Paradigms of pathogenesis: targeting the mobile genetic elements of disease

VF-Pred: Predicting virulence factor using sequence alignment percentage and ensemble learning models

This study introduces VF-Pred, a novel framework developed for the purpose of detecting virulence factors (VFs) through the analysis of genomic data. VFs are crucial for pathogens to successfully infect host tissue and evade the immune system, leading to the onset of infectious diseases. Identifying VFs accurately is of utmost importance in the quest for developing potent drugs and vaccines to counter these diseases. To accomplish this, VF-Pred combines various feature engineering techniques to generate inputs for distinct machine learning classification models. The collective predictions of these models are then consolidated by a final downstream model using an innovative ensembling approach. One notable aspect of VF-Pred is the inclusion of a novel Seq-Alignment feature, which significantly enhances the accuracy of the employed machine learning algorithms. The framework was meticulously trained on 982 features obtained from extensive feature engineering, utilizing a comprehensive ensemble of 25 models. The new downstream ensembling technique adopted by VF-Pred surpasses existing stacking strategies and other ensembling methods, delivering superior performance in VF detection. There have been similar studies done earlier, VF-Pred stands out in comparison showing higher accuracy (83.5 %), higher sensitivity (87 %) towards identification of VFs. Accessible through a user-friendly web page, VF-Pred can be accessed by providing the identifier and protein sequence, enabling the prediction of high or low likelihoods of VFs. Overall, VF-Pred showcases a highly promising methodology for the identification of VFs, potentially paving the way for the development of more effective strategies in the battle against infectious diseases.

Recent trends in the use of bacteriophages as replacement of antimicrobials against food-animal pathogens

A major public health impact is associated with foodborne illnesses around the globe. Additionally, bacteria are becoming more resistant to antibiotics, which pose a global threat. Currently, many scientific efforts have been made to develop and implement new technologies to combat bacteria considering the increasing emergence of multidrug-resistant bacteria. In recent years, there has been considerable interest in using phages as biocontrol agents for foodborne pathogens in animals used for food production and in food products themselves. Foodborne outbreaks persist, globally, in many foods, some of which lack adequate methods to control any pathogenic contamination (like fresh produce). This interest may be attributed both to consumers' desire for more natural food and to the fact that foodborne outbreaks continue to occur in many foods. Poultry is the most common animal to be treated with phage therapy to control foodborne pathogens. A large number of foodborne illnesses worldwide are caused by Salmonella spp. and Campylobacter, which are found in poultry and egg products. Conventional bacteriophage-based therapy can prevent and control humans and animals from various infectious diseases. In this context, describing bacteriophage therapy based on bacterial cells may offer a breakthrough for treating bacterial infections. Large-scale production of pheasants may be economically challenging to meet the needs of the poultry market. It is also possible to produce bacteriophage therapy on a large scale at a reduced cost. Recently, they have provided an ideal platform for designing and producing immune-inducing phages. Emerging foodborne pathogens will likely be targeted by new phage products in the future. In this review article, we will mainly focus on the Bacteriophages (phages) that have been proposed as an alternative strategy to antibiotics for food animal pathogens and their use for public health and food safety.

Horizontal gene transfer enables programmable gene stability in synthetic microbiota

The functions of many microbial communities exhibit remarkable stability despite fluctuations in the compositions of these communities. To date, a mechanistic understanding of this function-composition decoupling is lacking. Statistical mechanisms have been commonly hypothesized to explain such decoupling. Here, we proposed that dynamic mechanisms, mediated by horizontal gene transfer (HGT), also enable the independence of functions from the compositions of microbial communities. We combined theoretical analysis with numerical simulations to illustrate that HGT rates can determine the stability of gene abundance in microbial communities. We further validated these predictions using engineered microbial consortia of different complexities transferring one or more than a dozen clinically isolated plasmids, as well as through the reanalysis of data from the literature. Our results demonstrate a generalizable strategy to program the gene stability of microbial communities.

Molecular Modeling the Proteins from the exo-xis Region of Lambda and Shigatoxigenic Bacteriophages

Despite decades of intensive research on bacteriophage lambda, a relatively uncharacterized region remains between the exo and xis genes. Collectively, exo-xis region genes are expressed during the earliest stages of the lytic developmental cycle and are capable of affecting the molecular events associated with the lysogenic-lytic developmental decision. In Shiga toxin-producing E. coli (STEC) and enterohemorragic E. coli (EHEC) that are responsible for food- and water-borne outbreaks throughout the world, there are distinct differences of exo-xis region genes from their counterparts in lambda phage. Together, these differences may help EHEC-specific phage and their bacterial hosts adapt to the complex environment within the human intestine. Only one exo-xis region protein, Ea8.5, has been solved to date. Here, I have used the AlphaFold and RoseTTAFold machine learning algorithms to predict the structures of six exo-xis region proteins from lambda and STEC/EHEC phages. Together, the models suggest possible roles for exo-xis region proteins in transcription and the regulation of RNA polymerase.

Full pathogen characterisation: species identification including the detection of virulence factors and antibiotic resistance genes via multiplex DNA-assays

Antibiotic resistances progressively cause treatment failures, and their spreading dynamics reached an alarming level. Some strains have already been classified as highly critical, e.g. the ones summarised by the acronym ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.). To restrain this trend and enable effective medication, as much information as possible must be obtained in the least possible time. Here, we present a DNA microarray-based assay that screens for the most important sepsis-relevant 44 pathogenic species, 360 virulence factors (mediate pathogenicity in otherwise non-pathogenic strains), and 409 antibiotic resistance genes in parallel. The assay was evaluated with 14 multidrug resistant strains, including all ESKAPE pathogens, mainly obtained from clinical isolates. We used a cost-efficient ligation-based detection platform designed to emulate the highly specific multiplex detection of padlock probes. Results could be obtained within one day, requiring approximately 4 h for amplification, application to the microarray, and detection.

Analysis of virulence factors and antibiotic resistance genes in group B streptococcus from clinical samples

BACKGROUND

Streptococcus agalacticae (Group B Streptococcus, GBS) is one of the most important causative agents of serious infections among neonates. This study was carried out to identify antibiotic resistance and virulence genes associated with GBS isolated from pregnant women.

METHODS

A total of 43 GBS isolates were obtained from 420 vaginal samples collected from HIV positive and negative women who were 13-35 weeks pregnant attending Antenatal Care at Chitungwiza and Harare Central Hospitals in Zimbabwe. Identification tests of GBS isolates was done using standard bacteriological methods and molecular identification testing. Antibiotic susceptibility testing was done using the modified Kirby-Bauer method and E-test strips. The boiling method was used to extract DNA and Polymerase Chain Reaction (PCR) was used to screen for 13 genes. Data was fed into SPSS 24.0.

RESULTS

Nine distinct virulence gene profiles were identified and hly-scpB-bca-rib 37.2% (16/43) was common. The virulence genes identified were namely hly 97.8% (42/43), scpB 90.1% (39/43), bca 86.0% (37/43), rib 69.8% (30/43) and bac 11.6% (5/43). High resistance to tetracycline 97.7% (42/43) was reported followed by 72.1% (31/43) cefazolin, 69.8% (30/43) penicillin G, 58.1% (25/43) ampicillin, 55.8% (24/43) clindamycin, 46.5% (20/43) ceftriaxone, 34.9% (15/43) chloramphenicol, and 30.2% (13/43) for both erythromycin and vancomycin using disk diffusion. Antibiotic resistance genes among the resistant and intermediate-resistant isolates showed high frequencies for tetM 97.6% (41/42) and low frequencies for ermB 34.5% (10/29), ermTR 10.3% (3/29), mefA 3.4% (1/29), tetO 2.4% (1/42) and linB 0% (0/35). The atr housekeeping gene yielded 100% (43/43) positive results, whilst the mobile genetic element IS1548 yielded 9.3% (4/43).

CONCLUSION

The study showed high prevalence of hly, scpB, bca and rib virulence genes in S. agalactiae strains isolated from pregnant women. Tetracycline resistance was predominantly caused by the tetM gene, whilst macrolide resistance was predominantly due to the presence of erm methylase, with the ermB gene being more prevalent. Multi-drug resistance coupled with the recovery of resistant isolates to antimicrobial agents such as penicillins indicates the importance of GBS surveillance and susceptibility tests. It was also observed that in vitro phenotypic resistance is not always accurately predicted by resistance genotypes.

The Not-So-Strange Case of Dr. Jekyll and Mr. Hyde in Antibiotic Research: An Interdisciplinary Opportunity

Literary-rhetorical devices like figurative language and analogy can help explain concepts that exceed our capacity to grasp intuitively. It is not surprising these devices are used to discuss virulence, pathogenesis, and antibiotics. Allusions to Robert Louis Stevenson’s Strange Case of Dr. Jekyll and Mr. Hyde seem to be used with particular frequency in research pertaining to pathogens, especially in studies contemporary with our evolving understanding of antibiotic resistance. More recent references to the text have appeared in research parsing definitions of virulence and acknowledging the role of anti-virulence in future therapeutics. While it is obvious that scientists invoke Stevenson’s story for stylistic purposes, its use could go beyond the stylistic—and might even generate rhetorical and imaginative possibilities for framing research. This perspective discusses the first published allusion to Jekyll and Hyde in reference to virulence and pathogenesis; comments on a select number of specific instances of Jekyll and Hyde in contemporary scientific literature; briefly contextualizes the novel; and concludes with the implications of a more productive engagement with humanistic disciplines in the face of antibiotic resistance.

Searching for putative virulence factors in the genomes of Shewanella indica and Shewanella algae

Bacterial pathogens are a major threat to both humans and animals worldwide. It is crucial to understand the mechanisms of various disease processes at the molecular level. Shewanella species are widespread in the environment and some are considered as emerging opportunistic human and marine mammal pathogens. In this study, putative virulence factors on the genome of Shewanella indica BW, a bacterium isolated from the Bryde's whale (Balaenoptera edeni), were determined. Additionally, for comparative purposes, putative virulence factors from two other S. indica and ten S. algae strains were also determined using the Pathosystems Resource Integration Center (PATRIC) pipeline. We confirmed the presence of previously reported virulence factors and we are proposing several new candidate virulence factors. Interestingly, the putative virulence factors were very similar between the two species with the exception of microbial collagenase which was present in all S. algae genomes, but absent in all S. indica genomes.

DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy

Virulence factors (VFs) enable pathogens to infect their hosts. A wealth of individual, disease-focused studies has identified a wide variety of VFs, and the growing mass of bacterial genome sequence data provides an opportunity for computational methods aimed at predicting VFs. Despite their attractive advantages and performance improvements, the existing methods have some limitations and drawbacks. Firstly, as the characteristics and mechanisms of VFs are continually evolving with the emergence of antibiotic resistance, it is more and more difficult to identify novel VFs using existing tools that were previously developed based on the outdated data sets; secondly, few systematic feature engineering efforts have been made to examine the utility of different types of features for model performances, as the majority of tools only focused on extracting very few types of features. By addressing the aforementioned issues, the accuracy of VF predictors can likely be significantly improved. This, in turn, would be particularly useful in the context of genome wide predictions of VFs. In this work, we present a deep learning (DL)-based hybrid framework (termed DeepVF) that is utilizing the stacking strategy to achieve more accurate identification of VFs. Using an enlarged, up-to-date dataset, DeepVF comprehensively explores a wide range of heterogeneous features with popular machine learning algorithms. Specifically, four classical algorithms, including random forest, support vector machines, extreme gradient boosting and multilayer perceptron, and three DL algorithms, including convolutional neural networks, long short-term memory networks and deep neural networks are employed to train 62 baseline models using these features. In order to integrate their individual strengths, DeepVF effectively combines these baseline models to construct the final meta model using the stacking strategy. Extensive benchmarking experiments demonstrate the effectiveness of DeepVF: it achieves a more accurate and stable performance compared with baseline models on the benchmark dataset and clearly outperforms state-of-the-art VF predictors on the independent test. Using the proposed hybrid ensemble model, a user-friendly online predictor of DeepVF (http://deepvf.erc.monash.edu/) is implemented. Furthermore, its utility, from the user's viewpoint, is compared with that of existing toolkits. We believe that DeepVF will be exploited as a useful tool for screening and identifying potential VFs from protein-coding gene sequences in bacterial genomes.

The Anti-activator QslA Negatively Regulates Phenazine-1-Carboxylic Acid Biosynthesis by Interacting With the Quorum Sensing Regulator MvfR in the Rhizobacterium Pseudomonas aeruginosa Strain PA1201

Two almost identical gene clusters (phz1 and phz2) are responsible for phenazine-1-carboxylic acid (PCA) production in Pseudomonas aeruginosa (P. aeruginosa) strain MSH (derived from strain PA1201). Here, we showed that the anti-activator QslA negatively regulated PCA biosynthesis and phz1 expression in strain PA1201 but had little effect on phz2 expression. This downregulation was mediated by a 56-bp region within the 5'-untranslated region (5'-UTR) of the phz1 promoter and was independent of LasR and RsaL signaling. QslA also negatively regulated Pseudomonas quinolone signal (PQS) production. Indeed, QslA controlled the PQS threshold concentration needed for PQS-dependent PCA biosynthesis. The quorum sensing regulator MvfR was required for the QslA-dependent inhibition of PCA production. We identified a direct protein-protein interaction between QslA and MvfR. The ligand-binding domain of MvfR (residues 123-306) was involved in this interaction. Our results suggested that MvfR bound directly to the promoter of the phz1 cluster. QslA interaction with MvfR prevented the binding of MvfR to the phz1 promoter regions. Thus, this study depicted a new mechanism by which QslA controls PCA and PQS biosynthesis in P. aeruginosa.

The Bacteriology and Its Virulence Factors in Neonatal Infections: Threats to Child Survival Strategies

BACKGROUND

Neonatal infection refers to the infection of the newborn during the first twenty-eight days of life. It is one of the causes of infant morbidity and mortality worldwide. The aim of the study is to determine the relative contribution of the different pathogens to the overall disease burden. It will also determine the mechanisms of virulence of these pathogens that cause neonatal infections at Chukwuemeka Odumegwu Ojukwu University Teaching Hospital (COOUTH), Awka.

METHODS

Biological samples were collected from 30 neonates admitted at the special care baby unit (SCBU) of COOUTH and cultured using selective media and nutrient agar. The isolates were identified using microbiological and biochemical tests. The antibiogram study was determined using Kirby-Bauer disc diffusion method on Mueller Hinton Agar. Several methods previously reported in literature were used for the characterization of the virulence factors.

RESULTS

From the 30 blood samples collected, Pseudomonas spp. (19.7%), Escherichia coli (23%), Salmonella spp. (24.6%), and Staphylococcus aureus (32.8%) were isolated. Male to female ratio of study population was 1.5: 1. The isolates were 100 % resistant to ticarcillin, cephalothin, ceftazidime, and cefuroxime but appreciably susceptible to only levofloxacin (88.85%). They were moderately susceptible to ceftriaxone/sulbactam (39.05%) and azithromycin (26.46%). Common virulence factors identified among the isolates (up to 90 %) were hemolysin, biofilm formation, and acid resistance. Less common virulence factors were proteases (50 %), deoxyribonucleases (50 %), enterotoxins (63%), and lipopolysaccharide (70%). The virulence factors were found mostly among the S. aureus isolates.

CONCLUSIONS

Pseudomonas spp., Escherichia coli, Salmonella spp., and Staphylococcus aureus were implicated in neonatal infections in the center and most of them were resistant to conventional antibiotics. The organisms showed marked virulence and multidrug resistance properties. Levofloxacin, a fluoroquinolone, had superior activity on the isolates compared to other antibiotics used in the study.

Biofilm inhibition and pathogenicity attenuation in bacteria by Proteus mirabilis

Biofilms play an important role in the antibiotic resistance of encased bacteria, and biofilm formation is regulated by quorum sensing (QS). Inhibiting the QS system may, therefore, degrade the integrity of a biofilm and expose the bacterial pathogens within it to the deleterious effects of molecules such as antibiotics. Moreover, the use of QS inhibitors (QSIs) may provide a novel approach for treating bacterial infections of aquacultures. In the present study, the bacterium Proteus mirabilis was identified as a potential producer of QSIs. Varying concentrations (0.1-1.1%) of filtrates prepared from the culture of P. mirabilis inhibited biofilm formation by the pathogens Pseudomonas aeruginosa, Vibrio harveyi and Staphylococcus aureus by as much as 58.9%, 41.5% and 41.9%, respectively. These filtrates as well as the crude aqueous extracts prepared from them increased the sensitivities of pathogens to the inhibitory effects of kanamycin. The filtrates also showed pathogenicity attenuation potential in P. aeruginosa by decreasing the production of virulence factors. Moreover, the filtrates did not influence the planktonic growth of these pathogens. The results indicate that P. mirabilis may act as a non-specific (or broad-spectrum) inhibitor of biofilm formation that will help control infectious diseases that adversely affect the aquaculture industry.

Toward a cell-free hydantoinase process: screening for expression optimization and one-step purification as well as immobilization of hydantoinase and carbamoylase

The hydantoinase process is applied for the industrial synthesis of optically pure amino acids via whole cell biocatalysis, providing a simple and well-established method to obtain the catalyst. Nevertheless, whole cell approaches also bear disadvantages like intracellular degradation reactions, transport limitations as well as low substrate solubility. In this work the hydantoinase and carbamoylase from Arthrobacter crystallopoietes DSM 20117 were investigated with respect to their applicability in a cell-free hydantoinase process. Both enzymes were heterologously expressed in Escherichia coli BL21DE3. Cultivation and induction of the hydantoinase under oxygen deficiency resulted in markedly higher specific activities and a further increase in expression was achieved by codon-optimization. Further expression conditions of the hydantoinase were tested using the microbioreactor system BioLector^®, which showed a positive effect upon the addition of 3% ethanol to the cultivation medium. Additionally, the hydantoinase and carbamoylase were successfully purified by immobilized metal ion affinity using Ni Sepharose beads as well as by functionalized magnetic beads, while the latter method was clearly more effective with respect to recovery and purification factor. Immobilization of both enzymes via functionalized magnetic beads directly from the crude cell extract was successful and resulted in specific activities that turned out to be much higher than those of the purified free enzymes.

The Sit-and-Wait Hypothesis in Bacterial Pathogens: A Theoretical Study of Durability and Virulence

The intriguing sit-and-wait hypothesis predicts that bacterial durability in the external environment is positively correlated with their virulence. Since its first proposal in 1987, the hypothesis has been spurring debates in terms of its validity in the field of bacterial virulence. As a special case of the vector-borne transmission versus virulence tradeoff, where vector is now replaced by environmental longevity, there are only sporadic studies over the last three decades showing that environmental durability is possibly linked with virulence. However, no systematic study of these works is currently available and epidemiological analysis has not been updated for the sit-and-wait hypothesis since the publication of Walther and Ewald's (2004) review. In this article, we put experimental evidence, epidemiological data and theoretical analysis together to support the sit-and-wait hypothesis. According to the epidemiological data in terms of gain and loss of virulence (+/-) and durability (+/-) phenotypes, we classify bacteria into four groups, which are: sit-and-wait pathogens (++), vector-borne pathogens (+-), obligate-intracellular bacteria (--), and free-living bacteria (-+). After that, we dive into the abundant bacterial proteomic data with the assistance of bioinformatics techniques in order to investigate the two factors at molecular level thanks to the fast development of high-throughput sequencing technology. Sequences of durability-related genes sourced from Gene Ontology and UniProt databases and virulence factors collected from Virulence Factor Database are used to search 20 corresponding bacterial proteomes in batch mode for homologous sequences via the HMMER software package. Statistical analysis only identified a modest, and not statistically significant correlation between mortality and survival time for eight non-vector-borne bacteria with sit-and-wait potentials. Meanwhile, through between-group comparisons, bacteria with higher host-mortality are significantly more durable in the external environment. The results of bioinformatics analysis correspond well with epidemiological data, that is, non-vector-borne pathogens with sit-and-wait potentials have higher number of virulence and durability genes compared with other bacterial groups. However, the conclusions are constrained by the relatively small bacterial sample size and non-standardized experimental data.

Bacteriophages and its applications: an overview

Bacteriophages (or phages), the most abundant viral entity of the planet, are omni-present in all the ecosystems. On the basis of their unique characteristics and anti-bacterial property, phages are being freshly evaluated taxonomically. Phages replicate inside the host either by lytic or lysogenic mode after infecting and using the cellular machinery of a bacterium. Since their discovery by Twort and d'Herelle in the early 1900s, phage became an important agent for combating pathogenic bacteria in clinical treatments and its related research gained momentum. However, due to recent emergence of bacterial resistance on antibiotics, applications of phage (phage therapy) become an inevitable option of research. Phage particles become popular as a biotechnological tool and treatment of pathogenic bacteria in a range of applied areas. However, there are few concerns over the application of phage-based solutions. This review deals with the updated phage taxonomy (ICTV 2015 Release and subsequent revision) and phage biology and the recent development of its application in the areas of biotechnology, biosensor, therapeutic medicine, food preservation, aquaculture diseases, pollution remediation, and wastewater treatment and issues related with limitations of phage-based remedy.

Long-term microbiota and virome in a Zürich patient after fecal transplantation against Clostridium difficile infection

Fecal microbiota transplantation (FMT) is an emerging therapeutic option for Clostridium difficile infections that are refractory to conventional treatment. FMT introduces fecal microbes into the patient's intestine that prevent the recurrence of C. difficile, leading to rapid expansion of bacteria characteristic of healthy microbiota. However, the long-term effects of FMT remain largely unknown. The C. difficile patient described in this paper revealed protracted microbiota adaptation processes from 6 to 42 months post-FMT. Ultimately, bacterial communities were donor similar, suggesting sustainable stool engraftment. Since little is known about the consequences of transmitted viruses during C. difficile infection, we also interrogated virome changes. Our approach allowed identification of about 10 phage types per sample that represented larger viral communities, and phages were found to be equally abundant in the cured patient and donor. The healthy microbiota appears to be characterized by low phage abundance. Although viruses were likely transferred, the patient established a virome distinct from the donor. Surprisingly, the patient had sequences of algal giant viruses (chloroviruses) that have not previously been reported for the human gut. Chloroviruses have not been associated with intestinal disease, but their presence in the oropharynx may influence cognitive abilities. The findings suggest that the virome is an important indicator of health or disease. A better understanding of the role of viruses in the gut ecosystem may uncover novel microbiota-modulating therapeutic strategies.

Comparative Genomic Analysis of Mannheimia haemolytica from Bovine Sources

Bovine respiratory disease is a common health problem in beef production. The primary bacterial agent involved, Mannheimia haemolytica, is a target for antimicrobial therapy and at risk for associated antimicrobial resistance development. The role of M. haemolytica in pathogenesis is linked to serotype with serotypes 1 (S1) and 6 (S6) isolated from pneumonic lesions and serotype 2 (S2) found in the upper respiratory tract of healthy animals. Here, we sequenced the genomes of 11 strains of M. haemolytica, representing all three serotypes and performed comparative genomics analysis to identify genetic features that may contribute to pathogenesis. Possible virulence associated genes were identified within 14 distinct prophage, including a periplasmic chaperone, a lipoprotein, peptidoglycan glycosyltransferase and a stress response protein. Prophage content ranged from 2–8 per genome, but was higher in S1 and S6 strains. A type I-C CRISPR-Cas system was identified in each strain with spacer diversity and organization conserved among serotypes. The majority of spacers occur in S1 and S6 strains and originate from phage suggesting that serotypes 1 and 6 may be more resistant to phage predation. However, two spacers complementary to the host chromosome targeting a UDP-N-acetylglucosamine 2-epimerase and a glycosyl transferases group 1 gene are present in S1 and S6 strains only indicating these serotypes may employ CRISPR-Cas to regulate gene expression to avoid host immune responses or enhance adhesion during infection. Integrative conjugative elements are present in nine of the eleven genomes. Three of these harbor extensive multi-drug resistance cassettes encoding resistance against the majority of drugs used to combat infection in beef cattle, including macrolides and tetracyclines used in human medicine. The findings here identify key features that are likely contributing to serotype related pathogenesis and specific targets for vaccine design intended to reduce the dependency on antibiotics to treat respiratory infection in cattle.

Historical and current perspectives on Clostridium botulinum diversity

For nearly one hundred years, researchers have attempted to categorize botulinum neurotoxin-producing clostridia and the toxins that they produce according to biochemical characterizations, serological comparisons, and genetic analyses. Throughout this period the bacteria and their toxins have defied such attempts at categorization. Below is a description of both historic and current Clostridium botulinum strain and neurotoxin information that illustrates how each new finding has significantly added to the knowledge of the botulinum neurotoxin-containing clostridia and their diversity.

Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences

Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOB_F12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ–proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

Plasmids are difficult to analyze in WGS datasets, due to the fragmented nature of the obtained sequences. We developed a method, called PLACNET, which greatly facilitates this analysis. As an example, we analyzed the plasmidome of E. coli ST131, an ExPEC clonal group involved in human urinary tract infections and septicemia. Relevant variation within this clone (e.g., antibiotic resistance and virulence) is frequently caused by the acquisition and loss of plasmids and other mobile genetic elements. Nevertheless, our knowledge of the ST131 plasmidome is limited to a few antibiotic resistance plasmids and to identification of replicons from known plasmid groups. PLACNET analysis extends the number of sequenced plasmids in ST131, which can be used for comparative genomics, from 11 to 50. The ST131 plasmidome is seemingly huge, encompassing roughly 50% of the main plasmid groups of γ–proteobacteria. MOB_F12/IncF plasmids are apparently the most active players in the dissemination of relevant genetic information.

Curation, integration and visualization of bacterial virulence factors in PATRIC

Motivation: We’ve developed a highly curated bacterial virulence factor (VF) library in PATRIC (Pathosystems Resource Integration Center, www.patricbrc.org) to support infectious disease research. Although several VF databases are available, there is still a need to incorporate new knowledge found in published experimental evidence and integrate these data with other information known for these specific VF genes, including genomic and other omics data. This integration supports the identification of VFs, comparative studies and hypothesis generation, which facilitates the understanding of virulence and pathogenicity.

Results: We have manually curated VFs from six prioritized NIAID (National Institute of Allergy and Infectious Diseases) category A–C bacterial pathogen genera, Mycobacterium, Salmonella, Escherichia, Shigella, Listeria and Bartonella, using published literature. This curated information on virulence has been integrated with data from genomic functional annotations, trancriptomic experiments, protein–protein interactions and disease information already present in PATRIC. Such integration gives researchers access to a broad array of information about these individual genes, and also to a suite of tools to perform comparative genomic and transcriptomics analysis that are available at PATRIC.

Availability and implementation: All tools and data are freely available at PATRIC (http://patricbrc.org).

Contact:cmao@vbi.vt.edu.

Supplementary information:Supplementary data are available at Bioinformatics online.

What is a pathogen? Toward a process view of host-parasite interactions

Until quite recently and since the late 19(th) century, medical microbiology has been based on the assumption that some micro-organisms are pathogens and others are not. This binary view is now strongly criticized and is even becoming untenable. We first provide a historical overview of the changing nature of host-parasite interactions, in which we argue that large-scale sequencing not only shows that identifying the roots of pathogenesis is much more complicated than previously thought, but also forces us to reconsider what a pathogen is. To address the challenge of defining a pathogen in post-genomic science, we present and discuss recent results that embrace the microbial genetic diversity (both within- and between-host) and underline the relevance of microbial ecology and evolution. By analyzing and extending earlier work on the concept of pathogen, we propose pathogenicity (or virulence) should be viewed as a dynamical feature of an interaction between a host and microbes.

Horizontal gene transfer in the innovation and adaptation of land plants

Horizontal gene transfer (HGT) has been well documented in prokaryotes and unicellular eukaryotes, but its role in plants and animals remains elusive. In a recent study, we showed that at least 57 families of nuclear genes in the moss Physcomitrella patens were acquired from prokaryotes, fungi or viruses and that HGT played a critical role in plant colonization of land. In this paper, we categorize all acquired genes based on their putative functions and biological processes, and further address the importance of HGT in plant innovation and evolution.