Gut Microbial Perturbation and Host Response Induce Redox Pathway Upregulation along the Gut-Liver Axis during Giardiasis in C57BL/6J Mouse Model.

Apicomplexan infections, such as giardiasis and cryptosporidiosis, negatively impact a considerable proportion of human and commercial livestock populations. Despite this, the molecular mechanisms of disease, particularly the effect on the body beyond the gastrointestinal tract, are still poorly understood. To highlight host-parasite-microbiome biochemical interactions, we utilised integrated metabolomics-16S rRNA genomics and metabolomics-proteomics approaches in a C57BL/6J mouse model of giardiasis and compared these to Cryptosporidium and uropathogenic Escherichia coli (UPEC) infections. Comprehensive samples (faeces, blood, liver, and luminal contents from duodenum, jejunum, ileum, caecum and colon) were collected 10 days post infection and subjected to proteome and metabolome analysis by liquid and gas chromatography-mass spectrometry, respectively. Microbial populations in faeces and luminal washes were examined using 16S rRNA metagenomics. Proteome-metabolome analyses indicated that 12 and 16 key pathways were significantly altered in the gut and liver, respectively, during giardiasis with respect to other infections. Energy pathways including glycolysis and supporting pathways of glyoxylate and dicarboxylate metabolism, and the redox pathway of glutathione metabolism, were upregulated in small intestinal luminal contents and the liver during giardiasis. Metabolomics-16S rRNA genetics integration indicated that populations of three bacterial families-Autopobiaceae (Up), Desulfovibrionaceae (Up), and Akkermanasiaceae (Down)-were most significantly affected across the gut during giardiasis, causing upregulated glycolysis and short-chained fatty acid (SCFA) metabolism. In particular, the perturbed Akkermanasiaceae population seemed to cause oxidative stress responses along the gut-liver axis. Overall, the systems biology approach applied in this study highlighted that the effects of host-parasite-microbiome biochemical interactions extended beyond the gut ecosystem to the gut-liver axis. These findings form the first steps in a comprehensive comparison to ascertain the major molecular and biochemical contributors of host-parasite interactions and contribute towards the development of biomarker discovery and precision health solutions for apicomplexan infections.

Utilising lipid and, arginine and proline metabolism in blood plasma to differentiate the biochemical expression in functional dyspepsia (FD) and irritable bowel syndrome (IBS).

Functional gastrointestinal disorders (FGID) such as functional dyspepsia (FD) and irritable bowel syndrome (IBS) are highly prevalent and debilitating attributed to altered gut function and gut-brain interactions. FGID can be reliably diagnosed based upon the symptom pattern; but in the clinical setting FD or IBS a frequent diagnoses of exclusion after relevant structural causes of symptoms have been ruled out by appropriate testing. Thus far, there is no established biomarker for FGIDs. To address this limitation, we utilised multi-omics and chemometrics integration to characterise the blood plasma biochemistry in patients with IBS, FD, an overlap of FD/IBS, and controls using liquid chromatography-mass spectrometry (LC-MS) techniques.Cholesterol metabolism products Cholest-5,24-dien-3ß-ol, 3-O-ß-D-glucopyranoside, energy pathway metabolites, immunoglobulin-γ2 and immunoglobulin-κ, and carbonic anhydrase-1 proteins were particularly elevated in IBS. Furthermore, arginine and proline metabolisms, thyroid hormone synthesis, ferroptosis and, complementary and coagulation cascades were particularly upregulated in patients with IBS. Cer(d18:1/26:1(17Z)) and PI(14:0/22:1(11Z)) lipids were elevated in FD and FD-IBS but were depleted in IBS. Markers of central carbon metabolism and lipidome profiles allowed better discrimination and model predictability than metaproteome profile in healthy and FGID conditions.Overall, the multi-omics integration allowed the discrimination of healthy controls and FGID patients. It also effectively differentiated the biochemistry of FGID subtypes including FD, IBS and FD-IBS co-occurrence. This study points towards the possibility of multi-omics integration for rapid and high throughput analysis of plasma samples to support clinicians screen and diagnose patients with suspected FGIDs.

Synbiotic supplementation with prebiotic green banana resistant starch and probiotic Bacillus coagulans spores ameliorates gut inflammation in mouse model of inflammatory bowel diseases.

PURPOSE: The research goal is to develop dietary strategies to help address the growing incidence of inflammatory bowel diseases (IBD). This study has investigated the effectiveness of green banana resistant starch (GBRS) and probiotic Bacillus coagulans MTCC5856 spores for the amelioration of dextran-sulfate sodium (DSS)-induced colitis in mice. METHODS: Eight-week-old C57BL/6 mice were fed standard rodent chow diet supplemented with either B. coagulans, GBRS or its synbiotic combination. After 7 days supplementation, colitis was induced by adding 2% DSS in drinking water for 7 days while continuing the supplemented diets. Animal health was monitored and after 14 days all animals were sacrificed to measure the biochemical and histochemical changes associated with each supplement type. RESULTS: The disease activity index and histological damage score for DSS-control mice (6.1, 17.1, respectively) were significantly higher (p < 0.0001) than the healthy mice. Synbiotic supplementation alleviated these markers (- 67%, - 94% respectively) more adequately than B. coagulans (- 52%, - 58% respectively) or GBRS (- 57%, - 26%, respectively) alone. Compared to DSS-control synbiotic supplementation significantly (p < 0.0001) maintained expressions of tight junction proteins. Moreover, synbiotic effects accounted for ~ 40% suppression of IL-1ß and ~ 29% increase in IL-10 levels in serum while also reducing C-reactive protein (- 37%) compared to that of the DSS-control. While, B. coagulans alone could not induce additional levels of short-chain fatty acid (SCFA) production beyond the caecum, the synbiotic combination with GBRS resulted in substantial increased SCFA levels across the whole length of the colon. CONCLUSION: The synbiotic supplementation with B. coagulans and GBRS ameliorated the overall inflammatory status of the experimental IBD model via synergistic functioning. This supports researching its application in mitigating inflammation in human IBD.

Untargeted metabolomics analysis of the upper respiratory tract of ferrets following influenza A virus infection and oseltamivir treatment.

INTRODUCTION: Influenza is a highly contagious respiratory disease that causes high global morbidity and mortality each year. The dynamics of an influenza infection on the host metabolism, and how metabolism is altered in response to neuraminidase inhibitor drug therapy, is still in its infancy but of great importance. OBJECTIVES: We aim to investigate the suitability of ferret nasal wash samples for metabolomics-based analysis and characterization of influenza infections and oseltamivir treatment. METHODS: Virological and metabolic analyses were performed on nasal wash samples collected from ferrets treated with oseltamivir or a placebo. Untargeted metabolomics was performed using a gas chromatography coupled with mass spectrometery (GC-MS) based protocol that comprised a retention time (RT) locked method and the use of a commercial metabolomics library. RESULTS: Ferret activity was reduced at 2-3 days post infection, which coincided with the highest influenza viral titre. The metabolomics data indicated a shift in metabolism during various stages of infection. The neuraminidase inhibitor oseltamivir created considerable downregulation of energy center metabolites (glucose, sucrose, glycine and glutamine), which generated high levels of branched amino acids. This further increased branched amino acid degradation and deregulation via glycerate-type intermediates and biosynthesis of fatty acids in oseltamivir-treated animals where abrogated weight loss was observed. CONCLUSION: Metabolomics was used to profile influenza infection and antiviral drug treatment in ferrets. This has the potential to provide indicators for the early diagnosis of influenza infection and assess the effectiveness of drug therapies.

Winery biomass waste degradation by sequential sonication and mixed fungal enzyme treatments.

To increase the efficiency of winery-derived biomass biodegradation, grape pomace was ultrasonicated for 20min in the presence of 0.25M, 0.5Mand1.0MKOH and 1.0MNaOH. This was followed by treatment with a 1:1 (v/v) mix of crude enzyme preparation derived from Phanerochaete chrysosporium and Trametes versicolor for 18h and a further 18h treatment with a 60:14:4:2 percent ratio combination of enzymes derived from Aspergillus niger: Penicillium chrysogenum: Trichoderma harzianum: P. citrinum, repsectively. Process efficiency was evaluated by its comparison to biological only mixed fungal degradation over 16days. Ultrasonication treatment with 0.5MKOH followed by mixed enzyme treatment yielded the highest lignin degradation of about 13%. Cellulase, ß-glucosidase, xylanase, laccase and lignin peroxidase activities of 77.9, 476, 5,390.5, 66.7 and 29,230.7U/mL, respectively, were observed during biomass degradation. Gas chromatography-mass spectrometry (GC-MS) analysis of the degraded material identified commercially important compounds such as gallic acid, lithocholic acid, glycolic acid and lactic acid which were generated in considerable quantities. Thus, the combination of sonication pre-treatment and enzymatic degradation has the potential to considerably improve the breakdown of agricultural biomass and produce commercially useful compounds in markedly less time (<40h) with respect to biological only degradation (16days).

Chemometric Analysis of Lavender Essential Oils Using Targeted and Untargeted GC-MS Acquired Data for the Rapid Identification and Characterization of Oil Quality.

Standard raw material test methods such as the ISO Standard 11024 are focused on the identification of lavender oil and not the actual class/quality of the oil. However, the quality of the oil has a significant effect on its price at market. As such, there is a need for raw material tests to identify not only the type of oil but its quality. This paper describes two approaches to rapidly identifying and classifying lavender oil. First, the ISO Standard 11024 test method was evaluated in order to determine its suitability to assess lavender oil quality but due to its targeted and simplistic approach, it has the potential to miss classify oil quality. Second, utilizing the data generated by the ISO Standard 11024 test methodology, an untargeted chemometric predicative model was developed in order to rapidly assess and characterize lavender oils (Lavandulaangustifolia L.) for geographical/environmental adulteration that impact quality. Of the 170 compounds identified as per the ISO Standard 11024 test method utilizing GC-MS analyses, 15 unique compounds that greatly differentiate between the two classes of lavender were identified. Using these 15 compounds, a predicative multivariate chemometric model was developed that enabled lavender oil samples to be reliably differentiated based on quality. A misclassification analysis was performed and it was found that the predictions were sound (100% matching rate). Such an approach will enable producers, distributers, suppliers and manufactures to rapidly screen lavender essential oil. The authors concede that the validation and implementation of such an approach is more difficult than a conventional chromatographic assay. However, the rapid, reliable and less problematic screening is vastly superior and easily justifies any early implementation validation difficulties and costs.

A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research.

The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.

Intelligent Biological Networks: Improving Anti-Microbial Resistance Resilience through Nutritional Interventions to Understand Protozoal Gut Infections.

Enteric protozoan pathogenic infections significantly contribute to the global burden of gastrointestinal illnesses. Their occurrence is considerable within remote and indigenous communities and regions due to reduced access to clean water and adequate sanitation. The robustness of these pathogens leads to a requirement of harsh treatment methods, such as medicinal drugs or antibiotics. However, in addition to protozoal infection itself, these treatments impact the gut microbiome and create dysbiosis. This often leads to opportunistic pathogen invasion, anti-microbial resistance, or functional gastrointestinal disorders, such as irritable bowel syndrome. Moreover, these impacts do not remain confined to the gut and are reflected across the gut-brain, gut-liver, and gut-lung axes, among others. Therefore, apart from medicinal treatment, nutritional supplementation is also a key aspect of providing recovery from this dysbiosis. Future proteins, prebiotics, probiotics, synbiotics, and food formulations offer a good solution to remedy this dysbiosis. Furthermore, nutritional supplementation also helps to build resilience against opportunistic pathogens and potential future infections and disorders that may arise due to the dysbiosis. Systems biology techniques have shown to be highly effective tools to understand the biochemistry of these processes. Systems biology techniques characterize the fundamental host-pathogen interaction biochemical pathways at various infection and recovery stages. This same mechanism also allows the impact of the abovementioned treatment methods of gut microbiome remediation to be tracked. This manuscript discusses system biology approaches, analytical techniques, and interaction and association networks, to understand (1) infection mechanisms and current global status; (2) cross-organ impacts of dysbiosis, particularly within the gut-liver and gut-lung axes; and (3) nutritional interventions. This study highlights the impact of anti-microbial resistance and multi-drug resistance from the perspective of protozoal infections. It also highlights the role of nutritional interventions to add resilience against the chronic problems caused by these phenomena.

Unravelling the gut-lung axis: insights into microbiome interactions and Traditional Indian Medicine's perspective on optimal health.

The microbiome of the human gut is a complex assemblage of microorganisms that are in a symbiotic relationship with one another and profoundly influence every aspect of human health. According to converging evidence, the human gut is a nodal point for the physiological performance matrixes of the vital organs on several axes (i.e. gut-brain, gut-lung, etc). As a result of COVID-19, the importance of gut-lung dysbiosis (balance or imbalance) has been realised. In view of this, it is of utmost importance to develop a comprehensive understanding of the microbiome, as well as its dysbiosis. In this review, we provide an overview of the gut-lung axial microbiome and its importance in maintaining optimal health. Human populations have successfully adapted to geophysical conditions through traditional dietary practices from around the world. In this context, a section has been devoted to the traditional Indian system of medicine and its theories and practices regarding the maintenance of optimally customized gut health.

A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients.

BACKGROUND: Despite aggressive treatment, more than 90% of glioblastoma (GBM) patients experience recurrences. GBM response to therapy is currently assessed by imaging techniques and tissue biopsy. However, difficulties with these methods may cause misinterpretation of treatment outcomes. Currently, no validated therapy response biomarkers are available for monitoring GBM progression. Metabolomics holds potential as a complementary tool to improve the interpretation of therapy responses to help in clinical interventions for GBM patients. METHODS: Saliva and blood from GBM patients were collected pre and postoperatively. Patients were stratified conforming their progression-free survival (PFS) into favourable or unfavourable clinical outcomes (>9 months or PFS ≤ 9 months, respectively). Analysis of saliva (whole-mouth and oral rinse) and plasma samples was conducted utilising LC-QqQ-MS and LC-QTOF-MS to determine the metabolomic and lipidomic profiles. The data were investigated using univariate and multivariate statistical analyses and graphical LASSO-based graphic network analyses. RESULTS: Altogether, 151 metabolites and 197 lipids were detected within all saliva and plasma samples. Among the patients with unfavourable outcomes, metabolites such as cyclic-AMP, 3-hydroxy-kynurenine, dihydroorotate, UDP and cis-aconitate were elevated, compared to patients with favourable outcomes during pre-and post-surgery. These metabolites showed to impact the pentose phosphate and Warburg effect pathways. The lipid profile of patients who experienced unfavourable outcomes revealed a higher heterogeneity in the abundance of lipids and fewer associations between markers in contrast to the favourable outcome group. CONCLUSION: Our findings indicate that changes in salivary and plasma metabolites in GBM patients can potentially be employed as less invasive prognostic biomarkers/biomarker panel but validation with larger cohorts is required.

Multi-omics analysis of hospital-acquired diarrhoeal patients reveals biomarkers of enterococcal proliferation and Clostridioides difficile infection.

Hospital-acquired diarrhoea (HAD) is common, and often associated with gut microbiota and metabolome dysbiosis following antibiotic administration. Clostridioides difficile is the most significant antibiotic-associated diarrhoeal (AAD) pathogen, but less is known about the microbiota and metabolome associated with AAD and C. difficile infection (CDI) with contrasting antibiotic treatment. We characterised faecal microbiota and metabolome for 169 HAD patients (33 with CDI and 133 non-CDI) to determine dysbiosis biomarkers and gain insights into metabolic strategies C. difficile might use for gut colonisation. The specimen microbial community was analysed using 16 S rRNA gene amplicon sequencing, coupled with untargeted metabolite profiling using gas chromatography-mass spectrometry (GC-MS), and short-chain fatty acid (SCFA) profiling using GC-MS. AAD and CDI patients were associated with a spectrum of dysbiosis reflecting non-antibiotic, short-term, and extended-antibiotic treatment. Notably, extended antibiotic treatment was associated with enterococcal proliferation (mostly vancomycin-resistant Enterococcus faecium) coupled with putative biomarkers of enterococcal tyrosine decarboxylation. We also uncovered unrecognised metabolome dynamics associated with concomitant enterococcal proliferation and CDI, including biomarkers of Stickland fermentation and amino acid competition that could distinguish CDI from non-CDI patients. Here we show, candidate metabolic biomarkers for diagnostic development with possible implications for CDI and vancomycin-resistant enterococci (VRE) treatment.

Is there any biological insight (or respite) for insects exposed to plastics? Measuring the impact on an insects central carbon metabolism when exposed to a plastic feed substrate.

Insects used to treat organic waste streams and produce valuable protein products are increasingly exposed to plastic contaminated source material assimilating plastic carbon into organic biomass, which is pervasive and hazardous to organisms. Our understanding of this increased insect-plastic interaction remains limited and needs urgent scientific attention if plastic biodegradation and production rates of quality protein are to be improved. Herein, we investigated the biochemical impact of various plastics using three insect models. Black Soldier Fly (BSF), Mealworm (MW), and Wax Moth (WM) larva were each exposed to a plastic substrate (PET, PE, PS, Expanded PE, PP, and PLA) as the primary carbon source for five days to explore any positive metabolic benefits in terms of insect performance and plastic degradation potential. Central carbon metabolism (CCM) metabolites were analyzed via a targeted tMRM liquid chromatography triple quadrupole mass spectrometry (LC-QqQ-MS) method. Unique expressed pathways were observed for each insect model. When reared on PET, BSF larvae were found to have an elevated pyrimidine metabolism, while the purine metabolism pathway was strongly expressed on other plastics. BSF also exhibited a downregulated Vitamin B6 metabolism across all plastics, indicating a likely gut-symbiont breakdown. The MW and WM model insects were metabolically more active on PLA and expanded foam plastics. Further, WM exhibited an elevation in Vitamin B6 metabolism. This data suggests a positive insect-specific interaction towards certain plastic types that warrants further investigation. It is anticipated that through deeper insight into the metabolic impact and benefits afforded from certain plastics, an insect biotransformation pipeline can be established that links fit-for-purpose insect models to individual plastic types that address our growing plastic waste issue.

A Time-Series Metabolomic Analysis of SARS-CoV-2 Infection in a Ferret Model.

The global threat of COVID-19 has led to an increased use of metabolomics to study SARS-CoV-2 infections in animals and humans. In spite of these efforts, however, understanding the metabolome of SARS-CoV-2 during an infection remains difficult and incomplete. In this study, metabolic responses to a SAS-CoV-2 challenge experiment were studied in nasal washes collected from an asymptomatic ferret model (n = 20) at different time points before and after infection using an LC-MS-based metabolomics approach. A multivariate analysis of the nasal wash metabolome data revealed several statistically significant features. Despite no effects of sex or interaction between sex and time on the time course of SARS-CoV-2 infection, 16 metabolites were significantly different at all time points post-infection. Among these altered metabolites, the relative abundance of taurine was elevated post-infection, which could be an indication of hepatotoxicity, while the accumulation of sialic acids could indicate SARS-CoV-2 invasion. Enrichment analysis identified several pathways influenced by SARS-CoV-2 infection. Of these, sugar, glycan, and amino acid metabolisms were the key altered pathways in the upper respiratory channel during infection. These findings provide some new insights into the progression of SARS-CoV-2 infection in ferrets at the metabolic level, which could be useful for the development of early clinical diagnosis tools and new or repurposed drug therapies.

Multi-Omics, an Integrated Approach to Identify Novel Blood Biomarkers of Alzheimer's Disease.

The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD/MCI pathogenesis is unclear. This study compared the metabolomic and proteomic signature of plasma from cognitively normal (CN) and dementia patients diagnosed with MCI or AD, to identify specific cellular pathways and new biomarkers altered with the progression of the disease. We analysed 80 plasma samples from individuals with MCI or AD, as well as age- and gender-matched CN individuals, by utilising mass spectrometry methods and data analyses that included combined pathway analysis and model predictions. Several proteins clearly identified AD from the MCI and CN groups and included plasma actins, mannan-binding lectin serine protease 1, serum amyloid A2, fibronectin and extracellular matrix protein 1 and Keratin 9. The integrated pathway analysis showed various metabolic pathways were affected in AD, such as the arginine, alanine, aspartate, glutamate and pyruvate metabolism pathways. Therefore, our multi-omics approach identified novel plasma biomarkers for the MCI and AD groups, identified changes in metabolic processes, and may form the basis of a biomarker panel for stratifying dementia participants in future clinical trials.

Utilizing the Food-Pathogen Metabolome to Putatively Identify Biomarkers for the Detection of Shiga Toxin-Producing E. coli (STEC) from Spinach.

Shiga toxigenic E. coli (STEC) are an important cause of foodborne disease globally with many outbreaks linked to the consumption of contaminated foods such as leafy greens. Existing methods for STEC detection and isolation are time-consuming. Rapid methods may assist in preventing contaminated products from reaching consumers. This proof-of-concept study aimed to determine if a metabolomics approach could be used to detect STEC contamination in spinach. Using untargeted metabolic profiling, the bacterial pellets and supernatants arising from bacterial and inoculated spinach enrichments were investigated for the presence of unique metabolites that enabled categorization of three E. coli risk groups. A total of 109 and 471 metabolite features were identified in bacterial and inoculated spinach enrichments, respectively. Supervised OPLS-DA analysis demonstrated clear discrimination between bacterial enrichments containing different risk groups. Further analysis of the spinach enrichments determined that pathogen risk groups 1 and 2 could be easily discriminated from the other groups, though some clustering of risk groups 1 and 2 was observed, likely representing their genomic similarity. Biomarker discovery identified metabolites that were significantly associated with risk groups and may be appropriate targets for potential biosensor development. This study has confirmed that metabolomics can be used to identify the presence of pathogenic E. coli likely to be implicated in human disease.

Chemoradiation therapy changes oral microbiome and metabolomic profiles in patients with oral cavity cancer and oropharyngeal cancer.

BACKGROUND: Patients with oral cavity cancer (OCC) and oropharyngeal cancer (OPC) are often seen with locoregionally advanced disease requiring complex multimodality treatments. These treatments may have detrimental effects on the oral microbiome, which is critical to maintaining physiological balance and health. METHODS: The effects of different OCC and OPC treatment types on the oral microbiome and metabolomic profiles for 24-month post-treatment in patients with OCC and OPC were investigated using 16S rRNA gene amplicon next-generation sequencing and gas chromatography-mass spectrometry (GC-MS), respectively. RESULTS: Chemoradiation resulted in oral dysbiosis with specific depletion of genera which regulate the enterosalivary nitrate-nitrite-nitric oxide pathway. These data also correlate with the oral metabolomic profiles with nitric oxide-related precursor, modulator, or catalyst significantly downregulated in saliva samples from patients' postchemoradiation. CONCLUSIONS: Together, we have shown that oral dysbiosis due to the effects of chemoradiation could potentially have an impact on OCC and OPC patient's quality of life post-treatment.

A multi-platform metabolomics approach to identify possible biomarkers for human faecal contamination in Greenshell™ mussels (Perna canaliculus).

Bivalve molluscs have the potential to bioaccumulate microbial pathogens including noroviruses from aquatic environments and as such, there is a need for a rapid and cheap in-situ method for their detection. Here, we characterise the tissue-specific response of New Zealand Greenshell™ mussels (Perna canaliculus) to faecal contamination from two different sources (municipal sewage and human faeces). This is done with the view to identify potential biomarkers that could be further developed into low cost, rapid and sensitive in-situ biosensors for human faecal contamination detection of mussels in growing areas. Tissue-specific metabolic profiles from gills, haemolymph and digestive glands were analysed using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). Clear differentiation of metabolic profiles was observed among treatments in each tissue type. Overall, energy pathways such as glycolysis, citrate cycle and oxidative phosphorylation were downregulated across the three mussel tissues studied following simulated contamination events. Conversely, considerable sterol upregulation in the gills was observed after exposure to contamination. Additionally, free pools of nucleotide phosphates and the antioxidant glutathione declined considerably post-exposure to contamination in gills. These results provide important insights into the tissue-specific metabolic effects of human faecal contamination in mussels. This study demonstrates the utility of metabolomics as a tool for identifying potential biomarkers in mussels.

Metabolic Profiling from an Asymptomatic Ferret Model of SARS-CoV-2 Infection.

Coronavirus disease (COVID-19) is a contagious respiratory disease that is causing significant global morbidity and mortality. Understanding the impact of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infection on the host metabolism is still in its infancy but of great importance. Herein, we investigated the metabolic response during viral shedding and post-shedding in an asymptomatic SARS-CoV-2 ferret model (n = 6) challenged with two SARS-CoV-2 isolates. Virological and metabolic analyses were performed on (minimally invasive) collected oral swabs, rectal swabs, and nasal washes. Fragments of SARS-CoV-2 RNA were only found in the nasal wash samples in four of the six ferrets, and in the samples collected 3 to 9 days post-infection (referred to as viral shedding). Central carbon metabolism metabolites were analyzed during viral shedding and post-shedding periods using a dynamic Multiple Reaction Monitoring (dMRM) database and method. Subsequent untargeted metabolomics and lipidomics of the same samples were performed using a Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry (LC-QToF-MS) methodology, building upon the identified differentiated central carbon metabolism metabolites. Multivariate analysis of the acquired data identified 29 significant metabolites and three lipids that were subjected to pathway enrichment and impact analysis. The presence of viral shedding coincided with the challenge dose administered and significant changes in the citric acid cycle, purine metabolism, and pentose phosphate pathways, amongst others, in the host nasal wash samples. An elevated immune response in the host was also observed between the two isolates studied. These results support other metabolomic-based findings in clinical observational studies and indicate the utility of metabolomics applied to ferrets for further COVID-19 research that advances early diagnosis of asymptomatic and mild clinical COVID-19 infections, in addition to assessing the effectiveness of new or repurposed drug therapies.

Functional analysis of pristine estuarine marine sediments.

Traditional environmental monitoring techniques are well suited to resolving acute exposure effects but lack resolution in determining subtle shifts in ecosystem functions resulting from chronic exposure(s). Surveillance with sensitive omics-based technologies could bridge this gap but, to date, most omics-based environmental studies have focused on previously degraded environments, identifying key metabolic differences resulting from anthropogenic perturbations. Here, we apply omics-based approaches to pristine environments to establish blueprints of microbial functionality within healthy estuarine sediment communities. We collected surface sediments (n = 50) from four pristine estuaries along the Western Cape York Peninsula of Far North Queensland, Australia. Sediment microbiomes were analyzed for 16S rRNA amplicon sequences, central carbon metabolism metabolites and associated secondary metabolites via targeted and untargeted metabolic profiling methods. Multivariate statistical analyses indicated heterogeneity among all the sampled estuaries, however, taxa-function relationships could be established that predicted community metabolism potential. Twenty-four correlated gene-metabolite pathways were identified and used to establish sediment microbial blueprints of essential carbon metabolism and amino acid biosynthesis that were positively correlated with community metabolic function outputs (2-oxisocapraote, tryptophan, histidine citrulline and succinic acid). In addition, an increase in the 125 KEGG genes related to metal homeostasis and metal resistance was observed, although, none of the detected metabolites related to these specific genes upon integration. However, there was a correlation between metal abundance and functional genes related to Fe and Zn metabolism. Our results establish a baseline microbial blueprint for the pristine sediment microbiome, one that drives important ecosystem services and to which future ecosurveillance monitoring can be compared.

Cryptosporidiosis Modulates the Gut Microbiome and Metabolism in a Murine Infection Model.

Cryptosporidiosis is a major human health concern globally. Despite well-established methods, misdiagnosis remains common. Our understanding of the cryptosporidiosis biochemical mechanism remains limited, compounding the difficulty of clinical diagnosis. Here, we used a systems biology approach to investigate the underlying biochemical interactions in C57BL/6J mice infected with Cryptosporidium parvum. Faecal samples were collected daily following infection. Blood, liver tissues and luminal contents were collected 10 days post infection. High-resolution liquid chromatography and low-resolution gas chromatography coupled with mass spectrometry were used to analyse the proteomes and metabolomes of these samples. Faeces and luminal contents were additionally subjected to 16S rRNA gene sequencing. Univariate and multivariate statistical analysis of the acquired data illustrated altered host and microbial energy pathways during infection. Glycolysis/citrate cycle metabolites were depleted, while short-chain fatty acids and D-amino acids accumulated. An increased abundance of bacteria associated with a stressed gut environment was seen. Host proteins involved in energy pathways and Lactobacillus glyceraldehyde-3-phosphate dehydrogenase were upregulated during cryptosporidiosis. Liver oxalate also increased during infection. Microbiome-parasite relationships were observed to be more influential than the host-parasite association in mediating major biochemical changes in the mouse gut during cryptosporidiosis. Defining this parasite-microbiome interaction is the first step towards building a comprehensive cryptosporidiosis model towards biomarker discovery, and rapid and accurate diagnostics.