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Latent Fingermarks and Microbiome: Time and Community Succession

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Technologies for Fingermark Age Estimations: A Step Forward

Abstract

Trace evidence is a type of physical evidence that can be transferred between two objects, helping to reconstruct the sequence of events of a crime. From a forensic perspective, the human skin is a key element for, and source of, microbial trace evidence due to the constant exposure and contact with surfaces and continuous interaction with the environment. The most studied group of microorganisms in microbial forensics is bacteria. Bacteria are extremely diverse in terms of morphology, physiology, and metabolism. They have evolved to use a wide range of strategies to obtain energy, being able to survive and thrive in many different environments. This great diversity and adaptability make bacteria ubiquitous, that is, they can be found in every environment possible on Earth, a remarkable characteristic that can be of great investigative value as trace evidence. Microorganisms colonize the skin immediately after birth and remain there even after death. In healthy conditions, they are mainly located in the superficial layers of the epidermis, gland tracts, and hair follicles. The skin microbiota consists of a group of organisms that are routinely found in the human skin and can reestablish themselves after a perturbance. The human skin core microbiota includes four main phyla: Actinobacteria, Firmicutes, Proteobacteria, and Bacteroides. Recent advances in molecular analysis, especially modern sequencing techniques, have considerably increased the quantity of data available for forensic purposes. This information is valuable not only to identify the representative microbial communities but also to better understand the dynamics occurring within each community. High-throughput sequencing and alpha and beta diversity analysis have been employed to achieve a deeper understanding of the human skin microbiome and its uniqueness among individuals. This represents a means of personal identification as well as the distinctiveness of the microbiome when transferred from the skin to another surface. Several studies have reported that skin bacteria of individuals can also be found on their mobile phones or be traced back to a keyboard in such a way that a person could be identified based on the bacterial residue left on specific keys. The enormous metabolic and physiological diversity of bacteria allow microbial assemblages to readily evolve to the changing environments. Thus, the composition of skin microbiota has a high potential to successfully complement current forensic techniques for the reconstruction of criminal events at the scene.

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Abbreviations

DNA:

Deoxyribonucleic acid

RNA:

Ribonucleic acid

NGS:

Next-generation sequencing

OTU:

Operational taxonomic unit

PCR:

Polymerase chain reaction

QIIME:

Quantitative insights into microbial ecology

RDP:

Ribosomal database project

References

  1. Woese CR, Kandler O, Wheelis ML (1990) Towards a natural system of organisms: proposal for the domains archaea, Bacteria, and Eucarya. Proc Natl Acad Sci U S A 87(12):4576–4579

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Torsvik V, Øvreås L, Thingstad TF (2002) Prokaryotic diversity-magnitude, dynamics, and controlling factors. Science 296:1064–1066

    Article  CAS  PubMed  Google Scholar 

  3. Cowan MK, Smith H, Lusk J (eds) (2019) Microbiology fundamentals: a clinical approach, 3rd edn. McGraw-Hill, New York

    Google Scholar 

  4. Whitman WB, Coleman DC, Wiebe WJ (1998) Prokaryotes: the unseen majority. Proc Natl Acad Sci U S A 95(12):6578–6583. https://doi.org/10.1073/pnas.95.12.6578

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Carter OD, Tomberlin JK, Benbow ME, Metcalf JL (eds) (2017) Microbial forensics. Wiley, New Jersey

    Google Scholar 

  6. Metcalf JL, Xu ZZ, Bouslimani A, Dorrestein P, Carter DO, Knight R (2017) Microbiome tools for forensic science. Trends Biotechnol 35(9):814–823

    Article  CAS  PubMed  Google Scholar 

  7. Lederberg J, McCray A (2001) The scientist: ‘ome sweet’ omics – a genealogical treasury of words. Science 15(7):8

    Google Scholar 

  8. Radjabzadeh D, Boer CG, Beth SA et al (2020) Diversity, compositional and functional differences between gut microbiota of children and adults. Sci Rep 10:1040

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Tortora GJ, Funke BR, Case CL (eds) (2019) Microbiology: an introduction, 13th edn. Pearson, Boston

    Google Scholar 

  10. Kakizaki E, Kozawa S, Matsuda H, Muraoka E, Uchiyama T, Sakai M, Yukawa N (2010) Freshwater bacterioplankton cultured from liver, kidney, and lungs of a decomposed cadaver retrieved from a sandy seashore: possibility of drowning in a river and then floating out to sea. Legal Med 12(4):195–199

    Article  PubMed  Google Scholar 

  11. Burton JL, Saegeman V, Arribi A et al (2019) Postmortem microbiology sampling following death in hospital: an ESGFOR task force consensus statement. J Clin Pathol 72(5):329–336. https://doi.org/10.1136/jclinpath-2018-205365

    Article  PubMed  Google Scholar 

  12. Adserias-Garriga J, Hernandez M, Quijada NM, Rodriguez Lazaro D, Steadman D, Garcia-Gil J (2017) Daily thanatomicrobiome changes in soil as an approach of postmortem interval estimation: an ecological perspective. Forensic Sci Int 278:388–395. https://doi.org/10.1016/j.forsciint.2017.07.017

    Article  PubMed  Google Scholar 

  13. Adserias-Garriga J, Quijada NM, Hernandez M, Rodriguez Lazaro D, Steadman D, Garcia-Gil LJ (2017) Dynamics of the oral microbiota as a tool to estimate time since death. Mol Oral Microbiol 32(6):511–516. https://doi.org/10.1111/omi.12191.

    Article  CAS  PubMed  Google Scholar 

  14. Javan GT, Finley SJ, Tuomisto S, Hall A, Benbow ME, Mill DE (2019) An interdisciplinary review of the thanatomicrobiome in human decomposition. Forensic Sci Med Pathol 15(1):75–83. https://doi.org/10.1007/s12024-018-0061-0

    Article  PubMed  Google Scholar 

  15. Ward MJ, Goncheva M, Richardson E, McAdam PR, Raftis E, Kearns A et al (2016) Identification of source and skin populations for the emergence and global spread of the East-Asia clone of community-associated MRSA. Genome Biol 17:160

    Article  PubMed  PubMed Central  Google Scholar 

  16. Cardinale BJ et al (2012) Biodiversity loss and its impact on humanity. Nature 486(7401):59–67. https://doi.org/10.1038/nature11148.

    Article  CAS  PubMed  Google Scholar 

  17. Petchey OL, McPhearson PT, Casey TM, Morin PJ (1999) Environmental warming alters food-web structure and ecosystem function. Nature 402:69–72. https://doi.org/10.1038/47023

    Article  CAS  Google Scholar 

  18. Venail PA, Vives MJ (2013) Phylogenetic distance and species richness interactively affect the productivity of bacterial communities. Ecology 94(11):2529–2536. https://doi.org/10.1890/12-2002.1

    Article  PubMed  Google Scholar 

  19. Petchey OL, Gaston KJ (2006) Functional diversity: back to basics and looking forward. Ecol Lett 9(6):741–758. https://doi.org/10.1111/j.1461-0248.2006.00924.x

    Article  PubMed  Google Scholar 

  20. Ofiţeru ID et al (2010) Combined niche and neutral effects in a microbial wastewater treatment community. Proc Natl Acad Sci 107(35):15345–15350. https://doi.org/10.1073/pnas.1000604107.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Pedrós-Alió C (2012) The rare bacterial biosphere. Annu Rev Mar Sci 4:449–466

    Article  Google Scholar 

  22. Besemer K et al (2012) Unraveling assembly of stream biofilm communities. ISME J 6(8):1459–1468. https://doi.org/10.1038/ismej.2011.205

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. LeChevallier MW, Seidler RJ, Evans TM (1980) Enumeration and characterization of standard plate count bacteria in chlorinated and raw water supplies. Appl Environ Microbiol 40(5):922–930. https://doi.org/10.1128/aem.40.5.922-930.1980

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Staley JT, Konopka A (1985) Measurement of in situ activities of nonphotosynthetic microorganisms in aquatic and terrestrial habitats. Annu Rev Microbiol 39:321–346

    Article  CAS  PubMed  Google Scholar 

  25. Ward DM, Weller R, Bateson MM (1990) 16S rRNA sequences reveal numerous uncultured microorganisms in a natural community. Nature 345:63. https://doi.org/10.1038/345063a0

    Article  CAS  PubMed  Google Scholar 

  26. Schloss PD et al (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Caporaso JG et al (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5):335–336. https://doi.org/10.1038/nmeth.f.303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Cole JR et al (2014) Ribosomal database project: data and tools for high throughput rRNA analysis. Nucleic Acids Res 42(Database issue):D633–D642. https://doi.org/10.1093/nar/gkt1244

    Article  CAS  PubMed  Google Scholar 

  29. Larsen N et al (1993) The ribosomal database project. Nucleic Acids Res 21:3021–3023

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Maidak JR, Lilburn TG, Parker CT Jr, Saxman RJ, Garrity GM, Olsen GJ, Schmidt TM, Tiedje JM (2001) The RDP-II (ribosomal database project). Nucleic Acids Res 29:173–174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Pace NR, Stahl DA, Lane DJ, Olsen GJ (1986) The analysis of natural microbial populations by ribosomal RNA sequences. In: Marshall KC (ed) Advances in microbial ecology, vol 9. Springer, Boston. https://doi.org/10.1007/978-1-4757-0611-6_1

    Chapter  Google Scholar 

  32. Schmidt TM, DeLong EF, Pace NR (1991) Analysis of a marine picoplankton community by 16S rRNA gene cloning and sequencing. J Bacteriol 173(14):4371–4378. https://doi.org/10.1128/jb.173.14.4371-4378.1991

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Sanger F et al (1977) Nucleotide sequence of bacteriophage φx174 DNA. Nature 265:687–695. https://doi.org/10.1038/265687a0.

    Article  CAS  PubMed  Google Scholar 

  34. Schuster SC (2008) Next-generation sequencing transforms today’s biology. Nat Methods 5(1):16–18. https://doi.org/10.1038/nmeth1156

    Article  CAS  PubMed  Google Scholar 

  35. Pinto AJ, Xi C, Raskin L (2012) Bacterial community structure in the drinking water microbiome is governed by filtration processes. Environ Sci Technol 46(16):8851–8859. https://doi.org/10.1021/es302042t

    Article  CAS  PubMed  Google Scholar 

  36. Turnbaugh PJ et al (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444(7122):1027–1031. https://doi.org/10.1038/nature05414.

    Article  PubMed  Google Scholar 

  37. Arif I, Batool M, Schenk PM (2020) Plant microbiome engineering: expected benefits for improved crop growth and resilience. Trends Biotechnol 38(12):1385–1396. https://doi.org/10.1016/j.tibtech.2020.04.015

    Article  CAS  PubMed  Google Scholar 

  38. Vasileiadis S et al (2012) Soil bacterial diversity screening using single 16S rRNA gene V regions coupled with multi-million read generating sequencing technologies. PLoS One 7(8):e42671. https://doi.org/10.1371/journal.pone.0042671.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Kim M, Morrison M, Yu Z (2011) Evaluation of different partial 16S rRNA gene sequence regions for phylogenetic analysis of microbiomes. J Microbiol Methods 84(1):81–87. https://doi.org/10.1016/j.mimet.2010.10.020

    Article  CAS  PubMed  Google Scholar 

  40. Bruijns B, Tiggelaar R, Gardeniers R (2018) Massively parallel sequencing techniques for forensics: a review. Electrophoresis 39:2642–2654

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Fredricks DN (2001) Microbial ecology of human skin in health and disease. J Investig Dermatol Symp Proc 6:167–169. https://doi.org/10.1046/j.0022-202x.2001.00039.

    Article  CAS  PubMed  Google Scholar 

  42. Weinstein GD, McCullough JL, Ross P (1984) Cell proliferation in normal epidermis. J Investig Dermatol 82:623–628

    Article  CAS  PubMed  Google Scholar 

  43. Tong J, Li H (2014) The human skin. In: Marchesi RJ (ed) The human microbiota and microbiome. CABI, Oxfordshire, pp 72–89

    Chapter  Google Scholar 

  44. Leung MHY, Tong X, Wilkins D, Cheung HHL, Lee PKH (2018) Individual and household attributes influence the dynamics of the personal skin microbiota and its association network. Microbiome 6(1):26. Published 2018 Feb 2. https://doi.org/10.1186/s40168-018-0412-9

    Article  PubMed  PubMed Central  Google Scholar 

  45. Dréno B, Araviiskaia E, Berardesca E, Gontijo G, Sanchez Viera M, Xiang LF, Martin R, Bieber T (2016) Microbiome in healthy skin, update for dermatologists. J Eur Acad Dermatol Venereol 30(12):2038–2047. https://doi.org/10.1111/jdv.13965

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Grice EA, Kong HH, Conlan S, Deming CB, Davis J, Young AC et al (2009) Topographical and temporal diversity of the human skin microbiome. Science 324:1190–1192

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Costello EK, Lauber CL, Hamady M, Fierer N, Gordon JI, Knight R (2009) Bacterial community variation in human body habitats across space and time. Science 326:1694–1697

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Edgar RC (2018) Updating the 97% identity threshold for 16S ribosomal RNA OTUs. Bioinformatics 34(14):2371–2375. https://doi.org/10.1093/bioinformatics/bty113.

    Article  CAS  PubMed  Google Scholar 

  49. Fitz-Gibbon S, Tomida S, Chiu BH, Nguyen L, Du C, Liu M et al (2013) Propionibacterium acnes strain populations in the human skin microbiome associated with acne. J Investig Dermatol 133:2152–2160

    Article  CAS  PubMed  Google Scholar 

  50. Byrd AL, Belkaid Y, Segre JA (2018) The human skin microbiome. Nat Rev Microbiol 16(3):143–155. https://doi.org/10.1038/nrmicro.2017.157

    Article  CAS  PubMed  Google Scholar 

  51. Oh J, Byrd AL, Park M, NISC Comparative Sequencing Program, Kong HH, Segre JA (2016) Temporal stability of the human skin microbiome. Cell 165(4):854–866. https://doi.org/10.1016/j.cell.2016.04.008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Oh J, Byrd AL, Deming C et al (2014) Biogeography and individuality shape function in the human skin metagenome. Nature 514(7520):59–64. https://doi.org/10.1038/nature13786

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Fierer N, Hamady M, Lauber CL et al (2008) The influence of sex, handedness, and washing on the diversity of hand surface bacteria. Proc Natl Acad Sci U S A 105:17994–17999

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Bouslimani A, Porto C, Rath CM, Wang M, Guo Y, Gonzalez A et al (2015) Molecular cartography of the human skin surface in 3D. PNAS 112(17):E2120–E2129

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Finley S, Benbow ME, Javan G (2014) Microbial communities associated with human decomposition and their potential use as postmortem clocks. Int J Legal Med 129:623–632

    Article  PubMed  Google Scholar 

  56. Park J, Kim SJ, Lee JA, Kim JW, Kim SB (2017) Microbial forensic analysis of human-associated bacteria inhabiting hand surface. Forensic Sci Int Genet Suppl Ser 6:e510–e512

    Article  Google Scholar 

  57. Clarke TH, Gomez A, Singh H, Nelson KE, Brinkac LM (2017) Integrating the microbiome as a resource in the forensics toolkit. Forensic Sci Int Genet 30:141–147. https://doi.org/10.1016/j.fsigen.2017.06.008

    Article  CAS  PubMed  Google Scholar 

  58. Jain S, Kumar A, Gupta P, Prasad R (2005) Microbial forensics: a new forensic discipline. J Indian Acad Forensic Med 27(2). ISSN 0971-0973.

    Google Scholar 

  59. Pal P, Roy A, Moore G, Muzslay M, Lee E, Alder S, Wilson P, Powles T, Kelly J (2013) Keypad mobile phones are associated with a significant increased risk of microbial contamination compared to touch screen phones. J Infect Prev 14(2):65–68. https://doi.org/10.1177/1757177413475903

    Article  Google Scholar 

  60. Meadow JF, Altrichter AE, Green JL (2014) Mobile phones carry the personal microbiome of their owners. PeerJ 2:e447. https://doi.org/10.7717/peerj.447.

    Article  PubMed  PubMed Central  Google Scholar 

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Adserias-Garriga, J., Garcia-Gil, J.L. (2021). Latent Fingermarks and Microbiome: Time and Community Succession. In: De Alcaraz-Fossoul, J. (eds) Technologies for Fingermark Age Estimations: A Step Forward. Springer, Cham. https://doi.org/10.1007/978-3-030-69337-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-69337-4_11

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