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A Practical Approach to High-Throughput and Accurate Mapping-by-Sequencing in Arabidopsis.

Forward-directed genetic screens are extremely powerful in identifying novel genes involved in a specific biological process, including various chromatin regulatory pathways. However, the traditional ways of genetic mapping are time- and cost-demanding. Recently, the whole process was revolutionized by the development of mapping-by-sequencing (MBS) protocols. In MBS, the causal mutations and their positions within genes are identified directly by whole-genome sequencing and bioinformatics analysis of the bulk of mutant plants selected based on the mutant phenotype from a segregating population. MBS increases precision and economizes the mapping. Here, we describe a general protocol and provide practical tips on how to proceed with the mapping-by-sequencing on the example of Arabidopsis forward-directed genetic screen designed to identify mutants sensitive to a specific type of DNA damage. The described protocol is generally applicable to a wide range of genetic screens in various inbreeding species with a reference genome sequence.

Arabidopsis

Genome mining for new enediyne antibiotics.

Enediyne antibiotics epitomize nature's chemical creativity. They contain intricate molecular architectures that are coupled with potent biological activities involving double-stranded DNA scission. The recent explosion in microbial genome sequences has revealed a large reservoir of novel enediynes. However, while hundreds of enediyne biosynthetic gene clusters (BGCs) can be detected, less than two dozen natural products have been characterized to date as many clusters remain silent or sparingly expressed under standard laboratory growth conditions. This review focuses on four distinct strategies, which have recently enabled discoveries of novel enediynes: phenotypic screening from rare sources, biosynthetic manipulation, genomic signature-based PCR screening, and DNA-cleavage assays coupled with activation of silent BGCs via high-throughput elicitor screening. With an abundance of enediyne BGCs and emerging approaches for accessing them, new enediyne natural products and further insights into their biogenesis are imminent.

Enediynes

Deep clinical and genetic analysis of 17p13.3 region: 38 pediatric patients diagnosed using next-generation sequencing and literature review.

BACKGROUND: Chromosome 17p13.3 is a region of genomic instability associated with different neurodevelopmental diseases. The malformation spectrum of 17p13.3 microdeletions ranges from an isolated lissencephaly sequence to Miller-Dieker syndrome, while 17p13.3 microduplications result in autism, learning disabilities, microcephaly and other brain malformations. This study aims to provide a more comprehensive delineation of the clinical and genetic characteristics associated with 17p13.3 alterations. METHODS: We retrospectively analyzed the next-generation sequencing (NGS) data of more than 40 thousand patients from January 2016 to December 2021 and identified 38 pediatric patients with copy-number variations (CNVs) or single-nucleotide variations (SNVs) in 17p13.3 region. Published patients with CNVs in the 17p13.3 region were also collected and we performed a Chi-square test to compare the phenotype spectrum of microdeletions and microduplications. RESULTS: Among the 27 CNV patients, 20 patients with microdeletions and 7 patients with microduplications were found. PAFAH1B1 was the most frequently deleted gene and CRK was the most frequently duplicated gene. Affected genes in 11 SNV patients included PAFAH1B1 and PRPF8. Developmental delay was the most common abnormality detected in the 38 patients (29/38, 76.3%). Of note, Case 10 presented omphalocele and Case 23 presented scoliosis, webbed neck and bone cyst, all of which were unusual variant phenotypes in this region. The Chi-square test revealed that epilepsy, lissencephaly and short stature were statistically significant with microdeletions, while behavioral abnormalities and hand and foot abnormalities were significant with microduplications (p&#x2009;<&#x2009;0.01). CONCLUSIONS: While PAFAH1B1, YWHAE and CRK are associated with major phenotypes of 17p13.3, RTN4RL1 may be involved in white matter changes and HIC1 might contribute to the occurrence of omphalocele. This study provided a comprehensive understanding of genetic information and phenotype spectrum of the 17p13.3 region.

Humans

Identification of transcriptome SNPs between Xiphophorus lines and species for assessing allele specific gene expression within F&#x2081; interspecies hybrids.

Variations in gene expression are essential for the evolution of novel phenotypes and for speciation. Studying allelic specific gene expression (ASGE) within interspecies hybrids provides a unique opportunity to reveal underlying mechanisms of genetic variation. Using Xiphophorus interspecies hybrid fishes and high-throughput next generation sequencing technology, we were able to assess variations between two closely related vertebrate species, Xiphophorus maculatus and Xiphophorus couchianus, and their F(1) interspecies hybrids. We constructed transcriptome-wide SNP polymorphism sets between two highly inbred X. maculatus lines (JP 163 A and B), and between X. maculatus and a second species, X. couchianus. The X. maculatus JP 163 A and B parental lines have been separated in the laboratory for &#x2248;70 years and we were able to identify SNPs at a resolution of 1 SNP per 49 kb of transcriptome. In contrast, SNP polymorphisms between X. couchianus and X. maculatus species, which diverged &#x2248;5-10 million years ago, were identified about every 700 bp. Using 6524 transcripts with identified SNPs between the two parental species (X. maculatus and X. couchianus), we mapped RNA-seq reads to determine ASGE within F(1) interspecies hybrids. We developed an in silico X. couchianus transcriptome by replacing 90,788 SNP bases for X. maculatus transcriptome with the consensus X. couchianus SNP bases and provide evidence that this procedure overcomes read mapping biases. Employment of the in silico reference transcriptome and tolerating 5 mismatches during read mapping allow direct assessment of ASGE in the F(1) interspecies hybrids. Overall, these results show that Xiphophorus is a tractable vertebrate experimental model to investigate how genetic variations that occur during speciation may affect gene interactions and the regulation of gene expression.

Alleles

Human Systems Immunology in the Omics Era: Challenges, Methods, and Emerging Directions.

The human immune system is a highly complex, dynamic, and heterogeneous network shaped by genetic, environmental, and temporal influences. Advances in high-throughput omics technologies have transformed our ability to study this complexity directly and comprehensively in human cohorts. These developments have positioned systems immunology as a powerful framework for investigating coordinated immune responses, identifying regulatory mechanisms, and linking molecular patterns to clinical phenotypes. However, the analytical challenges inherent to large-scale, multimodal datasets-including batch effects, small sample sizes, high dimensionality, and substantial interindividual heterogeneity-require rigorous study design, robust statistical modeling, and thoughtful data analysis strategies. In this review, we summarize key technological foundations enabling modern human systems immunology, outline common analytical pitfalls and effective mitigation approaches, discuss data integration concepts, and highlight emerging opportunities in the field. Together, these technological and analytical advances are redefining how immune function is measured and interpreted in real-world human biology and hold significant promise for enhancing mechanistic insight, biomarker discovery, and precision medicine across immunological diseases and interventions.

Humans

Uniform processing and analysis of IGVF massively parallel reporter assay data with MPRAsnakeflow.

As researchers and clinicians seek to identify human genomic alterations relevant to traits and disorders, identifying and aggregating evidence providing mechanistic support for associations between alterations and phenotypes remains challenging. In particular, the study of noncoding genomic variation remains a major challenge because of the lack of accurate functional annotation for activity in a given context and across alleles. Experimental evidence is critical for prioritizing and interpreting functional effects of genetic alterations. Massively parallel reporter assays (MPRAs) have emerged as a powerful high-throughput approach, enabling quantification of regulatory element activity and allelic effects, as well as systematic dissection of gene regulatory logic and variant effects across different contexts. However, the diversity of MPRA designs, lack of standardized formats, and many potential processing parameters hamper data integration, reproducibility, and meta-analyses across studies. To address these challenges, the Impact of Genomic Variation on Function (IGVF) Consortium established an MPRA focus group to develop community standards, including harmonized file formats, and robust analysis pipelines for a wide range of library types and experimental designs. Here, we present these formats and comprehensive computational tools, MPRAlib and MPRAsnakeflow, for uniform processing from raw sequencing reads to counts, processing, and visualization. Using diverse MPRA data sets, we investigated technical variability sources including barcode sequence bias, outlier barcodes, and delivery method (episomal vs. lentiviral). Our results establish best practices for MPRA data generation and analysis, facilitating robust, reproducible research and large-scale integration. The presented tools and standards are publicly available, providing a foundation for future collaborative efforts in regulatory genomics.

Humans

A statistical simulation model to guide the choices of analytical methods in arrayed CRISPR screen experiments.

An arrayed CRISPR screen is a high-throughput functional genomic screening method, which typically uses 384 well plates and has different gene knockouts in different wells. Despite various computational workflows, there is currently no systematic way to find what is a good workflow for arrayed CRISPR screening data analysis. To guide this choice, we developed a statistical simulation model that mimics the data generating process of arrayed CRISPR screening experiments. Our model is flexible and can simulate effects on phenotypic readouts of various experimental factors, such as the effect size of gene editing, as well as biological and technical variations. With two examples, we showed that the simulation model can assist making principled choice of normalization and hit calling method for the arrayed CRISPR data analysis. This simulation model is implemented in an R package and can be downloaded from Github.

CRISPR-Cas Systems

Zebrafish as a versatile model in biomedical research, from disease modeling to regenerative medicine: a review.

Zebrafish are an effective animal model widely utilized in biomedical research. They are known for their rapid reproduction and substantial genetic similarity to humans. Their transparent embryos directly enable the visualization of developmental processes and disease progression. This makes zebrafish invaluable for studying a broad range of human diseases, including cancer, cardiovascular disorders, and neurodegenerative conditions. Compared with other vertebrate models, zebrafish offer several advantages, including ease of genome editing, cost-effective maintenance, and suitability for high-throughput drug screening. Recent advancements have expanded the use of zebrafish in disease modeling and regenerative medicine, providing deeper insights into the genetic and cellular mechanisms underlying human pathologies. Zebrafish provide a robust platform for evaluating the safety, efficacy, and regenerative potential of both natural and synthetic biomaterials, including hydroxyapatite, bioactive glass nanoparticles, and bioceramics. This capability facilitates the creation of artificial tissues that closely resemble native structures. Additionally, integrating artificial intelligence technologies has improved automated data analysis and phenotyping in zebrafish studies, enhancing both accuracy and throughput. This review highlights current applications of zebrafish in disease modeling, drug discovery, regenerative medicine, and biomaterial assessment, emphasizing their evolving role as a versatile preclinical platform supported by advanced genetic and computational tools.

Animals

Association Between cnm-Positive Streptococci and Cerebral Small Vessel Disease: Insights From Oral Health and Microbiome Status.

INTRODUCTION AND AIMS: Cerebral small vessel disease (CSVD) is associated with various severe neurological outcomes; while oral cnm-positive streptococci are suggested to be involved in cerebrovascular lesions, the specific associative features between these bacteria and CSVD have not yet been systematically investigated. This study aims to investigate the prevalence of cnm-positive streptococci in patients with CSVD and explore the correlation between infection and CSVD severity. By integrating oral health indices and microbiome sequencing, we evaluate the oral hygiene status and microbial dysbiosis characteristics of cnm-positive streptococci carriers. Furthermore, cnm-positive streptococci derived from CSVD patients will be isolated, identified, and subjected to whole-genome sequencing to provide a foundation for future research. METHODS: To explore cnm-positive streptococci prevalence and its association with CSVD, we conducted a case-control study comparing their oral detection rates between healthy controls and CSVD patients. We also performed 16S rRNA gene high-throughput sequencing of oral plaque microbiota and assessed oral health, including the simplified oral hygiene index (OHI-S), the decayed, missing, and filled teeth (DMFT) index, oral hygiene practices, gingival status, and saliva scores. RESULTS: cnm-positive streptococci were more prevalent in CSVD patients, correlating with higher OHI-S and microbial dysbiosis. Multivariable regression models (adjusted for demographic/vascular risk factors) linked cnm positivity to periventricular hyperintensities (PVH), deep white matter hyperintensities (DWMH), Fazekas score, and total CSVD burden (not cerebral microbleeds (CMBs)/lacunes). CONCLUSION: Oral cnm-positive streptococci are independently associated with CSVD phenotypes, particularly those characterized by white matter injury. These findings presents a potential oral-cerebrovascular interaction and imply that managing specific virulent oral strains may be a noteworthy consideration in future clinical research.

Humans

Missense variants pathogenicity annotation from homologous proteins.

MOTIVATION: High-throughput DNA sequencing has revealed millions of single nucleotide variants (SNVs) in the human genome, with a small fraction linked to disease. The effect of missense variants, which alter the protein sequence, is particularly challenging to interpret due to the scarcity of clinical annotations and experimental information. While using conservation and structural information, current prediction tools still struggle to predict variant pathogenicity. In this study, we explored the pathogenicity of homologous missense variants-variants in equivalent positions across homologous proteins-focusing on proteins involved in autosomal dominant diseases. RESULTS: Our analysis of 2976 pathogenic and 17&#xa0;555 non-pathogenic homologous variants demonstrated that pathogenicity can be extrapolated with 95% accuracy within a family, or up to 98% for closer homologs. Remarkably, the evaluation of 27 commonly used mutation predictor methods revealed that they were not fully capturing this biological feature. To facilitate the exploration of homologous variants, we created HomolVar, a web server that computationally predicts the pathogenesis of missense variants using annotations from homologous variants, freely available at https://rarevariants.org/HomolVar. Overall, these findings and the accompanying tool offer a robust method for predicting the pathogenicity of unannotated variants, enhancing genotype-phenotype correlations, and contributing to diagnosing rare genetic disorders. AVAILABILITY AND IMPLEMENTATION: HomolVar is freely available at https://rarevariants.org/HomolVar.

Mutation, Missense

DURABLE: A Workflow for Determining Corrosion-Driving and Protective Microbial Mechanisms.

Microbiologically influenced corrosion (MIC) threatens global infrastructure, causing billions of dollars in annual losses. Its persistence stems from unresolved mechanisms&#x2500;particularly the metabolites produced by microorganisms that drive or inhibit corrosion&#x2500;and the microbial community structures. Progress has been hindered by the absence of systematic workflows to rapidly and accurately identify MIC-relevant microorganisms and their functions. Here, we present DURABLE (Detection of Unique Corrosion Resistant or Accelerating Biologics in a Laboratory Environment), a pipeline that couples high-throughput microbial screening with genomic and metabolic workflows. We applied the DURABLE workflow to six diesel tank samples and revealed fuel-dependent microbial community structures, which showed greater diversity and evenness in bacterial communities than their fungal counterparts. The workflow used carbon steel beads to rapidly screen over 80 bacterial isolates for corrosive activity, reducing assay time to approximately 2 days compared with the conventional 30-day metal coupon test. More than 40 isolates were identified as corrosive. Further testing using mass spectrometry analysis revealed corrosion-associated metabolites, which were further validated using electrochemical assays. Thus, DURABLE achieved a &#x223c;15-fold increase in screening speed and provided a scalable and mechanistic framework for dissecting MIC dynamics. We expect this advance will enable the development of precision mitigation strategies in hydrocarbon fuel infrastructure.

Bacteria

Identification of intragenic variants in pediatric patients with intellectual disability in Peru.

BACKGROUND: Intellectual disability in Latin America can reach a frequency of 12% of the population, these may include nutritional deficiencies, exposure to toxic or infectious agents, and the lack of universal neonatal screening programs. In 90% of patients with intellectual disability, the etiology can be attributed to variants in the genome. OBJECTIVE: to determine intragenic variants in patients with intellectual disability between 5 and 18 years old at Instituto Nacional de Salud del Ni&#xf1;o. METHODS: It is a descriptive cross-sectional study with convenience sampling. A total of 124 children diagnosed with intellectual disability were selected based on psychological test results and availability for whole exome sequencing. In addition, a chromosomal analysis of 6.55&#xa0;M was performed on ten patients with a negative result in sequencing. Relative and absolute frequencies and measures of central tendency and dispersion were determined according to their nature. In addition, multiple linear regression and Poisson regression were used to determine the association between some clinical characteristics and the probability of occurrence in patients with positive results. RESULTS: The median age of the patients was 6.3 (IQR&#x2009;=&#x2009;5.95), males accounted for 57.3%, and 91.9% of the cases had mild intellectual disability. Exome sequencing determined the etiology in 30.6% of patients with intellectual disability, of which 52.6% were autosomal dominant inheritance. The most frequent genes found were MECP2, STXBP1 and LAMA2. A broad genotype-phenotype correlation was identified, highlighting the genetic heterogeneity of intellectual disability in this population. The presence of dermatologic lesions, dystonia, peripheral neurological disorders, and fourth finger flexion limitation were observed more frequently in patients with intellectual disability with "positive results". CONCLUSIONS: This study shows that one-third of patients with intellectual disability exhibit intragenic variants, highlighting the importance of genetic analysis for accurate diagnosis. The identification of genes such as MECP2, STXBP1, and LAMA2 underscores the genetic heterogeneity of intellectual disability in the studied population. These findings emphasize the need for genetic testing in clinical management and the implementation of early detection programs in Peru.

Humans

The diagnostic potential of combined quantitative polymerase chain reaction and next-generation sequencing using the same primers for periprosthetic joint infection.

Next-generation sequencing (NGS) enables the detection of specific pathogens unidentifiable by conventional cultures, but its application in orthopedics remains inconsistent due to background contamination and irreproducible findings. This study evaluated the diagnostic performance of a novel workflow combining broad-range 16S rRNA gene quantitative PCR (qPCR) screening with downstream NGS, focusing on bacterial biomass thresholds. The qPCR assay demonstrated excellent intrarater reliability, with an intraclass correlation coefficient (ICC) of 0.961 (95% confidence interval, 0.881 to 0.997). Based on serially diluted positive controls, a quantitative threshold of 10&#x2075; CFU/mL was established as the minimum concentration required for the consistent detection of fastidious taxa, such as Escherichia coli. When evaluated against conventional cultures using 95 sonicate fluid and 276 pre/intraoperative tissue samples, the qPCR assay achieved a sensitivity of 80% and a specificity of 72%. Subsequent NGS sequencing of 26 clinical samples and 9 controls showed concordance in 4 of 6 culture-positive infected cases with NGS taxonomy, whereas the remaining discrepancies were likely attributable to culture-based phenotypic misidentification. Notably, among the qPCR-positive cases, three were culture-negative, including two hip prosthesis loosening cases exhibiting polymicrobial profiles, and one post-traumatic osteoarthritis case harboring low-level Staphylococcus. Crucially, this post-traumatic patient developed delayed periprosthetic joint infection (PJI) 2 years post-surgery, with cultures identifying Staphylococcus previously detected by the initial NGS analysis. Integrating qPCR screening with targeted NGS effectively refines pathogen identification, filters environmental artifacts, and overcomes the diagnostic limitations of culture-negative infections in orthopedic practice.IMPORTANCENext-generation sequencing (NGS) enables the detection of specific pathogens in clinical samples that are not identifiable by conventional methods. However, NGS applications in orthopedics have not been quantitatively evaluated, and findings have been inconsistent owing to contaminants and the presence of non-credible causative organisms. These factors primarily stem from the failure to evaluate low-biomass samples and the absence of proper controls, such as negative controls or mock community DNA samples. This study demonstrates that interpreting results from low-biomass samples requires careful consideration because NGS relies on relative bacterial abundances; distinguishing likely pathogens from contaminants is particularly challenging when bacterial loads are low. We demonstrated that combining NGS with quantitative PCR (qPCR) and applying a Cq cutoff can reduce false positives.

Humans

Next-generation newborn screening: feasibility of combined genetic and biochemical testing for 95 treatable inherited metabolic disorders.

INTRODUCTION: Next-generation sequencing (NGS) is gaining attention in newborn screening (NBS) for its ability to detect treatable genetic disorders, especially those without a biochemical footprint. However, NGS-NBS requires interpreting variants without phenotype information or family trio analysis. Biochemical tests, preferably in dried blood spots (DBS), are therefore useful to confirm the pathogenicity of variants identified by NGS-NBS and increase its specificity and sensitivity. OBJECTIVES: We aimed to explore the potential of combined genetic-biochemical testing for 95 treatable Inherited Metabolic Disorders (IMD) considered eligible for NGS-NBS (100 genes) previously identified by our research group. METHODS: We reviewed the Collaborative Laboratory Integrated Reports (CLIR) and carried out systematic literature reviews in PubMed and Embase to identify biochemical tests for 95 IMD. Biochemical tests conducted on DBS were differentiated from tests that require referral. RESULTS: We identified DBS-biochemical tests for 72 of the 95 IMD (77/100 genes). DBS-based biochemical tests for 55 IMD (60 genes) are already implemented in NBS. For the other 23 IMD, biochemical tests in non-DBS specimens are reported, although some are less sensitive when measured at neonatal age in presymptomatic infants. CONCLUSION: We present a comprehensive overview of current biochemical tests for 95 IMD. These tests can be used to confirm inconclusive NGS-NBS results, and combined genetic-biochemical testing is expected to improve both the negative and positive predictive values of NBS programs.

Humans

Obtaining a Diagnostic Yield via Scan findings prior to the introduction of SEquencing retrospectivelY (ODYSSEY): a cohort study.

OBJECTIVE: To determine the retrospective yield of prenatal exome sequencing (PES) by establishing the proportion of children with a postnatal monogenic diagnosis that could have been diagnosed prenatally if PES had been available. METHODS: The study cohort comprised a sample of children in Northern Ireland, born between January 2010 and January 2018 (predating routine availability of PES), who received a monogenic diagnosis postnatally via next generation sequencing as part of either of two UK-wide studies (the 100&#x2009;000 Genomes Project (2015-2018) or the Deciphering Developmental Disorders study (2011-2015)). Clinical data were collected retrospectively and correlated with the current UK National Health Service PES protocol, including the phenotypic eligibility criteria for PES and the associated fetal anomalies gene panel. Cases were considered retrospective diagnoses if the fetal phenotype would have been eligible for PES and the diagnostic gene was included on the test panel, meaning prenatal diagnosis in this current era could have been feasible. RESULTS: Of 101 children, 17.8% (95%&#x2009;CI, 10.3-25.3%) had both an eligible fetal structural anomaly (FSA) (i.e. high-risk FSA) and a diagnostic gene on the associated test panel, meaning that they could have been diagnosed prenatally in the current clinical landscape. The median length of the diagnostic odyssey for this subgroup of children was 3.7&#x2009;years (1354&#x2009;(range, 822-2450)&#x2009;days). Moreover, 58.4% (n&#x2009;=&#x2009;59) of cases had no anomalies detected prenatally and 19.8% (n&#x2009;=&#x2009;20) had a FSA that would not meet the eligibility criteria for PES (low-risk FSA). Although these cases would have been ineligible for PES under the current clinical pathway, 89.9% (n&#x2009;=&#x2009;71/79) were affected by severe or profound syndromes. Postnatally, the most common functional anomalies were neurodevelopmental delay/intellectual disability and/or behavioral abnormality, which were observed in 80.2% (n&#x2009;=&#x2009;81) of the included children. However, 80.2% (n&#x2009;=&#x2009;65/81) of these affected children did not present with fetal anomalies eligible for PES. CONCLUSIONS: Almost one-fifth of children with a monogenic condition included in this study could have received a diagnosis via modern PES, avoiding a diagnostic odyssey lasting almost 4&#x2009;years. However, despite having a monogenic condition, over half of the children did not present with any structural anomalies in utero. This demonstrates the degree to which fetal imaging is limited in its ability to reassure parents of the absence of a fetal genetic syndrome. &#xa9; 2026 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Humans

Integrating histology and spatial transcriptomics via multimodal transformers and contrastive representation learning for accurate gene expression prediction.

Predicting spatial gene expression from Histological images is a fundamental task in understanding tissue organization and molecular phenotypes. However, existing methods often rely on single-model representations or lack effective alignment between image and transcriptomic features. To address these limitations, we propose a unified multimodal learning framework that integrates histological imaging and spatial transcriptomics through a shared latent representation space. Specifically, histological H&E images are encoded by a ResNet50-based convolutional stem and a MobileViT Transformer backbone to extract hierarchical visual representations. Both modalities are projected into a shared latent space via linear-GELU-dropout transformation blocks, enabling cross-modal alignment through a contrastive learning objective that maximizes agreement between the corresponding image and the spot embeddings. Experimental results on the 10x Genomics Visium dataset of human liver tissue demonstrate that MViTGene achieves significantly higher prediction accuracy than existing methods across multiple gene subsets, with improvements of 20%, 33%, and 12% in predicting marker genes, highly expressed genes, and highly variable genes, respectively. The significant improvement in relevance indicates that the model can more accurately capture the true correspondence between tissue morphology and gene expression, therefore enabling more reliable biological interpretation. It provides a computational tool for high-throughput spatial gene expression prediction that balances performance and interpretability.

Humans

Characterisation of Bordetella pertussis virulence and macrolide resistance in Australia by targeted culture-independent sequencing: a genomic epidemiology study.

BACKGROUND: Bordetella pertussis continues to circulate globally despite widespread vaccination, with a notable epidemic in 2024. Its resurgence is confounded by the emergence of pertactin-deficient, macrolide-resistant B pertussis strains in Asia and Europe, which are under-recognised by conventional diagnostics. We aimed to apply targeted culture-independent next-generation sequencing (tNGS) of respiratory specimens to improve global B pertussis diagnostic capability and genomic surveillance. METHODS: We did a nationwide genomic epidemiology study of B pertussis RT-PCR-positive respiratory specimens that were retrospectively and prospectively collected by diagnostic and public health laboratories in six of seven states and territories of Australia. Specimens underwent tNGS and macrolide-resistant B pertussis-specific PCR, and an opportunistic subset from New South Wales and Queensland were cultured for confirmatory susceptibility testing and whole-genome sequencing. Sequencing data were analysed for genome recovery, virulence profiles, and macrolide resistance mutations, and were compared with international macrolide-resistant B pertussis genomes and ancestral Australian genomes. The performance of the tNGS approach was assessed with logistic regression relative to RT-PCR cycle threshold values, and sensitivity and specificity values were calculated. FINDINGS: 255 respiratory specimens positive for B pertussis were included in the study. 64 (25%) were retrospectively collected between Jan 12, 2012, and Dec 31, 2023, and 191 (75%) were prospectively collected between Jan 1 and Oct 28, 2024. Of these 255 specimens, 148 (58%) yielded near-complete B pertussis genomes through tNGS. Seven co-circulating lineages of B pertussis were documented, including two associated with macrolide-resistance. Eight epidemiologically unrelated and geographically dispersed cases of macrolide-resistant B pertussis with a 23S rRNA 2037A&#x2192;G mutation were identified by tNGS and confirmed by whole-genome sequencing. Three of these were further validated by phenotypic testing. The estimated prevalence of macrolide resistance among Australian cases positive for B pertussis was 4% (eight of 188). INTERPRETATION: tNGS can recover near-complete B pertussis genomes directly from clinical specimens, enabling identification of macrolide resistance mutations and high-resolution phylogenetic analysis. These findings show that tNGS complements PCR-based surveillance by providing genome-wide assessment of resistance, virulence, and genomic diversity in a single workflow. FUNDING: NSW Health Prevention Research Support Program.

Macrolides

Performance of the IR Biotyper, Nanopore, and Illumina sequencing to discriminate Escherichia coli strains originating from poultry.

UNLABELLED: Escherichia coli is a highly diverse bacterial species that includes avian pathogenic E. coli (APEC), one of the most prevalent causative agents of disease in poultry worldwide. Rapid and accurate discrimination of E. coli strains is essential for outbreak management, antimicrobial resistance surveillance, and vaccine development. In this study, we compared the performance of Fourier Transform Infrared (FTIR) spectroscopy using the IR Biotyper system with Nanopore and Illumina whole-genome sequencing (WGS) for typing 200 E. coli isolates, originating from four poultry rearing farms in the Netherlands. From each farm, we sampled 10 one-day-old meat type rearing chicks, and from every chick, we isolated 5 E. coli strains. FTIR clustering showed strong concordance with WGS-based classifications, particularly serotyping and core-genome similarity determined by PopPUNK analysis (Adjusted Rand Index 0.75-0.92). While Nanopore and Illumina sequencing provided the highest genetic resolution, FTIR offered a faster (max 6 vs 12-28 days for 200 isolates) and more cost-effective alternative for assessing clonality. Across all methods, multiple strains were detected per farm, whereas most birds carried a single dominant E. coli strain. Our findings demonstrate that FTIR provides a reliable and scalable phenotypic method for rapid strain discrimination in E. coli, complementing WGS in diagnostic, surveillance, and epidemiological settings where speed and throughput are critical. IMPORTANCE: Escherichia coli is a major pathogen in poultry and a potential zoonotic risk for humans. Rapid and accurate discrimination of avian pathogenic E. coli (APEC) strains is critical for outbreak management, antimicrobial resistance surveillance, and the design of effective autogenous vaccines. In this study, we compared Fourier Transform Infrared (FTIR) spectroscopy with Nanopore and Illumina whole-genome sequencing for strain typing of E. coli isolates originating from poultry. The results show that FTIR provides comparable clustering accuracy to genomic approaches at a fraction of the time and costs. This work demonstrates that FTIR can serve as a practical, high-throughput alternative for routine monitoring of E. coli in veterinary diagnostics and food safety of poultry meat, enabling faster decision-making and more targeted interventions across the poultry production chain.

Animals