scholarly journals High-order interactions dominate the functional landscape of microbial consortia

2018 ◽  
Author(s):  
Alicia Sanchez-Gorostiaga ◽  
Djordje Bajić ◽  
Melisa L. Osborne ◽  
Juan F. Poyatos ◽  
Alvaro Sanchez

AbstractUnderstanding the link between community composition and function is a major challenge in microbial ecology, with implications for the management of natural microbiomes and the design of synthetic consortia. For this purpose, it is critical to understand the extent to which community functions and properties can be predicted from species traits and what role is played by complex interactions. Inspired by the study of complex genetic interactions and fitness landscapes, here we have examined how the amylolytic function of combinatorial assemblages of seven starch-degrading soil bacteria depends on the functional contributions from each species and their interactions. Filtering our experimental results through the theory of enzyme kinetics, we show that high-order functional interactions dominate the amylolytic rate of our consortia, even though this function is biochemically simple, redundantly distributed in the community, and additive in the absence of inter-species interactions. As the community grows in size, the contribution of high-order functional interactions grows too, making the community function increasingly unpredictable. We can explain the prevalence of high order effects and their sign from the redundancy of ecological interactions in the network, in particular from redundant facilitation towards a high-performing community member. Our results suggest that even simple functions can be dominated by complex interactions, posing challenges for the predictability and bottom-up engineering of ecosystem function in complex multi-species communities.

2021 ◽  
Author(s):  
Olga Lamprecht ◽  
Bettina Wagner ◽  
Nicolas Derlon ◽  
Ahmed Tlili

Phototrophic biofilms, also known as periphyton, drive crucial ecosystem processes and are subject to alterations due to a multitude of biotic and abiotic factors. In this context, understanding species dynamics in periphyton is a fundamental, yet challenging, requirement to accurately predict outcomes on functions and properties of complex communities. To address this challenge, we developed a workflow applying rational design based on existing knowledge on natural periphyton, to successfully obtain a stable, diverse and highly reproducible synthetic periphyton. We show that by using our synthetic community, with a known microbial composition, we are able to monitor dynamics of single species during periphyton development and their specific response to stressors such as increased temperature and herbicides. Importantly, we clearly demonstrate that these responses are mainly driven by species interactions and how they link to changes of community function and structure. Our synthetic periphyton is a powerful tool to perform mechanistic studies on periphyton structural and functional responses, as well as on species propagation, to any biotic and abiotic stressors and their combinations.


2021 ◽  
Author(s):  
Ashish B. George ◽  
Kirill S. Korolev

Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia.


2021 ◽  
Vol 9 (2) ◽  
pp. 417
Author(s):  
Sherli Koshy-Chenthittayil ◽  
Linda Archambault ◽  
Dhananjai Senthilkumar ◽  
Reinhard Laubenbacher ◽  
Pedro Mendes ◽  
...  

The human microbiome has been a focus of intense study in recent years. Most of the living organisms comprising the microbiome exist in the form of biofilms on mucosal surfaces lining our digestive, respiratory, and genito-urinary tracts. While health-associated microbiota contribute to digestion, provide essential nutrients, and protect us from pathogens, disturbances due to illness or medical interventions contribute to infections, some that can be fatal. Myriad biological processes influence the make-up of the microbiota, for example: growth, division, death, and production of extracellular polymers (EPS), and metabolites. Inter-species interactions include competition, inhibition, and symbiosis. Computational models are becoming widely used to better understand these interactions. Agent-based modeling is a particularly useful computational approach to implement the various complex interactions in microbial communities when appropriately combined with an experimental approach. In these models, each cell is represented as an autonomous agent with its own set of rules, with different rules for each species. In this review, we will discuss innovations in agent-based modeling of biofilms and the microbiota in the past five years from the biological and mathematical perspectives and discuss how agent-based models can be further utilized to enhance our comprehension of the complex world of polymicrobial biofilms and the microbiome.


2020 ◽  
Author(s):  
Tianming Yao ◽  
Ming-Hsu Chen ◽  
Stephen R. Lindemann

ABSTRACTDietary fibers are major substrates for the colonic microbiota, but the structural specificity of these fibers for the diversity, structure, and function of gut microbial communities are poorly understood. Here, we employed an in vitro sequential batch fecal culture approach to determine: 1) whether the chemical complexity of a carbohydrate structure influences its ability to maintain microbial diversity in the face of high dilution pressure and 2) whether substrate structuring or obligate microbe-microbe metabolic interactions (e.g. exchange of amino acids or vitamins) exert more influence on maintained diversity. Sorghum arabinoxylan (SAX, complex polysaccharide), inulin (low-complexity oligosaccharide) and their corresponding monosaccharide controls were selected as model carbohydrates. Our results demonstrate that complex carbohydrates stably sustain diverse microbial consortia. Further, very similar final consortia were enriched on SAX from the same individual’s fecal microbiota across a one-month interval, suggesting that polysaccharide structure is more influential than stochastic alterations in microbiome composition in governing the outcomes of sequential batch cultivation experiments. SAX-consuming consortia were anchored by Bacteroides ovatus and retained diverse consortia of >12 OTUs; whereas final inulin-consuming consortia were dominated either by Klebsiella pneumoniae or Bifidobacterium sp. and Escherichia coli. Furthermore, auxotrophic interactions were less influential in structuring microbial consortia consuming SAX than the less-complex inulin. These data suggest that carbohydrate structural complexity affords independent niches that structure fermenting microbial consortia, whereas other metabolic interactions govern the composition of communities fermenting simpler carbohydrates.IMPORTANCEThe mechanisms by which gut microorganisms compete for and cooperate on human-indigestible carbohydrates of varying structural complexity remain unclear. Gaps in this understanding make it challenging to predict the effect of a particular dietary fiber’s structure on the diversity, composition, or function of gut microbiomes, especially with inter-individual variability in diets and microbiomes. Here, we demonstrate that carbohydrate structure governs the diversity of gut microbiota under high dilution pressure, suggesting that such structures may support microbial diversity in vivo. Further, we also demonstrate that carbohydrate polymers are not equivalent in the strength by which they influence community structure and function, and that metabolic interactions among members arising due to auxotrophy exert significant influence on the outcomes of these competitions for simpler polymers. Collectively, these data suggest that large, complex dietary fiber polysaccharides structure the human gut ecosystem in ways that smaller and simpler ones may not.


2021 ◽  
Author(s):  
Lida Safaei ◽  
Mohsen Hatami ◽  
Mahmood Borhani Zarandi

Abstract In this paper, we analytically solve the coupled equations of a PT -Symmetric NLDC by considering high-order dispersion and nonlinear effects (Raman Scattering and self-steeping) simultaneously in normal dispersion regime. To the best of knowledge no works has been done in previous studies to decoupled these equations and obtain an exact analytical solution. The new exact bright solitary solutions are derived. In addition, to study the stability and instability of these propagated solitons in a PT -Symmetric NLDC, perturbation theory is used. Numerical methods are applied to find perturbed eigenvalues and eigenfunctions. The Stability of obtained four perturbed eigenvalues and perturbed eigenfunctions for a PT -Symmetric NLDC equations regard to high-order effects are examined. Using these results and simulating the propagation of perturbed temporal bright solitons through PT -Symmetric NLDC show that perturbed solitons are mostly stable. This means that high-order dispersion and nonlinear effects canceled each other and do not affected the propagated solitons. Furthermore, the evolution of perturbed solitons energies match well the previous results and con rmed the stability of these solitons in a PT -Symmetric NLDC. As seen the energies of pulses in bar and cross behave in two manner 1) the exchange of energy is happened in some periods, but the shape of each pulse in bar and cross is preserved. Therefore, the solitons under this eigenfunction perturbation are mostly stable. 2) the evolution of energy in the bar and cross, demonstrate that there is no changes in their energies and they remain constant. It is straightforward to show that in spite of considering high-order effects, the perturbed soliton conserve the shape and it remain stable. The deliverables of this article not only demonstrate a novel approach to ultra-fast pulses, solitons and optical couplers, but more fundamentally, they could give insight for improving the new medical equipments technologies, enabling innovations in nonlinear optics and their usage in designing new communication systems and Photonic devices.


2018 ◽  
Vol 2 ◽  
pp. e25343
Author(s):  
José Augusto Salim ◽  
Antonio Saraiva ◽  
Kayna Agostini ◽  
Marina Wolowski ◽  
Allan Veiga ◽  
...  

The Brazilian Plant-Pollinator Interactions Network*1 (REBIPP) aims to develop scientific and teaching activities in plant-pollinator interaction. The main goals of the network are to: generate a diagnosis of plant-pollinator interactions in Brazil; integrate knowledge in pollination of natural, agricultural, urban and restored areas; identify knowledge gaps; support public policy guidelines aimed at the conservation of biodiversity and ecosystem services for pollination and food production; and encourage collaborative studies among REBIPP participants. To achieve these goals the group has resumed and built on previous works in data standard definition done under the auspices of the IABIN-PTN (Etienne Américo et al. 2007) and FAO (Saraiva et al. 2010) projects (Saraiva et al. 2017). The ultimate goal is to standardize the ways data on plant-pollinator interactions are digitized, to facilitate data sharing and aggregation. A database will be built with standardized data from Brazilian researchers members of the network to be used by the national community, and to allow sharing data with data aggregators. To achieve those goals three task groups of specialists with similar interests and background (e.g botanists, zoologists, pollination biologists) have been created. Each group is working on the definition of the terms to describe plants, pollinators and their interactions. The glossary created explains their meaning, trying to map the suggested terms into Darwin Core (DwC) terms, and following the TDWG Standards Documentation Standard*2 in definition. Reaching a consensus on terms and their meaning among members of each group is challenging, since researchers have different views and concerns about which data are important to be included into a standard. That reflects the variety of research questions that underlie different projects and the data they collect. Thus, we ended up having a long list of terms, many of them useful only in very specialized research protocols and experiments, sometimes rarely collected or measured. Nevertheless we opted to maintain a very comprehensive set of terms, so that a large number of researchers feel that the standard meets their needs and that the databases based on it are a suitable place to store their data, thus encouraging the adoption of the data standard. An update of the work will soon be available at REBIPP website and will be open for comments and contributions. This proposal of a data standard is also being discussed within the TDWG Biological Interaction Data Interest Group*3 in order to propose an international standard for species interaction data. The importance of interaction data for guiding conservation practices and ecosystem services provision management has led to the proposal of defining Essential Biodiversity Variables (EBVs) related to biological interactions. Essential Biodiversity Variables (Pereira et al. 2013) were developed to identify key measurements that are required to monitoring biodiversity change. EBVs act as intermediate abstract layer between primary observations (raw data) and indicators (Niemeijer 2002). Five EBV classes have been defined in an initial stage: genetic composition, species populations, species traits, community composition, ecosystem function and ecosystem structure. Each EBV class defines a list of candidate EBVs for biodiversity change monitoring (Fig. 1). Consequently, digitalization of such data and making them available online are essential. Differences in sampling protocols may affect data scalability across space and time, hence imposing barriers to the full use of primary data and EBVs calculation (Henry et al. 2008). Thus, common protocols and methods should be adopted as the most straightforward approach to promote integration of collected data and to allow calculation of EBVs (Jürgens et al. 2011). Recently a Workshop was held by GLOBIS B*4 (GLOBal Infrastructures for Supporting Biodiversity research) to discuss Species Interactions EBVs (February, 26-28, Bari, Italy). Plant-pollinator interactions deserved a lot of attention and REBIPP's work was presented there. As an outcome we expect to define specific EBVs for interactions, and use plant-pollinators as an example, considering pairwise interactions as well as interaction network related variables. The terms in the plant-pollinator data standard under discussion at REBIPP will provide information not only on EBV related with interactions, but also on other four EBV classes: species populations, species traits, community composition, ecosystem function and ecosystem structure. As we said, some EBVs for specific ecosystem functions (e.g. pollination) lay beyond interactions network structures. The EBV 'Species interactions' (EBV class 'Community composition') should incorporate other aspects such as frequency (Vázquez et al. 2005), duration and empirical estimates of interaction strengths (Berlow et al. 2004). Overall, we think the proposed plant-pollinator interaction data standard which is currently being developed by REBIPP will contribute to data aggregation, filling many data gaps and can also provide indicators for long-term monitoring, being an essential source of data for EBVs.


2019 ◽  
pp. 266-284
Author(s):  
Gary G. Mittelbach ◽  
Brian J. McGill

Just as the dispersal of individuals may link the dynamics of populations in space, the dispersal of species among communities may link local communities into a metacommunity. Four different perspectives characterize how dispersal rates, environmental heterogeneity, and species traits interact to influence diversity in metacommunities. These perspectives are: patch dynamics, species sorting, mass effects, and the neutral perspective. The neutral perspective stands in stark contrast to the other three perspectives in that it assumes that niche differences between species are unimportant and that species are demographically identical in terms of their birth, death, and dispersal rates. Under the neutral perspective, species diversity is maintained by a balance between speciation, extinction, and dispersal. Although neutral theory is incompatible with realistic modes and rates of speciation, it has been enormously influential in focusing our attention on the linkages between species interactions on local scales, and evolutionary and biogeographic processes occurring on large scales.


Microbiome ◽  
2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Ran Mei ◽  
Wen-Tso Liu

Abstract Immigration is a process that can influence the assembly of microbial communities in natural and engineered environments. However, it remains challenging to quantitatively evaluate the contribution of this process to the microbial diversity and function in the receiving ecosystems. Currently used methods, i.e., counting shared microbial species, microbial source tracking, and neutral community model, rely on abundance profile to reveal the extent of overlapping between the upstream and downstream communities. Thus, they cannot suggest the quantitative contribution of immigrants to the downstream community function because activities of individual immigrants are not considered after entering the receiving environment. This limitation can be overcome by using an approach that couples a mass balance model with high-throughput DNA sequencing, i.e., ecogenomics-based mass balance. It calculates the net growth rate of individual microbial immigrants and partitions the entire community into active populations that contribute to the community function and inactive ones that carry minimal function. Linking activities of immigrants to their abundance further provides quantification of the contribution from an upstream environment to the downstream community. Considering only active populations can improve the accuracy of identifying key environmental parameters dictating process performance using methods such as machine learning.


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