 3D scaffolds, we can identify parameters that accurately model 3D cell shape. [ABSTRACT FROM AUTHOR]

Endo-ß-1,4-glucanase AkEG21 belonging to glycosyl hydrolase family 45 (GHF45) is the most abundant cellulase in the digestive fluid of sea hare (Aplysia kurodai). The specific activity of this 21-kDa enzyme is considerably lower than those of other endo ß-1,4-glucanases in the digestive fluid of A. kurodai, therefore its role in whole cellulose hydrolysis by sea hare is still uncertain. Although AkEG21 has a catalytic domain without a cellulose binding domain, it demonstrated stable binding to cellulose fibers, similar to that of fungal cellobiohydrolase (CBH) 1 and CBH 2, which is strongly inhibited by cellohexaose, suggesting the involvement of the catalytic site in cellulose binding. Cellulose-bound AkEG21 hydrolyzed cellulose to cellobiose, cellotriose and cellotetraose, but could not digest an external substrate, azo-carboxymethyl cellulose. Cellulose hydrolysis was considerably stimulated by the synergistic action of cellulose-bound AkEG21 and AkEG45, another ß-1,4-endoglucanase present in the digestive fluid of sea hare; however no synergy in carboxymethylcellulose hydrolysis was observed. When AkEG21 was removed from the digestive fluid by immunoprecipitation, the cellulose hydrolyzing activity of the fluid was significantly reduced, indicating a critical role of AkEG21 in cellulose hydrolysis by A. kurodai. These findings suggest that AkEG21 is a processive endoglucanase functionally equivalent to the CBH, which provides a CBH-independent mechanism for the mollusk to digest seaweed cellulose to glucose. [ABSTRACT FROM AUTHOR]

Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other hand, machine learning, complementary to metabolic modeling necessitates large amounts of data. Building such a database for metabolic engineering designs requires significant manpower and is prone to human errors and bias. We propose an approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate). Using engineered E. coli as an example, we manually extracted and curated a data set comprising about 1200 experimentally realized cell factories from ~100 papers. We furthermore augmented the key design features (e.g., genetic modifications and bioprocess variables) extracted from literature with additional features derived from running the genome-scale metabolic model iML1515 simulations with constraints that match the experimental data. Then, data augmentation and ensemble learning (e.g., support vector machines, gradient boosted trees, and neural networks in a stacked regressor model) are employed to alleviate the challenges of sparse, non-standardized, and incomplete data sets, while multiple correspondence analysis/principal component analysis are used to rank influential factors on bio-production. The hybrid framework demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions (Pearson correlation coefficients between 0.8 and 0.93 on new data not seen by the model). [ABSTRACT FROM AUTHOR]

Elucidating the causal mechanisms responsible for disease can reveal potential therapeutic targets for pharmacological intervention and, accordingly, guide drug repositioning and discovery. In essence, the topology of a network can reveal the impact a drug candidate may have on a given biological state, leading the way for enhanced disease characterization and the design of advanced therapies. Network-based approaches, in particular, are highly suited for these purposes as they hold the capacity to identify the molecular mechanisms underlying disease. Here, we present drug2ways, a novel methodology that leverages multimodal causal networks for predicting drug candidates. Drug2ways implements an efficient algorithm which reasons over causal paths in large-scale biological networks to propose drug candidates for a given disease. We validate our approach using clinical trial information and demonstrate how drug2ways can be used for multiple applications to identify: i) single-target drug candidates, ii) candidates with polypharmacological properties that can optimize multiple targets, and iii) candidates for combination therapy. Finally, we make drug2ways available to the scientific community as a Python package that enables conducting these applications on multiple standard network formats. Author summary: At any given time, a large set of biomolecules are interacting in ways that give rise to the normal functioning of a cell. By representing biological interactions as networks, we can reconstruct the complex molecular mechanisms that govern the physiology of a cell. These networks can then be analyzed to understand where the system fails and how that can give rise to disease. Similarly, using computational methods, we can also enrich these networks with drugs, diseases and disease phenotypes to estimate how a drug, or a combination of drugs, would behave in a system and whether it can be used to treat or alleviate the symptoms of a disease. In this paper, we present drug2ways, a novel methodology designed for drug discovery applications, that exploits the information contained in a biological network comprising causal relations between drugs, proteins, and diseases. Employing these networks and an efficient algorithm, drugways2 traverses over the ensemble of paths between a drug and a disease to propose the drugs that are most likely to cure the disease based on the information contained in the network. We hypothesize that this ensemble of paths could be used to simulate the mechanism of action of a drug and the directionality inferred through these paths could be used as a proxy to identify drug candidates. Through several experiments, we demonstrate how drug2ways can be used to find novel ways of using existing drugs, identify drug candidates, optimize treatments by targeting multiple disease phenotypes, and propose combination therapies. Owing to the generalizability of the algorithm and the accompanying software, we ambition that drug2ways could be applied to a variety of biological networks to generate new hypotheses for drug discovery and a better understanding of their mechanisms of action. [ABSTRACT FROM AUTHOR]

Cell membranes are flexible and often undergo large-scale morphological changes during processes like mitosis, protrusion and retraction, or vesicle fusion. Mathematical modeling of cell membranes depends on a representation of the free-form surface by discrete meshes. During morphological changes, these meshes must be adjusted under the minimization of the total free energy. Current methodology for meshing is limited in one of two ways: 1) Free energy-dependent methods have no restriction on the mesh geometry. The resulting irregular meshes cause artifacts in follow-up models of morphodynamics. 2) Geometry-dependent methods maintain mesh quality but violate the physics of free energy minimization. To fill this gap, we regulate mesh geometries via a free-energy-determined remeshing process: adding and removing mesh elements upon morphological changes based on barrier crossings in a double-barrier potential between neighboring vertices in the meshes. We test the method's robustness by reproducing the morphodynamics of red blood cells and vesicle fusions; and we demonstrate the method's adaptability by simulating the formation of filopodia, lamellipodia and invaginations. Finally, we use the method to study a mechanical decoupling effect of two connected membrane tethers that has been recently observed experimentally, but has not been mechanistically explained in the context of a complete membrane surface. We propose a biophysical model that strengthens the decoupling effect and broadens the original interpretation of the experiment. The method is developed in C/Matlab and distributed via https://github.com/DanuserLab/biophysicsModels. Author summary: Many cellular functions require morphological features such as tubulations, protrusions, and invaginations. These features emerge from membranes reshaped by curvature-inducing proteins, osmotic pressure, and other mechanical factors. To elucidate these morphodynamics mathematical models describing the relation between morphology, mechanics, and molecular compoisition are indispensable. The key to such models is discretizing the membrane. One popular discretization relies on meshing membranes into fully connected triangles. When necessary, the mesh configuration is updated via remeshing operations. These include adjusting the number of meshes, rearranging the mesh-to-mesh connectivity, and keeping the individual triangles nearly equilateral. Such flexibility and geometry is necessary accuracy wise. Current remeshing algorithms lack geometrical consistency or rely on user-defined rules that defy physical laws. Here, we propose a new algorithm that marries the needs for geometrical and physical accuracy in a double-barrier potential Vin. The two barriers confine the edges in the triangles to ensure their geometrical consistency. Large enough mechanical perturbations cause barrier crossings that trigger remeshing to restore the perturbed geometry. This physics-based algorithm is robust and more efficient than rule-based algorithms. We implement the algorithm to simulate distinct morphologies and to examine how lipid diffusion controls the mechanical coupling of distant locations on the membrane. [ABSTRACT FROM AUTHOR]

Information transmission in cells occurs quite accurately even when concentration changes are “read” by individual binding sites. In this paper we study ligand number and site occupancy fluctuations when ligands diffuse and react going beyond the analyses that focus on their asymptotic decay. In this way we show that, for immobile binding sites, fluctuations in the number of bound molecules decay on a relatively fast scale before the asymptotic behavior kicks in. This result can explain the observed co-existence of highly fluctuating instantaneous transcriptional activities with accumulated mRNA concentrations that have relatively small noise levels. We also show that the initial stages of the decay in the bound molecule number fluctuations have one or two characteristic timescales depending on the concentration of free molecules. This transition can explain the changes in enzyme activity observed at the single molecule level. [ABSTRACT FROM AUTHOR]

Dynamic properties are essential for microtubule (MT) physiology. Current techniques for in vivo imaging of MTs present intrinsic limitations in elucidating the isotype-specific nuances of tubulins, which contribute to their versatile functions. Harnessing the power of the AlphaFold2 pipeline, we engineered a strategy for the minimally invasive fluorescence labeling of endogenous tubulin isotypes or those harboring missense mutations. We demonstrated that a specifically designed 16-amino acid linker, coupled with sfGFP11 from the split-sfGFP system and integration into the H1-S2 loop of tubulin, facilitated tubulin labeling without compromising MT dynamics, embryonic development, or ciliogenesis in Caenorhabditis elegans. Extending this technique to human cells and murine oocytes, we visualized MTs with the minimal background fluorescence and a pathogenic tubulin isoform with fidelity. The utility of our approach across biological contexts and species set an additional paradigm for studying tubulin dynamics and functional specificity, with implications for understanding tubulin-related diseases known as tubulinopathies. GFP-tagged tubulins have been widely used to monitor and visualize tubulin isotypes, but this is known to interfere with their cellular functions. This study describes a functional labeling strategy, guided by AlphaFold2 structural predictions, to label endogenous tubulins across diverse species while preserving functionality. [ABSTRACT FROM AUTHOR]

Development of resistance and tolerance to antifungal drugs in Candida albicans can compromise treatment of infections caused by this pathogenic yeast species. The uniquely expanded C. albicans TLO gene family is comprised of 14 paralogous genes which encode Med2, a subunit of the multiprotein Mediator complex which is involved in the global control of transcription. This study investigates the acquisition of fluconazole tolerance in a mutant in which the entire TLO gene family has been deleted. This phenotype was reversed to varying degrees upon reintroduction of representative members of the alpha- and beta-TLO clades (i.e. TLO1 and TLO2), but not by TLO11, a gamma-clade representative. Comparative RNA sequencing analysis revealed changes in the expression of genes involved in a range of cellular functions, including ergosterol biosynthesis, mitochondrial function, and redox homeostasis. This was supported by the results of mass spectrometry analysis, which revealed alterations in sterol composition of the mutant cell membrane. Our data suggest that members of the C. albicans TLO gene family are involved in the control of ergosterol biosynthesis and mitochondrial function and may play a role in the responses of C. albicans to azole antifungal agents. [ABSTRACT FROM AUTHOR]

RNA pseudoknots play a crucial role in various cellular functions. Established pseudoknots show significant variation in both size and structural complexity. Specifically, three-stemmed pseudoknots are characterized by an additional stem-loop embedded in their structure. Recent findings highlight these pseudoknots as bacterial riboswitches and potent stimulators for programmed ribosomal frameshifting in RNA viruses like SARS-CoV2. To investigate the possible presence of functional three-stemmed pseudoknots in human mRNAs, we employed in-house developed computational methods to detect such structures within a dataset comprising 21,780 full-length human mRNA sequences. Numerous three-stemmed pseudoknots were identified. A selected set of 14 potential instances are presented, in which the start codon of the mRNA is found in close proximity either upstream, downstream, or within the identified three-stemmed pseudoknot. These pseudoknots likely play a role in translational initiation regulation. The probability of their existence gains support from their ranking as the most stable pseudoknot identified in the entire mRNA sequence, structural conservation across homologous mRNAs, stereochemical feasibility as demonstrated by structural modeling, and classification as members of the CPK-1 pseudoknot family, which includes many well-established pseudoknots. Furthermore, in four of the mRNAs, two or three closely spaced or tandem three-stemmed pseudoknots were identified. These findings suggest the frequent occurrence of three-stemmed pseudoknots in human mRNAs. A stepwise co-transcriptional folding mechanism is proposed for the formation of a three-stemmed pseudoknot structure. Our results not only provide fresh insights into the structures and functions of pseudoknots but also unveil the potential to target pseudoknots for treating human diseases. [ABSTRACT FROM AUTHOR]

Cancer initiates as a consequence of genomic mutations and its subsequent progression relies in part on increased production of ribosomes to maintain high levels of protein synthesis for unchecked cell growth. Recently, cytidine deaminases have been uncovered as sources of mutagenesis in cancer. In an attempt to form a connection between these 2 cancer driving processes, we interrogated the cytidine deaminase family of proteins for potential roles in human ribosome biogenesis. We identified and validated APOBEC3A and APOBEC4 as novel ribosome biogenesis factors through our laboratory's established screening platform for the discovery of regulators of nucleolar function in MCF10A cells. Through siRNA depletion experiments, we highlight APOBEC3A's requirement in making ribosomes and specific role within the processing and maturation steps that form the large subunit 5.8S and 28S ribosomal (r)RNAs. We demonstrate that a subset of APOBEC3A resides within the nucleolus and associates with critical ribosome biogenesis factors. Mechanistic insight was revealed by transient overexpression of both wild-type and a catalytically dead mutated APOBEC3A, which both increase cell growth and protein synthesis. Through an innovative nuclear RNA sequencing methodology, we identify only modest predicted APOBEC3A C-to-U target sites on the pre-rRNA and pre-mRNAs. Our work reveals a potential direct role for APOBEC3A in ribosome biogenesis likely independent of its editing function. More broadly, we found an additional function of APOBEC3A in cancer pathology through its function in ribosome biogenesis, expanding its relevance as a target for cancer therapeutics. Cancer initiation is driven by mutations and progression relies on increased protein synthesis, enabled in part by increased production of ribosomes. This study links both processes by showing that cytidine deaminase APOBEC3A, a source of cancer-initiating mutations, also contributes to cancer progression by promoting ribosome biogenesis. [ABSTRACT FROM AUTHOR]

As antimicrobial resistance increases, it is crucial to develop new treatment strategies to counter the emerging threat. In this paper, we consider combination therapies involving conventional antibiotics and debridement, coupled with a novel anti-adhesion therapy, and their use in the treatment of antimicrobial resistant burn wound infections. Our models predict that anti-adhesion–antibiotic–debridement combination therapies can eliminate a bacterial infection in cases where each treatment in isolation would fail. Antibiotics are assumed to have a bactericidal mode of action, killing bacteria, while debridement involves physically cleaning a wound (e.g. with a cloth); removing free bacteria. Anti-adhesion therapy can take a number of forms. Here we consider adhesion inhibitors consisting of polystyrene microbeads chemically coupled to a protein known as multivalent adhesion molecule 7, an adhesin which mediates the initial stages of attachment of many bacterial species to host cells. Adhesion inhibitors competitively inhibit bacteria from binding to host cells, thus rendering them susceptible to removal through debridement. An ordinary differential equation model is developed and the antibiotic-related parameters are fitted against new in vitro data gathered for the present study. The model is used to predict treatment outcomes and to suggest optimal treatment strategies. Our model predicts that anti-adhesion and antibiotic therapies will combine synergistically, producing a combined effect which is often greater than the sum of their individual effects, and that anti-adhesion–antibiotic–debridement combination therapy will be more effective than any of the treatment strategies used in isolation. Further, the use of inhibitors significantly reduces the minimum dose of antibiotics required to eliminate an infection, reducing the chances that bacteria will develop increased resistance. Lastly, we use our model to suggest treatment regimens capable of eliminating bacterial infections within clinically relevant timescales. [ABSTRACT FROM AUTHOR]

The subset of pro-inflammatory B cells, called late memory, tissue-like or double negative (DN), accumulates in the blood of elderly individuals. Here we show that DN B cells do not proliferate and do not make antibodies to influenza antigens, but they secrete antibodies with autoimmune reactivity, in agreement with their membrane phenotype (CD95+CD21-CD11c+) and their spontaneous expression of the transcription factor T-bet. These cells also increase in the blood of individuals with obesity and autoimmune diseases, but causative mechanisms and signaling pathways involved are known only in part. In the present paper we compare frequencies and metabolic requirements of these cells in the blood of healthy individuals of different ages and in the blood and the subcutaneous adipose tissue (SAT) of individuals with obesity. Results show that DN B cells from young individuals have minimal metabolic requirements, DN B cells from elderly and obese individuals utilize higher amounts of glucose to perform autoimmune antibody production and enroll in aerobic glycolysis to support their function. DN B cells from the SAT have the highest metabolic requirements as they activate oxidative phosphorylation, aerobic glycolysis and fatty acid oxidation. DN B cells from the SAT also show the highest levels of ROS and the highest levels of phosphorylated AMPK (5’-AMP activated kinase) and Sestrin 1, both able to mitigate stress and cell death. This metabolic advantage drives DN B cell survival and function (secretion of autoimmune antibodies). [ABSTRACT FROM AUTHOR]

The conduction of electrical signals through cardiac tissue is essential for maintaining the function of the heart, and conduction abnormalities are known to potentially lead to life-threatening arrhythmias. The properties of cardiac conduction have therefore been the topic of intense study for decades, but a number of questions related to the mechanisms of conduction still remain unresolved. In this paper, we demonstrate how the so-called EMI model may be used to study some of these open questions. In the EMI model, the extracellular space, the cell membrane, the intracellular space and the cell connections are all represented as separate parts of the computational domain, and the model therefore allows for study of local properties that are hard to represent in the classical homogenized bidomain or monodomain models commonly used to study cardiac conduction. We conclude that a non-uniform sodium channel distribution increases the conduction velocity and decreases the time delays over gap junctions of reduced coupling in the EMI model simulations. We also present a theoretical optimal cell length with respect to conduction velocity and consider the possibility of ephaptic coupling (i.e. cell-to-cell coupling through the extracellular potential) acting as an alternative or supporting mechanism to gap junction coupling. We conclude that for a non-uniform distribution of sodium channels and a sufficiently small intercellular distance, ephaptic coupling can influence the dynamics of the sodium channels and potentially provide cell-to-cell coupling when the gap junction connection is absent. [ABSTRACT FROM AUTHOR]

Demosponges possess a leucon-type canal system which is characterized by a highly complex network of canal segments and choanocyte chambers. As sponges are sessile filter feeders, their aquiferous system plays an essential role in various fundamental physiological processes. Due to the morphological and architectural complexity of the canal system and the strong interdependence between flow conditions and anatomy, our understanding of fluid dynamics throughout leuconoid systems is patchy. This paper provides comprehensive morphometric data on the general architecture of the canal system, flow measurements and detailed cellular anatomical information to help fill in the gaps. We focus on the functional cellular anatomy of the aquiferous system and discuss all relevant cell types in the context of hydrodynamic and evolutionary constraints. Our analysis is based on the canal system of the tropical demosponge Tethya wilhelma, which we studied using scanning electron microscopy. We found a hitherto undescribed cell type, the reticuloapopylocyte, which is involved in flow regulation in the choanocyte chambers. It has a highly fenestrated, grid-like morphology and covers the apopylar opening. The minute opening of the reticuloapopylocyte occurs in an opened, intermediate and closed state. These states permit a gradual regulation of the total apopylar opening area. In this paper the three states are included in a theoretical study into flow conditions which aims to draw a link between functional cellular anatomy, the hydrodynamic situation and the regular body contractions seen in T. wilhelma. This provides a basis for new hypotheses regarding the function of bypass elements and the role of hydrostatic pressure in body contractions. Our study provides insights into the local and global flow conditions in the sponge canal system and thus enhances current understanding of related physiological processes. [ABSTRACT FROM AUTHOR]

Knowledge of how a population of cancerous cells progress through the cell cycle is vital if the population is to be treated effectively, as treatment outcome is dependent on the phase distributions of the population. Estimates on the phase distribution may be obtained experimentally however the errors present in these estimates may effect treatment efficacy and planning. If mathematical models are to be used to make accurate, quantitative predictions concerning treatments, whose efficacy is phase dependent, knowledge of the phase distribution is crucial. In this paper it is shown that two different transition rates at the - checkpoint provide a good fit to a growth curve obtained experimentally. However, the different transition functions predict a different phase distribution for the population, but both lying within the bounds of experimental error. Since treatment outcome is effected by the phase distribution of the population this difference may be critical in treatment planning. Using an age-structured population balance approach the cell cycle is modelled with particular emphasis on the - checkpoint. By considering the probability of cells transitioning at the - checkpoint, different transition functions are obtained. A suitable finite difference scheme for the numerical simulation of the model is derived and shown to be stable. The model is then fitted using the different probability transition functions to experimental data and the effects of the different probability transition functions on the model's results are discussed. [ABSTRACT FROM AUTHOR]

Computational models of normal liver function and xenobiotic induced liver damage are increasingly being used to interpret in vitro and in vivo data and as an approach to the de novo prediction of the liver’s response to xenobiotics. The microdosimetry (dose at the level of individual cells) of xenobiotics vary spatially within the liver because of both compound-independent and compound-dependent factors. In this paper, we build model liver lobules to investigate the interplay between vascular structure, blood flow and cellular transport that lead to regional variations in microdosimetry. We then compared simulation results obtained using this complex spatial model with a simpler linear pipe model of a sinusoid and a very simple single box model. We found that variations in diffusive transport, transporter-mediated transport and metabolism, coupled with complex liver sinusoid architecture and blood flow distribution, led to three essential patterns of xenobiotic exposure within the virtual liver lobule: (1) lobular-wise uniform, (2) radially varying and (3) both radially and azimuthally varying. We propose to use these essential patterns of exposure as a reference for selection of model representations when a computational study involves modeling detailed hepatic responses to xenobiotics. [ABSTRACT FROM AUTHOR]

Over the last decades, predictive microbiology has made significant advances in the mathematical description of microbial spoiler and pathogen dynamics in or on food products. Recently, the focus of predictive microbiology has shifted from a (semi-)empirical population-level approach towards mechanistic models including information about the intracellular metabolism in order to increase model accuracy and genericness. However, incorporation of this subpopulation-level information increases model complexity and, consequently, the required run time to simulate microbial cell and population dynamics. In this paper, results of metabolic flux balance analyses (FBA) with a genome-scale model are used to calibrate a low-complexity linear model describing the microbial growth and metabolite secretion rates of Escherichia coli as a function of the nutrient and oxygen uptake rate. Hence, the required information about the cellular metabolism (i.e., biomass growth and secretion of cell products) is selected and included in the linear model without incorporating the complete intracellular reaction network. However, the applied FBAs are only representative for microbial dynamics under specific extracellular conditions, viz., a neutral medium without weak acids at a temperature of 37℃. Deviations from these reference conditions lead to metabolic shifts and adjustments of the cellular nutrient uptake or maintenance requirements. This metabolic dependency on extracellular conditions has been taken into account in our low-complex metabolic model. In this way, a novel approach is developed to take the synergistic effects of temperature, pH, and undissociated acids on the cell metabolism into account. Consequently, the developed model is deployable as a tool to describe, predict and control E. coli dynamics in and on food products under various combinations of environmental conditions. To emphasize this point,three specific scenarios are elaborated: (i) aerobic respiration without production of weak acid extracellular metabolites, (ii) anaerobic fermentation with secretion of mixed acid fermentation products into the food environment, and (iii) respiro-fermentative metabolic regimes in between the behaviors at aerobic and anaerobic conditions. [ABSTRACT FROM AUTHOR]

The continuous development of high electrical equipment towards high power output requires better heat dissipation performance of internal insulation structure. It challenges the traditional paper-based insulating materials, with poor thermal conductivity. Introducing thermally conductive and electrically insulating filler into cellulose-based insulating material can enhance heat conduction performance. This work provided a method to prepare thermally conductive and electrically insulating BN/cellulosic fibre composites. And the thermal conductivity of the composites was remarkably increased via grafting APTES and adding dual-sized fillers. The thermal conductivity of the composite reached 0.682 W/(m•k) that increased by 387% with h-BN loading of 41.08 wt%. Simultaneously, BN fillers improved the insulating properties of the resultant composites. The dielectric constant, breaking strength of and volume resistivity of the composites reached 4.75, 9.2 kV/mm-1 and 4.72×1014 Ω•m, respectively. The resultant insulating material which has better heat conduction property may have a vast potential for future development in electrical equipment. [ABSTRACT FROM AUTHOR]

FAcilitates Chromatin Transcription (FACT) is a complex of SSRP1 and SPT16 that is involved in chromatin remodeling during transcription, replication, and DNA repair. FACT has been mostly studied in cell-free or single cell model systems because general FACT knockout (KO) is embryonically lethal (E3.5). FACT levels are limited to the early stages of development and stem cell niches of adult tissues. FACT is upregulated in poorly differentiated aggressive tumors. Importantly, FACT inhibition (RNAi) is lethal for tumors but not normal cells, making FACT a lucrative target for anticancer therapy. To develop a better understanding of FACT function in the context of the mammalian organism under normal physiological conditions and in disease, we aimed to generate a conditional FACT KO mouse model. Because SPT16 stability is dependent on the SSRP1-SPT16 association and the presence of SSRP1 mRNA, we targeted the Ssrp1 gene using a CreERT2- LoxP approach to generate the FACT KO model. Here, we highlight the limitations of the CreERT2-LoxP (Rosa26) system that we encountered during the generation of this model. In vitro studies showed an inefficient excision rate of ectopically expressed CreERT2 (retroviral CreERT2) in fibroblasts with homozygous floxed Ssrp1. In vitro and in vivo studies showed that the excision efficiency could only be increased with germline expression of two alleles of Rosa26CreERT2. The expression of one germline Rosa26CreERT2 allele led to the incomplete excision of Ssrp1. The limited efficiency of the CreERT2-LoxP system may be sufficient for studies involving the deletion of genes that interfere with cell growth or viability due to the positive selection of the phenotype. However, it may not be sufficient for studies that involve the deletion of genes supporting growth, or those crucial for development. Although CreERT2-LoxP is broadly used, it has limitations that have not been widely discussed. This paper aims to encourage such discussions. [ABSTRACT FROM AUTHOR]

Recent experiments showed that engineered Escherichia coli colonies grow and self-organize into periodic stripes with high and low cell densities in semi-solid agar. The stripes develop sequentially behind a radially propagating colony front, similar to the formation of many other periodic patterns in nature. These bacteria were created by genetically coupling the intracellular chemotaxis pathway of wild-type cells with a quorum sensing module through the protein CheZ. In this paper, we develop multiscale models to investigate how this intracellular pathway affects stripe formation. We first develop a detailed hybrid model that treats each cell as an individual particle and incorporates intracellular signaling via an internal ODE system. To overcome the computational cost of the hybrid model caused by the large number of cells involved, we next derive a mean-field PDE model from the hybrid model using asymptotic analysis. We show that this analysis is justified by the tight agreement between the PDE model and the hybrid model in 1D simulations. Numerical simulations of the PDE model in 2D with radial symmetry agree with experimental data semi-quantitatively. Finally, we use the PDE model to make a number of testable predictions on how the stripe patterns depend on cell-level parameters, including cell speed, cell doubling time and the turnover rate of intracellular CheZ. [ABSTRACT FROM AUTHOR]

As the development of new classes of antibiotics slows, bacterial resistance to existing antibiotics is becoming an increasing problem. A potential solution is to develop treatment strategies with an alternative mode of action. We consider one such strategy: anti-adhesion therapy. Whereas antibiotics act directly upon bacteria, either killing them or inhibiting their growth, anti-adhesion therapy impedes the binding of bacteria to host cells. This prevents bacteria from deploying their arsenal of virulence mechanisms, while simultaneously rendering them more susceptible to natural and artificial clearance. In this paper, we consider a particular form of anti-adhesion therapy, involving biomimetic multivalent adhesion molecule 7 coupled polystyrene microbeads, which competitively inhibit the binding of bacteria to host cells. We develop a mathematical model, formulated as a system of ordinary differential equations, to describe inhibitor treatment of a Pseudomonas aeruginosa burn wound infection in the rat. Benchmarking our model against in vivo data from an ongoing experimental programme, we use the model to explain bacteria population dynamics and to predict the efficacy of a range of treatment strategies, with the aim of improving treatment outcome. The model consists of two physical compartments: the host cells and the exudate. It is found that, when effective in reducing the bacterial burden, inhibitor treatment operates both by preventing bacteria from binding to the host cells and by reducing the flux of daughter cells from the host cells into the exudate. Our model predicts that inhibitor treatment cannot eliminate the bacterial burden when used in isolation; however, when combined with regular or continuous debridement of the exudate, elimination is theoretically possible. Lastly, we present ways to improve therapeutic efficacy, as predicted by our mathematical model. [ABSTRACT FROM AUTHOR]

Lipids are essential components of biological membranes that present a wide diversity in eukaryotic cells. Recent impressive advances in lipid biochemistry and biophysics have enabled a refocus of our view of lipids as functional units for cellular activity. However, the gap between molecular and cellular processes remains to be bridged. Here, 2 papers meet the burden of proof that choline transporters participate in local lipid composition modifications at the trans-Golgi network, an intracellular compartment that serves as the main sorting station in the cell. Localization of choline transporters to this precise compartment could be a way for plant cells to quickly modify the membrane lipid composition and asymmetry during both the allocation of cargos and the recruitment of trafficking machineries into distinct subcellular pathways. [ABSTRACT FROM AUTHOR]

The multiple extremes resistant bacterium Deinococcus radiodurans is able to withstand harsh conditions of simulated outer space environment. The Tanpopo orbital mission performs a long-term space exposure of D. radiodurans aiming to investigate the possibility of interplanetary transfer of life. The revealing of molecular machinery responsible for survivability of D. radiodurans in the outer space environment can improve our understanding of underlying stress response mechanisms. In this paper, we have evaluated the molecular response of D. radiodurans after the exposure to space-related conditions of UVC irradiation and vacuum. Notably, scanning electron microscopy investigations showed that neither morphology nor cellular integrity of irradiated cells was affected, while integrated proteomic and metabolomic analysis revealed numerous molecular alterations in metabolic and stress response pathways. Several molecular key mechanisms of D. radiodurans, including the tricarboxylic acid cycle, the DNA damage response systems, ROS scavenging systems and transcriptional regulators responded in order to cope with the stressful situation caused by UVC irradiation under vacuum conditions. These results reveal the effectiveness of the integrative proteometabolomic approach as a tool in molecular analysis of microbial stress response caused by space-related factors. [ABSTRACT FROM AUTHOR]

Disturbed flow can eliminate the alignment of endothelial cells in the direction of laminar flow, and significantly impacts on atherosclerosis in collateral arteries near the bifurcation and high curvature regions. While shear stress induced Rac polarity has been shown to play crucial roles in cell polarity and migration, little is known about the spatiotemporal map of Rac under disturbed flow, and the mechanism of flow-induced cell polarity still needs to be elucidated. In this paper, disturbed flow or laminar flow with 15 dyn/cm2 of average shear stress was applied on bovine aortic endothelial cells (BAECs) for 30 minutes. A genetically-encoded PAK-PBD-GFP reporter was transfected into BAECs to visualize the real-time activation of Rac in living cell under fluorescence microscope. The imaging of the fluorescence intensity was analyzed by Matlab and the normalized data was converted into 3D spatiotemporal map. Then the changes of data upon chemical interference were fitted with logistic curve to explore the rule and mechanism of Rac polarity under laminar or disturbed flow. A polarized Rac activation was observed at the downstream edge along the laminar flow, which was enhanced by benzol alcohol-enhanced membrane fluidity but inhibited by nocodazole-disrupted microtubules or cholesterol-inhibited membrane fluidity, while no obvious polarized Rac activation could be found upon disturbed flow application. It is concluded that disturbed flow inhibits the flow-induced Rac polarized activation, which is related to the interaction of cell membrane and cytoskeleton, especially the microtubules. [ABSTRACT FROM AUTHOR]

AXL+ Siglec-6+ dendritic cells (ASDC) are novel myeloid DCs which can be subdivided into CD11c+ and CD123+ expressing subsets. We showed for the first time that these two ASDC subsets are present in inflamed human anogenital tissues where HIV transmission occurs. Their presence in inflamed tissues was supported by single cell RNA analysis of public databases of such tissues including psoriasis diseased skin and colorectal cancer. Almost all previous studies have examined ASDCs as a combined population. Our data revealed that the two ASDC subsets differ markedly in their functions when compared with each other and to pDCs. Relative to their cell functions, both subsets of blood ASDCs but not pDCs expressed co-stimulatory and maturation markers which were more prevalent on CD11c+ ASDCs, thus inducing more T cell proliferation and activation than their CD123+ counterparts. There was also a significant polarisation of naïve T cells by both ASDC subsets toward Th2, Th9, Th22, Th17 and Treg but less toward a Th1 phenotype. Furthermore, we investigated the expression of chemokine receptors that facilitate ASDCs and pDCs migration from blood to inflamed tissues, their HIV binding receptors, and their interactions with HIV and CD4 T cells. For HIV infection, within 2 hours of HIV exposure, CD11c+ ASDCs showed a trend in more viral transfer to T cells than CD123+ ASDCs and pDCs for first phase transfer. However, for second phase transfer, CD123+ ASDCs showed a trend in transferring more HIV than CD11c+ ASDCs and there was no viral transfer from pDCs. As anogenital inflammation is a prerequisite for HIV transmission, strategies to inhibit ASDC recruitment into inflamed tissues and their ability to transmit HIV to CD4 T cells should be considered. Author summary: This study highlights the significance of AXL+ Siglec-6+ dendritic cells (ASDC) in HIV transmission, particularly in inflamed peripheral tissues such as anogenital tissues, where HIV transmission is prevalent. It reveals that ASDCs are present in inflamed human tissues, including psoriasis affected skin, colorectal cancer and anogenital tissues. However, they are absent in uninflamed tissues. Furthermore, we investigated the expression of chemokine receptors that facilitate ASDC migration from blood to inflamed tissues, and their interactions with HIV and CD4 T cells. Notably, different subsets of ASDCs exhibit different expression levels of HIV binding receptors and showed trends of different phases of HIV transmission to T cells. Understanding ASDC involvement in HIV transmission could provide valuable insights for developing strategies to inhibit their recruitment to inflamed tissues and their ability to transmit the virus to CD4 T cells, potentially offering new avenues for HIV prevention and treatment. [ABSTRACT FROM AUTHOR]

Retinal detachment (RD) is the separation of the neural layer from the retinal pigmented epithelium thereby preventing the supply of nutrients to the cells within the neural layer of the retina. In vertebrates, primary photoreceptor cells consisting of rods and cones undergo daily renewal of their outer segment through the addition of disc-like structures and shedding of these discs at their distal end. When the retina detaches, the outer segment of these cells begins to degenerate and, if surgical procedures for reattachment are not done promptly, the cells can die and lead to blindness. The precise effect of RD on the renewal process is not well understood. Additionally, a time frame within which reattachment of the retina can restore proper photoreceptor cell function is not known. Focusing on rod cells, we propose a mathematical model to clarify the influence of retinal detachment on the renewal process. Our model simulation and analysis suggest that RD stops or significantly reduces the formation of new discs and that an alternative removal mechanism is needed to explain the observed degeneration during RD. Sensitivity analysis of our model parameters points to the disc removal rate as the key regulator of the critical time within which retinal reattachment can restore proper photoreceptor cell function. [ABSTRACT FROM AUTHOR]

Achillea fragrantissima is a shrub plant that belongs to the Asteraceae family in Arabia and Egypt. It is used as folk medicine and is a good source of phenolic acids, flavonoids, and some active compounds. To investigate the anti-cancer effect of A.fragrantissima on breast cancer MCF-7 cells and find the critical mechanism involved in apoptosis. The toxicity and pharmacokinetic studies of ethanolic extract of A.fragrantissima was examined for anti-breast cancer properties. In turn, cytotoxicity and cell viability were achieved by the MTT method. Furthermore, the trypan blue exclusion and microscopy examination proved the presence of apoptotic cells. Again, fluorescent staining such as AO/EtBr, DCFH-DA, Rho-123, and Hoechst-33342 reveals the cellular cytoplasmic disciplines upon A. fragrantissima effect. Moreover, cellular functioning tests like wound healing, colony formation, and Transwell invasion assay were demonstrated. In addition, the qRT-PCR technique authenticates the A. fragrantissima -induced apoptotic network genes (Caspase-3, Caspase-8, Caspase-9, Cytochrome c, BCL-2, BID, BAX, PARP, PTEN, PI3K, and Akt) expression were evaluated. Mainly, the Immunoblot technique proved the expressed level of apoptotic proteins such as cleaved PARP, CYCS, and FADD. This study confirmed that the A. fragrantissima exerts cytotoxicity at 20 μg/mL for 24 hrs in MCF-7 cells. Also, decreases cellular viability, producing apoptotic cells and damaged cellular surfaces with dead matter. Consequently, it creates ROS species accumulation, loss of mitochondrial membrane potential, and fragmentation of DNA in MCF-7 cells. Furthermore, it arrests cell migration, induces colony-forming ability loss, and suppresses cell invasion. In addition, A. fragrantissima significantly upregulates genes such as caspase-3, 9, cytochrome c, BID, BAX, and PTEN while downregulating the Pi3K/ Akt signaling. Nonetheless, A.fragrantissima induced cleaved PARP, CYCS, and FADD proteins in MCF-7 cells to avail apoptosis. [ABSTRACT FROM AUTHOR]

Recently, a low-level somatic mutation in the NRAS gene (c.182 A > G, Q61R) was identified in various specimens from patients with kaposiform lymphangiomatosis. However, it is unknown how these low-frequency mutated cells can affect the characterization and surrounding environment of their lesions. To understand the pathogenesis and association of these gene abnormalities, we established NRASQ61R mutated lymphatic endothelial cells transfected with lentivirus vector and undertook morphological and functional characterization, protein expression profiling, and metabolome analysis. NRASQ61R human dermal lymphatic endothelial cells showed poor tube formation, a low proliferation rate, and high migration ability, with an increase in the ratio of mutated cells. An analysis of signaling pathways showed inactivation of the PIK3/AKT/mTOR pathway and hyperactivation of the RAS/MAPK/ERK pathway, which was improved by MAPK kinase (MEK) inhibitor treatment. This study shows the theoretical circumstances induced in vitro by NRASQ61R-mutated cells in the affected lesions of kaposiform lymphangiomatosis patients. [ABSTRACT FROM AUTHOR]

The self-organization of cells relies on the profound complexity of protein-protein interactions. Challenges in directly observing these events have hindered progress toward understanding their diverse behaviors. One notable example is the interaction between molecular motors and cytoskeletal systems that combine to perform a variety of cellular functions. In this work, we leverage theory and experiments to identify and quantify the rate-limiting mechanism of the initial association between a cargo-bound kinesin motor and a microtubule track. Recent advances in optical tweezers provide binding times for several lengths of kinesin motors trapped at varying distances from a microtubule, empowering the investigation of competing models. We first explore a diffusion-limited model of binding. Through Brownian dynamics simulations and simulation-based inference, we find this simple diffusion model fails to explain the experimental binding times, but an extended model that accounts for the ADP state of the molecular motor agrees closely with the data, even under the scrutiny of penalizing for additional model complexity. We provide quantification of both kinetic rates and biophysical parameters underlying the proposed binding process. Our model suggests that a typical binding event is limited by ADP state rather than physical search. Lastly, we predict how these association rates can be modulated in distinct ways through variation of environmental concentrations and physical properties. Author summary: Cytoskeletal-motor assemblies self-organize to achieve cellular functions ranging from delivering intracellular cargoes to generating forces in mitosis. Advancements in single-molecule experiments have revealed immense detail about motor detachment and stepping, but relatively little regarding attachment. Newly available binding times for individual kinesin motors allow for the evaluation of mechanistic models of the process. We find that a model limited by both diffusive search and a weak-to-strong transition from ADP release best explains the data. The coupled chemo-mechanical nature of this interaction can be modulated more richly than either separately, possibly explaining the diversity and regulation observed in cells. More broadly, our study provides a timely vignette in leveraging computations with experiments to understand the mosaic of mechanisms underlying protein-protein interactions. [ABSTRACT FROM AUTHOR]

In this paper, modeling of the coupling medium between two neurons, the effects of the model parameters on the synchronization of those neurons, and compensation of coupling strength deficiency in synchronization are studied. Our study exploits the inter-neuronal coupling medium and investigates its intrinsic properties in order to get insight into neuronal-information transmittance and, there from, brain-information processing. A novel electrical model of the coupling medium that represents a well-known RLC circuit attributable to the coupling medium’s intrinsic resistive, inductive, and capacitive properties is derived. Surprisingly, the integration of such properties reveals the existence of a natural three-term control strategy, referred to in the literature as the proportional integral derivative (PID) controller, which can be responsible for synchronization between two neurons. Consequently, brain-information processing can rely on a large number of PID controllers based on the coupling medium properties responsible for the coherent behavior of neurons in a neural network. Herein, the effects of the coupling model (or natural PID controller) parameters are studied and, further, a supervisory mechanism is proposed that follows a learning and adaptation policy based on the particle swarm optimization algorithm for compensation of the coupling strength deficiency. [ABSTRACT FROM AUTHOR]

In their role as second messengers, cyclic nucleotides such as cAMP have a variety of intracellular effects. These complex tasks demand a highly organized orchestration of spatially and temporally confined cAMP action which should be best achieved by compartmentalization of the latter. A great body of evidence suggests that cAMP compartments may be established and maintained by cAMP degrading enzymes, e.g. phosphodiesterases (PDEs). However, the molecular and biophysical details of how PDEs can orchestrate cAMP gradients are entirely unclear. In this paper, using fusion proteins of cAMP FRET-sensors and PDEs in living cells, we provide direct experimental evidence that the cAMP concentration in the vicinity of an individual PDE molecule is below the detection limit of our FRET sensors (<100nM). This cAMP gradient persists in crude cytosol preparations. We developed mathematical models based on diffusion-reaction equations which describe the creation of nanocompartments around a single PDE molecule and more complex spatial PDE arrangements. The analytically solvable equations derived here explicitly determine how the capability of a single PDE, or PDE complexes, to create a nanocompartment depend on the cAMP degradation rate, the diffusive mobility of cAMP, and geometrical and topological parameters. We apply these generic models to our experimental data and determine the diffusive mobility and degradation rate of cAMP. The results obtained for these parameters differ by far from data in literature for free soluble cAMP interacting with PDE. Hence, restricted cAMP diffusion in the vincinity of PDE is necessary to create cAMP nanocompartments in cells. [ABSTRACT FROM AUTHOR]

Cross-feeding, a relationship wherein one organism consumes metabolites excreted by another, is a ubiquitous feature of natural and clinically-relevant microbial communities and could be a key factor promoting diversity in extreme and/or nutrient-poor environments. However, it remains unclear how readily cross-feeding interactions form, and therefore our ability to predict their emergence is limited. In this paper we developed a mathematical model parameterized using data from the biochemistry and ecology of an E. coli cross-feeding laboratory system. The model accurately captures short-term dynamics of the two competitors that have been observed empirically and we use it to systematically explore the stability of cross-feeding interactions for a range of environmental conditions. We find that our simple system can display complex dynamics including multi-stable behavior separated by a critical point. Therefore whether cross-feeding interactions form depends on the complex interplay between density and frequency of the competitors as well as on the concentration of resources in the environment. Moreover, we find that subtly different environmental conditions can lead to dramatically different results regarding the establishment of cross-feeding, which could explain the apparently unpredictable between-population differences in experimental outcomes. We argue that mathematical models are essential tools for disentangling the complexities of cross-feeding interactions. [ABSTRACT FROM AUTHOR]

Cell intercalation is a highly directed cell rearrangement that is essential for animal morphogenesis. As such, intercalation requires orchestration of cell polarity across the plane of the tissue. CDC-42 is a Rho family GTPase with key functions in cell polarity, yet its role during epithelial intercalation has not been established because its roles early in embryogenesis have historically made it difficult to study. To circumvent these early requirements, in this paper we use tissue-specific and conditional loss-of-function approaches to identify a role for CDC-42 during intercalation of the Caenorhabditis elegans dorsal embryonic epidermis. CDC-42 activity is enriched in the medial tips of intercalating cells, which extend as cells migrate past one another. Moreover, CDC-42 is involved in both the efficient formation and orientation of cell tips during cell rearrangement. Using conditional loss-of-function we also show that the PAR complex functions in tip formation and orientation. Additionally, we find that the sole C. elegans Eph receptor, VAB-1, functions during this process in an Ephrin-independent manner. Using epistasis analysis, we find that vab-1 lies in the same genetic pathway as cdc-42 and is responsible for polarizing CDC-42 activity to the medial tip. Together, these data establish a previously uncharacterized role for polarized CDC-42, in conjunction with PAR-6, PAR-3 and an Eph receptor, during epithelial intercalation. [ABSTRACT FROM AUTHOR]

Introduction: Infection causes a vast burden of disease, with significant mortality, morbidity and costs to health-care systems. However, identifying the pathogen causative infection can be challenging, resulting in high use of broad-spectrum antibiotics, much of which may be inappropriate. Novel metagenomic methods have potential to rapidly identify pathogens, however their clinical utility for many infections is currently unclear. Outcome from infection is also impacted by the effectiveness of immune responses, which can be impaired by age, co-morbidity and the infection itself. The aims of this study are twofold: To compare diversity of organisms identified and time-to-result using metagenomic methods versus traditional culture -based techniques, to explore the potential clinical role of metagenomic approaches to pathogen identification in a range of infections. To characterise the ex vivo function of immune cells from patients with acute infection, exploring host and pathogen-specific factors which may affect immune function and overall outcomes. Methods: This is a prospective observational study of patients with acute infection. Patients with symptoms suggestive of an acute infection will be recruited, and blood and bodily fluid relevant to the site of infection collected (for example, sputum and naso-oropharyngeal swabs for respiratory tract infections, or urine for a suspected urinary tract infection). Metagenomic analysis of samples will be compared to traditional microbiology, alongside the antimicrobials received. Blood and respiratory samples such as bronchoalveolar lavage will be used to isolate immune cells and interrogate immune cell function. Where possible, similar samples will be collected from matched participants without a suspected infection to determine the impact of infection on both microbiome and immune cell function. [ABSTRACT FROM AUTHOR]

Metabolism participates in the control of stem cell function and subsequent maintenance of tissue homeostasis. How this is achieved in the context of adult stem cell niches in coordination with other local and intrinsic signaling cues is not completely understood. The Target of Rapamycin (TOR) pathway is a master regulator of metabolism and plays essential roles in stem cell maintenance and differentiation. In the Drosophila male germline, mTORC1 is active in germline stem cells (GSCs) and early germ cells. Targeted RNAi-mediated downregulation of mTor in early germ cells causes a block and/or a delay in differentiation, resulting in an accumulation of germ cells with GSC-like features. These early germ cells also contain unusually large and dysfunctional autolysosomes. In addition, downregulation of mTor in adult male GSCs and early germ cells causes non-autonomous activation of mTORC1 in neighboring cyst cells, which correlates with a disruption in the coordination of germline and somatic differentiation. Our study identifies a previously uncharacterized role of the TOR pathway in regulating male germline differentiation. [ABSTRACT FROM AUTHOR]

The papillae of tunicate larvae contribute sensory, adhesive, and metamorphosis-regulating functions that are crucial for the biphasic lifestyle of these marine, non-vertebrate chordates. We have identified additional molecular markers for at least 5 distinct cell types in the papillae of the model tunicate Ciona, allowing us to further study the development of these organs. Using tissue-specific CRISPR/Cas9-mediated mutagenesis and other molecular perturbations, we reveal the roles of key transcription factors and signaling pathways that are important for patterning the papilla territory into a highly organized array of different cell types and shapes. We further test the contributions of different transcription factors and cell types to the production of the adhesive glue that allows for larval attachment during settlement, and to the processes of tail retraction and body rotation during metamorphosis. With this study, we continue working towards connecting gene regulation to cellular functions that control the developmental transition between the motile larva and sessile adult of Ciona. Ciona is a marine, non-vertebrate tunicate, whose papillae have many functions crucial for their biphasic lifestyle, which transitions between motile larva and sessile adult. These authors investigate the development of different Ciona papillae cell types and transcription factor patterns that contribute to attachment, patterning and metamorphosis of the larvae. [ABSTRACT FROM AUTHOR]

Synthetic biology dictates the data-driven engineering of biocatalysis, cellular functions, and organism behavior. Integral to synthetic biology is the aspiration to efficiently find, access, interoperate, and reuse high-quality data on genotype-phenotype relationships of native and engineered biosystems under FAIR principles, and from this facilitate forward-engineering strategies. However, biology is complex at the regulatory level, and noisy at the operational level, thus necessitating systematic and diligent data handling at all levels of the design, build, and test phases in order to maximize learning in the iterative design-build-test-learn engineering cycle. To enable user-friendly simulation, organization, and guidance for the engineering of biosystems, we have developed an open-source python-based computer-aided design and analysis platform operating under a literate programming user-interface hosted on Github. The platform is called teemi and is fully compliant with FAIR principles. In this study we apply teemi for i) designing and simulating bioengineering, ii) integrating and analyzing multivariate datasets, and iii) machine-learning for predictive engineering of metabolic pathway designs for production of a key precursor to medicinal alkaloids in yeast. The teemi platform is publicly available at PyPi and GitHub. Author summary: Bioengineering holds fantastic perspectives and is poised to change how we produce foods, materials, and medicines. However, rapid progress is limited by a lack of mechanistic knowledge in even the simplest model organisms, such as bacteria and yeast. Thus, to compensate, we often have to construct and study a large number of engineered cells and select the cells with the greatest potential for the given objective function. The targeted construction of engineered cells is often described as an iterative process of design, build, test, and learn (the DBTL cycle). Literate programming is a paradigm that encourages the combination of text and computer code with the potential to describe all workflows covered by the DBTL cycle. The purpose of the present work is to give a first estimate of the extent to which we can accelerate the individual steps in the DBTL cycle by using end-to-end literate programming workflows. To achieve this, we established an open-source platform called teemi, and used it to optimize production of a key precursor to medicinal alkaloids in yeast. We expect that teemi will enable higher DBTL throughput with fewer errors, better integration of IT tools with laboratory resources, and more effective knowledge capture. [ABSTRACT FROM AUTHOR]

Strong circadian (~24h) rhythms in heart rate (HR) are critical for flexible regulation of cardiac pacemaking function throughout the day. While this circadian flexibility in HR is sustained in diverse conditions, it declines with age, accompanied by reduced maximal HR performance. The intricate regulation of circadian HR involves the orchestration of the autonomic nervous system (ANS), circadian rhythms of body temperature (CRBT), and local circadian rhythmicity (LCR), which has not been fully understood. Here, we developed a mathematical model describing ANS, CRBT, and LCR in sinoatrial nodal cells (SANC) that accurately captures distinct circadian patterns in adult and aged mice. Our model underscores how the alliance among ANS, CRBT, and LCR achieves circadian flexibility to cover a wide range of firing rates in SANC, performance to achieve maximal firing rates, while preserving robustness to generate rhythmic firing patterns irrespective of external conditions. Specifically, while ANS dominates in promoting SANC flexibility and performance, CRBT and LCR act as primary and secondary boosters, respectively, to further enhance SANC flexibility and performance. Disruption of this alliance with age results in impaired SANC flexibility and performance, but not robustness This unexpected outcome is primarily attributed to the age-related reduction in parasympathetic activities, which maintains SANC robustness while compromising flexibility. Our work sheds light on the critical alliance of ANS, CRBT, and LCR in regulating time-of-day cardiac pacemaking function and dysfunction, offering insights into novel therapeutic targets for the prevention and treatment of cardiac arrhythmias. Author summary: The mammalian heart relies on the sinoatrial node, known as the cardiac pacemaker, to orchestrate heartbeats. These heartbeats slow down during sleep and accelerate upon waking, in anticipation of daily environmental changes. The heart's ability to rhythmically adapt to these 24-hour changes, known as circadian rhythms, is crucial for flexible cardiac performance throughout the day, accommodating various physiological states. However, with aging, the heart's circadian flexibility gradually weakens, accompanied by a decline in maximal heart rate. Previous studies have implicated the involvement of a master circadian clock and a local circadian clock within the heart, but their time-of-day interactions and altered dynamics during aging remain unclear. In this study, we developed a mathematical model to simulate the regulation of sinoatrial nodal cell pacemaking function by the master and local circadian clocks in adult and aged mice. Our results unveiled distinct roles played by these clocks in determining circadian patterns of sinoatrial nodal cells, shedding light on their critical alliance in regulating time-of-day cardiac pacemaking function and dysfunction. [ABSTRACT FROM AUTHOR]

The mammalian hippocampus plays a crucial role in producing a cognitive map of space—an internalized representation of the animal’s environment. We have previously shown that it is possible to model this map formation using a topological framework, in which information about the environment is transmitted through the temporal organization of neuronal spiking activity, particularly those occasions in which the firing of different place cells overlaps. In this paper, we discuss how gamma rhythm, one of the main components of the extracellular electrical field potential affects the efficiency of place cell map formation. Using methods of algebraic topology and the maximal entropy principle, we demonstrate that gamma modulation synchronizes the spiking of dynamical cell assemblies, which enables learning a spatial map at faster timescales. [ABSTRACT FROM AUTHOR]

In the present paper we consider a new type of mechanism by which neurotransmitter acetylcholine (ACh) regulates the properties of peripheral nerve fibers myelin. Our data show the importance of the relationship between the changes in the number of Schwann cell (SC) acetylcholine receptors (AChRs) and the axon excitation (different intervals between action potentials (APs)). Using Raman spectroscopy, an effect of activation of SC AChRs on the myelin membrane fluidity was investigated. It was found, that ACh stimulates an increase in lipid ordering degree of the myelin lipids, thus providing evidence for specific role of the “axon-SC” interactions at the axon excitation. It was proposed, that during the axon excitation, the SC membrane K+- depolarization and the Ca2+—influx led to phospholipase activation or exocytosis of intracellular membrane vesicles and myelin structure reorganization. [ABSTRACT FROM AUTHOR]

Interleukin-2 (IL2) is a growth factor for several immune cells and its function depends on its binding to IL2Rs in the cell membrane. The most accepted model for the assembling of IL2-IL2R complexes in the cell membrane is the Affinity Conversion Model (ACM). This model postulates that IL2R receptor association is sequential and dependent on ligand binding. Most likely free IL2 binds first to IL2Rα, and then this complex binds to IL2Rβ, and finally to IL2Rγ (γc). However, in previous mathematical models representing this process, the binding of γc has not been taken into account. In this work, the quantitative contribution of the number of IL2Rγ chain to the IL2-IL2R apparent binding affinity and signaling is studied. A mathematical model of the affinity conversion process including the γ chain in the dynamic, has been formulated. The model was calibrated by fitting it to experimental data, specifically, Scatchard plots obtained using human cell lines. This paper demonstrates how the model correctly explains available experimental observations. It was estimated, for the first time, the value of the kinetic coefficients of IL2-IL2R complexes interaction in the cell membrane. Moreover, the number of IL2R components in different cell lines was also estimated. It was obtained a variable distribution in the number of IL2R components depending on the cell type and the activation state. Of most significance, the study predicts that not only the number of IL2Rα and IL2Rβ, but also the number of γc determine the capacity of the cell to capture and retain IL2 in signalling complexes. Moreover, it is also showed that different cells might use different pathways to bind IL2 as consequence of its IL2R components distribution in the membrane. [ABSTRACT FROM AUTHOR]

Human parechovirus 1 (HPeV-1) (family Picornaviridae) is a global cause of pediatric respiratory and CNS infections for which there is no treatment. Although biochemical and in vitro studies have suggested that HPeV-1 binds to αVβ1, αVβ3 and αVβ6 integrin receptor(s), the actual cellular receptors required for infectious entry of HPeV-1 remain unknown. In this paper we analyzed the expression profiles of αVβ1, αVβ3, αVβ6 and α5β1 in susceptible cell lines (A549, HeLa and SW480) to identify which integrin receptors support HPeV-1 internalization and/or replication cycle. We demonstrate by antibody blocking assay, immunofluorescence microscopy and RT-qPCR that HPeV-1 internalizes and replicates in cell lines that express αVβ1 integrin but not αVβ3 or αVβ6 integrins. To further study the role of β1 integrin, we used a mouse cell line, GE11-KO, which is deficient in β1 expression, and its derivate GE11-β1 in which human integrin β1 subunit is overexpressed. HPeV-1 (Harris strain) and three clinical HPeV-1 isolates did not internalize into GE11-KO whereas GE11-β1 supported the internalization process. An integrin β1-activating antibody, TS2/16, enhanced HPeV-1 infectivity, but infection occurred in the absence of visible receptor clustering. HPeV-1 also co-localized with β1 integrin on the cell surface, and HPeV-1 and β1 integrin co-endocytosed into the cells. In conclusion, our results demonstrate that in some cell lines the cellular entry of HPeV-1 is primarily mediated by the active form of αVβ1 integrin without visible receptor clustering. [ABSTRACT FROM AUTHOR]

Stromal cells with a myofibroblast phenotype present in the normal human esophagus are increased in individuals with gastro-esophageal reflux disease (GERD). We have previously demonstrated that myofibroblasts stimulated with acid and TLR4 agonists increase IL-6 and IL-8 secretion using primary cultures of myofibroblasts established from normal human esophagus. While primary cultures have the advantage of reflecting the in vivo environment, a short life span and unavoidable heterogeneity limits the usefulness of this model in larger scale in vitro cellular signaling studies. The major aim of this paper therefore was to generate a human esophageal myofibroblast line with an extended lifespan. In the work presented here we have generated and characterized an immortalized human esophageal myofibroblast line by transfection with a commercially available GFP-hTERT lentivirus. Immortalized human esophageal myofibroblasts demonstrate phenotypic, genotypic and functional similarity to primary cultures of esophageal myofibroblasts we have previously described. We found that immortalized esophageal myofibroblasts retain myofibroblast spindle-shaped morphology at low and high confluence beyond passage 80, and express α-SMA, vimentin, and CD90 myofibroblast markers. Immortalized human esophageal myofibroblasts also express the putative acid receptor TRPV1 and TLR4 and retain the functional capacity to respond to stimuli encountered in GERD with secretion of IL-6. Finally, immortalized human esophageal myofibroblasts also support the stratified growth of squamous esophageal epithelial cells in 3D organotypic cultures. This newly characterized immortalized human esophageal myofibroblast cell line can be used in future cellular signaling and co-culture studies. [ABSTRACT FROM AUTHOR]

Microbial physiology exhibits growth laws that relate the macromolecular composition of the cell to the growth rate. Recent work has shown that these empirical regularities can be derived from coarse-grained models of resource allocation. While these studies focus on steady-state growth, such conditions are rarely found in natural habitats, where microorganisms are continually challenged by environmental fluctuations. The aim of this paper is to extend the study of microbial growth strategies to dynamical environments, using a self-replicator model. We formulate dynamical growth maximization as an optimal control problem that can be solved using Pontryagin’s Maximum Principle. We compare this theoretical gold standard with different possible implementations of growth control in bacterial cells. We find that simple control strategies enabling growth-rate maximization at steady state are suboptimal for transitions from one growth regime to another, for example when shifting bacterial cells to a medium supporting a higher growth rate. A near-optimal control strategy in dynamical conditions is shown to require information on several, rather than a single physiological variable. Interestingly, this strategy has structural analogies with the regulation of ribosomal protein synthesis by ppGpp in the enterobacterium Escherichia coli. It involves sensing a mismatch between precursor and ribosome concentrations, as well as the adjustment of ribosome synthesis in a switch-like manner. Our results show how the capability of regulatory systems to integrate information about several physiological variables is critical for optimizing growth in a changing environment. [ABSTRACT FROM AUTHOR]

For the first time in human history, the majority of the world's population resides in urban areas. Therefore, city managers are faced with new challenges related to the efficiency, equity and quality of the supply of resources, such as water, food and energy. Infrastructure in a city can be viewed as service points providing resources. These service points function together as a spatially collaborative system to serve an increasing population. To study the spatial collaboration among service points, we propose a shared network according to human's collective movement and resource usage based on data usage detail records (UDRs) from the cellular network in a city in western China. This network is shown to be not scale-free, but exhibits an interesting triangular property governed by two types of nodes with very different link patterns. Surprisingly, this feature is consistent with the urban-rural dualistic context of the city. Another feature of the shared network is that it consists of several spatially separated communities that characterize local people's active zones but do not completely overlap with administrative areas. According to these features, we propose the incorporation of human movement into infrastructure classification. The presence of well-defined spatially separated clusters confirms the effectiveness of this approach. In this paper, our findings reveal the spatial structure inside a city, and the proposed approach provides a new perspective on integrating human movement into the study of a spatially distributed system. [ABSTRACT FROM AUTHOR]

Prokaryotic proteins are regulated by pupylation, a type of post-translational modification that contributes to cellular function in bacterial organisms. In pupylation process, the prokaryotic ubiquitin-like protein (Pup) tagging is functionally analogous to ubiquitination in order to tag target proteins for proteasomal degradation. To date, several experimental methods have been developed to identify pupylated proteins and their pupylation sites, but these experimental methods are generally laborious and costly. Therefore, computational methods that can accurately predict potential pupylation sites based on protein sequence information are highly desirable. In this paper, a novel predictor termed as pbPUP has been developed for accurate prediction of pupylation sites. In particular, a sophisticated sequence encoding scheme [i.e. the profile-based composition of k-spaced amino acid pairs (pbCKSAAP)] is used to represent the sequence patterns and evolutionary information of the sequence fragments surrounding pupylation sites. Then, a Support Vector Machine (SVM) classifier is trained using the pbCKSAAP encoding scheme. The final pbPUP predictor achieves an AUC value of 0.849 in10-fold cross-validation tests and outperforms other existing predictors on a comprehensive independent test dataset. The proposed method is anticipated to be a helpful computational resource for the prediction of pupylation sites. The web server and curated datasets in this study are freely available at . [ABSTRACT FROM AUTHOR]

The Ca2+-sensing receptor (CaSR) regulates Ca2+ homeostasis in the body by monitoring extracellular levels of Ca2+ ([Ca2+]o) and amino acids. Mutations at the hinge region of the N-terminal Venus flytrap domain (VFTD) produce either receptor inactivation (L173P, P221Q) or activation (L173F, P221L) related to hypercalcemic or hypocalcemic disorders. In this paper, we report that both L173P and P221Q markedly impair the functional positive cooperativity of the CaSR as reflected by [Ca2+]o–induced [Ca2+]i oscillations, inositol-1-phosphate (IP1) accumulation and extracellular signal-regulated kinases (ERK1/2) activity. In contrast, L173F and P221L show enhanced responsiveness of these three functional readouts to [Ca2+]o. Further analysis of the dynamics of the VFTD mutants using computational simulation studies supports disruption in the correlated motions in the loss-of-function CaSR mutants, while these motions are enhanced in the gain-of-function mutants. Wild type (WT) CaSR was modulated by L-Phe in a heterotropic positive cooperative way, achieving an EC50 similar to those of the two activating mutations. The response of the inactivating P221Q mutant to [Ca2+]o was partially rescued by L-Phe, illustrating the capacity of the L-Phe binding site to enhance the positive homotropic cooperativity of CaSR. L-Phe had no effect on the other inactivating mutant. Moreover, our results carried out both in silico and in intact cells indicate that residue Leu173, which is close to residues that are part of the L-Phe-binding pocket, exhibited impaired heterotropic cooperativity in the presence of L-Phe. Thus, Pro221 and Leu173 are important for the positive homo- and heterotropic cooperative regulation elicited by agonist binding. [ABSTRACT FROM AUTHOR]

The xenobiotic response element (XRE) family of transcription factors (TFs), which are commonly encoded by bacteria and bacteriophage, regulate diverse features of bacterial cell physiology and impact phage infection dynamics. Through a pangenome analysis of Caulobacter species isolated from soil and aquatic ecosystems, we uncovered an apparent radiation of a paralogous XRE TF gene cluster, several of which have established functions in the regulation of holdfast adhesin development and biofilm formation in C. crescentus. We further discovered related XRE TFs throughout the class Alphaproteobacteria and its phages, including the φCbK Caulophage, suggesting that members of this cluster impact host-phage interactions. Here we show that a closely related group of XRE transcription factors encoded by both C. crescentus and φCbK can physically interact and function to control the transcription of a common gene set, influencing processes including holdfast development and the production of φCbK virions. The φCbK-encoded XRE paralog, tgrL, is highly expressed at the earliest stages of infection and can directly inhibit transcription of host genes including hfiA, a potent holdfast inhibitor, and gafYZ, an activator of prophage-like gene transfer agents (GTAs). XRE proteins encoded from the C. crescentus chromosome also directly repress gafYZ transcription, revealing a functionally redundant set of host regulators that may protect against spurious production of GTA particles and inadvertent cell lysis. Deleting the C. crescentus XRE transcription factors reduced φCbK burst size, while overexpressing these host genes or φCbK tgrL rescued this burst defect. We conclude that this XRE TF gene cluster, shared by C. crescentus and φCbK, plays an important role in adhesion regulation under phage-free conditions, and influences host-phage dynamics during infection. Author summary: During infection, bacteria and their viruses (i.e. phage) modulate each other's transcription to promote their own fitness. A broadly conserved group of proteins that are commonly engaged in this battle between host and virus are the xenobiotic response element (XRE) family of transcription factors (TFs). We identified a conserved cluster of XRE TF genes in Alphaproteobacteria and their bacteriophage. In Caulobacter crescentus and its phage, φCbK, these closely related transcription factors regulate a common gene set that impacts Caulobacter adhesion and phage virion production. We measured transcription of the φCbK genome across an infection cycle and discovered that the phage XRE TF gene, tgrL, is highly expressed at the earliest stages of infection, and we present evidence that TgrL enhances φCbK fitness. Our results offer an example of how an evolutionarily related set of transcription factors, found in both a host and its virus, influence host defense mechanisms and viral fitness. [ABSTRACT FROM AUTHOR]

Protein allocation determines the activity of cellular pathways and affects growth across all organisms. Therefore, different experimental and machine learning approaches have been developed to quantify and predict protein abundance and how they are allocated to different cellular functions, respectively. Yet, despite advances in protein quantification, it remains challenging to predict condition-specific allocation of enzymes in metabolic networks. Here, using protein-constrained metabolic models, we propose a family of constrained-based approaches, termed PARROT, to predict how much of each enzyme is used based on the principle of minimizing the difference between a reference and an alternative growth condition. To this end, PARROT variants model the minimization of enzyme reallocation using four different (combinations of) distance functions. We demonstrate that the PARROT variant that minimizes the Manhattan distance between the enzyme allocation of a reference and an alternative condition outperforms existing approaches based on the parsimonious distribution of fluxes or enzymes for both Escherichia coli and Saccharomyces cerevisiae. Further, we show that the combined minimization of flux and enzyme allocation adjustment leads to inconsistent predictions. Together, our findings indicate that minimization of protein allocation rather than flux redistribution is a governing principle determining steady-state pathway activity for microorganism grown in alternative growth conditions. Author summary: Protein allocation determines the activity of cells and affects diverse traits across all organisms. However, prediction of protein allocation, particularly for conditions that do not result at optimal growth and physiology, remains a very challenging problem. In this study, we present an approach called PARROT to predict how cells allocate their proteins in different conditions. We tested different variants of PARROT by considering different objectives within a constraint-based formulation and by how much resource allocation information is used to guide predictions. We found that minimizing adjustments in protein allocation, rather than flux phenotypes, is a key principle that microorganisms use under alternative growth conditions. By integrating this principle into our approaches and leveraging quantitative proteomics data, PARROT provides more accurate predictions of protein allocation in unseen conditions in comparison to existing contenders. Therefore, PARROT can help in advancing our understanding of protein allocation under different conditions and its physiological implications. Further, we can gain valuable insights into cellular responses and adaptive strategies across different environments. [ABSTRACT FROM AUTHOR]