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Immune checkpoint blockers (ICB) have become pivotal therapies in the clinical armamentarium against metastatic melanoma (MMel). Given the frequency of immune related adverse events and increasing use of ICB, predictors of response to CTLA-4 and/or PD-1 blockade represent unmet clinical needs. Using a systems biology-based approach to an assessment of 779 paired blood and tumor markers in 37 stage III MMel patients, we analyzed association between blood immune parameters and the functional immune reactivity of tumor-infiltrating cells after ex vivo exposure to ICB. Based on this assay, we retrospectively observed, in eight cohorts enrolling 190 MMel patients treated with ipilimumab, that PD-L1 expression on peripheral T cells was prognostic on overall and progression-free survival. Moreover, detectable CD137 on circulating CD8+ T cells was associated with the disease-free status of resected stage III MMel patients after adjuvant ipilimumab + nivolumab (but not nivolumab alone). These biomarkers should be validated in prospective trials in MMel.The clinical management of metastatic melanoma requires predictors of the response to checkpoint blockade. Here, the authors use immunological assays to identify potential prognostic/predictive biomarkers in circulating blood cells and in tumor-infiltrating lymphocytes from patients with resected stage III melanoma.

PD-1 blockade represents a major therapeutic avenue in anticancer immunotherapy. Delineating mechanisms of secondary resistance to this strategy is increasingly important. Here, we identified the deleterious role of signaling via the type I interferon (IFN) receptor in tumor and antigen presenting cells, that induced the expression of nitric oxide synthase 2 (NOS2), associated with intratumor accumulation of regulatory T cells (Treg) and myeloid cells and acquired resistance to anti-PD-1 monoclonal antibody (mAb). Sustained IFNβ transcription was observed in resistant tumors, in turn inducing PD-L1 and NOS2 expression in both tumor and dendritic cells (DC). Whereas PD-L1 was not involved in secondary resistance to anti-PD-1 mAb, pharmacological or genetic inhibition of NOS2 maintained long-term control of tumors by PD-1 blockade, through reduction of Treg and DC activation. Resistance to immunotherapies, including anti-PD-1 mAb in melanoma patients, was also correlated with the induction of a type I IFN signature. Hence, the role of type I IFN in response to PD-1 blockade should be revisited as sustained type I IFN signaling may contribute to resistance to therapy.

The metabolite α-ketoglutarate is membrane-impermeable, meaning that it is usually added to cells in the form of esters such as dimethyl -ketoglutarate (DMKG), trifluoromethylbenzyl α-ketoglutarate (TFMKG) and octyl α-ketoglutarate (O-KG). Once these compounds cross the plasma membrane, they are hydrolyzed by esterases to generate α-ketoglutarate, which remains trapped within cells. Here, we systematically compared DMKG, TFMKG and O-KG for their metabolic and functional effects. All three compounds similarly increased the intracellular levels of α-ketoglutarate, yet each of them had multiple effects on other metabolites that were not shared among the three agents, as determined by mass spectrometric metabolomics. While all three compounds reduced autophagy induced by culture in nutrient-free conditions, TFMKG and O-KG (but not DMKG) caused an increase in baseline autophagy in cells cultured in complete medium. O-KG (but neither DMKG nor TFMK) inhibited oxidative phosphorylation and exhibited cellular toxicity. Altogether, these results support the idea that intracellular α-ketoglutarate inhibits starvation-induced autophagy and that it has no direct respiration-inhibitory effect.

Ageing constitutes the most important risk factor for all major chronic ailments, including malignant, cardiovascular and neurodegenerative diseases. However, behavioural and pharmacological interventions with feasible potential to promote health upon ageing remain rare. Here we report the identification of the flavonoid 4,4'-dimethoxychalcone (DMC) as a natural compound with anti-ageing properties. External DMC administration extends the lifespan of yeast, worms and flies, decelerates senescence of human cell cultures, and protects mice from prolonged myocardial ischaemia. Concomitantly, DMC induces autophagy, which is essential for its cytoprotective effects from yeast to mice. This pro-autophagic response induces a conserved systemic change in metabolism, operates independently of TORC1 signalling and depends on specific GATA transcription factors. Notably, we identify DMC in the plant Angelica keiskei koidzumi, to which longevity- and health-promoting effects are ascribed in Asian traditional medicine. In summary, we have identified and mechanistically characterised the conserved longevity-promoting effects of a natural anti-ageing drug.

The analysis of tumor growth curves is standard practice in experimental oncology including tumor immunology. In experimental oncology, cancer cells are inoculated into rodents (mostly mice) and their growth is monitored by measuring tumor diameter, surface or volume over time as a function of distinct treatments. Then, different groups of tumors/treatments are compared among each other for their evolution and possible responses to treatment. The R package TumGrowth has been created as a software tool allowing to carry out a series of statistical comparisons across or between groups of tumor growth curves obtained in a standard laboratory, for experimenters with limited knowledge in statistics. TumGrowth is freely available online at https://kroemerlab.shinyapps.io/TumGrowth/ and can be downloaded into any computer. It offers an exhaustive panoply of tools to visualize and analyze complex data sets including longitudinal, cross-sectional and time-to-endpoint measurements.

The age-associated deterioration in cellular and organismal functions associates with dysregulation of nutrient-sensing pathways and disabled autophagy. The reactivation of autophagic flux may prevent or ameliorate age-related metabolic dysfunctions. Non-toxic compounds endowed with the capacity to reduce the overall levels of protein acetylation and to induce autophagy have been categorized as caloric restriction mimetics (CRMs). Here, we show that aspirin or its active metabolite salicylate induce autophagy by virtue of their capacity to inhibit the acetyltransferase activity of EP300. While salicylate readily stimulates autophagic flux in control cells, it fails to further increase autophagy levels in EP300-deficient cells, as well as in cells in which endogenous EP300 has been replaced by salicylate-resistant EP300 mutants. Accordingly, the pro-autophagic activity of aspirin and salicylate on the nematode Caenorhabditis elegans is lost when the expression of the EP300 ortholog cpb-1 is reduced. Altogether, these findings identify aspirin as an evolutionary conserved CRM., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)

Existing clinical, anatomopathological and molecular biomarkers fail to reliably predict the prognosis of cutaneous melanoma. Biomarkers for determining which patients receive adjuvant therapies are needed. The emergence of new technologies and the discovery of new immune populations with different prognostic values allow the immune network in the tumor to be better understood. Importantly, new molecules identified and expressed by immune cells have been shown to reduce the antitumor immune efficacy of therapies, prompting researchers to develop antibodies targeting these so-called "immune checkpoints", which have now entered the oncotherapeutic armamentarium.

Caloric restriction mimetics (CRMs) mimic the biochemical effects of nutrient deprivation by reducing lysine acetylation of cellular proteins, thus triggering autophagy. Treatment with the CRM hydroxycitrate, an inhibitor of ATP citrate lyase, induced the depletion of regulatory T cells (which dampen anticancer immunity) from autophagy-competent, but not autophagy-deficient, mutant KRAS-induced lung cancers in mice, thereby improving anticancer immunosurveillance and reducing tumor mass. Short-term fasting or treatment with several chemically unrelated autophagy-inducing CRMs, including hydroxycitrate and spermidine, improved the inhibition of tumor growth by chemotherapy in vivo. This effect was only observed for autophagy-competent tumors, depended on the presence of T lymphocytes, and was accompanied by the depletion of regulatory T cells from the tumor bed., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Pattern recognition receptors allow the innate immune system to perceive the presence of microbial products and to launch the first steps of the defense response. Some pattern recognition receptors also sense endogenous ligands that are released from uninfected dying cells, thereby activating immune responses against dead-cell antigens. This applies to toll-like receptors 3 and 4 (TLR3, TLR4), which sense double-stranded RNA and high-mobility group protein B1 (HMGB1), respectively, as well as to formyl peptide receptor-1 (FPR1), which interacts with Annexin A1 (ANXA1) from dead cells. Breast cancer patients who bear loss-of-function alleles in TLR3, TLR4, and FPR1 exhibit a reduced metastasis-free and overall survival after treatment with anthracycline-based adjuvant chemotherapy. These genetic defects are epistatic with respect to each other, suggesting that they act on the same pathway, linking chemotherapy to a therapeutically relevant anticancer immune response. Loss-of-function alleles in TLR4 and FPR1 also affect the prognosis of colorectal cancer patients treated with oxaliplatin-based chemotherapy. Altogether, these results support the idea that conventional anticancer treatments rely on stimulation of anticancer immune responses to become fully efficient. Cancer Res; 76(11); 3122-6. ©2016 AACR., (©2016 American Association for Cancer Research.)

Stage III metastatic melanomas require adequate adjuvant immunotherapy to prevent relapses. Prognostic factors are awaited to optimize the clinical management of these patients. The magnitude of metastatic lymph node invasion and the BRAF(V600) activating mutation have clinical significance. Based on a comprehensive immunophenotyping of 252 parameters per patient in paired blood and metastatic lymph nodes performed in 39 metastatic melanomas, we found that blood markers were as contributive as tumor-infiltrated lymphocyte immunotypes, and parameters associated with lymphocyte exhaustion/suppression showed higher clinical significance than those related to activation or lineage. High frequencies of CD45RA(+)CD4(+) and CD3(-)CD56(-) tumor-infiltrated lymphocytes appear to be independent prognostic factors of short progression-free survival. High NKG2D expression on CD8(+)tumor-infiltrated lymphocytes, low level of regulatory T-cell tumor-infiltrated lymphocytes, and low PD-L1 expression on circulating T cells were retained in the multivariate Cox analysis model to predict prolonged overall survival. Prospective studies are needed to determine whether such immunological markers may guide adjuvant therapies in stage III metastatic melanomas., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Melanoma prognosis is dictated by tumor-infiltrating lymphocytes, the migratory and functional behavior of which is guided by chemokine or cytokine gradients. Here, we retrospectively analyzed the expression patterns of 9 homing receptors (CCR/CXCR) in naive and memory CD4+ and CD8+ T lymphocytes in 57 patients with metastatic melanoma (MMel) with various sites of metastases to evaluate whether T cell CCR/CXCR expression correlates with intratumoral accumulation, metastatic progression, and/or overall survival (OS). Homing receptor expression on lymphocytes strongly correlated with MMel dissemination. Loss of CCR6 or CXCR3, but not cutaneous lymphocyte antigen (CLA), on circulating T cell subsets was associated with skin or lymph node metastases, loss of CXCR4, CXCR5, and CCR9 corresponded with lung involvement, and a rise in CCR10 or CD103 was associated with widespread dissemination. High frequencies of CD8+CCR9+ naive T cells correlated with prolonged OS, while neutralizing the CCR9/CCL25 axis in mice stimulated tumor progression. The expansion of CLA-expressing effector memory CD8+ T cells in response to a single administration of CTLA4 blockade predicted disease control at 3 months in 47 patients with MMel. Thus, specific CCR/CXCR expression patterns on circulating T lymphocytes may guide potential diagnostic and therapeutic approaches.

Antibodies targeting CTLA-4 have been successfully used as cancer immunotherapy. We find that the antitumor effects of CTLA-4 blockade depend on distinct Bacteroides species. In mice and patients, T cell responses specific for B. thetaiotaomicron or B. fragilis were associated with the efficacy of CTLA-4 blockade. Tumors in antibiotic-treated or germ-free mice did not respond to CTLA blockade. This defect was overcome by gavage with B. fragilis, by immunization with B. fragilis polysaccharides, or by adoptive transfer of B. fragilis-specific T cells. Fecal microbial transplantation from humans to mice confirmed that treatment of melanoma patients with antibodies against CTLA-4 favored the outgrowth of B. fragilis with anticancer properties. This study reveals a key role for Bacteroidales in the immunostimulatory effects of CTLA-4 blockade., (Copyright © 2015, American Association for the Advancement of Science.)

Antitumor immunity driven by intratumoral dendritic cells contributes to the efficacy of anthracycline-based chemotherapy in cancer. We identified a loss-of-function allele of the gene coding for formyl peptide receptor 1 (FPR1) that was associated with poor metastasis-free and overall survival in breast and colorectal cancer patients receiving adjuvant chemotherapy. The therapeutic effects of anthracyclines were abrogated in tumor-bearing Fpr1(-/-) mice due to impaired antitumor immunity. Fpr1-deficient dendritic cells failed to approach dying cancer cells and, as a result, could not elicit antitumor T cell immunity. Experiments performed in a microfluidic device confirmed that FPR1 and its ligand, annexin-1, promoted stable interactions between dying cancer cells and human or murine leukocytes. Altogether, these results highlight the importance of FPR1 in chemotherapy-induced anticancer immune responses., (Copyright © 2015, American Association for the Advancement of Science.)

Ever accumulating evidence indicates that the long-term effects of radiotherapy and chemotherapy largely depend on the induction (or restoration) of an anticancer immune response. Here, we investigated this paradigm in the context of esophageal carcinomas treated by neo-adjuvant radiochemotherapy, in a cohort encompassing 196 patients. We found that the density of the FOXP3+ regulatory T cell (Treg) infiltrate present in the residual tumor (or its scar) correlated with the pathological response (the less Tregs the more pronounced was the histological response) and predicted cancer-specific survival. In contrast, there was no significant clinical impact of the frequency of CD8+ cytotoxic T cells. At difference with breast or colorectal cancer, a loss-of-function allele of toll like receptor 4 (TLR4) improved cancer-specific survival of patients with esophageal cancer. While a loss-of-function allele of purinergic receptor P2X, ligand-gated ion channel, 7 (P2RX7) failed to affect cancer-specific survival, its presence did correlate with an increase in Treg infiltration. Altogether, these results corroborate the notion that the immunosurveillance seals the fate of patients with esophageal carcinomas treated with conventional radiochemotherapy.

Recently, we reported that saturated and unsaturated fatty acids trigger autophagy through distinct signal transduction pathways. Saturated fatty acids like palmitate (PA) induce autophagic responses that rely on phosphatidylinositol 3-kinase, catalytic subunit type 3 (PIK3C3, best known as VPS34) and beclin 1 (BECN1). Conversely, unsaturated fatty acids like oleate (OL) promote non-canonical, PIK3C3- and BECN1-independent autophagy. Here, we explored the metabolic effects of autophagy-inducing doses of PA and OL in mice. Mass spectrometry coupled to principal component analysis revealed that PA and OL induce well distinguishable changes in circulating metabolites as well as in the metabolic profile of the liver, heart, and skeletal muscle. Importantly, PA (but not OL) causes the depletion of multiple autophagy-inhibitory amino acids in the liver. Conversely, OL (but not PA) increased the hepatic levels of nicotinamide adenine dinucleotide (NAD), an obligate co-factor for autophagy-stimulatory enzymes of the sirtuin family. Moreover, PA (but not OL) raised the concentrations of acyl-carnitines in the heart, a phenomenon that perhaps is linked to its cardiotoxicity. PA also depleted the liver from spermine and spermidine, 2 polyamines have been ascribed with lifespan-extending activity. The metabolic changes imposed by unsaturated and saturated fatty acids may contribute to their health-promoting and health-deteriorating effects, respectively.

Several natural compounds found in health-related food items can inhibit acetyltransferases as they induce autophagy. Here we show that this applies to anacardic acid, curcumin, garcinol and spermidine, all of which reduce the acetylation level of cultured human cells as they induce signs of increased autophagic flux (such as the formation of green fluorescent protein-microtubule-associated protein 1A/1B-light chain 3 (GFP-LC3) puncta and the depletion of sequestosome-1, p62/SQSTM1) coupled to the inhibition of the mammalian target of rapamycin complex 1 (mTORC1). We performed a screen to identify the acetyltransferases whose depletion would activate autophagy and simultaneously inhibit mTORC1. The knockdown of only two acetyltransferases (among 43 candidates) had such effects: EP300 (E1A-binding protein p300), which is a lysine acetyltranferase, and NAA20 (N(α)-acetyltransferase 20, also known as NAT5), which catalyzes the N-terminal acetylation of methionine residues. Subsequent studies validated the capacity of a pharmacological EP300 inhibitor, C646, to induce autophagy in both normal and enucleated cells (cytoplasts), underscoring the capacity of EP300 to repress autophagy by cytoplasmic (non-nuclear) effects. Notably, anacardic acid, curcumin, garcinol and spermidine all inhibited the acetyltransferase activity of recombinant EP300 protein in vitro. Altogether, these results support the idea that EP300 acts as an endogenous repressor of autophagy and that potent autophagy inducers including spermidine de facto act as EP300 inhibitors.

Some of the anti-neoplastic effects of anthracyclines in mice originate from the induction of innate and T cell-mediated anticancer immune responses. Here we demonstrate that anthracyclines stimulate the rapid production of type I interferons (IFNs) by malignant cells after activation of the endosomal pattern recognition receptor Toll-like receptor 3 (TLR3). By binding to IFN-α and IFN-β receptors (IFNARs) on neoplastic cells, type I IFNs trigger autocrine and paracrine circuitries that result in the release of chemokine (C-X-C motif) ligand 10 (CXCL10). Tumors lacking Tlr3 or Ifnar failed to respond to chemotherapy unless type I IFN or Cxcl10, respectively, was artificially supplied. Moreover, a type I IFN-related signature predicted clinical responses to anthracycline-based chemotherapy in several independent cohorts of patients with breast carcinoma characterized by poor prognosis. Our data suggest that anthracycline-mediated immune responses mimic those induced by viral pathogens. We surmise that such 'viral mimicry' constitutes a hallmark of successful chemotherapy.

Acetyl-coenzyme A (AcCoA) is a major integrator of the nutritional status at the crossroads of fat, sugar, and protein catabolism. Here we show that nutrient starvation causes rapid depletion of AcCoA. AcCoA depletion entailed the commensurate reduction in the overall acetylation of cytoplasmic proteins, as well as the induction of autophagy, a homeostatic process of self-digestion. Multiple distinct manipulations designed to increase or reduce cytosolic AcCoA led to the suppression or induction of autophagy, respectively, both in cultured human cells and in mice. Moreover, maintenance of high AcCoA levels inhibited maladaptive autophagy in a model of cardiac pressure overload. Depletion of AcCoA reduced the activity of the acetyltransferase EP300, and EP300 was required for the suppression of autophagy by high AcCoA levels. Altogether, our results indicate that cytosolic AcCoA functions as a central metabolic regulator of autophagy, thus delineating AcCoA-centered pharmacological strategies that allow for the therapeutic manipulation of autophagy., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Cyclophosphamide is one of several clinically important cancer drugs whose therapeutic efficacy is due in part to their ability to stimulate antitumor immune responses. Studying mouse models, we demonstrate that cyclophosphamide alters the composition of microbiota in the small intestine and induces the translocation of selected species of Gram-positive bacteria into secondary lymphoid organs. There, these bacteria stimulate the generation of a specific subset of "pathogenic" T helper 17 (pT(H)17) cells and memory T(H)1 immune responses. Tumor-bearing mice that were germ-free or that had been treated with antibiotics to kill Gram-positive bacteria showed a reduction in pT(H)17 responses, and their tumors were resistant to cyclophosphamide. Adoptive transfer of pT(H)17 cells partially restored the antitumor efficacy of cyclophosphamide. These results suggest that the gut microbiota help shape the anticancer immune response.

Non-small cell lung carcinoma patients are frequently treated with cisplatin (CDDP), most often yielding temporary clinical responses. Here, we show that PARP1 is highly expressed and constitutively hyperactivated in a majority of human CDDP-resistant cancer cells of distinct histologic origin. Cells manifesting elevated intracellular levels of poly(ADP-ribosyl)ated proteins (PAR(high)) responded to pharmacologic PARP inhibitors as well as to PARP1-targeting siRNAs by initiating a DNA damage response that translated into cell death following the activation of the intrinsic pathway of apoptosis. Moreover, PARP1-overexpressing tumor cells and xenografts displayed elevated levels of PAR, which predicted the response to PARP inhibitors in vitro and in vivo more accurately than PARP1 expression itself. Thus, a majority of CDDP-resistant cancer cells appear to develop a dependency to PARP1, becoming susceptible to PARP inhibitor-induced apoptosis., (©2013 AACR.)

The antineoplastic agent cis-diammineplatinum(II) dichloride (cisplatin, CDDP) is part of the poorly effective standard treatment of non-small cell lung carcinoma (NSCLC). Here, we report a novel strategy to improve the efficacy of CDDP. In conditions in which CDDP alone or either of two PARP inhibitors, PJ34 hydrochloride hydrate or CEP 8983, used as standalone treatments were inefficient in killing NSCLC cells, the combination of CDDP plus PJ34 or that of CDDP plus CEP 8983 were found to kill a substantial fraction of the cells. This cytotoxic synergy could be recapitulated by combining CDDP and the siRNA-mediated depletion of the principal PARP isoform, PARP1, indicating that it is mediated by on-target effects of PJ34 or CEP 8983. CDDP and PARP inhibitors synergized in inducing DNA damage foci, mitochondrial membrane permeabilization leading to cytochrome c release, and dissipation of the inner transmembrane potential, caspase activation, plasma membrane rupture and loss of clonogenic potential in NSCLC cells. Collectively, our results indicate that CDDP can be advantageously combined with PARP inhibitors to kill several NSCLC cell lines, independently from their p53 status. Combined treatment with CDDP and PARP inhibitors elicits the intrinsic pathway of apoptosis.

Background: In preterm infants, the amplitude-integrated electroencephalogram (aEEG) is not established in clinical routine. The aim of this study was to derive normative data on aEEG parameters by means of longitudinal characterization and to evaluate the impact of gestational age (GA), postnatal age (PNA), postmenstrual age, sedation, and patent ductus arteriosus (PDA)., Methods: Recordings from 61 infants with GA 28-31 weeks were obtained during the first 72 h, then weekly until the age of 4 wk. Infants were divided into three groups: (i) no sedation, no PDA, (ii) sedation, no PDA, and (iii) sedation, PDA. Assessed parameters included background activity, cycling, amplitude, and log ratio of the maximum/minimum amplitude., Results: GA and PNA had a significant impact within 72 h. Sedation modified aEEG, and presence of PDA was associated with reduced aEEG scores within 72 h. The log ratio of the amplitude correlated with GA but was unaffected by sedation and PDA., Conclusion: Evaluation of electrocortical background activity within the first postnatal hours and longitudinally over days and weeks is important to better understand the postnatal factors impacting cerebral function in preterm infants. There is a need to agree on definitions and a standardized reporting system in order to permit comparisons between studies and establish aEEG as a method for routine monitoring of preterm infants.

Community-acquired pneumonia presents a spectrum of clinical phenotypes, from lobar pneumonia to septic shock, while mechanisms underlying progression are incompletely understood. In a transcriptomic and metabolomic study across tissues, we examined serotype-specific regulation of signaling and metabolic pathways in C57BL/6 mice intratracheally instilled with either serotype 19F Streptococcus pneumoniae (S19; causing lobar pneumonia), or serotype 2 S. pneumoniae (S2; causing septic pneumococcal disease,) or vehicle (Todd-Hewitt broth). Samples of lung, liver, and blood were collected at 6 and 24 h postinfection and subjected to microarray analysis and mass spectrometry. Results comprise a preferential induction of cholesterol biosynthesis in lobar pneumonia at low-infection doses (10(5) colony forming units/mouse) leading to increased plasma cholesterol (vehicle: 1.8±0.12 mM, S2: 2.3±0.10 mM, S19: 2.9±0.15 mM; P<0.05, comparing S19 to vehicle and S2). This induction was pneumolysin dependent, as a pneumolysin-deficient strain of serotype 19F failed to induce cholesterol biosynthesis (S19ΔPLY: 1.9±0.03 mM). Preincubation of pneumolysin with purified cholesterol or plasma from hypercholesterolemic mice prior to intratracheal instillation protected against lung barrier dysfunction and alveolar macrophage necrosis. Cholesterol may attenuate disease severity by neutralizing pneumolysin in the alveolar compartment and thus prevent septic disease progression.

Background & Aims: Liver is a target organ in many mitochondrial disorders, especially if the complex III assembly factor BCS1L is mutated. To reveal disease mechanism due to such mutations, we have produced a transgenic mouse model with c.232A>G mutation in Bcs1l, the causative mutation for GRACILE syndrome. The homozygous mice develop mitochondrial hepatopathy with steatosis and fibrosis after weaning. Our aim was to assess cellular mechanisms for disease onset and progression using metabolomics., Methods: With mass spectrometry we analyzed metabolite patterns in liver samples obtained from homozygotes and littermate controls of three ages. As oxidative stress might be a mechanism for mitochondrial hepatopathy, we also assessed H(2)O(2) production and expression of antioxidants., Results: Homozygotes had a similar metabolic profile at 14 days of age as controls, with the exception of slightly decreased AMP. At 24 days, when hepatocytes display first histopathological signs, increases in succinate, fumarate and AMP were found associated with impaired glucose turnover and beta-oxidation. At end stage disease after 30 days, these changes were pronounced with decreased carbohydrates, high levels of acylcarnitines and amino acids, and elevated biogenic amines, especially putrescine. Signs of oxidative stress were present in end-stage disease., Conclusions: The findings suggest an early Krebs cycle defect with increases of its intermediates, which might play a role in disease onset. During disease progression, carbohydrate and fatty acid metabolism deteriorate leading to a starvation-like condition. The mouse model is valuable for further investigations on mechanisms in mitochondrial hepatopathy and for interventions.

The broad view of the state of biological systems cannot be complete without the added value of integrating proteomic and genomic data with metabolite measurement. By definition, metabolomics aims at quantifying not less than the totality of small molecules present in a biofluid, tissue, organism, or any material beyond living systems. To cope with the complexity of the task, mass spectrometry (MS) is the most promising analytical environment to fulfill increasing appetite for more accurate and larger view of the metabolome while providing sufficient data generation throughput. Bioinformatics and associated disciplines naturally play a central role in bridging the gap between fast evolving technology and domain experts. Here, we describe the strategies to translate crude MS information into features characteristics of metabolites, and resources available to guide scientists along the metabolomics pipeline. A particular emphasis is put on pragmatic solutions to interpret the outcome of metabolomics experiments at the level of signal processing, statistical treatment, and biochemical understanding.

Prenatal inflammation is considered an important factor contributing to preterm birth and neonatal mortality and morbidity. The impact of prenatal inflammation on fetal bioenergetic status and the correlation of specific metabolites to inflammatory-induced developmental brain injury are unknown. We used a global metabolomics approach to examine plasma metabolites differentially regulated by intrauterine inflammation. Preterm-equivalent sheep fetuses were randomized to i.v. bolus infusion of either saline-vehicle or LPS. Blood samples were collected at baseline 2 h, 6 h and daily up to 10 days for metabolite quantification. Animals were killed at 10 days after LPS injection, and brain injury was assessed by histopathology. We detected both acute and delayed effects of LPS on fetal metabolism, with a long-term down-regulation of fetal energy metabolism. Within the first 3 days after LPS, 121 metabolites were up-regulated or down-regulated. A transient phase (4-6 days), in which metabolite levels recovered to baseline, was followed by a second phase marked by an opposing down-regulation of energy metabolites, increased pO(2) and increased markers of inflammation and ADMA. The characteristics of the metabolite response to LPS in these two phases, defined as 2 h to 2 days and at 6-9 days, respectively, were strongly correlated with white and grey matter volumes at 10 days recovery. Based on these results we propose a novel concept of inflammatory-induced hibernation of the fetus. Inflammatory priming of fetal metabolism correlated with measures of brain injury, suggesting potential for future biomarker research and the identification of therapeutic targets.

Current quantitative metabolomic research in brain tissue is challenged by several analytical issues. To compare data of metabolite pattern, ratios of individual metabolite concentrations and composed classifiers characterizing a distinct state, standardized workup conditions, and extraction medium are crucial. Differences in physicochemical properties of individual compounds and compound classes such as polarity determine extraction yields and, thus, ratios of compounds with varying properties. Also, variations in suppressive effects related to coextracted matrix components affect standards or references and their concentration-dependent responses.The selection of a common tissue extraction protocol is an ill-posed problem because it can be regarded as a multiple objective decision depending on factors such as sample handling practicability, measurement precision, control of matrix effects, and relevance of the chemical assay. This study systematically evaluates the impact of extraction solvents and the impact of the complex brain tissue on measured metabolite levels, taking into account ionization efficiency as well as challenges encountered in the trace-level quantification of the analytes in brain matrices. In comparison with previous studies that relied on nontargeted platforms, consequently emphasizing the global behavior of the metabolomic fingerprint, here we focus on several series of metabolites spanning over extensive polarity, concentration, and molecular mass ranges., (Copyright 2010 Elsevier Inc. All rights reserved.)

Metabolomics is a truly interdisciplinary field of science, which combines analytical chemistry, platform technology, mass spectrometry, and NMR spectroscopy with sophisticated data analysis. Applied to biomarker discovery, it includes aspects of pathobiochemistry, systems biology/medicine, and molecular diagnostics and requires bioinformatics and multivariate statistics. While successfully established in the screening of inborn errors in neonates, metabolomics is now widely used in the characterization and diagnostic research of an ever increasing number of diseases. In this Review we highlight important technical prerequisites as well as recent developments in metabolomics and metabolomics data analysis with special emphasis on their utility in biomarker identification and qualification, as well as targeted metabolomics by employing high-throughput mass spectrometry.

The mechanisms by which biotrophic and hemi-biotrophic fungal pathogens simultaneously subdue plant defences and sequester host nutrients are poorly understood. Using metabolite fingerprinting, we show that Magnaporthe grisea, the causal agent of rice blast disease, dynamically re-programmes host metabolism during plant colonization. Identical patterns of metabolic change occurred during M. grisea infections in barley, rice and Brachypodium distachyon. Targeted metabolite profiling by GC-MS confirmed the modulation of a conserved set of metabolites. In pre-symptomatic tissues, malate and polyamines accumulated, rather than being utilized to generate defensive reactive oxygen species, and the levels of metabolites associated with amelioration of redox stress in various cellular compartments increased dramatically. The activity of NADP-malic enzyme and generation of reactive oxygen species were localized to pathogen penetration sites, and both appeared to be suppressed in compatible interactions. Early diversion of the shikimate pathway to produce quinate was observed, as well as accumulation of non-polymerized lignin precursors. These data are consistent with modulation of defensive phenylpropanoid metabolism by M. grisea and the inability of susceptible hosts to mount a hypersensitive reaction or produce lignified papillae (both involving reactive oxygen species) to restrict pathogen invasion. Rapid proliferation of M. grisea hyphae in plant tissue after 3 days was associated with accelerated nutrient acquisition and utilization by the pathogen. Conversion of photoassimilate into mannitol and glycerol for carbon sequestration and osmolyte production appear to drive hyphal growth. Taken together, our results suggest that fungal pathogens deploy a common metabolic re-programming strategy in diverse host species to suppress plant defence and colonize plant tissue.

Background: Metabolomics experiments using Mass Spectrometry (MS) technology measure the mass to charge ratio (m/z) and intensity of ionised molecules in crude extracts of complex biological samples to generate high dimensional metabolite 'fingerprint' or metabolite 'profile' data. High resolution MS instruments perform routinely with a mass accuracy of < 5 ppm (parts per million) thus providing potentially a direct method for signal putative annotation using databases containing metabolite mass information. Most database interfaces support only simple queries with the default assumption that molecules either gain or lose a single proton when ionised. In reality the annotation process is confounded by the fact that many ionisation products will be not only molecular isotopes but also salt/solvent adducts and neutral loss fragments of original metabolites. This report describes an annotation strategy that will allow searching based on all potential ionisation products predicted to form during electrospray ionisation (ESI)., Results: Metabolite 'structures' harvested from publicly accessible databases were converted into a common format to generate a comprehensive archive in MZedDB. 'Rules' were derived from chemical information that allowed MZedDB to generate a list of adducts and neutral loss fragments putatively able to form for each structure and calculate, on the fly, the exact molecular weight of every potential ionisation product to provide targets for annotation searches based on accurate mass. We demonstrate that data matrices representing populations of ionisation products generated from different biological matrices contain a large proportion (sometimes > 50%) of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of m/z signals. An integrated isotope enumerator in MZedDB allowed verification of exact isotopic pattern distributions to corroborate experimental data., Conclusion: We conclude that although ultra-high accurate mass instruments provide major insight into the chemical diversity of biological extracts, the facile annotation of a large proportion of signals is not possible by simple, automated query of current databases using computed molecular formulae. Parameterising MZedDB to take into account predicted ionisation behaviour and the biological source of any sample improves greatly both the frequency and accuracy of potential annotation 'hits' in ESI-MS data.

Flow injection electrospray-mass spectrometry (FIE-MS) is finding utility as a first-pass metabolite fingerprinting tool in many research fields. We provide a protocol that has proved reliable in large-scale research projects involving diverse sample matrices originating from plants, microbes and mammalian biofluids. Using Brachypodium leaf material as an example matrix all steps are summarized from sample extraction to data quality assessment. Alternative procedures for dealing with other common matrices such as bloods and urine are included. With little sample pretreatment, no chromatography and instrument cycle times of <5 min it is feasible to analyze >1,000 samples per week. Analysis of a typical batch of 240 samples (including first-pass data analysis) can be accomplished within 48 h.

Metabolome analysis by flow injection electrospray mass spectrometry (FIE-MS) fingerprinting generates measurements relating to large numbers of m/z signals. Such data sets often exhibit high variance with a paucity of replicates, thus providing a challenge for data mining. We describe data preprocessing and modeling methods that have proved reliable in projects involving samples from a range of organisms. The protocols interact with software resources specifically for metabolomics provided in a Web-accessible data analysis package FIEmspro (http://users.aber.ac.uk/jhd) written in the R environment and requiring a moderate knowledge of R command-line usage. Specific emphasis is placed on describing the outcome of modeling experiments using FIE-MS data that require further preprocessing to improve quality. The salient features of both poor and robust (i.e., highly generalizable) multivariate models are outlined together with advice on validating classifiers and avoiding false discovery when seeking explanatory variables.

Flow injection electrospray mass spectrometry (FIE-MS) metabolite fingerprinting is widely used as a 'first pass' screen for compositional differences, where discrimination between samples can be achieved without any preconceptions. Powerful data analysis algorithms can be used to select and rank FIE-MS fingerprint variables highly explanatory of the biological problem under investigation. We describe how to create a species-specific FIE-MS/MS(n) metabolite database and how to then query the database to predict the identity of highly significant variables within FIE-MS fingerprints. The protocol details how to interpret m/z signals within the explanatory variable list based on a correlation analysis in conjunction with an investigation of mathematical relationships regarding (de)protonated molecular ions, salt adducts, neutral losses and dimeric associations routinely observed in FIE-MS fingerprints. Although designed for use by biologists/analytical chemists, collaboration with data-mining experts is generally advised. The protocol is applicable in any areas of bioscience research involving FIE-MS fingerprinting.

Interactions between plants and compatible fungal pathogens are spatially and temporally dynamic, posing a major challenge for sampling and data analysis. A protocol is described for the infection of the model grass species Brachypodium distachyon with Magnaporthe grisea (rice blast), together with modifications to extend the use to rice and barley. We outline a method for the preparation of long-term stocks of virulent fungal pathogens and for the generation of fungal inoculants for challenge of host plants. Host plant growth, pathogen inoculation and plant sampling protocols are presented together with methods for assessing the efficiency of both infection and sampling procedures. Included in the anticipated results is a description of the use of metabolite fingerprinting and multivariate data analysis to assess disease synchrony and validate system reproducibility between experiments. The design concepts will have value in any studies using biological systems that contain dynamic variance associated with large compositional changes in sample matrix over time.

Understanding attributes of crop varieties and food raw materials underlying desirable characteristics is a significant challenge. Metabolomics technology based on flow infusion electrospray ionization mass spectrometry (FIE-MS) has been used to investigate the chemical composition of potato cultivars associated with quality traits in harvested tubers. Through the combination of metabolite fingerprinting with random forest data modeling, a subset of metabolome signals explanatory of compositional differences between individual genotypes were ranked for importance. Interpretative analysis of highlighted signals based on ranking behavior, intensity correlations, and mathematical relationships of ion masses correctly predicted metabolites associated with flavor and pigmentation traits in potato tubers. GC-MS profiling was used to further validate proposed compositional differences. The potential for the development of a database strategy for large scale, long-term projects requiring comparison of chemical composition in plant breeding, mutant population analysis in functional genomics experiments, or food raw material analysis is described.

Powerful algorithms are required to deal with the dimensionality of metabolomics data. Although many achieve high classification accuracy, the models they generate have limited value unless it can be demonstrated that they are reproducible and statistically relevant to the biological problem under investigation. Random forest (RF) generates models, without any requirement for dimensionality reduction or feature selection, in which individual variables are ranked for significance and displayed in an explicit manner. In metabolome fingerprinting by mass spectrometry, each metabolite can be represented by signals at several m/z. Exploiting a prior understanding of expected biochemical differences between sample classes, we aimed to develop meaningful metrics relevant to the significance both of the overall RF model and individual, potentially explanatory, signals. Pair-wise comparison of related plant genotypes with strong phenotypic differences demonstrated that robust models are not only reproducible but also logically structured, highlighting correlated m/z derived from just a small number of explanatory metabolites reflecting the biological differences between sample classes. RF models were also generated by using groupings of samples known to be increasingly phenotypically similar. Although classification accuracy was often reasonable, we demonstrated reproducibly in both Arabidopsis and potato a performance threshold based on margin statistics beyond which such models showed little structure indicative of either generalizability or further biological interpretability. In a multiclass problem using 25 Arabidopsis genotypes, despite the complicating effects of ecotype background and secondary metabolome perturbations common to several mutations, the ranking of metabolome signals by RF provided scope for deeper interpretability.

There is current debate whether genetically modified (GM) plants might contain unexpected, potentially undesirable changes in overall metabolite composition. However, appropriate analytical technology and acceptable metrics of compositional similarity require development. We describe a comprehensive comparison of total metabolites in field-grown GM and conventional potato tubers using a hierarchical approach initiating with rapid metabolome "fingerprinting" to guide more detailed profiling of metabolites where significant differences are suspected. Central to this strategy are data analysis procedures able to generate validated, reproducible metrics of comparison from complex metabolome data. We show that, apart from targeted changes, these GM potatoes in this study appear substantially equivalent to traditional cultivars.

We introduce the Gaussian process (GP) model for the empirical modelling of the log P values of 44 1,2-dithiole-3-one molecules. A brief theoretical description of the method is given. Descriptive and predictive abilities of GP are evaluated and compared to multilinear regression results. Special attention is devoted to the automatic relevance determination (ARD) to reduce input variable numbers, which avoid the use of principal component analysis. The present approach was found to be an efficient method and a good alternative to more complicated using artificial neural network systems.