Metabolic modeling of Halomonas campaniensis improves polyhydroxybutyrate production under nitrogen limitation.

Poly-hydroxybutyrate (PHB) is an environmentally friendly alternative for conventional fossil fuel-based plastics that is produced by various microorganisms. Large-scale PHB production is challenging due to the comparatively higher biomanufacturing costs. A PHB overproducer is the haloalkaliphilic bacterium Halomonas campaniensis, which has low nutritional requirements and can grow in cultures with high salt concentrations, rendering it resistant to contamination. Despite its virtues, the metabolic capabilities of H. campaniensis as well as the limitations hindering higher PHB production remain poorly studied. To address this limitation, we present HaloGEM, the first high-quality genome-scale metabolic network reconstruction, which encompasses 888 genes, 1528 reactions (1257 gene-associated), and 1274 metabolites. HaloGEM not only displays excellent agreement with previous growth data and experiments from this study, but it also revealed nitrogen as a limiting nutrient when growing aerobically under high salt concentrations using glucose as carbon source. Among different nitrogen source mixtures for optimal growth, HaloGEM predicted glutamate and arginine as a promising mixture producing increases of 54.2% and 153.4% in the biomass yield and PHB titer, respectively. Furthermore, the model was used to predict genetic interventions for increasing PHB yield, which were consistent with the rationale of previously reported strategies. Overall, the presented reconstruction advances our understanding of the metabolic capabilities of H. campaniensis for rationally engineering this next-generation industrial biotechnology platform. KEY POINTS: A comprehensive genome-scale metabolic reconstruction of H. campaniensis was developed. Experiments and simulations predict N limitation in minimal media under aerobiosis. In silico media design increased experimental biomass yield and PHB titer.

The pH-dependent lactose metabolism of Lactobacillus delbrueckii subsp. bulgaricus: An integrative view through a mechanistic computational model.

The fermentation process of milk to yoghurt using Lactobacillus delbrueckii subsp. bulgaricus in co-culture with Streptococcus thermophilus is hallmarked by the breakdown of lactose to organic acids such as lactate. This leads to a substantial decrease in pH - both in the medium, as well as cytosolic. The latter impairs metabolic activities due to the pH-dependence of enzymes, which compromises microbial growth. To quantitatively elucidate the impact of the acidification on metabolism of L. bulgaricus in an integrated way, we have developed a proton-dependent computational model of lactose metabolism and casein degradation based on experimental data. The model accounts for the influence of pH on enzyme activities as well as cellular growth and proliferation of the bacterial population. We used a machine learning approach to quantify the cell volume throughout fermentation. Simulation results show a decrease in metabolic flux with acidification of the cytosol. Additionally, the validated model predicts a similar metabolic behaviour within a wide range of non-limiting substrate concentrations. This computational model provides a deeper understanding of the intricate relationships between metabolic activity and acidification and paves the way for further optimization of yoghurt production under industrial settings.

Metabolic behavior for a mutant Oenococcus oeni strain with high resistance to ethanol to survive under oenological multi-stress conditions.

Malolactic fermentation (MLF) positively influences the quality of the wine, and it occurs as a result of a lactic acid bacteria's metabolism, mainly of the Oenococcus oeni species. However, delays and halting of MLF are frequent problems in the wine industry. This is mainly because O. oeni's development is inhibited by different kinds of stress. Even though the sequencing of the genome of the PSU-1 strain of O. oeni, as well as other strains, has made it possible to identify genes involved in the resistance to some types of stress, all of the factors that could be involved are still unknown. With the aim of contributing to this knowledge, the random mutagenesis technique was used in this study as a strategy for genetic improvement of strains of the O. oeni species. The technique proved to be capable of generating a different and improved strain when compared to the PSU-1 strain (the parent from which it descends). Then, we evaluated the metabolic behavior of both strains in three different wines. We used synthetic MaxOeno wine (pH 3.5; 15% v/v ethanol), red wine (Cabernet Sauvignon), and white wine (Chardonnay). Furthermore, we compared the transcriptome of both strains, grown in MaxOeno synthetic wine. The specific growth rate of the E1 strain was on average 39% higher in comparison to the PSU-1 strain. Interestingly, E1 strain showed an overexpression of the OEOE_1794 gene, which encodes a UspA-like protein, which has been described as promoting growth. We observed that the E1 strain was able to convert, on average, 34% more malic acid into lactate than the PSU-1 strain, regardless of the wine being used. On the other hand, the E1 strain showed a flux rate of fructose-6-phosphate production that was 86% higher than the mannitol production rate, and the internal flux rates increase in the direction of pyruvate production. This coincides with the higher number of OEOE_1708 gene transcripts observed in the E1 strain grown in MaxOeno. This gene encodes for an enzyme fructokinase (EC 2.7.1.4) involved in the transformation of fructose to fructose-6-phosphate.

Ethanol-lactate transition of Lachancea thermotolerans is linked to nitrogen metabolism.

Climate change increases sugar content in grapes, resulting in unwanted increase in ethanol content of wine. Lachancea thermotolerans ferments glucose and fructose into both ethanol and lactate, decreasing final ethanol content and positively affecting wine acidity. Reported Lachancea thermotolerans strains show big variation in lactate production during fermentation. However, a mechanistic understanding of this lactate producing phenotype is currently lacking. Through a combination of metabolomics, transcriptomics, genomics and computational methods we show that the lactate production is induced by amino acid limitation in a high lactate producing strain. We found in fermentations in synthetic grape juice media that lactate production starts in the last stages of growth, marked by decreased growth rate and increased expression levels of stress related genes. This onset of lactate production is specific for the high lactate producing strain and independent of oxygen availability. The onset of lactate production was changed by increased amino acid content of the media, and it is shown by both computational methods and amino acid measurements that at the onset of lactate production amino acids become limiting for growth. This study shows that lactate production of Lachancea thermotolerans is directly linked to nitrogen availability in the media, an insight that can further aid in the improvement of wine quality.

Metabolic Modeling of Wine Fermentation at Genome Scale.

Wine fermentation is an ancient biotechnological process mediated by different microorganisms such as yeast and bacteria. Understanding of the metabolic and physiological phenomena taking place during this process can be now attained at a genome scale with the help of metabolic models. In this chapter, we present a detailed protocol for modeling wine fermentation using genome-scale metabolic models. In particular, we illustrate how metabolic fluxes can be computed, optimized and interpreted, for both yeast and bacteria under winemaking conditions. We also show how nutritional requirements can be determined and simulated using these models in relevant test cases. This chapter introduces fundamental concepts and practical steps for applying flux balance analysis in wine fermentation, and as such, it is intended for a broad microbiology audience as well as for practitioners in the metabolic modeling field.

A Multiphase Multiobjective Dynamic Genome-Scale Model Shows Different Redox Balancing among Yeast Species of the Saccharomyces Genus in Fermentation.

Yeasts constitute over 1,500 species with great potential for biotechnology. Still, the yeast Saccharomyces cerevisiae dominates industrial applications, and many alternative physiological capabilities of lesser-known yeasts are not being fully exploited. While comparative genomics receives substantial attention, little is known about yeasts' metabolic specificity in batch cultures. Here, we propose a multiphase multiobjective dynamic genome-scale model of yeast batch cultures that describes the uptake of carbon and nitrogen sources and the production of primary and secondary metabolites. The model integrates a specific metabolic reconstruction, based on the consensus Yeast8, and a kinetic model describing the time-varying culture environment. In addition, we proposed a multiphase multiobjective flux balance analysis to compute the dynamics of intracellular fluxes. We then compared the metabolism of S. cerevisiae and Saccharomyces uvarum strains in a rich medium fermentation. The model successfully explained the experimental data and brought novel insights into how cryotolerant strains achieve redox balance. The proposed model (along with the corresponding code) provides a comprehensive picture of the main steps occurring inside the cell during batch cultures and offers a systematic approach to prospect or metabolically engineering novel yeast cell factories. IMPORTANCE Nonconventional yeast species hold the promise to provide novel metabolic routes to produce industrially relevant compounds and tolerate specific stressors, such as cold temperatures. This work validated the first multiphase multiobjective genome-scale dynamic model to describe carbon and nitrogen metabolism throughout batch fermentation. To test and illustrate its performance, we considered the comparative metabolism of three yeast strains of the Saccharomyces genus in rich medium fermentation. The study revealed that cryotolerant Saccharomyces species might use the γ-aminobutyric acid (GABA) shunt and the production of reducing equivalents as alternative routes to achieve redox balance, a novel biological insight worth being explored further. The proposed model (along with the provided code) can be applied to a wide range of batch processes started with different yeast species and media, offering a systematic and rational approach to prospect nonconventional yeast species metabolism and engineering novel cell factories.

Oxytocin neurons enable social transmission of maternal behaviour.

Maternal care, including by non-biological parents, is important for offspring survival1-8. Oxytocin1,2,9-15, which is released by the hypothalamic paraventricular nucleus (PVN), is a critical maternal hormone. In mice, oxytocin enables neuroplasticity in the auditory cortex for maternal recognition of pup distress15. However, it is unclear how initial parental experience promotes hypothalamic signalling and cortical plasticity for reliable maternal care. Here we continuously monitored the behaviour of female virgin mice co-housed with an experienced mother and litter. This documentary approach was synchronized with neural recordings from the virgin PVN, including oxytocin neurons. These cells were activated as virgins were enlisted in maternal care by experienced mothers, who shepherded virgins into the nest and demonstrated pup retrieval. Virgins visually observed maternal retrieval, which activated PVN oxytocin neurons and promoted alloparenting. Thus rodents can acquire maternal behaviour by social transmission, providing a mechanism for adapting the brains of adult caregivers to infant needs via endogenous oxytocin.

Genome-scale metabolic models of Microbacterium species isolated from a high altitude desert environment.

The Atacama Desert is the most arid desert on Earth, focus of important research activities related to microbial biodiversity studies. In this context, metabolic characterization of arid soil bacteria is crucial to understand their survival strategies under extreme environmental stress. We investigated whether strain-specific features of two Microbacterium species were involved in the metabolic ability to tolerate/adapt to local variations within an extreme desert environment. Using an integrative systems biology approach we have carried out construction and comparison of genome-scale metabolic models (GEMs) of two Microbacterium sp., CGR1 and CGR2, previously isolated from physicochemically contrasting soil sites in the Atacama Desert. Despite CGR1 and CGR2 belong to different phylogenetic clades, metabolic pathways and attributes are highly conserved in both strains. However, comparison of the GEMs showed significant differences in the connectivity of specific metabolites related to pH tolerance and CO2 production. The latter is most likely required to handle acidic stress through decarboxylation reactions. We observed greater GEM connectivity within Microbacterium sp. CGR1 compared to CGR2, which is correlated with the capacity of CGR1 to tolerate a wider pH tolerance range. Both metabolic models predict the synthesis of pigment metabolites (ß-carotene), observation validated by HPLC experiments. Our study provides a valuable resource to further investigate global metabolic adaptations of bacterial species to grow in soils with different abiotic factors within an extreme environment.

KRAS4A directly regulates hexokinase 1.

The most frequently mutated oncogene in cancer is KRAS, which uses alternative fourth exons to generate two gene products (KRAS4A and KRAS4B) that differ only in their C-terminal membrane-targeting region1. Because oncogenic mutations occur in exons 2 or 3, two constitutively active KRAS proteins-each capable of transforming cells-are encoded when KRAS is activated by mutation2. No functional distinctions among the splice variants have so far been established. Oncogenic KRAS alters the metabolism of tumour cells3 in several ways, including increased glucose uptake and glycolysis even in the presence of abundant oxygen4 (the Warburg effect). Whereas these metabolic effects of oncogenic KRAS have been explained by transcriptional upregulation of glucose transporters and glycolytic enzymes3-5, it is not known whether there is direct regulation of metabolic enzymes. Here we report a direct, GTP-dependent interaction between KRAS4A and hexokinase 1 (HK1) that alters the activity of the kinase, and thereby establish that HK1 is an effector of KRAS4A. This interaction is unique to KRAS4A because the palmitoylation-depalmitoylation cycle of this RAS isoform enables colocalization with HK1 on the outer mitochondrial membrane. The expression of KRAS4A in cancer may drive unique metabolic vulnerabilities that can be exploited therapeutically.

Encrypted audio dataset based on the Collatz conjecture.

In information security, one way to keep a secret content is through encryption. The objective is to alter the content so that it is not intelligible, and therefore only the intended user can reveal the secret content. With the aim to provide examples of encrypted audio data, we applied a novel method of encryption based on the Collatz conjecture in five hundred speech recordings (50 speakers, 10 different messages), and then five hundred encrypted audio files were obtained. The main characteristics of our encrypted recordings are as follows: the spectrogram is quasi-uniform, histograms have a repetitive pattern, average of samples is around -0.4, standard deviation is around 0.55; Shannon entropy is around 7.5 (for 8-bits per sample). The novelty of the results consists in obtaining a completely different behavior than natural speech recordings, i.e.: spectrogram with higher energy in low frequencies, histogram with Gaussian behavior, average of samples around 0, standard deviation around 0.11, entropy around 5.5. A more comprehensive analysis of our encrypted signals may be obtained from the article "High-uncertainty audio signal encryption based on the Collatz conjecture" in the Journal of Information Security and Applications.

PET imaging study of brown adipose tissue (BAT) activity in mice devoid of receptor for advanced glycation end products (RAGE).

Brown adipose tissue (BAT) is responsible for adaptive thermogenesis. We previously showed that genetic deficiency of receptor for advanced glycation end products (RAGE) prevented the effects of high-fat diet (HFD). This study was to compare BAT activity in RAGE knock out (Ager-/-, RKO) and wild-type (WT) mice after treated with HFD or LFD. [18F]FDG PET-CT imaging under identical cold-stimulated conditions and mean standard uptake values (SUVmean), ratio of SUViBAT/SUVmuscle (SUVR, muscle as the reference region) and percentage ID/g were used for BAT quantification. The results showed that [18F]FDG uptake (e.g., SUVR) in WT-HFD mice was significantly reduced (three-fold) as compared to that in WT-LFD (1.40 +/- 0.07 and 4.03 +/- 0.38; P = 0.004). In contrast, BAT activity in RKO mice was not significantly affected by HFD, with SUVRRKO-LFD: 2.14 +/- 0.10 and SUVRRKO-LFD: 1.52 +/- 0.13 (P = 0.3). The uptake in WT-LFD was almost double of that in RKO-LFD (P = 0.004); however, there was no significant difference between RKO-HFD and WT-HFD mice (P = 0.3). These results, corroborating our previous findings on the measurement of mRNA transcripts for UCP1 in the BAT, suggest that RAGE may contribute to altered energy expenditure and provide a protective effect against HFD by Ager deletion (Ager -/-).

A systematic assessment of current genome-scale metabolic reconstruction tools.

BACKGROUND: Several genome-scale metabolic reconstruction software platforms have been developed and are being continuously updated. These tools have been widely applied to reconstruct metabolic models for hundreds of microorganisms ranging from important human pathogens to species of industrial relevance. However, these platforms, as yet, have not been systematically evaluated with respect to software quality, best potential uses and intrinsic capacity to generate high-quality, genome-scale metabolic models. It is therefore unclear for potential users which tool best fits the purpose of their research. RESULTS: In this work, we perform a systematic assessment of current genome-scale reconstruction software platforms. To meet our goal, we first define a list of features for assessing software quality related to genome-scale reconstruction. Subsequently, we use the feature list to evaluate the performance of each tool. To assess the similarity of the draft reconstructions to high-quality models, we compare each tool's output networks with that of the high-quality, manually curated, models of Lactobacillus plantarum and Bordetella pertussis, representatives of gram-positive and gram-negative bacteria, respectively. We additionally compare draft reconstructions with a model of Pseudomonas putida to further confirm our findings. We show that none of the tools outperforms the others in all the defined features. CONCLUSIONS: Model builders should carefully choose a tool (or combinations of tools) depending on the intended use of the metabolic model. They can use this benchmark study as a guide to select the best tool for their research. Finally, developers can also benefit from this evaluation by getting feedback to improve their software.

Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

In Vivo Evaluation of Neuronal Transport in Murine Models of Neurodegeneration Using Manganese-Enhanced MRI.

Manganese-enhanced MRI (MRI) is a technique that allows for a noninvasive in vivo estimation of neuronal transport. It relies on the physicochemical properties of manganese, which is both a calcium analogue being transported along neurons by active transport, and a paramagnetic compound that can be detected on conventional T1-weighted images. Here, we report a multi-session MEMRI protocol that helps establish time-dependent curves relating to neuronal transport along the olfactory tract over several days. The characterization of these curves via unbiased fitting enables us to infer objectively a set of three parameters (the rate of manganese transport from the maximum slope, the peak intensity, and the time to peak intensity). These parameters, measured previously in wild type mice during normal aging, have served as a baseline to demonstrate their significant sensitivity to pathogenic processes associated with Tau pathology. Importantly, the evaluation of these three parameters and their use as indicators can be extended to monitor any normal and pathogenic processes where neuronal transport is altered. This approach can be applied to characterize and quantify the effect of any neurological disease conditions on neuronal transport in animal models, together with the efficacy of potential therapies.

Traceability, reproducibility and wiki-exploration for "à-la-carte" reconstructions of genome-scale metabolic models.

Genome-scale metabolic models have become the tool of choice for the global analysis of microorganism metabolism, and their reconstruction has attained high standards of quality and reliability. Improvements in this area have been accompanied by the development of some major platforms and databases, and an explosion of individual bioinformatics methods. Consequently, many recent models result from "à la carte" pipelines, combining the use of platforms, individual tools and biological expertise to enhance the quality of the reconstruction. Although very useful, introducing heterogeneous tools, that hardly interact with each other, causes loss of traceability and reproducibility in the reconstruction process. This represents a real obstacle, especially when considering less studied species whose metabolic reconstruction can greatly benefit from the comparison to good quality models of related organisms. This work proposes an adaptable workspace, AuReMe, for sustainable reconstructions or improvements of genome-scale metabolic models involving personalized pipelines. At each step, relevant information related to the modifications brought to the model by a method is stored. This ensures that the process is reproducible and documented regardless of the combination of tools used. Additionally, the workspace establishes a way to browse metabolic models and their metadata through the automatic generation of ad-hoc local wikis dedicated to monitoring and facilitating the process of reconstruction. AuReMe supports exploration and semantic query based on RDF databases. We illustrate how this workspace allowed handling, in an integrated way, the metabolic reconstructions of non-model organisms such as an extremophile bacterium or eukaryote algae. Among relevant applications, the latter reconstruction led to putative evolutionary insights of a metabolic pathway.

Mapping the Physiological Response of Oenococcus oeni to Ethanol Stress Using an Extended Genome-Scale Metabolic Model.

The effect of ethanol on the metabolism of Oenococcus oeni, the bacterium responsible for the malolactic fermentation (MLF) of wine, is still scarcely understood. Here, we characterized the global metabolic response in O. oeni PSU-1 to increasing ethanol contents, ranging from 0 to 12% (v/v). We first optimized a wine-like, defined culture medium, MaxOeno, to allow sufficient bacterial growth to be able to quantitate different metabolites in batch cultures of O. oeni. Then, taking advantage of the recently reconstructed genome-scale metabolic model iSM454 for O. oeni PSU-1 and the resulting experimental data, we determined the redistribution of intracellular metabolic fluxes, under the different ethanol conditions. Four growth phases were clearly identified during the batch cultivation of O. oeni PSU-1 strain, according to the temporal consumption of malic and citric acids, sugar and amino acids uptake, and biosynthesis rates of metabolic products - biomass, erythritol, mannitol and acetic acid, among others. We showed that, under increasing ethanol conditions, O. oeni favors anabolic reactions related with cell maintenance, as the requirements of NAD(P)+ and ATP increased with ethanol content. Specifically, cultures containing 9 and 12% ethanol required 10 and 17 times more NGAM (non-growth associated maintenance ATP) during phase I, respectively, than cultures without ethanol. MLF and citric acid consumption are vital at high ethanol concentrations, as they are the main source for proton extrusion, allowing higher ATP production by F0F1-ATPase, the main route of ATP synthesis under these conditions. Mannitol and erythritol synthesis are the main sources of NAD(P)+, countervailing for 51-57% of its usage, as predicted by the model. Finally, cysteine shows the fastest specific consumption rate among the amino acids, confirming its key role for bacterial survival under ethanol stress. As a whole, this study provides a global insight into how ethanol content exerts a differential physiological response in O. oeni PSU-1 strain. It will help to design better strategies of nutrient addition to achieve a successful MLF of wine.

Spontaneous pneumomediastinum. case report

ABSTRACT Introduction: Spontaneous pneumomediastinum (SPM) is defined as the presence of air in the mediastinum. It is a rare entity considered benign and self-limiting, which mostly affects young adults. Its diagnosis is confirmed through clinical and radiological studies. Case description: 21-year-old male patient with cough and greenish expectoration for four days, associated with dyspnea, chest pain, fever and bilateral supraclavicular subcutaneous emphysema. Chest X-ray suggested pneumomediastinum, which was confirmed by tomography. The patient was hospitalized for observation and treatment. After a positive evolution, he was discharged on the sixth day. Discussion: SPM is a differential diagnosis in patients with chest pain and dyspnea. Its prevalence is lower than 0.01% and its mortality rate is low. It should be suspected in patients with chest pain and subcutaneous emphysema on physical examination. Between 70 and 90% of the cases can be identified by chest X-ray, while confirmation can be obtained through chest tomography. In most cases it does not require additional studies. Conclusion: SPM is a little known cause of acute chest pain, and rarely considered as a differential diagnosis; it is self-limited and has a good prognosis.

Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production.

BACKGROUND: Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. Only some Nannochloropsis species have been sequenced, but none of them benefit from a genome-scale metabolic model (GSMM), able to predict its metabolic capabilities. RESULTS: We present iNS934, the first GSMM for N. salina, including 2345 reactions, 934 genes and an exhaustive description of lipid and nitrogen metabolism. iNS934 has a 90% of accuracy when making simple growth/no-growth predictions and has a 15% error rate in predicting growth rates in different experimental conditions. Moreover, iNS934 allowed us to propose 82 different knockout strategies for strain optimization of triacylglycerols. CONCLUSIONS: iNS934 provides a powerful tool for metabolic improvement, allowing predictions and simulations of N. salina metabolism under different media and genetic conditions. It also provides a systemic view of N. salina metabolism, potentially guiding research and providing context to -omics data.

Infected pulmonary infarction case report / Infarto pulmonar infectado. reporte de caso

ABSTRACT Introduction: Pulmonary infarction occurs in 29% to 32% of patients with pulmonary thromboembolism (PTE). The infection of a pulmonary infarction is a complication in approximately 2 to 7% of the cases, which makes it a rare entity. Case Presentation: 49-year-old woman with pleuritic pain in the left hemithorax that irradiated to the dorsal region, associated with dyspnea and painful edema in the left lower limb of two days of evolution. Two weeks prior to admission, the patient suffered from a left knee trauma that required surgical intervention; however, due to unknown reasons, she did not receive antithrombotic prophylaxis. Physical examination showed tachycardia, tachypnea and painful edema with erythema in the left leg. After suspecting a pulmonary thromboembolism, anticoagulation medication was administered and a chest angiotomography was requested to confirm the diagnosis. The patient experienced signs of systemic inflammatory response, and respiratory deterioration. A control tomography was performed, suggesting infected pulmonary infarction. Antibiotic treatment was initiated, obtaining progressive improvement; the patient was subsequently discharged, and continued with anticoagulation medication and follow-up on an outpatient basis. Conclusions: Pulmonary infarction is a frequent complication in patients with PTE. Therefore, infected pulmonary infarction should be suspected in patients with clinical deterioration and systemic inflammatory response. The radiological difference between pulmonary infarction and pneumonia is not easily identified, thus the diagnostic approach is clinical, and anticoagulant and antimicrobial treatment should be initiated in a timely manner.

RESUMEN Introducción El infarto pulmonar ocurre entre un 29 y un 32% de pacientes con tromboembolismo pulmonar (TEP). Por su parte, la infección de un infarto pulmonar complica aproximadamente del 2 al 7% de los casos, lo que hace que el infarto pulmonar infectado sea una entidad poco frecuente. Descripción del caso Mujer de 49 años con dolor pleurítico en hemitórax izquierdo, irradiado a región dorsal, asociado a disnea y edema doloroso de miembro inferior izquierdo de dos días de evolución. Dos semanas antes de su ingreso la paciente sufrió trauma de rodilla izquierda, el cual que requirió intervención quirúrgica; sin embargo, por motivos desconocidos, no recibió profilaxis anti trombótica. En el examen físico se encontró taquicardia, taquipnea y edema doloroso con eritema en pierna izquierda. Al existir alta sospecha de tromboembolia pulmonar se inició anticoagulación y se solicitó angiotomografía de tórax, con la cual fue posible confirmar el diagnóstico. Durante su evolución, la paciente experimentó signos de respuesta inflamatoria sistémica, deterioro respiratorio. Se realizó tomografía de control sugestiva de infarto pulmonar infectado. Se inició antibiótico y la paciente mejoró de forma progresiva; después de esta mejora, fue dada de alta para continuar anticoagulación y seguimiento ambulatorios. Conclusiones El infarto pulmonar es una complicación frecuente en pacientes con TEP. Por lo tanto, debe sospecharse infarto pulmonar infectado en pacientes con deterioro clínico y respuesta inflamatoria sistémica. La diferencia radiológica entre infarto pulmonar y neumonía no es fácil de identificar, su enfoque diagnóstico es clínico y el tratamiento anticoagulante y antimicrobiano debe iniciarse de manera oportuna.

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation.

Oenococcus oeni is the main responsible agent for malolactic fermentation in wine, an unpredictable and erratic process in winemaking. To address this, we have constructed and exhaustively curated the first genome-scale metabolic model of Oenococcus oeni, comprising 660 reactions, 536 metabolites and 454 genes. In silico experiments revealed that nutritional requirements are predicted with an accuracy of 93%, while 14 amino acids were found to be essential for the growth of this bacterial species. When the model was applied to determine the non-growth associated maintenance, results showed that O. oeni grown at 12% ethanol concentration spent 30 times more ATP to stay alive than in the absence of ethanol. Most of this ATP is employed for extruding protons outside of the cell. A positive relationship was also found between specific consumption rates of fructose, amino acids, oxygen, and malic acid and the specific production rates of erythritol, lactate, and acetate, according to the ethanol content of the medium. The metabolic model reconstructed here represents a unique tool to predict the successful completion of wine malolactic fermentation carried out either by different strains of Oenococcus oeni, as well as at any particular physico-chemical composition of wine. It will also allow the development of consortium metabolic models that could be applied to winemaking to simulate and understand the interactions between O. oeni and other microorganisms that share this ecological niche.