Metabolic profiles reflect weight loss maintenance and the composition of diet after very-low-energy diet

Background & aims: Diet and weight loss affect circulating metabolome. However, metabolite profiles induced by different weight loss maintenance diets and underlying longer term weight loss maintenance remain unknown. Herein, we investigated after-weight-loss metabolic signatures of two isocaloric 24-wk weight maintenance diets differing in satiety value due to dietary fibre, protein and fat contents and identified metabolite features that associated with successful weight loss maintenance. Methods: Non-targeted LC-MS metabolomics approach was used to analyse plasma metabolites of 79 women and men (mean age \ub1 SD 49.7 \ub1 9.0 years; BMI 34.2 \ub1 2.5 kg/m2) participating in a weight management study. Participants underwent a 7-week very-low-energy diet (VLED) and were thereafter randomised into two groups for a 24-week weight maintenance phase. Higher satiety food (HSF) group consumed high-fibre, high-protein, and low-fat products, while lower satiety food (LSF) group consumed isocaloric low-fibre products with average protein and fat content as a part of their weight maintenance diets. Plasma metabolites were analysed before the VLED and before and after the weight maintenance phase. Metabolite features discriminating HSF and LSF groups were annotated. We also analysed metabolite features that discriminated participants who maintained ≥10% weight loss (HWM) and participants who maintained <10% weight loss (LWM) at the end of the study, irrespective of the diet. Finally, we assessed robust linear regression between metabolite features and anthropometric and food group variables. Results: We annotated 126 metabolites that discriminated the HSF and LSF groups and HWM and LWM groups (p < 0.05). Compared to LSF, the HSF group had lower levels of several amino acids, e.g. glutamine, arginine, and glycine, short-, medium- and long-chain acylcarnitines (CARs), odd- and even-chain lysoglycerophospholipids, and higher levels of fatty amides. Compared to LWM, the HWM group in general showed higher levels of glycerophospholipids with a saturated long-chain and a C20:4 fatty acid tail, and unsaturated free fatty acids (FFAs). Changes in several saturated odd- and even-chain LPCs and LPEs and fatty amides were associated with the intake of many food groups, particularly grain and dairy products. Increase in several (lyso)glycerophospholipids was associated with decrease in body weight and adiposity. Increased short- and medium-chain CARs were related to decreased body fat-free mass. Conclusions: Our results show that isocaloric weight maintenance diets differing in dietary fibre, protein, and fat content affected amino acid and lipid metabolism. Increased abundances of several phospholipid species and FFAs were related with greater weight loss maintenance. Our findings indicate common and distinct metabolites for weight and dietary related variables in the context of weight reduction and weight management. The study was registered in isrctn.org with identifier 67529475

Tissue-wide metabolomics reveals wide impact of gut microbiota on mice metabolite composition

The essential role of gut microbiota in health and disease is well recognized, but the biochemical details that underlie the beneficial impact remain largely undefined. To maintain its stability, microbiota participates in an interactive host-microbiota metabolic signaling, impacting metabolic phenotypes of the host. Dysbiosis of microbiota results in alteration of certain microbial and host metabolites. Identifying these markers could enhance early detection of certain diseases. We report LC-MS based non-targeted metabolic profiling that demonstrates a large effect of gut microbiota on mammalian tissue metabolites. It was hypothesized that gut microbiota influences the overall biochemistry of host metabolome and this effect is tissue-specific. Thirteen different tissues from germ-free (GF) and conventionally-raised (MPF) C57BL/6NTac mice were selected and their metabolic differences were analyzed. Our study demonstrated a large effect of microbiota on mammalian biochemistry at different tissues and resulted in statistically-significant modulation of metabolites from multiple metabolic pathways (p  ≤ 0.05). Hundreds of molecular features were detected exclusively in one mouse group, with the majority of these being unique to specific tissue. A vast metabolic response of host to metabolites generated by the microbiota was observed, suggesting gut microbiota has a direct impact on host metabolism.</p

Low-Dose Doxycycline Treatment Normalizes Levels of Some Salivary Metabolites Associated with Oral Microbiota in Patients with Primary Sjögren’s Syndrome

Saliva is a complex oral fluid, and plays a major role in oral health. Primary Sjögren’s syndrome (pSS), as an autoimmune disease that typically causes hyposalivation. In the present study, salivary metabolites were studied from stimulated saliva samples (n = 15) of female patients with pSS in a group treated with low-dose doxycycline (LDD), saliva samples (n = 10) of non-treated female patients with pSS, and saliva samples (n = 14) of healthy age-matched females as controls. Saliva samples were analyzed with liquid chromatography mass spectrometry (LC-MS) based on the non-targeted metabolomics method. The saliva metabolite profile differed between pSS patients and the healthy control (HC). In the pSS patients, the LDD treatment normalized saliva levels of several metabolites, including tyrosine glutamine dipeptide, phenylalanine isoleucine dipeptide, valine leucine dipeptide, phenylalanine, pantothenic acid (vitamin B5), urocanic acid, and salivary lipid cholesteryl palmitic acid (CE 16:0), to levels seen in the saliva samples of the HC. In conclusion, the data showed that pSS is associated with an altered saliva metabolite profile compared to the HC and that the LLD treatment normalized levels of several metabolites associated with dysbiosis of oral microbiota in pSS patients. The role of the saliva metabolome in pSS pathology needs to be further studied to clarify if saliva metabolite levels can be used to predict or monitor the progress and treatment of pSS

Metabolite Pattern Derived from Lactiplantibacillus plantarum-Fermented Rye Foods and In Vitro Gut Fermentation Synergistically Inhibits Bacterial Growth

ScopeFermentation improves many food characteristics using microbes, such as lactic acid bacteria (LAB). Recent studies suggest fermentation may also enhance the health properties, but mechanistic evidence is lacking. The study aims to identify a metabolite pattern reproducibly produced during sourdough and in vitro colonic fermentation of various whole-grain rye products and how it affects the growth of bacterial species of potential importance to health and disease.Methods and resultsThe study uses Lactiplantibacillus plantarum DSMZ 13890 strain, previously shown to favor rye as its substrate. Using LC-MS metabolomics, the study finds seven microbial metabolites commonly produced during the fermentations, including dihydroferulic acid, dihydrocaffeic acid, and five amino acid metabolites, and stronger inhibition is achieved when exposing the bacteria to a mixture of the metabolites in vitro compared to individual compound exposures.ConclusionThe study suggests that metabolites produced by LAB may synergistically modulate the local microbial ecology, such as in the gut. This could provide new hypotheses on how fermented foods influence human health via diet–microbiota interactions.</p

Low-Dose Doxycycline Treatment Normalizes Levels of Some Salivary Metabolites Associated with Oral Microbiota in Patients with Primary Sjögren’s Syndrome

Saliva is a complex oral fluid, and plays a major role in oral health. Primary Sjögren’s syndrome (pSS), as an autoimmune disease that typically causes hyposalivation. In the present study, salivary metabolites were studied from stimulated saliva samples (n = 15) of female patients with pSS in a group treated with low-dose doxycycline (LDD), saliva samples (n = 10) of non-treated female patients with pSS, and saliva samples (n = 14) of healthy age-matched females as controls. Saliva samples were analyzed with liquid chromatography mass spectrometry (LC-MS) based on the non-targeted metabolomics method. The saliva metabolite profile differed between pSS patients and the healthy control (HC). In the pSS patients, the LDD treatment normalized saliva levels of several metabolites, including tyrosine glutamine dipeptide, phenylalanine isoleucine dipeptide, valine leucine dipeptide, phenylalanine, pantothenic acid (vitamin B5), urocanic acid, and salivary lipid cholesteryl palmitic acid (CE 16:0), to levels seen in the saliva samples of the HC. In conclusion, the data showed that pSS is associated with an altered saliva metabolite profile compared to the HC and that the LLD treatment normalized levels of several metabolites associated with dysbiosis of oral microbiota in pSS patients. The role of the saliva metabolome in pSS pathology needs to be further studied to clarify if saliva metabolite levels can be used to predict or monitor the progress and treatment of pSS. </p

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data