Pirt is a membrane protein that is specifically expressed in the peripheral nervous system, where it has been shown to increase the sensitivity of the transient receptor potential vanilloid 1 (TRPV1) channel and modulate its role in heat pain. The broad expression of Pirt among dorsal root ganglion neurons suggests it may modulate other TRPs, such as the menthol and cooling sensor TRPM8. The discrepancies in the channel properties of TRPM8 in native neurons versus heterologous cells indicate the existence of endogenous modulators of the channel. Here we show that Pirt regulates the function of TRPM8 and its role in detecting cold. Pirt−/− mice exhibit decreased behavioral responses to cold and cool temperatures, and Pirt increases the sensitivity of TRPM8 to menthol and cool temperature. Our data suggest Pirt is an endogenous regulator of TRPM8.

Understanding the in vivo redox biology of cells is a complex albeit important biological problem. Studying redox processes within living cells without physical disruption or chemical modifications is essential in determining the native redox states of cells. In this study, the previously characterized reduction-oxidation sensitive green fluorescent protein (roGFP2) was used to elucidate the redox changes of the genetically engineered Escherichia coli strain, SHuffle. SHuffle cells were demonstrated to be under constitutive oxidative stress and responding transcriptionally in an OxyR-dependent manner. Using roGFP2 fused to either glutathione (GSH)- or hydrogen peroxide (H2O2)- sensitive proteins (glutaredoxin 1 or Orp1), the cytosolic redox state of both wild type and SHuffle cells based on GSH/GSSG and H2O2 pools was measured. These probes open the path to in vivo studies of redox changes and genetic selections in prokaryotic hosts.

The majority of protein sequence data published today is of metagenomic origin. However, our ability to assign functions to these sequences is often hampered by our general inability to cultivate the larger part of microbial species and the sheer amount of sequence data generated in these projects. Here we present a combination of bioinformatics, synthetic biology, and Escherichia coli genetics to discover biocatalysts in metagenomic datasets. We created a subset of the Global Ocean Sampling dataset, the largest metagenomic project published to date, by removing all proteins that matched Hidden Markov Models of known protein families from PFAM and TIGRFAM with high confidence (E-value > 10 −5 ). This essentially left us with proteins with low or no homology to known protein families, still encompassing ∼1.7 million different sequences. In this subset, we then identified protein families de novo with a Markov clustering algorithm. For each protein family, we defined a single representative based on its phylogenetic relationship to all other members in that family. This reduced the dataset to ∼17,000 representatives of protein families with more than 10 members. Based on conserved regions typical for lipases and esterases, we selected a representative gene from a family of 27 members for synthesis. This protein, when expressed in E. coli, showed lipolytic activity toward para-nitrophenyl (pNP) esters. The K m -value of the enzyme was 66.68 μM for pNP-butyrate and 68.08 μM for pNP-palmitate with k cat /K m values at 3.4 × 10 6 and 6.6 × 10 5 M −1 s −1 , respectively. Hydrolysis of model substrates showed enantiopreference for the R-form. Reactions yielded 43 and 61% enantiomeric excess of products with ibuprofen methyl ester and 2-phenylpropanoic acid ethyl ester, respectively. The enzyme retains 50% of its maximum activity at temperatures as low as 10 • C, its activity is enhanced in artificial seawater and buffers with higher salt concentrations with an optimum osmolarity of 3,890 mosmol/l.

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 (Δ trxA ), isomerase (Δ dsbC ), or oxidase (Δ dsbA ). 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.