Biology subjects

Silander, O. K.

Publications and source records attributed to Silander, O. K..

16 recordsLinked to original sources

bioRxiv2026

Benchmarking Tools for Identification of rRNA Modifications in Escherichia coli using Oxford Nanopore Direct RNA Sequencing

RNA modifications are important for RNA structure, stability, and ribosome function, but their identification and localisation remains challenging. Oxford Nanopore direct RNA sequencing (DRS) enables modification-agnostic detection in native RNA, but existing tool benchmarks have focused almost exclusively on m6A in eukaryotic mRNA, leaving multi-modification tool performance in bacterial systems largely untested. Here, we benchmark ten RNA modification detection tools spanning signal-comparison, error-rate, and hybrid approaches on Escherichia coli K-12 MG1655 16S and 23S rRNA, which harbour 11 and 25 known modified sites, respectively, across 17 modification types. Using native RNA and in vitro transcribed (IVT) unmodified RNA, we evaluate performance across 25 coverage levels (5x to 1000x). DiffErr and JACUSA2 showed the strongest discrimination performance (AUROC >0.9 on both 16S and 23S rRNA), with DiffErr achieving the highest F1 score on 16S and JACUSA2 showing the most consistent precision-recall balance across both rRNAs. Both tools achieved full transcript-wide scoring and, along with DRUMMER, exact positional localisation. Several other tools produced no output at many rRNA positions, and restricting evaluation to reported positions inflated apparent performance. Signal-based tools showed a systematic 1-4 nucleotide 5' offset from known modified positions, consistent with the [~]5-mer nucleotide stretch present in the read head of the nanopore; applying tool-specific offset corrections substantially improved per-site recovery and reduced false positives, substantially improving the performance of tools such as EpiNano and nanoDoc. At single-site resolution, no known modified site was recovered by all tools, and several m5C, m5U, and m6A sites were missed by the majority of tools. Tool combination analysis showed that pairing error-rate-based tools with offset-corrected signal-based tools improved site recovery beyond any individual tool, with the best three-tool combination recovering 30 of the 36 known sites while maintaining low false positive rates. These results establish that discrimination metrics (e.g. AUROC) alone are insufficient to evaluate modification detection tools: output completeness, positional precision, and per-modification-type sensitivity should be reported alongside standard benchmarking metrics.

bioinformatics↗

bioRxiv2024

pyRforest: A comprehensive R package for genomic data analysis featuring scikit-learn Random Forests in R

Random Forest models are widely used in genomic data analysis and can offer insights into complex biological mechanisms, particularly when features influence the target in interactive, non-linear, or non-additive ways. Currently, some of the most efficient Random Forest methods in terms of computational speed are implemented in Python. However, many biologists use R for genomic data analysis, as R offers a unified platform for performing additional statistical analysis and visualization. Here we present an R package, pyRforest, which integrates Python scikit-learn `RandomForestClassifier` algorithms into the R environment. pyRforest inherits the efficient memory management and parallelization of Python, and is optimized for classification tasks on large genomic datasets, such as those from RNA-seq. pyRforest offers several additional capabilities, including a novel rank-based permutation method for biomarker identification. This method can be used to estimate and visualize p-values for individual features, allowing the researcher to identify a subset of features for which there is robust statistical evidence of an effect. In addition, pyRforest includes methods for the calculation and visualization of SHapley ADditive Explanations (SHAP) values. Finally, pyRforest includes support for comprehensive downstream analysis for gene ontology and pathway enrichment. pyRforest thus improves the implementation and interpretability of Random Forest models for genomic data analysis by merging the strengths of Python with R. pyRforest can be downloaded at: https://www.github.com/tkolisnik/pyRforest with an associated vignette at https://github.com/tkolisnik/pyRforest/blob/main/vignettes/pyRforest-vignette.pdf.

bioinformatics↗

bioRxiv2024

A High-quality Oxford Nanopore Assembly of the Hourglass Dolphin (Sagmatias cruciger) Genome

The hourglass dolphin (Lagenorhynchus cruciger) is a small cetacean species of the Southern Ocean, with significance to iwi M[a]ori (M[a]ori tribes) of Aotearoa New Zealand as taonga (treasured/valued). Due to the remoteness and difficulty of surveying Antarctic waters, it remains one of the least-studied dolphin species. A recent stranding of an hourglass dolphin represented a rare opportunity to generate a genome assembly as a resource for future study into the conservation and evolutionary biology of this species. In this study, we present a high-quality genome assembly of an hourglass dolphin individual using a single sequencing platform, Oxford Nanopore Technologies, coupled with computationally efficient assembly methods. Our assembly strategy yielded a genome of high contiguity (N50 of 8.07 Mbp) and quality (98.3% BUSCO completeness). Compared to other Delphinoidea reference genomes, this assembly has fewer missing BUSCOs than any except Orcinus orca, more single-copy complete BUSCOs than any except Phocoena sinus, and 20% fewer duplicated BUSCOs than the average Delphinoidea reference genome. This suggests that it is one of the most complete and accurate marine mammal genomes to date. This study showcases the feasibility of a cost-effective mammalian genome assembly method, allowing for genomic data generation outside the traditional confines of academia and/or resource-rich genome assembly hubs, and facilitating the ability to uphold Indigenous data sovereignty. In the future the genome assembly presented here will allow valuable insights into the past population size changes, adaptation, vulnerability to future climate change of the hourglass dolphin and related species.

genomics↗

bioRxiv2022

Correlated substitutions reveal SARS-like coronaviruses recombine frequently with a diverse set of structured gene pools

Quantifying SARS-like coronavirus (SL-CoV) evolution is critical to understanding the origins of SARS-CoV-2 and the molecular processes that could underlie future epidemic viruses. While genomic evidence implicates recombination as a factor in the emergence of SARS-CoV-2, few studies have quantified recombination rates among SL-CoVs. Here, we infer recombination rates of SL-CoVs from correlated substitutions in sequencing data using a coalescent model with recombination. Our computationally-efficient, non-phylogenetic method infers recombination parameters of both sampled sequences and the unsampled gene pools with which they recombine. We apply this approach to infer recombination parameters for a range of positive-sense RNA viruses. We then analyze a set of 191 SL-CoV sequences (including SARS-CoV-2) and find that ORF1ab and S genes frequently undergo recombination. We identify which SL-CoV sequence clusters have recombined with shared gene pools, and show that these pools have distinct structures and high recombination rates, with multiple recombination events occurring per synonymous substitution. We find that individual genes have recombined with different viral reservoirs. By decoupling contributions from mutation and recombination, we recover the phylogeny of non-recombined portions for many of these SL-CoVs, including the position of SARS-CoV-2 in this clonal phylogeny. Lastly, by analyzing 444,145 SARS-CoV-2 whole genome sequences, we show current diversity levels are insufficient to infer the within-population recombination rate of the virus since the pandemic began. Our work offers new methods for inferring recombination rates in RNA viruses with implications for understanding recombination in SARS-CoV-2 evolution and the structure of clonal relationships and gene pools shaping its origins. Significance StatementQuantifying the population genetics of SARS-like coronavirus (SL-CoV) evolution is vital to deciphering the origins of SARS-CoV-2 and pinpointing viruses with epidemic potential. While some Bayesian approaches can quantify recombination for these pathogens, the required simulations of recombination networks do not scale well with the massive amounts of sequences available in the genomics era. Our approach circumvents this by measuring correlated substitutions in sequences and fitting these data to a coalescent model with recombination. This allows us to analyze hundreds of thousands of sample sequences, and infer recombination rates for unsampled viral reservoirs. Our results provide insights into both the clonal relationships of sampled SL-CoV sequence clusters and the evolutionary dynamics of the gene pools with which they recombine.

evolutionary biology↗

bioRxiv2022

Bacterial lipopolysaccharide modulates immune response in the colorectal tumor microenvironment

Immune responses can have opposing effects in colorectal cancer (CRC), the balance of which may determine whether a cancer regresses, progresses, or potentially metastasizes. These effects are evident in CRC consensus molecular subtypes (CMS) where both CMS1 and CMS4 contain immune infiltrates yet have opposing prognoses. The microbiome has previously been associated with CRC and immune response in CRC but has largely been ignored in the CRC subtype discussion. Using CMS subtyping, we aimed to determine the contributions of the microbiome to the pleiotropic effects evident in immune-infiltrated subtypes. We integrated host gene-expression and meta-transcriptomic data to determine the link between immune characteristics and microbiome contributions in these subtypes and identified lipopolysaccharide (LPS) binding as a potential functional mechanism. We identified candidate bacteria with LPS properties that could affect immune response, focusing on Fusobacterium periodonticum and Bacteroides fragilis in CMS1, and Porphyromonas asaccharolytica in CMS4. Treatment of peripheral blood mononuclear cells (PBMCs) with LPS isolated from these bacteria showed that F. periodonticum stimulates cytokine production in PBMCs while both B. fragilis and P. asaccharolytica had an inhibitory effect. Furthermore, LPS from the latter two species can inhibit the immunogenic properties of F. periodonticum LPS when co-incubated with PBMCs. We propose that different microbes in the CRC tumor microenvironment can alter the local immune activity, with important implications for prognosis and treatment response.

cancer biology↗

bioRxiv2022

Growth Condition Dependent Differences in Methylation Implies Transiently Differentiated DNA Methylation States in E. coli

DNA methylation in bacteria frequently serves as a simple immune system, allowing recognition of DNA from foreign sources, such as phages or selfish genetic elements. It is not well established whether methylation also frequently serves a more general epigenetic function, modifying bacterial phenotypes in a heritable manner. To address this question, here we use Oxford Nanopore sequencing to profile DNA modification marks in three natural isolates of E. coli. We first identify the DNA sequence motifs targeted by the methyltransferases in each strain. We then quantify the frequency of methylation at each of these motifs across the genome in different growth conditions. We find that motifs in specific regions of the genome consistently exhibit high or low levels of methylation. Furthermore, we show that there are replicable and consistent differences in methylated regions across different growth conditions. This suggests that during growth, E. coli transiently differentiates into distinct methylation states that depend on the growth state, raising the possibility that measuring DNA methylation alone can be used to infer bacterial growth states without additional information such as transcriptome or proteome data. These results provide new insights into the dynamics of methylation during bacterial growth, and provide evidence of differentiated cell states, a transient analogue to what is observed in the differentiation of cell types in multicellular organisms.

microbiology↗

bioRxiv2022

Transcriptional control of the lacZ promoter is under directional and diversifying selection

Bacterial cells often respond to changes in the environment by modifying protein expression. This can be achieved through changes in transcriptional or translational activity, or both. Recent research has shed some light on how natural selection shapes overall protein expression. Still, little is known about how selection acts on transcription or translation individually. To address part of this question, we implement an experimental system which allows us to measure how genetic changes affect transcription only, excluding the effects on translation. We use this system to quantify changes in three regulatory phenotypes of the lacZ promoter: transcriptional activity, plasticity, and cell-to-cell variability. We compare these phenotypes from segregating variants that have been subject to natural selection, and random variants that have never been subjected to natural selection. We show that natural selection filters out mutations causing large changes in transcriptional levels from the lacZ promoter. Further, we detect directional selection acting on transcriptional plasticity in combinations of glucose, galactose and lactose environments. Focusing on cell-to-cell variability in transcription, we describe both directional and diversifying selection acting on this phenotype depending on the environment used. We also observe a link between the phylogeny of the environmental E. coli strains and high and low transcriptional noise levels in glucose which are mediated by just one or two SNPs. Our results thus provide new insight into how one of the most well-characterized bacterial promoters is shaped in nature by selection.

evolutionary biology↗

bioRxiv2021

Do You Want to Build a Genome? Benchmarking Hybrid Bacterial Genome Assembly Methods

Long read sequencing technologies now allow routine highly contiguous assembly of bacterial genomes. However, because of the lower accuracy of some long read data, it is often combined with short read data (e.g. Illumina), to improve assembly quality. There are a number of methods available for producing such hybrid assemblies. Here we use Illumina and Oxford Nanopore (ONT) data from 49 natural isolates of Escherichia coli to characterise differences in assembly accuracy for five assembly methods (Canu, Unicycler, Raven, Flye, and Redbean). We evaluate assembly accuracy using five metrics designed to measure structural accuracy and sequence accuracy (indel and substitution frequency). We assess structural accuracy by quantifying (1) the contiguity of chromosomes and plasmids; (2) the fraction of concordantly mapped Illumina reads withheld from the assembly; and (3) whether rRNA operons are correctly oriented. We assess indel and substitution frequency by quantifying (1) the fraction of open reading frames that appear truncated and (2) the number of variants that are called using Illumina reads only. Applying these assembly metrics to a large number of E. coli strains, we find that different assembly methods offer different advantages. In particular, we find that Unicycler assemblies have the highest sequence accuracy in non-repetitive regions, while Flye and Raven tend to be the most structurally accurate. In addition, we find that there are unidentified strain-specific characteristics that affect ONT consensus accuracy, despite individual reads having similar levels of accuracy. The differences in consensus accuracy of the ONT reads can preclude accurate assembly regardless of assembly method. These results provide quantitative insight into the best approaches for hybrid assembly of bacterial genomes and the expected levels of structural and sequence accuracy. They also show that there are intrinsic idiosyncratic strain-level differences that inhibit accurate long read bacterial genome assembly. However, we also show it is possible to diagnose problematic assemblies, even in the absence of ground truth, by comparing long-read first and short-read first assemblies. Author NotesAll supporting data, code and protocols have been provided within the article or through supplementary data files. The supporting code is available from the GitHub repository https://github.com/GeorgiaBreckell/assembly_pipeline. nine supplementary figures and three supplementary tables are available with the online version of this article. Data summarySequence data and genome assemblies for the natural isolates are available at https://www.ebi.ac.uk/ena/browser/view/PRJEB36951. Genome assemblies for additional E. coli strains used here are available from NCBI: (MG1655, SE11, REL606, CFT073, W, IA136, O157:H7-EDL933)

genomics↗

bioRxiv2021

Long read sequencing reveals atypical mitochondrial genome structure in a New Zealand marine isopod

Most animal mitochondrial genomes are small, circular, and structurally conserved. However, recent work indicates that diverse taxa possess unusual mitochondrial genomes. In Isopoda, species in multiple lineages have atypical and rearranged mitochondrial genomes. However, more species of this speciose taxon need to be evaluated to understand the evolutionary origins of atypical mitochondrial genomes in this group. In this study, we report the presence of an atypical mitochondrial structure in the New Zealand endemic marine isopod, Isocladus armatus. Data from long and short read DNA sequencing, suggests that I. armatus has two mitochondrial chromosomes. The first chromosome consists of two mitochondrial genomes that have been inverted and fused together in a circular form, and the second chromosome consists of a single mitochondrial genome in a linearized form. This atypical mitochondrial structure has been detected in other isopod lineages, and our data from an additional divergent isopod lineage (Sphaeromatidae) lends support to the hypothesis that atypical structure evolved early in the evolution of Isopoda. Additionally, we find that a heteroplasmic site previously observed across many species within Isopoda is absent in I. armatus, but confirm the presence of two heteroplasmic sites recently reported in two other isopod species.

genomics↗

bioRxiv2021

Gene regulation is commonly selected for high plasticity and low noise

Bacteria often respond to dynamically changing environments by regulating gene expression. Despite this regulation being critically important for growth and survival, little is known about how selection shapes gene regulation in natural populations. To better understand the role natural selection plays in shaping bacterial gene regulation, here we compare differences in the regulatory behaviour of naturally segregating promoter variants from Escherichia coli (which have been subject to natural selection) to randomly mutated promoter variants (which have never been exposed to natural selection). We quantify gene expression phenotypes (expression level, plasticity, and noise) for hundreds of promoter variants across multiple environments, and show that segregating promoter variants are enriched for mutations with minimal effects on expression level. In many promoters, we infer that there is strong selection to maintain high levels of plasticity, and direct selection to decrease or increase cell-to-cell variability in expression. Finally, taking an integrated view, we show that across all phenotypes combined, segregating promoter variants are far more phenotypically similar than would be expected given their genetic divergence. This is the consequence of both stabilizing and directional selection acting on individual phenotypes to minimize differences among segregating variants. Taken together, these results expand our knowledge of how gene regulation is affected by natural selection and highlight the power of comparing naturally segregating polymorphisms to de novo random mutations to quantify the action of selection.

evolutionary biology↗

bioRxiv2021

Efficiency of the synthetic self-splicing RiboJ ribozyme is robust to cis- and trans-changes in genetic background

The expanding knowledge of the variety of synthetic genetic elements has enabled the construction of new and more efficient genetic circuits and yielded novel insights into molecular mechanisms. However, context dependence, in which interactions between proximal (cis) or distal (trans) elements affect the behaviour of these elements, can reduce their general applicability or predictability. Genetic insulators, which mitigate unintended context-dependent cis-interactions, have been used to address this issue. One of the most commonly used genetic insulators is a self-splicing ribozyme called RiboJ, which can be used to decouple upstream 5 UTR in mRNA from downstream sequences (e.g., open reading frames). Despite its general use as an insulator, there has been no systematic study quantifying the efficiency of RiboJ splicing or whether this autocatalytic activity is robust to trans- and cis-genetic context. Here, we determine the robustness of RiboJ splicing in the genetic context of six widely divergent E. coli strains. We also check for possible cis-effects by assessing two SNP versions close to the catalytic site of RiboJ. We show that mRNA molecules containing RiboJ are rapidly spliced even during rapid exponential growth and high levels of gene expression, with a mean efficiency of 98%. We also show that neither the cis- nor trans-genetic context has a significant impact on RiboJ activity, suggesting this element is robust to both cis- and trans-genetic changes.

synthetic biology↗

bioRxiv2020

Bac-PULCE: Bacterial Strain and AMR Profiling Using Long Reads via CRISPR Enrichment

Rapid identification of bacterial pathogens and their antimicrobial resistance (AMR) profiles is critical for minimising patient morbidity and mortality. While many sequencing methods allow deep genomic and metagenomic profiling of samples, widespread use (for example atpoint-of-care settings) is impeded because substantial sequencing and computational infrastructure is required for sequencing and analysis. Here we present Bac-PULCE (Bacterial strain and antimicrobial resistance Profiling Using Long reads via CRISPR Enrichment), which combines CRISPR-cas9 based targeted sequence enrichment with long-read sequencing. We show that this method allows simultaneous bacterial strain-level identification and antimicrobial resistance profiling of single isolates or metagenomic samples with minimal sequencing throughput. In contrast to short read sequencing, long read sequencing used in Bac-PULCE enables strain-level resolution even when targeting and sequencing highly conserved genomic regions, such as 16S rRNA. We show that these long reads allow sequencing of additional AMR genes linked to the targeted region. Additionally, long reads can be used to identify which species in a metagenomic sample harbour specific AMR loci. The ability to massively multiplex crRNAs suggests that this method has the potential to substantially increase the speed and specificity of pathogen strain identification and AMR profiling, while ensuring low computational overhead. ImportanceThere is a critical need for rapid and identification of bacterial strains and antibiotic resistance profiles in clinical settings. However, most current methods require both substantial laboratory infrastructure (e.g. for DNA sequencing), substantial compute infrastructure (e.g. for bioinformatic analyses), or both. Here we present a new method, Bac-PULCE, (Bacterial strain and antimicrobial resistance Profiling Using Long reads via CRISPR Enrichment), which combines CRISPR-cas9 based targeted sequence enrichment with long-read sequencing on the Oxford Nanopore platform. This allows rapid profiling of bacterial strains and antibiotic resistance genes in a sample while requiring very little laboratory or computational infrastructure.

genomics↗

bioRxiv2020

Rapid and Inexpensive Whole-Genome Sequencing of SARS-CoV2 using 1200 bp Tiled Amplicons and Oxford Nanopore Rapid Barcoding

Rapid and cost-efficient whole-genome sequencing of SARS-CoV-2, the virus that causes COVID-19, is critical for understanding viral transmission dynamics. Here we show that using a new multiplexed set of primers in conjunction with the Oxford Nanopore Rapid Barcode library kit allows for faster, simpler, and less expensive SARS-CoV-2 genome sequencing. This primer set results in amplicons that exhibit lower levels of variation in coverage compared to other commonly used primer sets. Using five SARS-CoV-2 patient samples with Cq values between 20 and 31, we show that high-quality genomes can be generated with as few as 10,000 reads (approximately 5 Mbp of sequence data). We also show that mis-classification of barcodes, which may be more likely when using the Oxford Nanopore Rapid Barcode library prep, is unlikely to cause problems in variant calling. This method reduces the time from RNA to genome sequence by more than half compared to the more standard ligation-based Oxford Nanopore library preparation method at considerably lower costs.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genomics↗

bioRxiv2020

Population Structure in a Direct-Developing Marine Isopod

Marine organisms generally exhibit one of two developmental modes: biphasic, with distinct adult and larval morphology, and direct development, in which larvae resemble adults. Developmental mode is thought to significantly influence dispersal, with direct developers expected to have much lower dispersal potential. However, in contrast to our relatively good understanding of dispersal and population connectivity for biphasic species, comparatively little is known about direct developers. In this study, we use a panel of 8,020 SNPs to investigate population structure and gene flow for a direct developing species, the New Zealand endemic marine isopod Isocladus armatus. On a small spatial scale (20 kms), gene flow between locations is extremely high and suggests an island model of migration. However, over larger spatial scales (600km), populations exhibit a clear pattern of isolation-by-distance. Because our sampling range is intersected by two well-known biogeographic barriers (the East Cape and the Cook Strait), our study provides an opportunity to understand how such barriers influence dispersal in direct developers. Our results indicate that I. armatus exhibits significant migration across these barriers, and suggests that ocean currents associated with these locations do not present a barrier to dispersal. Interestingly, we do find evidence of a north-south population genetic break occurring between M[a]hia and Wellington, two locations where there are no obvious biogeographic barriers between them. We conclude that developmental life history largely predicts dispersal in intertidal marine isopods. However, localised biogeographic processes can disrupt this expectation.

ecology↗

bioRxiv2019

The advantages and disadvantages of short- and long-read metagenomics to infer bacterial and eukaryotic community composition

BackgroundThe first step in understanding ecological community diversity and dynamics is quantifying community membership. An increasingly common method for doing so is through metagenomics. Because of the rapidly increasing popularity of this approach, a large number of computational tools and pipelines are available for analysing metagenomic data. However, the majority of these tools have been designed and benchmarked using highly accurate short read data (i.e. illumina), with few studies benchmarking classification accuracy for long error-prone reads (PacBio or Oxford Nanopore). In addition, few tools have been benchmarked for non-microbial communities.\n\nResultsHere we use simulated error prone Oxford Nanopore and high accuracy Illumina read sets to systematically investigate the effects of sequence length and taxon type on classification accuracy for metagenomic data from both microbial and non-microbial communities. We show that very generally, classification accuracy is far lower for non-microbial communities, even at low taxonomic resolution (e.g. family rather than genus).\n\nConclusionsWe then show that for two popular taxonomic classifiers, long error-prone reads can significantly increase classification accuracy, and this is most pronounced for non-microbial communities. This work provides insight on the expected accuracy for metagenomic analyses for different taxonomic groups, and establishes the point at which read length becomes more important than error rate for assigning the correct taxon.

bioinformatics↗

bioRxiv2018

New tools for diet analyses: nanopore sequencing of metagenomic DNA from stomach contents to quantify diet in an invasive population of rats

BackgroundUsing metagenomics to determine animal diet offers a new and promising alternative to current methods. Here we show that rapid and inexpensive diet quantification is possible through metagenomic sequencing with the portable Oxford Nanopore Technologies (ONT) MinION. Using an amplification-free approach, we profiled the stomach contents from wild-caught rats. ResultsWe conservatively identified diet items from over 50 taxonomic orders, ranging across nine phyla that include plants, vertebrates, invertebrates, and fungi. This highlights the wide range of taxa that can be identified using this simple approach. We calibrate the accuracy of this method by comparing the characteristics of reads matching the ground-truth host genome (rat) to those matching diet items, and show that at the family-level, false positive taxon assignments are approximately 97.5% accurate. We also suggest a way to mitigate for database biases in metagenomic approaches. Finally, we implement a constrained ordination analysis and show that we can identify the sampling location of an individual rat within tens of kilometres based on diet content alone. ConclusionsThis work establishes proof-of-principle for long-read metagenomic methods in quantitative diet analysis. We show that diet content can be quantified even with limited expertise, using a simple, amplification free workflow and a relatively inexpensive and accessible next generation sequencing method. Continued increases in the accuracy and throughput of ONT sequencing, along with improved genomic databases, suggests that a metagenomic approach to quantification of animal diets will become an important method in the future.

ecology↗