A method for comparative metabolomics in urine using high resolution mass spectrometry

Microbiome and metabolome in home-made fermented soybean foods of India revealed by metagenome-assembled genomes and metabolomics

Grep-chhurpi, peha, peron namsing and peruñyaan are lesser-known home-made fermented soybean foods prepared by the native people of Arunachal Pradesh in India. Present work aims to study the microbiome, their functional annotations, metabolites and recovery of metagenome-assembled genomes (MAGs) in these four fermented soybean foods. Metagenomes revealed the dominance of bacteria (97.80 %) with minor traces of viruses, eukaryotes and archaea. Bacillota is the most abundant phylum with Bacillus subtilis as the abundant species. Metagenome also revealed the abundance of lactic acid bacteria such as Enterococcus casseliflavus, Enterococcus faecium, Mammaliicoccus sciuri and Staphylococcus saprophyticus in all samples. B. subtilis was the major species found in all products. Predictive metabolic pathways showed the abundance of genes associated with metabolisms. Metabolomics analysis revealed both targeted and untargeted metabolites, which suggested their role in flavour development and therapeutic properties. High-quality MAGs, identified as B. subtilis, Enterococcus faecalis, Pediococcus acidilactici and B. velezensis, showed the presence of several biomarkers corresponding to various bio-functional properties. Gene clusters of secondary metabolites (antimicrobial peptides) and CRISPR-Cas systems were detected in all MAGs. This present work also provides key elements related to the cultivability of identified species of MAGs for future use as starter cultures in fermented soybean food product development. Additionally, comparison of microbiome and metabolites of grep-chhurpi, peron namsing and peruñyaan with that of other fermented soybean foods of Asia revealed a distinct difference.

Metagenomics and metabolomics of Toddy, an Indian fermented date palm beverage

Toddy is a popular fermented palm beverage of India. No scientific information on shotgun metagenomics and metabolomics are available on toddy of India till date. Hence, we choose the fermented date palm beverage, locally called khejur toddy, of West Bengal and Jharkhand states of India, to profile microbial community, their targeted and untargeted metabolites to study the putative bio-functional genes corresponding to regulatory metabolic pathways. Shotgun-based metataxonomic analyses revealed the existence of all domains where bacteria were the most abundant domain (94.48%) followed by eukaryotes (3.38%), viruses (1.53%) and archaea (0.61%). Overall, 54 phyla, 363 families, 1087 genera and 1885 species were observed and identified. Bacillota (49.3%) was the most abundant bacterial phylum. At species level, several species of bacteria and yeasts were detected in toddy samples which included Leuconostoc mesenteroides,Leuconostoc citreum,Lactobacillus helveticus,Lactiplantibacillus plantarum,Lactococcus lactis, Acetobacter malorum, Gluconobacter japonicus, Gluconacetobacter liquefaciens, Fructobacillus durionis, Zymomonas mobilis and yeastsSaccharomyces cerevisiae, Hanseniaspora uvarumandHanseniaspora guilliermondii. Toddy metagenome was also compared with metagenome of pulque, the Mexican fermented fresh sap ofAgave, which was retrieved from NCBI database, and also with metagenomic data of some amplicon-based previous studies on toddy and African fermented palm drink for similarity, dissimilarity and uniqueness among them. Predictive biosynthesis of ethanol, acetic acid, butanoate, linalool, staurosporine, prodigiosin, folic acid, riboflavin, etc. were annotated by KEGG/COG database. Clustered regularly interspaced short palindromic repeats (CRISPR) analysis detected 23 arrays (average length 23.69 bp ± 4.28). Comprehensive Antibiotic Resistance Database (CARD) analysis did not show the presence of any momentous antibiotic resistance gene among the major microbial members. Metabolomics analysis detected many primary and secondary metabolites. We believe this is the first report on complete shotgun metagenomics, and metabolomics of fermented palm drink of India as well as Eastern India.

Screening of hepatocellular carcinoma via machine learning based on atmospheric pressure glow discharge mass spectrometry

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a high mortality rate. The diagnosis of HCC is currently based on alpha-fetoprotein detection, imaging examinations, and liver biopsy, which are expensive or invasive. Here, we developed a cost-effective, time-saving, and painless method for the screening of HCC via machine learning based on atmospheric pressure glow discharge mass spectrometry (APGD-MS). Ninety urine samples from HCC patients and healthy control (HC) participants were analyzed. The relative quantification data were utilized to train machine learning models. Neural network was chosen as the best classifier with a classification accuracy of 94%. Besides, the levels of eleven urinary carbonyl metabolites were found to be significantly different between HCC and HC, including glycolic acid, pyroglutamic acid, acetic acid, etc. The possible reasons for the regulation were tentatively proposed. This method realizes the screening of HCC via potential urine metabolic biomarkers based on APGD-MS, bringing a hopeful point-of-care diagnosis of HCC in a patient-friendly manner.

Dynamics of microbial populations and metabolites of fermenting saps throughout tapping process of ron and oil palm trees in Côte d'Ivoire

Palm wine fermentation is a complex microbial process that evolves with tapping times. The dynamics in microbiota and metabolites throughout palm wine tapping days is still not established, which are critical for the distinctive characteristics of palm wine taste and quality, and thus the mastery of the daily quality fluctuation during tapping. We analyzed the changes in microbial community structure by amplicon sequencing of bacterial 16S rRNA gene and fungal internal transcribed spacer (ITS) region, and metabolite profile changes using mass spectrometry in palm wine collected over 25-30 days tapping of ron (Borassus aethiopum) and oil palms (Elaeis guineensis) from Côte d'Ivoire. The stage-wise collected palm wine samples showed distinct changes in microbial diversity and pH, supporting microbial community dynamics during palm wine tapping. Results highlighted the dominance of Saccharomyces cerevisiae in early stages and the emergence of non-Saccharomyces yeasts, particularly Hanseniaspora spp. in the later stages of oil palm wine tapping, vice versa in the case of ron palm wine tapping, with a unique presence of Saccharomycodes in the later stages (15-30 days). Fructophilic lactic acid bacteria (FLAB), mainly Fructobacillus and Leuconostoc, encountered in both types of palm wine tapping showed a decline at later stages of oil palm wine tapping. In this type of palm wine, acetic acid bacteria with genera Acetobacter and Glucanoacetobacter, by surpassing Lactobacillus in the last stage become dominant, whereas Lactobacillus remained dominant in ron palm wine throughout tapping days. The decline in the relative abundance of gevotroline and essential amino acids during the later stages of palm wine tapping (15-25 days) supports the difference in the health benefits of the palm wine obtained from different days of tapping, indicating that early stages of tapping is more nutritional and healthy than the later stages. The microbial dynamics may be a potential indicator of metabolite changes during palm sap fermentation, thus contributing to establish particular features of palm wines in different stages of tapping. This understanding of microbial ecology and chemical composition changes during palm wine tapping can be used as biomarkers to assess palm wine's quality and help to design an optimum starter culture.

Comparative metabolite profiling of rice contrasts reveal combined drought and heat stress signatures in flag leaf and spikelets

Under semi-irrigated ecosystem, rice is often exposed to a combination of drought and heat stress, especially at the reproductive stage, leading to substantial yield loss. Combined stress studies are very limited in rice partly due to the difficulty in creating heat stress on a larger scale. Here, 24 cultivars with specific stress adaptive traits were phenotyped for spikelet sterility under combined stress using the natural summer temperatures and open drought phenotyping facility, simulating the field conditions. LC-MS/MS based metabolite profiling was performed in flag leaves and spikelets of three cultivars contrasting for spikelet sterility and source (leaf weight) treated to drought, heat and combined stress. Constitutively regulated metabolites, metabolic signatures common to all stresses, cultivars and tissues, metabolites common to both the tissues across the stresses and cultivars and metabolites common to each cultivar across the tissues and stresses were identified. Under combined stress, metabolites differentially accumulated between cultivars contrasting for spikelet sterility but similar for source and cultivars contrasting for both spikelet sterility and source have been identified. These metabolites would serve as markers towards improving combined stress tolerance of rice.

Metagenomic-Metabolomic Mining of Kinema, a Naturally Fermented Soybean Food of the Eastern Himalayas

Kinema is a popular sticky fermented soybean food of the Eastern Himalayan regions of North East India, east Nepal, and south Bhutan. We hypothesized that some dominant bacteria in kinema may contribute to the formation of targeted and non-targeted metabolites for health benefits; hence, we studied the microbiome-metabolite mining of kinema. A total of 1,394,094,912 bp with an average of 464,698,304 ± 120,720,392 bp was generated from kinema metagenome, which resulted in the identification of 47 phyla, 331 families, 709 genera, and 1,560 species. Bacteria (97.78%) were the most abundant domain with the remaining domains of viruses, eukaryote, and archaea. Firmicutes (93.36%) was the most abundant phylum with 280 species of Bacillus, among which Bacillus subtilis was the most dominant species in kinema followed by B. glycinifermentans, B. cereus, B. licheniformis, B. thermoamylovorans, B. coagulans, B. circulans, B. paralicheniformis, and Brevibacillus borstelensis. Predictive metabolic pathways revealed the abundance of genes associated with metabolism (60.66%), resulting in 216 sub-pathways. A total of 361 metabolites were identified by metabolomic analysis (liquid chromatography-mass spectrophotometry, LC-MS). The presence of metabolites, such as chrysin, swainsonine, and 3-hydroxy-L-kynurenine (anticancer activity) and benzimidazole (antimicrobial, anticancer, and anti-HIV activities), and compounds with immunomodulatory effects in kinema supports its therapeutic potential. The correlation between the abundant species of Bacillus and primary and secondary metabolites was constructed with a bivariate result. This study proves that Bacillus spp. contribute to the formation of many targeted and untargeted metabolites in kinema for health-promoting benefits.

In Vitro Anticancer Activity of Imperata cylindrica Root's Extract toward Human Cervical Cancer and Identification of Potential Bioactive Compounds

Imperata cylindrica is traditionally used to cure several diseases including cancer, wounds, and hypertension. The present study was designed to investigate the anticancer activity of the methanolic root extract of I. cylindrica (IC-MeOH). The water-soluble tetrazolium-1 and colony formation assays were used to check the proliferation ability of the cells. Cell apoptosis and cell cycle were measured by flow cytometry-based fluorescence-activated cell sorting. The ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) analysis was used for the metabolites profiling of IC-MeOH. Based on high-mass accuracy, spectral data, and previous reports, tentative compound identifications were assigned. Our findings revealed that IC-MeOH inhibited the proliferation of HeLa and CaSki cells. The plant extract was also found to induce a concentration- and time-dependent apoptosis and cell cycle arrest in the G0/G1 phase (IC50 value) in CaSki cell line. Analysis of IC-MeOH permitted the identification of 10 compounds already reported for their anticancer activity, epicatechin, curcumin, (-)-yatein, caffeic acid, myricetin, jatrorrhizine, harmaline, cinnamaldehyde, dobutamine, and syringin. In conclusion, IC-MeOH is a rich source of cytotoxic metabolites that inhibits human cervical cancer proliferation via apoptosis and cell cycle arrest.

Tracking the time-dependent and tissue-specific processes of arsenic accumulation and stress responses in rice (Oryza sativa L.)

The present study analysed time (0.5 h to 24 h) and tissue [roots, old leaves (OL) and young leaves (YL)] dependent nature of arsenic (As) accumulation and ensuing responses in two contrasting varieties of rice (Oryza sativa L.); Pooja (tolerant) and CO-50 (moderately sensitive). Arsenic accumulation was 5.4-, 4.7- and 7.3-fold higher at 24 h in roots, OL and YL, respectively of var. CO-50 than that in var. Pooja. Arsenic accumulation in YL depicted a delayed accumulation; at 2 h onwards in var. Pooja (0.23 µg g^-1 dw) while at 1 h onwards in var. CO50 (0.26 µg g^-1 dw). The responses of oxidative stress parameters, antioxidant enzymes, metabolites and ions were also found to be tissue- and time-dependent and depicted differential pattern in the two varieties. Among hormone, salicylic acid and abscisic acid showed variable response in var. Pooja and var. CO-50. Metabolite analysis depicted an involvement of various metabolites in As stress responses of two varieties. In conclusion, an early sensing of the As stress, proper coordination of hormones, biochemical responses, ionic and metabolic profiles allowed var. Pooja to resist As stress and reduce As accumulation more effectively as compared to that of var. CO-50.

Metabolomics Profiles of Smokers from Two Ethnic Groups with Differing Lung Cancer Risk

African American (AA) smokers are at a higher risk of developing lung cancer compared to whites. The variations in the metabolism of nicotine and tobacco-derived carcinogens in these groups were reported previously with the levels of nicotine metabolites and carcinogen-derived metabolites measured using targeted approaches. While useful, these targeted strategies are not able to detect global metabolic changes for use in predicting the detrimental effects of tobacco use and ultimately lung cancer susceptibility among smokers. To address this limitation, we have performed global untargeted metabolomics profiling in urine of AA and white smokers to characterize the pattern of metabolites, identify differentially regulated pathways, and correlate these profiles with the observed variations in lung cancer risk between these two populations. Urine samples from AA (n = 30) and white (n = 30) smokers were used for metabolomics analysis acquired in both positive and negative electrospray ionization modes. LC-MS data were uploaded onto the cloud-based XCMS online (http://xcmsonline.scripps.edu) platform for retention time correction, alignment, feature detection, annotation, statistical analysis, data visualization, and automated systems biology pathway analysis. The latter identified global differences in the metabolic pathways in the two groups including the metabolism of carbohydrates, amino acids, nucleotides, fatty acids, and nicotine. Significant differences in the nicotine degradation pathway (cotinine glucuronidation) in the two groups were observed and confirmed using a targeted LC-MS/MS approach. These results are consistent with previous studies demonstrating AA smokers with lower glucuronidation capacity compared to whites. Furthermore, the d-glucuronate degradation pathway was found to be significantly different between the two populations, with lower amounts of the putative metabolites detected in AA compared to whites. We hypothesize that the differential regulation of the d-glucuronate degradation pathway is a consequence of the variations in the glucuronidation capacity observed in the two groups. Other pathways including the metabolism of amino acids, nucleic acids, and fatty acids were also identified, however, the biological relevance and implications of these differences across ethnic groups need further investigation. Overall, the applied metabolomics approach revealed global differences in the metabolic networks and endogenous metabolites in AA and whites, which could be used and validated as a new potential panel of biomarkers that could be used to predict lung cancer susceptibility among smokers in population-based studies.

Update on urine as a biomarker in cancer: a necessary review of an old story

Introduction: Cancer causes thousands of deaths worldwide each year. Therefore, monitoring of health status and the early diagnosis of cancer using noninvasive assays, such as the analysis of molecular biomarkers in urine, is essential. However, effective biomarkers for early diagnosis of cancer have not been established in many types of cancer.Areas covered: In this review, we discuss recent findings with regard to the use of urine composition as a biomarker in eleven types of cancer. We also highlight the use of urine biomarkers for improving early diagnosis.Expert opinion: Urinary biomarkers have been applied for clinical application of early diagnosis. The main limitation is a lack of integrated approaches for identification of new biomarkers in most cancer. The utilization of urinary biomarker detection will be promoted by improved detection methods and new data from different types of cancers. With the development of precision medicine, urinary biomarkers will play an increasingly important clinical role. Future early diagnosis would benefit from changes in the utilization of urinary biomarkers.

Microbial Diversity and Metabolite Profiles of Palm Wine Produced From Three Different Palm Tree Species in Côte d'Ivoire

Palm wine, the most commonly consumed traditional alcoholic beverage in Western Africa, harbours a complex microbiota and metabolites, which plays a crucial role in the overall quality and value of the product. In the present study, a combined metagenomic and metabolomic approach was applied to describe the microbial community structure and metabolites profile of fermented saps from three palm species (Elaeis guineensis, Raphia hookeri, Borassus aethiopum) in Côte d'Ivoire. Lactobacillaceae (47%), Leuconostocaceae (16%) and Acetobacteriaceae (28%) were the most abundant bacteria and Saccharomyces cerevisiae (87%) the predominant yeasts in these beverages. The microbial community structure of Raphia wine was distinctly different from the others. Multivariate analysis based on the metabolites profile clearly separated the three palm wine types. The main differentiating metabolites were putatively identified as gevotroline hydrochloride, sesartemin and methylisocitrate in Elaeis wine; derivative of homoserine, mitoxantrone in Raphia wine; pyrimidine nucleotide sugars (UDP-D-galacturonate) and myo-Inositol derivatives in Borassus wine. The enriched presence of gevotroline (an antipsychotic agent) and mitoxantrone (an anticancer drug) in palm wine supports its therapeutic potential. This work provides a valuable insight into the microbiology and biochemistry of palm wines and a rationale for selecting functional microorganisms for potential biotechnology applications.