Background. Cystic fibrosis (CF) is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE) that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy. Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples) to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data was analyzed with MS/MS molecular networking and multivariate statistics. Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable). Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF) and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events) as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes. Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset.

Medical responders to radiological and nuclear disasters currently lack sufficient high-throughput and minimally invasive biodosimetry tools to assess exposure and injury in the affected populations. For this reason, we have focused on developing robust radiation exposure biomarkers in easily accessible biofluids such as urine, serum and feces. While we have previously reported on urine and serum biomarkers, here we assessed perturbations in the fecal metabolome resulting from exposure to external X radiation in vivo. The gastrointestinal (GI) system is of particular importance in radiation biodosimetry due to its constant cell renewal and sensitivity to radiation-induced injury. While the clinical GI symptoms such as pain, bloating, nausea, vomiting and diarrhea are manifested after radiation exposure, no reliable bioindicator has been identified for radiation-induced gastrointestinal injuries. To this end, we focused on determining a fecal metabolomic signature in X-ray irradiated mice. There is overwhelming evidence that the gut microbiota play an essential role in gut homeostasis and overall health. Because the fecal metabolome is tightly correlated with the composition and diversity of the microorganism in the gut, we also performed fecal 16S rRNA sequencing analysis to determine the changes in the microbial composition postirradiation. We used in-house bioinformatics tools to integrate the 16S rRNA sequencing and metabolomic data, and to elucidate the gut integrated ecosystem and its deviations from a stable host-microbiome state that result from irradiation. The 16S rRNA sequencing results indicated that radiation caused remarkable alterations of the microbiome in feces at the family level. Increased abundance of common members of Lactobacillaceae and Staphylococcaceae families, and decreased abundances of Lachnospiraceae, Ruminococcaceae and Clostridiaceae families were found after 5 and 12 Gy irradiation. The metabolomic data revealed statistically significant changes in the microbial-derived products such as pipecolic acid, glutaconic acid, urobilinogen and homogentisic acid. In addition, significant changes were detected in bile acids such as taurocholic acid and 12-ketodeoxycholic acid. These changes may be associated with the observed shifts in the abundance of intestinal microbes, such as R. gnavus , which can transform bile acids.