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Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.

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Depression is a common and highly debilitating psychiatric illness. However, the pathophysiology of depression is not fully understood. In this study SpragueDawley rats were exposed to chronic unpredictable mild stress (CUMS) to induce depression. A metabonomic study on plasma of CUMS-induced depressive rats was performed to research the pathologic mechanism of depression by using 1 H nuclear magnetic resonance (NMR) spectroscopy and ultra performance liquid chromatography coupled to mass spectrometry (UPLC-MS). Clear separations between depressive rats and control rats were observed by principal component analysis (PCA) based on the data obtained using both analytical techniques and 18 significantly changed metabolites were identified as potential biomarkers of depression. Depressive rats were characterized by altered levels of plasma lysophosphatidylcholines, amino acids, cholic acid, choline, lactate, glycoproteins, glucose, ketone bodies, nucleosides and gut microflora metabolites, which were related to multiple perturbed metabolic pathways and contributed to the elucidation of the complex mechanism of depression. To the best of our knowledge, this is the first plasma metabonomic study on CUMS-induced depressive rats by using two complementary analytical technologies. Our results showed that metabonomic approach offers a useful tool to identify depression-specific biomarkers and provide new insights into the pathophysiology of depression.

Background As vaccines against SARS-CoV-2 are now being rolled out, a better understanding of immunity to the virus, whether from infection, or passive or active immunisation, and the durability of this protection is required. This will benefit from the ability to measure antibody-based protection to SARS-CoV-2, ideally with rapid turnaround and without the need for laboratory-based testing. Methods We have developed a lateral flow POC test that can measure levels of RBD-ACE2 neutralising antibody (NAb) from whole blood, with a result that can be determined by eye or quantitatively on a small instrument. We compared our lateral flow test with the gold-standard microneutralisation assay, using samples from convalescent and vaccinated donors, as well as immunised macaques. Findings We show a high correlation between our lateral flow test with conventional neutralisation and that this test is applicable with animal samples. We also show that this assay is readily adaptable to test for protection to newly emerging SARS-CoV-2 variants, including the beta variant which revealed a marked reduction in NAb activity. Lastly, using a cohort of vaccinated humans, we demonstrate that our whole-blood test correlates closely with microneutralisation assay data (specificity 100% and sensitivity 96% at a microneutralisation cutoff of 1:40) and that fingerprick whole blood samples are sufficient for this test. Interpretation Taken together, the COVID-19 NAb-test TM device described here provides a rapid readout of NAb based protection to SARS-CoV-2 at the point of care. Funding Support was received from the Victorian Operational Infrastructure Support Program and the Australian Government Department of Health. This work was supported by grants from the Department of Health and Human Services of the Victorian State Government; the ARC (CE140100011, CE140100036), the NHMRC (1113293, 2002317 and 1116530), and Medical Research Future Fund Awards (2005544, 2002073, 2002132). Individual researchers were supported by an NHMRC Emerging Leadership Level 1 Investigator Grants (1194036), NHMRC APPRISE Research Fellowship (1116530), NHMRC Leadership Investigator Grant (1173871), NHMRC Principal Research Fellowship (1137285), NHMRC Investigator Grants (1177174 and 1174555) and NHMRC Senior Principal Research Fellowships (1117766 and 1136322). Grateful support was also received from the A2 Milk Company and the Jack Ma Foundation.

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