Retrospective application of transposon-directed insertion-site sequencing to investigate niche-specific virulence of Salmonella Typhimurium in cattle

Randomly barcoded transposon mutant libraries for gut commensals I: Strategies for efficient library construction

Randomly barcoded transposon mutant libraries are powerful tools for studying gene function and organization, assessing gene essentiality and pathways, discovering potential therapeutic targets, and understanding the physiology of gut bacteria and their interactions with the host. However, construction of high-quality libraries with uniform representation can be challenging. In this review, we survey various strategies for barcoded library construction, including transposition systems, methods of transposon delivery, optimal library size, and transconjugant selection schemes. We discuss the advantages and limitations of each approach, as well as factors to consider when selecting a strategy. In addition, we highlight experimental and computational advances in arraying condensed libraries from mutant pools. We focus on examples of successful library construction in gut bacteria and their application to gene function studies and drug discovery. Given the need for understanding gene function and organization in gut bacteria, we provide a comprehensive guide for researchers to construct randomly barcoded transposon mutant libraries.

The advantage of intergenic regions as genomic features for machine-learning-based host attribution of Salmonella Typhimurium from the USA

Salmonella enterica is a taxonomically diverse pathogen with over 2600 serovars associated with a wide variety of animal hosts including humans, other mammals, birds and reptiles. Some serovars are host-specific or host-restricted and cause disease in distinct host species, while others, such as serovar S. Typhimurium (STm), are generalists and have the potential to colonize a wide variety of species. However, even within generalist serovars such as STm it is becoming clear that pathovariants exist that differ in tropism and virulence. Identifying the genetic factors underlying host specificity is complex, but the availability of thousands of genome sequences and advances in machine learning have made it possible to build specific host prediction models to aid outbreak control and predict the human pathogenic potential of isolates from animals and other reservoirs. We have advanced this area by building host-association prediction models trained on a wide range of genomic features and compared them with predictions based on nearest-neighbour phylogeny. SNPs, protein variants (PVs), antimicrobial resistance (AMR) profiles and intergenic regions (IGRs) were extracted from 3883 high-quality STm assemblies collected from humans, swine, bovine and poultry in the USA, and used to construct Random Forest (RF) machine learning models. An additional 244 recent STm assemblies from farm animals were used as a test set for further validation. The models based on PVs and IGRs had the best performance in terms of predicting the host of origin of isolates and outperformed nearest-neighbour phylogenetic host prediction as well as models based on SNPs or AMR data. However, the models did not yield reliable predictions when tested with isolates that were phylogenetically distinct from the training set. The IGR and PV models were often able to differentiate human isolates in clusters where the majority of isolates were from a single animal source. Notably, IGRs were the feature with the best performance across multiple models which may be due to IGRs acting as both a representation of their flanking genes, equivalent to PVs, while also capturing genomic regulatory variation, such as altered promoter regions. The IGR and PV models predict that ~45 % of the human infections with STm in the USA originate from bovine, ~40 % from poultry and ~14.5 % from swine, although sequences of isolates from other sources were not used for training. In summary, the research demonstrates a significant gain in accuracy for models with IGRs and PVs as features compared to SNP-based and core genome phylogeny predictions when applied within the existing population structure. This article contains data hosted by Microreact.

Novel method to recover Salmonella enterica cells for Tn-Seq approaches from lettuce leaves and agricultural environments using combination of sonication, filtration, and dialysis membrane

Salmonella enterica in agricultural environments has become an important concern, due to its potential transmission to humans and the associated public health risks. To identify genes contributing to Salmonella adaptation to such environments, transposon sequencing has been used in recent years. However, isolating Salmonella from atypical hosts, such as plant leaves, can pose technical challenges due to low bacterial content and the difficulty to separate an adequate number of bacteria from host tissues. In this study, we describe a modified methodology using a combination of sonication and filtration to recover S. enterica cells from lettuce leaves. We successfully recovered over a total of 3.5 × 106Salmonella cells in each biological replicate from two six-week old lettuce leaves, 7 days after infiltration with a Salmonella suspension of 5 × 107 colony forming units (CFU)/mL. Moreover, we have developed a dialysis membrane system as an alternative method for recovering bacteria from culture medium, mimicking a natural environment. Inoculating 107 CFU/mL of Salmonella into the media based on plant (lettuce and tomato) leaf and diluvial sand soil, a final concentration of 109.5 and 108.5 CFU/mL was obtained, respectively. One millilitre of the bacterial suspension after 24 h incubation at 28 °C using 60 rpm agitation was pelleted, corresponding to 109.5 and 108.5 cells from leaf- or soil-based media. The recovered bacterial population, from both lettuce leaves and environment-mimicking media, can adequately cover a presumptive library density of 106 mutants. In conclusion, this protocol provides an effective method to recover a Salmonella transposon sequencing library from in planta and in vitro systems. We expect this novel technique to foster the study of Salmonella in atypical hosts and environments, as well as other comparable scenarios.

Comparative genome analysis of Salmonella enterica serovar Gallinarum biovars Pullorum and Gallinarum decodes strain specific genes

Salmonella enterica serovar Gallinarum biovar Pullorum (bvP) and biovar Gallinarum (bvG) are the etiological agents of pullorum disease (PD) and fowl typhoid (FT) respectively, which cause huge economic losses to poultry industry especially in developing countries including India. Vaccination and biosecurity measures are currently being employed to control and reduce the S. Gallinarum infections. High endemicity, poor implementation of hygiene and lack of effective vaccines pose challenges in prevention and control of disease in intensively maintained poultry flocks. Comparative genome analysis unravels similarities and dissimilarities thus facilitating identification of genomic features that aids in pathogenesis, niche adaptation and in tracing of evolutionary history. The present investigation was carried out to assess the genotypic differences amongst S.enterica serovar Gallinarum strains including Indian strain S. Gallinarum Sal40 VTCCBAA614. The comparative genome analysis revealed an open pan-genome consisting of 5091 coding sequence (CDS) with 3270 CDS belonging to core-genome, 1254 CDS to dispensable genome and strain specific genes i.e. singletons ranging from 3 to 102 amongst the analyzed strains. Moreover, the investigated strains exhibited diversity in genomic features such as virulence factors, genomic islands, prophage regions, toxin-antitoxin cassettes, and acquired antimicrobial resistance genes. Core genome identified in the study can give important leads in the direction of design of rapid and reliable diagnostics, and vaccine design for effective infection control as well as eradication. Additionally, the identified genetic differences among the S. enterica serovar Gallinarum strains could be used for bacterial typing, structure based inhibitor development by future experimental investigations on the data generated.

Salmonella pathogenesis and host-adaptation in farmed animals

Salmonella is an animal and zoonotic pathogen of global importance. Depending on pathogen and host factors, infections can be asymptomatic or involve acute gastroenteritis or invasive disease. Genomic signatures associated with host-range, tissue tropism or differential virulence of Salmonella enterica serovars, and their variants, have emerged. In turn, it is becoming feasible to predict invasive potential, host-adaptation and zoonotic risk of Salmonella from sequence data to improve outbreak investigation, risk assessment and control strategies. Functional annotation of Salmonella genomes has accelerated with the screening of high-density mutant libraries, revealing host-specific, niche-specific and serovar-specific virulence factors. As natural hosts and reservoirs, farmed animals provide powerful insights into host-adaptation and pathogenesis of Salmonella not always evident from surrogate rodent or cell-based models.

Cross-species RNA-seq for deciphering host-microbe interactions

The human body is constantly exposed to microorganisms, which entails manifold interactions between human cells and diverse commensal or pathogenic bacteria. The cellular states of the interacting cells are decisive for the outcome of these encounters such as whether bacterial virulence programmes and host defence or tolerance mechanisms are induced. This Review summarizes how next-generation RNA sequencing (RNA-seq) has become a primary technology to study host-microbe interactions with high resolution, improving our understanding of the physiological consequences and the mechanisms at play. We illustrate how the discriminatory power and sensitivity of RNA-seq helps to dissect increasingly complex cellular interactions in time and space down to the single-cell level. We also outline how future transcriptomics may answer currently open questions in host-microbe interactions and inform treatment schemes for microbial disorders.

AlbaTraDIS: Comparative analysis of large datasets from parallel transposon mutagenesis experiments

Bacteria need to survive in a wide range of environments. Currently, there is an incomplete understanding of the genetic basis for mechanisms underpinning survival in stressful conditions, such as the presence of anti-microbials. Transposon directed insertion-site sequencing (TraDIS) is a powerful tool to identify genes and networks which are involved in survival and fitness under a given condition by simultaneously assaying the fitness of millions of mutants, thereby relating genotype to phenotype and contributing to an understanding of bacterial cell biology. A recent refinement of this approach allows the roles of essential genes in conditional stress survival to be inferred by altering their expression. These advancements combined with the rapidly falling costs of sequencing now allows comparisons between multiple experiments to identify commonalities in stress responses to different conditions. This capacity however poses a new challenge for analysis of multiple data sets in conjunction. To address this analysis need, we have developed ‘AlbaTraDIS’; a software application for rapid large-scale comparative analysis of TraDIS experiments that predicts the impact of transposon insertions on nearby genes. AlbaTraDIS can identify genes which are up or down regulated, or inactivated, between multiple conditions, producing a filtered list of genes for further experimental validation as well as several accompanying data visualisations. We demonstrate the utility of our new approach by applying it to identify genes used by Escherichia coli to survive in a wide range of different concentrations of the biocide Triclosan. AlbaTraDIS identified all well characterised Triclosan resistance genes, including the primary target, fabI. A number of new loci were also implicated in Triclosan resistance and the predicted phenotypes for a selection of these were validated experimentally with results being consistent with predictions. AlbaTraDIS provides a simple and rapid method to analyse multiple transposon mutagenesis data sets allowing this technology to be used at large scale. To our knowledge this is the only tool currently available that can perform these tasks. AlbaTraDIS is written in Python 3 and is available under the open source licence GNU GPL 3 from https://github.com/quadram-institute-bioscience/albatradis.

A decade of advances in transposon-insertion sequencing

It has been 10 years since the introduction of modern transposon-insertion sequencing (TIS) methods, which combine genome-wide transposon mutagenesis with high-throughput sequencing to estimate the fitness contribution or essentiality of each genetic component in a bacterial genome. Four TIS variations were published in 2009: transposon sequencing (Tn-Seq), transposon-directed insertion site sequencing (TraDIS), insertion sequencing (INSeq) and high-throughput insertion tracking by deep sequencing (HITS). TIS has since become an important tool for molecular microbiologists, being one of the few genome-wide techniques that directly links phenotype to genotype and ultimately can assign gene function. In this Review, we discuss the recent applications of TIS to answer overarching biological questions. We explore emerging and multidisciplinary methods that build on TIS, with an eye towards future applications.

In this Review, several experts discuss progress in the decade since the development of transposon-based approaches for bacterial genetic screens. They describe how advances in both experimental technologies and analytical strategies are resulting in insights into diverse biological processes.

Metabolic and genetic basis for auxotrophies in Gram-negative species

Auxotrophies constrain the interactions of bacteria with their environment, but are often difficult to identify. Here, we develop an algorithm (AuxoFind) using genome-scale metabolic reconstruction to predict auxotrophies and apply it to a series of available genome sequences of over 1,300 Gram-negative strains. We identify 54 auxotrophs, along with the corresponding metabolic and genetic basis, using a pangenome approach, and highlight auxotrophies conferring a fitness advantage in vivo. We show that the metabolic basis of auxotrophy is species-dependent and varies with 1) pathway structure, 2) enzyme promiscuity, and 3) network redundancy. Various levels of complexity constitute the genetic basis, including 1) deleterious single-nucleotide polymorphisms (SNPs), in-frame indels, and deletions; 2) single/multigene deletion; and 3) movement of mobile genetic elements (including prophages) combined with genomic rearrangements. Fourteen out of 19 predictions agree with experimental evidence, with the remaining cases highlighting shortcomings of sequencing, assembly, annotation, and reconstruction that prevent predictions of auxotrophies. We thus develop a framework to identify the metabolic and genetic basis for auxotrophies in Gram-negatives.

The SNAP hypothesis: Chromosomal rearrangements could emerge from positive Selection during Niche Adaptation

The relative linear order of most genes on bacterial chromosomes is not conserved over evolutionary timescales. One explanation is that selection is weak, allowing recombination to randomize gene order by genetic drift. However, most chromosomal rearrangements are deleterious to fitness. In contrast, we propose the hypothesis that rearrangements in gene order are more likely the result of selection during niche adaptation (SNAP). Partial chromosomal duplications occur very frequently by recombination between direct repeat sequences. Duplicated regions may contain tens to hundreds of genes and segregate quickly unless maintained by selection. Bacteria exposed to non-lethal selections (for example, a requirement to grow on a poor nutrient) can adapt by maintaining a duplication that includes a gene that improves relative fitness. Further improvements in fitness result from the loss or inactivation of non-selected genes within each copy of the duplication. When genes that are essential in single copy are lost from different copies of the duplication, segregation is prevented even if the original selection is lifted. Functional gene loss continues until a new genetic equilibrium is reached. The outcome is a rearranged gene order. Mathematical modelling shows that this process of positive selection to adapt to a new niche can rapidly drive rearrangements in gene order to fixation. Signature features (duplication formation and divergence) of the SNAP model were identified in natural isolates from multiple species showing that the initial two steps in the SNAP process can occur with a remarkably high frequency. Further bioinformatic and experimental analyses are required to test if and to which extend the SNAP process acts on bacterial genomes.

All life on earth has evolved from a universal common ancestor with a specific order of genes on the chromosome. This order is not maintained in modern species and the standard hypothesis is that changes reflect a lack of strong selection on gene order. Here, we propose an alternative hypothesis, SNAP. The occupation of a novel environment by bacteria is generally a trade-off situation. For example, while the bacteria may not be adapted to grow well under the new conditions, they may benefit by not having to share available resources with other microorganisms. Bacterial populations frequently acquire duplications of chromosomal segments containing genes that can help them adapt to a new environment. Other genes that are also duplicated are not required in two copies so that over time a superfluous copy can be lost. Eventually, the process of duplication and gene loss can lead to the rearrangement of the gene order in the chromosomal segment. The major benefit of this model over the standard hypothesis is that the process is driven by positive selection and can reach fixation rapidly.

Nature and consequences of interactions between Salmonella enterica serovar Dublin and host cells in cattle

Salmonella enterica is a veterinary and zoonotic pathogen of global importance. While murine and cell-based models of infection have provided considerable knowledge about the molecular basis of virulence of Salmonella, relatively little is known about salmonellosis in naturally-affected large animal hosts such as cattle, which are a reservoir of human salmonellosis. As in humans, Salmonella causes bovine disease ranging from self-limiting enteritis to systemic typhoid-like disease and exerts significant economic and welfare costs. Understanding the nature and consequences of Salmonella interactions with bovine cells will inform the design of effective vaccines and interventions to control animal and zoonotic infections. In calves challenged orally with S. Dublin expressing green fluorescent protein (GFP) we observed that the bacteria were predominantly extracellular in the distal ileal mucosa and within gut-associated lymph nodes 48 h post-infection. Intracellular bacteria, identified by flow cytometry using the GFP signal, were predominantly within MHCII⁺ macrophage-like cells. In contrast to observations from murine models, these S. Dublin-infected cells had elevated levels of MHCII and CD40 compared to both uninfected cells from the same tissue and cells from the cognate tissue of uninfected animals. Moreover, no gross changes of the architecture of infected lymph nodes were observed as was described previously in a mouse model. In order to further investigate Salmonella-macrophage interactions, net replication of S. enterica serovars that differ in virulence in cattle was measured in bovine blood-derived macrophages by enumeration of gentamicin-protected bacteria and fluorescence dilution, but did not correlate with host-specificity.

The fitness landscape of the African Salmonella Typhimurium ST313 strain D23580 reveals unique properties of the pBT1 plasmid

We have used a transposon insertion sequencing (TIS) approach to establish the fitness landscape of the African Salmonella enterica serovar Typhimurium ST313 strain D23580, to complement our previous comparative genomic and functional transcriptomic studies. We used a genome-wide transposon library with insertions every 10 nucleotides to identify genes required for survival and growth in vitro and during infection of murine macrophages. The analysis revealed genomic regions important for fitness under two in vitro growth conditions. Overall, 724 coding genes were required for optimal growth in LB medium, and 851 coding genes were required for growth in SPI-2-inducing minimal medium. These findings were consistent with the essentiality analyses of other S. Typhimurium ST19 and S. Typhi strains. The global mutagenesis approach also identified 60 sRNAs and 413 intergenic regions required for growth in at least one in vitro growth condition. By infecting murine macrophages with the transposon library, we identified 68 genes that were required for intra-macrophage replication but did not impact fitness in vitro. None of these genes were unique to S. Typhimurium D23580, consistent with a high conservation of gene function between S. Typhimurium ST313 and ST19 and suggesting that novel virulence factors are not involved in the interaction of strain D23580 with murine macrophages. We discovered that transposon insertions rarely occurred in many pBT1 plasmid-encoded genes (36), compared with genes carried by the pSLT-BT virulence plasmid and other bacterial plasmids. The key essential protein encoded by pBT1 is a cysteinyl-tRNA synthetase, and our enzymological analysis revealed that the plasmid-encoded CysRSpBT1 had a lower ability to charge tRNA than the chromosomally-encoded CysRSchr enzyme. The presence of aminoacyl-tRNA synthetases in plasmids from a range of Gram-negative and Gram-positive bacteria suggests that plasmid-encoded essential genes are more common than had been appreciated.