Skip to main content
Log in

Potential forensic biogeographic application of diatom colony consistency analysis employing pyrosequencing profiles of the 18S rDNA V7 region

  • Original Article
  • Published:
International Journal of Legal Medicine Aims and scope Submit manuscript

Abstract

Diatom examination has always been used for the diagnosis of drowning in forensic practice. However, traditional examination of the microscopic features of diatom frustules is time-consuming and requires taxonomic expertise. In this study, we demonstrate a potential DNA-based method of inferring suspected drowning site using pyrosequencing (PSQ) of the V7 region of 18S ribosome DNA (18S rDNA) as a diatom DNA barcode. By employing a sparse representation-based AdvISER-M-PYRO algorithm, the original PSQ signals of diatom DNA mixtures were deciphered to determine the corresponding taxa of the composite diatoms. Additionally, we evaluated the possibility of correlating water samples to collection sites by analyzing the PSQ signal profiles of diatom mixtures contained in the water samples via multidimensional scaling. The results suggest that diatomaceous PSQ profile analysis could be used as a cost-effective method to deduce the geographical origin of an environmental bio-sample.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Pollanen MS. (1998) Forensic diatomology and drowning. Elsevier Health Sciences

    Google Scholar 

  2. Ludes B, Coste M, North N, Doray S, Tracqui A, Kintz P (1999) Diatom analysis in victim’s tissues as an indicator of the site of drowning. Int J Legal Med 112:163–166

    Article  CAS  Google Scholar 

  3. Siver PA, Lord WD, McCarthy DJ (1994) Forensic limnology: the use of freshwater algal community ecology to link suspects to an aquatic crime scene in southern New England. J Forensic Sci 39:847–853

    Article  Google Scholar 

  4. Hürlimann J, Feer P, Elber F, Niederberger K, Dirnhofer R, Wyler D (2000) Diatom detection in the diagnosis of death by drowning. Int J Legal Med 114:6–14

    Article  Google Scholar 

  5. Mayr E (1942) Systematics and the origin of species, from the viewpoint of a zoologist. Harvard University Press, Cambridge

    Google Scholar 

  6. Evans KM, Wortley AH, Mann DG (2007) An assessment of potential diatom “barcode” genes (cox1, rbcL, 18S and ITS rDNA) and their effectiveness in determining relationships in Sellaphora (Bacillariophyta). Protist 158:349–364. https://doi.org/10.1016/j.protis.2007.04.001

    Article  CAS  Google Scholar 

  7. Hebert PD, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proc Biol Sci 270:313–321. https://doi.org/10.1098/rspb.2002.2218

    Article  CAS  Google Scholar 

  8. Zimmermann J, Jahn R, Gemeinholzer B (2011) Barcoding diatoms: evaluation of the V4 subregion on the 18S rRNA gene, including new primers and protocols. Org Divers Evol 11:173–192. https://doi.org/10.1007/s13127-011-0050-6

    Article  Google Scholar 

  9. Moniz MB, Kaczmarska I (2010) Barcoding of diatoms: nuclear encoded ITS revisited. Protist 161:7–34. https://doi.org/10.1016/j.protis.2009.07.001

    Article  CAS  Google Scholar 

  10. Mann DG, Sato S, Trobajo R, Vanormelingen P, Souffreau C (2010) DNA barcoding for species identification and discovery in diatoms. Cryptogamie Algol 31:557–577

    Google Scholar 

  11. Chen XG, Zhang J, Huang Y, Hou YP (2018) Diatom taxa identification based on single-cell isolation and rDNA sequencing. Forensic Sci Int: Genetics Supplement Series 4:e308–e3e9. https://doi.org/10.1016/j.fsigss.2013.10.157

    Google Scholar 

  12. Kakizaki E, Ogura Y, Kozawa S, Nishida S, Uchiyama T, Hayashi T, Yukawa N (2012) Detection of diverse aquatic microbes in blood and organs of drowning victims: first metagenomic approach using high-throughput 454-pyrosequencing. Forensic Sci Int 220:135–146. https://doi.org/10.1016/j.forsciint.2012.02.010

    Article  CAS  Google Scholar 

  13. Ronaghi M, Uhlén M, Nyren P (1998) A sequencing method based on real-time pyrophosphate. Science 281:363–365

    Article  CAS  Google Scholar 

  14. Chen G, Olson MT, O'Neill A, Norris A, Beierl K, Harada S, Debeljak M, Rivera-Roman K, Finley S, Stafford A, Gocke CD, Lin MT, Eshleman JR (2012) A virtual pyrogram generator to resolve complex pyrosequencing results. J Mol Diagn: JMD 14:149–159. https://doi.org/10.1016/j.jmoldx.2011.12.001

    Article  CAS  Google Scholar 

  15. Lavebratt C, Sengul S, Jansson M, Schalling M (2004) Pyrosequencing-based SNP allele frequency estimation in DNA pools. Hum Mutat 23:92–97. https://doi.org/10.1002/humu.10292

    Article  CAS  Google Scholar 

  16. Ambroise J, Deccache Y, Irenge L, Savov E, Robert A, Gala JL (2014) Amplicon identification using SparsE representation of multiplex PYROsequencing signal (AdvISER-M-PYRO): application to bacterial resistance genotyping. Bioinformatics 30:3590–3597. https://doi.org/10.1093/bioinformatics/btu516

    Article  CAS  Google Scholar 

  17. Huang K, Aviyente S (2007) Sparse representation for signal classification. Advances in neural information processing systems. 609–616

  18. Kasai F, Kawachi M, Erata M et al (2009) NIES-collection list of strains, 8th edn. vol 57, Jpn J Phycol (Sôrui), pp 1–350

  19. Auer A, Möttönen M (1988) Diatoms and drowning. Z Rechtsmedizin 101:87–98. https://doi.org/10.1007/bf00200290

    Article  CAS  Google Scholar 

  20. Doyle J (1991) DNA protocols for plants. In: Hewitt GM, Johnston AWB, Young JPW (eds) Molecular Techniques in Taxonomy. Springer Berlin Heidelberg Berlin, Heidelberg, pp 283–293

    Chapter  Google Scholar 

  21. Lavebratt C, Sengul S (2006) Single nucleotide polymorphism (SNP) allele frequency estimation in DNA pools using pyrosequencing. Nat Protoc 1:2573–2582. https://doi.org/10.1038/nprot.2006.442

    Article  CAS  Google Scholar 

  22. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596. https://doi.org/10.1093/nar/gks1219

    Article  CAS  Google Scholar 

  23. Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792–1797. https://doi.org/10.1093/nar/gkh340

    Article  CAS  Google Scholar 

  24. Ludwig W, Strunk O, Westram R, Richter L, Meier H, Yadhukumar, Buchner A, Lai T, Steppi S, Jobb G, Förster W, Brettske I, Gerber S, Ginhart AW, Gross O, Grumann S, Hermann S, Jost R, König A, Liss T, Lüssmann R, May M, Nonhoff B, Reichel B, Strehlow R, Stamatakis A, Stuckmann N, Vilbig A, Lenke M, Ludwig T, Bode A, Schleifer KH (2004) ARB: a software environment for sequence data. Nucleic Acids Res 32:1363–1371. https://doi.org/10.1093/nar/gkh293

    Article  CAS  Google Scholar 

  25. Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, Glöckner FO (2013) Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res 41:e1. https://doi.org/10.1093/nar/gks808

    Article  CAS  Google Scholar 

  26. RStudio Team (2015). RStudio: integrated development for R. RStudio, Inc., Boston, URL http://www.rstudio.com/

  27. Mardia KV (1978) Some properties of classical multi-dimensional scaling. Commun Stat-Theory Methods 7:1233–1241. https://doi.org/10.1080/03610927808827707

    Article  Google Scholar 

  28. Kanagawa T (2003) Bias and artifacts in multitemplate polymerase chain reactions (PCR). J Biosci Bioeng 96:317–323. https://doi.org/10.1016/S1389-1723(03)90130-7

    Article  CAS  Google Scholar 

  29. Godhe A, Asplund ME, Harnstrom K, Saravanan V, Tyagi A, Karunasagar I (2008) Quantification of diatom and dinoflagellate biomasses in coastal marine seawater samples by real-time PCR. Appl Environ Microbiol 74:7174–7182. https://doi.org/10.1128/AEM.01298-08

    Article  CAS  Google Scholar 

  30. Gong J, Dong J, Liu X, Massana R (2013) Extremely high copy numbers and polymorphisms of the rDNA operon estimated from single cell analysis of oligotrich and peritrich ciliates. Protist 164:369–379. https://doi.org/10.1016/j.protis.2012.11.006

    Article  CAS  Google Scholar 

  31. McManus GB, Katz LA (2009) Molecular and morphological methods for identifying plankton: what makes a successful marriage? J Plankton Res 31:1119–1129. https://doi.org/10.1093/plankt/fbp061

    Article  CAS  Google Scholar 

  32. Vannote RL, Minshall GW, Cummins KW, Sedell JR, Cushing CE (1980) The River Continuum Concept. Can J Fish Aquat Sci 37:130–137

    Article  Google Scholar 

Download references

Funding

This work was supported by a grant from the National Natural Science Foundation of China (reference numbers 81571861 and 81630054).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Yufang Wang or Ji Zhang.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Electronic supplementary material

ESM 1

(DOCX 1367 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, Y., Chen, X., Yang, Y. et al. Potential forensic biogeographic application of diatom colony consistency analysis employing pyrosequencing profiles of the 18S rDNA V7 region. Int J Legal Med 132, 1611–1620 (2018). https://doi.org/10.1007/s00414-018-1849-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00414-018-1849-x

Keywords

Navigation