Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies

Bingdi Liu , Lin Zhang , Jason H. Knouft , Fangqiong Ling

Front. Environ. Sci. Eng. ›› 2022, Vol. 16 ›› Issue (5) : 64

PDF (8900KB)
Front. Environ. Sci. Eng. ›› 2022, Vol. 16 ›› Issue (5) : 64 DOI: 10.1007/s11783-022-1543-6
RESEARCH ARTICLE
RESEARCH ARTICLE

Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies

Author information +
History +
PDF (8900KB)

Abstract

● Riverine microbiomes exhibited hyperlocal variation within a single transect.

● Certain family-level taxa directionally associated with river center and bank.

● Taxon accumulation curves within a transect urges more nuanced sampling design.

Microbial communities inhabiting river ecosystems play crucial roles in global biogeochemical cycling and pollution attenuation. Spatial variations in local microbial assemblages are important for detailed understanding of community assembly and developing robust biodiversity sampling strategies. Here, we intensely analyzed twenty water samples collected from a one-meter spaced transect from the near-shore to the near-center in the Meramec River in eastern Missouri, USA and examined the microbial community composition with 16S rRNA gene amplicon sequencing. Riverine microbiomes across the transect exhibited extremely high similarity, with Pearson’s correlation coefficients above 0.9 for all pairwise community composition comparisons. However, despite the high similarity, PERMANOVA revealed significant spatial differences between near-shore and near-center communities (p = 0.001). Sloan’s neutral model simulations revealed that within-transect community composition variation was largely explained by demographic stochasticity (R2 = 0.89). Despite being primarily explained by neutral processes, LefSe analyses also revealed taxa from ten families of which relative abundances differed directionally from the bank to the river center, indicating an additional role of environmental filtering. Notably, the local variations within a river transect can have profound impacts on the documentation of alpha diversity. Taxon-accumulation curves indicated that even twenty samples did not fully saturate the sampling effort at the genus level, yet four, six and seven samples were able to capture 80% of the phylum-level, family-level, and genus-level diversity, respectively. This study for the first time reveals hyperlocal variations in riverine microbiomes and their assembly mechanisms, demanding attention to more robust sampling strategies for documenting microbial diversity in riverine systems.

Graphical abstract

Keywords

Microbiome / Freshwater / Taxon accumulation curve / Community assembly

Cite this article

Download citation ▾
Bingdi Liu, Lin Zhang, Jason H. Knouft, Fangqiong Ling. Meter-scale variation within a single transect demands attention to taxon accumulation curves in riverine microbiome studies. Front. Environ. Sci. Eng., 2022, 16(5): 64 DOI:10.1007/s11783-022-1543-6

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

BattinT J, LuyssaertS, KaplanL A, AufdenkampeA K, RichterA, TranvikL J. (2009). The boundless carbon cycle. Nature Geoscience, 2( 9): 598– 600

[2]

BolyenE, RideoutJ R, DillonM R, BokulichN A, AbnetC C, Al-GhalithG A, AlexanderH, AlmE J, ArumugamM, AsnicarF. . (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology, 37( 8): 852– 857

[3]

CallahanB J, McMurdieP J, RosenM J, HanA W, JohnsonA J A, HolmesS P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 13( 7): 581– 583

[4]

CharonN W, CockburnA, LiC, LiuJ, MillerK A, MillerM R, MotalebM A, WolgemuthC W. (2012). The unique paradigm of spirochete motility and chemotaxis. Annual Review of Microbiology, 66( 1): 349– 370

[5]

ColeJ J PrairieY T CaracoN F McDowellW H TranvikL J StrieglR G DuarteC M P KortelainenJ A DowningJ A MiddelburgJ J MelackJ (2007). Plumbing the global carbon cycle: Integrating inland waters into the terrestrial carbon budget. Ecosystems (New York, N.Y.), 10( 1): 172− 185

[6]

CruaudP, VigneronA, FradetteM S, DoreaC C, CulleyA I, RodriguezM J, CharetteS J. (2020). Annual bacterial community cycle in a seasonally ice-covered river reflects environmental and climatic conditions. Limnology and Oceanography, 65( S1): S21– S37

[7]

CrumpB C, Amaral-ZettlerL A, KlingG W. (2012). Microbial diversity in arctic freshwaters is structured by inoculation of microbes from soils. ISME journal, 6( 9): 1629– 1639

[8]

EnsignS H DoyleM W (2006). Nutrient spiraling in streams and river networks. Journal of Geophysical Research. Biogeosciences, 111(G4)

[9]

FalkowskiP G, FenchelT, DelongE F. (2008). The microbial engines that drive Earth’s biogeochemical cycles. Science, 320( 5879): 1034– 1039

[10]

FaschingC, AkotoyeC, BižićM, FonvielleJ, IonescuD, MathavarajahS, ZoccaratoL, WalshD A, GrossartH, XenopoulosM A. (2020). Linking stream microbial community functional genes to dissolved organic matter and inorganic nutrients. Limnology and Oceanography, 65( S1): S71– S87

[11]

FukamiT ( 2015). Historical contingency in community assembly: Integrating niches, species pools, and priority effects. Annual Review of Ecology, Evolution, and Systematics, 46( 1): 1− 23

[12]

GilvearD J GreenwoodM T ThomsM C WoodP J ( 2016). River Science: Research and Management for the 21st Century. Hoboken: John Wiley & Sons

[13]

GweonH S, BowesM J, MoorhouseH L, OliverA E, BaileyM J, AcremanM C, ReadD S. (2021). Contrasting community assembly processes structure lotic bacteria metacommunities along the river continuum. Environmental Microbiology, 23( 1): 484– 498

[14]

KhleborodovaA ( 2020). Lefser: R implementation of the LEfSE method for microbiome biomarker discovery (Version R package version 140)

[15]

LarsbrinkJ, McKeeL S. (2020). Bacteroidetes bacteria in the soil: Glycan acquisition, enzyme secretion, and gliding motility. Advances in Applied Microbiology, 110 : 63– 98

[16]

LeventhalG E, BoixC, KuechlerU, EnkeT N, SliwerskaE, HolligerC, CorderoO X. (2018). Strain-level diversity drives alternative community types in millimetre-scale granular biofilms. Nature Microbiology, 3( 11): 1295– 1303

[17]

LingF, WhitakerR, LeChevallierM W, LiuW T. (2018). Drinking water microbiome assembly induced by water stagnation. The ISME journal, 12( 6): 1520– 1531

[18]

LoucaS, PolzM F, MazelF, AlbrightM B N, HuberJ A, O’ConnorM I, AckermannM, HahnA S, SrivastavaD S, CroweS A, DoebeliM, ParfreyL W. (2018). Function and functional redundancy in microbial systems. Nature Ecology & Evolution, 2( 6): 936– 943

[19]

McLellanS L, FisherJ C, NewtonR J. (2015). The microbiome of urban waters. International microbiology: The official journal of the Spanish Society for Microbiology, 18( 3): 141– 149

[20]

McMurdieP J, HolmesS. (2013). Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One, 8( 4): e61217

[21]

NewtonR J, JonesS E, EilerA, McMahonK D, BertilssonS. (2011). A guide to the natural history of freshwater lake bacteria. Microbiology and molecular biology reviews, 75( 1): 14– 49

[22]

OksanenJ BlanchetF G KindtR LegendreP MinchinP R O’HaraR B SimpsonG L SolymosP StevensM H H WagnerH ( 2020). Vegan: Community Ecology Package (Version R package version 25−7)

[23]

ParadisE ClaudeJ StrimmerK ( 2004). APE: Analyses of phylogenetics and evolution in R language. Bioinformatics (Oxford, England), 20( 2): 289− 290

[24]

PreheimS P, PerrottaA R, FriedmanJ, SmilieC, BritoI, SmithM B, AlmE. (2013). Computational methods for high-throughput comparative analyses of natural microbial communities. Methods in Enzymology, 531 : 353– 370

[25]

QuastC PruesseE YilmazP GerkenJ SchweerT YarzaP PepliesJ GlöcknerF O ( 2013). The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Research, 41(Database issue): D590–D596

[26]

ReadD S, GweonH S, BowesM J, NewboldL K, FieldD, BaileyM J, GriffithsR I. (2015). Catchment-scale biogeography of riverine bacterioplankton. ISME journal, 9( 2): 516– 526

[27]

Ruiz-GonzálezC, Niño-GarcíaJ P, DelGiorgio P A. (2015). Terrestrial origin of bacterial communities in complex boreal freshwater networks. Ecology Letters, 18( 11): 1198– 1206

[28]

SavioD, SinclairL, IjazU Z, ParajkaJ, ReischerG H, StadlerP, BlaschkeA P, BlöschlG, MachR L, KirschnerA K T, FarnleitnerA H, EilerA. (2015). Bacterial diversity along a 2600 km river continuum. Environmental Microbiology, 17( 12): 4994– 5007

[29]

SegataN, IzardJ, WaldronL, GeversD, MiropolskyL, GarrettW S, HuttenhowerC. (2011). Metagenomic biomarker discovery and explanation. Genome Biology, 12( 6): R60

[30]

SvobodaP, LindströmE S, AhmedOsman O, LangenhederS. (2018). Dispersal timing determines the importance of priority effects in bacterial communities. ISME journal, 12( 2): 644– 646

[31]

TheMissouri Department of Natural Resources (2015). The state of our Missouri waters-Meramec river watershed. Retrieved from www.ewgatewayorg/wp-content/uploads/ 2017.08/MRP-MeramecRiverWatershed.pdf

[32]

ThompsonJ R, PacochaS, PharinoC, Klepac-CerajV, HuntD E, BenoitJ, Sarma-RupavtarmR, DistelD L, PolzM F. (2005). Genotypic diversity within a natural coastal bacterioplankton population. Science, 307( 5713): 1311– 1313

[33]

VannoteR L, MinshallG W, CumminsK W, SedellJ R, CushingC E. (1980). The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences, 37( 1): 130– 137

[34]

WickhamH, AverickM, BryanJ, ChangW, McGowanL, FrançoisR, GrolemundG, HayesA, HenryL, HesterJ. . (2019). Welcome to the Tidyverse. Journal of Open Source Software, 4( 43): 1686

[35]

WithersP J A, JarvieH P. (2008). Delivery and cycling of phosphorus in rivers: A review. Science of the total environment, 400( 1−3): 379– 395

RIGHTS & PERMISSIONS

The Author(s) 2022. This article is published with open access at link.springer.com and journal.hep.com.cn

AI Summary AI Mindmap
PDF (8900KB)

Supplementary files

FSE-22018-OF-LBD_suppl_1

4429

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/