Duckweed: Beyond an Efficient Plant Model System.

Duckweed (Lemnaceae) rises as a crucial model system due to its unique characteristics and wide-ranging utility. The significance of physiological research and phytoremediation highlights the intricate potential of duckweed in the current era of plant biology. Special attention to duckweed has been brought due to its distinctive features of nutrient uptake, ion transport dynamics, detoxification, intricate signaling, and stress tolerance. In addition, duckweed can alleviate environmental pollutants and enhance sustainability by participating in bioremediation processes and wastewater treatment. Furthermore, insights into the genomic complexity of Lemnaceae species and the flourishing field of transgenic development highlight the opportunities for genetic manipulation and biotechnological innovations. Novel methods for the germplasm conservation of duckweed can be adopted to preserve genetic diversity for future research endeavors and breeding programs. This review centers around prospects in duckweed research promoting interdisciplinary collaborations and technological advancements to drive its full potential as a model organism.

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.

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.

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.

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.

Monitoring of some organochlorine residues in raw bovine milk in the west Delta area, Egypt.

Background: For decades, the use of organochlorine (OC) pesticides has had a detrimental effect on the environment and human health. Contamination of soil, water, and air has also resulted in contaminated milk. Aim: The purpose of this study was to investigate if any OC residues dichlorodiphenyltrichloroethane (DDT, Dieldrin, Endrin, and Lindane) were present in raw bovine milk from West Delta, Egypt. Methods: 200 fresh raw cow milk samples (500 ml of each sample) collected from three different governorates, west Delta, Egypt, for determination of OC pesticides residues using gas chromatography with an Agilent 6890A model gas chromatograph equipped with a 63Ni microelectron capture detector. Results: The obtained results revealed that åDDT, dieldrin, endrin, and lindane were detected in Alexandria, Behera, and Matrouh at incidence levels (22.7%, 30.7%, and 10%), (20%, 20%, and 16%), (9.33%, 13.3%, and 16%), and (12%, 10.7%, and 14%) with mean values of 232.2 ± 163.6, 156.4 ± 134.6 and 100.4 ± 85.9; 91.3 ± 61.2, 95.3 ± 59.8 and 57.6 ± 3.33; 15.7± 3.86, 15.1 ± 3.96 and 20.1 ± 7.33; 33.7 ± 10.6, 36.9 ± 5.51 and 52.2 ± 21.8 ng/g fat, respectively. El-Behera was the most contaminated province with an incidence level of 53.3% with a mean value of 136.8 ± 128.0 ng/g fat, followed by Alexandria at 44% with a mean value of 173.7 ± 155.5 ng/g fat, and finally, Matrouh 40% with a mean value of 74.5 ± 56.5 ng/g fat. Conclusion: This research demonstrated that milk samples contain varying levels of OC pesticide residues, which can be hazardous to consumer health. Therefore, to safeguard consumers, especially children, and the elderly, OC pesticide residues in milk must be closely monitored.

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.

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.

Evaluation of the Adsorption Efficacy of Bentonite on Aflatoxin M1 Levels in Contaminated Milk.

The existence of aflatoxin M1 (AFM1) in raw milk results in economic losses and public health risks. This research aims to examine the capability of bentonite to adsorb and/or eliminate AFM1 from various raw milk types. In addition, the effects of numerous bentonites (HAFR 1, 2, 3 and 4) on the nutritional characteristics of the milk were studied. Our findings revealed that goat milk had the highest value of AFM1 (490.30 ng/L) in comparison to other milks. AFM1 adsorption was influenced by applying bentonite (0.5 and 1 g) in a concentration-dependent manner for different time intervals (from 0 to 12 h). The percentage of AFM1 reached the maximum adsorption level after 12 h to 100, 98.5 and 98% for bentonites HAFR 3, 1 and 2, respectively. HAFR 3 (1 g bentonite) presented higher adsorption efficiency than other bentonites used in the phosphate buffer saline (PBS) and milk. Residual levels of AFM1 reached their lowest values of 0 and 1.5 ng/L while using HAFR 3 in PBS and milk, respectively. With regard to the influence of bentonite on the nutritional characteristics of milk, there was an increase in fat, protein and solid non-fat ratio while using HAFR 3 and 4, yet decreased lactose in comparison with the control. Scanning Electron Microscopy and Fourier Transform-Infrared Spectroscopy both identified bentonites as superior AFM1 binders. The results demonstrated that bentonite, particularly HAFR 3, was the most effective adsorbent and could thus be a promising candidate for the decontamination of AFM1 in milk.

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.

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.

Effect of circuit training with low-carbohydrate diet on body composition, cardiometabolic indices, and exercise capacity in adults with mild to moderate obesity in Saudi Arabia: A randomized control trial.

BACKGROUND: Circuit training that combines aerobic and resisted training is reported to reduce body fat, weight, and improve exercise capacity than performing either type of exercise independently. There is no study evaluating the combined effect of circuit training exercise (CTE) and dietary intervention (low-carbohydrate [LC] diet) among young males with obesity. METHODS: A randomized control trial was conducted to explore the effects of a combined program of CTE and a LC diet for adults with mild or moderate obesity. Seventy adults with obesity were allocated randomly into 2 groups. The experimental group (group 1) received circuit training with LC diet intervention, whereas the control (group 2) received only circuit training. The study variables such as exercise capacity, body composition, and cardiometabolic indices were measured at the baseline and the end of 60 days of intervention. RESULTS: The participants of group 1 showed significant improvements in body composition (body weight, body mass index, waist circumference, waist hip circumference, and body fat percentage), exercise capacity (maximal oxygen consumption), and cardiometabolic indices (high-density lipoprotein, low-density lipoprotein, triglycerides, and total cholesterol) with a P < .05 for all the variables, when compared with group 2. CONCLUSIONS: The combined structured CTE with controlled LC diet intervention in obese adults caused significant reduction in body composition and cardiometabolic indices variables and an increase in exercise capacity.

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).

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.

Bayesian and non-Bayesian inference under adaptive type-II progressive censored sample with exponentiated power Lindley distribution.

This paper deals with the statistical inference of the unknown parameters of three-parameter exponentiated power Lindley distribution under adaptive progressive type-II censored samples. The maximum likelihood estimator (MLE) cannot be expressed explicitly, hence approximate MLEs are conducted using the Newton-Raphson method. Bayesian estimation is studied and the Markov Chain Monte Carlo method is used for computing the Bayes estimation. For Bayesian estimation, we consider two loss functions, namely: squared error and linear exponential (LINEX) loss functions, furthermore, we perform asymptotic confidence intervals and the credible intervals for the unknown parameters. A comparison between Bayes estimation and the MLE is observed using simulation analysis and we perform an optimally criterion for some suggested censoring schemes by minimizing bias and mean square error for the point estimation of the parameters. Finally, a real data example is used for the illustration of the goodness of fit for this model.