Trade‐offs between constitutive and induced defences drive geographical and climatic clines in pine chemical defences

There is increasing evidence that geographic and climatic clines drive the patterns of plant defence allocation and defensive strategies. We quantified early growth rate and both constitutive and inducible chemical defences of 18 Pinaceae species in a common greenhouse environment and assessed their defensive allocation with respect to each species' range across climatic gradients spanning 31^o latitude and 2300 m elevation. Constitutive defences traded‐off with induced defences, and these defensive strategies were associated with growth rate such that slow‐growing species invested more in constitutive defence, whereas fast‐growing species invested more in inducible defence. The position of each pine species along this trade‐off axis was in turn associated with geography; moving poleward and to higher elevations, growth rate and inducible defences decreased, while constitutive defence increased. These geographic patterns in plant defence were most strongly associated with variation in temperature. Climatic and geographical clines thus act as drivers of defence profiles by mediating the constraints imposed by trade‐offs, and this dynamic underlays global patterns of defence allocation.     

Thiol redox biochemistry: insights from computer simulations

Thiol redox chemical reactions play a key role in a variety of physiological processes, mainly due to the presence of low-molecular-weight thiols and cysteine residues in proteins involved in catalysis and regulation. Specifically, the subtle sensitivity of thiol reactivity to the environment makes the use of simulation techniques extremely valuable for obtaining microscopic insights. In this work we review the application of classical and quantum–mechanical atomistic simulation tools to the investigation of selected relevant issues in thiol redox biochemistry, such as investigations on (1) the protonation state of cysteine in protein, (2) two-electron oxidation of thiols by hydroperoxides, chloramines, and hypochlorous acid, (3) mechanistic and kinetics aspects of the de novo formation of disulfide bonds and thiol−disulfide exchange, (4) formation of sulfenamides, (5) formation of nitrosothiols and transnitrosation reactions, and (6) one-electron oxidation pathways.     

Balance between the two kinin receptors in the progression of experimental focal and segmental glomerulosclerosis in mice

Focal and segmental glomerulosclerosis (FSGS) is one of the most important renal diseases related to end-stage renal failure. Bradykinin has been implicated in the pathogenesis of renal inflammation, whereas the role of its receptor 2 (B2RBK; also known as BDKRB2) in FSGS has not been studied. FSGS was induced in wild-type and B2RBK-knockout mice by a single intravenous injection of Adriamycin (ADM). In order to further modulate the kinin receptors, the animals were also treated with the B2RBK antagonist HOE-140 and the B1RBK antagonist DALBK. Here, we show that the blockage of B2RBK with HOE-140 protects mice from the development of FSGS, including podocyte foot process effacement and the re-establishment of slit-diaphragm-related proteins. However, B2RBK-knockout mice were not protected from FSGS. These opposite results were due to B1RBK expression. B1RBK was upregulated after the injection of ADM and this upregulation was exacerbated in B2RBK-knockout animals. Furthermore, treatment with HOE-140 downregulated the B1RBK receptor. The blockage of B1RBK in B2RBK-knockout animals promoted FSGS regression, with a less-inflammatory phenotype. These results indicate a deleterious role of both kinin receptors in an FSGS model and suggest a possible cross-talk between them in the progression of disease.KEY WORDS: Focal and segmental glomerulosclerosis, Bradykinin receptors, Inflammation, Podocyte, Fibrosis     

Glucose Kinetics in the Collagen-Induced Arthritis Model: An All-in-One Model to Assess Both Efficacy and Metabolic Side Effects of Glucocorticoids

Prednisolone and other glucocorticoids (GCs) are potent anti-inflammatory drugs, but chronic use is hampered by metabolic side effects. Therefore, there is an urgent medical need for improved GCs that are as effective as classical GCs but have a better safety profile. A well-established model to assess anti-inflammatory efficacy is the chronic collagen-induced arthritis (CIA) model in mice, a model with features resembling rheumatoid arthritis. Models to quantify undesired effects of glucocorticoids on glucose kinetics are less well-established. Recently, we have described a model to quantify basal blood glucose kinetics using stably-labeled glucose. In the present study, we have integrated this blood glucose kinetic model in the CIA model to enable quantification of both efficacy and adverse effects in one animal model. Arthritis scores were decreased after treatment with prednisolone, confirming the anti-inflammatory properties of GCs. Both inflammation and prednisolone induced insulin resistance as insulin secretion was strongly increased whereas blood glucose concentrations and hepatic glucose production were only slightly decreased. This insulin resistance did not directly resulted in hyperglycemia, indicating a highly adaptive compensatory mechanism in these mice. In conclusion, this ‘all-in-one’ model allows for studying effects of (novel) GC compounds on the development of arthritis and glucose kinetics in a single animal. This integrative model provides a valuable tool for investigating (drug-induced) metabolic dysregulation in an inflammatory setting.     

Deep-Sequencing of the Peach Latent Mosaic Viroid Reveals New Aspects of Population Heterogeneity

Viroids are small circular single-stranded infectious RNAs characterized by a relatively high mutation level. Knowledge of their sequence heterogeneity remains largely elusive and previous studies, using Sanger sequencing, were based on a limited number of sequences. In an attempt to address sequence heterogeneity from a population dynamics perspective, a GF305-indicator peach tree was infected with a single variant of the Avsunviroidae family member Peach latent mosaic viroid (PLMVd). Six months post-inoculation, full-length circular conformers of PLMVd were isolated and deep-sequenced. We devised an original approach to the bioinformatics refinement of our sequence libraries involving important phenotypic data, based on the systematic analysis of hammerhead self-cleavage activity. Two distinct libraries yielded a total of 3,939 different PLMVd variants. Sequence variants exhibiting up to ∼17% of mutations relative to the inoculated viroid were retrieved, clearly illustrating the high level of divergence dynamics within a unique population. While we initially assumed that most positions of the viroid sequence would mutate, we were surprised to discover that ∼50% of positions remained perfectly conserved, including several small stretches as well as a small motif reminiscent of a GNRA tetraloop which are the result of various selective pressures. Using a hierarchical clustering algorithm, the different variants harvested were subdivided into 7 clusters. We found that most sequences contained an average of 4.6 to 6.4 mutations compared to the variant used to initially inoculate the plant. Interestingly, it was possible to reconstitute and compare the sequence evolution of each of these clusters. In doing so, we identified several key mutations. This study provides a reliable pipeline for the treatment of viroid deep-sequencing. It also sheds new light on the extent of sequence variation that a viroid population can sustain, and which may give rise to a quasispecies.     

DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.     

Anti-Human Herpesvirus 6A/B IgG Correlates with Relapses and Progression in Multiple Sclerosis

Objective

To analyze the titers of the IgG and IgM antibodies against human herpesvirus 6A/B (HHV-6A/B) in multiple sclerosis (MS) patients treated with different disease modified therapies (DMTs) along two-years of follow-up.

Methods

We collected 2163 serum samples from 596 MS; for 301 MS patients a 2-years follow-up was performed. Serum samples of 337 healthy controls were also analyzed. Anti-HHV-6A/B IgG and IgM were analyzed by ELISA (Panbio).

Results

We found that 129/187 (69.0%) MS patients with a decrease of the anti-HHV-6A/B IgG titers after 2-years with DMTs were free of relapses and progression vs. 46/113 (40.7%) of MS patients with an increase of the anti-HHV-6A/B IgG titers (p = 0.0000015); the higher significance was found for natalizumab. Furthermore, we found that anti-HHV-6A/B IgG titers reached their highest value two weeks before the relapse (p = 0.0142), while the anti-HHV-6A/B IgM titers reached their highest value one month before the relapse (p = 0.0344).

Conclusion

The measurement of the anti-HHV-6A/B IgG titers could be a good biomarker of clinical response to the different DMTs. The increase of the anti-HHV-6A/B IgG and IgM titers predicts the upcoming clinical relapses. However, further longitudinal studies are needed to validate these results.