Generating Heterokaryotic Cells via Bacterial Cell-Cell Fusion.

Fusion of cells is an important and common biological process that leads to the mixing of cellular contents and the formation of multinuclear cells. Cell fusion occurs when distinct membranes are brought into proximity of one another and merge to become one. Fusion holds promise for biotechnological innovations, for instance, for the discovery of urgently needed new antibiotics. Here, we used antibiotic-producing bacteria that can proliferate without their cell wall as a model to investigate cell-cell fusion. We found that fusion between genetically distinct cells yields heterokaryons that are viable, contain multiple selection markers, and show increased antimicrobial activity. The rate of fusion induced using physical and chemical methods was dependent on membrane fluidity, which is related to lipid composition as a function of cellular age. Finally, by using an innovative system of synthetic membrane-associated lipopeptides, we achieved targeted fusion between distinctly marked cells to further enhance fusion efficiency. These results provide a molecular handle to understand and control cell-cell fusion, which can be used in the future for the discovery of new drugs. IMPORTANCE Cell-cell fusion is instrumental in introducing different sets of genes in the same environment, which subsequently leads to diversity. There is need for new protocols to fuse cells of different types together for biotechnological applications like drug discovery. We present here wall-deficient cells as a platform for the same. We identify the fluidity of the membrane as an important characteristic for the process of fusion. We demonstrate a cell-specific approach for fusion using synthetically designed peptides yielding cells with modified antibiotic production profiles. Overall, wall-deficient cells can be a chassis for innovative metabolite production by providing an alternative method for cell-cell fusion.

Stable human regulatory T cells switch to glycolysis following TNF receptor 2 costimulation.

Following activation, conventional T (Tconv) cells undergo an mTOR-driven glycolytic switch. Regulatory T (Treg) cells reportedly repress the mTOR pathway and avoid glycolysis. However, here we demonstrate that human thymus-derived Treg (tTreg) cells can become glycolytic in response to tumour necrosis factor receptor 2 (TNFR2) costimulation. This costimulus increases proliferation and induces a glycolytic switch in CD3-activated tTreg cells, but not in Tconv cells. Glycolysis in CD3-TNFR2-activated tTreg cells is driven by PI3-kinase-mTOR signalling and supports tTreg cell identity and suppressive function. In contrast to glycolytic Tconv cells, glycolytic tTreg cells do not show net lactate secretion and shuttle glucose-derived carbon into the tricarboxylic acid cycle. Ex vivo characterization of blood-derived TNFR2hiCD4+CD25hiCD127lo effector T cells, which were FOXP3+IKZF2+, revealed an increase in glucose consumption and intracellular lactate levels, thus identifying them as glycolytic tTreg cells. Our study links TNFR2 costimulation in human tTreg cells to metabolic remodelling, providing an additional avenue for drug targeting.

Zebrafish Larvae Are a Suitable Model to Investigate the Metabolic Phenotype of Drug-Induced Renal Tubular Injury.

Prevention and treatment of drug-induced renal injury (DIRI) rely on the availability of sensitive and specific biomarkers of early kidney injury and predictive animal models of human pathophysiology. This study aimed to evaluate the potential of zebrafish larvae as translational model in metabolic profiling of DIRI. Zebrafish larvae were exposed to the lethal concentration for 10% of the larvae (LC10) or ½ LC10 of gentamicin, paracetamol and tenofovir as tenofovir disoproxil fumarate (TDF) and tenofovir (TFV). Metabolites were extracted from whole larvae and analyzed by liquid chromatography-mass spectrometry. Principal component analysis showed that drug exposition to the LC10 of paracetamol, TFV, and TDF was the main source of the variance of the data. To identify the metabolites responsible for the toxic effects of the drugs, partial least squares discriminant analyses were built between the LC10 and ½ LC10 for each drug. Features with variable importance in projection> 1.0 were selected and Venn diagrams were built to differentiate between the common and drug specific metabolites of DIRI. Creatine, tyrosine, glutamine, guanosine, hypoxanthine were identified as common metabolites, adenosine and tryptophan as paracetamol-specific and xanthine and oxidized glutathione as tenofovir-specific. Those metabolic changes can be associated with alterations in energy metabolism, xenobiotic detoxification and protein catabolism, all described in the human pathophysiology of DIRI. Thus, zebrafish proved to be a suitable model to characterize the metabolic changes associated with DIRI. This information can be useful to early diagnose DIRI and to improve our knowledge on the mechanisms of DIRI.

Metabolic liver inflammation in obesity does not robustly decrease hepatic and circulating CETP.

BACKGROUND AND AIMS: We recently showed that plasma cholesteryl ester transfer protein (CETP) is mainly derived from VSIG4-positive Kupffer cells. Activation of these cells by the bacterial endotoxin lipopolysaccharide (LPS) strongly decreases CETP expression. As Kupffer cell activation plays a detrimental role in the progression of non-alcoholic fatty liver disease (NAFLD), we aimed to study if metabolic liver inflammation is also associated with a decrease in hepatic and circulating CETP. METHODS: We collected plasma and liver biopsy samples at various stages of NAFLD from 93 obese individuals who underwent bariatric surgery. Liver lobular inflammation was histologically determined, and liver CETP expression, CETP positive cells, circulating CETP concentrations, and liver VSIG4 expression were quantified. RESULTS: Mean (SD) plasma CETP concentration was 2.68 (0.89) µg/mL. In the presence of liver inflammation, compared to the absence of pathology, the difference in hepatic CETP expression was -0.03 arbitrary units (95% CI -0.26, 0.20), the difference in number of hepatic CETP positive cells (range 11-140 per mm2) was -20.0 per mm2 (95% CI -41.6, 1.9), and the difference in plasma CETP was -0.35 µg/mL (95% CI -0.80, 0.10). Hepatic VSIG4 expression was not associated with liver inflammation (0.00; 95% CI -0.15, 0.15). CONCLUSIONS: We found no strong evidence for a strong negative association between metabolic liver inflammation and CETP-related outcomes in obese individuals, although we observed consistent trends. These data indicate that metabolic liver inflammation does not mimic the strong effects of LPS on the hepatic expression and production of CETP by Kupffer cells.

An automated RP-SCX solid-phase extraction procedure for urinary peptidomics biomarker discovery studies.

Urine represents the most easily obtainable body fluid and consequently one of the most common samples in clinical chemistry. The majority of pathological changes in human organs may well be reflected in urine. In this way, urine analysis can aid in disease diagnosis, treatment monitoring, and prognosis. Currently, the most commonly used method for identification of new urine biomarkers involves centrifugation of the urine sample to collect either the soluble urine proteins or the urinary exosomes followed by 1 or 2 protein purification and separation steps before visualization and finally identification of potential biomarkers, usually by mass spectrometry. Here we present a generally applicable, rapid, and robust method for screening large number of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery. The method combines online sample pretreatment with a well-established mass spectrometric technique. Native peptides are extracted from urine samples on a miniaturized reverse-phase-strong cation exchange cartridge system. As the proper identification of native peptides often requires combination of data acquired on different mass analyzers, we have aimed at a procedure providing us with sufficient material to identify and characterize the differentially expressed markers.

Fibrinogen alpha chain O-glycopeptides as possible markers of urinary tract infection.

Urinary tract infection (UTI) is the most common bacterial infection leading to substantial morbidity and considerable health care expenditures across all ages. Here we present an exploratory UPLC-MS study of human urine in the context of febrile, complicated urinary tract infection aimed to reveal and identify possible markers of a host response on infection. A UPLC-MS based workflow, taking advantage of Ultra High Resolution (UHR) Qq-ToF-MS, and multivariate data handling were applied to a carefully selected group of 39 subjects with culture-confirmed febrile Escherichia coli UTI. Using a combination of unsupervised and supervised multivariate modeling we have pinpointed a number of peptides specific for UTI. An unequivocal structural identification of these peptides, as O-glycosylated fragments of the human fibrinogen alpha 1 chain, required MS2 and MS3 experiments on two different MS platforms: ESI-UHR-Qq-ToF and ESI-ion trap, a blast search and, finally, confirmation was achieved by matching experimental tandem mass spectra with those of custom synthesized candidate-peptides. In conclusion, exploiting non-targeted UPLC-MS based approach for the investigation of UTI related changes in urine, we have identified and structurally characterized unique O-glycopeptides, which are, to our knowledge, the first demonstration of O-glycosylation of human fibrinogen alpha 1-chain.

The feasibility of MS and advanced data processing for monitoring Schistosoma mansoni infection.

PURPOSE: Sensitive diagnosis, monitoring of disease progression and the evaluation of chemotherapeutic interventions are of prime importance for the improvement of control and prevention strategies for Schistosomiasis. The aim of the present study was to identify novel markers of Schistosoma mansoni infection and disease using urine samples from a large cohort from an area endemic for S. mansoni. EXPERIMENTAL DESIGN: Urine samples were collected and processed on an automated sample clean-up and fractionation system combining strong cation exchange and reversed phase, and analyzed by MS (MALDI ToF MS). The ClinPro Tools(™) (CPT) software and the Discrete Wavelet Transformation-Support Vector Machine (DWT-SVM) procedure were used for classification and statistical analysis. RESULTS: We observed a large difference in urinary peptide profiles between children and adults but classification based on infection was possible only for children. Here, in the external validation data set, 93% of the infected children were classified correctly with DWT-SVM (versus 76% for CPT). In addition 91% of low-infected children were classified correctly using DWT-SVM (versus 85% for CPT). The discriminating peptides were identified as fragments of collagen 1A1 and 1A3, and uromodulin. CONCLUSIONS AND CLINICAL RELEVANCE: In conclusion, we provide the usefulness of a peptidomics profiling approach combined with DWT-SVM in the monitoring of S. mansoni infection.

Improving mass measurement accuracy in mass spectrometry based proteomics by combining open source tools for chromatographic alignment and internal calibration.

Accurate mass determination enhances peptide identification in mass spectrometry based proteomics. We here describe the combination of two previously published open source software tools to improve mass measurement accuracy in Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS). The first program, msalign, aligns one MS/MS dataset with one FTICRMS dataset. The second software, recal2, uses peptides identified from the MS/MS data for automated internal calibration of the FTICR spectra, resulting in sub-ppm mass measurement errors.

Novel automated biomarker discovery work flow for urinary peptidomics.

BACKGROUND: Urine is potentially a rich source of peptide biomarkers, but reproducible, high-throughput peptidomic analysis is often hampered by the inherent variability in factors such as pH and salt concentration. Our goal was to develop a generally applicable, rapid, and robust method for screening large numbers of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery. METHODS: Peptide samples were trapped, desalted, pH-normalized, and fractionated on a miniaturized automatic reverse-phase strong cation exchange (RP-SCX) cartridge system. We analyzed eluted peptides using MALDI-TOF, Fourier transform ion cyclotron resonance, and liquid chromatography-iontrap mass spectrometry. We determined qualitative and quantitative reproducibility of the system and robustness of the method using BSA digests and urine samples, and we used a selected set of urine samples from Schistosoma haematobium-infected individuals to evaluate clinical applicability. RESULTS: The automated RP-SCX sample cleanup and fractionation system exhibits a high qualitative and quantitative reproducibility, with both BSA standards and urine samples. Because of the relatively high cartridge binding capacity (1-2 mL urine), eluted peptides can be measured with high sensitivity using multiple mass spectrometric techniques. As proof of principle, hemoglobin-derived peptides were identified in urine samples from S. haematobium-infected individuals, even when the microhematuria test was negative. CONCLUSIONS: We present a practical, step-by-step method for screening and identification of urinary peptides. Alongside the analytical method evaluation on standard samples, we demonstrate its feasibility with actual clinical material.

Amino acid profiling in urine by capillary zone electrophoresis - mass spectrometry.

Analysis of amino acid profiles in urine and plasma is an essential part of modern clinical diagnostic routine. Here we present an approach for the analysis of amino acids in urine by capillary electrophoresis/time-of-flight (TOF) mass spectrometry. At first a method combining improved separation, high dynamic range, and high sensitivity is presented. Detection limits in the mid nM-range are achieved through the use of pH-mediated stacking injection in combination with modern TOF detection technology. The method can be easily applied to detect differences in the amino acid profile in urine in a clinical context. Moreover, beside amino acids low molecular weight amines, peptides and related metabolites can be profiled. As a proof of concept, urine samples from patients suffering from osteoarthritis have been analyzed. Finally, the introduction of multivariate data analysis in the work flow was evaluated on spiked urine samples and real clinical material.