[1] Black carbon (BC), the product of incomplete combustion of fossil fuels and biomass (called elemental carbon (EC) in atmospheric sciences), was quantified in 12 different materials by 17 laboratories from different disciplines, using seven different methods. The materials were divided into three classes: (1) potentially interfering materials, (2) laboratory-produced BC-rich materials, and (3) BC-containing environmental matrices (from soil, water, sediment, and atmosphere). This is the first comprehensive intercomparison of this type (multimethod, multilab, and multisample), focusing mainly on methods used for soil and sediment BC studies. Results for the potentially interfering materials (which by definition contained no fire-derived organic carbon) highlighted situations where individual methods may overestimate BC concentrations. Results for the BC-rich materials (one soot and two chars) showed that some of the methods identified

SUMMARY A complicating factor for protein identification within complex mixtures by LC/MS/MS is the problem of “chimera” spectra, where two or more precursor ions with similar mass and retention time are co-sequenced by MS/MS. Chimera spectra show reduced scores due to unidentifiable fragment ions derived from contaminating parents. However, the extent of chimeras in LC/MS/MS datasets and their impact on protein identification workflows are incompletely understood. We report ChimeraCounter, a software program which detects chimeras in datasets collected on an Orbitrap/LTQ instrument. Evaluation of synthetic chimeras created from pairs of well-defined peptide MS/MS spectra reveal that chimeras reduce database search scores most significantly when contaminating fragment ion intensities exceed 20% of the targeted fragment ion intensities. In large scale datasets, the identification rate for chimera MS/MS is 2-fold lower compared to non-chimera spectra. Importantly, this occurs in a manner which depends not on absolute precursor ion intensity, but on intensity relative to the median precursor intensity distribution. We further show that chimeras reduce the number of accepted peptide identifications by increasing false negatives while showing little increase in false positives. The results provide a framework for identifying chimeras and characterizing their contribution to the poorly understood false negative class of MS/MS.

Argonaute proteins (Ago1–4) are essential components of the microRNA-induced silencing complex and play important roles in both microRNA biogenesis and function. Although Ago2 is the only one with the slicer activity, it is not clear whether the slicer activity is a universally critical determinant for Ago2's function in mammals. Furthermore, functional specificities associated with different Argonautes remain elusive. Here we report that microRNAs are randomly sorted to individual Argonautes in mammals, independent of the slicer activity. When both Ago1 and Ago2, but not either Ago1 or Ago2 alone, are ablated in the skin, the global expression of microRNAs is significantly compromised and it causes severe defects in skin morphogenesis. Surprisingly, Ago3 is able to load microRNAs efficiently in the absence of Ago1 and Ago2, despite a significant loss of global microRNA expression. Quantitative analyses reveal that Ago2 interacts with a majority of microRNAs (60%) in the skin, compared with Ago1 (30%) and Ago3 (<10%). This distribution is highly correlated with the abundance of each Argonaute, as quantified by shotgun proteomics. The quantitative correlation between Argonautes and their associated microRNAs is conserved in human cells. Finally, we measure the absolute expression of Argonaute proteins and determine that their copy number is ∼1.4 × 105 to 1.7 × 105 molecules per cell. Together, our results reveal a quantitative picture for microRNA activity in mammals.