Human rotavirus (HRV) is a major cause of viral gastroenteritis in infants; particularly in developing countries where malnutrition is prevalent. Malnutrition perturbs the infant gut microbiota leading to sub-optimal functioning of the immune system and further predisposing infants to enteric infections. Therefore, we hypothesized that malnutrition exacerbates rotavirus disease severity in infants. In the present study, we used a neonatal germ free (GF) piglets transplanted with a two-month-old human infant’s fecal microbiota (HIFM) on protein deficient and sufficient diets. We report the effects of malnourishment on the HRV infection and the HIFM pig microbiota in feces, intestinal and systemic tissues, using MiSeq 16S gene sequencing (V4-V5 region). Microbiota analysis indicated that the HIFM transplantation resulted in a microbial composition in pigs similar to that of the original infant feces. This model was then used to understand the interconnections between microbiota diversity, diet, and HRV infection. Post HRV infection, HIFM pigs on the deficient diet had lower body weights, developed more severe diarrhea and increased virus shedding compared to HIFM pigs on sufficient diet. However, HRV induced diarrhea and shedding was more pronounced in non-colonized GF pigs compared to HIFM pigs on either sufficient or deficient diet, suggesting that the microbiota alone moderated HRV infection. HRV infected pigs on sufficient diet showed increased microbiota diversity in intestinal tissues; whereas, greater diversity was observed in systemic tissues of HRV infected pigs fed with deficient diet. These results suggest that proper nourishment improves the microbiota quality in the intestines, alleviates HRV disease and lower probability of systemic translocation of potential opportunistic pathogens/pathobionts. In conclusion, our findings further support the role for microbiota and proper nutrition in limiting enteric diseases.

Genetic underpinnings of host–pathogen interactions in the parasitic plant Striga hermonthica, a root parasitic plant that ravages cereals in sub-Saharan Africa, are unclear. We performed a comparative transcriptome study on five genotypes of sorghum exhibiting diverse resistance responses to S. hermonthica using weighted gene co-expression network analysis (WGCNA). We found that S. hermonthica elicits both basal and effector-triggered immunity—like a bona fide pathogen. The resistance response was genotype specific. Some resistance responses followed the salicylic acid-dependent signaling pathway for systemic acquired resistance characterized by cell wall reinforcements, lignification, and callose deposition, while in others the WRKY-dependent signaling pathway was activated, leading to a hypersensitive response. In some genotypes, both modes of resistance were activated, while in others either mode dominated the resistance response. Cell wall-based resistance was common to all sorghum genotypes but strongest in IS2814, while a hypersensitive response was specific to N13, IS9830, and IS41724. WGCNA further allowed for pinpointing of S. hermonthica resistance causative genes in sorghum, including glucan synthase-like 10 gene, a pathogenesis-related thaumatin-like family gene, and a phosphoinositide phosphatase gene. Such candidate genes will form a good basis for subsequent functional validation and possibly future resistance breeding.

Stress-induced microspore embryogenesis is a widely employed method to achieve homozygosity in plant breeding programs. However, the molecular mechanisms that govern gametophyte de- and redifferentiation are understood poorly. In this study, RNA-Seq was used to evaluate global changes across the microspore transcriptome of soybean (Glycine max [L.] Merrill) as a consequence of pretreatment low-temperature stress. Expression analysis revealed more than 20,000 differentially expressed genes between treated and control microspore populations. Functional enrichment illustrated that many of these genes (e.g., those encoding heat shock proteins and cytochrome P450s) were upregulated to maintain cellular homeostasis through the mitigation of oxidative damage. Moreover, transcripts corresponding to saccharide metabolism, vacuolar transport, and other pollen-related developmental processes were drastically downregulated among treated microspores. Temperature stress also triggered cell wall modification and cell proliferation—characteristics that implied putative commitment to an embryonic pathway. These findings collectively demonstrate that pretreatment cold stress induces soybean microspore reprogramming through suppression of the gametophytic program while concomitantly driving sporophytic development.

Phytophthora sojaeis a soil-borne oomycete and the causal agent of Phytophthora root and stem rot (PRR) in soybean (Glycine max[L.] Merrill). Yield losses attributed toP.sojaeare devastating in disease-conducive environments, with global estimates surpassing 1.1 million tonnes annually. Historically, management of PRR has entailed host genetic resistance (both vertical and horizontal) complemented by disease-suppressive cultural practices (e.g., oomicide application). However, the vast expansion of complex and/or diverseP.sojaepathotypes necessitates developing novel technologies to attenuate PRR in field environments. Therefore, the objective of the present study was to couple high-throughput sequencing data and deep learning to elucidate molecular features in soybean following infection byP.sojae. In doing so, we generated transcriptomes to identify differentially expressed genes (DEGs) during compatible and incompatible interactions withP.sojaeand a mock inoculation. The expression data were then used to select two defense-related transcription factors (TFs) belonging to WRKY and RAV families. DNA Affinity Purification and sequencing (DAP-seq) data were obtained for each TF, providing putative DNA binding sites in the soybean genome. These bound sites were used to train Deep Neural Networks with convolutional and recurrent layers to predict new target sites of WRKY and RAV family members in the DEG set. Moreover, we leveraged publicly available Arabidopsis (Arabidopsis thaliana) DAP-seq data for five TF families enriched in our transcriptome analysis to train similar models. These Arabidopsis data-based models were used for cross-species TF binding site prediction on soybean. Finally, we created a gene regulatory network depicting TF-target gene interactions that orchestrate an immune response againstP.sojae. Information herein provides novel insight into molecular plant-pathogen interaction and may prove useful in developing soybean cultivars with more durable resistance toP.sojae.

Background: The rhizosphere microbiome displays structural and functional dynamism driven by plant, microbial, and environmental factors. While such plasticity is a well-evidenced determinant of host health, individual and community-level microbial activity within the rhizosphere remain poorly understood, due in part to the insufficient taxonomic resolution achieved through traditional marker gene amplicon sequencing. This limitation necessitates more advanced approaches (e.g., long-read sequencing) to derive ecological inferences with practical application. To this end, the present study coupled synthetic long-read technology with avidity sequencing to investigate eukaryotic and prokaryotic microbiome dynamics within the soybean (Glycine max) rhizosphere under field conditions. Results: Synthetic long-read sequencing permitted de novo reconstruction of the entire 18S-ITS1-ITS2 region of the eukaryotic rRNA operon as well as all nine hypervariable regions of the 16S rRNA gene. All full-length, mapped eukaryotic amplicon sequence variants displayed genus-level classification, and 44.77% achieved species-level classification. The resultant eukaryotic microbiome encompassed five kingdoms (19 genera) of protists in addition to fungi – a depth unattainable with conventional short-read methods. In the prokaryotic fraction, every full-length, mapped amplicon sequence variant was resolved at the species level, and 23.13% at the strain level. Thirteen species of Bradyrhizobium were thereby distinguished in the prokaryotic microbiome, with strain-level identification of the two Bradyrhizobium species most reported to nodulate soybean. Moreover, the applied methodology delineated structural and compositional dynamism in response to experimental parameters (i.e., growth stage, cultivar, and biostimulant application), unveiled a saprotroph-rich core microbiome, provided empirical evidence for host selection of mutualistic taxa, and identified key microbial co-occurrence network members likely associated with edaphic and agronomic properties. Conclusions: This study is the first to combine synthetic long-read technology and avidity sequencing to profile both eukaryotic and prokaryotic fractions of a plant-associated microbiome. Findings herein provide an unparalleled taxonomic resolution of the soybean rhizosphere microbiota and represent significant biological and technological advancements in crop microbiome research.

Societal Impact Statement: Witchweeds, parasitic plants of the genus Striga, are nicknamed “cereal killers” because of their devastating destruction of Africa's most staple cereals, including maize, sorghum, millets, and upland rice. The parasite relies on biomolecules emitted from the host roots to germinate and therefore initiate its infectious lifecycle. Some sorghum varieties have evolved to not produce effective germination stimulants, making them resistant to the parasite. Here, the genetic factors that underpin Striga germination were assessed, followed by a discussion of how such knowledge can be used to develop new Striga management strategies through the disruption of host–parasite communication exchange.Summary: Seeds of the parasitic plant Striga are dormant. They only germinate in response to biomolecules emitted from the host's root exudate, strigolactones (SL). But it is now emerging that Striga germination is a much more complex process regulated by crosstalk of hormone signaling pathways. To further understand the genetic basis of the communication exchange between Striga and its host sorghum, we performed a comparative transcriptomic analysis. We sought to identify major transcriptomic changes that define the germination process in Striga and a set of genes that may contribute to the differences in germination rates. Results showed that germination proceeds immediately after SL perception and is marked by a wave of transcriptional reprogramming to allow for metabolic processes of energy mobilization. Cluster analysis using self‐organizing maps revealed a time‐phased and genotype‐differentiated response to germination stimulation. The variation in germination was also a function of hormonal crosstalk. The early germination stage was associated with significant repression of genes in the abscisic acid (ABA) biosynthesis pathway. Other hormones influenced germination as follows: (i) ABA and auxin repressed germination; (ii) brassinosteroid, ethylene, and jasmonic acid promoted germination; and (iii) cytokinin had a more prominent role post‐germination rather than during germination. Perception of SL sets the germination program leading to different rates of germination in sorghum, followed by a complex hormonal regulation network that acts to either repress or enhance germination. We discuss the implications of these findings and present new plausible Striga management strategies.