Nitric oxide regulates metabolism in murine stress erythroid progenitors to promote recovery during inflammatory anemia.

Inflammation skews bone marrow hematopoiesis increasing the production of myeloid effector cells at the expense of steady-state erythropoiesis. A compensatory stress erythropoiesis response is induced to maintain homeostasis until inflammation is resolved. In contrast to steady-state erythroid progenitors, stress erythroid progenitors (SEPs) utilize signals induced by inflammatory stimuli. However, the mechanistic basis for this is not clear. Here we reveal a nitric oxide (NO)-dependent regulatory network underlying two stages of stress erythropoiesis, namely proliferation, and the transition to differentiation. In the proliferative stage, immature SEPs and cells in the niche increased expression of inducible nitric oxide synthase ( Nos2 or iNOS ) to generate NO. Increased NO rewires SEP metabolism to increase anabolic pathways, which drive the biosynthesis of nucleotides, amino acids and other intermediates needed for cell division. This NO-dependent metabolism promotes cell proliferation while also inhibiting erythroid differentiation leading to the amplification of a large population of non-committed progenitors. The transition of these progenitors to differentiation is mediated by the activation of nuclear factor erythroid 2-related factor 2 (Nfe2l2 or Nrf2). Nrf2 acts as an anti-inflammatory regulator that decreases NO production, which removes the NO-dependent erythroid inhibition and allows for differentiation. These data provide a paradigm for how alterations in metabolism allow inflammatory signals to amplify immature progenitors prior to differentiation. Key points: Nitric-oxide (NO) dependent signaling favors an anabolic metabolism that promotes proliferation and inhibits differentiation.Activation of Nfe2l2 (Nrf2) decreases NO production allowing erythroid differentiation.

Loss of selenoprotein W in murine macrophages alters the hierarchy of selenoprotein expression, redox tone, and mitochondrial functions during inflammation.

Macrophages play a pivotal role in mediating inflammation and subsequent resolution of inflammation. The availability of selenium as a micronutrient and the subsequent biosynthesis of selenoproteins, containing the 21st amino acid selenocysteine (Sec), are important for the physiological functions of macrophages. Selenoproteins regulate the redox tone in macrophages during inflammation, the early onset of which involves oxidative burst of reactive oxygen and nitrogen species. SELENOW is a highly expressed selenoprotein in bone marrow-derived macrophages (BMDMs). Beyond its described general role as a thiol and peroxide reductase and as an interacting partner for 14-3-3 proteins, its cellular functions, particularly in macrophages, remain largely unknown. In this study, we utilized Selenow knock-out (KO) murine bone marrow-derived macrophages (BMDMs) to address the role of SELENOW in inflammation following stimulation with bacterial endotoxin lipopolysaccharide (LPS). RNAseq-based temporal analyses of expression of selenoproteins and the Sec incorporation machinery genes suggested no major differences in the selenium utilization pathway in the Selenow KO BMDMs compared to their wild-type counterparts. However, selective enrichment of oxidative stress-related selenoproteins and increased ROS in Selenow-/- BMDMs indicated anomalies in redox homeostasis associated with hierarchical expression of selenoproteins. Selenow-/- BMDMs also exhibited reduced expression of arginase-1, a key enzyme associated with anti-inflammatory (M2) phenotype necessary to resolve inflammation, along with a significant decrease in efferocytosis of neutrophils that triggers pathways of resolution. Parallel targeted metabolomics analysis also confirmed an impairment in arginine metabolism in Selenow-/- BMDMs. Furthermore, Selenow-/- BMDMs lacked the ability to enhance characteristic glycolytic metabolism during inflammation. Instead, these macrophages atypically relied on oxidative phosphorylation for energy production when glucose was used as an energy source. These findings suggest that SELENOW expression in macrophages may have important implications on cellular redox processes and bioenergetics during inflammation and its resolution.

Novel EDGE encoding method enhances ability to identify genetic interactions.

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)-rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Semi-automated NMR Pipeline for Environmental Exposures: New Insights on the Metabolomics of Smokers versus Non-smokers.

Environmental exposure pathophysiology related to smoking can yield metabolic changes that are difficult to describe in a biologically informative fashion with manual proprietary software. Nuclear magnetic resonance (NMR) spectroscopy detects compounds found in biofluids yielding a metabolic snapshot. We applied our semi-automated NMR pipeline for a secondary analysis of a smoking study (MTBLS374 from the MetaboLights repository) (n = 112). This involved quality control (in the form of data preprocessing), automated metabolite quantification, and analysis. With our approach we putatively identified 79 metabolites that were previously unreported in the dataset. Quantified metabolites were used for metabolic pathway enrichment analysis that replicated 1 enriched pathway with the original study as well as 3 previously unreported pathways. Our pipeline generated a new random forest (RF) classifier between smoking classes that revealed several combinations of compounds. This study broadens our metabolomic understanding of smoking exposure by 1) notably increasing the number of quantified metabolites with our analytic pipeline, 2) suggesting smoking exposure may lead to heterogenous metabolic responses according to random forest modeling, and 3) modeling how newly quantified individual metabolites can determine smoking status. Our approach can be applied to other NMR studies to characterize environmental risk factors, allowing for the discovery of new biomarkers of disease and exposure status.

Ionized concentrations in Ca2+ and Mg2+ buffers must be measured, not calculated.

NEW FINDINGS: What is the topic of this review? The [Ca2+ ]/[Mg2+ ] in buffers are usually calculated using one of eight programs. These all give different values, thus [Ca2+ ]/[Mg2+ ] must be measured. What advances does it highlight? The ligand optimization method (LOM) using electrodes is an accurate method to do this. The limitations of the method are described. The LOM has been generalized to include calibration of fluorochromes and aequorin. It is the method of choice to measure intracellular equilibrium constants. Owing to the uncertainties for the values of resting [Ca2+ ], ∆[Ca2+ ] and the pK' values for intracellular Ca2+ /Mg2+ binding used in modelling, these values must now be re-examined critically. ABSTRACT: Modelling intracellular regulation of Ca2+ /Mg2+ is now an established part of physiology. However, the conclusions drawn from such studies depend on accurate knowledge of intracellular [Ca2+ ], ∆[Ca2+ ] and the pK' values for the intracellular binding of Ca2+ /Mg2+ . Calculation of [Ca2+ ]/[Mg2+ ] in buffers is normal. The eight freely available programs all give different values for the [Ca2+ ]/[Mg2+ ] in the buffer solutions, varying by up to a factor of 4.3. As a result, concentrations must be measured. There are two methods to do this, both based on the ligand optimization method (LOM): (1) calibration solutions from 0.5 to 4 mmol l-1 ; and (2) calibration solutions from 0.1 µmol l-1 to 2 mmol l-1 . Both methods can be used to calibrate Ca2+ /Mg2+ electrodes. Only Method 2 can be used directly to calibrate fluorochromes and aequorin. Software in the statistical program R to calculate the [Ca2+ ]/[Mg2+ ] in buffers is provided for both methods. The LOM has now been generalized for use with electrodes, fluorochromes and aequorin, making it the ideal method to determine the pK' values for intracellular binding of Ca2+ /Mg2+ . The [Ca2+ ]/[Mg2+ ] in buffers must be measured routinely, which is best done by calibrating electrodes with the LOM and software written in R. If [Ca2+ ]/[Mg2+ ] in buffers are calculated, the parameters used in modelling show the same degree of variability as the software programs. Uncritical acceptance of such parameters means that conclusions reached from such studies are relative, not absolute, and must now be re-examined.

CLARITE Facilitates the Quality Control and Analysis Process for EWAS of Metabolic-Related Traits.

While genome-wide association studies are an established method of identifying genetic variants associated with disease, environment-wide association studies (EWAS) highlight the contribution of nongenetic components to complex phenotypes. However, the lack of high-throughput quality control (QC) pipelines for EWAS data lends itself to analysis plans where the data are cleaned after a first-pass analysis, which can lead to bias, or are cleaned manually, which is arduous and susceptible to user error. We offer a novel software, CLeaning to Analysis: Reproducibility-based Interface for Traits and Exposures (CLARITE), as a tool to efficiently clean environmental data, perform regression analysis, and visualize results on a single platform through user-guided automation. It exists as both an R package and a Python package. Though CLARITE focuses on EWAS, it is intended to also improve the QC process for phenotypes and clinical lab measures for a variety of downstream analyses, including phenome-wide association studies and gene-environment interaction studies. With the goal of demonstrating the utility of CLARITE, we performed a novel EWAS in the National Health and Nutrition Examination Survey (NHANES) (N overall Discovery=9063, N overall Replication=9874) for body mass index (BMI) and over 300 environment variables post-QC, adjusting for sex, age, race, socioeconomic status, and survey year. The analysis used survey weights along with cluster and strata information in order to account for the complex survey design. Sixteen BMI results replicated at a Bonferroni corrected p < 0.05. The top replicating results were serum levels of g-tocopherol (vitamin E) (Discovery Bonferroni p: 8.67x10-12, Replication Bonferroni p: 2.70x10-9) and iron (Discovery Bonferroni p: 1.09x10-8, Replication Bonferroni p: 1.73x10-10). Results of this EWAS are important to consider for metabolic trait analysis, as BMI is tightly associated with these phenotypes. As such, exposures predictive of BMI may be useful for covariate and/or interaction assessment of metabolic-related traits. CLARITE allows improved data quality for EWAS, gene-environment interactions, and phenome-wide association studies by establishing a high-throughput quality control infrastructure. Thus, CLARITE is recommended for studying the environmental factors underlying complex disease.

Ionised concentrations in calcium and magnesium buffers: Standards and precise measurement are mandatory.

In Ca2+ and Mg2+ buffer solutions the ionised concentrations ([X2+]) are either calculated or measured. Calculated values vary by up to a factor of seven due to the following four problems: The calculated [X2+] in buffers are so inconsistent that calculation is not an option. Until standards are available, the [X2+] in the buffers must be measured. The Ligand Optimisation Method is an accurate and independently verified method of doing this (McGuigan & Stumpff, Anal. Biochem. 436, 29, 2013). Lack of standards means it is not possible to compare the published [Ca2+] in the nmolar range, and the apparent constant (K/) values for Ca2+ and Mg2+ binding to intracellular ligands amongst different laboratories. Standardisation of Ca2+/Mg2+ buffers is now essential. The parameters to achieve this are proposed.

Ionised concentrations in calcium and magnesium buffers: Standards and precise measurement are mandatory.

In Ca(2+) and Mg(2+) buffer solutions the ionised concentrations ([X(2+)]) are either calculated or measured. Calculated values vary by up to a factor of seven due to the following four problems: 1) There is no agreement amongst the tabulated constants in the literature. These constants have usually to be corrected for ionic strength and temperature. 2) The ionic strength correction entails the calculation of the single ion activity coefficient, which involves non-thermodynamic assumptions; the data for temperature correction is not always available. 3) Measured pH is in terms of activity i.e. pHa. pHa measurements are complicated by the change in the liquid junction potentials at the reference electrode making an accurate conversion from H(+) activity to H(+) concentration uncertain. 4) Ligands such as EGTA bind water and are not 100% pure. Ligand purity has to be measured, even when the [X(2+)] are calculated. The calculated [X(2+)] in buffers are so inconsistent that calculation is not an option. Until standards are available, the [X(2+)] in the buffers must be measured. The Ligand Optimisation Method is an accurate and independently verified method of doing this (McGuigan & Stumpff, Anal. Biochem. 436, 29, 2013). Lack of standards means it is not possible to compare the published [Ca(2+)] in the nmolar range, and the apparent constant (K(/)) values for Ca(2+) and Mg(2+) binding to intracellular ligands amongst different laboratories. Standardisation of Ca(2+)/Mg(2+) buffers is now essential. The parameters to achieve this are proposed.

An improvement to the ligand optimisation method (LOM) for measuring the apparent dissociation constant and ligand purity in Ca2+ and Mg2+ buffer solutions.

In Ca(2+)/Mg(2+) buffers the calculated ionised concentrations ([X(2+)]) can vary by up to a factor of seven. Since there are no defined standards it is impossible to check calculated [X(2+)], making measurement essential. The ligand optimisation method (LOM) is an accurate method to measure [X(2+)] in Ca(2+)/Mg(2+) buffers; independent estimation of ligand purity extends the method to pK(/) < 4. To simplify calculation, Excel programs ALE and AEC were compiled for LOM and its extension. This paper demonstrates that the slope of the electrode in the pX range 2.000-3.301 deviates from Nernstian behaviour as it depends on the value of the lumped interference, Σ. ALE was modified to include this effect; this modified program SALE, and the programs ALE and AEC were used on simulated data for Ca(2+)-EGTA and Mg(2+)-ATP buffers, to calculate electrode and buffer characteristics as a function of Σ. Ca(2+)-electrodes have a Σ < 10(-6) mol/l and there was no difference amongst the three methods. The Σ for Mg(2+)-electrodes lies between 10(-5) and 1.5 (∗) 10(-5) mol/l and calculated [Mg(2+)] with ALE were around 3% less than the true value. SALE and AEC correctly predicted [Mg(2+)]. SALE was used to recalculate K(/) and pK(/) on measured data for Ca(2+)-EGTA and Mg(2+)-EDTA buffers. These results demonstrated that it is pK(/) that is normally distributed. Until defined standards are available, [X(2+)] in Ca(2+)/Mg(2+) buffers have to be measured. The most appropriate method is to use Ca(2+)/Mg(2) electrodes combined with the Excel programs SALE or AEC.

Measuring Ca(2+) binding to short chain fatty acids and gluconate with a Ca(2+) electrode: role of the reference electrode.

Many organic anions bind free Ca(2+), the total concentration of which must be adjusted in experimental solutions. Because published values for the apparent dissociation constant (Kapp) describing the Ca(2+) affinity of short chain fatty acids (SCFAs) and gluconate are highly variable, Ca(2+) electrodes coupled to either a 3M KCl or a Na(+) selective electrode were used to redetermine Kapp. All solutions contained 130mM Na(+), whereas the concentration of the studied anion was varied from 15 to 120mM, replacing Cl(-) that was decreased concomitantly to maintain osmolarity. This induces changes in the liquid junction potential (LJP) at the 3M KCl reference electrode, leading to a systematic underestimation of Kapp if left uncorrected. Because the Na(+) concentration in all solutions was constant, a Na(+) electrode was used to directly measure the changes in the LJP at the 3 M KCl reference, which were under 5mV but twice those predicted by the Henderson equation. Determination of Kapp either after correction for these LJP changes or via direct reference to a Na(+) electrode showed that SCFAs do not bind Ca(2+) and that the Kapp for the binding of Ca(2+) to gluconate at pH 7.4, ionic strength 0.15M, and 23°C was 52.7mM.

Calculated and measured [Ca(2+)] in buffers used to calibrate Ca(2+) macroelectrodes.

The ionized concentration of calcium in physiological buffers ([Ca(2+)]) is normally calculated using either tabulated constants or software programs. To investigate the accuracy of such calculations, the [Ca(2+)] in EGTA [ethylene glycol-bis(ß-aminoethylether)-N,N,N|,N|-tetraacetic acid], BAPTA [1,2-bis(o-aminophenoxy) ethane-N,N,N|,N|-tetraacetic acid], HEDTA [N-(2-hydroxyethyl)-ethylenediamine-N,N|,N|-triacetic acid], and NTA [N,N-bis(carboxymethyl)glycine] buffers was estimated using the ligand optimization method, and these measured values were compared with calculated values. All measurements overlapped in the pCa range of 3.51 (NTA) to 8.12 (EGTA). In all four buffer solutions, there was no correlation between measured and calculated values; the calculated values differed among themselves by factors varying from 1.3 (NTA) to 6.9 (EGTA). Independent measurements of EGTA purity and the apparent dissociation constants for HEDTA and NTA were not significantly different from the values estimated by the ligand optimization method, further substantiating the method. Using two calibration solutions of pCa 2.0 and 3.01 and seven buffers in the pCa range of 4.0-7.5, calibration of a Ca(2+) electrode over the pCa range of 2.0-7.5 became a routine procedure. It is proposed that such Ca(2+) calibration/buffer solutions be internationally defined and made commercially available to allow the precise measurement of [Ca(2+)] in biology.

Automatic determination of ligand purity and apparent dissociation constant (K(app)) in Ca(2+)/Mg(2+) buffer solutions and the K(app) for Ca(2+)/Mg(2+) anion binding in physiological solutions from Ca(2+)/Mg(2+)-macroelectrode measurements.

Calibration of Ca(2+)/Mg(2+) macroelectrodes and flurochromes in the nmolar and mumolar range, respectively, require the use of buffer solutions. In these buffers the apparent dissociation constant (K(app)) has to be measured since calculation based on tabulated constants gives variable results. The ligand concentration [Ligand](T) has also to be estimated. The most accurate and general method for measuring both is the ligand optimisation method based on macroelectrode potential measurements, but this iterative method is time consuming, thus limiting its application. This paper describes an automatic program based on the method, which on entering the measured macroelectrode data calculates K(app), [Ligand](T) and the ionised concentration [X(2+)] within minutes. This optimisation method cannot be used at K(app) values greater than 0.1mM, but can be extended into this region if the anion concentration is known. The program has been modified to cover this eventuality. Ca(2+)/Mg(2+) macroelectrodes in conjunction with these programs offer an accurate, routine method for determining K(app) and [Ligand](T) in buffer solutions at the appropriate ionic strength, temperature and pH and the K(app) for divalent cations binding to physiological anions under experimental conditions.

Comparison between measured and calculated ionised concentrations in Mg2+ /ATP, Mg2+ /EDTA and Ca2+ /EGTA buffers; influence of changes in temperature, pH and pipetting errors on the ionised concentrations.

The apparent dissociation constants (Kapp) and total ligand concentrations ([Ligand]T) from extensive published and unpublished macroelectrode measurements for Mg2+/ATP, Mg2+/EDTA and Ca2+/EGTA buffers have been recalculated. These calculations were made feasible by the introduction of an Excel program which reduced the time of calculation for Kapp and [Ligand]T from over an hour to under five minutes. These estimations of Kapp and [Ligand]T allowed, not only a comparison between measured and calculated ionised magnesium and calcium concentrations ([Mg2+] and [Ca2+]) for Mg2+/ATP, Mg2+/EDTA and Ca2+/EGTA buffers but also a comparison amongst calculated values. Calculated [X2]1 values always differed from measured, and calculated values differed amongst themselves by factors of at least 2. These variations cast doubts on the published absolute values for intracellular [Mg2+] estimated by 31P-NMR and the resting values for [Ca2+] in cells. The allowable range for [X2+] in the buffers and consequently for Kapp and [Ligand]T has not been defined, which introduces uncertainties into published absolute values for [X2+]. This paper shows that an upper limit of +/- 10% deviation from the mean value for [X2+] is attainable. This requires the temperature to be maintained within +/- 0.5 degrees C, pH within +/- 0.01 units and pipetting errors of less than 0.25%. Until internationally defined buffer standards are available, the lack of correlation between measured and calculated [X2+] means that measurement of Kapp and [Ligand]T and hence [X2+] is more reliable than calculation.

Critical review of the methods used to measure the apparent dissociation constant and ligand purity in Ca2+ and Mg2+ buffer solutions.

Using simulated Ca2+ and Mg2+ buffers, methods proposed to measure both ligand purity and the apparent dissociation constant (Kapp) were investigated regarding (1) predicted accuracy of both parameters and (2) generality of the solution. The Bers' Ca2+ macroelectrode method [Bers, D. M., 1982 A simple method for the determination of free [Ca] in Ca-EGTA solutions Am. J. Physiol. 242, C404-C408] cannot be used with Mg2+ -macroelectrodes and is partly arbitrary since the linear part of the Scatchard plot is judged subjectively. Iterative methods have therefore been introduced. Iteration based on Bers' method or the lumped interference in the Nicolsky-Eisenman equation also failed with Mg2+ macroelectrodes. The Oiki et al., method [Oiki, S., Yomamoto, T., Okada, Y., 1994. Apparent stability constants and purity of Ca-chelating agents evaluated using Ca-sensitive electrodes by the double-log optimization method Cell Calcium 15, 209-46.] cannot be applied to Mg2+ macroelectrodes. The pH titration method of Moisescu and Pusch (Pflügers, Arch., 355, R122, 1975) predicted EGTA purity and Ca2+ contamination, but Kapp values for EGTA were approximate. It cannot be applied to Mg2+ binding. The partition method [Godt, R.E., 1974. Calcium-activated tension of skinned muscle fibres of the frog. Dependence on magnesium adenosine triphosphate concentration J. Gen. Physiol. 63, 722-739.] only approximately estimated the K(app). Calibration, maintaining contaminating [Ca2+]/[Mg2+] at < 1micromol l(-1), and setting standards by dilution, is the ultimate check of calculated ionised concentrations, although technically difficult. The macroelectrode method of Lüthi et al. [1997. Calibration of Mg2+ -selective macromolecules down to 1 micromol l(-1) in intracellular and Ca+ - containing extracellular solutions. Exp. Physiol. 82, 453-467] accurately predicted purity and Kapp at pKapp values > 4 and was independent of electrode characteristics. It is considered the method of choice. Macroelectrode primary calibration should be carried out in solutions varying from 0.5 to 10 mmol l(-1) combined with either Ca-EGTA or Mg-EDTA buffers; the [Ca2+] and [Mg2+] in other buffer ligands can be measured in a secondary calibration.

Use of Mg2+ and Ca2+ macroelectrodes to measure binding in extracellular-like physiological solutions.

Macroelectrodes designed to measure the extracellular free Mg2+ and Ca2+ concentrations ([Mg2+]o, [Ca2+]o) may be used to determine Mg2+ and Ca2+ binding to extracellular buffers. This is important, as buffer concentrations may change physiologically or experimentally. A simplified calibration method allowed [Mg2+]o and [Ca2+]o > 50 micromol/l to be accurately measured. The method was used to determine the apparent dissociation constant, Kapp (+/- SD) of Mg2+ binding to aspartate (22 degrees C, 101.7 +/- 22.5 mmol/l, n = 8; 44 degrees C, 45.2 +/- 8.3 mmol/l, n = 6), citrate (high affinity, 0.33 +/- 0.14 mmol/l, n = 4; low affinity, approximately 80 mmol/l), malate (15.9 +/- 1.0 mmol/l, n = 7) and Ca2+ binding to malate (10.3 +/- 1.1 mmol/l, n = 7). Calculated and measured Kapp for Ca2+ binding to malate were only in agreement if the concept of ionic equivalent was used to adapt the tabulated constants to the experimental conditions. For Mg2+ binding to aspartate, malate and citrate there was no or only limited agreement with the calculated Kapp. These findings emphasise the difficulties involved in calculating free concentrations in biological solutions. It is concluded that it is more accurate to measure Kapp at the appropriate ionic strength and temperature.