International Journal of Legal Medicine

, Volume 129, Issue 3, pp 623–632 | Cite as

Microbial communities associated with human decomposition and their potential use as postmortem clocks

  • Sheree J. Finley
  • M. Eric Benbow
  • Gulnaz T. JavanEmail author
Review Article


Most forensic research that is used to better understand how to estimate the postmortem interval (PMI) entails the study of the physiochemical characteristics of decomposition and the effects that environmental factors have on the decomposition process. Forensic entomology exploits the life cycles of arthropods like Diptera (blow flies or flesh flies) and Coleoptera (beetles) deposited on the decaying carcass to determine PMI. Forensic taphonomy, from the Greek word taphos meaning burial, studies the creation of the fossils of decomposed cadavers to ascertain information as to the nature and time of death. Compared to other areas of taphonomy, there have been relatively few forensic science studies that have investigated the impact of human decomposition on the microbial changes occurring on or in a corpse or in the soil communities underneath a body. Such research may facilitate the critical determination of PMI. Therefore, the scope of this review is to provide a concise summary of the current progress in the newly emerging field of microbial diversity and the next-generation metagenomic sequencing approaches for assessing these communities in humans and in the soil beneath decomposing human.


Microbial communities Human decomposition Postmortem microbial clocks 


Conflict of interest

The authors declare that they have no conflict of interest.


  1. 1.
    Pechal J et al (2013) Microbial community functional change during vertebrate carrion decomposition. PLoS One 8:e79035CrossRefPubMedCentralPubMedGoogle Scholar
  2. 2.
    Hyde E et al (2013) The living dead: bacterial community structure of a cadaver at the onset and end of bloat stage of decomposition. PLoS ONE 8:e77733CrossRefPubMedCentralPubMedGoogle Scholar
  3. 3.
    Metcalf J et al (2013) A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system. eLife 2:e01104CrossRefPubMedCentralPubMedGoogle Scholar
  4. 4.
    Pechal J et al (2013) The potential use of bacterial community succession in forensics as described by high throughput metagenomic sequencing. Int J Legal Med 128:193–205CrossRefPubMedGoogle Scholar
  5. 5.
    Carter D, Yellowlees D, Tibbett M (2008) Temperature affects microbial decomposition of cadavers (Rattus rattus) in contrasting soils. Appl Soil Ecol 40:129–137CrossRefGoogle Scholar
  6. 6.
    Benninger L, Carter D, Forbes S (2008) The biochemical alterations of soil beneath a decomposing carcass. Forensic Sci Int 180:70–75CrossRefPubMedGoogle Scholar
  7. 7.
    Carter D, Yellowlees D, Tibbett M (2007) Cadaver decomposition in terrestrial ecosystems. Naturwissenschaften 94:12–24CrossRefPubMedGoogle Scholar
  8. 8.
    Forbes S, Stuart B, Dadour I, Dent B (2004) A preliminary investigation of the stages of adipocere formation. J Forensic Sci 49:1–9CrossRefGoogle Scholar
  9. 9.
    The Human Microbiome Consortium (2012) Structure, function and diversity of human microbiome in an adult reference population. Nature 486:207–214CrossRefGoogle Scholar
  10. 10.
    Gilbert JA et al (2010) Meeting report. The terabase metagenomics workshop and the vision of an earth microbiome project. Stand Genomic Sci 3:249–253CrossRefPubMedCentralPubMedGoogle Scholar
  11. 11.
    Payne J (1965) A summer carrion study of the baby pig Sus scrofa Linnaeus. Ecology 46:592–602CrossRefGoogle Scholar
  12. 12.
    Tomberlin J et al (2011) A roadmap for bridging basic and applied research in forensic entomology. Annu Rev Entomol 56:401–421CrossRefPubMedGoogle Scholar
  13. 13.
    Matuszewski S, Bajerlein D, Konwerski S, Szpila K (2010) Insect succession and carrion decomposition in selected forests of Central Europe. Part 1: pattern and rate of decomposition. Forensic Sci Int 194:85–93CrossRefPubMedGoogle Scholar
  14. 14.
    Centeno N, Maldonado M, Oliva A (2002) Seasonal patterns of arthropods occuring on sheltered and unsheltered pig carcasses in Buenos Aires Province (Argentina). Forensic Sci Int 126:63–70CrossRefPubMedGoogle Scholar
  15. 15.
    Hewadikaram K, Goff M (1991) Effect of carcass size on rate of decomposition and arthropod succession patterns. Am J Forensic Med Pathol 12:235–240CrossRefPubMedGoogle Scholar
  16. 16.
    Scholenly K, Reid W (1987) Dynamics of heterotrophic succession in carrion arthropod assemblages: discrete series of a continuum of change? Oceologia (Berlin) 73:192–202CrossRefGoogle Scholar
  17. 17.
    Houck M, Siegel J (2006) Soil and glass. In: Fundamentals of forensic science. Elsevier, Amsterdam, pp 409–430Google Scholar
  18. 18.
    Baldrian P et al (2012) Active and total microbial communities in forest soil are largely differenct and highly stratified during decomposition. ISME J 6:248–258CrossRefPubMedCentralPubMedGoogle Scholar
  19. 19.
    Roesch L et al (2007) Pyrosequencing enumerates and contrasts soil microbial diversity. ISME J 1:283–290PubMedCentralPubMedGoogle Scholar
  20. 20.
    Vaninsberghe D, Hartmann M, Stewart G, Mohn W (2013) Isolation of a substantial proportion of forest soil bacterial communities detected via pyrotag sequencing. Appl Environ Microbiol 79:2096–2098CrossRefPubMedCentralPubMedGoogle Scholar
  21. 21.
    Peterson J et al (2009) The NIH human microbiome project. Genome Res 19:2317–2323CrossRefPubMedCentralPubMedGoogle Scholar
  22. 22.
    Seo S et al (2013) Improvement of short tandem repeat analysis of samples highly contaminated by humic acid. J Forensic Legal Med 20:922–928CrossRefGoogle Scholar
  23. 23.
    Antony-Babu A et al (2013) An improved method compatible with metagenomic analyses to extract genomic DNA form soil in Tuber melanosporum orchards. J Appl Microbiol 115:163–170CrossRefPubMedGoogle Scholar
  24. 24.
    Knauth S, Schmidt H, Tippkotter R (2012) Comparison of commercial kits for the extraction of DNA from paddy soils. Lett Appl Microbiol 56:222–228CrossRefGoogle Scholar
  25. 25.
    Sagova-Mareckova M et al (2008) Innovative methods for soil DNA purification tested in soils with widely differing characteristics. Appl Environ Microbiol 74:2902–2907CrossRefPubMedCentralPubMedGoogle Scholar
  26. 26.
    Griffiths R, Whiteley A, O’Donnell A, Bailey M (2000) Rapid method of coextraction of DNA and RNA from natural environments for analysis of ribosomal DNA- and rRNA-based microbial community composition. Appl Environ Microbiol 66:5488–5491CrossRefPubMedCentralPubMedGoogle Scholar
  27. 27.
    Moreira D (1998) Efficient removal of PCR inhibitors using agarose-embedded DNA preparations. Nucleic Acid Res 26:3309–3310CrossRefPubMedCentralPubMedGoogle Scholar
  28. 28.
    Monroe C, Grier C, Kemp B (2013) Evaluating the efficacy of various thermo-stable polymerases against co-extracted PCR inhibitors in ancient DNA samples. Forensic Sci Int 228:142–153CrossRefPubMedGoogle Scholar
  29. 29.
    Kermekchiev M, Kirilova L, Vail E, Barnes W (2009) Mutants of Taq DNA polymerases resistant to PCR inhibitors allow DNA amplification from whole blood and crude soil samples. Nucleic Acids Res 37:e40CrossRefPubMedCentralPubMedGoogle Scholar
  30. 30.
    Paulin M et al (2013) Improving Griffith’s protocol for co-extraction of microbial DNA and RNA in adsorptive soils. Soil Biol Biochem 63:37–49CrossRefGoogle Scholar
  31. 31.
    Janda J, Abbott S (2007) 16S rRNA gene secquencing for bacterial identification in the diagnostic laboratory: pluses, perils, and pitfalls. J Clin Microbiol 45:2761–2764CrossRefPubMedCentralPubMedGoogle Scholar
  32. 32.
    Wooley J, Godzik A, Friedberg I (2010) A primer on metagenomics. PLoS Comput Biol 6:e1000667CrossRefPubMedCentralPubMedGoogle Scholar
  33. 33.
    Lane D et al (1985) Rapid determination o f16S ribosomal RNA sequences for phylogenetic analyses. PNAS 82:6955–6959CrossRefPubMedCentralPubMedGoogle Scholar
  34. 34.
    Schloss P, Gevers S, Westcott S (2011) Reducing the effects of PCR amplicfication and sequencing artifacts on 16S rRNA-based studies. PLoS ONE 6:e27310CrossRefPubMedCentralPubMedGoogle Scholar
  35. 35.
    Haas B et al (2011) Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res 21:494–504CrossRefPubMedCentralPubMedGoogle Scholar
  36. 36.
    Chakravorty S et al (2007) A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J Microbiol Methods 69:330–339CrossRefPubMedCentralPubMedGoogle Scholar
  37. 37.
    El-Metwally S, Hamza T, Zakaria M, Helmy M (2013) Next-generation sequence assembly: four stages for data processing and computational challenges. PLoS Comput Biol 9:e1003345CrossRefPubMedCentralPubMedGoogle Scholar
  38. 38.
    Margulies M et al (2005) Genome sequencing in microfabricated high-density picoliter reactors. Nature 437:376–380PubMedCentralPubMedGoogle Scholar
  39. 39.
    Kosugi S et al (2013) Coval: improving alignment quality and variant calling accuracy for next-generation sequencing data. PLoS ONE 8:e75402CrossRefPubMedCentralPubMedGoogle Scholar
  40. 40.
    Drancourt M et al (2000) 16S ribosomal DNA sequence analysis of a large collection of environmental and clinical unidentifiable bacterial isolates. J Clin Microbiol 38:3623–3630PubMedCentralPubMedGoogle Scholar
  41. 41.
    Cline J, Braman J, Hogrefe H (1996) PCR fidelity of Pfu DNA polymerase and other thermostable DNA polymerases. Nucleic Acids Res 24:3546–3551CrossRefPubMedCentralPubMedGoogle Scholar
  42. 42.
    Kunkel T (1992) DNA replication fidelity. J Biol Chem 267:18251–18254PubMedGoogle Scholar
  43. 43.
    Teeling H, Glockner F (2012) Current opportunities and challenges in microbial metagenome analysis—a bioinformatic perspective. Brief Bioinform 13:728–742CrossRefPubMedCentralPubMedGoogle Scholar
  44. 44.
    Turnbaugh P et al (2007) The human microbiome project. Nature 449:804–810CrossRefPubMedCentralPubMedGoogle Scholar
  45. 45.
    Qin J et al (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464:59–65CrossRefPubMedCentralPubMedGoogle Scholar
  46. 46.
    Carter D, Yellowlees D, Tibbett M (2010) Moisture can be the dominant environmental parameter governing cadaver decomposition in soil. Forensic Sci Int 200:60–66CrossRefPubMedGoogle Scholar
  47. 47.
    Delmont T et al (2011) Metagenomic comparison of direct and indirect soil DNA extraction approaches. J Microbiol Methods 86:397–400CrossRefPubMedGoogle Scholar
  48. 48.
    Caporaso J et al (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6:1621–1624CrossRefPubMedCentralPubMedGoogle Scholar
  49. 49.
    Vass A et al (1992) Time since death determinations of human cadavers using soil solution. J Forensic Sci 37:1236–1253PubMedGoogle Scholar
  50. 50.
    Vass A (2001) Beyond the grave—understanding human decomposition. Microbiol Today 28:190–192Google Scholar
  51. 51.
    Gunn A, Pitt S (2012) Microbes as forensic indicators. Trop Biomed 29:311–330Google Scholar
  52. 52.
    Fiedler S, Graw M (2003) Decomposition of buried corpses, with special reference to the formation of adipocere. Naturwissenschaften 90:291–300CrossRefPubMedGoogle Scholar
  53. 53.
    Teo C, Pawita AKO, Atiah Ayunni A, Noor Hazfalinda H (2013) Post mortem changes in relation to different types of clothing. Malyasian J Pathol 35:77–85Google Scholar
  54. 54.
    Hawksworth D, Wiltshire P (2011) Forensic mycology: the use of fungi in criminal investigations. Forensic Sci Int 206:1–11CrossRefPubMedGoogle Scholar
  55. 55.
    Tabaac B et al (2013) Bacteria detected on surfaces of formalin fixed anatomy cadavers. Ital J Anat Embryol 118:1–5PubMedGoogle Scholar
  56. 56.
    Ritchie N, Schutter M, Dick R, Myrold D (2000) Use of length heterogeneity PCR and fatty acid methyl ester profiles to characterize microbial communities in soil. Appl Environ Mircrobiol 66:1668–1675CrossRefGoogle Scholar
  57. 57.
    Hill G et al (2000) Methods for assessing the composition and diversity of soil microbial communities. Appl Soil Ecol 15:25–36CrossRefGoogle Scholar
  58. 58.
    Buyer J, Sasser M (2012) High throughput phospholipid fatty acid analysis of soils. Appl Soil Ecol 61:127–130CrossRefGoogle Scholar
  59. 59.
    Moreno L et al (2011) The application of amplicon length heterogeneity PCR (LH-PCR) for monitoring the dynamics of soil microbial communities associated with cadaver decomposition. J Microbiol Methods 84:388–393CrossRefPubMedGoogle Scholar
  60. 60.
    Heath L, Saunders B (2006) Assessing the potential of bacterial DNA profiling for forensic soil comparisons. J Forensic Sci 51:1062–1068CrossRefPubMedGoogle Scholar
  61. 61.
    Moreno L et al (2006) Microbial metagenome profiling using amplicon length heterogeneity-polymerase chain reaction proves more effective than elemental analysis in discriminating soil specimens. J Forensic Sci 51:1315–1322CrossRefPubMedGoogle Scholar
  62. 62.
    Osborne C, Rees G, Bernstein Y, Janssen P (2006) New threshold and confidence estimates for terminal restriction fragment length polymorphism analysis of complex bacterial communities. Appl Environ Microbiol 72:1270–1278CrossRefPubMedCentralPubMedGoogle Scholar
  63. 63.
    Dunbar J, Ticknor L, Kuske C (2001) Phylogenetic specificity and reproducibility and new method for analysis of terminal restriction fragment profiles of 16S rRNA genes from bacterial communities. Appl Environ Microbiol 67:190–197CrossRefPubMedCentralPubMedGoogle Scholar
  64. 64.
    Martiny J et al (2006) Microbial biogeography; putting microorganisms on the map. Nat Rev Microbiol 4:102–112CrossRefPubMedGoogle Scholar
  65. 65.
    Muyzer G, DeWaal E, Uitterlinden A (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl Environ Microbiol 59:695–700PubMedCentralPubMedGoogle Scholar
  66. 66.
    Daniel R (2005) The metagenomics of soil. Nat Rev Microbiol 3:470–478CrossRefPubMedGoogle Scholar
  67. 67.
    Tringe S, Rubin E (2005) Metagenomics: DNA sequencing of environmental samples. Nat Rev Genet 6:805–814CrossRefPubMedGoogle Scholar
  68. 68.
    Quail M et al (2012) A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers. BMC Genomics 13:341CrossRefPubMedCentralPubMedGoogle Scholar
  69. 69.
    Mizrahi-Man O, Davenport E, Gilad Y (2013) Taxonomic classification of bacterial 16S rRNA genes using short sequencing reads: evaluation of effective study designs. PLoS ONE 8:e53608CrossRefPubMedCentralPubMedGoogle Scholar
  70. 70.
    Liu L et al (2012) Comparison of next-generation sequencing systems. J Biomed Biotechnol. doi: 10.1155/2012/251364 Google Scholar
  71. 71.
    Chandra J, Sabharwal K (1968) Determination of time since death from a study of various postmortem changes. J Indian Med Assoc 51:336–341PubMedGoogle Scholar
  72. 72.
    Campobasso C, DiVella G, Introna F (2001) Factors affecting decomposition and Diptera colonization. Forensic Sci Int 120:18–27CrossRefPubMedGoogle Scholar
  73. 73.
    Woese C (2000) Interpreting the universal phylogenetic tree. PNAS 97:8392–8396CrossRefPubMedCentralPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Sheree J. Finley
    • 1
  • M. Eric Benbow
    • 2
  • Gulnaz T. Javan
    • 1
    Email author
  1. 1.Forensic Science Program, Physical Sciences DepartmentAlabama State UniversityMontgomeryUSA
  2. 2.Department of Entomology and Department of Osteopathic MedicineMichigan State UniversityEast LansingUSA

Personalised recommendations