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Mendes, P.

Publications and source records attributed to Mendes, P..

9 recordsLinked to original sources

CuiT is a Cu importer required for metal homeostasis in Salmonella enterica

Copper (Cu) is an essential micronutrient that serves as a cofactor for redox enzymes but becomes toxic when unregulated. In bacteria, while Cu efflux systems are well characterized, mechanisms of Cu import remain poorly understood. Here, we characterize the major facilitator superfamily transporter CuiT (STM1486) as a key Cu importer in Salmonella enterica. Comparative genomics revealed that cuiT is evolutionarily conserved across Enterobacteriaceae, and structural modeling predicts a 12-transmembrane-helix architecture with conserved His, Met, and Cys residues suitable for Cu coordination. Functional analyses demonstrated that deletion of cuiT reduces intracellular Cu accumulation, slows Cu uptake kinetics, and diminishes expression of Cu-responsive genes, including copA, cueP, cueO, and golB. Conversely, overexpression of CuiT increases intracellular Cu but sensitizes cells to Cu stress, highlighting the need for tight regulation. Kinetic modeling indicates that CuiT mediates rapid Cu import, supporting larger intracellular Cu pools compared to Pseudomonas influx transporters. These findings position CuiT as a central component of the Salmonella Cu homeostasis network, linking Cu import to transcriptional regulation, redox balance, and stress adaptation. Our work provides mechanistic insights into bacterial Cu acquisition and suggests CuiT and associated pathways as potential targets for antimicrobial strategies. SignificanceCopper (Cu) is essential for bacterial redox enzymes but toxic when dysregulated. While Cu efflux pathways are well studied, mechanisms of Cu import are poorly understood. We identify CuiT, a conserved major facilitator superfamily transporter, as a key Cu importer in Salmonella enterica. CuiT controls intracellular Cu levels, influences Cu-responsive gene expression, and maintains redox balance and stress adaptation. Disruption or overexpression of CuiT perturbs Cu homeostasis, highlighting its regulatory importance. These findings reveal a critical bacterial Cu acquisition pathway and suggest CuiT and its network as potential antimicrobial targets, advancing understanding of metal homeostasis in pathogens.

microbiology↗

Modeling the iron storage protein ferritin reveals how residual ferrihydrite iron determines initial ferritin iron sequestration kinetics

Ferritin is the primary iron storage protein in mammalian cells and is necessary for cellular iron homeostasis. Its ability to sequester iron protects cells from rising concentrations of ferrous iron limiting oxidative cell damage. The dynamics of its sequestration behavior have been studied extensively experimentally, but mostly in vitro, rather than within mammalian cells, computational modeling efforts are lacking, and several open questions remain. The importance of FT modeling is driven by the idea that understanding the kinetics of ferritin iron sequestration and how it impacts the regulation of iron metabolism in the cells that compose the main iron regulatory tissues (eg. Kupffer cells, splenic macrophages, enterocytes, erythroblasts, etc.) is central to understanding systemic iron control. The focus of the work here is establishing a model that tractably simulates the ferritin iron sequestration kinetics in a mechanistic way for incorporation into larger cell models, in addition to contributing to the understanding of ferritin iron sequestration dynamics within cells. The models parameter values were determined from published kinetic and binding experiments and the model was validated against independent data not used in its construction. Simulation results indicate that FT concentration is the most impactful on overall sequestration dynamics, while the FT iron saturation (number of iron atoms sequestered per FT cage) fine tunes the initial rates. Finally, because this model has a small number of reactions and species, was built to represent important mechanistic details of FT kinetics, and has flexibility to include subtle changes in subunit composition, we propose this model to be used as a building block for models of iron metabolism in a variety of specific cell types.

systems biology↗

Understanding Lactobacillus paracasei and Streptococcus oralis biofilm interactions through agent-based modeling

As common commensals residing on mucosal tissues, Lactobacillus species are known to encourage health, while recent findings highlight the pathogenic roles of Streptococcus species in these environments. In this study we used a combination of in vivo imaging experiments and computational modeling to explore biofilm interactions between Streptococcus oralis, an accessory pathogen in oral Candidiasis, and Lactobacillus paracasei, an organism with known probiotic properties. A computational agent-based model was created where the two species only interact by competing for space and nutrients. Quantification of bacterial growth in live biofilms indicated that S. oralis biomass and cell numbers were much lower than predicted by the model. Two subsequent models were then created to examine more complex interactions between these species, one where L. paracasei secretes a surfactant, and another where L. paracasei secretes an inhibitor of S. oralis growth. Further biofilm experiments support the hypothesis that L. paracasei may secrete an inhibitor of S. oralis growth, although they do not exclude that a surfactant could also be involved. This contribution shows how agent-based modeling and experiments can be used in synergy to address multiple species biofilm interactions, with important roles in mucosal health and disease. IMPORTANCEWe previously discovered a role of the oral commensal Streptococcus oralis as an accessory pathogen. S. oralis increases the virulence of Candida albicans infections in murine oral candidiasis and epithelial cell models through mechanisms which promote the formation of tissue-damaging biofilms. Lactobacillus species have known inhibitory effects on biofilm formation of many microbes, including Streptococcus species. Agent-based modeling has great advantages as a means of exploring multifaceted relationships between organisms in complex environments such as biofilms. Here we used an iterative collaborative process between experimentation and modeling to reveal aspects of the mostly unexplored relationship between S. oralis and L. paracasei in biofilm growth. The inhibitory nature of L. paracasei on S. oralis in biofilms may be exploited as a means of preventing or alleviating mucosal fungal infections.

microbiology↗

MYC dosage compensation is mediated by miRNA-transcription factor interactions in aneuploid cancer

We hypothesize that dosage compensation of critical genes arises from systems-level properties for cancer cells to withstand the negative effects of aneuploidy. We identified several candidate genes in cancer multi-omics data and developed a biocomputational platform to construct a mathematical model of their interaction network with miRNAs and transcription factors, where the property of dosage compensation emerged for MYC and was dependent on the kinetic parameters of its feedback interactions with three micro-RNAs. These circuits were experimentally validated with a novel genetic tug-of-war technique by overexpressing an exogenous MYC leading to over-expression of the three microRNAs involved and down-regulation of endogenous MYC. In addition, MYC overexpression or inhibition of its compensating miRNAs led to dosage-dependent cytotoxicity in MYC-amplified colon cancer cells. Finally, we identified negative correlation of MYC dosage compensation with patient survival in TCGA breast cancer patients, highlighting the potential of this mechanism to prevent aneuploid cancer progression. HighlightsThe systems-level property of gene dosage-compensation emerges in silico in miRNA-transcription factor networks depending on the kinetic parameters of its interactions. We established a criterion to identify compensated candidate genes with low variation in expression despite high copy number variation. BioNetUCR is a novel biocomputational platform to model miRNA-transcription factor interactions We present a novel genetic tug-of-war technique to experimentally validate gene dosage compensation at the transcriptional level. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/440572v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@104a93forg.highwire.dtl.DTLVardef@1039ae9org.highwire.dtl.DTLVardef@1af41c6org.highwire.dtl.DTLVardef@1073e6a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

Complex networks of miRNA-transcription factors mediate gene dosage compensation in aneuploid cancer

Cancer complexity is consequence of enormous genomic instability leading to aneuploidy, a hallmark of most cancers. We hypothesize that dosage compensation of critical genes could arise from systems-level properties of complex networks of microRNAs (miRNA) and transcription factors (TF) as a way for cancer cells to withstand the negative effects of aneuploidy. We studied gene dosage compensation at the transcriptional level on data of the NCI-60 cancer cell line panel with the aid of computational models to identify candidate genes with low tolerance to variation in gene expression despite high variation in copy numbers. We identified a network of TF and miRNAs validated interactions with those genes to construct a mathematical model where the property of dosage compensation emerged for MYC and STAT3. Compensation was mediated by feedback and feed-forward motifs with 4 miRNAs and was dependent on the kinetic parameters of these TF-miRNA interactions, indicating that network analysis was not enough to identify this emergent property. The inhibition of miRNAs compensating MYC suggest a therapeutic potential of targeting gene dosage compensation against aneuploid cancer.

systems biology↗

Why most transporter mutations that cause antibiotic resistance are to efflux pumps rather than to import transporters

Genotypic microbial resistance to antibiotics with intracellular targets commonly arises from mutations that increase the activities of transporters (pumps) that cause the efflux of intracellular antibiotics. A priori it is not obvious why this is so much more common than are mutations that simply inhibit the activity of uptake transporters for the antibiotics. We analyse quantitatively a mathematical model consisting of one generic equilibrative transporter and one generic concentrative uptake transporter (representing any number of each), together with one generic efflux transporter. The initial conditions are designed to give an internal concentration of the antibiotic that is three times the minimum inhibitory concentration (MIC). The effect of varying the activity of each transporter type 100-fold is dramatically asymmetric, in that lowering the activities of individual uptake transporters has comparatively little effect on internal concentrations of the antibiotic. By contrast, increasing the activity of the efflux transporter lowers the internal antibiotic concentration to levels far below the MIC. Essentially, these phenomena occur because inhibiting individual influx transporters allows others to take up the slack, whereas increasing the activity of the generic efflux transporter cannot easily be compensated. The findings imply strongly that inhibiting efflux transporters is a much better approach for fighting antimicrobial resistance than is stimulating import transporters. This has obvious implications for the development of strategies to combat the development of microbial resistance to antibiotics and possibly also cancer therapeutics in human.

microbiology↗

A computational model to understand mouse iron physiology and diseases

It is well known that iron is an essential element for life but is toxic when in excess or in certain forms. Accordingly there are many diseases that result directly from either lack or excess of iron. Iron has also been associated with a wide range of other diseases and may have an important role in aging. Yet many molecular and physiological aspects of iron regulation have only been discovered recently and others are still awaiting elucidation. In the last 18 years, after the discovery of the hormone hepcidin, many details of iron regulation have become better understood and a clearer picture is starting to emerge, at least in qualitative terms. However there is still no good quantitative and dynamic description of iron absorption, distribution, storage and mobilization that agrees with the wide array of phenotypes presented in several iron-related diseases. The present work addresses this issue by developing a mathematical model of iron distribution in mice that was calibrated with existing ferrokinetic data and subsequently validated against data from a series of iron disorders, such as hemochromatosis, {beta}-thalassemia, atransferrinemia and anemia of inflammation. To adequately fit the ferrokinetic data required including the following mechanisms: a) the role of transferrin in deliving iron to tissues, b) the induction of hepcidin by high levels of transferrin-bound iron, c) the ferroportin-dependent hepcidin-regulated iron export from tissues, d) the erythropoietin regulation of erythropoiesis, and e) direct NTBI uptake by the liver. The utility of such a model to simulate disease interventions was demonstrated by using it to investigate the outcome of different schedules of transferrin treatment in {beta}-thalassemia. The present model is a successful step towards a comprehensive mathematical model of iron physiology incorporating cellular and organ level details.

systems biology↗

An important role for periplasmic storage in Pseudomonas aeruginosa copper homeostasis revealed by a combined experimental and computational modeling study

Biological systems require precise copper homeostasis enabling metallation of cuproproteins while preventing metal toxicity. In bacteria, sensing, transport and storage molecules act in coordination to fulfill these roles. However, there is not yet a kinetic schema explaining the system integration. Here, we report a model emerging from experimental and computational approaches that describes the dynamics of copper distribution in Pseudomonas aeruginosa. Based on copper uptake experiments, a minimal kinetic model describes well the copper distribution in the wild type bacteria but is unable to explain the behavior of the mutant strain lacking CopA1, a key Cu+ efflux ATPase. The model was expanded through an iterative hypothesis-driven approach, arriving to a mechanism that considers the induction of compartmental pools and the parallel function of CopA and Cus efflux systems. Model simulations support the presence of a periplasmic copper storage with a crucial role under dyshomeostasis conditions in P. aeruginosa. Importantly, the model predicts not only the interplay of periplasmic and cytoplasmic pools but also the existence of a threshold in the concentration of external copper beyond which cells lose their ability to control copper levels.

microbiology↗

A Metabolic Reaction Balancing Web Service for Computational Systems Biology

BackgroundIn metabolic network reconstruction the stoichiometric balancing of reactions is essential to create realistic constraint-based models. At the genome scale, balancing is a repetitive task that consumes valuable curator resource that could be deployed elsewhere. Automatic reaction balancing is possible and could be useful across computational systems biology, but widespread use of the appropriate code has been limited by the diversity of non-interoperable programming languages used in the field. RESTful web services offer a language-agnostic way of binding services together.\n\nResultsReaction balancing can be posed as a mixed integer linear programming problem to identify stoichiometric coefficients and infer commonly missing components. This functionality has been exposed as a web service that consumes a list of reactions as JSON or SBML. The reaction balancing web service has been deployed at http://www.nactem.ac.uk/balancer. Code is available via Github. By way of demonstration the service has been applied to a Chinese hamster ovary cell metabolic reconstruction to bring a further 219 reactions into balance.\n\nConclusionsThe majority of systems biology software cannot access existing automatic reaction balancing tools due to a lack of language-specific bindings. Web services bridge different languages by using widely-spoken web communication protocols, meaning that one binding works for almost all languages. Automatic reaction balancing can now be consumed by any systems biology software via a RESTful web service.

systems biology↗