Postmortem Microbiome Research Articles

Decomposition in an extreme cold environment and associated microbiome-prediction model implications for the postmortem interval estimation.

The accurate estimation of postmortem interval (PMI), the time between death and discovery of the body, is crucial in forensic science investigations as it impacts legal outcomes. PMI estimation in extremely cold environments becomes susceptible to errors and misinterpretations, especially with prolonged PMIs. This study addresses the lack of data on decomposition in extreme cold by providing the first overview of decomposition in such settings. Moreover, it proposes the first postmortem microbiome prediction model for PMI estimation in cold environments, applicable even when the visual decomposition is halted. The experiment was conducted on animal models in the second-coldest region in the United States, Grand Forks, North Dakota, and covered 23 weeks, including the winter months with temperatures as low as -39°C. Random Forest analysis models were developed to estimate the PMI based either uniquely on 16s rRNA gene microbial data derived from nasal swabs or based on both microbial data and measurable environmental parameters such as snow depth and outdoor temperatures, on a total of 393 samples. Among the six developed models, the best performing one was the complex model based on both internal and external swabs. It achieved a Mean Absolute Error (MAE) of 1.36 weeks and an R2 value of 0.91. On the other hand, the worst performing model was the minimal one that relied solely on external swabs. It had an MAE of 2.89 weeks and an R2 of 0.73. Furthermore, among the six developed models, the commonly identified predictors across at least five out of six models included the following genera: Psychrobacter (ASV1925 and ASV1929), Carnobacterium (ASV2872) and Pseudomonas (ASV1863). The outcome of this research provides the first microbial model able to predict PMI with an accuracy of 9.52 days over a six-month period of extreme winter conditions.

The Future Is Now: Unraveling the Expanding Potential of Human (Necro)Microbiome in Forensic Investigations.

The relevance of postmortem microbiological examinations has been controversial for decades, but the boom in advanced sequencing techniques over the last decade is increasingly demonstrating their usefulness, namely for the estimation of the postmortem interval. This comprehensive review aims to present the current knowledge about the human postmortem microbiome (the necrobiome), highlighting the main factors influencing this complex process and discussing the principal applications in the field of forensic sciences. Several limitations still hindering the implementation of forensic microbiology, such as small-scale studies, the lack of a universal/harmonized workflow for DNA extraction and sequencing technology, variability in the human microbiome, and limited access to human cadavers, are discussed. Future research in the field should focus on identifying stable biomarkers within the dominant Bacillota and Pseudomonadota phyla, which are prevalent during postmortem periods and for which standardization, method consolidation, and establishment of a forensic microbial bank are crucial for consistency and comparability. Given the complexity of identifying unique postmortem microbial signatures for robust databases, a promising future approach may involve deepening our understanding of specific bacterial species/strains that can serve as reliable postmortem interval indicators during the process of body decomposition. Microorganisms might have the potential to complement routine forensic tests in judicial processes, requiring robust investigations and machine-learning models to bridge knowledge gaps and adhere to Locard's principle of trace evidence.

The impact of freezing on the post-mortem human microbiome

IntroductionHuman donations are often used in forensic research as they can provide unique insights into post-mortem research that cannot be obtained with animal proxies. This is especially true for forensic microbiome research, as human circumstances such as drug-use or health conditions may influence the post-mortem microbiome. However, it is not always feasible to conduct such research immediately after death. Donors are often stored frozen in human taphonomy facilities, pending the start of any experimental study, yet little is known about how freezing may affect their microbiome.MethodsWe assessed the effects of freezing on the post-mortem human microbiome by analysing the microbial diversity and abundance of seven human donors at the Forensic Anthropology Center at Texas State (FACTS) before and after freezing. Swab samples were taken from five locations on each corpse upon arrival to FACTS and again after they had been frozen in storage for a period ranging between 11 and 40 days and subsequently thawed.ResultsAfter performing the microbiome analysis of the swabs via 16S rRNA gene metabarcoding, we found changes in the abundance levels of Proteobacteria, Bacteroidota and Firmicutes, as well as the presence of the new phyla Deinococcota and Myxococcota after freezing. However, none of these changes were significant when comparing community diversity before and after freezing.DiscussionOverall, our results show that the observed changes in the abundance of specific phyla before and after freezing are negligible, that freezing does not significantly alter the human microbiome and that frozen donors are suitable for forensic studies on the human thanatomicrobiome.

Practical value of microorganisms for forensic purposes (on the example of microbial flora of bony remnants from the historic burial site)

Phenotypic signs of dominants isolated from the surface of bony remnants from the historic burial site were analyzed in order to expand data on the biodiversity of microorganisms in the microbial flora of bony remnants and to assess the possibility of using the results of microbiological analysis in the evidence base of forensic examination and forensic archaeology. It was detected that only Deuteromycota and Eubacteria colonized all types of surfaces in the samples of bone fragments from the historic burial site (with the age in the range of 90-95 years); with the abundance of micromycetes, the proportion of Eubacteria naturally decreased, while with the increased bacterial background counts the rate of micromycetes detection decreased. The insignificant amount of nutrients in the bony remnants led to the decrease in the number and biological diversity of microorganisms contaminating them; species adapted to a hard-to-reach organic substrate dominated there. During the process of bony remnants decomposition, when the conditions of their location changed, inter-species competition and specific recolonization occurred by species of microorganisms most adapted to a hard-to-reach organic substrate in the abiotic and biotic conditions of existence given. The results obtained are important for the descriptive ecology and biology of specific groups of microorganisms in the postmortem microbiome and form the basis for a more thorough study of complex communications between species of microorganisms in the necrobiome of bony remnants - in the future it will allow putting forward original hypotheses about the involvement of microbes in the circulation of matter and energy, as well as to apply the information obtained in the evidence base of forensic examination and forensic archaeology.

The devil is in the details: Variable impacts of season, BMI, sampling site temperature, and presence of insects on the post-mortem microbiome.

Post-mortem microbial communities are increasingly investigated as proxy evidence for a variety of factors of interest in forensic science. The reported predictive power of the microbial community to determine aspects of the individual's post-mortem history (e.g., the post-mortem interval) varies substantially among published research. This observed variation is partially driven by the local environment or the individual themselves. In the current study, we investigated the impact of BMI, sex, insect activity, season, repeat sampling, decomposition time, and temperature on the microbial community sampled from donated human remains in San Marcos, TX using a high-throughput gene-fragment metabarcoding approach. In the current study, we investigated the impact of BMI, sex, insect activity, season, repeat sampling, decomposition time, and temperature on the microbial community sampled from donated human remains in San Marcos, TX using a high-throughput gene-fragment metabarcoding approach. We found that season, temperature at the sampling site, BMI, and sex had a significant effect on the post-mortem microbiome, the presence of insects has a homogenizing influence on the total bacterial community, and that community consistency from repeat sampling decreases as the decomposition process progresses. Moreover, we demonstrate the importance of temperature at the site of sampling on the abundance of important diagnostic taxa. The results of this study suggest that while the bacterial community or specific bacterial species may prove to be useful for forensic applications, a clearer understanding of the mechanisms underpinning microbial decomposition will greatly increase the utility of microbial evidence in forensic casework.

Correlation between postmortem microbial signatures and substance abuse disorders.

The microbiota gut-brain-axis is a bidirectional circuit that links the neural, endocrine, and immunological systems with gut microbial communities. The gut microbiome plays significant roles in human mind and behavior, specifically pain perception, learning capacity, memory, and temperament. Studies have shown that disruptions in the gut microbiota have been associated with substance use disorders. The interplay of gut microbiota in substance abuse disorders has not been elucidated; however, postmortem microbiome profiles may produce promising avenues for future forensic investigations. The goal of the current study was to determine gut microbiome composition in substance abuse disorder cases using transverse colon tissues of 21 drug overdose versus 19 non-overdose-related cases. We hypothesized that postmortem samples of the same cause of death will reveal similar microbial taxonomic relationships. We compared microbial diversity profiles using amplicon-based sequencing of the 16S rRNA gene V4 hypervariable region. The results demonstrated that the microbial abundance in younger-aged cases were found to have significantly more operational taxonomic units than older cases. Using weighted UniFrac analysis, the influence of substances in overdose cases was found to be a significant factor in determining microbiome similarity. The results also revealed that samples of the same cause of death cluster together, showing a high degree of similarity between samples and a low degree of similarity among samples of different causes of death. In conclusion, our examination of human transverse colon microflora in decomposing remains extends emerging literature on postmortem microbial communities, which will ultimately contribute to advanced knowledge of human putrefaction.

The role of postmortem microbiome knowledge in veterinary medicine

The role of postmortem microbiome knowledge in veterinary medicine

MALDI-TOF Mass Spectrometry Analysis and Human Post-Mortem Microbial Community: A Pilot Study.

Introduction: The human post-mortem microbiome (HPM) plays a major role in the decomposition process. Successional changes in post-mortem bacterial communities have been recently demonstrated using high throughput metagenomic sequencing techniques, showing great potential as a post-mortem interval (PMI) predictor. The aim of this study is to verify the application of the mass spectrometry technique, better known as MALDI-TOF MS (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry), as a cheap and quick method for microbe taxonomic identification and for studying the PM microbiome. Methods: The study was carried out on 18 human bodies, ranging from 4 months to 82 years old and with a PMI range from 24 h up to 15 days. The storage time interval in the coolers was included in the final PMI estimates. Using the PMI, the sample study was divided into three main groups: seven cases with a PMI < 72 h; six cases with a PMI of 72–168 h and five cases with a PMI > 168 h. For each body, microbiological swabs were sampled from five external anatomical sites (eyes, ears, nose, mouth, and rectum) and four internal organs (brain, spleen, liver, and heart). Results: The HPM became increasingly different from the starting communities over time in the internal organs as well as at skin sites; the HPM microbiome was mostly dominated by Firmicutes and Proteobacteria phyla; and a PM microbial turnover existed during decomposition, evolving with the PMI. Conclusions: MALDI-TOF is a promising method for PMI estimation, given its sample handling, good reproducibility, and high speed and throughput. Although several intrinsic and extrinsic factors can affect the structure of the HPM, MALDI-TOF can detect the overall microbial community turnover of most prevalent phyla during decomposition. Limitations are mainly related to its sensitivity due to the culture-dependent method and bias in the identification of new isolates.

Microbial community succession of submerged bones in an aquatic habitat.

After death, microbes (including bacteria and fungi) colonize carrion from a variety of sources during the decomposition process. The predictable succession of microbes could be useful for forensics, such as postmortem submersion interval estimation (PMSI) for aquatic deaths. However, gaps exist in our understanding of microbial succession on submerged bone, particularly regarding longer-term decomposition (>1year), fungal composition, and differences between internal and external microbial communities. To further explore this potential forensic tool, we described the postmortem microbial communities (bacteria and fungi) on and within submerged bones using targeted amplicon sequencing. We hypothesized predictable successional patterns of microbial colonization would be detected on the surface and within submerged bones, which would eventually converge to a similar microbial community. To best replicate forensic contexts, we sampled bones from replicate swine (Sus scrofa domesticus) carcasses submerged in a freshwater pond, every three months for nearly two years. Microbial bone (internal vs. external) community structure (taxa abundance and diversity) of bones differed for both bacteria and fungi, but internal and external communities did not converge to a similar structure. PMSI estimation models built with random forest regression of postmortem microbiomes were highly accurate (>80% variation explained in PMSI) and showed promise for forensic purposes. Overall, we provide further evidence that internal and external bone microbial communities submerged in an aquatic habitat are distinct and each community undergoes predictable succession, demonstrating potential utility in forensics for modeling PMSI in unattended deaths and/or cold cases.

Microbial Clock: A review on forensic microbiology for crime scene investigations

As with other branches of forensic science, forensic microbiology is the study of the microbes associated with a cadaver to determine Time Since Death, Post Mortem Interval, and also identify the cause of death and personal identification. The advent of forensic microbiology and metagenomics has been aided by advances in genetic sequencing technologies, which have improved microbiological sample techniques and dramatically evolved bioinformatics pipelines. Humans carry a variety of microbial communities in and on their bodies, which constantly interact with and change their surroundings. Main Body of the Abstract: We reviewed more than 80 papers that detailed various aspects of the Post-Mortem Microbiome in terms of the Microbial Clock to identify such as geolocation, personal identification, trace evidence, manner and cause of death, postmortem interval and Time Since Death. The fact that much of the research is carried out in mouse and swine models, which are often hard to emulate in human and real-time circumstances, is a key challenge for forensic medical and microbiological research Short Conclusion: To fully grasp its promise of individual Post-Mortem microbiome characterization in forensic sciences, we must include technology innovations that are either currently accessible or are being developed. Sophisticated microbial fingerprint and DNA recoverability would allow the detection of both victims and perpetrators, which are all greatly facilitated by a thorough understanding of the decomposition process. The review to address these obstacles is continuing, and microbiome-based evidence would be expected to play a role in crime scene investigations in the soon.

Estimation of time since death with the postmortem microbiome: a modern view and approaches to solving the problem

The aim of the review is to summarize and update the data of modern studies devoted to determining the post-mortem interval (PMI) with the use of microorganisms, as well as disclosing prospects for further study in the presented direction. Estimating the time elapsed since death based on the postmortem microbiome has great potential for accurate determination of PMI, but all methods currently used have their limitations. The dynamics of changes in microbial communities due to the influence of many external and internal factors significantly complicates the process of interpreting the results. The change of microbial communities in the human corpse has shown promising results for the assessment of PMI, but to date there is no evidence of the repeatability of such a continuity in various geographic and ecological conditions. The question of conducting new, large-scale studies, taking in all the factors that could affect the posthumous microbiome, is becoming urgent.

Ecological aspects of postmortem microbiome and possibility of their use in forensic practice

Through experimental reproduction of the decomposition process using the cadaver of rabbit Oryctolagus sp., the dynamics of cadaver microflora was studied; the dominant bacterial taxa were isolated in pure culture and identified; their ecological and trophic profiles and biodiversity were described based on the values of Simpson and Menchinic ecological indices. The dependence of cadaver rotting and skeletonization rate on the taxonomic profile of microorganisms, decomposition period, and abiotic environmental factors (temperature, acidity, soil moisture) was demonstrated. The data obtained contribute to justifying the use of microbiological methods in forensic practice. To establish objective causality patterns of microbial transformation of organic matter in nature, further targeted study of ecological patterns of cadaveric microflora is necessary.

At the Interface of Life and Death: Post-mortem and Other Applications of Vaginal, Skin, and Salivary Microbiome Analysis in Forensics.

Microbial forensics represents a promising tool to strengthen traditional forensic investigative methods and fill related knowledge gaps. Large-scale microbiome studies indicate that microbial fingerprinting can assist forensics in areas such as trace evidence, source tracking, geolocation, and circumstances of death. Nevertheless, the majority of forensic microbiome studies focus on soil and internal organ samples, whereas the microbiome of skin, mouth, and especially vaginal samples that are routinely collected in sexual assault and femicide cases remain underexplored. This review discusses the current and emerging insights into vaginal, skin, and salivary microbiome-modulating factors during life (e.g., lifestyle and health status) and after death (e.g., environmental influences and post-mortem interval) based on next-generation sequencing. We specifically highlight the key aspects of female reproductive tract, skin, and mouth microbiome samples relevant in forensics. To fill the current knowledge gaps, future research should focus on the degree to which the post-mortem succession rate and profiles of vaginal, skin, and saliva microbiota are sensitive to abiotic and biotic factors, presence or absence of oxygen and other gases, and the nutrient richness of the environment. Application of this microbiome-related knowledge could provide valuable complementary data to strengthen forensic cases, for example, to shed light on the circumstances surrounding death with (post-mortem) microbial fingerprinting. Overall, this review synthesizes the present knowledge and aims to provide a framework to adequately comprehend the hurdles and potential application of vaginal, skin, and salivary post-mortem microbiomes in forensic investigations.

Characterization of Bacterial Community Dynamics of the Human Mouth Throughout Decomposition via Metagenomic, Metatranscriptomic, and Culturing Techniques.

The postmortem microbiome has recently moved to the forefront of forensic research, and many studies have focused on the idea that predictable fluctuations in decomposer communities could be used as a “microbial clock” to determine time of death. Commonly, the oral microbiome has been evaluated using 16S rRNA gene sequencing to assess the changes in community composition throughout decomposition. We sampled the hard palates of three human donors over time to identify the prominent members of the microbiome. This study combined 16S rRNA sequencing with whole metagenomic (MetaG) and metatranscriptomic (MetaT) sequencing and culturing methodologies in an attempt to broaden current knowledge about how these postmortem microbiota change and might function throughout decomposition. In all four methods, Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were the dominant phyla, but their distributions were insufficient in separating samples based on decomposition stage or time or by donor. Better resolution was observed at the level of genus, with fresher samples from decomposition clustering away from others via principal components analysis (PCA) of the sequencing data. Key genera in driving these trends included Rothia; Lysinibacillus, Lactobacillus, Staphylococcus, and other Firmicutes; and yeasts including Candida and Yarrowia. The majority of cultures (89%) matched to sequences obtained from at least one of the sequencing methods, while 11 cultures were found in the same samples using all three methods. These included Acinetobacter gerneri, Comamonas terrigena, Morganella morganii, Proteus vulgaris, Pseudomonas koreensis, Pseudomonas moraviensis, Raoutella terrigena, Stenotrophomonas maltophilia, Bacillus cereus, Kurthia zopfii, and Lactobacillus paracasei. MetaG and MetaT data also revealed many novel insects as likely visitors to the donors in this study, opening the door to investigating them as potential vectors of microorganisms during decomposition. The presence of cultures at specific time points in decomposition, including samples for which we have MetaT data, will yield future studies tying specific taxa to metabolic pathways involved in decomposition. Overall, we have shown that our 16S rRNA sequencing results from the human hard palate are consistent with other studies and have expanded on the range of taxa shown to be associated with human decomposition, including eukaryotes, based on additional sequencing technologies.

Dysbiosis in the Dead: Human Postmortem Microbiome Beta-Dispersion as an Indicator of Manner and Cause of Death.

The postmortem microbiome plays an important functional role in host decomposition after death. Postmortem microbiome community successional patterns are specific to body site, with a significant shift in composition 48 h after death. While the postmortem microbiome has important forensic applications for postmortem interval estimation, it also has the potential to aid in manner of death (MOD) and cause of death (COD) determination as a reflection of antemortem health status. To further explore this association, we tested beta-dispersion, or the variability of microbiomes within the context of the “Anna Karenina Principle” (AKP). The foundational principle of AKP is that stressors affect microbiomes in unpredictable ways, which increases community beta-dispersion. We hypothesized that cases with identified M/CODs would have differential community beta-dispersion that reflected antemortem conditions, specifically that cardiovascular disease and/or natural deaths would have higher beta-dispersion compared to other deaths (e.g., accidents, drug-related deaths). Using a published microbiome data set of 188 postmortem cases (five body sites per case) collected during routine autopsy in Wayne County (Detroit), MI, we modeled beta-dispersion to test for M/COD associations a priori. Logistic regression models of beta-dispersion and case demographic data were used to classify M/COD. We demonstrated that beta-dispersion, along with case demographic data, could distinguish among M/COD – especially cardiovascular disease and drug related deaths, which were correctly classified in 79% of cases. Binary logistic regression models had higher correct classifications than multinomial logistic regression models, but changing the defined microbial community (e.g., full vs. non-core communities) used to calculate beta-dispersion overall did not improve model classification or M/COD. Furthermore, we tested our analytic approach on a case study that predicted suicides from other deaths, as well as distinguishing MOD (e.g., homicides vs. suicides) within COD (e.g., gunshot wound). We propose an analytical workflow that combines postmortem microbiome indicator taxa, beta-dispersion, and case demographic data for predicting MOD and COD classifications. Overall, we provide further evidence the postmortem microbiome is linked to the host’s antemortem health condition(s), while also demonstrating the potential utility of including beta-dispersion (a non-taxon dependent approach) coupled with case demographic data for death determination.

Cold Case Experiment Demonstrates the Potential Utility of Aquatic Microbial Community Assembly in Estimating a Postmortem Submersion Interval.

Microbial community assembly (MCA) of both human and nonhuman animal carcasses provides indicators useful for estimating the postmortem interval (PMI) in terrestrial settings. However, there are fewer studies estimating postmortem submersion intervals (PMSIs) in aquatic habitats. No aquatic studies to date assessed MCA in the context of a death investigation, with all previous studies focusing on important basic ecological questions. Within the context of a cold case investigation, we performed an experiment using replicate adult swine carcasses to describe postmortem MCA variability within a nonflowing aquatic habitat. Using high-throughput sequencing of carcass postmortem microbiomes, we described MCA variability and identified key taxa associated with decomposition in an aquatic habitat similar to the cold case body recovery site. We also modeled key taxa for estimating PMSIs, modeling within ±3days (mean square error) postmortem using random forest regression. Our findings show significant changes in microbial communities as decomposition progressed, and several taxa were identified as important indicator taxa which may be useful for future estimates of PMSI. While descriptive, this study provides initial findings quantifying MCA variability within a nonflowing aquatic habitat. Within the context of the cold case investigation, we discuss how postmortem microbial samples collected at the time of body recovery could have been an important piece of evidence for understanding the PMSI of recovered remains. Additional experimental studies are needed to explicitly test and identify mechanisms associated with postmortem MCA variability in other habitats and under different temperature (e.g., seasons) conditions.

Evaluating Bioinformatic Pipeline Performance for Forensic Microbiome Analysis*,†,‡.

Microbial communities have potential evidential utility for forensic applications. However, bioinformatic analysis of high-throughput sequencing data varies widely among laboratories. These differences can potentially affect microbial community composition and downstream analyses. To illustrate the importance of standardizing methodology, we compared analyses of postmortem microbiome samples using several bioinformatic pipelines, varying minimum library size or minimum number of sequences per sample, and sample size. Using the same input sequence data, we found that three open-source bioinformatic pipelines, MG-RAST, mothur, and QIIME2, had significant differences in relative abundance, alpha-diversity, and beta-diversity, despite the same input data. Increasing minimum library size and sample size increased the number of low-abundant and infrequent taxa detected. Our results show that bioinformatic pipeline and parameter choice affect results in important ways. Given the growing potential application of forensic microbiology to the criminal justice system, continued research on standardizing computational methodology will be important for downstream applications.

Total RNA Analysis of Bacterial Community Structural and Functional Shifts Throughout Vertebrate Decomposition.

Multiple methods have been proposed to provide accurate time since death estimations, and recently, the discovery of bacterial community turnover during decomposition has shown itself to have predictable patterns that may prove useful. In this study, we demonstrate the use of metatranscriptomics from the postmortem microbiome to simultaneously obtain community structure and functional data across postmortem intervals (PMIs). We found that bacterial succession patterns reveal similar trends as detected through DNA analysis, such as increasing Clostridiaceae as decomposition occurs, strengthening the reliability of total RNA community analyses. We also provide one of the first analyses of RNA transcripts to characterize bacterial metabolic pathways during decomposition. We found distinct pathways, such as amino acid metabolism, to be strongly up-regulated with increasing PMIs. Elucidating the metabolic activity of postmortem microbial communities provides the first steps to discovering postmortem functional biomarkers since functional redundancy across bacteria may reduce host individual microbiome variability.

Machine learning performance in a microbial molecular autopsy context: A cross-sectional postmortem human population study.

BackgroundThe postmortem microbiome can provide valuable information to a death investigation and to the human health of the once living. Microbiome sequencing produces, in general, large multi-dimensional datasets that can be difficult to analyze and interpret. Machine learning methods can be useful in overcoming this analytical challenge. However, different methods employ distinct strategies to handle complex datasets. It is unclear whether one method is more appropriate than others for modeling postmortem microbiomes and their ability to predict attributes of interest in death investigations, which require understanding of how the microbial communities change after death and may represent those of the once living host.Methods and findingsPostmortem microbiomes were collected by swabbing five anatomical areas during routine death investigation, sequenced and analyzed from 188 death cases. Three machine learning methods (boosted algorithms, random forests, and neural networks) were compared with respect to their abilities to predict case attributes: postmortem interval (PMI), location of death, and manner of death. Accuracy depended on the method used, the numbers of anatomical areas analyzed, and the predicted attribute of death.ConclusionsAll algorithms performed well but with distinct features to their performance. Xgboost often produced the most accurate predictions but may also be more prone to overfitting. Random forest was the most stable across predictions that included more anatomic areas. Analysis of postmortem microbiota from more than three anatomic areas appears to yield limited returns on accuracy, with the eyes and rectum providing the most useful information correlating with circumstances of death in most cases for this dataset.

Detection of critical antibiotic resistance genes through routine microbiome surveillance.

Population-based public health data on antibiotic resistance gene carriage is poorly surveyed. Research of the human microbiome as an antibiotic resistance reservoir has primarily focused on gut associated microbial communities, but data have shown more widespread microbial colonization across organs than originally believed, with organs previously considered as sterile being colonized. Our study demonstrates the utility of postmortem microbiome sampling during routine autopsy as a method to survey antibiotic resistance carriage in a general population. Postmortem microbial sampling detected pathogens of public health concern including genes for multidrug efflux pumps, carbapenem, methicillin, vancomycin, and polymixin resistances. Results suggest that postmortem assessments of host-associated microbial communities are useful in acquiring community specific data while reducing selective-participant biases.