scholarly journals Designing Metabolic Division of Labor in Microbial Communities

mSystems ◽  
2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Meghan Thommes ◽  
Taiyao Wang ◽  
Qi Zhao ◽  
Ioannis C. Paschalidis ◽  
Daniel Segrè
Keyword(s):  
Microbial Communities ◽  
Division Of Labor ◽  
Environmental Sustainability ◽  
Computational Models ◽  
Thought Experiment ◽  
Mixed Integer ◽  
Individual Species ◽  
Large Space ◽  
Individual Organism ◽  
Trade Off

ABSTRACTMicrobes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment usingin silicogenome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities ofEscherichia colistrains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor.IMPORTANCEUnderstanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

scholarly journals Designing metabolic division of labor in microbial communities

2018 ◽  
Author(s):  
Meghan Thommes ◽  
Taiyao Wang ◽  
Qi Zhao ◽  
Ioannis Ch. Paschalidis ◽  
Daniel Segrè
Keyword(s):  
Division Of Labor ◽  
Tca Cycle ◽  
Mixed Integer ◽  
Large Space ◽  
Individual Organism ◽  
The Tca Cycle ◽  
Gedanken Experiment ◽  
Microbiome Research ◽  
Complex Landscape ◽  
Genome Scale

AbstractMicrobes face a tradeoff between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken experiment” to investigate this tradeoff would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation, and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed integer linear programming to identify tradeoff solutions in communities of Escherichia coli strains. The strategies we found reveal a large space of nuanced and nonintuitive metabolic division of labor opportunities, including, for example, splitting the TCA cycle into two separate halves. The systematic computation of possible division of labor solutions for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displays a nonlinear boundary, indicating that the loss of an intracellular reaction is not necessarily compensated by a single imported metabolite. Different regions in this landscape are associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable, but outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor.

scholarly journals A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference

2021 ◽  
Vol 18 (9) ◽  
pp. 4760
Author(s):  
Peng Li ◽  
Di Wu
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Environmental Sustainability ◽  
Rapid Development ◽  
Consumer Preference ◽  
Service Level ◽  
Mixed Integer ◽  
Reverse Supply Chain ◽  
Related Factors ◽  
Dual Channel

The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.

Environmentally sustainable stochastic procurement model

2018 ◽  
Vol 29 (3) ◽  
pp. 472-498 ◽  
Author(s):  
Harpreet Kaur ◽  
Surya Prakash Singh
Keyword(s):  
Carbon Emissions ◽  
Environmental Sustainability ◽  
Lot Sizing ◽  
Planning Horizon ◽  
Business Environment ◽  
Manufacturing Firms ◽  
Mixed Integer ◽  
Content Type ◽  
Environmentally Sustainable ◽  
Procurement Planning

Purpose Procurement planning has always been a huge and challenging activity for business firms, especially in manufacturing. With government legislations about global concern over carbon emissions, the manufacturing firms are enforced to regulate and reduce the emissions caused throughout the supply chain. It is observed that procurement and logistics activities in manufacturing firms contribute heavily toward carbon emissions. Moreover, highly dynamic and uncertain business environment with uncertainty in parameters such as demand, supplier and carrier capacity adds to the complexity in procurement planning. The paper aims to discuss these issues. Design/methodology/approach This paper is a novel attempt to model environmentally sustainable stochastic procurement (ESSP) problem as a mixed-integer non-linear program. The ESSP optimizes the procurement plan of the firm including lot-sizing, supplier and carrier selection by addressing uncertainty and environmental sustainability. The model applies chance-constrained-based approach to address the uncertain parameters. Findings The proposed ESSP model is solved optimally for 30 data sets to validate the proposed ESSP and is further demonstrated using three illustrations solved optimally in LINGO 10. Originality/value The ESSP model simultaneously minimizes total procurement cost and carbon emissions over the entire planning horizon considering uncertain demand, supplier and carrier capacity.

scholarly journals A metaproteomics method to determine carbon sources and assimilation pathways of species in microbial communities

2018 ◽  
Author(s):  
Manuel Kleiner ◽  
Xiaoli Dong ◽  
Tjorven Hinzke ◽  
Juliane Wippler ◽  
Erin Thorson ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Carbon Isotope ◽  
Isotope Ratio ◽  
Single Cells ◽  
Stable Carbon Isotope ◽  
Carbon Sources ◽  
Food Sources ◽  
Individual Species ◽  
Stable Carbon

AbstractMeasurements of the carbon stable isotope ratio (δ13C) are widely used in biology to address major questions regarding food sources and metabolic pathways used by organisms. Measurement of these so called stable carbon isotope fingerprints (SIFs) for microbes involved in biogeochemical cycling and microbiota of plants and animals have led to major discoveries in environmental microbiology. Currently, obtaining SIFs for microbial communities is challenging as the available methods either only provide limited taxonomic resolution, such as with the use of lipid biomarkers, or are limited in throughput, such as NanoSIMS imaging of single cells.Here we present “direct Protein-SIF” and the Calis-p software package (https://sourceforge.net/projects/calis-p/), which enable high-throughput measurements of accurate δ13C values for individual species within a microbial community. We benchmark the method using 20 pure culture microorganisms and show that the method reproducibly provides SIF values consistent with gold standard bulk measurements performed with an isotope ratio mass spectrometer. Using mock community samples, we show that SIF values can also be obtained for individual species within a microbial community. Finally, a case study of an obligate bacteria-animal symbiosis showed that direct Protein-SIF confirms previous physiological hypotheses and can provide unexpected new insights into the symbionts’ metabolism. This confirms the usefulness of this new approach to accurately determine δ13C values for different species in microbial community samples.SignificanceTo understand the roles that microorganisms play in diverse environments such as the open ocean and the human intestinal tract, we need an understanding of their metabolism and physiology. A variety of methods such as metagenomics and metaproteomics exist to assess the metabolism of environmental microorganisms based on gene content and gene expression. These methods often only provide indirect evidence for which substrates are used by a microorganism in a community. The direct Protein-SIF method that we developed allows linking microbial species in communities to the environmental carbon sources they consume by determining their stable carbon isotope signature. Direct Protein-SIF also allows assessing which carbon fixation pathway is used by autotrophic microorganisms that directly assimilate CO2.

Multicriteria Synthesis of Trigeneration Systems Assisted With Renewable Energy Sources and Thermal Energy Storage

2017 ◽  
Author(s):  
Eduardo A. Pina ◽  
Miguel A. Lozano ◽  
Luis M. Serra
Keyword(s):  
Co2 Emissions ◽  
Energy Demand ◽  
High Efficiency ◽  
Programming Model ◽  
Environmental Concern ◽  
Renewable Energy Sources ◽  
Mixed Integer ◽  
Total Annual Cost ◽  
Trade Off ◽  
Conflicting Objectives

The increasing world energy demand as a result of society development brings forth a growing environmental concern. The use of high-efficiency alternative systems is becoming progressively more interesting due to economic reasons and regional incentives. The issue of finding the best configuration that minimizes total annual cost is not enough anymore, as the environmental concern has become one of the objectives in the synthesis of energy systems. The minimization of costs is often contradictory to the minimization of environmental impact. Multi-objective optimization tackles the conflicting objectives issue by providing a set of trade-off solutions, or Pareto solutions, that can be examined by the decision maker in order to choose the best configuration for the given scenario. The present work proposes a mixed integer linear programming model for the synthesis of a trigeneration system that must attend the electricity, heat, and cooling demands of a multifamily building complex in Zaragoza, Spain. The objective functions to be minimized are the overall annual costs and the overall annual CO2 emissions, considering investment, maintenance and operation costs. As a first approach, the single-objective configurations for each objective function are evaluated. Then, the Pareto frontier is obtained for the minimization of total annual costs and total annual CO2 emissions, allowing to obtain the best trade-off configuration, which brings results close to the optimal single objectives. It is worth mentioning that the treatment of the energy prices was simplified in order to keep on the same level of detail as energy CO2 emissions, which are given only on an annual basis. On the other hand, the optimization model developed can be further complicated in order to consider more complex situations.

The role of discounting in global social issues

1995 ◽  
Vol 18 (1) ◽  
pp. 144-144
Author(s):  
Craig Summers
Keyword(s):  
Environmental Sustainability ◽  
Social Issues ◽  
Self Control ◽  
Experimental Literature ◽  
Behavioral Models ◽  
Trade Off ◽  
Research Questions ◽  
New Research ◽  
Future Consequences

AbstractThe willingness to trade off large but ill-defined future consequences for immediate work characterizes social problems such as environmental sustainability. This commentary argues that important applications of behavioral models of self-control are being overlooked in the experimental literature. Tying the experimental literature to longterm health, environmental, and other risks makes the experimental work more germane, and raises new research questions for experimental modeling.

scholarly journals Study of Optimal Cam Design of Dual-Axle Spring-Loaded Camming Device

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1940 ◽  
Author(s):  
David Rybansky ◽  
Martin Sotola ◽  
Pavel Marsalek ◽  
Zdenek Poruba ◽  
Martin Fusek
Keyword(s):  
Topology Optimization ◽  
Bearing Capacity ◽  
Fall Prevention ◽  
Computational Models ◽  
Point Of View ◽  
Load Bearing Capacity ◽  
Parametric Curves ◽  
Trade Off ◽  
Cam Design ◽  
Operating Element

The spring-loaded camming device (SLCD), also known as “friend”, is a simple mechanism used to ensure the safety of the climber through fall prevention. SLCD consists of two pairs of opposing cams rotating separately, with one (single-axle SLCD) or two (dual-axle SLCD) pins connecting the opposing cams, a stem, connected to the pins, providing the attachment of the climbing rope, springs, which simultaneously push cams to a fully expanded position, and an operating element controlling the cam position. The expansion of cams is thus adaptable to allow insertion or removal of the device into/from a rock crack. While the pins, stem, operating element, and springs can be considered optimal, the (especially internal) shape of the cam allows space for improvement, especially where the weight is concerned. This paper focuses on optimizing the internal shape of the dual-axle SLCD cam from the perspective of the weight/stiffness trade-off. For this purpose, two computational models are designed and multi-step topology optimization (TOP) are performed. From the computational models’ point of view, SLCD is considered symmetric and only one cam is optimized and smoothened using parametric curves. Finally, the load-bearing capacity of the new cam design is analyzed. This work is based on practical industry requirements, and the obtained results will be reflected in a new commercial design of SLCD.

scholarly journals Designing microbial communities to maximize the thermodynamic driving force for the production of chemicals

2021 ◽  
Vol 17 (6) ◽  
pp. e1009093
Author(s):  
Pavlos Stephanos Bekiaris ◽  
Steffen Klamt
Keyword(s):  
Microbial Communities ◽  
Division Of Labor ◽  
Driving Force ◽  
Single Species ◽  
Microbial Consortia ◽  
Biotechnological Applications ◽  
Single Strain ◽  
Metabolic Burden ◽  
Thermodynamic Driving Force ◽  
Different Strains

Microbial communities have become a major research focus due to their importance for biogeochemical cycles, biomedicine and biotechnological applications. While some biotechnological applications, such as anaerobic digestion, make use of naturally arising microbial communities, the rational design of microbial consortia for bio-based production processes has recently gained much interest. One class of synthetic microbial consortia is based on specifically designed strains of one species. A common design principle for these consortia is based on division of labor, where the entire production pathway is divided between the different strains to reduce the metabolic burden caused by product synthesis. We first show that classical division of labor does not automatically reduce the metabolic burden when metabolic flux per biomass is analyzed. We then present ASTHERISC (Algorithmic Search of THERmodynamic advantages in Single-species Communities), a new computational approach for designing multi-strain communities of a single-species with the aim to divide a production pathway between different strains such that the thermodynamic driving force for product synthesis is maximized. ASTHERISC exploits the fact that compartmentalization of segments of a product pathway in different strains can circumvent thermodynamic bottlenecks arising when operation of one reaction requires a metabolite with high and operation of another reaction the same metabolite with low concentration. We implemented the ASTHERISC algorithm in a dedicated program package and applied it on E. coli core and genome-scale models with different settings, for example, regarding number of strains or demanded product yield. These calculations showed that, for each scenario, many target metabolites (products) exist where a multi-strain community can provide a thermodynamic advantage compared to a single strain solution. In some cases, a production with sufficiently high yield is thermodynamically only feasible with a community. In summary, the developed ASTHERISC approach provides a promising new principle for designing microbial communities for the bio-based production of chemicals.

scholarly journals The evolution of germ-soma specialization under different genetic and environmental effects

2021 ◽  
Author(s):  
Denis Tverskoi ◽  
Sergey Gavrilets
Keyword(s):  
Division Of Labor ◽  
Environmental Gradients ◽  
Biological Organization ◽  
Trade Off ◽  
Agent Based ◽  
Number Of Genes ◽  
Microenvironmental Factors ◽  
General Mathematical Model ◽  
Multicellular Organisms

Division of labor exists at different levels of biological organization - from cell colonies to human societies. One of the simplest examples of the division of labor in multicellular organisms is germ-soma specialization, which plays a key role in the evolution of organismal complexity. Here we formulate and study a general mathematical model exploring the emergence of germ-soma specialization in colonies of cells. We consider a finite population of colonies competing for resources. Colonies are of the same size and are composed by asexually reproducing haploid cells. Each cell can contribute to activity and fecundity of the colony, these contributions are traded-off. We assume that all cells within a colony are genetically identical but gene expression is affected by variation in the microenvironment experienced by individual cells. Through analytical theory and evolutionary agent-based modeling we show that the shape of the trade-off relation between somatic and reproductive functions, the type and extent of variation in within-colony microenvironment, and, in some cases, the number of genes involved, are important predictors of the extent of germ-soma specialization. Specifically, increasing convexity of the trade-off relation, the number of different environmental gradients acting within a colony, and the number of genes (in the case of random microenvironmental effects) promote the emergence of germ-soma specialization. Overall our results contribute towards a better understanding of the role of genetic, environmental, and microenvironmental factors in the evolution of germ-soma specialization.

Sign in / Sign up

Export Citation Format

Share Document