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Scientific Reports Volume 12 ,Issue 1 ,2022-10-21
Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks
Min-Zhi Jiang 1 Hai-Zhen Zhu 2 Nan Zhou 2 Chang Liu 2 Cheng-Ying Jiang 2 Yulin Wang 1 Shuang-Jiang Liu 1 , 2 , 3
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Received 2022-5-26, accepted for publication 2022-10-21, Published 2022-10-21

Co-occurrence networks inferred from the abundance data of microbial communities are widely applied to predict microbial interactions. However, the high workloads of bacterial isolation and the complexity of the networks themselves constrained experimental demonstrations of the predicted microbial associations and interactions. Here, we integrate droplet microfluidics and bar-coding logistics for high-throughput bacterial isolation and cultivation from environmental samples, and experimentally investigate the relationships between taxon pairs inferred from microbial co-occurrence networks. We collected Potamogeton perfoliatus plants (including roots) and associated sediments from Beijing Olympic Park wetland. Droplets of series diluted homogenates of wetland samples were inoculated into 126 96-well plates containing R2A and TSB media. After 10 days of cultivation, 65 plates with > 30% wells showed microbial growth were selected for the inference of microbial co-occurrence networks. We cultivated 129 bacterial isolates belonging to 15 species that could represent the zero-level OTUs (Zotus) in the inferred co-occurrence networks. The co-cultivations of bacterial isolates corresponding to the prevalent Zotus pairs in networks were performed on agar plates and in broth. Results suggested that positively associated Zotu pairs in the co-occurrence network implied complicated relations including neutralism, competition, and mutualism, depending on bacterial isolate combination and cultivation time.


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1. Yulin Wang.State Key Laboratory of Microbial Technology, Shandong University, 266000, Qingdao, People’s Republic of China.wangyulin@sdu.edu.cn
2. Shuang-Jiang Liu.State Key Laboratory of Microbial Technology, Shandong University, 266000, Qingdao, People’s Republic of China;State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center (EMRC), Institute of Microbiology, Chinese Academy of Sciences, 100101, Beijing, People’s Republic of China;University of Chinese Academy of Sciences, 100049, Beijing, People’s Republic of China.liusj@sdu.edu.cn


Min-Zhi Jiang,Hai-Zhen Zhu,Nan Zhou,Chang Liu,Cheng-Ying Jiang,Yulin Wang,Shuang-Jiang Liu. Droplet microfluidics-based high-throughput bacterial cultivation for validation of taxon pairs in microbial co-occurrence networks. Scientific Reports ,Vol.12, Issue 1(2022)



[1] DJ LaneRapid-determination of 16s ribosomal-rna sequences for phylogenetic analysesProc. Natl. Acad. Sci. U. S. A.198582695569591985PNAS...82.6955L1:CAS:528:DyaL28XjtFalug
[2] 3D
[3] 3D2413450391288
[4] N Jagmann, B PhilippSpoT-mediated regulation and amino acid prototrophy are essential for pyocyanin production during parasitic growth of Pseudomonas aeruginosa in a co-culture model system with Aeromonas hydrophilaFront. Microbiol.20189761297209725915560
[5] A RamettePseudomonas protegens sp. nov., widespread plant-protecting bacteria producing the biocontrol compounds 2,4-diacetylphloroglucinol and pyoluteorinSyst. Appl. Microbiol.2011341801881:CAS:528:DC
[6] 2BC3MXkvVSrt7g
[7] 3D21392918
[8] C QuastThe SILVA ribosomal RNA gene database project: improved data processing and web-based toolsNucleic Acids Res.201341D5905961:CAS:528:DC
[9] 2BC38XhvV2ksb
[10] 2FN23193283
[11] N Jagmann, HP Brachvogel, B PhilippParasitic growth of Pseudomonas aeruginosa in co-culture with the chitinolytic bacterium Aeromonas hydrophilaEnviron. Microbiol.201012178718021:CAS:528:DC
[12] 2BC3cXptFOgsL4
[13] 3D20553557
[14] RJ Williams, A Howe, KS HofmockelDemonstrating microbial co-occurrence pattern analyses within and between ecosystemsFront. Microbiol.20145358251010654102878
[15] X WangNiche differentiation of comammox Nitrospira in the mudflat and reclaimed agricultural soils along the north branch of Yangtze river estuaryFront. Microbiol.20201133584582
[16] N Ribeck, RE LenskiModeling and quantifying frequency-dependent fitness in microbial populations with cross-feeding interactionsEvolution2015691313132025787308
[17] KN Tsai, SH Lin, WC Liu, DY Wang et al.Inferring microbial interaction network from microbiome data using RMN algorithmBMC Syst. Biol.2015954263379304560064
[18] ZD KurtzSparse and Compositionally robust inference of microbial ecological networksPLoS Comput. Biol.201511259509564423992
[19] SN Steinway, MB Biggs, TP Loughran, JA Papin et al.Inference of network dynamics and metabolic interactions in the gut microbiomePLoS Comput. Biol.2015112015PLSCB..11E4338S261022874478025
[20] K Faust, J RaesMicrobial interactions: from networks to modelsNat. Rev. Microbiol.2012105385501:CAS:528:DC
[21] 2BC38XhtVehsL3M22796884
[22] WA WaltersPrimerProspector: de novo design and taxonomic analysis of barcoded polymerase chain reaction primersBioinformatics201127115911611:CAS:528:DC
[23] 2BC3MXksFKltLk
[24] 3D213498623072552
[25] JY ZhangNRT1.1B is associated with root microbiota composition and nitrogen use in field-grown riceNat. Biotechnol.2019376766841:CAS:528:DC
[26] 2BC1MXos1SktLs
[27] 3D31036930
[28] Ings, T. C. & Hawes, J. E. The history of ecological networks (ed. Dáttilo, W. & Rico-Gray, V) 15–28 (Springer, 2018).
[29] K ZhalninaDynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assemblyNat. Microbiol.201834704801:CAS:528:DC
[30] 2BC1cXlt1Okt70
[31] 3D29556109
[32] Y ChenParallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platformsIMeta20221e1
[33] C LiuEnlightening the taxonomy darkness of human gut microbiomes with a cultured biobankMicrobiome202191191:CAS:528:DC
[34] 2BB38XjsVegsbs
[35] 3D340207148140505
[36] Yi RenMajorbio Cloud: A one-stop, comprehensive bioinformatic platform for multiomics analysesIMeta20221e12
[37] D ForsterLake ecosystem robustness and resilience inferred from a climate-stressed protistan Plankton networkMicroorganisms202195491:CAS:528:DC
[38] 2BB3MXhvFygsbzF338009278001626
[39] GJ Brandon-Mong, GTW Shaw, WH Chen, CC Chen et al.A network approach to investigating the key microbes and stability of gut microbial communities in a mouse neuropathic pain modelBMC Microbiol.2020202951:CAS:528:DC
[40] 2BB3cXitVertr3M329986817525972
[41] P Frey-KlettBacterial-fungal interactions: hyphens between agricultural, clinical, environmental, and food microbiologistsMicrobiol. Mol. Biol. Rev.2011755836091:STN:280:DC
[42] 2BC38
[43] 2Fjs1Sntw
[44] 3D
[45] 3D221269953232736
[46] E Bairey, ED Kelsic, R KishonyHigh-order species interactions shape ecosystem diversityNat. Commun.20167122852016NatCo...712285B1:CAS:528:DC
[47] 2BC28Xhtlaju77E274816254974637
[48] Bastian, M., Heymann, S. & Jacomy, M. in Proceedings of the third international conference on Weblogs and Social Media, ICWSM 2009, San Jose, California, USA, May 17–20, 2009.
[49] J Tackmann, JF Matias Rodrigues, C von MeringRapid inference of direct interactions in large-scale ecological networks from heterogeneous microbial sequencing dataCell Syst.20199286296.e2881:CAS:528:DC
[50] 2BC1MXhvVOlsb3I31542415
[51] NT BaxterDynamics of human gut microbiota and short-chain fatty acids in response to dietary interventions with three fermentable fibersmBio201910e0251802566
[52] Batagelj, V. & Mrvar, Lecture notes in computer science (Jünger, M. & Mutzel, P.) 77–103 (Springer, 2003).
[53] JJ WernerBacterial community structures are unique and resilient in full-scale bioenergy systemsProc. Natl. Acad. Sci. U. S. A.2011108415841632011PNAS..108.4158W1:CAS:528:DC
[54] 2BC3MXjsF2ntLg
[55] 3D213681153053989
[56] CY JiangHigh-throughput single-cell cultivation on microfluidic streak platesAppl. Environ. Microbiol.201682221022182016ApEnM..82.2210J1:CAS:528:DC
[57] 2BC28Xht1Gns7fP268502944807504
[58] J ZhangHigh-throughput cultivation and identification of bacteria from the plant root microbiotaNat. Protoc.20211698810121:CAS:528:DC
[59] 2BB3MXht1OlsL8
[60] 3D33442053
[61] R Guimerà, LA Nunes AmaralFunctional cartography of complex metabolic networksNature20054338959002005Natur.433..895G157293482175124
[62] T WoykeSymbiosis insights through metagenomic analysis of a microbial consortiumNature20064439509552006Natur.443..950W1:CAS:528:DC
[63] 2BD28XhtFaksrvN16980956
[64] M MiliciCo-occurrence analysis of microbial taxa in the Atlantic ocean reveals high connectivity in the free-living bacterioplanktonFront. Microbiol.20167649271999704858663
[65] X LiuDistinct co-occurrence relationships and assembly processes of active methane-oxidizing bacterial communities between paddy and natural wetlands of northeast ChinaFront. Microbiol.202213351540548826055
[66] R Guimera, LA AmaralCartography of complex networks: modules and universal rolesJ. Stat. Mech.20052005nihpa3557318159217
[67] J HalfvarsonDynamics of the human gut microbiome in inflammatory bowel diseaseNat. Microbiol.20172170041:CAS:528:DC
[68] 2BC2sXkvFyqt7s
[69] 3D281918845319707
[70] A Barberán, ST Bates, EO Casamayor, N Fierer et al.Using network analysis to explore co-occurrence patterns in soil microbial communitiesISME J2012634335121900968
[71] J ZhouFunctional molecular ecological networksMBio20101e0011000169
[72] M Hamady, R KnightMicrobial community profiling for human microbiome projects: Tools, techniques, and challengesGenome Res.200919114111521:CAS:528:DC
[73] 2BD1MXosVCktL8
[74] 3D193837633776646
[75] MR Green, J SambrookConstructing a standard curve for real-time polymerase chain reaction (PCR) experimentsCold Spring Harb. Protoc.201810.1101/pdb.prot09502630275081
[76] JJ QinA human gut microbial gene catalogue established by metagenomic sequencingNature201046459651:CAS:528:DC
[77] 2BC3cXislahsLc
[78] 3D202036033779803
[79] M Goberna, M VerdúCautionary notes on the use of co-occurrence networks in soil ecologySoil Biol. Biochem.20221661:CAS:528:DC
[80] 2BB38XhtVehtb0
[81] 3D
[82] M Szoboszlay, CC TebbeHidden heterogeneity and co-occurrence networks of soil prokaryotic communities revealed at the scale of individual soil aggregatesMicrobiologyopen2021101:CAS:528:DC
[83] 2BB3MXnt1Klsr0
[84] 3D33369241
[85] L WangFacial skin microbiota-mediated host response to pollution stress revealed by microbiome networks of individualmSystems20216e003192134313461
[86] SG TringeComparative metagenomics of microbial communitiesScience20053085545572005Sci...308..554T1:CAS:528:DC
[87] 2BD2MXjtlOjt7c
[88] 3D15845853
[89] DJ Reasoner, EE GeldreichA new medium for the enumeration and subculture of bacteria from potable waterAppl. Environ. Microbiol.198549171985ApEnM..49....1R1:CAS:528:DyaL2MXhsVGltr8
[90] 3D3883894238333
[91] W XunSpecialized metabolic functions of keystone taxa sustain soil microbiome stabilityMicrobiome20219351:CAS:528:DC
[92] 2BB38XjsVemtrw
[93] 3D335178927849160
[94] RC EdgarSearch and clustering orders of magnitude faster than BLASTBioinformatics201026246024611:CAS:528:DC
[95] 2BC3cXht1WhtbzM20709691
[96] Y BaiFunctional overlap of the Arabidopsis leaf and root microbiotaNature20155283643692015Natur.528..364B1:CAS:528:DC
[97] 2BC2MXhvFemsbjL26633631
[98] R Levy, E BorensteinMetabolic modeling of species interaction in the human microbiome elucidates community-level assembly rulesProc. Natl. Acad. Sci. U. S. A.201311012804128092013PNAS..11012804L1:CAS:528:DC
[99] 2BC3sXht12htLfF238584633732988
[100] P GaoInfluences of seasonal monsoons on the taxonomic composition and diversity of bacterial community in the eastern tropical Indian OceanFront. Microbiol.20201133574800
[101] R LiuBulk and active sediment prokaryotic communities in the mariana and mussau trenchesFront. Microbiol.2020111521327654447381213
[102] F LiuCable bacteria extend the impacts of elevated dissolved oxygen into anoxic sedimentsISME J.20211515511563334794928114917
[103] MM VillaInterindividual variation in dietary carbohydrate metabolism by gut bacteria revealed with droplet microfluidic culturemSystems20205e0081900864
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