Guidelines for the use and interpretation of assays for monitoring autophagy in higher eukaryotes

Research in autophagy continues to accelerate,(1) and as a result many new scientists are entering the field. Accordingly, it is important to establish a standard set of criteria for monitoring macroautophagy in different organisms. Recent reviews have described the range of assays that have been used for this purpose.(2,3) There are many useful and convenient methods that can be used to monitor macroautophagy in yeast, but relatively few in other model systems, and there is much confusion regarding acceptable methods to measure macroautophagy in higher eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers of autophagosomes versus those that measure flux through the autophagy pathway; thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from fully functional autophagy that includes delivery to, and degradation within, lysosomes (in most higher eukaryotes) or the vacuole (in plants and fungi). Here, we present a set of guidelines for the selection and interpretation of the methods that can be used by investigators who are attempting to examine macroautophagy and related processes, as well as by reviewers who need to provide realistic and reasonable critiques of papers that investigate these processes. This set of guidelines is not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to verify an autophagic response.

Structural characterization of water-soluble atmospheric organic matter by ultrahigh-resolution mass spectrometry

Isolated water-soluble analytes extracted from fog water collected during a radiation fog event near Fresno, CA were analyzed using collision induced dissociation and ultrahigh-resolution mass spectrometry. Tandem mass analysis was performed on scan ranges between 100-400 u to characterize the structures of nitrogen and/or sulfur containing species. CHNO, CHOS, and CHNOS compounds were targeted specifically because of the high number of oxygen atoms contained in their molecular formulas. The presence of 22 neutral losses corresponding to fragment ions was evaluated for each of the 1308 precursors. Priority neutral losses represent specific polar functional groups (H2O, CO2, CH3OH, HNO3, SO3, etc., and several combinations of these). Additional neutral losses represent non-specific functional groups (CO, CH2O, C3H8, etc.) Five distinct monoterpene derived organonitrates, organosulfates, and nitroxy-organosulfates were observed in this study, including C10H16O7S, C10H17NO7S, C10H17 NO8S, C10H17NO9S, and C10H17NO10S. Nitrophenols and linear alkyl benzene sulfonates were present in high abundance. Liquid chromatography/mass spectrometery methodology was developed to isolate and quantify nitrophenols based on their fragmentation behavior.

Radiation metabolomics. 1. Identification of minimally invasive urine biomarkers for gamma-radiation exposure in mice

Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for gamma-radiation biodosimetry in a mouse model. Mice were gamma-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and beta-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose-response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to gamma radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans.

UPLC-ESI-TOFMS-based metabolomics and gene expression dynamics inspector self-organizing metabolomic maps as tools for understanding the cellular response to ionizing radiation

Global transcriptomic and proteomic profiling platforms have yielded important insights into the complex response to ionizing radiation (IR). Nonetheless, little is known about the ways in which small cellular metabolite concentrations change in response to IR. Here, a metabolomics approach using ultraperformance liquid chromatography coupled with electrospray time-of-flight mass spectrometry was used to profile, over time, the hydrophilic metabolome of TK6 cells exposed to IR doses ranging from 0.5 to 8.0 Gy. Multivariate data analysis of the positive ions revealed dose- and time-dependent clustering of the irradiated cells and identified certain constituents of the water-soluble metabolome as being significantly depleted as early as 1 h after IR. Tandem mass spectrometry was used to confirm metabolite identity. Many of the depleted metabolites are associated with oxidative stress and DNA repair pathways. Included are reduced glutathione, adenosine monophosphate, nicotinamide adenine dinucleotide, and spermine. Similar measurements were performed with a transformed fibroblast cell line, BJ, and it was found that a subset of the identified TK6 metabolites were effective in IR dose discrimination. The GEDI (Gene Expression Dynamics Inspector) algorithm, which is based on self-organizing maps, was used to visualize dynamic global changes in the TK6 metabolome that resulted from IR. It revealed dose-dependent clustering of ions sharing the same trends in concentration change across radiation doses. "Radiation metabolomics," the application of metabolomic analysis to the field of radiobiology, promises to increase our understanding of cellular responses to stressors such as radiation.

Radiation metabolomics. 2. Dose- and time-dependent urinary excretion of deaminated purines and pyrimidines after sublethal gamma-radiation exposure in mice

Gamma-radiation exposure of humans is a major public health concern as the threat of terrorism and potential hostile use of radiological devices increases worldwide. We report here the effects of sublethal gamma-radiation exposure on the mouse urinary metabolome determined using ultra-performance liquid chromatography-coupled time-of-flight mass spectrometry-based metabolomics. Five urinary biomarkers of sublethal radiation exposure that were statistically significantly elevated during the first 24 h after exposure to doses ranging from 1 to 3 Gy were unequivocally identified by tandem mass spectrometry. These are deaminated purine and pyrimidine derivatives, namely, thymidine, 2'-deoxyuridine, 2'-deoxyxanthosine, xanthine and xanthosine. Furthermore, the aminopyrimidine 2'-deoxycytidine appeared to display reduced urinary excretion at 2 and 3 Gy. The elevated biomarkers displayed a time-dependent excretion, peaking in urine at 8-12 h but returning to baseline by 36 h after exposure. It is proposed that 2'-deoxyuridine and 2'-deoxyxanthosine arise as a result of gamma irradiation by nitrosative deamination of 2'-deoxycytidine and 2'-deoxyguanosine, respectively, and that this further leads to increased synthesis of thymidine, xanthine and xanthosine. The urinary excretion of deaminated purines and pyrimidines, at the expense of aminopurines and aminopyrimidines, appears to form the core of the urinary radiation metabolomic signature of mice exposed to sublethal doses of ionizing radiation.

No surgical innovation without evaluation: the IDEAL recommendations

Surgery and other invasive therapies are complex interventions, the assessment of which is challenged by factors that depend on operator, team, and setting, such as learning curves, quality variations, and perception of equipoise. We propose recommendations for the assessment of surgery based on a five-stage description of the surgical development process. We also encourage the widespread use of prospective databases and registries. Reports of new techniques should be registered as a professional duty, anonymously if necessary when outcomes are adverse. Case series studies should be replaced by prospective development studies for early technical modifications and by prospective research databases for later pre-trial evaluation. Protocols for these studies should be registered publicly. Statistical process control techniques can be useful in both early and late assessment. Randomised trials should be used whenever possible to investigate efficacy, but adequate pre-trial data are essential to allow power calculations, clarify the definition and indications of the intervention, and develop quality measures. Difficulties in doing randomised clinical trials should be addressed by measures to evaluate learning curves and alleviate equipoise problems. Alternative prospective designs, such as interrupted time series studies, should be used when randomised trials are not feasible. Established procedures should be monitored with prospective databases to analyse outcome variations and to identify late and rare events. Achievement of improved design, conduct, and reporting of surgical research will need concerted action by editors, funders of health care and research, regulatory bodies, and professional societies.

Challenges in evaluating surgical innovation

Research on surgical interventions is associated with several methodological and practical challenges of which few, if any, apply only to surgery. However, surgical evaluation is especially demanding because many of these challenges coincide. In this report, the second of three on surgical innovation and evaluation, we discuss obstacles related to the study design of randomised controlled trials and non-randomised studies assessing surgical interventions. We also describe the issues related to the nature of surgical procedures-for example, their complexity, surgeon-related factors, and the range of outcomes. Although difficult, surgical evaluation is achievable and necessary. Solutions tailored to surgical research and a framework for generating evidence on which to base surgical practice are essential.

Evaluation and stages of surgical innovations

Surgical innovation is an important part of surgical practice. Its assessment is complex because of idiosyncrasies related to surgical practice, but necessary so that introduction and adoption of surgical innovations can derive from evidence-based principles rather than trial and error. A regulatory framework is also desirable to protect patients against the potential harms of any novel procedure. In this first of three Series papers on surgical innovation and evaluation, we propose a five-stage paradigm to describe the development of innovative surgical procedures.

Computer technology applications in surgical implant dentistry: a systematic review

PURPOSE: To assess the literature on accuracy and clinical performance of computer technology applications in surgical implant dentistry. MATERIALS AND METHODS: Electronic and manual literature searches were conducted to collect information about (1) the accuracy and (2) clinical performance of computer-assisted implant systems. Meta-regression analysis was performed for summarizing the accuracy studies. Failure/complication rates were analyzed using random-effects Poisson regression models to obtain summary estimates of 12-month proportions. RESULTS: Twenty-nine different image guidance systems were included. From 2,827 articles, 13 clinical and 19 accuracy studies were included in this systematic review. The meta-analysis of the accuracy (19 clinical and preclinical studies) revealed a total mean error of 0.74 mm (maximum of 4.5 mm) at the entry point in the bone and 0.85 mm at the apex (maximum of 7.1 mm). For the 5 included clinical studies (total of 506 implants) using computer-assisted implant dentistry, the mean failure rate was 3.36% (0% to 8.45%) after an observation period of at least 12 months. In 4.6% of the treated cases, intraoperative complications were reported; these included limited interocclusal distances to perform guided implant placement, limited primary implant stability, or need for additional grafting procedures. CONCLUSION: Differing levels and quantity of evidence were available for computer-assisted implant placement, revealing high implant survival rates after only 12 months of observation in different indications and a reasonable level of accuracy. However, future long-term clinical data are necessary to identify clinical indications and to justify additional radiation doses, effort, and costs associated with computer-assisted implant surgery.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Human urinary metabolomic profile of PPARalpha induced fatty acid beta-oxidation

Activation of the peroxisome proliferator-activated receptor alpha (PPARalpha) is associated with increased fatty acid catabolism and is commonly targeted for the treatment of hyperlipidemia. To identify latent, endogenous biomarkers of PPARalpha activation and hence increased fatty acid beta-oxidation, healthy human volunteers were given fenofibrate orally for 2 weeks and their urine was profiled by UPLC-QTOFMS. Biomarkers identified by the machine learning algorithm random forests included significant depletion by day 14 of both pantothenic acid (>5-fold) and acetylcarnitine (>20-fold), observations that are consistent with known targets of PPARalpha including pantothenate kinase and genes encoding proteins involved in the transport and synthesis of acylcarnitines. It was also concluded that serum cholesterol (-12.7%), triglycerides (-25.6%), uric acid (-34.7%), together with urinary propylcarnitine (>10-fold), isobutyrylcarnitine (>2.5-fold), (S)-(+)-2-methylbutyrylcarnitine (5-fold), and isovalerylcarnitine (>5-fold) were all reduced by day 14. Specificity of these biomarkers as indicators of PPARalpha activation was demonstrated using the Ppara-null mouse. Urinary pantothenic acid and acylcarnitines may prove useful indicators of PPARalpha-induced fatty acid beta-oxidation in humans. This study illustrates the utility of a pharmacometabolomic approach to understand drug effects on lipid metabolism in both human populations and in inbred mouse models.

Rifampicin-activated human pregnane X receptor and CYP3A4 induction enhance acetaminophen-induced toxicity

Acetaminophen (APAP) is safe at therapeutic levels but causes hepatotoxicity via N-acetyl-p-benzoquinone imine-induced oxidative stress upon overdose. To determine the effect of human (h) pregnane X receptor (PXR) activation and CYP3A4 induction on APAP-induced hepatotoxicity, mice humanized for PXR and CYP3A4 (TgCYP3A4/hPXR) were treated with APAP and rifampicin. Human PXR activation and CYP3A4 induction enhanced APAP-induced hepatotoxicity as revealed by hepatic alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities elevated in serum, and hepatic necrosis after coadministration of rifampicin and APAP, compared with APAP administration alone. In contrast, hPXR mice, wild-type mice, and Pxr-null mice exhibited significantly lower ALT/AST levels compared with TgCYP3A4/hPXR mice after APAP administration. Toxicity was coincident with depletion of hepatic glutathione and increased production of hydrogen peroxide, suggesting increased oxidative stress upon hPXR activation. Moreover, mRNA analysis demonstrated that CYP3A4 and other PXR target genes were significantly induced by rifampicin treatment. Urinary metabolomic analysis indicated that cysteine-APAP and its metabolite S-(5-acetylamino-2-hydroxyphenyl)mercaptopyruvic acid were the major contributors to the toxic phenotype. Quantification of plasma APAP metabolites indicated that the APAP dimer formed coincident with increased oxidative stress. In addition, serum metabolomics revealed reduction of lysophosphatidylcholine in the APAP-treated groups. These findings demonstrated that human PXR is involved in regulation of APAP-induced toxicity through CYP3A4-mediated hepatic metabolism of APAP in the presence of PXR ligands.

Serum metabolomics reveals irreversible inhibition of fatty acid beta-oxidation through the suppression of PPARalpha activation as a contributing mechanism of acetaminophen-induced hepatotoxicity

Metabolic bioactivation, glutathione depletion, and covalent binding are the early hallmark events after acetaminophen (APAP) overdose. However, the subsequent metabolic consequences contributing to APAP-induced hepatic necrosis and apoptosis have not been fully elucidated. In this study, serum metabolomes of control and APAP-treated wild-type and Cyp2e1-null mice were examined by liquid chromatography-mass spectrometry (LC-MS) and multivariate data analysis. A dose-response study showed that the accumulation of long-chain acylcarnitines in serum contributes to the separation of wild-type mice undergoing APAP-induced hepatotoxicity from other mouse groups in a multivariate model. This observation, in conjunction with the increase of triglycerides and free fatty acids in the serum of APAP-treated wild-type mice, suggested that APAP treatment can disrupt fatty acid beta-oxidation. A time-course study further indicated that both wild-type and Cyp2e1-null mice had their serum acylcarnitine levels markedly elevated within the early hours of APAP treatment. While remaining high in wild-type mice, serum acylcarnitine levels gradually returned to normal in Cyp2e1-null mice at the end of the 24 h treatment. Distinct from serum aminotransferase activity and hepatic glutathione levels, the pattern of serum acylcarnitine accumulation suggested that acylcarnitines can function as complementary biomarkers for monitoring the APAP-induced hepatotoxicity. An essential role for peroxisome proliferator-activated receptor alpha (PPARalpha) in the regulation of serum acylcarnitine levels was established by comparing the metabolomic responses of wild-type and Ppara-null mice to a fasting challenge. The upregulation of PPARalpha activity following APAP treatment was transient in wild-type mice but was much more prolonged in Cyp2e1-null mice. Overall, serum metabolomics of APAP-induced hepatotoxicity revealed that the CYP2E1-mediated metabolic activation and oxidative stress following APAP treatment can cause irreversible inhibition of fatty acid oxidation, potentially through suppression of PPARalpha-regulated pathways.

Fenofibrate metabolism in the cynomolgus monkey using ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry-based metabolomics

Fenofibrate, widely used for the treatment of dyslipidemia, activates the nuclear receptor, peroxisome proliferator-activated receptor alpha. However, liver toxicity, including liver cancer, occurs in rodents treated with fibrate drugs. Marked species differences occur in response to fibrate drugs, especially between rodents and humans, the latter of which are resistant to fibrate-induced cancer. Fenofibrate metabolism, which also shows species differences, has not been fully determined in humans and surrogate primates. In the present study, the metabolism of fenofibrate was investigated in cynomolgus monkeys by ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS)-based metabolomics. Urine samples were collected before and after oral doses of fenofibrate. The samples were analyzed in both positive-ion and negative-ion modes by UPLC-QTOFMS, and after data deconvolution, the resulting data matrices were subjected to multivariate data analysis. Pattern recognition was performed on the retention time, mass/charge ratio, and other metabolite-related variables. Synthesized or purchased authentic compounds were used for metabolite identification and structure elucidation by liquid chromatographytandem mass spectrometry. Several metabolites were identified, including fenofibric acid, reduced fenofibric acid, fenofibric acid ester glucuronide, reduced fenofibric acid ester glucuronide, and compound X. Another two metabolites (compound B and compound AR), not previously reported in other species, were characterized in cynomolgus monkeys. More importantly, previously unknown metabolites, fenofibric acid taurine conjugate and reduced fenofibric acid taurine conjugate were identified, revealing a previously unrecognized conjugation pathway for fenofibrate.