Electron bifurcation mechanism and homoacetogenesis explain products yields in mixed culture anaerobic fermentations

Anaerobic fermentation of organic wastes using microbial mixed cultures is a promising avenue to treat residues and obtain added-value products. However, the process has some important limitations that prevented so far any industrial application. One of the main issues is that we are not able to predict reliably the product spectrum (i.e. the stoichiometry of the process) because the complex microbial community behaviour is not completely understood. To address this issue, in this work we propose a new metabolic network of glucose fermentation by microbial mixed cultures that incorporates electron bifurcation and homoacetogenesis. Our methodology uses NADH balances to analyse published experimental data and evaluate the new stoichiometry proposed. Our results prove for the first time the inclusion of electron bifurcation in the metabolic network as a better description of the experimental results. Homoacetogenesis has been used to explain the discrepancies between observed and theoretically predicted yields of gaseous H2 and CO2 and it appears as the best solution among other options studied. Overall, this work supports the consideration of electron bifurcation as an important biochemical mechanism in microbial mixed cultures fermentations and underlines the importance of considering homoacetogenesis when analysing anaerobic fermentations

Microbial catabolic activities are naturally selected by metabolic energy harvest rate

The fundamental trade-off between yield and rate of energy harvest per unit of substrate has been largely discussed as a main characteristic for microbial established cooperation or competition. In this study, this point is addressed by developing a generalized model that simulates competition between existing and not experimentally reported microbial catabolic activities defined only based on well-known biochemical pathways. No specific microbial physiological adaptations are considered, growth yield is calculated coupled to catabolism energetics and a common maximum biomass-specific catabolism rate (expressed as electron transfer rate) is assumed for all microbial groups. Under this approach, successful microbial metabolisms are predicted in line with experimental observations under the hypothesis of maximum energy harvest rate. Two microbial ecosystems, typically found in wastewater treatment plants, are simulated, namely: (i) the anaerobic fermentation of glucose and (ii) the oxidation and reduction of nitrogen under aerobic autotrophic (nitrification) and anoxic heterotrophic and autotrophic (denitrification) conditions. The experimentally observed cross feeding in glucose fermentation, through multiple intermediate fermentation pathways, towards ultimately methane and carbon dioxide is predicted. Analogously, two-stage nitrification (by ammonium and nitrite oxidizers) is predicted as prevailing over nitrification in one stage. Conversely, denitrification is predicted in one stage (by denitrifiers) as well as anammox (anaerobic ammonium oxidation). The model results suggest that these observations are a direct consequence of the different energy yields per electron transferred at the different steps of the pathways. Overall, our results theoretically support the hypothesis that successful microbial catabolic activities are selected by an overall maximum energy harvest rate

Microbial diversity arising from thermodynamic constraints

The microbial world displays an immense taxonomic diversity. This diversity is manifested also in a multitude of metabolic pathways that can utilize different substrates and produce different products. Here, we propose that these observations directly link to thermodynamic constraints that inherently arise from the metabolic basis of microbial growth. We show that thermodynamic constraints can enable coexistence of microbes that utilise the same substrate but produce different end products. We find that this thermodynamics-driven emergence of diversity is most relevant for metabolic conversions with low free energy as seen for example under anaerobic conditions, where population dynamics is governed by thermodynamic effects rather than kinetic factors such as substrate uptake rates. These findings provide a general understanding of the microbial diversity based on the first-principles of thermodynamics. As such they provide a thermodynamics-based framework for explaining the observed microbial diversity in different natural and synthetic environments

New polymorphisms associated with response to anti-TNF drugs in patients with moderate-to-severe plaque psoriasis

Anti-tumor necrosis factor (anti-TNF) drugs are effective against psoriasis, although 20–30% of patients are nonresponders. Few pharmacogenomic studies have been performed to predict the response to anti-TNF drugs in psoriasis. We studied 173 polymorphisms to establish an association with the response to anti-TNF drugs in patients with moderate-to-severe plaque psoriasis (N=144). We evaluated the response using PASI75 at 3, 6 and 12 months. The results of the multivariate analysis showed an association between polymorphisms in PGLYR4, ZNF816A, CTNNA2, IL12B, MAP3K1 and HLA-C genes and the response at 3 months. Besides, the results for polymorphisms in IL12B and MAP3K1 were replicated at 6 months. We also obtained significant results for IL12B polymorphism at 1 year. Moreover, polymorphisms in FCGR2A, HTR2A and CDKAL1 were significant at 6 months. This is the first study to show an association with these polymorphisms. However, these biomarkers should be validated in large-scale studies before implementation in clinical practiceThis study was supported by Instituto de Salud Carlos III (FIS PI10/01740), Fundación Teófilo Hernando, and AbbVie. RPP has a grant from Universidad Autónoma de Madrid (FPI program 2013

Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders.

Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development

New individual-based model links microbial growth to the energy available in the environment

A new individual-based model is presented in which we aim to describe microbial growth constrained by the environmental conditions at each point of a 2D space. The model is characterized for a full description of the physico-chemistry of the system and uses thermodynamics to approximate the microbial growth. The growth parameters are estimated using the information of the surroundings and it employs only first principles instead of relying on measurements at the population level. This allows ab initio approximation of the growth parameters, and therefore directly links microbial growth and environmental conditions. For this reason, the model is characterised for its flexibility. We test the model in three very different scenarios: anaerobic digestion, aerobic heterotrophic growth and nitrification. Due to its flexibility, rigorous thermodynamic calculations and the possibility to estimate the parameters ab initio, the model will be further used to hypothesize the presence of new functional groups or microbial species not yet discovered and to model complex microbial populations not well understood. Moreover, it can be used to study the rules that control microbial evolution or/and immigration

Study of the competition between complete nitrification by a single organism and ammonia- and nitrite-oxidizing bacteria

Complete nitrification by only one microorganism has been recently experimentally discovered. However, it was theoretically predicted almost 10 years ago by hypothesizing that complete nitrifiers are yield strategist that have a metabolic advantage to survive in biofilms. In this work, we study the competition for ammonia between complete nitrifiers and the canonical division of labour between ammonia and nitrite oxidizing bacteria in biofilms by using an individual based model. The model calculates the maximum growth yield using thermodynamics to evaluate the limitation in growth for each functional group in each position of the computational domain. Our results suggest that the trade-off between growth yield and growth rate in ammonia oxidizing bacteria and in complete nitrifiers is not significant as to observe a clear advantage for complete nitrifiers existence in biofilms