Although the decoding rules have been largely elucidated, the physical-chemical reasons for the “correctness” of codon:anticodon duplexes have never been clear. In this work, on the basis of the available data, we propose that the correct codon:anticodon duplexes are those whose formation and interaction with the ribosomal decoding center are not accompanied by uncompensated losses of hydrogen and ionic bonds. Other factors such as proofreading, base–base stacking and aminoacyl–tRNA concentration contribute to the efficiency and accuracy of aminoacyl–tRNA selection, and certainly these factors are important; but we suggest that analyses of hydrogen and ionic bonding alone provides a robust first-order approximation of decoding accuracy. Thus our model can simplify predictions about decoding accuracy and error. The model can be refined with data, but is already powerful enough to explain all of the available data on decoding accuracy. Here we predict which duplexes should be considered correct, which duplexes are responsible for virtually all misreading, and we suggest an evolutionary scheme that gave rise to the mixed boxes of the genetic code.

The roles of the ribosomal E site are not fully understood. Prior evidence suggests that deacyl-tRNA in the E site can prevent frameshifting. We hypothesized that if the E-site codon must dissociate from its tRNA to allow for frameshifting, then weak codon:anticodon duplexes should allow for greater frameshifting than stronger duplexes. Using the well-characterized Escherichia coli RF2 (prfB) programmed frameshift to study frameshifting, we mutagenized the E-site triplet to all Unn and Cnn codons. Those variants should represent a very wide range of duplex stability. Duplex stability was estimated using two different methods. Frameshifting is inversely correlated with stability, as estimated by either method. These findings indicate that pairing between the deacyl-tRNA and the E-site codon opposes frameshifting. We discuss the implications of these findings on frame maintenance and on the RF2 programmed frameshift mechanism.

The spread of fecal pollutants and antibiotic resistance in the aquatic environment represents a major public health concern and is predicted to increase in light of climate change consequences and the increasing human population pressure on the lagoon and coastal areas. The city of Venice (Italy) is affected by diverse microbial pollution sources, including domestic wastewaters that, due to the lack of modern sewage treatment infrastructure in the historical city center, are released into canals. The outflowing jets of its tidal inlets thus represent a source of contamination for the nearby beaches on the barrier island separating the lagoon from the sea. Metagenomic analyses of DNA extracted from sediment samples from six sites in the canals of the city’s historic center were undertaken to characterize the microbial community composition, the presence of fecal microbes as well as other non-enteric pathogens, and the content of genes related to antibiotic (AB) and heavy metal (HM) resistance, and virulence. The six sites hosted similar prokaryotic communities, although variations in community composition likely related to oxygen availability were observed. All sites displayed relatively high levels of fecal contamination, including the presence of Fecal Indicator Bacteria, sewage- and alternative feces-associated bacteria. Relatively high levels of other potential pathogens were also found. About 1 in 500 genes identified at these sites are related to AB and HM resistance; conversely, genes related to virulence were rare. Our data suggest the existence of widespread sediment microbial pollution in the canals of Venice, coupled with the prevalence of ARGs to antibiotics frequently used in humans as well as of HMRGs to toxic metals that still persists in the lagoon. All of this evidence raises concerns about the consequences on the water quality of the lagoon and adjacent marine areas and the potential risks for humans, deserving further studies.

We present a novel missense suppression system for the selection of tRNA2Gln mutants that can efficiently translate the CGA (arginine) codon as glutamine. tRNA2Gln mutants were cloned from a partially randomized synthetic gene pool using a plasmid vector that simultaneously expresses the tRNA gene and, to ensure efficient aminoacylation, the glutamine aminoacyl-tRNA synthetase gene (glnS). tRNA mutants that insert glutamine at CGA were selected as missense suppressors of a lacZ mutant (lacZ625(CGA)) that contains CGA substituted for an essential glutamine codon. Preliminary characterizations of four suppressors is presented. All of them contain two anticodon mutations: C → U at position 34 and U → C at position 35, which allow for cognate translation of CGA. U35 was previously shown to be an important determinant for glutaminylation of tRNA2Gln in vitro; suppression in vivo requires overexpression of the glutaminyl-tRNA synthetase gene (glnS). One tRNA variant contains no further mutations and has the highest missense suppression activity (8%). Three other isolates each contain an additional point mutation that alters suppression efficiency. This system will be useful for further studies of tRNA structure and function. In addition, because relatively efficient translation of the rare CGA codon as glutamine is not toxic for Escherichia coli, it may be possible to translate this sense codon with other alternate meanings, a property which could greatly facilitate protein engineering.