The Gut-Eye Axis: Lessons Learned from Murine Models

Gut microbiome and diabetic retinopathy

During the last decades, the incidence of diabetes and a variety of complications such as diabetic retinopathy (DR) and cardiovascular diseases have been increased exponentially. Gut bacterial composition -microbiota - has been associated with the pathobiology of many inflammatory and metabolic disorders such as diabetes. Gut microbiota plays a crucial role in preserving the metabolic and immune homeostasis, protecting against pathogens and regulating host immunity; however, gut microbiome ecosystem can be altered by lifestyle, cigarette smoking, dietary patterns, and oxidative stress.Herein, we present a hypothesis on the potential complex association between gut microbiota and DR as one of the microvascular complications of diabetes.

Gut Microbiome in Retina Health: The Crucial Role of the Gut-Retina Axis

The term microbiome means not only a complex ecosystem of microbial species that colonize our body but also their genome and the surrounding environment in which they live. Recent studies support the existence of a gut-retina axis involved in the pathogenesis of several chronic progressive ocular diseases, including age-related macular disorders. This review aims to underline the importance of the gut microbiome in relation to ocular health. After briefly introducing the characteristics of the gut microbiome in terms of composition and functions, the role of gut microbiome dysbiosis, in the development or progression of retinal diseases, is highlighted, focusing on the relationship between gut microbiome composition and retinal health based on the recently investigated gut-retina axis.

A Review of the Impact of Alterations in Gut Microbiome on the Immunopathogenesis of Ocular Diseases

Recent studies have highlighted the association between ocular diseases and microbiota profiles of the host intestinal tract and oral cavity. There is mounting evidence supporting the existence of a 'gut-eye axis', whereby changes in gut microbiome alter host immunity, with consequential implications for ocular health and disease. In this review, we examined recent published findings on the association between gut microbiome and ocular morbidity, based on 25 original articles published between 2011 to 2020. The review included both clinical and in vivo animal studies, with particular focus on the influence of the microbiome on host immunity and metabolism. Significant associations between altered intestinal microbiome and specific ocular diseases and pathological processes, including Behçet's syndrome, autoimmune uveitis, age-related macular degeneration, choroidal neovascularization, bacterial keratitis, and Sjögren-like lacrimal keratoconjunctivitis have been demonstrated. Furthermore, alterations in the gut microbiome resulted in quantifiable changes in the host immune response, suggesting immunopathogenesis as the basis for the link between intestinal dysbiosis and ocular disease. We also examined and compared different techniques used in the identification and quantification of gut microorganisms. With our enhanced understanding of the potential role of gut commensals in ophthalmic disease, the stage is set for further studies on the underlying mechanisms linking the gut microbiome, the host immune response, and the pathogenesis of ophthalmic disease.

Alterations of the Gut Microbiome and Metabolome in Patients With Proliferative Diabetic Retinopathy

Diabetic retinopathy (DR) has been reported to associate with gut microbiota alterations in murine models and thus “gut-retina-axis” has been proposed. However, the role of gut microbiome and the associated metabolism in DR patients still need to be elucidated. In this study, we collected fecal samples from 45 patients with proliferative diabetic retinopathy (PDR) and 90 matched diabetic patients (1:2 according to age, sex, and duration of diabetes) without DR (NDR) and performed 16S rRNA gene sequencing and untargeted metabolomics. We observed significantly lower bacterial diversity in the PDR group than that in the NDR group. Differential gut bacterial composition was also found, with significant depletion of 22 families (e.g., Coriobacteriaceae, Veillonellaceae, and Streptococcaceae) and enrichment of two families (Burkholderiaceae and Burkholderiales_unclassified) in the PDR group as compared with the NDR group. There were significantly different fecal metabolic features, which were enriched in metabolic pathways such as arachidonic acid and microbial metabolism, between the two groups. Among 36 coabundance metabolite clusters, 11 were positively/negatively contributed to PDR using logistic regression analysis. Fifteen gut microbial families were significantly correlated with the 11 metabolite clusters. Furthermore, a fecal metabolite-based classifier was constructed to distinguish PDR patients from NDR patients accurately. In conclusion, PDR is associated with reduced diversity and altered composition of gut microbiota and specific microbe-metabolite interplay. Our findings help to better understand the disease pathogenesis and provide novel diagnostic and therapeutic targets for PDR.

Holistic perspective of the role of gut microbes in diabetes mellitus and its management

The gut microbiota (GM) plays a role in the development and progression of type 1 and type 2 diabetes mellitus (DM) and its complications. Gut dysbiosis contributes to the pathogenesis of DM. The GM has been shown to influence the efficacy of different antidiabetic medications. Intake of gut biotics, like prebiotics, probiotics and synbiotics, can improve the glucose control as well as the metabolic profile associated with DM. There is some preliminary evidence that it might even help with the cardiovascular, ophthalmic, nervous, and renal complications of DM and even contribute to the prevention of DM. More large-scale research studies are needed before wide spread use of gut biotics in clinical practice as an adjuvant therapy to the current management of DM.

Contribution of the Commensal Microflora to the Immunological Homeostasis and the Importance of Immune-Related Drug Development for Clinical Applications

Not long ago, self-reactive immune activity was considered as pathological trait. A paradigm shift has now led to the recognition of autoimmune processes as part of natural maintenance of molecular homeostasis. The immune system is assigned further roles beneath the defense against pathogenic organisms. Regarding the humoral immune system, the investigation of natural autoantibodies that are frequently found in healthy individuals has led to further hypotheses involving natural autoimmunity in other processes as the clearing of cellular debris or decrease in inflammatory processes. However, their role and origin have not been entirely clarified, but accumulating evidence links their formation to immune reactions against the gut microbiome. Antibodies targeting highly conserved proteins of the commensal microflora are suggested to show self-reactive properties, following the paradigm of the molecular mimicry. Here, we discuss recent findings, which demonstrate potential links of the commensal microflora to the immunological homeostasis and highlight the possible implications for various diseases. Furthermore, specific components of the immune system, especially antibodies, have become a focus of attention for the medical management of various diseases and provide attractive treatment options in the future. Nevertheless, the development and optimization of such macromolecules still represents a very time-consuming task, shifting the need to more medical agents with simple structural properties and low manufacturing costs. Synthesizing only the biologically active sites of antibodies has become of great interest for the pharmaceutical industry and offers a wide range of therapeutic application areas as it will be discussed in the present review article.

Association Between Gut Microbial Abundance and Sight-Threatening Diabetic Retinopathy

Purpose

To study the association between gut microbial abundance and sight-threatening diabetic retinopathy among patients with a history of type 2 diabetes mellitus.

Methods

An observational case-control study was performed using a sample population of diabetics referred to a tertiary eye institute. Sample subjects were identified as cases if they were diagnosed with sight-threatening diabetic retinopathy and controls if they were not but had at least a 10-year history of diabetes. Fecal swabs for all patients were collected for enumeration and identification of sequenced gut microbes. Statistical analyses were performed to associate the clinically relevant Bacteroidetes to Firmicutes relative abundance ratio (B/F ratio) with sight-threatening diabetic retinopathy and an optimal cutoff value for the ratio was identified using Youden's J statistics.

Results

A sample size of 58 diabetic patients was selected (37 cases, 21 controls). No statistically significant difference in the relative abundance among the predominant phyla between the groups were found. In our univariate analysis, the B/F ratio was elevated in cases compared to controls (cases, 1.45; controls, 0.94; P = 0.049). However, this statistically significant difference was not seen in our multivariate regression model. Optimal cutoff value of 1.05 for the B/F ratio was identified, and significant clustering of cases above this value was noted in beta diversity plotting.

Conclusions

No difference in gut microbial abundance for any particular phylum was noted between the control and diseased population. Increased gut microbial B/F ratio can be a potential biomarker for the development of sight-threatening diabetic retinopathy among type 2 diabetic patients.

Profiling of Diagnostic Information of and Latent Susceptibility to Bacterial Keratitis From the Perspective of Ocular Bacterial Microbiota

The ocular surface possesses its own bacterial microbiota. Once given a chance, opportunistic pathogens within ocular microbiota may lead to corneal infection like bacterial keratitis (BK). To reveal the possible factor that makes people vulnerable to BK from the perspective of ocular bacterial microbiota, as well as to compare diagnostic information provided by high-throughput 16S rDNA sequencing and bacterial culture, 20 patients with BK and 42 healthy volunteers were included. Conjunctival swabs and corneal scrapings collected from the diseased eyes of BK patients were subjected for both high-throughput 16S rDNA sequencing and bacterial culture. Conjunctival swabs collected from the normal eyes of BK patients and healthy volunteers were sent only for sequencing. For identifying the pathogens causing BK, high-throughput 16S rDNA sequencing presented a higher positive rate than bacterial culture (98.04% vs. 17.50%), with 92.11% reaching the genus level (including 10.53% down to the species level). However, none of the sequencing results was consistent with the cultural results. The sequencing technique appears to challenge culture, and could be a complement for pathogen identification. Moreover, compared to the eyes of healthy subjects, the ocular microbiota of three sample groups from BK patients contained significantly less Actinobacteria and Corynebacteria (determinate beneficial symbiotic bacteria), but significantly more Gammaproteobacteria, Pseudomonas, Bacteroides, and Escherichia-Shigella (common ocular pathogenic bacteria). Therefore, it is speculated that the imbalance of protective and aggressive bacteria in the ocular microbiota of healthy people may trigger susceptibility to BK. Based on this speculation, it seems promising to prevent and treat infectious oculopathy through regulating ocular microbiota.

Rebuilding Microbiome for Mitigating Traumatic Brain Injury: Importance of Restructuring the Gut-Microbiome-Brain Axis

Traumatic brain injury (TBI) is a damage to the brain from an external force that results in temporary or permanent impairment in brain functions. Unfortunately, not many treatment options are available to TBI patients. Therefore, knowledge of the complex interplay between gut microbiome (GM) and brain health may shed novel insights as it is a rapidly expanding field of research around the world. Recent studies show that GM plays important roles in shaping neurogenerative processes such as blood-brain-barrier (BBB), myelination, neurogenesis, and microglial maturation. In addition, GM is also known to modulate many aspects of neurological behavior and cognition; however, not much is known about the role of GM in brain injuries. Since GM has been shown to improve cellular and molecular functions via mitigating TBI-induced pathologies such as BBB permeability, neuroinflammation, astroglia activation, and mitochondrial dysfunction, herein we discuss how a dysbiotic gut environment, which in fact, contributes to central nervous system (CNS) disorders during brain injury and how to potentially ward off these harmful effects. We further opine that a better understanding of GM-brain (GMB) axis could help assist in designing better treatment and management strategies in future for the patients who are faced with limited options.

The Role of Inflammation and Infection in Age-Related Neurodegenerative Diseases: Lessons From Bacterial Meningitis Applied to Alzheimer Disease and Age-Related Macular Degeneration

Age-related neurodegenerative diseases, such as Alzheimer disease (AD) and age-related macular degeneration (AMD), are multifactorial and have diverse genetic and environmental risk factors. Despite the complex nature of the diseases, there is long-standing, and growing, evidence linking microbial infection to the development of AD dementia, which we summarize in this article. Also, we highlight emerging research findings that support a role for parainfection in the pathophysiology of AMD, a disease of the neurosensory retina that has been shown to share risk factors and pathological features with AD. Acute neurological infections, such as Bacterial Meningitis (BM), trigger inflammatory events that permanently change how the brain functions, leading to lasting cognitive impairment. Neuroinflammation likewise is a known pathological event that occurs in the early stages of chronic age-related neurodegenerative diseases AD and AMD and might be triggered as a parainfectious event. To date, at least 16 microbial pathogens have been linked to the development of AD; on the other hand, investigation of a microbe-AMD relationship is in its infancy. This mini-review article provides a synthesis of existing evidence indicating a contribution of parainfection in the aetiology of AD and of emerging findings that support a similar process in AMD. Subsequently, it describes the major immunopathological mechanisms that are common to BM and AD/AMD. Together, this evidence leads to our proposal that both AD and AMD may have an infectious aetiology that operates through a dysregulated inflammatory response, leading to deleterious outcomes. Last, it draws fresh insights from the existing literature about potential therapeutic options for BM that might alleviate neurological disruption associated with infections, and which could, by extension, be explored in the context of AD and AMD.

The Role of the Microbiome in Age-Related Macular Degeneration: A Review of the Literature

BACKGROUND

Age-related macular degeneration (AMD) is a progressive, multifactorial, degenerative disease and the leading cause of severe visual loss in the elderly population. The exact pathogenesis of AMD remains elusive, being the combination of genetic, environmental, metabolic, and functional processes. A better understanding of the disease's pathophysiology can lead to new treatment targets. The human microbiome seems to be a potential therapeutic pathway for AMD, as it has been recently proven to play a role in its pathogenesis.

SUMMARY

This review sheds light on the association between the microbiome and AMD. Key Messages: The current evidence based on the existing literature shows that there are differences in taxonomical and functional profiles in the human microbiome between patients with AMD and controls, suggesting that the microbiome is implicated in AMD onset and progression, being a link between AMD and nutrition/diet. Additionally, specific bacterial classes have been proposed as potential biomarkers for AMD diagnosis. Further randomized clinical studies with a large sample are needed to elucidate the role of the microbiome in AMD and to draw more solid conclusions.

Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies

A tiller number is the key determinant of rice plant architecture and panicle number and consequently controls grain yield. Thus, it is necessary to optimize the tiller number to achieve the maximum yield in rice. However, comprehensive analyses of the genetic basis of the tiller number, considering the development stage, tiller type, and related traits, are lacking. In this study, we sequence 219 Korean rice accessions and construct a high-quality single nucleotide polymorphism (SNP) dataset. We also evaluate the tiller number at different development stages and heading traits involved in phase transitions. By genome-wide association studies (GWASs), we detected 20 significant association signals for all traits. Five signals were detected in genomic regions near known candidate genes. Most of the candidate genes were involved in the phase transition from vegetative to reproductive growth. In particular, HD1 was simultaneously associated with the productive tiller ratio and heading date, indicating that the photoperiodic heading gene directly controls the productive tiller ratio. Multiple linear regression models of lead SNPs showed coefficients of determination (R²) of 0.49, 0.22, and 0.41 for the tiller number at the maximum tillering stage, productive tiller number, and productive tiller ratio, respectively. Furthermore, the model was validated using independent japonica rice collections, implying that the lead SNPs included in the linear regression model were generally applicable to the tiller number prediction. We revealed the genetic basis of the tiller number in rice plants during growth, By GWASs, and formulated a prediction model by linear regression. Our results improve our understanding of tillering in rice plants and provide a basis for breeding high-yield rice varieties with the optimum the tiller number.