PoMeLo: a systematic computational approach to predicting metabolic loss in pathogen genomes.

BACKGROUND: Genome streamlining, the process by which genomes become smaller and encode fewer genes over time, is a common phenomenon among pathogenic bacteria. This reduction is driven by selection for minimized energy expenditure in a nutrient-rich environment. As pathogens evolve to become more reliant on the host, metabolic genes and resulting capabilities are lost in favor of siphoning metabolites from the host. Characterizing genome streamlining, gene loss, and metabolic pathway degradation can be useful in assessing pathogen dependency on host metabolism and identifying potential targets for host-directed therapeutics. RESULTS: PoMeLo (Predictor of Metabolic Loss) is a novel evolutionary genomics-guided computational approach for identifying metabolic gaps in the genomes of pathogenic bacteria. PoMeLo leverages a centralized public database of high-quality genomes and annotations and allows the user to compare an unlimited number of genomes across individual genes and pathways. PoMeLo runs locally using user-friendly prompts in a matter of minutes and generates tabular and visual outputs for users to compare predicted metabolic capacity between groups of bacteria and individual species. Each pathway is assigned a Predicted Metabolic Loss (PML) score to assess the magnitude of genome streamlining. Optionally, PoMeLo places the results in an evolutionary context by including phylogenetic relationships in visual outputs. It can also initially compute phylogenetically-weighted mean genome sizes to identify genome streamlining events. Here, we describe PoMeLo and demonstrate its use in identifying metabolic gaps in genomes of pathogenic Treponema species. CONCLUSIONS: PoMeLo represents an advance over existing methods for identifying metabolic gaps in genomic data, allowing comparison across large numbers of genomes and placing the resulting data in a phylogenetic context. PoMeLo is freely available for academic and non-academic use at https://github.com/czbiohub-sf/pomelo .

Unraveling the Mechanisms of Efficient Phosphorus Utilization in Popcorn (Zea mays L. var. everta): Insights from Proteomic and Metabolite Analysis.

The expansion of agriculture and the need for sustainable practices drives breeders to develop plant varieties better adapted to abiotic stress such as nutrient deficiency, which negatively impacts yields. Phosphorus (P) is crucial for photosynthesis and plant growth, but its availability in the soil is often limited, hampering crop development. In this study, we examined the response of two popcorn inbred lines, L80 and P7, which have been characterized previously as P-use inefficient and P-use efficient, respectively, under low (stress) and high P (control) availability. Physiological measurements, proteomic analysis, and metabolite assays were performed to unravel the physiological and molecular responses associated with the efficient use of P in popcorn. We observed significant differences in protein abundances in response to the P supply between the two inbred lines. A total of 421 differentially expressed proteins (DEPs) were observed in L80 and 436 DEPs in P7. These proteins were involved in photosynthesis, protein biosynthesis, biosynthesis of secondary metabolites, and energy metabolism. In addition, flavonoids accumulated in higher abundance in P7. Our results help us understand the major components of P utilization in popcorn, providing new insights for popcorn molecular breeding programs.

Exploring the Interactions between Obesity and Diabetes: Implications for Understanding Metabolic Dysregulation in a Saudi Arabian Adult Population.

The rising prevalence of obesity in Saudi Arabia is a major contributor to the nation's high levels of cardiometabolic diseases such as type 2 diabetes. To assess the impact of obesity on the diabetic metabolic phenotype presented in young Saudi Arabian adults, participants (n = 289, aged 18-40 years) were recruited and stratified into four groups: healthy weight (BMI 18.5-24.99 kg/m2) with (n = 57) and without diabetes (n = 58) or overweight/obese (BMI > 24.99 kg/m2) with (n = 102) and without diabetes (n = 72). Distinct plasma metabolic phenotypes associated with high BMI and diabetes were identified using nuclear magnetic resonance spectroscopy and ultraperformance liquid chromatography mass spectrometry. Increased plasma glucose and dysregulated lipoproteins were characteristics of obesity in individuals with and without diabetes, but the obesity-associated lipoprotein phenotype was partially masked in individuals with diabetes. Although there was little difference between diabetics and nondiabetics in the global plasma LDL cholesterol and phospholipid concentration, the distribution of lipoprotein particles was altered in diabetics with a shift toward denser and more atherogenic LDL5 and LDL6 particles, which was amplified in the presence of obesity. Further investigation is warranted in larger Middle Eastern populations to explore the dysregulation of metabolism driven by interactions between obesity and diabetes in young adults.

Quality assessment of flax advanced breeding lines varying in seed coat color and their potential use in the food and industrial applications.

BACKGROUND: With the increasing consumer awareness of the strong relationship between food and health, flax became a promising functional food due to its bioactive nutraceutical composition. Intra-specific crosses of eight contrasting flax genotypes were performed previously, and within segregating F6 progeny families, we investigated a close-up composition of phytochemicals derived from whole seeds. RESULTS: The considerable genetic variation among the flax F6 families suggested that intra-specific hybridization is essential in flax breeding to obtain and broaden genetic variability and largely affirmed the opportunity for selecting promising lines. Also, significant variations in the targeted metabolite contents and antioxidant properties were observed among brown and yellow-seeded families. Notably, brown-seeded families expressed the highest average values of saturated fatty acids, protein, fiber, tocopherol, phenolics, SDG, and SECO lignans. Yellow-seeded families represented the highest average content of unsaturated fatty acids and mucilage. The cultivation year significantly affects flaxseed's composition and functional properties, presumably due to temperature, humidity, and sunshine time differences. Interestingly, the seeds obtained in warmer conditions were more potent and had more chemical constituents. The favorable genetic correlations among all evaluated traits suggest the possibility of joint genetic selection for several nutritional and phytochemical characteristics in flax. The current study highlights the importance and utilization of 19 top families as their seeds and oil play imperative roles in the pharmaceuticals and food industries. The antioxidant capacity of the seeds showed that families 84B, 23B, 35Y, 95Y, 30B, 88B, and 78B serve as a natural source of dietary antioxidants beneficial to human health. To increase the oxidative stability of the flaxseed oil, the quality evaluation identified some families with low levels of linolenic acid. CONCLUSIONS: These findings are essential to improving flaxseed's nutritional quality and therapeutic properties through a bulk breeding program.

Altitudinal variation of dragon fruit metabolite profiles as revealed by UPLC-MS/MS-based widely targeted metabolomics analysis.

BACKGROUND: Geographical factors affect the nutritional, therapeutic and commercial values of fruits. Dragon fruit (Hylocereus spp) is a popular fruit in Asia and a potential functional food with diverse pharmacological attributes. Although it is produced in various localities, the information related to the altitudinal variation of dragon fruit nutrients and active compounds is scarce. Hence, this study aimed to investigate the variations in metabolite profiles of H. polyrhizus (variety Jindu1) fruit pulps from three different altitudes of China, including Wangmo (WM, 650 m), Luodian (LD, 420 m), and Zhenning (ZN, 356 m). Jindu1 is the main cultivated pitaya variety in Guizhou province, China. RESULTS: The LC-MS (liquid chromatography-mass spectroscopy)-based widely targeted metabolic profiling identified 645 metabolites, of which flavonoids (22.64%), lipids (13.80%), phenolic acids (12.40%), amino acids and derivatives (10.39%), alkaloids (8.84%), and organic acids (8.37%) were dominant. Multivariate analyses unveiled that the metabolite profiles of the fruit differed regarding the altitude. Fruits from WM (highest altitude) were prime in quality, with higher levels of flavonoids, alkaloids, nucleotides and derivatives, amino acids and derivatives, and vitamins. Fruits from LD and ZN had the highest relative content of phenolic acids and terpenoids, respectively. We identified 69 significantly differentially accumulated metabolites across the pulps of the fruits from the three locations. KEGG analysis revealed that flavone and flavonol biosynthesis and isoflavonoid biosynthesis were the most differentially regulated. It was noteworthy that most active flavonoid compounds exhibited an increasing accumulation pattern along with the increase in altitude. Vitexin and isovitexin were the major differentially accumulated flavonoids. Furthermore, we identified two potential metabolic biomarkers (vitexin and kaempferol 3-O-[2-O-ß-D-galactose-6-O-a-L-rhamnose]-ß-D-glucoside) to discriminate between dragon fruits from different geographical origins. CONCLUSION: Our findings provide insights into metabolic changes in dragon fruits grown at different altitudes. Furthermore, they show that growing pitaya at high altitudes can produce fruit with higher levels of bioactive compounds, particularly flavonoids.

Development of capillary electrophoresis methods for the detection of microbial metabolites on potential future spaceflight missions.

The search for chemical indicators of life is a fundamental component of potential future spaceflight missions to ocean worlds. Capillary electrophoresis (CE) is a useful separation method for the determination of the small organic molecules, such as amino acids and nucleobases, that could be used to help determine whether or not life is present in a sample collected during such missions. CE is under development for spaceflight applications using multiple detection systems, such as laser induced fluorescence (LIF) and mass spectrometry (MS). Here we report CE-based methods for separation and detection of major polar metabolites in cells, such as amino acids, nucleobases/sides, and oxidized and reduced glutathione using detectors that are less expensive alternatives to LIF and MS. Direct UV detection, indirect UV detection, and capacitvely coupled contactless conductivity detection (C4D) were tested with CE, and a combination of direct UV and C4D allowed the detection of the widest variety of metabolites. The optimized method was used to profile metabolites found in samples of Escherichia coli and Pseudoalteromonas haloplanktis and showed distinct differences between the species.

Capillary electrophoresis-mass spectrometry for creatinine analysis in residual clinical plasma samples and comparison with gold standard assay.

When hospitalized, infants, particularly preterm, are often subjected to multiple painful needle procedures to collect sufficient blood for metabolic screening or diagnostic purposes using standard clinical tests. For example, at least 100 µL of whole blood is required to perform one creatinine plasma measurement with enzymatic colorimetric assays. As capillary electrophoresis-mass spectrometry (CE-MS) utilizing a sheathless porous tip interface only requires limited amounts of sample for in-depth metabolic profiling studies, the aim of this work was to assess the utility of this method for the determination of creatinine in low amounts of plasma using residual blood samples from adults and infants. By using a starting amount of 5 µL of plasma and an injection volume of only 6.7 nL, a detection limit (S/N = 3) of 30 nM could be obtained for creatinine, and intra- and interday precisions (for peak area ratios) were below 3.2%. To shorten the electrophoretic separation time, a multi-segment injection (MSI) strategy was employed to analyze up to seven samples in one electrophoretic run. The findings obtained by CE-MS for creatinine in pretreated plasma were compared with the values acquired by an enzymatic colorimetric assay typically used in clinical laboratories for this purpose. The comparison revealed that CE-MS could be used in a reliable way for the determination of creatinine in residual plasma samples from infants and adults. Nevertheless, to underscore the clinical efficacy of this method, a subsequent investigation employing an expanded pool of plasma samples is imperative. This will not only enhance the method's diagnostic utility but also contribute to minimizing both the amount and frequency of blood collection required for diagnostic purposes.

Discovery of metabolite biomarkers for odontogenic keratocysts.

INTRODUCTION: Odontogenic keratocysts (OKCs) are locally aggressive and have a high rate of recurrence, but the pathogenesis of OKCs is not fully understood. We aimed to investigate the serum metabolomic profile of OKCs and discover potential biomarkers. METHODS: Metabolomic analysis was performed on 42 serum samples from 22 OKC patients and 20 healthy controls (HCs) using gas chromatography‒mass spectrometry to identify dysregulated metabolites in the OKC samples. LASSO regression and receiver operating characteristic (ROC) curve analyses were used to select and validate metabolic biomarkers and develop diagnostic models. RESULTS: A total of 73 metabolites were identified in the serum samples, and 24 metabolites were dysregulated in the OKC samples, of which 4 were upregulated. Finally, a diagnostic panel of 10 metabolites was constructed that accurately diagnosed OKCs (sensitivity of 100%, specificity of 100%, area under the curve of 1.00). CONCLUSION: This study is the first to investigate the metabolic characteristics and potential metabolic biomarkers in the serum of OKC patients using GC‒MS. Our study provides further evidence to explore the pathogenesis of OKC.

Analyzing the impact of T7L variants overexpression on the metabolic profile of Escherichia coli.

INTRODUCTION: Exploring metabolic changes within host E. coli through an untargeted metabolomic study of T7L variants overexpression to optimize engineered endolysins for clinical/therapeutic use. AIM AND OBJECTIVE: This study aims to assess the impact of overexpressing T7L variants on the metabolic profiles of E. coli. The two variants considered include T7L-H37A, which has enhanced lytic activity compared to its wild-type protein, and T7L-H48K, a dead mutant with no significant activity. METHODS: 1H NMR-based metabolomics was employed to compare the metabolic profiles of E. coli cells overexpressing T7L wild-type protein and its variants. RESULTS: Overexpression of the T7L wild-type (T7L-WT) protein and its variants (T7L-H48K and T7L-H37A) was compared to RNAP overexpression in E. coli cells using 1H NMR-based metabolomics, analyzing a total of 75 annotated metabolites, including organic acids, amino acids, sugars, and nucleic acids. The results showed distinct clustering patterns for the two T7L variant groups compared with the WT, in which the dead mutant (H48K) group showed clustering close to that of RNAP. Pathway impact analysis revealed different effects of T7L variants on E. coli metabolic profiles, with T7L-H48K showing minimal alterations in energy and amino acid pathways linked to osmotic stress compared to noticeable alterations in these pathways for both T7L-H37A and T7L-WT. CONCLUSIONS: This study uncovered distinct metabolic fingerprints when comparing the overexpression of active and inactive mutants of T7L lytic enzymes in E. coli cells. These findings could contribute to the optimization and enhancement of suitable endolysins as potential alternatives to antibiotics.

Patient metabolic profile defined by liver and muscle 18F-FDG PET avidity is independently associated with overall survival in gastric cancer.

BACKGROUND: PET-CT-based patient metabolic profiling is a novel concept to incorporate patient-specific metabolism into gastric cancer care. METHODS: Staging PET-CTs, demographics, and clinicopathologic variables of gastric cancer patients were obtained from a prospectively maintained institutional database. PET-CT avidity was measured in tumor, liver, spleen, four paired muscles, and two paired fat areas in each patient. The liver to rectus femoris (LRF) ratio was defined as the ratio of SUVmean of liver to the average SUVmean of the bilateral rectus femoris muscles. Kaplan-Meier and Cox-proportional hazards models were used to identify the impact of LRF ratio on OS. RESULTS: Two hundred and one patients with distal gastroesophageal (48%) or gastric (52%) adenocarcinoma were included. Median age was 65 years, and 146 (73%) were male. On univariate analysis, rectus femoris PET-CT avidity and LRF ratio were significantly associated with overall survival (p < 0.05). LRF ratio was significantly higher in males, early-stage cancer, patients with an ECOG 0 or 1 performance status, patients with albumin > 3.5 mg/dL, and those with moderately differentiated tumor histology. In multivariable regression, gastric cancer stage, albumin, and LRF ratio were significant independent predictors of overall survival (LRF ratio HR = 0.73 (0.56-0.96); p = 0.024). Survival curves showed that the prognostic impact of LRF was associated with metastatic gastric cancer (p = 0.009). CONCLUSIONS: Elevated LRF ratio, a patient-specific PET-CT-based metabolic parameter, was independently associated with an improvement in OS in patients with metastatic gastric cancer. With prospective validation, LRF ratio may be a useful, host-specific metabolic parameter for prognostication in gastric cancer.

Metabolomics revealed disruptions in amino acid and antioxidant biochemistry in Daphnia magna exposed to industrial effluents associated with plastic and polymer production.

Industrial wastewater effluents are a major source of chemicals in aquatic environments, and many of these chemicals may negatively impact aquatic life. In this study, the crustacean Daphnia magna, a common model organism in ecotoxicity studies, was exposed for 48 h to nine different industrial effluent samples from manufacturing facilities associated with the production of plastics, polymers, and coating products at a range of dilutions: 10, 25, 50, 100% (undiluted). A targeted metabolomic-based approach using liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to quantify polar metabolites from individual daphnids that survived the 48 h exposure. Multivariate analyses and metabolite changes revealed metabolic perturbations across all effluent samples studied, with non-monotonic responses and both up and downregulation relative to the unexposed control. Pathway analyses indicated the disruption of similar and distinct pathways, mostly connected to protein synthesis, amino acid metabolism, and antioxidant processes. Overall, we observed disruptions in Daphnia biochemistry that were similar across the effluent samples, but with unique features for each effluent sample. Additionally, non-monotonic heightened responses suggested additive and/or synergistic interactions between the chemicals within the industrial effluents. These findings demonstrate that targeted metabolomic approaches are a powerful tool for the biomonitoring of aquatic ecosystems in the context of complex mixtures, such as industrial wastewater effluents.

Longitudinal characterization of the metabolome of dairy cows transitioning from one lactation to the next: Investigations in the liver.

This study aimed to investigate the metabolic changes in the livers of dairy cows from 1 wk before dry off to 1 wk after calving. Twelve high-yielding Holstein cows were included in a longitudinal study and housed in a tiestall barn. The cows were dried off at 6 wk before the expected calving date (dry period length = 42 d). During the entire lactation, the cows were milked twice daily at 0600 and 1700 h. Liver biopsies were taken from each cow at 4 different times: wk -7 (before drying off), -5 (after drying off), -1 and +1 relative to calving. A targeted metabolomics approach was performed by liquid chromatography and flow injection with electrospray ionization triple quadrupole mass spectrometry using the MxP Quant 500 kit (Biocrates Life Sciences AG). A total of 185 metabolites in the liver were used for the final data analysis. Principal component analysis revealed a clear separation by days of sampling, indicating a notable shift in metabolic phenotype from late lactation to the dry period and further changes after calving. Changes were observed in several classes of compounds, including AA and biogenic amines. In particular, the changes in acylcarnitines (AcylCN), phosphatidylcholines (PC), sphingomyelins (SM), and bile acids (BA) indicated extensive remodeling of the hepatic lipidome. The changes in AcylCN concentrations in early lactation suggest incomplete fatty acid oxidation in the liver, possibly indicating mitochondrial dysfunction or enzymatic imbalance. In addition, the changes in PC and SM species in early lactation indicate altered cell membrane composition, which may affect cell signaling and functionality. In addition, changes in BA concentrations and profiles indicate dynamic adaptations in BA synthesis, as well as lipid digestion and absorption during the observation period. In particular, principal component analysis showed an overlapping distribution of liver metabolites in primiparous and multiparous cows, indicating no significant difference between these groups. In addition, Volcano plots showed similar liver metabolism between primiparous and multiparous cows, with no significant fold changes (>1.5) in any metabolite at significant P-values (false discovery rate <0.05). These results provide valuable insight into the physiological ranges of liver metabolites during dry period and calving in healthy dairy cows and should contribute to the design and interpretation of future metabolite-based studies of the transition dairy cow.

A comparative untargeted metabolomic analysis and assessment of antiplasmodial potential of nine Albizia species.

The genus Albizia is one of the richest genera in phenolics besides other classes of secondary metabolites including saponins, terpenes, and alkaloids with promising medicinal applications. In the current study, UHPLC-PDA-ESI-MS/MS-based metabolic profiling of leaves of Albizia lebbeck, Albizia julibrissin, Albizia odoratissima, Albizia procera, Albizia anthelmintica, Albizia guachapele, Albizia myriophylla, Albizia richardiana, and Albizia lucidior resulted in the tentative identification of 64 metabolites, mainly flavonoids, phenolic acids, saponins, and alkaloids. Some metabolites were identified in Albizia for the first time and could be used as species-specific chemotaxonomic markers, including: apigenin 7-O-dihydroferuloyl hexoside isomers, apigenin 7-O-pentosyl hexoside, quercetin 3-O-rutinoside 7-O-deoxyhexoside, quercetin 3,7-di-O-hexoside deoxyhexoside, quercetin 7-O-feruloyl hexoside, methyl myricetin 7-O-deoxyhexoside, kaempferol di-3-O-di-deoxyhexoside-7-O-hexoside, and kaempferol 3-O-neohesperidoside 7-O-hexoside. Comparative untargeted metabolomic analysis was undertaken to discriminate between species and provide a chemotaxonomic clue that can be used together with morphological and genetic analyses for more accurate classification within this genus. Moreover, the in vitro antiplasmodial activity was assessed and correlated to the metabolic profile of selected species. This was followed by a molecular docking study and absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction of the identified budmunchiamine alkaloids, revealing promising interactions with the active site of lactate dehydrogenase of Plasmodium falciparum and good pharmacokinetics and pharmacodynamics, which could help in designing novel antimalarial drugs.

Widely Targeted Metabolomics Analysis Reveals Metabolites Important for Antioxidant Properties and Quality Traits in Different Fruit Parts of Aurantii Fructus Immatures.

In traditional Chinese medicine, Aurantii Fructus Immatures (AFIs) have been utilized for more than 2000 years. The proportions of different fruit parts are crucial for evaluating AFI quality in China. However, the basis for this statement's substance is unclear. Differences in quality are intimately correlated with a plant's metabolite composition. On the basis of a widely targeted metabolome, this study intended to investigate the metabolite composition and evaluate the antioxidant capacity of the peel and pulp of an AFI. Metabolites were identified and quantified by UHPLC-QqQ-MS. To assess their antioxidant ability, DPPH and ABTS assays were carried out. There were 1327 chemical compounds identified by UHPLC-QqQ-MS. After screening the differential metabolites using a multivariate statistical analysis, it was found that there were 695 significant differences in the metabolites between the peel and the pulp. Among them, it was discovered that the content of active ingredients in the peel group was higher than that in the pulp group. Furthermore, the aqueous extracts from the peel showed stronger antioxidant capacities than those from the pulp. The metabolites and antioxidant capacities were significantly different between the peel and the pulp. This study of different fruit parts might provide a guide for AFI quality assessments.

Isolation and characterization of a native strain of the entomopathogenic fungus Beauveria bassiana for the control of the palm weevil Dynamis borassi (Coleoptera: Curculionidae) in the neotropics.

This study aimed to isolate and characterize a native strain of Beauveria bassiana, coded as Bv065, showcasing its potential as a biological control agent targeting the palm weevil Dynamis borassi. Originating from a naturally infected D. borassi specimen collected in southwestern Colombia, the fungus underwent molecular identification and was identified as B. bassiana, exhibiting high sequence similarity with known reference strains. The physiological characterization revealed that Bv065 thrived within a temperature range of 25 to 30 °C and a pH range of 6 to 9. Moreover, the key carbon sources that allow optimal growth of the strain were identified through metabolic profiling, including sucrose, D-mannose, and γ-amino-butyric acid. These findings offer strategic insights for scalability and formulation methodologies. Additionally, enzymatic analyses unveiled robust protease activity within Bv065, crucial for catalysing insect cuticle degradation and facilitating host penetration, thus accentuating its entomopathogenic potential. Subsequent evaluations exposed Bv065's pathogenicity against D. borassi, causing significant mortality within nine days of exposure, albeit exhibiting limited effectiveness against Rhynchophorus palmarum. This study underscores the importance of understanding optimal growth conditions and metabolic preferences of B. bassiana strains for developing effective biopesticides. The findings suggest Bv065 as a promising candidate for integrated pest management strategies in neotropical regions, particularly for controlling palm weevil infestations in coconut and peach palm cultivation. Future research avenues include refining mass production methodologies, formulating novel delivery systems, and conducting comprehensive field efficacy trials to unlock the full potential of Bv065 in fostering sustainable pest management practices. Overall, this study contributes to the growing body of knowledge on entomopathogenic fungi and their pivotal role in biological control, offering nuanced perspectives on eco-friendly alternatives to conventional insecticidal interventions.

Statistical considerations and database limitations in NMR-based metabolic profiling studies.

INTRODUCTION: Interpretation and analysis of NMR-based metabolic profiling studies is limited by substantially incomplete commercial and academic databases. Statistical significance tests, including p-values, VIP scores, AUC values and FC values, can be largely inconsistent. Data normalization prior to statistical analysis can cause erroneous outcomes. OBJECTIVES: The objectives were (1) to quantitatively assess consistency among p-values, VIP scores, AUC values and FC values in representative NMR-based metabolic profiling datasets, (2) to assess how data normalization can impact statistical significance outcomes, (3) to determine resonance peak assignment completion potential using commonly used databases and (4) to analyze intersection and uniqueness of metabolite space in these databases. METHODS: P-values, VIP scores, AUC values and FC values, and their dependence on data normalization, were determined in orthotopic mouse model of pancreatic cancer and two human pancreatic cancer cell lines. Completeness of resonance assignments were evaluated using Chenomx, the human metabolite database (HMDB) and the COLMAR database. The intersection and uniqueness of the databases was quantified. RESULTS: P-values and AUC values were strongly correlated compared to VIP or FC values. Distributions of statistically significant bins depended strongly on whether or not datasets were normalized. 40-45% of peaks had either no or ambiguous database matches. 9-22% of metabolites were unique to each database. CONCLUSIONS: Lack of consistency in statistical analyses of metabolomics data can lead to misleading or inconsistent interpretation. Data normalization can have large effects on statistical analysis and should be justified. About 40% of peak assignments remain ambiguous or impossible with current databases. 1D and 2D databases should be made consistent to maximize metabolite assignment confidence and validation.

Characterization of chemoresistant human non-small cell lung cancer cells by metabolic and lipidomic profiling.

INTRODUCTION: Lung cancer is one of the most malignant cancers and the leading cause of cancer-related deaths worldwide, while acquired chemoresistance would represent a major problem in the treatment of non-small cell lung cancer (NSCLC) because of the reduced treatment effect and increased rates of recurrence. METHODS: To establish the chemoresistant NSCLC cells, doxorubicin was treated to A549 cells over 3 months at gradually increasing concentrations from 0.03 to 0.5 µM. Real-time PCR and Western blotting were employed for investigating mRNA and protein expression of the glutathione peroxidase (GPX) protein family and multidrug resistance protein 1 (MRP1) in A549 and A549/CR cells. We also employed gas chromatography mass-spectrometry and nano electrospray ionization mass-spectrometry coupled with multivariate statistical analysis to characterize the unique metabolic and lipidomic profiles of chemoresistant NSCLC cells in order to identify potential therapeutic targets. RESULTS: Reactive oxygen species levels were decreased, and mRNA and protein levels of GPX2 and multidrug resistance protein 1 (MRP1) were increased in A549/CR. We identified 87 metabolites and intact lipid species in A549 and A549/CR. Among these metabolites, lactic acid, glutamic acid, glycine, proline, aspartic acid, succinic acid, and ceramide, alongside the PC to PE ratio, and arachidonic acid-containing phospholipids were suggested as characteristic features of chemoresistant NSCLC cells (A549/CR). CONCLUSIONS: This study reveals characteristic feature differences between drug-resistance NSCLC cells and their parental cells. We suggest potential therapeutic targets in chemoresistant NSCLC. Our results provide new insight into metabolic and lipidomic alterations in chemoresistant NSCLC. This could be used as fundamental information to develop therapeutic strategies for the treatment of chemoresistant NSCLC patients.

Disclosing a metabolic signature of cisplatin resistance in MDA-MB-231 triple-negative breast cancer cells by NMR metabolomics.

This work compared the metabolic profile of a parental MDA-MB-231 cisplatin-sensitive triple negative breast cancer (TNBC) cell line with that of a derived cisplatin-resistant line, to characterize inherent metabolic adaptations to resistance, as a means for marker and new TNBC therapies discovery. Supported by cytotoxic, microscopic and biochemical characterization of both lines, Nuclear Magnetic Resonance (NMR) metabolomics was employed to characterize cell polar extracts for the two cell lines, as a function of time (0, 24 and 48 h), and identify statistically relevant differences both between sensitive and resistant cells and their time course behavior. Biochemical results revealed a slight increase in activation of the NF-κB pathway and a marked decrease of the ERK signaling pathway in resistant cells. This was accompanied by lower glycolytic and glutaminolytic activities, possibly linked to glutamine being required to increase stemness capacity and, hence, higher survival to cisplatin. The TCA cycle dynamics seemed to be time-dependent, with an apparent activation at 48 h preferentially supported by anaplerotic aromatic amino acids, leucine and lysine. A distinct behavior of leucine, compared to the other branched-chain-amino-acids, suggested the importance of the recognized relationship between leucine and in mTOR-mediated autophagy to increase resistance. Suggested markers of MDA-MB-231 TNBC cisplatin-resistance included higher phosphocreatine/creatine ratios, hypotaurine/taurine-mediated antioxidant protective mechanisms, a generalized marked depletion in nucleotides/nucleosides, and a distinctive pattern of choline compounds. Although the putative hypotheses generated here require biological demonstration, they pave the way to the use of metabolites as markers of cisplatin-resistance in TNBC and as guidance to develop therapies.

Differentiation and prognostic stratification of acute myeloid leukemia by serum-based spectroscopy coupling with metabolic fingerprints.

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by complex molecular and cytogenetic abnormalities. New approaches to predict the prognosis of AML have increasingly attracted attention. There were 98 non-M3 AML cases and 48 healthy controls were enrolled in the current work. Clinically routine assays for cytogenetic and molecular genetic analyses were performed on the bone marrow samples of patients with AML. Meanwhile, metabolic profiling of these AML subjects was also performed on the serum samples by combining Ag nanoparticle-based surface-enhanced Raman spectroscopy (SERS) with proton nuclear magnetic resonance (NMR) spectroscopy. Although most of the routine biochemical test showed no significant differences between the M0-M2 and M5 groups, the metabolic profiles were significantly different either between AML subtypes or between prognostic risk subgroups. Specific SERS bands were screened to serve as potential markers for AML subtypes. The results demonstrated that the classification models for M0-M2 and M5 shared two bands (i.e., 1328 and 741 cm-1 ), all came from nucleic acid signals. Furthermore, Metabolic profiles provided various differential metabolites responsible for different AML subtypes, and we found altered pathways mainly included energy metabolism like glycolysis, pyruvate metabolism, and metabolisms of nucleic acid bases as well as specific amino acid metabolisms. It is concluded that integration of SERS and NMR provides the rational and could be reliable to reveal AML differentiation, and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and prognostic evaluation.

Streptomonospora mangrovi sp. nov., isolated from mangrove soil showing similar metabolic capabilities, but distinct secondary metabolites profiles.

A novel actinomycete, designated strain S1-112 T, was isolated from a mangrove soil sample from Hainan, China, and characterized using a polyphasic approach. Strain S1-112 T showed the highest similarity of the 16S rRNA gene to Streptomonospora nanhaiensis 12A09T (99.24%). Their close relationship was further supported by phylogenetic analyses, which placed these two strains within a stable clade. The highest values of digital DNA-DNA hybridization (dDDH, 41.4%) and average nucleotide identity (ANI, 90.55%) were detected between strain S1-112 T and Streptomonospora halotolerans NEAU-Jh2-17 T. Genotypic and phenotypic characteristics demonstrated that strain S1-112 T could be distinguished from its closely related relatives. We also profiled the pan-genome and metabolic features of genomic assemblies of strains belonging to the genus Streptomonospora, indicating similar functional capacities and metabolic activities. However, all of these strains showed promising potential for producing diverse types of secondary metabolites. In conclusion, strain S1-112 T represents a novel species of the genus Streptomonospora, for which the name Streptomonospora mangrovi sp. nov. was proposed. The type strain is S1-112 T (= JCM 34292 T).