CXCL12 and MYC control energy metabolism to support adaptive responses after kidney injury.

Kidney injury is a common complication of severe disease. Here, we report that injuries of the zebrafish embryonal kidney are rapidly repaired by a migratory response in 2-, but not in 1-day-old embryos. Gene expression profiles between these two developmental stages identify cxcl12a and myca as candidates involved in the repair process. Zebrafish embryos with cxcl12a, cxcr4b, or myca deficiency display repair abnormalities, confirming their role in response to injury. In mice with a kidney-specific knockout, Cxcl12 and Myc gene deletions suppress mitochondrial metabolism and glycolysis, and delay the recovery after ischemia/reperfusion injury. Probing these observations in zebrafish reveal that inhibition of glycolysis slows fast migrating cells and delays the repair after injury, but does not affect the slow cell movements during kidney development. Our findings demonstrate that Cxcl12 and Myc facilitate glycolysis to promote fast migratory responses during development and repair, and potentially also during tumor invasion and metastasis.

Constitutional SAMD9L mutations cause familial myelodysplastic syndrome and transient monosomy 7.

Familial myelodysplastic syndromes arise from haploinsufficiency of genes involved in hematopoiesis and are primarily associated with early-onset disease. Here we describe a familial syndrome in seven patients from four unrelated pedigrees presenting with myelodysplastic syndrome and loss of chromosome 7/7q. Their median age at diagnosis was 2.1 years (range, 1-42). All patients presented with thrombocytopenia with or without additional cytopenias and a hypocellular marrow without an increase of blasts. Genomic studies identified constitutional mutations (p.H880Q, p.R986H, p.R986C and p.V1512M) in the SAMD9L gene on 7q21, with decreased allele frequency in hematopoiesis. The non-random loss of mutated SAMD9L alleles was attained via monosomy 7, deletion 7q, UPD7q, or acquired truncating SAMD9L variants p.R1188X and p.S1317RfsX21. Incomplete penetrance was noted in 30% (3/10) of mutation carriers. Long-term observation revealed divergent outcomes with either progression to leukemia and/or accumulation of driver mutations (n=2), persistent monosomy 7 (n=4), and transient monosomy 7 followed by spontaneous recovery with SAMD9L-wildtype UPD7q (n=2). Dysmorphic features or neurological symptoms were absent in our patients, pointing to the notion that myelodysplasia with monosomy 7 can be a sole manifestation of SAMD9L disease. Collectively, our results define a new subtype of familial myelodysplastic syndrome and provide an explanation for the phenomenon of transient monosomy 7. Registered at: www.clinicaltrials.gov; #NCT00047268.

Epithelioid hemangioendotheliomas of the liver and lung in children and adolescents.

Epithelioid hemangioendothelioma (EHE) is a rare, vascular sarcoma. Visceral forms arise in the liver/ lungs. We review the clinical and molecular phenotype of pediatric visceral EHE based on the case of a 9-year-old male child with EHE of the liver/lungs. His tumor expressed the EHE-specific fusion oncogene WWTR1-CAMTA1. Molecular characterization revealed a low somatic mutation rate and activated interferon signaling, angiogenesis regulation, and blood vessel remodeling. After polychemotherapy and resection of lung tumors, residual disease remained stable on oral lenalidomide. Literature review identified another 24 children with EHE of the liver/lungs. Most presented with multifocal, systemic disease. Only those who underwent complete resection achieved complete remission. Four children experienced rapid progression and died. In six children, disease remained stable for years without therapy. Two patients died from progressive EHE 21 and 24 years after first diagnosis. Natural evolution of pediatric visceral EHE is variable, and long-term prognosis remains unclear.

Visceral adipose tissue but not subcutaneous adipose tissue is associated with urine and serum metabolites.

Obesity is a complex multifactorial phenotype that influences several metabolic pathways. Yet, few studies have examined the relations of different body fat compartments to urinary and serum metabolites. Anthropometric phenotypes (visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), the ratio between VAT and SAT (VSR), body mass index (BMI), waist circumference (WC)) and urinary and serum metabolite concentrations measured by nuclear magnetic resonance spectroscopy were measured in a population-based sample of 228 healthy adults. Multivariable linear and logistic regression models, corrected for multiple testing using the false discovery rate, were used to associate anthropometric phenotypes with metabolites. We adjusted for potential confounding variables: age, sex, smoking, physical activity, menopausal status, estimated glomerular filtration rate (eGFR), urinary glucose, and fasting status. In a fully adjusted logistic regression model dichotomized for the absence or presence of quantifiable metabolite amounts, VAT, BMI and WC were inversely related to urinary choline (ß = -0.18, p = 2.73*10-3), glycolic acid (ß = -0.20, 0.02), and guanidinoacetic acid (ß = -0.12, p = 0.04), and positively related to ethanolamine (ß = 0.18, p = 0.02) and dimethylamine (ß = 0.32, p = 0.02). BMI and WC were additionally inversely related to urinary glutamine and lactic acid. Moreover, WC was inversely associated with the detection of serine. VAT, but none of the other anthropometric parameters, was related to serum essential amino acids, such as valine, isoleucine, and phenylalanine among men. Compared to other adiposity measures, VAT demonstrated the strongest and most significant relations to urinary and serum metabolites. The distinct relations of VAT, SAT, VSR, BMI, and WC to metabolites emphasize the importance of accurately differentiating between body fat compartments when evaluating the potential role of metabolic regulation in the development of obesity-related diseases, such as insulin resistance, type 2 diabetes, and cardiovascular disease.

Proteolysis-a characteristic of tumor-initiating cells in murine metastatic breast cancer.

Tumor initiating cells (TICs) have been identified and functionally characterized in hematological malignancies as well as in solid tumors such as breast cancer. In addition to their high tumor-initiating potential, TICs are founder cells for metastasis formation and are involved in chemotherapy resistance. In this study we explored molecular pathways which enable this tumor initiating potential for a cancer cell subset of the transgenic MMTV-PyMT mouse model for metastasizing breast cancer. The cell population, characterized by the marker profile CD24+CD90+CD45-, showed a high tumorigenicity compared to non-CD24+CD90+CD45- cancer cells in colony formation assays, as well as upon orthotopic transplantation into the mammary fat pad of mice. In addition, these orthotopically grown CD24+CD90+CD45- TICs metastasized to the lungs. The transcriptome of TICs freshly isolated from primary tumors by cell sorting was compared with that of sorted non-CD24+CD90+CD45- cancer cells by RNA-seq. In addition to more established TIC signatures, such as epithelial-to-mesenchymal transition or mitogen signaling, an upregulated gene set comprising several classes of proteolytic enzymes was uncovered in the TICs. Accordingly, TICs showed high intra- and extracellular proteolytic activity. Application of a broad range of protease inhibitors to TICs in a colony formation assay reduced anchorage independent growth and had an impact on colony morphology in 3D cell culture assays. We conclude that CD24+CD90+CD45- cells of the MMTV- PyMT mouse model possess an upregulated proteolytic signature which could very well represent a functional hallmark of metastatic TICs from mammary carcinomas.

Data Normalization of (1)H NMR Metabolite Fingerprinting Data Sets in the Presence of Unbalanced Metabolite Regulation.

Data normalization is an essential step in NMR-based metabolomics. Conducted properly, it improves data quality and removes unwanted biases. The choice of the appropriate normalization method is critical and depends on the inherent properties of the data set in question. In particular, the presence of unbalanced metabolic regulation, where the different specimens and cohorts under investigation do not contain approximately equal shares of up- and down-regulated features, may strongly influence data normalization. Here, we demonstrate the suitability of the Shapiro-Wilk test to detect such unbalanced regulation. Next, employing a Latin-square design consisting of eight metabolites spiked into a urine specimen at eight different known concentrations, we show that commonly used normalization and scaling methods fail to retrieve true metabolite concentrations in the presence of increasing amounts of glucose added to simulate unbalanced regulation. However, by learning the normalization parameters on a subset of nonregulated features only, Linear Baseline Normalization, Probabilistic Quotient Normalization, and Variance Stabilization Normalization were found to account well for different dilutions of the samples without distorting the true spike-in levels even in the presence of marked unbalanced metabolic regulation. Finally, the methods described were applied successfully to a real world example of unbalanced regulation, namely, a set of plasma specimens collected from patients with and without acute kidney injury after cardiac surgery with cardiopulmonary bypass use.

Identification of Plasma Metabolites Prognostic of Acute Kidney Injury after Cardiac Surgery with Cardiopulmonary Bypass.

Acute kidney injury (AKI) is a frequent complication after cardiopulmonary bypass, but early detection of postoperative AKI remains challenging. Protein biomarkers predict AKI excellently in homogeneous cohorts but are less reliable in patients suffering from various comorbidities. We employed nuclear magnetic resonance spectroscopy in a prospective study of 85 adult cardiac surgery patients to identify metabolites prognostic of AKI in plasma specimens collected 24 h after surgery. Postoperative AKI of stages 1-3, as defined by the Acute Kidney Injury Network (AKIN), developed in 33 cases. A random forests classifier trained on the NMR spectra prognosticated AKI across all stages, with an average accuracy of 80 ± 0.9% and an area under the receiver operating characteristic curve of 0.87 ± 0.01. Prognostications were based, on average, on 24 ± 2.8 spectral features. Among the set of discriminative ions and molecules identified were Mg(2+), lactate, and the glucuronide conjugate of propofol. Using creatinine, Mg(2+), and lactate levels to derive an AKIN index score, we found AKIN 1 disease to be largely indistinguishable from AKIN 0, in concordance with the rather mild nature of AKIN 1 disease.

Diclofenac inhibits lactate formation and efficiently counteracts local immune suppression in a murine glioma model.

Lactate formation in highly proliferative tumors such as malignant gliomas is associated with poor survival and contributes to the suppression of local immunity. Here, we report that diclofenac used at nontoxic concentrations significantly decreased lactate production in murine glioma cells and inhibited the expression of lactate dehydrogenase-A in vitro. Lactate reduction was accompanied by a dose-dependent inhibition of cell growth and a cell cycle arrest at the G2/M checkpoint. In the presence of diclofenac, murine bone marrow-derived dendritic cells (DCs) showed enhanced IL-12, but decreased IL-10 secretion on Toll-like receptor stimulation with R848 that correlated with reduced lactate levels in the glioma cell coculture and a blockade of signal transducers and activators of transcription 3 phosphorylation. In vivo, diclofenac treatment diminished intratumoral lactate levels and resulted in a significant delay of glioma growth. Ex vivo analyses revealed that tumor-infiltrating DCs regained their capacity to produce IL-12 on R848 stimulation. Moreover, diclofenac reduced the number of tumor-infiltrating regulatory T cells and impaired the upregulation of the Treg activation marker CD25. Nevertheless, a single intratumoral injection of R848 combined with diclofenac failed to induce an additional survival advantage in glioma-bearing mice. Further analyses illustrated that the presence of diclofenac during T-cell activation compromised INF-γ production and T-cell proliferation, indicating that immunotherapeutic approaches have to be carefully timed when combined with diclofenac. In summary, diclofenac appears as an attractive agent for targeting lactate production and counteracting local immune suppression in malignant gliomas.

Genetics and the history of the Samaritans: Y-chromosomal microsatellites and genetic affinity between Samaritans and Cohanim.

The Samaritans are a group of some 750 indigenous Middle Eastern people, about half of whom live in Holon, a suburb of Tel Aviv, and the other half near Nablus. The Samaritan population is believed to have numbered more than a million in late Roman times but less than 150 in 1917. The ancestry of the Samaritans has been subject to controversy from late Biblical times to the present. In this study, liquid chromatography/electrospray ionization/quadrupole ion trap mass spectrometry was used to allelotype 13 Y-chromosomal and 15 autosomal microsatellites in a sample of 12 Samaritans chosen to have as low a level of relationship as possible, and 461 Jews and non-Jews. Estimation of genetic distances between the Samaritans and seven Jewish and three non-Jewish populations from Israel, as well as populations from Africa, Pakistan, Turkey, and Europe, revealed that the Samaritans were closely related to Cohanim. This result supports the position of the Samaritans that they are descendants from the tribes of Israel dating to before the Assyrian exile in 722-720 BCE. In concordance with previously published single-nucleotide polymorphism haplotypes, each Samaritan family, with the exception of the Samaritan Cohen lineage, was observed to carry a distinctive Y-chromosome short tandem repeat haplotype that was not more than one mutation removed from the six-marker Cohen modal haplotype.

Performance evaluation of algorithms for the classification of metabolic 1H NMR fingerprints.

Nontargeted metabolite fingerprinting is increasingly applied to biomedical classification. The choice of classification algorithm may have a considerable impact on outcome. In this study, employing nested cross-validation for assessing predictive performance, six binary classification algorithms in combination with different strategies for data-driven feature selection were systematically compared on five data sets of urine, serum, plasma, and milk one-dimensional fingerprints obtained by proton nuclear magnetic resonance (NMR) spectroscopy. Support Vector Machines and Random Forests combined with t-score-based feature filtering performed well on most data sets, whereas the performance of the other tested methods varied between data sets.

State-of-the art data normalization methods improve NMR-based metabolomic analysis.

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0350-z) contains supplementary material, which is available to authorized users.

PROCOS: computational analysis of protein-protein complexes.

One of the main challenges in protein-protein docking is a meaningful evaluation of the many putative solutions. Here we present a program (PROCOS) that calculates a probability-like measure to be native for a given complex. In contrast to scores often used for analyzing complex structures, the calculated probabilities offer the advantage of providing a fixed range of expected values. This will allow, in principle, the comparison of models corresponding to different targets that were solved with the same algorithm. Judgments are based on distributions of properties derived from a large database of native and false complexes. For complex analysis PROCOS uses these property distributions of native and false complexes together with a support vector machine (SVM). PROCOS was compared to the established scoring schemes of ZRANK and DFIRE. Employing a set of experimentally solved native complexes, high probability values above 50% were obtained for 90% of these structures. Next, the performance of PROCOS was tested on the 40 binary targets of the Dockground decoy set, on 14 targets of the RosettaDock decoy set and on 9 targets that participated in the CAPRI scoring evaluation. Again the advantage of using a probability-based scoring system becomes apparent and a reasonable number of near native complexes was found within the top ranked complexes. In conclusion, a novel fully automated method is presented that allows the reliable evaluation of protein-protein complexes.