Multi Omics Insights Into Microbial Metabolism

Microbiome studies continue to reveal the intricate relationship between gut bacteria and their host, with advancements in next-generation sequencing and metabolomics providing a deeper understanding of these interactions and uncovering novel roles. Shifting from traditional single omics approaches to multi-omics integration has led to new discoveries. In this study, a multi-omic approach was employed to uncover the novel role of bile salt hydrolase (BSH) as an amine N-acyl transferase. Bile acids, crucial mediators in host-microbiome communication, have been extensively studied, but their diversity is still being appreciated. This study found a correlation between the bsh gene and the ability of bacteria to produce bacterial bile acid amidates (BBAAs), a novel class of bile acids. Pharmacological inhibition of the BSH enzyme in Bifidobacterium longum reduced BBAAs production, while knockout of the bsh gene in Bacteroides fragilis eliminated BBAAs synthesis. Heterologous expression of the bsh gene in non-producing Escherichia coli facilitated BBAAs production, and purified BSH enzyme experiments with its substrate taurocholic acid (TCA) unequivocally demonstrated its essential role in BBAAs synthesis. In vivo observations in germ-free mice monocolonized with WT B. fragilis confirmed the presence of BBAAs, while their absence was observed in mice monocolonized with the bsh knockout strain. Furthermore, BBAAs were detected in growing infants, suggesting a correlation between their presence and the developing microbiome and colonization with bsh harboring bacteria. The early-life detection of these amidates raises questions about their impact on the host and their potential to shape the host metabolome. Initial studies indicated that these amidates activate host ligand-activated transcription factors, including the farnesoid X receptor, pregnane X receptor, constitutive androstane receptor, and aryl hydrocarbon receptor, thereby potentially influencing host physiology. Additionally, through transcriptomics and untargeted metabolomics, a putative intermediate in the production of these amidates was proposed. Moreover, the integration of multi-omics approaches provides insights into the intricate interplay between xenobiotics (such as persistent organic pollutants) and pharmaceutical drugs with the gut microbiome. By combining metabolomics with next-generation sequencing data, bi-directional effects of these environmental pollutants and medications on the gut microbiome have been uncovered. Notably, the identification of microbial metabolites with consequential effects on the host has been a significant outcome of these investigations. The integration of multi-omics approaches enhances our understanding of the complexity of interactions between xenobiotics, the microbiome, and host physiology. These findings emphasize the importance of considering multi-omics integration to gain comprehensive insights into the impact of environmental factors, microbial metabolism, and host health.

Rapid progress in high-throughput experimental technologies has enabled generation of large-scale systems biology datasets. These span all biological hierarchies from genomics describing the genetic make-up, transcriptomics and proteomics at the gene and enzyme expression level, metabolomics that helps quantify the amount and nature of resultant biomolecules, to finally phenomics that describes the overall traits of an individual. This veritable data deluge necessitates algorithmic and computational advances that can leverage multi-omics integration, in order to facilitate the analysis of complex systems and extract meaningful insights. Flux balance analysis (FBA) using genome-scale metabolic (GSM) models provide an advantageous platform for doing so as these models are (relatively) parameter-free, can be constructed using the annotated genome alone and simulated in linear time offering scale-up benefits. GSMs model a network view of metabolism, wherein metabolites are cast as nodes in a graph linked via edges representing all possible biochemical conversions occurring within an organism. In Chapter 1, we present an overview of constraints-based analysis of metabolic networks, including the reconstruction of GSM models, their use within an optimization-based scheme such as FBA, and the various applications of such models. Next, we describe the extension of metabolic modeling frameworks, originally designed for microbial systems, to the study of plants. This is accompanied by its own set of challenges, such as accurately capturing the division of roles between the various tissue and organ systems and dealing with systematic biases that are typically associated with poorly annotated non-model systems. Finally, we explore how the incorporation of new data types, modeling schemes, and computational tools have impacted FBA by helping increase its predictive power and scope. FBA has proven to be quite adept at describing aggregated metabolite flows, i.e., providing a snapshot of metabolism as averaged over the entire growth cycle. However, it is also time invariant, and thus does not accommodate temporally varying cell processes such as sequestering different biomass components at various time points in a growth cycle However, we know from experiments that many organisms including cyanobacteria have a lifestyle that is heavily tailored around light availability and thus show metabolic oscillations. In Chapter 2, we present a framework called CycleSyn that augments FBA by accounting for such temporal trends. CycleSyn discretizes a growth cycle into individual time periods (called Time Point Models or TPMs), each described by its own GSM model. The flow of metabolites across TPMs is allowed while inventorying metabolite levels and only allowing for the utilization of currently or previously produced compounds. Additional time-dependent constraints can also be imposed to capture the cyclic nature of cellular processes. CycleSyn was used to develop a diurnal FBA model of Synechocystis sp. PCC 6803 metabolism. Predicted flux and metabolite pools were in line with published studies, paving the way for constructing time-resolved GSM models. Additionally, the metabolic reorganization that would be required to enable Synechocystis PCC 6803 to fix nitrogen by temporally separating it from photosynthesis was also explored. Similar to modeling multiple metabolic models at once in CycleSyn, in Chapter 3 we extend this to modeling multiple organisms together as in a community, so as to discern the underlying interactions. This community comprised a genetically streamlined unicellular cyanobacterium called Candidatus Atelocyanobacterium thalassa (or UCYN-A) living in a symbiosis with a phototrophic microalga. We used metabolic modeling to glean insights into UCYN-A's unique physiology and metabolic processes governing the symbiotic association. To this end, we developed an optimization-based framework that infers all possible trophic scenarios consistent with the observed data. Possible mechanisms employed by UCYN-A to accommodate diazotrophy with daytime carbon fixation by the host (i.e., two mutually incompatible processes) were also elucidated. We found that the metabolic functions of the two constituents, and UCYN-A's streamlined genome is optimized to support maximal nitrogen fixation flux, alluding that this symbiosis is as close to being a functional 'nitroplast' as any observed till date. We envision that the developed framework using UCYN-A and its algal host will be used as a roadmap and motivate the study of similarly unique microbial systems in the future. Understanding how genomic mutations impact the overall phenotype of an organism has been a focus of efforts aimed at improving growth yield, determining genetic markers governing a trait, and understanding adaptive processes. This has been performed conventionally using genome-wide association studies, which seek to identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. In Chapter 4, we propose a complementary tool called SNPeffect that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect was used to explain differential growth rate and metabolite accumulation in Arabidopsis and poplar as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicated that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally-characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino-acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition. Thus far, we have developed computational frameworks that examine how the metabolism of an organism dictates its total phenotype and interactions with other organisms in a community. In Chapter 5, we take the next step by examining ways in which an organism can impact its host, specifically how the infant gut microbiome is shaped. Fecal samples from newborn infants showed that gut bacteria is detectable by 16 h after birth. However, analysis of the microbiome, proteome, and metabolome data did not suggest a single genomic signature for neonatal gut colonization. Using flux balance modeling, we found E. coli to be the most common early colonizer. The appearance of bacteria was associated with decreased levels of free amino acids and an increase in products of bacterial fermentation, primarily acetate and succinate. Among all the microbial species found, these observations were only consistent with E. coli growing under anaerobic conditions using amino acid fermentation to support maximal ATP yield. These results provide a deep characterization of the first microbes in the human gut and show how the biochemical environment is altered by their appearance. Finally, in Chapter 6, we conclude with our efforts to develop computational frameworks enabling the integration of heterogeneous datasets within constraints-based optimization. We discuss current challenges associated with such modeling frameworks and their uses, and finally present future perspectives for augmenting these models with the incorporation of diverse data types, multi-scale modeling, cross-cutting applications.

In this book, the latest tools available for functional metagenomics research are described.This research enables scientists to directly access the genomes from diverse microbial genomes at one time and study these “metagenomes”. Using the modern tools of genome sequencing and cloning, researchers have now been able to harness this astounding metagenomic diversity to understand and exploit the diverse functions of microorganisms. Leading scientists from around the world demonstrate how these approaches have been applied in many different settings, including aquatic and terrestrial habitats, microbiomes, and many more environments. This is a highly informative and carefully presented book, providing microbiologists with a summary of the latest functional metagenomics literature on all specific habitats.

THE EVOLUTIONARY STRATEGIES THAT SHAPE ECOSYSTEMS In 1837 a young Charles Darwin took his notebook, wrote “I think”, and then sketched a rudimentary, stick-like tree. Each branch of Darwin’s tree of life told a story of survival and adaptation – adaptation of animals and plants not just to the environment but also to life with other living things. However, more than 150 years since Darwin published his singular idea of natural selection, the science of ecology has yet to account for how contrasting evolutionary outcomes affect the ability of organisms to coexist in communities and to regulate ecosystem functioning. In this book Philip Grime and Simon Pierce explain how evidence from across the world is revealing that, beneath the wealth of apparently limitless and bewildering variation in detailed structure and functioning, the essential biology of all organisms is subject to the same set of basic interacting constraints on life-history and physiology. The inescapable resulting predicament during the evolution of every species is that, according to habitat, each must adopt a predictable compromise with regard to how they use the resources at their disposal in order to survive. The compromise involves the investment of resources in either the effort to acquire more resources, the tolerance of factors that reduce metabolic performance, or reproduction. This three-way trade-off is the irreducible core of the universal adaptive strategy theory which Grime and Pierce use to investigate how two environmental filters selecting, respectively, for convergence and divergence in organism function determine the identity of organisms in communities, and ultimately how different evolutionary strategies affect the functioning of ecosystems. This book refl ects an historic phase in which evolutionary processes are finally moving centre stage in the effort to unify ecological theory, and animal, plant and microbial ecology have begun to find a common theoretical framework. Companion website This book has a companion website www.wiley.com/go/grime/evolutionarystrategies with Figures and Tables from the book for downloading.

Nitrogen fixation (catalyzed by the enzyme nitrogenase), cellular respiration (completed through the Tricarboxylic Acid (TCA) cycle) and mercury detoxification (through mercury methylation) are three metabolic processes used by a wide variety of microorganisms, but that also have far reaching impacts on nutrient cycling in the environment. Roseiflexus castenholzii has been found to have a unique nitrogenase gene cluster encoding several nitrogenase homologs, including the structural proteins NifH and NifDK and the radical SAM protein, NifB, necessary for cofactor biosynthesis. However, the genome of R. castenholzii lacks the suite of nitrogenase accessory proteins necessary for nitrogen fixation. To investigate the metabolic role of these nitrogenase homologs, expression and purification protocols were developed that aid in the biochemical characterization of these proteins. Synechococcus sp. PCC 7002 encodes three novel TCA proteins, contrary to previous studies that indicated these phototrophs have incomplete TCA cycles. Expression, purification and preliminary crystallization trials were completed on the three novel TCA proteins in order to gain insight into the structure of the proteins which will elucidate the mechanism of each novel enzyme and provide evidence into the novel TCA cycle utilized by these cyanobacteria. The third project presented examines the role of microorganisms in metabolizing mercury, producing methylmercury and providing an entry point for methylmercury into the food chain in Yellowstone National Park (YNP). In this project, environmental samples were enriched for a sulfate reducing organism and a culture containing three sulfate reducing bacteria (SRB) has been established. The SRB that are present and active in the enrichment samples are known to reduce sulfate and may be responsible for the presence of methyl mercury in algal mats that bioaccumulates through the food chain in YNP. The enrichment of SRB in this culture will enable the identification and characterization of the organisms that are capable of methylating mercury in hydrothermal systems. Collectively, the results presented herein increase the knowledge base of three metabolic processes used by microorganisms: nitrogen fixation, cellular respiration through the TCA cycle and mercury detoxification; these results will contribute to a broader understanding of how these processes have evolved and their impacts on the environment.

The 21st century has witnessed a complete revolution in the understanding and description of bacteria in eco- systems and microbial assemblages, and how they are regulated by complex interactions among microbes, hosts, and environments. The human organism is no longer considered a monolithic assembly of tissues, but is instead a true ecosystem composed of human cells, bacteria, fungi, algae, and viruses. As such, humans are not unlike other complex ecosystems containing microbial assemblages observed in the marine and earth environments. They all share a basic functional principle: Chemical communication is the universal language that allows such groups to properly function together. These chemical networks regulate interactions like metabolic exchange, antibiosis and symbiosis, and communication. The National Academies of Sciences, Engineering, and Medicine's Chemical Sciences Roundtable organized a series of four seminars in the autumn of 2016 to explore the current advances, opportunities, and challenges toward unveiling this "chemical dark matter" and its role in the regulation and function of different ecosystems. The first three focused on specific ecosystemsâ€"earth, marine, and humanâ€"and the last on all microbiome systems. This publication summarizes the presentations and discussions from the seminars.

With the advent of new technologies and acquired knowledge, the number of fields in omics and their applications in diverse areas are rapidly increasing in the postgenomics era. Such emerging fields—including pharmacogenomics, toxicogenomics, regulomics, spliceomics, metagenomics, and environomics—present budding solutions to combat global challenges in biomedicine, agriculture, and the environment. OMICS: Applications in Biomedical, Agricultural, and Environmental Sciences provides valuable insights into the applications of modern omics technologies to real-world problems in the life sciences. Filling a gap in the literature, it offers a broad, multidisciplinary view of current and emerging applications of omics in a single volume. Written by highly experienced active researchers, each chapter describes a particular area of omics and the associated technologies and applications. Topics covered include: Proteomics, epigenomics, and pharmacogenomics Toxicogenomics and the assessment of environmental pollutants Applications of plant metabolomics Nutrigenomics and its therapeutic applications Microalgal omics and omics approaches in biofuel production Next-generation sequencing and omics technology for transgenic plant analysis Omics approaches in crop improvement Engineering dark-operative chlorophyll synthesis Computational regulomics Omics techniques for the analysis of RNA splicing New fields, including metagenomics, glycomics, and miRNA Breast cancer biomarkers for early detection Environomics strategies for environmental sustainability This timely book explores a wide range of omics application areas in the biomedical, agricultural, and environmental sciences. Throughout, it highlights working solutions as well as open problems and future challenges. Demonstrating the diversity of omics, it introduces readers to state-of-the-art developments and trends in omics-driven research.

The interaction of microorganisms with geological activities results in processes influencing development of the Earth’s geo- and biospheres. In assessing these microbial functions, scientists have explored short- and longterm geological changes attributed to microorganisms and developed new approaches to evaluate the physiology of microbes including microbial interaction with the geological environment. As the field of geomicrobiology developed, it has become highly interdisciplinary and this book provides a review of the recent developments in a cross section of topics including origin of life, microbial-mineral interactions and microbial processes functioning in marine as well as terrestrial environments. A major component of this book addresses molecular techniques to evaluate microbial evolution and assess relationships of microbes in complex, natural c- munities. Recent developments in so-called ‘omics’ technologies, including (meta) genomics and (meta)proteomics, and isotope labeling methods allow new insights into the function of microbial community members and their possible geological impact. While this book summarizes current knowledge in various areas, it also reveals unresolved questions that require future investigations. Information in these chapters enhances our fundamental knowledge of geomicrobiology that contributes to the exploitation of microbial functions in mineral and environmental biotechn- ogy applications. It is our hope that this book will stimulate interest in the general field of geomicrobiology and encourage others to explore microbial processes as applied to the Earth.

Although we can't usually see them, microbes are essential for every part of human life-indeed all life on Earth. The emerging field of metagenomics offers a new way of exploring the microbial world that will transform modern microbiology and lead to practical applications in medicine, agriculture, alternative energy, environmental remediation, and many others areas. Metagenomics allows researchers to look at the genomes of all of the microbes in an environment at once, providing a "meta" view of the whole microbial community and the complex interactions within it. It's a quantum leap beyond traditional research techniques that rely on studying-one at a time-the few microbes that can be grown in the laboratory. At the request of the National Science Foundation, five Institutes of the National Institutes of Health, and the Department of Energy, the National Research Council organized a committee to address the current state of metagenomics and identify obstacles current researchers are facing in order to determine how to best support the field and encourage its success. The New Science of Metagenomics recommends the establishment of a "Global Metagenomics Initiative" comprising a small number of large-scale metagenomics projects as well as many medium- and small-scale projects to advance the technology and develop the standard practices needed to advance the field. The report also addresses database needs, methodological challenges, and the importance of interdisciplinary collaboration in supporting this new field.