Germination Shifts of C₃ and C₄ Species under Simulated Global Warming Scenario

<div><p>Research efforts around the world have been increasingly devoted to investigating changes in C₃ and C₄ species' abundance or distribution with global warming, as they provide important insight into carbon fluxes and linked biogeochemical cycles. However, changes in the early life stage (e.g. germination) of C₃ and C₄ species in response to global warming, particularly with respect to asymmetric warming, have received less attention. We investigated germination percentage and rate of C₃ and C₄ species under asymmetric (+3/+6°C at day/night) and symmetric warming (+5/+5°C at day/night), simulated by alternating temperatures. A thermal time model was used to calculate germination base temperature and thermal time constant. Two additional alternating temperature regimes were used to test temperature metrics effect. The germination percentage and rate increased continuously for C₄ species, but increased and then decreased with temperature for C₃ species under both symmetric and asymmetric warming. Compared to asymmetric warming, symmetric warming significantly overestimated the speed of germination percentage change with temperature for C₄ species. Among the temperature metrics (minimum, maximum, diurnal temperature range and average temperature), maximum temperature was most correlated with germination of C₄ species. Our results indicate that global warming may favour germination of C₄ species, at least for the C₄ species studied in this work. The divergent effects of asymmetric and symmetric warming on plant germination also deserve more attention in future studies.</p></div

Thermal time model parameter estimates (<i>T_b</i>, minimum temperature; <i>θ</i>₁, thermal time constant) for C₄ and C₃ species under the symmetric warming (SW) and asymmetric warming (AW) alternating temperature regimes.

<p>Thermal time model parameter estimates (<i>T_b</i>, minimum temperature; <i>θ</i>₁, thermal time constant) for C₄ and C₃ species under the symmetric warming (SW) and asymmetric warming (AW) alternating temperature regimes.</p

The two-way ANOVA analysis of the effects of plant photosynthetic type (PPT) and temperature treatments (T) in four temperature regimes on germination percentage and germination rate.

<p>ns, <i>P</i>>0.05;</p><p>*, <i>P</i><0.05;</p><p>**, <i>P</i><0.01;</p><p>***, <i>P</i><0.001</p>†<p>The degree of freedom for TmaxC temperature regime is 10 and df of other temperature regimes is 5.</p

Pearson correlation analysis of germination percentage (GP) and germination rate (GR) with temperature metrics (TM, minimum, maximum, average, diurnal temperature range (DTR)) from the four alternating temperature regimes for C₄ and C₃ species (<i>r</i>, correlation coefficient; <i>P</i>, probability for the correlation).

<p>Pearson correlation analysis of germination percentage (GP) and germination rate (GR) with temperature metrics (TM, minimum, maximum, average, diurnal temperature range (DTR)) from the four alternating temperature regimes for C₄ and C₃ species (<i>r</i>, correlation coefficient; <i>P</i>, probability for the correlation).</p

Germination rates of C₄ and C₃ species under different alternating temperature regimes.

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105139#pone-0105139-g001" target="_blank">Fig. 1</a> for symbols.</p

Trends and Predictors of Transmitted Drug Resistance (TDR) and Clusters with TDR in a Local Belgian HIV-1 Epidemic

<div><p>We aimed to study epidemic trends and predictors for transmitted drug resistance (TDR) in our region, its clinical impact and its association with transmission clusters. We included 778 patients from the AIDS Reference Center in Leuven (Belgium) diagnosed from 1998 to 2012. Resistance testing was performed using population-based sequencing and TDR was estimated using the WHO-2009 surveillance list. Phylogenetic analysis was performed using maximum likelihood and Bayesian techniques. The cohort was predominantly Belgian (58.4%), men who have sex with men (MSM) (42.8%), and chronically infected (86.5%). The overall TDR prevalence was 9.6% (95% confidence interval (CI): 7.7–11.9), 6.5% (CI: 5.0–8.5) for nucleoside reverse transcriptase inhibitors (NRTI), 2.2% (CI: 1.4–3.5) for non-NRTI (NNRTI), and 2.2% (CI: 1.4–3.5) for protease inhibitors. A significant parabolic trend of NNRTI-TDR was found (p = 0.019). Factors significantly associated with TDR in univariate analysis were male gender, Belgian origin, MSM, recent infection, transmission clusters and subtype B, while multivariate and Bayesian network analysis singled out subtype B as the most predictive factor of TDR. Subtype B was related with transmission clusters with TDR that included 42.6% of the TDR patients. Thanks to resistance testing, 83% of the patients with TDR who started therapy had undetectable viral load whereas half of the patients would likely have received a suboptimal therapy without this test. In conclusion, TDR remained stable and a NNRTI up-and-down trend was observed. While the presence of clusters with TDR is worrying, we could not identify an independent, non-sequence based predictor for TDR or transmission clusters with TDR that could help with guidelines or public health measures.</p></div

Examples of subtype B transmission clusters (TCs) with TDR: A maximum likelihood (ML) tree per subtype was constructed, and TCs were confirmed by Bayesian Phylogenetic analyses.

<p>(<b>A</b>) The ML tree for subtype B (Leuven ND cohort and control sequences) with the TCs colored in dark red. (<b>B</b>) The largest TC of subtype B: composed of therapy-naive patients, several nationalities and mutations at RT position 219; bootstrap values above 98% are shown. Abbreviations: AR: Argentina, CY: Cyprus, GE: Germany, IT: Italy, UK: United Kingdom, USA: United States of America, black diamond: men who have sex with men, asterisk: posterior distribution equal to 1 in the Bayesian phylogenetic analysis.</p

Temporal trends and factors associated with transmitted drug resistance (TDR).

<p>(<b>A</b>) Trends of prevalence of TDR (percentage) and the 95% confidence intervals (light shading) among newly diagnosed HIV-1 patients at ARC Leuven (Belgium) from 1998 to 2012 are shown for the overall-TDR, NRTI-TDR, NNRTI-TDR, PI-TDR in blue, MSM overall-TDR and Belgian overall-TDR in red. (<b>B</b>) The significant variables associated with TDR in the univariate analysis were included in the Bayesian network, the number next to the arcs represents the bootstrap support. Abbreviations: NRTI: nucleoside reverse transcriptase inhibitors, NNRTI: non-nucleoside reverse transcriptase inhibitors, MSM: men who have sex with men, PI: protease inhibitors.</p

Characteristics of transmission clusters containing Leuven patients with TDR.

<p>Abbreviations: ARCL: AIDS Reference Center Leuven, CRF: Circulating recombinant form, ESAR: European Society for Translational Antiviral Research, IVDU: intravenous drug user, NRTI: nucleoside reverse transcriptase inhibitors, NNRTI: non-nucleoside reverse transcriptase inhibitors, MSM: men who have sex with men, MTCT: mother to child transmission, PI: protease inhibitors,^†Patient ID includes patients of the Leuven cohort (bold and italics), ESAR controls and accession numbers of NCBI database *Control sequences have available year of sampling. ^‡Control sequences with year of diagnosis available. ^§Sequences were also included when the patient was on antiretroviral treatment.</p