Comparative analysis, diversification, and functional validation of plant nucleotide-binding site domain genes

Nucleotide-binding site (NBS) domain genes are one of the superfamily of resistance genes involved in plant responses to pathogens. The current study identified 12,820 NBS-domain-containing genes across 34 species covering from mosses to monocots and dicots. These identified genes are classified into 168 classes with several novel domain architecture patterns encompassing significant diversity among plant species. Several classical (NBS, NBS-LRR, TIR-NBS, TIR-NBS-LRR, etc.) and species-specific structural patterns (TIR-NBS-TIR-Cupin_1-Cupin_1, TIR-NBS-Prenyltransf, Sugar_tr-NBS etc.) were discovered. We observed 603 orthogroups (OGs) with some core (most common orthogroups; OG0, OG1, OG2, etc.) and unique (highly specific to species; OG80, OG82, etc.) OGs with tandem duplications. The expression profiling presented the putative upregulation of OG2, OG6, and OG15 in different tissues under various biotic and abiotic stresses in susceptible and tolerant plants to cotton leaf curl disease (CLCuD). The genetic variation between susceptible (Coker 312) and tolerant (Mac7) Gossypium hirsutum accessions identified several unique variants in NBS genes of Mac7 (6583 variants) and Coker312 (5173 variants). The protein-ligand and proteins-protein interaction showed a strong interaction of some putative NBS proteins with ADP/ATP and different core proteins of the cotton leaf curl disease virus. The silencing of GaNBS (OG2) in resistant cotton through virus-induced gene silencing (VIGS) demonstrated its putative role in virus tittering. The presented study will be further helpful in understanding the plant adaptation mechanism.

Molecular heterogeneity of quiescent melanocyte stem cells revealed by single-cell RNA-sequencing

Melanocyte stem cells (McSCs) of the hair follicle are a rare cell population within the skin and are notably underrepresented in whole-skin, single-cell RNA sequencing (scRNA-seq) datasets. Using a cell enrichment strategy to isolate KIT+/CD45- cells from the telogen skin of adult female C57BL/6J mice, we evaluated the transcriptional landscape of quiescent McSCs (qMcSCs) at high resolution. Through this evaluation, we confirmed existing molecular signatures for qMcCS subpopulations (e.g., Kit+, Cd34+/-, Plp1+, Cd274+/-, Thy1+, Cdh3+/-) and identified novel qMcSC subpopulations, including two that differentially regulate their immune privilege status. Within qMcSC subpopulations, we also predicted melanocyte differentiation potential, neural crest potential, and quiescence depth. Taken together, the results demonstrate that the qMcSC population is heterogeneous and future studies focused on investigating changes in qMcSCs should consider changes in subpopulation composition.

Molecular heterogeneity of quiescent melanocyte stem cells revealed by single-cell RNA-sequencing

Melanocyte stem cells (McSCs) of the hair follicle are a rare cell population within the skin and are notably underrepresented in whole-skin, single-cell RNA sequencing (scRNA-seq) datasets. Using a cell enrichment strategy to isolate KIT+/CD45-cells from the telogen skin of adult female C57BL/6J mice, we evaluated the transcriptional landscape of quiescent McSCs (qMcSCs) at high resolution. Through this evaluation, we confirmed existing molecular signatures for qMcCS subpopulations (e.g., Kit+, Cd34+/- , Plp1+, Cd274+/-, Thy1+, Cdh3+/- ) and identified novel qMcSC subpopulations, including two that differentially regulate their immune privilege status. Within qMcSC subpopulations, we also predicted melanocyte differentiation potential, neural crest potential, and quiescence depth. Taken together, the results demonstrate that the qMcSC population is heterogenous and future studies focused on investigating changes in qMcSCs should consider changes in subpopulation composition.

Significance

Single cell transcriptomics has revolutionized our ability to interrogate the dynamic nature of tissues. Here we provide a high-resolution map of the melanocyte stem cell population during quiescence. This map provides one of few examples highlighting broad heterogeneity in stem cells during the quiescent cell state. The map also unifies previous observations using other cell, molecular and functional analyses to define the unique features of the quiescent melanocyte stem cell population. This data provides a valuable resource to individuals interested in further evaluating aspects of cellular quiescence in stem cells broadly or melanocyte stem cells specifically.

The ORFans' tale: new insights in plant biology

Orphan genes (OGs) are protein-coding genes without a significant sequence similarity in closely related species. Despite their functional importance, very little is known about the underlying molecular mechanisms by which OGs participate in diverse biological processes. Here, we discuss the evolutionary mechanisms of OGs' emergence with relevance to species-specific adaptations. We also provide a mechanistic view of the involvement of OGs in multiple processes, including growth, development, reproduction, and carbon-metabolism-mediated immunity. We highlight the interconnection between OGs and the sucrose nonfermenting 1 (SNF1)-related protein kinases (SnRKs)-target of rapamycin (TOR) signaling axis for phytohormone signaling, nutrient metabolism, and stress responses. Finally, we propose a high-throughput pipeline for OGs' interspecies and intraspecies gene transfer through a transgenic approach for future biotechnological advances.

Integrative systems biology framework discovers common gene regulatory signatures in multiple mechanistically distinct inflammatory skin diseases

More than 20% of the population across the world is affected by non-communicable inflammatory skin diseases including psoriasis, atopic dermatitis, hidradenitis suppurativa, rosacea, etc. Many of these chronic diseases are painful and debilitating with limited effective therapeutic interventions. However, recent advances in psoriasis treatment have improved the effectiveness and provide better management of the disease. This study aims to identify common regulatory pathways and master regulators that regulate molecular pathogenesis. We designed an integrative systems biology framework to identify the significant regulators across several inflammatory skin diseases. With conventional transcriptome analysis, we identified 55 shared genes, which are enriched in several immune-associated pathways in eight inflammatory skin diseases. Next, we exploited the gene co-expression-, and protein-protein interaction-based networks to identify shared genes and protein components in different diseases with relevant functional implications. Additionally, the network analytics unravels 55 high-value proteins as significant regulators in molecular pathogenesis. We believe that these significant regulators should be explored with critical experimental approaches to identify the putative drug targets for more effective treatments. As an example, we identified IKZF1 as a shared significant master regulator in three inflammatory skin diseases, which can serve as a putative drug target with known disease-derived molecules for developing efficacious combinatorial treatments for hidradenitis suppurativa, atopic dermatitis, and rosacea. The proposed framework is very modular, which can indicate a significant path of molecular mechanism-based drug development from complex transcriptomics data and other multi-omics data.

NK and NKT cells in the pathogenesis of Hidradenitis suppurativa: Novel therapeutic strategy through targeting of CD2

Hidradenitis suppurativa (HS) is a chronic debilitating inflammatory skin disease with poorly understood pathogenesis. Single-cell RNAseq analysis of HS lesional and healthy individual skins revealed that NKT and NK cell populations were greatly expanded in HS, and they expressed elevated CD2, an activation receptor. Immunohistochemistry analyses confirmed significantly expanded numbers of CD2+ cells distributed throughout HS lesional tissue, and many co-expressed the NK marker, CD56. While CD4+ T cells were expanded in HS, CD8 T cells were rare. CD20+ B cells in HS were localized within tertiary follicle like structures. Immunofluorescence microscopy showed that NK cells (CD2 + CD56 dim ) expressing perforin, granzymes A and B were enriched within the hyperplastic follicular epidermis and tunnels of HS and juxtaposed with apoptotic cells. In contrast, NKT cells (CD2 + CD3 + CD56 bright ) primarily expressed granzyme A and were associated with α-SMA expressing fibroblasts within the fibrotic regions of the hypodermis. Keratinocytes and fibroblasts expressed high levels of CD58 (CD2 ligand) and they interacted with CD2 expressing NKT and NK cells. The NKT/NK maturation and activating cytokines, IL-12, IL-15 and IL-18, were significantly elevated in HS. Inhibition of cognate CD2-CD58 interaction with blocking anti-CD2 mAb in HS skin organotypic cultures resulted in a profound reduction of the inflammatory gene signature and secretion of inflammatory cytokines and chemokines in the culture supernate. In summary, we show that a cellular network of heterogenous NKT and NK cell populations drives inflammation, tunnel formation and fibrosis in the pathogenesis of HS. Furthermore, CD2 blockade is a viable immunotherapeutic approach for the management of HS.

Integrated Systems Biology Pipeline to Compare Co-Expression Networks in Plants and Elucidate Differential Regulators

To identify sets of genes that exhibit similar expression characteristics, co-expression networks were constructed from transcriptome datasets that were obtained from plant samples at various stages of growth and development or treated with diverse biotic, abiotic, and other environmental stresses. In addition, co-expression network analysis can provide deeper insights into gene regulation when combined with transcriptomics. The coordination and integration of all these complex networks to deduce gene regulation are major challenges for plant biologists. Python and R have emerged as major tools for managing complex scientific data over the past decade. In this study, we describe a reproducible protocol POTFUL (pant co-expression transcription factor regulators), implemented in Python 3, for integrating co-expression and transcription factor target protein networks to infer gene regulation.

The Lost and Found: Unraveling the Functions of Orphan Genes

Orphan Genes (OGs) are a mysterious class of genes that have recently gained significant attention. Despite lacking a clear evolutionary history, they are found in nearly all living organisms, from bacteria to humans, and they play important roles in diverse biological processes. The discovery of OGs was first made through comparative genomics followed by the identification of unique genes across different species. OGs tend to be more prevalent in species with larger genomes, such as plants and animals, and their evolutionary origins remain unclear but potentially arise from gene duplication, horizontal gene transfer (HGT), or de novo origination. Although their precise function is not well understood, OGs have been implicated in crucial biological processes such as development, metabolism, and stress responses. To better understand their significance, researchers are using a variety of approaches, including transcriptomics, functional genomics, and molecular biology. This review offers a comprehensive overview of the current knowledge of OGs in all domains of life, highlighting the possible role of dark transcriptomics in their evolution. More research is needed to fully comprehend the role of OGs in biology and their impact on various biological processes.

Ranking Plant Network Nodes Based on Their Centrality Measures

Biological networks are often large and complex, making it difficult to accurately identify the most important nodes. Node prioritization algorithms are used to identify the most influential nodes in a biological network by considering their relationships with other nodes. These algorithms can help us understand the functioning of the network and the role of individual nodes. We developed CentralityCosDist, an algorithm that ranks nodes based on a combination of centrality measures and seed nodes. We applied this and four other algorithms to protein-protein interactions and co-expression patterns in Arabidopsis thaliana using pathogen effector targets as seed nodes. The accuracy of the algorithms was evaluated through functional enrichment analysis of the top 10 nodes identified by each algorithm. Most enriched terms were similar across algorithms, except for DIAMOnD. CentralityCosDist identified more plant-pathogen interactions and related functions and pathways compared to the other algorithms.

Network Biology Analyses and Dynamic Modeling of Gene Regulatory Networks under Drought Stress Reveal Major Transcriptional Regulators in Arabidopsis

Drought is one of the most serious abiotic stressors in the environment, restricting agricultural production by reducing plant growth, development, and productivity. To investigate such a complex and multifaceted stressor and its effects on plants, a systems biology-based approach is necessitated, entailing the generation of co-expression networks, identification of high-priority transcription factors (TFs), dynamic mathematical modeling, and computational simulations. Here, we studied a high-resolution drought transcriptome of Arabidopsis. We identified distinct temporal transcriptional signatures and demonstrated the involvement of specific biological pathways. Generation of a large-scale co-expression network followed by network centrality analyses identified 117 TFs that possess critical properties of hubs, bottlenecks, and high clustering coefficient nodes. Dynamic transcriptional regulatory modeling of integrated TF targets and transcriptome datasets uncovered major transcriptional events during the course of drought stress. Mathematical transcriptional simulations allowed us to ascertain the activation status of major TFs, as well as the transcriptional intensity and amplitude of their target genes. Finally, we validated our predictions by providing experimental evidence of gene expression under drought stress for a set of four TFs and their major target genes using qRT-PCR. Taken together, we provided a systems-level perspective on the dynamic transcriptional regulation during drought stress in Arabidopsis and uncovered numerous novel TFs that could potentially be used in future genetic crop engineering programs.

Cdk5 mediates rotational force-induced brain injury

Millions of traumatic brain injuries (TBIs) occur annually. TBIs commonly result from falls, traffic accidents, and sports-related injuries, all of which involve rotational acceleration/deceleration of the brain. During these injuries, the brain endures a multitude of primary insults including compression of brain tissue, damaged vasculature, and diffuse axonal injury. All of these deleterious effects can contribute to secondary brain ischemia, cellular death, and neuroinflammation that progress for weeks, months, and lifetime after injury. While the linear effects of head trauma have been extensively modeled, less is known about how rotational injuries mediate neuronal damage following injury. Here, we developed a new model of repetitive rotational head trauma in rodents and demonstrated acute and prolonged pathological, behavioral, and electrophysiological effects of rotational TBI (rTBI). We identify aberrant Cyclin-dependent kinase 5 (Cdk5) activity as a principal mediator of rTBI. We utilized Cdk5-enriched phosphoproteomics to uncover potential downstream mediators of rTBI and show pharmacological inhibition of Cdk5 reduces the cognitive and pathological consequences of injury. These studies contribute meaningfully to our understanding of the mechanisms of rTBI and how they may be effectively treated.

Sparking a sulfur war between plants and pathogens

The biochemical versatility of sulfur (S) lends itself to myriad roles in plant-pathogen interactions. This review evaluates the current understanding of mechanisms by which pathogens acquire S from their plant hosts and highlights new evidence that plants can limit S availability during the immune responses. We discuss the discovery of host disease-susceptibility genes related to S that can be genetically manipulated to create new crop resistance. Finally, we summarize future research challenges and propose a research agenda that leverages systems biology approaches for a holistic understanding of this important element's diverse roles in plant disease resistance and susceptibility.

A pipeline of integrating transcriptome and interactome to elucidate central nodes in host-pathogens interactions

Investigating the complexity of host-pathogen interactions is challenging. Here, we outline a pipeline to identify important proteins and signaling molecules in human-viral interactomes. Firstly, we curate a comprehensive human interactome. Subsequently, we infer viral targets and transcriptome-specific human interactomes (VTTSHI) for papillomavirus and herpes viruses by integrating viral targets and transcriptome data. Finally, we reveal the common and shared nodes and pathways in viral pathogenesis following network topology and pathway enrichment analyses.

For complete details on the use and execution of this protocol, please refer to Kumar et al. (2020).

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Protocol for integrative analysis of transcriptome and proteome network data

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Network subgroup enrichment of two host-pathogen interaction networks

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Preprocessing of data and heterogeneous network integration

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

A modified standard American diet induces physiological parameters associated with metabolic syndrome in C57BL/6J mice

Investigations into the causative role that western dietary patterns have on obesity and disease pathogenesis have speculated that quality and quantity of dietary fats and/or carbohydrates have a predictive role in the development of these disorders. Standard reference diets such as the AIN-93 rodent diet have historically been used to promote animal health and reduce variation of results across experiments, rather than model modern human dietary habits or nutrition-related pathologies. In rodents high-fat diets (HFDs) became a classic tool to investigate diet-induced obesity (DIO). These murine diets often relied on a single fat source with the most DIO consistent HFDs containing levels of fat up to 45-60% (kcal), higher than the reported human intake of 33-35% (kcal). More recently, researchers are formulating experimental animal (pre-clinical) diets that reflect mean human macro- and micronutrient consumption levels described by the National Health and Nutrition Examination Survey (NHANES). These diets attempt to integrate relevant ingredient sources and levels of nutrients; however, they most often fail to include high-fructose corn syrup (HFCS) as a source of dietary carbohydrate. We have formulated a modified Standard American Diet (mSAD) that incorporates relevant levels and sources of nutrient classes, including dietary HFCS, to assess the basal physiologies associated with mSAD consumption. Mice proffered the mSAD for 15 weeks displayed a phenotype consistent with metabolic syndrome, exhibiting increased adiposity, fasting hyperglycemia with impaired glucose and insulin tolerance. Metabolic alterations were evidenced at the tissue level as crown-like structures (CLS) in adipose tissue and fatty acid deposition in the liver, and targeted 16S rRNA metagenomics revealed microbial compositional shifts between dietary groups. This study suggests diet quality significantly affects metabolic homeostasis, emphasizing the importance of developing relevant pre-clinical diets to investigate chronic diseases highly impacted by western dietary consumption patterns.

Advances in molecular pathogenesis of hidradenitis suppurativa: Dysregulated keratins and ECM signaling

Hidradenitis suppurativa (HS) is characterized by deep-seated, highly inflamed, and painful lumps/abscesses, fistulae, and sinus tracts that grow extensively deep in the dermis and are highly immunogenic in nature. In about one-third of the HS patients there is strong evidence for the role of γ-secretase mutations along with dysregulated Notch signaling. However, the contribution of dysregulated Notch signaling in HS pathogenesis in relation to hair follicle alterations and hyper-activation of the immune system remains undefined. A genome-wide association study (GWAS), proteomic data and functional investigations of identified sequence variants in HS pathology are not fully revealing. The disease initiation or progression may involve bacterial infection besides intrinsic functional defects in keratinocytes, which may be key to further exacerbate immune cell infiltration and cytokine production in and around the lesional tissue. The absence of a suitable animal model that could fully recapitulate the pathogenesis of HS is a major impediment for proper understanding the underlying mechanisms and development of effective treatments. The presence of extracellular matrix (ECM) degradation products along with dysregulation in keratinocytes and, dermal fibroblasts ultimately affect immune regulation and are various components of HS pathogenesis. Bacterial infection further exacerbates the complexity of the disease progression. While anti-TNFα therapy shows partial efficacy, treatment to cure HS is absent. Multiple clinical trials targeting various cytokines, complement C5a and ECM products are in progress. This review provides state-of-the-art information on these aspects with a focus on dysregulated keratinocyte and immune cells; and role of ECM, and Keratin functions in this regard.

A genome-wide comparative evolutionary analysis of zinc finger-BED transcription factor genes in land plants

Zinc finger (Zf)-BED proteins are a novel superfamily of transcription factors that controls numerous activities in plants including growth, development, and cellular responses to biotic and abiotic stresses. Despite their important roles in gene regulation, little is known about the specific functions of Zf-BEDs in land plants. The current study identified a total of 750 Zf-BED-encoding genes in 35 land plant species including mosses, bryophytes, lycophytes, gymnosperms, and angiosperms. The gene family size was somewhat proportional to genome size. All identified genes were categorized into 22 classes based on their specific domain architectures. Of these, class I (Zf-BED_DUF-domain_Dimer_Tnp_hAT) was the most common in the majority of the land plants. However, some classes were family-specific, while the others were species-specific, demonstrating diversity at different classification levels. In addition, several novel functional domains were also predicated including WRKY and nucleotide-binding site (NBS). Comparative genomics, transcriptomics, and proteomics provided insights into the evolutionary history, duplication, divergence, gene gain and loss, species relationship, expression profiling, and structural diversity of Zf-BEDs in land plants. The comprehensive study of Zf-BEDs in Gossypium sp., (cotton) also demonstrated a clear footprint of polyploidization. Overall, this comprehensive evolutionary study of Zf-BEDs in land plants highlighted significant diversity among plant species.

A TIReless battle: TIR domains in plant-pathogen interactions

Toll/interleukin-1 receptor (TIR) domain-containing proteins are conserved across kingdoms, and their mechanistic understanding holds promise for basic plant biology and agriculture. Here, we discuss the novel enzymatic TIR domain functions of nucleotide-binding leucine-rich repeat receptors (NLRs) in cell death, and posit how TIR domain-containing effectors mechanistically subvert host immune systems.

Combined inhibition of BET bromodomain and mTORC1/2 provides therapeutic advantage for rhabdomyosarcoma by switching cell death mechanism

Aberrant activation of multiple complex signaling pathways underlies the pathogenesis of rhabdomyosarcoma (RMS), which remains a cause of mortality in approximately 30% of children with RMS. Bromodomain and extraterminal (BET) domain chromatin remodeling regulates several of these pathways. Here, we targeted bromodomain 4 (BRD4) in combination with another molecular metabolic tumor driver, the Akt/mTOR signaling pathway, to provide a highly effective treatment for this neoplasm. We demonstrated that a nexus of these two molecular pathways underlies RMS pathogenesis. Our data show that the combined inhibition of the BET bromodomain and mTORC1/2 signaling abrogates aggressive RMS growth. Thus, the bromodomain inhibitor RVX-208 significantly augmented the therapeutic effects of the dual mTORC1/2 inhibitors, OSI-027 and PP242, both in vitro and in a human xenograft murine model. Drug-treated residual tumors showed a decrease in the activation of underlying signaling mechanisms characterized by a reduction in the expression of p-AKT, p-mTOR, p-p70S6K, cyclin D1, and proliferation. Our ChIP-seq data demonstrated that RVX-208 effectively blocked BRD4 occupancy on its target promoters. ChIP-qPCR assays further confirmed that RVX-208 treatment resulted in a significant decrease in H3K27ac and H4K8ac signals at their target loci. While single RVX-208 treatment induces apoptosis and a single mTORC1/2 inhibitor induces macropinocytosis, their combined treatment led to necroptosis-mediated cell death. These data suggest that combined treatment with drugs targeting BRD4 and mTORC1/2 may be an effective therapeutic intervention for drug-resistant RMS.

A Rice Protein Interaction Network Reveals High Centrality Nodes and Candidate Pathogen Effector Targets

Network science identifies key players in diverse biological systems including host-pathogen interactions. We demonstrated a scale-free network property for a comprehensive rice protein–protein interactome (RicePPInets) that exhibits nodes with increased centrality indices. While weighted k-shell decomposition was shown efficacious to predict pathogen effector targets in Arabidopsis, we improved its computational code for a broader implementation on large-scale networks including RicePPInets. We determined that nodes residing within the internal layers of RicePPInets are poised to be the most influential, central, and effective information spreaders. To identify central players and modules through network topology analyses, we integrated RicePPInets and co-expression networks representing susceptible and resistant responses to strains of the bacterial pathogens Xanthomonas oryzae pv. oryzae and X. oryzae pv. oryzicola (Xoc) and generated a RIce-Xanthomonas INteractome (RIXIN). This revealed that previously identified candidate targets of pathogen transcription activator-like (TAL) effectors are enriched in nodes with enhanced connectivity, bottlenecks, and information spreaders that are located in the inner layers of the network, and these nodes are involved in several important biological processes. Overall, our integrative multi-omics network-based platform provides a potentially useful approach to prioritizing candidate pathogen effector targets for functional validation, suggesting that this computational framework can be broadly translatable to other complex pathosystems.

Genome wide study of cysteine rich receptor like proteins in Gossypium sp

Cysteine-rich receptor-like-kinases (CRKs), a transmembrane subfamily of receptor-like kinase, play crucial roles in plant adaptation. As such cotton is the major source of fiber for the textile industry, but environmental stresses are limiting its growth and production. Here, we have performed a deep computational analysis of CRKs in five Gossypium species, including G. arboreum (60 genes), G. raimondii (74 genes), G. herbaceum (65 genes), G. hirsutum (118 genes), and G. barbadense (120 genes). All identified CRKs were classified into 11 major classes and 43 subclasses with the finding of several novel CRK-associated domains including ALMT, FUSC_2, Cript, FYVE, and Pkinase. Of these, DUF26_DUF26_Pkinase_Tyr was common and had elevated expression under different biotic and abiotic stresses. Moreover, the 35 land plants comparison identified several new CRKs domain-architectures. Likewise, several SNPs and InDels were observed in CLCuD resistant G. hirsutum. The miRNA target side prediction and their expression profiling in different tissues predicted miR172 as a major CRK regulating miR. The expression profiling of CRKs identified multiple clusters with co-expression under certain stress conditions. The expression analysis under CLCuD highlighted the role of GhCRK057, GhCRK059, GhCRK058, and GhCRK081 in resistant accession. Overall, these results provided primary data for future potential functional analysis as well as a reference study for other agronomically important crops.

Dynamic Regulation of the Nexus Between Stress Granules, Roquin, and Regnase-1 Underlies the Molecular Pathogenesis of Warfare Vesicants

The use of chemical warfare agents is prohibited but they have been used in recent Middle Eastern conflicts. Their accidental exposure (e.g. arsenical lewisite) is also known and causes extensive painful cutaneous injury. However, their molecular pathogenesis is not understood. Here, we demonstrate that a nexus of stress granules (SGs), integrated stress, and RNA binding proteins (RBPs) Roquin and Reganse-1 play a key role. Lewisite and its prototype phenylarsine oxide (PAO) induce SG assembly in skin keratinocytes soon after exposure, which associate with various RBPs and translation-related proteins. SG disassembly was detected several hours after exposure. The dynamics of SG assembly-disassembly associates with the chemical insult and cell damage. Enhanced Roquin and Regnase-1 expression occurs when Roquin was recruited to SGs and Regnase-1 to the ribosome while in the disassembling SGs their expression is decreased with consequent induction of inflammatory mediators. SG-targeted protein translational control is regulated by the phosphorylation-dependent activation of eukaryotic initiation factors 2α (eIF2α). Treatment with integrated stress response inhibitor (ISRIB), which blocks eIF2α phosphorylation, impacted SG assembly dynamics. Topical application of ISRIB attenuated the inflammation and tissue disruption in PAO-challenged mice. Thus, the dynamic regulation of these pathways provides underpinning to cutaneous injury and identify translational therapeutic approach for these and similar debilitating chemicals.

Network biology to uncover functional and structural properties of the plant immune system

In the last two decades, advances in network science have facilitated the discovery of important systems' entities in diverse biological networks. This graph-based technique has revealed numerous emergent properties of a system that enable us to understand several complex biological processes including plant immune systems. With the accumulation of multiomics data sets, the comprehensive understanding of plant-pathogen interactions can be achieved through the analyses and efficacious integration of multidimensional qualitative and quantitative relationships among the components of hosts and their microbes. This review highlights comparative network topology analyses in plant-pathogen co-expression networks and interactomes, outlines dynamic network modeling for cell-specific immune regulatory networks, and discusses the new frontiers of single-cell sequencing as well as multiomics data integration that are necessary for unraveling the intricacies of plant immune systems.

High Fructose Corn Syrup-Moderate Fat Diet Potentiates Anxio-Depressive Behavior and Alters Ventral Striatal Neuronal Signaling

The neurobiological mechanisms that mediate psychiatric comorbidities associated with metabolic disorders such as obesity, metabolic syndrome and diabetes remain obscure. High fructose corn syrup (HFCS) is widely used in beverages and is often included in food products with moderate or high fat content that have been linked to many serious health issues including diabetes and obesity. However, the impact of such foods on the brain has not been fully characterized. Here, we evaluated the effects of long-term consumption of a HFCS-Moderate Fat diet (HFCS-MFD) on behavior, neuronal signal transduction, gut microbiota, and serum metabolomic profile in mice to better understand how its consumption and resulting obesity and metabolic alterations relate to behavioral dysfunction. Mice fed HFCS-MFD for 16 weeks displayed enhanced anxiogenesis, increased behavioral despair, and impaired social interactions. Furthermore, the HFCS-MFD induced gut microbiota dysbiosis and lowered serum levels of serotonin and its tryptophan-based precursors. Importantly, the HFCS-MFD altered neuronal signaling in the ventral striatum including reduced inhibitory phosphorylation of glycogen synthase kinase 3β (GSK3β), increased expression of ΔFosB, increased Cdk5-dependent phosphorylation of DARPP-32, and reduced PKA-dependent phosphorylation of the GluR1 subunit of the AMPA receptor. These findings suggest that HFCS-MFD-induced changes in the gut microbiota and neuroactive metabolites may contribute to maladaptive alterations in ventral striatal function that underlie neurobehavioral impairment. While future studies are essential to further evaluate the interplay between these factors in obesity and metabolic syndrome-associated behavioral comorbidities, these data underscore the important role of peripheral-CNS interactions in diet-induced behavioral and brain function. This study also highlights the clinical need to address neurobehavioral comorbidities associated with obesity and metabolic syndrome.

Transcriptional circuitry atlas of genetic diverse unstimulated murine and human macrophages define disparity in population-wide innate immunity

Macrophages are ubiquitous custodians of tissues, which play decisive role in maintaining cellular homeostasis through regulatory immune responses. Within tissues, macrophage exhibit extremely heterogeneous population with varying functions orchestrated through regulatory response, which can be further exacerbated in diverse genetic backgrounds. Gene regulatory networks (GRNs) offer comprehensive understanding of cellular regulatory behavior by unfolding the transcription factors (TFs) and regulated target genes. RNA-Seq coupled with ATAC-Seq has revolutionized the regulome landscape influenced by gene expression modeling. Here, we employ an integrative multi-omics systems biology-based analysis and generated GRNs derived from the unstimulated bone marrow-derived macrophages of five inbred genetically defined murine strains, which are reported to be linked with most of the population-wide human genetic variants. Our probabilistic modeling of a basal hemostasis pan regulatory repertoire in diverse macrophages discovered 96 TFs targeting 6279 genes representing 468,291 interactions across five inbred murine strains. Subsequently, we identify core and distinctive GRN sub-networks in unstimulated macrophages to describe the system-wide conservation and dissimilarities, respectively across five murine strains. Our study concludes that discrepancies in unstimulated macrophage-specific regulatory networks not only drives the basal functional plasticity within genetic backgrounds, additionally aid in understanding the complexity of racial disparity among the human population during stress.

Molecular pathology associated with altered synaptic transcriptome in the dorsolateral prefrontal cortex of depressed subjects

Disrupted synaptic plasticity is the hallmark of major depressive disorder (MDD), with accompanying changes at the molecular and cellular levels. Often, the maladaptive molecular changes at the synapse are the result of global transcriptional reprogramming dictated by activity-dependent synaptic modulation. Thus far, no study has directly studied the transcriptome-wide expression changes locally at the synapse in MDD brain. Here, we have examined altered synaptic transcriptomics and their functional relevance in MDD with a focus on the dorsolateral prefrontal cortex (dlPFC). RNA was isolated from total fraction and purified synaptosomes of dlPFC from well-matched 15 non-psychiatric controls and 15 MDD subjects. Transcriptomic changes in synaptic and total fractions were detected by next-generation RNA-sequencing (NGS) and analyzed independently. The ratio of synaptic/total fraction was estimated to evaluate a shift in gene expression ratio in MDD subjects. Bioinformatics and network analyses were used to determine the biological relevance of transcriptomic changes in both total and synaptic fractions based on gene-gene network, gene ontology (GO), and pathway prediction algorithms. A total of 14,005 genes were detected in total fraction. A total of 104 genes were differentially regulated (73 upregulated and 31 downregulated) in MDD group based on 1.3-fold change threshold and p < 0.05 criteria. In synaptosomes, out of 13,236 detectable genes, 234 were upregulated and 60 were downregulated (>1.3-fold, p < 0.05). Several of these altered genes were validated independently by a quantitative polymerase chain reaction (qPCR). GO revealed an association with immune system processes and cell death. Moreover, a cluster of genes belonged to the nervous system development, and psychological disorders were discovered using gene-gene network analysis. The ratio of synaptic/total fraction showed a shift in expression of 119 genes in MDD subjects, which were primarily associated with neuroinflammation, interleukin signaling, and cell death. Our results suggest not only large-scale gene expression changes in synaptosomes, but also a shift in the expression of genes from total to synaptic fractions of dlPFC of MDD subjects with their potential role in immunomodulation and cell death. Our findings provide new insights into the understanding of transcriptomic regulation at the synapse and their possible role in MDD pathogenesis.

Epigenetic regulation in the pathogenesis of non-melanoma skin cancer

Understanding of cancer with the help of ever-expanding cutting edge technological tools and bioinformatics is revolutionizing modern cancer research by broadening the space of discovery window of various genomic and epigenomic processes. Genomics data integrated with multi-omics layering have advanced cancer research. Uncovering such layers of genetic mutations/modifications, epigenetic regulation and their role in the complex pathophysiology of cancer progression could lead to novel therapeutic interventions. Although a plethora of literature is available in public domain defining the role of various tumor driver gene mutations, understanding of epigenetic regulation of cancer is still emerging. This review focuses on epigenetic regulation association with the pathogenesis of non-melanoma skin cancer (NMSC). NMSC has higher prevalence in Caucasian populations compared to other races. Due to lack of proper reporting to cancer registries, the incidence rates for NMSC worldwide cannot be accurately estimated. However, this is the most common neoplasm in humans, and millions of new cases per year are reported in the United States alone. In organ transplant recipients, the incidence of NMSC particularly of squamous cell carcinoma (SCC) is very high and these SCCs frequently become metastatic and lethal. Understanding of solar ultraviolet (UV) light-induced damage and impaired DNA repair process leading to DNA mutations and nuclear instability provide an insight into the pathogenesis of metastatic neoplasm. This review discusses the recent advances in the field of epigenetics of NMSCs. Particularly, the role of DNA methylation, histone hyperacetylation and non-coding RNA such as long-chain noncoding (lnc) RNAs, circular RNAs and miRNA in the disease progression are summarized.

EffectorK, a comprehensive resource to mine for Ralstonia, Xanthomonas, and other published effector interactors in the Arabidopsis proteome

Pathogens deploy effector proteins that interact with host proteins to manipulate the host physiology to the pathogen's own benefit. However, effectors can also be recognized by host immune proteins, leading to the activation of defence responses. Effectors are thus essential components in determining the outcome of plant-pathogen interactions. Despite major efforts to decipher effector functions, our current knowledge on effector biology is scattered and often limited. In this study, we conducted two systematic large-scale yeast two-hybrid screenings to detect interactions between Arabidopsis thaliana proteins and effectors from two vascular bacterial pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. We then constructed an interactomic network focused on Arabidopsis and effector proteins from a wide variety of bacterial, oomycete, fungal, and invertebrate pathogens. This network contains our experimental data and protein-protein interactions from 2,035 peer-reviewed publications (48,200 Arabidopsis-Arabidopsis and 1,300 Arabidopsis-effector protein interactions). Our results show that effectors from different species interact with both common and specific Arabidopsis interactors, suggesting dual roles as modulators of generic and adaptive host processes. Network analyses revealed that effector interactors, particularly "effector hubs" and bacterial core effector interactors, occupy important positions for network organization, as shown by their larger number of protein interactions and centrality. These interactomic data were incorporated in EffectorK, a new graph-oriented knowledge database that allows users to navigate the network, search for homology, or find possible paths between host and/or effector proteins. EffectorK is available at www.effectork.org and allows users to submit their own interactomic data.

Integrative Network Biology Framework Elucidates Molecular Mechanisms of SARS-CoV-2 Pathogenesis

COVID-19 (Coronavirus disease 2019) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While the pathophysiology of this deadly virus is complex and largely unknown, we employ a network biology-fueled approach and integrate multiomics data pertaining to lung epithelial cells-specific co-expression network and human interactome to generate Calu-3-specific human-SARS-CoV-2 Interactome (CSI). Topological clustering and pathway enrichment analysis show that SARS-CoV-2 target central nodes of host-viral network that participate in core functional pathways. Network centrality analyses discover 28 high-value SARS-CoV-2 targets, which are possibly involved in viral entry, proliferation and survival to establish infection and facilitate disease progression. Our probabilistic modeling framework elucidates critical regulatory circuitry and molecular events pertinent to COVID-19, particularly the host modifying responses and cytokine storm. Overall, our network centric analyses reveal novel molecular components, uncover structural and functional modules, and provide molecular insights into SARS-CoV-2 pathogenicity that may foster effective therapeutic design. Funding: This work was supported by the National Science Foundation (IOS-1557796) to M.S.M., and U54 ES 030246 from NIH/NIEHS to M. A. Conflict of Interest: The authors declare no competing interests. The authors also declare no financial interests.

Molecular insight into cotton leaf curl geminivirus disease resistance in cultivated cotton (Gossypium hirsutum)

Cultivated cotton (Gossypium hirsutum) is the most important fibre crop in the world. Cotton leaf curl disease (CLCuD) is the major limiting factor and a threat to textile industry in India and Pakistan. All the local cotton cultivars exhibit moderate to no resistance against CLCuD. In this study, we evaluated an exotic cotton accession Mac7 as a resistance source to CLCuD by challenging it with viruliferous whiteflies and performing qPCR to evaluate the presence/absence and relative titre of CLCuD-associated geminiviruses/betasatellites. The results indicated that replication of pathogenicity determinant betasatellite is significantly attenuated in Mac7 and probably responsible for resistance phenotype. Afterwards, to decipher the genetic basis of CLCuD resistance in Mac7, we performed RNA sequencing on CLCuD-infested Mac7 and validated RNA-Seq data with qPCR on 24 independent genes. We performed co-expression network and pathway analysis for regulation of geminivirus/betasatellite-interacting genes. We identified nine novel modules with 52 hubs of highly connected genes in network topology within the co-expression network. Analysis of these hubs indicated the differential regulation of auxin stimulus and cellular localization pathways in response to CLCuD. We also analysed the differential regulation of geminivirus/betasatellite-interacting genes in Mac7. We further performed the functional validation of selected candidate genes via virus-induced gene silencing (VIGS). Finally, we evaluated the genomic context of resistance responsive genes and found that these genes are not specific to A or D sub-genomes of G. hirsutum. These results have important implications in understanding CLCuD resistance mechanism and developing a durable resistance in cultivated cotton.

Direct Regulation of the EFR-Dependent Immune Response by Arabidopsis TCP Transcription Factors

One layer of the innate immune system allows plants to recognize pathogen-associated molecular patterns (PAMPS), activating a defense response known as PAMP-triggered immunity (PTI). Maintaining an active immune response, however, comes at the cost of plant growth and development; accordingly, optimization of the balance between defense and development is critical to plant fitness. The TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) transcription factor family consists of well-characterized transcriptional regulators of plant development and morphogenesis. The three closely related class I TCP transcription factors TCP8, TCP14, and TCP15 have also been implicated in the regulation of effector-triggered immunity, but there has been no previous characterization of PTI-related phenotypes. To identify TCP targets involved in PTI, we screened a PAMP-induced gene promoter library in a yeast one-hybrid assay and identified interactions of these three TCPs with the EF-Tu RECEPTOR (EFR) promoter. The direct interactions between TCP8 and EFR were confirmed to require an intact TCP binding site in planta. A tcp8 tcp14 tcp15 triple mutant was impaired in EFR-dependent PTI and exhibited reduced levels of PATHOGENESIS-RELATED PROTEIN 2 and induction of EFR expression after elicitation with elf18 but also increased production of reactive oxygen species relative to Col-0. Our data support an increasingly complex role for TCPs at the nexus of plant development and defense.

Map of physical interactions between extracellular domains of Arabidopsis leucine-rich repeat receptor kinases

Plants use surface receptors to perceive information about many aspects of their local environment. These receptors physically interact to form both steady state and signalling competent complexes. The signalling events downstream of receptor activation impact both plant developmental and immune responses. Here, we present a comprehensive study of the physical interactions between the extracellular domains of leucine-rich repeat receptor kinases (LRR-RKs) in Arabidopsis. Using a sensitized assay, we tested reciprocal interactions among 200 of the 225 Arabidopsis LRR-RKs for a total search space of 40,000 interactions. Applying a stringent statistical cut-off and requiring that interactions performed well in both bait-prey and prey-bait orientations resulted in a high-confidence set of 567 bidirectional interactions. Additionally, we identified a total of 2,586 unidirectional interactions, which passed our stringent statistical cut-off in only one orientation. These datasets will guide further investigation into the regulatory roles of LRR-RKs in plant developmental and immune signalling decisions.

Transcriptomic analysis of cultivated cotton Gossypium hirsutum provides insights into host responses upon whitefly-mediated transmission of cotton leaf curl disease

Cotton is a commercial and economically important crop that generates billions of dollars in annual revenue worldwide. However, cotton yield is affected by a sap-sucking insect Bemisia tabaci (whitefly), and whitefly-borne cotton leaf curl disease (CLCuD). The causative agent of devastating CLCuD is led by the viruses belonging to the genus Begomovirus (family Geminiviridae), collectively called cotton leaf curl viruses. Unfortunately, the extensively cultivated cotton (Gossypium hirsutum) species are highly susceptible and vulnerable to CLCuD. Yet, the concomitant influence of whitefly and CLCuD on the susceptible G. hirsutum transcriptome has not been interpreted. In the present study we have employed an RNA Sequencing (RNA-Seq) transcriptomics approach to explore the differential gene expression in susceptible G. hirsutum variety upon infection with viruliferous whiteflies. Comparative RNA-Seq of control and CLCuD infected plants was done using Illumina HiSeq 2500. This study yielded 468 differentially expressed genes (DEGs). Among them, we identified 220 up and 248 downregulated DEGs involved in disease responses and pathogen defense. We selected ten genes for downstream RT-qPCR analyses on two cultivars, Karishma and MNH 786 that are susceptible to CLCuD. We observed a similar expression pattern of these genes in both susceptible cultivars that was also consistent with our transcriptome data further implying a wider application of our global transcription study on host susceptibility to CLCuD. We next performed weighted gene co-expression network analysis that revealed six modules. This analysis also identified highly co-expressed genes as well as 55 hub genes that co-express with ≥ 50 genes. Intriguingly, most of these hub genes are shown to be downregulated and enriched in cellular processes. Under-expression of such highly co-expressed genes suggests their roles in favoring the virus and enhancing plant susceptibility to CLCuD. We also discuss the potential mechanisms governing the establishment of disease susceptibility. Overall, our study provides a comprehensive differential gene expression analysis of G. hirsutum under whitefly-mediated CLCuD infection. This vital study will advance the understanding of simultaneous effect of whitefly and virus on their host and aid in identifying important G. hirsutum genes which intricate in its susceptibility to CLCuD.

Systems Biology and Machine Learning in Plant-Pathogen Interactions

Systems biology is an inclusive approach to study the static and dynamic emergent properties on a global scale by integrating multiomics datasets to establish qualitative and quantitative associations among multiple biological components. With an abundance of improved high throughput -omics datasets, network-based analyses and machine learning technologies are playing a pivotal role in comprehensive understanding of biological systems. Network topological features reveal most important nodes within a network as well as prioritize significant molecular components for diverse biological networks, including coexpression, protein-protein interaction, and gene regulatory networks. Machine learning techniques provide enormous predictive power through specific feature extraction from biological data. Deep learning, a subtype of machine learning, has plausible future applications because a domain expert for feature extraction is not needed in this algorithm. Inspired by diverse domains of biology, we here review classic systems biology techniques applied in plant immunity thus far. We also discuss additional advanced approaches in both graph theory and machine learning, which may provide new insights for understanding plant-microbe interactions. Finally, we propose a hybrid approach in plant immune systems that harnesses the power of both network biology and machine learning, with a potential to be applicable to both model systems and agronomically important crop plants.

Genome Editing: Targeting Susceptibility Genes for Plant Disease Resistance

Plant pathogens pose a major threat to crop productivity. Typically, phytopathogens exploit plants' susceptibility (S) genes to facilitate their proliferation. Disrupting these S genes may interfere with the compatibility between the host and the pathogens and consequently provide broad-spectrum and durable disease resistance. In the past, genetic manipulation of such S genes has been shown to confer disease resistance in various economically important crops. Recent studies have accomplished this task in a transgene-free system using new genome editing tools, including clustered regularly interspaced palindromic repeats (CRISPR). In this Opinion article, we focus on the use of genome editing to target S genes for the development of transgene-free and durable disease-resistant crop varieties.

Dynamic modeling of transcriptional gene regulatory network uncovers distinct pathways during the onset of Arabidopsis leaf senescence

Age-dependent senescence is a multifaceted and highly coordinated developmental phase in the life of plants that is manifested with genetic, biochemical and phenotypic continuum. Thus, elucidating the dynamic network modeling and simulation of molecular events, in particular gene regulatory network during the onset of senescence is essential. Here, we constructed a computational pipeline that integrates senescence-related co-expression networks with transcription factor (TF)-promoter relationships and microRNA (miR)-target interactions. Network structural and functional analyses revealed important nodes within each module of these co-expression networks. Subsequently, we inferred significant dynamic transcriptional regulatory models in leaf senescence using time-course gene expression datasets. Dynamic simulations and predictive network perturbation analyses followed by experimental dataset illustrated the kinetic relationships among TFs and their downstream targets. In conclusion, our network science framework discovers cohorts of TFs and their paths with previously unrecognized roles in leaf senescence and provides a comprehensive landscape of dynamic transcriptional circuitry.

Publisher Correction: An extracellular network of Arabidopsis leucine-rich repeat receptor kinases

In this Letter, an incorrect version of the Supplementary Information file was inadvertently used, which contained several errors. The details of references 59-65 were missing from the end of the Supplementary Discussion section on page 4. In addition, the section 'Text 3. Y2H on ICD interactions' incorrectly referred to 'Extended Data Fig. 4d' instead of 'Extended Data Fig. 3d' on page 3. Finally, the section 'Text 4. Interaction network analysis' incorrectly referred to 'Fig. 1b and Extended Data Fig. 6' instead of 'Fig. 2b and Extended Data Fig. 7' on page 3. These errors have all been corrected in the Supplementary Information.

Network biology discovers pathogen contact points in host protein-protein interactomes

In all organisms, major biological processes are controlled by complex protein-protein interactions networks (interactomes), yet their structural complexity presents major analytical challenges. Here, we integrate a compendium of over 4300 phenotypes with Arabidopsis interactome (AI-1MAIN). We show that nodes with high connectivity and betweenness are enriched and depleted in conditional and essential phenotypes, respectively. Such nodes are located in the innermost layers of AI-1MAIN and are preferential targets of pathogen effectors. We extend these network-centric analyses to Cell Surface Interactome (CSILRR) and predict its 35 most influential nodes. To determine their biological relevance, we show that these proteins physically interact with pathogen effectors and modulate plant immunity. Overall, our findings contrast with centrality-lethality rule, discover fast information spreading nodes, and highlight the structural properties of pathogen targets in two different interactomes. Finally, this theoretical framework could possibly be applicable to other inter-species interactomes to reveal pathogen contact points.

NPR1 in JazzSet with Pathogen Effectors

NON-EXPRESSOR OF PATHOGENESIS-RELATED GENES 1 (NPR1) is a master regulator of salicylic acid (SA)-mediated systemic acquired resistance (SAR), a broad-spectrum disease resistance mechanism in plants. NPR1 controls approximately 90% of SA-dependent transcriptome in Arabidopsis. Here, we discuss how pathogen effectors manipulate NPR1 functions in different cellular compartments to establish disease.

Transcriptomics reveals multiple resistance mechanisms against cotton leaf curl disease in a naturally immune cotton species, Gossypium arboreum

Cotton leaf curl disease (CLCuD), caused by cotton leaf curl viruses (CLCuVs), is among the most devastating diseases in cotton. While the widely cultivated cotton species Gossypium hirsutum is generally susceptible, the diploid species G. arboreum is a natural source for resistance against CLCuD. However, the influence of CLCuD on the G. arboreum transcriptome and the interaction of CLCuD with G. arboreum remains to be elucidated. Here we have used an RNA-Seq based study to analyze differential gene expression in G. arboreum under CLCuD infestation. G. arboreum plants were infested by graft inoculation using a CLCuD infected scion of G. hirsutum. CLCuD infested asymptomatic and symptomatic plants were analyzed with RNA-seq using an Illumina HiSeq. 2500. Data analysis revealed 1062 differentially expressed genes (DEGs) in G. arboreum. We selected 17 genes for qPCR to validate RNA-Seq data. We identified several genes involved in disease resistance and pathogen defense. Furthermore, a weighted gene co-expression network was constructed from the RNA-Seq dataset that indicated 50 hub genes, most of which are involved in transport processes and might have a role in the defense response of G. arboreum against CLCuD. This fundamental study will improve the understanding of virus-host interaction and identification of important genes involved in G. arboreum tolerance against CLCuD.

Elucidating the role of WRKY27 in male sterility in Arabidopsis

The WRKY proteins belong to a superfamily of TFs that play pivotal roles in responses to a wide range of biotic, abiotic, developmental and physiologic cues. Here, we assayed the accumulation of basal WRKY27 transcripts in diverse tissue including root, shoot, leaf and flowers. We demonstrated that plants over-expressing WRKY27 transcript levels exhibit growth aberrations and fertility defects. Scanning electron microscopic data suggest that WRKY27 overexpressor plants exhibit pollen dehiscence defects. Our fluorescein diacetate hydrolysis assay showed that flowers of plants overexpressing WRKY27 display significantly decreased pollen viability. These sterility-related phenotypes were not rescued by the exogenous applications of different phytohormones. Our results indicate the involvement of WRKY27 in particular for proper plant biomass accumulation and male fertility.

Global temporal dynamic landscape of pathogen-mediated subversion of Arabidopsis innate immunity

The universal nature of networks’ structural and physical properties across diverse systems offers a better prospect to elucidate the interplay between a system and its environment. In the last decade, several large-scale transcriptome and interactome studies were conducted to understand the complex and dynamic nature of interactions between Arabidopsis and its bacterial pathogen, Pseudomonas syringae pv. tomato DC3000. We took advantage of these publicly available datasets and performed “-omics”-based integrative, and network topology analyses to decipher the transcriptional and protein-protein interaction activities of effector targets. We demonstrated that effector targets exhibit shorter distance to differentially expressed genes (DEGs) and possess increased information centrality. Intriguingly, effector targets are differentially expressed in a sequential manner and make for 1% of the total DEGs at any time point of infection with virulent or defense-inducing DC3000 strains. We revealed that DC3000 significantly alters the expression levels of 71% effector targets and their downstream physical interacting proteins in Arabidopsis interactome. Our integrative “-omics”-–based analyses identified dynamic complexes associated with MTI and disease susceptibility. Finally, we discovered five novel plant defense players using a systems biology-fueled top-to-bottom approach and demonstrated immune-related functions for them, further validating the power and resolution of our network analyses.

Cytokinin Response Factor 6 Represses Cytokinin-Associated Genes during Oxidative Stress

Cytokinin is a phytohormone that is well known for its roles in numerous plant growth and developmental processes, yet it has also been linked to abiotic stress response in a less defined manner. Arabidopsis (Arabidopsis thaliana) Cytokinin Response Factor 6 (CRF6) is a cytokinin-responsive AP2/ERF-family transcription factor that, through the cytokinin signaling pathway, plays a key role in the inhibition of dark-induced senescence. CRF6 expression is also induced by oxidative stress, and here we show a novel function for CRF6 in relation to oxidative stress and identify downstream transcriptional targets of CRF6 that are repressed in response to oxidative stress. Analysis of transcriptomic changes in wild-type and crf6 mutant plants treated with H₂O₂ identified CRF6-dependent differentially expressed transcripts, many of which were repressed rather than induced. Moreover, many repressed genes also show decreased expression in 35S:CRF6 overexpressing plants. Together, these findings suggest that CRF6 functions largely as a transcriptional repressor. Interestingly, among the H₂O₂ repressed CRF6-dependent transcripts was a set of five genes associated with cytokinin processes: (signaling) ARR6, ARR9, ARR11, (biosynthesis) LOG7, and (transport) ABCG14. We have examined mutants of these cytokinin-associated target genes to reveal novel connections to oxidative stress. Further examination of CRF6-DNA interactions indicated that CRF6 may regulate its targets both directly and indirectly. Together, this shows that CRF6 functions during oxidative stress as a negative regulator to control this cytokinin-associated module of CRF6-dependent genes and establishes a novel connection between cytokinin and oxidative stress response.

Intrinsically Disordered Proteins: Controlled Chaos or Random Walk

Traditional conventions that a protein’s sequence dictates its definitive, tertiary structure, and that this fixed structure provides the protein with the ability to carry out its designated role(s) are still correct but not for all proteins. Research over the past decade discovered that several key proteins possess intrinsically disordered regions (IDRs) that are crucial to their ability to perform specific functions and are observed clustered together within important classes of proteins. In this review, we aim to demonstrate how free energy landscapes, molecular dynamics simulations, and homology modeling are helpful in understanding key conformational dynamics of intrinsically disordered proteins (IDPs). Additionally, we use a list of predicted IDPs found in Arabidopsis to identify chromatin organizers and transcriptional regulators as being highly enriched in IDPs. Furthermore, we focus our attention to specific proteins within these families such as HAC5, EFS, ANAC019, ANAC013, and ANAC046. Future studies are needed to experimentally identify additional IDPs and their binding mechanisms.

Heterotrimeric G-proteins in Picea abies and their regulation in response to Heterobasidion annosum s.l. infection

BACKGROUND

Heterotrimeric G-proteins are important signalling switches, present in all eukaryotic kingdoms. In plants they regulate several developmental functions and play an important role in plant-microbe interactions. The current knowledge on plant G-proteins is mostly based on model angiosperms and little is known about the G-protein repertoire and function in other lineages. In this study we investigate the heterotrimeric G-protein subunit repertoire in Pinaceae, including phylogenetic relationships, radiation and sequence diversity levels in relation to other plant linages. We also investigate functional diversification of the G-protein complex in Picea abies by analysing transcriptional regulation of the G-protein subunits in different tissues and in response to pathogen infection.

RESULTS

A full repertoire of G-protein subunits in several conifer species were identified in silico. The full-length P. abies coding regions of one Gα-, one Gβ- and four Gγ-subunits were cloned and sequenced. The phylogenetic analysis of the Gγ-subunits showed that PaGG1 clustered with A-type-like subunits, PaGG3 and PaGG4 clustered with C-type-like subunits, while PaGG2 and its orthologs represented a novel conifer-specific putative Gγ-subunit type. Gene expression analyses by quantitative PCR of P. abies G-protein subunits showed specific up-regulation of the Gα-subunit gene PaGPA1 and the Gγ-subunit gene PaGG1 in response to Heterobasidion annosum sensu lato infection.

CONCLUSIONS

Conifers possess a full repertoire of G-protein subunits. The differential regulation of PaGPA1 and PaGG1 indicates that the heterotrimeric G-protein complex represents a critical linchpin in Heterobasidion annosum s.l. perception and downstream signaling in P. abies.

Convergent targeting of a common host protein-network by pathogen effectors from three kingdoms of life

While conceptual principles governing plant immunity are becoming clear, its systems-level organization and the evolutionary dynamic of the host-pathogen interface are still obscure. We generated a systematic protein-protein interaction network of virulence effectors from the ascomycete pathogen Golovinomyces orontii and Arabidopsis thaliana host proteins. We combined this data set with corresponding data for the eubacterial pathogen Pseudomonas syringae and the oomycete pathogen Hyaloperonospora arabidopsidis. The resulting network identifies host proteins onto which intraspecies and interspecies pathogen effectors converge. Phenotyping of 124 Arabidopsis effector-interactor mutants revealed a correlation between intraspecies and interspecies convergence and several altered immune response phenotypes. Several effectors and the most heavily targeted host protein colocalized in subnuclear foci. Products of adaptively selected Arabidopsis genes are enriched for interactions with effector targets. Our data suggest the existence of a molecular host-pathogen interface that is conserved across Arabidopsis accessions, while evolutionary adaptation occurs in the immediate network neighborhood of effector targets.

The Top 10 oomycete pathogens in molecular plant pathology

Oomycetes form a deep lineage of eukaryotic organisms that includes a large number of plant pathogens which threaten natural and managed ecosystems. We undertook a survey to query the community for their ranking of plant-pathogenic oomycete species based on scientific and economic importance. In total, we received 263 votes from 62 scientists in 15 countries for a total of 33 species. The Top 10 species and their ranking are: (1) Phytophthora infestans; (2, tied) Hyaloperonospora arabidopsidis; (2, tied) Phytophthora ramorum; (4) Phytophthora sojae; (5) Phytophthora capsici; (6) Plasmopara viticola; (7) Phytophthora cinnamomi; (8, tied) Phytophthora parasitica; (8, tied) Pythium ultimum; and (10) Albugo candida. This article provides an introduction to these 10 taxa and a snapshot of current research. We hope that the list will serve as a benchmark for future trends in oomycete research.

TCP three-way handshake: linking developmental processes with plant immunity

The TCP gene family encodes plant-specific transcription factors involved in growth and development. Equally important are the interactions between TCP factors and other pathways extending far beyond development, as they have been found to regulate a variety of hormonal pathways and signaling cascades. Recent advances reveal that TCP factors are targets of pathogenic effectors and are likely to play a vital role in plant immunity. Our focus is on reviewing the involvement of TCP in known pathways and shedding light on other linkages in the nexus of plant immunity centered around TCP factors with an emphasis on the convergence of effectors, interconnected hormonal networks, utility of the circadian clock, and the potential mechanisms by which pathogen defense may occur.

Expression-based network biology identifies immune-related functional modules involved in plant defense

Background

Plants respond to diverse environmental cues including microbial perturbations by coordinated regulation of thousands of genes. These intricate transcriptional regulatory interactions depend on the recognition of specific promoter sequences by regulatory transcription factors. The combinatorial and cooperative action of multiple transcription factors defines a regulatory network that enables plant cells to respond to distinct biological signals. The identification of immune-related modules in large-scale transcriptional regulatory networks can reveal the mechanisms by which exposure to a pathogen elicits a precise phenotypic immune response.

Results

We have generated a large-scale immune co-expression network using a comprehensive set of Arabidopsis thaliana (hereafter Arabidopsis) transcriptomic data, which consists of a wide spectrum of immune responses to pathogens or pathogen-mimicking stimuli treatments. We employed both linear and non-linear models to generate Arabidopsis immune co-expression regulatory (AICR) network. We computed network topological properties and ascertained that this newly constructed immune network is densely connected, possesses hubs, exhibits high modularity, and displays hallmarks of a “real” biological network. We partitioned the network and identified 156 novel modules related to immune functions. Gene Ontology (GO) enrichment analyses provided insight into the key biological processes involved in determining finely tuned immune responses. We also developed novel software called OCCEAN (One Click Cis-regulatory Elements ANalysis) to discover statistically enriched promoter elements in the upstream regulatory regions of Arabidopsis at a whole genome level. We demonstrated that OCCEAN exhibits higher precision than the existing promoter element discovery tools. In light of known and newly discovered cis-regulatory elements, we evaluated biological significance of two key immune-related functional modules and proposed mechanism(s) to explain how large sets of diverse GO genes coherently function to mount effective immune responses.

Conclusions

We used a network-based, top-down approach to discover immune-related modules from transcriptomic data in Arabidopsis. Detailed analyses of these functional modules reveal new insight into the topological properties of immune co-expression networks and a comprehensive understanding of multifaceted plant defense responses. We present evidence that our newly developed software, OCCEAN, could become a popular tool for the Arabidopsis research community as well as potentially expand to analyze other eukaryotic genomes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-421) contains supplementary material, which is available to authorized users.

Engineering NLR immune receptors for broad-spectrum disease resistance

Two recent reports by Maekawa et al. and Narusaka et al. demonstrated the transfer of a nucleotide-binding domain and leucine-rich repeat (NLR) family of immune receptors into evolutionarily diverged plants without causing adverse fitness consequences. The applications of NLRs in engineering durable and broad-spectrum resistance in plants are highlighted here.