RESEARCH ARTICLE

High-throughput metabarcoding of SAR11 assemblages from the southwest Atlantic shelf and arid Patagonia: richness and associated rank abundance distributions

  • Leandro R. Jones ,
  • Julieta M. Manrique
Expand
  • Laboratorio de Virología y Genética Molecular, Universidad Nacional dela Patagonia San Juan Bosco, Trelew CP 9100, Argentina
lrj000@gmail.com

Received date: 01 Dec 2022

Revised date: 13 Mar 2023

Accepted date: 15 Mar 2023

Copyright

2023 The Author(s). Published by Higher Education Press.

Abstract

Background: Massively parallel sequencing of environmental DNA allows microbiological studies to be performed in greater detail than was possible with first-generation sequencing. For example, it facilitates the use of approaches hitherto largely applied to flora and fauna, such as rank abundance distribution (RAD) analyses.

Methods: Here, we set out to advance the knowledge on Ca. Pelagibacterales (SAR11) communities from southern South America using environmental sequences from the open ocean in the Argentine sea, the uncharted Engaño Bay, as well as a river and an oligohaline shallow lake from the Patagonian Steppe ecoregion. The structures of the SAR11 assemblages present in these ecosystems were dissected by direct and rarefaction-based estimates of species richness, and evaluations of the corresponding abundance distributions (ADs), which was addressed by RAD analyses.

Results: Microbial community composition analyses revealed that the studied SAR11 assemblages coexist with 27 bacterial phyla. SAR11 richness was in general very high, but ADs turned out to be highly uneven. The results were compatible with prior knowledge, and similar to that derived from point estimates of diversity. However, our comprehensive dissection allowed for more detailed quantitative comparisons to be made between the environments surveyed, and revealed differences regarding both richness and the underlying ADs.

Conclusions: Despite SAR11 assemblages being extremely rich, their ADs are very uneven. Richness and ADs can vary, not only between fresh and salt water, but also between oceanic and coastal marine environments. The obtained results provide insights on general topics such as adaptation and the contrast between marine and freshwater radiations.

Cite this article

Leandro R. Jones , Julieta M. Manrique . High-throughput metabarcoding of SAR11 assemblages from the southwest Atlantic shelf and arid Patagonia: richness and associated rank abundance distributions[J]. Quantitative Biology, 2023 , 11(3) : 332 -342 . DOI: 10.15302/J-QB-023-0329

SUPPLEMENTARY MATERIALS

The supplementary materials can be found online with this article at https://doi.org/10.15302/J-QB-023-0329.

ACKNOWLEDGEMENTS

This work was supported by grants PIP 2021–2023 11220200102657CO (CONICET), PICT 2020 series A-03643 (FONCyT), and PI 1657 (UNPSJB). LRJ and JMM are members of CONICET. Continuous support from civil association ArGen (Argentina Genetics) is most appreciated.

COMPLIANCE WITH ETHICS GUIDELINES

Conflicts of interest The authors Leandro R. Jones and Julieta M. Manrique declare that they have no conflict of interests.
This article does not contain any studies with human or animal subjects performed by any of the authors.

OPEN ACCESS

This article is licensed by the CC By under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
1
Falkowski,P. G., Fenchel,T. Delong,E. (2008). The microbial engines that drive earth’s biogeochemical cycles. Science, 320: 1034–1039

DOI

2
Falkowski,P., Scholes,R. J., Boyle,E., Canadell,J., Canfield,D., Elser,J., Gruber,N., Hibbard,K., gberg,P., Linder,S. . (2000). The global carbon cycle: a test of our knowledge of earth as a system. Science, 290: 291–296

DOI

3
Pomeroy,L. Williams,P. Azam,F. (2007). The Microbial Loop. Oceanography (Wash. D.C.), 20: 28–33

DOI

4
Jiao,N., Herndl,G. J., Hansell,D. A., Benner,R., Kattner,G., Wilhelm,S. W., Kirchman,D. L., Weinbauer,M. G., Luo,T., Chen,F. . (2010). Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean. Nat. Rev. Microbiol., 8: 593–599

DOI

5
Giovannoni,S. J., Britschgi,T. B., Moyer,C. L. Field,K. (1990). Genetic diversity in Sargasso Sea bacterioplankton. Nature, 345: 60–63

DOI

6
Amann,R. I., Ludwig,W. Schleifer,K. (1995). Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev., 59: 143–169

DOI

7
Cui,H., Li,Y. (2016). An overview of major metagenomic studies on human microbiomes in health and disease. Quant. Biol., 4: 192–206

DOI

8
Lloyd,K. G., Steen,A. D., Ladau,J., Yin,J. (2018). Phylogenetically novel uncultured microbial cells dominate earth microbiomes. mSystems, 3: e00055–e18

DOI

9
LegendreP.. and Legendre, L. (1998) Numerical Ecology. Amsterdam: Elsevier

10
Giovannoni,S. (2017). SAR11 bacteria: the most abundant plankton in the oceans. Annu. Rev. Mar. Sci., 9: 231–255

DOI

11
Haro-Moreno,J. M., Rodriguez-Valera,F., Rosselli,R., Martinez-Hernandez,F., Roda-Garcia,J. J., Gomez,M. L., Fornas,O., Martinez-Garcia,M. (2019). Ecogenomics of the SAR11 clade. Environ. Microbiol., 22: 1748–1763

DOI

12
Wilhelm,L. J., Tripp,H. J., Givan,S. A., Smith,D. P. Giovannoni,S. (2007). Natural variation in SAR11 marine bacterioplankton genomes inferred from metagenomic data. Biol. Direct, 2: 27

DOI

13
Delmont,T. O., Kiefl,E., Kilinc,O., Esen,O. C., Uysal,I., Giovannoni,S. Eren,A. (2019). Single-amino acid variants reveal evolutionary processes that shape the biogeography of a global SAR11 subclade. eLife, 8: e46497

DOI

14
rez,M., Haro-Moreno,J. M., Coutinho,F. H., Martinez-Garcia,M. (2020). The evolutionary success of the marine bacterium SAR11 analyzed through a metagenomic perspective. mSystems, 5: e00605–e00620

DOI

15
Kraemer,S., Ramachandran,A., Colatriano,D., Lovejoy,C. Walsh,D. (2020). Diversity and biogeography of SAR11 bacteria from the Arctic Ocean. ISME J., 14: 79–90

DOI

16
Ngugi,D. K. (2012). Combined analyses of the ITS loci and the corresponding 16S rRNA genes reveal high micro- and macrodiversity of SAR11 populations in the Red Sea. PLoS One, 7: e50274

DOI

17
Grote,J., Thrash,J. C., Huggett,M. J., Landry,Z. C., Carini,P., Giovannoni,S. J. (2012). Streamlining and core genome conservation among highly divergent members of the SAR11 clade. MBio, 3: e00252–e12

DOI

18
Henson,M. W., Lanclos,V. C., Faircloth,B. C. Thrash,J. (2018). Cultivation and genomics of the first freshwater SAR11 (LD12) isolate. ISME J., 12: 1846–1860

DOI

19
Cameron Thrash,J. C., Temperton,B., Swan,B. K., Landry,Z. C., Woyke,T., DeLong,E. F., Stepanauskas,R. Giovannoni,S. (2014). Single-cell enabled comparative genomics of a deep ocean SAR11 bathytype. ISME J., 8: 1440–1451

DOI

20
Carini,P., Van Mooy,B. A. S. V., Thrash,J. C., White,A., Zhao,Y., Campbell,E. O., Fredricks,H. F. Giovannoni,S. (2015). SAR11 lipid renovation in response to phosphate starvation. Proc. Natl. Acad. Sci. USA, 112: 7767–7772

DOI

21
Paver,S. F., Muratore,D., Newton,R. J. Coleman,M. (2018). Reevaluating the salty divide: phylogenetic specificity of transitions between marine and freshwater systems. mSystems, 3: e00232–e18

DOI

22
Herlemann,D. P., Woelk,J., Labrenz,M. (2014). Diversity and abundance of “Pelagibacterales” (SAR11) in the Baltic Sea salinity gradient. Syst. Appl. Microbiol., 37: 601–604

DOI

23
Oh,S., Zhang,R., Wu,Q. L. Liu,W. (2014). Draft genome sequence of a novel SAR11 clade species abundant in a Tibetan Lake. Genome Announc., 2: e01137–e14

DOI

24
Oh,S., Zhang,R., Wu,Q. L. Liu,W. (2016). Evolution and adaptation of SAR11 and Cyanobium in a saline Tibetan lake. Environ. Microbiol. Rep., 8: 595–604

DOI

25
Logares,R., Brate,J., Heinrich,F., Shalchian-Tabrizi,K. (2009). Infrequent transitions between saline and fresh waters in one of the most abundant microbial lineages (SAR11). Mol. Biol. Evol., 27: 347–357

DOI

26
Eiler,A., Mondav,R., Sinclair,L., Fernandez-Vidal,L., Scofield,D. G., Schwientek,P., Martinez-Garcia,M., Torrents,D., McMahon,K. D., Andersson,S. G. . (2016). Tuning fresh: radiation through rewiring of central metabolism in streamlined bacteria. ISME J., 10: 1902–1914

DOI

27
Latimer,A. M., Silander,J. A. Cowling,R. (2005). Neutral ecological theory reveals isolation and rapid speciation in a biodiversity hot spot. Science, 309: 1722–1725

DOI

28
West,N. J., re,C., Manes,C. Catala,P., Scanlan,D. J. (2016). Distinct spatial patterns of SAR11, SAR86, and actinobacteria diversity along a transect in the ultra-oligotrophic South Pacific Ocean. Front. Microbiol., 7: 234

DOI

29
Hellweger,F. L., van Sebille,E. Fredrick,N. (2014). Biogeographic patterns in ocean microbes emerge in a neutral agent-based model. Science, 345: 1346–1349

DOI

30
ManriqueJ. M.JonesL.. (2017) Are ocean currents too slow to counteract SAR11 evolution? A next-generation sequencing, phylogeographic analysis. Mol. Phylogenet. Evol., 107, 324–337

31
Vergin,K., Jhirad,N., Dodge,J., Carlson,C. (2017). Marine bacterioplankton consortia follow deterministic, non-neutral community assembly rules. Aquat. Microb. Ecol., 79: 165–175

DOI

32
Dogliotti,A., Lutz,V. (2014). Estimation of primary production in the southern Argentine continental shelf and shelf-break regions using field and remote sensing data. Remote Sens. Environ., 140: 497–508

DOI

33
PiccoloM. C.PerilloG. M.. (1999) The Argentina Estuaries: A Review. In: Estuaries of South America, Piccolo, M. C. & Perillo, G.M.E. (Ed.), Heidelberg: Springer

34
Carbonell-Silletta,L., Cavallaro,A., Pereyra,D. A., Askenazi,J. O., Goldstein,G., Scholz,F. G. Bucci,S. (2022). Soil respiration and N-mineralization processes in the Patagonian steppe are more responsive to fertilization than to experimental precipitation increase. Plant Soil, 479: 405–422

DOI

35
Derguy,M. R., Martinuzzi,S. (2022). Bioclimatic changes in ecoregions of southern South America: trends and projections based on Holdridge life zones. Austral Ecol., 47: 580–589

DOI

36
MataloniG.Quintana R. D.,. (2022) Freshwaters and Wetlands of Patagonia. Springer International Publishing

37
Matano,R. P., Palma,E. D. Piola,A. (2010). The influence of the Brazil and Malvinas Currents on the Southwestern Atlantic Shelf circulation. Ocean Sci., 6: 983–995

DOI

38
Torres Alberto,M. L., Bodnariuk,N., Ivanovic,M., Saraceno,M. Acha,E. (2020). Dynamics of the confluence of Malvinas and Brazil currents, and a southern Patagonian spawning ground, explain recruitment fluctuations of the main stock of Illex argentinus. Fish. Oceanogr., 30: 127–141

DOI

39
Giaccardi,L. I., Badenas,M. A., Jones,L. R. Manrique,J. (2022). Abundant microbes of surface sea waters of the uncharted Engaño Bay at the Atlantic Patagonian Coast: relevance of bacteria-sized photosynthetic eukaryotes. Aquat. Ecol., 56: 1217–1230

DOI

40
Schloss,P. D., Westcott,S. L., Ryabin,T., Hall,J. R., Hartmann,M., Hollister,E. B., Lesniewski,R. A., Oakley,B. B., Parks,D. H., Robinson,C. J. . (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol., 75: 7537–7541

DOI

41
Foster,Z. S. L., Sharpton,T. J. nwald,N. (2017). Metacoder: an R package for visualization and manipulation of community taxonomic diversity data. PLOS Comput. Biol., 13: e1005404

DOI

42
OksanenJ.,Blanchet F. G.,FriendlyM.,KindtR.,LegendreP., McGlinnD.,Minchin P. R.,HaraR. B.,SimpsonG. L.,SolymosP.,. (2020) vegan: community ecology package, available on the website of cran.r-project

43
R Core Team. (2022) R: a language and environment for statistical computing, R foundation for statistical computing, Vienna, Austria, available on the website of R-project

44
QuensenJ.. (2019) QsRutils: R functions useful for community ecology, available on the website of GitHub

45
Hurlbert,S. (1971). The nonconcept of species diversity: a critique and alternative parameters. Ecology, 52: 577–586

DOI

46
KindtR.. (2005) Tree Diversity Analysis: A Manual and Software for Common Statistical Methods for Ecological and Biodiversity Studies. Nairobi: World Agroforestry Centre (ICRAF)

47
Saeedghalati,M., Farahpour,F., Budeus,B., Lange,A., Westendorf,A. M., Seifert,M., ppers,R. (2017). Quantitative comparison of abundance structures of generalized communities: from B-cell receptor repertoires to microbiomes. PLOS Comput. Biol., 13: e1005362

DOI

48
SaeedghalatiM.,FarahpourF.. (2016) RADanalysis: normalization and study of rank abundance distributions. Available on the website of cran.R-project

Outlines

/