Mathematical kinetic modelling followed by in vitro and in vivo assays reveal the bifunctional rice GTPCHII/DHBPS enzymes and demonstrate the key roles of OsRibA proteins in the vitamin B2 pathway.

BACKGROUND: Riboflavin is the precursor of several cofactors essential for normal physical and cognitive development, but only plants and some microorganisms can produce it. Humans thus rely on their dietary intake, which at a global level is mainly constituted by cereals (> 50%). Understanding the riboflavin biosynthesis players is key for advancing our knowledge on this essential pathway and can hold promise for biofortification strategies in major crop species. In some bacteria and in Arabidopsis, it is known that RibA1 is a bifunctional protein with distinct GTP cyclohydrolase II (GTPCHII) and 3,4-dihydroxy-2-butanone-4-phosphate synthase (DHBPS) domains. Arabidopsis harbors three RibA isoforms, but only one retained its bifunctionality. In rice, however, the identification and characterization of RibA has not yet been described. RESULTS: Through mathematical kinetic modeling, we identified RibA as the rate-limiting step of riboflavin pathway and by bioinformatic analysis we confirmed that rice RibA proteins carry both domains, DHBPS and GTPCHII. Phylogenetic analysis revealed that OsRibA isoforms 1 and 2 are similar to Arabidopsis bifunctional RibA1. Heterologous expression of OsRibA1 completely restored the growth of the rib3∆ yeast mutant, lacking DHBPS expression, while causing a 60% growth improvement of the rib1∆ mutant, lacking GTPCHII activity. Regarding OsRibA2, its heterologous expression fully complemented GTPCHII activity, and improved rib3∆ growth by 30%. In vitro activity assays confirmed that both OsRibA1 and OsRibA2 proteins carry GTPCHII/DHBPS activities, but that OsRibA1 has higher DHBPS activity. The overexpression of OsRibA1 in rice callus resulted in a 28% increase in riboflavin content. CONCLUSIONS: Our study elucidates the critical role of RibA in rice riboflavin biosynthesis pathway, establishing it as the rate-limiting step in the pathway. By identifying and characterizing OsRibA1 and OsRibA2, showcasing their GTPCHII and DHBPS activities, we have advanced the understanding of riboflavin biosynthesis in this staple crop. We further demonstrated that OsRibA1 overexpression in rice callus increases its riboflavin content, providing supporting information for bioengineering efforts.

The first multi-tissue genome-scale metabolic model of a woody plant highlights suberin biosynthesis pathways in Quercus suber.

Over the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behaviour at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871). The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyse the pathways associated with the synthesis of suberin monomers, namely the acyl-lipids, phenylpropanoids, isoprenoids, and flavonoids production. The models developed in this work provide a systematic overview of the metabolism of Q. suber, including its secondary metabolism pathways and cork formation.

Metabolic reconstruction of the human pathogen Candida auris: using a cross-species approach for drug target prediction.

Candida auris is an emerging human pathogen, associated with antifungal drug resistance and hospital candidiasis outbreaks. In this work, we present iRV973, the first reconstructed Genome-scale metabolic model (GSMM) for C. auris. The model was manually curated and experimentally validated, being able to accurately predict the specific growth rate of C. auris and the utilization of several sole carbon and nitrogen sources. The model was compared to GSMMs available for other pathogenic Candida species and exploited as a platform for cross-species comparison, aiming the analysis of their metabolic features and the identification of potential new antifungal targets common to the most prevalent pathogenic Candida species. From a metabolic point of view, we were able to identify unique enzymes in C. auris in comparison with other Candida species, which may represent unique metabolic features. Additionally, 50 enzymes were identified as potential drug targets, given their essentiality in conditions mimicking human serum, common to all four different Candida models analysed. These enzymes represent interesting drug targets for antifungal therapy, including some known targets of antifungal agents used in clinical practice, but also new potential drug targets without any human homolog or drug association in Candida species.

Comorbid insomnia and sleep apnea in children: a preliminary explorative study.

Insomnia and sleep-disordered breathing (SDB) are prevalent sleep disorders. These disorders can therefore be concurrently present - comorbid insomnia and sleep apnea (COMISA). The prevalence of COMISA in the paediatric age range is unclear. As such, phenotypic constructs should help better define this comorbid condition if it exists in children and improve both diagnostic sensitivity and ultimately clinical care outcomes. We aimed to evaluate the frequency of insomnia in children and adolescents referred for evaluation of sleep symptoms suggestive of SDB in one initial (Cohort#1) and verify such findings in an independent cohort (Cohort#2) using a retrospective cross-sectional approach in patients aged 9-19 years presenting at a sleep centre to be evaluated for symptoms of SDB. Cohort #1 comprised 50 consecutive children (58% males; mean [SD] age 13.6 [3.3] years; median [interquartile range, IQR] Epworth Sleepiness Scale score 10 [6-12]) who were evaluated using validated SDB and insomnia questionnaires. Cohort#2 was extracted from electronic medical records and included 384 polysomnographically evaluated children (mean [SD] age 12.9 [3.6] years; mean [SD] body mass index z score 1.27 [0.28]; median Epworth Sleepiness Scale score 9.7 [4-17]). In Cohort #1, 56% were at high risk of SDB, 36% had insomnia alone, and 18% were at high risk of COMISA. The prevalence of COMISA in Cohort #2 was 16%, 72% had SDB alone, and 12% had insomnia alone. In both cohorts, COMISA manifested as increased propensity for sleepiness and fatigue during both waking and daytime. Thus, the presence of COMISA is frequent in the paediatric age range and accompanied by a more prominent symptomatic phenotype.

Clinical presentation and management strategies of cardiovascular autonomic dysfunction following a COVID-19 infection - A systematic review.

BACKGROUND: Cardiovascular autonomic dysfunction may reportedly occur after a coronavirus-disease-2019 (COVID-19) infection, but the available evidence is scattered. Here we sought to understand the acute and mid-term effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on cardiovascular autonomic function. METHODS: We performed a systematic PubMed, Embase, Web of Science, medRxiv, and bioRxiv search for cases of cardiovascular autonomic dysfunction during an acute SARS-CoV-2 infection or post-COVID-19 condition. The clinical-demographic characteristics of individuals in the acute versus post-COVID-19 phase were compared. RESULTS: We screened 6470 titles and abstracts. Fifty-four full-length articles were included in the data synthesis. One-hundred and thirty-four cases were identified: 81 during the acute SARS-CoV-2 infection (24 thereof diagnosed by history) and 53 in the post-COVID-19 phase. Post-COVID-19 cases were younger than those with cardiovascular autonomic disturbances in the acute SARS-CoV-2 phase (42 vs. 51 years old, p = 0.002) and were more frequently women (68% vs. 49%, p = 0.034). Reflex syncope was the most common cardiovascular autonomic disorder in the acute phase (p = 0.008) and postural orthostatic tachycardia syndrome (POTS) the most frequent diagnosis in individuals with post-COVID-19 orthostatic complaints (p < 0.001). Full recovery was more frequent in individuals with acute versus post-COVID-19 onset of cardiovascular autonomic disturbances (43% vs. 15%, p = 0.002). CONCLUSIONS: There is evidence from the scientific literature about different types of cardiovascular autonomic dysfunction developing during and after COVID-19. More data about the prevalence of autonomic disorders associated with a SARS-CoV-2 infection are needed to quantify its impact on human health.

Impact of the COVID-19 pandemic on clinical autonomic practice in Europe A survey of the European Academy of Neurology (EAN) and the European Federation of Autonomic Societies (EFAS).

OBJECTIVE: To investigate the impact of the coronavirus-disease-2019 (COVID-19) pandemic on European clinical autonomic practice. METHODS: Eighty-four neurology-driven or interdisciplinary autonomic centers in 22 European countries were invited to fill in a web-based survey between September and November 2021. RESULTS: Forty-six centers completed the survey (55%). During the first pandemic year, the number of performed tilt-table tests, autonomic outpatient and inpatient visits decreased respectively by 50%, 45% and 53%, and every-third center reported major adverse events due to postponed examinations or visits. The most frequent newly-diagnosed or worsened cardiovascular autonomic disorders after COVID-19 infection included postural orthostatic tachycardia syndrome (POTS), orthostatic hypotension, and recurrent vasovagal syncope, deemed likely related to the infection by ≥50% of the responders. Forty-seven percent of the responders also reported about people with new-onset of orthostatic intolerance, but negative tilt-table findings, and 16% about people with psychogenic pseudosyncope after COVID-19. Most patients were treated non-pharmacologically and symptomatic recovery at follow-up was observed in ≥45% of cases. By contrast, low frequencies of newly-diagnosed cardiovascular autonomic disorders following COVID-19 vaccination were reported, most frequently POTS and recurrent vasovagal syncope, and most of the responders judged a causal association unlikely. Non-pharmacological measures were the preferred treatment choice, with 50-100% recovery rates at follow-up. CONCLUSIONS: Cardiovascular autonomic disorders may develop or worsen following a COVID-19 infection, while the association with COVID-19 vaccines remains controversial. Despite the severe pandemic impact on European clinical autonomic practice, a specialized diagnostic work-up was pivotal to identify non-autonomic disorders in people with post-COVID-19 orthostatic complaints.

EFAS/EAN survey on the influence of the COVID-19 pandemic on European clinical autonomic education and research.

PURPOSE: To understand the influence of the coronavirus disease 2019 (COVID-19) pandemic on clinical autonomic education and research in Europe. METHODS: We invited 84 European autonomic centers to complete an online survey, recorded the pre-pandemic-to-pandemic percentage of junior participants in the annual congresses of the European Federation of Autonomic Societies (EFAS) and European Academy of Neurology (EAN) and the pre-pandemic-to-pandemic number of PubMed publications on neurological disorders. RESULTS: Forty-six centers answered the survey (55%). Twenty-nine centers were involved in clinical autonomic education and experienced pandemic-related didactic interruptions for 9 (5; 9) months. Ninety percent (n = 26/29) of autonomic educational centers reported a negative impact of the COVID-19 pandemic on education quality, and 93% (n = 27/29) established e-learning models. Both the 2020 joint EAN-EFAS virtual congress and the 2021 (virtual) and 2022 (hybrid) EFAS and EAN congresses marked higher percentages of junior participants than in 2019. Forty-one respondents (89%) were autonomic researchers, and 29 of them reported pandemic-related trial interruptions for 5 (2; 9) months. Since the pandemic begin, almost half of the respondents had less time for scientific writing. Likewise, the number of PubMed publications on autonomic topics showed the smallest increase compared with other neurological fields in 2020-2021 and the highest drop in 2022. Autonomic research centers that amended their trial protocols for telemedicine (38%, n = 16/41) maintained higher clinical caseloads during the first pandemic year. CONCLUSIONS: The COVID-19 pandemic had a substantial negative impact on European clinical autonomic education and research. At the same time, it promoted digitalization, favoring more equitable access to autonomic education and improved trial design.

Model-guided development of an evolutionarily stable yeast chassis.

First-principle metabolic modelling holds potential for designing microbial chassis that are resilient against phenotype reversal due to adaptive mutations. Yet, the theory of model-based chassis design has rarely been put to rigorous experimental test. Here, we report the development of Saccharomyces cerevisiae chassis strains for dicarboxylic acid production using genome-scale metabolic modelling. The chassis strains, albeit geared for higher flux towards succinate, fumarate and malate, do not appreciably secrete these metabolites. As predicted by the model, introducing product-specific TCA cycle disruptions resulted in the secretion of the corresponding acid. Adaptive laboratory evolution further improved production of succinate and fumarate, demonstrating the evolutionary robustness of the engineered cells. In the case of malate, multi-omics analysis revealed a flux bypass at peroxisomal malate dehydrogenase that was missing in the yeast metabolic model. In all three cases, flux balance analysis integrating transcriptomics, proteomics and metabolomics data confirmed the flux re-routing predicted by the model. Taken together, our modelling and experimental results have implications for the computer-aided design of microbial cell factories.

Inclusion of maintenance energy improves the intracellular flux predictions of CHO.

Chinese hamster ovary (CHO) cells are the leading platform for the production of biopharmaceuticals with human-like glycosylation. The standard practice for cell line generation relies on trial and error approaches such as adaptive evolution and high-throughput screening, which typically take several months. Metabolic modeling could aid in designing better producer cell lines and thus shorten development times. The genome-scale metabolic model (GSMM) of CHO can accurately predict growth rates. However, in order to predict rational engineering strategies it also needs to accurately predict intracellular fluxes. In this work we evaluated the agreement between the fluxes predicted by parsimonious flux balance analysis (pFBA) using the CHO GSMM and a wide range of 13C metabolic flux data from literature. While glycolytic fluxes were predicted relatively well, the fluxes of tricarboxylic acid (TCA) cycle were vastly underestimated due to too low energy demand. Inclusion of computationally estimated maintenance energy significantly improved the overall accuracy of intracellular flux predictions. Maintenance energy was therefore determined experimentally by running continuous cultures at different growth rates and evaluating their respective energy consumption. The experimentally and computationally determined maintenance energy were in good agreement. Additionally, we compared alternative objective functions (minimization of uptake rates of seven nonessential metabolites) to the biomass objective. While the predictions of the uptake rates were quite inaccurate for most objectives, the predictions of the intracellular fluxes were comparable to the biomass objective function.

Clinical autonomic nervous system laboratories in Europe: A joint survey of the European Academy of Neurology and the European Federation of Autonomic Societies: A joint survey of the European Academy of Neurology and the European Federation of Autonomic Societies.

BACKGROUND AND PURPOSE: Disorders of the autonomic nervous system (ANS) are common conditions, but it is unclear whether access to ANS healthcare provision is homogeneous across European countries. The aim of this study was to identify neurology-driven or interdisciplinary clinical ANS laboratories in Europe, describe their characteristics and explore regional differences. METHODS: We contacted the European national ANS and neurological societies, as well as members of our professional network, to identify clinical ANS laboratories in each country and invite them to answer a web-based survey. RESULTS: We identified 84 laboratories in 22 countries and 46 (55%) answered the survey. All laboratories perform cardiovascular autonomic function tests, and 83% also perform sweat tests. Testing for catecholamines and autoantibodies are performed in 63% and 56% of laboratories, and epidermal nerve fiber density analysis in 63%. Each laboratory is staffed by a median of two consultants, one resident, one technician and one nurse. The median (interquartile range [IQR]) number of head-up tilt tests/laboratory/year is 105 (49-251). Reflex syncope and neurogenic orthostatic hypotension are the most frequently diagnosed cardiovascular ANS disorders. Thirty-five centers (76%) have an ANS outpatient clinic, with a median (IQR) of 200 (100-360) outpatient visits/year; 42 centers (91%) also offer inpatient care (median 20 [IQR 4-110] inpatient stays/year). Forty-one laboratories (89%) are involved in research activities. We observed a significant difference in the geographical distribution of ANS services among European regions: 11 out of 12 countries from North/West Europe have at least one ANS laboratory versus 11 out of 21 from South/East/Greater Europe (p = 0.021). CONCLUSIONS: This survey highlights disparities in the availability of healthcare services for people with ANS disorders across European countries, stressing the need for improved access to specialized care in South, East and Greater Europe.

High Caloric Diet Induces Memory Impairment and Disrupts Synaptic Plasticity in Aged Rats.

The increasing consumption of sugar and fat seen over the last decades and the consequent overweight and obesity, were recently linked with a deleterious effect on cognition and synaptic function. A major question, which remains to be clarified, is whether obesity in the elderly is an additional risk factor for cognitive impairment. We aimed at unravelling the impact of a chronic high caloric diet (HCD) on memory performance and synaptic plasticity in aged rats. Male rats were kept on an HCD or a standard diet (control) from 1 to 24 months of age. The results showed that under an HCD, aged rats were obese and displayed significant long-term recognition memory impairment when compared to age-matched controls. Ex vivo synaptic plasticity recorded from hippocampal slices from HCD-fed aged rats revealed a reduction in the magnitude of long-term potentiation, accompanied by a decrease in the levels of the brain-derived neurotrophic factor receptors TrkB full-length (TrkB-FL). No alterations in neurogenesis were observed, as quantified by the density of immature doublecortin-positive neurons in the hippocampal dentate gyrus. This study highlights that obesity induced by a chronic HCD exacerbates age-associated cognitive decline, likely due to impaired synaptic plasticity, which might be associated with deficits in TrkB-FL signaling.

A review of methods for the reconstruction and analysis of integrated genome-scale models of metabolism and regulation.

The current survey aims to describe the main methodologies for extending the reconstruction and analysis of genome-scale metabolic models and phenotype simulation with Flux Balance Analysis mathematical frameworks, via the integration of Transcriptional Regulatory Networks and/or gene expression data. Although the surveyed methods are aimed at improving phenotype simulations obtained from these models, the perspective of reconstructing integrated genome-scale models of metabolism and gene expression for diverse prokaryotes is still an open challenge.

Identification and Microbial Production of the Raspberry Phenol Salidroside that Is Active against Huntington's Disease.

Edible berries are considered to be among nature's treasure chests as they contain a large number of (poly)phenols with potentially health-promoting properties. However, as berries contain complex (poly)phenol mixtures, it is challenging to associate any interesting pharmacological activity with a single compound. Thus, identification of pharmacologically interesting phenols requires systematic analyses of berry extracts. Here, raspberry (Rubus idaeus, var Prestige) extracts were systematically analyzed to identify bioactive compounds against pathological processes of neurodegenerative diseases. Berry extracts were tested on different Saccharomyces cerevisiae strains expressing disease proteins associated with Alzheimer's, Parkinson's, or Huntington's disease, or amyotrophic lateral sclerosis. After identifying bioactivity against Huntington's disease, the extract was fractionated and the obtained fractions were tested in the yeast model, which revealed that salidroside, a glycosylated phenol, displayed significant bioactivity. Subsequently, a metabolic route to salidroside was reconstructed in S cerevisiae and Corynebacterium glutamicum The best-performing S cerevisiae strain was capable of producing 2.1 mm (640 mg L-1) salidroside from Glc in shake flasks, whereas an engineered C glutamicum strain could efficiently convert the precursor tyrosol to salidroside, accumulating up to 32 mm (9,700 mg L-1) salidroside in bioreactor cultivations (yield: 0.81 mol mol-1). Targeted yeast assays verified that salidroside produced by both organisms has the same positive effects as salidroside of natural origin.

Metabolic engineering strategies for butanol production in Escherichia coli.

The global market of butanol is increasing due to its growing applications as solvent, flavoring agent, and chemical precursor of several other compounds. Recently, the superior properties of n-butanol as a biofuel over ethanol have stimulated even more interest. (Bio)butanol is natively produced together with ethanol and acetone by Clostridium species through acetone-butanol-ethanol fermentation, at noncompetitive, low titers compared to petrochemical production. Different butanol production pathways have been expressed in Escherichia coli, a more accessible host compared to Clostridium species, to improve butanol titers and rates. The bioproduction of butanol is here reviewed from a historical and theoretical perspective. All tested rational metabolic engineering strategies in E. coli to increase butanol titers are reviewed: manipulation of central carbon metabolism, elimination of competing pathways, cofactor balancing, development of new pathways, expression of homologous enzymes, consumption of different substrates, and molecular biology strategies. The progress in the field of metabolic modeling and pathway generation algorithms and their potential application to butanol production are also summarized here. The main goals are to gather all the strategies, evaluate the respective progress obtained, identify, and exploit the outstanding challenges.

A protocol for a multicentre, parallel-group, pragmatic randomised controlled trial to evaluate the NEVERMIND system in preventing and treating depression in patients with severe somatic conditions.

BACKGROUND: Depressive symptoms are common in individuals suffering from severe somatic conditions. There is a lack of interventions and evidence-based interventions aiming to reduce depressive symptoms in patients with severe somatic conditions. The aim of the NEVERMIND project is to address these issues and provide evidence by testing the NEVERMIND system, designed to reduce and prevent depressive symptoms in comparison to treatment as usual. METHODS: The NEVERMIND study is a parallel-groups, pragmatic randomised controlled trial to assess the effectiveness of the NEVERMIND system in reducing depressive symptoms among individuals with severe somatic conditions. The NEVERMIND system comprises a smart shirt and a user interface, in the form of a mobile application. The system is a real-time decision support system, aiming to predict the severity and onset of depressive symptoms by modelling the well-being condition of patients based on physiological data, body movement, and the recurrence of social interactions. The study includes 330 patients who have a diagnosis of myocardial infarction, breast cancer, prostate cancer, kidney failure, or lower limb amputation. Participants are randomised in blocks of ten to either the NEVERMIND intervention or treatment as usual as the control group. Clinical interviews and structured questionnaires are administered at baseline, at 12 weeks, and 24 weeks to assess whether the NEVERMIND system is superior to treatment as usual. The endpoint of primary interest is Beck Depression Inventory II (BDI-II) at 12 weeks defined as (i) the severity of depressive symptoms as measured by the BDI-II. Secondary outcomes include prevention of the onset of depressive symptoms, changes in quality of life, perceived stigma, and self-efficacy. DISCUSSION: There is a lack of evidence-based interventions aiming to reduce and prevent depressive symptoms in patients with severe somatic conditions. If the NEVERMIND system is effective, it will provide healthcare systems with a novel and innovative method to attend to depressive symptoms in patients with severe somatic conditions. TRIAL REGISTRATION: DRKS00013391. Registered 23 November 2017.

Heart failure patients have enhanced cerebral autoregulation response in acute ischemic stroke.

The cerebrovascular effects of a failing heart-pump are largely unknown. Chronic heart failure (HF) might cause pre-conditioning effect on cerebral hemodynamics but not study so far in acute stroke. We aimed to investigate if HF induces effects in dynamic cerebral autoregulation (CA), within 6 h of symptom-onset through chronic stage of ischemic stroke. We enrolled 50 patients with acute ischemic stroke. Groups with (N = 8) and without HF and 20 heathy controls were compared. Arterial blood pressure (Finometer) and cerebral blood flow velocity (transcranial Doppler) were monitored within 6 and at 24 h from symptom-onset and at 3 months. We assessed dynamic CA by transfer function analysis and cardiac disease markers. HF associated with higher phase (better dynamic CA) at ischemic hemisphere within 6 (p = 0.042) and at 24 h (p = 0.006) but this effect was not evident at 3 months (p > 0.05). Gain and coherence trends were similar between groups. We found a positive correlation between phase and admission troponin I levels (Spearman's r = 0.348, p = 0.044). Our findings advances on the knowledge of how brain and heart interact in acute ischemic stroke by showing a sustained dynamic cerebral autoregulation response in HF patients mainly with severe aortic valve disease. Understanding the physiological mechanisms that govern this complex interplay can be useful to find novel therapeutic targets which can improve outcome in ischemic stroke.

Comparison of pathway analysis and constraint-based methods for cell factory design.

BACKGROUND: Computational strain optimisation methods (CSOMs) have been successfully used to exploit genome-scale metabolic models, yielding strategies useful for allowing compound overproduction in metabolic cell factories. Minimal cut sets are particularly interesting since their definition allows searching for intervention strategies that impose strong growth-coupling phenotypes, and are not subject to optimality bias when compared with simulation-based CSOMs. However, since both types of methods have different underlying principles, they also imply different ways to formulate metabolic engineering problems, posing an obstacle when comparing their outputs. RESULTS: In this work, we perform an in-depth analysis of potential strategies that can be obtained with both methods, providing a critical comparison of performance, robustness, predicted phenotypes as well as strategy structure and size. To this end, we devised a pipeline including enumeration of strategies from evolutionary algorithms (EA) and minimal cut sets (MCS), filtering and flux analysis of predicted mutants to optimize the production of succinic acid in Saccharomyces cerevisiae. We additionally attempt to generalize problem formulations for MCS enumeration within the context of growth-coupled product synthesis. Strategies from evolutionary algorithms show the best compromise between acceptable growth rates and compound overproduction. However, constrained MCSs lead to a larger variety of phenotypes with several degrees of growth-coupling with production flux. The latter have proven useful in revealing the importance, in silico, of the gamma-aminobutyric acid shunt and manipulation of cofactor pools in growth-coupled designs for succinate production, mechanisms which have also been touted as potentially useful for metabolic engineering. CONCLUSIONS: The two main groups of CSOMs are valuable for finding growth-coupled mutants. Despite the limitations in maximum growth rates and large strategy sizes, MCSs help uncover novel mechanisms for compound overproduction and thus, analyzing outputs from both methods provides a richer overview on strategies that can be potentially carried over in vivo.

SamPler - a novel method for selecting parameters for gene functional annotation routines.

BACKGROUND: As genome sequencing projects grow rapidly, the diversity of organisms with recently assembled genome sequences peaks at an unprecedented scale, thereby highlighting the need to make gene functional annotations fast and efficient. However, the (high) quality of such annotations must be guaranteed, as this is the first indicator of the genomic potential of every organism. Automatic procedures help accelerating the annotation process, though decreasing the confidence and reliability of the outcomes. Manually curating a genome-wide annotation of genes, enzymes and transporter proteins function is a highly time-consuming, tedious and impractical task, even for the most proficient curator. Hence, a semi-automated procedure, which balances the two approaches, will increase the reliability of the annotation, while speeding up the process. In fact, a prior analysis of the annotation algorithm may leverage its performance, by manipulating its parameters, hastening the downstream processing and the manual curation of assigning functions to genes encoding proteins. RESULTS: Here SamPler, a novel strategy to select parameters for gene functional annotation routines is presented. This semi-automated method is based on the manual curation of a randomly selected set of genes/proteins. Then, in a multi-dimensional array, this sample is used to assess the automatic annotations for all possible combinations of the algorithm's parameters. These assessments allow creating an array of confusion matrices, for which several metrics are calculated (accuracy, precision and negative predictive value) and used to reach optimal values for the parameters. CONCLUSIONS: The potential of this methodology is demonstrated with four genome functional annotations performed in merlin, an in-house user-friendly computational framework for genome-scale metabolic annotation and model reconstruction. For that, SamPler was implemented as a new plugin for the merlin tool.

Genome-wide sequencing and metabolic annotation of Pythium irregulare CBS 494.86: understanding Eicosapentaenoic acid production.

BACKGROUND: Pythium irregulare is an oleaginous Oomycete able to accumulate large amounts of lipids, including Eicosapentaenoic acid (EPA). EPA is an important and expensive dietary supplement with a promising and very competitive market, which is dependent on fish-oil extraction. This has prompted several research groups to study biotechnological routes to obtain specific fatty acids rather than a mixture of various lipids. Moreover, microorganisms can use low cost carbon sources for lipid production, thus reducing production costs. Previous studies have highlighted the production of EPA by P. irregulare, exploiting diverse low cost carbon sources that are produced in large amounts, such as vinasse, glycerol, and food wastewater. However, there is still a lack of knowledge about its biosynthetic pathways, because no functional annotation of any Pythium sp. exists yet. The goal of this work was to identify key genes and pathways related to EPA biosynthesis, in P. irregulare CBS 494.86, by sequencing and performing an unprecedented annotation of its genome, considering the possibility of using wastewater as a carbon source. RESULTS: Genome sequencing provided 17,727 candidate genes, with 3809 of them associated with enzyme code and 945 with membrane transporter proteins. The functional annotation was compared with curated information of oleaginous organisms, understanding amino acids and fatty acids production, and consumption of carbon and nitrogen sources, present in the wastewater. The main features include the presence of genes related to the consumption of several sugars and candidate genes of unsaturated fatty acids production. CONCLUSIONS: The whole metabolic genome presented, which is an unprecedented reconstruction of P. irregulare CBS 494.86, shows its potential to produce value-added products, in special EPA, for food and pharmaceutical industries, moreover it infers metabolic capabilities of the microorganism by incorporating information obtained from literature and genomic data, supplying information of great importance to future work.

Mapping Salmonella typhimurium pathways using 13C metabolic flux analysis.

In the last years, Salmonella has been extensively studied not only due to its importance as a pathogen, but also as a host to produce pharmaceutical compounds. However, the full exploitation of Salmonella as a platform for bioproduct delivery has been hampered by the lack of information about its metabolism. Genome-scale metabolic models can be valuable tools to delineate metabolic engineering strategies as long as they closely represent the actual metabolism of the target organism. In the present study, a 13C-MFA approach was applied to map the fluxes at the central carbon pathways of S. typhimurium LT2 growing at glucose-limited chemostat cultures. The experiments were carried out in a 2L bioreactor, using defined medium enriched with 20% 13C-labeled glucose. Metabolic flux distributions in central carbon pathways of S. typhimurium LT2 were estimated using OpenFLUX2 based on the labeling pattern of biomass protein hydrolysates together with biomass composition. The results suggested that pentose phosphate is used to catabolize glucose, with minor fluxes through glycolysis. In silico simulations, using Optflux and pFBA as simulation method, allowed to study the performance of the genome-scale metabolic model. In general, the accuracy of in silico simulations was improved by the superimposition of estimated intracellular fluxes to the existing genome-scale metabolic model, showing a better fitting to the experimental extracellular fluxes, whereas the intracellular fluxes of pentose phosphate and anaplerotic reactions were poorly described.