Biology subjects

Lebov, J. F.

Publications and source records attributed to Lebov, J. F..

3 recordsLinked to original sources

bioRxiv2024

Deciphering Bacterial and Archaeal Transcriptional Dark Matter and Its Architectural Complexity

Transcripts are potential therapeutic targets, yet bacterial transcripts remain biological dark matter with uncharacterized biodiversity. We developed and applied an algorithm to predict transcripts for Escherichia coli K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria) with newly generated ONT direct RNA sequencing data while predicting transcripts for Listeria monocytogenes strains Scott A and RO15 (Bacteria:Firmicute), Pseudomonas aeruginosa strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and Haloferax volcanii (Archaea:Halobacteria) using publicly available data. From >5 million E. coli K12 ONT direct RNA sequencing reads, 2,484 mRNAs are predicted and contain more than half of the predicted E. coli proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used for the predictions, across all strains examined, the average size of the predicted mRNAs is 1.6-1.7 kbp while the median size of the predicted bacterial 5-and 3-UTRs are 30-90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions are of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in the E. coli E2348/69 LEE pathogenicity islands. We predicted small transcripts in the 100-200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being the nuo operon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, inexpensive, and reproducible method will facilitate the presentation of operons, transcripts, and UTR predictions alongside CDS and protein predictions in bacterial genome annotation as important resources for the research community.

genomics↗

bioRxiv2023

Common Analysis of Direct RNA SequencinG CUrrently Leads to Misidentification of 5-Methylcytosine Modifications at GCU Motifs

RNA modifications, such as methylation, can be detected with Oxford Nanopore Technologies direct RNA sequencing. One commonly used tool for detecting 5-methylcytosine (m5C) modifications is Tombo, which uses an "Alternative Model" to detect putative modifications from a single sample. We examined direct RNA sequencing data from diverse taxa including virus, bacteria, fungi, and animals. The algorithm consistently identified a 5-methylcytosine at the central position of a GCU motif. However, it also identified a 5-methylcytosine in the same motif in fully unmodified in vitro transcribed RNA, suggesting that this a frequent false prediction. In the absence of further validation, several published predictions of 5-methylcytosine in human coronavirus and human cerebral organoid RNA in a GCU context should be reconsidered. IMPORTANCEThe detection of chemical modifications to RNA is a rapidly expanding field within epigenetics. Nanopore sequencing technology provides an attractive means of detecting these modifications directly on the RNA, but accurate modification predictions are dependent upon the software developed to interpret the sequencing results. One of these tools, Tombo, allows users to detect modifications using sequencing results from a single RNA sample. However, we find that this method falsely predicts modifications in a specific sequence context across a variety of RNA samples, including RNA that lacks modifications. Results from previous publications include predictions in human coronaviruses with this sequence context and should be reconsidered. Our results highlight the importance of using RNA modification detection tools with caution in the absence of a control RNA sample for comparison.

genomics↗

bioRxiv2020

Phenotypic parallelism during experimental adaptation of a free-living bacterium to the zebrafish gut

Despite the fact that animals encounter a plethora of bacterial species throughout their lives, only a subset are capable of colonizing vertebrate digestive tracts, and these bacteria can profoundly influence the health and development of their animal hosts. However, it is still unknown how bacteria evolve symbioses with animal hosts, and this process is central to both the assembly and function of gut bacterial communities. Therefore, we used experimental evolution to study a free-living bacterium as it adapts to a novel vertebrate host. We serially passaged replicate populations of Shewanella oneidensis, through the digestive tracts of larval zebrafish (Danio rerio). After only 20 passages, representing approximately 200 bacterial generations, isolates from replicate evolved populations displayed an improved ability to colonize larval zebrafish digestive tracts during competition against their unpassaged ancestor. Upon sequencing the genomes of these evolved isolates, we discovered that the two isolates with the highest mean competitive fitness accumulated unique sets of mutations. We characterized the swimming motility and aggregation behavior of these isolates, as these phenotypes have previously been shown to alter host-microbe interactions. Despite exhibiting different biofilm characteristics, both isolates evolved augmented swimming motility. These enhancements are consistent with expectations based on the behavior of a closely related Shewanella strain previously isolated from the zebrafish digestive tract and suggest that our evolved isolates are pursuing a convergent adaptive trajectory with this zebrafish isolate. In addition, parallel enhancements in swimming motility among isolates from independently adapted populations implicates increased dispersal as an important factor in facilitating the onset of host association. Our results demonstrate that free-living bacteria can rapidly improve their associations with vertebrate hosts.

evolutionary biology↗