Abstract:Mental fatigue is characterized by a reduced capacity for work and a loss of capacity to respond to stimulation and is usually accompanied by a feeling of tiredness and drowsiness. Mental fatigue at work is a serious problem and can raise safety concerns especially in the transportation system. It is believed that mental fatigue is a direct or contributing cause of road and air related accidents and incidents. Psychological studies indicate that fatigue results in reduced work efficiency, alertness, and impair… Show more
“…Within Progenesis QI, feature sample variance is defined by the minimum percent coefficient of variance (min %CV) from any experimental group such that a low %CV value represents less abundance variance among biological samples. Based on other untargeted metabolomic studies, 42, 43 we considered features with a min %CV ≤30% as having acceptable abundance variation, with 69% of the features in HILIC-POS have a min %CV ≤30% and 57% of the features in HILIC-NEG have a min %CV ≤30%. The binning of features by min %CV ranges is shown in supplemental Fig.…”
The C. elegans gene swip-10 encodes an orphan metallo β-lactamase that genetic studies indicate is vital for limiting neuronal excitability and viability. Sequence analysis indicates that the mammalian gene Mblac1 is the likely ortholog of swip-10, with greatest sequence identity localized to the encoded protein's single metallo β-lactamase domain. The substrate for the SWIP-10 protein remains unknown and to date no functional roles have been ascribed to MBLAC1, though we have shown that the protein binds the neuroprotective β-lactam antibiotic, ceftriaxone. To gain insight into the functional role of MBLAC1 in vivo, we used CRISPR/Cas9 methods to disrupt N-terminal coding sequences of the mouse Mblac1 gene, resulting in a complete loss of protein expression in viable, homozygous knockout (KO) animals. Using serum from both WT and KO mice, we performed global, untargeted metabolomic analyses, resolving small molecules via hydrophilic interaction chromatography (HILIC) based ultra-performance liquid chromatography, coupled to mass spectrometry (UPLC-MS/MS). Unsupervised principal component analysis reliably segregated the metabolomes of MBLAC1 KO and WT mice, with 92 features subsequently nominated as significantly different by ANOVA, and for which we made tentative and putative metabolite assignments. Bioinformatic analyses of these molecules nominate validated pathways subserving bile acid biosynthesis and linoleate metabolism, networks known to be responsive to metabolic and oxidative stress. Our findings lead to hypotheses that can guide future targeted studies seeking to identify the substrate for MBLAC1 and how substrate hydrolysis supports the neuroprotective actions of ceftriaxone.
“…Within Progenesis QI, feature sample variance is defined by the minimum percent coefficient of variance (min %CV) from any experimental group such that a low %CV value represents less abundance variance among biological samples. Based on other untargeted metabolomic studies, 42, 43 we considered features with a min %CV ≤30% as having acceptable abundance variation, with 69% of the features in HILIC-POS have a min %CV ≤30% and 57% of the features in HILIC-NEG have a min %CV ≤30%. The binning of features by min %CV ranges is shown in supplemental Fig.…”
The C. elegans gene swip-10 encodes an orphan metallo β-lactamase that genetic studies indicate is vital for limiting neuronal excitability and viability. Sequence analysis indicates that the mammalian gene Mblac1 is the likely ortholog of swip-10, with greatest sequence identity localized to the encoded protein's single metallo β-lactamase domain. The substrate for the SWIP-10 protein remains unknown and to date no functional roles have been ascribed to MBLAC1, though we have shown that the protein binds the neuroprotective β-lactam antibiotic, ceftriaxone. To gain insight into the functional role of MBLAC1 in vivo, we used CRISPR/Cas9 methods to disrupt N-terminal coding sequences of the mouse Mblac1 gene, resulting in a complete loss of protein expression in viable, homozygous knockout (KO) animals. Using serum from both WT and KO mice, we performed global, untargeted metabolomic analyses, resolving small molecules via hydrophilic interaction chromatography (HILIC) based ultra-performance liquid chromatography, coupled to mass spectrometry (UPLC-MS/MS). Unsupervised principal component analysis reliably segregated the metabolomes of MBLAC1 KO and WT mice, with 92 features subsequently nominated as significantly different by ANOVA, and for which we made tentative and putative metabolite assignments. Bioinformatic analyses of these molecules nominate validated pathways subserving bile acid biosynthesis and linoleate metabolism, networks known to be responsive to metabolic and oxidative stress. Our findings lead to hypotheses that can guide future targeted studies seeking to identify the substrate for MBLAC1 and how substrate hydrolysis supports the neuroprotective actions of ceftriaxone.
“…The search strategy and the stepwise outcomes are outlined in Figure 1 . Manual review of the titles and abstracts of the 170 articles identified by the literature search revealed three studies of direct relevance: one study that examined the effect of shift work on the metabolome [ 61 ], one that examined the effects of mental fatigue (caused by a stressful occupation - air-traffic control) [ 62 ] and a third that investigated lifestyle stressors, including those related to work [ 63 ]. Figure 1 Literature Search Schematic.…”
Section: Resultsmentioning
confidence: 99%
“…In contrast, Chen et al. [ 62 ] may have missed relevant metabolites by their approach because it may have neglected combinatorial effects.…”
Section: Resultsmentioning
confidence: 99%
“…The urinary metabolomic changes associated with mental fatigue were studied in air-traffic controllers [ 62 ]. In this comprehensive LC-MS/MS analysis utilizing three different chromatographic separation conditions to increase the richness of the detected metabolome, the authors reported three putative biomarkers: decreased N2, N2-dimethylguanosine, decreased N-acetylarylamine (a well-known but discontinued analgesic) and increased alpha-carboxyethyl hydrochroman, a water-soluble metabolite of vitamin E. The authors offered limited biological interpretation of the results, suggesting that N,N-dimethylguanosine belonged to the tyrosine metabolism pathway (KEGG).…”
Section: Resultsmentioning
confidence: 99%
“…The finding that turnover of vitamin E might be increased in mental fatigue is interesting given its role as an antioxidant and the proposed role of oxidative stress in health deterioration caused by sleep loss [ 95 ]. Interestingly alpha-tocopherol (Vitamin E) was elevated in plasma in patients exhibiting exhaustion disorder [ 62 ], although the two findings appear at odds.…”
Given the immense and growing cost of occupational stress to society through lost productivity and the burden to healthcare systems, current best practices for detecting, managing and reducing stress in the workplace are clearly sub-optimal and substantially better methods are required. Subjective, self-reported psychology and psychiatry-based instruments are prone to biases whereas current objective, biology-based measures produce conflicting results and are far from reliable. A multivariate approach to occupational stress research is required that reflects the broad, coordinated, physiological response to demands placed on the body by exposure to diverse occupational stressors. A literature review was conducted to determine the extent of application of the emerging multivariate technology of metabolomics to occupational stress research. Of 170 articles meeting the search criteria, three were identified that specifically studied occupational stressors using metabolomics. A further ten studies were not specifically occupational or were of indirect or peripheral relevance. The occupational studies, although limited in number highlight the technological challenges associated with the application of metabolomics to investigate occupational stress. They also demonstrate the utility to evaluate stress more comprehensively than univariate biomarker studies. The potential of this multivariate approach to enhance our understanding of occupational stress has yet to be established. This will require more studies with broader analytical coverage of the metabolome, longitudinal sampling, combination with experience sampling methods and comparison with psychometric models of occupational stress. Progress will likely involve combining multi-omic data into a holistic, systems biology approach to detecting, managing and reducing occupational stress and optimizing workplace performance.
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