Genome-scale metabolic model led engineering of Nothapodytes nimmoniana plant cells for high camptothecin production.

Camptothecin (CPT) is a vital monoterpene indole alkaloid used in anti-cancer therapeutics. It is primarily derived from Camptotheca acuminata and Nothapodytes nimmoniana plants that are indigenous to Southeast Asia. Plants have intricate metabolic networks and use them to produce secondary metabolites such as CPT, which is a prerequisite for rational metabolic engineering design to optimize their production. By reconstructing metabolic models, we can predict plant metabolic behavior, facilitating the selection of suitable approaches and saving time, cost, and energy, over traditional hit and trial experimental approaches. In this study, we reconstructed a genome-scale metabolic model for N. nimmoniana (NothaGEM iSM1809) and curated it using experimentally obtained biochemical data. We also used in silico tools to identify and rank suitable enzyme targets for overexpression and knockout to maximize camptothecin production. The predicted over-expression targets encompass enzymes involved in the camptothecin biosynthesis pathway, including strictosidine synthase and geraniol 10-hydroxylase, as well as targets related to plant metabolism, such as amino acid biosynthesis and the tricarboxylic acid cycle. The top-ranked knockout targets included reactions responsible for the formation of folates and serine, as well as the conversion of acetyl CoA and oxaloacetate to malate and citrate. One of the top-ranked overexpression targets, strictosidine synthase, was chosen to generate metabolically engineered cell lines of N. nimmoniana using Agrobacterium tumefaciens-mediated transformation. The transformed cell line showed a 5-fold increase in camptothecin production, with a yield of up to 5 µg g-1.

Two-species community design of lactic acid bacteria for optimal production of lactate.

Microbial communities that metabolise pentose and hexose sugars are useful in producing high-value chemicals, resulting in the effective conversion of raw materials to the product, a reduction in the production cost, and increased yield. Here, we present a computational analysis approach called CAMP (Co-culture/Community Analyses for Metabolite Production) that simulates and identifies appropriate communities to produce a metabolite of interest. To demonstrate this approach, we focus on the optimal production of lactate from various Lactic Acid Bacteria. We used genome-scale metabolic models (GSMMs) belonging to Lactobacillus, Leuconostoc, and Pediococcus species from the Virtual Metabolic Human (VMH; https://vmh.life/) resource and well-curated GSMMs of L. plantarum WCSF1 and L. reuteri JCM 1112. We analysed 1176 two-species communities using a constraint-based modelling method for steady-state flux-balance analysis of communities. Flux variability analysis was used to detect the maximum lactate flux in the communities. Using glucose or xylose as substrates separately or in combination resulted in either parasitism, amensalism, or mutualism being the dominant interaction behaviour in the communities. Interaction behaviour between members of the community was deduced based on variations in the predicted growth rates of monocultures and co-cultures. Acetaldehyde, ethanol, acetate, among other metabolites, were found to be cross-fed between community members. L. plantarum WCSF1 was found to be a member of communities with high lactate yields. In silico community optimisation strategies to predict reaction knock-outs for improving lactate flux were implemented. Reaction knock-outs of acetate kinase, phosphate acetyltransferase, and fumarate reductase in the communities were found to enhance lactate production.

Modelling microbial communities: Harnessing consortia for biotechnological applications.

Microbes propagate and thrive in complex communities, and there are many benefits to studying and engineering microbial communities instead of single strains. Microbial communities are being increasingly leveraged in biotechnological applications, as they present significant advantages such as the division of labour and improved substrate utilisation. Nevertheless, they also present some interesting challenges to surmount for the design of efficient biotechnological processes. In this review, we discuss key principles of microbial interactions, followed by a deep dive into genome-scale metabolic models, focussing on a vast repertoire of constraint-based modelling methods that enable us to characterise and understand the metabolic capabilities of microbial communities. Complementary approaches to model microbial communities, such as those based on graph theory, are also briefly discussed. Taken together, these methods provide rich insights into the interactions between microbes and how they influence microbial community productivity. We finally overview approaches that allow us to generate and test numerous synthetic community compositions, followed by tools and methodologies that can predict effective genetic interventions to further improve the productivity of communities. With impending advancements in high-throughput omics of microbial communities, the stage is set for the rapid expansion of microbial community engineering, with a significant impact on biotechnological processes.

Comparative pan genome analysis of oral Prevotella species implicated in periodontitis.

Prevotella is part of the oral bacterial community implicated in periodontitis. Pan genome analyses of eight oral Prevotella species, P. dentalis, P. enoeca, P. fusca, P. melaninogenica, P. denticola, P. intermedia 17, P. intermedia 17-2 and P. sp. oral taxon 299 are presented in this study. Analysis of the Prevotella pan genome revealed features such as secretion systems, resistance to oxidative stress and clustered regularly interspaced short palindromic repeat (CRISPR)-Cas systems that enable the bacteria to adapt to the oral environment. We identified the presence of type VI secretion system (T6SS) in P. fusca and P. intermedia strains. For some VgrG and Hcp proteins which were not part of the core T6SS loci, we used gene neighborhood analysis and identified putative effector proteins and putative polyimmunity loci in P. fusca and polymorphic toxin systems in P. intermedia strains. Earlier studies have identified the presence of Por secretion system (PorSS) in P. gingivalis, P. melaninogenica and P. intermedia. We noted the presence of their homologs in six other oral Prevotella studied here. We suggest that in Prevotella, PorSS is used to secrete cysteine proteases such as interpain and C-terminal domain containing proteins with a "Por_secre_tail" domain. We identified subtype I-B CRISPR-Cas system in P. enoeca. Putative CRISPR-Cas system subtypes for 37 oral Prevotella and 30 non-oral Prevotella species were also predicted. Further, we performed a BLASTp search of the Prevotella proteins which are also conserved in the red-complex pathogens, against the human proteome to identify potential broad-spectrum drug targets. In summary, the use of a pan genome approach enabled identification of secretion systems and defense mechanisms in Prevotella that confer adaptation to the oral cavity.

A meta-metabolome network of carbohydrate metabolism: interactions between gut microbiota and host.

With the current knowledge of the multitude of microbes that inhabit the human body, it is increasingly clear that they constitute an integral component of the host. The gut microbiota community is principally involved in the metabolism of dietary constituents such as carbohydrates which account for majority of the energy intake from diet. Diet has gained an important role in shaping the composition of gut inhabitants. The quantity and type of food consumed is recognized as a causal factor for metabolic disorders such as obesity and diabetes. Analysis of host-microbe interactions can thus contribute to the understanding of such metabolic disorders. In this study, data from Kyoto Encyclopedia of Genes and Genomes and Carbohydrate Active EnZYmes Database was utilized as a starting point. Enzyme information from the host Homo sapiens coupled with details of the three predominant phyla of gut bacteria, namely Firmicutes, Bacteroidetes and Actinobacteria were used in the creation of a comprehensive metabolic network, which we refer to as 'meta-metabolome'. This 'meta-metabolome' provides a perspective of the degree to which microbes influence carbohydrate metabolism, in conjunction with host specific enzymes. Analysis of reactions in the network reveals the amplification of monosaccharide content brought about by microbial enzyme activity. The framework outlined in this study provides a holistic approach to assess host-microbe symbiosis. It also provides us with a means of analyzing how diet can be modulated to provide beneficial effects to the host or how probiotics can potentially be used to relieve certain metabolic disorders.