Advances in Genome-Scale Metabolic Modeling toward Microbial Community Analysis of the Human Microbiome

Engineering Gut Symbionts: A Way to Promote Bee Growth?

Bees play a crucial role as pollinators, contributing significantly to ecosystems. However, the honeybee population faces challenges such as global warming, pesticide use, and pathogenic microorganisms. Promoting bee growth using several approaches is therefore crucial for maintaining their roles. To this end, the bacterial microbiota is well-known for its native role in supporting bee growth in several respects. Maximizing the capabilities of these microorganisms holds the theoretical potential to promote the growth of bees. Recent advancements have made it feasible to achieve this enhancement through the application of genetic engineering. In this review, we present the roles of gut symbionts in promoting bee growth and collectively summarize the engineering approaches that would be needed for future applications. Particularly, as the engineering of bee gut symbionts has not been advanced, the dominant gut symbiotic bacteria Snodgrassella alvi and Gilliamella apicola are the main focus of the paper, along with other dominant species. Moreover, we propose engineering strategies that will allow for the improvement in bee growth with listed gene targets for modification to further encourage the use of engineered gut symbionts to promote bee growth.

Integrating biological knowledge for mechanistic inference in the host-associated microbiome

Advances in high-throughput technologies have enhanced our ability to describe microbial communities as they relate to human health and disease. Alongside the growth in sequencing data has come an influx of resources that synthesize knowledge surrounding microbial traits, functions, and metabolic potential with knowledge of how they may impact host pathways to influence disease phenotypes. These knowledge bases can enable the development of mechanistic explanations that may underlie correlations detected between microbial communities and disease. In this review, we survey existing resources and methodologies for the computational integration of broad classes of microbial and host knowledge. We evaluate these knowledge bases in their access methods, content, and source characteristics. We discuss challenges of the creation and utilization of knowledge bases including inconsistency of nomenclature assignment of taxa and metabolites across sources, whether the biological entities represented are rooted in ontologies or taxonomies, and how the structure and accessibility limit the diversity of applications and user types. We make this information available in a code and data repository at: https://github.com/lozuponelab/knowledge-source-mappings. Addressing these challenges will allow for the development of more effective tools for drawing from abundant knowledge to find new insights into microbial mechanisms in disease by fostering a systematic and unbiased exploration of existing information.

Microbially mediated metal corrosion

A wide diversity of microorganisms, typically growing as biofilms, has been implicated in corrosion, a multi-trillion dollar a year problem. Aerobic microorganisms establish conditions that promote metal corrosion, but most corrosion has been attributed to anaerobes. Microbially produced organic acids, sulfide and extracellular hydrogenases can accelerate metallic iron (Fe0) oxidation coupled to hydrogen (H2) production, as can respiratory anaerobes consuming H2 as an electron donor. Some bacteria and archaea directly accept electrons from Fe0 to support anaerobic respiration, often with c-type cytochromes as the apparent outer-surface electrical contact with the metal. Functional genetic studies are beginning to define corrosion mechanisms more rigorously. Omics studies are revealing which microorganisms are associated with corrosion, but new strategies for recovering corrosive microorganisms in culture are required to evaluate corrosive capabilities and mechanisms. Interdisciplinary studies of the interactions among microorganisms and between microorganisms and metals in corrosive biofilms show promise for developing new technologies to detect and prevent corrosion. In this Review, we explore the role of microorganisms in metal corrosion and discuss potential ways to mitigate it.

Integrating Omics Data in Genome-Scale Metabolic Modeling: A Methodological Perspective for Precision Medicine

Recent advancements in omics technologies have generated a wealth of biological data. Integrating these data within mathematical models is essential to fully leverage their potential. Genome-scale metabolic models (GEMs) provide a robust framework for studying complex biological systems. GEMs have significantly contributed to our understanding of human metabolism, including the intrinsic relationship between the gut microbiome and the host metabolism. In this review, we highlight the contributions of GEMs and discuss the critical challenges that must be overcome to ensure their reproducibility and enhance their prediction accuracy, particularly in the context of precision medicine. We also explore the role of machine learning in addressing these challenges within GEMs. The integration of omics data with GEMs has the potential to lead to new insights, and to advance our understanding of molecular mechanisms in human health and disease.

The Microbiome and Mental Health Across the Lifespan

INTRODUCTION

The combined genetic material of the microorganisms in the human body, known as the microbiome, is being increasingly recognized as a major determinant of human health and disease. Although located predominantly on mucosal surfaces, these microorganisms have profound effects on brain functioning through the gut-brain axis.

METHOD

The content of the chapter is based on a study group session at the annual meeting of the American College of Neuropsychopharmacology (ACNP). The objective was to discuss the emerging relationship between the human microbiome and mental health as relevant to ACNP's interests in developing and evaluating novel neuropsychiatric treatment strategies. The focus is on specific brain disorders, such as schizophrenia, substance use, and Alzheimer's disease, as well as on broader clinical issues such as suicidality, loneliness and wisdom in old age, and longevity.

RESULTS

Studies of schizophrenia indicate that the microbiome of individuals with this disorder differs from that of non-psychiatric comparison groups in terms of diversity and composition. Differences are also found in microbial metabolic pathways. An early study in substance use disorders found that individuals with this disorder have lower levels of beta diversity in their oral microbiome than a comparison group. This measure, along with others, was used to distinguish individuals with substance use disorders from controls. In terms of suicidality, there is preliminary evidence that persons who have made a suicide attempt differ from psychiatric and non-psychiatric comparison groups in measures of beta diversity. Exploratory studies in Alzheimer's disease indicate that gut microbes may contribute to disease pathogenesis by regulating innate immunity and neuroinflammation and thus influencing brain function. In another study looking at the microbiome in older adults, positive associations were found between wisdom and alpha diversity and negative associations with subjective loneliness. In other studies of older adults, here with a focus on longevity, individuals with healthy aging and unusually long lives had an abundance of specific microorganisms which distinguished them from other individuals.

DISCUSSION

Future studies would benefit from standardizing methods of sample collection, processing, and analysis. There is also a need for the standardized collection of relevant demographic and clinical data, including diet, medications, cigarette smoking, and other potentially confounding factors. While still in its infancy, research to date indicates a role for the microbiome in mental health disorders and conditions. Interventions are available which can modulate the microbiome and lead to clinical improvements. These include microbiome-altering medications as well as probiotic microorganisms capable of modulating the inflammation in the brain through the gut-brain axis. This research holds great promise in terms of developing new methods for the prevention and treatment of a range of human brain disorders.

In-Silico Functional Metabolic Pathways Associated to Chlamydia trachomatis Genital Infection

The advent of high-throughput technologies, such as 16s rDNA sequencing, has significantly contributed to expanding our knowledge of the microbiota composition of the genital tract during infections such as Chlamydia trachomatis. The growing body of metagenomic data can be further exploited to provide a functional characterization of microbial communities via several powerful computational approaches. Therefore, in this study, we investigated the predicted metabolic pathways of the cervicovaginal microbiota associated with C. trachomatis genital infection in relation to the different Community State Types (CSTs), via PICRUSt2 analysis. Our results showed a more rich and diverse mix of predicted metabolic pathways in women with a CST-IV microbiota as compared to all the other CSTs, independently from infection status. C. trachomatis genital infection further modified the metabolic profiles in women with a CST-IV microbiota and was characterized by increased prevalence of the pathways for the biosynthesis of precursor metabolites and energy, biogenic amino-acids, nucleotides, and tetrahydrofolate. Overall, predicted metabolic pathways might represent the starting point for more precisely designed future metabolomic studies, aiming to investigate the actual metabolic pathways characterizing C. trachomatis genital infection in the cervicovaginal microenvironment.

A Framework for the Systematic Selection of Biosensor Chassis for Environmental Synthetic Biology

Microbial biosensors sense and report exposures to stimuli, thereby facilitating our understanding of environmental processes. Successful design and deployment of biosensors hinge on the persistence of the microbial host of the genetic circuit, termed the chassis. However, model chassis organisms may persist poorly in environmental conditions. In contrast, non-model organisms persist better in environmental conditions but are limited by other challenges, such as genetic intractability and part unavailability. Here we identify ecological, metabolic, and genetic constraints for chassis development and propose a conceptual framework for the systematic selection of environmental biosensor chassis. We identify key challenges with using current model chassis and delineate major points of conflict in choosing the most suitable organisms as chassis for environmental biosensing. This framework provides a way forward in the selection of biosensor chassis for environmental synthetic biology.

Pathway Tools Management of Pathway/Genome Data for Microbial Communities

The Pathway Tools (PTools) software provides a suite of capabilities for storing and analyzing integrated collections of genomic and metabolic information in the form of organism-specific Pathway/Genome Databases (PGDBs). A microbial community is represented in PTools by generating a PGDB from each metagenome-assembled genome (MAG). PTools computes a metabolic reconstruction for each organism, and predicts its operons. The properties of individual MAGs can be investigated using the many search and visualization operations within PTools. PTools also enables the user to investigate the properties of the microbial community by issuing searches across the full community, and by performing comparative operations across genome and pathway information. The software can generate a metabolic network diagram for the community, and it can overlay community omics datasets on that network diagram. PTools also provides a tool for searching for metabolic transformation routes across an organism community.