Biology subjects

Iqbal, Z.

Publications and source records attributed to Iqbal, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Flex-It: A global standardised genotyping framework for Shigella flexneri

Shigella flexneri is the leading causative agent of shigellosis globally. The public health threat posed by S. flexneri is compounded by its emergence as a sexually transmissible infection, importance of international travel in driving dissemination, and the increasing prevalence of antimicrobial resistance (AMR). A rapid and robust computational method is needed to enhance genomic surveillance and systematically explore features of the population structure of this WHO priority pathogen, which is scalable and readily implementable across jurisdictions, particularly as vaccine development efforts are underway. Here, we present Flex-It, a genomic framework and genotyping scheme implemented in Mykrobe for S. flexneri serotypes 1-5, X & Y, compatible with previous approaches used to describe S. flexneris population structure. To develop Flex-It, we curated a retrospective dataset of 5,819 publicly available S. flexneri genomes. We characterised the global population structure for S. flexneri, exploring geographical and temporal traits, and showed the granular diversity of AMR and serotype profiles. We applied Flex-It to >13,000 genomes routinely generated by public health laboratories from Australia, the UK and the USA across a ten-year period. We found significant genotype diversity in all three locations, with the emergence of genotypes with converged resistance to all major drugs currently used for treatment. Flex-It provides an open-source, novel genotyping method that rapidly characterises S. flexneri and its ciprofloxacin resistance determinants in <1 minute from both short and long whole-genome sequencing reads. Flex-It provides the community with a standardised nomenclature to monitor the emergence and spread of S. flexneri lineages.

microbiology↗

bioRxiv2026

Cross-species architecture of the cardiac transverse-axial tubular system in mammals

Cardiac excitation-contraction coupling relies on a pancellular network of regular cardiomyocyte surface membrane invaginations, termed the transverse-axial tubular system (TATS). The TATS is ubiquitously present in adult mammalian cardiomyocytes, enabling efficient structural and functional coupling of sarcolemma and intracellular Ca2+ stores. However, TATS ultrastructural characteristics across species, and their relation to cardiomyocyte morphology and physiological parameters such as heart rate, remain largely unexplored. Here, we quantified TATS and cardiomyocyte features in a large confocal microscopy dataset (78 3D volumes) obtained from tissue slices across eight species (mouse, rat, rabbit, pig, horse, elephant, whale, and human). We developed and applied a semi-automated image analysis pipeline to quantify mean cytosolic distances to the nearest TATS (Cyto-TATSmin, a measure inversely related to TATS density), transverse-to-axial tubule ratio, and cardiomyocyte dimensions. Cyto-TATSmin and transverse tubule fraction differed substantially between species, with the lowest Cyto-TATSmin in mouse and highest in human. Within species, except mouse, rat, and horse, Cyto-TATSmin was positively correlated with cardiomyocyte cross-sectional area. Across all species, Cyto-TATSmin correlated with species life span and body weight, and was inversely correlated with average resting heart rate. Our findings reveal structural scaling principles within species differences in cardiac cellular ultrastructure and provide a resource for studying TATS organisation in health and disease. As TATS remodelling is a common hallmark of cardiac pathology, awareness of species-differences is needed to guide the design and interpretation of translational research.

cell biology↗

bioRxiv2025

Rapidly and reproducibly building a comprehensive catalogueof resistance-associated variants for M. tuberculosis

BackgroundCatalogues of genetic variants associated with resistance underpin whole-genome sequencing (WGS)-based predictions of drug susceptibility in Mycobacterium tuberculosis, and are essential for molecular diagnostics and surveillance. The current gold standard catalogues are those released by the WHO but the underlying data are not fully released and they are difficult to interpret. Open and reproducible methods would help address these problems, extending the important work already done. MethodsWe have developed an automated method, catomatic, that uses a binomial test to associate informative isolates with resistance or susceptibility, and built a catalogue (catomatic-1) from the same 39,358 samples used to construct the first edition of the WHO catalogue (WHOv1). We performed a sensitivity analysis to optimise statistical and bioinformatic parameters for each drug, and benchmarked catomatic-1 against WHOv1 using an independent Validation Dataset of 14,380 isolates. FindingsBy using simpler statistics, catomatic-1 algorithmically classified 1,329 genetic variants, ranging from five for linezolid to 440 for pyrazinamide. WHOv1 included generalisable rules added by a panel of experts, increasing its predictive coverage, but at the cost of reproducibility. Despite not including such expert rules, catomatic-1 achieves comparable performance for all drugs, with sensitivities for first-line agents above 88% on the independent Validation Dataset. The automated process allowed us to efficiently explore parameter space; for instance, detecting resistant variants with low read support improved the sensitivity for all drugs. InterpretationPerformant resistance catalogues for M. tuberculosis can be built automatically using transparent and reproducible statistical methods. As more data are collected, catalogue content and performance will evolve, highlighting the need for proper versioning, machine/human readability, and open access. This approach demonstrates resistance catalogues used in surveillance and diagnostics can be rapidly and reproducibily updated. FundingThe National Institute for Health and Care Research (NIHR), Engineering and Physics Sciences Research Council (EPSRC) and ORACLE Corporation. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and preprint servers (bioRxiv, medRxiv), and publicly available mutation catalogues for studies linking Mycobacterium tuberculosis genomic variants with drug resistance using whole-genome or targeted sequencing and phenotypic drug-susceptibility testing (pDST). Search terms combined "Mycobacterium tuberculosis", "genome sequencing", "mutation catalogue", "mutation effects", "drug resistance", and individual drug names, with no language or date restriction. We included studies providing paired, clinical genomic and pDST or MIC data, excluding purely in-silico or case-only reports. This work directly builds on methodologies and data published by five prior studies, and makes primary comparisons with the First (WHOv1) and Second (WHOv2) Editions of the WHO Catalogue of mutations in Mycobacterium tuberculosis. Added value of this studyWe developed catomatic, a transparent, reproducible tool for building catalogues of resistance- and susceptibility-associated genetic variants. Trained on the same samples used to build WHOv1 and benchmarked on an independent Validation Dataset, catomatic achieves comparable sensitivity, specificity, and definitive prediction rates to WHOv1 without expert-rule augmentation and despite using simpler statistics. It optimises parameters per drug, produces machine-readable outputs (CSV/JSON), and demonstrates that adjusting read-support thresholds can improve detection of minor resistance subpopulations. Implications of all the available evidenceCatalogues of resistance-associated variants for M. tuberculosis can be rapidly and transparently constructed. Making catalogues available in human/machine-readable formats with uncertainty estimates will improve uptake of WGS for M. tuberculosis surveillance and diagnostics; using a reproducible process permits diagnostic test manufacturers, researchers, clinical and public health laboratories to select the level of statistical support necessitated by their specific use-case, Policymakers should balance the benefits of expert rules against loss of reproducibility. Future work will expand the size of the datasets used, integrate minimum inhibitory concentration data, and establish consensus workflows for routine, transparent catalogue updates.

microbiology↗

bioRxiv2025

DDIAS is a single-stranded DNA-binding effector of the TOPBP1-CIP2A complex in mitosis

DNA double-strand breaks and unresolved DNA replication intermediates are particularly dangerous during mitosis. Paradoxically, cells inactivate canonical DNA repair mechanisms during chromosome segregation in favor of alternative pathways that depend on TOPBP1 and CIP2A, but how they function is still poorly defined. Here, we describe the identification of DDIAS as a mitosis-specific DNA damage response protein. We establish DDIAS as a phosphorylation-dependent component and effector of the TOPBP1-CIP2A complex with single-stranded DNA (ssDNA)-binding activity, and thereby delineate a ssDNA protection mechanism that safeguards chromosome integrity during mitosis, particularly in BRCA-deficient cells. We also identify biallelic inactivating mutations in DDIAS in a patient with a severe neurodevelopmental disorder. These findings highlight for the first time a potential physiological role for the DNA damage response in mitosis.

molecular biology↗

bioRxiv2025

Clustering of plasmid genomes for genomic epidemiology by using rearrangement distances, with pling

Integration of plasmids into genomic epidemiology is challenging, because there are no clearly defined evolving-units (equivalent to species), and because plasmids appear to evolve as much by structural change (rearrangements, insertions and deletions) as by mutation (1). Further, plasmids transfer horizontally between bacterial hosts (2), and thus a model beyond just a phylogeny is needed to integrate their genetic information with that of their hosts. Pling (3) is a tool designed to measure a genetic distance between plasmids that is related to how they empirically appear to evolve, by measuring the distance between two plasmids as the minimum number of structural changes needed to change one plasmid into the other (ignoring SNP differences). Having done this, it constructs a relatedness network of the plasmids under study, and then clusters them into groups that are credibly recently related. We give here a protocol for running pling, and how we integrate its information with plasmid typing and SNP information. Together, these provide a system for deciding which plasmids are worth treating as "the same plasmid" for the purposes of epidemiology, quantifying their relatedness in terms of rearrangements and SNPs, and then seeing how they are distributed across the host phylogeny.

bioinformatics↗

bioRxiv2025

Complete genomes reveal the full extent of Mycobacterium tuberculosis complex diversity across evolutionary scales

Advances in short-read sequencing have enhanced our understanding of Mycobacterium tuberculosis complex (MTBC), but fail to capture its complete genomic diversity. We applied long-read sequencing to 216 isolates from the Valencia Region (Spain) and generated high-quality, complete genomes, revealing detailed insights into MTBC evolution across timescales. Complete genome comparisons increased the estimated evolutionary rate by 1.5-fold, resulting in a median of 312 (-1 to 792) additional SNPs per pairwise comparison. Multiple diversity hotspots were identified, mostly in the pe/ppe genes and driven by gene conversion. However, most PE/PPE epitopes were hyperconserved, with notable exceptions involving vaccine candidates. Incorporating previously undetected SNPs and indels improved resolution in transmission analyses. Furthermore, patient-specific reference mapping validates only 5-10% of within-host diversity detected by standard pipelines, indicating substantial overestimation in previous studies. These findings expand our view of MTBC diversity and have important implications for understanding host-pathogen interactions, epidemiology, and transmission dynamics.

genomics↗

bioRxiv2025

Rab11FIP2 controls NLRP3 inflammasome activation through Rab11b

Membrane trafficking through the trans-Golgi network has recently been shown to guide activation of the NLRP3 inflammasome. The GTPases Rab11a and Rab11b, and their effector molecule Rab11-FIP2, are regulators of endosome trafficking and retrograde transport. Rab11-FIP2 binds phosphatidylinositol species including PI4P, enriched in the trans-Golgi network and peripheral endosomes following NLRP3 inflammasome activation. We here demonstrate that Rab11-FIP2 and Rab11b, but not Rab11a, control caspase-1 mediated cleavage of pro-IL-1{beta} and GSDMD, and pyroptotic cell death in human macrophages. Rab11-FIP2 also controlled LPS stimulated IKK{beta} activation by TAK1 and IKK{beta} mediated NLRP3 translocation to the trans-Golgi network. Furthermore, we show that NLRP3 bound Rab11-FIP2 via its KMKK motif and that Rab11-FIP2 interacts with NLRP3 via its N-terminal C2-domain. The formation of PI4P positive endosomes and ASC-specks were also controlled by Rab11-FIP2. Collectively our results demonstrate that Rab11-FIP2 and Rab11b control NLRP3 inflammasome activation on early endosomes in human macrophages.

immunology↗

bioRxiv2025

Amira: gene-space de Bruijn graphs to improve the detection of AMR genes from bacterial long reads

Accurate detection of antimicrobial resistance (AMR) genes is essential for the surveillance, epidemiology and genotypic prediction of AMR. This is typically done by generating an assembly from the sequencing reads of a bacterial isolate and running AMR gene detection tools on the assembly. However, despite advances in long-read sequencing that have greatly improved the quality and completeness of bacterial genome assemblies, assembly tools remain prone to large-scale errors caused by repeats in the genome, leading to inaccurate detection of AMR gene content and consequent impact on resistance prediction. In this work we present Amira, a tool to detect AMR genes directly from unassembled long-read sequencing data. Amira leverages the fact that multiple consecutive genes lie within a single read to construct gene-space de Bruijn graphs where the k-mer alphabet is the set of genes in the pan-genome of the species under study. Through this approach, the reads corresponding to different copies of AMR genes can be effectively separated based on the genomic context of the AMR genes, and used to infer the nucleotide sequence of each copy. Amira achieves significant improvements in genomic copy number recall and nucleotide accuracy, demonstrated through objective simulations and comparison with alternative read and assembly-based methods on samples with manually curated truth assemblies. Applied to a dataset of 32 Escherichia coli samples with diverse AMR gene content, Amira achieves a mean genomic-copy-number recall of 98.4% with precision 97.9% and nucleotide accuracy 99.9%. Finally, we show that Amira consistently detects more true AMR genes across all E. coli, K. pneumoniae and E. faecium nanopore datasets from the ENA (n=8580, 2448 and 415 respectively) than an assembly-based approach.

bioinformatics↗

bioRxiv2024

Integrative analysis of transcriptome and metabolism reveals functional roles of redox homeostasis in low light and salt combined stress in Leymus chinensis

Soil salinity (Salt) is one of the major limiting factors of Leymus chinensis (named sheepgrass) performance and alters their primary metabolic process and gene expression. Salt stress could accelerate inhibitive effects concomitant with low light (LL-Salt). However, little is known about physiological and molecular mechanisms under such LL-Salt in sheepgrass. This study aims to uncover the key reprogrammed metabolic pathways induced by LL-Salt through an integrated analysis of transcriptome and metabolism. Plant seedlings were exposed to six combinations of light intensity (moderate light, ML, and LL) and NaCl concentrations (0, 50, and 200mM) for 20 days. Results suggest that the growth of sheepgrass seedlings was dramatically inhibited with severe lodging phenotype, especially when exposed to LL-Salt combined conditions. Activities of an antioxidant enzyme, catalase, were significantly increased in LL but significantly decreased in salt stress, leading to a reverse pattern for H2O2 in LL and salt stress. Transcriptome analysis reveals 4921 downregulated differentially expressed genes (DEGs) with carbon metabolism pathways were significantly enriched compared to light response without salt (ML_0 vs LL_0). There are 194 overlapped downregulated DEGs induced by two salt treatments (ML_50 vs ML_0 and ML_200 vs ML_0), where the carbon metabolism pathway was also significantly enriched. In terms of interactive effects of LL-Salt treatments, we found that there are 16 overlapped DEGs, including a phytochrome-interacting transcription factor 4 (PIF4) with upregulation in LL treatment while downregulation in salt treatment, which was validated by qPCR. Metabolism analysis confirmed that in carbon metabolism, the contents of seven differentially abundant metabolites (DAMs), including sucrose, were all downregulated in both LL and salt treatment. In contrast, serine and glycolate in the photorespiration pathway were downregulated in LL while upregulated in salt treatment. A photorespiration regulatory gene, glycolate oxidase expression, was confirmed by qPCR. Collectively, we found that serval antioxidant redox pathways, including photorespiration, GSG/GSSH redox, and ABA signaling, participated in response to LL and salt combined events and highlighted the roles of cellular redox homeostasis in LL-Salt response in sheepgrass.

plant biology↗

bioRxiv2024

Spatio-temporal dynamics of the fibrotic niche in cardiac repair

The heart is one of the least regenerative organs in humans, and ischemic heart disease is the leading cause of death worldwide. Understanding the cellular and molecular processes that occur during cardiac wound healing is an essential prerequisite to reducing health burden and improve cardiac function after myocardial tissue damage. By integrating single-cell RNA-sequencing with imaging-based spatial transcriptomics, we reconstructed the spatio-temporal dynamics of the fibrotic niche after ventricular injury in adult mice. Our analysis reveals dynamic regulation of local cell communication niches over time. We identified interactions that regulate cardiac repair, including fibroblast proliferation silencing by Trem2high macrophages that prevents excessive fibrosis. Moreover, we discovered a rare population of dedifferentiating cardiomyocytes during early post-lesion stages, which was sustained by signals from myeloid and lymphoid cells. Culturing non-regenerative mouse cardiomyocytes or human heart tissue with these niche factors reactivated progenitor gene expression and cell cycle activity. In summary, this spatio-temporal cell type atlas provides valuable insights into the heterocellular interactions that control cardiac repair. HighlightsO_LIscRNA-seq and in situ sequencing reveal spatio-temporal dynamics of heart repair C_LIO_LILocal heterocellular communication niches coordinate overall wound response C_LIO_LIFibroblast cell cycle silencing by Trem2high macrophages suppresses excessive fibrosis C_LIO_LICardiomyocyte plasticity is promoted by myeloid and lymphoid cells C_LI

systems biology↗

bioRxiv2024

Typhi Mykrobe: fast and accurate lineage identification and antimicrobial resistance genotyping directly from sequence reads for the typhoid fever agent Salmonella Typhi

BackgroundTyphoid fever results from systemic infection with Salmonella enterica serovar Typhi (Typhi) and causes 10 million illnesses annually. Disease control relies on prevention (water, sanitation, and hygiene interventions or vaccination) and effective antimicrobial treatment. Antimicrobial resistant (AMR) Typhi lineages have emerged and become established in many parts of the world. Knowledge of local pathogen populations informed by genomic surveillance, including of lineages (defined by the GenoTyphi scheme) and AMR determinants, is increasingly used to inform local treatment guidelines and to inform vaccination strategy. Current tools for genotyping Typhi require multiple read alignment or assembly steps and have not been validated for analysis of data generated with Oxford Nanopore Technologies (ONT) long-read sequencing devices. Here, we introduce Typhi Mykrobe, a command line software tool for rapid genotyping of Typhi lineages, AMR determinants, and plasmid replicons direct from sequencing reads. ResultsWe validated Typhi Mykrobe lineage genotyping by comparison with the current standard read mapping-based approach and demonstrated 99.8% concordance across nearly 13,000 genomes sequenced with Illumina platforms. For the few isolates with discordant calls, we show that Typhi Mykrobe results are better supported by the evidence from raw sequence read data than the results generated using the mapping-based approach. We also demonstrate 99.9% concordance for detection of AMR determinants compared with the current standard assembly-based approach, with similar results for plasmid marker detection. Typhi Mykrobe predicts clinical resistance categorisation (S/I/R) for eight drug classes, and we show strong agreement with phenotypic categorisations generated from reference laboratory minimum inhibitory concentration (MIC) data for n=1,572 Illumina-sequenced isolates (>99% agreement within one doubling dilution). We show strong concordance (>96% for genotype and >98% for AMR and plasmid) between calls made from ONT reads and those made from Illumina reads for isolates sequenced on both platforms (n =93 genomes). Typhi Mykrobe takes less than a minute per sample and is available at https://github.com/typhoidgenomics/genotyphi. ConclusionsTyphi Mykrobe provides rapid and sensitive genotyping of Typhi genomes direct from Illumina and ONT reads, although lower accuracy was observed for R9 ONT data. It demonstrated accurate assignment of GenoTyphi lineage, detection of AMR determinants and prediction of corresponding AMR phenotypes, and identification of plasmid replicons.

microbiology↗

bioRxiv2024

Evidence that Dmrta2 acts as a transcriptional repressor of Pax6 in murine cortical progenitors and identification of a mutation crucial for DNA recognition associated with microcephaly in human

Dmrta2 (also designated Dmrt5) is a transcriptional regulator expressed in cortical progenitors in a caudomedialhigh/rostrolaterallow gradient with important roles at different steps of cortical development. Dmrta2 has been suggested to act in cortex development mainly by differential suppression of Pax6 and other homeobox transcription factors such as the ventral telencephalic regulator Gsx2, which remains to be fully demonstrated. Here we have addressed the epistatic relation between Pax6 and Dmrta2 by comparing phenotypes in mutant embryos or embryos overexpressing both genes in various allelic combinations. We showed that Dmrta2 cooperates with Pax6 in the maintenance of cortical identity in dorsal telencephalic progenitors and that it acts as a transcriptional repressor of Pax6 to control cortical patterning. Mechanistically, we show that in P19 cells, Dmrta2 can act as a DNA-binding dependent repressor on the Pax6 E60 enhancer and that a point mutation that affects its DNA binding properties leads to agenesis of the corpus callosum, pachygyria, and the absence of the cingulate gyrus. Finally, we provide evidence that Dmrta2 binds to the Zfp423 zinc finger protein and that it enhances its ability to recruit the NurD repressor complex. Together, our results highlight the importance and conserved function of Dmrta2 in cortical development and provide novel insights into its mechanism of action. SIGNIFICANCE STATEMENTCorticogenesis is controlled by an array of transcription factors that coordinate neural progenitor self-renewal and differentiation to generate correct cortical cell number and diversity. However, how this complex array of transcription factors works in concert to regulate this delicate process remains largely unknown. Here we provide important insights into the mechanism of action of Dmrta2 by demonstrating that it cooperates with the transcription factor Pax6 to define the pallium-subpallium boundary and that it acts by repressing it, likely via the recruitment of Zfp423 and the NurD repressor complex, to control cortical patterning. Our data also reveal that a point mutation that affects its DNA binding causes cortical abnormalities in human, further highlighting its importance in cortex development.

neuroscience↗

bioRxiv2024

Pre and Post antibiotic epoch: insights into the historical spread of antimicrobial resistance

Plasmids are now the primary vectors of antimicrobial resistance, but our understanding of how human industrialisation of antibiotics influenced this is limited by a paucity of data predating the antibiotic era (PAE). By investigating plasmids from clinically relevant bacteria isolated between 1917 and 1954 and comparing them to modern plasmids, we captured over 100 years of evolution. We show that while all PAE plasmids were devoid of resistance genes and most never acquired them, a small minority evolved to drive the global spread of resistance to first-line and last-resort antibiotics in Gram-negative bacteria. They have evolved through complex microevolution and fusion events into a distinct group of highly recombinogenic, multi-replicon, self-transmissible plasmids that now pose the highest risk to resistance dissemination, and therefore human health. One Sentence SummaryPre-antibiotic era bacteria reveal the origin and evolution of drug-resistance vectors.

genomics↗

bioRxiv2024

LexicMap: efficient sequence alignment against millions of prokaryotic genomes

Alignment against a database of genomes is a fundamental operation in bioinformatics, popularized by BLAST. However, the rate at which microbial genomes are sequenced has continued to increase, and there are now datasets in the millions, far beyond the abilities of existing alignment tools. We introduce LexicMap, a nucleotide sequence alignment tool for efficiently querying moderate length sequences (>250 bp) such as a gene, plasmid or long read against up to millions of prokaryotic genomes. A key innovation is to construct a small set of probe k-mers (e.g. n = 20,000) which are selected to efficiently sample the entire database to be indexed, such that every 250 bp window of each database genome contains multiple seed k-mers each with a shared prefix with one of the probes. Storing these seeds in a hierarchical index enables fast and low-memory alignment. We benchmark both accuracy as the query diverges from the match in the database, and potential to scale to databases of millions of bacterial genomes, showing that LexicMap achieves comparable accuracy with state-of-the-art, but with greater speed and lower memory use. We then benchmark LexicMap on small/diverse (GTDB) and large/redundant (AllTheBacteria and GenBank+RefSeq) databases. Alignment of a single gene against 2.34 million prokaryotic genomes from GenBank and RefSeq takes 3 (rare gene) to 33 (16S rRNA gene) minutes. Full alignment against all bacterial genomes is now possible in minutes with modest resources, supporting querying at scale which will be useful for many biological applications across epidemiology, ecology and evolution. LexicMap produces output in standard formats including that of BLAST and is available under MIT license at https://github.com/shenwei356/LexicMap.

bioinformatics↗

bioRxiv2024

TRACKING CLONAL AND PLASMID TRANSMISSION IN COLISTIN AND CARBAPENEM RESISTANT KLEBSIELLA PNEUMONIAE

The surveillance of mobile genetic elements facilitating the spread of antimicrobial resistance genes has been challenging. Here, we tracked both clonal and plasmid transmission in colistin- and carbapenem-resistant K. pneumoniae using short and long read sequencing technologies. We observed three clonal transmissions, all containing IncL plasmids and blaNDM-1, although not co-located on the same plasmid. One IncL-blaNDM-1 plasmid had been transferred between ST392 and ST15, and the promiscuous IncL-blaOXA-48 plasmid was likely shared between a singleton and a clonal transmission of ST392. Plasmids within clonal outbreaks and between clusters and STs had 0-2 SNP differences, showing high stability upon transfer to same or different STs. The simplest explanation of a single common IncL-blaNDM-1 plasmid spreading was in fact false, and we found blaNDM-1 in the context of five different plasmids, emphasizing the need to investigate plasmid-mediated transmission for effective containment of outbreaks. IMPORTANCEAntimicrobial resistance occupies a central stage in global public health emergencies. Recently, efforts to track the genetic elements that facilitate the spread of resistance genes to determine so-called plasmid outbreaks have been described, however, such short read sequencing hinders full knowledge about plasmid structure and makes this approach very challenging to implement. In this study we used both short and long read sequencing in clinical Klebsiella pneumoniae from University Hospital Centre Zagreb, Croatia which were resistant to both last resort antibiotics colistin and carbapenem. Our results show complex transmission networks and sharing of plasmids, emphasizing multiple transmissions of plasmids harbouring carbapenem and/or colistin resistance genes between and within K. pneumoniae clones. Only full length sequencing plus a novel way of determining plasmid clusters resulted in the full picture, showing how future active monitoring of plasmids as a vital tool for infection prevention and control could be implemented.

microbiology↗

bioRxiv2024

Rate variation and recurrent sequence errors in pandemic-scale phylogenetics

Phylogenetic analyses of genome sequences from infectious pathogens reveal essential information regarding their evolution and transmission, as seen during the COVID-19 pandemic. Recently developed pandemic-scale phylogenetic inference methods reduce the computational demand of phylogenetic reconstruction from genomic epidemiological datasets, allowing the analysis of millions of closely related genomes. However, widespread homoplasies, due to recurrent mutations and sequence errors, cause phylogenetic uncertainty and biases. We present new algorithms and models to substantially improve the computational performance and accuracy of pandemic-scale phylogenetics. In particular, we account for, and identify, mutation rate variation and recurrent sequence errors. We reconstruct reliable and public sequence alignment and phylogenetic tree of > 2 million SARS-CoV-2 genomes encapsulating the evolutionary history and global spread of the virus up to February 2023.

bioinformatics↗

bioRxiv2024

Applying rearrangement distances to enable plasmid epidemiology with pling

Plasmids are a key vector of antibiotic resistance, but the current bioinformatics toolkit is not well suited to tracking them. The rapid structural changes seen in plasmid genomes present considerable challenges to evolutionary and epidemiological analysis. Typical approaches are either low resolution (replicon typing) or use shared k-mer content to define a genetic distance. However this distance can both overestimate plasmid relatedness by ignoring rearrangements, and underestimate by over-penalising gene gain/loss. Therefore a model is needed which captures the key components of how plasmid genomes evolve structurally - through gene/block gain or loss, and rearrangement. A secondary requirement is to prevent promiscuous transposable elements (TEs) leading to over-clustering of unrelated plasmids. We choose the "Double Cut and Join Indel" model, in which plasmids are studied at a coarse level, as a sequence of signed integers (representing genes or aligned blocks), and the distance between two plasmids is the minimum number of rearrangement events or indels needed to transform one into the other. We show how this gives much more meaningful distances between plasmids. We introduce a software workflow pling (https://github.com/iqbal-lab-org/pling), which uses the DCJ-Indel model, to calculate distances between plasmids and then cluster them. In our approach, we combine containment distances and DCJ-Indel distances to build a TE-aware plasmid network. We demonstrate superior performance and interpretability to other plasmid clustering tools on the "Russian Doll" dataset and a hospital transmission dataset. Impact statementStudying plasmid transmission is a necessary component of understanding antibiotic resistance spread, but identifying recently related plasmids is difficult and often requires manual curation. Pling simplifies this by leveraging a combination of containment distances and rearrangement distances to cluster plasmids. The outcome are clusters of recently related plasmids with a clear backbone and relatively large core genomes, in contrast to other tools which sometimes overcluster. Additionally the network constructed by pling provides a framework with which to spot evolutionary events, such as potential fusions of plasmids and spread of transposable elements. Data summarySupplementary information and figures are available as an additional PDF. The tool presented in this paper is available under https://github.com/iqbal-lab-org/pling. Additional computational analysis and scripts are described and provided under https://github.com/babayagaofficial/pling_paper_analyses. The sequence data used can be found under BioProject no. PRJNA246471 in the National Center for Biotechnology Information for the "Russian doll" dataset (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA246471), and under Project no. PRJEB31034 in European Nucleotide Archive for the "Addenbrookes" dataset (https://www.ebi.ac.uk/ena/browser/view/PRJEB30134). All other genome sequences used were sourced from PLSDB (https://ccb-microbe.cs.uni-saarland.de/plsdb/), and lists of accession numbers can be found in the additional analysis github.

bioinformatics↗

bioRxiv2024

CELEBRIMBOR: Pangenomes from metagenomes

SummaryMetagenome Assembled Genomes (MAGs) are often incomplete, with sequences missing due to errors in assembly or low coverage. Incomplete MAGs present a particular challenge for identification of shared genes within a microbial population, known as core genes, as a core gene missing in only a few assemblies will result in it being mischaracterized at a lower frequency. Here, we present CELEBRIMBOR, a snakemake pangenome analysis pipeline which uses a measure of genome completeness to automatically adjust the frequency threshold at which core genes are identified, enabling accurate core gene identification in MAGs. Availability and implementationCELEBRIMBOR is published under open source Apache 2.0 licence at https://github.com/bacpop/CELEBRIMBOR and is available as a Docker container. Supplementary material is available in the online version of the article.

bioinformatics↗