The Role of the Microbiome in Drug Response

Effect of metformin on gut microbiota imbalance in patients with T2DM, and the value of probiotic supplementation

PURPOSE

To investigate the effect of metformin on gut microbiota imbalance in patients with type 2 diabetes mellitus (T2DM), and the value of probiotic supplementation.

METHODS

A total of 84 newly diagnosed T2DM patients were randomly divided into probiotics group, metformin group, and control group, with 28 patients in each group. The blood glucose control, islet function, gut microbiota, and inflammatory factors were compared between three groups.

RESULTS

After 3 months of treatment, fasting plasma glucose (FPG), 2-h postprandial plasma glucose (2-h PG), and glycosylated hemoglobin A1c (HbA1c) were evidently decreased in both probiotics and metformin groups (P < 0.05) and were lower than that in the control group prior to treatment. Besides, FPG, 2-h PG, and HbA1c were lower in the metformin group than that in the control group. FPG, 2-h PG, and HbA1c were further lower in the probiotic group than in the metformin group (P < 0.05). Fasting insulin (FINS) and islet β cell (HOMA-β) -function were dramatically increased in the same group (P < 0.05), while insulin-resistant islet β cells (HOMA-IR) were significantly lower in the same group (P < 0.05); FINS and HOMA-β were significantly higher, while HOMA-IR was significantly lower (P < 0.05) in both groups than in the control group prior to treatment. HOMA-IR was also lower in the probiotic group than in the metformin group after treatment (P < 0.05); the number of lactobacilli and bifidobacteria increased (P < 0.05) in both probiotic and metformin groups than in the control group prior to treatment, and the number of Enterobacteriaceae and Enterococcus was lower in the control group prior to treatment (P < 0.05). In addition, the number of lactobacilli and bifidobacteria was higher and the number of enterobacteria and enterococci was lower in the probiotic group than that in the metformin group after treatment, and the differences were statistically significant (P < 0.05). Lipopolysaccharide (LPS), interleukin 6 (IL-6), and C-reactive protein (CRP) levels were lower in both probiotic and metformin groups (P < 0.05). The serum LPS, IL-6, and CRP levels were lower in both probiotic and metformin groups, compared to the control group prior to the treatment (P < 0.05).

CONCLUSION

Metformin while treating T2DM assists in improving the imbalance of gut microbiota.

A diet of oxidative stress-adapted bacteria improves stress resistance and lifespan in C. elegans via p38-MAPK

Organisms across taxa face stresses including variable temperature, redox imbalance, and xenobiotics. Successfully responding to stress and restoring homeostasis are crucial for survival. Aging is associated with a decreased stress response and alterations in the microbiome, which contribute to disease development. Animals and their microbiota share their environment; however, microbes have short generation time and can rapidly evolve and potentially affect host physiology during stress. Here, we leverage Caenorhabditis elegans and its simplified bacterial diet to demonstrate how microbial adaptation to oxidative stress affects the host's lifespan and stress response. We find that worms fed stress-evolved bacteria exhibit enhanced stress resistance and an extended lifespan. Through comprehensive genetic and metabolic analysis, we find that iron in stress-evolved bacteria enhances worm stress resistance and lifespan via activation of the mitogen-activated protein kinase pathway. In conclusion, our study provides evidence that understanding microbial stress-mediated adaptations could be used to slow aging and alleviate age-related health decline.

Potential Drug-Nutrient Interactions of 45 Vitamins, Minerals, Trace Elements, and Associated Dietary Compounds with Acetylsalicylic Acid and Warfarin-A Review of the Literature

In cardiology, acetylsalicylic acid (ASA) and warfarin are among the most commonly used prophylactic therapies against thromboembolic events. Drug-drug interactions are generally well-known. Less known are the drug-nutrient interactions (DNIs), impeding drug absorption and altering micronutritional status. ASA and warfarin might influence the micronutritional status of patients through different mechanisms such as binding or modification of binding properties of ligands, absorption, transport, cellular use or concentration, or excretion. Our article reviews the drug-nutrient interactions that alter micronutritional status. Some of these mechanisms could be investigated with the aim to potentiate the drug effects. DNIs are seen occasionally in ASA and warfarin and could be managed through simple strategies such as risk stratification of DNIs on an individual patient basis; micronutritional status assessment as part of the medical history; extensive use of the drug-interaction probability scale to reference little-known interactions, and application of a personal, predictive, and preventive medical model using omics.

Mining the Metabolic Capacity of Clostridium sporogenes Aided by Machine Learning

Anaerobes dominate the microbiota of the gastrointestinal (GI) tract, where a significant portion of small molecules can be degraded or modified. However, the enormous metabolic capacity of gut anaerobes remains largely elusive in contrast to aerobic bacteria, mainly due to the requirement of sophisticated laboratory settings. In this study, we employed an in silico machine learning platform, MoleculeX, to predict the metabolic capacity of a gut anaerobe, Clostridium sporogenes, against small molecules. Experiments revealed that among the top seven candidates predicted as unstable, six indeed exhibited instability in C. sporogenes culture. We further identified several metabolites resulting from the supplementation of everolimus in the bacterial culture for the first time. By utilizing bioinformatics and in vitro biochemical assays, we successfully identified an enzyme encoded in the genome of C. sporogenes responsible for everolimus transformation. Our framework thus can potentially facilitate future understanding of small molecules metabolism in the gut, further improve patient care through personalized medicine, and guide the development of new small molecule drugs and therapeutic approaches.

mEnrich-seq: methylation-guided enrichment sequencing of bacterial taxa of interest from microbiome

Metagenomics has enabled the comprehensive study of microbiomes. However, many applications would benefit from a method that sequences specific bacterial taxa of interest, but not most background taxa. We developed mEnrich-seq (in which 'm' stands for methylation and seq for sequencing) for enriching taxa of interest from metagenomic DNA before sequencing. The core idea is to exploit the self versus nonself differentiation by natural bacterial DNA methylation and rationally choose methylation-sensitive restriction enzymes, individually or in combination, to deplete host and background taxa while enriching targeted taxa. This idea is integrated with library preparation procedures and applied in several applications to enrich (up to 117-fold) pathogenic or beneficial bacteria from human urine and fecal samples, including species that are hard to culture or of low abundance. We assessed 4,601 bacterial strains with mapped methylomes so far and showed broad applicability of mEnrich-seq. mEnrich-seq provides microbiome researchers with a versatile and cost-effective approach for selective sequencing of diverse taxa of interest.

Microbiota Implications in Endocrine-Related Diseases: From Development to Novel Therapeutic Approaches

This comprehensive review article delves into the critical role of the human microbiota in the development and management of endocrine-related diseases. We explore the complex interactions between the microbiota and the endocrine system, emphasizing the implications of microbiota dysbiosis for the onset and progression of various endocrine disorders. The review aims to synthesize current knowledge, highlighting recent advancements and the potential of novel therapeutic approaches targeting microbiota-endocrine interactions. Key topics include the impact of microbiota on hormone regulation, its role in endocrine pathologies, and the promising avenues of microbiota modulation through diet, probiotics, prebiotics, and fecal microbiota transplantation. We underscore the importance of this research in advancing personalized medicine, offering insights for more tailored and effective treatments for endocrine-related diseases.

B. longum CKD1 enhances the efficacy of anti-diabetic medicines through upregulation of IL- 22 response in type 2 diabetic mice

The gut microbiota plays a pivotal role in metabolic disorders, notably type 2 diabetes mellitus (T2DM). In this study, we investigated the synergistic potential of combining the effects of Bifidobacterium longum NBM7-1 (CKD1) with anti-diabetic medicines, LobeglitazoneⓇ (LO), SitagliptinⓇ (SI), and MetforminⓇ (Met), to alleviate hyperglycemia in a diabetic mouse model. CKD1 effectively mitigated insulin resistance, hepatic steatosis, and enhanced pancreatic β-cell function, as well as fortifying gut-tight junction integrity. In the same way, SI-CKD1 and Met- CKD1 synergistically improved insulin sensitivity and prevented hepatic steatosis, as evidenced by the modulation of key genes associated with insulin signaling, β-oxidation, gluconeogenesis, adipogenesis, and inflammation by qRT-PCR. The comprehensive impact on modulating gut microbiota composition was observed, particularly when combined with MetforminⓇ. This combination induced an increase in the abundance of Rikenellaceae and Alistipes related negatively to the T2DM incidence while reducing the causative species of Cryptosporangium, Staphylococcaceae, and Muribaculaceae. These alterations intervene in gut microbiota metabolites to modulate the level of butyrate, indole-3-acetic acid, propionate, and inflammatory cytokines and to activate the IL-22 pathway. However, it is meaningful that the combination of B. longum NBM7-1(CKD1) reduced the medicines' dose to the level of the maximal inhibitory concentrations (IC50). This study advances our understanding of the intricate relationship between gut microbiota and metabolic disorders. We expect this study to contribute to developing a prospective therapeutic strategy modulating the gut microbiota.

Drug-microbiota interactions: an emerging priority for precision medicine

Individual variability in drug response (IVDR) can be a major cause of adverse drug reactions (ADRs) and prolonged therapy, resulting in a substantial health and economic burden. Despite extensive research in pharmacogenomics regarding the impact of individual genetic background on pharmacokinetics (PK) and pharmacodynamics (PD), genetic diversity explains only a limited proportion of IVDR. The role of gut microbiota, also known as the second genome, and its metabolites in modulating therapeutic outcomes in human diseases have been highlighted by recent studies. Consequently, the burgeoning field of pharmacomicrobiomics aims to explore the correlation between microbiota variation and IVDR or ADRs. This review presents an up-to-date overview of the intricate interactions between gut microbiota and classical therapeutic agents for human systemic diseases, including cancer, cardiovascular diseases (CVDs), endocrine diseases, and others. We summarise how microbiota, directly and indirectly, modify the absorption, distribution, metabolism, and excretion (ADME) of drugs. Conversely, drugs can also modulate the composition and function of gut microbiota, leading to changes in microbial metabolism and immune response. We also discuss the practical challenges, strategies, and opportunities in this field, emphasizing the critical need to develop an innovative approach to multi-omics, integrate various data types, including human and microbiota genomic data, as well as translate lab data into clinical practice. To sum up, pharmacomicrobiomics represents a promising avenue to address IVDR and improve patient outcomes, and further research in this field is imperative to unlock its full potential for precision medicine.

Advancing our understanding of the influence of drug induced changes in the gut microbiome on bone health

The gut microbiome has been implicated in a multitude of human diseases, with emerging evidence linking its microbial diversity to osteoporosis. This review article will explore the molecular mechanisms underlying perturbations in the gut microbiome and their influence on osteoporosis incidence in individuals with chronic diseases. The relationship between gut microbiome diversity and bone density is primarily mediated by microbiome-derived metabolites and signaling molecules. Perturbations in the gut microbiome, induced by chronic diseases can alter bacterial diversity and metabolic profiles, leading to changes in gut permeability and systemic release of metabolites. This cascade of events impacts bone mineralization and consequently bone mineral density through immune cell activation. In addition, we will discuss how orally administered medications, including antimicrobial and non-antimicrobial drugs, can exacerbate or, in some cases, treat osteoporosis. Specifically, we will review the mechanisms by which non-antimicrobial drugs disrupt the gut microbiome's diversity, physiology, and signaling, and how these events influence bone density and osteoporosis incidence. This review aims to provide a comprehensive understanding of the complex interplay between orally administered drugs, the gut microbiome, and osteoporosis, offering new insights into potential therapeutic strategies for preserving bone health.

Regulation of Immune Homeostasis, Inflammation, and HIV Persistence by the Microbiome, Short-Chain Fatty Acids, and Bile Acids

Despite antiretroviral therapy (ART), people living with human immunodeficiency virus (HIV) (PLWH) continue to experience chronic inflammation and immune dysfunction, which drives the persistence of latent HIV and prevalence of clinical comorbidities. Elucidating the mechanisms that lead to suboptimal immunity is necessary for developing therapeutics that improve the quality of life of PLWH. Although previous studies have found associations between gut dysbiosis and immune dysfunction, the cellular/molecular cascades implicated in the manifestation of aberrant immune responses downstream of microbial perturbations in PLWH are incompletely understood. Recent literature has highlighted that two abundant metabolite families, short-chain fatty acids (SCFAs) and bile acids (BAs), play a crucial role in shaping immunity. These metabolites can be produced and/or modified by bacterial species that make up the gut microbiota and may serve as the causal link between changes to the gut microbiome, chronic inflammation, and immune dysfunction in PLWH. In this review, we discuss our current understanding of the role of the microbiome on HIV acquisition and latent HIV persistence despite ART. Further, we describe cellular/molecular cascades downstream of SCFAs and BAs that drive innate or adaptive immune responses responsible for promoting latent HIV persistence in PLWH. This knowledge can be used to advance HIV cure efforts.

A data-driven approach for predicting the impact of drugs on the human microbiome

Many medications can negatively impact the bacteria residing in our gut, depleting beneficial species, and causing adverse effects. To guide personalized pharmaceutical treatment, a comprehensive understanding of the impact of various drugs on the gut microbiome is needed, yet, to date, experimentally challenging to obtain. Towards this end, we develop a data-driven approach, integrating information about the chemical properties of each drug and the genomic content of each microbe, to systematically predict drug-microbiome interactions. We show that this framework successfully predicts outcomes of in-vitro pairwise drug-microbe experiments, as well as drug-induced microbiome dysbiosis in both animal models and clinical trials. Applying this methodology, we systematically map a large array of interactions between pharmaceuticals and human gut bacteria and demonstrate that medications' anti-microbial properties are tightly linked to their adverse effects. This computational framework has the potential to unlock the development of personalized medicine and microbiome-based therapeutic approaches, improving outcomes and minimizing side effects.

Decipher enzymes from human microbiota for drug discovery and development

The human microbiota plays an important role in human health and contributes to the metabolism of therapeutic drugs affecting their potency. However, the current knowledge on human gut bacterial metabolism is limited and lacks an understanding of the underlying mechanisms of observed drug biotransformations. Despite the complexity of the gut microbial community, genomic and metagenomic sequencing provides insights into the diversity of chemical reactions that can be carried out by the microbiota and poses new challenges to functionally annotate thousands of bacterial enzymes. Here, we outline methods to systematically address the structural and functional space of the human microbiome, highlighting a combination of in silico and in vitro approaches. Systematic knowledge about microbial enzymes could eventually be applied for personalized therapy, the development of prodrugs and modulators of unwanted bacterial activity, and the further discovery of new antibiotics.

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

There is a need to identify biomarkers predictive of response to neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC). We previously obtained evidence that a polyamine signature in the blood is associated with TNBC development and progression. In this study, we evaluated whether plasma polyamines and other metabolites may identify TNBC patients who are less likely to respond to NACT. Pre-treatment plasma levels of acetylated polyamines were elevated in TNBC patients that had moderate to extensive tumor burden (RCB-II/III) following NACT compared to those that achieved a complete pathological response (pCR/RCB-0) or had minimal residual disease (RCB-I). We further applied artificial intelligence to comprehensive metabolic profiles to identify additional metabolites associated with treatment response. Using a deep learning model (DLM), a metabolite panel consisting of two polyamines as well as nine additional metabolites was developed for improved prediction of RCB-II/III. The DLM has potential clinical value for identifying TNBC patients who are unlikely to respond to NACT and who may benefit from other treatment modalities.

Cancer as microenvironmental, systemic and environmental diseases: opportunity for transdisciplinary microbiomics science

Cancer is generally regarded as a localised disease, with the well-established role of the tumour microenvironment. However, the realm of cancer goes beyond the tumour microenvironment, and cancer should also be regarded as a systemic and environmental disease. The exposome (ie, the totality of exposures), which encompasses diets, supplements, smoking, alcohol, other lifestyle factors, medications, etc, likely alters the microbiome (inclusive of bacteria, viruses, archaea, fungi, parasites, etc) and immune system in various body sites and influences tumour phenotypes. The systemic metabolic/inflammatory status, which is likely influenced by exposures and intestinal physiological changes, may affect tissue microenvironment of colorectum and any other organs. Germline genomic factors can modify disease phenotypes via gene-by-environment interactions. Although challenges exist, it is crucial to advance not only basic experimental research that can analyse the effects of exposures, microorganisms and microenvironmental components on tumour evolution but also interdisciplinary human population research that can dissect the complex pathogenic roles of the exposome, microbiome and immunome. Metagenomic, metatranscriptomic and metabolomic analyses should be integrated into well-designed population research combined with advanced methodologies of artificial intelligence and molecular pathological epidemiology. Ideally, a prospective cohort study design that enables biospecimen (such as stool) collection before disease detection should be considered to address reverse causation and recall biases. Robust experimental and observational research together can provide insights into dynamic interactions between environmental exposures, microbiota, tumour and immunity during carcinogenesis processes, thereby helping us develop precision prevention and therapeutic strategies to ultimately reduce the cancer burden.

An overview of machine learning methods for monotherapy drug response prediction

For an increasing number of preclinical samples, both detailed molecular profiles and their responses to various drugs are becoming available. Efforts to understand, and predict, drug responses in a data-driven manner have led to a proliferation of machine learning (ML) methods, with the longer term ambition of predicting clinical drug responses. Here, we provide a uniquely wide and deep systematic review of the rapidly evolving literature on monotherapy drug response prediction, with a systematic characterization and classification that comprises more than 70 ML methods in 13 subclasses, their input and output data types, modes of evaluation, and code and software availability. ML experts are provided with a fundamental understanding of the biological problem, and how ML methods are configured for it. Biologists and biomedical researchers are introduced to the basic principles of applicable ML methods, and their application to the problem of drug response prediction. We also provide systematic overviews of commonly used data sources used for training and evaluation methods.

The Interplay between the Host Microbiome and Pathogenic Viral Infections

The microorganisms associated with an organism, the microbiome, have a strong and wide impact in their host biology. In particular, the microbiome modulates both the host defense responses and immunity, thus influencing the fate of infections by pathogens. Indeed, this immune modulation and/or interaction with pathogenic viruses can be essential to define the outcome of viral infections. Understanding the interplay between the microbiome and pathogenic viruses opens future venues to fight viral infections and enhance the efficacy of antiviral therapies. An increasing number of researchers are focusing on microbiome-virus interactions, studying diverse combinations of microbial communities, hosts, and pathogenic viruses. Here, we aim to review these studies, providing an integrative overview of the microbiome impact on viral infection across different pathosystems.

Metabolomic Approaches to Investigate the Effect of Metformin: An Overview

Metformin is the first-line antidiabetic drug that is widely used in the treatment of type 2 diabetes mellitus (T2DM). Even though the various therapeutic potential of metformin treatment has been reported, as well as the improvement of insulin sensitivity and glucose homeostasis, the mechanisms underlying those benefits are still not fully understood. In order to explain the beneficial effects on metformin treatment, various metabolomics analyses have been applied to investigate the metabolic alterations in response to metformin treatment, and significant systemic metabolome changes were observed in biofluid, tissues, and cells. In this review, we compare the latest metabolomic research including clinical trials, animal models, and in vitro studies comprehensively to understand the overall changes of metabolome on metformin treatment.

The effects of sex on pharmacogenetically guided drug treatment

Tweetable abstract Sex-related pharmacogenetics is emerging area of research to better explain sex discrepancies in drug response. Sex pharmacogenetics should be considered an essential step for personalized medicine.

Comparative analysis of oral-gut microbiota between captive and wild long-tailed macaque in Thailand

Long-tailed macaques (Macaca fascicularis), distributed in Southeast Asia, are generally used in biomedical research. At present, the expansion of human communities overlapping of macaques’ natural habitat causes human-macaque conflicts. To mitigate this problem in Thailand, the National Primate Research Center of Thailand, Chulalongkorn University (NPRCT-CU), was granted the permit to catch the surplus wild-born macaques and transfer them to the center. Based on the fact that the diets provided and the captive environments were different, their oral-gut microbiota should be altered. Thus, we investigated and compared the oral and fecal microbiome between wild-born macaques that lived in the natural habitats and those transferred to and reared in the NPRCT-CU for 1 year. The results from 16S rRNA high-throughput sequencing showed that the captive macaques had distinct oral-gut microbiota profiles and lower bacterial richness compared to those in wild macaques. The gut of wild macaques was dominated by Firmicutes which is probably associated with lipid absorption and storage. These results implicated the effects of captivity conditions on the microbiome that might contribute to crucial metabolic functions. Our study should be applied to the animal health care program, with respect to microbial functions, for non-human primates.

C. elegans: A biosensor for host-microbe interactions

Microbes are an integral part of life on this planet. Microbes and their hosts influence each other in an endless dance that shapes how the meta-organism interacts with its environment. Although great advances have been made in microbiome research over the past 20 years, the mechanisms by which both hosts and their microbes interact with each other and the environment are still not well understood. The nematode Caenorhabditis elegans has been widely used as a model organism to study a remarkable number of human-like processes. Recent evidence shows that the worm is a powerful tool to investigate in fine detail the complexity that exists in microbe-host interactions. By combining the large array of genetic tools available for both organisms together with deep phenotyping approaches, it has been possible to uncover key effectors in the complex relationship between microbes and their hosts. In this perspective, we survey the literature for insightful discoveries in the microbiome field using the worm as a model. We discuss the latest conceptual and technological advances in the field and highlight the strengths that make C. elegans a valuable biosensor tool for the study of microbe-host interactions.

Integrative Data Analytic Framework to Enhance Cancer Precision Medicine

With the advancement of high-throughput biotechnologies, we increasingly accumulate biomedical data about diseases, especially cancer. There is a need for computational models and methods to sift through, integrate, and extract new knowledge from the diverse available data, to improve the mechanistic understanding of diseases and patient care. To uncover molecular mechanisms and drug indications for specific cancer types, we develop an integrative framework able to harness a wide range of diverse molecular and pan-cancer data. We show that our approach outperforms the competing methods and can identify new associations. Furthermore, it captures the underlying biology predictive of drug response. Through the joint integration of data sources, our framework can also uncover links between cancer types and molecular entities for which no prior knowledge is available. Our new framework is flexible and can be easily reformulated to study any biomedical problem.

Towards a mechanistic understanding of reciprocal drug-microbiome interactions

Broad-spectrum antibiotics target multiple gram-positive and gram-negative bacteria, and can collaterally damage the gut microbiota. Yet, our knowledge of the extent of damage, the antibiotic activity spectra, and the resistance mechanisms of gut microbes is sparse. This limits our ability to mitigate microbiome-facilitated spread of antibiotic resistance. In addition to antibiotics, non-antibiotic drugs affect the human microbiome, as shown by metagenomics as well as in vitro studies. Microbiome-drug interactions are bidirectional, as microbes can also modulate drugs. Chemical modifications of antibiotics mostly function as antimicrobial resistance mechanisms, while metabolism of non-antibiotics can also change the drugs' pharmacodynamic, pharmacokinetic, and toxic properties. Recent studies have started to unravel the extensive capacity of gut microbes to metabolize drugs, the mechanisms, and the relevance of such events for drug treatment. These findings raise the question whether and to which degree these reciprocal drug-microbiome interactions will differ across individuals, and how to take them into account in drug discovery and precision medicine. This review describes recent developments in the field and discusses future study areas that will benefit from systems biology approaches to better understand the mechanistic role of the human gut microbiota in drug actions.

Impact drugs targeting cardiometabolic risk on the gut microbiota

PURPOSE OF REVIEW

Alterations in the gut microbiome composition or function are associated with risk factors for cardiometabolic diseases, including hypertension, hyperlipidemia and hyperglycemia. Based on recent evidence that also oral medications used to treat these conditions could alter the gut microbiome composition and function and, vice versa, that the gut microbiome could affect the efficacy of these treatments, we reviewed the literature on these observed interactions.

RECENT FINDINGS

While the interaction of metformin with the gut microbiome has been studied most, other drugs that target cardiometabolic risk are gaining attention and often showed associations with alterations in microbiome-related features, including alterations in specific microbial taxa or pathways, microbiome composition or microbiome-derived metabolites, while the gut microbiome was also involved in drug metabolism and drug efficacy. As for metformin, for some of them even a potential therapeutic effect via the gut microbiome is postulated. However, exact mechanisms remain to be elucidated.

SUMMARY

There is growing interest in clarifying the interactions between the gut microbiome and drugs to treat hypertension, hyperlipidemia and hyperglycemia as well as the first pass effect of microbiome on drug efficacy. While mostly analysed in animal models, also human studies are gaining more and more traction. Improving the understanding of the gut microbiome drug interaction can provide clinical directions for therapy by optimizing drug efficacy or providing new targets for drug development.

Enteral Medication for the Tube-Fed Patient: Making This Route Safe and Effective

The administration of medication through an enteral access device requires important forethought. Meeting a patient's therapeutic needs requires achieving expected drug bioavailability without increasing the risk for toxicity, therapeutic failure, or feeding tube occlusion. Superimposing gut dysfunction, critical illness, or enteral nutrition-drug interaction further increases the need for a systematic approach to prescribing, evaluating, and preparing a drug for administration through an enteral access device. This review will explain the fundamental factors involved in drug bioavailability through the gut, address the influencing considerations for the enterally fed patient, and describe best practices for enteral drug preparation and administration.

Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods

Microbiomes are integral components of diverse ecosystems, and increasingly recognized for their roles in the health of humans, animals, plants, and other hosts. Given their complexity (both in composition and function), the effective study of microbiomes (microbiomics) relies on the development, optimization, and validation of computational methods for analyzing microbial datasets, such as from marker-gene (e.g., 16S rRNA gene) and metagenome data. This review describes best practices for benchmarking and implementing computational methods (and software) for studying microbiomes, with particular focus on unique characteristics of microbiomes and microbiomics data that should be taken into account when designing and testing microbiomics methods.

Evolved bacterial resistance against fluoropyrimidines can lower chemotherapy impact in the Caenorhabditis elegans host

Metabolism of host-targeted drugs by the microbiome can substantially impact host treatment success. However, since many host-targeted drugs inadvertently hamper microbiome growth, repeated drug administration can lead to microbiome evolutionary adaptation. We tested if evolved bacterial resistance against host-targeted drugs alters their drug metabolism and impacts host treatment success. We used a model system of Caenorhabditis elegans, its bacterial diet, and two fluoropyrimidine chemotherapies. Genetic screens revealed that most of loss-of-function resistance mutations in Escherichia coli also reduced drug toxicity in the host. We found that resistance rapidly emerged in E. coli under natural selection and converged to a handful of resistance mechanisms. Surprisingly, we discovered that nutrient availability during bacterial evolution dictated the dietary effect on the host - only bacteria evolving in nutrient-poor media reduced host drug toxicity. Our work suggests that bacteria can rapidly adapt to host-targeted drugs and by doing so may also impact the host.

Current Trends in Experimental and Computational Approaches to Combat Antimicrobial Resistance

A multitude of factors, such as drug misuse, lack of strong regulatory measures, improper sewage disposal, and low-quality medicine and medications, have been attributed to the emergence of drug resistant microbes. The emergence and outbreaks of multidrug resistance to last-line antibiotics has become quite common. This is further fueled by the slow rate of drug development and the lack of effective resistome surveillance systems. In this review, we provide insights into the recent advances made in computational approaches for the surveillance of antibiotic resistomes, as well as experimental formulation of combinatorial drugs. We explore the multiple roles of antibiotics in nature and the current status of combinatorial and adjuvant-based antibiotic treatments with nanoparticles, phytochemical, and other non-antibiotics based on synergetic effects. Furthermore, advancements in machine learning algorithms could also be applied to combat the spread of antibiotic resistance. Development of resistance to new antibiotics is quite rapid. Hence, we review the recent literature on discoveries of novel antibiotic resistant genes though shotgun and expression-based metagenomics. To decelerate the spread of antibiotic resistant genes, surveillance of the resistome is of utmost importance. Therefore, we discuss integrative applications of whole-genome sequencing and metagenomics together with machine learning models as a means for state-of-the-art surveillance of the antibiotic resistome. We further explore the interactions and negative effects between antibiotics and microbiomes upon drug administration.

Targeting gut microbiota for precision medicine: Focusing on the efficacy and toxicity of drugs

Intra- and interindividual variation in drug responses is one major reason for the failure of drug therapy, drug toxicity, and even the death of patients. Precision medicine, or personalized medicine, is a field of medicine that customizes an individual's medical diagnosis and treatment based on his/her genes, microbiomes, environments, etc. Over the past decade, a large number of studies have demonstrated that gut microbiota can modify the efficacy and toxicity of drugs, and the extent of the modification varies greatly from person to person because of the variability of the gut microbiota. Personalized manipulation of gut microbiota is an important approach to rectify the abnormal drug response. In this review, we aim to improve drug efficacy and reduce drug toxicity by combining precision medicine and gut microbiota. After describing the interactions between gut microbiota and xenobiotics, we discuss (1) the effects of gut microbiota on drug efficacy and toxicity and the corresponding mechanisms, (2) the variability of gut microbiota, which leads to variation in drug responses, (3) the biomarkers used for the patient stratification and treatment decisions before the use of drugs, and (4) the methods used for the personalized manipulation of gut microbiota to improve drug outcomes. Overall, we hope to improve the drug response by incorporating the knowledge of gut microbiota into clinical practice.

Tissue regulatory T cells

Foxp3+  CD4+ regulatory T cells (Tregs) are an immune cell lineage endowed with immunosuppressive functionality in a wide array of contexts, including both anti-pathogenic and anti-self responses. In the past decades, our understanding of the functional diversity of circulating or lymphoid Tregs has grown exponentially. Only recently, the importance of Tregs residing within non-lymphoid tissues, such as visceral adipose tissue, muscle, skin and intestine, has been recognized. Not only are Tregs critical for influencing the kinetics and strength of immune responses, but the regulation of non-immune or parenchymal cells, also fall within the purview of tissue-resident or infiltrating Tregs. This review focuses on providing a systematic and comprehensive comparison of the molecular maintenance, local adaptation and functional specializations of Treg populations operating within different tissues.

Structure of a gut microbial diltiazem-metabolizing enzyme suggests possible substrate binding mode

When administrated orally, the vasodilating drug diltiazem can be metabolized into diacetyl diltiazem in the presence of Bacteroides thetaiotaomicron, a human gut microbe. The removal of acetyl group from the parent drug is carried out by the GDSL/SGNH-family hydrolase BT4096. Here the crystal structure of the enzyme was solved by mercury soaking and single-wavelength anomalous diffraction. The protein folds into two parts. The N-terminal part comprises the catalytic domain which is similar to other GDSL/SGNH hydrolases. The flanking C-terminal part is made up of a β-barrel subdomain and an α-helical subdomain. Structural comparison shows that the catalytic domain is most akin to acetyl-xylooligosaccharide esterase and allows a plausible binding mode of diltiazem to be proposed. The β-barrel subdomain is similar in topology to the immunoglobulin-like domains, including some carbohydrate-binding modules, of various bacterial glycoside hydrolases. Consequently, BT4096 might originally function as an oligosaccharide deacetylase with additional subdomains that could enhance substrate binding, and it acts on diltiazem just by accident.

Cancer therapy with iron oxide nanoparticles: Agents of thermal and immune therapies

Significant research and preclinical investment in cancer nanomedicine has produced several products, which have improved cancer care. Nevertheless, there exists a perception that cancer nanomedicine 'has not lived up to its promise' because the number of approved products and their clinical performance are modest. Many of these analyses do not consider the long clinical history and many clinical products developed from iron oxide nanoparticles. Iron oxide nanoparticles have enjoyed clinical use for about nine decades demonstrating safety, and considerable clinical utility and versatility. FDA-approved applications of iron oxide nanoparticles include cancer diagnosis, cancer hyperthermia therapy, and iron deficiency anemia. For cancer nanomedicine, this wealth of clinical experience is invaluable to provide key lessons and highlight pitfalls in the pursuit of nanotechnology-based cancer therapeutics. We review the clinical experience with systemic liposomal drug delivery and parenteral therapy of iron deficiency anemia (IDA) with iron oxide nanoparticles. We note that the clinical success of injectable iron exploits the inherent interaction between nanoparticles and the (innate) immune system, which designers of liposomal drug delivery seek to avoid. Magnetic fluid hyperthermia, a cancer therapy that harnesses magnetic hysteresis heating is approved for treating humans only with iron oxide nanoparticles. Despite its successful demonstration to enhance overall survival in clinical trials, this nanotechnology-based thermal medicine struggles to establish a clinical presence. We review the physical and biological attributes of this approach, and suggest reasons for barriers to its acceptance. Finally, despite the extensive clinical experience with iron oxide nanoparticles new and exciting research points to surprising immune-modulating potential. Recent data demonstrate the interactions between immune cells and iron oxide nanoparticles can induce anti-tumor immune responses. These present new and exciting opportunities to explore additional applications with this venerable technology. Clinical applications of iron oxide nanoparticles present poignant case studies of the opportunities, complexities, and challenges in cancer nanomedicine. They also illustrate the need for revised paradigms and multidisciplinary approaches to develop and translate nanomedicines into clinical cancer care.

Gut microbiota contributes towards immunomodulation against cancer: New frontiers in precision cancer therapeutics

The microbiota influences human health and the development of diverse diseases, including cancer. Microbes can influence tumor initiation and development in either a positive or negative manner. In addition, the composition of the gut microbiota affects the efficacy and toxicity of cancer therapeutics as well as therapeutic resistance. The striking impact of microbiota on oncogenesis and cancer therapy provides compelling evidence to support the notion that manipulating microbial networks represents a promising strategy for treating and preventing cancer. Specific microbes or the microbial ecosystem can be modified via a multiplicity of processes, and therapeutic methods and approaches have been evolving. Microbial manipulation can be applied as an adjunct to traditional cancer therapies such as chemotherapy and immunotherapy. Furthermore, this approach displays great promise as a stand-alone therapy following the failure of standard therapy. Moreover, such strategies may also benefit patients by avoiding the emergence of toxic side effects that result in treatment discontinuation. A better understanding of the host-microbial ecosystem in patients with cancer, together with the development of methodologies for manipulating the microbiome, will help expand the frontiers of precision cancer therapeutics, thereby improving patient care. This review discusses the roles of the microbiota in oncogenesis and cancer therapy, with a focus on efforts to harness the microbiota to fight cancer.

Therapies from Fucoidan: New Developments

Since our last review in 2015, the study and use of fucoidan has extended in several research areas. Clinical use of fucoidan for the treatment of renal disease has become available and human safety studies have been undertaken on radiolabeled fucoidan for the purpose of imaging thrombi. Fucoidan has been incorporated into an increasing number of commercially available supplements and topical treatments. In addition, new measuring techniques are now available to assess the biologically relevant uptake of fucoidans and to assist in production. Microbiome modulation and anti-pathogenic effects are increasingly promising applications for fucoidans, due to the need for alternative approaches to antibiotic use in the food chain. This review outlines promising new developments in fucoidan research, including potential future therapeutic use.