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Identification of volatile compounds from bacteria by spectrometric methods in medicine diagnostic and other areas: current state and perspectives. Appl Microbiol Biotechnol 2021; 105:6245-6255. [PMID: 34415392 PMCID: PMC8377328 DOI: 10.1007/s00253-021-11469-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 07/20/2021] [Accepted: 07/22/2021] [Indexed: 10/25/2022]
Abstract
Diagnosis of bacterial infections until today mostly relies on conventional microbiological methods. The resulting long turnaround times can lead to delayed initiation of adequate antibiotic therapy and prolonged periods of empiric antibiotic therapy (e.g., in intensive care medicine). Therewith, they contribute to the mortality of bacterial infections and the induction of multidrug resistances. The detection of species specific volatile organic compounds (VOCs) emitted by bacteria has been proposed as a possible diagnostic approach with the potential to serve as an innovative point-of-care diagnostic tool with very short turnaround times. A range of spectrometric methods are available which allow the detection and quantification of bacterial VOCs down to a range of part per trillion. This narrative review introduces the application of spectrometric analytical methods for the purpose of detecting VOCs of bacterial origin and their clinical use for diagnosing different infectious conditions over the last decade. KEY POINTS: • Detection of VOCs enables bacterial differentiation in various medical conditions. • Spectrometric methods may function as point-of-care diagnostics in near future.
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Elmassry MM, Piechulla B. Volatilomes of Bacterial Infections in Humans. Front Neurosci 2020; 14:257. [PMID: 32269511 PMCID: PMC7111428 DOI: 10.3389/fnins.2020.00257] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 03/09/2020] [Indexed: 02/06/2023] Open
Abstract
Sense of smell in humans has the capacity to detect certain volatiles from bacterial infections. Our olfactory senses were used in ancient medicine to diagnose diseases in patients. As humans are considered holobionts, each person's unique odor consists of volatile organic compounds (VOCs, volatilome) produced not only by the humans themselves but also by their beneficial and pathogenic micro-habitants. In the past decade it has been well documented that microorganisms (fungi and bacteria) are able to emit a broad range of olfactory active VOCs [summarized in the mVOC database (http://bioinformatics.charite.de/mvoc/)]. During microbial infection, the equilibrium between the human and its microbiome is altered, followed by a change in the volatilome. For several decades, physicians have been trying to utilize these changes in smell composition to develop fast and efficient diagnostic tools, particularly because volatiles detection is non-invasive and non-destructive, which would be a breakthrough in many therapies. Within this review, we discuss bacterial infections including gastrointestinal, respiratory or lung, and blood infections, focusing on the pathogens and their known corresponding volatile biomarkers. Furthermore, we cover the potential role of the human microbiota and their volatilome in certain diseases such as neurodegenerative diseases. We also report on discrete mVOCs that affect humans.
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Affiliation(s)
- Moamen M. Elmassry
- Department of Biological Sciences, Texas Tech University, Lubbock, TX, United States
| | - Birgit Piechulla
- Institute for Biological Sciences, University of Rostock, Rostock, Germany
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Hirani N, Joshi A, Anand S, Chowdhary A, Ganesan K, Agarwal M, Phadke N. Detection of a novel mutation in the rpoB gene in a multidrug resistant Mycobacterium tuberculosis isolate using whole genome next generation sequencing. J Glob Antimicrob Resist 2020; 22:270-274. [PMID: 32200129 DOI: 10.1016/j.jgar.2020.03.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 11/13/2019] [Accepted: 03/04/2020] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Mycobacterium tuberculosis (Mtb) drug resistance is a global concern. Moreover, multiple drug resistant (MDR), extensively drug resistant (XDR), and totally drug resistant (TDR) Mtb cases are on the rise in developing countries like India. Most of these cases are identified only 3-6 months after initiation of treatment owing to incomplete/failed clinical response and incomplete information from phenotypic drug resistance assays and/or targeted Mtb mutation analysis. Here, we report the development of an in-house whole genome sequencing (WGS) assay and bioinformatics pipeline that helped resolve the phenotype-genotype discrepancy in a clinical isolate. METHODOLOGY AND RESULTS A sample from a suspected drug resistant Mtb case tested by line probe assay (LPA) showed the absence of both the mutant and wild type alleles for an rpoB gene mutation site. An in-house next generation sequencing (NGS) assay was used for WGS of this isolate. Bioinformatics analysis revealed that the isolate harboured a novel insertional mutation in the 81-bp hotspot region of the rpoB gene and a S315T mutation in the katG gene, which could explain resistance to rifampicin and isoniazid, respectively. These results correlated with the clinical diagnosis, LPA, solid culture drug susceptibility testing, and pyrosequencing carried out on the sample. The WGS data also provided information regarding the isolate's lineage and indicated an absence of known mutations conferring resistance to other antitubercular drugs. CONCLUSION WGS is a highly sensitive, specific, and unbiased approach for identification of all possible drug resistance-conferring mutations, which can help clinicians make more informed treatment-related decisions.
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Affiliation(s)
- Nilma Hirani
- Department of Microbiology, Grant Govt Medical College & Sir JJ Group of Hospitals, Mumbai, India
| | - Ameeta Joshi
- Department of Microbiology, Grant Govt Medical College & Sir JJ Group of Hospitals, Mumbai, India
| | - Siddharth Anand
- GenePath Diagnostics India Pvt. Ltd., Pune, India; I-SHARE Foundation, Pune, India
| | - Abhay Chowdhary
- Department of Microbiology, Grant Govt Medical College & Sir JJ Group of Hospitals, Mumbai, India
| | - Karthik Ganesan
- GenePath Diagnostics India Pvt. Ltd., Pune, India; GenePath Diagnostics Inc., Ann Arbor, Michigan, USA; I-SHARE Foundation, Pune, India
| | - Meenal Agarwal
- GenePath Diagnostics India Pvt. Ltd., Pune, India; I-SHARE Foundation, Pune, India
| | - Nikhil Phadke
- GenePath Diagnostics India Pvt. Ltd., Pune, India; GenePath Diagnostics Inc., Ann Arbor, Michigan, USA; I-SHARE Foundation, Pune, India
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Jia ZL, Cen J, Wang JB, Zhang F, Xia Q, Wang X, Chen XQ, Wang RC, Hsiao CD, Liu KC, Zhang Y. Mechanism of isoniazid-induced hepatotoxicity in zebrafish larvae: Activation of ROS-mediated ERS, apoptosis and the Nrf2 pathway. CHEMOSPHERE 2019; 227:541-550. [PMID: 31004821 DOI: 10.1016/j.chemosphere.2019.04.026] [Citation(s) in RCA: 93] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 04/02/2019] [Accepted: 04/03/2019] [Indexed: 06/09/2023]
Abstract
Isoniazid (INH) is a first-line anti-tuberculosis drug. INH has been detected in surface waters which may create a risk to aquatic organisms. In this study, the hepatotoxicity of INH was elucidated using zebrafish. The liver morphology, transaminase level, redox-related enzyme activity, reactive oxygen species (ROS) content and mRNA levels of liver injury-related genes were measured. The results showed that INH (4, 6 mM) significantly caused liver atrophy and increased levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in zebrafish. INH (6 mM) led to decreased catalase (CAT) activity, glutathione peroxidase (GPx) activity and glutathione (GSH) content but increased ROS and malondialdehyde (MDA) levels. Moreover, INH (6 mM) decreased expression levels of miR-122 and pparα but increased mRNA levels of ap-1 and c-jun. Furthermore, mRNA levels of factors related to endoplasmic reticulum stress (ERS) (grp78, atf6, perk, ire1, xbp1s and chop), apoptosis (bax, cyt, caspase-3, caspase-8 and caspase-9) and the Nrf2 signalling pathway (nrf2, ho-1, nqo1, gclm and gclc) were significantly upregulated. INH may act on hepatotoxicity in zebrafish by increasing ROS content, which weakens the antioxidant capacity, leading to ERS, cell apoptosis and liver injury. In addition, the Nrf2 signalling pathway is activated as a stress compensation mechanism during INH-induced liver injury, but it is not sufficient to counteract INH-induced hepatotoxicity.
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Affiliation(s)
- Zhi-Li Jia
- Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory for Drug Screening Technology of Shandong Academy of Sciences, Key Laboratory for Biosensor of Shandong Province, Jinan, Shandong Province, PR China; Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, Henan Province, PR China
| | - Juan Cen
- Key Laboratory of Natural Medicine and Immuno-Engineering, Henan University, Kaifeng, Henan Province, PR China
| | - Jia-Bo Wang
- Beijing 302 Hospital of China, Beijing, PR China
| | - Feng Zhang
- College of Pharmacy, Henan University, Kaifeng, Henan Province, PR China
| | - Qing Xia
- Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory for Drug Screening Technology of Shandong Academy of Sciences, Key Laboratory for Biosensor of Shandong Province, Jinan, Shandong Province, PR China
| | - Xue Wang
- Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory for Drug Screening Technology of Shandong Academy of Sciences, Key Laboratory for Biosensor of Shandong Province, Jinan, Shandong Province, PR China
| | - Xi-Qiang Chen
- Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory for Drug Screening Technology of Shandong Academy of Sciences, Key Laboratory for Biosensor of Shandong Province, Jinan, Shandong Province, PR China
| | - Rong-Chun Wang
- Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory for Drug Screening Technology of Shandong Academy of Sciences, Key Laboratory for Biosensor of Shandong Province, Jinan, Shandong Province, PR China
| | - Chung-der Hsiao
- Department of Bioscience Technology, Chung Yuan Christian University, Chung-Li, Taiwan
| | - Ke-Chun Liu
- Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory for Drug Screening Technology of Shandong Academy of Sciences, Key Laboratory for Biosensor of Shandong Province, Jinan, Shandong Province, PR China
| | - Yun Zhang
- Biology Institute, Qilu University of Technology (Shandong Academy of Sciences), Key Laboratory for Drug Screening Technology of Shandong Academy of Sciences, Key Laboratory for Biosensor of Shandong Province, Jinan, Shandong Province, PR China.
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