Novel small RNA (sRNA) landscape of the starvation-stress response transcriptome of Salmonella enterica serovar typhimurium.

Small RNAs (sRNAs) are short (∼50-200 nucleotides) noncoding RNAs that regulate cellular activities across bacteria. Salmonella enterica starved of a carbon-energy (C) source experience a host of genetic and physiological changes broadly referred to as the starvation-stress response (SSR). In an attempt to identify novel sRNAs contributing to SSR control, we grew log-phase, 5-h C-starved and 24-h C-starved cultures of the virulent Salmonella enterica subspecies enterica serovar Typhimurium strain SL1344 and comprehensively sequenced their small RNA transcriptomes. Strikingly, after employing a novel strategy for sRNA discovery based on identifying dynamic transcripts arising from "gene-empty" regions, we identify 58 wholly undescribed Salmonella sRNA genes potentially regulating SSR averaging an ∼1,000-fold change in expression between log-phase and C-starved cells. Importantly, the expressions of individual sRNA loci were confirmed by both comprehensive transcriptome analyses and northern blotting of select candidates. Of note, we find 43 candidate sRNAs share significant sequence identity to characterized sRNAs in other bacteria, and ∼70% of our sRNAs likely assume characteristic sRNA structural conformations. In addition, we find 53 of our 58 candidate sRNAs either overlap neighboring mRNA loci or share significant sequence complementarity to mRNAs transcribed elsewhere in the SL1344 genome strongly suggesting they regulate the expression of transcripts via antisense base-pairing. Finally, in addition to this work resulting in the identification of 58 entirely novel Salmonella enterica genes likely participating in the SSR, we also find evidence suggesting that sRNAs are significantly more prevalent than currently appreciated and that Salmonella sRNAs may actually number in the thousands.

Under-Representation of Racial Groups in Genomics Studies of Gastroenteropancreatic Neuroendocrine Neoplasms.

Not all populations are poised to benefit from advancing genomics in gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN), as genomics have focused on White patients. This study aimed to evaluate racial populations represented in genomic studies of GEP-NENs and to provide evidence of differential genomic findings between racial groups in GEP-NENs. Manuscripts analyzing DNA, RNA, or DNA methylation in GEP-NENs were queried using PUBMED and EMBASE. NIH race/ethnicity term frequency was then determined by Natural Language Processing, followed by manual evaluation of tumor types and subjects by racial group. IHC of institutional tissue micro-arrays and analysis of AACR GENIE data analyzed was performed to determine mutational differences between Black and White pancreatic NEN (pNEN) patients. 313 manuscripts conducted the requisite genomic analyses, 16 of which included subject race data. Race data were included in 13/184 DNA, 4/107 RNA, and 1/54 DNA Methylation analyses. These studies included 89% White subjects (n = 2032), 5.8% Asian subjects (n = 132), 4.0% "Other" subjects (n = 93), and 1.2% Black subjects (n = 27). No Native American/Alaska Native, Native Hawaiian/Pacific Islander, or ethnically Hispanic/Latinx subjects were represented. There were significant differences in MEN1 mutations among Black and White patients in immunohistochemical (13:40) and GENIE data (24:268 patients per group, respectively), with 9 additional genes differentially mutated in the GENIE dataset. Genomic sequencing data for GEP-NENs is almost racially homogenous. Differences in pNEN genomics may exist between racial groups, highlighting a need for diversity in future genomic analyses of GEP-NENs to understand the putative influence of interracial genomic variation on GEP-NEN prevention, diagnosis, and therapy. Significance: There is little diversity in genomic studies of GEP-NENs, which may exhibit clinically impactful variation in their tumor biology among racial groups. Improved diversity in such studies is imperative for understanding this variation and its potential impacts on disease prevention, diagnosis, therapeutic targeting, and clinical outcomes.