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.

Wastewater surveillance demonstrates high predictive value for COVID-19 infection on board repatriation flights to Australia.

Controlling importation and transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from overseas travelers is essential for countries, such as Australia, New Zealand, and other island nations, that have adopted a suppression strategy to manage very low community transmission. Wastewater surveillance of SARS-CoV-2 RNA has emerged as a promising tool employed in public health response in many countries globally. This study aimed to establish whether the surveillance of aircraft wastewater can be used to provide an additional layer of information to augment individual clinical testing. Wastewater from 37 long-haul flights chartered to repatriate Australians was tested for the presence of SARS-CoV-2 RNA. Children 5 years or older on these flights tested negative for coronavirus disease 19 (COVID-19) (deep nasal and oropharyngeal reverse-transcription (RT)-PCR swab) 48 h before departure. All passengers underwent mandatory quarantine for 14-day post arrival in Howard Springs, NT, Australia. Wastewater from 24 (64.9 %) of the 37 flights tested positive for SARS-CoV-2 RNA. During the 14 day mandatory quarantine, clinical testing identified 112 cases of COVID-19. Surveillance for SARS-CoV-2 RNA in repatriation flight wastewater using pooled results from three RT-qPCR assays demonstrated a positive predictive value (PPV) of 87.5 %, a negative predictive value (NPV) of 76.9 % and 83.7% accuracy for COVID-19 cases during the post-arrival 14-day quarantine period. The study successfully demonstrates that the surveillance of wastewater from aircraft for SARS-CoV-2 can provide an additional and effective tool for informing the management of returning overseas travelers and for monitoring the importation of SARS CoV-2 and other clinically significant pathogens.

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.

Influence of Human Activities on Broad-Scale Estuarine-Marine Habitats Using Omics-Based Approaches Applied to Marine Sediments.

Rapid urban expansion and increased human activities have led to the progressive deterioration of many marine ecosystems. The diverse microbial communities that inhabit these ecosystems are believed to influence large-scale geochemical processes and, as such, analyzing their composition and functional metabolism can be a means to assessing an ecosystem's resilience to physical and chemical perturbations, or at the very least provide baseline information and insight into future research needs. Here we show the utilization of organic and inorganic contaminant screening coupled with metabolomics and bacterial 16S rRNA gene sequencing to assess the microbial community structure of marine sediments and their functional metabolic output. The sediments collected from Moreton Bay (Queensland, Australia) contained low levels of organic and inorganic contaminants, typically below guideline levels. The sequencing dataset suggest that sulfur and nitrite reduction, dehalogenation, ammonia oxidation, and xylan degradation were the major metabolic functions. The community metabolites suggest a level of functional homogeneity down the 40-cm core depth sampled, with sediment habitat identified as a significant driver for metabolic differences. The communities present in river and sandy channel samples were found to be the most active, with the river habitats likely to be dominated by photoheterotrophs that utilized carbohydrates, fatty acids and alcohols as well as reduce nitrates to release atmospheric nitrogen and oxidize sulfur. Bioturbated mud habitats showed overlapping faunal activity between riverine and sandy ecosystems. Nitrogen-fixing bacteria and lignin-degrading bacteria were most abundant in the sandy channel and bioturbated mud, respectively. The use of omics-based approaches provide greater insight into the functional metabolism of these impacted habitats, extending beyond discrete monitoring to encompassing whole community profiling that represents true phenotypical outputs. Ongoing omics-based monitoring that focuses on more targeted pathway analyses is recommended in order to quantify the flux changes within these systems and establish variations from these baseline measurements.