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The Enterobacteriaceae are a scientifically and medically important clade of bacteria, containing the gut commensal and model organismEscherichia coli, as well as several major human pathogens including multiple serovars ofSalmonella entericaandKlebsiella pneumoniae. Essential gene sets have been determined for several members of the Enterobacteriaceae, with theE. coliKeio single-gene deletion library often regarded as a gold standard for gene essentiality studies. However, it remains unclear how gene essentiality varies between related strains and species. To investigate this, we have assembled a collection of thirteen sequenced high-density transposon mutant libraries from five genera within the Enterobacteriaceae. We first benchmark a number of gene essentiality prediction approaches, investigate the effects of transposon density on essentiality prediction, and identify biases in transposon insertion sequencing data. Based on these investigations we develop a new classifier for gene essentiality. Using this new classifier, we define a core essential genome in the Enterobacteriaceae of 201 universally essential genes, and reconstruct an ancestral essential gene set of 296 genes. Despite the presence of a large cohort of variably essential genes, surprisingly we find an absence of evidence for genus-specific essential genes. A clear example of this sporadic essentiality is given by the set of genes regulating the σEextracytoplasmic stress response, which appears to have independently become essential multiple times in the Enterobacteriaceae. Finally, we compare our essential gene sets to the natural experiment of gene loss in obligate insect endosymbionts that have emerged from within the Enterobacteriaceae. This isolates a remarkably small set of genes absolutely required for survival, and uncovers several instances of essential stress responses masked by redundancy in free-living bacteria.

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.

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.

MotivationRecombinant 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.ResultsWe have discovered that global structural flexibility, which can be modeled by normalised B-factors, accurately predicts the solubility of 12,216 recombinant proteins expressed in Escherichia coli. We have optimised 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 maximising both protein expression and solubility.AvailabilityThe 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_paper2020.

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. This paper identifies a Serratia jumbo phage that, on infection, leads to the formation of a nucleus-like structure that protects phage DNA from CRISPR–Cas defence systems. However, the phage is still susceptible to CRISPR–Cas RNA targeting in the cytoplasm.

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., Comment: Minor updates

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.

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., Graphical Abstract Graphical AbstractOptimising recombinant protein production using TISIGNER.com

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.

MotivationSignal peptides are responsible for protein transport and secretion and are ubiquitous to all forms of life. The annotation of signal peptides is important for understanding protein translocation and toxin secretion and evolution.ResultsHere we explore the features of these signal sequences from eukaryotic proteins. Strikingly, we find that the signal peptides from secretory toxins have common features across kingdoms, supporting the idea of horizontal gene transfer or convergence of toxin genes across kingdoms. We leverage these features to build Razor, a simple yet powerful tool specialised in identifying signal peptides from toxins using the first 23 N-terminal residues. We demonstrate the usability of Razor by analysing all the sequences reviewed by UniProt. Indeed, Razor is able to identify toxins using their N-terminal sequences only. Strikingly, we also discover that many defensive proteins across kingdoms harbour a toxin-like signal peptide; some of these defensive proteins have emerged through convergent evolution, e.g. defensin and defensin-like protein families, and phospholipase families. In sum, Razor uses an approach independent of homology search to identify novel and known toxin classes across species using N-terminal residues.Availability and implementationRazor is available as a web application (https://tisigner.com/razor) and a command-line tool (https://github.com/Gardner-BinfLab/Razor).

Proteins and non-coding RNAs are functional products of the genome that carry out the bulk of crucial cellular processes. With recent technological advances, researchers can sequence genomes in the thousands as well as probe for specific genomic activities of multiple species and conditions. These studies have identified thousands of potential proteins, RNAs and associated activities, however there are conflicting conclusions on the functional implications depending upon the burden of evidence researchers use, leading to diverse interpretations of which regions of the genome are “functional”. Here we investigate the association between gene functionality and genomic features, by comparing established functional protein-coding and non-coding genes to non-genic regions of the genome. We find that the strongest and most consistent association between functional genes and any genomic feature is evolutionary conservation and transcriptional activity. Other strongly associated features include sequence alignment statistics, such as maximum between-site covariation. We have also identified some concerns with 1,000 Genomes Project and Genome Aggregation Database SNP densities, as short non-coding RNAs tend to have greater than expected SNP densities. Our results demonstrate the importance of evolutionary conservation and transcription for sequence functionality, which should both be taken into consideration when differentiating between functional sequences and noise.

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.

Planning experiments using accurate prediction algorithms could mitigate failures in recombinant protein production. We have developed TISIGNER.com with the aim of addressing the technical challenges in recombinant protein production. We offer two web services, TIsigner (Translation Initiation coding region designer) and SoDoPE (Soluble Domain for Protein Expression), which are specialised in prediction/optimisation of recombinant protein expression and solubility, respectively. Importantly, TIsigner and SoDoPE are linked, which allows users to switch between the tools when optimising their genes of interest.

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.

Ngatiwai Trust Board. et al., 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., N.J.G. acknowledges the support of Ngatiwai iwi, Allan Wilson Centre, University of Otago, New Zealand Department of Conservation, New Zealand Genomics and Illumina. J.I.A. was supported by CONICYT National Doctoral Scholarship No. 21130515. M.W. was supported by NIH grant R35 GM124827. Ensembl annotation was supported by the Wellcome Trust (WT108749/Z/15/Z) and the European Molecular Biology Laboratory.

DNA-based techniques are increasingly used for measuring the biodiversity (species presence, identity, abundance and community composition) of terrestrial and aquatic ecosystems. While there are numerous reviews of molecular methods and bioinformatic steps, there has been little consideration of the methods used to collect samples upon which these later steps are based. This represents a critical knowledge gap, as methodologically sound field sampling is the foundation for subsequent analyses. We reviewed field sampling methods used for metabarcoding studies of both terrestrial and freshwater ecosystem biodiversity over a nearly three-year period (n = 75). We found that 95% (n = 71) of these studies used subjective sampling methods and inappropriate field methods and/or failed to provide critical methodological information. It would be possible for researchers to replicate only 5% of the metabarcoding studies in our sample, a poorer level of reproducibility than for ecological studies in general. Our findings suggest greater attention to field sampling methods, and reporting is necessary in eDNA-based studies of biodiversity to ensure robust outcomes and future reproducibility. Methods must be fully and accurately reported, and protocols developed that minimize subjectivity. Standardization of sampling protocols would be one way to help to improve reproducibility and have additional benefits in allowing compilation and comparison of data from across studies.

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., Author summary Recombinant proteins are widely used as therapeutics, such as vaccines, monoclonal antibodies, hormones and enzymes. However, the success rate of recombinant protein production is about 50%. To address this problem, we propose optimising the unpairing propensities of nucleotides around translation initiation sites using a thermodynamic quantity called mRNA accessibility. Our study shows that this method is generalisable across prokaryotic and eukaryotic expression hosts. Importantly, we validated this method using laboratory experiments and computational modelling. Furthermore, we propose a low cost technique to tune protein expression by engineering minimal changes to genes of interest through our web application (https://tisigner.com/tisigner).