FLUXNET and modelling the global carbon cycle

Measurements of the net CO₂ flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO₂ source–sink patterns, CO₂ flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO₂ (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model‐data comparison. Flux measurements made over four vegetation types were used to calibrate the land‐surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land‐surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO₂ uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). This model is forced by satellite‐measured absorbed radiation and suggests that global net primary production (NPP) increased 6.2% over 1982–1999. Good agreement is found between global trends in NPP estimated by the PEM and a dynamic global vegetation model (DGVM), and between the DGVM and estimates of global NEE derived from a global inversion of atmospheric CO₂ measurements. Combining the PEM, DGVM, and inversion results suggests that CO₂ fertilization is playing a major role in current increases in NPP, with lesser impacts from increasing N deposition and growing season length. Both the PEM and the inversion identify the Amazon basin as a key region for the current net terrestrial CO₂ uptake (i.e. 33% of global NEE), as well as its interannual variability. The inversion's global NEE estimate of −1.2 Pg [C] yr⁻¹ for 1982–1995 is compatible with the PEM‐ and DGVM‐predicted trends in NPP. There is, thus, a convergence in understanding derived from process‐based models, remote‐sensing‐based observations, and inversion of atmospheric data. Future advances in field measurement techniques, including eddy covariance (particularly concerning the problem of night‐time fluxes in dense canopies and of advection or flow distortion over complex terrain), will result in improved constraints on land‐atmosphere CO₂ fluxes and the rigorous attribution of mechanisms to the current terrestrial net CO₂ uptake and its spatial and temporal heterogeneity. Global ecosystem models play a fundamental role in linking information derived from FLUXNET measurements to atmospheric CO₂ variability. A number of recommendations concerning FLUXNET data are made, including a request for more comprehensive site data (particularly historical information), more measurements in undisturbed ecosystems, and the systematic provision of error estimates. The greatest value of current FLUXNET data for global carbon cycle modelling is in evaluating process representations, rather than in providing an unbiased estimate of net CO₂ exchange.     

Large-scale identification of polymorphic microsatellites using an <Emphasis Type="Italic">in silico</Emphasis> approach

Background  

Simple Sequence Repeat (SSR) or microsatellite markers are valuable for genetic research. Experimental methods to develop SSR markers are laborious, time consuming and expensive. In silico approaches have become a practicable and relatively inexpensive alternative during the last decade, although testing putative SSR markers still is time consuming and expensive. In many species only a relatively small percentage of SSR markers turn out to be polymorphic. This is particularly true for markers derived from expressed sequence tags (ESTs). In EST databases a large redundancy of sequences is present, which may contain information on length-polymorphisms in the SSR they contain, and whether they have been derived from heterozygotes or from different genotypes. Up to now, although a number of programs have been developed to identify SSRs in EST sequences, no software can detect putatively polymorphic SSRs.     

Quantitative phosphoproteome analysis of lysophosphatidic acid induced chemotaxis applying dual-step (18)O labeling coupled with immobilized metal-ion affinity chromatography

Reversible protein phosphorylation is a central cellular regulatory mechanism in modulating protein activity and propagating signals within cellular pathways and networks. Development of more effective methods for the simultaneous identification of phosphorylation sites and quantification of temporal changes in protein phosphorylation could provide important insights into molecular signaling mechanisms in various cellular processes. Here we present an integrated quantitative phosphoproteomics approach and its application for comparative analysis of Cos-7 cells in response to lysophosphatidic acid (LPA) gradient stimulation. The approach combines trypsin-catalyzed (16)O/ (18)O labeling plus (16)O/ (18)O-methanol esterification for quantitation, a macro-immobilized metal-ion affinity chromatography trap for phosphopeptide enrichment, and LC-MS/MS analysis. LC separation and MS/MS are followed by neutral loss-dependent MS/MS/MS for phosphopeptide identification using a linear ion trap (LTQ)-FT mass spectrometer. A variety of phosphorylated proteins were identified and quantified including receptors, kinases, proteins associated with small GTPases, and cytoskeleton proteins. A number of hypothetical proteins were also identified as differentially expressed followed by LPA stimulation, and we have shown evidence of pseudopodia subcellular localization of one of these candidate proteins. These results demonstrate the efficiency of this quantitative phosphoproteomics approach and its application for rapid discovery of phosphorylation events associated with LPA gradient sensing and cell chemotaxis.     

The influence of sample preparation and replicate analyses on HeLa Cell phosphoproteome coverage

Ongoing optimization of proteomic methodologies seeks to improve both the coverage and confidence of protein identifications. The optimization of sample preparation, inclusion of technical replicates (repeated instrumental analysis of the same sample), and biological replicates (multiple individual samples) are crucial in proteomic studies to avoid the pitfalls associated with single point analysis and under-sampling. Phosphopeptides were isolated from HeLa cells and analyzed by nano-reversed phase liquid chromatography electrospray ionization tandem mass spectrometry (nano-RP-LC-MS/MS). We observed that a detergent-based protein extraction approach, followed with additional steps for nucleic acid removal, provided a simple alternative to the broadly used Trizol extraction. The evaluation of four technical replicates demonstrated measurement reproducibility with low percent variance in peptide responses at approximately 3%, where additional peptide identifications were made with each added technical replicate. The inclusion of six technical replicates for moderately complex protein extracts (approximately 4000 uniquely identified peptides per data set) affords the optimal collection of peptide information.     

Linear discriminant analysis-based estimation of the false discovery rate for phosphopeptide identifications

The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to characterize phosphopeptides in an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large data sets in a similar high-throughput fashion remains difficult, as does rigorously estimating the false discovery rate (FDR) of a set of phosphopeptide identifications. This article describes a data analysis pipeline designed to address these issues. The first step is to reanalyze phosphopeptide identifications that contain ambiguous assignments for the incorporated phosphate(s) to determine the most likely arrangement of the phosphate(s). The next step is to employ an expectation maximization algorithm to estimate the joint distribution of the peptide scores. A linear discriminant analysis is then performed to determine how to optimally combine peptide scores (in this case, from SEQUEST) into a discriminant score that possesses the maximum discriminating power. Based on this discriminant score, the p- and q-values for each phosphopeptide identification are calculated, and the phosphopeptide identification FDR is then estimated. This data analysis approach was applied to data from a study of irradiated human skin fibroblasts to provide a robust estimate of FDR for phosphopeptides. The Phosphopeptide FDR Estimator software is freely available for download at http://ncrr.pnl.gov/software/.     

Comparative proteomics of human monkeypox and vaccinia intracellular mature and extracellular enveloped virions.

Orthopoxviruses are among the largest and most complex of the animal viruses. In response to the recent emergence of monkeypox in Africa and the threat of smallpox bioterrorism, two orthopoxviruses with different pathogenic potentials, human monkeypox virus and vaccinia virus, were proteomically compared with the goal of identifying proteins required for pathogenesis. Orthopoxviruses were grown in HeLa cells to two different viral forms (intracellular mature virus and extracellular enveloped virus), purified by sucrose gradient ultracentrifugation, denatured using RapiGest surfactant, and digested with trypsin. Unfractionated samples and strong cation exchange HPLC fractions were analyzed by high-resolution reversed-phase nano-LC-MS/MS, and analyses of the MS/MS spectra using SEQUEST and X! Tandem resulted in the confident identification of hundreds of monkeypox, vaccinia, and copurified host-cell proteins. The unfractionated samples were additionally analyzed by LC-MS using an LTQ-Orbitrap, and the accurate mass and elution time tag approach was used to perform quantitative comparisons. Possible pathophysiological roles of differentially abundant Orthopoxvirus proteins are discussed. Data, processed results, and protocols are available at http://www.proteomicsresource.org/.