ObjectivesThe goal of this work was to explore the dynamic concentration profiles of 42 amino acids and the significance of these profiles in relation to sepsis, with the aim of providing guidance for clinical therapies.MethodsThirty-five critically ill patients with sepsis were included. These patients were further divided into sepsis (12 cases) and severe sepsis (23 cases) groups or survivor (20 cases) and non-survivor (15 cases) groups. Serum samples from the patients were collected on days 1, 3, 5, 7, 10, and 14 following intensive care unit (ICU) admission, and the serum concentrations of 42 amino acids were measured.ResultsThe metabolic spectrum of the amino acids changed dramatically in patients with sepsis. As the disease progressed further or with poor prognosis, the levels of the different amino acids gradually increased, decreased, or fluctuated over time. The concentrations of sulfur-containing amino acids (SAAs), especially taurine, decreased significantly as the severity of sepsis worsened or with poor prognosis of the patient. The serum concentrations of SAAs, especially taurine, exhibited weak negative correlations with the Sequential Organ Failure Assessment (SOFA) (r=-0.319) and Acute Physiology and Chronic Health Evaluation (APACHE) II (r=-0.325) scores. The areas under the receiver operating characteristic curves of cystine, taurine, and SAA levels and the SOFA and APACHE II scores, which denoted disease prognosis, were 0.623, 0.674, 0.678, 0.86, and 0.857, respectively.ConclusionsCritically ill patients with disorders of amino acid metabolism, especially of SAAs such as cystine and taurine, may provide an indicator of the need for the nutritional support of sepsis in the clinic.Trial RegistrationClinicalTrial.gov identifier NCT01818830.

Metabolic variations occur during normal pregnancy to provide the growing fetus with a supply of nutrients required for its development and to ensure the health of the woman during gestation. Mass spectrometry-based metabolomics was employed to study the metabolic phenotype variations in the maternal plasma that are induced by pregnancy in each of its three trimesters. Nontargeted metabolomics analysis showed that pregnancy significantly altered the profile of metabolites in maternal plasma. The levels of six metabolites were found to change significantly throughout pregnancy, with related metabolic pathway variations observed in biopterin metabolism, phospholipid metabolism, amino acid derivatives, and fatty acid oxidation. In particular, there was a pronounced elevation of dihydrobiopterin (BH₂), a compound produced in the synthesis of dopa, dopamine, norepinephrine, and epinephrine, in the second trimester, whereas it was markedly decreased in the third trimester. The turnover of BH₂ and tryptophan catabolites indicated that the fluctuations of neurotransmitters throughout pregnancy might reveal the metabolic adaption in the maternal body for the growth of the fetus. Furthermore, 11 lipid classes and 41 carnitine species were also determined and this showed variations in the presence of long-chain acylcarnitines and lysophospholipids in later pregnancy, suggesting changes of acylcarnitines and lysophospholipids to meet the energy demands in pregnant women. To our knowledge, this work is the first report of dynamic metabolic signatures and proposed related metabolic pathways in the maternal plasma for normal pregnancies and provided the basis for time-dependent metabolic trajectory against which disease-related disorders may be contrasted.

BackgroundMetabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy.FindingsIn this Data Note, LC–MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy.ConclusionsAs a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-015-0054-9) contains supplementary material, which is available to authorized users.

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The vagina contains at least a billion microbial cells, dominated by lactobacilli. Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age, as well as cervical, fecal, and salivary samples from a second cohort of 632 women. Factors such as pregnancy  history, delivery history, cesarean section, and breast  feeding were all more important than menstrual cycle in shaping the microbiome, and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data. Greater proportion of Bifidobacterium breve was seen with older age at sexual debut. The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history. Potential markers for lack of menstrual regularity, heavy flow, dysmenorrhea, and contraceptives were also identified. Lactobacilli were rare during breastfeeding or post-menopause. Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome. Gut and salivary microbiomes, plasma vitamins, metals, amino acids, and hormones showed associations with the vagino-cervical microbiome. Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.