scholarly journals Untangling the dynamics of persistence and colonization in microbial communities

2018 ◽  
Author(s):  
Sylvia L. Ranjeva ◽  
Joseph R. Mihaljevic ◽  
Maxwell B. Joseph ◽  
Anna R. Giuliano ◽  
Greg Dwyer
Keyword(s):  
Microbial Communities ◽  
Biotic Interactions ◽  
Mechanistic Modeling ◽  
Environmental Drivers ◽  
Modeling Approach ◽  
Environmental Requirements ◽  
Hpv Types ◽  
Environmental Responses ◽  
Species Occurrences ◽  
Potential Signal

AbstractA central goal of community ecology is to infer biotic interactions from observed distributions of co-occurring species. Evidence for biotic interactions, however, can be obscured by shared environmental requirements, posing a challenge for statistical inference. Here we introduce a dynamic statistical model that quantifies the effects of spatial and temporal covariance in longitudinal co-occurrence data. We separate the fixed pairwise effects of species occurrences on persistence and colonization rates, a potential signal of direct interactions, from latent pairwise correlations in occurrence, a potential signal of shared environmental responses. We apply our modeling approach to a pressing epidemiological question by examining how human papillomavirus (HPV) types coexist. Our results suggest that while HPV types respond similarly to common host traits, direct interactions are sparse and weak, so that HPV type diversity depends largely on shared environmental drivers. Our modeling approach is widely applicable to microbial communities and provides valuable insights that should lead to more directed hypothesis testing and mechanistic modeling.

Mechanistic Modeling of the Ball End Milling Process for Multi-Axis Machining of Free-Form Surfaces

2000 ◽  
Vol 123 (3) ◽  
pp. 369-379 ◽  
Author(s):  
Rixin Zhu ◽  
Shiv G. Kapoor ◽  
Richard E. DeVor
Keyword(s):  
End Milling ◽  
Chip Thickness ◽  
Mechanistic Modeling ◽  
Free Form ◽  
Surface Geometry ◽  
Workpiece Surface ◽  
Ball End Milling ◽  
Modeling Approach ◽  
Free Form Surfaces ◽  
Cutting Point

A mechanistic modeling approach to predicting cutting forces is developed for multi-axis ball end milling of free-form surfaces. The workpiece surface is represented by discretized point vectors. The modeling approach employs the cutting edge profile in either analytical or measured form. The engaged cut geometry is determined by classification of the elemental cutting point positions with respect to the workpiece surface. The chip load model determines the undeformed chip thickness distribution along the cutting edges with consideration of various process faults. Given a 5-axis tool path in a cutter location file, shape driving profiles are generated and piecewise ruled surfaces are used to construct the tool swept envelope. The tool swept envelope is then used to update the workpiece surface geometry employing the Z-map method. A series of 3-axis and 5-axis surface machining tests on Ti6A14V were conducted to validate the model. The model shows good computational efficiency, and the force predictions are found in good agreement with the measured data.

Mechanistic modeling of environmental drivers of woolly mammoth carrying capacity declines on St. Paul Island

Ecology ◽  
2018 ◽  
Vol 99 (12) ◽  
pp. 2721-2730 ◽  
Author(s):  
Yue Wang ◽  
Warren Porter ◽  
Paul D. Mathewson ◽  
Paul A. Miller ◽  
Russell W. Graham ◽  
...  
Keyword(s):  
Carrying Capacity ◽  
Mechanistic Modeling ◽  
Environmental Drivers ◽  
Woolly Mammoth

scholarly journals Parallel changes in gut microbiome composition and function in parallel local adaptation and speciation

2019 ◽  
Author(s):  
Diana J. Rennison ◽  
Seth M. Rudman ◽  
Dolph Schluter
Keyword(s):  
Microbial Communities ◽  
Local Adaptation ◽  
Biotic Interactions ◽  
Ecological Speciation ◽  
Microbiome Composition ◽  
Interacting Species ◽  
Microbe Interactions ◽  
Host Microbe Interactions ◽  
And Function ◽  
Host Evolution

AbstractThe processes of local adaptation and ecological speciation are often strongly shaped by biotic interactions such as competition and predation. One of the strongest lines of evidence that biotic interactions drive evolution comes from repeated divergence of lineages in association with repeated changes in the community of interacting species. Yet, relatively little is known about the repeatability of changes in gut microbial communities and their role in adaptation and divergence of host populations in nature. Here we utilize three cases of rapid, parallel adaptation and speciation in freshwater threespine stickleback to test for parallel changes in associated gut microbiomes. We find that features of the gut microbial communities have shifted repeatedly in the same direction in association with parallel divergence and speciation of stickleback hosts. These results suggest that changes to gut microbiomes can occur rapidly and predictably in conjunction with host evolution, and that host-microbe interactions might play an important role in host adaptation and diversification.

scholarly journals Disruption of cross-feeding interactions by invading taxa can cause invasional meltdown in microbial communities

2020 ◽  
Vol 287 (1927) ◽  
pp. 20192945 ◽  
Author(s):  
Cristina M. Herren
Keyword(s):  
Microbial Communities ◽  
Biotic Interactions ◽  
Invasion Risk ◽  
Invasional Meltdown ◽  
Native Community ◽  
Exchange Networks ◽  
Composition And Structure ◽  
Metabolite Exchange ◽  
Successful Invader ◽  
The Impact

The strength of biotic interactions within an ecological community affects the susceptibility of the community to invasion by introduced taxa. In microbial communities, cross-feeding is a widespread type of biotic interaction that has the potential to affect community assembly and stability. Yet, there is little understanding of how the presence of cross-feeding within a community affects invasion risk. Here, I develop a metabolite-explicit model where native microbial taxa interact through both cross-feeding and competition for metabolites. I use this model to study how the strength of biotic interactions, especially cross-feeding, influence whether an introduced taxon can join the community. I found that stronger cross-feeding and competition led to much lower invasion risk, as both types of biotic interactions lead to greater metabolite scarcity for the invader. I also evaluated the impact of a successful invader on community composition and structure. The effect of invaders on the native community was greatest at intermediate levels of cross-feeding; at this ‘critical’ level of cross-feeding, successful invaders generally cause decreased diversity, decreased productivity, greater metabolite availability, and decreased quantities of metabolites exchanged among taxa. Furthermore, these changes resulting from a successful primary invader made communities further susceptible to future invaders. The increase in invasion risk was greatest when the network of metabolite exchange between taxa was minimally redundant. Thus, this model demonstrates a case of invasional meltdown that is mediated by initial invaders disrupting the metabolite exchange networks of the native community.

scholarly journals Ester Linked Fatty Acid (ELFA) method should be used with caution for interpretating soil microbial communities and their relationships with environmental variables in forest soils

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251501
Author(s):  
Wenjuan Yu ◽  
Huanhuan Gao ◽  
Hongzhang Kang
Keyword(s):  
Fatty Acid ◽  
Microbial Biomass ◽  
Microbial Communities ◽  
Forest Soils ◽  
Environmental Variables ◽  
Phospholipid Fatty Acid ◽  
Soil Microbial Communities ◽  
Environmental Drivers ◽  
Soil Microbial ◽  
Forest Sites

As an alternative for phospholipid fatty acid (PLFA) analysis, a simpler ester linked fatty acid (ELFA) analysis has been developed to characterize soil microbial communities. However, few studies have compared the two methods in forest soils where the contribution of nonmicrobial sources may be larger than that of microbial sources. Moreover, it remains unclear whether the two methods yield similar relationships of microbial biomass and composition with environmental variables. Here, we compared PLFA and ELFA methods with respect to microbial biomass and composition and their relationships with environmental variables in six oriental oak (Quercus variabilis) forest sites along a 1500-km latitudinal gradient in East China. We found that both methods had a low sample-to-sample variability and successfully separated overall community composition of sites. However, total, bacterial, and fungal biomass, the fungal-to-bacterial ratio, and the gram-positive to gram-negative bacteria ratio were not significantly or strongly correlated between the two methods. The relationships of these microbial properties with environmental variables (pH, precipitation, and clay) greatly differed between the two methods. Our study indicates that despite its simplicity, the ELFA method may not be as feasible as the PLFA method for investigating microbial biomass and composition and for identifying their dominant environmental drivers, at least in forest soils.

scholarly journals Microbial Colonization in Marine Environments: Overview of Current Knowledge and Emerging Research Topics

2020 ◽  
Vol 8 (2) ◽  
pp. 78 ◽  
Author(s):  
Gabriella Caruso
Keyword(s):  
Microbial Communities ◽  
Environmental Changes ◽  
Current Knowledge ◽  
Cell Communication ◽  
Marine Ecosystems ◽  
Microbial Colonization ◽  
Artificial Substrates ◽  
Environmental Drivers ◽  
Future Research ◽  
Microbial Biofilms

Microbial biofilms are biological structures composed of surface-attached microbial communities embedded in an extracellular polymeric matrix. In aquatic environments, the microbial colonization of submerged surfaces is a complex process involving several factors, related to both environmental conditions and to the physical-chemical nature of the substrates. Several studies have addressed this issue; however, more research is still needed on microbial biofilms in marine ecosystems. After a brief report on environmental drivers of biofilm formation, this study reviews current knowledge of microbial community attached to artificial substrates, as obtained by experiments performed on several material types deployed in temperate and extreme polar marine ecosystems. Depending on the substrate, different microbial communities were found, sometimes highlighting the occurrence of species-specificity. Future research challenges and concluding remarks are also considered. Emphasis is given to future perspectives in biofilm studies and their potential applications, related to biofouling prevention (such as cell-to-cell communication by quorum sensing or improved knowledge of drivers/signals affecting biological settlement) as well as to the potential use of microbial biofilms as sentinels of environmental changes and new candidates for bioremediation purposes.

scholarly journals Habitat filtering shapes the differential structure of microbial communities in the Xilingol grassland

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jie Yang ◽  
Yanfen Wang ◽  
Xiaoyong Cui ◽  
Kai Xue ◽  
Yiming Zhang ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Habitat Preferences ◽  
Biotic Interactions ◽  
Illumina Miseq ◽  
Detailed Comparison ◽  
Niche Differentiation ◽  
Species Selection ◽  
Biogeographic Patterns ◽  
Xilingol Grassland ◽  
Steppe Grassland

AbstractThe spatial variability of microorganisms in grasslands can provide important insights regarding the biogeographic patterns of microbial communities. However, information regarding the degree of overlap and partitions of microbial communities across different habitats in grasslands is limited. This study investigated the microbial communities in three distinct habitats from Xilingol steppe grassland, i.e. animal excrement, phyllosphere, and soil samples, by Illumina MiSeq sequencing. All microbial community structures, i.e. for bacteria, archaea, and fungi, were significantly distinguished according to habitat. A high number of unique microorganisms but few coexisting microorganisms were detected, suggesting that the structure of microbial communities was mainly regulated by species selection and niche differentiation. However, the sequences of those limited coexisting microorganisms among the three different habitats accounted for over 60% of the total sequences, indicating their ability to adapt to variable environments. In addition, the biotic interactions among microorganisms based on a co-occurrence network analysis highlighted the importance of Microvirga, Blastococcus, RB41, Nitrospira, and four norank members of bacteria in connecting the different microbiomes. Collectively, the microbial communities in the Xilingol steppe grassland presented strong habitat preferences with a certain degree of dispersal and colonization potential to new habitats along the animal excrement- phyllosphere-soil gradient. This study provides the first detailed comparison of microbial communities in different habitats in a single grassland, and offers new insights into the biogeographic patterns of the microbial assemblages in grasslands.

scholarly journals Hybrid Modeling for Simultaneous Prediction of Flux, Rejection Factor and Concentration in Two-Component Crossflow Ultrafiltration

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1625
Author(s):  
Maximilian Krippl ◽  
Ignasi Bofarull-Manzano ◽  
Mark Duerkop ◽  
Astrid Dürauer
Keyword(s):  
Film Theory ◽  
Hybrid Models ◽  
Mechanistic Modeling ◽  
Time Resolved ◽  
Process Stage ◽  
Modeling Approach ◽  
Crossflow Ultrafiltration ◽  
Wide Range ◽  
Rejection Factor ◽  
The Impact

Ultrafiltration is a powerful method used in virtually every pharmaceutical bioprocess. Depending on the process stage, the product-to-impurity ratio differs. The impact of impurities on the process depends on various factors. Solely mechanistic models are currently not sufficient to entirely describe these complex interactions. We have established two hybrid models for predicting the flux evolution, the protein rejection factor and two components’ concentration during crossflow ultrafiltration. The hybrid models were compared to the standard mechanistic modeling approach based on the stagnant film theory. The hybrid models accurately predicted the flux and concentration over a wide range of process parameters and product-to-impurity ratios based on a minimum set of training experiments. Incorporating both components into the modeling approach was essential to yielding precise results. The stagnant film model exhibited larger errors and no predictions regarding the impurity could be made, since it is based on the main product only. Further, the developed hybrid models exhibit excellent interpolation properties and enable both multi-step ahead flux predictions as well as time-resolved impurity forecasts, which is considered to be a critical quality attribute in many bioprocesses. Therefore, the developed hybrid models present the basis for next generation bioprocessing when implemented as soft sensors for real-time monitoring of processes.

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