A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize

Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM) is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs) that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize

The Genome Sequence of the Fungal Pathogen Fusarium virguliforme That Causes Sudden Death Syndrome in Soybean

Fusarium virguliforme causes sudden death syndrome (SDS) of soybean, a disease of serious concern throughout most of the soybean producing regions of the world. Despite the global importance, little is known about the pathogenesis mechanisms of F. virguliforme. Thus, we applied Next-Generation DNA Sequencing to reveal the draft F. virguliforme genome sequence and identified putative pathogenicity genes to facilitate discovering the mechanisms used by the pathogen to cause this disease

Use of Dual RNA-seq for Systems Biology Analysis of Zea mays and Aspergillus flavus Interaction

The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore, the authors undertook a systems biology approach involving dual RNA-seq to determine the simultaneous response from the host and the pathogen. What was dramatically highlighted in the analysis is the uniformity in the development patterns of gene expression of the host and the pathogen during infection. This led to the development of a “stage of infection index” that was subsequently used to categorize the samples before down-stream system biology analysis. Additionally, we were able to ascertain that key maize genes in pathways such as the jasmonate, ethylene and ROS pathways, were up-regulated in the study. The stage of infection index used for the transcriptomic analysis revealed that A. flavus produces a relatively limited number of transcripts during the early stages (0 to 12 h) of infection. At later stages, in A. flavus, transcripts and pathways involved in endosomal transport, aflatoxin production, and carbohydrate metabolism were up-regulated. Multiple WRKY genes targeting the activation of the resistance pathways (i.e., jasmonate, phenylpropanoid, and ethylene) were detected using causal inference analysis. This analysis also revealed, for the first time, the activation of Z. mays resistance genes influencing the expression of specific A. flavus genes. Our results show that A. flavus seems to be reacting to a hostile environment resulting from the activation of resistance pathways in Z. mays. This study revealed the dynamic nature of the interaction between the two organisms

Ecology and diversity of culturable fungal species associated with soybean seedling diseases in the Midwestern United States

Aims: To isolate and characterize fungi associated with diseased soybean seedlings in Midwestern soybean production fields and to determine the influence of environmental and edaphic factors on their incidence. Methods and Results: Seedlings were collected from fields with seedling disease history in 2012 and 2013 for fungal isolation. Environmental and edaphic data associated with each field was collected. 3036 fungal isolates were obtained and assigned to 76 species. The most abundant genera recovered were Fusarium (73%) and Trichoderma (11.2%). Other genera included Mortierella, Clonostachys, Rhizoctonia, Alternaria, Mucor, Phoma, Macrophomina and Phomopsis. Most recovered species are known soybean pathogens. However, non-pathogenic organisms were also isolated. Crop history, soil density, water source, precipitation and temperature were the main factors influencing the abundance of fungal species. Conclusion: Key fungal species associated with soybean seedling diseases occurring in several US production regions were characterized. This work also identified major environment and edaphic factors affecting the abundance and occurrence of these species. Significance and Impact of the Study: The identification and characterization of the main pathogens associated with seedling diseases across major soybean-producing areas could help manage those pathogens, and devise more effective and sustainable practices to reduce the damage they cause

Chemical Profiles of Heterodera glycines Suppressive Soils in Double Cropping Soybean Production

We previously reported soybean fields double-cropped with winter wheat having reduced soybean cyst nematode (SCN) (Heterodera glycines) counts compared to fallow. A follow-up metagenomics study identified several fungal and bacterial taxa enriched in wheat fields, and some were reported to parasitize SCN. Knowing that phytocompounds with potential nematicidal activity are released via wheat roots and stubble, we implemented a dichloromethane-based extraction method and a gas chromatography-mass spectrometry (GCMS) system to investigate soil chemical profiles of samples collected from these fields and review the potential nematicidal activity of compounds with higher concentration in double cropping fields. 51 compounds were detected during the GCMS analysis, eight with unknown identification. Several compounds, including multiple fatty acids, had larger relative peak areas when double-cropped, compared to fallow samples. This study, along with our previously published one, provided a better understanding of the mechanisms that govern the effect of wheat on SCN populations. Rather than driven by a single mechanism, the suppression of SCN in soybean fields double-cropped with winter wheat was potentially linked to enriched microbial communities, increased populations of beneficial organisms, and higher concentrations of chemicals with potential nematicidal activity. To our knowledge, this is the first study using GCMS to characterize soil chemical profiles in soybean fields double-cropped with winter wheat regarding the suppression of SCN populations

Cost-effective in-house COVID-19 reverse transcription-polymerase chain reaction testing with yeast-derived Taq polymerase

BACKGROUND: Despite the decline of the COVID-19 pandemic, there continues to be a persistent requirement for reliable testing methods that can be adapted to future outbreaks and areas with limited resources. While the standard approach of using reverse transcription-polymerase chain reaction (RT-PCR) with Taq polymerase is effective, it faces challenges such as limited access to high-quality enzymes and the presence of bacterial DNA contamination in commercial kits, which can impact the accuracy of test results. METHODS: This study investigates the production of recombinant Taq polymerase in yeast cells and assesses its crude lysate in a multiplex RT-PCR assay for detecting the SARS-CoV-2 RNA-dependent RNA polymerase (RdRP) and N genes, with human Ribonuclease P serving as an internal control. RESULTS: The unpurified yeast Taq polymerase demonstrates sensitivity comparable to commercially purified bacterial Taq polymerase and unpurified bacterial counterparts in detecting the RdRP and N genes. It exhibits the highest specificity, with 100% accuracy, for the N gene. The specificity for the RdRP gene closely aligns with that of commercially purified bacterial Taq polymerase and unpurified bacterial Taq polymerase. CONCLUSIONS: The use of unpurified recombinant yeast Taq polymerase shows promise as a cost-effective approach for conducting in-house COVID-19 RT-PCR testing. By eliminating the need for chromatography purification steps, the production of RT-PCR kits can be streamlined, potentially improving accessibility and scalability, especially in resource-limited settings and future pandemics

Gene Expression Profiling of Peripheral Blood Mononuclear Cells in Type 2 Diabetes: An Exploratory Study

Background and Objectives: Visceral obesity is associated with chronic low-grade inflammation that predisposes to metabolic syndrome. Indeed, infiltration of adipose tissue with immune–inflammatory cells, including ‘classical’ inflammatory M1 and anti-inflammatory ‘alternative’ M2 macrophages, causes the release of a variety of bioactive molecules, resulting in the metabolic complications of obesity. This study examined the relative expression of macrophage phenotypic surface markers, cholesterol efflux proteins, scavenger receptors, and adenosine receptors in human circulating peripheral blood mononuclear cells (PBMCs), isolated from patients with type 2 diabetes mellitus (T2DM), with the aim to phenotypically characterize and identify biomarkers for these ill-defined cells. Materials and Methodology: PBMCs were isolated from four groups of adults: Normal-weight non-diabetic, obese non-diabetic, newly diagnosed with T2DM, and T2DM on metformin. The mRNA expression levels of macrophage phenotypic surface markers (interleukin-12 (IL-12), C-X-C motif chemokine ligand 10 (CXCL10), C-C motif chemokine ligand 17 (CCL17), and C-C motif receptor 7 (CCR7)), cholesterol efflux proteins (ATP-binding cassette transporter-1 (ABCA1), ATP binding cassette subfamily G member 1 (ABCG1), and sterol 27-hydroxylase (CYP27A)), scavenger receptors (scavenger receptor-A (SR-A), C-X-C motif ligand 16 (CXCL16), and lectin-like oxidized LDL receptor-1 (LOX-1)), and adenosine receptors (adenosine A2A receptor (A2AR) and adenosine A3 receptor (A3R)) were measured using qRT-PCR. Results: In PBMCs from T2DM patients, the expression of IL-12, CCR7, ABCA1, and SR-A1 was increased, whereas the expression of CXCL10, CCL17, ABCG1,27-hydroxylase, LOX-1, A2AR and A3R was decreased. On the other hand, treatment with the antidiabetic drug, metformin, reduced the expression of IL-12 and increased the expression of 27-hydroxylase, LOX-1, CXCL16 and A2AR. Conclusions: PBMCs in the circulation of patients with T2DM express phenotypic markers that are different from those typically present in adipose tissue M1 and M2 macrophages and could be representative of metabolically activated macrophages (MMe)-like cells. Our findings suggest that metformin alters phenotypic markers of MMe-like cells in circulation

Phylogenetic tree showing the relationship of <i>F. virguliforme</i> with other <i>Fusarium</i> species.

<p>The tree was constructed using 10 randomly selected single copy orthologous genes using PHYML program (WAG model of evolution) with 1,000 bootstraps.</p

General assembly statistics of the draft <i>Fusarium virguliforme</i> genome.

<p>General assembly statistics of the draft <i>Fusarium virguliforme</i> genome.</p

Heat-map depicting the Pfam domains in all <i>Fusarium</i> species.

<p><i>F. virguliforme</i> genome is rich in Pkinase_Tyr (Protein tyrosine kinase), Ank (Ankyrin repeat), and HET (Heterokaryon incompatibility proteins) as compared to the other <i>Fusarium</i> genomes.</p