Identification of leader-trailer helices of precursor ribosomal RNA in all phyla of bacteria and archaea.

Ribosomal RNAs are transcribed as part of larger precursor molecules. In Escherichia coli, complementary RNA segments flank each rRNA and form long leader-trailer (LT) helices, which are crucial for subunit biogenesis in the cell. A previous study of 15 representative species suggested that most but not all prokaryotes contain LT helices. Here, we use a combination of in silico folding and covariation methods to identify and characterize LT helices in 4,464 bacterial and 260 archaeal organisms. Our results suggest that LT helices are present in all phyla, including Deinococcota, which had previously been suspected to lack LT helices. In very few organisms, our pipeline failed to detect LT helices for both 16S and 23S rRNA. However, a closer case-by-case look revealed that LT helices are indeed present but escaped initial detection. 3,618 secondary structure models, many well-supported by nucleotide covariation, were generated. These structures show a high degree of diversity. Yet, all exhibit extensive base-pairing between the leader and trailer strands, in line with a common and essential function.

Analysis of programmed frameshifting during translation of prfB in Flavobacterium johnsoniae.

Ribosomes of Bacteroidia fail to recognize Shine-Dalgarno (SD) sequences due to sequestration of the 3' tail of the 16S rRNA on the 30S platform. Yet in these organisms, the prfB gene typically contains the programmed +1 frameshift site with its characteristic SD sequence. Here, we investigate prfB autoregulation in Flavobacterium johnsoniae, a member of the Bacteroidia. We find that the efficiency of prfB frameshifting in F. johnsoniae is low (∼7%) relative to that in Escherichia coli (∼50%). Mutation or truncation of bS21 in F. johnsoniae increases frameshifting substantially, suggesting that anti-SD (ASD) sequestration is responsible for the reduced efficiency. The frameshift site of certain Flavobacteriales, such as Winogradskyella psychrotolerans, has no SD. In F. johnsoniae, this W. psychrotolerans sequence supports frameshifting as well as the native sequence, and mutation of bS21 causes no enhancement. These data suggest that prfB frameshifting normally occurs without SD-ASD pairing, at least under optimal laboratory growth conditions. Chromosomal mutations that remove the frameshift or ablate the SD confer subtle growth defects in the presence of paraquat or streptomycin, respectively, indicating that both the autoregulatory mechanism and the SD element contribute to F. johnsoniae cell fitness. Analysis of prfB frameshift sites across 2686 representative bacteria shows loss of the SD sequence in many clades, with no obvious relationship to genome-wide SD usage. These data reveal unexpected variation in the mechanism of frameshifting and identify another group of organisms, the Verrucomicrobiales, that globally lack SD sequences.

UltraSEQ, a Universal Bioinformatic Platform for Information-Based Clinical Metagenomics and Beyond.

Applied metagenomics is a powerful emerging capability enabling the untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of-its-kind accurate and scalable metagenomic bioinformatic tool for potential clinical diagnostics and biosurveillance utility. Here, we present the results of the evaluation of our novel UltraSEQ pipeline using an in silico-synthesized metagenome, mock microbial community data sets, and publicly available clinical data sets from samples of different infection types, including both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in the in silico sample and detected all 10 bacterial and fungal species in the mock microbial community data set. For clinical data sets, even without requiring data set-specific configuration setting changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Furthermore, as an initial demonstration with a limited patient sample set, we show UltraSEQ's ability to provide antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results. Taken together, the above-described results demonstrate that the UltraSEQ platform offers a transformative approach for microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for the classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infections. IMPORTANCE Traditional clinical microbiology-based diagnostic tests rely on targeted methods that can detect only one to a few preselected organisms or slow, culture-based methods. Although widely used today, these methods have several limitations, resulting in rates of cases of an unknown etiology of infection of >50% for several disease types. Massive developments in sequencing technologies have made it possible to apply metagenomic methods to clinical diagnostics, but current offerings are limited to a specific disease type or sequencer workflow and/or require laboratory-specific controls. The limitations associated with current clinical metagenomic offerings result from the fact that the backend bioinformatic pipelines are optimized for the specific parameters described above, resulting in an excess of unmaintained, redundant, and niche tools that lack standardization and explainable outputs. In this paper, we demonstrate that UltraSEQ uses a novel, information-based approach that enables accurate, evidence-based predictions for diagnosis as well as the functional characterization of a sample.

Ribosomes lacking bS21 gain function to regulate protein synthesis in Flavobacterium johnsoniae.

Ribosomes of Bacteroidia (formerly Bacteroidetes) fail to recognize Shine-Dalgarno (SD) sequences even though they harbor the anti-SD (ASD) of 16S rRNA. Inhibition of SD-ASD pairing is due to sequestration of the 3' tail of 16S rRNA in a pocket formed by bS21, bS18, and bS6 on the 30S platform. Interestingly, in many Flavobacteriales, the gene encoding bS21, rpsU, contains an extended SD sequence. In this work, we present genetic and biochemical evidence that bS21 synthesis in Flavobacterium johnsoniae is autoregulated via a subpopulation of ribosomes that specifically lack bS21. Mutation or depletion of bS21 in the cell increases translation of reporters with strong SD sequences, such as rpsU'-gfp, but has no effect on other reporters. Purified ribosomes lacking bS21 (or its C-terminal region) exhibit higher rates of initiation on rpsU mRNA and lower rates of initiation on other (SD-less) mRNAs than control ribosomes. The mechanism of autoregulation depends on extensive pairing between mRNA and 16S rRNA, and exceptionally strong SD sequences, with predicted pairing free energies of < -13 kcal/mol, are characteristic of rpsU across the Bacteroidota. This work uncovers a clear example of specialized ribosomes in bacteria.

Function-based classification of hazardous biological sequences: Demonstration of a new paradigm for biohazard assessments.

Bioengineering applies analytical and engineering principles to identify functional biological building blocks for biotechnology applications. While these building blocks are leveraged to improve the human condition, the lack of simplistic, machine-readable definition of biohazards at the function level is creating a gap for biosafety practices. More specifically, traditional safety practices focus on the biohazards of known pathogens at the organism-level and may not accurately consider novel biodesigns with engineered functionalities at the genetic component-level. This gap is motivating the need for a paradigm shift from organism-centric procedures to function-centric biohazard identification and classification practices. To address this challenge, we present a novel methodology for classifying biohazards at the individual sequence level, which we then compiled to distinguish the biohazardous property of pathogenicity at the whole genome level. Our methodology is rooted in compilation of hazardous functions, defined as a set of sequences and associated metadata that describe coarse-level functions associated with pathogens (e.g., adherence, immune subversion). We demonstrate that the resulting database can be used to develop hazardous "fingerprints" based on the functional metadata categories. We verified that these hazardous functions are found at higher levels in pathogens compared to non-pathogens, and hierarchical clustering of the fingerprints can distinguish between these two groups. The methodology presented here defines the hazardous functions associated with bioengineering functional building blocks at the sequence level, which provide a foundational framework for classifying biological hazards at the organism level, thus leading to the improvement and standardization of current biosecurity and biosafety practices.

Maturation of 23S rRNA includes removal of helix H1 in many bacteria.

In most bacteria, the three ribosomal RNAs (rRNAs) are encoded together in each of several near-identical operons. As soon as the nascent precursor rRNA emerges from RNA polymerase, ribosome assembly begins. This process entails ribosomal protein binding, rRNA folding, rRNA modification, and rRNA processing. In the model organisms Escherichia coli and Bacillus subtilis, rRNA processing results in similar mature rRNAs, despite substantial differences in the cohort of RNAses involved. A recent study of Flavobacterium johnsoniae, a member of the phylum Bacteroidota (formerly Bacteroidetes), revealed that helix H1 of 23S rRNA is absent from ribosomes, apparently a consequence of rRNA maturation. In this work, we mined RNA-seq data from 19 individual organisms and ocean metatranscriptomic samples to compare rRNA processing across diverse bacterial lineages. We found that mature ribosomes from multiple clades lack H1, and typically these ribosomes also lack an encoded H98. For all groups analysed, H1 is predicted to form in precursor rRNA as part of a longer leader-trailer helix. Hence, we infer that evolutionary loss of H98 sets the stage for H1 removal during 50S subunit maturation.