scholarly journals Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities

2021 ◽  
Vol 17 (7) ◽  
pp. e1009140
Author(s):  
Liliana Angeles-Martinez ◽  
Vassily Hatzimanikatis

The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that unevenly reduce the diffusion of nutrients. Herein, we investigated how the crowding conditions and metabolic variability among cells shape the dynamics of microbial communities. For this, we developed CROMICS, a spatio-temporal framework that combines techniques such as individual-based modeling, scaled particle theory, and thermodynamic flux analysis to explicitly incorporate the cell metabolism and the impact of the presence of macromolecular components on the nutrients diffusion. This framework was used to study two archetypical microbial communities (i) Escherichia coli and Salmonella enterica that cooperate with each other by exchanging metabolites, and (ii) two E. coli with different production level of extracellular polymeric substances (EPS) that compete for the same nutrients. In the mutualistic community, our results demonstrate that crowding enhanced the fitness of cooperative mutants by reducing the leakage of metabolites from the region where they are produced, avoiding the resource competition with non-cooperative cells. Moreover, we also show that E. coli EPS-secreting mutants won the competition against the non-secreting cells by creating less dense structures (i.e. increasing the spacing among the cells) that allow mutants to expand and reach regions closer to the nutrient supply point. A modest enhancement of the relative fitness of EPS-secreting cells over the non-secreting ones were found when the crowding effect was taken into account in the simulations. The emergence of cell-cell interactions and the intracellular conflicts arising from the trade-off between growth and the secretion of metabolites or EPS could provide a local competitive advantage to one species, either by supplying more cross-feeding metabolites or by creating a less dense neighborhood.

2002 ◽  
Vol 46 (1-2) ◽  
pp. 405-412 ◽  
Author(s):  
E. Müller ◽  
K. Kriebitzsch ◽  
P.A. Wilderer ◽  
S. Wuertz

Settling problems caused by pin-point sludge constitute a serious problem in biological wastewater treatment, particularly in many industrial plants. Until now, most studies focused on the relationship between pin-point sludge formation and either shearing forces or the impact of toxicants. This study deals with the community structure in both the micro- and macrofloc fraction which was analyzed by fluorescent in situ hybridization (FISH) and BIOLOG substrate utilization patterns. It was shown that each fraction consisted of different microbial communities with unique metabolic profiles suggesting that pin-point sludge formation is not due to dispersal of intact flocs but to microcolonies growing separately. Alternatively, macroflocs may have an architecture leading to segregation of microbial communities after floc dispersal. Further it could be shown that the formation of microflocs was influenced by sludge age. The best sludge sedimentation was obtained for a sludge age of 5 and 10 days. Additional analysis of extracellular polymeric substances (EPS) suggested that the lower protein to carbohydrate ratio of 10-day-old sludge led to better flocculation compared to 20-day-old sludge containing similar total amounts of EPS. From a practical point of view, addition of potassium (0.1 g/l) effected a noticeable improvement of sludge settleability.


Author(s):  
Helen Kurkjian ◽  
M. Javad Akbari ◽  
Babak Momeni

AbstractIn human microbiota, the prevention or promotion of invasions can be crucial to human health. Invasion outcomes, in turn, are impacted by the composition of resident communities and interactions among resident microbes. Microbial communities differ from communities composed of other types of organisms in that many microbial interactions are mediated by chemicals that are released into or consumed from the environment. We ask what determines invasion outcomes in such microbial communities. Here, we use a model based on chemical-mediated interactions among microbial species to assess the impact of positive and negative interactions on invasion outcomes. We classified invasion outcomes as resistance, augmentation, displacement, or disruption depending on whether the richness of the resident community was maintained or dropped and whether the invader was maintained in the community or went extinct. We found that as the number of invaders increased relative to size of the resident community, resident communities were increasingly disrupted. As facilitation of the invader by the resident community increased, resistance outcomes were replaced by displacement and augmentation. By contrast, as facilitation increased among residents, displacement outcomes shifted to resistance. When facilitation of the resident community by the invader was eliminated, augmentation outcomes were replaced by displacement outcomes, while when inhibition of residents by invaders was eliminated, there was little change in the frequency of invasion outcomes. These results suggest that a better understanding of the chemical-mediated interactions within resident communities and between residents and invaders is crucial to predicting the success of invasions into microbial communities.


2020 ◽  
Author(s):  
Bjorn J.M. Robroek ◽  
Magalí Martí ◽  
Bo H. Svensson ◽  
Marc G. Dumont ◽  
Annelies J. Veraart ◽  
...  

AbstractEnviro-climatological changes are thought to be causing alterations in ecosystem processes through shifts in plant and microbial communities; however, how links between plant and microbial communities change with enviro-climatological change is likely to be less straightforward but may be fundamental for many ecological processes. To address this, we assessed the composition of the plant community and the prokaryotic community –using amplicon-based sequencing– of three European peatlands that were distinct in enviro-climatological conditions. Bipartite networks were used to construct site-specific plant-prokaryote co-occurrence networks. Our data show that between sites, plant and prokaryotic communities differ and that turnover in interactions between the communities was complex. Essentially, turnover in plant-microbial interactions is much faster than turnover in the respective communities. Our findings suggest that network rewiring does largely result from novel associations between species that are common and shared across the networks. Turnover in network composition is largely driven by novel interactions between a core community of plants and microorganisms. Taken together our results indicate that plant-microbe associations are context dependent, and that changes in enviro-climatological conditions will likely lead to network rewiring. Integrating turnover in plant-microbe interactions into studies that assess the impact of enviro-climatological change on peatland ecosystems is essential to understand ecosystem dynamics and must be combined with studies on the impact of these changes on ecosystem processes.


2021 ◽  
Author(s):  
Sana Romdhane ◽  
Aymé Spor ◽  
Julie Aubert ◽  
David Bru ◽  
Marie-Christine Breuil ◽  
...  

AbstractMicrobial communities play important roles in all ecosystems and yet a comprehensive understanding of the ecological processes governing the assembly of these communities is missing. To address the role of biotic interactions between microorganisms in assembly and for functioning of the soil microbiota, we used a top-down manipulation approach based on the removal of various populations in a natural soil microbial community. We hypothesized that removal of certain microbial groups will strongly affect the relative fitness of many others, therefore unraveling the contribution of biotic interactions in shaping the soil microbiome. Here we show that 39% of the dominant bacterial taxa across treatments were subjected to competitive interactions during soil recolonization, highlighting the importance of biotic interactions in the assembly of microbial communities in soil. Moreover, our approach allowed the identification of microbial community assembly rule as exemplified by the competitive exclusion between members of Bacillales and Proteobacteriales. Modified biotic interactions resulted in greater changes in activities related to N- than to C-cycling. Our approach can provide a new and promising avenue to study microbial interactions in complex ecosystems as well as the links between microbial community composition and ecosystem function.


Pathogens ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 96
Author(s):  
Jiwasmika Baishya ◽  
Karishma Bisht ◽  
Jeanette N. Rimbey ◽  
Kiddist D. Yihunie ◽  
Shariful Islam ◽  
...  

The human microbiota is an array of microorganisms known to interact with the host and other microbes. These interactions can be competitive, as microbes must adapt to host- and microorganism-related stressors, thus producing toxic molecules, or cooperative, whereby microbes survive by maintaining homeostasis with the host and host-associated microbial communities. As a result, these microbial interactions shape host health and can potentially result in disease. In this review, we discuss these varying interactions across microbial species, their positive and negative effects, the therapeutic potential of these interactions, and their implications on our knowledge of human well-being.


2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 307
Author(s):  
Chi Zhang ◽  
Naixia Mou ◽  
Jiqiang Niu ◽  
Lingxian Zhang ◽  
Feng Liu

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade−1, p = 0.81) and SCD (s = −2.3 d decade−1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.


2021 ◽  
Vol 9 (2) ◽  
pp. 183
Author(s):  
Xuehua Ma ◽  
Yi Zhou ◽  
Luyi Yang ◽  
Jianfeng Tong

Rapid development of the economy increased marine litter around Zhoushan Island. Social-ecological scenario studies can help to develop strategies to adapt to such change. To investigate the present situation of marine litter pollution, a stratified random sampling (StRS) method was applied to survey the distribution of marine coastal litters around Zhoushan Island. A univariate analysis of variance was conducted to access the amount of litter in different landforms that include mudflats, artificial and rocky beaches. In addition, two questionnaires were designed for local fishermen and tourists to provide social scenarios. The results showed that the distribution of litter in different landforms was significantly different, while the distribution of litter in different sampling points had no significant difference. The StRS survey showed to be a valuable method for giving a relative overview of beach litter around Zhoushan Island with less effort in a future survey. The questionnaire feedbacks helped to understand the source of marine litter and showed the impact on the local environment and economy. Based on the social-ecological scenarios, governance recommendations were provided in this paper.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Verónica Lloréns-Rico ◽  
Sara Vieira-Silva ◽  
Pedro J. Gonçalves ◽  
Gwen Falony ◽  
Jeroen Raes

AbstractWhile metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible.


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