A microbial clock provides an accurate estimate of the postmortem interval in a mouse model system

Frozen: Thawing and Its Effect on the Postmortem Microbiome in Two Pediatric Cases. J Forensic Sci 2017;62:1399-1405. [PMID: 28120409 DOI: 10.1111/1556-4029.13419]

Previous postmortem microbiome studies have focused on characterizing taxa turnover during an undisturbed decomposition process. How coexisting conditions (e.g., frozen, buried, burned) affect the human microbiome at the time of discovery is less well understood. Microbiome data were collected from two pediatric cases at the Wayne County Medical Examiner in Michigan. The bodies were found frozen, hidden in a freezer for an extended time. Microbial communities were sampled from six external anatomic locations at three time points during the thawing process, prior to autopsy. The 16S rRNA V4 gene amplicon region was sequenced using high-throughput sequencing (Illumina MiSeq). Microbial diversity increased, and there was a distinct shift in microbial community structure and abundance throughout the thawing process. Overall, these data demonstrate that the postmortem human microbiome changes during the thawing process, and have important forensic implications when bodies have been substantially altered, modified, and concealed after death.

A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem Interval

Research on the human microbiome, the microbiota that live in, on, and around the human person, has revolutionized our understanding of the complex interactions between microbial life and human health and disease. The microbiome may also provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death. Current methods of estimating PMI for cadavers discovered in uncontrolled, unstudied environments have substantial limitations, some of which may be overcome through the use of microbial indicators. In this project, we sampled the microbiomes of decomposing human cadavers, focusing on the skin microbiota found in the nasal and ear canals. We then developed several models of statistical regression to establish an algorithm for predicting the PMI of microbial samples. We found that the complete data set, rather than a curated list of indicator species, was preferred for training the regressor. We further found that genus and family, rather than species, are the most informative taxonomic levels. Finally, we developed a k-nearest- neighbor regressor, tuned with the entire data set from all nasal and ear samples, that predicts the PMI of unknown samples with an average error of ±55 accumulated degree days (ADD). This study outlines a machine learning approach for the use of necrobiome data in the prediction of the PMI and thereby provides a successful proof-of- concept that skin microbiota is a promising tool in forensic death investigations.

Effect of Substrate on Identification of Microbial Communities in Poultry Carcass Composting and Microorganisms Associated with Poultry Carcass Decomposition

Three composting systems, which consisted of different ratios of chicken manure, sawdust, and poultry carcasses, were used to investigate the effect of substrate on the identification of microbial communities and microorganisms associated with poultry carcass decomposition by characterizing the microbial communities and physicochemical parameters. The physicochemical and Miseq Illumina sequencing results showed the composition of substrate had a significant effect on the identification and metabolic capabilities of microbial communities in decomposting process. Poultry carcasses might be the potential driver for the identification of bacterial communities in poultry carcass composting, whereas the initial C/N ratio may mainly contribute to the diversity of fungal communities and the similar dominant microbial communities in treatments. Poultry carcasses and initial C/N ratio could respectively affect the composition and abundance of microorganisms associated with the decomposition of poultry carcasses. Understanding the potential composting driver could allow development of an efficient carcass degradation system.

Human Thanatomicrobiome Succession and Time Since Death

The thanatomicrobiome (thanatos, Greek for death) is a relatively new term and is the study of the microbes colonizing the internal organs and orifices after death. Recent scientific breakthroughs in an initial study of the thanatomicrobiome have revealed that a majority of the microbes within the human body are the obligate anaerobes, Clostridium spp., in the internal postmortem microbial communities. We hypothesized that time-dependent changes in the thanatomicrobiome within internal organs can estimate the time of death as a human body decays. Here we report a cross-sectional study of the sampling of 27 human corpses from criminal cases with postmortem intervals between 3.5–240 hours. The impetus for examining microbial communities in different internal organs is to address the paucity of empirical data on thanatomicrobiomic succession caused by the limited access to these organs prior to death and a dearth of knowledge regarding the movement of microbes within remains. Our sequencing results of 16S rRNA gene amplicons of 27 postmortem samples from cadavers demonstrated statistically significant time-, organ-, and sex-dependent changes. These results suggest that comprehensive knowledge of the number and abundance of each organ’s signature microorganisms could be useful to forensic microbiologists as a new source of data for estimating postmortem interval.

Microbial effects on the development of forensically important blow fly species

Colonisation times and development rates of specific blow fly species are used to estimate the minimum Post Mortem Interval (mPMI). The presence or absence of bacteria on a corpse can potentially affect the development and survival of blow fly larvae. Therefore an understanding of microbial-insect interactions is important for improving the interpretation of mPMI estimations. In this study, the effect of two bacteria (Escherichia coli and Staphylococcus aureus) on the growth rate and survival of three forensically important blow fly species (Lucilia sericata, Calliphora vicina and Calliphora vomitoria) was investigated. Sterile larvae were raised in a controlled environment (16:8h day: night light cycle, 23:21°C day: night temperature cycle and a constant 35% relative humidity) on four artificial diets prepared with 100μl of 10(5) CFU bacterial solutions as follows: (1) E. coli, (2) S. aureus, (3) a 50:50 E. coli:S. aureus mix and (4) a sterile bacteria-free control diet. Daily measurements (length, width and weight) were taken from first instar larvae through to the emergence of adult flies. Survival rates were also determined at pupation and adult emergence. Results indicate that bacteria were not essential for the development of any of the blow fly species. However, larval growth rates were affected by bacterial diet, with effects differing between blow fly species. Peak larval weights also varied according to species-diet combination; C. vomitoria had the largest weight on E. coli and mixed diets, C. vicina had the largest weight on S. aureus diets, and treatment had no significant effect on the peak larval weight of L. sericata. These results indicate the potential for the bacteria that larvae are exposed to during development on a corpse to alter both developmental rates and larval weight in some blow fly species.

Potential use of bacterial community succession for estimating post-mortem interval as revealed by high-throughput sequencing

Decomposition is a complex process involving the interaction of both biotic and abiotic factors. Microbes play a critical role in the process of carrion decomposition. In this study, we analysed bacterial communities from live rats and rat remains decomposed under natural conditions, or excluding sarcosaphagous insect interference, in China using Illumina MiSeq sequencing of 16S rRNA gene amplicons. A total of 1,394,842 high-quality sequences and 1,938 singleton operational taxonomic units were obtained. Bacterial communities showed notable variation in relative abundance and became more similar to each other across body sites during the decomposition process. As decomposition progressed, Proteobacteria (mostly Gammaproteobacteria) became the predominant phylum in both the buccal cavity and rectum, while Firmicutes and Bacteroidetes in the mouth and rectum, respectively, gradually decreased. In particular, the arrival and oviposition of sarcosaphagous insects had no obvious influence on bacterial taxa composition, but accelerated the loss of biomass. In contrast to the rectum, the microbial community structure in the buccal cavity of live rats differed considerably from that of rats immediately after death. Although this research indicates that bacterial communities can be used as a “microbial clock” for the estimation of post-mortem interval, further work is required to better understand this concept.

Microbial Signatures of Cadaver Gravesoil During Decomposition

Genomic studies have estimated there are approximately 10(3)-10(6) bacterial species per gram of soil. The microbial species found in soil associated with decomposing human remains (gravesoil) have been investigated and recognized as potential molecular determinants for estimates of time since death. The nascent era of high-throughput amplicon sequencing of the conserved 16S ribosomal RNA (rRNA) gene region of gravesoil microbes is allowing research to expand beyond more subjective empirical methods used in forensic microbiology. The goal of the present study was to evaluate microbial communities and identify taxonomic signatures associated with the gravesoil human cadavers. Using 16S rRNA gene amplicon-based sequencing, soil microbial communities were surveyed from 18 cadavers placed on the surface or buried that were allowed to decompose over a range of decomposition time periods (3-303 days). Surface soil microbial communities showed a decreasing trend in taxon richness, diversity, and evenness over decomposition, while buried cadaver-soil microbial communities demonstrated increasing taxon richness, consistent diversity, and decreasing evenness. The results show that ubiquitous Proteobacteria was confirmed as the most abundant phylum in all gravesoil samples. Surface cadaver-soil communities demonstrated a decrease in Acidobacteria and an increase in Firmicutes relative abundance over decomposition, while buried soil communities were consistent in their community composition throughout decomposition. Better understanding of microbial community structure and its shifts over time may be important for advancing general knowledge of decomposition soil ecology and its potential use during forensic investigations.

Fluorescently labeled bacteria provide insight on post-mortem microbial transmigration

Microbially mediated mechanisms of human decomposition begin immediately after death, and are a driving force for the conversion of a once living organism to a resource of energy and nutrients. Little is known about post-mortem microbiology in cadavers, particularly the community structure of microflora residing within the cadaver and the dynamics of these communities during decomposition. Recent work suggests these bacterial communities undergo taxa turnover and shifts in community composition throughout the post-mortem interval. In this paper we describe how the microbiome of a living host changes and transmigrates within the body after death thus linking the microbiome of a living individual to post-mortem microbiome changes. These differences in the human post-mortem from the ante-mortem microbiome have demonstrated promise as evidence in death investigations. We investigated the post-mortem structure and function dynamics of Staphylococcus aureus and Clostridium perfringens after intranasal inoculation in the animal model Mus musculus L. (mouse) to identify how transmigration of bacterial species can potentially aid in post-mortem interval estimations. S. aureus was tracked using in vivo and in vitro imaging to determine colonization routes associated with different physiological events of host decomposition, while C. perfringens was tracked using culture-based techniques. Samples were collected at discrete time intervals associated with various physiological events and host decomposition beginning at 1h and ending at 60 days post-mortem. Results suggest that S. aureus reaches its highest concentration at 5-7 days post-mortem then begins to rapidly decrease and is undetectable by culture on day 30. The ability to track these organisms as they move in to once considered sterile space may be useful for sampling during autopsy to aid in determining post-mortem interval range estimations, cause of death, and origins associated with the geographic location of human remains during death investigations.

Postmortem muscle protein degradation in humans as a tool for PMI delimitation

Forensic estimation of time since death relies on diverse approaches, including measurement and comparison of environmental and body core temperature and analysis of insect colonization on a dead body. However, most of the applied methods have practical limitations or provide insufficient results under certain circumstances. Thus, new methods that can easily be implemented into forensic routine work are required to deliver more and discrete information about the postmortem interval (PMI). Following a previous work on skeletal muscle degradation in the porcine model, we analyzed human postmortem skeletal muscle samples of 40 forensic cases by Western blotting and casein zymography. Our results demonstrate predictable protein degradation processes in human muscle that are distinctly associated with temperature and the PMI. We provide information on promising degradation markers for certain periods of time postmortem, which can be useful tools for time since death delimitation. In addition, we discuss external influencing factors such as age, body mass index, sex, and cause of death that need to be considered in future routine application of the method in humans.

Review of Postmortem Interval Estimation Using Vitreous Humor: Past, Present, and Future

For decades, forensic scientists have sought a means of estimating the postmortem interval using laboratory analyses. The best known of these attempts uses a linear regression formula based on the increasing concentration of potassium ions in vitreous humor following death. Like all laboratory analyses, the determination of a potassium concentration is subject to pre-analytical, analytical, and post-analytical errors. Any error is magnified when entered into a regression formula that itself is subject to statistical variation, typically with a 95% confidence interval. Estimating the postmortem interval based solely on the concentration of potassium in vitreous humor proved too simplistic for accurate modeling of the myriad factors that influence postmortem changes. Research continues, using more complicated algorithms involving multivariate ion and chemical analyses and genomic sequencing of the postmortem biome. However refined estimates of the postmortem interval based on laboratory analysis become, sound medical practice will still require the integration of scene findings and information concerning the last time that a given decedent was known to be alive with the results of postmortem examination and laboratory analyses into a medical opinion concerning the postmortem interval.

The Thanatomicrobiome: A Missing Piece of the Microbial Puzzle of Death

Death is a universal phenomenon; however, is there "life after death?" This topic has been investigated for centuries but still there are gray areas that have yet to be elucidated. Forensic microbiologists are developing new applications to investigate the dynamic and coordinated changes in microbial activity that occur when a human host dies. There is currently a paucity of explorations of the thanatomicrobiome (thanatos-, Greek for death) and epinecrotic communities (microbial communities residing in and/or moving on the surface of decomposing remains). Ongoing studies can help clarify the structure and function of these postmortem microbiomes. Human microbiome studies have revealed that 75-90% of cells in the body prior to death are microbial. Upon death, putrefaction occurs and is a complicated process encompassing chemical degradation and autolysis of cells. Decomposition also involves the release of contents of the intestines due to enzymes under the effects of abiotic and biotic factors. These factors likely have predictable effects on postmortem microbial communities and can be leveraged for forensic studies. This mini review provides a critical examination of emerging research relating to thanatomicrobiome and epinecrotic communities, how each is studied, and possible strategies of stochastic processes.

Dynamics of Necrophagous Insect and Tissue Bacteria for Postmortem Interval Estimation During the Warm Season in Romania

The estimation of postmortem interval (PMI) is affected by several factors including the cause of death, the place where the body lay after death, and the weather conditions during decomposition. Given the climatic differences among biogeographic locations, the understanding of necrophagous insect species biology and ecology is required when estimating PMI. The current experimental model was developed in Romania during the warm season in an outdoor location. The aim of the study was to identify the necrophagous insect species diversity and dynamics, and to detect the bacterial species present during decomposition in order to determine if their presence or incidence timing could be useful to estimate PMI. The decomposition process of domestic swine carcasses was monitored throughout a 14-wk period (10 July-10 October 2013), along with a daily record of meteorological parameters. The chronological succession of necrophagous entomofauna comprised nine Diptera species, with the dominant presence of Chrysomya albiceps (Wiedemann 1819) (Calliphoridae), while only two Coleoptera species were identified, Dermestes undulatus (L. 1758) and Creophilus maxillosus Brahm 1970. The bacterial diversity and dynamics from the mouth and rectum tissues, and third-instar dipteran larvae were identified using denaturing gradient gel electrophoresis analysis and sequencing of bacterial 16S rRNA gene fragments. Throughout the decomposition process, two main bacterial chronological groups were differentiated, represented by Firmicutes and Gammaproteobacteria. Twenty-six taxa from the rectal cavity and 22 from the mouth cavity were identified, with the dominant phylum in both these cavities corresponding to Firmicutes. The present data strengthen the postmortem entomological and microbial information for the warm season in this temperate-continental area, as well as the role of microbes in carcass decomposition.

Improved Bacterial 16S rRNA Gene (V4 and V4-5) and Fungal Internal Transcribed Spacer Marker Gene Primers for Microbial Community Surveys

We continue to uncover a wealth of information connecting microbes in important ways to human and environmental ecology. As our scientific knowledge and technical abilities improve, the tools used for microbiome surveys can be modified to improve the accuracy of our techniques, ensuring that we can continue to identify groundbreaking connections between microbes and the ecosystems they populate, from ice caps to the human body. It is important to confirm that modifications to these tools do not cause new, detrimental biases that would inhibit the field rather than continue to move it forward. We therefore demonstrated that two recently modified primer pairs that target taxonomically discriminatory regions of bacterial and fungal genomic DNA do not introduce new biases when used on a variety of sample types, from soil to human skin. This confirms the utility of these primers for maintaining currently recommended microbiome research techniques as the state of the art.

Designing primers for PCR-based taxonomic surveys that amplify a broad range of phylotypes in varied community samples is a difficult challenge, and the comparability of data sets amplified with varied primers requires attention. Here, we examined the performance of modified 16S rRNA gene and internal transcribed spacer (ITS) primers for archaea/bacteria and fungi, respectively, with nonaquatic samples. We moved primer bar codes to the 5′ end, allowing for a range of different 3′ primer pairings, such as the 515f/926r primer pair, which amplifies variable regions 4 and 5 of the 16S rRNA gene. We additionally demonstrated that modifications to the 515f/806r (variable region 4) 16S primer pair, which improves detection of Thaumarchaeota and clade SAR11 in marine samples, do not degrade performance on taxa already amplified effectively by the original primer set. Alterations to the fungal ITS primers did result in differential but overall improved performance compared to the original primers. In both cases, the improved primers should be widely adopted for amplicon studies.

IMPORTANCE We continue to uncover a wealth of information connecting microbes in important ways to human and environmental ecology. As our scientific knowledge and technical abilities improve, the tools used for microbiome surveys can be modified to improve the accuracy of our techniques, ensuring that we can continue to identify groundbreaking connections between microbes and the ecosystems they populate, from ice caps to the human body. It is important to confirm that modifications to these tools do not cause new, detrimental biases that would inhibit the field rather than continue to move it forward. We therefore demonstrated that two recently modified primer pairs that target taxonomically discriminatory regions of bacterial and fungal genomic DNA do not introduce new biases when used on a variety of sample types, from soil to human skin. This confirms the utility of these primers for maintaining currently recommended microbiome research techniques as the state of the art.

Microbial community assembly and metabolic function during mammalian corpse decomposition

Vertebrate corpse decomposition provides an important stage in nutrient cycling in most terrestrial habitats, yet microbially mediated processes are poorly understood. Here we combine deep microbial community characterization, community-level metabolic reconstruction, and soil biogeochemical assessment to understand the principles governing microbial community assembly during decomposition of mouse and human corpses on different soil substrates. We find a suite of bacterial and fungal groups that contribute to nitrogen cycling and a reproducible network of decomposers that emerge on predictable time scales. Our results show that this decomposer community is derived primarily from bulk soil, but key decomposers are ubiquitous in low abundance. Soil type was not a dominant factor driving community development, and the process of decomposition is sufficiently reproducible to offer new opportunities for forensic investigations.

Estimating Time Since Death from Postmortem Human Gut Microbial Communities

Postmortem succession of human-associated microbial communities ("human microbiome") has been suggested as a possible method for estimating postmortem interval (PMI) for forensic analyses. Here we evaluate human gut bacterial populations to determine quantifiable, time-dependent changes postmortem. Gut microflora were repeatedly sampled from the proximal large intestine of 12 deceased human individuals as they decayed under environmental conditions. Three intestinal bacterial genera were quantified by quantitative PCR (qPCR) using group-specific primers targeting 16S rRNA genes. Bacteroides and Lactobacillus relative abundances declined exponentially with increasing PMI at rates of Nt=0.977e(-0.0144t) (r2=0.537, p<0.001) and Nt=0.019e(-0.0087t) (r2=0.396, p<0.001), respectively, where Nt is relative abundance at time (t) in cumulative degree hours. Bifidobacterium relative abundances did not change significantly: Nt=0.003e(-0.002t) (r2=0.033, p=0.284). Therefore, Bacteroides and Lactobacillus abundances could be used as quantitative indicators of PMI.

Functional and Structural Succession of Soil Microbial Communities below Decomposing Human Cadavers

The ecological succession of microbes during cadaver decomposition has garnered interest in both basic and applied research contexts (e.g. community assembly and dynamics; forensic indicator of time since death). Yet current understanding of microbial ecology during decomposition is almost entirely based on plant litter. We know very little about microbes recycling carcass-derived organic matter despite the unique decomposition processes. Our objective was to quantify the taxonomic and functional succession of microbial populations in soils below decomposing cadavers, testing the hypotheses that a) periods of increased activity during decomposition are associated with particular taxa; and b) human-associated taxa are introduced to soils, but do not persist outside their host. We collected soils from beneath four cadavers throughout decomposition, and analyzed soil chemistry, microbial activity and bacterial community structure. As expected, decomposition resulted in pulses of soil C and nutrients (particularly ammonia) and stimulated microbial activity. There was no change in total bacterial abundances, however we observed distinct changes in both function and community composition. During active decay (7 - 12 days postmortem), respiration and biomass production rates were high: the community was dominated by Proteobacteria (increased from 15.0 to 26.1% relative abundance) and Firmicutes (increased from 1.0 to 29.0%), with reduced Acidobacteria abundances (decreased from 30.4 to 9.8%). Once decay rates slowed (10 - 23 d postmortem), respiration was elevated, but biomass production rates dropped dramatically; this community with low growth efficiency was dominated by Firmicutes (increased to 50.9%) and other anaerobic taxa. Human-associated bacteria, including the obligately anaerobic Bacteroides, were detected at high concentrations in soil throughout decomposition, up to 198 d postmortem. Our results revealed the pattern of functional and compositional succession in soil microbial communities during decomposition of human-derived organic matter, provided insight into decomposition processes, and identified putative predictor populations for time since death estimation.

Postmortem degradation of skeletal muscle proteins: a novel approach to determine the time since death

Estimating the time since death is a very important aspect in forensic sciences which is pursued by a variety of methods. The most precise method to determine the postmortem interval (PMI) is the temperature method which is based on the decrease of the body core temperature from 37 °C. However, this method is only useful in the early postmortem phase (~0-36 h). The aim of the present work is to develop an accurate method for PMI determination beyond this present limit. For this purpose, we used sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), Western blotting, and casein zymography to analyze the time course of degradation of selected proteins and calpain activity in porcine biceps femoris muscle until 240 h postmortem (hpm). Our results demonstrate that titin, nebulin, desmin, cardiac troponin T, and SERCA1 degraded in a regular and predictable fashion in all samples investigated. Similarly, both the native calpain 1 and calpain 2 bands disintegrate into two bands subsequently. This degradation behavior identifies muscular proteins and enzymes as promising substrates for future molecular-based PMI determination technologies.

Natural bacterial communities serve as quantitative geochemical biosensors

Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive.

IMPORTANCE

Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

Natural bacterial communities serve as quantitative geochemical biosensors

Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive.

Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

Community priming--effects of sequential stressors on microbial assemblages

Microbes in nature are exposed to complex environmental stressors which challenge their functioning or survival. Priming is the improved reaction of an organism to an environmental stressor following a preceding, often milder stress event. This phenomenon, also known as cross-protection, predictive response strategy or acquired stress resistance, is becoming an increasingly well-established research topic in microbiology, which has so far been examined from the perspective of a single organism or population. However, microbes in nature occur as part of communities; thus it is timely to highlight the need to also include this level beyond the individual species in studies of priming effects. We here introduce a conceptual framework for such studies at the level of the microbial assemblage and also chart a way forward for empirical and theoretical study. We illustrate some of the elements of our framework with a simple simulation model. Given the dynamic habitat of many microbes, incorporating priming is important for a more complete understanding of microbial community responses to stress.

Potential Use of Bacterial Community Succession in Decaying Human Bone for Estimating Postmortem Interval

Bacteria are taphonomic agents of human decomposition, potentially useful for estimating postmortem interval (PMI) in late-stage decomposition. Bone samples from 12 individuals and three soil samples were analyzed to assess the effects of decomposition and advancing time on bacterial communities. Results indicated that partially skeletonized remains maintained a presence of bacteria associated with the human gut, whereas bacterial composition of dry skeletal remains maintained a community profile similar to soil communities. Variation in the UniFrac distances was significantly greater between groups than within groups (p < 0.001) for the unweighted metric and not the weighted metric. The members of the bacterial communities were more similar within than between decomposition stages. The oligotrophic environment of bone relative to soft tissue and the physical protection of organic substrates may preclude bacterial blooms during the first years of skeletonization. Therefore, community membership (unweighted) may be better for estimating PMI from skeletonized remains than community structure (weighted).

Microbial communities on flower surfaces act as signatures of pollinator visitation

Microbes are easily dispersed from one place to another, and immigrant microbes might contain information about the environments from which they came. We hypothesized that part of the microbial community on a flower's surface is transferred there from insect body surfaces and that this community can provide information to identify potential pollinator insects of that plant. We collected insect samples from the field, and found that an insect individual harbored an average of 12.2 × 10⁵ microbial cells on its surface. A laboratory experiment showed that the microbial community composition on a flower surface changed after contact with an insect, suggesting that microbes are transferred from the insect to the flower. Comparison of the microbial fingerprint approach and direct visual observation under field condition suggested that the microbial community on a flower surface could to some extent indicate the structure of plant–pollinator interactions. In conclusion, species-specific insect microbial communities specific to insect species can be transferred from an insect body to a flower surface, and these microbes can serve as a “fingerprint” of the insect species, especially for large-bodied insects. Dispersal of microbes is a ubiquitous phenomenon that has unexpected and novel applications in many fields and disciplines.

Forensic analysis of the microbiome of phones and shoes

BACKGROUND

Microbial interaction between human-associated objects and the environments we inhabit may have forensic implications, and the extent to which microbes are shared between individuals inhabiting the same space may be relevant to human health and disease transmission. In this study, two participants sampled the front and back of their cell phones, four different locations on the soles of their shoes, and the floor beneath them every waking hour over a 2-day period. A further 89 participants took individual samples of their shoes and phones at three different scientific conferences.

RESULTS

Samples taken from different surface types maintained significantly different microbial community structures. The impact of the floor microbial community on that of the shoe environments was strong and immediate, as evidenced by Procrustes analysis of shoe replicates and significant correlation between shoe and floor samples taken at the same time point. Supervised learning was highly effective at determining which participant had taken a given shoe or phone sample, and a Bayesian method was able to determine which participant had taken each shoe sample based entirely on its similarity to the floor samples. Both shoe and phone samples taken by conference participants clustered into distinct groups based on location, though much more so when an unweighted distance metric was used, suggesting sharing of low-abundance microbial taxa between individuals inhabiting the same space.

CONCLUSIONS

Correlations between microbial community sources and sinks allow for inference of the interactions between humans and their environment.

Distinctive thanatomicrobiome signatures found in the blood and internal organs of humans

According to the Human Microbiome Project, 90% of the cells in a healthy adult body are microorganisms. What happens to these cells after human host death, defined here as the thanatomicrobiome (i.e., thanatos-, Greek defn., death), is not clear. To fill the void, we examined the thanatomicrobiome of the spleen, liver, brain, heart and blood of human cadavers. These organs are thought to be devoid of microorganisms in a healthy adult host. We report that the thanatomicrobiome was highly similar among organ tissues from the same cadaver but very different among the cadavers possibly due to differences in the elapsed time since death and/or environmental factors. Isolation of microbial DNA from cadavers is known to be a challenge. We compared the effectiveness of two methods by amplifying the 16S rRNA genes and sequencing the amplicons from four cadavers. Paired comparisons revealed that the conventional DNA extraction method (bead-beating in phenol/chloroform/bead-beating followed by ethanol precipitation) yielded more 16S rRNA amplicons (28 of 30 amplicons) than a second method (repeated cycles of heating/cooling followed by centrifugation to remove cellular debris) (19 of 30 amplicons). Shannon diversity index of the 16S rRNA genes revealed no significant difference by extraction method. The present report provides a proof of principle that the thanatomicrobiome may be an efficient biomarker to study postmortem transformations of cadavers.

Vertebrate decomposition is accelerated by soil microbes

Carrion decomposition is an ecologically important natural phenomenon influenced by a complex set of factors, including temperature, moisture, and the activity of microorganisms, invertebrates, and scavengers. The role of soil microbes as decomposers in this process is essential but not well understood and represents a knowledge gap in carrion ecology. To better define the role and sources of microbes in carrion decomposition, lab-reared mice were decomposed on either (i) soil with an intact microbial community or (ii) soil that was sterilized. We characterized the microbial community (16S rRNA gene for bacteria and archaea, and the 18S rRNA gene for fungi and microbial eukaryotes) for three body sites along with the underlying soil (i.e., gravesoils) at time intervals coinciding with visible changes in carrion morphology. Our results indicate that mice placed on soil with intact microbial communities reach advanced stages of decomposition 2 to 3 times faster than those placed on sterile soil. Microbial communities associated with skin and gravesoils of carrion in stages of active and advanced decay were significantly different between soil types (sterile versus untreated), suggesting that substrates on which carrion decompose may partially determine the microbial decomposer community. However, the source of the decomposer community (soil- versus carcass-associated microbes) was not clear in our data set, suggesting that greater sequencing depth needs to be employed to identify the origin of the decomposer communities in carrion decomposition. Overall, our data show that soil microbial communities have a significant impact on the rate at which carrion decomposes and have important implications for understanding carrion ecology.

Glycosylated proteins preserved over millennia: N-glycan analysis of Tyrolean Iceman, Scythian Princess and Warrior

An improved understanding of glycosylation will provide new insights into many biological processes. In the analysis of oligosaccharides from biological samples, a strict regime is typically followed to ensure sample integrity. However, the fate of glycans that have been exposed to environmental conditions over millennia has not yet been investigated. This is also true for understanding the evolution of the glycosylation machinery in humans as well as in any other biological systems. In this study, we examined the glycosylation of tissue samples derived from four mummies which have been naturally preserved: – the 5,300 year old “Iceman called Oetzi”, found in the Tyrolean Alps; the 2,400 year old “Scythian warrior” and “Scythian Princess”, found in the Altai Mountains; and a 4 year old apartment mummy, found in Vienna/Austria. The number of N-glycans that were identified varied both with the age and the preservation status of the mummies. More glycan structures were discovered in the contemporary sample, as expected, however it is significant that glycan still exists in the ancient tissue samples. This discovery clearly shows that glycans persist for thousands of years, and these samples provide a vital insight into ancient glycosylation, offering us a window into the distant past.

Shotgun microbial profiling of fossil remains

Millions to billions of DNA sequences can now be generated from ancient skeletal remains thanks to the massive throughput of next-generation sequencing platforms. Except in cases of exceptional endogenous DNA preservation, most of the sequences isolated from fossil material do not originate from the specimen of interest, but instead reflect environmental organisms that colonized the specimen after death. Here, we characterize the microbial diversity recovered from seven c. 200- to 13 000-year-old horse bones collected from northern Siberia. We use a robust, taxonomy-based assignment approach to identify the microorganisms present in ancient DNA extracts and quantify their relative abundance. Our results suggest that molecular preservation niches exist within ancient samples that can potentially be used to characterize the environments from which the remains are recovered. In addition, microbial community profiling of the seven specimens revealed site-specific environmental signatures. These microbial communities appear to comprise mainly organisms that colonized the fossils recently. Our approach significantly extends the amount of useful data that can be recovered from ancient specimens using a shotgun sequencing approach. In future, it may be possible to correlate, for example, the accumulation of postmortem DNA damage with the presence and/or abundance of particular microbes.