One hurdle to understanding how molecular machines work, and how they evolve, is our inability to see their structures in situ. Here we describe a minicell system that enables in situ cryogenic electron microscopy imaging and single particle analysis to investigate the structure of an iconic molecular machine, the bacterial flagellar motor, which spins a helical propeller for propulsion. We determine the structure of the high-torque Campylobacter jejuni motor in situ, including the subnanometre-resolution structure of the periplasmic scaffold, an adaptation essential to high torque. Our structure enables identification of new proteins, and interpretation with molecular models highlights origins of new components, reveals modifications of the conserved motor core, and explain how these structures both template a wider ring of motor proteins, and buttress the motor during swimming reversals. We also acquire insights into universal principles of flagellar torque generation. This approach is broadly applicable to other membrane-residing bacterial molecular machines complexes.

ABSTRACT Background Knowing the molecules encoded by bacterial pathogens and how their expression is regulated is essential to understand how they survive, colonize, and cause disease. RNA-seq technologies that map transcriptomes have revealed a wealth of new transcripts in bacterial pathogens. However, they do not provide direct evidence or coordinates for coding potential. In particular, they miss small proteins (≤ 50-100 amino acids) translated from small open reading frames (sORFs). However, this still poorly annotated component of bacterial genomes shows emerging roles in bacterial physiology and virulence. Results Here, we present an integrated approach based on complementary ribosome profiling (Ribo-seq) techniques to map the “translatome” of Campylobacter jejuni , the most common cause of bacterial gastroenteritis. Besides conventional Ribo-seq, we employed translation initiation site (TIS) profiling to map start codons and reveal internal sORFs. We also developed a Ribo-seq approach for mapping of translation termination sites (TTS), which revealed stop codons not apparent from the reference genome in virulence-associated loci. Our translatome map confirms translation of leaderless ORFs and leader peptides, re-annotates start or stop codons of 35 genes, and reveals isoforms generated by internal start sites. It also adds 42 novel sORFs in diverse contexts to the C. jejuni annotation, such as within small RNAs, in 5′ untranslated regions (UTRs), or internal/out-of-frame/antisense in larger ORFs. Using epitope tagging/western blot and mass spectrometry we validated expression of almost 60 annotated and novel sORFs, including cioY , which we show encodes a conserved, 34 amino acid component of the CioAB terminal oxidase. Conclusions Overall, we provide a blueprint for integrating several Ribo-seq approaches to refine and enrich bacterial annotations.

Motivation Ribosome profiling (Ribo-seq) is a powerful approach based on ribosome-protected RNA fragments to explore the translatome of a cell, and is especially useful for the detection of small proteins (<=70 amino acids) that are recalcitrant to biochemical and in silico approaches. While pipelines are available to analyze Ribo-seq data, none are designed explicitly for the analysis of Ribo-seq data from prokaryotes, nor are they focused on the discovery of unannotated open reading frames (ORFs) in bacteria. Results We present HRIBO (High-throughput annotation by Ribo-seq), a workflow to enable reproducible and high-throughput analysis of bacterial Ribo-seq data. The workflow performs all required pre-processing and quality control steps. Importantly, HRIBO outputs annotation-independent ORF predictions based on two complementary bacteria-focused tools, and integrates them with additional features. This facilitates the rapid discovery of novel ORFs and their prioritization for functional characterization. Availability HRIBO is a free and open source project available under the GPL-3 license at: https://github.com/RickGelhausen/HRIBO