The PitA protein contributes to colistin susceptibility in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is an opportunistic pathogen that causes a wide range of problematic infections in individuals with predisposing conditions. Infections can be treated with colistin but some isolates are resistant to this antibiotic. To better understand the genetic basis of resistance, we experimentally evolved 19 independent resistant mutants from the susceptible laboratory strain PAO1. Whole genome sequencing identified mutations in multiple genes including phoQ and pmrB that have previously been associated with resistance, pitA that encodes a phosphate transporter, and carB and eno that encode enzymes of metabolism. Individual mutations were engineered into the genome of strain PAO1. Mutations in pitA, pmrB and phoQ increased the minimum inhibitory concentration (MIC) for colistin 8-fold, making the bacteria resistant. Engineered pitA/phoQ and pitA/pmrB double mutants had higher MICs than single mutants, demonstrating additive effects on colistin susceptibility. Single carB and eno mutations did not increase the MIC suggesting that their effect is dependent on the presence of other mutations. Many of the resistant mutants had increased susceptibility to ß-lactams and lower growth rates than the parental strain demonstrating that colistin resistance can impose a fitness cost. Two hundred and fourteen P. aeruginosa isolates from a range of sources were tested and 18 (7.8%) were colistin resistant. Sequence variants in genes identified by experimental evolution were present in the 18 resistant isolates and may contribute to resistance. Overall our results identify pitA mutations as novel contributors to colistin resistance and demonstrate that resistance can reduce fitness of the bacteria.

Finding priority bacterial ribosomes for future structural and antimicrobial research based upon global RNA and protein sequence analysis.

Ribosome-targeting antibiotics comprise over half of antibiotics used in medicine, but our fundamental knowledge of their binding sites is derived primarily from ribosome structures of non-pathogenic species. These include Thermus thermophilus, Deinococcus radiodurans and the archaean Haloarcula marismortui, as well as the commensal and sometimes pathogenic organism, Escherichia coli. Advancements in electron cryomicroscopy have allowed for the determination of more ribosome structures from pathogenic bacteria, with each study highlighting species-specific differences that had not been observed in the non-pathogenic structures. These observed differences suggest that more novel ribosome structures, particularly from pathogens, are required for a more accurate understanding of the level of diversity of the entire bacterial ribosome, with the potential of leading to innovative advancements in antibiotic research. In this study, high accuracy covariance and hidden Markov models were used to annotate ribosomal RNA and protein sequences respectively from genomic sequence, allowing us to determine the underlying ribosomal sequence diversity using phylogenetic methods. This analysis provided evidence that the current non-pathogenic ribosome structures are not sufficient representatives of some pathogenic bacteria, such as Campylobacter pylori, or of whole phyla such as Bacteroidota (Bacteroidetes).

Sustained software development, not number of citations or journal choice, is indicative of accurate bioinformatic software.

BACKGROUND: Computational biology provides software tools for testing and making inferences about biological data. In the face of increasing volumes of data, heuristic methods that trade software speed for accuracy may be employed. We have studied these trade-offs using the results of a large number of independent software benchmarks, and evaluated whether external factors, including speed, author reputation, journal impact, recency and developer efforts, are indicative of accurate software. RESULTS: We find that software speed, author reputation, journal impact, number of citations and age are unreliable predictors of software accuracy. This is unfortunate because these are frequently cited reasons for selecting software tools. However, GitHub-derived statistics and high version numbers show that accurate bioinformatic software tools are generally the product of many improvements over time. We also find an excess of slow and inaccurate bioinformatic software tools, and this is consistent across many sub-disciplines. There are few tools that are middle-of-road in terms of accuracy and speed trade-offs. CONCLUSIONS: Our findings indicate that accurate bioinformatic software is primarily the product of long-term commitments to software development. In addition, we hypothesise that bioinformatics software suffers from publication bias. Software that is intermediate in terms of both speed and accuracy may be difficult to publish-possibly due to author, editor and reviewer practises. This leaves an unfortunate hole in the literature, as ideal tools may fall into this gap. High accuracy tools are not always useful if they are slow, while high speed is not useful if the results are also inaccurate.

Analysis of 11,430 recombinant protein production experiments reveals that protein yield is tunable by synonymous codon changes of translation initiation sites.

Recombinant protein production is a key process in generating proteins of interest in the pharmaceutical industry and biomedical research. However, about 50% of recombinant proteins fail to be expressed in a variety of host cells. Here we show that the accessibility of translation initiation sites modelled using the mRNA base-unpairing across the Boltzmann's ensemble significantly outperforms alternative features. This approach accurately predicts the successes or failures of expression experiments, which utilised Escherichia coli cells to express 11,430 recombinant proteins from over 189 diverse species. On this basis, we develop TIsigner that uses simulated annealing to modify up to the first nine codons of mRNAs with synonymous substitutions. We show that accessibility captures the key propensity beyond the target region (initiation sites in this case), as a modest number of synonymous changes is sufficient to tune the recombinant protein expression levels. We build a stochastic simulation model and show that higher accessibility leads to higher protein production and slower cell growth, supporting the idea of protein cost, where cell growth is constrained by protein circuits during overexpression.

SorTn-seq: a high-throughput functional genomics approach to discovering regulators of bacterial gene expression.

We recently developed a high-throughput functional genomics approach, named 'SorTn-seq', to identify factors affecting expression of any gene of interest in bacteria. Our approach facilitates high-throughput screening of complex mutant pools, a task previously hindered by a lack of suitable techniques. SorTn-seq combines high-density, Tn5-like transposon mutagenesis with fluorescence-activated cell sorting of a strain harboring a promoter-fluorescent reporter fusion, to isolate mutants with altered gene expression. The transposon mutant pool is sorted into different bins on the basis of fluorescence, and mutants are deep-sequenced to identify transposon insertions. DNA is prepared for sequencing by using commercial kits augmented with custom primers, enhancing ease of use and reproducibility. Putative regulators are identified by comparing the number of insertions per genomic feature in the different sort bins, by using existing bioinformatic pipelines and software packages. SorTn-seq can be completed in 1-2 weeks and requires general microbiology skills and basic flow cytometry experience.

On the optimistic performance evaluation of newly introduced bioinformatic methods.

Most research articles presenting new data analysis methods claim that "the new method performs better than existing methods," but the veracity of such statements is questionable. Our manuscript discusses and illustrates consequences of the optimistic bias occurring during the evaluation of novel data analysis methods, that is, all biases resulting from, for example, selection of datasets or competing methods, better ability to fix bugs in a preferred method, and selective reporting of method variants. We quantitatively investigate this bias using an example from epigenetic analysis: normalization methods for data generated by the Illumina HumanMethylation450K BeadChip microarray.

Evolution of virulence in a novel family of transmissible mega-plasmids.

Some Serratia entomophila isolates have been successfully exploited in biopesticides due to their ability to cause amber disease in larvae of the Aotearoa (New Zealand) endemic pasture pest, Costelytra giveni. Anti-feeding prophage and ABC toxin complex virulence determinants are encoded by a 153-kb single-copy conjugative plasmid (pADAP; amber disease-associated plasmid). Despite growing understanding of the S. entomophila pADAP model plasmid, little is known about the wider plasmid family. Here, we sequence and analyse mega-plasmids from 50 Serratia isolates that induce variable disease phenotypes in the C. giveni insect host. Mega-plasmids are highly conserved within S. entomophila, but show considerable divergence in Serratia proteamaculans with other variants in S. liquefaciens and S. marcescens, likely reflecting niche adaption. In this study to reconstruct ancestral relationships for a complex mega-plasmid system, strong co-evolution between Serratia species and their plasmids were found. We identify 12 distinct mega-plasmid genotypes, all sharing a conserved gene backbone, but encoding highly variable accessory regions including virulence factors, secondary metabolite biosynthesis, Nitrogen fixation genes and toxin-antitoxin systems. We show that the variable pathogenicity of Serratia isolates is largely caused by presence/absence of virulence clusters on the mega-plasmids, but notably, is augmented by external chromosomally encoded factors.

TISIGNER.com: web services for improving recombinant protein production.

Experiments that are planned using accurate prediction algorithms will mitigate failures in recombinant protein production. We have developed TISIGNER (https://tisigner.com) with the aim of addressing technical challenges to recombinant protein production. We offer three web services, TIsigner (Translation Initiation coding region designer), SoDoPE (Soluble Domain for Protein Expression) and Razor, which are specialised in synonymous optimisation of recombinant protein expression, solubility and signal peptide analysis, respectively. Importantly, TIsigner, SoDoPE and Razor are linked, which allows users to switch between the tools when optimising genes of interest.

The Rcs stress response inversely controls surface and CRISPR-Cas adaptive immunity to discriminate plasmids and phages.

Bacteria harbour multiple innate defences and adaptive CRISPR-Cas systems that provide immunity against bacteriophages and mobile genetic elements. Although some bacteria modulate defences in response to population density, stress and metabolic state, a lack of high-throughput methods to systematically reveal regulators has hampered efforts to understand when and how immune strategies are deployed. We developed a robust approach called SorTn-seq, which combines saturation transposon mutagenesis, fluorescence-activated cell sorting and deep sequencing to characterize regulatory networks controlling CRISPR-Cas immunity in Serratia sp. ATCC 39006. We applied our technology to assess csm gene expression for ~300,000 mutants and uncovered multiple pathways regulating type III-A CRISPR-Cas expression. Mutation of igaA or mdoG activated the Rcs outer-membrane stress response, eliciting cell-surface-based innate immunity against diverse phages via the transcriptional regulators RcsB and RcsA. Activation of this Rcs phosphorelay concomitantly attenuated adaptive immunity by three distinct type I and III CRISPR-Cas systems. Rcs-mediated repression of CRISPR-Cas defence enabled increased acquisition and retention of plasmids. Dual downregulation of cell-surface receptors and adaptive immunity in response to stress by the Rcs pathway enables protection from phage infection without preventing the uptake of plasmids that may harbour beneficial traits.

ncVarDB: a manually curated database for pathogenic non-coding variants and benign controls.

Variants within the non-coding genome are frequently associated with phenotypes in genome-wide association studies. These non-coding regions may be involved in the regulation of gene expression, encode functional non-coding RNAs, or influence splicing and other cellular functions. We have curated a list of characterized non-coding human genome variants based on the published evidence that indicates phenotypic consequences of the variation. In order to minimize annotation errors, two curators have independently verified the supporting evidence for pathogenicity of each non-coding variant in the published literature. The database consists of 721 non-coding variants linked to the published literature describing the evidence of functional consequences. We have also sampled 7228 covariate-matched benign controls, that have a population frequency of over 5%, from the single nucleotide polymorphism database (dbSNP151) database. These were sampled controlling for potential confounding factors such as linkage with pathogenic variants, annotation type (untranslated region, intron, intergenic, etc.) and variant type (substitution or indel). The dataset presented here represents a curated repository, with a potential use for the training or evaluation of algorithms used in the prediction of non-coding variant functionality. Database URL: https://github.com/Gardner-BinfLab/ncVarDB.

The tuatara genome reveals ancient features of amniote evolution.

The tuatara (Sphenodon punctatus)-the only living member of the reptilian order Rhynchocephalia (Sphenodontia), once widespread across Gondwana1,2-is an iconic species that is endemic to New Zealand2,3. A key link to the now-extinct stem reptiles (from which dinosaurs, modern reptiles, birds and mammals evolved), the tuatara provides key insights into the ancestral amniotes2,4. Here we analyse the genome of the tuatara, which-at approximately 5 Gb-is among the largest of the vertebrate genomes yet assembled. Our analyses of this genome, along with comparisons with other vertebrate genomes, reinforce the uniqueness of the tuatara. Phylogenetic analyses indicate that the tuatara lineage diverged from that of snakes and lizards around 250 million years ago. This lineage also shows moderate rates of molecular evolution, with instances of punctuated evolution. Our genome sequence analysis identifies expansions of proteins, non-protein-coding RNA families and repeat elements, the latter of which show an amalgam of reptilian and mammalian features. The sequencing of the tuatara genome provides a valuable resource for deep comparative analyses of tetrapods, as well as for tuatara biology and conservation. Our study also provides important insights into both the technical challenges and the cultural obligations that are associated with genome sequencing.

Publisher Correction: The tuatara genome reveals ancient features of amniote evolution.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Solubility-Weighted Index: fast and accurate prediction of protein solubility.

MOTIVATION: Recombinant protein production is a widely used technique in the biotechnology and biomedical industries, yet only a quarter of target proteins are soluble and can therefore be purified. RESULTS: We have discovered that global structural flexibility, which can be modeled by normalized B-factors, accurately predicts the solubility of 12 216 recombinant proteins expressed in Escherichia coli. We have optimized these B-factors, and derived a new set of values for solubility scoring that further improves prediction accuracy. We call this new predictor the 'Solubility-Weighted Index' (SWI). Importantly, SWI outperforms many existing protein solubility prediction tools. Furthermore, we have developed 'SoDoPE' (Soluble Domain for Protein Expression), a web interface that allows users to choose a protein region of interest for predicting and maximizing both protein expression and solubility. AVAILABILITY AND IMPLEMENTATION: The SoDoPE web server and source code are freely available at https://tisigner.com/sodope and https://github.com/Gardner-BinfLab/TISIGNER-ReactJS, respectively. The code and data for reproducing our analysis can be found at https://github.com/Gardner-BinfLab/SoDoPE_paper_2020. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Author Correction: An evaluation of the accuracy and speed of metagenome analysis tools.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A jumbo phage that forms a nucleus-like structure evades CRISPR-Cas DNA targeting but is vulnerable to type III RNA-based immunity.

CRISPR-Cas systems provide bacteria with adaptive immunity against bacteriophages1. However, DNA modification2,3, the production of anti-CRISPR proteins4,5 and potentially other strategies enable phages to evade CRISPR-Cas. Here, we discovered a Serratia jumbo phage that evades type I CRISPR-Cas systems, but is sensitive to type III immunity. Jumbo phage infection resulted in a nucleus-like structure enclosed by a proteinaceous phage shell-a phenomenon only reported recently for distantly related Pseudomonas phages6,7. All three native CRISPR-Cas complexes in Serratia-type I-E, I-F and III-A-were spatially excluded from the phage nucleus and phage DNA was not targeted. However, the type III-A system still arrested jumbo phage infection by targeting phage RNA in the cytoplasm in a process requiring Cas7, Cas10 and an accessory nuclease. Type III, but not type I, systems frequently targeted nucleus-forming jumbo phages that were identified in global viral sequence datasets. The ability to recognize jumbo phage RNA and elicit immunity probably contributes to the presence of both RNA- and DNA-targeting CRISPR-Cas systems in many bacteria1,8. Together, our results support the model that jumbo phage nucleus-like compartments serve as a barrier to DNA-targeting, but not RNA-targeting, defences, and that this phenomenon is widespread among jumbo phages.

Essential guidelines for computational method benchmarking.

In computational biology and other sciences, researchers are frequently faced with a choice between several computational methods for performing data analyses. Benchmarking studies aim to rigorously compare the performance of different methods using well-characterized benchmark datasets, to determine the strengths of each method or to provide recommendations regarding suitable choices of methods for an analysis. However, benchmarking studies must be carefully designed and implemented to provide accurate, unbiased, and informative results. Here, we summarize key practical guidelines and recommendations for performing high-quality benchmarking analyses, based on our experiences in computational biology.

Convergent regulatory evolution and loss of flight in paleognathous birds.

A core question in evolutionary biology is whether convergent phenotypic evolution is driven by convergent molecular changes in proteins or regulatory regions. We combined phylogenomic, developmental, and epigenomic analysis of 11 new genomes of paleognathous birds, including an extinct moa, to show that convergent evolution of regulatory regions, more so than protein-coding genes, is prevalent among developmental pathways associated with independent losses of flight. A Bayesian analysis of 284,001 conserved noncoding elements, 60,665 of which are corroborated as enhancers by open chromatin states during development, identified 2355 independent accelerations along lineages of flightless paleognaths, with functional consequences for driving gene expression in the developing forelimb. Our results suggest that the genomic landscape associated with morphological convergence in ratites has a substantial shared regulatory component.

Transcriptional noise and exaptation as sources for bacterial sRNAs.

Understanding how new genes originate and integrate into cellular networks is key to understanding evolution. Bacteria present unique opportunities for both the natural history and experimental study of gene origins, due to their large effective population sizes, rapid generation times, and ease of genetic manipulation. Bacterial small non-coding RNAs (sRNAs), in particular, many of which operate through a simple antisense regulatory logic, may serve as tractable models for exploring processes of gene origin and adaptation. Understanding how and on what timescales these regulatory molecules arise has important implications for understanding the evolution of bacterial regulatory networks, in particular, for the design of comparative studies of sRNA function. Here, we introduce relevant concepts from evolutionary biology and review recent work that has begun to shed light on the timescales and processes through which non-functional transcriptional noise is co-opted to provide regulatory functions. We explore possible scenarios for sRNA origin, focusing on the co-option, or exaptation, of existing genomic structures which may provide protected spaces for sRNA evolution.

Genomic correlates of extraintestinal infection are linked with changes in cell morphology in Campylobacter jejuni.

Campylobacter jejuni is the most common cause of bacterial diarrheal disease in the world. Clinical outcomes of infection can range from asymptomatic infection to life-threatening extraintestinal infections. This variability in outcomes for infected patients has raised questions as to whether genetic differences between C. jejuni isolates contribute to their likelihood of causing severe disease. In this study, we compare the genomes of ten C. jejuni isolates that were implicated in extraintestinal infections with reference gastrointestinal isolates, in order to identify unusual patterns of sequence variation associated with infection outcome. We identified a collection of genes that display a higher burden of uncommon mutations in invasive isolates compared with gastrointestinal close relatives, including some that have been previously linked to virulence and invasiveness in C. jejuni. Among the top genes identified were mreB and pgp1, which are both involved in determining cell shape. Electron microscopy confirmed morphological differences in isolates carrying unusual sequence variants of these genes, indicating a possible relationship between extraintestinal infection and changes in cell morphology.

Identifying accurate metagenome and amplicon software via a meta-analysis of sequence to taxonomy benchmarking studies.

Metagenomic and meta-barcode DNA sequencing has rapidly become a widely-used technique for investigating a range of questions, particularly related to health and environmental monitoring. There has also been a proliferation of bioinformatic tools for analysing metagenomic and amplicon datasets, which makes selecting adequate tools a significant challenge. A number of benchmark studies have been undertaken; however, these can present conflicting results. In order to address this issue we have applied a robust Z-score ranking procedure and a network meta-analysis method to identify software tools that are consistently accurate for mapping DNA sequences to taxonomic hierarchies. Based upon these results we have identified some tools and computational strategies that produce robust predictions.