Gene machines

Abstract:

Transcription in bacteria is controlled by multiple molecular mechanisms that precisely regulate gene expression. It has been recently shown that initial RNA synthesis by the bacterial RNA polymerase (RNAP) is interrupted by pauses; however, the pausing determinants and the relationship of pausing with productive and abortive RNA synthesis remain poorly understood. Using single-molecule FRET and biochemical analysis, here we show that the pause encountered by RNAP after the synthesis of a 6-nt RNA (ITC6) renders the promoter escape strongly dependent on the NTP concentration. Mechanistically, the paused ITC6 acts as a checkpoint that directs RNAP to one of three competing pathways: productive transcription, abortive RNA release, or a new unscrunching/scrunching pathway. The cyclic unscrunching/scrunching of the promoter generates a long-lived, RNA-bound paused state; the abortive RNA release and DNA unscrunching are thus not as tightly linked as previously thought. Finally, our new model couples the pausing with the abortive and productive outcomes of initial transcription.

Abstract:

Biological function is fundamentally determined by nucleic acid and protein sequence. Beyond encoding genetic information, nucleic acids also display complex physicochemical parameters that shape structure, dynamics, and interactions. Understanding how sequence variation sculpts the energetic landscapes underlying these properties requires methods that capture both molecular diversity and dynamic behavior. Single-molecule techniques are ideally suited to this task, but conventional formats remain time and cost intensive. Recent breakthroughs have enabled highly multiplexed approaches for observing molecular dynamics across millions of individual molecules representing thousands of sequences or barcoded entities. Though still in development, these methods have begun to bridge sequence, structure, dynamics, and function at scale, opening new opportunities in drug discovery, molecular diagnostics, and functional genomics. Editor’s summary How DNA and RNA molecules fold, move, and interact is controlled by their sequence in complex ways that remain obscure. Existing methods can either determine sequences or measure single-molecule dynamics, but they typically do not connect both types of information for large numbers of distinct sequences at once. Kapanidis et al . reviewed new approaches that track the real-time dynamics of hundreds of thousands of individual molecules and then read out the exact sequence of each one. By linking sequence to kinetic “behavior profiles,” these methods open new routes to understanding mutations, drug action, and molecular mechanisms. —Di Jiang BACKGROUND Biomolecules derive their function from sequence. Small changes in DNA, RNA, or protein sequence can shift structure, mechanics, and reaction pathways. These effects shape folding, binding equilibria, and the mechanochemical cycles of molecular machines. Ensemble assays have mapped many sequence-function relationships, but population averaging obscures transient intermediates, rare states, alternative pathways, and static heterogeneity. Single-molecule methods overcome this limitation. Techniques such as single-molecule fluorescence resonance energy transfer (smFRET), colocalization imaging, optical and magnetic tweezers, and nanopore-based force spectroscopy reveal real-time transitions between structural states that bulk measurements hide. Yet typical single-molecule experiments are slow and low throughput, typically probing one construct at a time. This bottleneck has limited our ability to explore large sequence spaces and to connect specific sequences to detailed kinetics. ADVANCES New multiplexed single-molecule strategies now address this gap. Recent work links the functional “phenotype” of an individual molecule to its precise sequence across thousands of variants in one experiment. Two general approaches have emerged: MUSCLE (multiplexed single-molecule characterization at the library scale) and SPARXS (single-molecule parallel analysis for rapid exploration of sequence space) couple TIRF (total internal reflection fluorescence)–based fluorescence trajectories with in situ Illumina sequencing, generating millions of spatially registered traces tied directly to a known variant. SPIN-seq (single-molecule phenotyping and in situ sequencing) uses single-molecule sequencing-by-hybridization on surface-immobilized DNA to identify each sequence variant after kinetic imaging on the same TIRF microscope. These methods now enable sequence-resolved measurements of conformational dynamics, kinetic landscapes, reaction pathways, and static heterogeneity at scale. This capability has already revealed how sequence tunes Holliday junction isomerization, DNA hairpin breathing, and Cas9-induced target unwinding and rewinding. It complements earlier single-molecule work showing that the stepping behavior of polymerases, helicases, polymerases, and ribosomes is dictated by local, sequence-dependent energy barriers. Multiplexing now generalizes such analyses to full libraries measured under identical conditions. Technical challenges remain: Field-of-view limitations, photobleaching, and incomplete cluster formation reduce throughput relative to standard next-generation sequencing. Rare behaviors may be missed when sampling limits are reached, and nonequilibrium reactions are difficult to synchronize across large sample surfaces. Advances in imaging hardware, photostable labeling, and optically fmotions and rotational degrees of be key for further development. OUTLOOK The scope of multiplexed single-molecule techniques is also expanding beyond nucleic acids. Display technologies or DNA-barcoded proteins could support high-throughput kinetic analysis of peptide and protein libraries, including protein-protein, protein-ligand, and aptamer-ligand interactions relevant to drug discovery. Integrations with super-resolution imaging, force spectroscopy, or DNA origami scaffolds may extend measurements to mesoscale (tens to hundreds of nanometers up to a few micrometers) structural motions and rotational degrees of freedom. The iterative interplay between large-scale single-molecule datasets and machine-learning models will enable deeper interpretation and accelerate the discovery of sequence-function relationships. Ultimately, these developments reunite high-throughput sequencing with single-molecule biophysics. Tying molecular identity to dynamic behavior for millions of molecules provides a powerful route to map sequence-structure-function relationships with unprecedented resolution. This convergence promises a next generation of tools for mechanistic biology and molecular engineering. Sequence-function relationships across complex kinetic landscapes. Conventional single-molecule assays reveal functional phenotypes such as Cas9 R-loop formation, rewinding, and conformational equilibria yet seldom show how these dynamic processes depend on sequence. Multiplexed approaches integrate pooled library assembly, kinetic imaging, in situ sequencing, and per-molecule registration to assign trajectories to specific variants, enabling direct analysis of how sequence modulates energetic landscapes, intermediate states, and pathway heterogeneity.

Abstract:

Conjugal transfer of plasmids between bacteria is a major route for the spread of antimicrobial resistance. Many conjugative plasmids encode exclusion systems that inhibit redundant conjugation. In incompatibility group F (IncF) plasmids surface exclusion is mediated by the outer membrane protein TraT. Here we report the cryoEM structure of the TraT exclusion protein complex from the canonical F plasmid of Escherichia coli. TraT is a hollow homodecamer shaped like a chef’s hat. In contrast to most outer membrane proteins, TraT spans the outer membrane using transmembrane a-helices. We develop a microscopy-based conjugation assay to  probe the effects of directed mutagenesis on TraT. Our analysis provides no support for the idea that TraT has specific interactions with partner proteins. Instead, we infer that TraT is most likely to function by physical interference with conjugation. This work provides structural insight into a natural inhibitor of microbial gene transfer.

Abstract:

Influenza A, a negative-sense RNA virus, has a genome that consists of eight single-stranded RNA segments. Influenza co-infections can result in reassortant viruses that contain gene segments from multiple strains, causing pandemic outbreaks with severe consequences for human health. The outcome of reassortment is likely influenced by a selective sequence-specific genome packaging mechanism. To uncover the contributions of individual segment pairings to selective packaging, we set out to statistically analyse packaging defects and inter-segment distances in individual A/Puerto Rico/8/34 (H1N1) (PR8) virus particles. To enable such analysis, we developed a multiplexed DNA-PAINT approach capable of assessing the segment stoichiometry of >10 000 individual virus particles in one experiment; our approach can also spatially resolve the individual segments inside complete virus particles with a localization precision of ∼10 nm. Our results show the influenza genome can be assembled through multiple pathways in a redundant and cooperative process guided by preferentially interacting segment pairs and aided by synergistic effects that enhance genome assembly, driving it to completion. Our structural evidence indicates that the interaction strength of segment pairs affects the spatial configuration of the gene segments, which appears to be preserved in mature virions. As our method quantified the interactions of whole influenza segments instead of identifying individual sequence-based interactions, our results can serve as a template to quantify the contributions of individual sequence motifs to selective packaging.