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In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced. [ABSTRACT FROM AUTHOR]

The clinical relevance of cancer stem cells (CSC) remains a major challenge for current cancer therapies, but preliminary findings indicate that specific targeting may be possible. Recent studies have shown that these tumor subpopulations promote tumor angiogenesis through the increased production of VEGF, whereas the VEGF neutralizing antibody bevacizumab specifically inhibits CSC growth. Moreover, nimotuzumab, a monoclonal antibody against the epidermal growth factor receptor (EGFR) with a potent antiangiogenic activity, has been shown by our group to reduce the frequency of CSC-like subpopulations in mouse models of brain tumors when combined with ionizing radiation. These studies and subsequent reports from other groups support the relevance of approaches based on molecular-targeted therapies to selectively attack CSC. This review discusses the relevance of targeting both the EGFR and angiogenic pathways as valid approaches to this aim. We discuss the relevance of identifying better molecular markers to develop drug screening strategies that selectively target CSC. [ABSTRACT FROM AUTHOR]

Abstract: Aiming to get a better insight on the impact of regulatory CD25+CD4+ T cells in tumor immunobiology, a simple mathematical model was formulated and studied. This model is an extension of a previous model for the dynamics of autoreactive regulatory cells and effector cells that interact upon their co-localized activation at the antigen presenting cells (APCs). It assumes that tumor growth stimulates the activation and migration to the adjacent lymph node of fresh APCs loaded with tumor antigens. These APCs stimulate the growth of both effector and regulatory T cells, which may then migrate to the tumor site and induce tumor cell destruction. Our results predict the existence of two alternative dynamic modes of unbounded tumor growth. In the first mode, the tumor induces the expansion of effector T cells that outcompete regulatory T cells, but nevertheless fail to control the tumor. In the second mode, the tumor induces a balanced expansion of both effector and regulatory T cells, which prevents the tumor from being destroyed by the immune cells. Tumors characterized by a high specific growth rate, low immunogenicity, and that are relatively resistant to T cell destructive functions, will grow in the first mode; conversely, tumors that have a slow specific growth rate, that are immunogenic, and/or that are more sensitive to destruction by T cells will grow in the second mode. Overall, this result provides a simple explanation to the fact that the development of some tumors expands regulatory T cells while others do not, predicting how some key dynamical properties of the tumor determine either one or the other type of behavior. [Copyright &y& Elsevier]

Regulatory CD4+ T cells, enriched in the CD25 pool of healthy individuals, mediate natural tolerance and prevent autoimmune diseases. Despite their fundamental and potential clinical significance, regulatory T (TR) cells have not yet been incorporated in a coherent theory of the immune system. This article reviews experimental evidence and theoretical arguments supporting a model of TR cell dynamics, uncovering some of its most relevant biological implications. According to this model, the persistence and expansion of TR cell populations depend strictly on specific interactions they make with antigen-presenting cells (APCs) and conventional effector T (TE) cells. This three-partner crossregulation imposes that TR cells feed on the specific autoimmune activities they suppress, with implications ranging from their interactions with other cells to their repertoire selection in the periphery and in the thymus, and to the relationship between these cells and the innate immune system. These implications stem from the basic prediction that the peripheral dynamics sort the CD4+ T-cell repertoire into two subsets: a less diverse set of small clones of autoreactive effector and regulatory cells that regulate each other’s growth, and a more diverse set of barely autoreactive TE cell clones, whose expansion is limited only by APC availability. It is argued that such partitioning of the repertoire sets the ground for self–non-self discrimination. [ABSTRACT FROM AUTHOR]

A mutein with stronger antitumor activity and lower toxicity than wild-type human interleukin-2 (IL-2) has been recently described. The rationale behind its design was to reinforce the immunostimulatory potential through the introduction of four mutations that would selectively disrupt the interaction with the IL-2 receptor alpha chain (thought to be critical for both IL-2-driven expansion of T regulatory cells and IL-2-mediated toxic effects). Despite the successful results of the mutein in several tumor models, characterization of its interactions was still to be performed. The current work, based on phage display of IL-2-derived variants, showed the individual contribution of each mutation to the impairment of alpha chain binding. A more sensitive assay, based on the ability of phage-displayed IL-2 variants to induce proliferation of the IL-2-dependent CTLL-2 cell line, revealed differences between the mutated variants. The results validated the mutein design, highlighting the importance of the combined effects of the four mutations. The developed phage display-based platform is robust and sensitive, allows a fast comparative evaluation of multiple variants, and could be broadly used to engineer IL-2 and related cytokines, accelerating the development of cytokine-derived therapeutics. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Elucidating the network of interactions established by Interleukin-2 is a key step to understanding its role as a master regulator of the immune system. Binding of this cytokine by specific antibodies gives rise to different classes of immune complexes that boost or inhibit immune responses. The molecular bases of such functional dichotomy are likely related to the nature of the recognized epitopes, making it necessary to perform fine epitope mapping studies. The current work was aimed at developing a versatile platform to do so. This was accomplished by display of human and mouse Interleukin-2 on filamentous phages, together with extensive mutagenesis of both antigens and high throughput screening of binding properties of more than 200 variants. Detailed molecular pictures of the epitopes were thus delineated for four antibodies against either human or mouse Interleukin-2, which refined and, in some cases, modified the conclusions derived from previous mapping studies with peptide libraries. Overlapping surface patches on mouse Interleukin-2 that also coincide with the predicted interface between the cytokine and its receptor alpha chain were shown to be recognized by two monoclonal antibodies that promote enhancement of immune responses, shedding new light on the structural bases of their biological activity. Our strategy was powerful enough to reveal multiple binding details and could be used to map the epitopes recognized by other antibodies and to explore additional interactions involving Interleukin-2 and related cytokines, thus contributing to our understanding of the complex structure–function relationships within the immune system. [Copyright &y& Elsevier]

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a recent outbreak of coronavirus disease (COVID-19). In Cuba, the first case of COVID-19 was reported on March 11, 2020. Elderly individuals with multiple comorbidities are particularly susceptible to adverse clinical outcomes in the course of SARS-CoV-2 infection. During the outbreak, a local transmission event took place in a nursing home in Villa Clara province, Cuba, in which 19 elderly residents tested positive for SARS-CoV-2. Methods: Based on the increased susceptibility to cytokine release syndrome, inducing respiratory and systemic complications in this population, 19 patients were included in an expanded access clinical trial to receive itolizumab, an anti-CD6 monoclonal antibody. Results: All patients had underlying medical conditions. The product was well tolerated. After the first dose, the course of the disease was favorable, and 18 of the 19 patients (94.7%) were discharged clinically recovered with negative real-time reverse transcription polymerase chain reaction test results at 13 days. After one dose of itolizumab, circulating IL-6 decreased within the first 24–48 h in patients with high baseline values, whereas in patients with low levels, this concentration remained over low values. To preliminarily assess the effect of itolizumab, a control group was selected among the Cuban COVID-19 patients that did not receive immunomodulatory therapy. The control subjects were well matched regarding age, comorbidities, and severity of the disease. The percentage of itolizumab-treated, moderately ill patients who needed to be admitted to the intensive care unit was only one-third of that of the control group not treated with itolizumab. Additionally, treatment with itolizumab reduced the risk of death 10 times as compared with the control group. Conclusion: This study corroborates that the timely use of itolizumab in combination with other antivirals reduces COVID-19 disease worsening and mortality. The humanized antibody itolizumab emerges as a therapeutic alternative for patients with COVID-19. Our results suggest the possible use of itolizumab in patients with cytokine release syndrome from other pathologies. [ABSTRACT FROM AUTHOR]

Abstract: The workshop “Bioinformatics for Biotechnology Applications (HavanaBioinfo 2012)”, held December 8–11, 2012 in Havana, aimed at exploring new bioinformatics tools and approaches for large-scale proteomics, genomics and chemoinformatics. Major conclusions of the workshop include the following: (i) development of new applications and bioinformatics tools for proteomic repository analysis is crucial; current proteomic repositories contain enough data (spectra/identifications) that can be used to increase the annotations in protein databases and to generate new tools for protein identification; (ii) spectral libraries, de novo sequencing and database search tools should be combined to increase the number of protein identifications; (iii) protein probabilities and FDR are not yet sufficiently mature; (iv) computational proteomics software needs to become more intuitive; and at the same time appropriate education and training should be provided to help in the efficient exchange of knowledge between mass spectrometrists and experimental biologists and bioinformaticians in order to increase their bioinformatics background, especially statistics knowledge. [Copyright &y& Elsevier]

Abstract: One of the fundamental properties of the immune system is its capacity to avoid autoimmune diseases. The mechanism underlying this process, known as self-tolerance, is hitherto unresolved but seems to involve the control of clonal expansion of autoreactive lymphocytes. This article reviews mathematical modeling of self-tolerance, addressing two specific hypotheses. The first hypothesis posits that self-tolerance is mediated by tuning of activation thresholds, which makes autoreactive T lymphocytes reversibly “anergic” and unable to proliferate. The second hypothesis posits that the proliferation of autoreactive T lymphocytes is instead controlled by specific regulatory T lymphocytes. Models representing the population dynamics of autoreactive T lymphocytes according to these two hypotheses were derived. For each model we identified how cell density affects tolerance, and predicted the corresponding phase spaces and bifurcations. We show that the simple induction of proliferative anergy, as modeled here, has a density dependence that is only partially compatible with adoptive transfers of tolerance, and that the models of tolerance mediated by specific regulatory T cells are closer to the observations. [Copyright &y& Elsevier]