Cellular Metabolome Research Articles

Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

Regulatory role of hexosamine biosynthetic pathway on hepatic cancer stem cell marker CD133 under low glucose conditions.

Cancer was hypothesized to be driven by cancer stem cells (CSCs), but the metabolic determinants of CSC-like phenotype still remain elusive. Here, we present that hexosamine biosynthetic pathway (HBP) at least in part rescues cancer cell fate with inactivation of glycolysis. Firstly, metabolomic analysis profiled cellular metabolome in CSCs of hepatocellular carcinoma using CD133 cell-surface marker. The metabolic signatures of CD133-positive subpopulation compared to CD133-negative cells highlighted HBP as one of the distinct metabolic pathways, prompting us to uncover the role of HBP in maintenance of CSC-like phenotype. To address this, CSC-like phenotypes and cell survival were investigated in cancer cells under low glucose conditions. As a result, HBP inhibitor azaserine reduced CD133-positive subpopulation and CD133 expression under high glucose condition. Furthermore, treatment of N-Acetylglucosamine in part restores CD133-positive subpopulation when either 2.5 mM glucose in culture media or glycolytic inhibitor 2-deoxy-D-glucose in HCC cell lines was applied, enhancing CD133 expression as well as promoting cancer cell survival. Together, HBP might be a key metabolic determinant in the functions of hepatic CSC marker CD133.

Alterations in cellular metabolome after pharmacological inhibition of Notch in glioblastoma cells.

Notch signaling can promote tumorigenesis in the nervous system and plays important roles in stem-like cancer cells. However, little is known about how Notch inhibition might alter tumor metabolism, particularly in lesions arising in the brain. The gamma-secretase inhibitor MRK003 was used to treat glioblastoma neurospheres, and they were subdivided into sensitive and insensitive groups in terms of canonical Notch target response. Global metabolomes were then examined using proton magnetic resonance spectroscopy, and changes in intracellular concentration of various metabolites identified which correlate with Notch inhibition. Reductions in glutamate were verified by oxidation-based colorimetric assays. Interestingly, the alkylating chemotherapeutic agent temozolomide, the mTOR-inhibitor MLN0128, and the WNT inhibitor LGK974 did not reduce glutamate levels, suggesting that changes to this metabolite might reflect specific downstream effects of Notch blockade in gliomas rather than general sequelae of tumor growth inhibition. Global and targeted expression analyses revealed that multiple genes important in glutamate homeostasis, including glutaminase, are dysregulated after Notch inhibition. Treatment with an allosteric inhibitor of glutaminase, compound 968, could slow glioblastoma growth, and Notch inhibition may act at least in part by regulating glutaminase and glutamate.

Metabolic Reprogramming in Mutant IDH1 Glioma Cells

BackgroundMutations in isocitrate dehydrogenase (IDH) 1 have been reported in over 70% of low-grade gliomas and secondary glioblastomas. IDH1 is the enzyme that catalyzes the oxidative decarboxylation of isocitrate to α-ketoglutarate while mutant IDH1 catalyzes the conversion of α-ketoglutarate into 2-hydroxyglutarate. These mutations are associated with the accumulation of 2-hydroxyglutarate within the tumor and are believed to be one of the earliest events in the development of low-grade gliomas. The goal of this work was to determine whether the IDH1 mutation leads to additional magnetic resonance spectroscopy (MRS)–detectable changes in the cellular metabolome.MethodsTwo genetically engineered cell models were investigated, a U87-based model and an E6/E7/hTERT immortalized normal human astrocyte (NHA)-based model. For both models, wild-type IDH1 cells were generated by transduction with a lentiviral vector coding for the wild-type IDH1 gene while mutant IDH1 cells were generated by transduction with a lentiviral vector coding for the R132H IDH1 mutant gene. Metabolites were extracted from the cells using the dual-phase extraction method and analyzed by 1H-MRS. Principal Component Analysis was used to analyze the MRS data.ResultsPrincipal Component Analysis clearly discriminated between wild-type and mutant IDH1 cells. Analysis of the loading plots revealed significant metabolic changes associated with the IDH1 mutation. Specifically, a significant drop in the concentration of glutamate, lactate and phosphocholine as well as the expected elevation in 2-hydroxyglutarate were observed in mutant IDH1 cells when compared to their wild-type counterparts.ConclusionThe IDH1 mutation leads to several, potentially translatable MRS-detectable metabolic changes beyond the production of 2-hydroxyglutarate.

TEFMA: computing thermodynamically feasible elementary flux modes in metabolic networks.

: Elementary flux modes (EFMs) are important structural tools for the analysis of metabolic networks. It is known that many topologically feasible EFMs are biologically irrelevant. Therefore, tools are needed to find the relevant ones. We present thermodynamic tEFM analysis (tEFMA) which uses the cellular metabolome to avoid the enumeration of thermodynamically infeasible EFMs. Specifically, given a metabolic network and a not necessarily complete metabolome, tEFMA efficiently returns the full set of thermodynamically feasible EFMs consistent with the metabolome. Compared with standard approaches, tEFMA strongly reduces the memory consumption and the overall runtime. Thus tEFMA provides a new way to analyze unbiasedly hitherto inaccessible large-scale metabolic networks. https://github.com/mpgerstl/tEFMA CONTACT: : christian.jungreuthmayer@boku.ac.at or juergen.zanghellini@boku.ac.at Supplementary data are available at Bioinformatics online.

Age-related proteostasis and metabolic alterations in Caspase-2-deficient mice.

Ageing is a complex biological process for which underlying biochemical changes are still largely unknown. We performed comparative profiling of the cellular proteome and metabolome to understand the molecular basis of ageing in Caspase-2-deficient (Casp2−/−) mice that are a model of premature ageing in the absence of overt disease. Age-related changes were determined in the liver and serum of young (6–9 week) and aged (18–24 month) wild-type and Casp2−/− mice. We identified perturbed metabolic pathways, decreased levels of ribosomal and respiratory complex proteins and altered mitochondrial function that contribute to premature ageing in the Casp2−/− mice. We show that the metabolic profile changes in the young Casp2−/− mice resemble those found in aged wild-type mice. Intriguingly, aged Casp2−/− mice were found to have reduced blood glucose and improved glucose tolerance. These results demonstrate an important role for caspase-2 in regulating proteome and metabolome remodelling during ageing.

Dengue virus induces and requires glycolysis for optimal replication.

Viruses rely on host cellular metabolism to provide the energy and biosynthetic building blocks required for their replication. Dengue virus (DENV), a member of the Flaviviridae family, is one of the most important arthropod-borne human pathogens worldwide. We analyzed global intracellular metabolic changes associated with DENV infection of primary human cells. Our metabolic profiling data suggested that central carbon metabolism, particularly glycolysis, is strikingly altered during a time course of DENV infection. Glucose consumption is increased during DENV infection and depriving DENV-infected cells of exogenous glucose had a pronounced impact on viral replication. Furthermore, the expression of both glucose transporter 1 and hexokinase 2, the first enzyme of glycolysis, is upregulated in DENV-infected cells. Pharmacologically inhibiting the glycolytic pathway dramatically reduced DENV RNA synthesis and infectious virion production, revealing a requirement for glycolysis during DENV infection. Thus, these experiments suggest that DENV induces the glycolytic pathway to support efficient viral replication. This study raises the possibility that metabolic inhibitors, such as those that target glycolysis, could be used to treat DENV infection in the future. Approximately 400 million people are infected with dengue virus (DENV) annually, and more than one-third of the global population is at risk of infection. As there are currently no effective vaccines or specific antiviral therapies for DENV, we investigated the impact DENV has on the host cellular metabolome to identify metabolic pathways that are critical for the virus life cycle. We report an essential role for glycolysis during DENV infection. DENV activates the glycolytic pathway, and inhibition of glycolysis significantly blocks infectious DENV production. This study provides further evidence that viral metabolomic analyses can lead to the discovery of novel therapeutic targets to block the replication of medically important human pathogens.

TrypanoCyc: a community-led biochemical pathways database for Trypanosoma brucei

The metabolic network of a cell represents the catabolic and anabolic reactions that interconvert small molecules (metabolites) through the activity of enzymes, transporters and non-catalyzed chemical reactions. Our understanding of individual metabolic networks is increasing as we learn more about the enzymes that are active in particular cells under particular conditions and as technologies advance to allow detailed measurements of the cellular metabolome. Metabolic network databases are of increasing importance in allowing us to contextualise data sets emerging from transcriptomic, proteomic and metabolomic experiments. Here we present a dynamic database, TrypanoCyc (http://www.metexplore.fr/trypanocyc/), which describes the generic and condition-specific metabolic network of Trypanosoma brucei, a parasitic protozoan responsible for human and animal African trypanosomiasis. In addition to enabling navigation through the BioCyc-based TrypanoCyc interface, we have also implemented a network-based representation of the information through MetExplore, yielding a novel environment in which to visualise the metabolism of this important parasite.

Abstract 1835: Transcriptome and metabolome reprogramming in EGFR-mutant NSCLC early adaptive drug-escape against erlotinib

Abstract Background. Advanced NSCLC with sensitizing EGFR mutation is being treated with EGFR inhibitor first-line. Despite initial tumor response, targeted therapy invariably fails due to acquired resistance. Classical studies of acquired drug resistance focusing on late clinical events in rebiopsy studies have identified some resistance mechanisms including T790M-EGFR, MET amplification and AXL upregulation. Methods. HCC827 and PC-9 NSCLC cells (sensitizing EGFR exon 19-del) were used in vitro and in vivo drug-sensitive models. MTS viability assay, TLVM cell mobility assay, immunoblot and immunofluorescence and in vivo xenograft IHC analysis were performed. Transcriptome analysis of HCC827 cells under erlotinib inhibition time-course was performed using Affymetrix microarray gene expression profiling (Human GeneChip 1.0 ST arrays) in triplicate at 0 hr, 8 hr, 9 days of erlotinib-treatment, and 9 days pretreatment with erlotinib followed by 7 days drug-washout. Data analysis was performed using PCA, heatmap, BAMarray and PathwayStudio 6.0 analysis. We also performed mass-spectrometry-based global profiling analysis of cellular metabolome in 5 replicate. Results. We analyzed drug-sensitive HCC827 and PC-9 cells under erlotinib inhibition to characterize the adaptive response that engenders drug resistance. We identified an early adaptive drug-escape that emerged after 9 days of erlotinib, characterized with MET-independent mitochondrial BCL-2/BCL-xL prosurvival priming to result in 100-fold IC50 increase towards resistance. These cells displayed a quiescence state associated with retarded cell proliferation/cytoskeletal functions. Transcriptome profiling analysis of the early adaptive resistant HCC827 cells revealed a remarkable genome-wide adaptive reprogramming of gene expression signature, involving pathways of cell adhesion, cell cycle regulation, cell division/mitosis, glycolysis and gluconeogenesis, response to DNA damage stimulus, and DNA repair. Metabolomic profiling revealed a global adaptive metabolic reprogramming also, with resultant suppression of glucose and TCA cycle metabolism, and lipid bioenergetics. Our studies also identified autocrine TGFβ2 signaling pathway in mediating the early adaptive resistance in the mutated-EGFR lung cancer cells that escaped erlotinib inhibition through a combination of quiescence-state and EMT, cellular metabolic reprogramming and STAT3/BCL-2/BCL-xL mitochondrial prosurvival priming. Conclusion. Early adaptive drug-escape emerges within a subpopulation of EGFR-mutant NSCLC under erlotinib inhibition. This constitutes an early-stage minimal residual disease leading to eventual resistant tumor relapse. These early drug-escaping tumor cells undergo global cellular reprogramming with upregulated mitochondrial prosurvival priming, representing attractive therapeutic targets to eradicate drug resistance. Citation Format: Patrick C. Ma, Praveena S. Thiagarajan, Patrick Leahy, Rakesh Bagai, Ivy Shi, Wei Zhang, Yan Feng, Martina L. Veigl, Daniel Lindner, David Danielpour, Lihong Yin. Transcriptome and metabolome reprogramming in EGFR-mutant NSCLC early adaptive drug-escape against erlotinib. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1835. doi:10.1158/1538-7445.AM2014-1835

Bacterial whole-cell biocatalysts by surface display of enzymes: toward industrial application.

Despite the first report on the bacterial display of a recombinant peptide appeared almost 30 years ago, industrial application of cells with surface-displayed enzymes is still limited. To display an enzyme on the surface of a living cell bears several advantages. First of all, neither the substrate nor the product of the enzymatic reaction needs to cross a membrane barrier. Second, the enzyme being linked to the cell can be separated from the reaction mixture and hence the product by simple centrifugation. Transfer to a new substrate preparation results in multiple cycles of enzymatic conversion. Finally, the anchoring in a matrix, in this case, the cell envelope stabilizes the enzyme and makes it less accessible to proteolytic degradation and material adsorption resulting in continuous higher activities. These advantages in common need to balance some disadvantages before this application can be taken into account for industrial processes, e.g., the exclusion of the enzyme from the cellular metabolome and hence from redox factors or other co-factors that need to be supplied. Therefore, this digest describes the different systems in Gram-positive and Gram-negative bacteria that have been used for the surface display of enzymes so far and focuses on examples among these which are suitable for industrial purposes or for the production of valuable resources, not least in order to encourage a broader application of whole-cell biocatalysts with surface-displayed enzymes.

A metabolic map of hematopoietic stem cells

Background A general problem in biology is whether different types of cells in the same tissue are metabolically different from each other, and whether such differences are important for cellular function. Experiments that can comprehensively measure the cellular metabolome typically require millions of cultured cells and cannot be used with small numbers of rare cells freshly isolated from tissues. In particular, hematopoietic stem cells (HSCs), the blood forming stem cells of the bone marrow, have been intensively studied for decades but their metabolic composition is largely unknown. Results We have developed a method to measure metabolites in small numbers of HSCs. The HSC isolation and mass spectrometry methods have been optimized for maintenance of the metabolome during purification, sensitivity and robustness. About 50 metabolites can be quantified from 10,000 HSCs, covering a wide spectrum of the cellular metabolome. Several metabolic differences exist between HSCs and other bone marrow cells, including restricted progenitors. I am investigating the role of these metabolic adaptations in HSCs. Conclusion

Ion Mobility Derived Collision Cross Sections to Support Metabolomics Applications

Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD < 5% for 99%). We also determined the reproducibility of CCS measurements in various biological matrixes including urine, plasma, platelets, and red blood cells using ultra performance liquid chromatography (UPLC) coupled with TW-IM-MS. The mean RSD was < 2% for 97% of the CCS values, compared to 80% of retention times. Finally, as proof of concept, we used UPLC–TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches.

Potential Applications and Development of Cell Metabolomics in Natural Products

Natural products play a vital role in drug discovery. Metabolomics, the systematic analysis of small molecular metabolites in biological systems, has been increasingly applied to discovering biomarkers, identifying perturbed pathways and discovering new drugs. It enables the examination and identification of endogenous biochemical reaction products occurring within a living cell. Cell metabolomics has many potential applications and advantages to currently used methods at various aspects in the natural product era. This review covers recent developments in the use of metabolomics to characterize cellular metabolome and interpret them in terms of metabolic changes taking place in a wide range of situations, especially, highlights the key roles of the endogenous small-molecule metabolites in the natural product field.

Cell Metabolomics

Abstract Metabolomics technologies enable the examination and identification of endogenous biochemical reaction products, revealing information on the precise metabolic pathways and processes within a living cell. Metabolism is either directly or indirectly involved with every aspect of cell function, and metabolomics is thus believed to be a reflection of the phenotype of any cell. Metabolomics analysis of cells has many potential applications and advantages compared to currently used methods in the postgenomics era. Cell metabolomics is an emerging field that addresses fundamental biological questions and allows one to observe metabolic phenomena in cells. Cell metabolomics consists of four sequential steps: (a) sample preparation and extraction, (b) metabolic profiles of low-weight metabolites based on MS or NMR spectroscopy techniques, (c) pattern recognition approaches and bioinformatics data analysis, (d) metabolites identification resulting in putative biomarkers and molecular targets. The biomarkers are eventually placed in metabolic networks to provide insight on the cellular biochemical phenomena. This article analyzes the recent developments in use of metabolomics to characterize and interpret the cellular metabolome in a wide range of pathophysiological and clinical contexts, and the putative roles of the endogenous small molecule metabolites in this new frontier of postgenomics biology and systems medicine.

Radiation-Induced Metabolome Delineates Glioblastoma and Glioblastoma Stem Cell Subtypes and Correlate With Their Relative Radiation Sensitivities

To evaluate the radiation induced intracellular and extracellular metabolic changes in the cellular metabolome of Glioblastoma (GBM) and Glioblastoma Stem Cells (GSC) and correlate the differentially regulated metabolic profiles with their relative radiation resistance/sensitivities.

Analysis of Bacterial Biofilms Using NMR-Based Metabolomics

Infectious diseases can be difficult to cure, especially if the pathogen forms a biofilm. After decades of extensive research into the morphology, physiology and genomics of biofilm formation, attention has recently been directed toward the analysis of the cellular metabolome in order to understand the transformation of a planktonic cell to a biofilm. Metabolomics can play an invaluable role in enhancing our understanding of the underlying biological processes related to the structure, formation and antibiotic resistance of biofilms. A systematic view of metabolic pathways or processes responsible for regulating this 'social structure' of microorganisms may provide critical insights into biofilm-related drug resistance and lead to novel treatments. This review will discuss the development of NMR-based metabolomics as a technology to study medically relevant biofilms. Recent advancements from case studies reviewed in this manuscript have shown the potential of metabolomics to shed light on numerous biological problems related to biofilms.

Proteome dynamics and early salt stress response of the photosynthetic organism Chlamydomonas reinhardtii

BackgroundThe cellular proteome and metabolome are underlying dynamic regulation allowing rapid adaptation to changes in the environment. System-wide analysis of these dynamics will provide novel insights into mechanisms of stress adaptation for higher photosynthetic organisms. We applied pulsed-SILAC labeling to a photosynthetic organism for the first time and we established a method to study proteome dynamics in the green alga Chlamydomonas reinhardtii, an emerging model system for plant biology. In addition, we combined the analysis of protein synthesis with metabolic profiling to study the dynamic changes of metabolism and proteome turnover under salt stress conditions.ResultsTo study de novo protein synthesis an arginine auxotroph Chlamydomonas strain was cultivated in presence of stable isotope-labeled arginine for 24 hours. From the time course experiment in 3 salt concentrations we could identify more than 2500 proteins and their H/L ratio in at least one experimental condition; for 998 protiens at least 3 ratio counts were detected in the 24 h time point (0 mM NaCl). After fractionation we could identify 3115 proteins and for 1765 of them we determined their de novo synthesis rate. Consistently with previous findings we showed that RuBisCO is among the most prominent proteins in the cell; and similar abundance and turnover for the small and large RuBisCO subunit could be calculated. The D1 protein was identified among proteins with a high synthesis rates. A global median half-life of 45 h was calculated for Chlamydomonas proteins under the chosen conditions.ConclusionTo investigate the temporal co-regulation of the proteome and metabolome, we applied salt stress to Chlamydomonas and studied the time dependent regulation of protein expression and changes in the metabolome. The main metabolic response to salt stress was observed within the amino acid metabolism. In particular, proline was up-regulated manifold and according to that an increased carbon flow within the proline biosynthetic pathway could be measured. In parallel the analysis of abundance and de novo synthesis of the corresponding enzymes revealed that metabolic rearrangements precede adjustments of protein abundance.

Strategy for choosing extraction procedures for NMR-based metabolomic analysis of mammalian cells

Metabolomic analysis of mammalian cells can be applied across multiple fields including medicine and toxicology. It requires the acquisition of reproducible, robust, reliable, and homogeneous biological data sets. Particular attention must be paid to the efficiency and reliability of the extraction procedure. Even though a number of recent studies have dealt with optimizing a particular protocol for specific matrices and analytical techniques, there is no universal method to allow the detection of the entire cellular metabolome. Here, we present a strategy for choosing extraction procedures from adherent mammalian cells for the global NMR analysis of the metabolome. After the quenching of cells, intracellular metabolites are extracted from the cells using one of the following solvent systems of varying polarities: perchloric acid, acetonitrile/water, methanol, methanol/water, and methanol/chloroform/water. The hydrophilic metabolite profiles are analysed using (1)H nuclear magnetic resonance (NMR) spectroscopy. We propose an original geometric representation of metabolites reflecting the efficiency of extraction methods. In the case of NMR-based analysis of mammalian cells, this methodology demonstrates that a higher portion of intracellular metabolites are extracted by using methanol or methanol/chloroform/water. The preferred method is evaluated in terms of biological variability for studying metabolic changes caused by the phenotype of four different human breast cancer cell lines, showing that the selected extraction procedure is a promising tool for metabolomic and metabonomic studies of mammalian cells. The strategy proposed in this paper to compare extraction procedures is applicable to NMR-based metabolomic studies of various systems.

Methyl jasmonate deficiency alters cellular metabolome, including the aminome of tomato (Solanum lycopersicum L.) fruit

Exogenous treatment with jasmonates (JA) has been shown to reduce the levels of polyamines in many plants. But the role of endogenous JA on polyamine biosynthesis or other cellular metabolites has thus far remained uninvestigated. We developed transgenic tomato (Solanum lycopersicum L.) having severely reduced methyl JA levels by silencing a fruit ripening-associated lipoxygenase (LOX), SlLoxB, using a truncated LOX gene under the control of the constitutive CaMV35S promoter. The LOX suppressed and MeJA-deficient fruits had lowered polyamine levels. Thus, these transgenic fruits were used as a plant model to evaluate the effects of reduced endogenous MeJA on cellular metabolites in ripening tomato fruits using NMR spectroscopy. During on-shelf ripening, transgenic fruits were significantly reduced in the content of 19 out of 30 metabolites examined, including Ile, Val, Ala, Thr, Asn Tyr, Glu, Gln, His, Phe, Trp, GABA, citrate, succinate, myo-inositol, unidentified compound B, nucleic acid compound Nucl1, choline, and trigonelline as compared to the wild-type azygous counterparts. A significant increase in β-glucose levels in transgenic fruits was observed at the pink stage. The transgenic fruits were equivalent to the wild type in lycopene level and chlorophyll degradation rates. Taken together, these results show that intracellular MeJA significantly regulates overall primary metabolism, especially aminome (amino acids and polyamines) of ripening fruits.

Phosphatidylinositol transfer proteins: Negotiating the regulatory interface between lipid metabolism and lipid signaling in diverse cellular processes

Phosphoinositides represent only a small percentage of the total cellular lipid pool. Yet, these molecules play crucial roles in diverse intracellular processes such as signal transduction at membrane-cytosol interface, regulation of membrane trafficking, cytoskeleton organization, nuclear events, and the permeability and transport functions of the membrane. A central principle in such lipid-mediated signaling is the appropriate coordination of these events. Such an intricate coordination demands fine spatial and temporal control of lipid metabolism and organization, and consistent mechanisms for specifically coupling these parameters to dedicated physiological processes. In that regard, recent studies have identified Sec14-like phosphatidylcholine transfer protein (PITPs) as "coincidence detectors," which spatially and temporally link the diverse aspects of the cellular lipid metabolome with phosphoinositide signaling. The integral role of PITPs in eukaryotic signal transduction design is amply demonstrated by the mammalian diseases associated with the derangements in the function of these proteins, to stress response and developmental regulation in plants, to fungal dimorphism and pathogenicity, to membrane trafficking in yeast, and higher eukaryotes. This review updates the recent advances made in the understanding of how these proteins, specifically PITPs of the Sec14-protein superfamily, operate at the molecular level and further describes how this knowledge has advanced our perception on the diverse biological functions of PITPs.