scholarly journals Metabolic overlap in environmentally diverse microbial communities

2019 ◽  
Author(s):  
Eric R. Hester ◽  
Mike S.M. Jetten ◽  
Cornelia U. Welte ◽  
Sebastian Lücker
Keyword(s):  
Microbial Communities ◽  
Future Research ◽  
Aquatic Environments ◽  
Competition And Cooperation ◽  
Microbial Species ◽  
Common Resource ◽  
Animal Hosts ◽  
Genome Scale ◽  
Genome Information ◽  
Detailed Picture

AbstractThe majority of microbial communities consist of hundreds to thousands of species, creating a massive network of organisms competing for available resources within an ecosystem. In natural microbial communities it appears that many microbial species have highly redundant metabolisms and seemingly are capable of utilizing the same substrates. This is paradoxical, as theory indicates that species requiring a common resource should outcompete one another. To better understand why microbial species can co-exist, we developed Metabolic Overlap (MO) as a new metric to survey the functional redundancy of microbial communities at the genome scale across a wide variety of ecosystems. Using metagenome-assembled genomes, we surveyed over 1200 studies across ten ecosystem types. We found the highest MO in extreme (i.e., low pH/high temperature) and aquatic environments, while the lowest MO was observed in communities associated with animal hosts, or the built/engineered environment. In addition, different metabolism subcategories were explored for their degree of metabolic overlap. For instance, overlap in nitrogen metabolism was among the lowest in Animal and Engineered ecosystems, while the most was in species from the Built environment. Together, we present a metric that utilizes whole genome information to explore overlapping niches of microbes. This provides a detailed picture of potential metabolic competition and cooperation between species present in an ecosystem, indicates the main substrate types sustaining the community and serves as a valuable tool to generate hypotheses for future research.

scholarly journals Pathway-based and phylogenetically adjusted quantification of metabolic interaction between microbial species

2020 ◽  
Author(s):  
Tony J. Lam ◽  
Moses Stamboulian ◽  
Wontack Han ◽  
Yuzhen Ye
Keyword(s):  
Microbial Communities ◽  
Bacterial Species ◽  
Microbial Interactions ◽  
Phylogenetic Distance ◽  
Phylogenetic Relatedness ◽  
Bacterial Interactions ◽  
Competition And Cooperation ◽  
Microbial Species ◽  
Metabolic Interactions ◽  
Genome Scale

AbstractMicrobial community members exhibit various forms of interactions. Taking advantage of the increasing availability of microbiome data, many computational approaches have been developed to infer bacterial interactions from the co-occurrence of microbes across diverse microbial communities. Additionally, the introduction of genome-scale metabolic models have also enabled the inference of metabolic interactions, such as competition and cooperation, between bacterial species. By nature, phylogenetically similar microbial species are likely to share common functional profiles or biological pathways due to their genomics similarity. Without properly factoring out the phylogenetic relationship, any estimation of the competition and cooperation based on functional/pathway profiles may bias downstream applications.To address these challenges, we developed a novel approach for estimating the competition and complementarity indices for a pair of microbial species, adjusted by their phylogenetic distance. An automated pipeline, PhyloMint, was implemented to construct competition and complementarity indices from genome scale metabolic models derived from microbial genomes. Application of our pipeline to 2,815 human-gut bacteria showed high correlation between phylogenetic distance and metabolic competition/cooperation indices among bacteria. Using a discretization approach, we were able to detect pairs of bacterial species with cooperation scores significantly higher than the average pairs of bacterial species with similar phylogenetic distances. A network community analysis of high metabolic cooperation but low competition reveals distinct modules of bacterial interactions. Our results suggest that niche differentiation plays a dominant role in microbial interactions, while habitat filtering also plays a role among certain clades of bacterial species.Author summaryMicrobial communities, also known as microbiomes, are formed through the interactions of various microbial species. Utilizing genomic sequencing, it is possible to infer the compositional make-up of communities as well as predict their metabolic interactions. However, because some species are more similarly related to each other, while others are more distantly related, one cannot directly compare metabolic relationships without first accounting for their phylogenetic relatedness. Here we developed a computational pipeline which predicts complimentary and competitive metabolic relationships between bacterial species, while normalizing for their phylogenetic relatedness. Our results show that phylogenetic distances are correlated with metabolic interactions, and factoring out such relationships can help better understand microbial interactions which drive community formation.

scholarly journals Fast automated reconstruction of genome-scale metabolic models for microbial species and communities

2018 ◽  
Author(s):  
Daniel Machado ◽  
Sergej Andrejev ◽  
Melanie Tramontano ◽  
Kiran Raosaheb Patil
Keyword(s):  
Microbial Communities ◽  
Single Species ◽  
Model Organisms ◽  
Universal Model ◽  
Microbial Species ◽  
Scale Models ◽  
Metabolic Models ◽  
User Friendly ◽  
Genome Scale ◽  
Automated Tool

AbstractGenome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism and model-guided re-engineering. Recent applications of metabolic models have also demonstrated their usefulness in unraveling cross-feeding within microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging far behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual cura-tion required to obtain good quality models and thus physiologically meaningful simulation results. Here, we present an automated tool – CarveMe – for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation-ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We build reconstructions for two model organisms, Escherichia coli and Bacillus subtillis, as well as a collection of human gut bacteria, and show that CarveMe models perform similarly to manually curated models in reproducing experimental phenotypes. Finally, we demonstrate the scalability of CarveMe through reconstructing 5587 bacterial models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.

scholarly journals Synergies of Systems Biology and Synthetic Biology in Human Microbiome Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Bouchra Ezzamouri ◽  
Saeed Shoaie ◽  
Rodrigo Ledesma-Amaro
Keyword(s):  
Synthetic Biology ◽  
Microbial Communities ◽  
System Biology ◽  
Large Scale ◽  
Human Microbiome ◽  
Host Responses ◽  
Future Research ◽  
Host Interactions ◽  
Health And Disease ◽  
Genome Scale

A number of studies have shown that the microbial communities of the human body are integral for the maintenance of human health. Advances in next-generation sequencing have enabled rapid and large-scale quantification of the composition of microbial communities in health and disease. Microorganisms mediate diverse host responses including metabolic pathways and immune responses. Using a system biology approach to further understand the underlying alterations of the microbiota in physiological and pathological states can help reveal potential novel therapeutic and diagnostic interventions within the field of synthetic biology. Tools such as biosensors, memory arrays, and engineered bacteria can rewire the microbiome environment. In this article, we review the computational tools used to study microbiome communities and the current limitations of these methods. We evaluate how genome-scale metabolic models (GEMs) can advance our understanding of the microbe–microbe and microbe–host interactions. Moreover, we present how synergies between these system biology approaches and synthetic biology can be harnessed in human microbiome studies to improve future therapeutics and diagnostics and highlight important knowledge gaps for future research in these rapidly evolving fields.

scholarly journals Relationships among intramammary health, udder and teat characteristics, and productivity of extensively managed ewes

2021 ◽  
Vol 99 (4) ◽  
Author(s):  
Ryan M Knuth ◽  
Whitney C Stewart ◽  
Joshua B Taylor ◽  
Bledar Bisha ◽  
Carl J Yeoman ◽  
...  
Keyword(s):  
Future Research ◽  
Morphometric Traits ◽  
Maldi Tof Ms ◽  
Microbial Species ◽  
Maldi Tof ◽  
Microbial Invasion ◽  
Lactation Stage ◽  
The Impact ◽  
Culture Positive ◽  
Tof Ms

Abstract Mastitis is an economically important disease and its subclinical state is difficult to diagnose, which makes mitigation more challenging. The objectives of this study were to screen clinically healthy ewes in order to 1) identify cultivable microbial species in milk, 2) evaluate somatic cell count (SCC) thresholds associated with intramammary infection, and 3) estimate relationships between udder and teat morphometric traits, SCC, and ewe productivity. Milk was collected from two flocks in early (<5 d) and peak (30 to 45 d) lactation to quantify SCC (n = 530) and numerate cultivable microbial species by culture-based isolation followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS; n = 243) identification. Within flock and lactation stage, 11% to 74% (mean = 36%) of samples were culture positive. More than 50 unique identifications were classified by MALDI-TOF MS analysis, and Bacillus licheniformis (18% to 27%), Micrococcus flavus (25%), Bacillus amyloliquefaciens (7% to 18%), and Staphylococcus epidermidis (26%) were among the most common within flock and across lactation stage. Optimum SCC thresholds to identify culture-positive samples ranged from 175 × 103 to 1,675 × 103 cells/mL. Ewe productivity was assessed as total 120-d adjusted litter weight (LW120) and analyzed within flock with breed, parity, year, and the linear covariate of log10 SCC (LSCC) at early or peak lactation. Although dependent on lactation stage and year, each 1-unit increase in LSCC (e.g., an increase in SCC from 100 × 103 to 1,000 × 103 cells/mL) was predicted to decrease LW120 between 9.5 and 16.1 kg when significant. Udder and teat traits included udder circumference, teat length, teat placement, and degree of separation of the udder halves. Correlations between traits were generally low to moderate within and across lactation stage and most were not consistently predictive of ewe LSCC. Overall, the frequencies of bacteria-positive milk samples indicated that subclinical mastitis (SCM) is common in these flocks and can impact ewe productivity. Therefore, future research is warranted to investigate pathways and timing of microbial invasion, genomic regions associated with susceptibility, and husbandry to mitigate the impact of SCM in extensively managed ewes.

Simulated Herbicide Spray Retention on Floating Aquatic Plants as Affected by Carrier Volume and Adjuvant Type

2021 ◽  
pp. 1-23
Author(s):  
Benjamin P. Sperry ◽  
Christopher R. Mudge ◽  
Kurt D. Getsinger
Keyword(s):  
Spray Deposition ◽  
Foliar Spray ◽  
Future Research ◽  
Plant Management ◽  
Aquatic Environments ◽  
Leaf Architecture ◽  
Mesocosm Experiments ◽  
Pesticide Load ◽  
Giant Salvinia ◽  
Carrier Volume

Foliar delivery of herbicides is a common means for plant management in aquatic environments. Though this technique is decades old, little is known about vegetative spray retention relative to this application method. A more complete understanding of maximizing herbicide retention could lead to improved plant management while simultaneously decreasing pesticide load in aquatic environments. Therefore, outdoor mesocosm experiments were conducted in 2020 to evaluate the effect of adjuvant type on foliar spray retention in waterhyacinth. Additionally, the effect of carrier volume on spray retention in waterhyacinth, waterlettuce, and giant salvinia was documented. Spray deposition did not differ among the nine adjuvants tested; however, spray retention was reduced 6 to 11% when an adjuvant was excluded from the spray solution. The effect of carrier volume on spray retention in waterhyacinth, waterlettuce, and giant salvinia was also investigated. Decreases in spray retention was most sensitive to increased carrier volume in waterhyacinth, followed by giant salvinia and waterlettuce. Among species, spray retention potential, as determined by intercept estimates, was greatest in waterlettuce and giant salvinia regardless of carrier volume. Asymptotes estimates for waterhyacinth, waterlettuce, and giant salvinia were 33, 46, and 79% spray retention, respectively. In other words, spray retention was the lowest and remained relatively constant at these values for the high carrier volumes tested (935 and 1870 L ha−1), which were likely due to the presence of pubescence on leaves and flatter leaf architecture represented by waterlettuce and giant salvinia compared to the glabrous vertical leaves of waterhyacinth. Future research will evaluate these concepts under field conditions.

scholarly journals The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities

2018 ◽  
Vol 35 (13) ◽  
pp. 2332-2334 ◽  
Author(s):  
Federico Baldini ◽  
Almut Heinken ◽  
Laurent Heirendt ◽  
Stefania Magnusdottir ◽  
Ronan M T Fleming ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Microbial Interactions ◽  
Microbial Genome ◽  
Metagenomic Data ◽  
Metabolic Interactions ◽  
Constraint Based Modeling ◽  
Genome Scale

Abstract Motivation The application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes. Results To address this gap, we created a comprehensive toolbox to model (i) microbe–microbe and host–microbe metabolic interactions, and (ii) microbial communities using microbial genome-scale metabolic reconstructions and metagenomic data. The Microbiome Modeling Toolbox extends the functionality of the constraint-based reconstruction and analysis toolbox. Availability and implementation The Microbiome Modeling Toolbox and the tutorials at https://git.io/microbiomeModelingToolbox.

scholarly journals A Microbial Perspective on the Grand Challenges in Comparative Animal Physiology

mSystems ◽  
2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Kevin D. Kohl
Keyword(s):  
Microbial Communities ◽  
Vertical Integration ◽  
Temporal Integration ◽  
Data Sets ◽  
Grand Challenges ◽  
Animal Physiology ◽  
Physiological Processes ◽  
Microbe Interactions ◽  
Animal Hosts ◽  
Host Microbe Interactions

ABSTRACTInteractions with microbial communities can have profound influences on animal physiology, thereby impacting animal performance and fitness. Therefore, it is important to understand the diversity and nature of host-microbe interactions in various animal groups (invertebrates, fish, amphibians, reptiles, birds, and mammals). In this perspective, I discuss how the field of host-microbe interactions can be used to address topics that have been identified as grand challenges in comparative animal physiology: (i) horizontal integration of physiological processes across organisms, (ii) vertical integration of physiological processes across organizational levels within organisms, and (iii) temporal integration of physiological processes during evolutionary change. Addressing these challenges will require the use of a variety of animal models and the development of systems approaches that can integrate large, multiomic data sets from both microbial communities and animal hosts. Integrating host-microbe interactions into the established field of comparative physiology represents an exciting frontier for both fields.

THE INTERACTIONS OF VERTEBRATES AND INVERTEBRATES IN PEATLANDS AND MARSHES

1987 ◽  
Vol 119 (S140) ◽  
pp. 15-30 ◽  
Author(s):  
Henry R. Murkin ◽  
Bruce D.J. Batt
Keyword(s):  
Current Knowledge ◽  
Life Cycles ◽  
Future Research ◽  
Aquatic Environments ◽  
Research Needs ◽  
Avian Community ◽  
Wide Range ◽  
Dead Plant ◽  
Living Organisms ◽  
And Function

AbstractThis paper reviews the interactions of vertebrates and invertebrates in peatlands and marshes to assess current knowledge and future research needs. Living organisms may interact through a number of direct trophic and nutrient pathways and a variety of non-trophic, habitat-dependent relationships. Freshwater marshes and peatlands are dynamic aquatic environments and organisms that occupy these areas must be adapted to a wide range of environmental conditions. The avian community illustrates the main interactions of invertebrates and vertebrates in peatlands and marshes. Waterfowl, along with fish and furbearers, are the most economically important vertebrates using these habitats. Each of these groups has important trophic and habitat links to the invertebrates within wetlands.The most common interaction between vertebrates and invertebrates is the use of invertebrates as food by vertebrates. Few studies, however, have dealt with trophic dynamics or secondary production within wetlands. Waterfowl, fish, and many other wetland vertebrates, during all or part of their life cycles, regularly feed on invertebrates. Some invertebrates are vectors of disease and parasites to vertebrates. Vertebrates can directly affect the structural substrate that invertebrates depend on as habitat through consumption of macrophytes or through the use of living and dead plant material in the construction of houses and nests. Conversely, herbivorous invertebrates may directly affect the survival and distribution of macrophytes in wetlands. Macrophyte distribution, in turn, is an important factor in determining vertebrate use of wetlands. The general lack of both taxonomic and ecological information on invertebrates in wetlands is the main hindrance to future elucidation of vertebrate–invertebrate interactions in these environments. Development of invertebrate sampling techniques suitable for wetland habitats also is necessary. More specific research needs must be met to develop a better understanding of the structure and function of these dynamic systems.

scholarly journals Ontogenetic Differences in Dietary Fat Influence Microbiota Assembly in the Zebrafish Gut

mBio ◽  
2015 ◽  
Vol 6 (5) ◽  
Author(s):  
Sandi Wong ◽  
W. Zac Stephens ◽  
Adam R. Burns ◽  
Keaton Stagaman ◽  
Lawrence A. David ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Microbial Communities ◽  
Dietary Fat ◽  
Rrna Gene ◽  
Microbiota Composition ◽  
Ideal Model ◽  
Surrounding Environment ◽  
Animal Hosts ◽  
The Relationship ◽  
Gut Microbiota Composition

ABSTRACT Gut microbiota influence the development and physiology of their animal hosts, and these effects are determined in part by the composition of these microbial communities. Gut microbiota composition can be affected by introduction of microbes from the environment, changes in the gut habitat during development, and acute dietary alterations. However, little is known about the relationship between gut and environmental microbiotas or about how host development and dietary differences during development impact the assembly of gut microbiota. We sought to explore these relationships using zebrafish, an ideal model because they are constantly immersed in a defined environment and can be fed the same diet for their entire lives. We conducted a cross-sectional study in zebrafish raised on a high-fat, control, or low-fat diet and used bacterial 16S rRNA gene sequencing to survey microbial communities in the gut and external environment at different developmental ages. Gut and environmental microbiota compositions rapidly diverged following the initiation of feeding and became increasingly different as zebrafish grew under conditions of a constant diet. Different dietary fat levels were associated with distinct gut microbiota compositions at different ages. In addition to alterations in individual bacterial taxa, we identified putative assemblages of bacterial lineages that covaried in abundance as a function of age, diet, and location. These results reveal dynamic relationships between dietary fat levels and the microbial communities residing in the intestine and the surrounding environment during ontogenesis. IMPORTANCE The ability of gut microbiota to influence host health is determined in part by their composition. However, little is known about the relationship between gut and environmental microbiotas or about how ontogenetic differences in dietary fat impact gut microbiota composition. We addressed these gaps in knowledge using zebrafish, an ideal model organism because their environment can be thoroughly sampled and they can be fed the same diet for their entire lives. We found that microbial communities in the gut changed as zebrafish aged under conditions of a constant diet and became increasingly different from microbial communities in their surrounding environment. Further, we observed that the amount of fat in the diet had distinct age-specific effects on gut community assembly. These results reveal the complex relationships between microbial communities residing in the intestine and those in the surrounding environment and show that these relationships are shaped by dietary fat throughout the life of animal hosts.

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