Metagenome-wide measurement of protein synthesis in the human fecal microbiota using MetaRibo-Seq

Fremin, Brayon J.; Bhatt, Ami S.

doi:10.1101/482430

Cited by 2 publications

(6 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Focusing only on the 5’ and 3’ ends of reads, representing where MNase fragmentation of the RNA occured, we find that ends of Ribo-Seq reads were overrepresented specifically at junctions between structured and unstructured regions of ssrS . This association was reproducibly observed across studies - in our Ribo-Seq experiments on E. coli MG1655 (Figure 1A), similar experiments performed by Li et al in 2014 1 , and from MetaRibo-Seq experiments carried out on a fecal sample containing a clinical E. coli strain, referred to in a previous manuscript as Sample E 11 . Importantly, this fragmentation pattern was not reproduced in RNA-seq libraries that were not exposed to MNase digestion 1 (Figure 1D).…”

Section: Observationsupporting

confidence: 87%

“…All of these ncRNAs were found to be transcribed (RPKM > 10) in RNA-Seq data from Li et al, 2014 1,2 . 61 of the 65 known ncRNAs (94%) produced a Ribo-Seq signal (RPKM > 10) in Ribo-Seq experiments from Li et al, 2014 1,2 and in Ribo-Seq of MG1655 E. coli performed in our laboratory and recently reported 11 (Table S1). Taken together, this highlights that ‘contaminant’ signals in Ribo-Seq experiments are widespread across different structured RNAs.…”

Section: Observationmentioning

confidence: 68%

“…(B) Ribo-Seq signal across an 18 repeat CRISPR array in Ruminococcus lactaris , also predicted by minCED 12 . For reference, this was predicted from Sample A in previous work 11 . Arrows indicate direct repeats.…”

Section: Observationmentioning

confidence: 99%

See 2 more Smart Citations

Repurposing Ribo-Seq to provide insights into structured RNAs

Fremin

Bhatt

2020

Preprint

Self Cite

View full text Add to dashboard Cite

8Ribosome profiling (Ribo-Seq) is a powerful method to study translation in bacteria. 9 However, this method can enrich RNAs that are not bound by ribosomes, but rather, are 10 protected from degradation in another way. For example, Escherichia coli Ribo-Seq libraries 11 also capture reads from most non-coding RNAs (ncRNAs). These fragments of ncRNAs pass all 12 size selection steps of the Ribo-Seq protocol and survive hours of MNase treatment, presumably 13 without protection from the ribosome or other macromolecules or proteins. Since bacterial 14 ribosome profiling does not directly isolate ribosomes, but instead uses broad size range cutoffs 15 to fractionate actively translated RNAs, it is understandable that some ncRNAs are retained after 16 size selection. However, how these 'contaminants' survive MNase treatment is unclear. Through 17 analyzing metaRibo-Seq reads across ssrS, a well established structured RNA in E. coli, and 18 structured direct repeats from Clustered Regularly Interspaced Short Palindromic Repeats 19 (CRISPR) arrays in Ruminococcus lactaris, we observed that these RNAs are protected from 20 MNase treatment by virtue of their secondary structure. Therefore, large volumes of data 21 previously discarded as contaminants in bacterial Ribo-Seq experiments can, in fact, be used to 22 gain information regarding the in vivo secondary structure of ncRNAs, providing unique insight 23 into their native functional structures. 25Importance 26 We observe that 'contaminant' signals in bacterial Ribo-Seq experiments that are often 27 disregarded and discarded, in fact, strongly overlap with structured regions of ncRNAs. 28 Structured ncRNAs are pivotal mediators of bioregulation in bacteria and their functions are 29 often reliant on their specific structures. We present an approach to access important RNA 30 structural information through merely repurposing 'contaminant' signals in bacterial Ribo-Seq 31 experiments. This powerful approach enables us to partially resolve RNA structures, identify 32 novel structured RNAs, and elucidate RNA structure-function relationships in bacteria at a large-33 scale and in vivo. 34 35 Observation 36Ribosome profiling (Ribo-Seq) in bacteria is a method that enriches for ribosome-37 protected RNAs and therefore, enables the study of active translation events 1,2 . However, this 38 enrichment is not highly selective for ribosomes as relevant protocols do not specifically isolate 39 ribosomes, but rather select for them within an expected size range. Ribo-Seq is especially 40 challenging in bacteria because, unlike in yeast and eukaryotes, bacteria have a broad size 41 distribution of ribosome-protected footprints, ranging from 15-40 nucleotides 3 . The size range 42 that should be selected can vary across Ribo-Seq protocols; at present, most Ribo-Seq 43 experiments on bacteria target a size range of 15 to 45 nucleotides, as was used by Li et al, 44 2014 1 . Hence, bacterial ribosome profiling protocols must adopt less stringent size selection to 45 comprehensively...

show abstract

Section: Observationsupporting

confidence: 87%

Section: Observationmentioning

confidence: 68%

See 1 more Smart Citation

Repurposing Ribo-Seq to provide insights into structured RNAs

Fremin

Bhatt

2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this study, we analyzed metagenomics and RNA-seq without fragment size selection on four taxonomically diverse fecal samples from four different human subjects (A -healthy adult, Bpatient with hematological disorder undergoing treatment, C -patient with cancer undergoing treatment, D -patient with Alzheimer's disease). These are the same samples used in a previous study 10 . First, metagenomic DNA sequencing data from four human stool samples was obtained; these data had previously been subjected to computational assembly and the resultant contigs (longer contiguous DNA sequences that are "in silico" assembled from smaller DNA fragments) were collected.…”

Section: Rna-seq Along With Comparative Genomics Enables Targeted Himentioning

confidence: 99%

“…Quality trimmed metagenomic reads were assembled using metaSPAdes 3.7.0 33 as previously performed 10 . For all samples, a maximum of 60 million metagenomic reads were used to generate assemblies.…”

Section: De Novo Assemblymentioning

confidence: 99%

A combined RNA-Seq and comparative genomics approach identifies 1,085 candidate structured RNAs expressed in human microbiomes

Fremin

Bhatt

2020

Preprint

Self Cite

View full text Add to dashboard Cite

Structured RNAs play varied bioregulatory roles within microbes. To date, hundreds of candidate structured RNAs have been predicted using informatic approaches by searching for motif structures in genomic sequence data. However, only a subset of these candidate structured RNAs, those from culturable, well-studied microbes, have been shown to be transcribed. As the human microbiome contains thousands of species and strains of microbes, we sought to apply both informatic and experimental approaches to these organisms to identify novel transcribed structured RNAs. We combine an experimental approach, RNA-Seq, with an informatic approach, comparative genomics across the human microbiome project, to discover 1,085 candidate, conserved structured RNAs that are actively transcribed in human fecal microbiomes.These predictions include novel tracrRNAs that associate with Cas9 and RNA structures encoded in overlapping regions of the genome that are in opposing orientations. In summary, this combined experimental and computational approach enables the discovery of thousands of novel candidate structured RNAs.

show abstract

Metagenome-wide measurement of protein synthesis in the human fecal microbiota using MetaRibo-Seq

Abstract: 2 9 3 0

Cited by 2 publications

References 60 publications

Repurposing Ribo-Seq to provide insights into structured RNAs

Repurposing Ribo-Seq to provide insights into structured RNAs

A combined RNA-Seq and comparative genomics approach identifies 1,085 candidate structured RNAs expressed in human microbiomes

Contact Info

Product

Resources

About