Time-of-flight Mass Spectrometry Research Articles

Cutaneous Prototheca wickerhamii infection identified with the matrix-assisted laser desorption/ionization time-of flight mass spectrometry after protein extraction protocol for filamentous fungi isolates from a facial discharge of a 66-year-old female patient in Korea: a case report

Prototheca wickerhamii is an achlorophyllic algae that rarely acts as an opportunistic pathogen in humans. We report the case of a 66-year-old female patient with a history of diabetes mellitus who presented with a pus-like discharge from face, facial redness, and swelling. The patient was admitted to the emergency room with worsening facial pain. Gram staining from pus-like discharge revealed yeast like features; however, an isolated colony on a blood agar plate was not identified using VITEK 2 (Biomerieux) or matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF) using VITEK®MS (Biomerieux). Lactophenol cotton blue staining of the colony revealed characteristic sporangia and endospore features. After performing the protein extraction procedure for filamentous fungi (mold) isolates using ethanol and formic acid, MALDI-TOF MS identified the colony as Prototheca wickerhamii, with 99.9% confidence. This case indicates that Prototheca spp. require specialized sample preparation steps, such as the ethanol/formic acid extraction procedure, for identification using MALDI-TOF MS.

Automatic identification of clinically important Aspergillus species by artificial intelligence-based image recognition: proof-of-concept study

ABSTRACT While morphological examination is the most widely used for Aspergillus identification in clinical laboratories, PCR–sequencing and MALDI–TOF MS are emerging technologies in more financially-competent laboratories. However, mycological expertise, molecular biologists and/or expensive equipment are needed for these. Recently, artificial intelligence (AI), especially image recognition, is being increasingly employed in medicine for fast and automated disease diagnosis. We explored the potential utility of AI in identifying Aspergillus species. In this proof-of-concept study, using 2813, 2814 and 1240 images from four clinically important Aspergillus species for training, validation and testing, respectively; the performances and accuracies of automatic Aspergillus identification using colonial images by three different convolutional neural networks were evaluated. Results demonstrated that ResNet-18 outperformed Inception-v3 and DenseNet-121 and is the best algorithm of choice because it made the fewest misidentifications (n = 8) and possessed the highest testing accuracy (99.35%). Images showing more unique morphological features were more accurately identified. AI-based image recognition using colonial images is a promising technology for Aspergillus identification. Given its short turn-around-time, minimal demand of expertise, low reagent/equipment costs and user-friendliness, it has the potential to serve as a routine laboratory diagnostic tool after the database is further expanded.

MALDI - TOF MS for the identification of obligate anaerobes and metronidazole susceptibility of anaerobic Gram negative bacilli

MALDI-TOF MS, though has facilitated rapid and accurate anaerobe identification, the problem of rising metronidazole resistance amongst the members of Bacteroides fragilis group is cause for concern. In this one-year study period,152 anaerobic Gram negative bacilli and 60 Gram positive anaerobes were isolated from 167 samples obtained from clinically suspected anaerobic infections. Bacteroides fragilis accounted for 56 % of the total anaerobic GNB and Peptoniphilus asacchrarolyticus was the most commonly isolated Gram positive cocci. All isolates were identified by the MALDI–TOF MS except one isolate each of Clostridium and Peptostreptococcus. E-test for members of Bacteroides fragilis group, demonstrated 26.8 % metronidazole resistance.

Authenticity of cinnamon verum determined by MALDI TOF MS and machine learning

Authenticity of cinnamon verum determined by MALDI TOF MS and machine learning

The neurotoxic effect of Naja nubiae (Serpentes: Elapidae) venom from Sudan.

Neurotoxicity is a common feature of elapid snake envenomation. There are limited studies on the toxicity of Naja nubiae venom, the Nubian spitting cobra, from north-east Africa. We used the chick biventer cervicis nerve-muscle preparation to demonstrate the neurotoxic effect of N. nubiae venom and to compare it with the potent neurotoxic cobra Naja melanoleuca venom. Venoms were separated by successive reverse-phase high-performance liquid chromatography (RP-HPLC) runs and the molecular mass of the neurotoxins was determined by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS). Both venoms caused time-dependent inhibition of nerve-mediated twitches with a t90 value of 22.2±1.9min and 12.9±1.2min for N. nubiae and N. melanoleuca venoms, respectively. Prior incubation of some commercial antivenom (EchiTab-Plus-ICP [Costa Rica], CSL, Parkville, Victoria, Australia) and snake venom antisera [India]) did not prevent the neurotoxic effect of N. nubiae venom. The chromatographic separation of N. nubiae and N. melanoleuca venoms followed by MALDI-TOF MS analysis revealed that short-chain α-neurotoxin accounted for 8.4% of N. nubiae and 14.8% of N. melanoleuca whole venoms. N. nubiae venom, which was previously known as cytotoxic venom, exhibits considerable in vitro neurotoxic effects on chick nerve-muscle preparations that may have consequences for antivenom development in north-east Africa.

Metabolite profiling in ten bread wheat (Triticum aestivum L.) genotypes in response to drought stress

Wheat is frequently constrained by extreme environmental conditions such as drought. Improving drought tolerance in wheat genotypes is crucial for ensuring food security, especially considering the challenges posed by climate change. To reveal the involvement of metabolites in drought response, ten diverse wheat genotypes were investigated under control and water scarcity conditions. The field experiments were set-up, using a 5 × 2 alpha lattice design, with two replicates per treatment, in the 2022 and 2023 growing seasons. Metabolites associated with drought tolerance were analysed using ultra-high performance liquid chromatography, coupled with a quadruple time of flight mass spectrometry (UHPLC-qTOF-MS). Multivariate statistical analysis (MVDA) tools, viz. principal component analysis (PCA) and the orthogonal projection to latent structures-discriminant analysis (OPLS-DA) loading scatter plot were used to identify the metabolites that are positively and negatively correlated to drought stress. Significant variation (p < 0.05) among genotypes was observed, with 58 metabolites annotated, including phenolic acids, carbohydrates, and fatty acids. The annotated compounds were linked to thirteen most significant pathways, with one carbon metabolism, cutin, suberin and wax synthesis and starch and sucrose metabolism being significantly affected by water stress, based on the KEGG pathway analysis. The two high-yielding wheat genotypes (LM48 and BW140) under drought stress displayed significant upregulation of key metabolites such as sinapoyl hydroxyagmatine, 7-oxostigmasterol, 1-O-caffeoyl-3-O-p-coumaroylglycerol, and 3-beta-3-lupanol, when compared to the non-stressed conditions. This study demonstrates the prospects of applied metabolomics for chemotaxonomic classification, phenotyping and selection in plant breeding, as well as potential use in crop improvement.

A Perspective of Multi-Reflecting TOF MS.

Time-of-flight mass spectrometry (TOF MS) excels in rapid and high-sensitivity analysis, making it a cornerstone of analytical chemistry. But as sample complexity explodes in omics studies, so does the need for higher resolving power to ensure accurate results. Traditional TOF instruments face a challenge: achieving high resolution often requires a very large instrument. To overcome this limitation, scientists developed alternative designs for TOF analyzers called multi-pass TOF analyzers (MPT). These MPT analyzers come in two main configurations: multi-turn (MTT) and multi-reflecting (MRT). Drawing on the authors' extensive experience, this review describes two decades of MPT advancements. It highlights the critical development of optimized analyzer designs, tracing the evolution towards mirror-based MRT instruments, generally providing superior resolution and spatial acceptance compared to MTT. While the manuscript attempts to overview MTT advances, it primarily focuses on MRT technology. Additionally, the review explores the role of orthogonal accelerators and trap pulse converters, comparing their efficiency and the dynamic range limits imposed by space charge effects. By comparing various MRT configurations and commercially available instruments, the review sets out to inform and empower researchers so they can make informed decisions about MRT mass spectrometers.

Multi-Domain Data Integration for Plasma Diagnostics in Semiconductor Manufacturing Using Tri-CycleGAN

The precise monitoring of chemical reactions in plasma-based processes is crucial for advanced semiconductor manufacturing. This study integrates three diagnostic techniques—Optical Emission Spectroscopy (OES), Quadrupole Mass Spectrometry (QMS), and Time-of-Flight Mass Spectrometry (ToF-MS)—into a reactive ion etcher (RIE) system to analyze CF4-based plasma. To synchronize and integrate data from these different domains, we developed a Tri-CycleGAN model that utilizes three interconnected CycleGANs for bi-directional data transformation between OES, QMS, and ToF-MS. This configuration enables accurate mapping of data across domains, effectively compensating for the blind spots of individual diagnostic techniques. The model incorporates self-attention mechanisms to address temporal misalignments and a direct loss function to preserve fine-grained features, further enhancing data accuracy. Experimental results show that the Tri-CycleGAN model achieves high consistency in reconstructing plasma measurement data under various conditions. The model’s ability to fuse multi-domain diagnostic data offers a robust solution for plasma monitoring, potentially improving precision, yield, and process control in semiconductor manufacturing. This work lays a foundation for future applications of machine learning-based diagnostic integration in complex plasma environments.

TOF-MS based characterization of polyglycerol polyricinoleate (PGPR) samples

Time-of-flight mass spectrometry (TOF-MS) was used to unravel the composition of commercial polyglycerol polyricinoleate (PGPR) samples, by identifying the various molecular species present. To cover the broad range of molecular weights for the present species, a combination of three ionisation conditions was used. Species exceeding the molecular weight of pentaglycerol hexaricinoleate were difficult to detect. Over 100 molecular species were observed and identified in the analysed samples, including free polyglycerols, ricinoleates, and PGPR-esters. Commercial PGPR samples were shown to be mainly composed of esterification products of di-, tri-, and tetraglycerol, while the esterification degree mainly varied from 1 to 5. The TOF-MS analysis was proven to be reproducible with a relative standard deviation (RSD) below 2.86% for three independent measurements on different days. The method proved to be very suitable to evaluate batch-to-batch variations and to compare the composition of different types of commercial PGPR’s. Moreover, this method can be applied to monitor the quality of PGPR products during the synthesis process. Furthermore, it can also provide fundamental knowledge for optimizing PGPR composition to improve its functionality.

Enhanced detection of Pythium insidiosum via lipid profiling with matrix-assisted laser desorption ionization time of flight mass spectrometry

Pythiosis is a severe disease in humans and animals globally, caused by the pathogenic oomycete Pythium insidiosum. Early and accurate detection is crucial for effective treatment, but traditional diagnostic methods have limitations. This study presents an alternative approach using Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) for lipid profiling to efficiently identify P. insidiosum. The study involved extracting microbial lipid components using optimized chloroform: methanol biphasic method and creating a lipid profile database with samples from 30 P. insidiosum isolates and 50 various fungi. The methodology was validated on 25 blinded samples for assay detection performance. Unique lipid profiles allowed species-specific identification with high efficiency: scores ≥ 2.682 indicated P. insidiosum, scores ≤ 2.512 suggested fungi, and scores in between pointed to other oomycetes. The assay demonstrated sensitivity, specificity, and accuracy of 100%, 80%, and 88%, respectively, for detecting P. insidiosum. The limited detection specificity was due to false positive samples from closely related Pythium species, which are not a significant clinical concern. The findings show that MALDI-TOF MS lipid profiling can efficiently identify P. insidiosum, offering significant advantages in sample preparation, stability, and reproducibility over protein profile-based methods. This study marks the first instance of lipid profiles being reported for P. insidiosum, paving the way for clinical use in improving accurate detection and facilitating timely treatment interventions.

Spatial distribution and temporal evolution of wall-stabilized DME/O2 premixed cool flames

The low-temperature oxidation of dimethyl ether (DME) was investigated in premixed wall-stabilized cool flames at two equivalence ratios (ϕ) of 0.2 and 0.5. Using a time-of-flight mass spectrometry (TOF-MS) coupled with gas chromatography (GC), the spatial distributions of major intermediate species, including DME, CH2O (formaldehyde), CO, CO2, and CH3OCHO (methyl formate), were quantified under well-controlled boundary conditions. Moreover, the temporal evolutions of multiple intermediate species in the wall-stabilized cool flame ignition process were measured via TOF-MS, while the wall temperature was gradually ramped up from 550 K to 730 K. Several kinetic models were examined herein to assess the estimated low-temperature reactivity of DME by comparing the one-dimensional axisymmetric simulation results with the experimental data. Wall-stabilized cool flame structures at equivalence ratios ϕ of 0.2 and 0.5 were quantitatively examined with the major intermediate species. It is found that the kinetic models reasonably predict the onset of the reaction zone near the wall. Among these models, Kurimoto et al.’s model gives better predictions for the distributions of CH2O and CO, which are characteristic species of cool flames. In addition, time-resolved measurements of the unsteady cool flames identified the negative temperature coefficient (NTC) turnover points for different species across various temperature regions. It is also found that the Kurimoto et al. model still indicates a slightly higher reactivity of DME in the low-temperature range, resulting in earlier DME consumption and a shift of NTC window to lower temperatures at ϕ = 0.2.

Decline of soil volatile organic compounds from a Mediterranean deciduous forest under a future drier climate

Biogenic volatile organic compounds (BVOCs) are crucial for ecosystem functioning, atmospheric chemistry and climate. While modulation of BVOC emissions from living vegetation with biotic and abiotic factors is well documented, how these factors drive soil BVOC emissions remain less understood, particularly in Mediterranean forests. To fill this gap, this pioneer study investigates whether BVOC fluxes from natural soil covered by litter (referred to as forest soil) vary under natural and amplified long-term water stress (35% annual rain exclusion over the past 10 years) in a deciduous oak Mediterranean forest (Quercus pubescens Willd.) compared to natural climate conditions. This aim has only been tackled in a single evergreen Mediterranean forest so far. Using proton transfer reaction time of flight mass spectrometer (PTR-ToF-MS) we also provide, for the first time, a detailed diurnal cycle of soil BVOCs in relation to air temperature, air humidity, and biotic factors including soil respiration and litter content in lignin, cellulose and hemicellulose. The main results revealed that forest soil represents a source of most BVOCs (e.g., acetaldehyde, acetone, acrolein, hexanol, monoterpenes) with maximum values at mid-day (42 μgC.m−2. h−1) in response to higher temperatures while it acts as a clear sink of isoprene. Total soil BVOC emission rates, together with soil respiration, decreased by 43% after a decade of partial rain restriction. These results will contribute to enhance further modeling of soil BVOC emissions under various climate scenarios both at regional and global scales.

Use of stable isotope combined with intact cell lipidomic by routine MALDI mass spectrometry analysis for rapid drug susceptibility assay in mycobacteria.

Rapid, accurate, and easy-to-perform diagnostic assays are required to address the current need for the diagnosis of resistant pathogens. That is particularly the case for mycobacteria, such as the human pathogen Mycobacterium tuberculosis, which requires up to 2weeks for the determination of the drug susceptibility profile using the conventional broth microdilution method. To address this challenge, we investigated the incorporation of deuterium, the stable isotope of hydrogen, into lipids as a read out of the drug susceptibility profile. Deuterium is incorporated into newly synthesized proteins or lipids in place of hydrogen as bacterial cells grow, increasing the mass of the macromolecules, which can then be observed via matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). As proof-of-concept, we used the non-pathogenic Mycobacterium smegmatis mc2155 strain, which is susceptible to the aminoglycoside antibiotic kanamycin, and M.smegmatis mc2155 containing the empty vector pVV16, which is kanamycin-resistant. Bacteria were incubated in a culture medium containing 50% of deuterium oxide (D2O) and either 1 or 2 times the minimal inhibitory concentration (MIC50) of kanamycin. Lipids were then analyzed using the MBT lipid Xtract matrix combined with routine MALDI mass spectrometry in the positive ion mode to evaluate the changes in the lipid profile. Using this approach, we were able to distinguish susceptible from resistant bacteria in less than 5h, a process that would take 72 h using the conventional broth microdilution method. We therefore propose a solution for the rapid determination of drug susceptibility profiles using a phenotypic assay combining D2O stable isotope labelling and lipid analysis by routine MALDI mass spectrometry.

Changing composition of street drug nyaope and its implications in South Africa

Nyaope is a Novel Psychoacve Substance (NPS) that connues to bring major challenges to the health and social well-being of users and their communies in South Africa. The acve ingredients that make up this cocktail drug Nyaope were first idenfied in 2015 using Time-of- flight mass spectrometry (TOF-MS) in the samples collected from the surrounding areas of the capital city Pretoria, and they were found to be variable across the samples. This variability had posed challenges to the treatment and rehabilitaon programmes. The current study was conducted in 2020, and included significantly a larger number of Nyaope samples collected from two provinces: Gauteng and Kwa Zulu-Natal of South Africa. The analycal method applied was also an improved model of TOF-MS analyser with a larger library of various drugs and their metabolites for matching the ingredients. Strikingly, many non-addicve drugs that were found in the previous samples were not found in this study. The new trend of formulaon has become more addicve and compact with major opiates and a few selected opioids, and with paracetamol and caffeine in different combinaons. This study reports differences in the physical appearance and the chemical composion of street drug Nyaope across the 2 provinces of South Africa: Gauteng and KwaZulu Natal (KZN), and also compared with the previous findings of 2015 in the samples collected in Gauteng province. The drug appears to be widely consumed and has serious health consequences as per previous studies, and therefore, understanding the chemical substances used in the drug will be helpful in both treatment and rehabilitaon efforts.

Microbiome-derived metabolites in early to mid-pregnancy and risk of gestational diabetes: a metabolome-wide association study

BackgroundPre-diagnostic disturbances in the microbiome-derived metabolome have been associated with an increased risk of diabetes in non-pregnant populations. However, the roles of microbiome-derived metabolites, the end-products of microbial metabolism, in gestational diabetes (GDM) remain understudied. We examined the prospective association of microbiome-derived metabolites in early to mid-pregnancy with GDM risk in a diverse population.MethodsWe conducted a prospective discovery and validation study, including a case–control sample of 91 GDM and 180 non-GDM individuals within the multi-racial/ethnic The Pregnancy Environment and Lifestyle Study (PETALS) as the discovery set, a random sample from the PETALS (42 GDM, 372 non-GDM) as validation set 1, and a case–control sample (35 GDM, 70 non-GDM) from the Gestational Weight Gain and Optimal Wellness randomized controlled trial as validation set 2. We measured untargeted fasting serum metabolomics at gestational weeks (GW) 10–13 and 16–19 by gas chromatography/time-of-flight mass spectrometry (TOF–MS), liquid chromatography (LC)/quadrupole TOF–MS, and hydrophilic interaction LC/quadrupole TOF–MS. GDM was diagnosed using the 3-h, 100-g oral glucose tolerance test according to the Carpenter-Coustan criteria around GW 24–28.ResultsAmong 1362 annotated compounds, we identified 140 of gut microbiome metabolism origin. Multivariate enrichment analysis illustrated that carbocyclic acids and branched-chain amino acid clusters at GW 10–13 and the unsaturated fatty acids cluster at GW 16–19 were positively associated with GDM risk (FDR < 0.05). At GW 10–13, the prediction model that combined conventional risk factors and LASSO-selected microbiome-derived metabolites significantly outperformed the model with only conventional risk factors including fasting glucose (discovery AUC: 0.884 vs. 0.691; validation 1: 0.945 vs. 0.731; validation 2: 0.987 vs. 0.717; all P < 0.01). At GW 16–19, similar results were observed (discovery AUC: 0.802 vs. 0.691, P < 0.01; validation 1: 0.826 vs. 0.780; P = 0.10).ConclusionsDysbiosis in microbiome-derived metabolites is present early in pregnancy among individuals progressing to GDM.

Translating 2D-Chromatographic Fingerprinting to Quantitative Volatilomics: Unrevealing Compositional Changes in Maize Silage Volatilome for Robust Marker Discovery.

This study examines the complex volatilome of maize silage, both with and without commercial heterolactic strain inoculation, conserved for 100 days, using quantitative volatilomics. Chemical classes linked to microbial metabolism were analyzed across a concentration range from 10 μg g-1 to 1 ng g-1. A reference method using comprehensive two-dimensional gas chromatography (GC × GC) and time-of-flight mass spectrometry (TOF MS) with loop-type thermal modulation (TM) was translated to a differential-flow modulation (FM) platform with parallel MS and flame ionization detector (FID) detection. With translation, the original method's analyte elution order and resolution are preserved. The new method allowed for accurate quantification using multiple headspace solid-phase microextraction (MHS-SPME) and FID-predicted relative response factors (RRFs). Both methods showed comparable discriminatory power with FM GC × GC-MS/FID achieving satisfactory quantification accuracy without external calibration. Analysis of 98 volatiles provided insights into silage fermentation, supporting marker discovery and correlations with silage quality and stability.

Multi-proxy investigations of Bronze Age diet and environment in the hyper-arid eastern Tarim Basin (Lop Nur), northwest China

Humans have a long history of occupying ecologically marginal regions, and the ancient cultural mechanisms of adaptation to these challenging environments remain poorly understood. We examine archaeological deposits from a Bronze Age settlement in the hyper-arid eastern Tarim Basin (Lop Nur), identifying well-preserved plant remains and bone fragments that shed light on the palaeodiet and past environmental setting. We use the newly developed peptide mass fingerprinting method of ZooMS (zooarchaeology by mass spectrometry) and TimsTOF MS (trapped ion mobility time of flight mass spectrometry) to identify fragments of ancient fish bones as Cyprinidae and possible Salmonidae, indicating both their consumption and the former presence of intra-settlement fresh water-bodies. Remains of littoral and aquatic plants attest to a marshy palaeo-delta at the confluence of the Tarim and Kongque rivers, testifying to a former biodiverse oasis in the Lop Desert when humans occupied the site. We conclude that the use of both aquatic and desert peripheral resources, combined with the intentional management of local environments, were all essential prehistoric adaptations. In addition, we show that radiocarbon dates of aquatic remains have an offset spanning hundreds to thousands of years, due to a freshwater reservoir effect, requiring careful consideration of ages for archaeological bones in the broader region.

Antimicrobial Action of Lactobacillus spp. Isolated from Yoghurt against Escherichia coli, Salmonella Enteritidis and Listeria monocytogenes: A Pilot Study

Milk has been a dietary staple around the world for centuries. In recent years, consumer interest in healthy foods and organic products has increased due to their health-promoting properties. Fermented dairy products, including yoghurt, are receiving special attention for their properties and the presence of probiotic bacteria. The quantitative and qualitative (MALDI TOF MS) evaluation of lactic acid bacteria (LAB) in different types of yoghurt (with different shelf lives) was carried out. The effect of the Lactobacillus spp. strains isolated from yoghurts (with potential antimicrobial activity) against foodborne pathogenic bacteria (Escherichia coli, Salmonella Enteritidis and Listeria monocytogenes) was evaluated. The presence of Lactobacillus spp. (Lactobacillus rhamnosus and Lactobacillus paracasei) in the tested yoghurts was demonstrated. In the samples tested, not all the lactic acid bacteria (LAB) declared by the manufacturer were identified. The number of live bacteria present in the product was influenced by the type of yoghurt. The number of bacteria did not fall below the World Health Organization (WHO) recommended level by the last day of validity. It was shown that a mixed culture (L. rhamnosus and L. paracasei, isolated from tested yoghurts) had the most significant effect on changing the number of pathogenic microorganisms. The consumption of dairy products, which are a source of LAB, can reduce the risk of foodborne pathogen infections.

Integrated lipidomic and transcriptomics to explore the effects of ethyl acetate extract of Herpetospermum pedunculosum on nonalcoholic fatty liver disease in mice

Ethnopharmacological relevanceHerpetospermum pedunculosum (Ser.) C.B. Clarke (HP), a traditional Tibetan medicine used to treat hepatobiliary diseases, was confirmed that lignans-enriched ethyl acetate extract of HP (EAHP) could alleviate the hepatic injury by modern pharmacological evidence. However, the effects and potential mechanisms of EAHP against nonalcoholic fatty liver disease (NAFLD) are still unknown. Aim of the studyTo reveal the effects of EAHP on NAFLD and explore the potential mechanisms from the perspective of lipidomics and transcriptomics. Materials and methodsUPLC‒Q–TOF‒MS analysis was carried out to investigate the chemical components of EAHP. A Choline-deficient, L-amino acid defined, high fat diet (CDAHFD) was used to establish a NAFLD mouse model. The anti-NAFLD effects of various dosages of EAHP were evaluated by biochemical indexes and histological analysis. Hepatic lipidomic and transcriptomic analysis and multiple bioinformatics methods were used to screen biomarkers and signaling pathways. The levels of the corresponding genes were verified by qPCR. Results36 kinds of compounds were identified by UPLC‒Q–TOF‒MS analysis. Oral treatment with EAHP significantly decrease the liver index and the levels of ALT and AST in the serum. The measurements lipid content and Oil Red O staining results suggested that EAHP ameliorated lipid metabolism disorders by reducing the content of TG and LDL-C, increasing HDL-C in the liver. H&E staining and ELISA revealed that EAHP restored hepatic inflammatory infiltration and decrease the levels of IL-1β, IL-6, TNF-α, and increase IL-10 in the serum. Lipidomic analysis showed that EAHP could regulate CDAHFD-induced lipid metabolic disorder. The different lipid metabolites included TG, phosphatidyl choline (PC), diacylglycerol (DG), phosphatidylethanolamine (PE), phosphatidylinositol (PI), ceramide (Cer). Transcriptomic analysis revealed that Bmp8b, Nbl1, Rgma, Sphk1, Thbs1, and Ugt8a were important regulators, which were associated with TGF-β signaling pathway and sphingolipid metabolism. The expressions of above genes detected by were qPCR consistent with transcriptomic data. ConclusionsThe ameliorative effects of EAHP on NAFLD are potentially attributable to the regulation of sphingolipid metabolism and TGF-β signaling pathway, etc., which results in abnormal hepatic lipid metabolism and inflammatory response.

Ultrafast metaproteomics for quantitative assessment of strain isolates and microbiomes

BackgroundMicrobial communities are essential in human health and environmental regulation, but present a challenge for the analytical science due to their diversity and dynamic range. Tandem mass spectrometry provides functional insights on microbial life cycle, but is time-consuming. MALDI TOF excels in rapid species identification, but not functional assessment. To address critical challenges in human health and environmental sustainability, microbiology needs advanced mass spectrometry methods and bioinformatic tools enabling both rapid identification and accurate assessment of functional activity of microbial communities. ResultsWe show for the first time that both identity and functional activity of microorganisms and their communities can be accurately determined in experiments as short as 7 min per sample, using the basic Orbitrap MS configuration without peptide fragmentation. The approach was validated using strain isolates, mock microbiomes composed of bacteria spiked at known concentrations and human fecal microbiomes. Our new bioinformatic algorithm identifies the bacterial species with an accuracy of 95 %, when no prior information on the sample is available. Microbiome composition was resolved at the genus level with the mean difference between the actual and identified components of 12 %. For mock microbiomes, Pearson coefficient of up to 0.97 was achieved in estimates of strain biomass change. By the example of Rhodococcus biodegradation of n-alkanes, phenols and its derivatives, we showed the accurate assessment of functional activity of strain isolates, compared with the standard label-free and label-based approaches. SignificanceOur approach makes microbial proteomics fast, functional and insightful using the Orbitrap instruments even without employing peptide fragmentation technology. The approach can be applied to any microorganisms and can take a niche in routine functional assessment of microbial pathogens and consortiums in clinical diagnostics together with MALDI TOF MS and 16S rRNA gene sequencing.