The significance of microbiome in personalized medicine

Interactions between the intestinal microbiota and drug metabolism - Clinical implications and future opportunities

The importance of the intestinal microbita in a multitude of physiological processes is well-evidenced. These include metabolism of nutrients and xenobiotics, biosynthesis of vitamin K and vitamin B12, immunomodulation, maintenance of the gut mucosal barrier integrity and protection against some pathogens. Interindividual differences in the intestinal microbiota composition have impacts on health. The bioavailability and activity of some pharmaceuticals are heavily influenced by interindividual variability in metabolism, which has a genetic basis. This variability, primarily occurring in the liver but also in the intestine, has been studied extensively. Despite the advancement of this field - pharmacogenetics - its integration into clinical practice remains limited for reasons discussed herein. This highlights the even greater challenge of applying emerging knowledge on variability in the gut microbiota to drug therapy. However, ignoring these opportunities would be a mistake. While clinical applications of microbiota-guided drug therapy are currently absent and the ideas in this article are largely theoretical, research is uncovering that in cases where a substantial portion of a drug or its metabolites reaches the colon, or where drugs are formulated for colonic delivery, the gut microbiota can significantly affect drug metabolism and activity. Greater focus should be placed on research into how interindividual variability in the intestinal microbiome can modify pharmaceutical bioavailability and activity. This article is deliberately speculative and exploratory but proposes that, though there are still no clinical examples of microbiome-guided drug therapy, these interactions could afford opportunities for improvements in personalised medicine and also for drug design.

The Gut Mycobiome for Precision Medicine

The human gastrointestinal tract harbors a vast array of microorganisms, which play essential roles in maintaining metabolic balance and immune function. While bacteria dominate the gut microbiome, fungi represent a much smaller, often overlooked fraction. Despite their relatively low abundance, fungi may significantly influence both health and disease. Advances in next-generation sequencing, metagenomics, metatranscriptomics, metaproteomics, metabolomics, and computational biology have provided novel opportunities to study the gut mycobiome, shedding light on its composition, functional genes, and metabolite interactions. Emerging evidence links fungal dysbiosis to various diseases, including inflammatory bowel disease, colorectal cancer, metabolic disorders, and neurological conditions. The gut mycobiome also presents a promising avenue for precision medicine, particularly in biomarker discovery, disease diagnostics, and targeted therapeutics. Nonetheless, significant challenges remain in effectively integrating gut mycobiome knowledge into clinical practice. This review examines gut fungal microbiota, highlighting analytical methods, associations with human diseases, and its potential role in precision medicine. It also discusses pathways for clinical translation, particularly in diagnosis and treatment, while addressing key barriers to implementation.

Microbiomes in action: multifaceted benefits and challenges across academic disciplines

Microbiomes combine the species and activities of all microorganisms living together in a specific habitat. They comprise unique ecological niches with influences that scale from local to global ecosystems. Understanding the connectivity of microbiomes across academic disciplines is important to help mitigate global climate change, reduce food insecurity, control harmful diseases, and ensure environmental sustainability. However, most publications refer to individual microbiomes, and those integrating two or more related disciplines are rare. This review examines the multifaceted benefits of microbiomes across agriculture, food manufacturing and preservation, the natural environment, human health, and biocatalyst processes. Plant microbiomes, by improving plant nutrient cycling and increasing plant abiotic and biotic stress resilience, have increased crop yields by over 20%. Food microbiomes generate approximately USD 30 billion to the global economy through the fermented food industry alone. Environmental microbiomes help detoxify pollutants, absorb more than 90% of heavy metals, and facilitate carbon sequestration. For human microbiomes, an adult person can carry up to 38 trillion microbes which regulate well being, immune functionality, reproductive function, and disease prevention. Microbiomes are used to optimize biocatalyst processes which produce bioenergy and biochemicals; bioethanol production alone is valued at over USD 83 billion p.a. However, challenges, including knowledge gaps, engaging indigenous communities, technical limitations, regulatory considerations, the need for interdisciplinary collaboration, and ethical issues, must be overcome before the potential for microbiomes can be more effectively realized.

Wise Roles and Future Visionary Endeavors of Current Emperor: Advancing Dynamic Methods for Longitudinal Microbiome Meta-Omics Data in Personalized and Precision Medicine

Understanding the etiological complexity of diseases requires identifying biomarkers longitudinally associated with specific phenotypes. Advanced sequencing tools generate dynamic microbiome data, providing insights into microbial community functions and their impact on health. This review aims to explore the current roles and future visionary endeavors of dynamic methods for integrating longitudinal microbiome multi-omics data in personalized and precision medicine. This work seeks to synthesize existing research, propose best practices, and highlight innovative techniques. The development and application of advanced dynamic methods, including the unified analytical frameworks and deep learning tools in artificial intelligence, are critically examined. Aggregating data on microbes, metabolites, genes, and other entities offers profound insights into the interactions among microorganisms, host physiology, and external stimuli. Despite progress, the absence of gold standards for validating analytical protocols and data resources of various longitudinal multi-omics studies remains a significant challenge. The interdependence of workflow steps critically affects overall outcomes. This work provides a comprehensive roadmap for best practices, addressing current challenges with advanced dynamic methods. The review underscores the biological effects of clinical, experimental, and analytical protocol settings on outcomes. Establishing consensus on dynamic microbiome inter-studies and advancing reliable analytical protocols are pivotal for the future of personalized and precision medicine.

Exploring the Frontier: The Human Microbiome's Role in Rare Childhood Neurological Diseases and Epilepsy

Emerging research into the human microbiome, an intricate ecosystem of microorganisms residing in and on our bodies, reveals that it plays a pivotal role in maintaining our health, highlighting the potential for microbiome-based interventions to prevent, diagnose, treat, and manage a myriad of diseases. The objective of this review is to highlight the importance of microbiome studies in enhancing our understanding of rare genetic epilepsy and related neurological disorders. Studies suggest that the gut microbiome, acting through the gut-brain axis, impacts the development and severity of epileptic conditions in children. Disruptions in microbial composition can affect neurotransmitter systems, inflammatory responses, and immune regulation, which are all critical factors in the pathogenesis of epilepsy. This growing body of evidence points to the potential of microbiome-targeted therapies, such as probiotics or dietary modifications, as innovative approaches to managing epilepsy. By harnessing the power of the microbiome, we stand to develop more effective and personalized treatment strategies for children affected by this disease and other rare neurological diseases.

Personalized identification of autism-related bacteria in the gut microbiome using explainable artificial intelligence

Autism spectrum disorder (ASD) affects social interaction and communication. Emerging evidence links ASD to gut microbiome alterations, suggesting that microbial composition may play a role in the disorder. This study employs explainable artificial intelligence (XAI) to examine the contributions of individual microbial species to ASD. By using local explanation embeddings and unsupervised clustering, the research identifies distinct ASD subgroups, underscoring the disorder's heterogeneity. Specific microbial biomarkers associated with ASD are revealed, and the best classifiers achieved an AU-ROC of 0.965 ± 0.005 and an AU-PRC of 0.967 ± 0.008. The findings support the notion that gut microbiome composition varies significantly among individuals with ASD. This work's broader significance lies in its potential to inform personalized interventions, enhancing precision in ASD management and classification. These insights highlight the importance of individualized microbiome profiles for developing tailored therapeutic strategies for ASD.

Extracellular Vesicles of the Probiotic Escherichia coli Nissle 1917 Reduce PepT1 Levels in IL-1β-Treated Caco-2 Cells via Upregulation of miR-193a-3p

PepT1, a proton-coupled oligopeptide transporter, is crucial for intestinal homeostasis. It is mainly expressed in small intestine enterocytes, facilitating the absorption of di/tri-peptides from dietary proteins. In the colon, PepT1 expression is minimal to prevent excessive responses to proinflammatory peptides from the gut microbiota. However, increased colonic PepT1 is linked to chronic inflammatory diseases and colitis-associated cancer. Despite promising results from animal studies on the benefits of extracellular vesicles (EVs) from beneficial gut commensals in treating IBD, applying probiotic EVs as a postbiotic strategy in humans requires a thorough understanding of their mechanisms. Here, we investigate the potential of EVs of the probiotic Nissle 1917 (EcN) and the commensal EcoR12 in preventing altered PepT1 expression under inflammatory conditions, using an interleukin (IL)-1-induced inflammation model in Caco-2 cells. The effects are evaluated by analyzing the expression of PepT1 (mRNA and protein) and miR-193a-3p and miR-92b, which regulate, respectively, PepT1 mRNA translation and degradation. The influence of microbiota EVs on PepT1 expression is also analyzed in the presence of bacterial peptides that are natural substrates of colonic PepT1 to clarify how the regulatory mechanisms function under both physiological and pathological conditions. The main finding is that EcN EVs significantly decreases PepT1 protein via upregulation of miR-193a-3p. Importantly, this regulatory effect is strain-specific and only activates in cells exposed to IL-1β, suggesting that EcN EVs does not control PepT1 expression under basal conditions but can play a pivotal role in response to inflammation as a stressor. By this mechanism, EcN EVs may reduce inflammation in response to microbiota in chronic intestinal disorders by limiting the uptake of bacterial proinflammatory peptides.

Network impact of a single-time-point microbial sample

The human microbiome plays a crucial role in determining our well-being and can significantly influence human health. The individualized nature of the microbiome may reveal host-specific information about the health state of the subject. In particular, the microbiome is an ecosystem shaped by a tangled network of species-species and host-species interactions. Thus, analysis of the ecological balance of microbial communities can provide insights into these underlying interrelations. However, traditional methods for network analysis require many samples, while in practice only a single-time-point microbial sample is available in clinical screening. Recently, a method for the analysis of a single-time-point sample, which evaluates its 'network impact' with respect to a reference cohort, has been applied to analyze microbial samples from women with Gestational Diabetes Mellitus. Here, we introduce different variations of the network impact approach and systematically study their performance using simulated 'samples' fabricated via the Generalized Lotka-Volttera model of ecological dynamics. We show that the network impact of a single sample captures the effect of the interactions between the species, and thus can be applied to anomaly detection of shuffled samples, which are 'normal' in terms of species abundance but 'abnormal' in terms of species-species interrelations. In addition, we demonstrate the use of the network impact in binary and multiclass classifications, where the reference cohorts have similar abundance profiles but different species-species interactions. Individualized analysis of the human microbiome has the potential to improve diagnosis and personalized treatments.

From the Gut to the Brain: Is Microbiota a New Paradigm in Parkinson's Disease Treatment?

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiota in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiota axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiota. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiota on PD and whether this may be a new paradigm for treating this devastating disease.

The gut microbiome as a modulator of arterial function and age-related arterial dysfunction

The arterial system is integral to the proper function of all other organs and tissues. Arterial function is impaired with aging, and arterial dysfunction contributes to the development of numerous age-related diseases, including cardiovascular diseases. The gut microbiome has emerged as an important regulator of both normal host physiological function and impairments in function with aging. The purpose of this review is to summarize more recently published literature demonstrating the role of the gut microbiome in supporting normal arterial development and function and in modulating arterial dysfunction with aging in the absence of overt disease. The gut microbiome can be altered due to a variety of exposures, including physiological aging processes. We explore mechanisms by which the gut microbiome may contribute to age-related arterial dysfunction, with a focus on changes in various gut microbiome-related compounds in circulation. In addition, we discuss how modulating circulating levels of these compounds may be a viable therapeutic approach for improving artery function with aging. Finally, we identify and discuss various experimental considerations and research gaps/areas of future research.

Promoting advanced medical services in the framework of 3PM-a proof-of-concept by the "Centro" Region of Portugal

Multidisciplinary team from three universities based in the "Centro" Region of Portugal developed diverse approaches as parts of a project dedicated to enhancing and expanding Predictive, Preventive, and Personalized Medicine (3PM) in the Region. In a sense, outcomes acted as a proof-of-concept, in that they demonstrated the feasibility, but also the relevance of the approaches. The accomplishments comprise defining a new regional strategy for implementing 3PM within the Region, training of human resources in genomic sequencing, and generating good practices handbooks dedicated to diagnostic testing via next-generation sequencing, to legal and ethical concerns, and to knowledge transfer and entrepreneurship, aimed at increasing literacy on 3PM approaches. Further approaches also included support for entrepreneurship development and start-ups, and diverse and relevant initiatives aimed at increasing literacy relevant to 3PM. Efforts to enhance literacy encompassed citizens across the board, from patients and high school students to health professionals and health students. This focus on empowerment through literacy involved a variety of initiatives, including the creation of an illustrated book on genomics and the production of two theater plays centered on genetics. Additionally, authors stressed that genomic tools are relevant, but they are not the only resources 3PM is based on. Thus, they defend that other initiatives intended to enable citizens to take 3PM should include multi-omics and, having in mind the socio-economic burden of chronic diseases, suboptimal health status approaches in the 3PM framework should also be considered, in order to anticipate medical intervention in the subclinical phase.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00353-9.

Decentralized ORP Measurements for Gut Redox Status Monitoring: Toward Personalized Gut Microbiota Balance

Gut microbiome targeting has emerged as a new generation of personalized medicine and a potential wellness and disease driver. Specifically, the gut redox balance plays a key role in shaping the gut microbiota and its link with the host, immune system, and disease evolution. In this sense, precise and personalized nutrition has proven synergy and capability to modulate the gut microbiome environment through the formulation of dietary interventions, such as vitamin support. Accordingly, there are urgent demands for simple and effective analytical platforms for understanding the relationship between the tailored vitamin administration and the gut microbiota balance by rapid noninvasive on-the-spot oxidation/reduction potential monitoring for frequent and close surveillance of the gut redox status and targeting by personalized nutrition interventions. Herein, we present a disposable potentiometric sensor chip and a homemade multiwell potentiometric array to address the interplay of vitamin levels with the oxidation/reduction potential in human feces and saliva. The potentiometric ORP sensing platforms have been successfully validated and scaled up for the setup of a multiapplication prototype for cross-talk-free simple screening of many specimens. The interpersonal variability of the gut microbiota environment illustrates the potential of feces and saliva samples for noninvasive, frequent, and decentralized monitoring of the gut redox status to support timely human microbiota surveillance and guide precise dietary intervention toward restoring and promoting personalized gut redox balance.

The contribution of age-related changes in the gut-brain axis to neurological disorders

Trillions of microbes live symbiotically in the host, specifically in mucosal tissues such as the gut. Recent advances in metagenomics and metabolomics have revealed that the gut microbiota plays a critical role in the regulation of host immunity and metabolism, communicating through bidirectional interactions in the microbiota-gut-brain axis (MGBA). The gut microbiota regulates both gut and systemic immunity and contributes to the neurodevelopment and behaviors of the host. With aging, the composition of the microbiota changes, and emerging studies have linked these shifts in microbial populations to age-related neurological diseases (NDs). Preclinical studies have demonstrated that gut microbiota-targeted therapies can improve behavioral outcomes in the host by modulating microbial, metabolomic, and immunological profiles. In this review, we discuss the pathways of brain-to-gut or gut-to-brain signaling and summarize the role of gut microbiota and microbial metabolites across the lifespan and in disease. We highlight recent studies investigating 1) microbial changes with aging; 2) how aging of the maternal microbiome can affect offspring health; and 3) the contribution of the microbiome to both chronic age-related diseases (e.g., Parkinson's disease, Alzheimer's disease and cerebral amyloidosis), and acute brain injury, including ischemic stroke and traumatic brain injury.

Triangulating nutrigenomics, metabolomics and microbiomics toward personalized nutrition and healthy living

The unique physiological and genetic characteristics of individuals influence their reactions to different dietary constituents and nutrients. This notion is the foundation of personalized nutrition. The field of nutrigenetics has witnessed significant progress in understanding the impact of genetic variants on macronutrient and micronutrient levels and the individual's responsiveness to dietary intake. These variants hold significant value in facilitating the development of personalized nutritional interventions, thereby enabling the effective translation from conventional dietary guidelines to genome-guided nutrition. Nevertheless, certain obstacles could impede the extensive implementation of individualized nutrition, which is still in its infancy, such as the polygenic nature of nutrition-related pathologies. Consequently, many disorders are susceptible to the collective influence of multiple genes and environmental interplay, wherein each gene exerts a moderate to modest effect. Furthermore, it is widely accepted that diseases emerge because of the intricate interplay between genetic predisposition and external environmental influences. In the context of this specific paradigm, the utilization of advanced "omic" technologies, including epigenomics, transcriptomics, proteomics, metabolomics, and microbiome analysis, in conjunction with comprehensive phenotyping, has the potential to unveil hitherto undisclosed hereditary elements and interactions between genes and the environment. This review aims to provide up-to-date information regarding the fundamentals of personalized nutrition, specifically emphasizing the complex triangulation interplay among microbiota, dietary metabolites, and genes. Furthermore, it highlights the intestinal microbiota's unique makeup, its influence on nutrigenomics, and the tailoring of dietary suggestions. Finally, this article provides an overview of genotyping versus microbiomics, focusing on investigating the potential applications of this knowledge in the context of tailored dietary plans that aim to improve human well-being and overall health.

Microbial Dysbiosis and Male Infertility: Understanding the Impact and Exploring Therapeutic Interventions

The human microbiota in the genital tract is pivotal for maintaining fertility, but its disruption can lead to male infertility. This study examines the relationship between microbial dysbiosis and male infertility, underscoring the promise of precision medicine in this field. Through a comprehensive review, this research indicates microbial signatures associated with male infertility, such as altered bacterial diversity, the dominance of pathogenic species, and imbalances in the genital microbiome. Key mechanisms linking microbial dysbiosis to infertility include inflammation, oxidative stress, and sperm structural deterioration. Emerging strategies like targeted antimicrobial therapies, probiotics, prebiotics, and fecal microbiota transplantation have shown potential in adjusting the genital microbiota to enhance male fertility. Notably, the application of precision medicine, which customizes treatments based on individual microbial profiles and specific causes of infertility, emerges as a promising approach to enhance treatment outcomes. Ultimately, microbial dysbiosis is intricately linked to male infertility, and embracing personalized treatment strategies rooted in precision medicine principles could be the way forward in addressing infertility associated with microbial factors.

Exploring the complex role of gut microbiome in the development of precision medicine strategies for targeting microbial imbalance-induced colon cancer

The gut microbiome has been increasingly recognized as a key player in the development and progression of colon cancer. Alterations in the gut microbiota, known as dysbiosis, can lead to a variety of medical issues. Microbial adaptation through signals and small molecules can enhance pathogen colonization and modulate host immunity, significantly impacting disease progression. Quorum sensing peptides and molecules have been linked to the progression of colon cancer. Various interventions, such as fecal microbiota transplantation, probiotics, prebiotics, synbiotics, and antibiotics, have been used to reverse dysbiosis with mixed results and potential side effects. Thus, a personalized approach to treatment selection based on patient characteristics, such as individual gut microbiota manipulation, is necessary to prevent and treat diseases like colon cancer. With advances in metagenomic sequencing and other omics technologies, there has been a growing interest in developing precision medicine strategies for microbial imbalance-induced colon cancer. This review serves as a comprehensive synthesis of current knowledge on the gut microbiome involvement in colon cancer. By exploring the potential of utilizing the gut microbiome as a target for precision medicine, this review underscores the exciting opportunities that lie ahead. Although challenges exist, the integration of microbiome data into precision medicine approaches has the potential to revolutionize the management of colon cancer, providing patients with more personalized and effective treatment options.

Machine learning approaches in microbiome research: challenges and best practices

Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To assist decision-making, we offer a set of recommendations on algorithm selection, pipeline creation and evaluation, stemming from the COST Action ML4Microbiome. We compared the suggested approaches on a multi-cohort shotgun metagenomics dataset of colorectal cancer patients, focusing on their performance in disease diagnosis and biomarker discovery. It is demonstrated that the use of compositional transformations and filtering methods as part of data preprocessing does not always improve the predictive performance of a model. In contrast, the multivariate feature selection, such as the Statistically Equivalent Signatures algorithm, was effective in reducing the classification error. When validated on a separate test dataset, this algorithm in combination with random forest modeling, provided the most accurate performance estimates. Lastly, we showed how linear modeling by logistic regression coupled with visualization techniques such as Individual Conditional Expectation (ICE) plots can yield interpretable results and offer biological insights. These findings are significant for clinicians and non-experts alike in translational applications.

Gut Microbiota Modulation of Short Bowel Syndrome and the Gut-Brain Axis

Short bowel syndrome (SBS) is a condition that results from a reduction in the length of the intestine or its functional capacity. SBS patients can have significant side effects and complications, the etiology of which remains ill-defined. Thus, facilitating intestinal adaptation in SBS remains a major research focus. Emerging data supports the role of the gut microbiome in modulating disease progression. There has been ongoing debate on defining a "healthy" gut microbiome, which has led to many studies analyzing the bacterial composition and shifts that occur in gastrointestinal disease states such as SBS and the resulting systemic effects. In SBS, it has also been found that microbial shifts are highly variable and dependent on many factors, including the anatomical location of bowel resection, length, and structure of the remnant bowel, as well as associated small intestinal bacterial overgrowth (SIBO). Recent data also notes a bidirectional communication that occurs between enteric and central nervous systems called the gut-brain axis (GBA), which is regulated by the gut microbes. Ultimately, the role of the microbiome in disease states such as SBS have many clinical implications and warrant further investigation. The focus of this review is to characterize the role of the gut microbiota in short bowel syndrome and its impact on the GBA, as well as the therapeutic potential of altering the microbiome.

Revitalizing myocarditis treatment through gut microbiota modulation: unveiling a promising therapeutic avenue

Numerous studies have demonstrated that gut microbiota plays an important role in the development and treatment of different cardiovascular diseases, including hypertension, heart failure, myocardial infarction, arrhythmia, and atherosclerosis. Furthermore, evidence from recent studies has shown that gut microbiota contributes to the development of myocarditis. Myocarditis is an inflammatory disease that often results in myocardial damage. Myocarditis is a common cause of sudden cardiac death in young adults. The incidence of myocarditis and its associated dilated cardiomyopathy has been increasing yearly. Myocarditis has gained significant attention on social media due to its association with both COVID-19 and COVID-19 vaccinations. However, the current therapeutic options for myocarditis are limited. In addition, little is known about the potential therapeutic targets of myocarditis. In this study, we review (1) the evidence on the gut-heart axis, (2) the crosslink between gut microbiota and the immune system, (3) the association between myocarditis and the immune system, (4) the impact of gut microbiota and its metabolites on myocarditis, (5) current strategies for modulating gut microbiota, (6) challenges and future directions for targeted gut microbiota in the treatment of myocarditis. The approach of targeting the gut microbiota in myocarditis is still in its infancy, and this is the study to explore the gut microbiota-immune system-myocarditis axis. Our findings are expected to pave the way for the use of gut microbiota as a potential therapeutic target in the treatment of myocarditis.

Oral Microbiome, Mental Health, and Sleep Outcomes During the COVID-19 Pandemic: An Observational Study in Chinese and Korean American Immigrants

COVID-19 is a systemic disease whose effects are not limited to the respiratory system. The oral microbiome (OM)-brain axis is of growing interest in understanding the broader, neuropsychiatric, impacts of the COVID-19 pandemic through a systems biology lens. In this context, mental health and sleep disturbance are often reported by Asian Americans. In a cross-sectional observational study design, we examined the associations of the oral microbiome with mental health among Asian Americans during the COVID-19 pandemic (between November 2020 and April 2021). Participants (n = 20) were adult Chinese and Korean American immigrants in Atlanta, Georgia, and primarily born outside the United States (60%) with a mean age of 34.8 years ±14 (standard deviation). Participants reported depressive symptoms, anxiety, and sleep disturbance, as measured by standard questionnaires. The OM was characterized by 16S rRNA V3-V4 gene using saliva. Depressive symptoms and anxiety were reported by 60% (n = 12) of participants, whereas 35% (n = 7) reported sleep disturbance. The α-diversity was significantly associated with depressive symptoms, and marginally with anxiety. Participants with depressive symptoms and anxiety had enriched Rothia and Scardovia, respectively, whereas those without symptoms had enriched Fusobacterium. Individuals with sleep disturbance had enriched Kingella. In conclusion, this study suggests significant associations of the OM diversity with certain mental health dimensions such as depressive symptoms and anxiety. Specific taxa were associated with these symptoms. The present observations in a modest sample size suggest the possible relevance of the OM-brain axis in studies of mental health during COVID-19.

Unlocking a novel determinant of athletic performance: The role of the gut microbiota, short-chain fatty acids, and "biotics" in exercise

The gut microbiota refers to the collection of trillions of intestinal microorganisms that modulate central aspects of health and disease through influential effects on host physiology. Recently, a connection has been made between the gut microbiota and exercise. Initial investigations demonstrated the beneficial effects of exercise on the gut microbiota, with cross-sectional studies revealing positive correlations between exercise-associated states, and healthy gut microbiota and exercise interventions showed post-intervention increases in the abundance of beneficial bacterial taxa. More recent investigations have focused on exploring the reverse relationship: the influence of the gut microbiota on exercise performance. Murine investigations have revealed that certain bacterial taxa may enhance endurance exercise performance by augmenting various aspects of lactate metabolism. Further, short-chain fatty acids-which modulate metabolism at various organ sites, including within skeletal muscle-have been shown to enhance endurance exercise capacity in mice. This review highlights what is currently known about the connection between the gut microbiota and exercise, with a particular focus on the ergogenic potential of the gut microbiota and how it may be leveraged to enhance endurance exercise performance.

The Importance of the Microbiota in Shaping Women’s Health—The Current State of Knowledge

According to current knowledge, a properly colonized human microbiota contributes to the proper functioning of the body. The composition of the natural flora changes depending on age, health, living conditions, and the use of antimicrobial agents: antibiotics, disinfectants, and some cosmetics. The human body is diversely populated with microorganisms and undergoes constant changes under the influence of various factors, and its proper composition is extremely important for the proper functioning of the body. Given the above, it was decided that we would review current scientific research that explains the cause–effect relationship between the composition of microorganisms populating the human body and health, focusing on women’s health. As a result, an overview paper was prepared based on 109 scientific sources from 2009–2022. Special attention was paid to the most recent scientific studies of the last five years, which account for more than 75% of the cited sources.

Microbial Proteins in Stomach Biopsies Associated with Gastritis, Ulcer, and Gastric Cancer

(1) Background: Gastric cancer (GC) is the fourth leading cause of cancer-related deaths worldwide. Helicobacter pylori infection is a major risk factor, but other microbial species may also be involved. In the context of an earlier proteomics study of serum and biopsies of patients with gastroduodenal diseases, we explored here a simplified microbiome in these biopsies (H. pylori, Acinetobacter baumannii, Escherichia coli, Fusobacterium nucleatum, Bacteroides fragilis) on the protein level. (2) Methods: A cohort of 75 patients was divided into groups with respect to the findings of the normal gastric mucosa (NGM) and gastroduodenal disorders such as gastritis, ulcer, and gastric cancer (GC). The H. pylori infection status was determined. The protein expression analysis of the biopsy samples was carried out using high-definition mass spectrometry of the tryptic digest (label-free data-independent quantification and statistical analysis). (3) Results: The total of 304 bacterial protein matches were detected based on two or more peptide hits. Significantly regulated microbial proteins like virulence factor type IV secretion system protein CagE from H. pylori were found with more abundance in gastritis than in GC or NGM. This finding could reflect the increased microbial involvement in mucosa inflammation in line with current hypotheses. Abundant proteins across species were heat shock proteins and elongation factors. (4) Conclusions: Next to the bulk of human proteins, a number of species-specific bacterial proteins were detected in stomach biopsies of patients with gastroduodenal diseases, some of which, like those expressed by the cag pathogenicity island, may provide gateways to disease prevention without antibacterial intervention in order to reduce antibiotic resistance.

Machine Learning Data Analysis Highlights the Role of Parasutterella and Alloprevotella in Autism Spectrum Disorders

In recent years, the involvement of the gut microbiota in disease and health has been investigated by sequencing the 16S gene from fecal samples. Dysbiotic gut microbiota was also observed in Autism Spectrum Disorder (ASD), a neurodevelopmental disorder characterized by gastrointestinal symptoms. However, despite the relevant number of studies, it is still difficult to identify a typical dysbiotic profile in ASD patients. The discrepancies among these studies are due to technical factors (i.e., experimental procedures) and external parameters (i.e., dietary habits). In this paper, we collected 959 samples from eight available projects (540 ASD and 419 Healthy Controls, HC) and reduced the observed bias among studies. Then, we applied a Machine Learning (ML) approach to create a predictor able to discriminate between ASD and HC. We tested and optimized three algorithms: Random Forest, Support Vector Machine and Gradient Boosting Machine. All three algorithms confirmed the importance of five different genera, including Parasutterella and Alloprevotella. Furthermore, our results show that ML algorithms could identify common taxonomic features by comparing datasets obtained from countries characterized by latent confounding variables.

Unlocking the Potential of the Human Microbiome for Identifying Disease Diagnostic Biomarkers

The human microbiome encodes more than three million genes, outnumbering human genes by more than 100 times, while microbial cells in the human microbiota outnumber human cells by 10 times. Thus, the human microbiota and related microbiome constitute a vast source for identifying disease biomarkers and therapeutic drug targets. Herein, we review the evidence backing the exploitation of the human microbiome for identifying diagnostic biomarkers for human disease. We describe the importance of the human microbiome in health and disease and detail the use of the human microbiome and microbiota metabolites as potential diagnostic biomarkers for multiple diseases, including cancer, as well as inflammatory, neurological, and metabolic diseases. Thus, the human microbiota has enormous potential to pave the road for a new era in biomarker research for diagnostic and therapeutic purposes. The scientific community needs to collaborate to overcome current challenges in microbiome research concerning the lack of standardization of research methods and the lack of understanding of causal relationships between microbiota and human disease.

DivCom: A Tool for Systematic Partition of Groups of Microbial Profiles Into Intrinsic Subclusters and Distance-Based Subgroup Comparisons

When analyzing microbiome data, one of the main objectives is to effectively compare the microbial profiles of samples belonging to different groups. Beta diversity measures the level of similarity among samples, usually in the form of dissimilarity matrices. The use of suitable statistical tests in conjunction with those matrices typically provides us with all the necessary information to evaluate the overall similarity of groups of microbial communities. However, in some cases, this approach can lead us to deceptive conclusions, mainly due to the uneven dispersions of the groups and the existence of unique or unexpected substructures in the dataset. To address these issues, we developed divide and compare (DivCom), an automated tool for advanced beta diversity analysis. DivCom reveals the inner structure of groups by dividing their samples into the appropriate number of clusters and then compares the distances of every profile to the centers of these clusters. This information can be used for determining the existing interrelation of the groups. The proposed methodology and the developed tool were assessed by comparing the response of anemic patients with or without inflammatory bowel disease to different iron replacement therapies. DivCom generated results that revealed the inner structure of the dataset, evaluated the relationship among the clusters, and assessed the effect of the treatments. The DivCom tool is freely available at: https://github.com/Lagkouvardos/DivCom.

Oral Microbiome Research on Oral Lichen Planus: Current Findings and Perspectives

Simple Summary

Oral lichen planus is a disease of the oral mucosa, which frequently affects women aged 40 years or older. Though the T cell-mediated immune response is involved in the development of oral lichen planus, attempts to identify a microorganism that causes the disease have been unsuccessful. Recent studies on the development of oral lichen planus are focusing on the role of the oral microbiome, which includes oral microbiota and their products, and the host environment. The role of the human microbiome in various diseases has been identified and regulating the microbiome is becoming important in personalized medicine. In this review, we summarized current findings on the role of the oral microbiome in the development of oral lichen planus. The homeostasis of the oral microbiome is disrupted in patients, and functional analysis of oral microbiota and oral mucosa implies that pathways involved in defense against bacterial infection and in the inflammatory response are activated in the oral lichen planus-associated oral microbiome. Though the lack of studies to date makes it difficult to conclude, further studies on the oral microbiome associated with the disease will enable a holistic understanding of the role of the oral microbiome in the development of oral lichen planus and developing a personalized therapy for the disease.

Abstract

Oral lichen planus (OLP) is a chronic inflammatory disease of the oral mucosa with an unknown etiology. The role of oral microbes in the development of OLP has gained researchers’ interest. In this review, we summarized the findings of studies focused on the relationship between OLP and oral microbiome, which includes the composition of oral microbiota, molecules produced by oral microbiota or the host, and the oral environment of the host. According to the studies, the oral microbial community in OLP patients undergoes dysbiosis, and the microbial dysbiosis in OLP patients is more prominent in the buccal mucosa than in the saliva. However, no same microorganisms have been suggested to be associated with OLP in multiple investigations, implying that the functional aspects of the oral microbiota are more important in OLP development than the composition of the oral microbiota. According to studies on host factors that make up the oral environment, signal pathways involved in cellular processes, such as keratinization, inflammation, and T cell responses are triggered in OLP. Studies on the functional aspects of the oral microbiota, as well as interactions between the host and the oral microbiota, are still lacking, and more research is required.

A Systematic Approach to Diagnostic Laboratory Software Requirements Analysis

Genetics plays an ever-increasing role in medical diagnostics. The requirements for laboratory diagnostics are constantly changing due to new emerging diagnostic procedures, methodologies, devices, and regulatory requirements. Standard software already available for laboratories often cannot keep up with the latest developments or is focused on research rather than process automation. Although the software utilized in diagnostic laboratories is subject to regulatory requirements, there is no well-defined formal procedure for software development. Reference models have been developed to formalize these solutions, but they do not facilitate the initial requirements analysis or the development process itself. A systematic requirements engineering process is however not only essential to ensure the quality of the final product but is also required by regulations such as the European In Vitro Diagnostic Regulation and international standards such as IEC 62304. This paper shows, by example, the systematic requirements analysis of a system for qPCR-based (quantitative polymerase chain reaction) gene expression analysis. Towards this goal, a multi-step research approach was employed, which included literature review, user interviews, and market analysis. Results revealed the complexity of the field with many requirements to be considered for future implementation.

The Intestinal Microbiota May Be a Potential Theranostic Tool for Personalized Medicine

The human intestine is colonized by a huge number of microorganisms from the moment of birth. This set of microorganisms found throughout the human body, is called the microbiota; the microbiome indicates the totality of genes that the microbiota can express, i.e., its genetic heritage. Thus, microbiota participates in and influences the proper functioning of the organism. The microbiota is unique for each person; it differs in the types of microorganisms it contains, the number of each microorganism, and the ratio between them, but mainly it changes over time and under the influence of many factors. Therefore, the correct functioning of the human body depends not only on the expression of its genes but also on the expression of the genes of the microorganisms it coexists with. This fact makes clear the enormous interest of community science in studying the relationship of the human microbiota with human health and the incidence of disease. The microbiota is like a unique personalized "mold" for each person; it differs quantitatively and qualitatively for the microorganisms it contains together with the relationship between them, and it changes over time and under the influence of many factors. We are attempting to modulate the microbial components in the human intestinal microbiota over time to provide positive feedback on the health of the host, from intestinal diseases to cancer. These interventions to modulate the intestinal microbiota as well as to identify the relative microbiome (genetic analysis) can range from dietary (with adjuvant prebiotics or probiotics) to fecal transplantation. This article researches the recent advances in these strategies by exploring their advantages and limitations. Furthermore, we aim to understand the relationship between intestinal dysbiosis and pathologies, through the research of resident microbiota, that would allow the personalization of the therapeutic antibiotic strategy.

Interaction of cervical microbiome with epigenome of epithelial cells: Significance of inflammation to primary healthcare

One pillar of the predictive, preventive, and personalized medicine framework strategies is the female health. The evaluation of women's lifestyle and dietary habits in context with genetic and modifiable risk factors may reflect the prevention of cervical cancer before the occurrence of clinical symptoms and prediction of cervical lesion behavior. The main aim of this review is to analyze publications in the field of precision medicine that allow the use of research knowledge of cervical microbiome, epigenetic modifications, and inflammation in potential application in clinical practice. Personalized approach in evaluating patient's risk of future development of cervical abnormality should consider the biomarkers of the local microenvironment characterized by the microbial composition, epigenetic pattern of cervical epithelium, and presence of chronic inflammation. Novel sequencing techniques enable a more detailed characterization of actual state in cervical epithelium. Better understanding of all changes in multiomics level enables a better assessment of disease prognosis and selects the eligible targeted therapy in personalized medicine. Restoring of healthy vaginal microflora and reversing the outbreak of cervical abnormality can be also achieved by dietary habits as well as uptake of prebiotics, probiotics, synbiotics, microbial transplantation, and others.

Recent Advances in Understanding the Structure and Function of the Human Microbiome

Trillions of microbes live within our bodies in a deep symbiotic relationship. Microbial populations vary across body sites, driven by differences in the environment, immunological factors, and interactions between microbial species. Major advances in genome sequencing enable a better understanding of microbiome composition. However, most of the microbial taxa and species of the human microbiome are still unknown. Without revealing the identity of these microbes as a first step, we cannot appreciate their role in human health and diseases. A shift in the microbial balance, termed dysbiosis, is linked to a broad range of diseases from simple colitis and indigestion to cancer and dementia. The last decade has witnessed an explosion in microbiome research that led to a better understanding of the microbiome structure and function. This understanding leads to potential opportunities to develop next-generation microbiome-based drugs and diagnostic biomarkers. However, our understanding is limited given the highly personalized nature of the microbiome and its complex and multidirectional interactions with the host. In this review, we discuss: (1) our current knowledge of microbiome structure and factors that shape the microbial composition, (2) recent associations between microbiome dysbiosis and diseases, and (3) opportunities of new microbiome-based therapeutics. We analyze common themes, promises, gaps, and challenges of the microbiome research.

Redrawing therapeutic boundaries: microbiota and cancer

The unexpected roles of the microbiota in cancer challenge explanations of carcinogenesis that focus on tumor-intrinsic properties. Most tumors contain bacteria and viruses, and the host's proximal and distal microbiota influence both cancer incidence and therapeutic responsiveness. Continuing the history of cancer-microbe research, these findings raise a key question: to what extent is the microbiota relevant for clinical oncology? We approach this by critically evaluating three issues: how the microbiota provides a predictive biomarker of cancer growth and therapeutic responsiveness, the microbiota's causal role(s) in cancer development, and how therapeutic manipulations of the microbiota improve patient outcomes in cancer. Clarifying the conceptual and empirical aspects of the cancer-associated microbiota can orient future research and guide its implementation in clinical oncology.

The role of microbiota and immune system crosstalk in cancer development and therapy

Cancer is a multifactorial disease that is the second leading cause of death after cardiovascular disease in the world. In recent years, microbiota's role in the regulation and homeostasis of the immune system has been considered. Moreover, the immune system can affect the microbiota content. These interactions are critical to the functioning of the immune system. Numerous studies in animal and human models have shown the association of changes in microbiota components with the formation of an inhibitory microenvironment in the tumor and its escape from the immune system. Microbiota also plays a crucial role in the success of various anti-tumor treatments, and its modification leads to success in cancer treatment. The success of anti-tumor therapies that directly target the immune system, such as immune checkpoint blockade and T cell therapy, is also affected by the patient's microbiota composition. It seems that in addition to examining the patient's genetics, precision medicine should pay attention to the patient's microbiota in choosing the appropriate treatment method, and together with usual anti-tumor therapies, microbiota may be modified. This review discusses various aspects of the relationship between microbiota and anti-tumor immunity and its successful treatment.

OUP accepted manuscript

The intestinal microbiota plays a crucial role in health and changes in its composition are linked with major global human diseases. Fully understanding what shapes the human intestinal microbiota composition and knowing ways of modulating the composition are critical for promotion of life-course health, combating diseases, and reducing global health disparities. We aim to provide a foundation for understanding what shapes the human intestinal microbiota on an individual and global scale, and how interventions could utilize this information to promote life-course health and reduce global health disparities. We briefly review experiences within the first 1,000 days of life and how long-term exposures to environmental elements or geographic specific cultures have lasting impacts on the intestinal microbiota. We also discuss major public health threats linked to the intestinal microbiota, including antimicrobial resistance and disappearing microbial diversity due to globalization. In order to promote global health, we argue that the interplay of the larger ecosystem with intestinal microbiota research should be utilized for future research and urge for global efforts to conserve microbial diversity.

Precision Medicine and Obesity

Obesity is a chronic, relapsing, and multifactorial disease, with a rising prevalence and an associated high economic burden. Achieving successful and sustained weight loss outcomes with current interventions is challenging. This is due, at least in part, to the disease's heterogenous pathophysiology that is yet to be completely understood. Technological advances and greater capabilities for the extraction and storage of information have facilitated the application of precision medicine. Several precision medicine initiatives have been proposed to improve obesity outcomes. Most of these initiatives are based on -omics technologies. Although the data generated from these technologies have led to developing hypotheses that may explain the underpinnings of obesity, their applicability to the clinical practice is yet to be determined. There are other initiatives that have identified quantitative or qualitative physiologic traits that can be targeted and that could have a more immediate clinical impact. This review aims to provide a perspective of current initiatives for precision medicine for obesity.

Personalized Immunotherapy in Colorectal Cancers: Where Do We Stand?

Colorectal cancer (CRC) is the second leading cause of cancer death in the world. Immunotherapy using monoclonal antibodies, immune-checkpoint inhibitors, adoptive cell therapy, and cancer vaccines has raised great hopes for treating poor prognosis metastatic CRCs that are resistant to the conventional therapies. However, high inter-tumor and intra-tumor heterogeneity hinder the success of immunotherapy in CRC. Patients with a similar tumor phenotype respond differently to the same immunotherapy regimen. Mutation-based classification, molecular subtyping, and immunoscoring of CRCs facilitated the multi-aspect grouping of CRC patients and improved immunotherapy. Personalized immunotherapy using tumor-specific neoantigens provides the opportunity to consider each patient as an independent group deserving of individualized immunotherapy. In the recent decade, the development of sequencing and multi-omics techniques has helped us classify patients more precisely. The expansion of such advanced techniques along with the neoantigen-based immunotherapy could herald a new era in treating heterogeneous tumors such as CRC. In this review article, we provided the latest findings in immunotherapy of CRC. We elaborated on the heterogeneity of CRC patients as a bottleneck of CRC immunotherapy and reviewed the latest advances in personalized immunotherapy to overcome CRC heterogeneity.

The nutritional profile and human health benefit of pigmented rice and the impact of post-harvest processes and product development on the nutritional components: A review

Pigmented rice has attracted considerable attention due to its nutritional value, which is in large conferred by its abundant content of phenolic compounds, considerable micronutrient concentrations, as well as its higher resistant starch and thereby slower digestibility properties. A wide range of phenolic compounds identified in pigmented rice exhibit biological activities such as antioxidant activity, anti-inflammatory, anticancer, and antidiabetic properties. Post-harvest processes significantly reduce the levels of these phytochemicals, but recent developments in processing methods have allowed greater retention of their contents. Pigmented rice has also been converted to different products for food preservation and to derive functional foods. Profiling a large set of pigmented rice cultivars will thus not only provide new insights into the phytochemical diversity of rice and the genes underlying the vast array of secondary metabolites present in this species but also provide information concerning their nutritional benefits, which will be instrumental in breeding healthier rice. The present review mainly focuses on the nutritional composition of pigmented rice and how it can impact human health alongside the effects of post-harvest processes and product development methods to retain the ambient level of phytochemicals in the final processed form in which it is consumed.

Compositional variation of the human fecal microbiome in relation to azo-reducing activity: a pilot study

Background

Through an arsenal of microbial enzymes, the gut microbiota considerably contributes to human metabolic processes, affecting nutrients, drugs, and environmental poisons. Azoreductases are a predominant group of microbiota-derived enzymes involved in xenobiotic metabolism and drug activation, but little is known about how compositional changes in the gut microbiota correlate with its azo-reducing activity.

Results

To this end, we used high-throughput 16S rRNA amplicon sequencing, with Illumina MiSeq, to determine the microbial community composition of stool samples from 16 adults with different azo-reducing activity. High azo-reducing activity positively correlated with the relative abundance of phylum Firmicutes (especially genera Streptococcus and Coprococcus) but negatively with phylum Bacteroidetes (especially genus Bacteroides). Typical variations in the Firmicutes-to-Bacteroidetes and Prevotella-to-Bacteroides ratios were observed among samples. Multivariate analysis of the relative abundance of key microbial taxa and other diversity parameters confirmed the Firmicutes proportion as a major variable differentiating high and non-azo-reducers, while Bacteroidetes relative abundance was correlated with azo-reduction, sex, and BMI.

Conclusions

This pilot study showed that stool samples with higher azo-reducing activity were enriched in Firmicutes but with relatively fewer Bacteroidetes. More samples and studies from different geographical areas are needed to bolster this conclusion. Better characterization of different azoreductase-producing gut microbes will increase our knowledge about the fate and differential human responses to azodye-containing drugs or orally consumed chemicals, thus contributing to efforts towards implementing microbiome testing in precision medicine and toxicology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13099-021-00454-0.

NOD1 in the interplay between microbiota and gastrointestinal immune adaptations

Nucleotide-binding oligomerization domain 1 (NOD1), a pattern recognition receptor (PRR) that detects bacterial peptidoglycan fragments and other danger signals, has been linked to inflammatory pathologies. NOD1, which is expressed by immune and non-immune cells, is activated after recognizing microbe-associated molecular patterns (MAMPs). This recognition triggers host defense responses and both immune memory and tolerance can also be achieved during these processes. Since the gut microbiota is currently considered a master regulator of human physiology central in health and disease and the intestine metabolizes a wide range of nutrients, drugs and hormones, it is a fact that dysbiosis can alter tissues and organs homeostasis. These systemic alterations occur in response to gastrointestinal immune adaptations that are not yet fully understood. Even if previous evidence confirms the connection between the microbiota, the immune system and metabolic disorders, much remains to be discovered about the contribution of NOD1 to low-grade inflammatory pathologies such as obesity, diabetes and cardiovascular diseases. This review compiles the most recent findings in this area, while providing a dynamic and practical framework with future approaches for research and clinical applications on targeting NOD1. This knowledge can help to rate the consequences of the disease and to stratify the patients for therapeutic interventions.

Assessment of Oral Vancomycin-Induced Alterations in Gut Bacterial Microbiota and Metabolome of Healthy Men

Several classes of antibiotics have reduced the mortality caused by infectious diseases; however, orally administered antibiotics alter the composition of gut microbiota, leading to dysbiosis-related disease. Therefore, in this study, we used 16S rRNA gene sequencing- and metabolomics-based approaches to investigate the effects of oral vancomycin on gut bacterial microbiota and the metabolome in biospecimens collected from healthy men. Samples collected from 11 healthy men were analyzed using 16S rRNA gene sequencing and metabolomics. 16S rRNA gene sequencing was performed to analyze the gut bacterial microbiota, and GC-TOFMS-based untargeted metabolomics was performed to analyze fecal, urine, and plasma metabolomics. Spearman's rank correlation was utilized to explore the associations between gut bacterial microbiota and metabolome. Fecal 16S rRNA gene sequencing analysis showed decreased relative abundance of genera belonging to the phyla Bacteroidetes and Firmicutes, and increased relative abundance of genera of the phyla Proteobacteria and Fusobacteria. Fecal metabolomics analysis showed that levels of uracil, L-aspartic acid, lithocholic acid, and deoxycholic acid were significantly higher at baseline, whereas that of dihydrouracil was significantly higher after vancomycin administration. No significant metabolic markers were selected from urine and plasma metabolomics analysis. This study demonstrates that oral vancomycin administration induces alterations in gut bacterial microbiota and metabolome. Correlation analysis between our two datasets shows that alteration of the gut bacterial microbiota, induced by oral vancomycin, potentially affected the systemic activity of dihydropyrimidine dehydrogenase. This correlation should be further examined in future studies to define the effects of gut bacterial microbiota on drug-metabolizing enzymes, thereby contributing to the development of personalized therapy.

The commensal consortium of the gut microbiome is associated with favorable responses to anti-programmed death protein 1 (PD-1) therapy in thoracic neoplasms

OBJECTIVE

Immune checkpoint inhibitors have revolutionized cancer therapy for multiple types of solid tumors, but as expected, a large percentage of patients do not show durable responses. Biomarkers that can predict clinical responses to immunotherapies at diagnosis are therefore urgently needed. Herein, we determined the associations between baseline gut commensal microbes and the clinical treatment efficiencies of patients with thoracic neoplasms during anti-programmed death protein 1 (PD-1) therapy.

METHODS

Forty-two patients with advanced thoracic carcinoma who received anti-PD-1 treatment were enrolled in the study. Baseline and time-serial stool samples were analyzed using 16S ribosomal RNA gene sequencing. Tumor responses, patient progression-free survival, and overall survival were used to measure clinical outcomes.

RESULTS

The diversities of the baseline gut microbiota were similar between responders (n = 23) and nonresponders (n = 19). The relative abundances of the Akkermansiaceae, Enterococcaceae, Enterobacteriaceae, Carnobacteriaceae and Clostridiales Family XI bacterial families were significantly higher in the responder group. These 5 bacterial families acted as a commensal consortium and better stratified patients according to clinical responses (P = 0.014). Patients with a higher abundance of commensal microbes had prolonged PFS (P = 0.00016). Using multivariable analysis, the abundance of the commensal consortium was identified as an independent predictor of anti-PD-1 immunotherapy in thoracic neoplasms (hazard ratio: 0.17; 95% confidence interval: 0.05-0.55; P = 0.003).

CONCLUSIONS

Baseline gut microbiota may have a critical impact on anti-PD-1 treatment in thoracic neoplasms. The abundance of gut commensal microbes at diagnosis might be useful for the early prediction of anti-PD-1 immunotherapy responses.

Exploring the human hair follicle microbiome

Human hair follicles (HFs) carry complex microbial communities that differ from the skin surface microbiota. This likely reflects that the HF epithelium differs from the epidermal barrier in that it provides a moist, less acidic, and relatively ultraviolet light-protected environment, part of which is immune-privileged, thus facilitating microbial survival. Here we review the current understanding of the human HF microbiome and its potential physiological and pathological functions, including in folliculitis, acne vulgaris, hidradenitis suppurativa, alopecia areata and cicatricial alopecias. While reviewing the main human HF bacteria (such as Propionibacteria, Corynebacteria, Staphylococci and Streptococci), viruses, fungi and parasites as human HF microbiome constituents, we advocate a broad view of the HF as an integral part of the human holobiont. Specifically, we explore how the human HF may manage its microbiome via the regulated production of antimicrobial peptides (such as cathelicidin, psoriasin, RNAse7 and dermcidin) by HF keratinocytes, how the microbiome may impact on cytokine and chemokine release from the HF, and examine hair growth-modulatory effects of antibiotics, and ask whether the microbiome affects hair growth in turn. We highlight major open questions and potential novel approaches to the management of hair diseases by targeting the HF microbiome.

Deep learning in systems medicine

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM.

geneRFinder: gene finding in distinct metagenomic data complexities

Background

Microbes perform a fundamental economic, social, and environmental role in our society. Metagenomics makes it possible to investigate microbes in their natural environments (the complex communities) and their interactions. The way they act is usually estimated by looking at the functions they play in those environments and their responsibility is measured by their genes. The advances of next-generation sequencing technology have facilitated metagenomics research however it also creates a heavy computational burden. Large and complex biological datasets are available as never before. There are many gene predictors available that can aid the gene annotation process though they lack handling appropriately metagenomic data complexities. There is no standard metagenomic benchmark data for gene prediction. Thus, gene predictors may inflate their results by obfuscating low false discovery rates.

Results

We introduce geneRFinder, an ML-based gene predictor able to outperform state-of-the-art gene prediction tools across this benchmark by using only one pre-trained Random Forest model. Average prediction rates of geneRFinder differed in percentage terms by 54% and 64%, respectively, against Prodigal and FragGeneScan while handling high complexity metagenomes. The specificity rate of geneRFinder had the largest distance against FragGeneScan, 79 percentage points, and 66 more than Prodigal. According to McNemar’s test, all percentual differences between predictors performances are statistically significant for all datasets with a 99% confidence interval.

Conclusions

We provide geneRFinder, an approach for gene prediction in distinct metagenomic complexities, available at gitlab.com/r.lorenna/generfinder and https://osf.io/w2yd6/, and also we provide a novel, comprehensive benchmark data for gene prediction—which is based on The Critical Assessment of Metagenome Interpretation (CAMI) challenge, and contains labeled data from gene regions—available at https://sourceforge.net/p/generfinder-benchmark.

Modulation of human intestinal microbiota in a clinical trial by consumption of a β-D-glucan-enriched extract obtained from Lentinula edodes

PURPOSE

The aim of this study was to evaluate the hypocholesterolemic, immune- and microbiota-modulatory effect of a mushroom extract in hypercholesterolemic subjects.

METHODS

A randomized, controlled, double-blind, and parallel clinical trial was carried out with subjects from 18 to 65 years old (n = 52) with untreated mild hypercholesterolemia. Volunteers consumed a β-D-glucan-enriched (BGE) mixture (10.4 g/day) obtained from shiitake mushrooms (Lentinula edodes) ensuring a 3.5 g/day of fungal β-D-glucans or a placebo incorporated in three different commercial creams.

RESULTS

This mixture showed hypocholesterolemic activities in vitro and in animal studies. After eight weeks intervention, no significant differences in lipid- or cholesterol-related parameters were found compared to placebo subjects as well as before and after the BGE mixture administration. No inflammatory or immunomodulatory responses were noticed and no changes in IL-1β, IL-6, TNF-α or oxLDL were recorded. However, consumption of the BGE mixture was safe and managed to achieve the dietary fibre intake recommended as cardiovascular protective diet. Moreover, the BGE mixture modulated the colonic microbiota differently compared to placebo. Microbial community composition varied from before to after the intervention with several genera being positively or negatively correlated with some biomarkers related to cholesterol metabolism.

CONCLUSION

These results suggested a relation between cholesterol metabolism, microbiota and BGE administration. Nevertheless, the precise significance of this differential modulation was not fully elucidated and requires further studies.

Information Theoretic Metagenome Assembly Allows the Discovery of Disease Biomarkers in Human Microbiome

Quantitative metagenomics is an important field that has delivered successful microbiome biomarkers associated with host phenotypes. The current convention mainly depends on unsupervised assembly of metagenomic contigs with a possibility of leaving interesting genetic material unassembled. Additionally, biomarkers are commonly defined on the differential relative abundance of compositional or functional units. Accumulating evidence supports that microbial genetic variations are as important as the differential abundance content, implying the need for novel methods accounting for the genetic variations in metagenomics studies. We propose an information theoretic metagenome assembly algorithm, discovering genomic fragments with maximal self-information, defined by the empirical distributions of nucleotides across the phenotypes and quantified with the help of statistical tests. Our algorithm infers fragments populating the most informative genetic variants in a single contig, named supervariant fragments. Experiments on simulated metagenomes, as well as on a colorectal cancer and an atherosclerotic cardiovascular disease dataset consistently discovered sequences strongly associated with the disease phenotypes. Moreover, the discriminatory power of these putative biomarkers was mainly attributed to the genetic variations rather than relative abundance. Our results support that a focus on metagenomics methods considering microbiome population genetics might be useful in discovering disease biomarkers with a great potential of translating to molecular diagnostics and biotherapeutics applications.