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Largus T Angenent - One of the best experts on this subject based on the ideXlab platform.
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the isolate caproiciproducens sp 7d4c2 produces n caproate at mildly acidic conditions from hexoses genome and rbox comparison with related strains and Chain elongating bacteria
Frontiers in Microbiology, 2021Co-Authors: Sofia Esquivelelizondo, Caner Bagci, Monika Temovska, Byoung Seung Jeon, Irina Bessarab, Rohan B H Williams, Daniel H Huson, Largus T AngenentAbstract:Bulk production of medium-Chain carboxylates (MCCs) with 6-12 carbon atoms is of great interest to biotechnology. Open cultures (e.g., reactor microbiomes) have been utilized to generate MCCs in bioreactors. When in-line MCC extraction and prevention of product inhibition is required, the bioreactors have been operated at mildly acidic pH (5.0-5.5). However, Model Chain-elongating bacteria grow optimally at neutral pH values. Here, we isolated a Chain-elongating bacterium (strain 7D4C2) that grows at mildly acidic pH. We studied its metabolism and compared its whole genome and the reverse β-oxidation (rBOX) genes to other bacteria. Strain 7D4C2 produces lactate, acetate, n-butyrate, n-caproate, biomass, and H2/CO2 from hexoses. With only fructose as substrate (pH 5.5), the maximum n-caproate specificity (i.e., products per other carboxylates produced) was 60.9 ± 1.5%. However, this was considerably higher at 83.1 ± 0.44% when both fructose and n-butyrate (electron acceptor) were combined as a substrate. A comparison of 7D4C2 cultures with fructose and n-butyrate with an increasing pH value from 4.5 to 9.0 showed a decreasing n-caproate specificity from ∼92% at mildly acidic pH (pH 4.5-5.0) to ∼24% at alkaline pH (pH 9.0). Moreover, when carboxylates were extracted from the broth (undissociated n-caproic acid was ∼0.3 mM), the n-caproate selectivity (i.e., product per substrate fed) was 42.6 ± 19.0% higher compared to 7D4C2 cultures without extraction. Based on the 16S rRNA gene sequence, strain 7D4C2 is most closely related to the isolates Caproicibacter fermentans (99.5%) and Caproiciproducens galactitolivorans (94.7%), which are Chain-elongating bacteria that are also capable of lactate production. Whole-genome analyses indicate that strain 7D4C2, C. fermentans, and C. galactitolivorans belong to the same genus of Caproiciproducens. Their rBOX genes are conserved and located next to each other, forming a gene cluster, which is different than for other Chain-elongating bacteria such as Megasphaera spp. In conclusion, Caproiciproducens spp., comprising strain 7D4C2, C. fermentans, C. galactitolivorans, and several unclassified strains, are Chain-elongating bacteria that encode a highly conserved rBOX gene cluster. Caproiciproducens sp. 7D4C2 (DSM 110548) was studied here to understand n-caproate production better at mildly acidic pH within microbiomes and has the additional potential as a pure-culture production strain to convert sugars into n-caproate.
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the isolate caproiciproducens sp 7d4c2 produces n caproate at mildly acidic conditions from hexoses genome and rbox comparison with related strains and Chain elongating bacteria
bioRxiv, 2020Co-Authors: Sofia Esquivelelizondo, Caner Bagci, Monika Temovska, Byoung Seung Jeon, Irina Bessarab, Rohan B H Williams, Daniel H Huson, Largus T AngenentAbstract:Abstract Background Bulk production of medium-Chain carboxylates (MCCs) with 6-12 carbon atoms is of great interest to biotechnology. Open cultures (e.g., reactor microbiomes) have been utilized to generate MCCs in bioreactors. When in-line MCC extraction and prevention of product inhibition is required, the bioreactors have been operated at mildly acidic pH (5.0-5.5). However, Model Chain-elongating bacteria grow optimally at neutral pH values. Here, we isolated a Chain-elongating bacterium (strain 7D4C2) that thrives at mildly acidic pH. We studied its metabolism and compared its whole genome and the reverse β-oxidation (rBOX) genes to other bacteria. Results Strain 7D4C2 produces lactate, acetate, n-butyrate, n-caproate, biomass, and H2/CO2 from hexoses. With only fructose as substrate (pH 5.5), the maximum n-caproate specificity (i.e., products per other carboxylates produced) was 60.9 ± 1.5%. However, this was considerably higher at 83.1 ± 0.44% when both fructose and n-butyrate (electron acceptor) were combined as a substrate. A comparison of serum bottles with fructose and n-butyrate with an increasing pH value from 4.5 to 9.0 showed a decreasing n-caproate specificity from ∼92% at mildly acidic pH (pH 4.5-5.0) to ∼24% at alkaline pH (pH 9.0). Moreover, when carboxylates were extracted from the broth (undissociated n-caproic acid was ∼0.3 mM), the n-caproate selectivity (i.e., product per substrate fed) was 42.6 ± 19.0% higher compared to serum bottles without extraction. Based on the 16S rRNA gene sequence, strain 7D4C2 is most closely related to the isolates Caproicibacter fermentans (99.5%) and Caproiciproducens galactitolivorans (94.7%), which are Chain-elongating bacteria that are also capable of lactate production. Whole-genome analyses indicate that strain 7D4C2, C. fermentans, and C. galactitolivorans belong to the same genus of Caproiciproducens. Their rBOX genes are conserved and located next to each other, forming a gene cluster, which is different than for other Chain-elongating bacteria such as Megasphaera spp. Conclusions Caproiciproducens spp., comprising strain 7D4C2, C. fermentans, C. galactitolivorans, and several unclassified strains, are Chain-elongating bacteria that encode a highly conserved rBOX gene cluster. Caproiciproducens sp. 7D4C2 (DSM 110548) was studied here to understand n-caproate production better at mildly acidic pH within microbiomes and has the additional potential as a pure-culture production strain to convert sugars into n-caproate.
Geert Wets - One of the best experts on this subject based on the ideXlab platform.
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disaggregation of nation wide dynamic population exposure estimates in the netherlands applications of activity based transport Models
Atmospheric Environment, 2009Co-Authors: Carolien Beckx, Luc Int Panis, T Theo A Arentze, Davy Janssens, Inge Uljee, Geert WetsAbstract:Traditional exposure studies that link concentrations with population data do not always take into account the temporal and spatial variations in both concentrations and population density. In this paper we present an integrated Model Chain for the determination of nation-wide exposure estimates that incorporates temporally and spatially resolved information about people's location and activities (obtained from an activity-based transport Model) and about ambient pollutant concentrations (obtained from a dispersion Model). To the best of our knowledge, it is the first time that such an integrated exercise was successfully carried out in a fully operational modus for all Models under consideration. The evaluation of population level exposure in The Netherlands to NO2 at different time-periods, locations, for different subpopulations (gender, socio-economic status) and during different activities (residential, work, transport, shopping) is chosen as a case-study to point out the new features of this methodology. Results demonstrate that, by neglecting people's travel behaviour, total average exposure to NO2 will be underestimated by 4% and hourly exposure results can be underestimated by more than 30%. A more detailed exposure analysis reveals the intra-day variations in exposure estimates and the presence of large exposure differences between different activities (traffic > work > shopping > home) and between subpopulations (men > women, low socio-economic class > high socio-economic class). This kind of exposure analysis, disaggregated by activities or by subpopulations, per time of day, provides useful insight and information for scientific and policy purposes. It demonstrates that policy measures, aimed at reducing the overall (average) exposure concentration of the population may impact in a different way depending on the time of day or the subgroup considered. From a scientific point of view, this new approach can be used to reduce exposure misclassification.
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the contribution of activity based transport Models to air quality Modelling a validation of the albatross aurora Model Chain
Science of The Total Environment, 2009Co-Authors: Carolien Beckx, Wouter Lefebvre, Luc Int Panis, Karen Van De Vel, T Theo A Arentze, Davy Janssens, Geert WetsAbstract:The potential advantages of using activity-based transport Models for air quality purposes have been recognized for a long time but Models that have been developed along these lines are still scarce. In this paper we demonstrate that an activity-based Model provides useful information for predicting hourly ambient pollutant concentrations. For this purpose, the traffic emissions obtained in a previous application of the activity-based Model ALBATROSS were used as input for the AURORA air quality Model to predict hourly concentrations of NO2, PM10 and O3 in the Netherlands. Predicted concentrations were compared with measured concentrations at 37 monitoring stations from the Dutch air quality monitoring network. A statistical analysis was performed to evaluate Model performance for different pollutants, locations and time periods. Results confirm that Modelled and measured concentrations present the same geographical and temporal variation. The overall index of agreement for the prediction of hourly pollutant concentrations amounted to 0.64, 0.75 and 0.57 for NO2, O3 and PM10 respectively. Concerning the predictions for NO2, a major traffic pollutant, a more thorough analysis revealed that the ALBATROSS–AURORA Model Chain yielded better predictions near traffic locations than near background stations. Further, the Model performed better in urban areas, on weekdays and during the day, consistent with the emission results obtained in a previous study. The results in this paper demonstrate the ability of the activity-based Model to predict the contribution of traffic sources to local air pollution with sufficient accuracy and confirms the usefulness of activity-based transport Models for air quality purposes. The fact that the ALBATROSS–AURORA Chain provides reliable pollutant concentrations on hourly basis for the whole Netherlands instead of using only daily averages near traffic stations is a plus for future exposure studies aiming at more realistic exposure analyses and health impact assessments.
Daniel H Huson - One of the best experts on this subject based on the ideXlab platform.
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the isolate caproiciproducens sp 7d4c2 produces n caproate at mildly acidic conditions from hexoses genome and rbox comparison with related strains and Chain elongating bacteria
Frontiers in Microbiology, 2021Co-Authors: Sofia Esquivelelizondo, Caner Bagci, Monika Temovska, Byoung Seung Jeon, Irina Bessarab, Rohan B H Williams, Daniel H Huson, Largus T AngenentAbstract:Bulk production of medium-Chain carboxylates (MCCs) with 6-12 carbon atoms is of great interest to biotechnology. Open cultures (e.g., reactor microbiomes) have been utilized to generate MCCs in bioreactors. When in-line MCC extraction and prevention of product inhibition is required, the bioreactors have been operated at mildly acidic pH (5.0-5.5). However, Model Chain-elongating bacteria grow optimally at neutral pH values. Here, we isolated a Chain-elongating bacterium (strain 7D4C2) that grows at mildly acidic pH. We studied its metabolism and compared its whole genome and the reverse β-oxidation (rBOX) genes to other bacteria. Strain 7D4C2 produces lactate, acetate, n-butyrate, n-caproate, biomass, and H2/CO2 from hexoses. With only fructose as substrate (pH 5.5), the maximum n-caproate specificity (i.e., products per other carboxylates produced) was 60.9 ± 1.5%. However, this was considerably higher at 83.1 ± 0.44% when both fructose and n-butyrate (electron acceptor) were combined as a substrate. A comparison of 7D4C2 cultures with fructose and n-butyrate with an increasing pH value from 4.5 to 9.0 showed a decreasing n-caproate specificity from ∼92% at mildly acidic pH (pH 4.5-5.0) to ∼24% at alkaline pH (pH 9.0). Moreover, when carboxylates were extracted from the broth (undissociated n-caproic acid was ∼0.3 mM), the n-caproate selectivity (i.e., product per substrate fed) was 42.6 ± 19.0% higher compared to 7D4C2 cultures without extraction. Based on the 16S rRNA gene sequence, strain 7D4C2 is most closely related to the isolates Caproicibacter fermentans (99.5%) and Caproiciproducens galactitolivorans (94.7%), which are Chain-elongating bacteria that are also capable of lactate production. Whole-genome analyses indicate that strain 7D4C2, C. fermentans, and C. galactitolivorans belong to the same genus of Caproiciproducens. Their rBOX genes are conserved and located next to each other, forming a gene cluster, which is different than for other Chain-elongating bacteria such as Megasphaera spp. In conclusion, Caproiciproducens spp., comprising strain 7D4C2, C. fermentans, C. galactitolivorans, and several unclassified strains, are Chain-elongating bacteria that encode a highly conserved rBOX gene cluster. Caproiciproducens sp. 7D4C2 (DSM 110548) was studied here to understand n-caproate production better at mildly acidic pH within microbiomes and has the additional potential as a pure-culture production strain to convert sugars into n-caproate.
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the isolate caproiciproducens sp 7d4c2 produces n caproate at mildly acidic conditions from hexoses genome and rbox comparison with related strains and Chain elongating bacteria
bioRxiv, 2020Co-Authors: Sofia Esquivelelizondo, Caner Bagci, Monika Temovska, Byoung Seung Jeon, Irina Bessarab, Rohan B H Williams, Daniel H Huson, Largus T AngenentAbstract:Abstract Background Bulk production of medium-Chain carboxylates (MCCs) with 6-12 carbon atoms is of great interest to biotechnology. Open cultures (e.g., reactor microbiomes) have been utilized to generate MCCs in bioreactors. When in-line MCC extraction and prevention of product inhibition is required, the bioreactors have been operated at mildly acidic pH (5.0-5.5). However, Model Chain-elongating bacteria grow optimally at neutral pH values. Here, we isolated a Chain-elongating bacterium (strain 7D4C2) that thrives at mildly acidic pH. We studied its metabolism and compared its whole genome and the reverse β-oxidation (rBOX) genes to other bacteria. Results Strain 7D4C2 produces lactate, acetate, n-butyrate, n-caproate, biomass, and H2/CO2 from hexoses. With only fructose as substrate (pH 5.5), the maximum n-caproate specificity (i.e., products per other carboxylates produced) was 60.9 ± 1.5%. However, this was considerably higher at 83.1 ± 0.44% when both fructose and n-butyrate (electron acceptor) were combined as a substrate. A comparison of serum bottles with fructose and n-butyrate with an increasing pH value from 4.5 to 9.0 showed a decreasing n-caproate specificity from ∼92% at mildly acidic pH (pH 4.5-5.0) to ∼24% at alkaline pH (pH 9.0). Moreover, when carboxylates were extracted from the broth (undissociated n-caproic acid was ∼0.3 mM), the n-caproate selectivity (i.e., product per substrate fed) was 42.6 ± 19.0% higher compared to serum bottles without extraction. Based on the 16S rRNA gene sequence, strain 7D4C2 is most closely related to the isolates Caproicibacter fermentans (99.5%) and Caproiciproducens galactitolivorans (94.7%), which are Chain-elongating bacteria that are also capable of lactate production. Whole-genome analyses indicate that strain 7D4C2, C. fermentans, and C. galactitolivorans belong to the same genus of Caproiciproducens. Their rBOX genes are conserved and located next to each other, forming a gene cluster, which is different than for other Chain-elongating bacteria such as Megasphaera spp. Conclusions Caproiciproducens spp., comprising strain 7D4C2, C. fermentans, C. galactitolivorans, and several unclassified strains, are Chain-elongating bacteria that encode a highly conserved rBOX gene cluster. Caproiciproducens sp. 7D4C2 (DSM 110548) was studied here to understand n-caproate production better at mildly acidic pH within microbiomes and has the additional potential as a pure-culture production strain to convert sugars into n-caproate.
Luc Int Panis - One of the best experts on this subject based on the ideXlab platform.
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disaggregation of nation wide dynamic population exposure estimates in the netherlands applications of activity based transport Models
Atmospheric Environment, 2009Co-Authors: Carolien Beckx, Luc Int Panis, T Theo A Arentze, Davy Janssens, Inge Uljee, Geert WetsAbstract:Traditional exposure studies that link concentrations with population data do not always take into account the temporal and spatial variations in both concentrations and population density. In this paper we present an integrated Model Chain for the determination of nation-wide exposure estimates that incorporates temporally and spatially resolved information about people's location and activities (obtained from an activity-based transport Model) and about ambient pollutant concentrations (obtained from a dispersion Model). To the best of our knowledge, it is the first time that such an integrated exercise was successfully carried out in a fully operational modus for all Models under consideration. The evaluation of population level exposure in The Netherlands to NO2 at different time-periods, locations, for different subpopulations (gender, socio-economic status) and during different activities (residential, work, transport, shopping) is chosen as a case-study to point out the new features of this methodology. Results demonstrate that, by neglecting people's travel behaviour, total average exposure to NO2 will be underestimated by 4% and hourly exposure results can be underestimated by more than 30%. A more detailed exposure analysis reveals the intra-day variations in exposure estimates and the presence of large exposure differences between different activities (traffic > work > shopping > home) and between subpopulations (men > women, low socio-economic class > high socio-economic class). This kind of exposure analysis, disaggregated by activities or by subpopulations, per time of day, provides useful insight and information for scientific and policy purposes. It demonstrates that policy measures, aimed at reducing the overall (average) exposure concentration of the population may impact in a different way depending on the time of day or the subgroup considered. From a scientific point of view, this new approach can be used to reduce exposure misclassification.
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the contribution of activity based transport Models to air quality Modelling a validation of the albatross aurora Model Chain
Science of The Total Environment, 2009Co-Authors: Carolien Beckx, Wouter Lefebvre, Luc Int Panis, Karen Van De Vel, T Theo A Arentze, Davy Janssens, Geert WetsAbstract:The potential advantages of using activity-based transport Models for air quality purposes have been recognized for a long time but Models that have been developed along these lines are still scarce. In this paper we demonstrate that an activity-based Model provides useful information for predicting hourly ambient pollutant concentrations. For this purpose, the traffic emissions obtained in a previous application of the activity-based Model ALBATROSS were used as input for the AURORA air quality Model to predict hourly concentrations of NO2, PM10 and O3 in the Netherlands. Predicted concentrations were compared with measured concentrations at 37 monitoring stations from the Dutch air quality monitoring network. A statistical analysis was performed to evaluate Model performance for different pollutants, locations and time periods. Results confirm that Modelled and measured concentrations present the same geographical and temporal variation. The overall index of agreement for the prediction of hourly pollutant concentrations amounted to 0.64, 0.75 and 0.57 for NO2, O3 and PM10 respectively. Concerning the predictions for NO2, a major traffic pollutant, a more thorough analysis revealed that the ALBATROSS–AURORA Model Chain yielded better predictions near traffic locations than near background stations. Further, the Model performed better in urban areas, on weekdays and during the day, consistent with the emission results obtained in a previous study. The results in this paper demonstrate the ability of the activity-based Model to predict the contribution of traffic sources to local air pollution with sufficient accuracy and confirms the usefulness of activity-based transport Models for air quality purposes. The fact that the ALBATROSS–AURORA Chain provides reliable pollutant concentrations on hourly basis for the whole Netherlands instead of using only daily averages near traffic stations is a plus for future exposure studies aiming at more realistic exposure analyses and health impact assessments.
Julia Gottschall - One of the best experts on this subject based on the ideXlab platform.
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complex terrain experiments in the new european wind atlas
Philosophical Transactions of the Royal Society A, 2017Co-Authors: Jakob Mann, Nikolas Angelou, Johan Arnqvist, Doron Callies, Elena Cantero, Chavez R Arroyo, Michael Courtney, Joan Cuxart, Ebba Dellwik, Julia GottschallAbstract:The New European Wind Atlas project will create a freely accessible wind atlas covering Europe and Turkey, develop the Model Chain to create the atlas and perform a series of experiments on flow in...