Nitrogen input quality changes the biochemical composition of soil organic matter stabilized in the fine fraction: a long-term study

The chemical composition of soil organic matter (SOM) is a key determinant of its biological stability. Our objective in this study was to evaluate the effects of various sources of supplemental N on the chemical composition of SOM in the fine (<5 μm) mineral fraction. Treatments were fallow, maize/soybean in rotation, and continuous maize receiving no fertilizer (maize0N), synthetic fertilizer N (maize + N), or composted manure (maize + manure). The chemical structures in SOM associated with the fine fraction were determined using XANES spectroscopy at the C and N K-edges, which was assessed using multidimensional scaling. Analysis of amino sugar biomarkers were used to evaluate the fungal:bacterial contributions to the SOM. The addition of N to soils (i.e., maize + N, maize + manure, and maize/soybean treatments) resulted in the enrichment of proteinaceous compounds. Soils which did not receive supplemental N (i.e., fallow and maize0N treatments) were enriched in plant-derived compounds (e.g., aromatics, phenolics, carboxylic acids and aliphatic compounds), suggesting that decomposition of plant residues was constrained by N-limitation. Microbial populations assessed by amino sugar biomarker ratios showed that the highest contributions to SOM by bacteria occurred in the maize + manure treatment (high N input), and by fungi in the fallow treatment (low N input). The SOM in the maize + N and maize/soybean treatments was enriched in N-bonded aromatics; we attribute this enrichment to the abiotic reaction of inorganic N with organic C structures. The SOM in the maize + manure treatment was enriched in pyridinic-N, likely as a result of intense microbial processing and high SOM turnover. The presences of signals for ketone and pyrrole compounds in XANES spectra suggest their use as biomarkers for microbially transformed and stabilized SOM. The SOM in the maize + manure treatment was enriched in ketones which are likely microbial by-products of fatty acid catabolism. Pyrrole compounds, which may accumulate over the long term as by-products of protein transformations by an N-limited microbial community, were dominant in the fallow soil. A combination of molecular spectroscopy and biomarker analysis showed that the source of supplemental N to soil influences the stable C- and N-containing compounds of SOM in a long-term field study. Indeed, any increase in N availability allowed the microbial community to transform plant material into microbial by-products which occur as stable SOM compounds in the fine soil fraction.     

Hemocytes and Plasma of the Eastern Oyster (Crassostrea virginica) Display a Diverse Repertoire of Sulfated and Blood Group A-modified N-Glycans

The eastern oyster (Crassostrea virginica) has become a useful model system for glycan-dependent host-parasite interactions due to the hijacking of the oyster galectin CvGal1 for host entry by the protozoan parasite Perkinsus marinus, the causative agent of Dermo disease. In this study, we examined the N-glycans of both the hemocytes, which via CvGal1 are the target of the parasite, and the plasma of the oyster. In combination with HPLC fractionation, exoglycosidase digestion, and fragmentation of the glycans, mass spectrometry revealed that the major N-glycans of plasma are simple hybrid structures, sometimes methylated and core α1,6-fucosylated, with terminal β1,3-linked galactose; a remarkable high degree of sulfation of such glycans was observed. Hemocytes express a larger range of glycans, including core-difucosylated paucimannosidic forms, whereas bi- and triantennary glycans were found in both sources, including structures carrying sulfated and methylated variants of the histo-blood group A epitope. The primary features of the oyster whole hemocyte N-glycome were also found in dominin, the major plasma glycoprotein, which had also been identified as a CvGal1 glycoprotein ligand associated with hemocytes. The occurrence of terminal blood group moieties on oyster dominin and on hemocyte surfaces can account in part for their affinity for the endogenous CvGal1.     

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics.With well-developed algorithms and computational tools for mass spectrometry (MS)¹ data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1–9). Nevertheless, the bottom-up approach is suboptimal for the analysis of protein posttranslational modifications (PTMs) and sequence variants as a result of protein digestion (10). Alternatively, the protein-based top-down proteomics approach analyzes intact proteins, which provides a “bird''s eye” view of all proteoforms (11), including those arising from sequence variations, alternative splicing, and diverse PTMs, making it a disruptive technology for the comprehensive analysis of proteoforms (12–24). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped.The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs.Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28, 29), Mascot Top Down (also known as Big-Mascot) (30), MS-TopDown (31), and MS-Align+ (32), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes “shotgun annotated” databases (33) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32). Mascot Top Down (30) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31) employs the spectral alignment algorithm (35), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax.Recently, new software tools have been developed for proteoform characterization (36, 37). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36). Another software tool, ProSight Lite, developed recently by the Kelleher group (37), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking.Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations.     

Soil C erosion and burial in cropland

Erosion influences the lateral and vertical distribution of soil in agricultural landscapes. A better understanding of the effects of erosion and redistribution on soil organic carbon (C) within croplands would improve our knowledge of how management practices may affect global C dynamics. In this study, the vertical and lateral distribution of soil organic C was characterized to evaluate the amounts and timescales of soil organic C movement, deposition and burial over the last 50 years in different agroecosystems across Canada. There was strong evidence that a substantial portion of eroded sediment and soil organic C was deposited as colluvium close to its source area, thereby burying the original topsoil. The deepest aggraded profile was in a potato field and contained over 70 cm of deposited soil indicating an accumulation rate of 152 Mg ha yr^?1; aggraded profiles in other sites had soil deposition rates of 40–90 Mg ha^?1 yr^?1. The largest stock of soil organic C was 463 Mg ha^?1 (to 60 cm depth) and soil C deposition ranged from about 2 to 4 Mg ha^?1 yr^?1 across all sites. A distinct feature observed in the aggraded profiles at every site was the presence of a large increase in soil organic C concentration near the bottom of the A horizon; the concentration of this C was greater than that at the soil surface. Compared to aggraded profiles, the SOC concentration in eroded profiles did not differ with depth, suggesting that dynamic replacement of soil organic C had occurred in eroded soils. A large amount of soil organic C is buried in depositional areas of Canadian croplands; mineralization of this stock of C appears to have been constrained since burial, but it may be vulnerable to future loss by management practices, land use change and a warming climate.     

Short-term mineralization of maize residues in soils as determined by carbon-13 natural abundance

Studies of soil organic matter equilibria must include estimates of C turnover. The objective of this study was to provide data on how the natural ¹³C abundance method can be used to determine the flow of C from C₄ residues and soil organic matter (C₃-source) in a short-term incubation. Corn residue was added at a rate of 5.7 mg C g⁻¹ soil to two soils, a clay and a sandy clay loam. During the course of a 35-day incubation in a CO₂-free system, CO₂-C and ¹³C natural abundance of the respired CO₂ were measured. About 20% of the corn residue-C added was mineralized in both soils as determined from the CO₂ respired and the ¹³C natural abundance of the respired CO₂. Mineralization of the added residues was also calculated as the difference of the total amount of the respired CO₂-C between the control and the corn residue-treated soils divided by the total amount of corn residue-C. Values were 35% for the clay soil, and 30% for the sandy clay loam soil. The difference in values calculated from the ¹³ C natural abundance and the difference method was due to mineralization of the indigenous soil organic C resulting from the addition of corn residues. Use of the natural ¹³C abundance method could determine the degree of ‘priming effect’ in soils amended with C₄-C residues. This revised version was published online in June 2006 with corrections to the Cover Date.     

Isotopic evidence for the provenance and turnover of organic carbon by soil microorganisms in the Antarctic dry valleys

The extremely cold and arid Antarctic dry valleys are one of the most environmentally harsh terrestrial ecosystems supporting organisms in which the biogeochemical transformations of carbon are exclusively driven by microorganisms. The natural abundance of ¹³C and ¹⁵N in source organic materials and soils have been examined to obtain evidence for the provenance of the soil organic matter and the C loss as CO₂ during extended incubation (approximately 1200 days at 10°C under moist conditions) has been used to determine the potential decay of soil organic C. The organic matter in soils remote from sources of liquid water or where lacustrine productivity was low had isotope signatures characteristic of endolithic (lichen) sources, whereas at more sheltered and productive sites, the organic matter in the soils that was a mixture mainly lacustrine detritus and moss-derived organic matter. Soil organic C declined by up to 42% during extended incubation under laboratory conditions (equivalent to 50–73 years in the field on a thermal time basis), indicating relatively fast turnover, consistent with previous studies indicating mean residence times for soil organic C in dry valley soils in the range 52–123 years and also with recent inputs of relatively labile source materials.     

Litter decay controlled by temperature,not soil properties,affecting future soil carbon

Widespread global changes, including rising atmospheric CO₂ concentrations, climate warming and loss of biodiversity, are predicted for this century; all of these will affect terrestrial ecosystem processes like plant litter decomposition. Conversely, increased plant litter decomposition can have potential carbon‐cycle feedbacks on atmospheric CO₂ levels, climate warming and biodiversity. But predicting litter decomposition is difficult because of many interacting factors related to the chemical, physical and biological properties of soil, as well as to climate and agricultural management practices. We applied ¹³C‐labelled plant litter to soil at ten sites spanning a 3500‐km transect across the agricultural regions of Canada and measured its decomposition over five years. Despite large differences in soil type and climatic conditions, we found that the kinetics of litter decomposition were similar once the effect of temperature had been removed, indicating no measurable effect of soil properties. A two‐pool exponential decay model expressing undecomposed carbon simply as a function of thermal time accurately described kinetics of decomposition. (R² = 0.94; RMSE = 0.0508). Soil properties such as texture, cation exchange capacity, pH and moisture, although very different among sites, had minimal discernible influence on decomposition kinetics. Using this kinetic model under different climate change scenarios, we projected that the time required to decompose 50% of the litter (i.e. the labile fractions) would be reduced by 1–4 months, whereas time required to decompose 90% of the litter (including recalcitrant fractions) would be reduced by 1 year in cooler sites to as much as 2 years in warmer sites. These findings confirm quantitatively the sensitivity of litter decomposition to temperature increases and demonstrate how climate change may constrain future soil carbon storage, an effect apparently not influenced by soil properties.     

Top-down Proteomics: Technology Advancements and Applications to Heart Diseases

Introduction: Heart diseases are a leading cause of morbidity and mortality for both men and women worldwide, and impose significant economic burdens on the healthcare systems. Despite substantial effort over the last several decades, the molecular mechanisms underlying diseases of the heart remain poorly understood.

Areas covered: Altered protein post-translational modifications (PTMs) and protein isoform switching are increasingly recognized as important disease mechanisms. Top-down high-resolution mass spectrometry (MS)-based proteomics has emerged as the most powerful method for the comprehensive analysis of PTMs and protein isoforms. Here, we will review recent technology developments in the field of top-down proteomics, as well as highlight recent studies utilizing top-down proteomics to decipher the cardiac proteome for the understanding of the molecular mechanisms underlying diseases of the heart.

Expert commentary: Top-down proteomics is a premier method for the global and comprehensive study of protein isoforms and their PTMs, enabling the identification of novel protein isoforms and PTMs, characterization of sequence variations, and quantification of disease-associated alterations. Despite significant challenges, continuous development of top-down proteomics technology will greatly aid the dissection of the molecular mechanisms underlying diseases of the hearts for the identification of novel biomarkers and therapeutic targets.     

High throughput screening of disulfide‐containing proteins in a complex mixture

The formation of disulfide bonds between cysteine residues is crucial for the stabilization of native protein structures and, thus, determination of disulfide linkages is an important facet of protein structural characterization. Nonetheless, the identification of disulfide bond linkages remains a significant analytical challenge, particularly in large proteins with complex disulfide patterns. Herein, we have developed a new LC/MS strategy for rapid screening of disulfides in an intact protein mixture after a straightforward reduction step with tris(2‐carboxyethyl)phosphine. LC/MS analysis of reduced and nonreduced protein mixtures quickly revealed disulfide‐containing proteins owing to a 2 Da mass increase per disulfide reduction and, subsequently, the total number of disulfide bonds in the intact proteins could be determined. We have demonstrated the effectiveness of this method in a protein mixture composed of both disulfide‐containing and disulfide‐free proteins. Our method is simple (no need for proteolytic digestion, alkylation, or the removal of reducing agents prior to MS analysis), high throughput (fast on‐line LC/MS analysis), and reliable (no S–S scrambling), underscoring its potential as a rapid disulfide screening method for proteomics applications.     

Uncertainty analysis of soil organic carbon stock change in Canadian cropland from 1991 to 2001

National estimates of changes in the amount of soil organic carbon (SOC) in cropland requires an assessment of uncertainty for accounting and reporting under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol. Canada has data sets on SOC stocks in croplands, historical changes in SOC levels due to management practices, and historical changes in the area of land devoted to certain soil management practices. We conducted an analysis of uncertainty of the change in SOC levels due to management practices in Canada from 1991 to 2001 using Monte Carlo analysis and a simple model. Probability distribution functions were determined for each of the inputs of the model, enabling us to assess the uncertainty for the output. The storage rate of SOC in cropland soils of Canada for the 10‐year period ranged from 3.2 to 8.3 Mt C yr^?1 at 95% confidence, with a mean of 5.7 Mt C yr^?1. Approximately 67% (about 3.8 Mt C yr^?1) of the increase in SOC storage in Canada occurred in Saskatchewan where the cropland area under no‐till increased from 10% to 35%, and the area of summer‐fallow declined from 43% to 20% during the study period. The large uncertainty in the effect of no‐till on SOC stock changes in the Gray‐Brown Luvisols of Ontario contributed most to the variance in the model output. If trends in agricultural management continue for the next 10‐year census period, the estimated SOC storage would comprise between 7% and 19% of the gap required to achieve the 6% reduction in 1990 greenhouse gas emission levels for Canada under the Kyoto Protocol.