Microbial functional pathways based on metatranscriptomic profiling enable effective saliva-based health assessments for precision wellness.

It is increasingly recognized that an important step towards improving overall health is to accurately measure biomarkers of health from the molecular activities prevalent in the oral cavity. We present a general methodology for computationally quantifying the activity of microbial functional pathways using metatranscriptomic data. We describe their implementation as a collection of eight oral pathway scores using a large salivary sample dataset (n = 9350), and we evaluate score associations with oropharyngeal disease phenotypes within an unseen independent cohort (n = 14,129). Through this validation, we show that the relevant oral pathway scores are significantly worse in individuals with periodontal disease, acid reflux, and nicotine addiction, compared with controls. Given these associations, we make the case to use these oral pathway scores to provide molecular health insights from simple, non-invasive saliva samples, and as molecular endpoints for actionable interventions to address the associated conditions.

A novel method for sampling subgingival microbiome: a comparative metatranscriptomic study.

The subgingival microbiome has been implicated in oral and systemic diseases such as periodontitis and Alzheimer's disease. However, subgingival sampling is challenging. We developed a novel method of sampling the subgingival microbiome by rotationally swabbing the supragingival area, named subgingival-P (for proxy) samples. We sampled and metatranscriptomically analyzed subgingival and subgingival-P samples of three different teeth in 20 individuals. The subgingival-P samples were comparable to the subgingival samples in the relative abundances of microorganisms and microbial gene expression levels. Our data demonstrate that the novel method of collecting and analyzing the subgingival-P samples can act as a proxy for the subgingiva, paving the way for large and diverse studies investigating the role of the subgingival microbiome in health and disease.

An accurate aging clock developed from large-scale gut microbiome and human gene expression data.

Accurate measurement of the biological markers of the aging process could provide an "aging clock" measuring predicted longevity and enable the quantification of the effects of specific lifestyle choices on healthy aging. Using machine learning techniques, we demonstrate that chronological age can be predicted accurately from (1) the expression level of human genes in capillary blood and (2) the expression level of microbial genes in stool samples. The latter uses a very large metatranscriptomic dataset, stool samples from 90,303 individuals, which arguably results in a higher quality microbiome-aging model than prior work. Our analysis suggests associations between biological age and lifestyle/health factors, e.g., people on a paleo diet or with IBS tend to have higher model-predicted ages and people on a vegetarian diet tend to have lower model-predicted ages. We delineate the key pathways of systems-level biological decline based on the age-specific features of our model.

Comparison of the gut microbiome composition between men with erectile dysfunction and a matched cohort: a pilot study.

BACKGROUND: To-date there have been minimal studies to investigate an association between the gut microbiome and erectile dysfunction. There have been many inflammatory diseases linked to gut microbiome dysbiosis; such as cardiovascular disease and metabolic syndrome. These same inflammatory diseases have been heavily linked to erectile dysfunction. Given the correlations between both conditions and cardiovascular disease and the metabolic syndrome, we believe that it is worthwhile to investigate a link between the two. OBJECTIVE: To investigate the potential association between the gut microbiome and erectile dysfunction. METHODS: Stool samples were collected from 28 participants with erectile dysfunction and 32 age-matched controls. Metatranscriptome sequencing was used to analyze the samples. RESULTS: No significant differences were found in the gut microbiome characteristics, including Kyoto Encyclopedia of Genes and Genomes richness (p = 0.117), Kyoto Encyclopedia of Genes and Genomes diversity (p = 0.323), species richness (p = 0.364), and species diversity (p = 0.300), between the erectile dysfunction and control groups. DISCUSSION: The association of gut microbiome dysbiosis and pro-inflammatory conditions has been well studied and further literature continues to add to this evidence. Our main limitation for this study was our small-sample size due to recruitment issues. We believe that a study with a larger population size may find an association between the gut microbiome and erectile dysfunction. CONCLUSIONS: The results of this study do not support a significant association between the gut microbiome and erectile dysfunction. Further research is needed to fully understand the relationship between these two conditions.

Detecting salivary host and microbiome RNA signature for aiding diagnosis of oral and throat cancer.

OBJECTIVE: Oral squamous cell carcinoma (OSCC) and oropharyngeal squamous cell carcinoma (OPSCC) can go undetected resulting in late detection and poor outcomes. We describe the development and validation of CancerDetect for Oral & Throat cancer™ (CDOT), to detect markers of OSCC and/or OPSCC within a high-risk population. MATERIAL AND METHODS: We collected saliva samples from 1,175 individuals who were 50 years or older, or adults with a tobacco use history. 945 of those were used to train a classifier using machine learning methods, resulting in a salivary microbial and human metatranscriptomic signature. The classifier was then independently validated on the 230 remaining samples prospectively collected and unseen by the classifier, consisting of 20 OSCC (all stages), 76 OPSCC (all stages), and 134 negatives (including 14 pre-malignant). RESULTS: On the validation cohort, the specificity of the CDOT test was 94 %, sensitivity was 90 % for participants with OSCC, and 84.2 % for participants with OPSCC. Similar classification results were observed among people in early stage (stages I & II) vs late stage (stages III & IV). CONCLUSIONS: CDOT is a non-invasive test that can be easily administered in dentist offices, primary care centres and specialised cancer clinics for early detection of OPSCC and OSCC. This test, having received FDA's breakthrough designation for accelerated review, has the potential to enable early diagnosis, saving lives and significantly reducing healthcare expenditure.

Investigating the association between the symptoms of women with Fibromyalgia, Digestive function, and markers of the microbiota of the Gastrointestinal Tract (The FIDGIT Study): study protocol.

BACKGROUND: Fibromyalgia a common idiopathic condition affecting around 1.4% of adults globally. Its signature symptom is chronic widespread pain, with a constellation of somatic and psychological symptoms. Fibromyalgia is associated with significant reductions in quality of life, yet to date there is no biochemical marker for its diagnosis. Previous studies have indicated a strong association with gastrointestinal dysfunction, and more recently, alterations to the gut microbiome. No studies have examined the inter-relationship between fibromyalgia, gastrointestinal dysfunction, and the microbiome. This prospective observational case-controlled study will gather data on gastrointestinal function, dietary intake, fermentation patterns of ingested carbohydrates, and symptoms commonly associated with fibromyalgia. These will be evaluated alongside human gene expression and metatranscriptomic analysis of the oral and faecal microbiome. METHODS: Adult women aged ≥18 years diagnosed with fibromyalgia and/or meeting ACR 2016 criteria, and healthy family or age-matched controls will be recruited from the community. From consenting participants, we will collect detailed survey information and samples of blood, urine, stool, saliva, and breath. DISCUSSION: This is the first prospective study examining interactions between digestive function, human gene expression, and the gut microbiome together with general, and fibromyalgia-specific, symptoms experienced by New Zealand women. This exploration will allow an in-depth understanding of clinically relevant factors that are associated with fibromyalgia and will guide further research and contribute to improved management of this poorly understood condition. TRIAL REGISTRATION: The study was approved by the New Zealand Health and Disability Committee (HDEC) (ref: 20/CEN/197) and registered with the Australia and New Zealand Clinical Trials Registry (ANZCTR), registration number ACTRN12620001337965. Written consent will be obtained after providing participants with detailed information about the procedures. Access to data will be restricted to the immediate research team, and all samples and survey data will be deidentified and coded before analysis.

Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes.

BACKGROUND: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is thought to involve alterations in the gut microbiome, but robust microbial signatures have been challenging to identify. As prior studies have primarily focused on composition, we hypothesized that multi-omics assessment of microbial function incorporating both metatranscriptomics and metabolomics would further delineate microbial profiles of IBS and its subtypes. METHODS: Fecal samples were collected from a racially/ethnically diverse cohort of 495 subjects, including 318 IBS patients and 177 healthy controls, for analysis by 16S rRNA gene sequencing (n = 486), metatranscriptomics (n = 327), and untargeted metabolomics (n = 368). Differentially abundant microbes, predicted genes, transcripts, and metabolites in IBS were identified by multivariate models incorporating age, sex, race/ethnicity, BMI, diet, and HAD-Anxiety. Inter-omic functional relationships were assessed by transcript/gene ratios and microbial metabolic modeling. Differential features were used to construct random forests classifiers. RESULTS: IBS was associated with global alterations in microbiome composition by 16S rRNA sequencing and metatranscriptomics, and in microbiome function by predicted metagenomics, metatranscriptomics, and metabolomics. After adjusting for age, sex, race/ethnicity, BMI, diet, and anxiety, IBS was associated with differential abundance of bacterial taxa such as Bacteroides dorei; metabolites including increased tyramine and decreased gentisate and hydrocinnamate; and transcripts related to fructooligosaccharide and polyol utilization. IBS further showed transcriptional upregulation of enzymes involved in fructose and glucan metabolism as well as the succinate pathway of carbohydrate fermentation. A multi-omics classifier for IBS had significantly higher accuracy (AUC 0.82) than classifiers using individual datasets. Diarrhea-predominant IBS (IBS-D) demonstrated shifts in the metatranscriptome and metabolome including increased bile acids, polyamines, succinate pathway intermediates (malate, fumarate), and transcripts involved in fructose, mannose, and polyol metabolism compared to constipation-predominant IBS (IBS-C). A classifier incorporating metabolites and gene-normalized transcripts differentiated IBS-D from IBS-C with high accuracy (AUC 0.86). CONCLUSIONS: IBS is characterized by a multi-omics microbial signature indicating increased capacity to utilize fermentable carbohydrates-consistent with the clinical benefit of diets restricting this energy source-that also includes multiple previously unrecognized metabolites and metabolic pathways. These findings support the need for integrative assessment of microbial function to investigate the microbiome in IBS and identify novel microbiome-related therapeutic targets. Video Abstract.

A clinically validated human saliva metatranscriptomic test for global systems biology studies.

The authors report here the development of a high-throughput, automated, inexpensive and clinically validated saliva metatranscriptome test that requires less than 100 µl of saliva. RNA is preserved at the time of sample collection, allowing for ambient-temperature transportation and storage for up to 28 days. Critically, the RNA preservative is also able to inactivate pathogenic microorganisms, rendering the samples noninfectious and allowing for safe and easy shipping. Given the unique set of convenience, low cost, safety and technical performance, this saliva metatranscriptomic test can be integrated into longitudinal, global-scale systems biology studies that will lead to an accelerated development of precision medicine, diagnostic and therapeutic tools.

Pathogen detection and characterization from throat swabs using unbiased metatranscriptomic analyses.

OBJECTIVES: Infectious diseases are common but are not easily or readily diagnosed with current methodologies. This problem is further exacerbated by the constant presence of mutated, emerging, and novel pathogens. One of the most common sites of infection by many pathogens is the human throat. However, there is no universal diagnostic test that can distinguish these pathogens. Metatranscriptomic (MT) analysis of the throat represents an important and novel development in infectious disease detection and characterization, because it is able to identify all pathogens using a fully unbiased approach. METHODS: To test the utility of an MT approach to pathogen detection, throat samples were collected from participants before, during, and after an acute sickness. RESULTS: Clear sickness-associated shifts in pathogenic microorganisms were detected in the patients. Important insights into microbial functions and antimicrobial resistance genes were obtained. CONCLUSION: MT analysis of the throat represents an effective method for the unbiased identification and characterization of pathogens. Because MT data include all microorganisms in the sample, this approach should not only allow the identification of pathogens, but provide an understanding of the effects of the resident throat microbiome in the context of human health and disease.

Gut Microbiome Activity Contributes to Prediction of Individual Variation in Glycemic Response in Adults.

Limiting postprandial glycemic response (PPGR) is an important intervention in reducing the risk of chronic metabolic diseases and has been shown to impart significant health benefits in people with elevated levels of blood sugar. In this study, we collected gut microbiome activity data by assessing the metatranscriptome, and we measured the glycemic responses of 550 adults who consumed more than 30,000 meals, collectively, from omnivore or vegetarian/gluten-free diets. We demonstrate that gut microbiome activity, anthropometric factors, and food macronutrients modulate individual variation in glycemic response. We employ two predictive models, including a mixed-effects linear regression model (R = 0.77) and a gradient boosting machine model (Rtrain = 0.80/R2train = 0.64; Rtest = 0.64/R2test = 0.40), which demonstrate variation in PPGR between individuals when ingesting the same foods. All features in the final mixed-effects linear regression model were significant (p < 0.05) except for two features which were retained as suggestive: glutamine production pathways (p = 0.08) and the interaction between tyrosine metabolizers and carbs (p = 0.06). We introduce molecular functions as features in these two models, aggregated from microbial activity data, and show their statistically significant contributions to glycemic control. In summary, we demonstrate for the first time that metatranscriptomic activity of the gut microbiome is correlated with PPGR among adults.

Blood sugar dysregulation is caused by various underlying conditions, including type 2 diabetes, and this may lead to extended periods of hypoglycemia or hyperglycemia, which can be harmful or deadly. Clinically, glycemic control is a primary therapeutic target for dysglycemia, and food and nutrition are frequent interventions used to reduce postprandial blood glucose excursions. Primary determinants of postprandial glycemic response (PPGR) include dietary carbohydrates, individual phenotypes, and individual molecular characteristics which include the gut microbiome. Typical investigations of gut microbiomes depend on analysis methods which have poor taxonomic resolution, cannot identify certain microorganisms, and are prone to errors. In this study, each RNA molecule was identified and counted, allowing quantitative strain-level taxonomic classification and molecular pathway analysis. The primary goal of the study was to assess the impact of microbial functional activity on PPGR. The study was conducted in the USA and involved a multiethnic population of healthy adults with HbA1c levels below 6.5. All participants received 14-day omnivore diets or vegetarian/gluten-free diets, depending on nutritional requirements (omnivore diets include meat while vegetarian/gluten-free diets exclude both gluten and meat). Over this timeframe, blood glucose levels were measured in 15-min intervals, 24 h per day, capturing postprandial responses for more than 27,000 meals, including more than 18,000 provided meals which spanned a wide range of foods and macronutrient characteristics. Computational modeling demonstrated the statistical significance of all features and identified new features which may be relevant to glycemic control. These results show, for the first time, that a person's glycemic response depends on individual traits, including both their anthropometrics and their gut metatranscriptome, representing the activity of gut microbiomes.

The salivary metatranscriptome as an accurate diagnostic indicator of oral cancer.

Despite advances in cancer treatment, the 5-year mortality rate for oral cancers (OC) is 40%, mainly due to the lack of early diagnostics. To advance early diagnostics for high-risk and average-risk populations, we developed and evaluated machine-learning (ML) classifiers using metatranscriptomic data from saliva samples (n = 433) collected from oral premalignant disorders (OPMD), OC patients (n = 71) and normal controls (n = 171). Our diagnostic classifiers yielded a receiver operating characteristics (ROC) area under the curve (AUC) up to 0.9, sensitivity up to 83% (92.3% for stage 1 cancer) and specificity up to 97.9%. Our metatranscriptomic signature incorporates both taxonomic and functional microbiome features, and reveals a number of taxa and functional pathways associated with OC. We demonstrate the potential clinical utility of an AI/ML model for diagnosing OC early, opening a new era of non-invasive diagnostics, enabling early intervention and improved patient outcomes.

A clinically validated human capillary blood transcriptome test for global systems biology studies.

To prevent and treat chronic diseases, including cancer, a global application of systems biology is needed. We report here a whole blood transcriptome test that needs only 50 µl of capillary (fingerprick) blood. This test is suitable for global applications because the samples are preserved at ambient temperature for up to 4 weeks and the RNA preservative inactivates all pathogens, enabling safe transportation. Both the laboratory and bioinformatic steps are automated and performed in a clinical lab, which minimizes batch effects and creates unbiased datasets. Given its clinical testing performance and accessibility to traditionally underrepresented and diverse populations, this test offers a unique ability to reveal molecular mechanisms of disease and enable longitudinal, population-scale studies.

Correction: California condor microbiomes: Bacterial variety and functional properties in captive-bred individuals.

[This corrects the article DOI: 10.1371/journal.pone.0225858.].

California condor microbiomes: Bacterial variety and functional properties in captive-bred individuals.

Around the world, scavenging birds such as vultures and condors have been experiencing drastic population declines. Scavenging birds have a distinct digestive process to deal with higher amounts of bacteria in their primary diet of carcasses in varying levels of decay. These observations motivate us to present an analysis of captive and healthy California condor (Gymnogyps californianus) microbiomes to characterize a population raised together under similar conditions. Shotgun metagenomic DNA sequences were analyzed from fecal and cloacal samples of captive birds. Classification of shotgun DNA sequence data with peptide signatures using the Sequedex package provided both phylogenetic and functional profiles, as well as individually annotated reads for targeted confirmatory analysis. We observed bacterial species previously associated with birds and gut microbiomes, including both virulent and opportunistic pathogens such as Clostridium perfringens, Propionibacterium acnes, Shigella flexneri, and Fusobacterium mortiferum, common flora such as Lactobacillus johnsonii, Lactobacillus ruminus, and Bacteroides vulgatus, and mucosal microbes such as Delftia acidovorans, Stenotrophomonas maltophilia, and Corynebacterium falsnii. Classification using shotgun metagenomic reads from phylogenetic marker genes was consistent with, and more specific than, analysis based on 16S rDNA data. Classification of samples based on either phylogenetic or functional profiles of genomic fragments differentiated three types of samples: fecal, mature cloacal and immature cloacal, with immature birds having approximately 40% higher diversity of microbes.

A Robust Metatranscriptomic Technology for Population-Scale Studies of Diet, Gut Microbiome, and Human Health.

A functional readout of the gut microbiome is necessary to enable precise control of the gut microbiome's functions, which support human health and prevent or minimize a wide range of chronic diseases. Stool metatranscriptomic analysis offers a comprehensive functional view of the gut microbiome, but despite its usefulness, it has rarely been used in clinical studies due to its complexity, cost, and bioinformatic challenges. This method has also received criticism due to potential intrasample variability, rapid changes, and RNA degradation. Here, we describe a robust and automated stool metatranscriptomic method, called Viomega, which was specifically developed for population-scale studies. Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes. We applied this method to 10,000 human stool samples and performed several small-scale studies to demonstrate sample stability and consistency. In summary, Viomega is an inexpensive, high-throughput, automated, and accurate sample-to-result stool metatranscriptomic technology platform for large-scale studies and a wide range of applications.

Gut microbiota and their putative metabolic functions in fragmented Bengal tiger population of Nepal.

Bengal tigers (Panthera tigris tigris) serve a pivotal role as an apex predator in forest ecosystems. To increase our knowledge on factors impacting the viability and health of this endangered species, we studied the gut microbiota in 32 individual Bengal tigers from three geographically separated areas (Chitwan National Park (CNP), Bardia National Park (BNP) and Suklaphanta Wildlife Reserve (SWR)) in Nepal, using noninvasive genetic sampling methods. Gut microbiota influence the immune system, impact various physiological functions, and modulates metabolic reactions, that ultimately impact the host health, behavior and development. Across the tiger populations in Nepal, we found significant differences in the composition of microbial communities based on their geographic locations. Specifically, we detected significant differences between CNP and the other two protected areas (CNP vs BNP: pseudo t = 1.944, P = 0.006; CNP vs SWR: pseudo t = 1.9942, P = 0.0071), but no differences between BNP and SWR. This mirrors what has been found for tiger gene flow in the same populations, suggesting gut microbiota composition and host gene flow may be linked. Furthermore, predictive metagenome functional content analysis (PICRUSt) revealed a higher functional enrichment and diversity for significant gut microbiota in the Chitwan tiger population and the lowest enrichment and diversity in Suklaphanta. The CNP tiger population contained higher proportions of microbiota that are associated with predicted functions relevant for metabolism of amino acid, lipid, xenobiotics biodegradation, terpenoides and polyketides than the SWR population. We conclude the tiger population structure, gut microbiota profile and associated functional metabolic categories are correlated, with geographically most separated CNP and SWR tiger population having the most distinct and different host genotype and microbiota profiles. Our work dramatically expands the understanding of tiger microbiota in wild populations and provides a valuable case study on how to investigate genetic diversity at different hierarchical levels, including hosts as well as their microbial communities.

High-throughput phenotyping of cell-to-cell interactions in gel microdroplet pico-cultures.

Microbiomes exert significant influence on our planet's ecology. Elucidating the identities of individual microbes within these communities and how they interact is a vital research imperative. Using traditional plating and culturing methods, it is impractical to assess even a small fraction of the interactions that exist within microbial communities. To address this technology gap, we integrated gel microdroplet technology with microfluidics to generate millions of microdroplet cultures (MDs) that sequester individual cells for phenotyping MDs, facilitating rapid analysis and viable recovery using flow cytometry. Herein, we describe a validated high-throughput phenotyping pipeline that elucidates cell-to-cell interactions for millions of combinations of microorganisms. Through iterative co-culturing of an algae and a pool of environmentally sourced microbes, we successfully isolated bacteria that improved algal growth.

Investigating intestinal permeability and gut microbiota roles in acute coronary syndrome patients.

Background: Acute Coronary Syndrome (ACS) is a leading cause of morbidity and mortality. Perturbed gut- microbiota (dysbiosis) and increased intestinal permeability (leaky-gut) with translocation of bacterial antigens, play critical role in obesity and metabolic syndrome, which are also major ACS risk factors. Additionally, Trimethylamine-N-Oxide (TMAO), a metabolite produced by phylum Proteobacteria in gut is implicated in developing ACS. As Proteobacteria is a major source of translocated antigen lipopolysaccharides (LPS), we hypothesized that ACS patients have leaky-gut condition characterized by dysbiosis with increased Proteobacteria, leading to elevated blood levels of TMAO and LPS. Methods: In a pilot case-control study, we enrolled 19 ACS patients (within 72-h of cardiac events) and 19 healthy-controls. Gut barrier function was determined using lactulose-to-mannitol urinary excretion ratio (L/M ratio). Stool microbiome composition was examined using16S sequencing and predictive functional analysis for LPS biosynthesis pathway by PICRUSt tool. Serum TMAO and LPS levels were measured. Results: ACS patients had increased Gammaproteobacteria compared to controls:1.8 ±3.0 vs. 0.2 ±0.4% (P =0.04). Though Proteobacteria level was increased but not statistically significant: 4.1 ±3.8 vs. 2.1 ±1.7% (P =0.056). L/M-ratio was three times higher in ACS patients; 0.06 ±0.07 vs 0.023 ±0.02, (P =0.014). Surprisingly, there was no difference in the mean serum LPS or TMAO levels. However, PICRUSt analysis indicated increased Proteobacteria population increasingly contributed to LPS biosynthesis in ACS patients only. Conclusions: ACS patients likely to have leaky-gut and perturbed gut microbiota. Further studies are required to precisely define the role of dysbiosis in ACS.

Biostimulation and microbial community profiling reveal insights on RDX transformation in groundwater.

Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) is a high explosive released to the environment as a result of weapons manufacturing and testing worldwide. At Los Alamos National Laboratory, the Technical Area (TA) 16 260 Outfall discharged high-explosives-bearing water from a high-explosives-machining facility to Cañon de Valle during 1951 through 1996. These discharges served as a primary source of high-explosives and inorganic-element contamination in the area. Data indicate that springs, surface water, alluvial groundwater, and perched-intermediate groundwater contain explosive compounds, including RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine); HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine); and TNT (2,4,6-trinitrotoluene). RDX has been detected in the regional aquifer in several wells, and a corrective measures evaluation is planned to identify remedial alternatives to protect the regional aquifer. Perched-intermediate groundwater at Technical Area 16 is present at depths from 650 ft to 1200 ft bgs. In this study, we examined the microbial diversity in a monitoring well completed in perched-intermediate groundwater contaminated by RDX, and examined the response of the microbial population to biostimulation under varying geochemical conditions. Results show that the groundwater microbiome was dominated by Actinobacteria and Proteobacteria. A total of 1,605 operational taxonomic units (OTUs) in 96 bacterial genera were identified. Rhodococcus was the most abundant genus (30.6%) and a total of 46 OTUs were annotated as Rhodococcus. One OTU comprising 25.2% of total sequences was closely related to a RDX -degrading strain R. erythropolis HS4. A less abundant OTU from the Pseudomonas family closely related to RDX-degrading strain P. putida II-B was also present. Biostimulation significantly enriched Proteobacteria but decreased/eliminated the population of Actinobacteria. Consistent with RDX degradation, the OTU closely related to the RDX-degrading P. putida strain II-B was specifically enriched in the RDX-degrading samples. Analysis of the accumulation of RDX-degradation products reveals that during active RDX degradation, there is a transient increase in the concentration of the degradation products MNX, DNX, TNX, and NDAB. The accumulation of these degradation products suggests that RDX is degraded via sequential reduction of the nitro functional groups followed by abiotic ring-cleavage. The results suggest that strict anaerobic conditions are needed to stimulate RDX degradation under the TA-16 site-specific conditions.