Formation, characterization and modeling of emergent synthetic microbial communities

Computational and Structural Biotechnology Journal - Tập 19 - Trang 1917-1927 - 2021
Jia Wang1, Dana L. Carper1, Leah H. Burdick1, Him K. Shrestha1,2, Manasa R. Appidi1,2, Paul E. Abraham1, Collin M. Timm1, Robert L. Hettich1, Dale A. Pelletier1, Mitchel J. Doktycz1
1Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
2Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, USA

Tóm tắt

Từ khóa


Tài liệu tham khảo

Fisher, 2014, Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression, PLoS ONE, 9, 10.1371/journal.pone.0102451

Harcombe William, 2014, Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics, Cell Rep, 7, 1104, 10.1016/j.celrep.2014.03.070

Hanemaaijer, 2015, Systems modeling approaches for microbial community studies: from metagenomics to inference of the community structure, Front Microbiol, 6, 10.3389/fmicb.2015.00213

Wright, 2016, Inhibitory interactions promote frequent bistability among competing bacteria, Nat Commun, 7, 11274, 10.1038/ncomms11274

Khandelwal, 2013, Community flux balance analysis for microbial consortia at balanced growth, PLoS ONE, 8, 10.1371/journal.pone.0064567

Gilmore, 2019, Top-down enrichment guides in formation of synthetic microbial consortia for biomass degradation, ACS Synth Biol, 8, 2174, 10.1021/acssynbio.9b00271

Brown, 2012, Twenty-one genome sequences from Pseudomonas species and 19 genome sequences from diverse bacteria Isolated from the rhizosphere and endosphere of Populus deltoides, J Bacteriol, 194, 5991, 10.1128/JB.01243-12

Kotoky, 2020, Difference in the rhizosphere microbiome of melia azedarach during removal of benzo(a)pyrene from cadmium co-contaminated soil, Chemosphere, 258, 10.1016/j.chemosphere.2020.127175

Yin, 2020, The rhizosphere microbiome of Mikania micrantha provides insight into adaptation and invasion, Front Microbiol, 11, 1462, 10.3389/fmicb.2020.01462

de la Torre-Hernández, 2020, Composition, structure, and PGPR traits of the rhizospheric bacterial communities associated with wild and cultivated Echinocactus platyacanthus and Neobuxbaumia polylopha, Front Microbiol, 11, 1424, 10.3389/fmicb.2020.01424

Timm, 2015, Metabolic functions of Pseudomonas fluorescens strains from Populus deltoides depend on rhizosphere or endosphere isolation compartment, Front Microbiol, 6, 1118, 10.3389/fmicb.2015.01118

Wagner, 2016, Host genotype and age shape the leaf and root microbiomes of a wild perennial plant, Nat Commun, 7, 12151, 10.1038/ncomms12151

Pent, 2017, Bacterial communities in boreal forest mushrooms are shaped both by soil parameters and host identity, Front Microbiol, 8, 836, 10.3389/fmicb.2017.00836

Pii, 2015, Microbial interactions in the rhizosphere: Beneficial influences of plant growth-promoting rhizobacteria on nutrient acquisition process. A review, Biol Fertil Soils, 51, 403, 10.1007/s00374-015-0996-1

Timm, 2018, Abiotic stresses shift belowground Populus-associated bacteria toward a core stress microbiome, mSystems, 3, e00070, 10.1128/msystems.00070-17

Zelezniak, 2015, Metabolic dependencies drive species co-occurrence in diverse microbial communities, PNAS, 112, 6449, 10.1073/pnas.1421834112

Tan, 2015, Unraveling interactions in microbial communities-from co-cultures to microbiomes, J Microbiol, 53, 295, 10.1007/s12275-015-5060-1

De Roy, 2014, Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities, Environ Microbiol, 16, 1472, 10.1111/1462-2920.12343

Großkopf, 2014, Synthetic microbial communities, Curr Opin Microbiol, 18, 72, 10.1016/j.mib.2014.02.002

Qu, 2020, Rhizosphere microbiome assembly and its impact on plant growth, J Agric Food Chem, 68, 5024, 10.1021/acs.jafc.0c00073

Chodkowski, 2017, A synthetic community system for probing microbial interactions driven by exometabolites, mSystems, 2, e00129, 10.1128/mSystems.00129-17

Goldford, 2018, Emergent simplicity in microbial community assembly, Science, 361, 469, 10.1126/science.aat1168

Bauer, 2018, From network analysis to functional metabolic modeling of the human gut microbiota, mSystems, 3, e00209, 10.1128/mSystems.00209-17

Dahabieh, 2020, Multimodal microorganism development: Integrating top-down biological engineering with bottom-up rational design, Trends Biotechnol, 38, 241, 10.1016/j.tibtech.2019.09.006

Peng, 2016, Microbial communities for bioprocessing: lessons learned from nature, Curr Opin Chem Eng, 14, 103, 10.1016/j.coche.2016.09.003

Elzinga, 2019, The use of defined microbial communities to model host-microbe interactions in the human gut, Microbiol Mol Biol Rev, 83, e00054, 10.1128/MMBR.00054-18

Liu, 2020, Interaction variability shapes succession of synthetic microbial ecosystems, Nat Commun, 11, 309, 10.1038/s41467-019-13986-6

Guo, 2016, The contribution of high-order metabolic interactions to the global activity of a four-species microbial community, PLOS Comput Bio, 12

Venturelli, 2018, Deciphering microbial interactions in synthetic human gut microbiome communities, Mol Syst Biol, 14, 10.15252/msb.20178157

Rodríguez Amor, 2019, Bottom-up approaches to synthetic cooperation in microbial communities, Life, 9, 22, 10.3390/life9010022

Faust, 2012, Microbial interactions: From networks to models, Nat Rev Microbiol, 10, 538, 10.1038/nrmicro2832

Xu, 2019, Modeling microbial communities from atrazine contaminated soils promotes the development of biostimulation solutions, ISME J, 13, 494, 10.1038/s41396-018-0288-5

Friedman, 2017, Community structure follows simple assembly rules in microbial microcosms, Nat Ecol Evol, 1, 0109, 10.1038/s41559-017-0109

Stolyar, 2007, Metabolic modeling of a mutualistic microbial community, Mol Syst Biol, 3, 92, 10.1038/msb4100131

Ye, 2014, Metabolic model reconstruction and analysis of an artificial microbial ecosystem for vitamin C production, J Biotechnol, 182–183, 61, 10.1016/j.jbiotec.2014.04.027

Ravikrishnan, 2020, Investigating metabolic interactions in a microbial co-culture through integrated modelling and experiments, Comput Struct Biotechnol J, 18, 1249, 10.1016/j.csbj.2020.03.019

Chang, 2020, Artificially selecting bacterial communities using propagule strategies, Evolution, 74, 2392, 10.1111/evo.14092

Schaefer, 2013, LuxR- and LuxI-type quorum-sensing circuits are prevalent in members of the Populus deltoides microbiome, Appl Environ Microbiol, 79, 5745, 10.1128/AEM.01417-13

Levy, 2018, Genomic features of bacterial adaptation toplants, Nat Genet, 50, 138, 10.1038/s41588-017-0012-9

Hasim, 2018, Elucidating duramycin’s bacterial selectivity and mode of action on the bacterial cell envelope, Front Microbiol, 9, 219, 10.3389/fmicb.2018.00219

Neidhardt, 1974, Culture medium for enterobacteria, J Bacteriol, 119, 736, 10.1128/jb.119.3.736-747.1974

Reasoner, 1985, A new medium for the enumeration and subculture of bacteria from potable water, Appl Environ Microbiol, 49, 1, 10.1128/aem.49.1.1-7.1985

Cregger, 2018, The Populus holobiont: Dissecting the effects of plant niches and genotype on the microbiome, Microbiome, 6, 31, 10.1186/s40168-018-0413-8

Rognes, 2016, VSEARCH: a versatile open source tool for metagenomics, PeerJ, 4, 10.7717/peerj.2584

Martin, 2011, Cutadapt removes adapter sequences from high-throughput sequencing reads, EMBnet J, 17, 10, 10.14806/ej.17.1.200

Bolyen, 2019, Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2, Nat Biotechnol, 37, 852, 10.1038/s41587-019-0209-9

Callahan, 2016, DADA2: High-resolution sample inference from Illumina amplicon data, Nat Methods, 13, 581, 10.1038/nmeth.3869

Jagannath, 2010, Influence of competing metabolic processes on the molecular weight of hyaluronic acid synthesized by Streptococcus zooepidemicus, Biochem Eng J, 48, 148, 10.1016/j.bej.2009.09.003

Shiroda, 2014, RpoS impacts the lag phase of Salmonella enterica during osmotic stress, FEMS Microbiol Lett, 357, 195

Arkin, 2018, KBase: The United States department of energy systems biology knowledgebase, Nat Biotechnol, 36, 566, 10.1038/nbt.4163

Henry, 2016, Microbial community metabolic modeling: a community data-driven network reconstruction, J Cell Physiol, 231, 2339, 10.1002/jcp.25428

Aziz, 2008, The RAST server: rapid annotations using subsystems technology, BMC Genom, 9, 75, 10.1186/1471-2164-9-75

Overbeek, 2014, The SEED and the rapid annotation of microbial genomes using subsystems technology (RAST), Nucleic Acids Res, 42, D206, 10.1093/nar/gkt1226

Brettin, 2015, RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes, Sci Rep, 5, 8365, 10.1038/srep08365

Batth, 2019, Protein aggregation capture on microparticles enables multipurpose proteomics sample preparation, Mol Cell Proteom, 18, 1027, 10.1074/mcp.TIR118.001270

Eng, 1994, An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database, J Am Soc Mass Spectrom, 5, 976, 10.1016/1044-0305(94)80016-2

Käll, 2007, Semi-supervised learning for peptide identification from shotgun proteomics datasets, Nat Methods, 4, 923, 10.1038/nmeth1113

Polpitiya, 2008, DAnTE: a statistical tool for quantitative analysis of -omics data, Bioinformatics, 24, 1556, 10.1093/bioinformatics/btn217

Kleiner, 2017, Assessing species biomass contributions in microbial communities via metaproteomics, Nat Commun, 8, 1558, 10.1038/s41467-017-01544-x

Gottel, 2011, Distinct microbial communities within the endosphere and rhizosphere of Populus deltoides roots across contrasting soil types, Appl Environ Microbiol, 77, 5934, 10.1128/AEM.05255-11

Germerodt, 2016, Pervasive selection for cooperative cross-feeding in bacterial communities, PLOS Comput Biol, 12, 10.1371/journal.pcbi.1004986

Pollock, 2018, The madness of microbiome: attempting to find consensus “best practice” for 16S microbiome studies, Appl Environ Microbiol, 84, e02627, 10.1128/AEM.02627-17

Sipos, 2007, Effect of primer mismatch, annealing temperature and PCR cycle number on 16S rRNA gene-targetting bacterial community analysis, FEMS Microbiol Ecol, 60, 341, 10.1111/j.1574-6941.2007.00283.x

Campanaro, 2018, Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies, Sci Rep, 8, 1926, 10.1038/s41598-018-20414-0

Neurohr, 2020, Relevance and regulation of cell density, Trends Cell Biol, 30, 213, 10.1016/j.tcb.2019.12.006

Milo, 2013, What is the total number of protein molecules per cell volume? A call to rethink some published values, BioEssays, 35, 1050, 10.1002/bies.201300066

Smith, 2015, Dietary input of microbes and host genetic variation shape among-population differences in stickleback gut microbiota, ISME J, 9, 2515, 10.1038/ismej.2015.64

Saxer, 2009, Spatial structure leads to ecological breakdown and loss of diversity, Proc R Soc B Biol Sci, 276, 2065, 10.1098/rspb.2008.1827

Benomar, 2015, Nutritional stress induces exchange of cell material and energetic coupling between bacterial species, Nat Commun, 6, 6283, 10.1038/ncomms7283

Zengler, 2018, The social network of microorganisms — how auxotrophies shape complex communities, Nat Rev Microbiol, 16, 383, 10.1038/s41579-018-0004-5

Calatayud, 2020, Positive associations among rare species and their persistence in ecological assemblages, Nat Ecol Evol, 4, 40, 10.1038/s41559-019-1053-5

Orth, 2010, What is flux balance analysis?, Nat Biotechnol, 28, 245, 10.1038/nbt.1614

Bertrand, 2019, Lag phase is a dynamic, organized, adaptive, and evolvable period that prepares bacteria for cell division, J Bacteriol, 201, e00697, 10.1128/JB.00697-18

Lee, 2016, Comparative analysis of bacterial diversity in the rhizosphere of tomato by culture-dependent and-independent approaches, J Microbiol, 54, 823, 10.1007/s12275-016-6410-3

Kim, 2017, Effects of minimal media vs. complex media on the metabolite profiles of Escherichia coli and Saccharomyces cerevisiae, Process Biochem, 57, 64, 10.1016/j.procbio.2017.04.003

Whitham, 2003, Community and ecosystem genetics: a consequence of the extended phenotype, Ecology, 84, 559, 10.1890/0012-9658(2003)084[0559:CAEGAC]2.0.CO;2

Langenheder, 2012, Role of functionally dominant species in varying environmental regimes: evidence for the performance-enhancing effect of biodiversity, BMC Ecol, 12, 14, 10.1186/1472-6785-12-14

Abreu, 2019, Mortality causes universal changes in microbial community composition, Nat Commun, 10, 2120, 10.1038/s41467-019-09925-0

Concepción-Acevedo, 2015, Malthusian parameters as estimators of the fitness of microbes: a cautionary tale about the low sede of high throughput, PLoS ONE, 10, 10.1371/journal.pone.0126915

Pekkonen, 2013, Resource availability and competition shape the evolution of survival and growth ability in a bacterial community, PLoS ONE, 8, 10.1371/journal.pone.0076471

Bittleston, 2020, Context-dependent dynamics lead to the assembly of functionally distinct microbial communities, Nat Commun, 11, 1440, 10.1038/s41467-020-15169-0

Lipson, 2015, The complex relationship between microbial growth rate and yield and its implications for ecosystem processes, Front Microbiol, 6, 615, 10.3389/fmicb.2015.00615

Zarecki, 2014, A novel nutritional predictor links microbial fastidiousness with lowered ubiquity, growth rate, and cooperativeness, PLoS Comput Biol, 10, 10.1371/journal.pcbi.1003726

Goelzer, 2011, Bacterial growth rate reflects a bottleneck in resource allocation, Biochim Biophys Acta Gen Subj, 1810, 978, 10.1016/j.bbagen.2011.05.014

Franzosa, 2015, Sequencing and beyond: integrating molecular 'omics' for microbial community profiling, Nat Rev Microbiol, 13, 360, 10.1038/nrmicro3451

Zomorrodi, 2016, Synthetic ecology of microbes: mathematical models and applications, J Mol Biol, 428, 837, 10.1016/j.jmb.2015.10.019

Sousa, 2017, Evolution of commensal bacteria in the intestinal tract of mice, Curr Opin Microbiol, 38, 114, 10.1016/j.mib.2017.05.007

Joseph, 2020, Compositional lotka-volterra describes microbial dynamics in the simplex, PLoS Comput Biol, 16, 10.1371/journal.pcbi.1007917

Song, 2017, Bacterial strategies along nutrient and time gradients, revealed by metagenomic analysis of laboratory microcosms, FEMS Microbiol Ecol, 93, 10.1093/femsec/fix114

Widder, 2016, Challenges in microbial ecology: building predictive understanding of community function and dynamics, ISME J, 10, 2557, 10.1038/ismej.2016.45

Louca, 2015, Calibration and analysis of genome-based models for microbial ecology, eLife, 4, 10.7554/eLife.08208

Cardona, 2016, Network-based metabolic analysis and microbial community modeling, Curr Opin Microbiol, 31, 124, 10.1016/j.mib.2016.03.008

Bae, 2004, Occurrence and significance of Bacillus thuringiensis on wine grapes, Int J Food Microbiol, 94, 301, 10.1016/j.ijfoodmicro.2004.01.013