From Gut to Hormones: Unraveling the Role of Gut Microbiota in (Phyto)Estrogen Modulation in Health and Disease.

The human gut microbiota regulates estrogen metabolism through the "estrobolome," the collection of bacterial genes that encode enzymes like ß-glucuronidases and ß-glucosidases. These enzymes deconjugate and reactivate estrogen, influencing circulating levels. The estrobolome mediates the enterohepatic circulation and bioavailability of estrogen. Alterations in gut microbiota composition and estrobolome function have been associated with estrogen-related diseases like breast cancer, enometrial cancer, and polycystic ovarian syndrome (PCOS). This is likely due to dysregulated estrogen signaling partly contributed by the microbial impacts on estrogen metabolism. Dietary phytoestrogens also undergo bacterial metabolism into active metabolites like equol, which binds estrogen receptors and exhibits higher estrogenic potency than its precursor daidzein. However, the ability to produce equol varies across populations, depending on the presence of specific gut microbes. Characterizing the estrobolome and equol-producing genes across populations can provide microbiome-based biomarkers. Further research is needed to investigate specific components of the estrobolome, phytoestrogen-microbiota interactions, and mechanisms linking dysbiosis to estrogen-related pathology. However, current evidence suggests that the gut microbiota is an integral regulator of estrogen status with clinical relevance to women's health and hormonal disorders.

Identification of quantitative trait loci (QTLs) regulating leaf SPAD value and trichome density in mungbean (Vigna radiata L.) using genotyping-by-sequencing (GBS) approach.

Quantitative trait loci (QTL) mapping is used for the precise localization of genomic regions regulating various traits in plants. Two major QTLs regulating Soil Plant Analysis Development (SPAD) value (qSPAD-7-1) and trichome density (qTric-7-2) in mungbean were identified using recombinant inbred line (RIL) populations (PMR-1×Pusa Baisakhi) on chromosome 7. Functional analysis of QTL region identified 35 candidate genes for SPAD value (16 No) and trichome (19 No) traits. The candidate genes regulating trichome density on the dorsal leaf surface of the mungbean include VRADI07G24840, VRADI07G17780, and VRADI07G15650, which encodes for ZFP6, TFs bHLH DNA-binding superfamily protein, and MYB102, respectively. Also, candidate genes having vital roles in chlorophyll biosynthesis are VRADIO7G29860, VRADIO7G29450, and VRADIO7G28520, which encodes for s-adenosyl-L-methionine, FTSHI1 protein, and CRS2-associated factor, respectively. The findings unfolded the opportunity for the development of customized genotypes having high SPAD value and high trichome density having a possible role in yield and mungbean yellow vein mosaic India virus (MYMIV) resistance in mungbean.

Genome-wide association studies for earliness, MYMIV resistance, and other associated traits in mungbean (Vigna radiata L. Wilczek) using genotyping by sequencing approach.

Yellow mosaic disease (YMD) remains a major constraint in mungbean (Vigna radiata (L.)) production; while short-duration genotypes offer multiple crop cycles per year and help in escaping terminal heat stress, especially during summer cultivation. A comprehensive genotyping by sequencing (GBS)-based genome-wide association studies (GWAS) analysis was conducted using 132 diverse mungbean genotypes for traits like flowering time, YMD resistance, soil plant analysis development (SPAD) value, trichome density, and leaf area. The frequency distribution revealed a wide range of values for all the traits. GBS studies identified 31,953 high-quality single nucleotide polymorphism (SNPs) across all 11 mungbean chromosomes and were used for GWAS. Structure analysis revealed the presence of two genetically distinct populations based on ΔK. The linkage disequilibrium (LD) varied throughout the chromosomes and at r2 = 0.2, the mean LD decay was estimated as 39.59 kb. Two statistical models, mixed linear model (MLM) and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) identified 44 shared SNPs linked with various candidate genes. Notable candidate genes identified include FPA for flowering time (VRADI10G01470; chr. 10), TIR-NBS-LRR for mungbean yellow mosaic India virus (MYMIV) resistance (VRADI09G06940; chr. 9), E3 ubiquitin-protein ligase RIE1 for SPAD value (VRADI07G28100; chr. 11), WRKY family transcription factor for leaf area (VRADI03G06560; chr. 3), and LOB domain-containing protein 21 for trichomes (VRADI06G04290; chr. 6). In-silico validation of candidate genes was done through digital gene expression analysis using Arabidopsis orthologous (compared with Vigna radiata genome). The findings provided valuable insight for marker-assisted breeding aiming for the development of YMD-resistant and early-maturing mungbean varieties.

Does gut brain axis has an impact on Parkinson's disease (PD)?

Parkinson's Disease (PD) is becoming a growing global concern by being the second most prevalent disease next to Alzheimer's Disease (AD). Henceforth new exploration is needed in search of new aspects towards the disease mechanism and origin. Evidence from recent studies has clearly stated the role of Gut Microbiota (GM) in the maintenance of the brain and as a root cause of various diseases and disorders including other neurological conditions. In the case of PD, with an unknown etiology, the GM is said to have a larger impact on the disease pathophysiology. Although GM and its metabolites are crucial for maintaining the normal physiology of the host, it is an undeniable fact that there is an influence of GM in the pathophysiology of PD. As such the Enteroendocrine Cells (EECs) in the epithelium of the intestine are one of the significant regulators of the gut-brain axis and act as a communication mediator between the gut and the brain. The communication is established via the molecules of neuroendocrine which are said to have a crucial part in neurological diseases such as AD, PD, and other psychiatry-related disorders. This review is focused on understanding the proper role of GM and EECs in PD. Here, we also focus on some of the metabolites and compounds that can interact with the PD genes causing various dysfunctions in the cell and facilitating the disease conditions using bioinformatical tools. Various mechanisms concerning EECs and PD, their identification, the latest studies, and available current therapies have also been discussed.

Corrigendum: Yellow Mosaic Disease (YMD) of Mungbean (Vigna radiata (L.) Wilczek): Current Status and Management Opportunities.

[This corrects the article DOI: 10.3389/fpls.2020.00918.].

Yellow Mosaic Disease (YMD) of Mungbean (Vigna radiata (L.) Wilczek): Current Status and Management Opportunities.

Globally, yellow mosaic disease (YMD) remains a major constraint of mungbean production, and management of this deadly disease is still the biggest challenge. Thus, finding ways to manage YMD including development of varieties possessing resistance against mungbean yellow mosaic virus (MYMV) and mungbean yellow mosaic India virus (MYMIV) is a research priority for mungbean crop. Characterization of YMD resistance using various advanced molecular and biochemical approaches during plant-virus interactions has unfolded a comprehensive network of pathogen survival, disease severity, and the response of plants to pathogen attack, including mechanisms of YMD resistance in mungbean. The biggest challenge in YMD management is the effective utilization of an array of information gained so far, in an integrated manner for the development of genotypes having durable resistance against yellow mosaic virus (YMV) infection. In this backdrop, this review summarizes the role of various begomoviruses, its genomic components, and vector whiteflies, including cryptic species in the YMD expression. Also, information about the genetics of YMD in both mungbean and blackgram crops is comprehensively presented, as both the species are crossable, and same viral strains are also found affecting these crops. Also, implications of various management strategies including the use of resistance sources, the primary source of inoculums and vector management, wide-hybridization, mutation breeding, marker-assisted selection (MAS), and pathogen-derived resistance (PDR) are thoroughly discussed. Finally, the prospects of employing various powerful emerging tools like translational genomics, and gene editing using CRISPR/Cas9 are also highlighted to complete the YMD management perspective in mungbean.