Background

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism's genome as a database restricts metabolite identification to only those compounds that the organism can produce.

Results

To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment's MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis.

Conclusions

Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

BACKGROUND: The Northern Territory (NT) of Australia has a mix of climates, sparsely distributed population and a large proportion of the populace are Indigenous Australians, and influenza is known to have a disproportionate impact upon this group. Understanding the epidemiology of influenza in this region would inform public health strategies. OBJECTIVES: To assess if there are consistent patterns in characteristics of influenza outbreaks in the NT. METHODS: Laboratory confirmed influenza cases in the NT are notified to the NT Centre for Disease Control. We conducted analyses on notified cases from 2007-2016 to determine incidence rates (by age group, Indigenous status and area), seasonality of cases and spatial distribution of influenza types. Notified cases were linked to laboratory datasets to update information on influenza type or subtype RESULTS: The disparity in Indigenous and non-Indigenous notification rates varied by age group, with rate ratios for Indigenous versus non-Indigenous ranging from 1.58 (95% CI:1.39, 1.80) for ages 15-24 to 5.56 (95% CI: 4.71, 6.57) for ages 55-64. The disparity between Indigenous and non-Indigenous notification rates appeared higher in the Central Australia region. Indigenous versus non-Indigenous hospitalisation and mortality rate ratios were 6.51 (95% CI: 5.91, 7.18) and 5.46 (95% CI: 2.40, 12.71) respectively. Inter-seasonal peaks during February and March occurred in 2011, 2013 and 2014, and were due to influenza activity in the tropical north of the NT. CONCLUSIONS: Our results highlight the importance of influenza vaccination across all age groups for Indigenous Australians. An early vaccination campaign targeted against outbreaks in February-March would be best focused on the tropical north.

Toxoplasma gondii is a ubiquitous eukaryotic pathogen responsible for toxoplasmosis in humans and animals. This parasite is an obligate intracellular pathogen and actively invades susceptible host cells, a process which is mediated by specific receptor-ligand interactions. Here, we have identified an unnatural 2,4-disulfated d-glucuronic acid (Di-S-GlcA), a hexuronic acid composed of heparin/heparan sulfate, as a potential carbohydrate ligand that can selectively bind to T. gondii parasites. More importantly, the gelatin conjugated Di-S-GlcA multivalent probe displayed strong inhibition of parasite entry into host cells. These results open perspective for the future use of Di-S-GlcA epitopes in biomedical applications against toxoplasmosis.

Annual epidemics of seasonal influenza cause hundreds of thousands of deaths, high levels of morbidity, and substantial economic loss. Yet, global influenza circulation has been heavily suppressed by public health measures and travel restrictions since the onset of the COVID-19 pandemic. Notably, the influenza B/Yamagata lineage has not been conclusively detected since April 2020, and A(H3N2), A(H1N1), and B/Victoria viruses have since circulated with considerably less genetic diversity. Travel restrictions have largely confined regional outbreaks of A(H3N2) to South and Southeast Asia, B/Victoria to China, and A(H1N1) to West Africa. Seasonal influenza transmission lineages continue to perish globally, except in these select hotspots, which will likely seed future epidemics. Waning population immunity and sporadic case detection will further challenge influenza vaccine strain selection and epidemic control. We offer a perspective on the potential short- and long-term evolutionary dynamics of seasonal influenza and discuss potential consequences and mitigation strategies as global travel gradually returns to pre-pandemic levels.

Swine populations are known to be an important source of new human strains of influenza A, including those responsible for global pandemics. Yet our knowledge of the epidemiology of influenza in swine is dismayingly poor, as highlighted by the emergence of the 2009 pandemic strain and the paucity of data describing its origins. Here, we analyse a unique dataset arising from surveillance of swine influenza at a Hong Kong abattoir from 1998 to 2010. We introduce a state-space model that estimates disease exposure histories by joint inference from multiple modes of surveillance, integrating both virological and serological data. We find that an observed decrease in virus isolation rates is not due to a reduction in the regional prevalence of influenza. Instead, a more likely explanation is increased infection of swine in production farms, creating greater immunity to disease early in life. Consistent with this, we find that the weekly risk of exposure on farms equals or exceeds the exposure risk during transport to slaughter. We discuss potential causes for these patterns, including competition between influenza strains and shifts in the Chinese pork industry, and suggest opportunities to improve knowledge and reduce prevalence of influenza in the region.

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of liver disease worldwide, and its prevalence increases continuously. As it predisposes to hepatocellular carcinoma both in the presence and in the absence of cirrhosis, it is not surprising that the incidence of NAFLD-related hepatocellular carcinoma would also rise. Some of the mechanisms involved in hepatocarcinogenesis are particular to individuals with fatty liver, and they help explain why liver cancer develops even in patients without cirrhosis. Genetic and immune-mediated mechanisms seem to play an important role in the development of hepatocellular carcinoma in this population. Currently, it is consensual that patients with NAFLD-related cirrhosis should be surveilled with ultrasonography every 6 mo (with or without alpha-fetoprotein), but it is known that they are less likely to follow this recommendation than individuals with other kinds of liver disease. Moreover, the performance of the methods of surveillance are lower in NAFLD than they are in other liver diseases. Furthermore, it is not clear which subgroups of patients without cirrhosis should undergo surveillance. Understanding the mechanisms of hepatocarcinogenesis in NAFLD could hopefully lead to the identification of biomarkers to be used in the surveillance for liver cancer in these individuals. By improving surveillance, tumors could be detected in earlier stages, amenable to curative treatments.

We report a systematic, cellular phenotype-based antimalarial screening of the Medicines for Malaria Venture Pathogen Box collection, which facilitated the identification of specific blockers of late-stage intraerythrocytic development of Plasmodium falciparum First, from standard growth inhibition assays, we identified 173 molecules with antimalarial activity (50% effective concentration [EC50] ≤ 10 μM), which included 62 additional molecules over previously known antimalarial candidates from the Pathogen Box. We identified 90 molecules with EC50 of ≤1 μM, which had significant effect on the ring-trophozoite transition, while 9 molecules inhibited the trophozoite-schizont transition and 21 molecules inhibited the schizont-ring transition (with ≥50% parasites failing to proceed to the next stage) at 1 μM. We therefore rescreened all 173 molecules and validated hits in microscopy to prioritize 12 hits as selective blockers of the schizont-ring transition. Seven of these molecules inhibited the calcium ionophore-induced egress of Toxoplasma gondii, a related apicomplexan parasite, suggesting that the inhibitors may be acting via a conserved mechanism which could be further exploited for target identification studies. We demonstrate that two molecules, MMV020670 and MMV026356, identified as schizont inhibitors in our screens, induce the fragmentation of DNA in merozoites, thereby impairing their ability to egress and invade. Further mechanistic studies would facilitate the therapeutic exploitation of these molecules as broadly active inhibitors targeting late-stage development and egress of apicomplexan parasites relevant to human health.

The MYC oncogene is often dysregulated in human cancer, including hepatocellular carcinoma (HCC). MYC is considered undruggable to date. Here, we comprehensively identify genes essential for survival of MYChigh but not MYClow cells by a CRISPR/Cas9 genome-wide screen in a MYC-conditional HCC model. Our screen uncovers novel MYC synthetic lethal (MYC-SL) interactions and identifies most MYC-SL genes described previously. In particular, the screen reveals nucleocytoplasmic transport to be a MYC-SL interaction. We show that the majority of MYC-SL nucleocytoplasmic transport genes are upregulated in MYChigh murine HCC and are associated with poor survival in HCC patients. Inhibiting Exportin-1 (XPO1) in vivo induces marked tumor regression in an autochthonous MYC-transgenic HCC model and inhibits tumor growth in HCC patient-derived xenografts. XPO1 expression is associated with poor prognosis only in HCC patients with high MYC activity. We infer that MYC may generally regulate and require altered expression of nucleocytoplasmic transport genes for tumorigenesis.

In 2018, a 15-year-old female adolescent in Australia was infected with swine influenza A(H3N2) variant virus. The virus contained hemagglutinin and neuraminidase genes derived from 1990s-like human seasonal viruses and internal protein genes from influenza A(H1N1)pdm09 virus, highlighting the potential risk that swine influenza A virus poses to human health in Australia.

STUDY OBJECTIVES: Slow wave and spindle coupling supports memory consolidation, and loss of coupling is linked with cognitive decline and neurodegeneration. Coupling is proposed to be a possible biomarker of neurological disease, yet little is known about the different subtypes of coupling that normally occur throughout human development and aging. Here we identify distinct subtypes of spindles within slow wave upstates and describe their relationships with sleep stage across the human lifespan. METHODS: Coupling within a cross-sectional cohort of 582 subjects was quantified from stages N2 and N3 sleep across ages 6-88 years old. Results were analyzed across the study population via mixed model regression. Within a subset of subjects, we further utilized coupling to identify discrete subtypes of slow waves by their coupled spindles. RESULTS: Two different subtypes of spindles were identified during the upstates of (distinct) slow waves: an early-fast spindle, more common in stage N2 sleep, and a late-fast spindle, more common in stage N3. We further found stages N2 and N3 sleep contain a mixture of discrete subtypes of slow waves, each identified by their unique coupled-spindle timing and frequency. The relative contribution of coupling subtypes shifts across the human lifespan, and a deeper sleep phenotype prevails with increasing age. CONCLUSIONS: Distinct subtypes of slow waves and coupled spindles form the composite of slow wave sleep. Our findings support a model of sleep-dependent synaptic regulation via discrete slow wave/spindle coupling subtypes and advance a conceptual framework for the development of coupling-based biomarkers in age-associated neurological disease.