Artificial intelligence and synthetic biology approaches for human gut microbiome

Gut microbiome and orthopaedic health: Bridging the divide between digestion and bone integrity

The gut microbiome, a complex ecosystem of microorganisms in the digestive tract, has emerged as a critical factor in human health, influencing metabolic, immune, and neurological functions. This review explores the connection between the gut microbiome and orthopedic health, examining how gut microbes impact bone density, joint integrity, and skeletal health. It highlights mechanisms linking gut dysbiosis to inflammation in conditions such as rheumatoid arthritis and osteoarthritis, suggesting microbiome modulation as a potential therapeutic strategy. Key findings include the microbiome’s role in bone metabolism through hormone regulation and production of short-chain fatty acids, crucial for mineral absorption. The review also considers the effects of diet, probiotics, and fecal microbiota transplantation on gut microbiome composition and their implications for orthopedic health. While promising, challenges in translating microbiome research into clinical practice persist, necessitating further exploration and ethical consideration of microbiome-based therapies. This interdisciplinary research aims to link digestive health with musculoskeletal integrity, offering new insights into the prevention and management of bone and joint diseases.

Assembly of functional microbial ecosystems: from molecular circuits to communities

Microbes compete and cooperate with each other via a variety of chemicals and circuits. Recently, to decipher, simulate, or reconstruct microbial communities, many researches have been engaged in engineering microbiomes with bottom-up synthetic biology approaches for diverse applications. However, they have been separately focused on individual perspectives including genetic circuits, communications tools, microbiome engineering, or promising applications. The strategies for coordinating microbial ecosystems based on different regulation circuits have not been systematically summarized, which calls for a more comprehensive framework for the assembly of microbial communities. In this review, we summarize diverse cross-talk and orthogonal regulation modules for de novo bottom-up assembling functional microbial ecosystems, thus promoting further consortia-based applications. First, we review the cross-talk communication-based regulations among various microbial communities from intra-species and inter-species aspects. Then, orthogonal regulations are summarized at metabolites, transcription, translation, and post-translation levels, respectively. Furthermore, to give more details for better design and optimize various microbial ecosystems, we propose a more comprehensive design-build-test-learn procedure including function specification, chassis selection, interaction design, system build, performance test, modeling analysis, and global optimization. Finally, current challenges and opportunities are discussed for the further development and application of microbial ecosystems.

Concepts and criteria defining emerging microbiome applications

In recent years, microbiomes and their potential applications for human, animal or plant health, food production and environmental management came into the spotlight of major national and international policies and strategies. This has been accompanied by substantial R&D investments in both public and private sectors, with an increasing number of products entering the market. Despite widespread agreement on the potential of microbiomes and their uses across disciplines, stakeholders and countries, there is no consensus on what defines a microbiome application. This often results in non-comprehensive communication or insufficient documentation making commercialisation and acceptance of the novel products challenging. To showcase the complexity of this issue we discuss two selected, well-established applications and propose criteria defining a microbiome application and their conditions of use for clear communication, facilitating suitable regulatory frameworks and building trust among stakeholders.

Metagenomic and culture-dependent analysis of Rhinopithecius bieti gut microbiota and characterization of a novel genus of Sphingobacteriaceae

Culture-dependent and metagenomic binning techniques were employed to gain an insight into the diversification of gut bacteria in Rhinopithecius bieti, a highly endangered primate endemic to China. Our analyses revealed that Bacillota_A and Bacteroidota were the dominant phyla. These two phyla species are rich in carbohydrate active enzymes, which could provide nutrients and energy for their own or hosts' survival under different circumstances. Among the culturable bacteria, one novel bacterium, designated as WQ 2009T, formed a distinct branch that had a low similarity to the known species in the family Sphingobacteriaceae, based on the phylogenetic analysis of its 16S rRNA gene sequence or phylogenomic analysis. The ANI, dDDH and AAI values between WQ 2009T and its most closely related strains S. kitahiroshimense 10CT, S. pakistanense NCCP-246T and S. faecium DSM 11690T were significantly lower than the accepted cut-off values for microbial species delineation. All results demonstrated that WQ 2009T represent a novel genus, for which names Rhinopithecimicrobium gen. nov. and Rhinopithecimicrobium faecis sp. nov. (Type strain WQ 2009T = CCTCC AA 2021153T = KCTC 82941T) are proposed.

Gut microbiota and childhood malnutrition: Understanding the link and exploring therapeutic interventions

Childhood malnutrition is a metabolic condition that affects the physical and mental well-being of children and leads to resultant disorders in maturity. The development of childhood malnutrition is influenced by a number of physiological and environmental factors including metabolic stress, infections, diet, genetic variables, and gut microbiota. The imbalanced gut microbiota is one of the main environmental risk factors that significantly influence host physiology and childhood malnutrition progression. In this review, we have evaluated the gut microbiota association with undernutrition and overnutrition in children, and then the quantitative and qualitative significance of gut dysbiosis in order to reveal the impact of gut microbiota modification using probiotics, prebiotics, synbiotics, postbiotics, fecal microbiota transplantation, and engineering biology methods as new therapeutic challenges in the management of disturbed energy homeostasis. Understanding the host-microbiota interaction and the remote regulation of other organs and pathways by gut microbiota can improve the effectiveness of new therapeutic approaches and mitigate the negative consequences of childhood malnutrition.

Effectiveness of Psychobiotics in the Treatment of Psychiatric and Cognitive Disorders: A Systematic Review of Randomized Clinical Trials

In this study, a systematic review of randomized clinical trials conducted from January 2000 to December 2023 was performed to examine the efficacy of psychobiotics-probiotics beneficial to mental health via the gut-brain axis-in adults with psychiatric and cognitive disorders. Out of the 51 studies involving 3353 patients where half received psychobiotics, there was a notably high measurement of effectiveness specifically in the treatment of depression symptoms. Most participants were older and female, with treatments commonly utilizing strains of Lactobacillus and Bifidobacteria over periods ranging from 4 to 24 weeks. Although there was a general agreement on the effectiveness of psychobiotics, the variability in treatment approaches and clinical presentations limits the comparability and generalization of the findings. This underscores the need for more personalized treatment optimization and a deeper investigation into the mechanisms through which psychobiotics act. The research corroborates the therapeutic potential of psychobiotics and represents progress in the management of psychiatric and cognitive disorders.

Neuroinflammation and Schizophrenia: New Therapeutic Strategies through Psychobiotics, Nanotechnology, and Artificial Intelligence (AI)

The prevalence of schizophrenia, affecting approximately 1% of the global population, underscores the urgency for innovative therapeutic strategies. Recent insights into the role of neuroinflammation, the gut-brain axis, and the microbiota in schizophrenia pathogenesis have paved the way for the exploration of psychobiotics as a novel treatment avenue. These interventions, targeting the gut microbiome, offer a promising approach to ameliorating psychiatric symptoms. Furthermore, advancements in artificial intelligence and nanotechnology are set to revolutionize psychobiotic development and application, promising to enhance their production, precision, and effectiveness. This interdisciplinary approach heralds a new era in schizophrenia management, potentially transforming patient outcomes and offering a beacon of hope for those afflicted by this complex disorder.

Early prediction of the severe course, survival, and ICU requirements in acute pancreatitis by artificial intelligence

OBJECTIVE

To evaluate the success of artificial intelligence for early prediction of severe course, survival, and intensive care unit(ICU) requirement in patients with acute pancreatitis(AP).

METHODS

Retrospectively, 1334 patients were included the study. Severity is determined according to the Revised Atlanta Classification(RAC). The success of machine learning(ML) method was evaluated by 13 simple demographic, clinical, etiologic, and laboratory features obtained on ER admission. Additionally, it was evaluated whether Balthazar-computerized tomography severity index(CTSI) at 48-h contributed to success. The dataset was split into two parts, 90% for ML(of which 70% for learning and 30% for testing) and 10% for validation and 5-fold stratified sampling has been utilized. Variable Importance was used in the selection of features during training phase of machine. The Gradient Boost Algorithm trained the machine by KNIME analytics platform. SMOTE has been applied to increase the minority classes for training. The combined effects of the measured features were examined by multivariate logistic regression analysis and reciever operating curve curves of the prediction and confidence of the target variables were obtained.

RESULTS

Accuracy values for the early estimation of Atlanta severity score, ICU requirement, and survival were found as 88.20%, 98.25%, and 92.77% respectively. When Balthazar-CTSI score is used, results were found as 91.02%, 92.25%, and 98% respectively.

CONCLUSIONS

The ML method we used successfully predicted the severe course, ICU requirement and survival, with promising accuracy values of over 88%. If 48-h Balthazar-CTSI is included in the calculation, the severity score and survival rates increase even more.

Multi-Objective Optimization Tuning Framework for Kinetic Parameter Selection and Estimation

Semi-mechanistic kinetic (i.e., dynamic) models based on first principles are particularly relevant in biology, as they can explain and predict functional behavior that arises from varying concentrations of the cellular components over time. Here, we describe a computational tuning framework to facilitate both the selection of kinetic parameters for these models and its estimation from experimental data. On the one hand, the tuning framework uses multi-objective optimization to generate a model-based set of guidelines for the selection of the kinetic parameters. These parameter values are the required ones to provide a biological system with desired behavior, while fulfilling the design criteria encoded in the optimization problem itself. On the other hand, this framework can also be used to estimate the parameter values of biological systems from experimental data, once the optimization objectives had been defined appropriately. The methodology gives accurate identification results, as it provides clear orientation on the effect of the parameter values over the system's behavior even under different experimental scenarios. It is particularly useful for easily combining time-course-averaged data and steady-state distribution data. This protocol also addresses aspects related to the appropriate description of the kinetic models and the settings of the software tools. Therefore, it supplies for hands-on testing to evaluate the validity of the underlying technical assumptions of the biological kinetic models.

Probiotics Interactions and the Modulation of Major Signalling Pathways in Host Model Organism Caenorhabditis elegans

Microorganisms live in the human digestive system and the gut microbiome constitutes part of our prime determining component for healthy aging and wellness. Gut microbiota has broad influences on its host, beginning from the digestion of food and nutrients absorption to protective roles against invading pathogens and host immune system regulation. Dysbiosis of the gut microbial composition has been linked to numerous diseases and there is a need to have a better grasp on what makes a 'good' gut microbiome. Caenorhabditis elegans (C. elegans) model organism is considered as a well-suited in-vivo model system and, is at the frontline of probiotic research because of its well-defined characteristics and prolific nature. Most importantly, C. elegans feeds on bacteria, which speeds up manipulations and investigations in probiotics research tremendously. With its unique salient features of short lifespan, and ease of propagation, different unknown probiotics biological roles can be measured at an organism level with precision in the form of worm's stress responses, survivability, and lifespan. In this review, new insights on the different mechanisms underlying the establishment of probiotics regulations of conserved signalling pathways such as p38 MAPK/SKN-1, DAF-2/DAF-16, and JNK-1/DAF-16 is highlighted based on information obtained from C. elegans studies. Along with the current state of knowledge and the uniqueness of C. elegans as a model organism, explorations of its future contribution and scope in synthetic biology and probiotics engineering strains are also addressed. This is expected to strengthen our understanding of probiotics roles and to facilitate novel discovery and applications, for specific therapeutics against age-related disorders and various pathophysiological conditions.