Sample preparation and recent trends in volatolomics for diagnosing gastrointestinal diseases

Sample Collection and Processing in Volatile Organic Compound Analysis for Gastrointestinal Cancers

Volatile organic compounds have drawn significant attention in recent years as a novel tool for non-invasive detection of a wide range of diseases, including gastrointestinal cancers, for which the need for effective, affordable, and non-invasive screening methods is substantial. Sample preparation is a fundamental step that greatly influences the quality of results and the feasibility of wide-range applications. This review summarizes sampling methods used in studies aiming at testing the diagnostic value of volatile organic compounds in gastrointestinal cancers, discussing in detail some of the recent advancements in automated sampling techniques. Finally, we propose some directions in which sample collection and processing can improve for VOC analysis to be popularized in clinical settings.

The overshadowed role of electron ionization-mass spectrometry in analytical biotechnology

Target and untargeted analysis of several compounds are crucial methods in important areas such as omics sciences. Gas chromatography coupled to mass spectrometry (GC-MS) is widely used for volatile and thermally stable compounds. In this case, the electron ionization technique (EI) is preferable as it produces highly fragmented and reproducible spectra comparable to spectral libraries. However, only a fraction of target compounds is analyzable by GC without chemical derivatization. Therefore, liquid chromatography (LC) coupled with MS is the most used technique. Contrary to EI, electrospray ionization does not produce reproducible spectra. That is why researchers have been working on interfaces between LC and EI-MS to bridge the gap between those techniques. This short review will discuss advancements, applications, and perspectives on biotechnological analysis.

Identification by volatolomics of hydrocarbon, oxygenated, sulfur and aromatic markers of livestock exposure to α-hexabromocyclododecane

Volatile organic compounds (VOC)-based metabolomics, or volatolomics, was investigated for revealing livestock exposure to chemical contamination. Three farm animals, namely laying hens, broilers, and pigs, were experimentally exposed to 5 or 50 ng α-HBCDD g^-1 feed. Liver and egg yolk for hens were analysed by headspace-SPME-GC-MS to reveal candidate markers of the livestock exposure to α-HBCDD. For hens, 2-butanol was found as marker in egg. In liver, twelve VOCs were highlighted as markers, with three aromatic VOCs - styrene, o-xylene, α-methylstyrene - highlighted for the two α-HBCDD doses. For broilers, six markers were revealed, with interestingly, styrene and phenol which were also found as markers in hen liver. For pigs, ten markers were revealed and the seven tentatively identified markers were oxygenated and sulfur VOCs. The candidate markers tentatively identified were discussed in light of previous volatolomics data, in particular from a γ-HBCDD exposure of laying hens.

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

Electronic nose to distinguish bladder cancer by urinary odour feature: A pilot study

BACKGROUND

No study has yet investigated the use of electronic nose (eNose) technology to reveal pattern recognition of urological diseases, including bladder cancer.

OBJECTIVE

We sought to determine the diagnostic performance of the eNose in recognizing urinary odour in patients with bladder cancer.

METHODS

The eNose is a commercially available model equipped with two sensors. The angle of the two sensors (θ) depends on the kinds of chemical substances, thus defining θ as the feature of odour. Quantity of odour is the number of θ detected during a measurement. Urine samples were from 36 untreated patients with bladder cancer, 29 with urolithiasis, 10 with urinary tract infection (UTI), and 27 healthy volunteers.

RESULTS

Based on ROC analysis of the quantity in patients with bladder cancer, an optimal cut-off value for θ of 49, 48, and 55 was applied to compare with samples from the healthy volunteer, urolithiasis and UTI groups, respectively. There were significantly differences between bladder cancer and the other conditions using these specific points (p< 0.0001, respectively). The resulting diagnostic sensitivity was 61.4%, 45.6%, and 60.8%, and specificity was 52.8%, 68.4%, and 90.2%, respectively. The AUC for bladder cancer was 0.565, 0.548, and 0.909, respectively.

CONCLUSION

The eNose is a small, portable, rapid, low cost, and noninvasive instrument for distinguishing bladder cancer from other benign conditions.

Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome

Volatilome analysis is growing in attention for the diagnosis of diseases in animals and humans. In particular, volatilome analysis in fecal samples is starting to be proposed as a fast, easy and noninvasive method for disease diagnosis. Volatilome comprises volatile organic compounds (VOCs), which are produced during both physiological and patho-physiological processes. Thus, VOCs from a pathological condition often differ from those of a healthy state and therefore the VOCs profile can be used in the detection of some diseases. Due to their strengths and advantages, feces are currently being used to obtain information related to health status in animals. However, they are complex samples, that can present problems for some analytical techniques and require special consideration in their use and preparation before analysis. This situation demands an effort to clarify which analytic options are currently being used in the research context to analyze the possibilities these offer, with the final objectives of contributing to develop a standardized methodology and to exploit feces potential as a diagnostic matrix. The current work reviews the studies focused on the diagnosis of animal diseases through fecal volatilome in order to evaluate the analytical methods used and their advantages and limitations. The alternatives found in the literature for sampling, storage, sample pretreatment, measurement and data treatment have been summarized, considering all the steps involved in the analytical process.

A Novel Framework with High Diagnostic Sensitivity for Lung Cancer Detection by Electronic Nose

The electronic nose (e-nose) system is a newly developing detection technology for its advantages of non-invasiveness, simple operation, and low cost. However, lung cancer screening through e-nose requires effective pattern recognition frameworks. Existing frameworks rely heavily on hand-crafted features and have relatively low diagnostic sensitivity. To handle these problems, gated recurrent unit based autoencoder (GRU-AE) is adopted to automatically extract features from temporal and high-dimensional e-nose data. Moreover, we propose a novel margin and sensitivity based ordering ensemble pruning (MSEP) model for effective classification. The proposed heuristic model aims to reduce missed diagnosis rate of lung cancer patients while maintaining a high rate of overall identification. In the experiments, five state-of-the-art classification models and two popular dimensionality reduction methods were involved for comparison to demonstrate the validity of the proposed GRU-AE-MSEP framework, through 214 collected breath samples measured by e-nose. Experimental results indicated that the proposed intelligent framework achieved high sensitivity of 94.22%, accuracy of 93.55%, and specificity of 92.80%, thereby providing a new practical means for wide disease screening by e-nose in medical scenarios.

Hyaluronate-Functionalized Graphene for Label-Free Electrochemical Cytosensing

Electrochemical sensors for early tumor cell detection are currently an important area of research, as this special region directly improves the efficiency of cancer treatment. Functional graphene is a promising alternative for selective recognition and capture of target cancer cells. In our work, an effective cytosensor of hyaluronate-functionalized graphene (HG) was prepared through chemical reduction of graphene oxide. The as-prepared HG nanostructures were characterized with Fourier transform infrared spectroscopy and transmission electron microscopy coupled with cyclic voltammograms and electrochemical impedance spectroscopy, respectively. The self-assembly of HG with ethylene diamine, followed by sodium hyaluronate, enabled the fabrication of a label-free electrochemical impedance spectroscopy cytosensor with high stability and biocompatibility. Finally, the proposed cytosensor exhibited satisfying electrochemical behavior and cell-capture capacity for human colorectal cancer cells HCT-116, and also displayed a wide linear range, from 5.0 × 10² cells∙mL-1 to 5.0 × 10⁶ cells∙mL-1, and a low detection limit of 100 cells∙mL-1 (S/N = 3) for quantification. This work paves the way for graphene applications in electrochemical cytosensing and other bioassays.

Influence of Water Molecules on the Detection of Volatile Organic Compounds (VOC) Cancer Biomarkers by Nanocomposite Quantum Resistive Vapor Sensors vQRS

The anticipated diagnosis of various fatal diseases from the analysis of volatile organic compounds (VOC) biomarkers of the volatolome is the object of very dynamic research. Nanocomposite-based quantum resistive vapor sensors (vQRS) exhibit strong advantages in the detection of biomarkers, as they can operate at room temperature with low consumption and sub ppm (part per million) sensitivity. However, to meet this application they need to detect some ppm or less amounts of biomarkers in patients' breath, skin, or urine in complex blends of numerous VOC, most of the time hindered by a huge amount of water molecules. Therefore, it is crucial to analyze the effects of moisture on the chemo-resistive sensing behavior of carbon nanotubes based vQRS. We show that in the presence of water molecules, the sensors cannot detect the right amount of VOC molecules present in their environment. These perturbations of the detection mechanism are found to depend on the chemical interactions between water and other VOC molecules, but also on their competitive absorption on sensors receptive sites, located at the nanojunctions of the conductive architecture. This complex phenomenon studied with down to 12.5 ppm of acetone, ethanol, butanone, toluene, and cyclohexane mixed with 100 ppm of water was worth to investigate in the prospect of future developments of devices analysing real breath samples in which water can reach a concentration of 6%.

A targeted metabolomic protocol for quantitative analysis of volatile organic compounds in urine of children with celiac disease

Volatile organic compounds (VOCs) in biological samples have gained popularity for disease monitoring and diagnosis. Celiac disease (CD) is one of the many prevalent health conditions which are challenging to diagnose. The aim of this study was to optimize a solid phase microextraction followed by gas chromatography-mass spectrometry, for quantitative analysis of a wide range of VOCs in the urine of patients with CD. Multivariate design of experiment was used to optimize the extraction conditions for the analysis of 15 urinary VOCs. Based on the performed experiments, extraction using 2.98 g of sodium chloride and 21 μL of 6 M hydrochloric acid for 15 min at 30 °C, using a CAR/PDMS fiber in headspace mode was found to be the most effective procedure for the analysis of the selected biomarkers. It was also demonstrated that the proposed method could distinguish between children with CD and healthy children based on the profile of VOCs. It is believed that quantitative analysis of these biomarkers will extend our understanding of CD and could be used for monitoring in patients under treatment.