Biochar application to soils may increase carbon (C) sequestration due to the inputs of recalcitrant organic C. However, the effects of biochar application on the soil greenhouse gases (GHGs) fluxes appear variable among many case studies; therefore the efficacy of biochar as a carbon sequestration agent for climate change mitigation remains uncertain. We performed a meta-analysis of 91 published papers with 552 paired comparisons to obtain a central tendency of three main GHG fluxes (i.e., CO 2 , CH 4 , and N 2 O) in response to biochar application. Our results showed that biochar application significantly increased soil CO 2 fluxes by 22.14%, but decreased N 2 O fluxes by 30.92% and did not affect CH 4 fluxes. As a consequence, biochar application may significantly contribute to increased global warming potential (GWP) of total soil GHG fluxes due to the large stimulation of CO 2 fluxes. However, soil CO 2 fluxes were suppressed when biochar was added to fertilized soils, indicating that Accepted ArticleThis article is protected by copyright. All rights reserved. biochar application is unlikely to stimulate CO 2 fluxes in the agriculture sector, in which N fertilizer inputs are common. Responses of soil GHG fluxes mainly varied with biochar feedstock source and soil texture, and the pyrolysis temperature of biochar. Soil and biochar pH, biochar applied rate and latitude also influence soil GHG fluxes, but to a more limited extent.Our findings provide a scientific basis for developing more rational strategies towards widespread adoption of biochar as a soil amendment for climate change mitigation.

No abstract

Shotgun proteome analysis platforms based on multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a powerful means to discover biomarker candidates in tissue specimens. Analysis platforms must balance sensitivity for peptide detection, reproducibility of detected peptide inventories and analytical throughput for protein amounts commonly present in tissue biospecimens (<100 µg), such that platform stability is sufficient to detect modest changes in complex proteomes. We compared shotgun proteomics platforms by analyzing tryptic digests of whole cell and tissue proteomes using strong cation exchange (SCX) and isoelectric focusing (IEF) separations of peptides prior to LC-MS/MS analysis on a LTQ-Orbitrap hybrid instrument. IEF separations provided superior reproducibility and resolution for peptide fractionation from samples corresponding to both large (100 µg) and small (10 µg) protein inputs. SCX generated more peptide and protein identifications than did IEF with small (10 µg) samples, whereas the two platforms yielded similar numbers of identifications with large (100 µg) samples. In nine replicate analyses of tryptic peptides from 50 µg colon adenocarcinoma protein, overlap in protein detection by the two platforms was 77% of all proteins detected by both methods combined. IEF more quickly approached maximal detection, with 90% of IEF-detectable medium abundance proteins (those detected with a total of 3-4 peptides) detected within three replicate analyses. In contrast, the SCX platform required six replicates to detect 90% of SCX-detectable medium abundance proteins. High reproducibility and efficient resolution of IEF peptide separations make the IEF platform superior to the SCX platform for biomarker discovery via shotgun proteomic analyses of tissue specimens.

Accurate determination of protein molecular mass to within 1 Da would be a boon to protein characterization. It would then become possible to (a) count the number of disulfide bridges (-S-S-is 2 Da lighter than 2 -SH); (b) identify deamidation (-NH 2 is 1 Da lighter than -OH); (c) identify such post-translational modifications as phosphorylation and glycosylation; (d) resolve and identify adducts; (e) identify variant amino acid sequences; etc. Determination of the molecular mass of a neutral protein to within 1 Da from measurement of the mass of its gas-phase ion might appear easy. After all, electrospray ionization can now routinely generate abundant multiply-charged gas-phase unhydrated quasimolecular ions, (M + nH) n+ , for most proteins, 1,2 and Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry 3-7 can determine the ion mass to parts-per-million accuracy at typical electrosprayed protein multiply-charged ion mass-to-charge ratios, 500 e m/z e 2000. 8 However, the monoisotopic mass (see below) of a protein inferred from the mass(es) of its corresponding ions may still be wrong by up to several Dalton! There are three stages in the determination of the molecular weight of a neutral protein from its electrosprayed ion mass spectrum. 9 (Our electrospray FT-ICR mass spectra were obtained with a homebuilt instrument operating at 9.4 T, as described elsewhere. 10 ) First, electrospray ionization produces protein ions with various numbers of attached protons and thus several charge states. The first stage in protein mass analysis is therefore to separate the individual charge states (e.g., (M + zH) z+ , (M + (z+1)H) (z+1)+ , etc.). Second, since mass spectrometry reports mass-to-charge ratio, it is necessary to determine the ion charge in order to determine its mass. The massto-charge ratio spectrum of a protein of a given charge state exhibits numerous "isotopic" peaks (see below) spaced ∼1 Da apart (Figure 1). High-resolution FT-ICR mass spectrometry can resolve those peaks for proteins of molecular mass up to more than 100 000 Da, so that the charge state, z, may be determined simply as the reciprocal of the separation between two adjacent isotopic peaks differing in mass by ∼1 Da. 11 However, protein mass measurement accuracy is presently limited by the third stage of mass analysis: namely, knowledge of the isotopic composition (i.e., the constituent chemical formula(s) composing each mass spectral peak). For organic molecules of less than ∼1000 Da, determination of molecular weight from the singly-charged molecular (M + ) or quasimolecular (e.g., (M + H) + ) ion is relatively simple. Why then is it so much more difficult to determine the mass of a biological macromolecule? The problem is apparent from Figure 1 (top). The natural abundance of 13 C is 1.066-1.106% relative to 12 C as 100%. 8 However, for a molecule containing n carbons, the isotopic distribution is a binomial expansion (0.9889 + 0.0111) n , and it is ∼n% as likely that a given molecule will contain one 13 C as that all of the c...