Publications

Transgenic expression of a double-stranded RNA in plants can induce silencing of homologous mRNAs in fungal pathogens. Although such host-induced gene silencing is well documented, the molecular mechanisms by which RNAs can move from the cytoplasm of plant cells across the plasma membrane of both the host cell and fungal cell are poorly understood. Indirect evidence suggests that this RNA transfer may occur at a very early stage of the infection process, prior to breach of the host cell wall, suggesting that silencing RNAs might be secreted onto leaf surfaces. To assess whether Arabidopsis plants possess a mechanism for secreting RNA onto leaf surfaces, we developed a protocol for isolating leaf surface RNA separately from intercellular (apoplastic) RNA. This protocol yielded abundant leaf surface RNA that displayed an RNA banding pattern distinct from apoplastic RNA, suggesting that it may be secreted directly onto the leaf surface rather than exuded through stomata or hydathodes. Notably, this RNA was not associated with either extracellular vesicles or protein complexes; however, RNA species longer than 100 nucleotides could be pelleted by ultracentrifugation. Furthermore, pelleting was inhibited by the divalent cation chelator EGTA, suggesting that these RNAs may form condensates on the leaf surface. These leaf surface RNAs are derived almost exclusively from Arabidopsis, but come from diverse genomic sources, including rRNA, tRNA, mRNA, intergenic RNA, microRNAs, and small interfering RNAs, with tRNAs especially enriched. We speculate that endogenous leaf surface RNA plays an important role in the assembly of distinct microbial communities on leaf surfaces.

Extracellular vesicles (EVs) produced by Arabidopsis are highly heterogeneous in protein content. Specific EV subpopulations have been proposed to participate in plant immunity, particularly during plant-fungal interaction. To understand the origins of plant EV heterogeneity, we used a proximity labeling approach to identify proteins and pathways involved in the secretion of distinct EV subpopulations. Proximity labeling, co-immunoprecipitation, and fluorescence microscopy in Nicotiana benthamiana all indicated a general role in EV secretion for EXO70 proteins (a subunit of the exocyst complex) and the immune-related protein RPM1-INTERACTING PROTEIN 4 (RIN4), while the ER-localized VAMP-ASSOCIATED PROTEIN 27(VAP27) was specifically associated with the EV marker protein TETRAPSANIN8 (TET8). Despite being secreted in separate EV populations, we found that TET8 and PENETRATION 1 (PEN1) co-localized in multivesicular body-like subcellular structures. Based on these results, we tested Arabidopsis mutants and identified several proteins involved in EV secretion, including members of the exo70 family, rin4, rabA2a, scd1 (a GTP-exchange factor for RabE GTPases), and vap27. We also uncovered a possible connection between trichomes and EVs, as the trichomeless mutant glabrous1 secreted approximately half the number of EVs as wild type. Furthermore, PEN1 MVB-like structures were prevalent in guard cells, suggesting that guard cells may contribute to secretion of PEN1+ EVs on the leaf surface. Lastly, we found that exo70 family mutants are more susceptible to infection with the fungal pathogen Colletotrichum higginsianum, underlining the importance of secretion for plant immunity. Together, our results unravel some of the complex mechanisms that give rise to EV subpopulations in plants.

The phyllosphere, which includes the surfaces of plant leaves and stems, is one of the largest and most diverse microbial habitats on Earth, yet it remains understudied in plant-microbe interaction research. Recent studies have highlighted the significant role of phyllosphere epiphytic bacteria in enhancing plant health. These microorganisms help improve nutrient uptake, defend against pathogens, and increase resilience to environmental stressors.

In recent years, phyllosphere-associated microorganisms have been assembled into synthetic microbial communities (SynComs) to replicate or augment natural microbial populations. This review examines the emerging field of phyllosphere-modulating synthetic communities (PMS) and their potential to enhance plant fitness and protection. We explore the latest advancements in the design of SynComs, with a focus on their agricultural applications. Despite promising results, a consensus is lacking on best practices for standardizing the development and application of PMS, with the complexity of PMS reported in the literature ranging from a few species to as many as 48 core phyla, including Proteobacteria, Firmicutes, and Actinobacteria.

Outer membrane vesicles (OMVs) are membrane-encapsulated spherical structures ~120 nm in diameter derived from Gram-negative bacterial cell envelopes. OMVs are primarily generated by outer membrane blebbing but contain proteins, DNA, and RNAs at concentrations distinct from that of the intracellular complement. OMVs have been associated with a number of different cellular functions including intercellular communication and resistance to phage.

As bacterial small RNAs (sRNAs) also participate in bacteriophage defense and are specifically delivered to and enriched in OMVs, we recently elected to examine the effects of P22 infection on Salmonella cytosolic and OMV sRNA abundance by employing RNA sequencing.

We find that P22 infection triggers a global reduction in sRNAs (with Salmonella sRNA expression levels averaging only 15.6% those observed in noninfected cells) coupled with a reciprocal 72.7% global increase in Salmonella tRNA expression levels. Additionally, of note, while OMV small noncoding RNA (sncRNA) abundance is normally ~1/10 that found in the cytosol, we find that P22 infection triggers active OMV encapsulation and secretion of: (1) a subset of sRNAs, (2) all Salmonella tRNAs including one highly complementary to the P22 genome, and, much to our surprise, (3) ten distinct sRNAs expressed from P22.

In summary, the work presented here identifies several Salmonella sncRNA cytosolic and/or OMV abundances significantly altered during P22 infection, and to our knowledge, this constitutes the first reported characterization of bacteriophage-encoded sRNAs being actively secreted within host OMVs.

Y RNAs are a poorly-studied class of small non-coding RNAs (sncRNAs) which have previously been implicated in the pathogenesis of different human diseases, including cardiac and autoimmune conditions, as well as certain cancers. In recent years, however, multiple studies have reported correlations between Y RNA expressions and disease outcomes in viral infections (e.g., IAV, HIV, HPV, and SARS-CoV-2) as well as potential mechanistic roles that Y RNAs may play in host anti-viral defense. These studies suggest that Y RNAs may be associated with upregulation of viral defense proteins as well as altered cell-cell communication during viral infections. In this review, current literature detailing Y RNA effects on human viral infection will be summarized and future directions in the study of these relationships discussed.

Pseudomonas fulva MTT5, isolated from maize leaf surfaces, exhibits broad-spectrum antimicrobial activity. We present the complete genome sequence of P. fulva MTT5. The 4.9 Mb genome contains 4,488 predicted genes and a GC content of 61.5%. Identified biosynthetic gene clusters highlight the strain’s potential as a source of novel antibiotics.

Fall armyworms (Spodoptera frugiperda) are an invasive agricultural pest whose adaptability and resilience are increasingly linked to their gut microbiota. In this study, we performed a global-scale in-silico meta-analysis of publicly available 16S rRNA datasets to identify a conserved core gut microbiota and assess how geography and diet shape microbial community structure and function. Using both prevalence-based and unsupervised clustering approaches, we defined a robust global core microbiota composed of 88 high-confidence ASVs, including genera such as Enterococcus, Pseudomonas, and Acinetobacter, which were consistently present regardless of geographical region or diet. These taxa are important in nutrient metabolism, detoxification, and stress tolerance, contributing to host fitness and ecological success. Geographic origin significantly influenced gut microbiota diversity and composition, with continent- and country-level differences supported by alpha/beta diversity metrics and supervised machine learning classification (AUC = 1.0). Diet also influenced microbial community structure, although its effect was weaker than that of geography, explaining 11.9% of the variation compared to 13.5%. Functional predictions using PICRUSt2 revealed region-specific enrichment of pathways related to xenobiotic degradation, amino acid metabolism, and vitamin biosynthesis, suggesting specific microbial taxa may contribute to host adaptation and resilience through these metabolic functions. This is the first global synthesis of the S. frugiperda gut microbiota that integrates geographic and dietary factors. The identification of a global-level conserved core microbiota provides a foundation for developing synthetic microbial communities and microbiome-informed pest management strategies aimed at enhancing control efficacy.

Plants are a largely untapped source of antibiotic-producing microorganisms. In this study, 237 bacteria were isolated from the leaf surface of field-grown Zea mays. Screening 49 Gammaproteobacteria isolates for antibiotic activity identified eighteen isolates of interest. These findings underscore the plant phyllosphere as a valuable reservoir for discovering novel antibiotics.

Noncoding RNAs <200 nucleotides (nt) in length are referred to as short noncoding RNAs (sncRNAs) and include microRNAs (miRNAs), piwi-interacting RNAs, small nucleolar RNAs, transfer RNAs, etc. One striking example of the regulatory capabilities of sncRNAs comes from a group of small yet potent RNAs called miRNAs. MiRNAs are ∼20-nt RNAs excised from longer pre-miRNA hairpins, and to date, thousands of miRNAs have been identified across an array of species with specific roles for miRNAs defined in virtually every cellular activity (e.g. growth, differentiation, apoptosis, and disease). Importantly, studies aimed at evaluating the transcriptomic changes of miRNAs have now revealed the existence of miRNA-like fragments derived from other types of sncRNAs and suggest similar regulatory capacities may be associated with these novel sncRNA fragments. Unfortunately, many biologically relevant sncRNA-excised fragments remain uncharacterized due to their routine exclusion during initial miRNA characterizations as “sncRNA degradation products” as well as nearly all sncRNA informatic analyses continuing to solely assess annotated miRNA expressions. To address this, several platforms aimed at identifying novel sncRNA fragments have recently been developed. That said, the principal analytical tools currently employed to characterize novel sncRNA fragments often require significant computational expertise hindering their widespread utilization. As such, the development of a user-friendly platform, requiring minimal programming experience yet capable of identifying and characterizing RNA fragments excised from any sncRNA from any species is highly desirable and potentially impactful. In light of this, we have developed FragmentFinder—an intuitive, Windows-executable resource designed to require absolutely no computational background and capable of accurately characterizing all (annotated and unknown) sncRNA-derived RNAs within a raw small RNA sequencing file in real time.

Today, due to the size of many genomes and the increasingly large sizes of sequencing files, independently analyzing sequencing data is largely impossible for a biologist with little to no programming expertise. As such, biologists are typically faced with the dilemma of either having to spend a significant amount of time and effort to learn how to program themselves or having to identify (and rely on) an available computer scientist to analyze large sequence data sets. That said, the advent of AI-powered programs like ChatGPT may offer a means of circumventing the disconnect between biologists and their analysis of genomic data critically important to their field. The work detailed herein demonstrates how implementing ChatGPT into an existing Course-based Undergraduate Research Experience curriculum can provide a means for equipping biology students with no programming expertise the power to generate their own programs and allow those students to carry out a publishable, comprehensive analysis of real-world Next Generation Sequencing (NGS) datasets. Relying solely on the students' biology background as a prompt for directing ChatGPT to generate Python codes, we found students could readily generate programs able to deal with and analyze NGS datasets greater than 10 gigabytes. In summary, we believe that integrating ChatGPT into education can help bridge a critical gap between biology and computer science and may prove similarly beneficial in other disciplines. Additionally, ChatGPT can provide biological researchers with powerful new tools capable of mediating NGS dataset analysis to help accelerate major new advances in the field.