Search bioRxiv⌕ Search

bioRxiv · 10.1101/697888

Cross-kingdom recognition of bacterial small RNAs induces transgenerational pathogenic avoidance

Abstract

We recently discovered that C. elegans can pass on a learned avoidance of pathogenic Pseudomonas aeruginosa (PA14) to four generations of its progeny. This transgenerational inheritance is bacterial species-specific, but how C. elegans recognizes and distinguishes different bacteria and transmits this information to future generations is not apparent. Here we show that small RNAs purified from pathogenic PA14 are sufficient not only to induce avoidance of pathogens in mothers, but also to confer transgenerational inheritance of this species-specific behavior for four generations, all without direct contact with pathogenic bacteria. This behavior requires the small RNA transporters SID-1 and SID-2, RNA interference pathway components, the piRNA Piwi/Argonaute pathway, a functioning germline, and TGF-{beta} ligand daf-7 expression in the ASI sensory neuron. Our results suggest that C. elegans \"reads\" small RNAs expressed by pathogenic bacteria, and uses this information to induce an escape behavior that lasts for four additional generations. C. elegans may have evolved this trans-kingdom signaling system to avoid pathogens in abundant classes of bacteria in its environment and its microbiome.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kaletsky, R., Moore, R. S., Parsons, L. R., Murphy, C. T.. 2019-07-11. Cross-kingdom recognition of bacterial small RNAs induces transgenerational pathogenic avoidance. https://doi.org/10.1101/697888

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Host control and regulation of human anellovirus persistence

Anelloviruses are the most abundant and diverse eukaryotic viruses known to infect humans and can persist throughout our lifetimes. Despite their ubiquity, the host factors governing their physiologic distribution and abundance remain poorly understood. Here, we construct a viral pangenome of 2,023 strains to quantify anellovirus DNA in >1.1 million participants spanning three genetic biobanks. Genome-wide association studies identify 121 loci linked to viral persistence, predominantly via immune regulation by NF-kB signaling. Further, we associate variable anellovirus detection with conditions characterized by immune dysfunction, including lymphoid malignancies. By screening 3.2 petabases of human single-cell sequencing data, we identify myeloid progenitors in the bone marrow as a prominent site of anellovirus transcription in vivo. Finally, Perturb-seq of anellovirus proteins reveals that anellovirus ORF2, particularly from Alphatorquevirus, attenuates TNF-a-induced NF-kB signaling, connecting host genetic variation, cellular context, and viral immunomodulation to characterize the persistence of the eukaryotic human virome's most abundant component.

genetics↗

SARDINE unlocks EWAS summary statistics for large-scale epigenetic biomarker analysis

Epigenetic clocks are increasingly used to study biological aging, yet their interpretation and utility remain uncertain. Meanwhile, the growing wealth of epigenome-wide association study (EWAS) summary statistics remains largely untapped for evaluating these biomarkers. Here, we introduce SARDINE, a statistical framework that estimates epigenetic clock-phenotype associations using EWAS summary statistics, clock weights, and reference methylation covariance, without individual-level data. SARDINE accurately reproduced individual-level association estimates across 38 epigenetic biomarkers and four phenotypes in 15,677 individuals. Applying SARDINE to diverse EWAS datasets revealed substantial heterogeneity in biomarker associations with aging, diseases, and lifestyle factors. By transforming CpG-level EWAS results into interpretable biomarker-level associations, SARDINE unlocks a largely underutilized data resource and establishes a scalable paradigm for systematic biomarker evaluation and discovery in aging research.

genetics↗

Deep transcriptomic analysis of molecular mediators of complex traits in heterogeneous stock (HS) rats

Rats are a powerful model organism for genome-wide association studies (GWAS) of physiological and behavioral traits. Heterogeneous Stock (HS) rats, which were created by intercrossing 8 inbred rat strains, are heavily used for this purpose because of their genetic diversity and accumulated recombinations due to over 100 generations of outbreeding, which improves mapping precision. However, functional genomics resources for post-GWAS interpretation of genomic findings have been limited. We processed 3,160 RNA-seq samples, 1,932 of which were previously unpublished, from 13 tissues as part of RatGTEx. We used Pantry to quantify six modalities of transcriptome regulation (expression, isoform ratio, intron excision ratio, alternative transcription start site (TSS), alternative poly(A), and RNA stability) in each sample, which allowed us to identify 144,876 independent quantitative trait loci (QTL) for 22,599 genes. We performed a transcriptome-wide association study (TWAS) with 19,796 unique genes across tissues and transcriptional modalities and 308 traits collected from 14 studies using FUSION, which identified 7,473 significant gene-trait associations. This work presents a significant expansion of the RatGTEx resource in terms of samples, modes of transcriptome regulation, and genetic analyses. Our findings provide molecular evidence for the involvement of specific genes in mediating GWAS signals through a range of transcriptome regulatory mechanisms. These gene-to-phenotype relationships can be easily applied to genetic analyses in humans and other species. Further experiments can use this evidence to confirm these molecular mediators and target them for the treatment of behavioral and physiological traits and disorders. To facilitate use of these results, we have updated results on RatGTEx.org and provided a new interactive TWAS web portal (twas.ratgtex.org).

genetics↗