Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data

We address the problem of analyzing sets of noisy time-varying signals that all report on the same process but confound straightforward analyses due to complex inter-signal heterogeneities and measurement artifacts. In particular we consider single-molecule experiments which indirectly measure the distinct steps in a biomolecular process via observations of noisy time-dependent signals such as a fluorescence intensity or bead position. Straightforward hidden Markov model (HMM) analyses attempt to characterize such processes in terms of a set of conformational states, the transitions that can occur between these states, and the associated rates at which those transitions occur; but require ad-hoc post-processing steps to combine multiple signals. Here we develop a hierarchically coupled HMM that allows experimentalists to deal with inter-signal variability in a principled and automatic way. Our approach is a generalized expectation maximization hyperparameter point estimation procedure with variational Bayes at the level of individual time series that learns an single interpretable representation of the overall data generating process.Comment: 9 pages, 5 figure

Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage

Bacteria in the 16S rRNA clade SAR86 are among the most abundant uncultivated constituents of microbial assemblages in the surface ocean for which little genomic information is currently available. Bioinformatic techniques were used to assemble two nearly complete genomes from marine metagenomes and single-cell sequencing provided two more partial genomes. Recruitment of metagenomic data shows that these SAR86 genomes substantially increase our knowledge of non-photosynthetic bacteria in the surface ocean. Phylogenomic analyses establish SAR86 as a basal and divergent lineage of γ-proteobacteria, and the individual genomes display a temperature-dependent distribution. Modestly sized at 1.25–1.7 Mbp, the SAR86 genomes lack several pathways for amino-acid and vitamin synthesis as well as sulfate reduction, trends commonly observed in other abundant marine microbes. SAR86 appears to be an aerobic chemoheterotroph with the potential for proteorhodopsin-based ATP generation, though the apparent lack of a retinal biosynthesis pathway may require it to scavenge exogenously-derived pigments to utilize proteorhodopsin. The genomes contain an expanded capacity for the degradation of lipids and carbohydrates acquired using a wealth of tonB-dependent outer membrane receptors. Like the abundant planktonic marine bacterial clade SAR11, SAR86 exhibits metabolic streamlining, but also a distinct carbon compound specialization, possibly avoiding competition

A conformational switch in initiation factor 2 controls the fidelity of translation initiation in bacteria

Initiation factor (IF) 2 controls the fidelity of translation initiation by selectively increasing the rate of 50S ribosomal subunit joining to 30S initiation complexes (ICs) that carry an N-formyl-methionyl-tRNA (fMet-tRNA(fMet)). Previous studies suggest that rapid 50S subunit joining involves a GTP- and fMet-tRNA(fMet)-dependent "activation" of IF2, but a lack of data on the structure and conformational dynamics of 30S IC-bound IF2 has precluded a mechanistic understanding of this process. Here, using an IF2-tRNA single-molecule fluorescence resonance energy transfer signal, we directly observe the conformational switch that is associated with IF2 activation within 30S ICs that lack IF3. Based on these results, we propose a model of IF2 activation that reveals how GTP, fMet-tRNA(fMet), and specific structural elements of IF2 drive and regulate this conformational switch. Notably, we find that domain III of IF2 plays a pivotal, allosteric, role in IF2 activation, suggesting that this domain can be targeted for the development of novel antibiotics

Translation factors direct intrinsic ribosome dynamics during translation termination and ribosome recycling.

Characterizing the structural dynamics of the translating ribosome remains a major goal in the study of protein synthesis. Deacylation of peptidyl-tRNA during translation elongation triggers fluctuations of the pretranslocation ribosomal complex between two global conformational states. Elongation factor G-mediated control of the resulting dynamic conformational equilibrium helps to coordinate ribosome and tRNA movements during elongation and is thus a crucial mechanistic feature of translation. Beyond elongation, deacylation of peptidyl-tRNA also occurs during translation termination, and this deacylated tRNA persists during ribosome recycling. Here we report that specific regulation of the analogous conformational equilibrium by translation release and ribosome recycling factors has a critical role in the termination and recycling mechanisms. Our results support the view that specific regulation of the global state of the ribosome is a fundamental characteristic of all translation factors and a unifying theme throughout protein synthesis. Ribosome, tRNA and translation factor structural rearrangements are hypothesized to have important mechanistic roles throughout protein synthesis. Some of the most well-characterized conformational changes of the translational machinery include the movements of tRNAs from their classical to their hybrid ribosome binding configurations, movement of the ribosomal L1 stalk from an open to a closed conformation, and the counterclockwise rotation, or ratcheting, of the small (30S) ribosomal subunit relative to the large (50S) subunit The essential features of our dynamic model have recently been largely validated. smFRET studies of pretranslocation complexes have reported spontaneous and reversible intersubunit rotation between two major conformations, nonratcheted and ratcheted 10 , as well as fluctuations of the L1 stalk between open and closed conformations 11 (J.F and R.L.G., unpublished data). Collectively, these studies revealed that the equilibrium constants governing the nonratcheted#ratcheted ribosome and open#closed L1 stalk equilibria are closely correlated 11 , reinforcing the idea that these dynamic processes are coupled. Consistent with this model, two recent cryo-EM studies used classification methods to reveal the existence of both GS1-and GS2-like conformations within a single pretranslocation sample 6,7 , without any detectable intermediates. Nevertheless, our GS1#GS2 model certainly does not incorporate all of the dynamic complexity encompassed by a B2.5-MDa biomolecular machine. In addition, it remains entirely possible that short-lived and/or rarely sampled intermediates have so far eluded detection by smFRET experiments and cryo-EM reconstructions. Thus, the GS1#GS2 model represents the simplest dynamic model that is consistent with the available data, providing a convenient framework for investigating the dynamics of the translating ribosome. We have previously reported that reversible transitions between GS1 and GS2 are prompted by peptidyltransfer to either an A-site aminoacyl-tRNA (aa-tRNA) or to the antibiotic puromycin 8 . Puromycin mimics the 3¢-terminal residue of aa-tRNA 12 but, unlike a fully intact aa-tRNA, dissociates rapidly from the A site upon peptidyltransfer. Therefore, deacylation of P-site peptidyl-tRNA alone, regardless of A-site occupancy, is necessary and sufficient to trigger GS1#GS2 fluctuations. Binding of the GTPase ribosomal translocase, elongation factor G (EF-G), stabilizes GS2 (refs. 8, Beyond elongation, a deacylated tRNA also occupies the P site during translation termination and ribosome recycling, raising the possibility that regulation of the GS1#GS2 equilibrium may be mechanistically important throughout these additional stages of protein synthesis. During termination, a stop codon in the A site o