Biology subjects

Seeman, T.

Publications and source records attributed to Seeman, T..

5 recordsLinked to original sources

bioRxiv2026

Stressful exposure from the 2004 Indian Ocean Tsunami drives long-term changes in thyroid hormone physiology

Stressful events are associated with long-term adverse health impacts, but the causal mechanisms linking these exposures to subsequent disease remain poorly understood. One plausible mechanism is persistent changes to hormonal signaling that regulate metabolic homeostasis. Here, we examine the long-term impacts of stress associated with exposure to the 2004 Indian Ocean tsunami on levels of free triiodothyronine (FT3), a circulating measure of biologically active thyroid hormone, using data from the Study of Tsunami Aftermath and Recovery. We measure biomarkers 20 years after the tsunami in a population-representative sample age 35y+ in 2024 who, at the time of the tsunami, were living along the coast of Aceh, Indonesia, the most affected part of the Indian Ocean Basin. Because respondents were first interviewed before the tsunami and subsequently tracked regardless of migration, the sample avoids a major source of selection bias common in long-term disaster studies. We identify the causal effect of tsunami exposure using variation in community-level tsunami mortality, comparing communities within the same sub-district. We find that greater tsunami exposure reduced levels of FT3 20 years later. Exposure also altered relationships between FT3, body composition, and cortisol and increased cardiometabolic risk. These findings identify persistent alteration of thyroid hormone physiology as a potential pathway linking severe stressful exposures to long-term cardiometabolic disease risk.

physiology↗

bioRxiv2023

High performance Legionella pneumophila source attribution using genomics-based machine learning classification

Fundamental to effective Legionnaires disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionised pathogen surveillance but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here we present a powerful machine learning approach that assigns the geographical source of Legionnaires disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires disease outbreaks through detailed case investigations. Our classification models were developed in a cross-validation framework using only environmental L. pneumophila genomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534-genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance - agreement with epidemiological information. Our multivariate statistical learning approach maximises use of genomic variation data and is thus well-suited for supporting Legionnaires disease outbreak investigations.

bioinformatics↗

bioRxiv2023

The WalKR two-component regulator coordinates cell wall homeostasis with DNA replication in Staphylococcus aureus

Among the 16 two-component systems (TCSs) in the opportunistic human pathogen Staphylococcus aureus, only WalKR is essential. Like orthologous systems in other Bacillota, S. aureus WalKR controls autolysins involved in peptidoglycan remodelling and is therefore intimately involved in cell division. However, despite the importance of WalKR in S. aureus, the basis for its essentiality is not understood and the regulon poorly defined. Here, we defined a consensus WalR DNA-binding motif and the direct WalKR regulon by using functional genomics, including ChIP-seq, with a panel of isogenic walKR mutants that had a spectrum of altered activities. Consistent with prior findings, the direct regulon includes multiple autolysin genes. However, this work also revealed that WalR directly regulates at least five essential genes involved in lipoteichoic acid synthesis (ltaS); translation (rplK); DNA compaction (hup); initiation of DNA replication (dnaA, hup); and purine nucleotide metabolism (prs). Thus, WalKR in S. aureus serves as a polyfunctional regulator that contributes to fundamental control over critical cell processes by co-ordinately linking cell wall homeostasis with purine biosynthesis, protein biosynthesis, and DNA replication. Collectively, our findings address the essentiality of this locus and highlight the importance of WalKR as a bona fide target for novel anti-staphylococcal therapeutics.

microbiology↗

bioRxiv2020

Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria

BackgroundPairwise single nucleotide polymorphisms (SNPs) are a cornerstone for genomic approaches to multidrug-resistant organisms (MDROs) transmission inference in hospitals. However, the impact of key analysis parameters on these inferences has not been systematically analysed. MethodsWe conducted a multi-hospital 15-month prospective study, sequencing 1537 MDRO genomes for comparison; methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus faecium, and extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae. We systematically assessed the impact of sample and reference genome diversity, masking of prophage and regions of recombination, cumulative genome analysis compared to a three-month sliding-window, and the comparative effects each of these had when applying a SNP threshold for inferring likely transmission ([≤]15 SNPs for S. aureus, [≤]25 for other species). FindingsAcross the species, using a reference genome of the same sequence type provided a greater degree of pairwise SNP resolution, compared to species and outgroup-reference alignments that typically resulted in inflated SNP distances and the possibility of missed transmission events. Omitting prophage regions had minimal impacts, however, omitting recombination regions a highly variable effect, often inflating the number of closely related pairs. Estimating pairwise SNP distances was more consistent using a sliding-window than a cumulative approach. InterpretationThe use of a closely-related reference genome, without masking of prophage or recombination regions, and a sliding-window for isolate inclusion is best for accurate and consistent MDRO transmission inference. The increased stability and resolution provided by these approaches means SNP thresholds for putative transmission inference can be more reliably applied among diverse MDROs. FundingThis work was supported by the Melbourne Genomics Health Alliance (funded by the State Government of Victoria, Department of Health and Human Services, and the ten member organizations); an National Health and Medical Research Council (Australia) Partnership grant (GNT1149991) and individual grants from National Health and Medical Research Council (Australia) to NLS (GNT1093468), JCK (GNT1008549) and BPH (GNT1105905).

genomics↗

bioRxiv2019

Functional genomics reveals extensive diversity in Staphylococcus epidermidis restriction modification systems compared to Staphylococcus aureus.

Staphylococcus epidermidis is a significant opportunistic pathogen of humans. Molecular studies in this species have been hampered by the presence of restriction-modification (RM) systems that limit introduction of foreign DNA. Here we establish the complete genomes and methylomes for seven clinically significant, genetically diverse S. epidermidis isolates and perform the first systematic genomic analyses of the type I RM systems within both S. epidermidis and Staphylococcus aureus. Our analyses revealed marked differences in the gene arrangement, chromosomal location and movement of type I RM systems between the two species. Unlike S. aureus, S. epidermidis type I RM systems demonstrate extensive diversity even within a single genetic lineage. This is contrary to current assumptions and has important implications for approaching the genetic manipulation of S. epidermidis. Using Escherichia coli plasmid artificial modification (PAM) to express S. epidermidis hsdMS, we readily overcame restriction barriers in S. epidermidis, and achieved transformation efficiencies equivalent to those of modification deficient mutants. With these functional experiments we demonstrate how genomic data can be used to predict both the functionality of type I RM systems and the potential for a strain to be transformation proficient. We outline an efficient approach for the genetic manipulation of S. epidermidis from diverse genetic backgrounds, including those that have hitherto been intractable. Additionally, we identified S. epidermidis BPH0736, a naturally restriction defective, clinically significant, multidrug-resistant ST2 isolate as an ideal candidate for molecular studies.\n\nImportanceStaphylococcus epidermidis is a major cause of hospital-acquired infections, especially those related to implanted medical devices. Understanding how S. epidermidis causes disease and devising ways to combat these infections has been hindered by an inability to genetically manipulate \"hospital-adapted\" strains that cause clinical disease. Here we provide the first comprehensive analyses of the mechanisms whereby S. epidermidis resists the uptake of foreign DNA and demonstrate that these are distinct from those described for S. aureus. Until now it had been assumed that these are the same. Using these insights, we demonstrate an efficient approach for the genetic manipulation of S. epidermidis to enable the study of clinically relevant isolates for the first time.

microbiology↗