FlySilico: Flux balance modeling of Drosophila larval growth and resource allocation

Changes in the wing shape and size in fruit flies exposed to micro and nanoplastics

Geometric morphometrics analysis (GMA) is a well-known technique to identify minute changes in Drosophila wings. This study aimed to determine potential changes in Drosophila wings shape and size after exposure to polystyrene nanoplastics (NPs) (50 nm) and microplastics (MPs) (1 μm). Flies were exposed from eggs to pupal eclosion and analyzed using GMA. Results revealed a difference in shape and size between male and female wings, as expected, due to sexual dimorphism. Therefore, wings were analyzed by sex. Wings of MPs and NPs treated females were elongated compared to controls and had a constriction of the wing joint. Additionally, MPs treated female flies had the most dissimilar shape compared to controls. In male flies, NPs flies had smaller wings compared to MPs and control flies. Compared to control, NPs wings of males were shrunken at the joint and in the entire proximal region of the wing. However, male MPs wings had a narrower anal region and were slightly elongated. These results reveal that wing shape and size can change in a different way based on the sex of the flies and size of plastic particles that larvae interacted with. All the changes in the wings occurred only within the normally allowed wing variation and treatment with NPs/MPs did not cause development of the aberrant phenotypes. Results can pave the way for further understanding of how MPs and NPs can alter phenotypes of flies.

Phytoconstituent Profiles Associated with Relevant Antioxidant Potential and Variable Nutritive Effects of the Olive, Sweet Almond, and Black Mulberry Gemmotherapy Extracts

The extracts of whole plants or specific organs from different plant species are gaining increasing attention for their phytotherapy applications. Accordingly, we prepared standardized gemmotherapy extracts (GTEs) from young shoots/buds of olive (Olea europaea), sweet almond (Prunus amygdalus), and black mulberry (Morus nigra), and analyzed the corresponding phytonutrient profiles. We identified 42, 103, and 109 phytonutrients in the olive, almond, and black mulberry GTEs, respectively, containing amino acids, vitamins, polyphenols, flavonoids, coumarins, alkaloids, iridoids, carboxylic acids, lignans, terpenoids, and others. In order to assess the physiological effects generated by the GTEs, we developed a translational nutrition model based on Drosophila melanogaster and Cyprinus carpio. The results indicate that GTEs could influence, to a variable extent, viability and ATP synthesis, even though both are dependent on the specific carbohydrate load of the applied diet and the amino acid and polyphenol pools provided by the GTEs. It seems, therefore, likely that the complex chemical composition of the GTEs offers nutritional properties that cannot be separated from the health-promoting mechanisms that ultimately increase viability and survival. Such an approach sets the paves the way for the nutritional genomic descriptions regarding GTE-associated health-promoting effects.

A new metabolic model of Drosophila melanogaster and the integrative analysis of Parkinson's disease

High conservation of the disease-associated genes between flies and humans facilitates the common use of Drosophila melanogaster to study metabolic disorders under controlled laboratory conditions. However, metabolic modeling studies are highly limited for this organism. We here report a comprehensively curated genome-scale metabolic network model of Drosophila using an orthology-based approach. The gene coverage and metabolic information of the draft model derived from a reference human model were expanded via Drosophila-specific KEGG and MetaCyc databases, with several curation steps to avoid metabolic redundancy and stoichiometric inconsistency. Furthermore, we performed literature-based curations to improve gene-reaction associations, subcellular metabolite locations, and various metabolic pathways. The performance of the resulting Drosophila model (8,230 reactions, 6,990 metabolites, and 2,388 genes), iDrosophila1 (https://github.com/SysBioGTU/iDrosophila), was assessed using flux balance analysis in comparison with the other currently available fly models leading to superior or comparable results. We also evaluated the transcriptome-based prediction capacity of iDrosophila1, where differential metabolic pathways during Parkinson's disease could be successfully elucidated. Overall, iDrosophila1 is promising to investigate system-level metabolic alterations in response to genetic and environmental perturbations.

Metabolic Modeling of Hermetia illucens Larvae Resource Allocation for High-Value Fatty Acid Production

All plant and animal kingdom organisms use highly connected biochemical networks to facilitate sustaining, proliferation, and growth functions. While the biochemical network details are well known, the understanding of the intense regulation principles is still limited. We chose to investigate the Hermetia illucens fly at the larval stage because this stage is a crucial period for the successful accumulation and allocation of resources for the subsequent organism's developmental stages. We combined iterative wet lab experiments and innovative metabolic modeling design approaches to simulate and explain the H. illucens larval stage resource allocation processes and biotechnology potential. We performed time-based growth and high-value chemical compound accumulation wet lab chemical analysis experiments on larvae and the Gainesville diet composition. We built and validated the first H. illucens medium-size, stoichiometric metabolic model to predict the effects of diet-based alterations on fatty acid allocation potential. Using optimization methods such as flux balance and flux variability analysis on the novel insect metabolic model, we predicted that doubled essential amino acid consumption increased the growth rate by 32%, but pure glucose consumption had no positive impact on growth. In the case of doubled pure valine consumption, the model predicted a 2% higher growth rate. In this study, we describe a new framework for researching the impact of dietary alterations on the metabolism of multi-cellular organisms at different developmental stages for improved, sustainable, and directed high-value chemicals.

The fat body cortical actin network regulates Drosophila inter-organ nutrient trafficking, signaling, and adipose cell size

Defective nutrient storage and adipocyte enlargement (hypertrophy) are emerging features of metabolic syndrome and type 2 diabetes. Within adipose tissues, how the cytoskeletal network contributes to adipose cell size, nutrient uptake, fat storage, and signaling remain poorly understood. Utilizing the Drosophila larval fat body (FB) as a model adipose tissue, we show that a specific actin isoform-Act5C-forms the cortical actin network necessary to expand adipocyte cell size for biomass storage in development. Additionally, we uncover a non-canonical role for the cortical actin cytoskeleton in inter-organ lipid trafficking. We find Act5C localizes to the FB cell surface and cell-cell boundaries, where it intimately contacts peripheral LDs (pLDs), forming a cortical actin network for cell architectural support. FB-specific loss of Act5C perturbs FB triglyceride (TG) storage and LD morphology, resulting in developmentally delayed larvae that fail to develop into flies. Utilizing temporal RNAi-depletion approaches, we reveal that Act5C is indispensable post-embryogenesis during larval feeding as FB cells expand and store fat. Act5C-deficient FBs fail to grow, leading to lipodystrophic larvae unable to accrue sufficient biomass for complete metamorphosis. In line with this, Act5C-deficient larvae display blunted insulin signaling and reduced feeding. Mechanistically, we also show this diminished signaling correlates with decreased lipophorin (Lpp) lipoprotein-mediated lipid trafficking, and find Act5C is required for Lpp secretion from the FB for lipid transport. Collectively, we propose that the Act5C-dependent cortical actin network of Drosophila adipose tissue is required for adipose tissue size-expansion and organismal energy homeostasis in development, and plays an essential role in inter-organ nutrient transport and signaling.

Modeling Drosophila gut microbe interactions reveals metabolic interconnectivity

We know a lot about varying gut microbiome compositions. Yet, how the bacteria affect each other remains elusive. In mammals, this is largely based on the sheer complexity of the microbiome with at least hundreds of different species. Thus, model organisms such as Drosophila melanogaster are commonly used to investigate mechanistic questions as the microbiome consists of only about 10 leading bacterial species. Here, we isolated gut bacteria from laboratory-reared Drosophila, sequenced their respective genomes, and used this information to reconstruct genome-scale metabolic models. With these, we simulated growth in mono- and co-culture conditions and different media including a synthetic diet designed to grow Drosophila melanogaster. Our simulations reveal a synergistic growth of some but not all gut microbiome members, which stems on the exchange of distinct metabolites including tricarboxylic acid cycle intermediates. Culturing experiments confirmed our predictions. Our study thus demonstrates the possibility to predict microbiome-derived growth-promoting cross-feeding.

Genome-scale metabolic network reconstruction of model animals as a platform for translational research

Genome-scale metabolic models (GEMs) are used extensively for analysis of mechanisms underlying human diseases and metabolic malfunctions. However, the lack of comprehensive and high-quality GEMs for model organisms restricts translational utilization of omics data accumulating from the use of various disease models. Here we present a unified platform of GEMs that covers five major model animals, including Mouse1 (Mus musculus), Rat1 (Rattus norvegicus), Zebrafish1 (Danio rerio), Fruitfly1 (Drosophila melanogaster), and Worm1 (Caenorhabditis elegans). These GEMs represent the most comprehensive coverage of the metabolic network by considering both orthology-based pathways and species-specific reactions. All GEMs can be interactively queried via the accompanying web portal Metabolic Atlas. Specifically, through integrative analysis of Mouse1 with RNA-sequencing data from brain tissues of transgenic mice we identified a coordinated up-regulation of lysosomal GM2 ganglioside and peptide degradation pathways which appears to be a signature metabolic alteration in Alzheimer's disease (AD) mouse models with a phenotype of amyloid precursor protein overexpression. This metabolic shift was further validated with proteomics data from transgenic mice and cerebrospinal fluid samples from human patients. The elevated lysosomal enzymes thus hold potential to be used as a biomarker for early diagnosis of AD. Taken together, we foresee that this evolving open-source platform will serve as an important resource to facilitate the development of systems medicines and translational biomedical applications.

A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer

In silico models of biomolecular regulation in cancer, annotated with patient-specific gene expression data, can aid in the development of novel personalized cancer therapeutic strategies. Drosophila melanogaster is a well-established animal model that is increasingly being employed to evaluate such preclinical personalized cancer therapies. Here, we report five Boolean network models of biomolecular regulation in cells lining the Drosophila midgut epithelium and annotate them with colorectal cancer patient-specific mutation data to develop an in silico Drosophila Patient Model (DPM). We employed cell-type-specific RNA-seq gene expression data from the FlyGut-seq database to annotate and then validate these networks. Next, we developed three literature-based colorectal cancer case studies to evaluate cell fate outcomes from the model. Results obtained from analyses of the proposed DPM help: (i) elucidate cell fate evolution in colorectal tumorigenesis, (ii) validate cytotoxicity of nine FDA-approved CRC drugs, and (iii) devise optimal personalized treatment combinations. The personalized network models helped identify synergistic combinations of paclitaxel-regorafenib, paclitaxel-bortezomib, docetaxel-bortezomib, and paclitaxel-imatinib for treating different colorectal cancer patients. Follow-on therapeutic screening of six colorectal cancer patients from cBioPortal using this drug combination demonstrated a 100% increase in apoptosis and a 100% decrease in proliferation. In conclusion, this work outlines a novel roadmap for decoding colorectal tumorigenesis along with the development of personalized combinatorial therapeutics for preclinical translational studies.

The Metabolic Response to Infection With Wolbachia Implicates the Insulin/Insulin-Like-Growth Factor and Hypoxia Signaling Pathways in Drosophila melanogaster

The endosymbiotic bacteria, Wolbachia, are best known for their ability to manipulate insect-host reproduction systems that enhance their vertical transmission within host populations. Increasingly, Wolbachia have been shown to depend on their hosts' metabolism for survival and in turn provision metabolites to their host. Wolbachia depends completely on the host for iron and as such iron has been speculated to be a fundamental aspect of Wolbachia-host interplay. However, the mechanisms by which dietary iron levels, Wolbachia, and its host interact remain to be elucidated. To understand the metabolic dependence of Wolbachia on its host, the possibility of metabolic provisioning and extraction, and the interplay with available dietary iron, we have used NMR-based metabolomics and compared metabolite profiles of Wolbachia-infected and uninfected Drosophila melanogaster flies raised on varying levels of dietary iron. We observed marked metabolite differences in the affected metabolite pathways between Wolbachia-infected and uninfected Drosophila, which were dependent on the dietary iron levels. Excess iron led to lipid accumulation, whereas iron deficiency led to changes in carbohydrate levels. This represents a major metabolic shift triggered by alterations in iron levels. Lipids, some amino acids, carboxylic acids, and nucleosides were the major metabolites altered by infection. The metabolic response to infection showed a reprogramming of the mitochondrial metabolism in the host. Based on these observations, we developed a physiological model which postulates that the host's insulin/insulin-like-growth factor pathway is depressed and the hypoxia signaling pathway is activated upon Wolbachia infection. This reprogramming leads to predominantly non-oxidative metabolism in the host, whereas Wolbachia maintains oxidative metabolism. Our data also support earlier predictions of the extraction of alanine from the host while provisioning riboflavin and ATP to the host.