microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Reproducibility of COVID-era infectious disease models.

Infectious disease modelling has been prominent throughout the COVID-19 pandemic, helping to understand the virus' transmission dynamics and inform response policies. Given their potential importance and translational impact, we evaluated the computational reproducibility of infectious disease modelling articles from the COVID era. We found that four out of 100 randomly sampled studies released between January 2020 and August 2022 could be completely computationally reproduced using the resources provided (e.g., code, data, instructions) whilst a further eight were partially reproducible. For the 100 most highly cited articles from the same period we found that 11 were completely reproducible with a further 22 partially reproducible. Reflecting on our experience, we discuss common issues affecting computational reproducibility and how these might be addressed.

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics.

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Replicating superspreader dynamics with compartmental models.

Infectious disease outbreaks often exhibit superspreader dynamics, where most infected people generate no, or few secondary cases, and only a small fraction of individuals are responsible for a large proportion of transmission. Although capturing this heterogeneity is critical for estimating outbreak risk and the effectiveness of group-specific interventions, it is typically neglected in compartmental models of infectious disease transmission-which constitute the most common transmission dynamic modeling framework. In this study we propose different classes of compartmental epidemic models that incorporate transmission heterogeneity, fit them to a number of real outbreak datasets, and benchmark their performance against the canonical superspreader model (i.e., the negative binomial branching process model). We find that properly constructed compartmental models can capably reproduce observed superspreader dynamics and we provide the pathogen-specific parameter settings required to do so. As a consequence, we also show that compartmental models parameterized according to a binary clinical classification have limited support.

Quantifying the impact of Wolbachia releases on dengue infection in Townsville, Australia.

From October 2014 to February 2019, local authorities in Townsville, North Queensland, Australia continually introduced Wolbachia-infected mosquitoes to control seasonal outbreaks of dengue infection. In this study, we develop a mathematical modelling framework to estimate the effectiveness of this intervention as well as the relative dengue transmission rates of Wolbachia-infected and wild-type mosquitoes. We find that the transmission rate of Wolbachia-infected mosquitoes is reduced approximately by a factor of 20 relative to the uninfected wild-type population. In addition, the Townsville Wolbachia release program led to a 65% reduction in predicted dengue incidence during the release period and over 95% reduction in the 24 months that followed. Finally, to investigate the potential impact of other Wolbachia release programs, we use our estimates of relative transmissibility to calculate the relationship between the reproductive number of dengue and the proportion of Wolbachia-infected mosquitoes in the vector population.

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data.

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.

Effects of a ketogenic and low-fat diet on the human metabolome, microbiome, and foodome in adults at risk for Alzheimer's disease.

INTRODUCTION: The ketogenic diet (KD) is an intriguing therapeutic candidate for Alzheimer's disease (AD) given its protective effects against metabolic dysregulation and seizures. Gut microbiota are essential for KD-mediated neuroprotection against seizures as well as modulation of bile acids, which play a major role in cholesterol metabolism. These relationships motivated our analysis of gut microbiota and metabolites related to cognitive status following a controlled KD intervention compared with a low-fat-diet intervention. METHODS: Prediabetic adults, either with mild cognitive impairment (MCI) or cognitively normal (CN), were placed on either a low-fat American Heart Association diet or high-fat modified Mediterranean KD (MMKD) for 6 weeks; then, after a 6-week washout period, they crossed over to the alternate diet. We collected stool samples for shotgun metagenomics and untargeted metabolomics at five time points to investigate individuals' microbiome and metabolome throughout the dietary interventions. RESULTS: Participants with MCI on the MMKD had lower levels of GABA-producing microbes Alistipes sp. CAG:514 and GABA, and higher levels of GABA-regulating microbes Akkermansia muciniphila. MCI individuals with curcumin in their diet had lower levels of bile salt hydrolase-containing microbes and an altered bile acid pool, suggesting reduced gut motility. DISCUSSION: Our results suggest that the MMKD may benefit adults with MCI through modulation of GABA levels and gut-transit time.

A Systematic Review of Mathematical Models of Dengue Transmission and Vector Control: 2010-2020.

Vector control methods are considered effective in averting dengue transmission. However, several factors may modify their impact. Of these controls, chemical methods, in the long run, may increase mosquitoes' resistance to chemicides, thereby decreasing control efficacy. The biological methods, which may be self-sustaining and very effective, could be hampered by seasonality or heatwaves (resulting in, e.g., loss of Wolbachia infection). The environmental methods that could be more effective than the chemical methods are under-investigated. In this study, a systematic review is conducted to explore the present understanding of the effectiveness of vector control approaches via dengue transmission models.

Modelling the ecological dynamics of mosquito populations with multiple co-circulating Wolbachia strains.

Wolbachia intracellular bacteria successfully reduce the transmissibility of arthropod-borne viruses (arboviruses) when introduced into virus-carrying vectors such as mosquitoes. Despite the progress made by introducing Wolbachia bacteria into the Aedes aegypti wild-type population to control arboviral infections, reports suggest that heat-induced loss-of-Wolbachia-infection as a result of climate change may reverse these gains. Novel, supplemental Wolbachia strains that are more resilient to increased temperatures may circumvent these concerns, and could potentially act synergistically with existing variants. In this article, we model the ecological dynamics among three distinct mosquito (sub)populations: a wild-type population free of any Wolbachia infection; an invading population infected with a particular Wolbachia strain; and a second invading population infected with a distinct Wolbachia strain from that of the first invader. We explore how the range of possible characteristics of each Wolbachia strain impacts mosquito prevalence. Further, we analyse the differential system governing the mosquito populations and the Wolbachia infection dynamics by computing the full set of basic and invasive reproduction numbers and use these to establish stability of identified equilibria. Our results show that releasing mosquitoes with two different strains of Wolbachia did not increase their prevalence, compared with a single-strain Wolbachia-infected mosquito introduction and only delayed Wolbachia dominance.

Phylodynamic signatures in the emergence of community-associated MRSA.

Community-associated, methicillin-resistant Staphylococcus aureus (MRSA) lineages have emerged in many geographically distinct regions around the world during the past 30 y. Here, we apply consistent phylodynamic methods across multiple community-associated MRSA lineages to describe and contrast their patterns of emergence and dissemination. We generated whole-genome sequencing data for the Australian sequence type (ST) ST93-MRSA-IV from remote communities in Far North Queensland and Papua New Guinea, and the Bengal Bay ST772-MRSA-V clone from metropolitan communities in Pakistan. Increases in the effective reproduction number (Re) and sustained transmission (Re > 1) coincided with spread of progenitor methicillin-susceptible S. aureus (MSSA) in remote northern Australian populations, dissemination of the ST93-MRSA-IV genotype into population centers on the Australian East Coast, and subsequent importation into the highlands of Papua New Guinea and Far North Queensland. Applying the same phylodynamic methods to existing lineage datasets, we identified common signatures of epidemic growth in the emergence and epidemiological trajectory of community-associated S. aureus lineages from America, Asia, Australasia, and Europe. Surges in Re were observed at the divergence of antibiotic-resistant strains, coinciding with their establishment in regional population centers. Epidemic growth was also observed among drug-resistant MSSA clades in Africa and northern Australia. Our data suggest that the emergence of community-associated MRSA in the late 20th century was driven by a combination of antibiotic-resistant genotypes and host epidemiology, leading to abrupt changes in lineage-wide transmission dynamics and sustained transmission in regional population centers.

Enhancing untargeted metabolomics using metadata-based source annotation.

Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

Mathematical analysis of a two-strain tuberculosis model in Bangladesh.

Tuberculosis (TB) is an airborne infectious disease that causes millions of deaths worldwide each year (1.2 million people died in 2019). Alarmingly, several strains of the causative agent, Mycobacterium tuberculosis (MTB)-including drug-susceptible (DS) and drug-resistant (DR) variants-already circulate throughout most developing and developed countries, particularly in Bangladesh, with totally drug-resistant strains starting to emerge. In this study we develop a two-strain DS and DR TB transmission model and perform an analysis of the system properties and solutions. Both analytical and numerical results show that the prevalence of drug-resistant infection increases with an increasing drug use through amplification. Both analytic results and numerical simulations suggest that if the basic reproduction numbers of both DS ([Formula: see text]) and DR ([Formula: see text]) TB are less than one, i.e. [Formula: see text] the disease-free equilibrium is asymptotically stable, meaning that the disease naturally dies out. Furthermore, if [Formula: see text], then DS TB dies out but DR TB persists in the population, and if [Formula: see text] both DS TB and DR TB persist in the population. Further, sensitivity analysis of the model parameters found that the transmission rate of both strains had the greatest influence on DS and DR TB prevalence. We also investigated the effect of treatment rates and amplification on both DS and DR TB prevalence; results indicate that inadequate or inappropriate treatment makes co-existence more likely and increases the relative abundance of DR TB infections.

Multi-omics of human plasma reveals molecular features of dysregulated inflammation and accelerated aging in schizophrenia.

Schizophrenia is a devastating psychiatric illness that detrimentally affects a significant portion of the worldwide population. Aging of schizophrenia patients is associated with reduced longevity, but the potential biological factors associated with aging in this population have not yet been investigated in a global manner. To address this gap in knowledge, the present study assesses proteomics and metabolomics profiles in the plasma of subjects afflicted with schizophrenia compared to non-psychiatric control patients over six decades of life. Global, unbiased analyses of circulating blood plasma can provide knowledge of prominently dysregulated molecular pathways and their association with schizophrenia, as well as features of aging and gender in this disease. The resulting data compiled in this study represent a compendium of molecular changes associated with schizophrenia over the human lifetime. Supporting the clinical finding of schizophrenia's association with more rapid aging, both schizophrenia diagnosis and age significantly influenced the plasma proteome in subjects assayed. Schizophrenia was broadly associated with prominent dysregulation of inflammatory and metabolic system components. Proteome changes demonstrated increased abundance of biomarkers for risk of physiologic comorbidities of schizophrenia, especially in younger individuals. These findings advance our understanding of the molecular etiology of schizophrenia and its associated comorbidities throughout the aging process.

Estimating the global burden of Epstein-Barr virus-related cancers.

BACKGROUND: More than 90% of the adult population globally is chronically infected by the Epstein-Barr virus (EBV). It is well established that EBV is associated with a number of malignancies, and advances in knowledge of EBV-related malignancies are being made every year. Several studies have analysed the global epidemiology and geographic distribution of EBV-related cancers. However, most have only described a single cancer type or subtype in isolation or limited their study to the three or four most common EBV-related cancers. This review will present an overview on the spectrum of cancers linked to EBV based on observations of associations and proportions in the published literature while also using these observations to estimate the incidence and mortality burden of some of these cancers. METHOD: We have reviewed the literature on defining features, distribution and outcomes across six cancers with a relatively large EBV-related case burden: Nasopharyngeal carcinoma (NPC), Gastric carcinoma (GC), Hodgkin lymphoma (HL), Burkitt lymphoma (BL), Diffuse large B-cell lymphoma (DLBCL) and Extranodal NK/T-cell lymphoma, Nasal type (ENKTL-NT). We retrieved published region-specific EBV-related case proportions for NPC, GC, HL and BL and performed meta-analyses on pooled region-specific studies of EBV-related case proportions for DLBCL and ENKTL-NT. We match these pooled proportions with their respective regional incidence and mortality numbers retrieved from a publicly available cancer database. Additionally, we also reviewed the literature on several other less common EBV-related cancers to summarize their key characteristics herein. CONCLUSION: We estimated that EBV-related cases from these six cancers accounted for 239,700-357,900 new cases and 137,900-208,700 deaths in 2020. This review highlights the significant global impact of EBV-related cancers and extends the spectrum of disease that could benefit from an EBV-specific therapeutic.

Understanding how Victoria, Australia gained control of its second COVID-19 wave.

During 2020, Victoria was the Australian state hardest hit by COVID-19, but was successful in controlling its second wave through aggressive policy interventions. We calibrated a detailed compartmental model of Victoria's second wave to multiple geographically-structured epidemic time-series indicators. We achieved a good fit overall and for individual health services through a combination of time-varying processes, including case detection, population mobility, school closures, physical distancing and face covering usage. Estimates of the risk of death in those aged ≥75 and of hospitalisation were higher than international estimates, reflecting concentration of cases in high-risk settings. We estimated significant effects for each of the calibrated time-varying processes, with estimates for the individual-level effect of physical distancing of 37.4% (95%CrI 7.2-56.4%) and of face coverings of 45.9% (95%CrI 32.9-55.6%). That the multi-faceted interventions led to the dramatic reversal in the epidemic trajectory is supported by our results, with face coverings likely particularly important.

Sustaining effective COVID-19 control in Malaysia through large-scale vaccination.

INTRODUCTION: As of 3rd June 2021, Malaysia is experiencing a resurgence of COVID-19 cases. In response, the federal government has implemented various non-pharmaceutical interventions (NPIs) under a series of Movement Control Orders and, more recently, a vaccination campaign to regain epidemic control. In this study, we assessed the potential for the vaccination campaign to control the epidemic in Malaysia and four high-burden regions of interest, under various public health response scenarios. METHODS: A modified susceptible-exposed-infectious-recovered compartmental model was developed that included two sequential incubation and infectious periods, with stratification by clinical state. The model was further stratified by age and incorporated population mobility to capture NPIs and micro-distancing (behaviour changes not captured through population mobility). Emerging variants of concern (VoC) were included as an additional strain competing with the existing wild-type strain. Several scenarios that included different vaccination strategies (i.e. vaccines that reduce disease severity and/or prevent infection, vaccination coverage) and mobility restrictions were implemented. RESULTS: The national model and the regional models all fit well to notification data but underestimated ICU occupancy and deaths in recent weeks, which may be attributable to increased severity of VoC or saturation of case detection. However, the true case detection proportion showed wide credible intervals, highlighting incomplete understanding of the true epidemic size. The scenario projections suggested that under current vaccination rates complete relaxation of all NPIs would trigger a major epidemic. The results emphasise the importance of micro-distancing, maintaining mobility restrictions during vaccination roll-out and accelerating the pace of vaccination for future control. Malaysia is particularly susceptible to a major COVID-19 resurgence resulting from its limited population immunity due to the country's historical success in maintaining control throughout much of 2020.

Modelling direct and herd protection effects of vaccination against the SARS-CoV-2 Delta variant in Australia.

OBJECTIVES: To analyse the outcomes of COVID-19 vaccination by vaccine type, age group eligibility, vaccination strategy, and population coverage. DESIGN: Epidemiologic modelling to assess the final size of a COVID-19 epidemic in Australia, with vaccination program (Pfizer, AstraZeneca, mixed), vaccination strategy (vulnerable first, transmitters first, untargeted), age group eligibility threshold (5 or 15 years), population coverage, and pre-vaccination effective reproduction number ( Reffv¯ ) for the SARS-CoV-2 Delta variant as factors. MAIN OUTCOME MEASURES: Numbers of SARS-CoV-2 infections; cumulative hospitalisations, deaths, and years of life lost. RESULTS: Assuming Reffv¯ = 5, the current mixed vaccination program (vaccinating people aged 60 or more with the AstraZeneca vaccine and people under 60 with the Pfizer vaccine) will not achieve herd protection unless population vaccination coverage reaches 85% by lowering the vaccination eligibility age to 5 years. At Reffv¯ = 3, the mixed program could achieve herd protection at 60-70% population coverage and without vaccinating 5-15-year-old children. At Reffv¯ = 7, herd protection is unlikely to be achieved with currently available vaccines, but they would still reduce the number of COVID-19-related deaths by 85%. CONCLUSION: Vaccinating vulnerable people first is the optimal policy when population vaccination coverage is low, but vaccinating more socially active people becomes more important as the Reffv¯ declines and vaccination coverage increases. Assuming the most plausible Reffv¯ of 5, vaccinating more than 85% of the population, including children, would be needed to achieve herd protection. Even without herd protection, vaccines are highly effective in reducing the number of deaths.

Vaccines and variants: Modelling insights into emerging issues in COVID-19 epidemiology.

Mathematical modelling has played a pivotal role in understanding the epidemiology of and guiding public health responses to the ongoing coronavirus disease of 2019 (COVID-19) pandemic. Here, we review the role of epidemiological models in understanding evolving epidemic characteristics, including the effects of vaccination and Variants of Concern (VoC). We highlight ways in which models continue to provide important insights, including (1) calculating the herd immunity threshold and evaluating its limitations; (2) verifying that nascent vaccines can prevent severe disease, infection, and transmission but may be less efficacious against VoC; (3) determining optimal vaccine allocation strategies under efficacy and supply constraints; and (4) determining that VoC are more transmissible and lethal than previously circulating strains, and that immune escape may jeopardize vaccine-induced herd immunity. Finally, we explore how models can help us anticipate and prepare for future stages of COVID-19 epidemiology (and that of other diseases) through forecasts and scenario projections, given current uncertainties and data limitations.