OpenLB
Open Library of Bioscience
Advanced Search
International journal of legal medicine
Jul, 2025;139 (4): 1863-1877.

Microbiota signature of the lung as the promising bioindicator for drowning diagnosis and postmortem submersion interval estimation.

Kuo Zeng, Fu-Yuan Zhang, Ming-Zhe Wu, Hao-Miao Yuan, Shu-Kui Du, Jin-Cheng Ying, Yan Zhang, Lin-Lin Wang, Rui Zhao, Da-Wei Guan
Author Information
  1. Kuo Zeng: Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China.
  2. Fu-Yuan Zhang: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.
  3. Ming-Zhe Wu: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.
  4. Hao-Miao Yuan: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.
  5. Shu-Kui Du: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.
  6. Jin-Cheng Ying: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.
  7. Yan Zhang: Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China.
  8. Lin-Lin Wang: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China. wangll@cmu.edu.cn.
  9. Rui Zhao: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China. rzhao@cmu.edu.cn.
  10. Da-Wei Guan: Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China. dwguan@cmu.edu.cn.
PMID: 40067359 DOI: 10.1007/s00414-025-03458-6

Abstract

Drowning diagnosis and postmortem submersion interval (PMSI) estimation are still major challenges in forensic practice. Our recent studies provided evidence that microbiota successions in multiple organs, including intestine, liver, and brain, were valuable indicators for PMSI estimation. Meanwhile, microbiota in the lung from corpses submerged for 3 days presented obvious difference between drowning and postmortem submersion. However, gaps exist in our understanding of how long this difference lasts and how the decomposer microbial community in the lung changes with progression of decomposition. Here, we characterized the postmortem microbiota in the lung of mice submerged for 0 to 14 days, which were drowned or sacrificed by CO asphyxia. Our study revealed that most samples collected before 3 days postmortem were not qualified enough for sequencing. The microbiota in the lung was largely influenced by the microbes colonized in the aquatic environment. Differences in microbiota between drowning and postmortem submersion faded over decomposition and could be used for drowning diagnosis within 10 days postmortem. Meanwhile, 22 taxa with good discriminative ability were identified to establish the classification model for discriminating drowning and postmortem submersion (AUC = 0.92, accuracy = 81.25%) by random forest algorithm. Twenty other candidates exhibiting obviously temporal changes were selected for PMSI estimation, which yield satisfactory performance (mean absolute errors ± the standard error = 0.976 ± 0.189 d). Altogether, we provide further evidence that microbiota signature of the lung is a promising bioindicator for the forensic death investigations of decomposed bodies recovered from water.

Keywords

Aquatic habitat Decomposition Drowning diagnosis Microbial community Postmortem submersion interval

References

World Health Organization (2021) Drowning. https://www.who.int/en/news-room/fact-sheets/detail/drowning
Rutty GN, Bradley CJ, Biggs MJ, Hollingbury FE, Hamilton SJ, Malcomson RD, Holmes CW (2015) Detection of bacterioplankton using PCR probes as a diagnostic indicator for drowning; the Leicester experience. Leg Med (Tokyo) 17(5):401–408. https://doi.org/10.1016/j.legalmed.2015.06.001 [DOI: 10.1016/j.legalmed.2015.06.001]
Bierens JJ (2006) Handbook on drowning: prevention, rescue, treatment, vol 50. Springer Science & Business Media
Perez-Carceles MD, del Pozo S, Sibon A, Noguera JA, Osuna E, Vizcaya MA, Luna A (2012) Serum biochemical markers in drowning: diagnostic efficacy of strontium and other trace elements. Forensic Sci Int 214(1–3):159–166. https://doi.org/10.1016/j.forsciint.2011.07.047 [DOI: 10.1016/j.forsciint.2011.07.047]
Fucci N, Campobasso CP, Mastrogiuseppe L, Puccinelli C, Marcheggiani S, Mancini L, Marino L, Pascali VL (2017) Diatoms in drowning cases in forensic veterinary context: a preliminary study. Int J Legal Med 131(6):1573–1580. https://doi.org/10.1007/s00414-017-1565-y [DOI: 10.1007/s00414-017-1565-y]
Allam F, Ali DM, Ali SFE (2022) Drowning versus postmortem submersion: biochemical and histopathological examination and Estimation of postmortem intervals (an experimental study). Leg Med (Tokyo) 59:102138. https://doi.org/10.1016/j.legalmed.2022.102138 [DOI: 10.1016/j.legalmed.2022.102138]
Palazzo C, Pelletti G, Fais P, Boscolo-Berto R, Fersini F, Gaudio RM, Pelotti S (2020) Postmortem submersion interval in human bodies recovered from fresh water in an area of mediterranean climate. Application and comparison of preexisting models. Forensic Sci Int 306:110051. https://doi.org/10.1016/j.forsciint.2019.110051 [DOI: 10.1016/j.forsciint.2019.110051]
Palazzo C, Pelletti G, Fais P, Giorgetti A, Boscolo-Berto R, Gaudio RM, Pirani F, Tagliabracci A, Pelotti S (2021) Application of aquatic decomposition scores for the determination of the post mortem submersion interval on human bodies recovered from the Northern Adriatic sea. Forensic Sci Int 318:110599. https://doi.org/10.1016/j.forsciint.2020.110599 [DOI: 10.1016/j.forsciint.2020.110599]
Hyun CH, Kim H, Ryu S, Kim W (2019) Preliminary study on microeukaryotic community analysis using NGS technology to determine postmortem submersion interval (PMSI) in the drowned pig. J Microbiol 57(11):1003–1011. https://doi.org/10.1007/s12275-019-9198-0 [DOI: 10.1007/s12275-019-9198-0]
Verma MK, Ahmed V, Gupta S, Kumar J, Pandey R, Mandhan V, Chauhan NS (2018) Functional metagenomics identifies novel genes ABCTPP, TMSRP1 and TLSRP1 among human gut enterotypes. Sci Rep 8(1):1397. https://doi.org/10.1038/s41598-018-19862-5 [DOI: 10.1038/s41598-018-19862-5]
Dmitrijs F, Guo J, Huang Y, Liu Y, Fang X, Jiang K, Zha L, Cai J, Fu X (2022) Bacterial succession in microbial biofilm as a potential Indicator for postmortem submersion interval Estimation. Front Microbiol 13:951707. https://doi.org/10.3389/fmicb.2022.951707 [DOI: 10.3389/fmicb.2022.951707]
Lucci A, Campobasso CP, Cirnelli A, Lorenzini G (2008) A promising Microbiological test for the diagnosis of drowning. Forensic Sci Int 182(1–3):20–26. https://doi.org/10.1016/j.forsciint.2008.09.004 [DOI: 10.1016/j.forsciint.2008.09.004]
Cartozzo C, Simmons T, Swall J, Singh B (2021) Postmortem submersion interval (PMSI) Estimation from the Microbiome of Sus scrofa bone in a freshwater river. Forensic Sci Int 318:110480. https://doi.org/10.1016/j.forsciint.2020.110480 [DOI: 10.1016/j.forsciint.2020.110480]
Metcalf JL, Xu ZZ, Weiss S, Lax S, Van Treuren W, Hyde ER, Song SJ, Amir A, Larsen P, Sangwan N, Haarmann D, Humphrey GC, Ackermann G, Thompson LR, Lauber C, Bibat A, Nicholas C, Gebert MJ, Petrosino JF, Reed SC, Gilbert JA, Lynne AM, Bucheli SR, Carter DO, Knight R (2016) Microbial community assembly and metabolic function during mammalian corpse decomposition. Science 351(6269):158–162. https://doi.org/10.1126/science.aad2646 [DOI: 10.1126/science.aad2646]
Aoyagi M, Iwadate K, Fukui K, Abe S, Sakai K, Maebashi K, Ochiai E, Nakamura M (2009) A novel method for the diagnosis of drowning by detection of Aeromonas sobria with PCR method. Leg Med (Tokyo) 11(6):257–259. https://doi.org/10.1016/j.legalmed.2009.07.003 [DOI: 10.1016/j.legalmed.2009.07.003]
Kakizaki E, Takahama K, Seo Y, Kozawa S, Sakai M, Yukawa N (2008) Marine bacteria comprise a possible indicator of drowning in seawater. Forensic Sci Int 176(2–3):236–247. https://doi.org/10.1016/j.forsciint.2007.09.018 [DOI: 10.1016/j.forsciint.2007.09.018]
Wade W (2002) Unculturable bacteria–the uncharacterized organisms that cause oral infections. J R Soc Med 95(2):81–83. https://doi.org/10.1177/014107680209500207 [DOI: 10.1177/014107680209500207]
Belk A, Xu ZZ, Carter DO, Lynne A, Bucheli S, Knight R, Metcalf JL (2018) Microbiome data accurately predicts the postmortem interval using random forest regression models. Genes (Basel) 9(2). https://doi.org/10.3390/genes9020104
Dash HR, Das S (2020) Thanatomicrobiome and epinecrotic community signatures for Estimation of post-mortem time interval in human cadaver. Appl Microbiol Biotechnol 104(22):9497–9512. https://doi.org/10.1007/s00253-020-10922-3 [DOI: 10.1007/s00253-020-10922-3]
Emmons AL, Mundorff AZ, Hoeland KM, Davoren J, Keenan SW, Carter DO, Campagna SR, DeBruyn JM (2022) Postmortem skeletal microbial community composition and function. Buried Hum Remains mSystems 7(2):e0004122. https://doi.org/10.1128/msystems.00041-22 [DOI: 10.1128/msystems.00041-22]
Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, Prill RJ, Tripathi A, Gibbons SM, Ackermann G, Navas-Molina JA, Janssen S, Kopylova E, Vazquez-Baeza Y, Gonzalez A, Morton JT, Mirarab S, Zech Xu Z, Jiang L, Haroon MF, Kanbar J, Zhu Q, Jin Song S, Kosciolek T, Bokulich NA, Lefler J, Brislawn CJ, Humphrey G, Owens SM, Hampton-Marcell J, Berg-Lyons D, McKenzie V, Fierer N, Fuhrman JA, Clauset A, Stevens RL, Shade A, Pollard KS, Goodwin KD, Jansson JK, Gilbert JA, Knight R (2017) Earth Microbiome Project C A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551 (7681):457–463. https://doi.org/10.1038/nature24621
Wang LL, Zhang FY, Zeng K, Dong WW, Yuan HY, Wang ZW, Liu J, Pan JQ, Zhao R, Guan DW (2022) Microbial communities in the liver and brain are informative for postmortem submersion interval Estimation in the late phase of decomposition: A study in mouse cadavers recovered from freshwater. Front Microbiol. https://doi.org/10.3389/fmicb.2022.1052808 [DOI: 10.3389/fmicb.2022.1052808]
Zhang FY, Wang PF, Zeng K, Yuan HY, Wang ZW, Li XJ, Yuan HM, Du SK, Guan DW, Wang LL, Zhao R (2022) Postmortem submersion interval Estimation of cadavers recovered from freshwater based on gut microbial community succession. Front Microbiol. https://doi.org/10.3389/fmicb.2022.988297 [DOI: 10.3389/fmicb.2022.988297]
Wang LL, Zhang FY, Dong WW, Wang CL, Liang XY, Suo LL, Jian C, Zhang M, Guo XS, Jiang PH, Guan DW, Zhao R (2020) A novel approach for the forensic diagnosis of drowning by Microbiological analysis with next-generation sequencing and unweighted UniFrac-based PCoA. Int J Legal Med 134(6):2149–2159. https://doi.org/10.1007/s00414-020-02358-1 [DOI: 10.1007/s00414-020-02358-1]
Zhang FY, Wang LL, Dong WW, Zhang M, Tash D, Li XJ, Du SK, Yuan HM, Zhao R, Guan DW (2022) A preliminary study on early postmortem submersion interval (PMSI) Estimation and cause-of-death discrimination based on nontargeted metabolomics and machine learning algorithms. Int J Legal Med 136(3):941–954. https://doi.org/10.1007/s00414-022-02783-4 [DOI: 10.1007/s00414-022-02783-4]
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5):335–336. https://doi.org/10.1038/nmeth.f.303 [DOI: 10.1038/nmeth.f.303]
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, Bai Y, Bisanz JE, Bittinger K, Brejnrod A, Brislawn CJ, Brown CT, Callahan BJ, Caraballo-Rodriguez AM, Chase J, Cope EK, Da Silva R, Diener C, Dorrestein PC, Douglas GM, Durall DM, Duvallet C, Edwardson CF, Ernst M, Estaki M, Fouquier J, Gauglitz JM, Gibbons SM, Gibson DL, Gonzalez A, Gorlick K, Guo J, Hillmann B, Holmes S, Holste H, Huttenhower C, Huttley GA, Janssen S, Jarmusch AK, Jiang L, Kaehler BD, Kang KB, Keefe CR, Keim P, Kelley ST, Knights D, Koester I, Kosciolek T, Kreps J, Langille MGI, Lee J, Ley R, Liu YX, Loftfield E, Lozupone C, Maher M, Marotz C, Martin BD, McDonald D, McIver LJ, Melnik AV, Metcalf JL, Morgan SC, Morton JT, Naimey AT, Navas-Molina JA, Nothias LF, Orchanian SB, Pearson T, Peoples SL, Petras D, Preuss ML, Pruesse E, Rasmussen LB, Rivers A, Robeson MS 2nd, Rosenthal P, Segata N, Shaffer M, Shiffer A, Sinha R, Song SJ, Spear JR, Swafford AD, Thompson LR, Torres PJ, Trinh P, Tripathi A, Turnbaugh PJ, Ul-Hasan S, van der Hooft JJJ, Vargas F, Vazquez-Baeza Y, Vogtmann E, von Hippel M, Walters W, Wan Y, Wang M, Warren J, Weber KC, Williamson CHD, Willis AD, Xu ZZ, Zaneveld JR, Zhang Y, Zhu Q, Knight R, Caporaso JG (2019) Reproducible, interactive, scalable and extensible Microbiome data science using QIIME 2. Nat Biotechnol 37(8):852–857. https://doi.org/10.1038/s41587-019-0209-9 [DOI: 10.1038/s41587-019-0209-9]
Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26(19):2460–2461. https://doi.org/10.1093/bioinformatics/btq461 [DOI: 10.1093/bioinformatics/btq461]
Cole JR, Wang Q, Fish JA, Chai B, McGarrell DM, Sun Y, Brown CT, Porras-Alfaro A, Kuske CR, Tiedje JM (2014) Ribosomal database project: data and tools for high throughput rRNA analysis. Nucleic Acids Res 42(Database issue):D633–642. https://doi.org/10.1093/nar/gkt1244 [DOI: 10.1093/nar/gkt1244]
Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71(12):8228–8235. https://doi.org/10.1128/AEM.71.12.8228-8235.2005 [DOI: 10.1128/AEM.71.12.8228-8235.2005]
Shenhav L, Thompson M, Joseph TA, Briscoe L, Furman O, Bogumil D, Mizrahi I, Pe’er I, Halperin E (2019) FEAST: fast expectation-maximization for microbial source tracking. Nat Methods 16(7):627–632. https://doi.org/10.1038/s41592-019-0431-x [DOI: 10.1038/s41592-019-0431-x]
Breiman L (2001) Random forests. #N/A 45(1):5–32. https://doi.org/10.1023/A:1010933404324 [DOI: 10.1023/A]
Zhang FY, Wang LL, Zeng K, Dong WW, Yuan HY, Ma XY, Wang ZW, Zhao Y, Zhao R, Guan DW (2024) A fundamental study on postmortem submersion interval Estimation by metabolomics analyzing of gastrocnemius muscle from submersed rat models in freshwater. Int J Legal Med. https://doi.org/10.1007/s00414-024-03258-4 [DOI: 10.1007/s00414-024-03258-4]
Moitas B, Caldas IM, Sampaio-Maia B (2023) Microbiology and postmortem interval: a systematic review. Forensic Sci Med Pathol. https://doi.org/10.1007/s12024-023-00733-z [DOI: 10.1007/s12024-023-00733-z]
Franceschetti L, Lodetti G, Blandino A, Amadasi A, Bugelli V (2024) Exploring the role of the human Microbiome in forensic identification: opportunities and challenges. Int J Legal Med. https://doi.org/10.1007/s00414-024-03217-z [DOI: 10.1007/s00414-024-03217-z]
Garcia MG, Perez-Carceles MD, Osuna E, Legaz I (2020) Impact of the human Microbiome in forensic sciences: a systematic review. Appl Environ Microbiol 86(22). https://doi.org/10.1128/AEM.01451-20
Goncalves Pessoa RB, de Oliveira WF, Marques DSC, Dos Santos Correia MT, de Carvalho E, Coelho L (2019) The genus Aeromonas: A general approach. Microb Pathog 130:81–94. https://doi.org/10.1016/j.micpath.2019.02.036 [DOI: 10.1016/j.micpath.2019.02.036]
Wang Y, Wang M, Xu W, Wang Y, Zhang Y, Wang J (2021) Estimating the postmortem interval of carcasses in the water using the carrion insect, brain tissue RNA, bacterial biofilm, and algae. Front Microbiol 12:774276. https://doi.org/10.3389/fmicb.2021.774276 [DOI: 10.3389/fmicb.2021.774276]
Pechal JL, Schmidt CJ, Jordan HR, Benbow ME (2018) A large-scale survey of the postmortem human microbiome, and its potential to provide insight into the living health condition. Sci Rep 8(1):5724. https://doi.org/10.1038/s41598-018-23989-w [DOI: 10.1038/s41598-018-23989-w]
Kakizaki E, Kozawa S, Sakai M, Yukawa N (2009) Bioluminescent bacteria have potential as a marker of drowning in seawater: two immersed cadavers retrieved near estuaries. Leg Med (Tokyo) 11(2):91–96. https://doi.org/10.1016/j.legalmed.2008.10.004 [DOI: 10.1016/j.legalmed.2008.10.004]
Voloshynovych VM, Kasala RO, Stambulska UY, Voloshynovych MS (2019) Determination the presence of amplification products of 16s rRNA microcystis aeruginosa as a biomarker of drowning. Rom J Leg Med 27:16–21 [DOI: 10.4323/rjlm.2019.16]
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(1–3):135–146. https://doi.org/10.1016/j.forsciint.2012.02.010 [DOI: 10.1016/j.forsciint.2012.02.010]
Huys G, Coopman V, Van Varenbergh D, Cordonnier J (2012) Selective culturing and genus-specific PCR detection for identification of Aeromonas in tissue samples to assist the medico-legal diagnosis of death by drowning. Forensic Sci Int 221(1–3):11–15. https://doi.org/10.1016/j.forsciint.2012.03.017 [DOI: 10.1016/j.forsciint.2012.03.017]
Hau HH, Gralnick JA (2007) Ecology and biotechnology of the genus Shewanella. Annu Rev Microbiol 61:237–258. https://doi.org/10.1146/annurev.micro.61.080706.093257 [DOI: 10.1146/annurev.micro.61.080706.093257]
Maillot NJ, Honore FA, Byrne D, Mejean V, Genest O (2019) Cold adaptation in the environmental bacterium Shewanella oneidensis is controlled by a J-domain co-chaperone protein network. Commun Biol 2:323. https://doi.org/10.1038/s42003-019-0567-3 [DOI: 10.1038/s42003-019-0567-3]
Kakizaki E, Kozawa S, Imamura N, Uchiyama T, Nishida S, Sakai M, Yukawa N (2011) Detection of marine and freshwater bacterioplankton in immersed victims: Post-mortem bacterial invasion does not readily occur. Forensic Sci Int 211(1–3):9–18. https://doi.org/10.1016/j.forsciint.2011.03.036 [DOI: 10.1016/j.forsciint.2011.03.036]
Wallace JR, Receveur JP, Hutchinson PH, Kaszubinski SF, Wallace HE, Benbow ME (2021) Microbial community succession on submerged vertebrate carcasses in a tidal river habitat: implications for aquatic forensic investigations. J Forensic Sci 66(6):2307–2318. https://doi.org/10.1111/1556-4029.14869 [DOI: 10.1111/1556-4029.14869]
Can I, Javan GT, Pozhitkov AE, Noble PA (2014) Distinctive thanatomicrobiome signatures found in the blood and internal organs of humans. J Microbiol Methods 106:1–7. https://doi.org/10.1016/j.mimet.2014.07.026 [DOI: 10.1016/j.mimet.2014.07.026]
Javan GT, Finley SJ, Smith T, Miller J, Wilkinson JE (2017) Cadaver thanatomicrobiome signatures: the ubiquitous nature of Clostridium species in human decomposition. Front Microbiol 8:2096. https://doi.org/10.3389/fmicb.2017.02096 [DOI: 10.3389/fmicb.2017.02096]
Johnson HR, Trinidad DD, Guzman S, Khan Z, Parziale JV, DeBruyn JM, Lents NH (2016) A machine learning approach for using the postmortem skin Microbiome to estimate the postmortem interval. PLoS ONE 11(12):e0167370. https://doi.org/10.1371/journal.pone.0167370 [DOI: 10.1371/journal.pone.0167370]

Grants

  1. 2022YFC3302002/National Key Research and Development Program of China
  2. 2023YFC3303902/National Key Research and Development Program of China
  3. 2022JH2/20200028/Program of Science and Technology of Liaoning Province
  4. LJ212410159041/Liaoning Provincial Department of Education Science Research Project
  5. 2023-PYKT-002/Cultivation Project of the Liaoning Province Key Laboratory of Forensic Bio-evidence Science
  6. 202410159044/College Students' Innovative Entrepreneurial Training Plan Program

MeSH Term

Lung
Drowning
Animals
Postmortem Changes
Microbiota
Immersion
Male
Mice
RNA, Ribosomal, 16S
Forensic Pathology
Mice, Inbred C57BL

Chemicals

RNA, Ribosomal, 16S
Journal Article

Word Cloud

Similar Articles

Cited By