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Pathogen genomics has increasingly been integrated into infectious disease surveillance, outbreak detection, and response globally. However, formal evaluation of pathogen genomic surveillance systems has been a major gap. In Australia, the AusTrakka platform was established and deployed nationally to address barriers to genomic data sharing across jurisdictions, enhance interoperability and usability, and improve governance of public health genomic data. Here we present our evaluation of AusTrakka and examine how its utilisation and impact shifted throughout the COVID-19 pandemic. We utilised the US Centers for Disease Control (CDC) Updated Guidelines for Evaluating Public Health Surveillance Systems to guide assessment of the AusTrakka platform. The evaluation used a mixed-methods approach consisting of a quantitative analysis of AusTrakka utilisation data throughout the COVID-19 pandemic and a qualitative component comprised key informant interviews and analysis of investigation reports produced by the AusTrakka National Analysis Team. Quantitative and qualitative data were collected concurrently between June 2020 and October 2022. Semi-structured individual and group interviews were held with key informants (n = 63) representing all jurisdictions across Australia and New Zealand. These included individuals representing public health laboratories and health departments, infectious disease physicians, genomic epidemiologists, and bioinformaticians. AusTrakka users reported that the platform had a very high degree of usefulness as a centralised platform to enable sharing sequence data across jurisdictions, facilitate multijurisdictional outbreak investigations, and clarify transmission chains. Acceptability was a key system that contributed to the usefulness of the platform, enhanced through collective design of data governance frameworks. Integration of epidemiological data with the pathogen genomic data was an ongoing challenge in data completeness. Robust evaluation of pathogen genomics surveillance systems is critical to identify contextual and system elements that impact the capacity of these systems to accomplish their objectives. Our findings demonstrate the importance of strong stakeholder engagement in developing data governance mechanisms for pathogen genomics in ultimately ensuring the capacity of surveillance systems to detect outbreaks and support public health utility, and reinforce the value of a nationally developed, purpose-built approach in Australia.
The clinical phenotype and pathogenic mechanism of 46,XY disorders of sex development (DSD) are complex, and several pathogenic variants are identified by next-generation sequencing. However, these variants currently require additional interpretation and validation prior to their application in 46,XY DSD diagnosis and clinical guidance. Here, we identified three genetic variants in two 46,XY DSD patients by whole exome sequencing screening and Sanger sequencing validation. The pathogenicity of three genetic variants was identified by in silico analysis and functional experiments. One patient carrying the reported pathogenic variant (c.319 C > T) of NR5A1 showed a phenotype of 46,XY complete gonadal dysgenesis, which was different from the reported 46,XY partial gonadal dysgenesis. These findings suggested that the variant (c.319 C > T) of NR5A1 contributes to the clinical phenotypic heterogeneity of 46,XY DSD. The other patient carried two genetic variants, among which the c.1252 C > T variant of NR5A1 produced truncated protein and lost the transcriptional activation of NR5A1 to the targeted genes. The other c.769G > A variant of DHX37 had no significant effect on the expression level and cellular localization of DHX37, and the downstream signaling pathway of DHX37. Moreover, the in silico and structural analysis identified the c.769G > A variant of DHX37 as a deleterious variant that may affect DHX37 function. According to the American College of Medical Genetics and Genomics guidelines and relevant literature reports, combined with the patient's clinical phenotype and pedigreed analysis, it is proposed that the likely pathogenic variant identified in this patient is the c.1252 C > T variant of NR5A1. Nonetheless, the potential pathogenicity of the DHX37 (c.769G > A) variant of this patient also merits further investigation and consideration. Our results have expanded the clinical phenotype spectrum and genetic diagnosis spectrum of 46,XY DSD, which will contribute to the accurate diagnosis and treatment guidance for 46,XY DSD patients and provide evidence-based genetic counseling for 46,XY DSD family fertility.
Genomic medicine increasingly depends on patients' willingness to share genomic and medical data. While data sharing supports advances in personalised care, it also raises ethical and social concerns related to privacy, trust and participation. Understanding these factors requires attention to patients' health literacy and their capacity to interpret and act upon genomic information. A systematic review was conducted according to PRISMA guidelines to identify empirical studies published between 2015 and 2025 that explored patients' understanding of genomic information and their willingness to share data. Searches were performed in PubMed, Web of Science and Scopus. Eligible studies included qualitative, quantitative and mixed-methods designs. Findings were synthesised thematically and Nutbeam's model of health literacy was used in the discussion to interpret the results. Fifteen studies met the inclusion criteria. Participants demonstrated basic understanding of genetic terms but limited knowledge of data infrastructures and governance. Trust was a central factor influencing willingness to share data, often compensating for limited genomic literacy. Moral and altruistic motives encouraged engagement, whereas financial considerations played a minor, context-dependent role. Data sharing in genomic medicine relies on more than factual knowledge. Strengthening health literacy through transparent, dialogue-based, and participatory approaches can promote informed, autonomous, and ethically responsible participation in genomic research.
Streptococcus periodonticum is a facultative anaerobic, Gram-positive coccus originally isolated from human periodontitis lesions and implicated in colorectal cancer pathogenesis. This study aimed to comprehensively characterize the genome of strain CRC221, isolated from human colorectal tumor tissue, to support future research on its potential role in tumorigenesis. Genomic DNA from strain CRC221 was sequenced using Illumina NovaSeq 6000 and PacBio platforms. The final assembly yielded a complete circular chromosome of 1,851,769 bp with 38.81% GC content. Structural annotation predicted 1,837 genes, comprising 1,707 protein-coding sequences (CDSs), 12 rRNAs, 59 tRNAs, 3 non-coding RNAs, and 56 pseudogenes. Functional annotation associated most CDSs with core bacterial survival pathways, particularly carbohydrate and amino acid metabolism. Notably, 94 genes were annotated as virulence factors, 68 as antibiotic resistance genes, and 319 as pathogen-host interaction factors. Comparative genomics revealed an ANI of 97.51% and a dDDH value of 71.8% against the reference S. periodonticum genome (GCA_003963555.1). Pan-genome analysis indicated an open genome architecture containing 199 conserved core genes. These genomic data provide a foundation for investigating the biological characteristics of intratumoral S. periodonticum and its potential relevance to colorectal cancer.
Cognitive dysfunction ("brain fog") is a commonly reported post-COVID-19 symptom. Leveraging data from five general population cohorts across four European countries (Estonia, Iceland, Norway, and Sweden), we assessed long-term prevalence of impaired subjective cognitive function among individuals diagnosed with COVID-19 by acute illness severity. The included cohorts consisted of adult participants recruited from March 2020 and followed with self-report measures of cognitive function and past COVID-19 infection (except one cohort consisting of clinically confirmed COVID-19 cases) through February 2023. In a cross-sectional analysis we contrasted the prevalence of impaired cognitive function among individuals with and without a COVID-19 diagnosis, overall and by illness severity up to 32 months post-diagnosis. We adjusted for age, gender, education, relationship status, binge drinking, body mass index, previous psychiatric diagnosis, number of chronic medical conditions, and response period. In a longitudinal analysis, we assessed potential changes in cognitive function scores before and after COVID-19 diagnosis. The study population consisted of 153,841 participants (71% women), with 31,359 (20.4%) reporting a positive COVID-19 test. Overall, a COVID-19 diagnosis was not statistically significantly associated with increased prevalence ratio (PR) of impaired cognitive function (PR 1.30 [95% CI: 0.98-1.71]). Individuals bedridden due to COVID-19 for 1-6 days (PR 1.38 [95% CI 0.96-1.99]) or ≥ 7 days (2.59 [1.55-4.33]) had higher prevalence of impaired cognitive function compared to those never diagnosed, while individuals never bedridden had a lower prevalence to those never diagnosed with COVID-19 (0.89 [0.80-1.00]). These findings were corroborated in the longitudinal analysis where a pre- to post diagnosis decline in cognitive function was observed among individuals bedridden due to COVID-19 (p < 0.0001). The data indicates that a severe COVID-19 acute illness course is associated with impaired cognitive function up to 18-32 months after COVID-19 diagnosis.
Accessory genome regions of plant pathogenic fungi, which are highly variable and consist of niche-adaptive genes, play a crucial role in shaping host-specific interactions but are notoriously difficult to assemble. Fusarium oxysporum causes some of the world’s most economically devasting diseases, however, understanding how it interacts with its host is hindered by challenges in assembly of accessory genome regions/chromosomes, even with long read sequencing technologies. F. oxysporum f. sp. lactucae (FOLac) races 1 and 4 possess highly similar core genomes but cause distinct virulence phenotypes on specific lettuce cultivars. The availability of fully assembled genomes for the two races is needed to advance our understanding of the genetic basis of pathogenicity and the evolutionary processes underlying the diversification of FOLac and other F. oxysporum pathogens. We developed an assembly workflow for generating gapless, telomere-to-telomere (T2T) complete genome assemblies for FOLac races 1 and 4. The T2T assemblies allowed for the identification of 16 chromosomes (5 accessory) and 20,616 predicted genes for race 1 and 19 chromosomes (8 accessory) and 20,292 predicted genes for race 4. Comparative genomics revealed major structural differences in their accessory genome regions, including genome rearrangement and large-scale chromosome duplication, with results suggesting transposable elements as the main drivers of those genomic changes. The analysis of Secreted in Xylem (SIX) effector gene profiles uncovered a similar presence/absence pattern among FOLac races 2–4, distinguishing them from race 1. Searches for genes unique to each race resulted in the identification of 687 race 1- and 536 race 4-specific genes. Assembly and genomic features comparing T2T to contig-level Illumina assemblies showed that 17–23% of genome sizes and ~ 10% of predicted genes were missing from Illumina assembly, mostly within accessory genome regions. T2T assemblies revealed large-scale differences in accessory genome structure and content between two otherwise highly similar pathogenic races. These differences provide a framework for understanding evolutionary processes that led to the diversification of pathogens within F. oxysporum on a fine evolutionary timescale, the identification of genes that may be responsible for host-pathogen interaction, and the identification of race-specific sequences useful for diagnostics. The online version contains supplementary material available at 10.1186/s12864-026-12744-5.
Hypervirulent Klebsiella pneumoniae (hvKp)-associated pyogenic liver abscess is most commonly linked to K1/K2 capsule serotypes and canonical lineages such as ST23, ST65, and ST86. Reports of hvKp outside these lineages remain rare but carry significant public health implications. We investigated an unusual case of liver abscess in an immunocompetent patient caused by hvKp sequence type 111 (ST111). Five isolates (KP1-KP5) recovered from a patient with pyogenic liver abscess were characterized by antimicrobial susceptibility testing, whole-genome sequencing, and pulsed-field gel electrophoresis. To investigate the contribution of the virulence plasmid to the host strain, CRISPR/Cas9-mediated plasmid curing was performed, followed by functional analyses including phenotypic characterization and a murine infection model. In addition, comparative genomic analyses were conducted to elucidate the epidemiological relationships and genetic determinants underlying hypervirulence. The five isolates recovered from the patient were genetically identical. Genomic analysis identified a 181 kb IncHI1B/IncFIB virulence plasmid encoding rmpADC and the salmochelin cluster (iroBCDN), but lacking iuc and rmpA2. Remarkably, the plasmid also carried the yersiniabactin locus (ybt), typically chromosomal in origin. Comparative genomics revealed that similar ST111 strains have been reported exclusively in China, suggesting clonal expansion of a previously unrecognized hvKp lineage. Functional assays demonstrated that plasmid curing abolished the hypermucoviscous phenotype, reduced capsule production, and completely attenuated virulence in murine models, confirming the plasmid as the principal driver of hypervirulence. Interestingly, plasmid loss enhanced biofilm formation and alleviated growth burden, indicating fitness trade-offs associated with virulence. This study describes a rare case of hvKp ST111 liver abscess and identifies a novel plasmid conferring hypervirulence. These findings broaden the recognized diversity of hvKp and highlight that non-canonical lineages can acquire potent virulence determinants capable of causing severe disease. Ongoing clinical and genomic surveillance is essential to detect and contain emerging hvKp clones before widespread dissemination.
Leishmaniasis is a vector-borne parasitic disease caused by Leishmania protozoa. The disease manifests in several clinical presentations including cutaneous, mucocutaneous, and visceral leishmaniasis. The diagnosis of leishmaniasis is complex and often requires a combination of clinical assessment, microscopy, serological tests, and molecular techniques especially in immunocompromised cases. However, traditional diagnostic methods have limitations in terms of accuracy, sensitivity, and the expertise required, leading to an urgent need for advanced, automated diagnostic tools. The aim of this research is to develop a deep learning-based decision-support system for the microscopic examination of tissue samples to support non-experts with the live diagnosis of the disease. Tissue samples from lesions were collected from patients diagnosed with cutaneous leishmaniasis in Libya and Palestine for the purpose of preparing microscopic slides. The samples were then visualized using a high-performance laboratory microscope and a mobile, low-cost device. The captured images were subsequently used to train the object detection framework YOLOv8 with the aim of identifying Leishmania parasites. A graphical user interface was developed for the application of the deep learning model, which enables real-time detection of the parasites using a microscope camera, as well as recognition from previously generated images and videos. The deep learning YOLOv8 framework was successfully trained using data generated by the advanced microscope and employed for the detection of Leishmania parasites. Subsequent finetuning with a combined set containing the aforementioned data and microscopic images generated with the low-cost device resulted in a considerable improvement in accuracy. The efficacy of the model was demonstrated through its successful operation on previously unseen data. Object detection yielded a mean average precision of 0.78 for the combined datasets. The evaluation process for determining the presence of parasites in an image resulted in 91% accuracy, 91% sensitivity, 90% specificity and 94% precision on the test data. Deep learning-based YOLOv8 achieved accurate Leishmania detection in tissue samples, enhancing decision-support for non-experts via real-time graphical user interface support. This innovation can simplify diagnostics by addressing traditional method limitations, enabling early, accessible leishmaniasis detection in resource-limited settings, and potentially inspiring similar applications in other parasitic diseases. Not applicable.
Human nephrogenesis is complete at 34-36 weeks gestation, with 60% of nephrons forming during the third trimester through lateral branch nephrogenesis (LBN). Currently, no mechanism exists for LBN as there are no late gestation human kidney transcriptional datasets. We hypothesized that an induced but dividing population of nephron progenitor cells (NPCs) would contribute to the amplification of nephrons in late gestation. We used the rhesus macaque, an established model of LBN, to help identify potential mechanisms. Single-cell RNA-sequencing (scRNA-Seq) was performed on cortically-enriched fetal rhesus kidneys (n = 9) from late second trimester and third trimester during LBN. This data was integrated with publicly available human scRNA-seq datasets from 8-18 weeks gestation kidneys (n = 8) using Harmony package. Differentially expressed genes and ligand-receptor interactions were assessed and validated using RNAScope™ on human and rhesus archival tissue. Label transfer of previously defined kidney cell populations was performed on scRNA-seq data from 64,782 rhesus cells, including 7,879 nephron progenitor cells (NPCs) identified based on marker gene expression. Pseudotime analyses identified a late gestation-specific lineage branch of induced NPC in rhesus that was not observed in mid-gestation humans. Differential expression analyses identified increased SFRP1, FZD4, and TLE2 and decreased FZD7, SHISA2, SHISA3, and TLE4 within the late-gestation rhesus NPC compared to mid-gestation human NPC and increased SEMA3D within the rhesus ureteric bud (UB) tip, suggesting a compositional shift in WNT and SEMA signaling components within the naive NPC population during LBN. The rhesus macaque uniquely enables molecular studies of late-gestation primate nephrogenesis. Our study suggests the hypothesis that a transitional state of self-renewing NPCs supported by compositional shifts in key pathways may underlie the switch from branching phase nephrogenesis to lateral branch nephrogenesis and support ongoing nephron formation in late gestation. However, it remains to be determined if these changes within the late gestation NPC are time-dependent or species-dependent.
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Biallelic DIAPH1 mutations are linked to hereditary microcephaly syndrome, yet the underlying pathogenic mechanism remains unelucidated. This study aimed to clarify how DIAPH1 biallelic mutations cause microcephaly and visual impairment, focusing on the gene's regulatory role in the Wnt/β-catenin signaling pathway. Whole exome sequencing was performed on a patient's peripheral blood to identify DIAPH1 mutations. A zebrafish model was established by microinjecting mutant human DIAPH1 cDNA into one-cell embryos (no zebrafish DIAPH1 homolog exists). Phenotypic analyses (morphology, neuronal axon growth, behavior) and quantitative real-time PCR for Wnt/β-catenin pathway genes were conducted. Data were mean ± SEM; statistical tests (Student's t-test, ANOVA, χ²) used GraphPad Prism 5.0 (P < 0.05, P < 0.0001 for significance). Compound heterozygous DIAPH1 mutations (c.1051 C > T, p.R351X; c.609delA, p.E203E fs*19) were found and associated with clinical symptoms. Mutant DIAPH1 zebrafish showed abnormal eye shape, shortened body length, axis defects, impaired motor axon growth, reduced locomotor activity, upregulated WNT8A, WNT9A, LRP5, LRP6, and downregulated AXIN1, AXIN2, β-CATENIN, indicating excessive Wnt/β-catenin pathway activation. DIAPH1 compound heterozygous mutations may trigger microcephaly and visual impairment by abnormally activating the Wnt/β-catenin pathway. The zebrafish model provides a reliable in vivo system for studying DIAPH1-related microcephaly, advancing understanding of hereditary primary microcephaly pathogenesis and potential therapeutic target exploration.
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Early and efficient management of bloodstream infections (BSIs) reduces the risk of complications and death. Therefore, it is crucial to identify antimicrobials with good activity against bacteria isolated from BSIs. This study aimed to determine the bacterial pathogens involved in BSIs, pooled antimicrobial resistance (AMR) rate, AMR phenotype rates, and the evolution of AMR over the years in West Africa. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA 2020) were used, and the protocol for this review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database with the registration identification number (CRD420251064773). Keywords were used to conduct a systematic literature review of electronic databases such as Google Scholar, African Journals Online, PubMed, ResearchGate, Embase, and Scopus. Data analyses were conducted using Stata/MP 17.0, and a random-effects model was used to estimate pooled estimates. Twenty-three research articles, including samples collected between 2003 and 2022, were selected for this study. The prevalence of BSIs was 13.1% (95% CI: 12.8-13.3) (6,864 blood culture-positive out of the 52,566 patients screened for BSIs). A total of 4,992 bacteria were isolated, including 3,219 Gram-negative bacteria (GNB) and 1,773 Gram-positive bacteria (GPB). The pooled AMR rates of 20 antimicrobials were obtained, and the highest were for ampicillin [73% (95% CI: 66, 80)] and trimethoprim-sulfamethoxazole [72% (95% CI: 63, 80)]. The lowest pooled AMR rates were observed for the carbapenems [10% (95% CI: 1, 25)] and clindamycin [15% (95% CI: 6, 27)]. GNB were more resistant to ampicillin (P = 0.003) and amoxicillin-clavulanate (P = 0.002) than GPB, and the pooled prevalence of multidrug-resistant bacteria (MDR) was 53% (95% CI: 30, 75). There were significant upward trends for ciprofloxacin (P = 0.007), carbapenems (P = 0.010), ofloxacin (P = 0.013), and third-generation cephalosporins (3GCs) (P = 0.032) when comparing the pooled AMR rates of 2004-2013 to those of 2014-2022. Carbapenems and clindamycin showed relatively low resistance rates, but high study heterogeneity and limited data warrant caution in their empiric use. Overall, the findings highlight the need to prioritize local antibiograms and strengthen antimicrobial stewardship to address rising AMR in West Africa. Not applicable.
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