Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Populations of Populus angustifolia have evolved distinct metabolic profiles that influence their surrounding soil



Plant-microbial-soil interactions are key to understanding plant community succession, invasion success, patterns of biodiversity and aspects of ecosystem function. Yet root and rhizosphere chemistry is highly complex, and little is known about natural variation across environmental gradients. Variation in tree species root chemical phenotypes should alter how rhizosphere microbes respond, showing a plant conditioning effect on the chemical makeup of the soil. Here, we used metabolomics to assess bulk small molecule profiles addressing the hypothesis that genetic variation across a species range would result in varying metabolic profiles in roots and surrounding soil.


Using UPLC-HRMS we assessed the small molecule profile of root tissue and surrounding rhizosphere soil from 5-year old plant clones collected from six populations of Populus angustifolia across the western U.S., grown in a common environment.


Population-level variation was found in over 12,000 root metabolomes and over 5000 soil organic compounds across the populations. Redundancy analysis of over twelve thousand metabolites suggests that plant population origin can account for up to 36% of the variation in roots and 30% of the variation in rhizosphere soil chemistry. Co-inertia analysis indicates that variation in root metabolite profiles explains 15% of the variation in paired soil samples.


Distinct populations have evolved different root tissue metabolomes. The difference in root metabolites across populations altered the rhizosphere soil composition, creating variable soil chemical communities from a homogenous starting condition. This suggests that intra-specific plant conditioning of soil varies by plant population.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Data availability

Data consists of two curated spreadsheets of LC-MS output which gives the relative concentration of each metabolite in each sample and sufficient meta-data about the sample (one for soil samples and one for root samples), the raw spectra from the LC-MS output, as well as 10,956 EXCEL files associated with the 7 golden rules output (for each metabolite the program could solve for) which was sub sampled for the Van Krevelen diagrams shown here. All data is available on MetaboLights database.


  1. 1.

    Here we use the notation soil rhizosphere metabolome, with the understanding that soil rhizosphere chemistry is a complex matrix that could encompass root exudates, microbial metabolomes and extra-cellular soil chemical processes.


  1. Badri DV, Weir TL, van der Lelie D, Vivanco JM (2009) Rhizosphere chemical dialogues: plant–microbe interactions. Curr Opin Biotechnol 20:642–650

  2. Baetz U, Martinoia E (2014) Root exudates: the hidden part of plant defense. Trends Plant Sci 19:90–98

  3. Bardgett RD, Wardle DA (2010) Aboveground-belowground linkages biotic interactions, ecosystem processes, and global change. Oxford University Press, Oxford

  4. Berini, JL, Brockman SA, Hegeman AD, Reich PB, Muthukrishnan R, Montgomery RA, and Forester JD (2018) Combinations of abiotic factors differentially alter production of plant secondary metabolites in five woody plant species in the boreal-temperate transition zone. Frontiers in Plant Science

  5. Bever JD, Westover KM, Antonovics J (1997) Incorporating the soil community into plant population dynamics: the utility of the feedback approach. J Ecol 85:561

  6. Bezemer TM, Lawson CS, Hedlund K, Edwards AR, Brook AJ, Igual JM, Mortimer SR, Van Der Putten WH (2006) Plant species and functional group effects on abiotic and microbial soil properties and plant-soil feedback responses in two grasslands. J Ecol 94:893–904

  7. Brockman SA, Roden EV, Hegeman AD (2018) Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen. Metabolomics 14:48

  8. Cáceres M, Jansen F (2016) Indicspecies. R package—functions to assess the strength and significance of relationship of species site group associations

  9. Chamberlain K, Guerrieri E, Pennacchio F, Pettersson J, Pickett JA, Poppy GM, Powell W, Wadhams LJ, Woodcock CM (2001) Can aphid-induced plant signals be transmitted aerially and through the rhizosphere? Biochem Syst Ecol 29:1063–1074

  10. Clasquin MF, Melamud E, and Rabinowitz JD (2012) LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine. Current protocols in bioinformatics chapter 14:Unit14.11

  11. Conner JK, Hartl DL (2004) A primer of ecological genetics. Sinauer Associates, Inc., Sunderland, Massachusetts

  12. Coskun D, Britto DT, Shi W, and Kronzucker HJ (2017) How plant root exudates shape the nitrogen cycle

  13. Crutsinger GM, Sanders NJ, Classen AT (2009) Comparing intra- and inter-specific effects on litter decomposition in an old-field ecosystem. Basic Appl Ecol 10:535–543

  14. Dixon RA, Strack D (2003) Phytochemistry meets genome analysis, and beyond. Phytochemistry 62:815–816

  15. Dolédec S, Chessel D (1994) Co-inertia analysis: an alternative method for studying species–environment relationships. Freshw Biol 31:277–294

  16. Dray S, Dufour A-B (2007) The ade4 package: implementing the duality diagram for ecologists. J Stat Softw 22

  17. Escudero N, Marhuenda-Egea FC, Ibanco-Canẽte R, Zavala-Gonzalez EA, Lopez-Llorca LV (2015) A metabolomic approach to study the rhizodeposition in the tritrophic interaction: tomato, Pochonia chlamydosporia and Meloidogyne javanica. Metabolomics 10:788–804

  18. Evans LM, Slavov GT, Rodgers-Melnick E, Martin J, Ranjan P, Muchero W, Brunner AM, Schackwitz W, Gunter L, Chen JG, Tuskan GA, Difazio SP (2014) Population genomics of Populus trichocarpa identifies signatures of selection and adaptive trait associations. Nat Genet 46:1089–1096

  19. Evans LM, Allan GJ, Difazio SP, Slavov GT, Wilder JA, Floate KD, Rood SB, Whitham TG (2015) Geographical barriers and climate influence demographic history in narrowleaf cottonwoods. Heredity 114:387–396

  20. Harsch MA, Phillips A, Zhou Y, Leung M-R, Rinnan DS, Kot M (2017) Moving forward: insights and applications of moving-habitat models for climate change ecology. J Ecol 105:1169–1181

  21. Hobbie SE, Reich PB, Oleksyn J, Ogdahl M, Zytkowiak R, Hale C, Karolewski P (2006) Tree species effects on decomposition and forest floor dynamics in a common garden. Ecology 87:2288–2297

  22. Holman JD, Tabb DL, and Mallick P (2014) Employing ProteoWizard to convert raw mass spectrometry data. Pages 13.24.1-13.24.9 current protocols in bioinformatics. John Wiley & Sons, Inc., Hoboken, NJ, USA

  23. Hu L, Robert CAM, Cadot S, Zhang X, Ye M, Li B, Manzo D, Chervet N, Steinger T, van der Heijden MGA, Schlaeppi K, Erb M (2018) Root exudate metabolites drive plant-soil feedbacks on growth and defense by shaping the rhizosphere microbiota. Nat Commun 9:2738

  24. Jandová K, Dostál P, Cajthaml T, Kameník Z (2015) Intraspecific variability in allelopathy of Heracleum mantegazzianum is linked to the metabolic profile of root exudates. Ann Bot 115:821–831

  25. Kardol P, Martijn Bezemer T, Van Der Putten WH (2006) Temporal variation in plant-soil feedback controls succession. Ecol Lett 9:1080–1088

  26. Khorassani R, Hettwer U, Ratzinger A, Steingrobe B, Karlovsky P, Claassen N (2011) Citramalic acid and salicylic acid in sugar beet root exudates solubilize soil phosphorus. BMC Plant Biol 11:121

  27. Kiers ET, Denison RF (2008) Sanctions, cooperation, and the stability of plant-Rhizosphere mutualisms. Annu Rev Ecol Evol Syst 39:215–236

  28. Kind T, Fiehn O (2007) Seven Golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinformatics 8:105

  29. Kuhl C, Tautenhahn R, Böttcher C, Larson TR, Neumann S (2012) CAMERA: an integrated strategy for compound spectra extraction and annotation of liquid chromatography/mass spectrometry data sets. Anal Chem 84:283–289

  30. Lojewski NR, Fischer DG, Bailey JK, Schweitzer JA, Whitham TG, Hart SC (2012) Genetic components to belowground carbon fluxes in a riparian forest ecosystem: a common garden approach. New Phytol 195:631–639

  31. Lu W, Clasquin MF, Melamud E, Amador-Noguez D, Caudy AA, Rabinowitz JD (2010) Metabolomic analysis via reversed-phase ion-pairing liquid chromatography coupled to a stand alone orbitrap mass spectrometer. Anal Chem 82:3212–3221

  32. Madritch MD, Hunter MD (2005) Phenotypic variation in oak litter influences short- and long-term nutrient cycling through litter chemistry. Soil Biol Biochem 37:319–327

  33. Madritch MD, Greene SL, Lindroth RL (2009) Genetic mosaics of ecosystem functioning across aspen-dominated landscapes. Oecologia 160:119–127

  34. Marti G, Erb M, Boccard J, Glauser G, Doyen GR, Villard N, Robert CAM, Turlings TCJ, Rudaz S, Wolfender JL (2013) Metabolomics reveals herbivore-induced metabolites of resistance and susceptibility in maize leaves and roots. Plant Cell Environ 36:621–639

  35. Melillo JM, Aber JD, Muratore JF (1982) Nitrogen and lignin control of hardwood leaf litter decomposition dynamics. Ecology 63:621–626

  36. Mhlongo MI, Piater LA, Madala NE, Labuschagne N, Dubery IA (2018) The chemistry of plant–microbe interactions in the Rhizosphere and the potential for metabolomics to reveal signaling related to defense priming and induced systemic resistance. Front Plant Sci 9:112

  37. Michalet S, Rohr J, Warshan D, Bardon C, Roggy JC, Domenach AM, Czarnes S, Pommier T, Combourieu B, Guillaumaud N, Bellvert F, Comte G, Poly F (2013) Phytochemical analysis of mature tree root exudates in situ and their role in shaping soil microbial communities in relation to tree N-acquisition strategy. Plant Physiol Biochem 72:169–177

  38. Minor EC, Swenson MM, Mattson BM, Oyler AR (2014) Structural characterization of dissolved organic matter: a review of current techniques for isolation and analysis. Environ Sci: Process Impacts 16:2064–2079

  39. Oksanen AJ, Blanchet FG, Friendly M, Kindt R, Legendre P, Mcglinn D, Minchin PR, Hara RBO, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H (2016) Vegan: Community Ecology Package. Accessed Aug 2019

  40. Peters K, Worrich A, Weinhold A, Alka O, Balcke G, Birkemeyer C, Bruelheide H, Calf OW, Dietz S, Dührkop K, Gaquerel E, Heinig U, Kücklich M, Macel M, Müller C, Poeschl Y, Pohnert G, Ristok C, Rodríguez VM, Ruttkies C, Schuman M, Schweiger R, Shahaf N, Steinbeck C, Tortosa M, Treutler H, Ueberschaar N, Velasco P, Weiß BM, Widdig A, Neumann S, van Dam NM (2018) Current challenges in plant eco-metabolomics

  41. Pétriacq P, Williams A, Cotton A, McFarlane AE, Rolfe SA, Ton J (2017) Metabolite profiling of non-sterile rhizosphere soil. Plant J 92:147–162

  42. Pichersky E, Lewinsohn E (2011) Convergent evolution in plant specialized metabolism. Annu Rev Plant Biol 62:549–566

  43. Pregitzer CC, Bailey JK, Schweitzer JA (2013) Genetic by environment interactions affect plant-soil linkages. Ecol Evol 3:2322–2333

  44. Rasmann S, Turlings TCJ (2016) Root signals that mediate mutualistic interactions in the rhizosphere. Curr Opin Plant Biol 32:62–68

  45. Ristok C, Poeschl Y, Dudenhöffer J-H, Ebeling A, Eisenhauer N, Vergara F, Wagg C, van Dam NM, Weinhold A (2019) Plant species richness elicits changes in the metabolome of grassland species via soil biotic legacy. Journal of Ecology Early view

  46. Schweitzer JA, Madritch MD, Bailey JK, Leroy CJ, Fischer DG, Rehill BJ, Lindroth RL, Hagerman AE, Wooley SC, Hart SC, Whitham TG (2008) From genes to ecosystems: the genetic basis of condensed tannins and their role in nutrient regulation in a Populus model system

  47. Schweitzer JA, Fischer DG, Rehill BJ, Wooley SC, Woolbright SA, Lindroth RL, Whitham TG, Zak DR, Hart SC (2011) Forest gene diversity is correlated with the composition and function of soil microbial communities. Popul Ecol 53:35–46

  48. Schweitzer JA, Juric I, van de Voorde TFJ, Clay K, van der Putten WH, Bailey JK (2014) Are there evolutionary consequences of plant-soil feedbacks along soil gradients? Funct Ecol 28:55–64

  49. Stough JMA, Dearth SP, Denny JE, LeCleir GR, Schmidt NW, Campagna SR, Wilhelm SW (2016) Functional characteristics of the gut microbiome in C57BL/6 mice differentially susceptible to plasmodium yoelii. Front Microbiol 7:1520

  50. Swenson TL, Karaoz U, Swenson JM, Bowen BP, Northen TR (2018) Linking soil biology and chemistry in biological soil crust using isolate exometabolomics. Nat Commun 9:19

  51. Tautenhahn R, Patti GJ, Rinehart D, Siuzdak G (2012) XCMS online: a web-based platform to process untargeted metabolomic data. Anal Chem 84:5035–5039

  52. Team R. D. C., and R. R Development Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical Computing

  53. Tschaplinski TJ, Plett JM, Engle NL, Deveau A, Cushman KC, Martin MZ, Doktycz MJ, Tuskan GA, Brun A, Kohler A, Martin F (2014) Populus trichocarpa and Populus deltoides exhibit different Metabolomic responses to colonization by the symbiotic fungus Laccaria bicolor. Mol Plant-Microbe Interact 27:546–556

  54. van Dam NM, Bouwmeester HJ (2016) Metabolomics in the Rhizosphere: tapping into belowground chemical communication. Trends Plant Sci 21:256–265

  55. van der Putten WH (1997) Plant-soil feedback as a selective force. Trends Ecol Evol 12:169–170

  56. van der Putten WH, Bradford MA, Pernilla Brinkman E, van de Voorde TFJ, Veen GF (2016) Where, when and how plant–soil feedback matters in a changing world. Funct Ecol 30:1109–1121

  57. Van der Putten WH (2003) Plant defense belowground and spatiotemporal processes in natural vegetation. Ecology 84:2269–2280

  58. Van Krevelen D (1950) Graphical statistical method for the study of structure and reaction processes of coal. Fuel 29:269–284

  59. Van Nuland ME, Bailey JK, Schweitzer JA (2017) Divergent plant–soil feedbacks could alter future elevation ranges and ecosystem dynamics. Nat Ecol Evol 1:0150

  60. Van Nuland ME, Ware IM, Bailey JK, Schweitzer JA (2018) Geographic variation in plant evolutionary responses to soil fertility is mediated by soil microbial communities. Funct Ecol 33:95–106

  61. Vitousek PM, Walker LR, Whiteaker LD, Mueller-Dombois D, Matson PA (1987) Biological invasion by Myrica faya alters ecosystem development in Hawaii. Science 238:802–804

  62. Ware IM, Van Nuland ME, Schweitzer JA, Yang Z, Schadt CW, Sidak-Loftis LC, Stone NE, Busch JD, Wagner DM, Bailey JK (2019) Climate-driven reduction of genetic variation in plant phenology alters soil communities and nutrient pools. Glob Chang Biol 25:1514–1528

  63. Whitham TG, Bailey JK, Schweitzer JA, Shuster SM, Bangert RK, LeRoy CJ, Lonsdorf EV, Allan GJ, DiFazio SP, Potts BM, Fischer DG, Gehring CA, Lindroth RL, Marks JC, Hart SC, Wimp GM, Wooley SC (2006) A framework for community and ecosystem genetics: from genes to ecosystems. Nat Rev Genet 7:510–523

  64. Wolfe BE, Rodgers VL, Stinson KA, Pringle A (2008) The invasive plant Alliaria petiolata (garlic mustard) inhibits ectomycorrhizal fungi in its introduced range. J Ecol 96:777–783

  65. Yonekura-Sakakibara K, Saito K (2009) Functional genomics for plant natural product biosynthesis. Nat Prod Rep 26:1466

Download references


The authors would like to thank Ian Ware, Michael van Nuland, Philip Patterson, and Courtney Gorman for assistance in the field and greenhouse as well as Terrell Carter and Michaela Humby for their help in the lab. Thank you to Melissa Liotta and Shannon Bayliss for their help building figures. Thanks to Ken McFarland and Jeff Martin for their greenhouse expertise. We would like to acknowledge funding from The University of Tennessee, Department of Ecology and Evolutionary Biology.

Author information

LOM, HFC, SRC, JKB, and JAS formulated the initial questions. EDT, SPD, HFC, and SRC performed the chemical assays. LOM, SRB, EDT, HFC, and SRC performed the chemical analysis. LOM and SRB performed the statistical analyses. Writing was shared by all authors.

Correspondence to Liam O. Mueller.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Responsible Editor: Luz E. de-Bashan.

Electronic supplementary material


(DOCX 18 kb)


(XLSX 433 kb)


(DOCX 13 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mueller, L.O., Borstein, S.R., Tague, E.D. et al. Populations of Populus angustifolia have evolved distinct metabolic profiles that influence their surrounding soil. Plant Soil (2020).

Download citation


  • Co-inertia
  • Distance based redundancy analysis
  • LC-MS
  • Metabolomics
  • Orbitrap
  • Plant conditioning
  • Rhizosphere
  • Van Krevelen diagrams