Trait variation in juvenile plants from the soil seed bank of temperate forests in relation to macro- and microclimate

Aim

The soil seed bank is a key component of the biodiversity of plant communities, but various aspects of its functioning in temperate forest ecosystems are still unknown. We here adopted a trait-based approach to investigate the effects of macro- and microclimatic gradients on the juvenile plant communities from the realized seed bank of two types of European temperate forest.

Location

Oak-dominated forests in Italy and Belgium.

Methods

We analysed the variation of key functional traits (plant height, leaf area, leaf dry weight, specific leaf area and leaf number) of juvenile plants from the realised soil seed bank in relation to elevation (from 0 to 800 m a.s.l.), forest type (thinned and unthinned forest) and distance to the forest edge. We translocated soil samples from the forest core to the edge (and vice versa) and from high- to low-elevation forests to test the effects of edge and warming respectively.

Results

Taller communities developed at the forest edge due to higher light availability and warmer temperatures. The translocation from the core to the edge did not significantly modify mean trait values. Instead, the shadier and cooler microclimate of the forest core reduced the mean leaf area, mean dry weight, height and leaf number in the communities realised from the edge soil. The translocation from high- to lowland forests led to increased values for all traits (except specific leaf area). Edge vs core trait variation was more driven by intraspecific variability, whereas the translocation from high- to low-elevation forests caused trait changes mostly due to species turnover.

Conclusions

Global warming might result in a functional shift of the understorey due to both an early filtering effect on the seedlings from soil seed banks and their adaptive trait adjustments to temperature increase. Furthermore, our study underpins the importance of edge vs core microclimate in driving the functional composition of the realised soil seed bank.     

CT Air Trapping Is Independently Associated with Lung Function Reduction over Time

Purpose

We aimed to study the association between lung function decline and quantitative computed tomography (CT) air trapping.

Materials and Methods

Current and former heavy smokers in a lung cancer screening trial underwent volumetric low-dose CT in inspiration and expiration. Spirometry was obtained at baseline and after 3 years. The expiratory to inspiratory ratio of mean lung density (E/I-ratio_MLD) was used to quantify air trapping. CT emphysema was defined as voxels in inspiratory CT below −950 Hounsfield Unit. Linear mixed modeling was used to determine the association between CT air trapping and lung function.

Results

We included 985 subjects with a mean age of 61.3 years. Independent of CT emphysema, CT air trapping was significantly associated with a reduction in forced expiratory volume in one second (FEV₁) and the ratio of FEV₁ over the forced vital capacity (FEV₁/FVC); FEV₁ declines with 33 mL per percent increase in CT air trapping, while FEV₁/FVC declines 0.58% per percent increase (both p<0.001). CT air trapping further elicits accelerated loss of FEV₁/FVC (additional 0.24% reduction per percent increase; p = 0.014).

Conclusion

In a lung cancer screening cohort, quantitatively assessed air trapping on low-dose CT is independently associated with reduced lung function and accelerated decline of FEV₁/FVC.     

Phenotypical variation within 22 families with Pompe disease

Background

Pompe disease has a broad clinical spectrum, in which the phenotype is partially explained by the genotype. The aim of this study was to describe phenotypical variation among siblings with non-classic Pompe disease. We hypothesized that siblings and families with the same genotype share more similar phenotypes than the total population of non-classic Pompe patients, and that this might reveal genotype-phenotype correlations.

Methods

We identified all Dutch families in which two or three siblings were diagnosed with Pompe disease and described genotype, acid α-glucosidase activity, age at symptom onset, presenting symptoms, specific clinical features, mobility and ventilator dependency.

Results

We identified 22 families comprising two or three siblings. All carried the most common mutation c.-32-13 T?>?G in combination with another pathogenic mutation. The median age at symptom onset was 33 years (range 1–62 years). Within sibships symptom onset was either in childhood or in adulthood. The median variation in symptom onset between siblings was nine years (range 0–31 years). Presenting symptoms were similar across siblings in 14 out of 22 families. Limb girdle weakness was most frequently reported. In some families ptosis or bulbar weakness were present in all siblings. A large variation in disease severity (based on wheelchair/ventilator dependency) was observed in 11 families. This variation did not always result from a difference in duration of the disease since a third of the less affected siblings had a longer course of the disease. Enzyme activity could not explain this variation either. In most families male patients were more severely affected. Finally, symptom onset varied substantially in twelve families despite the same GAA genotype.

Conclusion

In most families with non-classic Pompe disease siblings share a similar phenotype regarding symptom onset, presenting symptoms and specific clinical features. However, in some families the course and severity of disease varied substantially. This phenotypical variation was also observed in families with identical GAA genotypes. The commonalities and differences indicate that besides genotype, other factors such as epigenetic and environmental effects influence the clinical presentation and disease course.

     

Deconvolution and Database Search of Complex Tandem Mass Spectra of Intact Proteins: A COMBINATORIAL APPROACH*

Top-down proteomics studies intact proteins, enabling new opportunities for analyzing post-translational modifications. Because tandem mass spectra of intact proteins are very complex, spectral deconvolution (grouping peaks into isotopomer envelopes) is a key initial stage for their interpretation. In such spectra, isotopomer envelopes of different protein fragments span overlapping regions on the m/z axis and even share spectral peaks. This raises both pattern recognition and combinatorial challenges for spectral deconvolution. We present MS-Deconv, a combinatorial algorithm for spectral deconvolution. The algorithm first generates a large set of candidate isotopomer envelopes for a spectrum, then represents the spectrum as a graph, and finally selects its highest scoring subset of envelopes as a heaviest path in the graph. In contrast with other approaches, the algorithm scores sets of envelopes rather than individual envelopes. We demonstrate that MS-Deconv improves on Thrash and Xtract in the number of correctly recovered monoisotopic masses and speed. We applied MS-Deconv to a large set of top-down spectra from Yersinia rohdei (with a still unsequenced genome) and further matched them against the protein database of related and sequenced bacterium Yersinia enterocolitica. MS-Deconv is available at http://proteomics.ucsd.edu/Software.html.Top-down proteomics is a mass spectrometry-based approach for identification of proteins and their post-translational modifications (PTMs)1 (1–14). Unlike the “bottom-up” approach where proteins are first digested into peptides and then a peptide mixture is analyzed by mass spectrometry, the top-down approach analyzes intact proteins. Thus, it has advantages in detecting and localizing PTMs as well as identifying multiple protein species (e.g. proteolytically processed protein species). Despite its advantages, top-down proteomics presents many challenges. These include requirement of high sample quantity, sophisticated instrumentation, protein separation, and robust computational analysis tools. For this reason, top-down proteomics has rarely been used for analyzing complex mixtures (12–18), and it is typically used to study single purified proteins. However, this situation is quickly changing with recent top-down studies of complex protein mixtures (14, 19).Because of the existence of natural isotopes, fragment ions of the same chemical formula and charge state are usually represented by a collection of spectral peaks in tandem mass spectra called an isotopomer envelope. The monoisotopic mass of a chemical formula is the sum of the masses of the atoms using the principal (most abundant) isotope for each element. Spectral deconvolution focuses on grouping spectral peaks into isotopomer envelopes. By doing so, the charge state and monoisotopic mass of each envelope are effectively determined. A complex multi-isotopic peak list in the m/z space is translated into a simple monoisotopic mass list that is easier to analyze.Given the monoisotopic mass and charge state of a fragment ion, its theoretical isotopic distribution can be predicted by assuming the fragment ion has an average elemental composition with respect to its mass (20) or using its precise elemental composition if the protein is known. Exploiting this, many deconvolution methods use theoretical isotopic distributions to detect and evaluate candidate isotopomer envelopes, which is the envelope detection problem (Fig. 1). To evaluate the fit of a candidate envelope to its theoretical isotopic distribution, many metrics have been proposed (20–32).Open in a separate windowFig. 1.Envelope detection. a, a theoretical isotopic distribution is predicted with the monoisotopic mass and charge state of a fragment ion. b, an observed envelope is detected by mapping peaks in the theoretical distribution to the spectrum. c, match between the theoretical isotopic distribution and the observed envelope. d, the theoretical isotopic distribution is scaled (the intensities of the peaks are multiplied by a constant) to have the best fit with the intensities of peaks in the observed envelope. Finally, a score for the observed envelope can be computed by comparing it with the intensity-scaled theoretical isotopic distribution.The candidate envelopes often overlap and share peaks, leading to a combinatorial problem of selecting the list of envelopes that best explains the spectrum (Fig. 2). In contrast to the well studied envelope detection problem, the envelope selection problem remains poorly explored. Most deconvolution algorithms follow a simple greedy approach to selecting the set of envelopes where the highest scoring envelopes are iteratively selected and removed from the spectrum. Although this approach often generates reasonable sets of envelopes for simple spectra, its performance deteriorates in cases of complex spectra.Open in a separate windowFig. 2.Envelope selection problem. Overlapping envelopes lead to a difficult combinatorial problem of selecting an optimal set of envelopes. We illustrate two cases where a deconvolution method that follows a greedy envelope selection outputs the envelope E₂, whereas the optimal solution consists of the envelopes E₁ and E₃. Example a illustrates the case where envelopes do not share peaks, and example b illustrates the case where envelopes share a spectral peak (E₁ and E₃).In particular, the greedy approach performs well when the envelopes are distributed sparsely along the m/z axis. Large proteins have many fragments that appear in multiple charge states. The high number of envelopes/peaks and the small m/z spread of the fragments with high charge states result in narrow m/z regions with high peak density. In these peak-dense regions, envelopes may overlap and share peaks, and the greedy approach and even manual interpretation often fail to find the optimal combination of envelopes (supplemental Fig. 1).Several methods have been proposed to explore the envelope selection problem. McIlwain et al. (33) presented a dynamic programming algorithm for selecting a set of envelopes such that the m/z ranges of the envelopes do not overlap. This non-overlapping condition becomes too restrictive for complex spectra of intact proteins. Samuelsson et al. (34) proposed a method that follows a non-negative sparse regression scheme. Du and Angeletti (35) and Renard et al. (36) addressed the envelope selection problem as a statistical problem of variable selection and used LASSO to solve it.Here, we present MS-Deconv, a combinatorial algorithm for spectral deconvolution. MS-Deconv (i) generates a large set of candidate envelopes, (ii) constructs an envelope graph encoding all envelopes and relationships between them, and (iii) finds a heaviest path in the envelope graph. Although the envelope graph of a complex spectrum is large (exceeding a million nodes in some cases), the heaviest path algorithm can efficiently find an optimal set of envelopes. MS-Deconv explicitly scores combinations of candidate envelopes rather than individual envelopes as in previous approaches.We tested MS-Deconv on a data set of top-down spectra from known proteins and evaluated the monoisotopic masses recovered by MS-Deconv. A mass was classified as a true positive if it was matched to the monoisotopic mass of a theoretical fragment ion of the protein within a specific parts per million (ppm) tolerance. We compared the performance of MS-Deconv with the widely used Thrash (20) and Xtract (37) and demonstrated that, with a few exceptions, MS-Deconv recovers more true positive masses. For example, for the collisionally activated dissociation (CAD) spectrum of bacteriorhodopsin (BR) with charge 10, the percentage of true positive masses among the top 150 masses is above 70% for MS-Deconv and less than 50% for Thrash. Additionally, MS-Deconv is ∼33 times faster than Thrash and 4 times faster than Xtract. Furthermore, MS-Deconv implements some user-friendly features: (i) outputs the set of peptide sequence tags, (ii) provides protein and spectral annotations, and (iii) allows one to inspect the recovered envelopes. We also tested MS-Deconv on a large LC-MS/MS data set from Yersinia rohdei (with a still unsequenced genome) (19). Y. rohdei is a non-pathogenic bacterium that is often used as a simulant for the potential bioterrorism agent Yersinia pestis, the causative agent of plague. We applied MS-Deconv to extract monoisotopic mass lists from top-down spectra and compared the mass lists with those reported by Thrash. We used ProSightPC (38) and the spectral alignment algorithm (39) to identify related proteins from a protein database of Yersinia enterocolitica (with a closely related and sequenced genome). The results demonstrated that MS-Deconv reported more matched fragments than Thrash for most proteins. Additionally, using spectral alignment, we identified eight proteins in Y. rohdei that were not reported in the ProSightPC-based searches (19) of the Y. enterocolitica protein database.     

Intraradical dynamics of two coexisting isolates of the arbuscular mycorrhizal fungus Glomus intraradices sensu lato as estimated by real-time PCR of mitochondrial DNA

Real-time PCR in nuclear ribosomal DNA (nrDNA) is becoming a well-established tool for the quantification of arbuscular mycorrhizal (AM) fungi, but this genomic region does not allow the specific amplification of closely related genotypes. The large subunit of mitochondrial DNA (mtDNA) has a higher-resolution power, but mtDNA-based quantification has not been previously explored in AM fungi. We applied real-time PCR assays targeting the large subunit of mtDNA to monitor the DNA dynamics of two isolates of Glomus intraradices sensu lato coexisting in the roots of medic (Medicago sativa). The mtDNA-based quantification was compared to quantification in nrDNA. The ratio of copy numbers determined by the nrDNA- and mtDNA-based assays consistently differed between the two isolates. Within an isolate, copy numbers of the nuclear and the mitochondrial genes were closely correlated. The two quantification approaches revealed similar trends in the dynamics of both isolates, depending on whether they were inoculated alone or together. After 12 weeks of cultivation, competition between the two isolates was observed as a decrease in the mtDNA copy numbers of one of them. The coexistence of two closely related isolates, which cannot be discriminated by nrDNA-based assays, was thus identified as a factor influencing the dynamics of AM fungal DNA in roots. Taken together, the results of this study show that real-time PCR assays targeted to the large subunit of mtDNA may become useful tools for the study of coexisting AM fungi.     

Low concentrations of nitrate and ammonium stimulate nodulation and N2 fixation while inhibiting specific nodulation (nodule DW g−1 root dry weight) and specific N2 fixation (N2 fixed g−1 root dry weight) in soybean

Nitrate N is a major inhibitor of the soybean/Bradyrhizobium symbiosis in legumes and although this inhibition has been studied for many years, as yet no consensus has been reached on the specific and quantitative interactions between nitrate and ammonium supply and N₂ fixation. The effect of nitrate and ammonium supply on plant growth, nodulation and N₂ fixation capacity during the full growth cycle was investigated in both greenhouse and growth chamber experiments with three soybean genotypes. The results show that a high concentration of mineral N (10 mM), either as nitrate or ammonium or ammonium nitrate significantly suppressed nodule number, nodule dry weight and total N₂ fixed per plant of nodulated soybeans. However, lower mineral N concentrations, either 1 mM or 3.75 mM significantly enhanced nodule number, nodule dry weight and total N₂ fixed per plant, while specific nodulation (nodule dry weight g^–1 root DW, SNOD) and specific N₂ fixation (total N₂ fixed g^–1 root DW, SNF) were significantly reduced, particularly at the early vegetative growth stage V4, compared to the treatment with N₂ fixation as the only N source, in both growth chamber and greenhouse experiments. Therefore, we suggest that SNOD or SNF might be better indicators to express the suppressing effect of mineral N addition on nodule performance and N₂ fixed. Our studies also showed that ammonium alone was the more efficient N source than either ammonium nitrate or nitrate for soybean, as it resulted in higher biomass accumulation, nodule dry weight, total N accumulation and total N₂ fixed by 23, 20, 18 and 44%, respectively, compared to NO₃ ^– as the N source.     

In vivo measurements of diffuse reflectance and time‐resolved autofluorescence emission spectra of basal cell carcinomas

We present a clinical investigation of diffuse reflectance and time‐resolved autofluorescence spectra of skin cancer with an emphasis on basal cell carcinoma. A total of 25 patients were measured using a compact steady‐state diffuse reflectance/fluorescence spectrometer and a fibre‐optic‐coupled multispectral time‐resolved spectrofluorometer. Measurements were performed in vivo prior to surgical excision of the investigated region. Singular value decomposition was used to reduce the dimensionality of steady state diffuse reflectance and fluorescence spectra. Linear discriminant analysis was then applied to the measurements of basal cell carcinomas (BCCs) and used to predict the tissue disease state with a leave‐one‐out methodology. This approach was able to correctly diagnose 87% of the BCCs. With 445 nm excitation a decrease in the spectrally averaged fluorescence lifetime was observed between normal tissue and BCC lesions with a mean value of 886 ps. Furthermore, the fluorescence lifetime for BCCs was lower than that of the surrounding healthy tissue in all cases and statistical analysis of the data revealed that this decrease was significant (p = 0.002). (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A Microscale Model for Combined CO2 Diffusion and Photosynthesis in Leaves

Transport of CO₂ in leaves was investigated by combining a 2-D, microscale CO₂ transport model with photosynthesis kinetics in wheat (Triticum aestivum L.) leaves. The biophysical microscale model for gas exchange featured an accurate geometric representation of the actual 2-D leaf tissue microstructure and accounted for diffusive mass exchange of CO_2. The resulting gas transport equations were coupled to the biochemical Farquhar-von Caemmerer-Berry model for photosynthesis. The combined model was evaluated using gas exchange and chlorophyll fluorescence measurements on wheat leaves. In general a good agreement between model predictions and measurements was obtained, but a discrepancy was observed for the mesophyll conductance at high CO₂ levels and low irradiance levels. This may indicate that some physiological processes related to photosynthesis are not incorporated in the model. The model provided detailed insight into the mechanisms of gas exchange and the effects of changes in ambient CO₂ concentration or photon flux density on stomatal and mesophyll conductance. It represents an important step forward to study CO₂ diffusion coupled to photosynthesis at the leaf tissue level, taking into account the leaf''s actual microstructure.     

Identification and validation of housekeeping genes in brains of the desert locust Schistocerca gregaria under different developmental conditions

Background  

To obtain reliable quantitative RT-PCR data, normalization relative to stable housekeeping genes is required. However, in practice, expression levels of 'typical' housekeeping genes have been found to vary between tissues and under different experimental conditions. To date, validation studies of reference genes in insects are extremely rare and have never been performed in locusts. In this study, putative housekeeping genes were identified in the desert locust, Schistocerca gregaria and two different software programs (geNorm and Normfinder) were applied to assess the stability of thesegenes.