A genome-scale metabolic model for the denitrifying bacterium Thauera sp. MZ1T accurately predicts degradation of pollutants and production of polymers.

The denitrifying bacterium Thauera sp. MZ1T, a common member of microbial communities in wastewater treatment facilities, can produce different compounds from a range of carbon (C) and nitrogen (N) sources under aerobic and anaerobic conditions. In these different conditions, Thauera modifies its metabolism to produce different compounds that influence the microbial community.

Spatial chemistry of citrus reveals molecules bactericidal to Candidatus Liberibacter asiaticus.

Huanglongbing (HLB), associated with the psyllid-vectored phloem-limited bacterium, Candidatus Liberibacter asiaticus (CLas), is a disease threat to all citrus production worldwide. Currently, there are no sustainable curative or prophylactic treatments available. In this study, we utilized mass spectrometry (MS)-based metabolomics in combination with 3D molecular mapping to visualize complex chemistries within plant tissues to explore how these chemistries change in vivo in HLB-infected trees.

Mixotrophic growth of a ubiquitous marine diatom.

Diatoms are major players in the global carbon cycle, and their metabolism is affected by ocean conditions. Understanding the impact of changing inorganic nutrients in the oceans on diatoms is crucial, given the changes in global carbon dioxide levels. Here, we present a genome-scale metabolic model (MK1961) for , an in silico resource to understand uncharacterized metabolic functions in this ubiquitous diatom.

Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass.

Unlabelled: Growing environmental concerns and the need to adopt a circular economy have highlighted the importance of waste valorization for resource recovery. Microbial consortia-enabled biotechnologies have made significant developments in the biomanufacturing of valuable resources from waste biomass that serve as suitable alternatives to petrochemical-derived products. These microbial consortia-based processes are designed following a top-down or bottom-up engineering approach.

Inverse-Vaccines for Rheumatoid Arthritis Re-establish Metabolic and Immunological Homeostasis in Joint Tissues.

Rheumatoid arthritis (RA) causes immunological and metabolic imbalances in tissue, exacerbating inflammation in affected joints. Changes in immunological and metabolic tissue homeostasis at different stages of RA are not well understood. Herein, the changes in the immunological and metabolic profiles in different stages in collagen induced arthritis (CIA), namely, early, intermediate, and late stage is examined.

Metabolic engineering of Synechococcus elongatus 7942 for enhanced sucrose biosynthesis.

The capability of cyanobacteria to produce sucrose from CO and light has a remarkable societal and biotechnological impact since sucrose can serve as a carbon and energy source for a variety of heterotrophic organisms and can be converted into value-added products. However, most metabolic engineering efforts have focused on understanding local pathway alterations that drive sucrose biosynthesis and secretion in cyanobacteria rather than analyzing the global flux re-routing that occurs following induction of sucrose production by salt stress. Here, we investigated global metabolic flux alterations in a sucrose-secreting (cscB-overexpressing) strain relative to its wild-type Synechococcus elongatus 7942 parental strain.

The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions.

The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically.

A model industrial workhorse: Bacillus subtilis strain 168 and its genome after a quarter of a century.

The vast majority of genomic sequences are automatically annotated using various software programs. The accuracy of these annotations depends heavily on the very few manual annotation efforts that combine verified experimental data with genomic sequences from model organisms. Here, we summarize the updated functional annotation of Bacillus subtilis strain 168, a quarter century after its genome sequence was first made public.

Optimization of nutrient utilization efficiency and productivity for algal cultures under light and dark cycles using genome-scale model process control.

Algal cultivations are strongly influenced by light and dark cycles. In this study, genome-scale metabolic models were applied to optimize nutrient supply during alternating light and dark cycles of Chlorella vulgaris. This approach lowered the glucose requirement by 75% and nitrate requirement by 23%, respectively, while maintaining high final biomass densities that were more than 80% of glucose-fed heterotrophic culture.

Predicting stress response and improved protein overproduction in Bacillus subtilis.

Bacillus subtilis is a well-characterized microorganism and a model for the study of Gram-positive bacteria. The bacterium can produce proteins at high densities and yields, which has made it valuable for industrial bioproduction. Like other cell factories, metabolic modeling of B.

Multi-Objective Optimization of Microalgae Metabolism: An Evolutive Algorithm Based on FBA.

Studies enabled by metabolic models of different species of microalgae have become significant since they allow us to understand changes in their metabolism and physiological stages. The most used method to study cell metabolism is FBA, which commonly focuses on optimizing a single objective function. However, recent studies have brought attention to the exploration of simultaneous optimization of multiple objectives.

Flux balance analysis of the ammonia-oxidizing bacterium Nitrosomonas europaea ATCC19718 unravels specific metabolic activities while degrading toxic compounds.

The ammonia-oxidizing bacterium Nitrosomonas europaea has been widely recognized as an important player in the nitrogen cycle as well as one of the most abundant members in microbial communities for the treatment of industrial or sewage wastewater. Its natural metabolic versatility and extraordinary ability to degrade environmental pollutants (e.g.

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data.

Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g.

Host DNA Depletion in Saliva Samples for Improved Shotgun Metagenomics.

Host DNA makes up the majority of DNA in a saliva sample. Therefore, shotgun metagenomics can be an inefficient way to evaluate the microbial populations of saliva since often <10% of the sequencing reads are microbial. In this chapter, we describe a method to deplete human DNA from fresh or frozen saliva samples, allowing for more efficient shotgun metagenomic sequencing of the salivary microbial community.

Kinetic, metabolic, and statistical analytics: addressing metabolic transport limitations among organelles and microbial communities.

Microbial organisms engage in a variety of metabolic interactions. A crucial part of these interactions is the exchange of molecules between different organelles, cells, and the environment. The main forces mediating this metabolic exchange are transporters.

Biotechnology for secure biocontainment designs in an emerging bioeconomy.

Genetically modified organisms (GMOs) have emerged as an integral component of a sustainable bioeconomy, with an array of applications in agriculture, bioenergy, and biomedicine. However, the rapid development of GMOs and associated synthetic biology approaches raises a number of biosecurity concerns related to environmental escape of GMOs, detection thereof, and impact upon native ecosystems. A myriad of genetic safeguards have been deployed in diverse microbial hosts, ranging from classical auxotrophies to global genome recoding.

The sum is greater than the parts: exploiting microbial communities to achieve complex functions.

Multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology.

Linking metabolic phenotypes to pathogenic traits among "Candidatus Liberibacter asiaticus" and its hosts.

Candidatus Liberibacter asiaticus (CLas) has been associated with Huanglongbing, a lethal vector-borne disease affecting citrus crops worldwide. While comparative genomics has provided preliminary insights into the metabolic capabilities of this uncultured microorganism, a comprehensive functional characterization is currently lacking. Here, we reconstructed and manually curated genome-scale metabolic models for the six CLas strains A4, FL17, gxpsy, Ishi-1, psy62, and YCPsy, in addition to a model of the closest related culturable microorganism, L.

Synthetic microbial communities of heterotrophs and phototrophs facilitate sustainable growth.

Microbial communities comprised of phototrophs and heterotrophs hold great promise for sustainable biotechnology. Successful application of these communities relies on the selection of appropriate partners. Here we construct four community metabolic models to guide strain selection, pairing phototrophic, sucrose-secreting Synechococcus elongatus with heterotrophic Escherichia coli K-12, Escherichia coli W, Yarrowia lipolytica, or Bacillus subtilis.

Modeling of nitrogen fixation and polymer production in the heterotrophic diazotroph DJ.

Nitrogen fixation is an important metabolic process carried out by microorganisms, which converts molecular nitrogen into inorganic nitrogenous compounds such as ammonia (NH). These nitrogenous compounds are crucial for biogeochemical cycles and for the synthesis of essential biomolecules, i.e.

Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes.

Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules.

Author Correction: Environmental stimuli drive a transition from cooperation to competition in synthetic phototrophic communities.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Environmental stimuli drive a transition from cooperation to competition in synthetic phototrophic communities.

Phototrophic communities of photosynthetic algae or cyanobacteria and heterotrophic bacteria or fungi are pervasive throughout the environment. How interactions between members contribute to the resilience and affect the fitness of phototrophic communities is not fully understood. Here, we integrated metatranscriptomics, metabolomics and phenotyping with computational modelling to reveal condition-dependent secretion and cross-feeding of metabolites in a synthetic community.

Utilizing genome-scale models to optimize nutrient supply for sustained algal growth and lipid productivity.

Nutrient availability is critical for growth of algae and other microbes used for generating valuable biochemical products. Determining the optimal levels of nutrient supplies to cultures can eliminate feeding of excess nutrients, lowering production costs and reducing nutrient pollution into the environment. With the advent of omics and bioinformatics methods, it is now possible to construct genome-scale models that accurately describe the metabolism of microorganisms.

Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates.

Dietary habits have been associated with alterations of the human gut resident microorganisms contributing to obesity, diabetes and cancer. In Western diets, red meat is a frequently eaten food, but long-term consumption has been associated with increased risk of disease. Red meat is enriched in N-glycolylneuraminic acid (Neu5Gc) that cannot be synthesized by humans.