Potential applications of soil microbial ecology and next-generation sequencing in criminal investigations

Applied Soil Ecology 88 (2015) 69–78

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Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil

Review

Potential applications of soil microbial ecology and next-generation sequencing in criminal investigations Sheree J. Finley a , M. Eric Benbow b , Gulnaz T. Javan a, * a b

Forensic Science Program, Physical Sciences Department, Alabama State University, Montgomery, AL 36104, United States Department of Entomology and Department of Osteopathic Medicine, Michigan State University, East Lansing, MI, 48824, United States

A R T I C L E I N F O

A B S T R A C T

Article history: Received 13 May 2014 Received in revised form 23 December 2014 Accepted 6 January 2015 Available online xxx

The complex relationships between the changes in microbial community profiles and postmortem interval (PMI) estimates have recently been discussed in the forensic literature. Edaphic, necrobiomic microorganisms at the cadaver-soil interface construct multi-species communities that change in richness and activity when the host body dies and begins to decompose. Characterization of these dynamic changes has been made possible by current advances in high throughput, next-generation platforms. The effectiveness of these metagenomic technologies is that they pride the foundations of a framework for identification of grave sites and the determination of postmortem timelines, or “microbial clocks.” The proposed clocks may help substantiate the estimation of PMI. Studies have demonstrated the differences between soils collected at grave sites and control soils which may be useful in identifying clandestine grave sites. In this review is the discussion of the recent and formative findings involving sequencing applications of soil microbial communities relating the differences in taxon richness and abundance patterns as molecular tools with broad and important applications in forensics. ã 2015 Elsevier B.V. All rights reserved.

Keywords: Forensic soil Soil microbial ecology Necrobiome ecology

Contents 1. 2. 3.

4. 5.

6. 7.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Epinecrotic soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The making of gravesoil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The effect of soil on decomposition . . . . . . . . . . . . . . . . . . . 3.1. Stages of decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Gravesoil microbial ecology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Microbial communities of gravesoil . . . . . . . . . . . . . . . . . . . 4.1. Taxonomic resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Next-generation metagenomic sequencing . . . . . . . . . . . . . 5.1. Whole metagenome-based, amplicon-based and functional 5.2. Applications of gravesoil in criminal investigations . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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1. Introduction

* Corresponding author at: Alabama State University, Forensic Science Program, Alabama State University, 915 S. Jackson St., Hatch Hall Building Room 251, Montgomery, AL 36104, United States. Tel.: + 334 229 5202. E-mail address: [email protected] (G.T. Javan). http://dx.doi.org/10.1016/j.apsoil.2015.01.001 0929-1393/ ã 2015 Elsevier B.V. All rights reserved.

The history of soil ecology research is vast and extensive. Much of the research in the field of soil ecology has been conducted for the benefit of agricultural developments or to study the deleterious impact of environmental stressors on edaphic ecosystems. However, genomic studies of the abundance and activity of soil necrobiomic microbial communities associated with decaying

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human and animal cadavers, along with the underlying soils, have steadily advanced to the forefront of applied ecological research (Can et al., 2014; Hyde et al., 2013; Metcalf et al., 2013; Pechal et al., 2013, 2014). Recent emphases on decomposition ecology have yielded robust investigations of the soil ecological necrobiome, namely the macro- and micro-organisms associated with decaying heterotrophic biomass (Benbow et al., 2013). Cadaver decomposition is a complex succession of chemical, biological and geochemical changes within the carcass that directly affects the niche, functions and ecology of the microorganisms in the neighboring soil (Finley et al., 2014). Microbes generally do not live in single species communities (Wooley et al., 2010). Accordingly, necrobiomic microorganisms at the cadaversoil interface reside in multi-species communities that rapidly and measurably change in abundance and activity when the host body dies. The microorganisms associated with the necrobiomic communities have been referred to as the epinecrotic microbial communities of the decomposing carcass (Pechal et al., 2014). These communities have recently been proposed to be useful for forensic investigations, and a laboratory study using mice carcasses tracked changes in the soil beneath the remains and demonstrated measureable shifts in the community (Metcalf et al., 2013). Traditional forensic decomposition studies have focused mainly on the macroscopic, observable postmortem evidence such as animal scavengers or entomological developmental stages. However, there is a growing awareness that the microorganisms on a dead host and in the soil beneath it could potentially be used as evidence in criminal investigations. The goal of this paper is to review recent trends in soil microbial ecology and how new technologies may open up new lines of applications in the forensic sciences – a novel and promising line of inquiry for soil ecologists. A second goal is to discuss next-generation approaches to research into this area of soil microbial ecology for application in carrion decomposition studies. Decomposition is a fundamental process in ecosystem function and energy flow where nutrients are recycled into the ecosystem food cycle. Recent microbial ecology literature suggests that microbial communities exhibit a wide range of successional patterns depending on environmental conditions (Shade et al., 2013). For example, studies have demonstrated that microbial communities change directionally on the surface of leaves (Redford and Fierer, 2009) and in seasonal patterns in surface waters of aquatic systems (Gilbert et al., 2012). Likewise, studies have shown that microbial succession is a characteristic of carrion decomposition (Metcalf et al., 2013; Pechal et al., 2014), as demonstrated by high-throughput, next-generation sequencing techniques. Past sequencing technology was limited to culturable microbial taxa. Therefore, next-generation approaches are opening up new lines of inquiry within the microbiological sciences, including soil microbial ecology. However, current sequencing technology is limited by the sheer size of the genomes sequenced, where whole-genome sequencing is limited to 109 bases per single run (El-Metwally et al., 2013). An entire soil metagenome may approach an estimated 1015 base pairs (Delmont et al., 2011). Notwithstanding, an attempt to monitor the changes in the soil epinecrotic signatures during decomposition provides an innovative molecular tool for criminal investigators for the estimation of the PMI or identifying clandestine grave sites. The necrobiome is comprised of organisms that include bacteria fungi, protists, invertebrates and vertebrates (Benbow et al., 2013). A pivotal study using replicate pigs documented two major findings in the microbial component of the necrobiome: (1) bacterial communities change during the decomposition process and (2) the sequence of the apparent changes could potentially be used to formulate time of death estimates in forensic investigations (Pechal et al., 2014). Furthermore, findings from the

Human Microbiome Project (HMP) demonstrated that although human bacterial community structure displays minimal variability during an adult lifespan, it differs considerably among individuals (Turnbaugh et al., 2007). These finding indicate that conceivably the individualized microbial community’s fingerprint has applications in forensic criminal investigations beyond the other communities of the necrobiome (i.e., necrophagous insects and scavengers) that has been traditionally used during investigations. Necrophagous insect taxa are the predominant eukaryotic promoters of vertebrate cadaver decomposition (Benbow et al., 2013; Matuszewski et al., 2010; Payne, 1965; VanLaerhoven, 2010). One limitation to these approaches is that postmortem observations do not change continuously (Lv et al., 2014). For example, blow fly larvae are useful until the advanced decay stage of decomposition, which can occur as soon as 10–14 days after death in warmer months (Payne, 1965). Also, once the fly larvae pupate, it is more difficult to estimate the PMI. Thus, animal consumption and entomological evidences are not as effective in long-term PMI determinations (Lv et al., 2014). A roadmap and framework to unify basic and applied research for understanding the ecological, evolutionary and genetic mechanisms occurring during cadaver decomposition has been proposed (Tomberlin et al., 2011) that addresses the potential role of microbes during the carrion decomposition process. Likewise, in this review, a discussion of how high throughput, next-generation metagenomic sequencing may become more widely used in forensics, by first providing a critical examination of a conceptual framework and then providing more details into the processes and considerations important for such applications. Then this will provide suggestions for future research to formulate tools using the individualized microbial community's fingerprint for forensic investigations. 2. Epinecrotic soils Soil epinecrotic microbial communities, the microorganisms on and/or in decomposing heterotrophic biomass, has recently garnered much forensic research interest. Soils are extremely heterogeneous terrestrial ecosystems that contain highly complex composites of layers of both organic and inorganic molecules. These layers are made up of both living and the remnants of decomposing animals, plants, bacteria, fungi and other microorganisms (Turbé et al., 2010). Edaphic microorganisms such as algae, bacteria and fungi form the majority of the soil biomass and are ubiquitous in soils. These microorganisms represent a large portion of the Earth’s living biomass, with between 106 and 107 grams of microbial biomass per square meter of surface soils (Baldrian et al., 2012). The study of soil microbial ecosystems is hampered not only by the heterogeneity of soil but also by the sheer number of microbial cells and diversity of distinct taxa per gram of soil. Studies have estimated that the number of species of bacteria per gram of soil varies between 2000 and 8.3 million cells depending on the soil type (Roesch et al., 2007). Approximately 80% of edaphic bacteria are located in the pores between soil particles, free or attached to particle surfaces such as the ultrathin water films surrounding soil particles (Stotzky, 1997; Ranjard and Richaume, 2001). Another immensely diverse group of edaphic decomposers are fungi. Fungi are one of the major decomposers in virtually all terrestrial environments and are implicated to be a large contributor to vertebrate decomposition on soil (Killham, 1994; Parkinson et al., 2009). Several environmental factors define the microbial niche and how this niche influences the dominance of edaphic bacteria and fungi. The initial pH of the soil can have an effect on the predominant microbial decomposer and the rate of decomposition (Haslam and Tibbett, 2009; Killiam, 2004; Wilson-Taylor, 2012).

S.J. Finley et al. / Applied Soil Ecology 88 (2015) 69–78

Studies have shown that bacteria are the dominant microorganism responsible for the observed decomposition in gravesoil at pH 5.5–7.5 (Haslam and Tibbett, 2009). However, fungal decomposers are less sensitive to such strict pH parameters and thrive in either acidic or alkaline soils depending on the fungi (Turbé et al., 2010). For example, in succession studies of 23 ammonia fungi that stimulate cadaver decomposition, early phase fungi, such as Deuteromycetes molds, Discomycetes cup-fungi and Agaricales gill-fungi, thrive under neutral to slightly alkaline conditions (pH 7–9) (Sagara et al., 2008). Conversely, late phase fungi, such as Basidiomycetes, thrive in slightly acidic optimal pH of 5–7. In terms of moisture sensitivity, when soil moisture decreases, so does the activity of the both bacterial and fungal decomposers (Manzoni et al., 2012). Studies have shown that soil retains higher moisture content as ammonia fungi decompose vertebrate cadavers and produce ammonia (Sagara et al., 2008). Bacteria are typically more sensitive than fungi to desiccation stress. Manzoni et al. (2012) have shown that as the soil dries, conditions shift from favorable for bacteria taxa decomposers to more favorable for fungi taxa (Manzoni et al., 2012). Fungi are welladapted to desiccation stress due to the ability of hyphae-forming taxa to “scavenge” water in dry soils (Lennon et al., 2012). Fungi also exhibit less of a response to changes in moisture because of their chitinous cell walls (Strickland and Rousk, 2010). In reference to temperature, fungal and bacterial growth rates are optimal at temperatures around 25–30  C (Pietikainen et al., 2005). However, in general, fungi decomposers dominate in soil in winter whereas bacteria are more active in the summer (Turbé et al., 2010). As with moisture changes, fungi are more resistant to temperature fluctuations than bacteria because of their chitinous cell walls (Strickland and Rousk, 2010). Since decomposition generally occurs near the soil surface, oxygen limitation in soil can have an effect on microbial activity, favoring microbes that are adaptive to anaerobic conditions (Turbé et al., 2010).

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scavenger fur, feathers and scavenger carcasses. The incorporation of all of these components into the underlying gravesoil has been referred to as the “cadaver decomposition island” (CDI) (Carter et al., 2007, 2010). 3.1. The effect of soil on decomposition There are several soil characteristics that have an effect on cadaver decomposition (Table 1) (Carter et al., 2010; Girvan et al., 2003; Haslam and Tibbett, 2009; Mann and Meadows, 1990 Teo et al., 2013; Tumer et al., 2013). The type and particle size of the neighboring soil are among the most important factors that affect the decomposition rate of cadavers in soil (Girvan et al., 2003; Tumer et al., 2013). Soil incubation studies have indicated that decomposition by-products cause the pH of the soil environment to shift, initially becoming more alkaline, and then more acidic (Haslam and Tibbett, 2009). Typically, the underlying soil is more alkaline than a cadaver. However, as the necrobiomic microbes metabolize organic biomass, the CO2 that is evolved is converted into carbonic acid that lowers the pH of the underlying soil. A study of soil of contrasting pH shows that the rate of decomposition of mammalian muscle tissue in acidic soil is three times greater than in alkaline soil (Haslam and Tibbett, 2009). In response to acidification, bacterial abundance and diversity has been shown to decrease (Baldrian et al., 2012). Additionally, decomposition in dry, sandy soil is retarded. However, in high moisture sandy soil containing high levels of minerals such as calcium, phosphorus and manganese, there is evidence of pseudomorphic mineralization (mummification). In contrast, fine-textured clayey soil with low rates of gas diffusion causes the less-efficient anaerobic decomposers to dominate resulting in decreased decomposition (Tumer et al., 2013). Under the latter conditions, decomposition can be further retarded due to adipocerous formation that is found around the cadaver and/or the internal organs (Pfeiffer et al., 1998; Tumer et al., 2013).

3. The making of gravesoil 3.2. Stages of decomposition Soils with large particle sizes provide greater surface area that can harbor an increased amount of microbial decomposers. Studies by Girvan et al. (2003) using denaturing gradient gel electrophoresis (DGGE) and terminal restriction fragment length polymorphism (T-RFLP) analyses of the 16S gene, found that the type of soil is one of the primary determinants of the composition of the bacterial communities in soils irrespective of cadaveric contact (Girvan et al., 2003). For example, decomposition is most pronounced in loamy and organic soil. Conversely, decomposition in dry, sandy soil can be inhibited due to the diffusion of gasses through the soil. Contained in the cadaveric fluids (purge) that efflux into the soil from body orifices, are minerals and microorganisms that are incorporated into the soil ecosystem. The microorganisms perform integral roles in the recycling of nutrients. Additionally, energy, moisture and insect larvae are mutually exchanged at the cadaversoil interface forming gravesoil (Benninger et al., 2008; Carter et al., 2007). Added to the underlying gravesoil are insect and worm fecal matter and their puparia and carcasses as well as deposits of

There are several stages of cadaver decomposition, namely fresh, bloat, active decay, advanced decay, and putrid dry stages (Hewadikaram and Goff, 1991; Matuszewski et al., 2010; Payne, 1965). The fresh stage begins at death and continues until the carcass begins to bloat, leading to the bloat stage. Bloating occurs due to microbial metabolic activity that produces gaseous by-products that cause the carrion to inflate. The gas attracts and/or repels certain necrophagous insect taxa to the carcass (Burkepile et al., 2006). Active decay follows bloating and is observed as the body begins to rapidly decompose primarily due to insect activity (Matuszewski et al., 2010). Advanced decay is characterized by a decrease in necrophagous insect activity as the host is consumed (Hewadikaram and Goff, 1991). When all that remains is bones, dry skin, and hair, the carcass is considered to be in the putrid dry stage (Payne, 1965). Although these stages have been defined based on the activity of certain insect species, the decomposition process is really a continuum, rather than discrete series (Schoenly and Reid, 1987).

Table 1 List of edaphic indicators that impact cadaver decomposition rates. Indicator

Condition

Reference

pH of soil Moisture of soil Particle size of soil Type of soil Burial location and depth

Decomposition rate is higher in acidic soils Depends on the type of soil Large particle size harbors more microbial decomposers Loamy and organic soils increase decomposition Bodies in graves decay slower than on the surface

Haslam and Tibbett, 2009; Mann et al., 1990 Carter et al., 2010; Mann et al., 1990 Girvan et al., 2003 Tumer et al., 2013 Teo et al., 2013; Mann et al., 1990

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Because of this more continuous rather than discrete process, microbial communities may offer a novel and more precise means of using organisms for estimating the PMI compared to other methods like the total body score system (TBS). The TBS, as described by Megyesi et al. (2005), is a subjective alternative to scavenger and insect studies. This method observes the bloating and purging of the head and trunk to mark the end of early decomposition (Hyde et al., 2013; Megyesi et al., 2005). The TBS provides a tool for law enforcement agents and forensic researchers to assess decomposition as a total point value to represent the total amount of decay. This system is accompanied by accumulated degree-day (ADD) data which is a function of the thermal summation of the consecutive average daily temperature. According to studies by Megyesi et al. (2005) ADD accounts for approximately 80% of the variation in decomposition. Although this method compensate for differences in temperature, it depends on the subjective observations of the forensic investigators. 4. Gravesoil microbial ecology As the corpse decomposes, the gravesoil necrobiome is comprised of bacteria, fungi, protists, worms, invertebrates and vertebrates (Benbow et al., 2013). During the active decay stage of decomposition, enteric, aerobic organisms initiate putrefaction and deplete the cadaver of oxygen (Moreno et al., 2011). Thereafter, anaerobic organisms predominate until the time of skin rupture (Moreno et al., 2006, 2011). This skin rupture is caused when tissues distend due to the buildup of residual gases produced by bacteria undergoing anaerobic respiration and fermentation. During the late stages of decomposition, enteric microorganisms are replaced by microbes from the soil microbial community (Hyde et al., 2014), or possibly brought in by necrophagous flies that secrete and defecate microbes onto a decomposing resource. Using amplicon length heterogeneity-PCR (LH-PCR), studies indicate that measurable changes occur in the soil bacterial community during the decomposition process (Moreno et al., 2011). Amplicons corresponding to anaerobic bacteria, not indigenous to the soil, were shown to produce differences between soil collected from grave sites and control soil. This study, therefore, sets the precedent for the use of molecular methods to locate clandestine grave sites. Among the bacteria linked to these amplicons are those that are most often part of the commensal flora of the intestines, mouth and skin. Most of the microorganisms effuse concomitantly from bodily orifices and distended tissues as the cadaveric fluids efflux into the underlying soil. The microbial communities remain active for months after the cessation of the putrefaction stage (Moreno et al., 2011). 4.1. Microbial communities of gravesoil Many of the studies conducted on the microbial community activity in vertebrates agree that there is a significant shift between aerobic bacteria, namely Staphylococcus and Enterobacteriacae, to the anaerobic bacteria, Clostridia and Bacteroides (Carter et al., 2008; Hopkins et al., 2000; Howard et al., 2010; Pechal et al., 2014;). Endogenous enteric-associated bacteria initially dominate cadaver decomposition (Carter et al., 2008; Fiedler and Graw, 2003; Tuomisto et al., 2013). The putrefaction is furthered by endogenous bacteria from the gastrointestinal tract and other microorganisms that spread to areas of the body through the blood and lymphatic systems (Can et al., 2014). Within six to nine days after death aerobic microorganisms predominate, depleting the cadaver of oxygen (Hyde et al., 2013; Metcalf et al., 2013). Metcalf et al. (2013) recent studies have proven to be pivotal toward the elucidation of soil microbial succession in decomposing carcasses using next-generation sequencing techniques. The

mouse model is commonly used due to the ease in which to manipulate the animals and control the PMI. Interestingly, these studies show that during active decay, upon the depletion of oxygen, endogenous anaerobes, Firmicutes in the Lactobacillaceae family and Bacteroidetes in the Bacteroidaceae family increase in the abdominal cavity of the carcasses (Metcalf et al., 2013). These studies further support previous findings that under anaerobic respiration, the bacteria produce gaseous hydrocarbons and ammonia compounds that bloat the cadaver beyond the capacity of the decaying skin, causing ruptures (Fiedler and Graw, 2003). Exposure of the mice abdominal cavities to oxygen allows several aerobic taxa to flourish: Alphaproteobacteria, Rhizobiales in the Phyllobacteriaceae, Hyphomicrobiaceae and Brucellaceae families, and facultative anaerobic Gammaproteobacteria, particularly of the Enterobacteriaceae family (Metcalf et al., 2013). Likewise, a Hyde et al. (2014) metagenomic study using a human cohort of two cadavers left to decompose in natural, outdoor conditions was the first documentation of the bacterial species present during human decomposition. This study found Acinetobacter, a common bacterial genus found in soil, in the late stages of cadaver decomposition. A study by Lauber et al. (2014) employed next-generation sequencing methods and demonstrated that the rate in which carrion decomposes increases in the presence of a diverse set of microorganisms in soil. The study characterized the prokaryotic and eukaryotic microbial communities in the underlying gravesoil of mice. Mice placed on soil containing intact, endogenous microbial communities decayed at a rate 2–3 times faster than that of mice placed on soil that was sterilized to remove endogenous microorganisms. Additonally, the diffeneces in microbial community composition was assessed. The results show that even though several microbial eukaryotes, such as Mucoromycotina, were present in the active and advanced decay stages in the nonsterilized soil, but not in sterile soil. There are only few mycological protocols established to aid forensic investigators, and judicially, there are no legal precedents to guide adjudication in criminal investigations. However, there are noted forensic uses of fungal soil communities. For example, Hebeloma syrjense is often referred to as the “corpse finder” (Bunyard, 2004). Studies of fungal decomposers confirm that fungi belonging to the ammonia group are the first in the succession of cadaver decomposition. However, researchers have not fully elucidated the role of fungal growth on the process of cadaver decomposition and the making of estimates of PMI (Fiedler and Graw, 2003; Hawksworth and Wiltshire, 2011; Tranchida et al., 2014). Ammonia and post-putrefaction fungi undergo a succession of fruiting and have been identified as visible grave markers in forest ecosystems (Carter and Tibbett, 2003). Studies have demonstrated that these fungi mark the location with a black color above the ground of buried and decomposing vertebrate cadavers (Sagara et al., 2008). This black color is created by the output of excess ammonia by ammonia fungi that consequently cause an increase in soil pH which solubilizes black humic and fulvic acids. Tranchida et al. (2014) also found that Dichotomomyces cejpii, Talaromyces sp., T. trachyspermus, T. flavus of the Ascomycota phylum, were the predominant fungal species in cadaver soil (Tranchida et al., 2014). This study confirms earlier studies that fungi belonging to the ammonia group are the first in the succession of cadaver decomposition (Sagara et al., 2008). 5. Taxonomic resolution Research toward the taxonomic resolution and characterizing of the soil metagenomes is currently underway. The diversity of the microorganisms in soil can be estimated using one of two approaches, cellular cultures or molecular biology techniques.

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Cellular methods of controlled growth of microorganisms under laboratory conditions have only yielded a fraction of taxa, and therefore only reveal a subset of the overall microbial community. Of the molecular techniques, conventional, vector-based cloning protocols have been used. However, the inherent cloning biases that hamper vector-based cloning procedures are unavoidable (Shokralla et al., 2012). As a result, cloning methods have all but been replaced with newer molecular approaches. Prior to the use of next-generation sequencing, multiple molecular techniques were employed to address microbial diversity in natural ecosystems. While these techniques proved very useful for better ascertaining microbial communities of environmental samples, these techniques were costly, timeconsuming and could not be used to identify non-culturable microbes. To distinguish among species of microorganisms, morphological identification of species under the microscope has been replaced in part by molecular methods involving developing profiles based on phospholipids and methods that characterize the DNA of the species (Heath and Saunders, 2009; Moreno et al., 2006, 2011; Osborne et al., 2006; Ritchie et al., 2000). The bio-metric profiling approaches use several chemotaxonomic or culture-dependent genotyping techniques based on polymorphism, DNA length, fatty acid analysis, and denaturing techniques. One such technique is T-RFLP and is based on the inherent differences in the length of DNA when digested by restriction endonuclease (Osborne et al., 2006). Another widely used technique is LH-PCR which is based on the hyper-variability of 16S ribosomal rDNA gene intergenic spacer regions (RISA) (Moreno et al., 2006, 2011; Osborne et al., 2006; Ritchie et al., 2000). Fatty acid methyl esters (FAMEs) and phospholipid fatty acid (PFLA) analyses exploit the fact that unique fatty acids are indicative of specific organisms and can be used as accepted taxonomic discriminators for species identification (Hill et al., 2000). DGGE and temperature gel gradient electrophoresis (TGGE) have been used to resolve soil strains and species (Muyzer et al., 1993). These techniques are low-throughput and time-consuming (Vanwonterghem et al., 2014). 5.1. Next-generation metagenomic sequencing The emergence of next-generation and other high-throughput metagenomic sequencing approaches has also revolutionized the field of genomics by facilitating the sequencing of up to 600 gigabases of DNA per sample in a single run at the same cost of sequencing dozens of samples via the chain termination, Sanger-based method (El-Metwally et al., 2013; Logares et al., 2012; Margulies et al., 2005). Unfortunately, the current nextgeneration methodologies involve a significantly higher error rate per read relative to the Sanger sequencing method (Kosugi et al.,

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2013). Roche Life Sciences 454 (discontinued), Illumina Inc., MiSeq and HiSeq and Life Technologies Ion Torrent Personal Genome Machine (PGM) are the leading instrumentation platforms of high-throughput next-generation sequencing. The sequences are uploaded to a metagenomic sequencing center for the very complex annotation and determination of the microbial abundances at multiple levels of taxonomic resolution. Rarefaction curves are generated to describe the number of species discovered in a sample as a function of the number of individual samples. These new technologies are now opening up new fields of inquiry for microbiologists and ecologists and will no doubt play an important role in studying soil microbial communities for both basic science questions and applications such as in forensics. Loman et al. (2012) provide a comprehensive review of metagenomic studies. 5.2. Whole metagenome-based, amplicon-based and functional metagenomic strategies Several of the newer metagenomic molecular approaches have advanced our understanding of specific epinecrotic interactions between the species and the host as well as their functional genes and metabolic processes (Fig. 1). These approaches offer a tremendous technological resource for studying soil microorganisms. The value of metagenomic studies is that the relationship between microbes and the ecological habitats in which they occupy can be studied concurrently. The three culture-independent strategies are whole metagenome-based sequencing, amplicon-based sequencing and functional metagenomic analyses that do not use DNA. These methods have the ultimate goal of reconstructing the sequences of large genomic data or the functional processes of a selection of its genes. Whole-genome, also known as “shotgun” method reconstructs multiple genomes in a single sample. This method fragments an entire genome into random reads then independently analyzes the reads (El-Metwally et al., 2013; Logares et al., 2012; Loman et al., 2012 Wooley et al., 2010). The reads are assembled into progressively longer contiguous sequences, called contigs. The contigs are formed from the overlaps between the reads to reconstruct the entire genome (Wooley et al., 2010). The initial, unassembled reads are digitally normalized and then partitioned into large metagenomic assemblies of sequences. The other method analyzes conserved functional gene markers through cloning methods to generate vast DNA libraries. The amplicon-based methods assess microbial phylogeny based on PCR amplicons, namely the 16S rRNA gene for species identification of bacteria, 18S rRNA gene for eukaryotic identification and the nuclear ribosomal internal transcribed spacer (ITS) region for the identification of fungal DNA (Baldrian et al., 2012;

Fig. 1. Schematic of shotgun-based, amplicon-based and functional-based metagenomics of the epinecrotic soil microbiome. (Adapted from Solomon et al., 2014).

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Schoch et al., 2012; Shokralla et al., 2012). The genes are sequenced separately using the appropriate universal primers. The collective results of 16S prokaryotic gene sequencing, for example, has provided a genus identification of greater than 90% in most cases and species identification of 65–83% (Janda and Abbott, 2007). Studies have shown that closely phylogenetically-related bacteria in soil have 16S rRNA gene sequences that differ by as little as 0.3 to 2.7% (Janda and Abbott, 2007). With no universal threshold of what constitutes a definitive species match, Drancourt et al. (2000) suggested a >99 and >97% sequence similarity as the cut-off for species and genus identification, respectively. It is also well established that for use of 16S rRNA gene sequencing for microbial identification: a minimum of 500–525 bp sequenced, but ideally 1,300–1,500 bp; and a minimum of >99%, and ideally >99.5% sequence similarity be used for species identification. The amplicon-based sequencing methods are not without limitations. For example, there are multiple sources of biases and errors in 16S rRNA gene analyses. Factors such as the number of 16S rRNA copies per genome, DNA extraction and purification methods, as well as PCR inhibitors, primer selection and cycling artifacts lead to misrepresentation and reduce the effects of 16S rRNA gene-based analyses (Schloss et al., 2011). The inhibition and biases introduced by the PCR inhibitor, humic acids in soil are welldocumented (Antony-Babu et al., 2013; Knauth et al., 2012; Moreira, 1998; Sagova-Mareckova et al., 2008; Seo et al., 2013). Different studies have proven that estimating bacterial diversity in soil can be contradictory according to the technique used. For 16S rRNA cloning and sequencing, the estimate is approximately 103 bacterial species per gram of soil, for 16S rRNA pyrosequencing and taxonomic microarray, the number approaches 104 species, and for reassociation kinetics of soil DNA, the number increases further to between 106 and 107 species (Maron et al., 2011). Functional-based metagenomic strategies provide direct evidence for potentially correlating the cadaver-soil epinecrotic communities with their specific metabolic processes (Carvalhais et al., 2012; Solomon et al., 2014 Wooley et al., 2010). These methods move beyond the use of DNA sequence information. RNA, proteins and metabolites are extracted directly from soil samples and provide data to reconstruct the metabolic function and pathways happening in the soil. Metaproteomics analyze the extracted proteins to identify the structure and quantify the translational activity of specific classes of enzymes in the soil. Metabolomics describe the chemical processes of the metabolites to provide a chemical fingerprint of the fluxes occurring in active cells in the soil. Metatranscriptomics analyze the gene expression to provide a snapshot of transcriptional profiles in the soil at the exact time of sampling. The two major drawbacks to molecular methods are that, because of the diverse composition and nature of soil, no standardized DNA extraction method exists that creates reproducible results across the diverse varieties of soil samples. Further, the efficiency of the amplified gene(s) depends on the selected genetic sequence, the efficient removal of endogenous amplification inhibitors and the experimental conditions. Thus, the Earth Microbiome Project (EMP), a consortium of multinational, mulitdisciplinary collaborators, is spearheading evironmental metagenomic data curation with a goal of systematically characterizing the taxonomic and functional diversity of the microbial genomes of the Earth’s biomes. In 2010 researchers of the EMP proposed to analyze 200,000 samples comprised of the Earth’s approximately 1030 microbial cells using metagenomics, metatranscriptomic and amplicon sequencing (Gilbert et al., 2010). To this end, a global Gene Atlas comprised of the models of the differenct biomes has been curated. The consortium provides standard EMP DNA extraction protocols as well as 16S rRNA

amplification protocols as delinated by Caporaso and collegues (Caporaso et al., 2012). Included in the EMP protocols are the primers for paired-end 16S community sequencing on the Illumina HiSeq platform using prokayotic 515F and 806R primers. This effort provides the infrastructure to integrate localized soil studies with global patterns of soil microbial community diversity and therefore it has tremendous potential utility in forensics. This project is a tremendous challenge, given the huge amounts of data that are generated for each sample. The resulting proliferation of sequence data necessitates their assignment to phylogenetic groups. The process by which the sequencing data is analyzed from next-generation sequencing involves the aligning and trimming of the sequences using the pyrosequencing pipelines such as the Ribosomal Database Project (RDP) and BLAST (Logares et al., 2012; Scholz et al., 2012). Correspondingly, the creation of curated, online databases of DNA sequences that have been validated experimentally and are nonredundant have been established. The databases include MG-RAST, CAMERA, and IMG-M (Haas et al., 2011; Logares et al., 2012). The sheer amount of sequence data has significant challenges as it relates to the post-sequencing data processing. First, there is no standardized, comprehensive pipeline covering all aspects of metagenomic analysis. Quality control steps that identify and remove assembly and gene-finding errors have to be optimized to increase the fidelity of these methods. Next, sequences are assembled by metagenome assemblers such Genovo, Meta-IDBA, MetaVelvet for short reads and MAP for longer reads (Teeling and Glockner, 2012). Microbial sequencing of soil and other environmental samples create a mixture of sequences from a variety of organisms and often contain a number of short assemblies and unassembled reads. The QIIME database is specifically used for the comparison and analysis of environmental microbial communities (Logares et al., 2012). Accuracy of gene assemblage is contingent upon the standardization of these programs. Sequence reads are processed by gene prediction programs, such as MetaGene, MetaGeneAnnotator, Orphelia and FragGeneScan to extrapolate the gene sequences (Logares et al., 2012). Thus, another challenge to metagenomic analysis is that gene prediction programs can only classify sequences with existing homologues in public databases. Furthermore, a large number of these genes are hypothetical that have either no or insufficient homologues with known taxa (Logares et al., 2012). 6. Applications of gravesoil in criminal investigations Forensic soil science builds upon the Locard Exchange Principle that states that physical components, i.e., soil, can be exchanged when two entities come into contact with each other (Fitzpatrick, 2008). Physical evidence is critically important to a criminal investigation to counter or verify the frequently incomplete and/or inaccurate statements provided by victims, suspects, and witnesses. The “physical” evidence in edaphic epinecrotic communities is “molecular” and is best assessed by metagenomic means. Results from the next-generation sequencing studies of HMP demonstrate that although human bacterial community structure often exhibits insignificant variability during an adult lifespan, the structure does vary significantly among individuals (Turnbaugh et al., 2007). These findings indicate that perhaps the individualized microbial community’s fingerprint has applications in forensic criminal investigations. The transfer of microorganisms at the cadaver-soil interface is a molecular application of Locard’s principle. Thus, soil has the potential to associate or disassociate with a specific location to determine if a corpse has been transferred from one location to another. The variable microbial composition of soil has been targeted as a tool for soil “fingerprinting,” potentially leading to the

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identification of the origin of the soil (Concheri et al., 2011; Lenz and Foran, 2010). Concheri et al. (2011) examined the proportional distribution of chemical elements and the bacterial DNA fingerprints of soil as signature markers to prove the similarity of two soil samples. These studies show a level of consistency with the highest similarity of samples from the same site and the progressive deviation in similarity of the other soil. Lenz and Foran (2010) have demonstrated through T-RFLP profiling of the recombination protein A (recA) gene that soil exhibits the potential to be differentiated at a distance of 10 feet from the main collection site (Lenz and Foran, 2010). Traditionally, gravesoil under decomposing cadavers has been used primary to identify burial sites. However, gravesoil has the potential to estimate postmortem microbial clocks (Fig. 2). Briefly, forensic investigators use a 2.54 cm soil corer to collect soil under cadavers. Additionally, control soil is collected approximately 1 m away from the cadaver. The samples are placed in sterile containers. Commercial DNA extraction kits are used to extract genomic DNA from the soil samples in order to perform nextgeneration, metagenomic sequencing (Knauth et al., 2012). Assembly software is employed to assemble the sequences into whole genomes, and the taxa are classified based on bioinformatic analysis (Loman et al., 2012 Wooley et al., 2010). The PMI-specific microbial gene signature is determined through metagenomic annotations and clustering. Trends in the microbial abundances are observed to estimate a postmortem microbial clock (Metcalf et al., 2013). Researchers have characterized microbial communities in gravesoil for fingerprint-like patterns for their use in forensic

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investigations to estimate PMI. A study of cadavers placed in shallow, clandestine graves over a 16 week sampling interval, reveal that the level of indicator organisms, anaerobic bacteria not native to the soil, produced measurable differences (Moreno et al., 2011). For example, nitrogen-fixing bacteria decreased in the gravesoil as the body decomposed. After four weeks of environmental exposure, the bacteria began to increase in the gravesoil. Moreno et al. (2011) suggest that these measurable changes may provide leads to forensic investigators in criminal scenarios involving burial sites. As stated previously, the Metcalf et al. (2013) study demonstrated gravesoil microbial succession in decomposing mice carcasses using next-generation sequencing techniques (Metcalf et al., 2013). Using the mouse model system to study the body cavities and associated gravesoil of 40 mice over a 48-day period, a “microbial clock” is demonstrated. The PMI estimates correlate to actual PMIs within approximately three days. Investigations into the use of soil testate amoebae for the discrimination of forensic soil samples determined that they can be used in “cold cases” and have been recovered from dried sediment residues on clothing 10 years after death (Swindles and Ruffell, 2009). Further, Szelecz et al. (2014) suggested that soil testate amoebae found under decomposing pigs potentially can be used to estimate PMI (Szelecz et al., 2014). This study demonstrated that no living or encysted testate amoeba were detectable 22 and 33 days after the postmortem place of the pigs. The authors therefore suggest that soil protozoa can be useful in cases beyond 4–6 weeks of arthropod colonization when their PMI estimates are less dependable. Subsequently, the protozoan community

Fig. 2. Framework for using soil microbial communities to estimate postmortem microbial clocks (Adapted from Pechal et al., 2013).

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recovered but not completely even when tested 10 months after the initial placement of the pigs. 7. Conclusion Researchers from different disciplines of science are investigating new methods to accurately and systematically estimate PMI to replace less accurate and subjective traditional methods like hypostasis, putrefaction, body temperature and mortis (algor, livor, and rigor) (Chandra and Sabharwal, 1968). As of yet, despite vast advances in science and technology, there has not been a single method that forensic investigators can use routinely to estimate PMI accurately; however, there are numerous promising approaches that are being studied in forensic laboratories. One of these approaches is the use of mRNA in estimating PMI. The fact that DNA, mRNA and protein degrade chemically after death is the concept that researchers are investigating to find a concise method to determine PMI (Lv et al., 2014). RNA’s susceptibility to degradation can be a useful and precise way of determining PMI. Researches have shown that lower temperatures retards degradation of RNA and different RNA subtypes have varying degradation pattern. Another approach is the examination of the diversity of skin-associated bacterial communities. Research has shown that its diversity is much higher than previously determined, with a high degree of variability among locations of the body (Fierer et al., 2010). On the other hand, studies have also demonstrated that the bacterial communities on objects and skin can be quantitatively compared to match the object to the individual with high degree of certainty. The fact that skin bacteria are highly resistant to environmental stresses, such as moisture, temperature and UV exposure, and that they may persist on touched surfaces for prolonged periods of time, affords the use of skin bacteria as “fingerprints” for forensic identification. Furthermore, using culture-based techniques, researchers determined that common skin-associated bacteria have been found to persist on formalin-embalmed cadavers (Tabaac et al., 2013). The number of viable bacteria from the axilla, oronasal and perianal regions of ten embalmed cadavers were found to have a broad range of opportunistic pathogens such as Staphylococcus, Corynebacterium and Gemella. The implications of this research are far reaching for the study of epinecrotic communities under decomposing corpses. The aim of this review was to provide insight into the current techniques and methods available for forensic investigators to determine a predictive model for estimating PMI based on metagenomic studies of epinecrotic soil communities. Although the use of insect evidence has its merits, new methodology and analyses have provided novel tools for the estimation of PMI using longitudinal examination of quantitative variables. Together with the findings of the HMP and the very informative gravesoils studies, new frontiers for PMI determinants are on the horizon. Refinement, verification and standardization of each next-generation techniques are important to the implementation in forensic investigations. However, through concerted efforts across forensic, microbiological and ecological disciplines, the framework for these molecular forensic tools is forthcoming. Acknowledgment This work was supported by National Science Foundation (NSF) grant HRD 1401075.

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