Biology subjects

Payne, M.

Publications and source records attributed to Payne, M..

25 records · Page 2Linked to original sources

bioRxiv2022

Programmed cell death-1 receptor mediated regulation of Tbet+ NK1.1- Innate Lymphoid Cells within the Tumor Microenvironment

Innate Lymphoid Cells (ILCs) play a key role in tissue mediated immunity and can be controlled by co-receptor signaling. Here we define a subset of ILCs that are Tbet+NK1.1- and are present within the tumor microenvironment (TME). We show programmed death-1 receptor (PD-1) expression on ILCs within TME is found in Tbet+NK1.1-ILCs. PD-1 significantly controlled the proliferation and function of Tbet+NK1.1-ILCs in multiple murine and human tumors. We found tumor derived lactate enhanced PD-1 expression on Tbet+NK1.1-ILCs within the TME, which resulted in dampened mTOR signaling along with increased fatty acid uptake. In line with these metabolic changes, PD-1 deficient Tbet+NK1.1-ILCs expressed significantly increased IFN{gamma}, granzyme B and K. Furthermore, PD1 deficient Tbet+NK1.1- ILCs contributed towards diminished tumor growth in an experimental murine model of melanoma. These data demonstrate that PD-1 can regulate anti-tumor responses of Tbet+NK1.1-ILCs within the tumor microenvironment. HighlightsO_LITbet+NK1.1- ILCs are found in WT and PD1 ko mice C_LIO_LIPD-1 is expressed on Tbet+NK1.1- ILC1s within multiple TME C_LIO_LIPD-1 controls the proliferation and function of Tbet+NK1.1- ILCs within the tumor microenvironment by modulating fatty acid metabolism. C_LIO_LIPD-1 regulates the proliferation of human Tbet+ ILC1s in human cutaneous squamous cell carcinoma (cSCC) and melanoma tumor microenvironment. C_LI

immunology↗

bioRxiv2022

Microwell-based flow culture reduces hypoxia-induced phenotype and restores drug response in prostate cancer spheroids

3D cancer spheroids represent a highly promising model for study of cancer progression and therapeutic development. Wide-scale adoption of cancer spheroids, however, remains a challenge due to the lack of control over hypoxic gradients that may cloud the assessment of cell morphology and drug response. Here, we present a Microwell Flow Device (MFD) that generates in-well laminar flow around 3D tissues via repetitive tissue sedimentation. Using a prostate cancer cell line, we demonstrate the spheroids in the MFD exhibit improved cell growth, reduced necrotic core formation, enhanced structural integrity, and down-regulated expression of cell stress genes. The flow-cultured spheroids also exhibit an improved sensitivity to chemotherapy with greater transcriptional response. These results demonstrate how fluidic stimuli reveal the cellular phenotype previously masked by severe necrosis. Our platform advances 3D cellular models and enables study into hypoxia modulation, cancer metabolism, and drug screening within pathophysiological conditions.

bioengineering↗

bioRxiv2022

MGTdb: A web service and database for studying the global and local genomic epidemiology of bacterial pathogens

Multilevel genome typing (MGT) enables the genomic characterization of bacterial isolates and the relationships among them. The MGT system describes an isolate using multiple multilocus sequence typing (MLST) schemes, referred to as levels. Thus, for a new isolate, sequence types (STs) assigned at multiple precisely defined levels can be used to type isolates at multiple resolutions. The MGT designation for isolates is stable, and assignment is faster than existing approaches. MGTs utility has been demonstrated in multiple species. This paper presents a publicly accessible web service called MGTdb, which enables the assignment of MGT sequence types to isolates, along with their storage, retrieval and analysis. The MGTdb web service enables upload of genome data as sequence reads or alleles, which are processed and assigned MGT identifiers. Additionally, any newly sequenced isolates deposited in NCBI Sequence Read Archive are also regularly retrieved (currently daily), processed, assigned MGT and made publicly available in MGTdb. Interactive visualisation tools are presented to assist analysis, along with capabilities to download publicly available isolates and assignments for use with external software. MGTdb is currently available for Salmonella enterica serovars Typhimurium and Enteritidis, and Vibrio cholerae. We demonstrate the usability of MGTdb through three case studies to study the long-term national surveillance of S. Typhimurium, and the local epidemiology and outbreaks of S. Typhimurium, and the global epidemiology of V. cholerae. Thus, MGTdb enables epidemiological and microbiological investigations at multiple levels of resolution for all publicly available isolates of these pathogens. Database URLhttps://mgtdb.unsw.edu.au

bioinformatics↗

bioRxiv2022

Genomic epidemiology and multilevel genome typing of Australian Salmonella enterica serovar Enteritidis

Salmonella enterica serovar Enteritidis is one of the leading causes of salmonellosis in Australia. However, the majority of S. Enteritidis cases in Australia are travel-related with a small proportion being locally acquired. This study aimed to characterise the genomic features of Australian S. Enteritidis and compare them with international strains using multilevel genome typing (MGT). A total of 568 S. Enteritidis isolates from two Australian states across two consecutive years were analysed using the S. Enteritidis MGT scheme and database (MGTdb) - which contained 40,390 publicly available genomes from 99 countries. The Australian S. Enteritidis strains were divided into three phylogenetic clades (A, B and C). Clades A and C represented 16.4% and 3.5% of the total isolates, respectively, and were of local origin. Clade B accounted for 80.1% of the isolates which belonged to seven previously defined lineages but was dominated by the global epidemic lineage (MGT4-CC1). At MGT5 level, three out of five top sequence types (STs) in Australia were also top STs in Asia, suggesting that a fair proportion of Australian S. Enteritidis cases may be epidemiologically linked with Asian strains. In 2018, a large egg-associated local outbreak was caused by a recently defined clade B lineage prevalent in Europe and was closely related, but not directly linked, to three isolates from Europe. Additionally, antimicrobial-resistance genes were only found in Australian clade B isolates, with a predicted multidrug resistance (MDR) rate of 11.7%. Over half (54.8%) of the MDR isolates belonged to 10 MDR-associated MGT-STs, which were also frequent in Asian S. Enteritidis. IncX1 plasmids were frequently present in the Australian MDR isolates. Overall, this study investigated the genomic epidemiology of S. Enteritidis in Australia, including the first large local outbreak, using MGT. The open MGT platform enables a standardised and sharable nomenclature that can be effectively applied to public health for unified surveillance of S. Enteritidis nationally and globally. ImportanceSalmonella enterica serovar Enteritidis is a leading cause of foodborne infections. We previously developed a genomic typing database - MGTdb for S. Enteritidis to facilitate global surveillance of this pathogen. In this study we examined the genomic features of Australian S. Enteritidis using the MGTdb and found that Australian S. Enteritidis is mainly epidemiologically linked with Asian strains (especially strains carrying antimicrobial resistance genes) followed by European strains. The first large-scale egg-associated local outbreak in Australia was caused by a recently defined lineage prevalent in Europe, and three European isolates in the MGTdb were closely related but not directly linked to this outbreak. In summary, the S. Enteritidis MGTdb open platform is shown to be a potential powerful tool for national and global public health surveillance of this pathogen.

genomics↗

bioRxiv2021

Crosstalk between β-catenin and WT1 signalling activity in acute myeloid leukemia

Wnt signalling is an evolutionary conserved signal transduction pathway heavily implicated in normal development and disease. The central mediator of this pathway, {beta}-catenin, is frequently overexpressed, mislocalised and overactive in acute myeloid leukaemia (AML) where it mediates the establishment, maintenance and drug resistance of leukaemia stem cells. Critical to the stability, localisation and activity of {beta}-catenin are the protein-protein interactions it forms, yet these are poorly defined in AML. We recently performed the first {beta}-catenin interactome study in blood cells of any kind and identified a plethora of novel interacting partners. This study shows for the first time that {beta}-catenin interacts with Wilms tumour protein (WT1), a protein frequently overexpressed and mutated in AML, in both myeloid cell lines and also primary AML samples. We demonstrate crosstalk between the signalling activity of these two proteins in myeloid cells, and show that modulation of either protein can affect expression of the other. Finally, we demonstrate that WT1 mutations frequently observed in AML can increase stabilise {beta}-catenin and augment Wnt signalling output. This study has uncovered new context-dependent molecular interactions for {beta}-catenin which could inform future therapeutic strategies to target this dysregulated molecule in AML. Article summaryO_LI{beta}-Catenin is frequently dysregulated in acute myeloid leukemia (AML) and protein interactions govern its stability, localization and activity, but these are poorly defined in AML. C_LIO_LIThis study shows for the first time that {beta}-catenin and Wilms tumour protein (WT1) interact and influence each others expression level and signalling activity in AML cells, which could inform future therapeutic strategies. C_LI

cancer biology↗

bioRxiv2021

Cluster-specific gene marker enhance Shigella and Enteroinvasive Escherichia coli in silico serotyping

Shigella and enteroinvasive Escherichia coli (EIEC) cause human bacillary dysentery with similar invasion mechanisms and share similar physiological, biochemical and genetic characteristics. The ability to differentiate Shigella and EIEC from each other is important for clinical diagnostic and epidemiologic investigations. The existing genetic signatures may not discriminate between Shigella and EIEC. However, phylogenetically, Shigella and EIEC strains are composed of multiple clusters and are different forms of E. coli. In this study, we identified 10 Shigella clusters, 7 EIEC clusters and 53 sporadic types of EIEC by examining over 17,000 publicly available Shigella/EIEC genomes. We compared Shigella and EIEC accessory genomes to identify the cluster-specific gene markers or marker sets for the 17 clusters and 53 sporadic types. The gene markers showed 99.63% accuracy and more than 97.02% specificity. In addition, we developed a freely available in silico serotyping pipeline named Shigella EIEC Cluster Enhanced Serotype Finder (ShigEiFinder) by incorporating the cluster-specific gene markers and established Shigella/EIEC serotype specific O antigen genes and modification genes into typing. ShigEiFinder can process either paired end Illumina sequencing reads or assembled genomes and almost perfectly differentiated Shigella from EIEC with 99.70% and 99.81% cluster assignment accuracy for the assembled genomes and mapped reads respectively. ShigEiFinder was able to serotype over 59 Shigella serotypes and 22 EIEC serotypes and provided a high specificity with 99.40% for assembled genomes and 99.38% for mapped reads for serotyping. The cluster markers and our new serotyping tool, ShigEiFinder (https://github.com/LanLab/ShigEiFinder), will be useful for epidemiologic and diagnostic investigations. Impact statementThe differentiation of Shigella strains from enteroinvasive E. coli (EIEC) is important for clinical diagnosis and public health epidemiologic investigations. The similarities between Shigella and EIEC strains make this differentiation very difficult as both share common ancestries within E. coli. However, Shigella and EIEC are phylogenetically separated into multiple clusters, making high resolution separation using cluster specific genomic markers possible. In this study, we identified 17 Shigella or EIEC clusters including five that were newly identified through examination of over 17,000 publicly available Shigella and EIEC genomes. We further identified an individual or a set of cluster-specific gene markers for each cluster using comparative genomic analysis. These markers can then be used to classify isolates into clusters and were used to develop an in silico pipeline, ShigEiFinder (https://github.com/LanLab/ShigEiFinder) for accurate differentiation, cluster typing and serotyping of Shigella and EIEC from Illumina sequencing reads or assembled genomes. This study will have broad application from understanding the evolution of Shigella/EIEC to diagnosis and epidemiology. Data summarySequencing data have been deposited at the National Center for Biotechnology Information under BioProject number PRJNA692536. RepositoriesRaw sequence data are available from NCBI under the BioProject number PRJNA692536.

microbiology↗

bioRxiv2020

Elucidation of global and local epidemiology of Salmonella Enteritidis through multilevel genome typing

Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26,670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA were identified; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018, revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified MDR associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for S. Enteritidis surveillance and outbreak detection. Impact statementSalmonella enterica serovar Enteritidis is a common foodborne pathogen that can cause large outbreaks. Surveillance and high-resolution typing are essential for outbreak prevention and control. Genome sequencing offers unprecedented power for these purposes and a standardised method or platform for the interpretation, comparison and communication of genomic typing data is highly desirable. In this work, we developed a genomic typing scheme called Multilevel Genome Typing (MGT) for S. Enteritidis. We analysed 26,670 publicly available genomes of S. Enteritidis using MGT. We characterised the geographic and temporal distribution of S. Enteritidis MGT types as well as their association with multidrug resistance (MDR) and virulence genes. A publicly available MGT database for S. Enteritidis was established, which has the potential facilitate the unified global public health surveillance for this pathogen. Data SummaryO_LIThe MGT database for S. Enteritidis is available at https://mgtdb.unsw.edu.au/enteritidis/. C_LIO_LIAll accession numbers of the public available genomes were available in the MGT database and Data Set S1, Tab 1. And there were no newly sequenced data in this study. C_LIO_LISupplementary material: Supplementary Fig. S1 to S7, supplementary methods and supporting results about the evaluation of potential repeat sequencing bias. C_LIO_LIData Set S1: Supporting tables of the main results. C_LIO_LIData Set S2. Supporting tables of the repeat sequencing bias evaluation by removing the potential repeat sequencing isolates. Note outbreak isolates may also be removed. C_LI

genomics↗