Hybrid volatilomics in cancer diagnosis by HS-GC-FID fingerprinting.

Assessing volatile organic compounds (VOCs) as cancer signatures is one of the most promising techniques toward developing non-invasive, simple, and affordable diagnosis. Here, we have evaluated the feasibility of employing static headspace extraction (HS) followed by gas chromatography with flame ionization detector (GC-FID) as a screening tool to discriminate between cancer patients (head and neck-HNC,n= 15; and gastrointestinal cancer-GIC,n= 19) and healthy controls (n= 37) on the basis of a non-target (fingerprinting) analysis of oral fluid and urine. We evaluated the discrimination considering a single bodily fluid and adopting the hybrid approach, in which the oral fluid and urinary VOCs profiles were combined through data fusion. We used supervised orthogonal partial least squares discriminant analysis for classification, and we assessed the prediction power of the models by analyzing the values of goodness of prediction (Q2Y), area under the curve (AUC), sensitivity, and specificity. The individual models HNC urine, HNC oral fluid, and GIC oral fluid successfully discriminated between healthy controls and positive samples (Q2Y = 0.560, 0.525, and 0.559; AUC = 0.814, 0.850, and 0.926; sensitivity = 84.8, 70.2, and 78.6%; and specificity = 82.3; 81.5; 87.5%, respectively), whereas GIC urine was not adequate (Q2Y = 0.292, AUC = 0.694, sensitivity = 66.1%, and specificity = 77.0%). Compared to the respective individual models, Q2Y for the hybrid models increased (0.623 for hybrid HNC and 0.562 for hybrid GIC). However, sensitivity was higher for HNC urine and GIC oral fluid than for hybrid HNC (75.6%) and hybrid GIC (69.8%), respectively. These results suggested that HS-GC-FID fingerprinting is suitable and holds great potential for cancer screening. Additionally, the hybrid approach tends to increase the predictive power if the individual models present suitable quality parameter values. Otherwise, it is more advantageous to use a single body fluid for analysis.

ChiMera: an easy to use pipeline for bacterial genome based metabolic network reconstruction, evaluation and visualization.

BACKGROUND: Genome-scale metabolic reconstruction tools have been developed in the last decades. They have helped to reconstruct eukaryotic and prokaryotic metabolic models, which have contributed to fields, e.g., genetic engineering, drug discovery, prediction of phenotypes, and other model-driven discoveries. However, the use of these programs requires a high level of bioinformatic skills. Moreover, the functionalities required to build models are scattered throughout multiple tools, requiring knowledge and experience for utilizing several tools. RESULTS: Here we present ChiMera, which combines tools used for model reconstruction, prediction, and visualization. ChiMera uses CarveMe in the reconstruction module, generating a gap-filled draft reconstruction able to produce growth predictions using flux balance analysis for gram-positive and gram-negative bacteria. ChiMera also contains two modules for metabolic network visualization. The first module generates maps for the most important pathways, e.g., glycolysis, nucleotides and amino acids biosynthesis, fatty acid oxidation and biosynthesis and core-metabolism. The second module produces a genome-wide metabolic map, which can be used to retrieve KEGG pathway information for each compound in the model. A module to investigate gene essentiality and knockout is also present. CONCLUSIONS: Overall, ChiMera uses automation algorithms to combine a variety of tools to automatically perform model creation, gap-filling, flux balance analysis (FBA), and metabolic network visualization. ChiMera models readily provide metabolic insights that can aid genetic engineering projects, prediction of phenotypes, and model-driven discoveries.

Sphingolipids signature in plasma and tissue as diagnostic and prognostic tools in oral squamous cell carcinoma.

Enzymes related to sphingolipids metabolism has been suggested as altered in oral squamous cell carcinoma (OSCC). However, clinical relevance of diverse sphingolipids in OSCC is not fully known. Here, we evaluated sphingolipidomics in plasma and tumor tissues as a tool for diagnosis/prognosis in OSCC patients. Plasma was obtained from 58 controls and 56 OSCC patients, and paired tumor and surgical margin tissues (n = 42). The levels of 28 sphingolipids molecules were obtained by mass spectrometry. Furthermore, sphingolipids were analyzed with clinical and pathological characteristics to search the potential for diagnosis and prognosis. Lower levels of 17 sphingolipids was found in the plasma of OSCC patients compared to controls while four were elevated in tumor tissues. C18:0 dyhidroceramide and C24:0 lactosylceramide in plasma were associated with perineural invasion, while tissue levels of ceramide and dyhidroceramide were associated with advanced tumor stage and perineural invasion. High plasma levels of C24:0 ceramide (HR = 0.10, p = 0.0036) and C24:1 glucosylceramide (HR = 6.62, p = 0.0023), and tissue levels of C24:0 dyhidroceramide (HR = 3.95, p = 0.032) were identified as independent prognostic factors. Moreover, we identified signatures composed by i) sphinganine-1-phosphate and C16 ceramide-1-phosphate in plasma with significant diagnostic accuracy, while ii) C24:0 ceramide, C24:0 dyhidroceramide, and C24:1 glucosylceramide plasma levels, and iii) C24:0 dyhidrosphingomyelin and C24:0 ceramide tissue levels showed value to predict survival in patients aged 60 years or older. We proposed the sphingolipids signatures in plasma and tumor tissues as biomarkers candidates to diagnosis and prognosis in OSCC.

Mining novel cis-regulatory elements from the emergent host Rhodosporidium toruloides using transcriptomic data.

The demand for robust microbial cell factories that produce valuable biomaterials while resisting stresses imposed by current bioprocesses is rapidly growing. Rhodosporidium toruloides is an emerging host that presents desirable features for bioproduction, since it can grow in a wide range of substrates and tolerate a variety of toxic compounds. To explore R. toruloides suitability for application as a cell factory in biorefineries, we sought to understand the transcriptional responses of this yeast when growing under experimental settings that simulated those used in biofuels-related industries. Thus, we performed RNA sequencing of the oleaginous, carotenogenic yeast in different contexts. The first ones were stress-related: two conditions of high temperature (37 and 42°C) and two ethanol concentrations (2 and 4%), while the other used the inexpensive and abundant sugarcane juice as substrate. Differential expression and functional analysis were implemented using transcriptomic data to select differentially expressed genes and enriched pathways from each set-up. A reproducible bioinformatics workflow was developed for mining new regulatory elements. We then predicted, for the first time in this yeast, binding motifs for several transcription factors, including HAC1, ARG80, RPN4, ADR1, and DAL81. Most putative transcription factors uncovered here were involved in stress responses and found in the yeast genome. Our method for motif discovery provides a new realm of possibilities in studying gene regulatory networks, not only for the emerging host R. toruloides, but for other organisms of biotechnological importance.

Time-Scale Shifting of Volatile Semiochemical Levels in Wild Type Lychnophora ericoides (Brazilian arnica) and Pollinator Records.

Lychnophora ericoides is a Brazilian folk phytomedicine from Cerrado's "campus rupestris". Its volatile organic compounds includes bisabolene-derivatives as major compounds. Herein we provide the chemical profiling of constitutive volatile sesquiterpenes from L. ericoides leaves, timeframe emissions surveys, and pollinators records. In situ samples of L. ericoides were harvested. A headspace-solid phase micro extraction method of pre-concentration was optimized. Identification was done through GC-MS. Isolation and structural elucidation were performed whenever necessary. Pollinators were registered in pictures and video. Short time-series and harmonic regressions determined rhythms of single compounds, and average chromatographic signal area was used to determine mono and sesquiterpene rhythms. Concluding, optimized headspace-solid phase micro extraction method of terpenes level analysis was reached. α-Pinene, ß-pinene, α-terpinene, para-cymene, limonene, γ-terpinene, terpinen-4-ol, dehydro-sesquicineole, and ß-guaiene were identified using GC-MS data. 11-dehydro cadinol and ortho-acetoxy bisabolol were elucidated. Sesquiterpenes concentrations were higher due to temperature rise, lower leaf age, and flowering seasons. Harmonic regressions determined that daylight might control levels of terpenes. Hummingbird, hemiptera insects, and wasps were recorded visiting Compositae capitulum for the first time. We studied nondomestic plants from in situ conditions and concluded that bisabolene-derivative levels were more abundant than monoterpenes during flowering throughout the summer.