The soybean cyst nematode (SCN) is the most serious pathogen problem of US soybean production. This nematode is an obligate parasite that becomes sedentary inside the soybean root and induces hundreds of soybean cells to completely change their morphology and function to form a novel plant organ, the syncytium, which nourishes the parasite.
Morphological and physiological changes in the soybean root and the developing syncytium are conditioned by specific gene expression profiles in each of the affected cells. So far, researchers have been able to assess gene expression levels as averages over many cells that are harvested together. However, if one wants to assess the true mechanisms governing syncytium formation and successful nematode infection, one needs to assess gene expression profiles in a cell-specific manner. In other words, in order to fully understand SCN infection and to develop novel control strategies, the scientific community needs to resolve gene expression changes to the single-cell level in infected soybean roots. Similarly, we need to assess gene expression profiles in a single-cell specific manner also in the infecting nematode, particularly in the gland cells producing disease-inducing effector proteins. The exciting news is that all these questions now are answerable in our laboratory using technology and know-how we have established or easily can establish if funded.

Our enabling preliminary discoveries are that we have established a soybean hairy root composite plant system and an extensive vector repertoire, with which we will be able to swiftly express gene constructs in transgenic soybean roots. Second, we have been using cell sorting technology to sort plant and nematode nuclei by size and appearance and will be able to perform transcriptomic analyses of sorted nuclei. While the exact experimental approach is subject to change and adjustments as new techniques become available, the following two objectives will be pursued.
Objective 1) We will drive a nuclearly-localized green fluorescent protein (gfp) variant using a soybean promoter that becomes active in the syncytium. Consequently, syncytial nuclei will harbor gfp and will fluoresce when excited. When subjected to cell sorting, we will be able to purify populations of syncytial soybean cells at different time points during nematode infection. We will then use these nuclei fractions to perform transcriptomic analyses to answer the questions mentioned above.
Objective 2) We have demonstrated that we can purify nematode gland cells through cell sorting based on size and appearance. Again, as a result, we are able to purify populations of SCN gland cell nuclei at different time points during nematode infection and from different strains of SCN as well as from nematodes that have been feeding on different soybean cultivars. We will then use these nuclei fractions to perform transcriptomic analyses to answer the questions mentioned above.

Year 1
Milestones:
• Finalize inoculation and preparation procedure
• Perform first experiment
o SCN inoculated soybean roots over time
o Perform single-cell transcriptomics
• Finalize experimental procedure for SCN nuclei harvest
• Perform first experiment
o SCN life stages
o Perform single-cell transcriptomics

Year 2
Milestones:
• Perform gene expression analyses; cluster analyses; network analyses
• Design and perform next soybean transcriptomic experiment using different R genetics and nematode populations
• Perform gene expression analyses; cluster analyses; network analyses
• Design and perform next SCN transcriptomic experiment using different HG types and soybean resistance genes

Year 3
Milestones:
• Perform gene expression analyses; cluster analyses; network analyses

Updated April 29, 2025:
Progress Report April 2025
• Project Title: Cyst Nematode Single-Cell Omics
• Lead PI: Thomas Baum
The Baum lab has made substantial headway into the milestones laid out for Year 1 of our project on “Cyst nematode single-cell omics.” For Objective 1, we have successfully established an inoculation method to localize SCN-infected root regions, utilizing the aid of a 3D-printed inoculated chamber developed in the Baum lab. Using this new method, we can routinely inoculate young soybean root radicles with large numbers of penetrative juveniles and concentrate the resulting infective nematodes into a region of heavily infected soybean root tissue that can be rapidly harvested at set timepoints. By utilizing our method for focusing the infected tissue, we have subverted, for the moment, the need to incorporate a fluorescent tag into the system to identify and retrieve syncytium-specific nuclei. Instead, we are opting to collect all the nuclei from the highly infested root region and utilizing the power of next generation sequencing to rapidly sequence all the nuclei. We then identify the syncytium-specific nuclei by utilizing gene tags unique to our syncytial tissue.
Working in collaboration with Mark Libault at the University of Missouri, Khalid Meksem at Southern Illinois University and Tarek Hewezi at the University of Tennessee, we have designed an experiment where we inoculated and harvested soybean roots at two time points and utilizing both a susceptible and resistant soybean variety against an avirulent SCN population. We have collected nuclei from the infected regions for all these conditions, as well as from mock inoculated control roots for those same conditions, all with replicates, and sequenced them in a pilot experiment. The data from this experiment are currently being analyzed, the results of which will educate our next steps for Objective 1.
For Objective 2, we have made great strides toward our ability to sequence SCN gland cell nuclei on a large scale. Our lab has previously established the ability to routinely extract whole gland cells and sequence small populations of these to generate small scale transcriptomic analysis of these cells. Recently, we have had a breakthrough in scale. By using a combination of established nematologic methodology, as well as existing nuclei extraction buffers and techniques, we have shown the ability to extract, isolate and detect gland cell nuclei from these very same gland cells. More importantly, this can be done at scale, meaning we can perform this technique on large numbers of nematodes, starting with pre-parasitic juveniles, which are easily obtained, and from which, we can generate pools of thousands of gland cell nuclei.
An existing hurdle in this approach is that these gland cell nuclei are present in a mixture with other nuclei from the nematode body. However, we can use the unique fact that our gland cell nuclei are much larger (on the order of 5 to 10 times) than non-gland cell nuclei to our advantage and apply the established technique of cell/nuclei sorting to our pool of nuclei. Utilizing our Flow Cytometry Facility on campus, we have successfully sorted nematode nuclei and identified unique regions in our sort that represent enriched regions of gland cell nuclei, which can be isolated and collected based on their unique properties. We have been able to collect pools of nuclei consisting of nearly 90% gland cell nuclei. Next steps for us for Objective 2 will be to generate next-generation sequencing libraries for these gland cell nuclei and sequence those libraries to verify identity using gene tags that are unique to gland cells. Furthermore, utilizing gene tags that differentiate between the two types of gland cells, dorsal and subventral, each with unique developmental functions, we can sort our transcripts by gland cell type. This will further enhance the functionality of our resulting single nuclei transcriptomic analysis of the gland cells. Finally, by employing this technique on the differential SCN life stages, we will finally be able to generate a complete picture of the gland transcriptome over the SCN life cycle, allowing us to identify several unique potential targets to attack in engineering resistance against SCN.

View uploaded report

Updated March 24, 2026:
Progress Report April 2026
• Project Title: Cyst Nematode Single-Cell Omics
• Lead PI: Thomas Baum
This project set out to decipher single cell gene expression specifics in the soybean feeding cells (the syncytium) of the soybean cyst nematode (SCN; Objective 1) and in the SCN gland cells that produce the disease-inducing nematode secretions(so-called effectors) (Objective 2). The Baum lab continued to make great progress towards both objectives in Year 2 of our project.

Objective 1) Perform transcriptomic analyses in soybean cells after SCN infection
As reported earlier, for this objective, we joined forces with scientists Mark Libault at the University of Missouri, Khalid Meksem at Southern Illinois University and Tarek Hewezi at the University of Tennessee and collaboratively made solid progress analyzing gene expression specifics in single cells from different SCN-infected soybean cultivars. The continued generation of sequence data and their analyses continues to proceed on track and is allowing first intriguing insights. We have analyzed the data collected in Year 1 and have established preliminary identification of cell type clusters of infected soybean root tissues from these data. We are just now beginning to explore these clusters to identify cell types that may consist of the SCN feeding cells, i.e., the early developing syncytial cells we are targeting to discover. An additional successful and surprising outcome from this exploration of the single cell sequence data generated from Objective 1 is that we are able to detect large quantities of nematode cells from this same experiment. Therefore, we can assemble nematode cell types into their own clusters. This was unexpected, given the scope of this experiment, but could be impactful enough to change our approach to Objective 2. In short, we were able to identify sufficient gland cells in these assays and are studying the gland cell gene expression now.

Objective 2) Perform transcriptomic and genomic analyses in the SCN gland cells that produce so-called effectors.
In pilot experiments, utilizing SCN infective juveniles, we have generated next-generation sequencing libraries for the two gland cell nuclei types, the dorsal and the subventral gland cells. We successfully sequenced those libraries to verify identity using gene tags that are unique to those two gland cell types. We have demonstrated that we can, in fact, sort our transcripts by gland cell type and identify deep sequence pools for each gland cell type (Figure 1). Next steps will be to refine these cell/nuclei type assemblies and explore how complete these assemblies are with respect to all known SCN effectors for a given life stage. With this success in hand, we are now preparing to apply this novel technique to additional life stages of SCN, involving a more extensive experimental setup. While labor intensive, this will clearly define the expression of the nematode’s effector repertoire and the related regulatory genes across the SCN life cycle.
All in all, the proposed work is proceeding very nicely and is on track to be successful. We continue to be excited about our discoveries and are looking forward to sharing additional insights.


Figure 1. Cluster analysis of sorted SCN gland nuclei
Four clusters of nuclei type were formed (Panel A) via UMAP analysis when assembling the SCN single nuclei sequencing data, of which cluster 3 associated with known subventral gland gene markers (Panel B) and cluster 0 associated with known dorsal gland gene markers (Panel C). In Panels B and C, red is denoted as higher expression.

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The research ideas raised here are of primary scientific and academic interest but are uncannily directly relevant to future projects to target SCN by new molecular approaches as it will uncover key aspects of infection biology. The research idea proposed here will lead to powerful preliminary data, which will enable the submission of competitive research proposals to federal funding outlets. Successful completion of the proposed work will set in motion the development of a completely novel omics research field in the analyses of nematode pathosystems. Moderate ISRC seed funding will be eminently important to jump-start this research avenue.