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Title: The Role of Extracellular RNA in Intercellular and Interkingdom Communication
All cellular organisms secrete RNAs. Emerging evidence identifies intercellular communication as a key
function of extracellular RNA (exRNA), including communication between organisms. RNA has many
characteristics that make it a good signal: it is ephemeral, information-dense, and common to all forms of
life. Understanding how to manipulate exRNA communication can advance both agriculture and medicine
through the development of new environmentally friendly pesticides, treatments of dysbiosis in both plants
and animals (converting unhealthy microbiomes to healthy ones), and a host of new diagnostic and
therapeutic tools for earlier detection and/or treatment of disease. For example, a bacterial bee gut symbiont
was recently engineered to express a dsRNA that targets parasitic mite genes. Remarkably, this RNA
accumulated in the bee hemolymph where no bacteria are present, and was taken up by the mites, inhibiting
their growth, potentially providing a new exRNA-based alternative to traditional miticides for protecting
beehives (Leonard et al., 2020). Similarly, there is compelling evidence that RNAs secreted from
mammalian cells can be taken up by bacteria and impact prokaryotic protein expression. Liu et al., (2016)
showed that several different microRNAs shed by mouse gut epithelial cells are contained in mouse fecal
material and notably, that several of these RNAs are taken up by gut bacteria and alter the expression of
genes with complementary sequences. This work shows that hosts can actively regulate their microbiomes
via RNA transfer. Here, we propose exRNA-based communication goes beyond miRNAs, as analysis of
exRNAs in plants and animals has established that miRNAs make up a tiny fraction of total exRNA, with
many ncRNAs being far more abundant. Further, recent findings suggest that circular RNAs and tRNA
fragments are especially abundant in exRNA; these RNAs have been implicated in diverse mechanisms
of gene regulation and have been shown to increase in abundance in response to stress (Thompson et al.,
2008). Critically, we have recently discovered that plant exRNAs are highly enriched in the post-
transcriptional modification N6methyladenine (m6A), suggesting that post-transcriptional modifications may
tag specific RNAs for export (Zand Karimi et al., 2022). Consistent with this idea, a large number of
mammalian small ncRNAs were recently shown to bear sialylated glycans; the majority of these glycoRNAs
localized to the cell surface (Flynn et al., 2022).
In summary, as multicellular organismal health is intimately tied to its microbiota and intercellular
communication, we believe that a deeper understanding of the determinants of exRNA communication will
transform our understanding of this communication and likely lead to new agricultural and medical
innovations. While the ability of cells to communicate through the exchange of exRNA has now been
demonstrated across all domains of life, the mechanistic details regarding how exRNAs are selected and
marked for secretion, how these exRNA identify their target cells, and the effects their delivery have on
cellular recipients remain almost entirely undescribed. Here we propose to address the following
fundamental RESEARCH QUESTIONS:
1) Do exRNA modifications direct intra- and/or inter-organismal cellular communication? (Aims 1 & 2)
2) Do host exRNAs shape the structure and activity of their microbiomes through regulating prokaryotic
gene expression? (Aim 3)
3) Are exRNA modification roles universally conserved or are they class/species-specific? (Aims 1-2-3)
CONTEMPLATED AIMS: As we are interested in the universality of the signal, we propose a
taxonomically broad approach to establish general patterns and leverage unique tools.
Aim 1: Define the modification-based exRNA secretory code. There are three (3) classes of exRNA that
potentially contribute to communication: (i) vesicle-contained RNA, (ii) membrane-bound RNA, and (iii) free
RNA. Specific chemical modifications of biological molecules are an efficient way of regulating molecular
function. We hypothesize that RNA contained within these classes have different modifications (exRNA ZIP
codes) that direct RNAs into specific secretory pathways.
Aim 1a – Identify exRNA modifications associated with specific exRNA classes: To characterize the RNA
modifications found on exRNAs from all three (3) classes of exRNA across eukaryotic kingdoms we will
use human cell lines, army cutworm (Spodortera frugiperda) cell lines, and maize (Zea mays) leaves. We
will first sequence the RNAs and identify the modifications (e.g. m6A, glycosylations) associated with each
class (and total RNA control) using both small and long RNA-seq as well as Nanopore direct RNA
sequencing and tandem Mass Spec (MS) to interrogate the transcriptomes and epitranscriptomes of each
exRNA class. (Months 1 - 18).
Aim 1b – Identify specific modifications and sequences significantly associated with exRNA classes across
kingdoms. We will apply logistic regression, AJIVE, and Deep Learning to determine the RNA modifications
and ratio of different RNA populations associated with each organism and then utilize these analyses to
identify shared or signature modification motifs across taxa. (Months 18 - 40).
Aim 1c – Assess modification roles in RNA secretion: Determine if specific RNA modifications are
necessary and/or sufficient for directing individual RNAs for secretion via one of the distinct exRNA class
mechanisms. We will create and introduce synthetic RNAs bearing modifications identified as being
associated with individual classes in Aim 1b, then determine if these synthetic RNAs are specifically
enriched in our predicted exRNA populations. Alternatively, modified residues identified in RNAs localized
to specific classes may be directly mutated. (Months 25 - 48).
Aim 2: Characterize exRNA populations participating in inter-species and intra-organismal cellular
communication. We hypothesize that in both inter-species and intra-organismal cellular communication
RNAs are transferred from the signaler cell (plant/insect/vertebrate) into the receiver cell (bacteria/self);
AND that the class of extracellular RNAs moving from cell to cell differ for these two types of communication.
To address these hypotheses, we will:
Aim 2a – Define characteristics of exRNAs participating in inter-species cellular communication: We will (i)
study the RNA transfer between eukaryotes and their associated bacterial community, (ii) identify the
signals that drive that movement, and (iii) assess the conservation and universality of these signals. We
will evaluate interspecies communication by probing: human gut epithelial, insect, and plant leaf interactions
with specific microbial communities. We will sequence the transcriptomes of recipient microbes to identify
internalized host RNAs, then correlate these with exRNA class transcriptomes to determine mode of
delivery. In addition, we will identify enriched RNA modifications in microbial transcriptomes (+/- host RNA
delivery) by MS and statistical analyses performed as in Aim 1. As a complementary approach, we will use
sequence capture to isolate exRNAs shown to be preferentially taken up by bacterial symbionts and then
define their modifications by MS. (Months 13 - 40).
Aim 2b – Define characteristics of exRNAs participating in intra-organismal cellular communication: We
will determine whether classes of RNA utilized in intra-organismal cellular communication differ from those
used for inter-species cellular communication. To this end, we will culture cells in media containing labeled
nucleotides, isolate and purify labeled RNA from each of the 3 exRNA classes, and then incubate “receiver”
cells with purified sets of labeled RNAs. We will then image internalized exRNAs using PAGE and
autoradiography to show which class of RNA is primarily delivered to recipient cells during intra-organismal
communication. We will gel purify labeled RNAs within receivers and subject them to MS and statistical
analyses as in Aim 1. (Months 13 - 36).
Aim 3: Establish functional roles for exRNAs in shaping microbial communities.
Aim 3a – Determine the effects of exRNAs on microbe community structure: To test whether exRNAs
regulate microbiome community structure, we will take total exRNA purified from (i) human epithelial cell
culture, and (ii) the extracellular space of maize leaves, and apply it to a synthetic community of ten (10)
bacterial species that are abundant in the human colon (growing in liquid culture). Maize exRNA is included
here as a proxy for the impact of dietary exRNAs on microbiome structure and as a control for the specificity
of exRNA impact. We will harvest the cells 24 hours later and determine the relative abundance of each
species by 16S rRNA sequencing. We will infer a general role of exRNAs in regulating microbial species
composition by comparing changes in community composition induced by (i) plant exRNAs, (ii) human
exRNAs, (iii) no RNA (control), and (iv) synthetic RNA (control). (Months 1 - 24).
Aim 3b – Assess RNA class impact: If total exRNAs impact community composition (Aim 3a), we will test
whether specific subsets of exRNA (e.g types of RNA, RNA with m6A modifications) have strong effects.
For example, tRNA fragments have been implicated in translation inhibition in a sequence-specific manner,
similar to miRNAs (Lee et al., 2009). If tRNA fragments induce the largest impact, that would suggest that
the change in community composition is mediated by changes in the abundance of specific proteins in
specific species. We will then identify specific RNAs and proteins reduced upon exRNA application using
metatranscriptomics and quantitative proteomics. (Months 10 - 30).
Aim 3c – Define individual exRNA functions: As a final step, we will select individual candidate RNAs, using
a combination of abundance and motif specificity. We will CRISPR knockout and/or mutate the modification
site of the selected exRNAs to assess phenotypic effects in individual member species and also effects on
bacterial communities, and conversely, flood the system with the selected exRNA to confirm a reciprocal
response. (Months 24 - 48).
REFERENCES:
Leonard, SP, Powell, JE, Perutka, J, Geng, P, Heckmann, LC, Horak, RD, Davies, BW, Ellington, AD,
Barrick, JE, and Moran, NA. (2020). Engineered symbionts activate honey bee immunity and limit
pathogens. Science 367, 573-576.
Liu, S, da Cunha, AP, Rezende, RM, Cialic, R, Wei, Z, Bry, L, Comstock, LE, Gandhi, R, and Weiner,
HL. (2016). The host shapes the gut microbiota via fecal microRNA. Cell Host Microbe 19, 32-43.
Maori E, Navarro IC, Boncristiani H, Seilly DJ, Rudolph KLM, Sapetschnig A, Lin CC, Ladbury JE,
Evans JD, Heeney JL, et al. (2019) A secreted RNA binding protein forms RNA-stabilizing granules in the
honeybee royal jelly. Mol Cell 74: 598–608 e596
Thompson, DM, Lu, C, Green, PJ, and Parker, R. (2008). tRNA cleavage is a conserved response to
oxidative stress in eukaryotes. RNA 14, 2095-2103.
Zand Karimi, H, Baldrich, P, Rutter, BD, Borniego, L, Zajt, KK, Meyers, BC, and Innes, RW. (2022).
Arabidopsis apoplastic fluid contains sRNA- and circular RNA-protein complexes that are located outside
extracellular vesicles. Plant Cell 34, 1863-1881.
Flynn RA, Pedram K, Malaker SA, Batista PJ, Smith BAH, Johnson AG, George BM, Majzoub K,
Villalta PW, Carette JE, Bertozzi CR. (2021). Small RNAs are modified with N-glycans and displayed on
the surface of living cells. Cell. 2021 Jun 10;184(12):3109-3124.
Lee YS, Shibata Y, Malhotra A, Dutta A. (2009). A novel class of small RNAs: tRNA-derived RNA
fragments (tRFs). Genes Dev. Nov 15;23(22):2639-49.
Status | Active |
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Effective start/end date | 3/1/23 → 2/28/27 |
Funding
- National Science Foundation: $856,318.00
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Projects
- 1 Active
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Participant Support: Ideas Lab: The Role of Extracellular RNA in Intercellular and Interkingdom Communication
Corbin, K. (PI)
3/1/23 → 2/28/27
Project: Research project