Case 314: Cerebral Proliferative Angiopathy.

HISTORY: An 18-year-old man presented to the neurosurgery outpatient department with recurrent episodes of epistaxis for the past 8 years and altered behavior for the past month. Epistaxis was scanty in amount, intermittent, spontaneous, and not associated with any trauma or nasal obstruction or breathing difficulties. Bleeding used to stop spontaneously after some time. There was no history of associated headache, seizures, vomiting, fever, or loss of consciousness. On physical examination, the patient was afebrile, with normal vital signs and normal Glasgow Coma Scale score (15 of 15) at the time of presentation. Multiple dilated engorged veins were visible on the forehead; however, there was no evidence of abnormal skin pigmentation. Neurologic examination yielded findings that were within normal limits. Laboratory examinations revealed a hemoglobin level of 11 g/dL (normal range, 13.2-16.6 g/dL), with the rest of the parameters within normal limits. This patient underwent unenhanced CT of the brain and paranasal sinuses followed by contrast-enhanced MRI of the brain for further evaluation.

Case 314.

HISTORY: An 18-year-old man presented to the neurosurgery outpatient department with recurrent episodes of epistaxis for the past 8 years and altered behavior for the past month. Epistaxis was scanty in amount, intermittent, spontaneous, and not associated with any trauma or nasal obstruction or breathing difficulties. Bleeding used to stop spontaneously after some time. There was no history of associated headache, seizures, vomiting, fever, or loss of consciousness. On physical examination, the patient was afebrile, with normal vital signs and normal Glasgow Coma Scale score (15 of 15) at the time of presentation. Multiple dilated engorged veins were visible on the forehead; however, there was no evidence of abnormal skin pigmentation. Neurologic examination yielded findings that were within normal limits. Laboratory examinations revealed a hemoglobin level of 11 g/dL (normal range, 13.2-16.6 g/dL), with the rest of the parameters within normal limits. This patient underwent unenhanced CT of the brain and paranasal sinuses followed by contrast-enhanced MRI of the brain for further evaluation (Figs 1-3).

Molib: A machine learning based classification tool for the prediction of biofilm inhibitory molecules.

Identification of biofilm inhibitory small molecules appears promising for therapeutic intervention against biofilm-forming bacteria. However, the experimental identification of such molecules is a time-consuming task, and thus, the computational approaches emerge as promising alternatives. We developed the 'Molib' tool to predict the biofilm inhibitory activity of small molecules. We curated a training dataset of biofilm inhibitory molecules, and the structural and chemical features were used for feature selection, followed by algorithms optimization and building of machine learning-based classification models. On five-fold cross validation, Random Forest-based descriptor, fingerprint and hybrid classification models showed accuracies of 0.93, 0.88 and 0.90, respectively. The performances of all models were evaluated on two different validation datasets including biofilm inhibitory and non-inhibitory molecules, attesting to its accuracy (≥ 0.90). The Molib web server would serve as a highly useful and reliable tool for the prediction of biofilm inhibitory activity of small molecules.

Mechanistic elucidation of amphetamine metabolism by tyramine oxidase from human gut microbiota using molecular dynamics simulations.

The human gut harbors diverse bacterial species in the gut, which play an important role in the metabolism of food and host health. Recent studies have also revealed their role in altering the pharmacological properties and efficacy of oral drugs through promiscuous metabolism. However, the atomistic details of the enzyme-drug interactions of gut bacterial enzymes which can potentially carry out the metabolism of drug molecules are still scarce. A well-known example is the FDA drug amphetamine (a central nervous system stimulant), which has been predicted to undergo promiscuous metabolism by gut bacteria. Therefore, to understand the atomistic details and energy landscape of the gut microbial enzyme-mediated metabolism of this drug, molecular dynamics studies were performed. It was observed that amphetamine binds to tyramine oxidase from the Escherichia coli strain present in the human gut microbiota at the binding site harboring polar and nonpolar amino acids. The stability analysis of amphetamine at the binding site showed that the binding is stable and the free energy for the binding of amphetamine was found to be ~ -51.71 kJ/mol. The insights provided by this study on promiscuous metabolism of amphetamine by a gut enzyme will be very useful to improve the efficacy of the drug.

Gut microbiome composition of wild western lowland gorillas is associated with individual age and sex factors.

OBJECTIVES: Environmental and ecological factors, such as geographic range, anthropogenic pressure, group identity, and feeding behavior are known to influence the gastrointestinal microbiomes of great apes. However, the influence of individual host traits such as age and sex, given specific dietary and social constraints, has been less studied. The objective of this investigation was to determine the associations between an individual's age and sex on the diversity and composition of the gut microbiome in wild western lowland gorillas. MATERIALS AND METHODS: Publicly available 16S rRNA data generated from fecal samples of different groups of Gorilla gorilla gorilla in the Central African Republic were downloaded and bioinformatically processed. The groups analyzed included habituated, partially habituated and unhabituated gorillas, sampled during low fruit (dry, n = 28) and high fruit (wet, n = 82) seasons. Microbial community analyses (alpha and beta diversity and analyses of discriminant taxa), in tandem with network-wide approaches, were used to (a) mine for specific age and sex based differences in gut bacterial community composition and to (b) asses for gut community modularity and bacterial taxa with potential functional roles, in the context of seasonal food variation, and social group affiliation. RESULTS: Both age and sex significantly influenced gut microbiome diversity and composition in wild western lowland gorillas. However, the largest differences were observed between infants and adults in habituated groups and between adults and immature gorillas within all groups, and across dry and wet seasons. Specifically, although adults always showed greater bacterial richness than infants and immature gorillas, network-wide analyses showed higher microbial community complexity and modularity in the infant gorilla gut. Sex-based microbiome differences were not evident among adults, being only detected among immature gorillas. CONCLUSIONS: The results presented point to a dynamic gut microbiome in Gorilla spp., associated with ontogeny and individual development. Of note, the gut microbiomes of breastfeeding infants seemed to reflect early exposure to complex, herbaceous vegetation. Whether increased compositional complexity of the infant gorilla gut microbiome is an adaptive response to an energy-limited diet and an underdeveloped gut needs to be further tested. Overall, age and sex based gut microbiome differences, as shown here, maybe mainly attributed to access to specific feeding sources, and social interactions between individuals within groups.

Mechanistic and structural insight into promiscuity based metabolism of cardiac drug digoxin by gut microbial enzyme.

The recent advances in microbiome studies have revealed the role of gut microbiota in altering the pharmacological properties of oral drugs, which contributes to patient-response variation and undesired effect of the drug molecule. These studies are essential to guide us for achieving the desired efficacy and pharmacological activity of the existing drug molecule or for discovering novel and more effective therapeutics. However, one of the main limitations is the lack of atomistic details on the binding and metabolism of these drug molecules by gut-microbial enzymes. Therefore, in this study, for a well-known and important FDA-approved cardiac glycoside drug, digoxin, we report the atomistic details and energy economics for its binding and metabolism by the Cgr2 protein of Eggerthella lenta DSM 2243. It was observed that the binding pocket of digoxin to Cgr2 primarily involved the negatively charged polar amino acids and a few non-polar hydrophobic residues. The drug digoxin was found to bind Cgr2 at the same binding site as that of fumarate, which is the proposed natural substrate. However, digoxin showed a much lower binding energy (17.75 ± 2 Kcal mol-1 ) than the binding energy (42.17 ± 2 Kcal mol-1 ) of fumarate. This study provides mechanistic insights into the structural and promiscuity-based metabolism of widely used cardiac drug digoxin and presents a methodology, which could be useful to confirm the promiscuity-based metabolism of other orally administrated drugs by gut microbial enzymes and also help in designing strategies for improving the efficacy of the drugs.

Prediction of anti-inflammatory proteins/peptides: an insilico approach.

BACKGROUND: The current therapy for inflammatory and autoimmune disorders involves the use of nonspecific anti-inflammatory drugs and other immunosuppressant, which are often accompanied with potential side effects. As an alternative therapy, anti-inflammatory peptides are recently being exploited as anti-inflammatory agents for treatment of various inflammatory diseases such as Alzheimer's disease and rheumatoid arthritis. Thus, understanding the correlation between amino acid sequence and its potential anti-inflammatory property is of great importance for the discovery of novel and efficient anti-inflammatory peptide-based therapeutics. METHODS: In this study, we have developed a prediction tool for the classification of peptides as anti-inflammatory epitopes or non anti-inflammatory epitopes. The training was performed using experimentally validated epitopes obtained from Immune epitope database and analysis resource database. Different sequence-based features and their hybrids with motif information were employed for development of support vector machine-based machine learning models. Similarly, machine learning models were also constructed using random forest. RESULTS: The composition and terminal residue conservation analysis of peptides revealed the dominance of leucine, serine, tyrosine and arginine residues in anti-inflammatory epitopes as compared to non anti-inflammatory epitopes. Similarly, the anti-inflammatory epitopes specific motifs were found to be rich in hydrophobic and polar residues. The hybrid of tripeptide composition-based support vector machine model and motif yielded the best performance on 10-fold cross validation with an accuracy of 78.1% and MCC of 0.58. The same displayed an accuracy of 72% and MCC of 0.45 on validation dataset, rejecting any possibility of over-fitting. The tripeptide composition-based random forest model displayed an accuracy of 0.8 and MCC of 0.59 on 10-fold cross validation, however, the accuracy (0.68) and MCC (0.31) was lower as compared to support vector machine model on validation dataset. Thus, the support vector machine model is implemented as the default model and an additional option of using the random forest model is provided. CONCLUSION: The prediction models along with tools for epitope mapping and similarity search have been provided as a web server which is freely accessible at http://metagenomics.iiserb.ac.in/antiinflam/ .

Prediction of peptidoglycan hydrolases- a new class of antibacterial proteins.

BACKGROUND: The efficacy of antibiotics against bacterial infections is decreasing due to the development of resistance in bacteria, and thus, there is a need to search for potential alternatives to antibiotics. In this scenario, peptidoglycan hydrolases can be used as alternate antibacterial agents due to their unique property of cleaving peptidoglycan cell wall present in both gram-positive and gram-negative bacteria. Along with a role in maintaining overall peptidoglycan turnover in a cell and in daughter cell separation, peptidoglycan hydrolases also play crucial role in bacterial pathophysiology requiring development of a computational tool for the identification and classification of novel peptidoglycan hydrolases from genomic and metagenomic data. RESULTS: In this study, the known peptidoglycan hydrolases were divided into multiple classes based on their site of action and were used for the development of a computational tool 'HyPe' for identification and classification of novel peptidoglycan hydrolases from genomic and metagenomic data. Various classification models were developed using amino acid and dipeptide composition features by training and optimization of Random Forest and Support Vector Machines. Random Forest multiclass model was selected for the development of HyPe tool as it showed up to 71.12 % sensitivity, 99.98 % specificity, 99.55 % accuracy and 0.80 MCC in four different classes of peptidoglycan hydrolases. The tool was validated on 24 independent genomic datasets and showed up to 100 % sensitivity and 0.94 MCC. The ability of HyPe to identify novel peptidoglycan hydrolases was also demonstrated on 24 metagenomic datasets. CONCLUSIONS: The present tool helps in the identification and classification of novel peptidoglycan hydrolases from complete genomic or metagenomic ORFs. To our knowledge, this is the only tool available for the prediction of peptidoglycan hydrolases from genomic and metagenomic data. AVAILABILITY: http://metagenomics.iiserb.ac.in/hype/ and http://metabiosys.iiserb.ac.in/hype/ .

ProInflam: a webserver for the prediction of proinflammatory antigenicity of peptides and proteins.

BACKGROUND: Proinflammatory immune response involves a complex series of molecular events leading to inflammatory reaction at a site, which enables host to combat plurality of infectious agents. It can be initiated by specific stimuli such as viral, bacterial, parasitic or allergenic antigens, or by non-specific stimuli such as LPS. On counter with such antigens, the complex interaction of antigen presenting cells, T cells and inflammatory mediators like IL1α, IL1ß, TNFα, IL12, IL18 and IL23 lead to proinflammatory immune response and further clearance of infection. In this study, we have tried to establish a relation between amino acid sequence of antigen and induction of proinflammatory response. RESULTS: A total of 729 experimentally-validated proinflammatory and 171 non-proinflammatory epitopes were obtained from IEDB database. The A, F, I, L and V amino acids and AF, FA, FF, PF, IV, IN dipeptides were observed as preferred residues in proinflammatory epitopes. Using the compositional and motif-based features of proinflammatory and non-proinflammatory epitopes, we have developed machine learning-based models for prediction of proinflammatory response of peptides. The hybrid of motifs and dipeptide-based features displayed best performance with MCC = 0.58 and an accuracy of 87.6 %. CONCLUSION: The amino acid sequence-based features of peptides were used to develop a machine learning-based prediction tool for the prediction of proinflammatory epitopes. This is a unique tool for the computational identification of proinflammatory peptide antigen/candidates and provides leads for experimental validations. The prediction model and tools for epitope mapping and similarity search are provided as a comprehensive web server which is freely available at http://metagenomics.iiserb.ac.in/proinflam/ and http://metabiosys.iiserb.ac.in/proinflam/ .

Woods: A fast and accurate functional annotator and classifier of genomic and metagenomic sequences.

Functional annotation of the gigantic metagenomic data is one of the major time-consuming and computationally demanding tasks, which is currently a bottleneck for the efficient analysis. The commonly used homology-based methods to functionally annotate and classify proteins are extremely slow. Therefore, to achieve faster and accurate functional annotation, we have developed an orthology-based functional classifier 'Woods' by using a combination of machine learning and similarity-based approaches. Woods displayed a precision of 98.79% on independent genomic dataset, 96.66% on simulated metagenomic dataset and >97% on two real metagenomic datasets. In addition, it performed >87 times faster than BLAST on the two real metagenomic datasets. Woods can be used as a highly efficient and accurate classifier with high-throughput capability which facilitates its usability on large metagenomic datasets.

Potentiometric sensing of ibuprofen over ferric oxide doped chitosan grafted polypyrrole-based electrode.

The present work demonstrates the correlation between structure, properties, and self-sensing protocols of in situ prepared ferric oxide doped grafted copolymer composite, comprised of ferric oxide, chitosan, and polypyrrole (α-Fe2O3-en-CHIT-g-PPy) for residual ibuprofen present in natural and artificial samples. The chemical structure, morphology, functionality, and physio-mechanical properties of the composite were determined by Fourier transform infrared spectrometer (FT-IR), Raman spectra, X-ray diffraction (XRD), Scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS), Two probe method, and standard ASTM techniques to explore sensing nature. The results confirm the evolution of axially aligned structure against 110 planes of α-Fe2O3 and chemically functionalized expanded polymer matrix during in-situ chemical polymerization of pyrrole, with better porosity, interactivity, and improved electrical conductivity i.e. 7.32 × 10-3 S cm-1. Further, a thin film of prepared composite coated on an ITO glass plate was explored for potentiometric sensing of ibuprofen (IBU) present in artificial and natural samples without the use of any additional energy sources. The observed sensing parameters are the sensing ranging 0.5 µM to 100.0 µM, sensitivity 2.5081 mV µM-1 cm-2, response time 50 s, recovery time 10 s, and stability for 60 days. The sensing mechanism of the IBU sensor and effective charge transfer in the electrode was also discussed based on changes in IR spectra of the electrode recorded before and after sensing due to surface oxidation of IBU due to the presence of iron and doping effect of iron oxide in the composite.

Revealing the interface chemistry of polyaniline grafted biomass via statistical modeling of multi-component dye systems: optimization, kinetics, thermodynamics, and adsorption mechanism.

The growing need to examine the adsorption capabilities of innovative materials in real-world water samples has encouraged a shift from single to multicomponent adsorption systems. In this study, a novel composite, PANI-g-SM was synthesized by covalently grafting a lignocellulosic biomass, Saccharum munja (SM) with polyaniline (PANI). The as-synthesized composite was investigated for the simultaneous adsorption of cationic (Methylene Blue (MB); Crystal Violet (CV)) and anionic dyes (Reactive Red 35 (RR); Fast Green FCF (FG)) from four single components and two binary systems, MB + RR and CV + FG. Further, the effect and interaction of pH (2-11), dosage (0.01-0.04 g/10 mL), and initial concentration (0.0313 to 0.1563 mmol/L) on the elimination of dyes by PANI-g-SM were studied through a novel design of Box-Behnken of Response Surface Methodology (RSM) technique which was found to be highly useful for revealing the chemistry of interfaces in multi-component systems. The extended Langmuir model for the binary system indicated the presence of synergism, as result the maximum monolayer adsorption capacity increased by 44.44%, 645.83%, 67.88%, and 441.07% for MB, RR, CV, and FG dye, respectively. Further, the adsorption process mainly followed a pseudo-second-order kinetic model, and the thermodynamic studies revealed the exothermic nature of adsorption for RR and FG dye while endothermic for MB and CV dye, respectively with Δ G varying from - 1.68 to - 6.12 kJ/mol indicating the spontaneity of the process. Importantly, the efficacy of the composite was evaluated for the treatment of textile industry effluent highlighting its potential as an adsorbent for wastewater treatment.

Diagnostic Approaches to Helicobacter pylori: A Comparative Study of Detection in Gastric Biopsy and Aspirates.

Background Helicobacter pylori is one of the most common bacterial pathogens in humans. It is a microaerophilic bacteria with multiple unipolar flagella. It is associated with the development of various lesions like chronic gastritis, gastric ulcers, adenocarcinoma, and mucosa-associated lymphomas. The aim of this study was a comparative evaluation of the rapid urease test (RUT) and polymerase chain reaction (PCR) in gastric biopsy and aspirates for the detection of H. pylori infection and to further determine the sensitivity and specificity of RUT and PCR. Method Endoscopic guided biopsy tissue and gastric aspirate specimens were collected from 110 patients with symptoms like gastritis, dyspepsia, etc., and subjected to RUT and PCR for detection of H. pylori infection. Results A total of 110 samples, including both biopsy tissue (77) and gastric aspirate (33) were subjected to RUT and PCR. RUT for biopsy tissue showed the highest sensitivity (97.18%), compared to gastric aspirate (78.94%). Comparing RUT with PCR, the sensitivity and specificity of PCR were 93.33% and 90.0%, respectively. The positive predictive value (PPV) of PCR was 97.67%, the negative predictive value (NPV) was 75.0%, and the accuracy was 92.73%. Conclusion The present study showed that RUT is a rapid and accurate invasive test for the detection of Helicobacter pylori infection in biopsy tissue as compared to gastric aspirate specimens, which are more sensitive to PCR. The study also showed that biopsy tissue was found to be a superior specimen for the detection of Helicobacter pylori as compared to gastric aspirate.

Influence of poly(n-isopropylacrylamide)-CNT-polyaniline three-dimensional electrospun microfabric scaffolds on cell growth and viability.

This study investigates the effect on: (1) the bulk surface and (2) the three-dimensional non-woven microfabric scaffolds of poly(N-isopropylacrylamide)-CNT-polyaniline on growth and viability of cells. The poly(N-isopropylacrylamide)-CNT-polyaniline was prepared using coupling chemistry and electrospinning was then used for the fabrication of responsive, non-woven microfabric scaffolds. The electrospun microfabrics were assembled in regular three-dimensional scaffolds with OD: 400-500 µm; L: 6-20 cm. Mice fibroblast cells L929 were seeded on the both poly(N-isopropylacrylamide)-CNT-polyaniline bulk surface as well as non-woven microfabric scaffolds. Excellent cell proliferation and viability was observed on poly(N-isopropylacrylamide)-CNT-polyaniline non-woven microfabric matrices in compare to poly(N-isopropylacrylamide)-CNT-polyaniline bulk and commercially available Matrigel™ even with a range of cell lines up to 168 h. Temperature dependent cells detachment behavior was observed on the poly(N-isopropylacrylamide)-CNT-polyaniline scaffolds by varying incubation at below lower critical solution temperature of poly(N-isopropylacrylamide). The results suggest that poly(N-isopropylacrylamide)-CNT-polyaniline non-woven microfabrics could be used as a smart matrices for applications in tissue engineering.

Decentralised systems - definition and drivers in the current context.

This paper explores the current context for decentralised approaches in the provision of urban water services. It examines the recent history of decentralised systems' implementation in Australia and identifies its drivers. The drivers included addressing capacity constraints of centralised systems, mitigating the environmental impact of urban development, and increasing the resilience of urban water systems to episodic droughts and the projected impacts of climate change. The concepts of integrated urban water management and water sensitive urban design were prevalent in many of the innovative approaches used for the provision of decentralised urban water services. However, there remains a degree of confusion among water professionals in the terminology adopted for on-site and decentralised systems. Based on a literature review, consultation with water industry professionals and examination of decentralised urban developments in Australia, this paper has developed a generalised definition of decentralised systems for adoption across the water sector. The definition encompasses the various development scales in which decentralised systems are implemented, and reflects the new functions and characteristics inherent to those systems.

Intravascular Papillary Endothelial Hyperplasia Involving the Hand: A Case Report of a Rare Entity.

Masson's tumor, also named intravascular papillary endothelial hyperplasia (IPEH), is a rare, benign vascular tumor. Evaluation by clinical features can be confused with other soft tissue tumors. Therefore, the diagnosis should be confirmed by histopathological examination. The patient reported here is 67 years old and came to us with a small painful lesion over the left thumb of about two months duration. Histopathological examination was consistent with Masson's tumor (IPEH) following excisional biopsy, with good functional outcomes. To the best of our knowledge, this is the first report of this entity from Kuwait. Dermatologists and surgeons should know about this rare entity and its unusual presentation, to be able to distinguish it from similar presenting serious conditions, especially angiosarcoma. Through this report, we purport to facilitate recognition of this condition apart from some other conditions it may mimic.

A comprehensive review on the metal-based green valorized nanocomposite for the remediation of emerging colored organic waste.

In today's era, "green" synthesis is an emerging research trend. It has gained widespread attention owing to its dynamic behavior, reliability, simplicity, sustainability, and environment friendly approach for fabricating various nanomaterials. Green fabrication of metal/metal oxides nanomaterials, hybrid materials, and other metal-based nanocomposite can be utilized to remove toxic colored aqueous pollutants. Nanomaterials synthesized by using green approach is considered to be the significant tool to minimize unwanted or harmful by-products otherwise released from traditional synthesis methods. Various kinds of biosynthesized nanomaterials, such as animal waste and plant-based, have been successfully applied and well documented in the literature. However, their application part, especially for the cure of colored organic polluted water, has not been reported as a single review article. Therefore, the current work aims to assemble reports on using novel biosynthesized green metal-based nanomaterials to exclude harmful dyes from polluted water.

Estimation of SARS-CoV-2 IgG Antibodies in Healthcare Worker-Administered Covishield and Covaxin Vaccines at a Tertiary Care Hospital in Jharkhand, India.

Introduction To mitigate the impact of the COVID-19 pandemic caused by the SARS-CoV-2 virus, global distribution of vaccines such as Covishield and Covaxin has been undertaken. This research aimed to assess the responses and potential differences between these vaccines by examining the presence and levels of SARS-CoV-2 IgG antibodies in healthcare professionals who received them. Methodology A comprehensive cross-sectional study was conducted at a tertiary care facility in Ranchi involving 227 healthcare professionals who had completed both doses of either Covishield or Covaxin. Blood samples were collected and subjected to chemiluminescence immunoassay analysis to measure IgG antibodies. Demographic data, immunization records, and previous COVID-19 infections were recorded. Statistical analyses, including analysis of variance (ANOVA), linear regression, and independent sample t-tests were performed. Results Antibody titers exhibited variability, potentially influenced by factors. There was no difference in antibody titers between recipients of Covishield and Covaxin vaccines. Linear regression analysis revealed a correlation between antibody levels and the number of days after vaccination. Factors such as age, gender, blood group, and prior COVID-19 infections did not significantly impact antibody titers. Conclusions This study contributes to responses elicited by Covishield and Covaxin vaccines among healthcare workers. The results highlight that Covishield showed a higher mean titer value than Covaxin, which is not statistically significant. The overall model showed statistically significant results indicating age, type of vaccine, number of days after vaccination, blood group, and previous history of COVID-19 infection collectively influenced the CoV-2 IgG titer values. The findings indicate that age, number of days after vaccination, and prior history of COVID-19 infection have substantial relationships with the CoV-2 IgG titer, but sex, vaccine type, and blood group show lesser, nonsignificant associations.

The role of intestine in metabolic dysregulation in murine Wilson disease.

Background and aims: Major clinical manifestations of Wilson disease (WD) are related to copper accumulation in the liver and the brain, and little is known about other tissues involvement in metabolic changes in WD. In vitro studies suggested that the loss of intestinal ATP7B could contribute to metabolic dysregulation in WD. We tested this hypothesis by evaluating gut microbiota and lipidome in two mouse models of WD and by characterizing a new mouse model with a targeted deletion of Atp7b in intestine. Methods: Cecal content 16S sequencing and untargeted hepatic and plasma lipidome analyses in the Jackson Laboratory toxic-milk and the Atp7b null global knockout mouse models of WD were profiled and integrated. Intestine-specific Atp7b knockout mice ( Atp7b ΔIEC ) was generated using B6.Cg-Tg(Vil1-cre)997Gum/J mice and Atp7b Lox/Lox mice, and characterized using targeted lipidome analysis following a high-fat diet challenge. Results: Gut microbiota diversity was reduced in animal models of WD. Comparative prediction analysis revealed amino acid, carbohydrate, and lipid metabolism functions to be dysregulated in the WD gut microbial metagenome. Liver and plasma lipidomic profiles showed dysregulated tri- and diglyceride, phospholipid, and sphingolipid metabolism in WD models. When challenged with a high-fat diet, Atp7b ΔIEC mice exhibited profound alterations to fatty acid desaturation and sphingolipid metabolism pathways as well as altered APOB48 distribution in intestinal epithelial cells. Conclusion: Coordinated changes of gut microbiome and lipidome analyses underlie systemic metabolic manifestations in murine WD. Intestine-specific ATP7B deficiency affected both intestinal and systemic response to a high-fat challenge. WD is a systemic disease in which intestinal-specific ATP7B loss and diet influence phenotypic presentations.

The role of intestine in metabolic dysregulation in murine Wilson disease.

BACKGROUND: The clinical manifestations of Wilson disease (WD) are related to copper accumulation in the liver and the brain, but little is known about other tissue involvement regarding metabolic changes in WD. In vitro studies suggested that the loss of intestinal ATP7B affects metabolic dysregulation in WD. We tested this hypothesis by evaluating the gut microbiota and lipidome in 2 mouse models of WD and by characterizing a new mouse model with a targeted deletion of Atp7b in the intestine. METHODS: Cecal content 16S sequencing and untargeted hepatic and plasma lipidome analyses in the Jackson Laboratory toxic-milk and the Atp7b null global knockout mouse models of WD were profiled and integrated. Intestine-specific Atp7b knockout mice (Atp7bΔIEC) were generated and characterized using targeted lipidome analysis following a high-fat diet challenge. RESULTS: Gut microbiota diversity was reduced in animal models of WD. Comparative prediction analysis revealed amino acid, carbohydrate, and lipid metabolism functions to be dysregulated in the WD gut microbial metagenome. Liver and plasma lipidomic profiles showed dysregulated triglyceride and diglyceride, phospholipid, and sphingolipid metabolism in WD models. However, Atp7bΔIEC mice did not show gut microbiome differences compared to wild type. When challenged with a high-fat diet, Atp7bΔIEC mice exhibited profound alterations to fatty acid desaturation and sphingolipid metabolism pathways as well as altered APOB48 distribution in intestinal epithelial cells. CONCLUSIONS: Gut microbiome and lipidome underlie systemic metabolic manifestations in murine WD. Intestine-specific ATP7B deficiency affected both intestinal and systemic response to a high-fat challenge but not the microbiome profile, at least at early stages. WD is a systemic disease in which intestinal-specific ATP7B loss and diet influence the phenotype and the lipidome profile.