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.

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.

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.

Continental-scale temperature variability during the past two millennia

Past global climate changes had strong regional expression. To elucidate their spatio-temporal pattern, we reconstructed past temperatures for seven continental-scale regions during the past one to two millennia. The most coherent feature in nearly all of the regional temperature reconstructions is a long-term cooling trend, which ended late in the nineteenth century. At multi-decadal to centennial scales, temperature variability shows distinctly different regional patterns, with more similarity within each hemisphere than between them. There were no globally synchronous multi-decadal warm or cold intervals that define a worldwide Medieval Warm Period or Little Ice Age, but all reconstructions show generally cold conditions between ad 1580 and 1880, punctuated in some regions by warm decades during the eighteenth century. The transition to these colder conditions occurred earlier in the Arctic, Europe and Asia than in North America or the Southern Hemisphere regions. Recent warming reversed the long-term cooling; during the period ad 1971–2000, the area-weighted average reconstructed temperature was higher than any other time in nearly 1,400 years.

Genomics and the origin of species

Speciation is a fundamental evolutionary process, the knowledge of which is crucial for understanding the origins of biodiversity. Genomic approaches are an increasingly important aspect of this research field. We review current understanding of genome-wide effects of accumulating reproductive isolation and of genomic properties that influence the process of speciation. Building on this work, we identify emergent trends and gaps in our understanding, propose new approaches to more fully integrate genomics into speciation research, translate speciation theory into hypotheses that are testable using genomic tools and provide an integrative definition of the field of speciation genomics

Inter-hemispheric temperature variability over the past millennium

The Earth’s climate system is driven by a complex interplay of internal chaotic dynamics and natural and anthropogenic external forcing. Recent instrumental data have shown a remarkable degree of asynchronicity between Northern Hemisphere and Southern Hemisphere temperature fluctuations, thereby questioning the relative importance of internal versus external drivers of past as well as future climate variability1, 2, 3. However, large-scale temperature reconstructions for the past millennium have focused on the Northern Hemisphere4, 5, limiting empirical assessments of inter-hemispheric variability on multi-decadal to centennial timescales. Here, we introduce a new millennial ensemble reconstruction of annually resolved temperature variations for the Southern Hemisphere based on an unprecedented network of terrestrial and oceanic palaeoclimate proxy records. In conjunction with an independent Northern Hemisphere temperature reconstruction ensemble5, this record reveals an extended cold period (1594–1677) in both hemispheres but no globally coherent warm phase during the pre-industrial (1000–1850) era. The current (post-1974) warm phase is the only period of the past millennium where both hemispheres are likely to have experienced contemporaneous warm extremes. Our analysis of inter-hemispheric temperature variability in an ensemble of climate model simulations for the past millennium suggests that models tend to overemphasize Northern Hemisphere–Southern Hemisphere synchronicity by underestimating the role of internal ocean–atmosphere dynamics, particularly in the ocean-dominated Southern Hemisphere. Our results imply that climate system predictability on decadal to century timescales may be lower than expected based on assessments of external climate forcing and Northern Hemisphere temperature variations5, 6 alone.

Evaluation of Cage Designs and Feeding Regimes for Honey Bee (Hymenoptera: Apidae) Laboratory Experiments

The aim of this study was to improve cage systems for maintaining adult honey bee (Apis mellifera L.) workers under in vitro laboratory conditions. To achieve this goal, we experimentally evaluated the impact of different cages, developed by scientists of the international research network COLOSS (Prevention of honey bee COlony LOSSes), on the physiology and survival of honey bees. We identified three cages that promoted good survival of honey bees. The bees from cages that exhibited greater survival had relatively lower titers of deformed wing virus, suggesting that deformed wing virus is a significant marker reflecting stress level and health status of the host. We also determined that a leak- and drip-proof feeder was an integral part of a cage system and a feeder modified from a 20-ml plastic syringe displayed the best result in providing steady food supply to bees. Finally, we also demonstrated that the addition of protein to the bees' diet could significantly increase the level ofvitellogenin gene expression and improve bees' survival. This international collaborative study represents a critical step toward improvement of cage designs and feeding regimes for honey bee laboratory experiments.

Genome-wide Association Studies Identify Genetic Loci Associated with Albuminuria in Diabetes

Elevated concentrations of albumin in the urine, albuminuria, are a hallmark of diabetic kidney disease and associate with increased risk for end-stage renal disease and cardiovascular events. To gain insight into the pathophysiological mechanisms underlying albuminuria, we conducted meta-analyses of genome-wide association studies and independent replication in up to 5,825 individuals of European ancestry with diabetes mellitus and up to 46,061 without diabetes, followed by functional studies. Known associations of variants in CUBN, encoding cubilin, with the urinary albumin-to-creatinine ratio (UACR) were confirmed in the overall sample (p=2.4*10(-10)). Gene-by-diabetes interactions were detected and confirmed for variants in HS6ST1 and near RAB38/CTSC. SNPs at these loci demonstrated a genetic effect on UACR in individuals with but not without diabetes. The change in average UACR per minor allele was 21% for HS6ST1 and 13% for RAB38/CTSC (p=6.3*10(-7) and 5.8*10(-7), respectively). Experiments using streptozotocin-treated diabetic Rab38 knockout and control rats showed higher urinary albumin concentrations and reduced amounts of megalin and cubilin at the proximal tubule cell surface in Rab38 knockout vs. control rats. Relative expression of RAB38 was higher in tubuli of patients with diabetic kidney disease compared to controls. The loci identified here confirm known and highlight novel pathways influencing albuminuria.

Murine coronavirus ubiquitin-like domain is important for papain-like protease stability and viral pathogenesis

Ubiquitin-like domains (Ubls) now are recognized as common elements adjacent to viral and cellular proteases; however, their function is unclear. Structural studies of the papain-like protease (PLP) domains of coronaviruses (CoVs) revealed an adjacent Ubl domain in severe acute respiratory syndrome CoV, Middle East respiratory syndrome CoV, and the murine CoV, mouse hepatitis virus (MHV). Here, we tested the effect of altering the Ubl adjacent to PLP2 of MHV on enzyme activity, viral replication, and pathogenesis. Using deletion and substitution approaches, we identified sites within the Ubl domain, residues 785 to 787 of nonstructural protein 3, which negatively affect protease activity, and valine residues 785 and 787, which negatively affect deubiquitinating activity. Using reverse genetics, we engineered Ubl mutant viruses and found that AM2 (V787S) and AM3 (V785S) viruses replicate efficiently at 37°C but generate smaller plaques than wild-type (WT) virus, and AM2 is defective for replication at higher temperatures. To evaluate the effect of the mutation on protease activity, we purified WT and Ubl mutant PLP2 and found that the proteases exhibit similar specific activities at 25°C. However, the thermal stability of the Ubl mutant PLP2 was significantly reduced at 30°C, thereby reducing the total enzymatic activity. To determine if the destabilizing mutation affects viral pathogenesis, we infected C57BL/6 mice with WT or AM2 virus and found that the mutant virus is highly attenuated, yet it replicates sufficiently to elicit protective immunity. These studies revealed that modulating the Ubl domain adjacent to the PLP reduces protease stability and viral pathogenesis, revealing a novel approach to coronavirus attenuation. IMPORTANCE Introducing mutations into a protein or virus can have either direct or indirect effects on function. We asked if changes in the Ubl domain, a conserved domain adjacent to the coronavirus papain-like protease, altered the viral protease activity or affected viral replication or pathogenesis. Our studies using purified wild-type and Ubl mutant proteases revealed that mutations in the viral Ubl domain destabilize and inactivate the adjacent viral protease. Furthermore, we show that a CoV encoding the mutant Ubl domain is unable to replicate at high temperature or cause lethal disease in mice. Our results identify the coronavirus Ubl domain as a novel modulator of viral protease stability and reveal manipulating the Ubl domain as a new approach for attenuating coronavirus replication and pathogenesis.

Environmental correlates of species rank − abundance distributions in global drylands

Theoretical models predict lognormal species abundance distributions (SADs) in stable and productive environments, with log-series SADs in less stable, dispersal driven communities. We studied patterns of relative species abundances of perennial vascular plants in global dryland communities to: (i) assess the influence of climatic and soil characteristics on the observed SADs, (ii) infer how environmental variability influences relative abundances, and (iii) evaluate how colonisation dynamics and environmental filters shape abundance distributions. We fitted lognormal and log-series SADs to 91 sites containing at least 15 species of perennial vascular plants. The dependence of species relative abundances on soil and climate variables was assessed using general linear models. Irrespective of habitat type and latitude, the majority of the SADs (70.3%) were best described by a lognormal distribution. Lognormal SADs were associated with low annual precipitation, higher aridity, high soil carbon content, and higher variability of climate variables and soil nitrate. Our results do not corroborate models predicting the prevalence of log-series SADs in dryland communities. As lognormal SADs were particularly associated with sites with drier conditions and a higher environmental variability, we reject models linking lognormality to environmental stability and high productivity conditions. Instead our results point to the prevalence of lognormal SADs in heterogeneous environments, allowing for more evenly distributed plant communities, or in stressful ecosystems, which are generally shaped by strong habitat filters and limited colonisation. This suggests that drylands may be resilient to environmental changes because the many species with intermediate relative abundances could take over ecosystem functioning if the environment becomes suboptimal for dominant species.