HAIviz: an interactive dashboard for visualising and integrating healthcare-associated genomic epidemiological data.

Existing tools for phylogeographic and epidemiological visualisation primarily provide a macro-geographic view of epidemic and pandemic transmission events but offer little support for detailed investigation of outbreaks in healthcare settings. Here, we present HAIviz, an interactive web-based application designed for integrating and visualising genomic epidemiological information to improve the tracking of healthcare-associated infections (HAIs). HAIviz displays and links the outbreak timeline, building map, phylogenetic tree, patient bed movements, and transmission network on a single interactive dashboard. HAIviz has been developed for bacterial outbreak investigations but can be utilised for general epidemiological investigations focused on built environments for which visualisation to customised maps is required. This paper describes and demonstrates the application of HAIviz for HAI outbreak investigations.

Melioidosis Queensland: An analysis of clinical outcomes and genomic factors.

BACKGROUND: The clinical and genomic epidemiology of melioidosis varies across regions. AIM: To describe the clinical and genetic diversity of B. pseudomallei across Queensland, Australia. METHODS: Whole genome sequencing of clinical isolates stored at the melioidosis reference lab from 1996-2020 was performed and analysed in conjunction with available clinical data. RESULTS: Isolates from 292 patients were analysed. Bacteraemia was present in 71% and pneumonia in 65%. The case-fatality rate was 25%. Novel sequence types (ST) accounted for 51% of all isolates. No association was identified between the variable virulence factors assessed and patient outcome. Over time, the proportion of First Nation's patients declined from 59% to 26%, and the proportion of patients aged >70 years rose from 13% to 38%. CONCLUSION: This study describes a genomically diverse and comparatively distinct collection of B. pseudomallei clinical isolates from across Queensland, Australia. An increasing incidence of melioidosis in elderly patients may be an important factor in the persistently high case-fatality in this region and warrants further investigation and directed intervention.

ScrepYard: An online resource for disulfide-stabilized tandem repeat peptides.

Receptor avidity through multivalency is a highly sought-after property of ligands. While readily available in nature in the form of bivalent antibodies, this property remains challenging to engineer in synthetic molecules. The discovery of several bivalent venom peptides containing two homologous and independently folded domains (in a tandem repeat arrangement) has provided a unique opportunity to better understand the underpinning design of multivalency in multimeric biomolecules, as well as how naturally occurring multivalent ligands can be identified. In previous work, we classified these molecules as a larger class termed secreted cysteine-rich repeat-proteins (SCREPs). Here, we present an online resource; ScrepYard, designed to assist researchers in identification of SCREP sequences of interest and to aid in characterizing this emerging class of biomolecules. Analysis of sequences within the ScrepYard reveals that two-domain tandem repeats constitute the most abundant SCREP domain architecture, while the interdomain "linker" regions connecting the functional domains are found to be abundant in amino acids with short or polar sidechains and contain an unusually high abundance of proline residues. Finally, we demonstrate the utility of ScrepYard as a virtual screening tool for discovery of putatively multivalent peptides, by using it as a resource to identify a previously uncharacterized serine protease inhibitor and confirm its predicted activity using an enzyme assay.

Clinical Implementation of Routine Whole-genome Sequencing for Hospital Infection Control of Multi-drug Resistant Pathogens.

BACKGROUND: Prospective whole-genome sequencing (WGS)-based surveillance may be the optimal approach to rapidly identify transmission of multi-drug resistant (MDR) bacteria in the healthcare setting. METHODS: We prospectively collected methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), carbapenem-resistant Acinetobacter baumannii (CRAB), extended-spectrum beta-lactamase (ESBL-E), and carbapenemase-producing Enterobacterales (CPE) isolated from blood cultures, sterile sites, or screening specimens across three large tertiary referral hospitals (2 adult, 1 paediatric) in Brisbane, Australia. WGS was used to determine in silico multi-locus sequence typing (MLST) and resistance gene profiling via a bespoke genomic analysis pipeline. Putative transmission events were identified by comparison of core genome single nucleotide polymorphisms (SNPs). Relevant clinical meta-data were combined with genomic analyses via customised automation, collated into hospital-specific reports regularly distributed to infection control teams. RESULTS: Over 4 years (April 2017 to July 2021) 2660 isolates were sequenced. This included MDR gram-negative bacilli (n = 293 CPE, n = 1309 ESBL), MRSA (n = 620), and VRE (n = 433). A total of 379 clinical reports were issued. Core genome SNP data identified that 33% of isolates formed 76 distinct clusters. Of the 76 clusters, 43 were contained to the 3 target hospitals, suggesting ongoing transmission within the clinical environment. The remaining 33 clusters represented possible inter-hospital transmission events or strains circulating in the community. In 1 hospital, proven negligible transmission of non-multi-resistant MRSA enabled changes to infection control policy. CONCLUSIONS: Implementation of routine WGS for MDR pathogens in clinical laboratories is feasible and can enable targeted infection prevention and control interventions.

Optimized Method for Bacterial Nucleic Acid Extraction from Positive Blood Culture Broth for Whole-Genome Sequencing, Resistance Phenotype Prediction, and Downstream Molecular Applications.

The application of direct metagenomic sequencing from positive blood culture broth may solve the challenges of sequencing from low-bacterial-load blood samples in patients with sepsis. Forty prospectively collected blood culture broth samples growing Gram-negative bacteria were extracted using commercially available kits to achieve high-quality DNA. Species identification via metagenomic sequencing and susceptibility prediction via a machine-learning algorithm (AREScloud) were compared to conventional methods and other rapid diagnostic platforms (Accelerate Pheno and blood culture identification [BCID] panel). A two-kit method (using MolYsis Basic and Qiagen DNeasy UltraClean kits) resulted in optimal extractions. Taxonomic profiling by direct metagenomic sequencing matched conventional identification in 38/40 (95%) samples. In two polymicrobial samples, a second organism was missed by sequencing. Prediction models were able to accurately infer susceptibility profiles for 6 common pathogens against 17 antibiotics, with an overall categorical agreement (CA) of 95% (increasing to >95% for 5/6 of the most common pathogens, if Klebsiella oxytoca was excluded). The performance of whole-genome sequencing (WGS)-antimicrobial susceptibility testing (AST) was suboptimal for uncommon pathogens (e.g., Elizabethkingia) and some ß-lactamase inhibitor antibiotics (e.g., ticarcillin-clavulanate). The time to pathogen identification was the fastest with BCID (1 h from blood culture positivity). Accelerate Pheno provided a susceptibility result in approximately 8 h. Illumina-based direct sequencing methods provided results in time frames similar to those of conventional culture-based methods. Direct metagenomic sequencing from blood cultures for pathogen detection and susceptibility prediction is feasible. Additional work is required to optimize algorithms for uncommon species and complex resistance genotypes as well as to streamline methods to provide more rapid results.

Phase variation in the glycosyltransferase genes of Pasteurella multocida associated with outbreaks of fowl cholera on free-range layer farms.

Fowl cholera caused by Pasteurella multocida has re-emerged in Australian poultry production since the increasing adoption of free-range production systems. Currently, autogenous killed whole-cell vaccines prepared from the isolates previously obtained from each farm are the main preventative measures used. In this study, we use whole-genome sequencing and phylogenomic analysis to investigate outbreak dynamics, as well as monitoring and comparing the variations in the lipopolysaccharide (LPS) outer core biosynthesis loci of the outbreak and vaccine strains. In total, 73 isolates from two different free-range layer farms were included. Our genomic analysis revealed that all investigated isolates within the two farms (layer A and layer B) carried LPS type L3, albeit with a high degree of genetic diversity between them. Additionally, the isolates belonged to five different sequence types (STs), with isolates belonging to ST9 and ST20 being the most prevalent. The isolates carried ST-specific mutations within their LPS type L3 outer core biosynthesis loci, including frameshift mutations in the outer core heptosyltransferase gene (htpE) (ST7 and ST274) or galactosyltransferase gene (gatG) (ST20). The ST9 isolates could be separated into three groups based on their LPS outer core biosynthesis loci sequences, with evidence for potential phase variation mechanisms identified. The potential phase variation mechanisms included a tandem repeat insertion in natC and a single base deletion in a homopolymer region of gatG. Importantly, our results demonstrated that two of the three ST9 groups shared identical rep-PCR (repetitive extragenic palindromic PCR) patterns, while carrying differences in their LPS outer core biosynthesis loci region. In addition, we found that ST9 isolates either with or without the natC tandem repeat insertion were both associated with a single outbreak, which would indicate the importance of screening more than one isolate within an outbreak. Our results strongly suggest the need for a metagenomics culture-independent approach, as well as a genetic typing scheme for LPS, to ensure an appropriate vaccine strain with a matching predicted LPS structure is used.

CATHAI: cluster analysis tool for healthcare-associated infections.

Motivation: Whole genome sequencing (WGS) is revolutionizing disease surveillance where it facilitates high-resolution clustering of related organism and outbreak detection. However, visualizing and efficiently communicating genomic data back to clinical staff is crucial for the successful deployment of a targeted infection control response. Results: CATHAI (cluster analysis tool for healthcare-associated infections) is an interactive web-based visualization platform that couples WGS informed clustering with associated metadata, thereby converting sequencing data into informative and accessible clinical information for the management of healthcare-associated infections (HAI) and nosocomial outbreaks. Availability and implementation: All code associated with this application are free available from https://github.com/FordeGenomics/cathai. A demonstration version of CATHAI is available online at https://cathai.fordelab.com.

Using genomics to understand inter- and intra- outbreak diversity of Pasteurella multocida isolates associated with fowl cholera in meat chickens.

Fowl cholera, caused by Pasteurella multocida, continues to be a challenge in meat-chicken-breeder operations and has emerged as a problem for free-range meat chickens. Here, using whole-genome sequencing (WGS) and phylogenomic analysis, we investigate isolate relatedness during outbreaks of fowl cholera on a free-range meat chicken farm over a 5-year period. Our genomic analysis revealed that while all outbreak isolates were sequence type (ST) 20, they could be separated into two distinct clades (clade 1 and clade 2) consistent with difference in their lipopolysaccharide (LPS) type. The isolates from the earlier outbreaks (clade 1) were carrying LPS type L3 while those from the more recent outbreaks (clade 2) were LPS type L1. Additionally, WGS data indicated high inter- and intra-chicken genetic diversity during a single outbreak. Furthermore, we demonstrate that while a killed autogenous vaccine carrying LPS type L3 had been successful in protecting against challenge from L3 isolates it might have driven the emergence of the closely related clade 2, against which the vaccine was ineffective. The genomic results also revealed a 14 bp deletion in the galactosyltransferase gene gatG in LPS type L3 isolates, which would result in producing a semi-truncated LPS in those isolates. In conclusion, our study clearly demonstrates the advantages of genomic analysis over the conventional PCR-based approaches in providing clear insights in terms of linkage of isolate within and between outbreaks. More importantly, it provides more detailed information than the multiplex PCR on the possible structure of outer LPS, which is very important in the case of strain selection for killed autogenous vaccines.

SRA Down Under: Cache and Analysis Platform for Infectious Disease.

SRA, NCBI's Sequence Read Archive, is a valuable resource holding a near definitive collection of the world's collective sequenced reads for academic purposes. Increasingly, these reads are being used for both basic research and clinical investigations. When time is a critical factor in analysis, such as during bacterial outbreaks, the geographical separation between Australia and the offshore NCBI SRA servers can result in significant delays that may have adverse clinical outcomes. To address this, Queensland Genomics commissioned a pilot program for the establishment of a local Australian SRA Cache. Utilizing the hosting capabilities of the NeCTAR Research Cloud, QRIScloud's HTC infrastructure and the MeDiCI data fabric as a storage solution, and the software stack of Cromwell for workflow management, PostgreSQL database for sample and job metadata, and a coordinator Python Flask application, a local cache of seventeen bacterial species was established. Furthermore, the workflow capabilities of Cromwell were leveraged to provide analysis solutions for cached sample data, including quality control and taxonomic profiling, and individual and multiple sample analysis. Moving forward to a broader rollout of increased bacterial species, it was found that the initial storage estimation did not keep up with the exponential increase sequencing reads uploaded to NCBI SRA, which while highlighting the increasing availability and importance in modern research, will need to be addressed.

Determinants of Zika virus host tropism uncovered by deep mutational scanning.

Arboviruses cycle between, and replicate in, both invertebrate and vertebrate hosts, which for Zika virus (ZIKV) involves Aedes mosquitoes and primates1. The viral determinants required for replication in such obligate hosts are under strong purifying selection during natural virus evolution, making it challenging to resolve which determinants are optimal for viral fitness in each host. Herein we describe a deep mutational scanning (DMS) strategy2-5 whereby a viral cDNA library was constructed containing all codon substitutions in the C-terminal 204 amino acids of ZIKV envelope protein (E). The cDNA library was transfected into C6/36 (Aedes) and Vero (primate) cells, with subsequent deep sequencing and computational analyses of recovered viruses showing that substitutions K316Q and S461G, or Q350L and T397S, conferred substantial replicative advantages in mosquito and primate cells, respectively. A 316Q/461G virus was constructed and shown to be replication-defective in mammalian cells due to severely compromised virus particle formation and secretion. The 316Q/461G virus was also highly attenuated in human brain organoids, and illustrated utility as a vaccine in mice. This approach can thus imitate evolutionary selection in a matter of days and identify amino acids key to the regulation of virus replication in specific host environments.