Deciphering transcript architectural complexity in bacteria and archaea.

RNA transcripts are potential therapeutic targets, yet bacterial transcripts have uncharacterized biodiversity. We developed an algorithm for transcript prediction called tp.py using it to predict transcripts (mRNA and other RNAs) in K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria), strains Scott A and RO15 (Bacteria:Firmicute), strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and (Archaea:Halobacteria).

Cohort study: Neurological and cognitive-behavioral sequelae of acquired Zika virus infection among Nicaraguan children.

Background: ZIKV has neuroinvasive properties, and in utero exposure can cause birth defects, but little is known about the neurological and neurocognitive impacts of acquired ZIKV infection, particularly in children.

Methods: We assessed neurological symptoms frequency among ZIKV-infected children within one year after ZIKV infection. Three to 5 years post-infection, these children and a matched group of uninfected children were assessed via questionnaires, neurological exams, and neuropsychological testing to evaluate the association between prior ZIKV infection and subsequent neurological symptoms, and cognitive-behavioral function.

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.

Common analysis of direct RNA sequencinG CUrrently leads to misidentification of mC 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 (mC) 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 viruses, bacteria, fungi, and animals.

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

RNA modifications, such as méthylation, can be detected with Oxford Nanopore Technologies direct RNA sequencing. One commonly used tool for detecting 5-methylcytosine (mC) 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.