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This summer I worked on projects that involved RNA sequencing of pathogens after an infection of host cells. The goal of these projects was to continue developing pathogen enrichment strategies for transcriptomic analysis, and also to perform hostpathogen interaction studies.
To best safeguard human and animal health requires early detection and characterization of disease events. This must include effective surveillance for emerging infectious diseases. Both deliberate and natural outbreaks have enormous economic and public health impacts, and can present serious threats to national security. In this project, we developed novel next generation detection technologies to protect the agricultural economy and biosecurity. The first technology is a multiplexed assay to simultaneously detection 10 swine viral and bacterial pathogens. The second one is the Lawrence Livermore Microbial Detection Array (LLMDA) which can detect more than 10,000 microbial species including 4219 viruses, 5367 bacteria, 265 fungi, 117 protozoa and 293 archaea. We analyzed a series of swine clinical samples from past disease events to demonstrate the utility of the assays for faster and cheaper detection of emerging and foreign animal disease pathogens, and their utility as s routine diagnosis and surveillance tool. A second goal of the study is to better understand mechanisms of African swine fever virus (ASFV) infection in pigs to aid the development of countermeasures and diagnostics. There is no vaccine available for ASF. ASF outbreak is on the rise on several European countries. Though ASF is not currently in the U.S., a potential outbreak in the U.S. would be detrimental to the swine industry and the US agricultural economy. We pursued a genome-wide approach to characterize the pig immune responses after ASFV infection. We used RNA sequencing and bioinformatics methods to identify genes and pathways that are affected during ASF infection. We have identified a list of most differentially expressed genes that are in the immune response pathways.
Rift Valley Fever Virus (RVFV) is a category A biodefense pathogen due to its potential for intentional spread by aerosols and the lack of a licensed vaccine or antiviral therapeutic. Although the brain is a major target of viral replication and tissue damage following aerosol infection, little is known about innate immune responses to RVFV in the brain. We are investigating the responses of resident innate immune cells of the brain (microglia and astrocytes) during RVFV infection, in order to identify how these cells are capable of controlling RVFV replication. Microglia mount a robust response to RVFV that is dependent upon mitochondrial antiviral-signaling protein (MAVS) and independent of toll-like receptors 3 and 7. Mice genetically modified to have nonfunctional MAVS (MAVS "knock out" or KO mice) have significantly higher viral loads in the brain following intranasal infection, but surprisingly, many markers of immune activity were similarly upregulated in the brains of MAVS KO and wild type (WT, or “normal”) mice. This is in contrast to the in vitro response, where microglia and astrocytes derived from MAVS KO mice were unresponsive to RVFV infection. RNA-sequencing analysis of infected brain tissue revealed that key antiviral genes are not activated in the MAVS KO animals. These results are an important step towards understanding the molecular pathways responsible for controlling RVFV infection in the brain and lay the groundwork for the development of targeted therapies for the prevention of RVFV encephalitis.
Funding from this project supported new research in environmental biotechnology at WVSU Energy and Environmental Science Institute (WVSUEESI) to develop biological treatment techniques for FGD wastewater using photosynthetic organisms algae and plants. We tested the possibility of using algae and plants in treating FGD wastewater. Results suggested that algae and plants could able to perform normal photosynthesis under low concentrations of selenium. However, higher concentrations of selenium are lethal on photosynthesis. The total protein data indicated that FGD wastewater induced the accumulation of complete proteins in the duckweeds compared to control plants. It appears that nitrate, nitrates, and other compounds in FGD wastewater promote total protein accumulation. The FGD wastewater treatment has triggered Triacylglycerols (TAG) and carbohydrate accumulation in duckweed. We studied the differential gene expression using RNA-Sequencing data. Gene expression analysis revealed that glycolysis, fatty acid, triacylglycerol biosynthesis, and starch degradation were up-regulated; on the contrary, gluconeogenesis, photosynthesis, and starch biosynthesis genes were down-regulated by FGD wastewater treatment. We confirmed the expression of some of these genes using q-RT PCR analysis. We demonstrated that when FGD gypsum was blended with the coal mine soil to grow the bioenergy crop, Camelina, it could grow and produce seed. Moreover, Camelina is a non-edible oilseed crop and has heavy metal sequestering properties, making it the right reclamation choice. Besides, this project provided the opportunity for WVSU undergraduates to integrate hands-on research and education. Funding from this grant helped us to enhance student hands-on experience in water quality and environmental science and participation in STEM research and education.
The goal of this work was to pioneer a novel, low-overhead protocol for simultaneously assaying cell-surface markers and intracellular gene expression in a single mammalian cell. The purpose of developing such a method is to be able to understand the mechanisms by which pathogens engage with individual mammalian cells, depending on their cell surface proteins, and how both host and pathogen gene expression changes are reflective of these mechanisms. The knowledge gained from such analyses of single cells will ultimately lead to more robust pathogen detection and countermeasures. Our method was aimed at streamlining both the upstream cell sample preparation using microfluidic methods, as well as the actual library making protocol. Specifically, we wanted to implement a random hexamer-based reverse transcription of all RNA within a single cell (as opposed to oligo dT-based which would only capture polyadenylated transcripts), and then use a CRISPR-based method called scDash to deplete ribosomal DNAs (since ribosomal RNAs make up the majority of the RNA in a mammalian cell). After significant troubleshooting, we demonstrate that we are able to prepare cDNA from RNA using the random hexamer primer, and perform the rDNA depletion. We also show that we can visualize individually stained cells, setting up the pipeline for connecting surface markers to RNA-sequencing profiles. Finally, we test a number of devices for various parts of the pipeline, including bead generation, optical barcoding and cell dispensing, and demonstrate that while some of these have potential, more work is needed to optimize this part of the pipeline.
Single-cell multiomics provides comprehensive insights into gene regulatory networks, cellular diversity, and temporal dynamics. While tools for co-profiling single-cell genomes, transcriptomes, and epigenomes are available, accessing proteomes in parallel is more challenging. We developed nanoSPLITS (nanodroplet SPlitting for Linked-multimodal Investigations of Trace Samples), an integrated platform that enables global profiling of the transcriptome and proteome from same single cells using RNA sequencing and mass spectrometry-based proteomics, respectively. nanoSPLITS can precisely quantify over 5000 genes, 2000 proteins, and 140 phosphopeptides per single cell and identify candidate cell markers from these modalities. By exploring Cdk1-mediated cell cycle arrest, we demonstrate how nanoSPLITS single-cell multiomics can provide comprehensive cellular characterization with insights into covarying protein/gene clusters, unique phosphorylation events, and mitotic pathways.
Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.
Through this grant, we developed a comparative framework to elucidate the mechanisms behind variations in environmental stress responses among a diverse group of species within the Brassicaceae family. Our focus was on the differences in physiological and transcriptomic responses to abscisic acid (ABA), a hormone associated with water stress. We examined the differential growth responses of four Brassicaceae species, finding that most exhibited reduced root growth correlated with smaller meristem size. In contrast, Schrenkiella parvula showed accelerated growth due to increased root cell elongation. We employed RNA sequencing to analyze the transcriptional responses to ABA across these species, and innovative bioinformatics techniques were used to pinpoint biological pathways with significant divergence. Additionally, we utilized DAP-seq to map the gene regulatory networks associated with ABAresponsive transcription factors, revealing that variations in the regulation of growth hormone biosynthesis play a critical role in the distinct ABA effects on root growth among the species. This research sets a new standard for comparative physiology by integrating comparative genomics and transcriptomics to uncover pathway divergences.
The DOE‐BER “EvoNet” project investigates the genetic and molecular basis of plant resilience in extreme environments. We do this by identifying key genes that enable “extreme survivor” species to thrive in the nitrogen-poor soils of Chile’s hyper-arid Atacama Desert. Our collections focus on 32 Atacama extremophile species, including seven grass species with potential biofuel applications. To identify genes-of-importance to survival we compared genomic and transcriptomic profiles of extremophile species that thrive in the Atacama to those of closely related “sister” species from nitrogen-rich arid and mesic regions of California. Deep RNA sequencing and de novo transcriptome assembly across these triplet species sets supported a phylogenomic framework for identifying positively selected genes associated with adaptive divergence. Our integrative analysis combined ecological and environmental data, metagenomics, evolutionary and systems biology, and metabolomics. This enabled us to create an unprecedented framework for systematically understanding how non-model plants have adapted to survive in extreme conditions. Our resulting database of positively selected ortholog groups in the extremophile plants offers promising targets for engineering crop and biofuel species with enhanced resilience to drought and extreme weather. Additionally, our newest dataset explores and exploits a complementary metabolomic approach. This new aspect provides innovative strategies to manipulate plant cell metabolism, further supporting efforts to improve agricultural productivity in the face of extreme climates. Importantly, our combined evolutionary- and metabolomic-based strategies focused on convergent patterns of adaptation, providing a genetic and metabolomic toolkit for improving crop and biofuel resilience across diverse plant species. Finally, our novel exploration of ecological and evolutionary dynamics delivered to the community a phylogenomic computational pipeline called “PhyloGeneious.” Our continued adaptations of this pipeline are publicly available to expedite evolutionary genomic research for future scientific discoveries. In total, our DOE-BER has provided genomic, metabolomic, and computational strategies to understand how extremophile plants provide evolutionary and physiological targets for improving agricultural and biofuel production.
Single cell RNA sequencing (scRNA-Seq) technologies have greatly enhanced our understanding of islet cell transcriptomes and have revealed the existence of ß cell heterogeneity. However, comparison of scRNA-Seq datasets from different groups have highlighted inconsistencies in gene expression patterns, primarily due to variable detection of lower abundance transcripts. Furthermore, such analyses are unable to uncover the spatial organization of heterogeneous gene expression. Here we used fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) to quantify transcripts in single cells in mouse pancreatic islet sections. We compared the expression patterns of Insulin 2 (Ins2) with Mafa and Ucn3 – two genes expressed in ß cells as they mature, as well as Rgs4 – a factor with variably reported expression in the islet. This approach accurately quantified transcripts across a wide range of expression levels - from single copies to over hundred copies per cell in one islet. Importantly, fliFISH allowed evaluation of transcript heterogeneity in the spatial context of an intact islet. These studies confirm the existence of a high degree of heterogeneous gene expression levels within the islet and highlight relative and radial expression patterns that likely reflect distinct ß cell maturation states along the radial axis of the islet.
The data package consists of isolated pancreatic islets from 3 human donors treated with IL-1β, IFNγ or IL-1β + IFNγ for 6 h and IL-1β, IFNγ, IL-1β + IFNγ, IL-1β + IFNγ + NMMA or NMMA for 18 h and submitted for scRNA-seq. This study examines cytokine-stimulated changes in gene expression in human islets using single-cell RNA sequencing. Data contributors: Jennifer S Stancill & John A Corbett: Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI, USA Data repository: GSE251730 Publication: 10.1093/function/zqae015
This dataset contains single-nucleus RNA sequencing data from poplar (Populusspp.) roots under control and methyl jasmonate (MeJA) treatment conditions. It was generated to investigate cell type-specific stress responses and to establish a high-resolution transcriptomic atlas in a perennial woody species.
Lymphocytes can heavily influence intestinal health, but resolving intestinal lymphocyte function is challenging as the intestine contains a vastly heterogeneous mixture of cells. Pigs are an advantageous biomedical model, but deeper understanding of intestinal lymphocytes is warranted to improve model utility. Twenty-six cell types were identified in the porcine ileum by single-cell RNA sequencing and further compared with cells in human and murine ileum. Though general consensus of cell subsets across species was revealed, some porcine-specific lymphocyte subsets were identified. Differential tissue dissection and in situ analyses conferred spatial context, revealing similar locations of lymphocyte subsets in Peyer’s patches and epithelium in pig-to-human comparisons. Like humans, activated and effector lymphocytes were abundant in the ileum but not periphery of pigs, suggesting tissue-specific and/or activation-associated gene expression. Gene signatures for peripheral and ileal innate lymphoid cells newly discovered in pigs were defined and highlighted similarities to human innate lymphoid cells. Overall, we reveal novel lymphocyte subsets in pigs and highlight utility of pigs for intestinal research applications.
Corynebacterium glutamicum is an ideal microbial chassis for production of valuable bioproducts including amino acids and next generation biofuels. Here we resequence engineered isopentenol (IP) producing C. glutamicum BRC-JBEI 1.1.2 strain and assess differential transcriptional profiles using RNA sequencing under industrially relevant conditions including scale transition and compare the presence vs absence of an ionic liquid, cholinium lysinate ([Ch][Lys]). Analysis of the scale transition from shake flask to bioreactor with transcriptomics identified a distinct pattern of metabolic and regulatory responses needed for growth in this industrial format. These differential changes in gene expression corroborate altered accumulation of organic acids and bioproducts, including succinate, acetate, and acetoin that occur when cells are grown in the presence of 50 mM [Ch][Lys] in the stirred-tank reactor. This new genome assembly and differential expression analysis of cells grown in a stirred tank bioreactor clarify the cell response of an C. glutamicum strain engineered to produce IP.
During spaceflight, astronauts are exposed to various physiological and psychological stressors that have been associated with adverse health effects. Therefore, there is an unmet need to develop novel diagnostic tools to predict early alterations in astronauts’ health. Small nucleolar RNA (snoRNA) is a type of short non-coding RNA (60–300 nucleotides) known to guide 2'-O-methylation (Nm) or pseudouridine (ψ) of ribosomal RNA (rRNA), small nuclear RNA (snRNA), or messenger RNA (mRNA). Emerging evidence suggests that dysregulated snoRNAs may be key players in regulating fundamental cellular mechanisms and in the pathogenesis of cancer, heart, and neurological disease. Therefore, we sought to determine whether the spaceflight-induced snoRNA changes in astronaut’s peripheral blood (PB) plasma extracellular vesicles (PB-EV) and peripheral blood mononuclear cells (PBMCs). Using unbiased small RNA sequencing (sRNAseq), we evaluated changes in PB-EV snoRNA content isolated from astronauts (n = 5/group) who underwent median 12-day long Shuttle missions between 1998 and 2001. Using stringent cutoff (fold change > 2 or log 2 -fold change >1, FDR < 0.05), we detected 21 down-and 9—up-regulated snoRNAs in PB-EVs 3 days after return (R + 3) compared to 10 days before launch (L-10). qPCR validation revealed that SNORA74A was significantly down-regulated at R + 3 compared to L-10. We next determined snoRNA expression levels in astronauts’ PBMCs at R + 3 and L-10 (n = 6/group). qPCR analysis further confirmed a significant increase in SNORA19 and SNORA47 in astronauts’ PBMCs at R + 3 compared to L-10. Notably, many downregulated snoRNA-guided rRNA modifications, including four Nms and five ψs. Our findings revealed that spaceflight induced changes in PB-EV and PBMCs snoRNA expression, thus suggesting snoRNAs may serve as potential novel biomarkers for monitoring astronauts’ health.
Plant roots co-inhabit the soil with a diverse consortium of microbes of which a number attempt to enter symbiosis with the plant. These microbes may be pathogenic, mutualistic, or commensal. Hence, the health and survival of plants is heavily reliant on their ability to perceive different microbial lifestyles and respond appropriately. Emerging research suggests that there is a pivotal role for plant root secondary metabolites in responding to microbial colonization. However, it is largely unknown if plants are able to differentiate between microbes of different lifestyles and respond differently during the earliest stages of pre-symbiosis (i.e., prior to physical contact). In studying plant responses to a range of microbial isolates, we questioned: (1) if individual microbes of different lifestyles and species caused alterations to the plant root metabolome during pre-symbiosis, and (2) if these early metabolite responses correlate with the outcome of the symbiotic interaction in later phases of colonization. We compared the changes of the root tip metabolite profile of the model tree Eucalyptus grandis during pre-symbiosis with two isolates of a pathogenic fungus (Armillaria luteobubalina), one isolate of a pathogenic oomycete (Phytophthora cinnamomi), two isolates of an incompatible mutualistic fungus (Suillus granulatus), and six isolates of a compatible mutualistic fungus (Pisolithus microcarpus). Untargeted metabolite profiling revealed predominantly positive root metabolite responses at the pre-symbiosis stage, prior to any observable phenotypical changes of the root tips. Metabolite responses in the host tissue that were specific to each microbial species were identified. A deeper analysis of the root metabolomic profiles during pre-symbiotic contact with six strains of P. microcarpus showed a connection between these early metabolite responses in the root with later colonization success. Further investigation using isotopic tracing revealed a portion of metabolites found in root tips originated from the fungus. RNA-sequencing also showed that the plant roots undergo complementary transcriptomic reprogramming in response to the fungal stimuli. Taken together, our results demonstrate that the early metabolite responses of plant roots are partially selective toward the lifestyle of the interacting microbe, and that these responses can be crucial in determining the outcome of the interaction.
During spaceflight, astronauts are exposed to multiple unique environmental factors, particularly microgravity and ionizing radiation, that can cause a range of harmful health consequences. Over the past decades, increasing evidence demonstrates that the space environment can induce changes in gene expression and RNA processing. Long non-coding RNA (lncRNA) represent an emerging area of focus in molecular biology as they modulate chromatin structure and function, the transcription of neighboring genes, and affect RNA splicing, stability, and translation. They have been implicated in cancer development and associated with diverse cardiovascular conditions and associated risk factors. However, their role on astronauts’ health after spaceflight remains poorly understood. In this perspective article, we provide new insights into the potential role of exosomal lncRNA after spaceflight. We analyzed the transcriptional profile of exosomes isolated from peripheral blood plasma of three astronauts who flew on various Shuttle missions between 1998–2001 by RNA-sequencing. Computational analysis of the transcriptome of these exosomes identified 27 differentially expressed lncRNAs with a Log 2 fold change, with molecular, cellular, and clinical implications.
Osteoarthritis (OA) is the most common joint disease, affecting over 300 million people world-wide. Accumulating evidence attests to the important roles of the immune system in OA pathogenesis. Understanding the role of various immune cells in joint degeneration or joint repair after injury is vital for improving therapeutic strategies for treating OA. Post-traumatic osteoarthritis (PTOA) develops in ~50% of individuals who have experienced an articular trauma like an anterior cruciate ligament (ACL) rupture. Here, using the high resolution of single-cell RNA sequencing, we delineated the temporal dynamics of immune cell accumulation in the mouse knee joint after ACL rupture. Our study identified multiple immune cell types in the joint including neutrophils, monocytes, macrophages, B cells, T cells, NK cells and dendritic cells. Monocytes and macrophage populations showed the most dramatic changes after injury. Further characterization of monocytes and macrophages reveled 9 major subtypes with unique transcriptomics signatures, including a tissue resident Lyve1 hi Folr2 hi macrophage population and Trem2 hi Fcrls + recruited macrophages, both showing enrichment for phagocytic genes and growth factors such as Igf1 , Pdgfa and Pdgfc. We also identified several genes induced or repressed after ACL injury in a cell type-specific manner. This study provides new insight into PTOA-associated changes in the immune microenvironment and highlights macrophage subtypes that may play a role in joint repair after injury.