Isotopic and molecular distributions of biochemicals from fresh and buried Rhizophora mangle leaves†

Rhizophora mangle L. (red mangrove) is the dominant species of mangrove in the Americas. At Twin Cays, Belize (BZ) red mangroves are present in a variety of stand structures (tall >5 m in height, transition ~2–4 m and dwarf ~1–1.5 m). These height differences are coupled with very different stable carbon and nitrogen isotopic values[1] (mean tall δ(13)C = -28.3‰, δ(15)N = 0‰; mean tall δ(13)C = -25.3‰, δ(15)N = -10‰). To determine the utility of using these distinct isotopic compositions as 'biomarkers' for paleoenvironmental reconstruction of mangrove ecosystems and nutrient availability, we investigated the distribution and isotopic (δ(13)C and δ(15)N) composition of different biochemical fractions (water soluble compounds, free lipids, acid hydrolysable compounds, individual amino acids, and the residual un-extractable compounds) in fresh and preserved red mangrove leaves from dwarf and tall trees. The distribution of biochemicals are similar in dwarf and tall red mangrove leaves, suggesting that, regardless of stand structure, red mangroves use nutrients for biosynthesis and metabolism in a similar manner. However, the δ(13)C and δ(15)N of the bulk leaf, the biochemical fractions, and seven amino acids can be used to distinguish dwarf and tall trees at Twin Cays, BZ. The data support the theory that the fractionation of carbon and nitrogen occurs prior to or during uptake in dwarf and tall red mangrove trees. Stable carbon and nitrogen isotopes could, therefore, be powerful tools for predicting levels of nutrient limitation at Twin Cays. The δ(13)C and δ(15)N of biochemical fractions within preserved leaves, reflect sedimentary cycling and nitrogen immobilization. The δ(15)N of the immobilized fraction reveals the overlying stand structure at the time of leaf deposition. The isotopic composition of preserved mangrove leaves could yield significant information about changes in ecosystem dynamics, nutrient limitation and past stand structure in mangrove paleoecosystems

A novel point mutation in P450c17 (CYP17) causing combined 17 alpha-hydroxylase/17,20-lyase deficiency

Context: Combined 17 alpha-hydroxylase/17,20-lyase deficiency is a rare cause of congenital adrenal hyperplasia and hypogonadism. Novel single amino acid changes in P450c17 provide potentially important insights into key structural domains for enzyme function.Objective, Design, and Setting: We report a novel missense mutation in P450c17 in a 17-yr-old female presenting with a malignant mixed germ cell tumor with yolk sac elements who demonstrated clinical and biochemical features of combined 17 alpha-hydroxylase/17,20-lyase deficiency.Methods: Quantitative urinary steroid analysis was performed by high resolution gas chromatography. All eight coding exons of CYP17 were PCR amplified and sequenced. The position of arginine at codon 96 was modeled using the CYP17 structure 2c17 (www.rcsb.org). The CYP17 genes were subcloned into pcDNA3, expressed in HEK-293 cells, and chromatographed.Patient and Results: 17 beta-Hydroxylase deficiency was confirmed by marked reductions in urinary and serum cortisol, androgens, and estradiol. Mutational analysis revealed a novel homozygous R96Q missense mutation in P450c17, affecting an amino acid in a key substrate-binding region of the enzyme, leading to complete inactivity.Conclusion: The description of a second missense mutation at codon 96 (R96W and R96Q) in the substrate-binding region of P450c17 provides strong evidence for the key role of this amino acid in 17 alpha-hydroxylase/17,20-lyase function. An association between a malignant germ cell tumor and 17 alpha-hydroxylase deficiency has not been reported previously, although the presence of gonadoblastoma in the ovary of a patient with this condition has recently been described

The relationship between smoking and quality of life in advanced lung cancer patients: a prospective longitudinal study.

PURPOSE: Smoking is a major cause of lung cancer, and continued smoking may compromise treatment efficacy and quality of life (health-related quality of life (HRQoL)) in patients with advanced lung cancer. Our aims were to determine (i) preference for treatments which promote quality over length of life depending on smoking status, (ii) the relationship between HRQoL and smoking status at diagnosis (T1), after controlling for demographic and clinical variables, and (iii) changes in HRQoL 6 months after diagnosis (T2) depending on smoking status. METHODS: Two hundred ninety-six patients with advanced lung cancer were given questionnaires to assess HRQoL (EORTC QLQ-C30), time-trade-off for life quality versus quantity (QQQ) and smoking history (current, former or never smoker) at diagnosis (T1) and 6 months later (T2). Medical data were extracted from case records. RESULTS: Questionnaires were returned by 202 (68.2 %) patients at T1 and 114 (53.3 %) at T2. Patients favoured treatments that would enhance quality of life over increased longevity. Those who continued smoking after diagnosis reported worse HRQoL than former smokers or those who never smoked. Smoking status was a significant independent predictor of coughing in T1 (worse in smokers) and cognitive functioning in T2 (better in never smokers). CONCLUSIONS: Smoking by patients with advanced lung cancer is associated with worse symptoms on diagnosis and poorer HRQoL for those who continue smoking. The results have implications to help staff explain the consequences of smoking to patients

Mitochondrial echoes of first settlement and genetic continuity in El Salvador

Background: From Paleo-Indian times to recent historical episodes, the Mesoamerican isthmus played an important role in the distribution and patterns of variability all around the double American continent. However, the amount of genetic information currently available on Central American continental populations is very scarce. In order to shed light on the role of Mesoamerica in the peopling of the New World, the present study focuses on the analysis of the mtDNA variation in a population sample from El Salvador. Methodology/Principal Findings: We have carried out DNA sequencing of the entire control region of the mitochondrial DNA (mtDNA) genome in 90 individuals from El Salvador. We have also compiled more than 3,985 control region profiles from the public domain and the literature in order to carry out inter-population comparisons. The results reveal a predominant Native American component in this region: by far, the most prevalent mtDNA haplogroup in this country (at ~90%) is A2, in contrast with other North, Meso- and South American populations. Haplogroup A2 shows a star-like phylogeny and is very diverse with a substantial proportion of mtDNAs (45%; sequence range 16090–16365) still unobserved in other American populations. Two different Bayesian approaches used to estimate admixture proportions in El Salvador shows that the majority of the mtDNAs observed come from North America. A preliminary founder analysis indicates that the settlement of El Salvador occurred about 13,400±5,200 Y.B.P.. The founder age of A2 in El Salvador is close to the overall age of A2 in America, which suggests that the colonization of this region occurred within a few thousand years of the initial expansion into the Americas. Conclusions/Significance: As a whole, the results are compatible with the hypothesis that today's A2 variability in El Salvador represents to a large extent the indigenous component of the region. Concordant with this hypothesis is also the observation of a very limited contribution from European and African women (~5%). This implies that the Atlantic slave trade had a very small demographic impact in El Salvador in contrast to its transformation of the gene pool in neighbouring populations from the Caribbean facade

Diversity of isoprene-degrading bacteria in phyllosphere and soil communities from a high isoprene-emitting environment: a Malaysian oil palm plantation

Background: Isoprene is the most abundantly produced biogenic volatile organic compound (BVOC) on Earth, with annual global emissions almost equal to those of methane. Despite its importance in atmospheric chemistry and climate, little is known about the biological degradation of isoprene in the environment. The largest source of isoprene is terrestrial plants, and oil palms, the cultivation of which is expanding rapidly, are among the highest isoprene-producing trees. Results: DNA stable isotope probing (DNA-SIP) to study the microbial isoprene-degrading community associated with oil palm trees revealed novel genera of isoprene-utilising bacteria including Novosphingobium, Pelomonas, Rhodoblastus, Sphingomonas and Zoogloea in both oil palm soils and on leaves. Amplicon sequencing of isoA genes, which encode the α-subunit of the isoprene monooxygenase (IsoMO), a key enzyme in isoprene metabolism, confirmed that oil palm trees harbour a novel diversity of isoA sequences. In addition, metagenome assembled genomes (MAGs) were reconstructed from oil palm soil and leaf metagenomes and putative isoprene degradation genes were identified. Analysis of unenriched metagenomes showed that isoA-containing bacteria are more abundant in soils than in the oil palm phyllosphere. Conclusion: This study greatly expands the known diversity of bacteria that can metabolise isoprene and contributes to a better understanding of the biological degradation of this important but neglected climate-active gas

Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone