Skip to main content

Next Generation High Throughput Sequencing to Assess Microbial Communities: An Application Based on Water Quality

Abstract

Traditional techniques to identify different contaminants (biological or chemical) in the waters are slow, laborious, and can require specialized expertise. Hence, the rapid determination of water quality using more sensitive and reliable metagenomic based approaches attains special importance. Metagenomics deals with the study of genetic material that is recovered from microbial communities present in environmental samples. In traditional techniques cultivation-based methodologies were used to describe the diversity of microorganisms in environmental samples. It has failed to function as a robust marker because of limited taxonomic and phylogenetic implications. In this backdrop, high-throughput DNA sequencing approaches have proven very powerful in microbial source tracking because of investigating the full variety of genome-based analysis such as microbial genetic diversity and population structure played by them. Next generation sequencing technologies can reveal a greater proportion of microbial communities that have not been reported earlier by traditional techniques. The present review highlights the shift from traditional techniques for the basic study of community composition to next-generation sequencing (NGS) platforms and their potential applications to the biomonitoring of water quality in relation to human health.

This is a preview of subscription content, access via your institution.

Fig. 1

References

  1. Alteio LV, Schulz F, Seshadri R, Varghese N, Rodriguez-Reillo W, Ryan E, Goudeau D, Eichorst SA, Malmstrom RR, Bowers RM, Katz LA (2020) Complementary metagenomic approaches improve reconstruction of microbial diversity in a forest soil. mSystems. https://doi.org/10.1128/mSystems.00768-19

    Article  Google Scholar 

  2. Boon E, Meehan CJ, Whidden C, Wong DHJ, Langille MGI, Beiko RG (2014) Interactions in the microbiome: communities of organisms and communities of genes. FEMS Microbiol Rev 38:814–821

    Article  Google Scholar 

  3. Bouseettine R, Hassou N, Bessi H, Ennaji MM (2020) Water borne transmission of enteric viruses and their impact on public health. Emerg Reemerg Viral Pathog 2020:907–932. https://doi.org/10.1016/B978-0-12-819400-3.00040-5

    Article  Google Scholar 

  4. Cai L, Zhang T (2013) Detecting human bacterial pathogens in wastewater treatment plants by a high-throughput shotgun sequencing technique. Environ Sci Technol 47(10):5433–5441

    CAS  Article  Google Scholar 

  5. Cao Q, Han SJ, Tulevski GS, Zhu Y, Lu DD, Haensch W (2013) Arrays of single-walled carbon nanotubes with full surface coverage for high-performance electronics. Nat Nanotechnol 8(3):180–186

    CAS  Article  Google Scholar 

  6. Carter KM, Lu M, Luo Q, Jiang H, An L (2020) Microbial community dissimilarity for source tracking with application in forensic studies. PLoS ONE 15:e0236082

    CAS  Article  Google Scholar 

  7. Chang BV, Chiang F, Yuan SY (2005) Biodegradation of nonylphenol in sewage sludge. Chemosphere 60:1652–1659

    CAS  Article  Google Scholar 

  8. Chun-Te Lin J, Liu YS, Wang WK (2020) A full-scale study of high-rate anaerobic bioreactors for whiskey distillery wastewater treatment with size fractionation and metagenomic analysis of granular sludge. Biores Technol 306:123032

    Article  Google Scholar 

  9. Dubinsky EA, Esmaili L, Hulls JR, Cao Y, Griffith JF, Andersen GL (2012) Application of phylogenetic microarray analysis to discriminate sources of fecal pollution. Environ Sci Technol 46(8):4340–4347

    CAS  Article  Google Scholar 

  10. Dubinsky EA, Butkus SR, Andersen GL (2016) Microbial source tracking in impaired watersheds using Phylo Chip and machine-learning classification. Water Res 105:56–64. https://doi.org/10.1016/j.watres.2016.08.035

    CAS  Article  Google Scholar 

  11. Frey KG, Herrera-Galeano JE, Redden CL, Luu TV, Servetas SL, Mateczun AJ, Mokashi VP, Bishop-Lilly KA (2014) Comparison of three next-generation sequencing platforms for metagenomic sequencing and identification of pathogens in blood. BMC Genomics 15(1):96. https://doi.org/10.1186/1471-2164

    Article  Google Scholar 

  12. Gao R, Cao B, Hu Y, Feng Z, Wang D, Hu W, Chen J, Jie Z, Qiu H, Xu K, Xu X (2013) Human infection with a novel avian-origin influenza A (H7N9) virus. N Engl J Med 368(20):1888–1897

    CAS  Article  Google Scholar 

  13. Genthe B, Roux WJ, Schachtschneider S, Oberholster PJ, Aneck-Hahn NH, Chamier J (2013) Health risk implications from simultaneous exposure to multiple environmental contaminants. Ecotoxicol Environ Saf 93:171–179

    CAS  Article  Google Scholar 

  14. Ghai R, Rodriguez-Valera F, McMahon KD, Toyama D, Rinke R, de Oliveira TCS, Garcia JW, de Miranda FP, Henrique-Silva F (2011) Metagenomics of the water column in the pristine upper course of the Amazon River. PLoS ONE 6(8):e23785. https://doi.org/10.1371/journal.pone.0023785

    CAS  Article  Google Scholar 

  15. Glenn TC (2011) Field guide to next generation DNA sequencers. Molecular Ecol Res 5:759–769

    Article  Google Scholar 

  16. Handelsman J (2004) Metagenomics: application of genomics to uncultured microorganisms. Microbiol Mol Biol Rev 68:669–685

    CAS  Article  Google Scholar 

  17. Harwood VJ, Staley C, Badgley BD, Borges K, Korajkic A (2014) Microbial source tracking markers for detection of fecal contamination in environmental waters: relationships between pathogens and human health outcomes. FEMS Microbiol Rev 38:1–40. https://doi.org/10.1111/1574-6976.12031

    CAS  Article  Google Scholar 

  18. Hellmér M, Paxéus N, Magnius L, Enache E, Arnholm B, Johansson A, Bergström T (2014) Detection of pathogenic viruses in sewage provided early warnings of Hepatitis A virus and Norovirus outbreaks. Appl Environ Microbiol 80(21):6771

    Article  Google Scholar 

  19. Hodzic J, Gurbeta L, Omanovic-Miklicanin E, Badnjevic A (2017) Overview of next-generation sequencing platforms used in published draft plant genomes in light of genotypization of immortelle plant (Helichrysium arenarium). Med Arch 71(4):288

    Article  Google Scholar 

  20. Inskeep WP, Jay ZJ, Tringe SG, Herrgard M, Rusch DB (2013) The YNP metagenome project: environmental parameters responsible for microbial distribution in the yellow stone geothermal ecosystem. Front Microbiol 4:67. https://doi.org/10.3389/fmicb.2013.00067

    CAS  Article  Google Scholar 

  21. Jehan S, Khattak SA, Muhammad S, Ali L, Rashid A, Hussain ML (2020) Human health risks by potentially toxic metals in drinking water along the Hattar Industrial Estate. Pakistan Environ Sci Pollut Res 27(3):2677–2690

    CAS  Article  Google Scholar 

  22. Knight R, Jansson J, Field D, Fierer N, Desai N, Fuhrman JA, Hugenholtz P, Van Der Lelie D, Meyer F, Stevens R, Bailey MJ (2011) Unlocking the potential of Metagenomics through replicated experimental design. Nat Biotechnol 30:513–520. https://doi.org/10.1038/nbt.2235

    CAS  Article  Google Scholar 

  23. Kunin V, Raes J, Harris JK, Spear JR, Walker JJ, Ivanova N, Von Mering C, Bebout BM, Pace NR, Bork P, Hugenholtz P (2008) Millimeter-scale genetic gradients and community-level molecular convergence in a hypersaline microbial mat. Mol Syst Biol 4(1):198. https://doi.org/10.1038/msb.2008.35

    Article  Google Scholar 

  24. Langille MG, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Thurber RLV, Knight R, Beiko RG (2013) Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 31(9):814–821

    CAS  Article  Google Scholar 

  25. Levine AD, Asano T (2004) Recovering sustainable water from wastewater. Env Sci Technol 38:201A-208A

    CAS  Article  Google Scholar 

  26. Li C, Cui YL, Tian GL, Shu Y, Wang XF, Tian H, Ren TL (2015) Flexible CNT-array double helices strain sensor with high stretchability for motion capture. Sci Rep 5(1):1–8

    Google Scholar 

  27. Mardis ER (2008) The impact of next-generation sequencing technology on genetics. Trends Genet 24:133–141. https://doi.org/10.1016/mj.tig.2007.12.007

    CAS  Article  Google Scholar 

  28. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J, Braverman MS, Chen YJ, Chen Z, Dewell SB (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437(7057):376–380

    CAS  Article  Google Scholar 

  29. Mathai PP, Staley C, Sadowsky MJ (2020) Sequence-enabled community-based microbial source tracking in surface waters using machine learning classification: A review. J Microbiol Methods 177:106050

    CAS  Article  Google Scholar 

  30. Miller RR, Montoya V, Gardy JL, Patrick DMP, Tang P (2013) Metagenomics for pathogen detection in public health. Genome med 5(9):81

    Article  Google Scholar 

  31. Olm MR, Crits-Christoph A, Diamond S, Lavy A, Carnevali PBM, Banfield JF (2020) Consistent metagenome-derived metrics verify and delineate bacterial species boundaries. mSystems. https://doi.org/10.1128/mSystems.00731-19

    Article  Google Scholar 

  32. Quail MA, Smith M, Coupland P, Otto TD, Harris SR, Connor TR, Bertoni A, Swerdlow HP, Gu Y (2012) A tale of three next generation sequencing platforms: comparison of ion torrent, Pacific biosciences and IlluminaMiSeq sequencers. BMC Genomics 13(1):1–13

    Article  Google Scholar 

  33. Roguet A, Esen ÖC, Eren AM, Newton RJ, McLellan SL (2020) FORENSIC: an online platform for fecal source identification. mSystems. https://doi.org/10.1128/mSystems.00869-19.e00869-19

    Article  Google Scholar 

  34. Rosario K, Nilsson C, Lim YW, Ruan Y, Breitbart M (2009) Metagenomic analysis of viruses in reclaimed water. Environ Microbiol 11:2806–2820

    CAS  Article  Google Scholar 

  35. Sanz JL, Köchling T (2019) Next-generation sequencing and waste/wastewater treatment: a comprehensive overview. Rev Environ SciBiotechnol 1–46

  36. Segata N, Huttenhower C (2011) Toward an efficient method of identifying core genes for evolutionary and functional microbial phylogenies. PLoS ONE 6(9):e24704

    CAS  Article  Google Scholar 

  37. Shenhav L, Thompson M, Joseph TA, Briscoe L, Furman O, Bogumil D, Mizrahi I, Peer I, Halperin E (2019) FEAST: fast expectation-maximization for microbial source tracking. Nat Methods 16:627–632. https://doi.org/10.1038/s41592-019-0431-x

    CAS  Article  Google Scholar 

  38. Shomar B, Al-Darwish K, Vincent A (2020) Optimization of wastewater treatment processes using molecular bacteriology. J Water Process Eng 33:101030

    Article  Google Scholar 

  39. Smith RJ, Jeffries TC, Roudnew B, Fitch AJ, Seymour JR, Delpin MW, Newton K, Brown MH, Mitchell JG (2012) Metagenomic comparison of microbial communities in habiting confined and unconfined aquifer ecosystems. Environ Microbiol 14:240–253. https://doi.org/10.1111/j.1462-2920.2011.02614.x

    CAS  Article  Google Scholar 

  40. Staley C, Sadowsky MJ (2016) Application of metagenomics to assess microbial communities in water and other environmental matrices. J Mar Biol Assoc UK 96:121–129. https://doi.org/10.1017/S0025315415001496

    Article  Google Scholar 

  41. Staley C, Gould TJ, Wang P, Phillips J, Cotner JB, Sadowsky MJ (2014a) Bacterial community structure is indicative of chemical inputs in the Upper Mississippi River. Front Microbiol 5:524

    Google Scholar 

  42. Staley C, Gould TJ, Wang P, Phillips J, Cotner JB, Sadowsky MJ (2014b) Core functional traits of bacterial communities in the Upper Mississippi River show limited variation in response to land cover. Front Microbiol 5:414. https://doi.org/10.3389/fmicb.2014.00414

    Article  Google Scholar 

  43. Steele HL, Jaeger KE, Daniel R, Streit WR (2009) Advances in recovery of novel biocatalysts from metagenomes. J Mol Microbiol Biotechnol 16:25–37. https://doi.org/10.1159/000142892

    CAS  Article  Google Scholar 

  44. Tan B, Ng CM, Nshimyimana JP, Loh LL, Gin KYH, Thompson JR (2015) Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities. Front Microbiol 6:1027

    Google Scholar 

  45. Torsvik V, Goksoyr J, Daae FL (1990) High diversity in DNA of soil bacteria. Appl Environ Microbiol 56:782–787

    CAS  Article  Google Scholar 

  46. Tringe SG, Mering CV, Kobayashi A, Salamov AA, Kevin C, Chang HW, Podar M, Short JM, Mathur EJ, Detter JC, Bork P, Philip H, Rubin EM (2005) Comparative metagenomics of microbial communities. Science. https://doi.org/10.1126/science.1107851

    Article  Google Scholar 

  47. Unno T, Di DY, Jang J, Suh YS, Sadowsky MJ, Hur HG (2012) Integrated online system for a pyrosequencing-based microbial source tracking method that targets Bacteroidetes 16S rDNA. Environ Sci Technol 46:93–98. https://doi.org/10.1021/es201380c

    CAS  Article  Google Scholar 

  48. Vandewalle JL, Goetz GW, Huse SM, Morrison HG, Sogin ML, Hoffmann RG, Yan K, McLellan SL (2012) Acinetobacter, Aeromonas and Trichococcus populations dominate the microbial community within urban sewer infrastructure. Environ Microbiol 14:2538–2552. https://doi.org/10.1111/j.1462-2920.2012.02757.x

    CAS  Article  Google Scholar 

  49. Venter JC, Remington K, Heidelberg JF, Halpern AL, Rusch D, Eisen JA, Wu DY, Paulsen I, Nelson KE, Nelson W, Fouts DE, Levy S, Knap AH, Lomas MW, Nealson K, White O, Peterson J, Hoffman J, Parsons R, Baden-Tillson H, Pfannkoch C, Rogers YH, Smith HO (2004) Environmental genome shotgun sequencing of the Sargasso Sea. Science 304:66–74

    CAS  Article  Google Scholar 

  50. Warren RL, Sutton GG, Jones SJM, Holt RA (2007) Assembling millions of short DNA sequences using SSAKE. Bioinformatics 23(4):500–501

    CAS  Article  Google Scholar 

  51. Woodhouse JN, Fan L, Brown MV, Thomas T, Neilan BA (2013) Deep sequencing of non-ribosomal peptide synthetases and polyketide synthases from the microbiomes of Australian marine sponges. ISME J7:1842–1851. https://doi.org/10.1038/ismej.2013.65

    CAS  Article  Google Scholar 

  52. Yutin N, Suzuki MT, Teeling H, Weber M, Venter JC, Rusch DB (2007) Assessing diversity and biogeography of aerobic anoxygenic phototrophic bacteria in surface waters of the Atlantic and Pacific Oceans using the Global Ocean Sampling expedition metagenomes. Environ Microbiol 9:1464–1475. https://doi.org/10.1111/j.1462-2920.2007.01265.x

    CAS  Article  Google Scholar 

Download references

Acknowledgements

The financial support by DST-SERB, Govt. of India under the National Post-Doctoral Fellowship (Grant No. PDF/20l8/001689) to GAW is acknowledged. The grant to MAS under the DBT supported Indo-Canadian project No. BT/IN/IC-IMPACTS/30/MAS/2015-2016 to MAS under IC-Impacts on ‘Biomonitoring of water quality in relation to human health using biosensors and nanoparticle based purification system’ is also acknowledged.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Gowher A. Wani.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wani, G.A., Khan, M.A., Dar, M.A. et al. Next Generation High Throughput Sequencing to Assess Microbial Communities: An Application Based on Water Quality. Bull Environ Contam Toxicol 106, 727–733 (2021). https://doi.org/10.1007/s00128-021-03195-7

Download citation

Keywords

  • Metagenomics
  • Next generation sequencing
  • Water quality
  • Bacterial community composition
  • Public health