TY - JOUR AB - Glycosylphosphatidylinositol-anchored proteins (GPI-APs) are anchored at the outer phospholipid layer of eukaryotic plasma membranes exclusively by a glycolipid. GPI-APs are not only released into extracellular compartments by lipolytic cleavage. In addition, certain GPI-APs with the glycosylphosphatidylinositol anchor including their fatty acids remaining coupled to the carboxy-terminus of their protein components are also detectable in body fluids, in response to certain stimuli, such as oxidative stress, radicals or high-fat diet. As a consequence, the fatty acid moieties of GPI-APs must be shielded from access of the aqueous environment by incorporation into membranes of extracellular vesicles or into micelle-like complexes together with (lyso)phospholipids and cholesterol. The GPI-APs released from somatic cells and tissues are transferred via those complexes or EVs to somatic as well as pluripotent stem cells with metabolic consequences, such as upregulation of glycogen and lipid synthesis. From these and additional findings, the following hypotheses are developed: i) Transfer of GPI-APs via EVs or micelle-like complexes leads to the induction of new phenotypes in the daughter cells or zygotes, which are presumably not restricted to metabolism. ii) The membrane topographies transferred by the concerted action of GPI-APs and interacting components are replicated by self-organization and self-templation and remain accessible to structural changes by environmental factors. iii) Transfer from mother cells and gametes to their daughter cells and zygotes, respectively, is not restricted to DNA and genes, but also encompasses non-genetic matter, such as GPI-APs and specific membrane constituents. iv) The intergenerational transfer of membrane matter between mammalian organisms is understood as an epigenetic mechanism for phenotypic plasticity, which does not rely on modifications of DNA and histones, but is regarded as molecular mechanism for the inheritance of acquired traits, such as complex metabolic diseases. v) The missing interest in research of non-genetic matter of inheritance, which may be interpreted in the sense of Darwin's "Gemmules" or Galton's "Stirps", should be addressed in future investigations of the philosophy of science and sociology of media. AU - Müller, G. AU - Müller, T.D. C1 - 70298 C2 - 55495 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Transfer of membrane(s) matter(s)-non-genetic inheritance of (metabolic) phenotypes? JO - Front. Mol. Biosci. VL - 11 PB - Frontiers Media Sa PY - 2024 SN - 2296-889X ER - TY - JOUR AB - Ca2+ ions serve as pleiotropic second messengers in the cell, regulating several cellular processes. Mitochondria play a fundamental role in Ca2+ homeostasis since mitochondrial Ca2+ (mitCa2+) is a key regulator of oxidative metabolism and cell death. MitCa2+ uptake is mediated by the mitochondrial Ca2+ uniporter complex (MCUc) localized in the inner mitochondrial membrane (IMM). MitCa2+ uptake stimulates the activity of three key enzymes of the Krebs cycle, thereby modulating ATP production and promoting oxidative metabolism. As Paracelsus stated, "Dosis sola facit venenum,"in pathological conditions, mitCa2+ overload triggers the opening of the mitochondrial permeability transition pore (mPTP), enabling the release of apoptotic factors and ultimately leading to cell death. Excessive mitCa2+ accumulation is also associated with a pathological increase of reactive oxygen species (ROS). In this article, we review the precise regulation and the effectors of mitCa2+ in physiopathological processes. AU - D'Angelo, D.* AU - Vecellio Reane, D. AU - Raffaello, A.* C1 - 69032 C2 - 53817 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Neither too much nor too little: Mitochondrial calcium concentration as a balance between physiological and pathological conditions. JO - Front. Mol. Biosci. VL - 10 PB - Frontiers Media Sa PY - 2023 SN - 2296-889X ER - TY - JOUR AB - Methoprene-tolerant (Met) and germ cell-expressed (Gce) proteins were shown to be juvenile hormone (JH) receptors of Drosophila melanogaster with partially redundant functions. We raised the question of where the functional differentiation of paralogs comes from. Therefore, we tested Met and Gce interaction patterns with selected partners. In this study, we showed the ability of Gce and its C-terminus (GceC) to interact with 14-3-3 in the absence of JH. In contrast, Met or Met C-terminus (MetC) interactions with 14-3-3 were not observed. We also performed a detailed structural analysis of Met/Gce interactions with the nuclear receptor fushi tarazu factor-1 (Ftz-F1) ligand-binding domain. We showed that GceC comprising an Ftz-F1-binding site and full-length protein interacts with Ftz-F1. In contrast to Gce, only MetC (not full-length Met) can interact with Ftz-F1 in the absence of JH. We propose that the described differences result from the distinct tertiary structure and accessibility of binding sites in the full-length Met/Gce. Moreover, we hypothesize that each interacting partner can force disordered MetC and GceC to change the structure in a partner-specific manner. The observed interactions seem to determine the subcellular localization of Met/Gce by forcing their translocation between the nucleus and the cytoplasm, which may affect the activity of the proteins. The presented differences between Met and Gce can be crucial for their functional differentiation during D. melanogaster development and indicate Gce as a more universal and more active paralog. It is consistent with the theory indicating gce as an ancestor gene. AU - Kolonko-Adamska, M.* AU - Zawadzka-Kazimierczuk, A.* AU - Bartosińska-Marzec, P.* AU - Koźmiński, W.* AU - Popowicz, G.M. AU - Krężel, A.* AU - Ożyhar, A.* AU - Greb-Markiewicz, B.* C1 - 68339 C2 - 54755 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Interaction patterns of methoprene-tolerant and germ cell-expressed Drosophila JH receptors suggest significant differences in their functioning. JO - Front. Mol. Biosci. VL - 10 PB - Frontiers Media Sa PY - 2023 SN - 2296-889X ER - TY - JOUR AB - Both targeted and untargeted mass spectrometry-based metabolomics approaches are used to understand the metabolic processes taking place in various organisms, from prokaryotes, plants, fungi to animals and humans. Untargeted approaches allow to detect as many metabolites as possible at once, identify unexpected metabolic changes, and characterize novel metabolites in biological samples. However, the identification of metabolites and the biological interpretation of such large and complex datasets remain challenging. One approach to address these challenges is considering that metabolites are connected through informative relationships. Such relationships can be formalized as networks, where the nodes correspond to the metabolites or features (when there is no or only partial identification), and edges connect nodes if the corresponding metabolites are related. Several networks can be built from a single dataset (or a list of metabolites), where each network represents different relationships, such as statistical (correlated metabolites), biochemical (known or putative substrates and products of reactions), or chemical (structural similarities, ontological relations). Once these networks are built, they can subsequently be mined using algorithms from network (or graph) theory to gain insights into metabolism. For instance, we can connect metabolites based on prior knowledge on enzymatic reactions, then provide suggestions for potential metabolite identifications, or detect clusters of co-regulated metabolites. In this review, we first aim at settling a nomenclature and formalism to avoid confusion when referring to different networks used in the field of metabolomics. Then, we present the state of the art of network-based methods for mass spectrometry-based metabolomics data analysis, as well as future developments expected in this area. We cover the use of networks applications using biochemical reactions, mass spectrometry features, chemical structural similarities, and correlations between metabolites. We also describe the application of knowledge networks such as metabolic reaction networks. Finally, we discuss the possibility of combining different networks to analyze and interpret them simultaneously. AU - Amara, A.* AU - Frainay, C.* AU - Jourdan, F.* AU - Naake, T.* AU - Neumann, S.* AU - Novoa-del-Toro, E.M.* AU - Salek, R.M.* AU - Salzer, L. AU - Scharfenberg, S.* AU - Witting, M. C1 - 64750 C2 - 52435 TI - Networks and graphs discovery in metabolomics data analysis and interpretation. JO - Front. Mol. Biosci. VL - 9 PY - 2022 SN - 2296-889X ER - TY - JOUR AB - Type 1 diabetes is a chronic disease of the pancreas characterized by the loss of insulin-producing beta cells. Access to human pancreas samples for research purposes has been historically limited, restricting pathological analyses to animal models. However, intrinsic differences between animals and humans have made clinical translation very challenging. Recently, human pancreas samples have become available through several biobanks worldwide, and this has opened numerous opportunities for scientific discovery. In addition, the use of new imaging technologies has unraveled many mysteries of the human pancreas not merely in the presence of disease, but also in physiological conditions. Nowadays, multiplex immunofluorescence protocols as well as sophisticated image analysis tools can be employed. Here, we described the use of QuPath—an open-source platform for image analysis—for the investigation of human pancreas samples. We demonstrate that QuPath can be adequately used to analyze whole-slide images with the aim of identifying the islets of Langerhans and define their cellular composition as well as other basic morphological characteristics. In addition, we show that QuPath can identify immune cell populations in the exocrine tissue and islets of Langerhans, accurately localizing and quantifying immune infiltrates in the pancreas. Therefore, we present a tool and analysis pipeline that allows for the accurate characterization of the human pancreas, enabling the study of the anatomical and physiological changes underlying pancreatic diseases such as type 1 diabetes. The standardization and implementation of these analysis tools is of critical importance to understand disease pathogenesis, and may be informative for the design of new therapies aimed at preserving beta cell function and halting the inflammation caused by the immune attack. AU - Apaolaza Gallegos, S.P. AU - Petropoulou, P.-I. AU - Rodriguez-Calvo, T. C1 - 62398 C2 - 50855 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Whole-slide image analysis of human pancreas samples to elucidate the immunopathogenesis of type 1 diabetes using the QuPath software. JO - Front. Mol. Biosci. VL - 8 PB - Frontiers Media Sa PY - 2021 SN - 2296-889X ER - TY - JOUR AB - Rare diseases, although individually rare, collectively affect approximately 350 million people worldwide. Currently, nearly 6,000 distinct rare disorders with a known molecular basis have been described, yet establishing a specific diagnosis based on the clinical phenotype is challenging. Increasing integration of whole exome sequencing into routine diagnostics of rare diseases is improving diagnostic rates. Nevertheless, about half of the patients do not receive a genetic diagnosis due to the challenges of variant detection and interpretation. During the last years, RNA sequencing is increasingly used as a complementary diagnostic tool providing functional data. Initially, arbitrary thresholds have been applied to call aberrant expression, aberrant splicing, and mono-allelic expression. With the application of RNA sequencing to search for the molecular diagnosis, the implementation of robust statistical models on normalized read counts allowed for the detection of significant outliers corrected for multiple testing. More recently, machine learning methods have been developed to improve the normalization of RNA sequencing read count data by taking confounders into account. Together the methods have increased the power and sensitivity of detection and interpretation of pathogenic variants, leading to diagnostic rates of 10–35% in rare diseases. In this review, we provide an overview of the methods used for RNA sequencing and illustrate how these can improve the diagnostic yield of rare diseases. AU - Schlieben, L.D. AU - Prokisch, H. AU - Yépez, V.A.* C1 - 62302 C2 - 50603 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - How machine learning and statistical models advance molecular diagnostics of rare disorders via analysis of RNA sequencing data. JO - Front. Mol. Biosci. VL - 8 PB - Frontiers Media Sa PY - 2021 SN - 2296-889X ER - TY - JOUR AB - The early-life metabolome of the intestinal tract is dynamically influenced by colonization of gut microbiota which in turn is affected by nutrition, i.e. breast milk or formula. A detailed examination of fecal metabolites was performed to investigate the effect of probiotics in formula compared to control formula and breast milk within the first months of life in healthy neonates. A broad metabolomics approach was conceptualized to describe fecal polar and semi-polar metabolites affected by feeding type within the first year of life. Fecal metabolomes were clearly distinct between formula- and breastfed infants, mainly originating from diet and microbial metabolism. Unsaturated fatty acids and human milk oligosaccharides were increased in breastfed, whereas Maillard products were found in feces of formula-fed children. Altered microbial metabolism was represented by bile acids and aromatic amino acid metabolites. Elevated levels of sulfated bile acids were detected in stool samples of breastfed infants, whereas secondary bile acids were increased in formula-fed infants. Microbial co-metabolism was supported by significant correlation between chenodeoxycholic or lithocholic acid and members of Clostridia. Fecal metabolites showed strong inter- and intra-individual behavior with features uniquely present in certain infants and at specific time points. Nevertheless, metabolite profiles converged at the end of the first year, coinciding with solid food introduction. AU - Sillner, N. AU - Walker, A. AU - Lucio, M. AU - Maier, T.V. AU - Bazanella, M.* AU - Rychlik, M.* AU - Haller, D.* AU - Schmitt-Kopplin, P. C1 - 62266 C2 - 50758 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Longitudinal profiles of dietary and microbial metabolites in formula- and breastfed infants. JO - Front. Mol. Biosci. VL - 8 PB - Frontiers Media Sa PY - 2021 SN - 2296-889X ER - TY - JOUR AB - Metabolism is one of the attributes of life and supplies energy and building blocks to organisms. Therefore, understanding metabolism is crucial for the understanding of complex biological phenomena. Despite having been in the focus of research for centuries, our picture of metabolism is still incomplete. Metabolomics, the systematic analysis of all small molecules in a biological system, aims to close this gap. In order to facilitate such investigations a blueprint of the metabolic network is required. Recently, several metabolic network reconstructions for the model organism Caenorhabditis elegans have been published, each having unique features. We have established the WormJam Community to merge and reconcile these (and other unpublished models) into a single consensus metabolic reconstruction. In a series of workshops and annotation seminars this model was refined with manual correction of incorrect assignments, metabolite structure and identifier curation as well as addition of new pathways. The WormJam consensus metabolic reconstruction represents a rich data source not only for in silico network-based approaches like flux balance analysis, but also for metabolomics, as it includes a database of metabolites present in C. elegans, which can be used for annotation. Here we present the process of model merging, correction and curation and give a detailed overview of the model. In the future it is intended to expand the model toward different tissues and put special emphasizes on lipid metabolism and secondary metabolism including ascaroside metabolism in accordance to their central role in C. elegans physiology. AU - Witting, M. AU - Hastings, J.* AU - Rodriguez, N.* AU - Joshi, C.J.* AU - Hattwell, J.P.N.* AU - Ebert, P.R.* AU - van Weeghel, M.* AU - Gao, A.W.* AU - Wakelam, M.J.O.* AU - Houtkooper, R.H.* AU - Mains, A.* AU - Novère, N.L.* AU - Sadykoff, S.* AU - Schroeder, F.* AU - Lewis, N.E.* AU - Schirra, H.J.* AU - Kaleta, C.* AU - Casanueva, O.* C1 - 54863 C2 - 45888 CY - Avenue Du Tribunal Federal 34, Lausanne, Ch-1015, Switzerland TI - Modeling meets metabolomics— the WormJam consensus model as basis for metabolic studies in the model organism Caenorhabditis elegans. JO - Front. Mol. Biosci. VL - 5 PB - Frontiers Media Sa PY - 2018 SN - 2296-889X ER - TY - JOUR AB - Intrinsically disordered linkers provide multi-domain proteins with degrees of conformational freedom that are often essential for function. These highly dynamic assemblies represent a significant fraction of all proteomes, and deciphering the physical basis of their interactions represents a considerable challenge. Here we describe the difficulties associated with mapping the large-scale domain dynamics and describe two recent examples where solution state methods, in particular NMR spectroscopy, are used to investigate conformational exchange on very different timescales. AU - Delaforge, E.* AU - Milles, S.* AU - Huang, J.R.* AU - Bouvier, D.* AU - Jensen, M.R.* AU - Sattler, M. AU - Hart, D.J.* AU - Blackledge, M.J.* C1 - 49577 C2 - 40833 SP - 54 TI - Investigating the role of large-scale domain dynamics in protein-protein interactions. JO - Front. Mol. Biosci. VL - 3 PY - 2016 SN - 2296-889X ER -