Biology subjects

Meric, G.

Publications and source records attributed to Meric, G..

12 recordsLinked to original sources

bioRxiv2026

Bacterial diversity and strain dynamics in the infant respiratory microbiome during the first year of life

BackgroundMicrobial colonisation of the human body begins immediately after birth, with each body site forming a distinct ecological niche. While early gut microbial dynamics and their links to paediatric health have been considerably studied, the bacterial colonisation of the early infant respiratory system remains poorly understood, particularly at the species and strain level. ResultsHere, we generated and analysed whole genome sequencing of 925 isolates from six dominant genera in nasopharyngeal samples from 58 healthy infants enrolled in the Childhood Asthma Study (CAS) in Western Australia, collected longitudinally from birth (2, 6, and 12 months old). Our results expanded genomic reference catalogues and uncovered substantial strain-level diversity in dominant infant airway taxa. Plate-sweep metagenomics identified four microbiome profile groups (MPGs) with age-dependent membership, confirming prior observations while enabling high-resolution species and strain analyses. Community maturation was characterised by a shift from early Staphylococcus aureus dominance to increased Moraxella catarrhalis dominance by 12 months of age, alongside marked temporal changes in prevalence and cohort-level strain diversity. ConclusionsThese findings resolve infant nasopharyngeal microbiota composition at the species and strain level, revealing taxon-specific colonisation patterns. By substantially expanding publicly available reference genomes for underrepresented airway taxa, this work also provides a foundation for functional follow-up studies of the early respiratory microbiota and respiratory outcomes.

microbiology↗

bioRxiv2021

Host ecology regulates interspecies recombination in bacteria of the genus Campylobacter

Horizontal gene transfer (HGT) can allow traits that have evolved in one bacterial species to transfer to another. This has potential to rapidly promote new adaptive trajectories such as zoonotic transfer or antimicrobial resistance. However, for this to occur requires gaps to align in barriers to recombination within a given time frame. Chief among these barriers is the physical separation of species with distinct ecologies in separate niches. Within the genus Campylobacter there are species with divergent ecologies, from rarely isolated single host specialists to multi-host generalist species that are among the most common global causes of human bacterial gastroenteritis. Here, by characterising these contrasting ecologies, we can quantify HGT among sympatric and allopatric species in natural populations. Analysing recipient and donor population ancestry among genomes from 30 Campylobacter species we show that cohabitation in the same host can lead to a 6-fold increase in HGT between species. This accounts for up to 30% of all SNPs within a given species and identifies highly recombinogenic genes with functions including host adaptation and antimicrobial resistance. As described in some animal and plant species, ecological factors are a major evolutionary force for speciation in bacteria and changes to the host landscape can promote partial convergence of distinct species through HGT.

microbiology↗

bioRxiv2021

Trycycler: consensus long-read assemblies for bacterial genomes

Assembly of bacterial genomes from long-read data (generated by Oxford Nanopore or Pacific Biosciences platforms) can often be complete: a single contig for each chromosome or plasmid in the genome. However, even complete bacterial genome assemblies constructed solely from long reads still contain a variety of errors, and different assemblies of the same genome often contain different errors. Here, we present Trycycler, a tool which produces a consensus assembly from multiple input assemblies of the same genome. Benchmarking using both simulated and real sequencing reads showed that Trycycler consensus assemblies contained fewer errors than any of those constructed with a single long-read assembler. Post-assembly polishing with Medaka and Pilon further reduced errors and yielded the most accurate genome assemblies in our study. As Trycycler can require human judgement and manual intervention, its output is not deterministic, and different users can produce different Trycycler assemblies from the same input data. However, we demonstrated that multiple users with minimal training converge on similar assemblies that are consistently more accurate than those produced by automated assembly tools. We therefore recommend Trycycler+Medaka+Pilon as an ideal approach for generating high-quality bacterial reference genomes. Data availabilitySupplementary figures, tables and code can be found at: github.com/rrwick/Trycycler-paper Reads, assemblies and reference sequences can be found at: bridges.monash.edu/articles/dataset/Trycycler_paper_dataset/14890734

bioinformatics↗

bioRxiv2021

Non-serotype 2 isolates from healthy pigs are a potential zoonotic reservoir of Streptococcus suis genetic diversity and antimicrobial resistance

Streptococcus suis is a leading cause of bacterial meningitis in SE Asia, with frequent zoonotic transfer to humans associated with close contact with pigs. A small number of invasive lineages are responsible for endemic infection in the swine industry causing considerable global economic losses. A lack of surveillance and a rising trend in clinical treatment failure has raised concerns of growing antimicrobial resistance (AMR) among invasive S. suis. The source-sink dynamics between healthy and disease isolates is poorly understood and, in this study, we sample and sequence a collection of isolates predominantly from healthy pigs in Chiang Mai province, Northern Thailand. Pangenome comparisons with a selection of invasive serotype 2 isolates identified increased genetic diversity and more frequent AMR carriage in isolates from healthy pigs. Multiple antimicrobial resistance genes were identified conferring resistance to aminoglycosides, lincosamides, tetracycline and macrolides. All isolates were non-susceptinle to three or more different antimicrobial classes, and 75% of non-serotype 2 isolates were non-susceptible to 6 or more classes (compared to 37.5% of serotype 2 isolates). Antimicrobial resistance genes were found on integrative and conjugative elements (ICE) previously observed in other species, suggesting mobile gene pool which can be accessed by invasive disease isolates. Significance statementThe zoonotic pathogen Streptococcus suis causes respiratory disease in pigs and is among the most common causative agents of human clinical bacterial meningitis in SE Asia. We collected isolates from farmed healthy pigs in Northern Thailand, representing a source population from which invasive isolates have recently emerged - linked to the pork production industry. Pangenome characterisation of the isolates revealed a reservoir of genetic diversity and antimicrobial resistance suggesting that One Health approaches may be beneficial in tackling the increase in antimicrobial resistance.

microbiology↗

bioRxiv2021

Assessing and removing the effect of unwanted technical variations in microbiome data

Varying technologies and experimental approaches used in microbiome studies often lead to irreproducible results due to unwanted technical variations. Such variations, often unaccounted for and of unknown source, may interfere with true biological signals, resulting in misleading biological conclusions. In this work, we aim to characterize the major sources of technical variations in microbiome data and demonstrate how a state-of-the art approach can minimize their impact on downstream analyses. We analyzed 184 pig faecal metagenomes encompassing 21 specific combinations of deliberately introduced factors of technical and biological variations. We identify several known experimental factors, specifically storage conditions and freeze-thaw cycles, as a likely major source of unwanted variation in metagenomes. We also observed that these unwanted technical variations do not affect taxa uniformly, with freezing samples affecting taxa of class Bacteroidia the most, for example. Additionally, we benchmarked the performance of a novel batch correcting tool used in this study, RUV-III-NB (https://github.com/limfuxing/ruvIIInb/), to other popular batch correction methods, including ComBat, ComBat-seq, RUVg, and RUVs. While RUV-III-NB performed consistently robustly across our sensitivity and specificity metrics, most other methods did not remove unwanted variations optimally, with RUVg even overcorrecting and removing some of the true biological signals from the samples. Our analyses suggests that a careful consideration of possible technical confounders is critical in the experimental design of microbiome studies to ensure accurate biological reading of microbial taxa of interest, and that the inclusion of technical replicates is necessary to efficiently remove unwanted variations computationally.

bioinformatics↗

bioRxiv2021

OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures

We introduce Operational Genomic Unit (OGU), a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent from taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldomly applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in one synthetic and two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome datasets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project dataset, and more accurate prediction of human age by the gut microbiomes in the Finnish population. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate OGU adoption in future metagenomics studies. ImportanceShotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. However, current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution compared to 16S rRNA amplicon sequence variant analysis. To solve these challenges, we introduce Operational Genomic Units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition while (ii) permitting use of phylogeny-aware tools. Our analysis of real-world datasets shows several advantages over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGU as standard practice in metagenomic studies.

bioinformatics↗

bioRxiv2021

Cross-species evolutionary rewiring in the enteric bacterium Campylobacter

Significance StatementGenetic exchange among bacteria shapes the microbial world. From the acquisition of antimicrobial resistance genes to fundamental questions about the nature of bacterial species, this powerful evolutionary force has preoccupied scientists for decades. However, the mixing of genes between species rests on a paradox. On one hand, promoting adaptation by conferring novel functionality, on the other potentially introducing disharmonious gene combinations (negative epistasis) that will be selected against. Taking an interdisciplinary approach to analyse natural populations of the enteric bacteria Campylobacter, an ideal example of long-range admixture, we demonstrate that genes can independently transfer across species boundaries and rejoin in epistasis in a recipient genome. This challenges conventional ideas and highlights the possibility of single step evolution by saltation. AbstractRecombination of short DNA fragments via horizontal gene transfer (HGT) can both introduce beneficial alleles and create genomic disharmony through negative epistasis. For non-core (accessory) genes, the negative epistatic cost is likely to be minimal because the incoming genes have not co-evolved with the recipient genome. By contrast, for the core genome, interspecific recombination is expected to be rare because disruptive allelic replacement is likely to introduce negative epistasis. Why then is homologous recombination common in the core of bacterial genomes? To understand this enigma we take advantage of an exceptional model system, the common enteric pathogens Campylobacter jejuni and Campylobacter coli, that are known for very high magnitude interspecies gene flow in the core genome. As expected, HGT does indeed disrupt co-adapted allele pairings (negative epistasis). However, multiple HGT events enable recovery of the genomes co-adaption between introgressing alleles, even in core metabolism genes (e.g., formate dehydrogenase). These findings demonstrate that, even for complex traits, genetic coalitions can be decoupled, transferred and independently reinstated in a new genetic background - facilitating transition between fitness peaks. In this example, the two-step recombinational process is associated with C. coli that are adapted to the agricultural niche.

microbiology↗

bioRxiv2021

The carbon footprint of bioinformatics

Bioinformatic research relies on large-scale computational infrastructures which have a non-zero carbon footprint. So far, no study has quantified the environmental costs of bioinformatic tools and commonly run analyses. In this study, we estimate the bioinformatic carbon footprint (in kilograms of CO2 equivalent units, kgCO2e) using the freely available Green Algorithms calculator (www.green-algorithms.org). We assess (i) bioinformatic approaches in genome-wide association studies (GWAS), RNA sequencing, genome assembly, metagenomics, phylogenetics and molecular simulations, as well as (ii) computation strategies, such as parallelisation, CPU (central processing unit) vs GPU (graphics processing unit), cloud vs. local computing infrastructure and geography. In particular, for GWAS, we found that biobank-scale analyses emitted substantial kgCO2e and simple software upgrades could make GWAS greener, e.g. upgrading from BOLT-LMM v1 to v2.3 reduced carbon footprint by 73%. Switching from the average data centre to a more efficient data centres can reduce carbon footprint by ~34%. Memory over-allocation can be a substantial contributor to an algorithms carbon footprint. The use of faster processors or greater parallelisation reduces run time but can lead to, sometimes substantially, greater carbon footprint. Finally, we provide guidance on how researchers can reduce power consumption and minimise kgCO2e. Overall, this work elucidates the carbon footprint of common analyses in bioinformatics and provides solutions which empower a move toward greener research.

bioinformatics↗

bioRxiv2019

Correcting index databases improves metagenomic studies

Assessing the taxonomic composition of metagenomic samples is an important first step in understanding the biology and ecology of microbial communities in complex environments. Despite a wealth of algorithms and tools for metagenomic classification, relatively little effort has been put into the critical task of improving the quality of reference indices to which metagenomic reads are assigned. Here, we inferred the taxonomic composition of 404 publicly available metagenomes from human, marine and soil environments, using custom index databases modified according to two factors: the number of reference genomes used to build the databases, and the monophyletic strictness of species definitions. Index databases built following the NCBI taxonomic system were also compared to others using Genome Taxonomy Database (GTDB) taxonomic redefinitions. We observed a considerable increase in the rate of read classification using modified reference index databases as compared to a default NCBI RefSeq database, with up to a 4.4-, 6.4- and 2.2-fold increase in classified reads per sample for human, marine and soil metagenomes, respectively. Importantly, targeted correction for 70 common human pathogens and bacterial genera in the index database increased their specific detection levels in human metagenomes. We also show the choice of index database can influence downstream diversity and distance estimates for microbiome data. Overall, the study shows a large amount of accessible information in metagenomes remains unexploited using current methods, and that the same data analysed using different index databases could potentially lead to different conclusions. These results have implications for the power and design of individual microbiome studies, and for comparison and meta-analysis of microbiome datasets.

bioinformatics↗

bioRxiv2019

Domestication of Campylobacter jejuni NCTC 11168

Reference and type strains of well-known bacteria have been a cornerstone of microbiology research for decades. The sharing of well-characterised isolates among laboratories has parallelised research efforts and enhanced the reproducibility of experiments, leading to a wealth of knowledge about trait variation in different species and the underlying genetics. Campylobacter jejuni strain NCTC 11168, deposited at the National Collection of Type Cultures in 1977, has been adopted widely as a reference strain by researchers worldwide and was the first Campylobacter for which the complete genome was published (in 2000). In this study, we collected 23 C. jejuni NCTC 11168 reference isolates from laboratories across the UK and compared variation in simple laboratory phenotypes with genetic variation in sequenced genomes. Putatively identical isolates identified previously to have aberrant phenotypes varied by up to 281 SNPs (in 15 genes) compared to the most recent reference strain. Isolates also display considerable phenotype variation in motility, morphology, growth at 37{degrees}C, invasion of chicken and human cell lines and susceptibility to ampicillin. This study provides evidence of ongoing evolutionary change among C. jejuni isolates as they are cultured in different laboratories and highlights the need for careful consideration of genetic variation within laboratory reference strains.\n\nImpact statementIn this paper, we comment on the changing role of laboratory reference strains. While the model organism allows basic comparison within and among laboratories, it is important to remember the effect even small differences in isolate genomes can have on the validity and reproducibility of experimental work. We quantify differences in 23 reference Campylobacter genomes and compare them with observable differences in common laboratory phenotypes.\n\nData summaryShort read data are archived on the NCBI SRA associated with BioProject accession PRJNA517467 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA517467).\n\nAll assembled genomes are also available on FigShare (doi: 10.6084/m9.figshare.7849268). Phylogeny visualised on microreact: https://microreact.org/project/NCTC11168.\n\nRepositoriesShort read data are archived on the NCBI SRA repository, associated with BioProject accession PRJNA517467 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA517467; Table S1).\n\nThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

microbiology↗

bioRxiv2018

High-resolution sweep metagenomics using ultrafast read mapping and inference

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP method for identifying and estimating the relative abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our method facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

bioinformatics↗

bioRxiv2017

Epistasis mediated alleviation of the cost of antibiotic resistance for MRSA

Understanding how multi-drug resistant pathogens evolve is key to identifying means of curtailing their further emergence and dissemination. Fitness costs imposed on bacteria by resistance mechanisms are believed to hamper their dissemination in an antibiotic free environment, however, some have been reported to have little or no cost, which suggests there are few barriers preventing their global spread. One such apparently cost-free resistance mechanism acquired by the major human pathogen Staphylococcus aureus is to the clinically important antibiotic mupirocin, which is mediated by mutation of the highly-conserved and essential isoleucyl-tRNA synthethase (ileS) gene. In Genome Wide Association Studies (GWAS) on two genetically and geographically distinct MRSA lineages we have found this mutation to be associated with changes in bacterial virulence, driven through epistatic interactions with other loci. Given the potential dual effect of this mutation on both antibiotic resistance and virulence we adopted a proteomic approach and observed pleiotropic effects. This analysis revealed that the activity of the secretory apparatus of the PSM family of cytolytic toxins, the Pmt system, is affected in the mupirocin resistant mutant, which explains why it is less toxic. As an energetically costly activity, this reduction in toxicity masks the fitness costs associated with this resistance mutation, a cost that becomes apparent when toxin production is required. Given the widespread use of this antibiotic, and that this resistance often results from a single nucleotide substitution in the ileS gene, these hidden fitness costs provide an explanation for why this resistance mechanism is not more prevalent. This work also demonstrates how population-based genomic analysis of virulence and antibiotic resistance can contribute to uncovering hidden features of the biology of microbial pathogens.

microbiology↗