Are metacaspases caspases?

The identification of caspases as major regulators of apoptotic cell death in animals initiated a quest for homologous peptidases in other kingdoms. With the discovery of metacaspases in plants, fungi, and protozoa, this search had apparently reached its goal. However, there is compelling evidence that metacaspases lack caspase activity and that they are not responsible for the caspaselike activities detected during plant and fungal cell death. In this paper, we attempt to broaden the discussion of these peptidases to biological functions beyond apoptosis and cell death. We further suggest that metacaspases and paracaspases, although sharing structural and mechanistic features with the metazoan caspases, form a distinct family of clan CD cysteine peptidases

Dual Signaling of the Fas Receptor: Initiation of Both Apoptotic and Necrotic Cell Death Pathways

Murine L929 fibrosarcoma cells were transfected with the human Fas (APO-1/CD95) receptor, and the role of various caspases in Fas-mediated cell death was assessed. Proteolytic activation of procaspase-3 and -7 was shown by Western analysis. Acetyl-Tyr-Val-Ala-Asp-chloromethylketone and benzyloxycarbonyl-Asp(OMe)-Glu(OMe)-Val-Asp(OMe)-fluoromethylketone, tetrapeptide inhibitors of caspase-1– and caspase-3–like proteases, respectively, failed to block Fas-induced apoptosis. Unexpectedly, the broad-spectrum caspase inhibitors benzyloxycarbonyl-Val-Ala-Asp(OMe)-fluoromethylketone and benzyloxycarbonyl-Asp(OMe)-fluoromethylketone rendered the cells even more sensitive to Fas-mediated cell death, as measured after 18 h incubation. However, when the process was followed microscopically, it became clear that anti-Fas–induced apoptosis of Fas-transfected L929 cells was blocked during the first 3 h, and subsequently the cells died by necrosis. As in tumor necrosis factor (TNF)-induced necrosis, Fas treatment led to accumulation of reactive oxygen radicals, and Fas-mediated necrosis was inhibited by the oxygen radical scavenger butylated hydroxyanisole. However, in contrast to TNF, anti-Fas did not activate the nuclear factor κB under these necrotic conditions. These results demonstrate the existence of two different pathways originating from the Fas receptor, one rapidly leading to apoptosis, and, if this apoptotic pathway is blocked by caspase inhibitors, a second directing the cells to necrosis and involving oxygen radical production

Phagocytosis of necrotic cells by macrophages is phosphatidylserine dependent and does not induce inflammatory cytokine production

Apoptotic cells are cleared by phagocytosis during development, homeostasis, and pathology. However, it is still unclear how necrotic cells are removed. We compared the phagocytic uptake by macrophages of variants of L929sA murine fibrosarcoma cells induced to die by tumor necrosis factor-induced necrosis or by Fas-mediated apoptosis. We show that apoptotic and necrotic cells are recognized and phagocytosed by macrophages, whereas living cells are not. In both cases, phagocytosis occurred through a phosphatidylserine-dependent mechanism, suggesting that externalization of phosphatidylserine is a general trigger for clearance by macrophages. However, uptake of apoptotic cells was more efficient both quantitatively and kinetically than phagocytosis of necrotic cells. Electron microscopy showed clear morphological differences in the mechanisms used by macrophages to engulf necrotic and apoptotic cells. Apoptotic cells were taken up as condensed membrane-bound particles of various sizes rather than as whole cells, whereas necrotic cells were internalized only as small cellular particles after loss of membrane integrity. Uptake of neither apoptotic nor necrotic L929 cells by macrophages modulated the expression of proinflammatory cytokines by the phagocytes

Potential Use of a Serpin from Arabidopsis for Pest Control

Although genetically modified (GM) plants expressing toxins from Bacillus thuringiensis (Bt) protect agricultural crops against lepidopteran and coleopteran pests, field-evolved resistance to Bt toxins has been reported for populations of several lepidopteran species. Moreover, some important agricultural pests, like phloem-feeding insects, are not susceptible to Bt crops. Complementary pest control strategies are therefore necessary to assure that the benefits provided by those insect-resistant transgenic plants are not compromised and to target those pests that are not susceptible. Experimental GM plants producing plant protease inhibitors have been shown to confer resistance against a wide range of agricultural pests. In this study we assessed the potential of AtSerpin1, a serpin from Arabidopsis thaliana (L). Heynh., for pest control. In vitro assays were conducted with a wide range of pests that rely mainly on either serine or cysteine proteases for digestion and also with three non-target organisms occurring in agricultural crops. AtSerpin1 inhibited proteases from all pest and non-target species assayed. Subsequently, the cotton leafworm Spodoptera littoralis Boisduval and the pea aphid Acyrthosiphon pisum (Harris) were fed on artificial diets containing AtSerpin1, and S. littoralis was also fed on transgenic Arabidopsis plants overproducing AtSerpin1. AtSerpin1 supplied in the artificial diet or by transgenic plants reduced the growth of S. littoralis larvae by 65% and 38%, respectively, relative to controls. Nymphs of A. pisum exposed to diets containing AtSerpin1 suffered high mortality levels (LC50 = 637 µg ml−1). The results indicate that AtSerpin1 is a good candidate for exploitation in pest control

A phloem‐localized Arabidopsis metacaspase (AtMC3) improves drought tolerance

Increasing drought phenomena pose a serious threat to agricultural productivity. Although plants have multiple ways to respond to the complexity of drought stress, the underlying mechanisms of stress sensing and signaling remain unclear. The role of the vasculature, in particular the phloem, in facilitating inter-organ communication is critical and poorly understood.Combining genetic, proteomic and physiological approaches, we investigated the role of AtMC3, a phloem-specific member of the metacaspase family, in osmotic stress responses in Arabidopsis thaliana. Analyses of the proteome in plants with altered AtMC3 levels revealed differential abundance of proteins related to osmotic stress pointing into a role of the protein in water-stress-related responses.Overexpression of AtMC3 conferred drought tolerance by enhancing the differentiation of specific vascular tissues and maintaining higher levels of vascular-mediated transportation, while plants lacking the protein showed an impaired response to drought and inability to respond effectively to the hormone abscisic acid.Overall, our data highlight the importance of AtMC3 and vascular plasticity in fine-tuning early drought responses at the whole plant level without affecting growth or yield.ISSN:0028-646XISSN:1469-813

Optimization-based Methodologies and Algorithms for Dynamic Metabolic Flux Analysis

Mathematical models for the growth, survival, inactivation and product formation of microbial organisms are becoming increasingly important for the model-based design, optimization and control of bioreactors in (industrial) biotechnology, and for assessment of food safetynbsp;quality throughout the supply chain in predictive microbiology. However, existing models mostly focus on describing these systemsnbsp;a macroscopic point of view. To further enhance the applicabilitynbsp;robustness of these models, integration of mechanistic knowledge is a necessity. The objective of this research is the development of advanced numerical strategies that take advantage of microscopic, mechanistic knowledge in the form of a biochemical reaction network, to infer intracellular knowledge and to build new generation predictive models. The general framework that is used throughout the work is the dynamic metabolic flux analysis model structure, with its descriptive and predictive modes. In the first part, a novel algorithm for offline, dynamic estimation of metabolic fluxes based on B-spline flux parameterizations is developed. This algorithm addresses the disadvantages of existing methodologies. Furthermore, a self-contained strategy for choosing the set of free fluxes in the dynamic metabolic flux analysis model is described. The algorithm is illustrated on two simulated case studies. The second part describes the application of this algorithm in a relevant predictive microbiology case study involving the estimation of metabolic fluxes during a lag phase induced through a sudden shift in temperature. Two bioreactor experiments, performed to gather the necessarynbsp;for the estimation, are described,nbsp;after the definition of the metabolic reaction network, the fluxes are estimated. The evolution of the different metabolic pathways is analyzed and some interesting patterns can be discerned. Finally, in the last part, also an online methodology for flux estimation based on the predictive dynamic metabolic flux analysis model structure is shown. The methodology uses two black-box kinetic flux models and moving horizon estimation to get continuously updated estimates ofnbsp;fluxes and a predictive model, ready for model-based control. The influence of important methodology parameters is assessed on a small-scalenbsp;study, and the performance of the algorithm with a realistic, medium-scale network is determined.status: publishe

Dynamic estimation of specific fluxes in metabolic networks using non-linear dynamic optimization

BACKGROUND: Metabolic network models describing the biochemical reaction network and material fluxes inside microorganisms open interesting routes for the model-based optimization of bioprocesses. Dynamic metabolic flux analysis (dMFA) has lately been studied as an extension of regular metabolic flux analysis (MFA), rendering a dynamic view of the fluxes, also in non-stationary conditions. Recent dMFA implementations suffer from some drawbacks, though. More specifically, the fluxes are not estimated as specific fluxes, which are more biologically relevant. Also, the flux profiles are not smooth, and additional constraints like, e.g., irreversibility constraints on the fluxes, cannot be taken into account. Finally, in all previous methods, a basis for the null space of the stoichiometric matrix, i.e., which set of free fluxes is used, needs to be chosen. This choice is not trivial, and has a large influence on the resulting estimates. RESULTS: In this work, a new methodology based on a B-spline parameterization of the fluxes is presented. Because of the high degree of non-linearity due to this parameterization, an incremental knot insertion strategy has been devised, resulting in a sequence of non-linear dynamic optimization problems. These are solved using state-of-the-art dynamic optimization methods and tools, i.e., orthogonal collocation, an interior-point optimizer and automatic differentiation. Also, a procedure to choose an optimal basis for the null space of the stoichiometric matrix is described, discarding the need to make a choice beforehand. The proposed methodology is validated on two simulated case studies: (i) a small-scale network with 7 fluxes, to illustrate the operation of the algorithm, and (ii) a medium-scale network with 68 fluxes, to show the algorithm's capabilities for a realistic network. The results show an accurate correspondence to the reference fluxes used to simulate the measurements, both in a theoretically ideal setting with no experimental noise, and in a realistic noise setting. CONCLUSIONS: Because, apart from a metabolic reaction network and the measurements, no extra input needs to be given, the resulting algorithm is a systematic, integrated and accurate methodology for dynamic metabolic flux analysis that can be run online in real-time if necessary.status: publishe