Further delineation of the phenotypic and metabolomic profile of ALDH1L2-related neurodevelopmental disorder.

ALDH1L2, a mitochondrial enzyme in folate metabolism, converts 10-formyl-THF (10-formyltetrahydrofolate) to THF (tetrahydrofolate) and CO2. At the cellular level, deficiency of this NADP+-dependent reaction results in marked reduction in NADPH/NADP+ ratio and reduced mitochondrial ATP. Thus far, a single patient with biallelic ALDH1L2 variants and the phenotype of a neurodevelopmental disorder has been reported. Here, we describe another patient with a neurodevelopmental disorder associated with a novel homozygous missense variant in ALDH1L2, Pro133His. The variant caused marked reduction in the ALDH1L2 enzyme activity in skin fibroblasts derived from the patient as probed by 10-FDDF, a stable synthetic analog of 10-formyl-THF. Additional associated abnormalities in these fibroblasts include reduced NADPH/NADP+ ratio and pool of mitochondrial ATP, upregulated autophagy and dramatically altered metabolomic profile. Overall, our study further supports a link between ALDH1L2 deficiency and abnormal neurodevelopment in humans.

Exploratory Untargeted Metabolomics of Dried Blood Spot Samples from Newborns with Maple Syrup Urine Disease.

Currently, tandem mass spectrometry-based newborn screening (NBS), which examines targeted biomarkers, is the first approach used for the early detection of maple syrup urine disease (MSUD) in newborns, followed by confirmatory genetic mutation tests. However, these diagnostic approaches have limitations, demanding the development of additional tools for the diagnosis/screening of MUSD. Recently, untargeted metabolomics has been used to explore metabolic profiling and discover the potential biomarkers/pathways of inherited metabolic diseases. Thus, we aimed to discover a distinctive metabolic profile and biomarkers/pathways for MSUD newborns using untargeted metabolomics. Herein, untargeted metabolomics was used to analyze dried blood spot (DBS) samples from 22 MSUD and 22 healthy control newborns. Our data identified 210 altered endogenous metabolites in MSUD newborns and new potential MSUD biomarkers, particularly L-alloisoleucine, methionine, and lysoPI. In addition, the most impacted pathways in MSUD newborns were the ascorbate and aldarate pathways and pentose and glucuronate interconversions, suggesting that oxidative and detoxification events may occur in early life. Our approach leads to the identification of new potential biomarkers/pathways that could be used for the early diagnosis/screening of MSUD newborns but require further validation studies. Our untargeted metabolomics findings have undoubtedly added new insights to our understanding of the pathogenicity of MSUD, which helps us select the appropriate early treatments for better health outcomes.

E. coli Secretome Metabolically Modulates MDA-MB-231 Breast Cancer Cells' Energy Metabolism.

Breast cancer (BC) is commonly diagnosed in women. BC cells are associated with altered metabolism, which is essential to support their energetic requirements, cellular proliferation, and continuous survival. The altered metabolism of BC cells is a result of the genetic abnormalities of BC cells. Risk factors can also enhance it, including age, lifestyle, hormone disturbances, etc. Other unknown BC-promoting risk factors are under scientific investigation. One of these investigated factors is the microbiome. However, whether the breast microbiome found in the BC tissue microenvironment can impact BC cells has not been studied. We hypothesized that E. coli, part of a normal breast microbiome with more presence in BC tissue, secretes metabolic molecules that could alter BC cells' metabolism to maintain their survival. Thus, we directly examined the impact of the E. coli secretome on the metabolism of BC cells in vitro. MDA-MB-231 cells, an in vitro model of aggressive triple-negative BC cells, were treated with the E. coli secretome at different time points, followed by untargeted metabolomics analyses via liquid chromatography-mass spectrometry to identify metabolic alterations in the treated BC cell lines. MDA-MB-231 cells that were not treated were used as controls. Moreover, metabolomic analyses were performed on the E. coli secretome to profile the most significant bacterial metabolites affecting the metabolism of the treated BC cell lines. The metabolomics results revealed about 15 metabolites that potentially have indirect roles in cancer metabolism that were secreted from E. coli in the culture media of MDA-MB-231 cells. The cells treated with the E. coli secretome showed 105 dysregulated cellular metabolites compared to controls. The dysregulated cellular metabolites were involved in the metabolism of fructose and mannose, sphingolipids, amino acids, fatty acids, amino sugar, nucleotide sugar, and pyrimidine, which are vital pathways required for the pathogenesis of BC. Our findings are the first to show that the E. coli secretome modulates the BC cells' energy metabolism, highlighting insights into the possibility of altered metabolic events in BC tissue in the actual BC tissue microenvironment that are potentially induced by the local bacteria. Our study provides metabolic data that could be as a basis for future studies searching for the underlying mechanisms mediated by bacteria and their secretome to alter the metabolism of BC cells.

Lipids Alterations Associated with Metformin in Healthy Subjects: An Investigation Using Mass Spectrometry Shotgun Approach.

Metformin is an orally effective insulin-sensitizing drug widely prescribed for treating type 2 diabetes mellitus (T2DM). Metformin has been reported to alter lipid metabolism. However, the molecular mechanisms behind its impact on lipid metabolism remain partially explored and understood. In the current study, mass spectrometry-based lipid profiling was used to investigate the lipidomic changes in the serum of 26 healthy individuals after a single-dose intake of metformin. Samples were analyzed at five-time points: preadministration, before the maximum concentration of metformin (Cmax), Cmax, after Cmax, and 36 h post-administration. A total of 762 molecules were significantly altered between the five-time points. Based on a comparison between baseline level and Cmax, metformin significantly increased and decreased the level of 33 and 192 lipids, respectively (FDR ≤ 0.05 and fold change cutoff of 1.5). The altered lipids are mainly involved in arachidonic acid metabolism, steroid hormone biosynthesis, and glycerophospholipid metabolism. Furthermore, several lipids acted in an opposed or similar manner to metformin levels and included fatty acyls, sterol lipids, glycerolipids, and glycerophospholipids. The significantly altered lipid species pointed to fundamental lipid signaling pathways that could be linked to the pleiotropic effects of metformin in T2DM, insulin resistance, polycystic ovary syndrome, cancer, and cardiovascular diseases.

Effective removal of heavy metals from industrial effluent wastewater by a multi metal and drug resistant Pseudomonas aeruginosa strain RA-14 using integrated sequencing batch reactor.

Sequencing batch reactor (SBR) is useful in removal of both non-biodegradable and biodegradable contaminants from wastewater. The main aim of the present investigation was to evaluate the potential of biocatalyst strain RA-14 on heavy metal removal under SBR. The selected strain was screened from the soil sediment contaminated with heavy metals. It was able to survive at different (Hg2+, Pb2+, Zn2+, Cu2+, Cd2+ and Ni2+) heavy metals (>500 ppm). The bacterial strain RA-14 showed maximum bioaccumulation potential than other strains. Heavy metal resistance patterns of Pb2+ > Cu2 > Cd2+ > Hg2+, Ni2+ and Zn2 was observed. Strain RA-14 was resistant to penicillin-G, nalidixic acid, ceftazidime, cefotaxime, kanamycin and ampicillin. The results revealed that bioaccumulation activities were improved at pH 7.0 (83.2 ± 1.8%), 40 °C (89.34 ± 3%) and affected at higher pH values and temperature. The results showed that contact time and initial Lead concentration was also affected Lead accumulation. The heavy metal tolerant strain RA-14 was further investigated towards heavy metal removal in SBR. Heavy metal was removed in SBR within 10 h of hydraulic retention time. Heavy metal removal was high at 2 mg/L (0.33 mg/L Cu2+, 0.33 mg/L Hg2+, 0.33 mg/L Pb2+, 0.33 mg/L Zn2+, 0.33 mg/L Cd2+ and 0.33 mg/L Ni2+) heavy metals. Total nitrogen, biological oxygen demand (BOD) and chemical oxygen demand (COD) of treated water in SBR was removed and the removal efficacy was 91.3 ± 2.1%, 97.6 ± 3.3%, and 94.3 ± 4.4%, respectively in 10 h hydraulic retention time. However, the efficiency of BOD, COD and total nitrogen content removal was decreased, due to the reduced metabolic process of bacteria after 10 h. The SBR reactor proved to be an efficient method for the treatment of various heavy metals from the wastewater.

Metabolomic Profiling of Blood Plasma in Females with Hyperplasia and Endometrial Cancer.

Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.

A Distinctive Metabolomics Profile and Potential Biomarkers for Very Long Acylcarnitine Dehydrogenase Deficiency (VLCADD) Diagnosis in Newborns.

Very long-chain acylcarnitine dehydrogenase deficiency (VLCADD) is a rare inherited metabolic disorder associated with fatty acid ß-oxidation and characterized by genetic mutations in the ACADVL gene and accumulations of acylcarnitines. VLCADD, developed in neonates or later adults, can be diagnosed using newborn bloodspot screening (NBS) or genetic sequencing. These techniques have limitations, such as a high false discovery rate and variants of uncertain significance (VUS). As a result, an extra diagnostic tool is needed to deliver improved performance and health outcomes. As VLCADD is linked with metabolic disturbance, we postulated that newborn patients with VLCADD could display a distinct metabolomics pattern compared to healthy newborns and other disorders. Herein, we applied an untargeted metabolomics approach using liquid chromatography-high resolution mass spectrometry (LC-HRMS) to measure the global metabolites in dried blood spot (DBS) cards collected from VLCADD newborns (n = 15) and healthy controls (n = 15). Two hundred and six significantly dysregulated endogenous metabolites were identified in VLCADD, in contrast to healthy newborns. Fifty-eight and one hundred and eight up- and down-regulated endogenous metabolites were involved in several pathways such as tryptophan biosynthesis, aminoacyl-tRNA biosynthesis, amino sugar and nucleotide sugar metabolism, pyrimidine metabolism and pantothenate, and CoA biosynthesis. Furthermore, biomarker analyses identified 3,4-Dihydroxytetradecanoylcarnitine (AUC = 1), PIP (20:1)/PGF1alpha) (AUC = 0.982), and PIP2 (16:0/22:3) (AUC = 0.978) as potential metabolic biomarkers for VLCADD diagnosis. Our findings showed that compared to healthy newborns, VLCAADD newborns exhibit a distinctive metabolic profile, and identified potential biomarkers that can be used for early diagnosis, which improves the identification of the affected patients earlier. This allows for the timely administration of proper treatments, leading to improved health. However, further studies with large independent cohorts of VLCADD patients with different ages and phenotypes need to be studied to validate our potential diagnostic biomarkers and their specificity and accuracy during early life.

Metabolomic profile of patients on levothyroxine treatment for hypothyroidism.

Background: Hypothyroidism is clinically characterized by a decrease in levels of the circulating thyroid hormones namely thyroxine and triiodothyronine. The main treatment for hypothyroidism is thyroid hormone replacement using levothyroxine to normalize serum thyroid hormone levels. Objectives: In this study, we explored the metabolic changes in the plasma of patients with hypothyroidism after reaching a euthyroid state with levothyroxine treatment. Methods: Plasma samples from 18 patients diagnosed as overt hypothyroidism were collected before and after levothyroxine treatment upon reaching a euthyroid state and were analyzed by high-resolution mass spectrometry-based metabolomics. Multivariate and univariate analyses evaluated data to highlight potential metabolic biomarkers. Results: Liquid chromatography-mass spectrometry-based metabolomics revealed a significant decrease in the levels of ceramide, phosphatidylcholine, triglycerides, acylcarnitine, and peptides after levothyroxine treatment; this could indicate a change in the fatty acid transportation system and an enhanced ß-oxidation, compared with a hypothyroid state. At the same time, the decrease in the peptides suggested a shift in protein synthesis. In addition, there was a considerable rise in glycocholic acid following therapy, suggesting the involvement of thyroid hormones in stimulating bile acid production and secretion. Conclusions: A metabolomic analysis of patients with hypothyroidism revealed significant changes in several metabolites and lipids after treatment. This study showed the value of the metabolomics technique in providing a complementary understanding of the pathophysiology of hypothyroidism and as a crucial tool for examining the molecular impact of levothyroxine treatment on hypothyroidism. It was an important tool for investigating the therapeutic effects of levothyroxine on hypothyroidism at the molecular level.

Biomarker discovery in galactosemia: Metabolomics with UPLC/HRMS in dried blood spots.

Introduction:Galactosemia (GAL) is a genetic disorder that results in disturbances in galactose metabolism and can lead to life-threatening complications. However, the underlying pathophysiology of long-term complications in GAL remains poorly understood. Methods: In this study, a metabolomics approach using ultra-performance liquid chromatography coupled with high-resolution mass spectrometry was used to investigate metabolomic changes in dried blood spots of 15 patients with GAL and 39 healthy individuals. Results: The study found that 2,819 metabolites underwent significant changes in patients with GAL compared to the control group. 480 human endogenous metabolites were identified, of which 209 and 271 were upregulated and downregulated, respectively. PA (8:0/LTE4) and ganglioside GT1c (d18:0/20:0) metabolites showed the most significant difference between GAL and the healthy group, with an area under the curve of 1 and 0.995, respectively. Additionally, the study identified potential biomarkers for GAL, such as 17-alpha-estradiol-3-glucuronide and 16-alpha-hydroxy DHEA 3-sulfatediphosphate. Conclusion: This metabolomics study deepened the understanding of the pathophysiology of GAL and presented potential biomarkers that might serve as prognostic biomarkers to monitor the progression or support the clinical diagnosis of GAL.

Metabolic Alteration of MCF-7 Cells upon Indirect Exposure to E. coli Secretome: A Model of Studying the Microbiota Effect on Human Breast Tissue.

According to studies, the microbiome may contribute to the emergence and spread of breast cancer. E. coli is one of the Enterobacteriaceae family recently found to be present as part of the breast tissue microbiota. In this study, we focused on the effect of E. coli secretome free of cells on MCF-7 metabolism. Liquid chromatography-mass spectrometry (LC-MS) metabolomics was used to study the E. coli secretome and its role in MCF-7 intra- and extracellular metabolites. A comparison was made between secretome-exposed cells and unexposed controls. Our analysis revealed significant alterations in 31 intracellular and 55 extracellular metabolites following secretome exposure. Several metabolic pathways, including lactate, aminoacyl-tRNA biosynthesis, purine metabolism, and energy metabolism, were found to be dysregulated upon E. coli secretome exposure. E. coli can alter the breast cancer cells' metabolism through its secretome which disrupts key metabolic pathways of MCF-7 cells. These microbial metabolites from the secretome hold promise as biomarkers of drug resistance or innovative approaches for cancer treatment, either as standalone therapies or in combination with other medicines.

Demaghi, a polyherbal formulation, mitigates aluminum chloride-induced neurological impairment in mice: Insights from phytochemical analysis and behavioral assessment.

Herbal products have been very popular in Pakistan for their curative significance against various disorders. Demaghi (DEMG) is a widely used herbal product claimed to own natural substances having neuroprotective potential. The current study aims to scientifically validate the chemical composition as well as its neuroprotective claims of this widely used herbal tonic. The commercially available Demaghi product was chemically characterized for its phytocomposition. The mice were treated with two doses of Demaghi (DEMG 50 mg and 100 mg/kg/day), and the effects of its prolonged exposure on animal anxiety, memory, and depression were noted through a series of behavioral tests in the AlCl3-induced memory deficient mice model. Besides that, dissected brains were biochemically analyzed for oxidative stress markers and acetylcholinesterase activity, as well as histopathological changes. The study outcomes showed that DEMG (100 mg/kg/day) has prominent anti-anxiety effects, memory-enhancing properties, and anti-depressants effects observed in the AlCl3-induced memory-deficient mice model. Biochemical assays also showed a greater decrease in oxidative stress of tested animals treated with 100 mg/kg/day of DEMG. The histopathological analysis also revealed that administration of DEMG reduced the AlCl3-induced toxicity. UPLC-MS results revealed the presence of many phytoconstituents, which showed to support cholinergic signaling in in-silico studies. The current research validates the neurological benefits of Demaghi for memory-boosting properties. The phytocompounds present in Demaghi exert neuroprotective effects, possibly by enhancing the cholinergic neurotransmission and combating the neurotoxin-induced oxidative stress.

Lipidomics Profiling of Metformin-Induced Changes in Obesity and Type 2 Diabetes Mellitus: Insights and Biomarker Potential.

Metformin is the first-line oral medication for treating type 2 diabetes mellitus (T2DM). In the current study, an untargeted lipidomic analytical approach was used to investigate the alterations in the serum lipidome of a cohort of 89 participants, including healthy lean controls and obese diabetic patients, and to examine the alterations associated with metformin administration. A total of 115 lipid molecules were significantly dysregulated (64 up-regulated and 51 down-regulated) in the obese compared to lean controls. However, the levels of 224 lipid molecules were significantly dysregulated (125 up-regulated and 99 down-regulated) in obese diabetic patients compared to the obese group. Metformin administration in obese diabetic patients was associated with significant dysregulation of 54 lipid molecule levels (20 up-regulated and 34 down-regulated). Levels of six molecules belonging to five lipid subclasses were simultaneously dysregulated by the effects of obesity, T2DM, and metformin. These include two putatively annotated triacylglycerols (TGs), one plasmenyl phosphatidylcholine (PC), one phosphatidylglycerol (PGs), one sterol lipid (ST), and one Mannosyl-phosphoinositol ceramide (MIPC). This study provides new insights into our understanding of the lipidomics alterations associated with obesity, T2DM, and metformin and offers a new platform for potential biomarkers for the progression of diabetes and treatment response in obese patients.

The metabolomics approach revealed a distinctive metabolomics pattern associated with hyperthyroidism treatment.

Background: Hyperthyroidism is characterized by increased thyroid hormone production, which impacts various processes, including metabolism and energy expenditure. Yet, the underlying mechanism and subsequent influence of these changes are unknown. Metabolomics is a broad analytical method that enables qualitative and quantitative examination of metabolite level changes in biological systems in response to various stimuli, pathologies, or treatments. Objectives: This study uses untargeted metabolomics to explore the potential pathways and metabolic patterns associated with hyperthyroidism treatment. Methods: The study consisted of 20 patients newly diagnosed with hyperthyroidism who were assessed at baseline and followed up after starting antithyroid treatment. Two blood samples were taken from each patient, pre (hyperthyroid state) and post-treatment (euthyroid state). Hyperthyroid and euthyroid states were identified based on thyroxine and thyroid-stimulating hormone levels. The metabolic alteration associated with antithyroid therapy was investigated using liquid chromatography- high-resolution mass spectrometry. The untargeted metabolomics data was analyzed using both univariate and multivariate analyses using MetaboAnalyst v5.0. The significant metabolic pattern was identified using the lab standard pipeline, which included molecular annotation in the Human Metabolome Database, LipidMap, LipidBlast, and METLIN. The identified metabolites were examined using pathway and network analyses and linked to cellular metabolism. Results: The results revealed a strong group separation between the pre- and post-hyperthyroidism treatment (Q2 = 0.573, R2 = 0.995), indicating significant differences in the plasma metabolome after treatment. Eighty-three mass ions were significantly dysregulated, of which 53 and 30 characteristics were up and down-regulated in the post-treatment compared to the pre-treatment group, respectively. The medium-chain acylcarnitines, octanoylcarnitine, and decanoylcarnitine, previously found to rise in hyperthyroid patients, were among the down-regulated metabolites, suggesting that their reduction could be a possible biomarker for monitoring euthyroid restoration. Kynurenine is a downregulated tryptophan metabolite, indicating that the enzyme kynurenine 3-hydroxylase, inhibited in hyperthyroidism, is back functioning. L-cystine, a cysteine dimer produced from cysteine oxidation, was among the down-regulated metabolites, and its accumulation is considered a sign of oxidative stress, which was reported to accompany hyperthyroidism; L-cystine levels dropped, this suggests that the plasma level of L-cystine can be used to monitor the progress of euthyroid state restoration. Conclusion: The plasma metabolome of patients with hyperthyroidism before and after treatments revealed differences in the abundance of several small metabolites. Our findings add to our understanding of hyperthyroidism's altered metabolome and associated metabolic processes and shed light on acylcarnitines as a new biomarker for treatment monitoring in conjunction with thyroxine and thyroid-stimulating hormone.

Metabolomics-Microbiome Crosstalk in the Breast Cancer Microenvironment.

Breast cancer, the most frequent cancer diagnosed among females, is associated with a high mortality rate worldwide. Alterations in the microbiota have been linked with breast cancer development, suggesting the possibility of discovering disease biomarkers. Metabolomics has emerged as an advanced promising analytical approach for profiling metabolic features associated with breast cancer subtypes, disease progression, and response to treatment. The microenvironment compromises non-cancerous cells such as fibroblasts and influences cancer progression with apparent phenotypes. This review discusses the role of metabolomics in studying metabolic dysregulation in breast cancer caused by the effect of the tumor microenvironment on multiple cells such as immune cells, fibroblasts, adipocytes, etc. Breast tumor cells have a unique metabolic profile through the elevation of glycolysis and the tricarboxylic acid cycle metabolism. This metabolic profile is highly sensitive to microbiota activity in the breast tissue microenvironment. Metabolomics shows great potential as a tool for monitoring metabolic dysregulation in tissue and associating the findings with microbiome expression.