Common extraction protocols and sampling procedures for GC-MS metabolite profiling were applied to the MCF-7 breast cancer cell culture as a model system of adherent growing cells and validated for repeatability and reproducibility. For normalization of a concentration series after methanolic extraction, results obtained with cell count normalization equalled normalization to the chromatogram total ion current as a chromatogram-intrinsic parameter, indicating that cell counting as an additional experimental step could be omitted. However, we show here that both normalization strategies should only be applied for comparison of extracts with similar concentrations complicating comparisons of different samples, e.g. with different biological origin. Therefore, the application of TIC thresholds for the comparison of differently concentrated extracts is recommended with respect to the accuracy of the data, the working effort and complexity of the biological experiment. For proof of concept, MCF-7 cell samples generated by different sampling procedures were assessed using these thresholds. Within this context, direct extraction of adherent growing cells without any further preparation steps, which allows for rapid quenching of cell metabolism and efficient sample extraction, is discussed as an alternative to conventional cell counting and extraction. In conclusion, we recommend the consideration of chromatogram intensity thresholds for the mean comparison of differently concentrated sample replicates in GC-MS metabolite profiling.

The energy metabolism of most tumor cells relies on aerobic glycolysis (Warburg effect) characterized by an increased glycolytic flux that is accompanied by the increased formation of the cytotoxic metabolite methylglyoxal (MGO). Consequently, the rate of detoxification of this reactive glycolytic byproduct needs to be increased in order to prevent deleterious effects to the cells. This is brought about by an increased expression of glyoxalase 1 (GLO1) that is the rate-limiting enzyme of the MGO-detoxifying glyoxalase system. Here, we overexpressed GLO1 in HEK 293 cells and silenced it in MCF-7 cells using shRNA. Tumor-related properties of wild type and transformed cells were compared and key glycolytic enzyme activities assessed. Furthermore, the cells were subjected to hypoxic conditions to analyze the impact on cell proliferation and enzyme activities. Our results demonstrate that knockdown of GLO1 in the cancer cells significantly reduced tumor-associated properties such as migration and proliferation, whereas no functional alterations where found by overexpression of GLO1 in HEK 293 cells. In contrast, hypoxia caused inhibition of cell growth of all cells except of those overexpressing GLO1. Altogether, we conclude that GLO1 on one hand is crucial to maintaining tumor characteristics of malignant cells, and, on the other hand, supports malignant transformation of cells in a hypoxic environment when overexpressed.

In cancer research, cell lines are used to explore the molecular basis of the disease as a substitute to tissue biopsies. Breast cancer in particular is a very heterogeneous type of cancer, and different subgroups of cell lines have been established according to their genomic profiles and tumor characteristics. We applied GCMS metabolite profiling to five selected breast cancer cell lines and found this heterogeneity reflected on the metabolite level as well. Metabolite profiles of MCF-7 cells belonging to the luminal gene cluster proved to be more different from those of the basal A cell line JIMT-1 and the basal B cell lines MDA-MB-231, MDA-MB-435, and MDA-MB-436 with only slight differences in the intracellular metabolite pattern. Lactate release into the cultivation medium as an indicator of glycolytic activity was correlated to the metabolite profiles and physiological characteristics of each cell line. In conclusion, pantothenic acid, beta-alanine and glycerophosphoglycerol appeared to be related to the glycolytic activity designated through high lactate release. Other physiological parameters coinciding with glycolytic activity were high glyoxalase 1 (Glo1) and lactate dehydrogenase (LDH) enzyme activity as well as cell migration as an additional important characteristic contributing to the aggressiveness of tumor cells. Metabolite profiles of the cell lines are comparatively discussed with respect to known biomarkers of cancer progression.

Soil bacteria damage and destroy starch granules in archaeological contexts, but most studies of this kind of damage report on pairings of a single bacterial species with starches from a single plant species. Here we report the results of experiments in which starch granules from multiple plants were digested by a community of soil bacteria. The damage patterns of this bacterial community generally match those for single bacterial strains, and vary among plant species. However, when the bacteria are exposed to a mixture of starches from different taxa, certain plants are digested in favor of others. This variation in digestion could lead to a bias in the starches represented in the archaeological record. The types of damage observed in this experiment are further compared against that observed on archaeological starches recovered from dental calculus and stone tools