Precision Medicine Goes Microscopic: Engineering the Microbiome to Improve Drug Outcomes

Microbiome Integrity Enhances the Efficacy and Safety of Anticancer Drug

The intricate relationship between anticancer drugs and the gut microbiome influences cancer treatment outcomes. This review paper focuses on the role of microbiome integrity in enhancing the efficacy and safety of anticancer drug therapy, emphasizing the pharmacokinetic interactions between anticancer drugs and the gut microbiota. It explores how disruptions to microbiome composition, or dysbiosis, can alter drug metabolism, immune responses, and treatment side effects. By examining the mechanisms of microbiome disruption caused by anticancer drugs, this paper highlights specific case studies of drugs like cyclophosphamide, 5-fluorouracil, and irinotecan, and their impact on microbial diversity and clinical outcomes. The review also discusses microbiome-targeted strategies, including prebiotics, probiotics, postbiotics, and fecal microbiota transplantation (FMT), as promising interventions to enhance cancer treatment. Furthermore, the potential of microbiome profiling in personalizing therapy and integrating these interventions into clinical practice is explored. Finally, this paper proposes future research directions, including developing novel biomarkers and a deeper comprehension of drug-microbiome interactions, to respond to current gaps in knowledge and improve patient outcomes in cancer care.

Multi-omics joint analysis reveals the mechanism underlying Chinese herbal Yougui Pill in the treatment of knee osteoarthritis

ETHNOPHARMACOLOGICAL RELEVANCE

Yougui Pill (YGP), originating from Jingyue Quanshu, comprises 10 traditional Chinese medicines (TCMs). This classic prescription is renowned for its ability to tonify the kidney, warm the kidney, promote yang, warm the interior, and dispel cold. YGP has proven effective in treating degenerative knee arthritis, osteoporosis, delayed fracture healing, and other orthopedic conditions, making it a widely used clinical prescription for knee osteoarthritis (KOA).

AIM OF THE STUDY

Although YGP is commonly used in clinical practice, its pharmacodynamic material basis and anti-arthritis mechanisms remain unclear. This study aims to comprehensively analyze the chemical constituents of YGP and elucidate its anti-arthritis mechanisms.

MATERIALS AND METHODS

Ultra-high performance liquid chromatography coupled with electrospray ionization-triple quadrupole-linear ion trap mass spectrometry(ESI-Q TRAP-MS/MS) was used to identify the chemical constituents of YGP. The Hulth method was utilized to establish KOA rat model, and pathological examinations were performed to assess the anti-arthritis effects of YGP. Integrated metabolomics and transcriptomics analyses were conducted to explore the anti-arthritis mechanisms of YGP. Key targets were confirmed via immunohistochemistry.

RESULTS

A total of 1981 chemical components were identified in YGP, predominantly phenolic acids and flavonoids. Compared with the model group, 422 differentially expressed metabolites and 214 differentially expressed genes were identified, primarily involving the MAPK signaling pathway, FoxO signaling pathway, and PI3K-Akt pathway. YGP exerted an anti-osteoarthritis effect by inhibiting the excessive activation of the EGFR/ERT/FOS signaling pathway.

CONCLUSIONS

TCM offers significant advantages in the treatment of KOA, addressing the shortcomings of current clinical medications. YGP displayed exceptional pharmacodynamic effects. This study elucidated its pharmacodynamic material basis and anti-osteoarthritis mechanisms, providing substantial support for its clinical application and the development of related drugs.

Discovering microbiota functions via chemical probe incorporation for targeted sequencing

Our microbiota plays crucial roles in immune development and homeostasis and has been implicated in virtually all major diseases of the 21st century. Nevertheless, our understanding of the exact microbial functions that underlie these correlations remains extremely limited, due in large part to the difficulty of profiling cellular activities within non-model organisms and complex communities. Over the past decade, new flow cytometric approaches have been developed to distinguish specific microbial populations based on their interactions with metabolite analogs, modified biomolecules, and reactive compounds. By selecting and separating active microbes via fluorescence-activated cell sorting, PRobe INcorporation for Targeted sequencing (PRINT-seq) has inspired innovative approaches to identify and characterize functional members of our microbiota. Here, we provide a broad overview of this evolving technology and summarize how this method has been recently employed as a diagnostic fingerprint for diverse microbial activities.

Pharma[e]cology: How the Gut Microbiome Contributes to Variations in Drug Response

Drugs represent our first, and sometimes last, line of defense for many diseases, yet despite decades of research we still do not fully understand why a given drug works in one patient and fails in the next. The human gut microbiome is one of the missing puzzle pieces, due to its ability to parallel and extend host pathways for drug metabolism, along with more complex host-microbiome interactions. Herein, we focus on the well-established links between the gut microbiome and drugs for heart disease and cancer, plus emerging data on neurological disease. We highlight the interdisciplinary methods that are available and how they can be used to address major remaining knowledge gaps, including the consequences of microbial drug metabolism for treatment outcomes. Continued progress in this area promises fundamental biological insights into humans and their associated microbial communities and strategies for leveraging the microbiome to improve the practice of medicine.

Next-Generation Probiotics and Chronic Diseases: A Review of Current Research and Future Directions

The burgeoning field of microbiome research has profoundly reshaped our comprehension of human health, particularly highlighting the potential of probiotics and fecal microbiota transplantation (FMT) as therapeutic interventions. While the benefits of traditional probiotics are well-recognized, the efficacy and mechanisms remain ambiguous, and FMT's long-term effects are still being investigated. Recent advancements in high-throughput sequencing have identified gut microbes with significant health benefits, paving the way for next-generation probiotics (NGPs). These NGPs, engineered through synthetic biology and bioinformatics, are designed to address specific disease states with enhanced stability and viability. This review synthesizes current research on NGP stability, challenges in delivery, and their applications in preventing and treating chronic diseases such as diabetes, obesity, and cardiovascular diseases. We explore the physiological characteristics, safety profiles, and mechanisms of action of various NGP strains while also addressing the challenges and opportunities presented by their integration into clinical practice. The potential of NGPs to revolutionize microbiome-based therapies and improve clinical outcomes is immense, underscoring the need for further research to optimize their efficacy and ensure their safety.

Teosinte populations exhibit weak local adaptation to their rhizosphere biota despite strong effects of biota source on teosinte fitness and traits

While biotic interactions often impose selection, species and populations vary in whether they are locally adapted to biotic interactions. Evolutionary theory predicts that environmental conditions drive this variable local adaptation by altering the fitness impacts of species interactions. To investigate the influence of an environmental gradient on adaptation between a plant and its associated rhizosphere biota, we cross-combined teosinte (Zea mays ssp. mexicana) and rhizosphere biota collected across a gradient of decreasing temperature, precipitation, and nutrients in a greenhouse common garden experiment. We measured both fitness and phenotypes expected to be influenced by biota, including concentrations of nutrients in leaves. Independent, main effects of teosinte and biota source explained most variation in teosinte fitness and traits. For example, biota from warmer sites provided population-independent fitness benefits across teosinte hosts. Effects of biota that depended on teosinte genotype were often not specific to their local hosts, and most traits had similar relationships to fitness across biota treatments. However, we found weak patterns of local adaptation between teosinte and biota from colder sites, suggesting environmental gradients may alter the importance of local adaptation in teosinte-biota interactions, as evolutionary theory predicts.

A systematic framework for understanding the microbiome in human health and disease: from basic principles to clinical translation

The human microbiome is a complex and dynamic system that plays important roles in human health and disease. However, there remain limitations and theoretical gaps in our current understanding of the intricate relationship between microbes and humans. In this narrative review, we integrate the knowledge and insights from various fields, including anatomy, physiology, immunology, histology, genetics, and evolution, to propose a systematic framework. It introduces key concepts such as the 'innate and adaptive genomes', which enhance genetic and evolutionary comprehension of the human genome. The 'germ-free syndrome' challenges the traditional 'microbes as pathogens' view, advocating for the necessity of microbes for health. The 'slave tissue' concept underscores the symbiotic intricacies between human tissues and their microbial counterparts, highlighting the dynamic health implications of microbial interactions. 'Acquired microbial immunity' positions the microbiome as an adjunct to human immune systems, providing a rationale for probiotic therapies and prudent antibiotic use. The 'homeostatic reprogramming hypothesis' integrates the microbiome into the internal environment theory, potentially explaining the change in homeostatic indicators post-industrialization. The 'cell-microbe co-ecology model' elucidates the symbiotic regulation affecting cellular balance, while the 'meta-host model' broadens the host definition to include symbiotic microbes. The 'health-illness conversion model' encapsulates the innate and adaptive genomes' interplay and dysbiosis patterns. The aim here is to provide a more focused and coherent understanding of microbiome and highlight future research avenues that could lead to a more effective and efficient healthcare system.

The Gut Microbiota and Diabetes: Research, Translation, and Clinical Applications-2023 Diabetes, Diabetes Care, and Diabetologia Expert Forum

This article summarizes the state of the science on the role of the gut microbiota (GM) in diabetes from a recent international expert forum organized by Diabetes, Diabetes Care, and Diabetologia, which was held at the European Association for the Study of Diabetes 2023 Annual Meeting in Hamburg, Germany. Forum participants included clinicians and basic scientists who are leading investigators in the field of the intestinal microbiome and metabolism. Their conclusions were as follows: 1) the GM may be involved in the pathophysiology of type 2 diabetes, as microbially produced metabolites associate both positively and negatively with the disease, and mechanistic links of GM functions (e.g., genes for butyrate production) with glucose metabolism have recently emerged through the use of Mendelian randomization in humans; 2) the highly individualized nature of the GM poses a major research obstacle, and large cohorts and a deep-sequencing metagenomic approach are required for robust assessments of associations and causation; 3) because single-time point sampling misses intraindividual GM dynamics, future studies with repeated measures within individuals are needed; and 4) much future research will be required to determine the applicability of this expanding knowledge to diabetes diagnosis and treatment, and novel technologies and improved computational tools will be important to achieve this goal.

The gut microbiota and diabetes: research, translation, and clinical applications - 2023 Diabetes, Diabetes Care, and Diabetologia Expert Forum

This article summarises the state of the science on the role of the gut microbiota (GM) in diabetes from a recent international expert forum organised by Diabetes, Diabetes Care, and Diabetologia, which was held at the European Association for the Study of Diabetes 2023 Annual Meeting in Hamburg, Germany. Forum participants included clinicians and basic scientists who are leading investigators in the field of the intestinal microbiome and metabolism. Their conclusions were as follows: (1) the GM may be involved in the pathophysiology of type 2 diabetes, as microbially produced metabolites associate both positively and negatively with the disease, and mechanistic links of GM functions (e.g. genes for butyrate production) with glucose metabolism have recently emerged through the use of Mendelian randomisation in humans; (2) the highly individualised nature of the GM poses a major research obstacle, and large cohorts and a deep-sequencing metagenomic approach are required for robust assessments of associations and causation; (3) because single time point sampling misses intraindividual GM dynamics, future studies with repeated measures within individuals are needed; and (4) much future research will be required to determine the applicability of this expanding knowledge to diabetes diagnosis and treatment, and novel technologies and improved computational tools will be important to achieve this goal.

The Gut Microbiota and Diabetes: Research, Translation, and Clinical Applications-2023 Diabetes, Diabetes Care, and Diabetologia Expert Forum

This article summarizes the state of the science on the role of the gut microbiota (GM) in diabetes from a recent international expert forum organized by Diabetes, Diabetes Care, and Diabetologia, which was held at the European Association for the Study of Diabetes 2023 Annual Meeting in Hamburg, Germany. Forum participants included clinicians and basic scientists who are leading investigators in the field of the intestinal microbiome and metabolism. Their conclusions were as follows: 1) the GM may be involved in the pathophysiology of type 2 diabetes, as microbially produced metabolites associate both positively and negatively with the disease, and mechanistic links of GM functions (e.g., genes for butyrate production) with glucose metabolism have recently emerged through the use of Mendelian randomization in humans; 2) the highly individualized nature of the GM poses a major research obstacle, and large cohorts and a deep-sequencing metagenomic approach are required for robust assessments of associations and causation; 3) because single-time point sampling misses intraindividual GM dynamics, future studies with repeated measures within individuals are needed; and 4) much future research will be required to determine the applicability of this expanding knowledge to diabetes diagnosis and treatment, and novel technologies and improved computational tools will be important to achieve this goal.

Human gut Actinobacteria boost drug absorption by secreting P-glycoprotein ATPase inhibitors

Drug efflux transporters are a major determinant of drug efficacy and toxicity. A canonical example is P-glycoprotein (P-gp), an efflux transporter that controls the intestinal absorption of diverse compounds. Despite a rich literature on the dietary and pharmaceutical compounds that impact P-gp activity, its sensitivity to gut microbial metabolites remains an open question. Surprisingly, we found that the cardiac drug-metabolizing gut Actinobacterium Eggerthella lenta increases drug absorption in mice. Experiments in cell culture revealed that E. lenta produces a soluble factor that post-translationally inhibits P-gp ATPase efflux activity. P-gp inhibition is conserved in the Eggerthellaceae family but absent in other Actinobacteria. Comparative genomics identified genes associated with P-gp inhibition. Finally, activity-guided biochemical fractionation coupled to metabolomics implicated a group of small polar metabolites with P-gp inhibitory activity. These results highlight the importance of considering the broader relevance of the gut microbiome for drug disposition beyond first-pass metabolism.

Analysis of the mechanism of curcumin against osteoarthritis using metabolomics and transcriptomics

Curcumin, a polyphenolic compound derived from the turmeric plant (Curcuma longa), has been extensively studied for its anti-inflammatory and anti-proliferative properties. The safety and efficacy of curcumin have been thoroughly validated. Nevertheless, the underlying mechanism for treating osteoarthritis remains ambiguous. This study aims to reveal the potential mechanism of curcumin in treating osteoarthritis by using metabolomics and transcriptomics. Firstly, we validated the effect of curcumin on inflammatory factors in human articular chondrocytes. Secondly, we explored the cellular metabolism mechanism of curcumin against osteoarthritis using cell metabolomics. Thirdly, we assessed the differences in gene expression of human articular chondrocytes through transcriptomics. Lastly, to evaluate the essential targets and elucidate the potential mechanism underlying the therapeutic effects of curcumin in osteoarthritis, we conducted a screening of the proteins within the shared pathway of metabolomics and transcriptomics. Our results demonstrated that curcumin significantly decreased the levels of inflammatory markers, such as IL-β, IL-6, and TNF-α, in human articular chondrocytes. Cell metabolomics identified 106 differential metabolites, including beta-aminopropionitrile, 3-amino-2-piperidone, pyrrole-2-carboxaldehyde, and various other components. The transcriptomic analysis yielded 1050 differential mRNAs. Enrichment analysis showed that the differential metabolites and mRNAs were significantly enriched in seven pathways, including glycine, serine, and threonine metabolism; pentose and glucuronate interconversions; glycerolipid metabolism; histidine metabolism; mucin-type o-glycan biosynthesis; inositol phosphate metabolism; and cysteine and methionine metabolism. A total of 23 key targets were identified to be involved in these pathways. We speculate that curcumin may alleviate osteoarthritis by targeting key proteins involved in glycine, serine, and threonine metabolism; inhibiting pyruvate production; and modulating glycolysis.

Psycho-Pharmacomicrobiomics: A Systematic Review and Meta-Analysis

BACKGROUND

Understanding the interactions between the gut microbiome and psychotropic medications (psycho-pharmacomicrobiomics) could improve treatment stratification strategies in psychiatry. In this systematic review and meta-analysis, we first explored whether psychotropics modify the gut microbiome; second, we investigated whether the gut microbiome affects the efficacy and tolerability of psychotropics.

METHODS

Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we searched (November 2022) for longitudinal and cross-sectional studies that investigated the effect of psychotropics on the gut microbiome. The primary outcome was the difference in diversity metrics (alpha and beta) before and after treatment with psychotropics (longitudinal studies) and in medicated compared with unmedicated individuals (cross-sectional studies). Secondary outcomes included the association between gut microbiome and efficacy and tolerability outcomes. Random effect meta-analyses were conducted on alpha diversity metrics, while beta diversity metrics were pooled using distance data extracted from graphs. Summary statistics included standardized mean difference and Higgins I2 for alpha diversity metrics and F and R values for beta diversity metrics.

RESULTS

Nineteen studies were included in our synthesis; 12 investigated antipsychotics and 7 investigated antidepressants. Results showed significant changes in alpha (4 studies; standard mean difference: 0.12; 95% CI: 0.01-0.23; p = .04; I2: 14%) and beta (F = 15.59; R2 = 0.05; p < .001) diversity metrics following treatment with antipsychotics and antidepressants, respectively. Altered gut microbiome composition at baseline was associated with tolerability and efficacy outcomes across studies, including response to antidepressants (2 studies; alpha diversity; standard mean difference: 2.45; 95% CI: 0.50-4.40; p < .001, I2: 0%).

CONCLUSIONS

Treatment with psychotropic medications is associated with altered gut microbiome composition, and the gut microbiome may in turn influence the efficacy and tolerability of these medications.

Insects' essential role in understanding and broadening animal medication

Like humans, animals use plants and other materials as medication against parasites. Recent decades have shown that the study of insects can greatly advance our understanding of medication behaviors. The ease of rearing insects under laboratory conditions has enabled controlled experiments to test critical hypotheses, while their spectrum of reproductive strategies and living arrangements - ranging from solitary to eusocial communities - has revealed that medication behaviors can evolve to maximize inclusive fitness through both direct and indirect fitness benefits. Studying insects has also demonstrated in some cases that medication can act through modulation of the host's innate immune system and microbiome. We highlight outstanding questions, focusing on costs and benefits in the context of inclusive host fitness.

Integrating microbiome science and evolutionary medicine into animal health and conservation

Microbiome science has provided groundbreaking insights into human and animal health. Similarly, evolutionary medicine - the incorporation of eco-evolutionary concepts into primarily human medical theory and practice - is increasingly recognised for its novel perspectives on modern diseases. Studies of host-microbe relationships have been expanded beyond humans to include a wide range of animal taxa, adding new facets to our understanding of animal ecology, evolution, behaviour, and health. In this review, we propose that a broader application of evolutionary medicine, combined with microbiome science, can provide valuable and innovative perspectives on animal care and conservation. First, we draw on classic ecological principles, such as alternative stable states, to propose an eco-evolutionary framework for understanding variation in animal microbiomes and their role in animal health and wellbeing. With a focus on mammalian gut microbiomes, we apply this framework to populations of animals under human care, with particular relevance to the many animal species that suffer diseases linked to gut microbial dysfunction (e.g. gut distress and infection, autoimmune disorders, obesity). We discuss diet and microbial landscapes (i.e. the microbes in the animal's external environment), as two factors that are (i) proposed to represent evolutionary mismatches for captive animals, (ii) linked to gut microbiome structure and function, and (iii) potentially best understood from an evolutionary medicine perspective. Keeping within our evolutionary framework, we highlight the potential benefits - and pitfalls - of modern microbial therapies, such as pre- and probiotics, faecal microbiota transplants, and microbial rewilding. We discuss the limited, yet growing, empirical evidence for the use of microbial therapies to modulate animal gut microbiomes beneficially. Interspersed throughout, we propose 12 actionable steps, grounded in evolutionary medicine, that can be applied to practical animal care and management. We encourage that these actionable steps be paired with integration of eco-evolutionary perspectives into our definitions of appropriate animal care standards. The evolutionary perspectives proposed herein may be best appreciated when applied to the broad diversity of species under human care, rather than when solely focused on humans. We urge animal care professionals, veterinarians, nutritionists, scientists, and others to collaborate on these efforts, allowing for simultaneous care of animal patients and the generation of valuable empirical data.

Prediction of Human Microbe-Drug Association based on Layer Attention Graph Convolutional Network

Human microbes are closely associated with a variety of complex diseases and have emerged as drug targets. Identification of microbe-related drugs is becoming a key issue in drug development and precision medicine. It can also provide guidance for solving the increasingly serious problem of drug resistance enhancement in viruses.

METHODS

In this paper, we have proposed a novel model of layer attention graph convolutional network for microbe-drug association prediction. First, multiple biological data have been integrated into a heterogeneous network. Then, the heterogeneous network has been incorporated into a graph convolutional network to determine the embedded microbe and drug. Finally, the microbe-drug association scores have been obtained by decoding the embedding of microbe and drug based on the layer attention mechanism.

RESULTS

To evaluate the performance of our proposed model, leave-one-out crossvalidation (LOOCV) and 5-fold cross-validation have been implemented on the two datasets of aBiofilm and MDAD. As a result, based on the aBiofilm dataset, our proposed model has attained areas under the curve (AUC) of 0.9178 and 0.9022 on global LOOCV and local LOOCV, respectively. Based on aBiofilm dataset, the proposed model has attained an AUC value of 0.9018 and 0.8902 on global LOOCV and local LOOCV, respectively. In addition, the average AUC and standard deviation of the proposed model for 5- fold cross-validation on the aBiofilm and MDAD datasets were 0.9141±6.8556e-04 and 0.8982±7.5868e-04, respectively. Also, two kinds of case studies have been further conducted to evaluate the proposed models.

CONCLUSION

Traditional methods for microbe-drug association prediction are timeconsuming and laborious. Therefore, the computational model proposed was used to predict new microbe-drug associations. Several evaluation results have shown the proposed model to achieve satisfactory results and that it can play a role in drug development and precision medicine.

Bacterial butyrate mediates the anti-atherosclerotic effect of silybin

Silybin (SIL) is a versatile bioactive compound used for improving liver damage and lipid disorders and is also thought to be beneficial for atherosclerosis (AS). The goal of this study was to investigate the efficacy of SIL in the treatment of AS in ApoE-/-mice fed a high-fat diet and explore the mechanism underlying treatment outcomes. We found that SIL significantly alleviated AS-related parameters, including the extent of aortic plaque formation, hyperlipidemia, and adhesion molecule secretion in the vascular endothelium. 16 S rRNA gene sequencing analysis, together with the application of antibiotics, showed that intestinal butyrate-producing bacteria mediated the ameliorative effect of SIL on AS. Further analysis revealed that SIL facilitated butyrate production by increasing the level of butyryl-CoA: acetate CoA-transferase (BUT). The increased expression of monocarboxylic acid transporter-1 (MCT1) induced by butyrate and MCT4 induced by SIL in the apical and basolateral membranes of colonocytes, respectively, resulted in enhanced absorption of intestinal butyrate into the circulation, leading to the alleviation of arterial endothelium dysfunction. Moreover, the SIL-mediated increase in intestinal butyrate levels restored gut integrity by upregulating the expression of tight junction proteins and promoting gut immunity, thus inhibiting the AS-induced inflammatory response. This is the first study to show that SIL can alleviate AS by modulating the production of bacterial butyrate and its subsequent absorption.

Byproducts of inflammatory radical metabolism provide transient nutrient niches for microbes in the inflamed gut

Louis Pasteur's experiments on tartaric acid laid the foundation for our understanding of molecular chirality, but major questions remain. By comparing the optical activity of naturally-occurring tartaric acid with chemically-synthesized paratartaric acid, Pasteur realized that naturally-occurring tartaric acid contained only L-tartaric acid while paratartaric acid consisted of a racemic mixture of D- and L-tartaric acid. Curiously, D-tartaric acid has no known natural source, yet several gut bacteria specifically degrade D-tartaric acid. Here, we investigated the oxidation of monosaccharides by inflammatory reactive oxygen and nitrogen species. We found that this reaction yields an array of alpha hydroxy carboxylic acids, including tartaric acid isomers. Utilization of inflammation- derived D- and L-tartaric acid enhanced colonization by Salmonella Typhimurium and E. coli in murine models of gut inflammation. Our findings suggest that byproducts of inflammatory radical metabolism, such as tartrate and other alpha hydroxy carboxylic acids, create transient nutrient niches for enteric pathogens and other potentially harmful bacteria. Furthermore, this work illustrates that inflammatory radicals generate a zoo of molecules, some of which may erroneously presumed to be xenobiotics.

Exploring the role of gut microbiota in advancing personalized medicine

Ongoing extensive research in the field of gut microbiota (GM) has highlighted the crucial role of gut-dwelling microbes in human health. These microbes possess 100 times more genes than the human genome and offer significant biochemical advantages to the host in nutrient and drug absorption, metabolism, and excretion. It is increasingly clear that GM modulates the efficacy and toxicity of drugs, especially those taken orally. In addition, intra-individual variability of GM has been shown to contribute to drug response biases for certain therapeutics. For instance, the efficacy of cyclophosphamide depends on the presence of Enterococcus hirae and Barnesiella intestinihominis in the host intestine. Conversely, the presence of inappropriate or unwanted gut bacteria can inactivate a drug. For example, dehydroxylase of Enterococcus faecalis and Eggerthella lenta A2 can metabolize L-dopa before it converts into the active form (dopamine) and crosses the blood-brain barrier to treat Parkinson's disease patients. Moreover, GM is emerging as a new player in personalized medicine, and various methods are being developed to treat diseases by remodeling patients' GM composition, such as prebiotic and probiotic interventions, microbiota transplants, and the introduction of synthetic GM. This review aims to highlight how the host's GM can improve drug efficacy and discuss how an unwanted bug can cause the inactivation of medicine.

Humoral Immunity Against Aspergillus fumigatus

Aspergillus fumigatus is one the most ubiquitous airborne opportunistic human fungal pathogens. Understanding its interaction with host immune system, composed of cellular and humoral arm, is essential to explain the pathobiology of aspergillosis disease spectrum. While cellular immunity has been well studied, humoral immunity has been poorly acknowledge, although it plays a crucial role in bridging the fungus and immune cells. In this review, we have summarized available data on major players of humoral immunity against A. fumigatus and discussed how they may help to identify at-risk individuals, be used as diagnostic tools or promote alternative therapeutic strategies. Remaining challenges are highlighted and leads are given to guide future research to better grasp the complexity of humoral immune interaction with A. fumigatus.

Equipment and Methods for Concurrently Housing Germfree and Gnotobiotic Mice in the Same Room

Here, we combined the use of 2 technologies that have not previously been used together-a positively pressurized isolator IVC (IsoIVC-P) and a modular isolator with integrated vaporized hydrogen peroxide (VHP) technology???to develop highly tractable and scalable methods to support long-term maintenance of germfree mouse colonies and the concurrent use of germfree and gnotobiotic mice in the same room. This space-efficient system increases the practicality of microbiome studies. Specifically, the exterior surfaces of microbially similar IsoIVC-P were sterilized by using VHP prior to opening the cages and handling the mice therein. This space-efficient system increases the feasibility of microbiome studies. After over 74 wk of experimentation and handling equivalent to more than 1,379,693 germfree mouse-days, we determined that the method and practices we developed have a weekly performance metric of 0.0001 sterility breaks per husbandry unit; this rate is comparable to the isolator 'gold standard.' These data were achieved without adverse incidents while maintaining an Altered Schaedler Flora colony and multiple gnotobiotic studies involving fecal microbial transplants in the same room. Our novel IsoIVC-P???VHP workstation housing system thus improves microbiome research efficiency, eliminates hazards, and reduces risks associated with traditional methods.

Can we manage gut microbiome imbalances in patients with bipolar disorder with pharmacotherapy?

INTRODUCTION

A novel new area of exploration in the treatment of bipolar disorder is the gut brain axis. Studies have shown significant differences between the gut microbiome in those with bipolar disorder and those without the illness, as well as documented microbiome changes associated with the effects of bipolar pharmacotherapy and targeted microbial interventions. Although we have evidence suggesting the bi-directional relationship between the gut microbiome and psychiatric disorders, we are still unable to utilize this understanding clinically.

AREAS COVERED

We need to better understand the factors that impact the microbiome in this illness and vice versa.

EXPERT OPINION

Additionally, changes in gut microbiome in bipolar disorder might be used for biomarker identification with a potential to help in diagnosis and monitoring of the condition. It is an important area for further research and may provide improved therapeutic outcomes.

Informatics for your Gut: at the Interface of Nutrition, the Microbiome, and Technology

BACKGROUND

A significant portion of individuals in the United States and worldwide experience diseases related to or driven by diet. As research surrounding user-centered design and the microbiome grows, movement of the spectrum of translational science from bench to bedside for improvement of human health through nutrition becomes more accessible. In this literature survey, we examined recent literature examining informatics research at the interface of nutrition and the microbiome.

OBJECTIVES

The objective of this survey was to synthesize recent literature describing how technology is being applied to understand health at the interface of nutrition and the microbiome focusing on the perspective of the consumer.

METHODS

A survey of the literature published between January 1, 2021 and October 10, 2022 was performed using the PubMed database and resulting literature was evaluated against inclusion and exclusion criteria.

RESULTS

A total of 139 papers were retrieved and evaluated against inclusion and exclusion criteria. After evaluation, 45 papers were reviewed in depth revealing four major themes: (1) microbiome and diet, (2) usability,(3) reproducibility and rigor, and (4) precision medicine and precision nutrition.

CONCLUSIONS

A review of the relationships between current literature on technology, nutrition and the microbiome, and self-management of dietary patterns was performed. Major themes that emerged from this survey revealed exciting new horizons for consumer management of diet and disease, as well as progress towards elucidating the relationship between diet, the microbiome, and health outcomes. The survey revealed continuing interest in the study of diet-related disease and the microbiome and acknowledgement of needs for data re-use, sharing, and unbiased and rigorous measurement of the microbiome. The literature also showed trends toward enhancing the usability of digital interventions to support consumer health and home management, and consensus building around how precision medicine and precision nutrition may be applied in the future to improve human health outcomes and prevent diet-related disease.

Gut Microbiota and Microbial Metabolism in Early Risk of Cardiometabolic Disease

Cardiometabolic disease comprises cardiovascular and metabolic dysfunction and underlies the leading causes of morbidity and mortality, both within the United States and worldwide. Commensal microbiota are implicated in the development of cardiometabolic disease. Evidence suggests that the microbiome is relatively variable during infancy and early childhood, becoming more fixed in later childhood and adulthood. Effects of microbiota, both during early development, and in later life, may induce changes in host metabolism that modulate risk mechanisms and predispose toward the development of cardiometabolic disease. In this review, we summarize the factors that influence gut microbiome composition and function during early life and explore how changes in microbiota and microbial metabolism influence host metabolism and cardiometabolic risk throughout life. We highlight limitations in current methodology and approaches and outline state-of-the-art advances, which are improving research and building toward refined diagnosis and treatment options in microbiome-targeted therapies.

The Interplay between Gut Microbiota and Oral Medications and Its Impact on Advancing Precision Medicine

Trillions of diverse microbes reside in the gut and are deeply interwoven with the human physiological process, from food digestion, immune system maturation, and fighting invading pathogens, to drug metabolism. Microbial drug metabolism has a profound impact on drug absorption, bioavailability, stability, efficacy, and toxicity. However, our knowledge of specific gut microbial strains, and their genes that encode enzymes involved in the metabolism, is limited. The microbiome encodes over 3 million unique genes contributing to a huge enzymatic capacity, vastly expanding the traditional drug metabolic reactions that occur in the liver, manipulating their pharmacological effect, and, ultimately, leading to variation in drug response. For example, the microbial deactivation of anticancer drugs such as gemcitabine can lead to resistance to chemotherapeutics or the crucial role of microbes in modulating the efficacy of the anticancer drug, cyclophosphamide. On the other hand, recent findings show that many drugs can shape the composition, function, and gene expression of the gut microbial community, making it harder to predict the outcome of drug-microbiota interactions. In this review, we discuss the recent understanding of the multidirectional interaction between the host, oral medications, and gut microbiota, using traditional and machine-learning approaches. We analyze gaps, challenges, and future promises of personalized medicine that consider gut microbes as a crucial player in drug metabolism. This consideration will enable the development of personalized therapeutic regimes with an improved outcome, ultimately leading to precision medicine.

Optimizing ex vivo culture conditions to study human gut microbiome

The inter-individual variations of gut microbiome contribute to the different responses toward drug therapy among populations, developing a reliable ex vivo culture method for mixed bacteria is the urgent need for predicting personal reaction to drug therapy. Unfortunately, very few attentions have been paid to the bias that could be introduced during the culture process for mixed bacteria. Here we systemically evaluated the factors that may affect the outcomes of cultured bacteria from human feces. We demonstrated that inter-individual difference of host gut microbiome was the main factor affecting the outcomes of cultured bacteria, followed by the culture medium and time point. We further optimized a new medium termed GB based on our established multi-dimensional evaluation method, which could mimic the status of in situ host gut microbiome to the highest extent. Finally, we assessed the inter-individual metabolism by host gut microbiome from 10 donors on three frequently used clinical drugs (aspirin, levodopa and doxifluridine) based on the optimized GB medium. Our results revealed obvious variation in drug metabolism by microbiome from different donors, especially levodopa and doxifluridine. This work suggested the optimized culture medium had the potential for exploring the inter-individual impacts of host gut microbiome on drug metabolism.

A Taxonomy-Agnostic Approach to Targeted Microbiome Therapeutics-Leveraging Principles of Systems Biology

The study of human microbiomes has yielded insights into basic science, and applied therapeutics are emerging. However, conflicting definitions of what microbiomes are and how they affect the health of the "host" are less understood. A major impediment towards systematic design, discovery, and implementation of targeted microbiome therapeutics is the continued reliance on taxonomic indicators to define microbiomes in health and disease. Such reliance often confounds analyses, potentially suggesting associations where there are none, and conversely failing to identify significant, causal relationships. This review article discusses recent discoveries pointing towards a molecular understanding of microbiome "dysbiosis" and away from a purely taxonomic approach. We highlight the growing role of systems biological principles in the complex interrelationships between the gut microbiome and host cells, and review current approaches commonly used in targeted microbiome therapeutics, including fecal microbial transplant, bacteriophage therapies, and the use of metabolic toxins to selectively eliminate specific taxa from dysbiotic microbiomes. These approaches, however, remain wholly or partially dependent on the bacterial taxa involved in dysbiosis, and therefore may not capitalize fully on many therapeutic opportunities presented at the bioactive molecular level. New technologies capable of addressing microbiome-associated diseases as molecular problems, if solved, will open possibilities of new classes and categories of targeted microbiome therapeutics aimed, in principle, at all dysbiosis-driven disorders.

Microbially produced vitamin B12 contributes to the lipid-lowering effect of silymarin

Silymarin has been used for improving hepatic damage and lipid disorders, but its action mechanism remains to be clarified. Here, we investigate the contributions of the gut microbiota to the improvement of liver lipid metabolism by silymarin. We find i) strong and significant microbial shifts upon silymarin but not silibinin treatment; ii) over 60% variations of liver fat are explained by silymarin-induced bacterial B12 production in male rats but not in male germ-free mice; iii) fecal microbiota transplantation confirms their protective roles against liver fat accumulation; iv) upregulation of one-carbon metabolism and fatty acid degradation pathways are observed based on the liver transcriptome analyses; and v) in humans the delta changes of serum B12 associate negatively with the fluctuations of serum triglycerides. Overall, we reveal a mechanism of action underpinning the lipid-lowering effect of silymarin via the gut microbiota and its vitamin B12 producing capabilities.

Correlation Between Serum and Urine Biomarkers and the Intensity of Acute Radiation Cystitis in Patients Treated With Radiation Therapy for Localized Prostate Cancer: Protocol for the Radiotoxicity Bladder Biomarkers (RABBIO) Study

BACKGROUND

Despite improvements in radiation techniques, pelvic radiotherapy is responsible for acute and delayed bladder adverse events, defined as radiation cystitis. The initial symptoms of bladder injury secondary to pelvic irradiation are likely to occur during treatment or within 3 months of radiotherapy in approximately 50% of irradiated patients, and have a significant impact on their quality of life. The pathophysiology of radiation cystitis is not well understood, particularly because of the risk of complications associated with access to bladder tissue after irradiation, which limits our ability to study this process and develop treatments.

OBJECTIVE

It is an original study combining digital data collection to monitor patients' symptoms and biological markers during irradiation. The main objective of our study is to evaluate the correlation of biological biomarkers with the intensity of acute radiation cystitis and the quality of life of patients, assessed with the digital telemonitoring platform Cureety.

METHODS

Patients with intermediate-risk localized prostate cancer who are eligible for localized radiotherapy will be included. Inflammatory biomarkers will be analyzed in urine and blood samples before the start of radiotherapy and at weeks 4, 12, and 48 of irradiation, through quantitative methods such as a multiplex Luminex assay, flow cytometry, and enzyme-linked immunosorbent assay. We will also characterize the patients' gut and urine microbiota composition using 16S ribosomal RNA sequencing technology. Between sample collection visits, patients will complete various questionnaires related to radiation cystitis symptoms (using the International Prostate Symptom Score), adverse events, and quality of life (using the Functional Assessment of Cancer Therapy-Prostate questionnaire), using the Cureety digital remote monitoring platform. Upon receipt of the questionnaires, an algorithm will process the information and classify patients in accordance with the severity of symptoms and adverse events reported on the basis of Common Terminology Criteria for Adverse Events and International Prostate Symptom Score standards. This will allow us to correlate levels of urinary, blood, and fecal biomarkers with the severity of acute radiation cystitis symptoms and patient-reported quality of life.

RESULTS

The study started in March 2022. We estimate a recruitment period of approximately 18 months, and the final results are expected in 2024.

CONCLUSIONS

This prospective study is the first to explore the overexpression of inflammatory proteins in fluid biopsies from patients with symptoms of acute radiation cystitis. In addition, the 1-year follow-up after treatment will allow us to predict which patients are at risk of late radiation cystitis and to refer them for radioprotective treatment. The results of this study will allow us to develop strategies to limit radiation damage to the bladder and improve the quality of life of patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05246774; https://clinicaltrials.gov/ct2/show/NCT05246774?term=NCT05246774.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/38362.

TCA and SSRI Antidepressants Exert Selection Pressure for Efflux-Dependent Antibiotic Resistance Mechanisms in Escherichia coli

Microbial diversity is reduced in the gut microbiota of animals and humans treated with selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs). The mechanisms driving the changes in microbial composition, while largely unknown, is critical to understand considering that the gut microbiota plays important roles in drug metabolism and brain function. Using Escherichia coli, we show that the SSRI fluoxetine and the TCA amitriptyline exert strong selection pressure for enhanced efflux activity of the AcrAB-TolC pump, a member of the resistance-nodulation-cell division (RND) superfamily of transporters. Sequencing spontaneous fluoxetine- and amitriptyline-resistant mutants revealed mutations in marR and lon, negative regulators of AcrAB-TolC expression. In line with the broad specificity of AcrAB-TolC pumps these mutants conferred resistance to several classes of antibiotics. We show that the converse also occurs, as spontaneous chloramphenicol-resistant mutants displayed cross-resistance to SSRIs and TCAs. Chemical-genomic screens identified deletions in marR and lon, confirming the results observed for the spontaneous resistant mutants. In addition, deletions in 35 genes with no known role in drug resistance were identified that conferred cross-resistance to antibiotics and several displayed enhanced efflux activities. These results indicate that combinations of specific antidepressants and antibiotics may have important effects when both are used simultaneously or successively as they can impose selection for common mechanisms of resistance. Our work suggests that selection for enhanced efflux activities is an important factor to consider in understanding the microbial diversity changes associated with antidepressant treatments. IMPORTANCE Antidepressants are prescribed broadly for psychiatric conditions to alter neuronal levels of synaptic neurotransmitters such as serotonin and norepinephrine. Two categories of antidepressants are selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs); both are among the most prescribed drugs in the United States. While it is well-established that antidepressants inhibit reuptake of neurotransmitters there is evidence that they also impact microbial diversity in the gastrointestinal tract. However, the mechanisms and therefore biological and clinical effects remain obscure. We demonstrate antidepressants may influence microbial diversity through strong selection for mutant bacteria with increased AcrAB-TolC activity, an efflux pump that removes antibiotics from cells. Furthermore, we identify a new group of genes that contribute to cross-resistance between antidepressants and antibiotics, several act by regulating efflux activity, underscoring overlapping mechanisms. Overall, this work provides new insights into bacterial responses to antidepressants important for understanding antidepressant treatment effects.

Antibiotics, the microbiome and gastrointestinal cancers: A causal interference?

Our understanding of the gut microbiota has significantly evolved over the last two decades. Advances in the analysis of the gut microbiome continues to reveal complex microbial communities and discoveries about their role in health and diseases, including cancer development, are continuously growing. In addition, research has demonstrated that the use of antibiotics can modulate the gut microbiota composition negatively and influence cancer treatment outcomes, suggesting that antibiotics should be avoided if possible. In this article, we review the role of the gut microbiota in the formation of GI cancers. We show that specific bacterial populations can positively or negatively affect cancer formation with specific attention given to gastric and colorectal cancer. We also review the role of microbial-targeted therapies on cancer treatment outcomes.

Bringing pharmacomicrobiomics to the clinic through well-designed studies

Pharmacomicrobiomic studies investigate drug-microbiome interactions, such as the effect of microbial variation on drug response and disposition. Studying and understanding the interactions between the gut microbiome and drugs is becoming increasingly relevant to clinical practice due to its potential for avoiding adverse drug reactions or predicting variability in drug response. The highly variable nature of the human microbiome presents significant challenges to assessing microbes' influence. Studies aiming to explore drug-microbiome interactions should be well-designed to account for variation in the microbiome over time and collect data on confounders such as diet, disease, concomitant drugs, and other environmental factors. Here, we assemble a set of important considerations and recommendations for the methodological features required for performing a pharmacomicrobiomic study in humans with a focus on the gut microbiome. Consideration of these factors enable discovery, reproducibility, and more accurate characterization of the relationships between a given drug and the microbiome. Furthermore, appropriate interpretation and dissemination of results from well-designed studies will push the field closer to clinical relevance and implementation.

Host and gut bacteria share metabolic pathways for anti-cancer drug metabolism

Pharmaceuticals have extensive reciprocal interactions with the microbiome, but whether bacterial drug sensitivity and metabolism is driven by pathways conserved in host cells remains unclear. Here we show that anti-cancer fluoropyrimidine drugs inhibit the growth of gut bacterial strains from 6 phyla. In both Escherichia coli and mammalian cells, fluoropyrimidines disrupt pyrimidine metabolism. Proteobacteria and Firmicutes metabolized 5-fluorouracil to its inactive metabolite dihydrofluorouracil, mimicking the major host mechanism for drug clearance. The preTA operon was necessary and sufficient for 5-fluorouracil inactivation by E. coli, exhibited high catalytic efficiency for the reductive reaction, decreased the bioavailability and efficacy of oral fluoropyrimidine treatment in mice and was prevalent in the gut microbiomes of colorectal cancer patients. The conservation of both the targets and enzymes for metabolism of therapeutics across domains highlights the need to distinguish the relative contributions of human and microbial cells to drug efficacy and side-effect profiles.

Microenvironmental Factors that Shape Bacterial Metabolites in Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a significant global health problem that involves chronic intestinal inflammation and can involve severe comorbidities, including intestinal fibrosis and inflammation-associated colorectal cancer (CRC). Disease-associated alterations to the intestinal microbiota often include fecal enrichment of Enterobacteriaceae, which are strongly implicated in IBD development. This dysbiosis of intestinal flora accompanies changes in microbial metabolites, shaping host:microbe interactions and disease risk. While there have been numerous studies linking specific bacterial taxa with IBD development, our understanding of microbial function in the context of IBD is limited. Several classes of microbial metabolites have been directly implicated in IBD disease progression, including bacterial siderophores and genotoxins. Yet, our microbiota still harbors thousands of uncharacterized microbial products. In-depth discovery and characterization of disease-associated microbial metabolites is necessary to target these products in IBD treatment strategies. Towards improving our understanding of microbiota metabolites in IBD, it is important to recognize how host relevant factors influence microbiota function. For example, changes in host inflammation status, metal availability, interbacterial community structure, and xenobiotics all play an important role in shaping gut microbial ecology. In this minireview, we outline how each of these factors influences gut microbial function, with a specific focus on IBD-associated Enterobacteriaceae metabolites. Importantly, we discuss how altering the intestinal microenvironment could improve the treatment of intestinal inflammation and associated disorders, like intestinal fibrosis and CRC.

Pharmacomicrobiomics: Influence of gut microbiota on drug and xenobiotic metabolism

Gut microbiota is the most diverse and complex biological ecosystem, which is estimated to consist of greater than 5 million distinct genes and 100 trillion cells which are in constant communication with the host environment. The interaction between the gut microbiota and drugs and other xenobiotic compounds is bidirectional, quite complicated, and not fully understood yet. The impact of xenobiotics from pollution, manufacturing processes or from the environment is harmful to human health at varying degrees and this needs to be recognized and addressed. The gut microbiota is capable of biotransforming/metabolizing of various drugs and xenobiotic compounds as well as altering the activity and toxicity of these substances, thereby influencing how a host responds to drugs and xenobiotics and this emerging field is known as pharmacomicrobiomics. In this review, we discussed different mechanisms of drug-gut microbiota interaction and highlighted the influence of drug-gut microbiome interactions on the clinical response in humans.

Gut Microbiota Metabolism of Azathioprine: A New Hallmark for Personalized Drug-Targeted Therapy of Chronic Inflammatory Bowel Disease

Despite the growing number of new drugs approved for the treatment of inflammatory bowel disease (IBD), the long-term clinical use of thiopurine therapy and the well-known properties of conventional drugs including azathioprine have made their place in IBD therapy extremely valuable. Despite the fact that thiopurine S-methyltransferase (TPMT) polymorphism has been recognized as a major cause of the interindividual variability in the azathioprine response, recent evidence suggests that there might be some yet unknown causes which complicate dosing strategies causing either failure of therapy or toxicity. Increasing evidence suggests that gut microbiota, with its ability to release microbial enzymes, affects the pharmacokinetics of numerous drugs and subsequently drastically alters clinical effectiveness. Azathioprine, as an orally administered drug which has a complex metabolic pathway, is the prime illustrative candidate for such microbial metabolism of drugs. Comprehensive databases on microbial drug-metabolizing enzymes have not yet been generated. This study provides insights into the current evidence on microbiota-mediated metabolism of azathioprine and systematically accumulates findings of bacteria that possess enzymes required for the azathioprine biotransformation. Additionally, it proposes concepts for the identification of gut bacteria species responsible for the metabolism of azathioprine that could aid in the prediction of dose-response effects, complementing pharmacogenetic approaches already applied in the optimization of thiopurine therapy of IBD. It would be of great importance to elucidate to what extent microbiota-mediated metabolism of azathioprine contributes to the drug outcomes in IBD patients which could facilitate the clinical implementation of novel tools for personalized thiopurine treatment of IBD.

Microbiomics: The Next Pillar of Precision Medicine and Its Role in African Healthcare

Limited access to technologies that support early monitoring of disease risk and a poor understanding of the geographically unique biological and environmental factors underlying disease, represent significant barriers to improved health outcomes and precision medicine efforts in low to middle income countries. These challenges are further compounded by the rich genetic diversity harboured within Southern Africa thus necessitating alternative strategies for the prediction of disease risk and clinical outcomes in regions where accessibility to personalized healthcare remains limited. The human microbiome refers to the community of microorganisms (bacteria, archaea, fungi and viruses) that co-inhabit the human body. Perturbation of the natural balance of the gut microbiome has been associated with a number of human pathologies, and the microbiome has recently emerged as a critical determinant of drug pharmacokinetics and immunomodulation. The human microbiome should therefore not be omitted from any comprehensive effort towards stratified healthcare and would provide an invaluable and orthogonal approach to existing precision medicine strategies. Recent studies have highlighted the overarching effect of geography on gut microbial diversity as it relates to human health. Health insights from international microbiome datasets are however not yet verified in context of the vast geographical diversity that exists throughout the African continent. In this commentary we discuss microbiome research in Africa and its role in future precision medicine initiatives across the African continent.

Next-generation sequencing: insights to advance clinical investigations of the microbiome

Next-generation sequencing (NGS) technology has advanced our understanding of the human microbiome by allowing for the discovery and characterization of unculturable microbes with prediction of their function. Key NGS methods include 16S rRNA gene sequencing, shotgun metagenomic sequencing, and RNA sequencing. The choice of which NGS methodology to pursue for a given purpose is often unclear for clinicians and researchers. In this Review, we describe the fundamentals of NGS, with a focus on 16S rRNA and shotgun metagenomic sequencing. We also discuss pros and cons of each methodology as well as important concepts in data variability, study design, and clinical metadata collection. We further present examples of how NGS studies of the human microbiome have advanced our understanding of human disease pathophysiology across diverse clinical contexts, including the development of diagnostics and therapeutics. Finally, we share insights as to how NGS might further be integrated into and advance microbiome research and clinical care in the coming years.

A programmable encapsulation system improves delivery of therapeutic bacteria in mice

Living bacteria therapies have been proposed as an alternative approach to treating a broad array of cancers. In this study, we developed a genetically encoded microbial encapsulation system with tunable and dynamic expression of surface capsular polysaccharides that enhances systemic delivery. Based on a small RNA screen of capsular biosynthesis pathways, we constructed inducible synthetic gene circuits that regulate bacterial encapsulation in Escherichia coli Nissle 1917. These bacteria are capable of temporarily evading immune attack, whereas subsequent loss of encapsulation results in effective clearance in vivo. This dynamic delivery strategy enabled a ten-fold increase in maximum tolerated dose of bacteria and improved anti-tumor efficacy in murine models of cancer. Furthermore, in situ encapsulation increased the fraction of microbial translocation among mouse tumors, leading to efficacy in distal tumors. The programmable encapsulation system promises to enhance the therapeutic utility of living engineered bacteria for cancer.

Transient capsule induction allows engineered bacteria to evade initial immune surveillance in a colorectal cancer model.

Machine Learning Predicts Drug Metabolism and Bioaccumulation by Intestinal Microbiota

Over 150 drugs are currently recognised as being susceptible to metabolism or bioaccumulation (together described as depletion) by gastrointestinal microorganisms; however, the true number is likely higher. Microbial drug depletion is often variable between and within individuals, depending on their unique composition of gut microbiota. Such variability can lead to significant differences in pharmacokinetics, which may be associated with dosing difficulties and lack of medication response. In this study, literature mining and unsupervised learning were used to curate a dataset of 455 drug-microbiota interactions. From this, 11 supervised learning models were developed that could predict drugs' susceptibility to depletion by gut microbiota. The best model, a tuned extremely randomised trees classifier, achieved performance metrics of AUROC: 75.1% ± 6.8; weighted recall: 79.2% ± 3.9; balanced accuracy: 69.0% ± 4.6; and weighted precision: 80.2% ± 3.7 when validated on 91 drugs. This machine learning model is the first of its kind and provides a rapid, reliable, and resource-friendly tool for researchers and industry professionals to screen drugs for susceptibility to depletion by gut microbiota. The recognition of drug-microbiome interactions can support successful drug development and promote better formulations and dosage regimens for patients.

Stigmasterol Restores the Balance of Treg/Th17 Cells by Activating the Butyrate-PPARγ Axis in Colitis

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder with gut microbiota disequilibrium and regulatory T (Treg)/T helper 17 (Th17) immune imbalance. Stigmasterol, a plant-derived sterol, has shown anti-inflammatory effects. Our study aimed to identify the effects of stigmasterol on experimental colitis and the related mechanisms. Stigmasterol treatment restored the Treg/Th17 balance and altered the gut microbiota in a dextran sodium sulfate (DSS)-induced colitis model. Transplantation of the faecal microbiota of stigmasterol-treated mice significantly alleviated inflammation. Additionally, stigmasterol treatment enhanced the production of gut microbiota-derived short-chain fatty acids (SCFAs), particularly butyrate. Next, human naïve CD4+ T cells sorted from IBD patients were cultured under Treg- or Th17-polarizing conditions; butyrate supplementation increased the differentiation of Tregs and decreased Th17 cell differentiation. Mechanistically, butyrate activated peroxisome proliferator-activated receptor gamma (PPARγ) and reprogrammed energy metabolism, thereby promoting Treg differentiation and inhibiting Th17 differentiation. Our results demonstrate that butyrate-mediated PPARγ activation restores the balance of Treg/Th17 cells, and this may be a possible mechanism, by which stigmasterol attenuates IBD.

Small Molecule Metabolites at the Host-Microbiota Interface

The trillions of bacteria that constitutively colonize the human gut collectively generate thousands of unique small molecules. These microbial metabolites can accumulate both locally and systemically and potentially influence nearly all aspects of mammalian biology, including immunity, metabolism, and even mood and behavior. In this review, we briefly summarize recent work identifying bioactive microbiota metabolites, the means through which they are synthesized, and their effects on host physiology. Rather than offering an exhaustive list of all known bioactive microbial small molecules, we select a few examples from each key class of metabolites to illustrate the diverse impacts of microbiota-derived compounds on the host. In addition, we attempt to address the microbial logic behind specific biotransformations. Finally, we outline current and emerging strategies for identifying previously undiscovered bioactive microbiota metabolites that may shape human health and disease.

The efficacy and toxicity of antineoplastic antimetabolites: Role of gut microbiota

The incidence and mortality of cancer are rapidly growing all over the world. Nowadays, antineoplastic antimetabolites still play a key role in the chemotherapy of cancer. However, the interindividual variations in the efficacy and toxicity of antineoplastic antimetabolites are nonnegligible challenges to their clinical applications. Although many studies have focused on genetic variation, the reasons for these interindividual variations have still not been fully understood. Gut microbiota is reported to be associated with the efficacy and toxicity of antineoplastic antimetabolites. In this review, we summarize the interaction of antineoplastic antimetabolites on gut microbiota and the influences of shifted gut microbiota profiles on the efficacy and toxicity of antineoplastic antimetabolites. The factors affecting the efficacy and toxicity of antineoplastic antimetabolites via gut microbiota are also discussed. In addition, we present our viewpoints that regulating the gut microbiota may increase the efficacy and decrease the toxicity of antineoplastic antimetabolites. This will help us better understand the new mechanism via gut microbiota and promote individualized use of antineoplastic antimetabolites.

The relationship between gastrointestinal cancers and the microbiota

The contribution of the microbiota to disease progression and treatment efficacy is often neglected when determining who is at the highest risk of developing gastrointestinal cancers or designing treatment strategies for patients. We reviewed the current literature on the effect of the human microbiota on cancer risk, prognosis, and treatment efficacy. We highlight emerging research that seeks to identify microbial signatures as biomarkers for various gastrointestinal cancers, and discuss how we could harness knowledge of the microbiome to detect, prevent, and treat these cancers. Finally, we outline further research needed in the field of gastrointestinal cancers and the microbiota, and describe the efforts required to increase the accuracy and reproducibility of data linking the microbiome to cancer.

Characterization of gut microbiome in mice model of depression with divergent response to escitalopram treatment

Depression is a common and heterogeneous mental disorder. Although several antidepressants are available to treat the patients with depression, the factors which could affect and predict the treatment response remain unclear. Here, we characterize the longitudinal changes of microbial composition and function during escitalopram treatment in chronic unpredictable mild stress (CUMS) mice model of depression based on 16 S rRNA sequencing and metabolomics. Consequently, we found that escitalopram (ESC) administration serves to increase the alpha-diversity of the gut microbiome in ESC treatment group. The microbial signatures between responder (R) and non-responder (NR) groups were significantly different. The R group was mainly characterized by increased relative abundances of genus Prevotellaceae_UCG-003, and depleted families Ruminococcaceae and Lactobacillaceae relative to NR group. Moreover, we identified 15 serum metabolites responsible for discriminating R and NR group. Those differential metabolites were mainly involved in phospholipid metabolism. Significantly, the bacterial OTUs belonging to family Lachnospiraceae, Helicobacteraceae, and Muribaculaceae formed strong co-occurring relationships with serum metabolites, indicating alternations of gut microbiome and metabolites as potential mediators in efficiency of ESC treatment. Together, our study demonstrated that the alterations of microbial compositions and metabolic functions might be relevant to the different response to ESC, which shed new light in uncovering the mechanisms of differences in efficacy of antidepressants.

Diet-induced dysbiosis of the maternal gut microbiome in early life programming of neurodevelopmental disorders

The maternal gut microbiome plays a critical role in fetal and early postnatal development, shaping fundamental processes including immune maturation and brain development, among others. Consequently, it also contributes to fetal programming of health and disease. Over the last decade, epidemiological studies and work in preclinical animal models have begun to uncover a link between dysbiosis of the maternal gut microbiome and neurodevelopmental disorders in offspring. Neurodevelopmental disorders are caused by both genetic and environmental factors, and their interactions; however, clinical heterogeneity, phenotypic variability, and comorbidities make identification of underlying mechanisms difficult. Among environmental factors, exposure to maternal obesity in utero confers a significant increase in risk for neurodevelopmental disorders. Obesogenic diets in humans, non-human primates, and rodents induce functional modifications in maternal gut microbiome composition, which animal studies suggest are causally related to adverse mental health outcomes in offspring. Here, we review evidence linking maternal diet-induced gut dysbiosis to neurodevelopmental disorders and discuss how it could affect pre- and early postnatal brain development. We are hopeful that this burgeoning field of research will revolutionize antenatal care by leading to accessible prophylactic strategies, such as prenatal probiotics, to improve mental health outcomes in children affected by maternal diet-induced obesity.

Machine Learning as a Precision-Medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids

PURPOSE

Coronavirus disease-2019 (COVID-19) continues to be a global threat and remains a significant cause of hospitalizations. Recent clinical guidelines have supported the use of corticosteroids or remdesivir in the treatment of COVID-19. However, uncertainty remains about which patients are most likely to benefit from treatment with either drug; such knowledge is crucial for avoiding preventable adverse effects, minimizing costs, and effectively allocating resources. This study presents a machine-learning system with the capacity to identify patients in whom treatment with a corticosteroid or remdesivir is associated with improved survival time.

METHODS

Gradient-boosted decision-tree models used for predicting treatment benefit were trained and tested on data from electronic health records dated between December 18, 2019, and October 18, 2020, from adult patients (age ≥18 years) with COVID-19 in 10 US hospitals. Models were evaluated for performance in identifying patients with longer survival times when treated with a corticosteroid versus remdesivir. Fine and Gray proportional-hazards models were used for identifying significant findings in treated and nontreated patients, in a subset of patients who received supplemental oxygen, and in patients identified by the algorithm. Inverse probability-of-treatment weights were used to adjust for confounding. Models were trained and tested separately for each treatment.

FINDINGS

Data from 2364 patients were included, with men comprising slightly more than 50% of the sample; 893 patients were treated with remdesivir, and 1471 were treated with a corticosteroid. After adjustment for confounding, neither corticosteroids nor remdesivir use was associated with increased survival time in the overall population or in the subpopulation that received supplemental oxygen. However, in the populations identified by the algorithms, both corticosteroids and remdesivir were significantly associated with an increase in survival time, with hazard ratios of 0.56 and 0.40, respectively (both, P = 0.04).

IMPLICATIONS

Machine-learning methods have the capacity to identify hospitalized patients with COVID-19 in whom treatment with a corticosteroid or remdesivir is associated with an increase in survival time. These methods may help to improve patient outcomes and allocate resources during the COVID-19 crisis.

A framework for microbiome science in public health

Human microbiome science has advanced rapidly and reached a scale at which basic biology, clinical translation and population health are increasingly integrated. It is thus now possible for public health researchers, practitioners and policymakers to take specific action leveraging current and future microbiome-based opportunities and best practices. Here we provide an outline of considerations for research, education, interpretation and scientific communication concerning the human microbiome and public health. This includes guidelines for population-scale microbiome study design; necessary physical platforms and analysis methods; integration into public health areas such as epidemiology, nutrition, chronic disease, and global and environmental health; entrepreneurship and technology transfer; and educational curricula. Particularly in the near future, there are both opportunities for the incorporation of microbiome-based technologies into public health practice, and a growing need for policymaking and regulation around related areas such as prebiotic and probiotic supplements, novel live-cell therapies and fecal microbiota transplants.

Connecting the dots: Targeting the microbiome in drug toxicity

The gut microbiota has a vast influence on human health and its role in initiating, aggravating, or ameliorating diseases is beginning to emerge. Recently, its contribution to heterogeneous toxicological responses is also gaining attention, especially in drug-induced toxicity. Whether they are orally administered or not, drugs may interact with the gut microbiota directly or indirectly, which leads to altered toxicity. Present studies focus more on the unidirectional influence of how xenobiotics disturb intestinal microbial composition and functions, and thus induce altered homeostasis. However, interactions between the gut microbiota and xenobiotics are bidirectional and the impact of the gut microbiota on xenobiotics, especially on drugs, should not be neglected. Thus, in this review, we focus on how the gut microbiota modulates drug toxicity by highlighting the microbiome, microbial enzyme, and microbial metabolites. We connect the dots between drugs, the microbiome, microbial enzymes or metabolites, drug metabolites, and host toxicological responses to facilitate the discovery of microbial targets and mechanisms associated with drug toxicity. Besides this, current mainstream strategies to manipulate drug toxicity by targeting the microbiome are summarized and discussed. The review provides technical reference for the evaluation of medicinal properties in the research and development of innovative drugs, and for the future exploitation of strategies to reduce drug toxicity by targeting the microbiome.