**3. Discussion and Future Prospects**

Increasing advancement in research on neurodegenerative diseases indicates that these pathologies are very complex processes with often forgotten microbiome- and immunerelated components. The publications and studies mentioned in this review present evidence for the relationship between neurodegenerative diseases, mainly HD, and the intestinal microbiome. So far, the focus has been on understanding the pathology of the disease based on molecular biomarkers, which hopefully could effectively contribute to the development of future therapies [97]. Recent studies on the effect of the intestinal microbiome and its metabolites also pave the way for new branches in the field of HD. Microbial metabolites have the potential to modulate the pathogenesis of HD. SCFAs can influence the immune system and ameliorate inflammation, both in the CNS and the peripheral nerves. Studies on mouse models that were supplemented with sodium butyrate showed a beneficial effect on their motor skills, mitochondrial and transcriptional dysfunction [28,29]. This suggests that therapeutic interventions promoting butyrate production by patients' microbiota have the potential to ameliorate disease symptoms. However, there are still many open questions regarding the bacteria inhabiting healthy and diseased digestive systems. The results of research involving microbiota carried out so far are still not entirely conclusive due to microbiome complexity and numerous contributing factors. Therefore, there is still a long way to go to fully understand the communication in the gut—brain axis, including in pathological conditions like HD.

Moreover, the microbiome results are not always consistent. The large amount of data generated in experiments is hard to compile, and one needs to be attentive when analyzing and drawing conclusions based on it. Insufficiently known taxonomies of species inhabiting the intestines and inaccurate and non-standardized terminology related to the subject of the microbiome are often misleading and generate mistakes when classifying individual bacteria into appropriate classes, groups, or families. Furthermore, the choice of mouse model, its strain, sex, or age is essential in the studies concerning the microbiome. For example, two studies in a mouse model of HD confirm an increase in *Bacteriodetes* and a decrease in *Firmicutes* [88,90]. The first one was carried out on the R6/1 line, and the second on the R6/2 mouse model. Additionally, the study conducted on another HD model contradicts these results. At 3 months of age, BACHD mice exhibit the opposite trend of increased *Firmicutes* and decreased *Bacteriodetes*. Interestingly, re-analysis on 6-month-old mice showed the opposite, which rather confirms the results of the previous two studies [93]. The presented results display certain consistency, despite the use of different models, but only when using older mice from the BACHD line. It can be assumed that the microbiome diversity changes in the same fashion as organisms mature. It is also worth noting that some of the results show statistical significance only in the group of males, both in animal and human studies [88,95]. On the other hand, only female mice showed a positive reaction to the transplant of a healthy microbiome [87]. These findings also indicate the effect of female hormones on microbiome composition. In the study conducted by the Hannan group, the body weight of WT and HD mice differed significantly, as HD mice lost weight with age. This could be due to differences in the composition of the microbiome and the level of food absorption, which is inversely proportional to body weight [98]. Increased thirst was also noted, possibly due to xerostomia, which both patients and HD mice suffer from, or hypothalamic degeneration, which is associated with increased thirst [99]. Interestingly, increased water intake by the animals did not change the water content of the feces. The reason could be the microbiological environment in the intestines. This result may suggest a very precise regulation of water absorption [100]. Some of the cited studies indicate an increased level of alpha diversity compared to other groups [88,91,96]. A higher level of this index is believed to indicate a healthier and more resilient microbial environment [101]. Studies in other models of neurodegenerative diseases, such as AD and PD, have also linked movement deficits with lower levels of alpha diversity in patients compared to controls [102–104]. Human HD studies have shown lower [95] and higher [96] values of alpha diversity in CAG repeat overexpressors compared to healthy controls. Recent extensive meta-analyses have found no associations between alpha diversity and neurological disorders, particularly in PD and MS [105]. Interestingly, there are also studies that prove that increased diversity does not always correlate with better patient conditions [106,107]. According to Coyte et al., a decrease in the stability

of the microbiome environment may also result in higher alpha diversity [108]. Research also shows that the alpha level of diversity may also be related to diet, body weight, and gastrointestinal physiology [109].

Another essential factor that should be considered when conducting experiments related to the microbiome and neurodegeneration in humans is the environment. Each of the mentioned experiments was performed under slightly different conditions, especially in humans. Environmental changes are noticeable among the participants of a project, despite the fact that the control group was chosen from the close family members of the patients [96]. The composition of the gut microbiome is also influenced by various factors, such as physical activity [110,111]. The difference in this respect between healthy and disease-affected individuals certainly existed during the project. This proves how difficult it is to compose appropriate groups in experiments assuming the study of the microbiome. In addition to differences in physical activity, each person has different nutritional preferences, which certainly influence the composition of the microbiome and are a burden for bioinformaticians to be leveled in statistical analyses [112,113]. In addition, the quoted research was performed on distinct continents, which results in diametrically different environmental conditions such as climate or local food accessibility that affect diet [114]. Sampling for testing is an extremely important point in the whole experiment. Typically, the collected samples are snap frozen to eliminate the adverse effect of air on aerophobic bacteria in the samples. In both of these experiments [95,96], the samples were obtained in a different way, and the patients were responsible for collecting and delivering the samples to the laboratory, which might have affected the composition of the microbiome in the samples. Conducting research on mouse models can be better standardized and reproducible by applying a specific sampling and storage protocol. Collection should be as quick as possible, with a caution not to contaminate the sample with other DNA or with bacteria residing on fur.

Animal experiments also have the advantage of breeding in more standardized conditions, typically SPF, though the microbiome may vary slightly. On the other hand, the place of origin of the animal, lineage, strain, age, disease model, maintenance method, or even environmental enrichment in the cages are all aspects that should be considered when studying the microbiome. Mice are also known to be coprophages to reabsorb essential nutrients such as vitamins; thus, when housing a few mice in the same cage, one should consider the natural microbiome transfer between them and dodge the "cage effect" [91]. Additionally, all existing mouse models of HD differ from each other by the dynamics of disease progression or the degree of interference in the animal's genome [115,116]. At this point, it is worth considering at what age and on what model such tests should be carried out. The studies we quoted were based on various models and were carried out on animals of different ages. As with human studies, comparing results obtained in mouse experiments is equally problematic, although the experiments were more standardized.

Animal models of HD provide us with tools to study the mammalian microbiome and its possible implications for disease progression in a highly controlled environment. Most studies presented in this review used R6/1 or R6/2 models, which are well established for HD; however, they are characterized by early onset, rapid disease progression, and premature death. As previously mentioned, in humans, the symptoms of HD occur well into adulthood, at 35–40 years of age, with continuous progression for the next 10–15 years, which points to a need for other models with slower disease progression, such as YAC128, Hu128/21, or BACHD. Aging is also closely linked to changes in microbiome composition, so these models might be more applicable for long term studies of changes in microbiome composition and possible dietary or therapeutic interventions that might better translate to humans. There was only one study utilizing the BACHD model that showed pronounced differences in microbiota composition at different ages [93]. Long-term studies on both pre- and post-symptomatic animals are important for a better understanding of the microbiome and HD pathology, but they also have the unique ability to find the most suitable timepoints for therapeutic interventions. Using these models might also be relevant in fecal microbiota transfer studies, as the R6/2 model used by Gubert and colleagues has shown that the engraftment was unsuccessful in male mice [87]. Using models with slower disease progression might provide the researchers with a variety of timepoints and disease phenotypes to choose from, which might impact the success of the microbiota transplant.

There is also a fruit fly model of HD (FL-HD) that exhibits similar symptoms such as motor deficits, mHTT aggregates, disrupted gene expression, and dysbiosis in the gut. The *Drosophila* microbiome is, however, much less complex than the mammalian microbiome, which can help in analyzing single species and their impact on dysbiosis. A study conducted on female fruit flies has found that gut colonization by *E. coli* worsened the HD symptoms, as there was an increase in aggregate buildup and earlier death. A therapy using crocin was used in *Drosophila* with beneficial effects. This therapy ameliorated motor deficits and extended the lifespan, but what is more interesting is that it provided resistance to *E. coli* colonization and had positive effects on the microbiome [117]. Crocin is a carotenoid exhibiting anti-inflammatory, antioxidant, and neuroprotective properties. Crocin, or its major byproduct, crocetin, has been suggested to act in the gut and modulate the gut microbiome. Another study has shown that oral administration of crocin was beneficial for cerebral ischemic/reperfusion (I/R) injuries in rats, while the intravenous route of administration was not. It suggests that the therapeutic effects are mediated through the gut microbiota [118]. As such, crocin might provide beneficial effects in HD, ameliorating inflammation, oxidative stress, and gut dysbiosis, which makes it a promising target for further studies.

Interestingly, a few studies have found that prion infection can also lead to dysbiosis and significant changes in microbial metabolites. The microbial richness (alpha diversity) was higher in healthy controls, and the microbiome structure was significantly different between healthy and infected groups. Prion diseases are linked to neuroinflammation, and while the mechanism underlying the gut dysbiosis in this type of disease is not well understood, it is nonetheless an interesting topic to further examine the relationship between the gut and the brain [119,120].

According to the latest research, taking pro- and pre-biotics can help with nervous system diseases. So far, the effect of taking these substances on the progression of HD has not been proven, but it has been studied in other neurodegenerative diseases. There are several studies confirming the psychophysiological effect of prebiotics on the body. Chitosan oligosaccharide (COS) has been shown to have a positive effect on cognitive deficits in a rat model of AD by reducing oxidative stress and neuroinflammatory responses [121]. In studies on amyotrophic lateral sclerosis, it was proven that the use of galactooligosaccharides (GOS) reduced the activation of microglia and astrocytes and caused less death of motor neurons [122]. Other studies conducted in a mouse model of PD showed that long-term intake of probiotics resulted in a neuroprotective effect on dopaminergic neurons, effectively counteracting motor disorders in animals [123]. Unfortunately, few similar studies have been conducted in humans so far. The examples of research cited above prove that the use of products containing both pro- and prebiotic bacterial strains could act as an effective supporting therapy in the treatment of neurodegenerative diseases. Perhaps in the future, effective and personalized drugs based solely on these compounds will be developed.

**Author Contributions:** Conceptualization, L.P.; writing—original draft preparation, L.P., A.K., D.W. and J.O.M.; writing—review and editing, L.P., A.K., D.W. and J.O.M.; visualization, A.K.; supervision, L.P.; funding acquisition, L.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** We would like to thank Anna Zimniewicz for her support in gathering material for this review article.

**Conflicts of Interest:** The authors declare no conflict of interest.
