Identifying Small Proteins by Ribosome Profiling with Stalled Initiation Complexes

Abstract

Small proteins consisting of 50 or fewer amino acids have been identified as regulators of larger proteins in bacteria and eukaryotes. Despite the importance of these molecules, the total number of small proteins remains unknown because conventional annotation pipelines usually exclude small open reading frames (smORFs). We previously identified several dozen small proteins in the model organism Escherichia coli using theoretical bioinformatic approaches based on sequence conservation and matches to canonical ribosome binding sites. Here, we present an empirical approach for discovering new proteins, taking advantage of recent advances in ribosome profiling in which antibiotics are used to trap newly initiated 70S ribosomes at start codons. This approach led to the identification of many novel initiation sites in intergenic regions in E. coli. We tagged 41 smORFs on the chromosome and detected protein synthesis for all but three. Not only are the corresponding genes intergenic but they are also found antisense to other genes, in operons, and overlapping other open reading frames (ORFs), some impacting the translation of larger downstream genes. These results demonstrate the utility of this method for identifying new genes, regardless of their genomic context. IMPORTANCE Proteins comprised of 50 or fewer amino acids have been shown to interact with and modulate the functions of larger proteins in a range of organisms. Despite the possible importance of small proteins, the true prevalence and capabilities of these regulators remain unknown as the small size of the proteins places serious limitations on their identification, purification, and characterization. Here, we present a ribosome profiling approach with stalled initiation complexes that led to the identification of 38 new small proteins.

Are Antisense Proteins in Prokaryotes Functional?

“…The 10 sRNAs these belong to are shown in Figure 1A. Weaver et al (2019) found ribosome profiling evidence, including evidence specifically for translation initiation (using retapamulin), for nine antisense overlapping gene candidates in E. coli K12, also shown in Figure 1A. As reported in a recent pre-print found many overlapping ORFs in Mycobacterium tuberculosis associated with ribosomes using retapamulin.…”

“…The first study of ribosome profiling in bacteria used chloramphenicol in one of the two methods presented (Oh et al, 2011), which has since been shown to stall the ribosome at initiation and thereby can assist in inferring translation initiation site positions , Glaub et al, 2019). More precise stalling has been achieved with the use of tetracycline (Nakahigashi et al, 2016), retapamulin (Meydan et al, 2019), and the antibacterial peptide Onc112 (Weaver et al, 2019). Properties of ribosomes at different stages of translation, including initiation, have recently been studied in Escherichia coli K12 with TCP-seq (Sharma and Anand, 2019).…”

Ribosome Profiling in Archaea Reveals Leaderless Translation, Novel Translational Initiation Sites, and Ribosome Pausing at Single Codon Resolution

“…Mapping translation start sites (TSS) transcriptome-wide with antibiotics to trap initiation complexes has proven to be a powerful strategy in eukaryotes and bacteria (26,27,42). The need for accurate identification of TSS is particularly apparent in Archaea where most gene annotations are generated from general computational pipelines that are not totally reliable.…”

“…TSS identification with harringtonine (HHT) ribosome profiling libraries was done using previously published custom python scripts that were modified for our purposes (26,27). Identification of novel TSS and smORFs was done as previously published (26,27) with the following changes: (a) rpkm was calculated for each TSS peak in both the HHT and no challenge library, (b) the TSS peak rpkm were >5-fold enriched in HHT compared to no challenge, and (c) the ORF rpkm were >5-fold enriched in no challenge compared to HHT. Identification of known TSS, internal TSS (iTSS), and N-terminal extensions was done as previously published using density files assigned to the 3'-end of reads and adjusted for the P-site (15 nt offset) (26).…”

“…We then leveraged HHT-treatment to comprehensively identify initiation sites in Hv using previously established computational methods (26,27). In brief, we identified all potential ORFs, asked if peaks of ribosome density aligned near the start codon of each potential ORF (± 3 nt), verified that these ORFs were translated in profiling data without HHT treatment (≥ 1 rpkm ribosome density), and assigned the type of TSS 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 based on the gene annotation (NCBI RefSeq).…”