Plant mRNAs move into a fungal pathogen via extracellular vesicles to reduce infection.

Cross-kingdom small RNA trafficking between hosts and microbes modulates gene expression in the interacting partners during infection. However, whether other RNAs are also transferred is unclear. Here, we discover that host plant Arabidopsis thaliana delivers mRNAs via extracellular vesicles (EVs) into the fungal pathogen Botrytis cinerea. A fluorescent RNA aptamer reporter Broccoli system reveals host mRNAs in EVs and recipient fungal cells. Using translating ribosome affinity purification profiling and polysome analysis, we observe that delivered host mRNAs are translated in fungal cells. Ectopic expression of two transferred host mRNAs in B. cinerea shows that their proteins are detrimental to infection. Arabidopsis knockout mutants of the genes corresponding to these transferred mRNAs are more susceptible. Thus, plants have a strategy to reduce infection by transporting mRNAs into fungal cells. mRNAs transferred from plants to pathogenic fungi are translated to compromise infection, providing knowledge that helps combat crop diseases.

Determinants of genetic diversity in Neotropical salamanders (Plethodontidae: Bolitoglossini).

Genetic diversity is the raw material of evolution, yet the reasons why it varies among species remain poorly understood. While studies at deeper phylogenetic scales point to the influence of life history traits on genetic diversity, it appears to be more affected by population size but less predictable at shallower scales. We used proxies for population size, mutation rate, direct selection, and linked selection to test factors affecting genetic diversity within a diverse assemblage of Neotropical salamanders, which vary widely for these traits. We estimated genetic diversity of noncoding loci using ddRADseq and coding loci using RNAseq for an assemblage of Neotropical salamanders distributed from northern Mexico to Costa Rica. Using ddRADseq loci, we found no significant association with genetic diversity, while for RNAseq data we found that environmental heterogeneity and proxies of population size predict a substantial portion of the variance in genetic diversity across species. Our results indicate that diversity of coding loci may be more predictable than that of noncoding loci, which appears to be mostly unpredictable at shallower phylogenetic scales. Our results suggest that coding loci may be more appropriate for genetic diversity estimates used in conservation planning because of the lack of any association between the variables we used and genetic diversity of noncoding loci.

Machine learning-guided discovery and design of non-hemolytic peptides.

Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are cost-effective and time-saving strategies used to predict biological activities from primary sequences. Their limitations lie in the diversity of peptide sequences and biological information within these models. Additional outlier detection methods are needed to set the boundaries for reliable predictions; the applicability domain. Antimicrobial peptides (AMPs) constitute an extensive library of peptides offering promising avenues against antibiotic-resistant infections. Most AMPs present in clinical trials are administrated topically due to their hemolytic toxicity. Here we developed machine learning models and outlier detection methods that ensure robust predictions for the discovery of AMPs and the design of novel peptides with reduced hemolytic activity. Our best models, gradient boosting classifiers, predicted the hemolytic nature from any peptide sequence with 95-97% accuracy. Nearly 70% of AMPs were predicted as hemolytic peptides. Applying multivariate outlier detection models, we found that 273 AMPs (~ 9%) could not be predicted reliably. Our combined approach led to the discovery of 34 high-confidence non-hemolytic natural AMPs, the de novo design of 507 non-hemolytic peptides, and the guidelines for non-hemolytic peptide design.

Disentangling sRNA-Seq data to study RNA communication between species.

Many organisms exchange small RNAs (sRNAs) during their interactions, that can target or bolster defense strategies in host-pathogen systems. Current sRNA-Seq technology can determine the sRNAs present in any symbiotic system, but there are very few bioinformatic tools available to interpret the results. We show that one of the biggest challenges comes from sequences that map equally well to the genomes of both interacting organisms. This arises due to the small size of the sRNAs compared to large genomes, and because a large portion of sequenced sRNAs come from genomic regions that encode highly conserved miRNAs, rRNAs or tRNAs. Here, we present strategies to disentangle sRNA-Seq data from samples of communicating organisms, developed using diverse plant and animal species that are known to receive or exchange RNA with their symbionts. We show that sequence assembly, both de novo and genome-guided, can be used for these sRNA-Seq data, greatly reducing the ambiguity of mapping reads. Even confidently mapped sequences can be misleading, so we further demonstrate the use of differential expression strategies to determine true parasite-derived sRNAs within host cells. We validate our methods on new experiments designed to probe the nature of the extracellular vesicle sRNAs from the parasitic nematode Heligmosomoides bakeri that get into mouse intestinal epithelial cells.

Plant Proteins Are Smaller Because They Are Encoded by Fewer Exons than Animal Proteins.

Protein size is an important biochemical feature since longer proteins can harbor more domains and therefore can display more biological functionalities than shorter proteins. We found remarkable differences in protein length, exon structure, and domain count among different phylogenetic lineages. While eukaryotic proteins have an average size of 472 amino acid residues (aa), average protein sizes in plant genomes are smaller than those of animals and fungi. Proteins unique to plants are ∼81aa shorter than plant proteins conserved among other eukaryotic lineages. The smaller average size of plant proteins could neither be explained by endosymbiosis nor subcellular compartmentation nor exon size, but rather due to exon number. Metazoan proteins are encoded on average by ∼10 exons of small size [∼176 nucleotides (nt)]. Streptophyta have on average only ∼5.7 exons of medium size (∼230nt). Multicellular species code for large proteins by increasing the exon number, while most unicellular organisms employ rather larger exons (>400nt). Among subcellular compartments, membrane proteins are the largest (∼520aa), whereas the smallest proteins correspond to the gene ontology group of ribosome (∼240aa). Plant genes are encoded by half the number of exons and also contain fewer domains than animal proteins on average. Interestingly, endosymbiotic proteins that migrated to the plant nucleus became larger than their cyanobacterial orthologs. We thus conclude that plants have proteins larger than bacteria but smaller than animals or fungi. Compared to the average of eukaryotic species, plants have ∼34% more but ∼20% smaller proteins. This suggests that photosynthetic organisms are unique and deserve therefore special attention with regard to the evolutionary forces acting on their genomes and proteomes.