Functional metagenomics of the thioredoxin superfamily.

Environmental sequence data of microbial communities now makes up the majority of public genomic information. The assignment of a function to sequences from these metagenomic sources is challenging because organisms associated with the data are often uncharacterized and not cultivable. To overcome these challenges, we created a rationally designed expression library of metagenomic proteins covering the sequence space of the thioredoxin superfamily. This library of 100 individual proteins represents more than 22,000 thioredoxins found in the Global Ocean Sampling data set. We screened this library for the functional rescue of Escherichia coli mutants lacking the thioredoxin-type reductase (ΔtrxA), isomerase (ΔdsbC), or oxidase (ΔdsbA). We were able to assign functions to more than a quarter of our representative proteins. The in vivo function of a given representative could not be predicted by phylogenetic relation but did correlate with the predicted isoelectric surface potential of the protein. Selected proteins were then purified, and we determined their activity using a standard insulin reduction assay and measured their redox potential. An unexpected gel shift of protein E5 during the redox potential determination revealed a redox cycle distinct from that of typical thioredoxin-superfamily oxidoreductases. Instead of the intramolecular disulfide bond formation typical for thioredoxins, this protein forms an intermolecular disulfide between the attacking cysteines of two separate subunits during its catalytic cycle. Our functional metagenomic approach proved not only useful to assign in vivo functions to representatives of thousands of proteins but also uncovered a novel reaction mechanism in a seemingly well-known protein superfamily.

Low-bias phosphopeptide enrichment from scarce samples using plastic antibodies.

Phosphospecific enrichment techniques and mass spectrometry (MS) are essential tools for comprehending the cellular phosphoproteome. Here, we report a fast and simple approach for low sequence-bias phosphoserine (pS) peptide capture and enrichment that is compatible with low biological or clinical sample input. The approach exploits molecularly imprinted polymers (MIPs, "plastic antibodies") featuring tight neutral binding sites for pS or pY that are capable of cross-reacting with phosphopeptides of protein proteolytic digests. The versatility of the resulting method was demonstrated with small samples of whole-cell lysate from human embryonic kidney (HEK) 293T cells, human neuroblastoma SH-SY5Y cells, mouse brain or human cerebrospinal fluid (CSF). Following pre-fractionation of trypsinized proteins by strong cation exchange (SCX) chromatography, pS-MIP enrichment led to the identification of 924 phosphopeptides in the HEK 293T whole-cell lysate, exceeding the number identified by TiO2-based enrichment (230). Moreover, the phosphopeptides were extracted with low sequence bias and showed no evidence for the characteristic preference of TiO2 for acidic amino acids (aspartic and glutamic acid). Applying the method to human CSF led to the discovery of 47 phosphopeptides belonging to 24 proteins and revealed three previously unknown phosphorylation sites.

Search and decoy: the automatic identification of mass spectra.

In recent years, the generation and interpretation of MS/MS spectra for the identification of peptides and proteins has matured to a frequently used automatic workflow in Proteomics. Several software solutions for the automated analysis of MS/MS spectra allow for high-throughput/high-performance analyses of complex samples. Related to MS/MS searches, target-decoy approaches have gained more and more popularity: in a "decoy" part of the search database nonexistent sequences mimic real sequences (the "target" sequences). With their help, the number of falsely identified peptides/proteins can be estimated after a search and the resulting protein list can be cut at a specified false discovery rate (FDR). This is an essential prerequisite for all quantitative approaches, as they rely on correct identifications. Especially the label-free approach "spectral counting"-gaining more and more popularity due to low costs and simplicity-depends directly on the correctness of peptide-spectrum matches (PSMs). This work's aim is to describe five popular search engines-especially their general properties regarding protein identification, but also their quantification abilities, if those go beyond spectral counting. By doing so, Proteomics researchers are enabled to compare their features and to choose an appropriate solution for their specific question. Furthermore, the search engines are applied to a spectrum data set generated from a complex sample with a Thermo LTQ Velos OrbiTrap (Thermo Fisher Scientific, Waltham, MA, USA). The results of the search engines are compared, e.g., regarding time requirements, peptides and proteins found, and the search engines' behavior using the decoy approach.