Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants

Marine Bacteria and Omic Approaches: A Novel and Potential Repository for Bioremediation Assessment

Marine environments accommodating diverse assortments of life constitute a great pool of differentiated natural resources. The cumulative need to remedy unpropitious effects of anthropogenic activities on estuaries, and coastal marine ecosystems has propelled the development of effective bioremediation strategies. Marine bacteria producing biosurfactants are promising agents for bio-remediating oil pollution in marine environments, making them prospective candidates for enhancing oil recovery. Molecular omics technologies are considered an emerging field of research in ecological and diversity assessment owing to their utility in environmental surveillance and bioremediation of polluted sites. A thorough literature review was undertaken to understand the applicability of different omic techniques employed for bioremediation assessment using marine bacteria. This review further establishes that for bioremediation of environmental pollutants (i.e., heavy metals, hydrocarbons, xenobiotic and numerous recalcitrant compounds), organisms isolated from marine environments can be better utilized for their removal. The literature survey shows that omics approaches can provide exemplary knowledge about microbial communities and their role in the bioremediation of environmental pollutants. This review centres on applications of marine bacteria in enhanced bioremediation, utilizing the omics approaches that can be a vital biological contrivance in environmental monitoring to tackle environmental degradation. The paper aims to identify the gaps in investigations involving marine bacteria to help researchers, ecologists, and decision-makers to develop a holistic understanding regarding their utility in bioremediation assessment.

Disease, Drugs and Dysbiosis: Understanding Microbial Signatures in Metabolic Disease and Medical Interventions

Since the discovery of the potential role for the gut microbiota in health and disease, many studies have gone on to report its impact in various pathologies. These studies have fuelled interest in the microbiome as a potential new target for treating disease Here, we reviewed the key metabolic diseases, obesity, type 2 diabetes and atherosclerosis and the role of the microbiome in their pathogenesis. In particular, we will discuss disease associated microbial dysbiosis; the shift in the microbiome caused by medical interventions and the altered metabolite levels between diseases and interventions. The microbial dysbiosis seen was compared between diseases including Crohn’s disease and ulcerative colitis, non-alcoholic fatty liver disease, liver cirrhosis and neurodegenerative diseases, Alzheimer’s and Parkinson’s. This review highlights the commonalities and differences in dysbiosis of the gut between diseases, along with metabolite levels in metabolic disease vs. the levels reported after an intervention. We identify the need for further analysis using systems biology approaches and discuss the potential need for treatments to consider their impact on the microbiome.

PlantSEED enables automated annotation and reconstruction of plant primary metabolism with improved compartmentalization and comparative consistency

Genome-scale metabolic reconstructions help us to understand and engineer metabolism. Next-generation sequencing technologies are delivering genomes and transcriptomes for an ever-widening range of plants. While such omic data can, in principle, be used to compare metabolic reconstructions in different species, organs and environmental conditions, these comparisons require a standardized framework for the reconstruction of metabolic networks from transcript data. We previously introduced PlantSEED as a framework covering primary metabolism for 10 species. We have now expanded PlantSEED to include 39 species and provide tools that enable automated annotation and metabolic reconstruction from transcriptome data. The algorithm for automated annotation in PlantSEED propagates annotations using a set of signature k-mers (short amino acid sequences characteristic of particular proteins) that identify metabolic enzymes with an accuracy of about 97%. PlantSEED reconstructions are built from a curated template that includes consistent compartmentalization for more than 100 primary metabolic subsystems. Together, the annotation and reconstruction algorithms produce reconstructions without gaps and with more accurate compartmentalization than existing resources. These tools are available via the PlantSEED web interface at http://modelseed.org, which enables users to upload, annotate and reconstruct from private transcript data and simulate metabolic activity under various conditions using flux balance analysis. We demonstrate the ability to compare these metabolic reconstructions with a case study involving growth on several nitrogen sources in roots of four species.

From plant metabolic engineering to plant synthetic biology: The evolution of the design/build/test/learn cycle

Genetic improvement of crops started since the dawn of agriculture and has continuously evolved in parallel with emerging technological innovations. The use of genome engineering in crop improvement has already revolutionised modern agriculture in less than thirty years. Plant metabolic engineering is still at a development stage and faces several challenges, in particular with the time necessary to develop plant based solutions to bio-industrial demands. However the recent success of several metabolic engineering approaches applied to major crops are encouraging and the emerging field of plant synthetic biology offers new opportunities. Some pioneering studies have demonstrated that synthetic genetic circuits or orthogonal metabolic pathways can be introduced into plants to achieve a desired function. The combination of metabolic engineering and synthetic biology is expected to significantly accelerate crop improvement. A defining aspect of both fields is the design/build/test/learn cycle, or the use of iterative rounds of testing modifications to refine hypotheses and develop best solutions. Several technological and technical improvements are now available to make a better use of each design, build, test, and learn components of the cycle. All these advances should facilitate the rapid development of a wide variety of bio-products for a world in need of sustainable solutions.

A comparative UPLC-Q/TOF-MS-based metabolomics approach for distinguishing Zingiber officinale Roscoe of two geographical origins

Ginger, the rhizome of Zingiber officinale Roscoe, is a popular spice used in the food, beverage and confectionary industries. In this study, we report an untargeted UPLC-Q/TOF-MS-based metabolomics approach for comprehensively discriminating between ginger from two geographical locations, Ghana in West Africa and China. Forty batches of fresh ginger from both countries were discriminated using principal component analysis and orthogonal partial least squares discrimination analysis. Sixteen differential metabolites were identified between the gingers from the two geographical locations, six of which were identified as the marker compounds responsible for the discrimination. Our study highlights the essence and predictive power of metabolomics in detecting minute differences in same varieties of plants/plant samples based on the levels and composition of their metabolites.

Using fluorescence lifetime microscopy to study the subcellular localization of anthocyanins

Anthocyanins are flavonoid pigments that accumulate in most seed plants. They are synthesized in the cytoplasm but accumulate inside the vacuoles. Anthocyanins are pigmented at the lower vacuolar pH, but in the cytoplasm they can be visualized based on their fluorescence properties. Thus, anthocyanins provide an ideal system for the development of new methods to investigate cytoplasmic pools and association with other molecular components. We have analyzed the fluorescence decay of anthocyanins by fluorescence lifetime imaging microscopy (FLIM), in both in vitro and in vivo conditions, using wild-type and mutant Arabidopsis thaliana seedlings. Within plant cells, the amplitude-weighted mean fluorescence lifetime (τ_m ) correlated with distinct subcellular localizations of anthocyanins. The vacuolar pool of anthocyanins exhibited shorter τ_m than the cytoplasmic pool. Consistently, lowering the pH of anthocyanins in solution shortened their fluorescence decay. We propose that FLIM is a useful tool for understanding the trafficking of anthocyanins and, potentially, for estimating vacuolar pH inside intact plant cells.