Bacterial genome sequencing and its use in infectious diseases

A System of Rapidly Detecting Escherichia Coli in Food Based on a Nanoprobe and Improved ATP Bioluminescence Technology

Bacterial contamination is an important factor causing food security issues. Among the bacteria, Escherichia coli is one of the main pathogens of food-borne microorganisms. However, traditional bacterial detection approaches cannot meet the requirements of real-time and on-site detection. Thus, it is of great significance to develop a rapid and accurate detection of bacteria in food to ensure food safety and safeguard human health. The pathogen heat-treatment module was designed in this paper based on the techniques including nanoprobe, pathogen heat-treatment, graphene transparent electrode (GTE), and adenosine triphosphate (ATP) bioluminescence technology. The system mainly consists of two parts: one is the optical detection unit; the other is the data processing unit. And it can quickly and automatically detect the number of bacterial colonies in food such as milk etc. The system uses not only the probe to capture and enrich E. coli by antigen-antibody interaction but also the heat treatment to increase the amount of ATP released from bacterial cells within five minutes. To enhance the detecting accuracy and sensitivity, the electric field generated by GTE is adopted in the system to enrich ATP. Compared to the other conventional methods, the linear correlation coefficient of the system can be reached 0.975, and the system meets the design requirements. Under the optimal experimental conditions, the detection can be completed within 25 min, and the detectable concentration of bacteria is in the range of 3.1 × 10¹–10⁶ CFU/mL. This system satisfies the demands of a fast and on-site inspection.

Computational Design of a Multi-Epitope Vaccine Against Porphyromonas gingivalis

Porphyromonas gingivalis is a Gram-negative pathogenic bacterium associated with chronic periodontitis. The development of a chimeric peptide-based vaccine targeting this pathogen could be highly beneficial in preventing oral bone loss as well as other severe gum diseases. We applied a computational framework to design a multi-epitope-based vaccine candidate against P. gingivalis. The vaccine comprises epitopes from subunit proteins prioritized from the P. gingivalis reference strain (P. gingivalis ATCC 33277) using several reported vaccine properties. Protein-based subunit vaccines were prioritized through genomics techniques. Epitope prediction was performed using immunoinformatic servers and tools. Molecular modeling approaches were used to build a putative three-dimensional structure of the vaccine to understand its interactions with host immune cells through biophysical techniques such as molecular docking simulation studies and binding free energy methods. Genome subtraction identified 18 vaccine targets: six outer-membrane, nine cytoplasmic membrane-, one periplasmic, and two extracellular proteins. These proteins passed different vaccine checks required for the successful development of a vaccine candidate. The shortlisted proteins were subjected to immunoinformatic analysis to map B-cell derived T-cell epitopes, and antigenic, water-soluble, non-toxic, and good binders of DRB1*0101 were selected. The epitopes were then modeled into a multi-epitope peptide vaccine construct (linked epitopes plus adjuvant) to enhance immunogenicity and effectively engage both innate and adaptive immunity. Further, the molecular docking approach was used to determine the binding conformation of the vaccine to TLR2 innate immune receptor. Molecular dynamics simulations and binding free energy calculations of the vaccine–TLR2 complex were performed to highlight key intermolecular binding energies. Findings of this study will be useful for vaccine developers to design an effective vaccine for chronic periodontitis pathogens, specifically P. gingivalis.

Primary Isolation of Mycobacterium ulcerans

Primary isolation of Mycobacterium ulcerans is the separation and growth of the bacterium from a mixed population either in clinical specimen or environmental specimen in pure cultures. It is a crucial activity as it can be used to monitor antimicrobial treatment, surveillance for antimicrobial resistance, and molecular epidemiology studies toward understanding pathogen ecology and transmission as well as pathogen biology. The process involves removal of unwanted fast-growing bacteria using 5% oxalic acid, inoculation on Lowenstein-Jensen medium supplemented with glycerol, and incubation at temperatures between 30 °C and 33 °C.

Staphylococcus aureus and Cystic Fibrosis-A Close Relationship. What Can We Learn from Sequencing Studies?

Staphylococcus aureus is next to Pseudomonas aeruginosa the most isolated pathogen from the airways of cystic fibrosis (CF) patients, who are often infected by a dominant S. aureus clone for extended periods. To be able to persist, the pathogen has to adapt to the hostile niche of the airways to counteract host defence, antibiotic therapy and the competition with coinfecting pathogens. S. aureus is equipped with many virulence factors including adhesins, toxins that are localized on the chromosome, on plasmids or are phage-related. S. aureus is especially versatile and adaptation and evolution of the pathogen occurs by the acquisition of new genes by horizontal gene transfer (HGT), changes in nucleotides (single nucleotide variations, SNVs) that can cause a selective advantage for the bacteria and become fixed in subpopulations. Methicillin-resistant S. aureus are a special threat to CF patients due to the more severe lung disease occurring in infected patients. Today, with decreasing costs for sequencing, more and more studies using S. aureus isolates cultured from CF patients are being published, which use whole genome sequencing (WGS), multilocus sequence typing (MLST) or spa-sequence typing (spa-typing) to follow the population dynamics of S. aureus, elucidate the underlying mechanisms of phenotypic variants, newly acquired resistance or adaptation to the host response in this particular niche. In the first part of this review, an introduction to the genetic make-up and the pathogenesis of S. aureus with respect to CF is provided. The second part presents an overview of recent studies and their findings using genotypic methods such as single or multilocus sequencing and whole genome sequencing, which identify factors contributing to the adaptation of S. aureus and its evolution in the airways of individuals with CF.

Insights Into Subspecies Discrimination Potentiality From Bacteria MALDI-TOF Mass Spectra by Using Data Mining and Diversity Studies

Bacterial identification at subspecies level is critical in clinical care and epidemiological investigations due to the different epidemic potentialities of a species. For this purpose, matrix-assisted laser desorption ionization – time-of-flight mass spectrometry (MALDI-TOF MS) has been proposed in place of molecular genotyping, but with some result discrepancies. The aim of this work is to methodically mine the expression diversities of MALDI-TOF bacterial species spectra and their possible latent organization in order to evaluate their subspecies specific expression. Peak expression diversities of MALDI-TOF spectra coming from routine identifications have been analyzed using Hill numbers, rarefaction curves, and peak clustering. Some size effect critical thresholds were estimated using change point analyses. We included 167,528 spectra corresponding to 405 species. Species spectra diversities have a broad size-dependent variability, which may be influenced by the kind of sampling. Peak organization is characterized by the presence of a main cluster made of the most frequently co-occurring peaks and around 20 secondary clusters grouping less frequently co-occurring peaks. The 35 most represented species in our sample are distributed in two groups depending on the focusing of their protein synthesis activity on the main cluster or not. Our results may advocate some analogy with genomics studies of bacteria, with a main species-related cluster of co-occurring peaks and several secondary clusters, which may host peaks able to discriminate bacterial subgroups. This systematic study of the expression diversities of MALDI-TOF spectra shows that latent organization of co-occurring peaks supports subspecies discrimination and may explain why studies on MALDI-TOF-based typing exhibit some result divergences.

Interest of bacterial pangenome analyses in clinical microbiology

Thanks to the progress and decreasing costs in genome sequencing technologies, more than 250,000 bacterial genomes are currently available in public databases, covering most, if not all, of the major human-associated phylogenetic groups of these microorganisms, pathogenic or not. In addition, for many of them, sequences from several strains of a given species are available, thus enabling to evaluate their genetic diversity and study their evolution. In addition, the significant cost reduction of bacterial whole genome sequencing as well as the rapid increase in the number of available bacterial genomes have prompted the development of pangenomic software tools. The study of bacterial pangenome has many applications in clinical microbiology. It can unveil the pathogenic potential and ability of bacteria to resist antimicrobials as well identify specific sequences and predict antigenic epitopes that allow molecular or serologic assays and vaccines to be designed. Bacterial pangenome constitutes a powerful method for understanding the history of human bacteria and relating these findings to diagnosis in clinical microbiology laboratories in order to optimize patient management.

Coculture at the crossroads of the new microbiology techniques for the isolation of strict intracellular bacteria

Coculture played a major role in clinical microbiology by elucidating strict intracellular bacteria era. Since some of these bacteria are human pathogens, in-depth studies at the strain level are necessary to better understand their pathologies and treatment. Over the last decades, culture-independent tools have taken over the diagnostic procedure at the expense of coculture. These tools, although proven to be rapid and efficient, cannot overcome the need to culture the bacteria, as strain isolation remains a key factor to understanding its epidemiology, virulence and antibiotic susceptibility testing. Moreover, strain availability allows the development of molecular and serological tools, and remains crucial for taxonomy. This review revisits the current status of culture, its advantages, drawbacks and future needs.

Molecular typing of cytotoxin-producing Klebsiella oxytoca isolates by 16S-23S internal transcribed spacer PCR

Cytotoxin is one of the important pathogenic factors, which plays a role in the virulence of Klebsiella oxytoca. The aim of this study was to investigate molecular typing of clinical isolates of the cytotoxin-producing K. oxytoca using internal transcribed spacer (ITS) PCR. A total of 75 isolates of K. oxytoca were isolated from clinical samples; they were verified as K. oxytoca by standard microbiological tests and PCR. Production of toxin determines the cytotoxic effects on HEp-2 cells. The genetic diversity of isolates of the cytotoxin-producing K. oxytoca were defined by ITS-PCR. Of all the isolates investigated, five K. oxytoca strains isolated from stool cultures, two strains from blood samples, one strain from a wound and one strain isolated from urine had cytotoxic effects on HEp-2 cells. The ITS-PCR patterns showed genetic diversity among cytotoxin-producing isolates. The ITS-PCR method had good discriminatory power; performance of this method and interpretation of the results were easy and repeatable. Five genetic diversity patterns were identified by ITS-PCR.

Using WGS to identify antibiotic resistance genes and predict antimicrobial resistance phenotypes in MDR Acinetobacter baumannii in Tanzania

BACKGROUND

Reliable phenotypic antimicrobial susceptibility testing can be a challenge in clinical settings in low- and middle-income countries. WGS is a promising approach to enhance current capabilities.

AIM

To study diversity and resistance determinants and to predict and compare resistance patterns from WGS data of Acinetobacter baumannii with phenotypic results from classical microbiological testing at a tertiary care hospital in Tanzania.

METHODS AND RESULTS

MLST using Pasteur/Oxford schemes yielded eight different STs from each scheme. Of the eight, two STs were identified to be global clones 1 (n = 4) and 2 (n = 1) as per the Pasteur scheme. Resistance testing using classical microbiology determined between 50% and 92.9% resistance across all drugs. Percentage agreement between phenotypic and genotypic prediction of resistance ranged between 57.1% and 100%, with coefficient of agreement (κ) between 0.05 and 1. Seven isolates harboured mutations at significant loci (S81L in gyrA and S84L in parC). A number of novel plasmids were detected, including pKCRI-309C-1 (219000 bp) carrying 10 resistance genes, pKCRI-43-1 (34935 bp) carrying two resistance genes and pKCRI-49-1 (11681 bp) and pKCRI-28-1 (29606 bp), each carrying three resistance genes. New ampC alleles detected included ampC-69, ampC-70 and ampC-71. Global clone 1 and 2 isolates were found to harbour ISAba1 directly upstream of the ampC gene. Finally, SNP-based phylogenetic analysis of the A. baumannii isolates revealed closely related isolates in three clusters.

CONCLUSIONS

The validity of the use of WGS in the prediction of phenotypic resistance can be appreciated, but at this stage is not sufficient for it to replace conventional antimicrobial susceptibility testing in our setting.

New Laboratory Tools for Emerging Bacterial Challenges

Since its creation, the Méditerranée-Infection foundation has aimed at optimizing the management of infectious diseases and surveying the local and global epidemiology. This pivotal role was permitted by the development of rational sampling, point-of-care tests, and extended automation as well as new technologies, including mass spectrometry for colony identification, real-time genomics for isolate characterization, and the development of versatile and permissive culture systems. By identifying and characterizing emerging microbial pathogens, these developments provided significant breakthroughs in infectious diseases.

Comparison of whole genome sequencing to restriction endonuclease analysis and gel diffusion precipitin-based serotyping of Pasteurella multocida

The gel diffusion precipitin test (GDPT) and restriction endonuclease analysis (REA) have commonly been used in the serotyping and genotyping of Pasteurella multocida. Whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) analysis has become the gold standard for other organisms, offering higher resolution than previously available methods. We compared WGS to REA and GDPT on 163 isolates of P. multocida to determine if WGS produced more precise results. The isolates used represented the 16 reference serovars, isolates with REA profiles matching an attenuated fowl cholera vaccine strain, and isolates from 10 different animal species. Isolates originated from across the United States and from Chile. Identical REA profiles clustered together in the phylogenetic tree. REA profiles that differed by only a few bands had fewer SNP differences than REA profiles with more differences, as expected. The GDPT results were diverse but it was common to see a single serovar show up repeatedly within clusters. Several errors were found when examining the REA profiles. WGS was able to confirm these errors and compensate for the subjectivity in analysis of REA. Also, results of WGS and SNP analysis correlated more closely with the epidemiologic data than GDPT. In silico results were also compared to a lipopolysaccharide rapid multiplex PCR test. From the data produced in our study, WGS and SNP analysis was superior to REA and GDPT and highlighted some of the issues with the older tests.

Respiratory Tularemia: Francisella Tularensis and Microarray Probe Designing

BACKGROUND

Francisella tularensis (F. tularensis) is the etiological microorganism for tularemia. There are different forms of tularemia such as respiratory tularemia. Respiratory tularemia is the most severe form of tularemia with a high rate of mortality; if not treated. Therefore, traditional microbiological tools and Polymerase Chain Reaction (PCR) are not useful for a rapid, reliable, accurate, sensitive and specific diagnosis. But, DNA microarray technology does. DNA microarray technology needs to appropriate microarray probe designing.

OBJECTIVE

The main goal of this original article was to design suitable long oligo microarray probes for detection and identification of F. tularensis.

METHOD

For performing this research, the complete genomes of F. tularensis subsp. tularensis FSC198, F. tularensis subsp. holarctica LVS, F. tularensis subsp. mediasiatica, F. tularensis subsp. novicida (F. novicida U112), and F. philomiragia subsp. philomiragia ATCC 25017 were studied via NCBI BLAST tool, GView and PanSeq Servers and finally the microarray probes were produced and processed via AlleleID 7.7 software and Oligoanalyzer tool, respectively.

RESULTS

In this in silico investigation, a number of long oligo microarray probes were designed for detecting and identifying F. tularensis. Among these probes, 15 probes were recognized as the best candidates for microarray chip designing.

CONCLUSION

Calibrated microarray probes reduce the biasis of DNA microarray technology as an advanced, rapid, accurate and cost-effective molecular diagnostic tool with high specificity and sensitivity. Professional microarray probe designing provides us with much more facility and flexibility regarding preparation of a microarray diagnostic chip.

Real time application of whole genome sequencing for outbreak investigation - What is an achievable turnaround time?

Whole genome sequencing (WGS) is increasingly employed in clinical settings, though few assessments of turnaround times (TAT) have been performed in real-time. In this study, WGS was used to investigate an unfolding outbreak of vancomycin resistant Enterococcus faecium (VRE) among 3 patients in the ICU of a tertiary care hospital. Including overnight culturing, a TAT of just 48.5 h for a comprehensive report was achievable using an Illumina Miseq benchtop sequencer. WGS revealed that isolates from patient 2 and 3 differed from that of patient 1 by a single nucleotide polymorphism (SNP), indicating nosocomial transmission. However, the unparalleled resolution provided by WGS suggested that nosocomial transmission involved two separate events from patient 1 to patient 2 and 3, and not a linear transmission suspected by the time line. Rapid TAT's are achievable using WGS in the clinical setting and can provide an unprecedented level of resolution for outbreak investigations.

Utility of algorithms for the analysis of integratedSalmonellasurveillance data

The objective of this study was to assess the use of statistical algorithms in identifying significant clusters ofSalmonellaspp. across different sectors of the food chain within an integrated surveillance programme. Three years of weeklySalmonellaserotype data from farm animals, meat, and humans were used to create baseline models (first two years) and identify weeks with counts higher than expected using surveillance algorithms in the third (test) year. During the test year, an expert working group identified events of interest reviewing descriptive analyses of same data. The algorithms did not identifySalmonellaevents presenting as gradual increases or seasonal patterns as identified by the working group. However, the algorithms did identify clusters for further investigation, suggesting they could be a valuable complementary tool within an integrated surveillance system.

Evidence for Elizabethkingia anophelis transmission from mother to infant, Hong Kong

Genome sequencing can provide rapid insights on transmission and pathogenesis of emerging pathogens.

Elizabethkingia anophelis, recently discovered from mosquito gut, is an emerging bacterium associated with neonatal meningitis and nosocomial outbreaks. However, its transmission route remains unknown. We use rapid genome sequencing to investigate 3 cases of E. anophelis sepsis involving 2 neonates who had meningitis and 1 neonate’s mother who had chorioamnionitis. Comparative genomics revealed evidence for perinatal vertical transmission from a mother to her neonate; the 2 isolates from these patients, HKU37 and HKU38, shared essentially identical genome sequences. In contrast, the strain from another neonate (HKU36) was genetically divergent, showing only 78.6% genome sequence identity to HKU37 and HKU38, thus excluding a clonal outbreak. Comparison to genomes from mosquito strains revealed potential metabolic adaptations in E. anophelis under different environments. Maternal infection, not mosquitoes, is most likely the source of neonatal E. anophelis infections. Our findings highlight the power of genome sequencing in gaining rapid insights on transmission and pathogenesis of emerging pathogens.

Whole-genome sequencing targets drug-resistant bacterial infections

During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today’s WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.

The rebirth of culture in microbiology through the example of culturomics to study human gut microbiota

Bacterial culture was the first method used to describe the human microbiota, but this method is considered outdated by many researchers. Metagenomics studies have since been applied to clinical microbiology; however, a "dark matter" of prokaryotes, which corresponds to a hole in our knowledge and includes minority bacterial populations, is not elucidated by these studies. By replicating the natural environment, environmental microbiologists were the first to reduce the "great plate count anomaly," which corresponds to the difference between microscopic and culture counts. The revolution in bacterial identification also allowed rapid progress. 16S rRNA bacterial identification allowed the accurate identification of new species. Mass spectrometry allowed the high-throughput identification of rare species and the detection of new species. By using these methods and by increasing the number of culture conditions, culturomics allowed the extension of the known human gut repertoire to levels equivalent to those of pyrosequencing. Finally, taxonogenomics strategies became an emerging method for describing new species, associating the genome sequence of the bacteria systematically. We provide a comprehensive review on these topics, demonstrating that both empirical and hypothesis-driven approaches will enable a rapid increase in the identification of the human prokaryote repertoire.

Current and past strategies for bacterial culture in clinical microbiology

A pure bacterial culture remains essential for the study of its virulence, its antibiotic susceptibility, and its genome sequence in order to facilitate the understanding and treatment of caused diseases. The first culture conditions empirically varied incubation time, nutrients, atmosphere, and temperature; culture was then gradually abandoned in favor of molecular methods. The rebirth of culture in clinical microbiology was prompted by microbiologists specializing in intracellular bacteria. The shell vial procedure allowed the culture of new species of Rickettsia. The design of axenic media for growing fastidious bacteria such as Tropheryma whipplei and Coxiella burnetii and the ability of amoebal coculture to discover new bacteria constituted major advances. Strong efforts associating optimized culture media, detection methods, and a microaerophilic atmosphere allowed a dramatic decrease of the time of Mycobacterium tuberculosis culture. The use of a new versatile medium allowed an extension of the repertoire of archaea. Finally, to optimize the culture of anaerobes in routine bacteriology laboratories, the addition of antioxidants in culture media under an aerobic atmosphere allowed the growth of strictly anaerobic species. Nevertheless, among usual bacterial pathogens, the development of axenic media for the culture of Treponema pallidum or Mycobacterium leprae remains an important challenge that the patience and innovations of cultivators will enable them to overcome.

Clinical detection and characterization of bacterial pathogens in the genomics era

The availability of genome sequences obtained using next-generation sequencing (NGS) has revolutionized the field of infectious diseases. Indeed, more than 38,000 bacterial and 5,000 viral genomes have been sequenced to date, including representatives of all significant human pathogens. These tremendous amounts of data have not only enabled advances in fundamental biology, helping to understand the pathogenesis of microorganisms and their genomic evolution, but have also had implications for clinical microbiology. Here, we first review the current achievements of genomics in the development of improved diagnostic tools, including those that are now available in the clinic, such as the design of PCR assays for the detection of microbial pathogens, virulence factors or antibiotic-resistance determinants, or the design of optimized culture media for 'unculturable' pathogens. We then review the applications of genomics to the investigation of outbreaks, either through the design of genotyping assays or the direct sequencing of the causative strains. Finally, we discuss how genomics might change clinical microbiology in the future.

An evolutionary analysis of genome expansion and pathogenicity in Escherichia coli

BACKGROUND

There are several studies describing loss of genes through reductive evolution in microbes, but how selective forces are associated with genome expansion due to horizontal gene transfer (HGT) has not received similar attention. The aim of this study was therefore to examine how selective pressures influence genome expansion in 53 fully sequenced and assembled Escherichia coli strains. We also explored potential connections between genome expansion and the attainment of virulence factors. This was performed using estimations of several genomic parameters such as AT content, genomic drift (measured using relative entropy), genome size and estimated HGT size, which were subsequently compared to analogous parameters computed from the core genome consisting of 1729 genes common to the 53 E. coli strains. Moreover, we analyzed how selective pressures (quantified using relative entropy and dN/dS), acting on the E. coli core genome, influenced lineage and phylogroup formation.

RESULTS

Hierarchical clustering of dS and dN estimations from the E. coli core genome resulted in phylogenetic trees with topologies in agreement with known E. coli taxonomy and phylogroups. High values of dS, compared to dN, indicate that the E. coli core genome has been subjected to substantial purifying selection over time; significantly more than the non-core part of the genome (p<0.001). This is further supported by a linear association between strain-wise dS and dN values (β = 26.94 ± 0.44, R2~0.98, p<0.001). The non-core part of the genome was also significantly more AT-rich (p<0.001) than the core genome and E. coli genome size correlated with estimated HGT size (p<0.001). In addition, genome size (p<0.001), AT content (p<0.001) as well as estimated HGT size (p<0.005) were all associated with the presence of virulence factors, suggesting that pathogenicity traits in E. coli are largely attained through HGT. No associations were found between selective pressures operating on the E. coli core genome, as estimated using relative entropy, and genome size (p~0.98).

CONCLUSIONS

On a larger time frame, genome expansion in E. coli, which is significantly associated with the acquisition of virulence factors, appears to be independent of selective forces operating on the core genome.

Whole genome sequencing of bacteria in cystic fibrosis as a model for bacterial genome adaptation and evolution

Cystic fibrosis (CF) airways harbor a wide variety of new and/or emerging multidrug resistant bacteria which impose a heavy burden on patients. These bacteria live in close proximity with one another, which increases the frequency of lateral gene transfer. The exchange and movement of mobile genetic elements and genomic islands facilitate the spread of genes between genetically diverse bacteria, which seem to be advantageous to the bacterium as it allows adaptation to the new niches of the CF lungs. Niche adaptation is one of the major evolutionary forces shaping bacterial genome composition and in CF the chronic strains adapt and become less virulent. The purpose of this review is to shed light on CF bacterial genome alterations. Next-generation sequencing technology is an exciting tool that may help us to decipher the genome architecture and the evolution of bacteria colonizing CF lungs.

Genomics and metagenomics in medical microbiology

Over the last two decades, sequencing tools have evolved from laborious time-consuming methodologies to real-time detection and deciphering of genomic DNA. Genome sequencing, especially using next generation sequencing (NGS) has revolutionized the landscape of microbiology and infectious disease. This deluge of sequencing data has not only enabled advances in fundamental biology but also helped improve diagnosis, typing of pathogen, virulence and antibiotic resistance detection, and development of new vaccines and culture media. In addition, NGS also enabled efficient analysis of complex human micro-floras, both commensal, and pathological, through metagenomic methods, thus helping the comprehension and management of human diseases such as obesity. This review summarizes technological advances in genomics and metagenomics relevant to the field of medical microbiology.

Update on tick-borne rickettsioses around the world: a geographic approach

Tick-borne rickettsioses are caused by obligate intracellular bacteria belonging to the spotted fever group of the genus Rickettsia. These zoonoses are among the oldest known vector-borne diseases. However, in the past 25 years, the scope and importance of the recognized tick-associated rickettsial pathogens have increased dramatically, making this complex of diseases an ideal paradigm for the understanding of emerging and reemerging infections. Several species of tick-borne rickettsiae that were considered nonpathogenic for decades are now associated with human infections, and novel Rickettsia species of undetermined pathogenicity continue to be detected in or isolated from ticks around the world. This remarkable expansion of information has been driven largely by the use of molecular techniques that have facilitated the identification of novel and previously recognized rickettsiae in ticks. New approaches, such as swabbing of eschars to obtain material to be tested by PCR, have emerged in recent years and have played a role in describing emerging tick-borne rickettsioses. Here, we present the current knowledge on tick-borne rickettsiae and rickettsioses using a geographic approach toward the epidemiology of these diseases.

Investigation of antibiotic resistance in the genomic era of multidrug-resistant Gram-negative bacilli, especially Enterobacteriaceae, Pseudomonas and Acinetobacter

The increase and spread of multidrug-resistant (MDR) Gram-negative bacteria, including Enterobacteriaceae, Pseudomonas and Acinetobacter species, have become major concerns worldwide. Although the frequent misuse of antibiotic drugs has greatly contributed to worldwide antibiotic resistance by causing a large dispersal of resistance determinants, recent studies demonstrate that these resistance determinants could have emerged from ancient or environmental sources. Moreover, during the last 10 years, we have been witnessing the emergence and development of technologies for high-throughput sequencing, coinciding with an exponential increase in the number of bacterial genomes sequenced. These sequencing technologies allow a complete study of MDR bacterial genomes and are the best way to investigate the genetic determinants of antimicrobial resistance. Accordingly, studies using genome sequencing to decipher resistance determinants in Enterobacteriaceae, Pseudomonas and Acinetobacter species have demonstrated several advantages including, among others: an exhaustive identification of resistance determinants from any clinical, epidemiological or environmental MDR bacterium; identification of the acquisition mechanisms for resistance determinants exchanged between bacterial species through mobile genetic elements and elucidation and understanding, in record time (less than 1 week), of some critical or epidemic events caused by particular pathogenic bacteria. Therefore, it is clear today that the bacterial genome sequencing approach has revolutionized all fields of scientific research and represents a powerful tool to explore the world of microorganisms.

Modern clinical microbiology: new challenges and solutions

In the twenty-first century, the clinical microbiology laboratory plays a central part in optimizing the management of infectious diseases and surveying local and global epidemiology. This pivotal role is made possible by the adoption of rational sampling, point-of-care tests, extended automation and new technologies, including mass spectrometry for colony identification, real-time genomics for isolate characterization, and versatile and permissive culture systems. When balanced with cost, these developments can improve the workflow and output of clinical microbiology laboratories and, by identifying and characterizing microbial pathogens, provide significant input to scientific discovery.

Real-time genomic epidemiological evaluation of human Campylobacter isolates by use of whole-genome multilocus sequence typing

Sequence-based typing is essential for understanding the epidemiology of Campylobacter infections, a major worldwide cause of bacterial gastroenteritis. We demonstrate the practical and rapid exploitation of whole-genome sequencing to provide routine definitive characterization of Campylobacter jejuni and Campylobacter coli for clinical and public health purposes. Short-read data from 384 Campylobacter clinical isolates collected over 4 months in Oxford, United Kingdom, were assembled de novo. Contigs were deposited at the pubMLST.org/campylobacter website and automatically annotated for 1,667 loci. Typing and phylogenetic information was extracted and comparative analyses were performed for various subsets of loci, up to the level of the whole genome, using the Genome Comparator and Neighbor-net algorithms. The assembled sequences (for 379 isolates) were diverse and resembled collections from previous studies of human campylobacteriosis. Small subsets of very closely related isolates originated mainly from repeated sampling from the same patients and, in one case, likely laboratory contamination. Much of the within-patient variation occurred in phase-variable genes. Clinically and epidemiologically informative data can be extracted from whole-genome sequence data in real time with straightforward, publicly available tools. These analyses are highly scalable, are transparent, do not require closely related genome reference sequences, and provide improved resolution (i) among Campylobacter clonal complexes and (ii) between very closely related isolates. Additionally, these analyses rapidly differentiated unrelated isolates, allowing the detection of single-strain clusters. The approach is widely applicable to analyses of human bacterial pathogens in real time in clinical laboratories, with little specialist training required.

Microbial variome database: point mutations, adaptive or not, in bacterial core genomes

Analysis of genetic differences (gene presence/absence and nucleotide polymorphisms) among strains of a bacterial species is crucial to understanding molecular mechanisms of bacterial pathogenesis and selecting targets for novel antibacterial therapeutics. However, lack of genome-wide association studies on large and epidemiologically well-defined strain collections from the same species makes it difficult to identify the genes under positive selection and define adaptive polymorphisms in those genes. To address this need and to overcome existing limitations, we propose to create a "microbial variome"--a species-specific resource database of genomic variations based on molecular evolutionary analysis. Here, we present prototype variome databases of Escherichia coli and Salmonella enterica subspecies enterica (http://depts.washington.edu/sokurel/variome, last accessed March 26, 2013). The prototypes currently include the point mutations data of core protein-coding genes from completely sequenced genomes of 22 E. coli and 17 S. enterica strains. These publicly available databases allow for single- and multiple-field sorting, filtering, and searching of the gene variability data and the potential adaptive significance. Such resource databases would immensely help experimental research, clinical diagnostics, epidemiology, and environmental control of human pathogens.

Small Indian mongooses and masked palm civets serve as new reservoirs of Bartonella henselae and potential sources of infection for humans

The prevalence and genetic properties of Bartonella species were investigated in small Indian mongooses and masked palm civets in Japan. Bartonella henselae, the causative agent of cat-scratch disease (CSD) was isolated from 15.9% (10/63) of the mongooses and 2.0% (1/50) of the masked palm civets, respectively. The bacteraemic level ranged from 3.0 × 10¹ to 8.9 × 10³ CFU/mL in mongooses and was 7.0 × 10³ CFU/mL in the masked palm civet. Multispacer typing (MST) analysis based on nine intergenic spacers resulted in the detection of five MST genotypes (MSTs 8, 14, 37, 58 and 59) for the isolates, which grouped in lineage 1 with MST genotypes of isolates from all CSD patients and most of the cats in Japan. It was also found that MST14 from the mongoose strains was the predominant genotype of cat and human strains. This is the first report on the isolation of B. henselae from small Indian mongooses and masked palm civets. The data obtained in the present study suggest that these animals serve as new reservoirs for B. henselae, and may play a role as potential sources of human infection.

The rhizome of the multidrug-resistant Enterobacter aerogenes genome reveals how new "killer bugs" are created because of a sympatric lifestyle

Here, we sequenced the 5,419,609 bp circular genome of an Enterobacter aerogenes clinical isolate that killed a patient and was resistant to almost all current antibiotics (except gentamicin) commonly used to treat Enterobacterial infections, including colistin. Genomic and phylogenetic analyses explain the discrepancies of this bacterium and show that its core genome originates from another genus, Klebsiella. Atypical characteristics of this bacterium (i.e., motility, presence of ornithine decarboxylase, and lack of urease activity) are attributed to genomic mosaicism, by acquisition of additional genes, such as the complete 60,582 bp flagellar assembly operon acquired "en bloc" from the genus Serratia. The genealogic tree of the 162,202 bp multidrug-resistant conjugative plasmid shows that it is a chimera of transposons and integrative conjugative elements from various bacterial origins, resembling a rhizome. Moreover, we demonstrate biologically that a G53S mutation in the pmrA gene results in colistin resistance. E. aerogenes has a large RNA population comprising 8 rRNA operons and 87 cognate tRNAs that have the ability to translate transferred genes that use different codons, as exemplified by the significantly different codon usage between genes from the core genome and the "mobilome." On the basis of our findings, the evolution of this bacterium to become a "killer bug" with new genomic repertoires was from three criteria that are "opportunity, power, and usage" to indicate a sympatric lifestyle: "opportunity" to meet other bacteria and exchange foreign sequences since this bacteria was similar to sympatric bacteria; "power" to integrate these foreign sequences such as the acquisition of several mobile genetic elements (plasmids, integrative conjugative element, prophages, transposons, flagellar assembly system, etc.) found in his genome; and "usage" to have the ability to translate these sequences including those from rare codons to serve as a translator of foreign languages.

Microbial culturomics: paradigm shift in the human gut microbiome study

Comprehensive determination of the microbial composition of the gut microbiota and the relationships with health and disease are major challenges in the 21st century. Metagenomic analysis of the human gut microbiota detects mostly uncultured bacteria. We studied stools from two lean Africans and one obese European, using 212 different culture conditions (microbial culturomics), and tested the colonies by using mass spectrometry and 16S rRNA amplification and sequencing. In parallel, we analysed the same three samples by pyrosequencing 16S rRNA amplicons targeting the V6 region. The 32 500 colonies obtained by culturomics have yielded 340 species of bacteria from seven phyla and 117 genera, including two species from rare phyla (Deinococcus-Thermus and Synergistetes, five fungi, and a giant virus (Senegalvirus). The microbiome identified by culturomics included 174 species never described previously in the human gut, including 31 new species and genera for which the genomes were sequenced, generating c. 10 000 new unknown genes (ORFans), which will help in future molecular studies. Among these, the new species Microvirga massiliensis has the largest bacterial genome so far obtained from a human, and Senegalvirus is the largest virus reported in the human gut. Concurrent metagenomic analysis of the same samples produced 698 phylotypes, including 282 known species, 51 of which overlapped with the microbiome identified by culturomics. Thus, culturomics complements metagenomics by overcoming the depth bias inherent in metagenomic approaches.

Exploration of multivariate analysis in microbial coding sequence modeling

BACKGROUND

Gene finding is a complicated procedure that encapsulates algorithms for coding sequence modeling, identification of promoter regions, issues concerning overlapping genes and more. In the present study we focus on coding sequence modeling algorithms; that is, algorithms for identification and prediction of the actual coding sequences from genomic DNA. In this respect, we promote a novel multivariate method known as Canonical Powered Partial Least Squares (CPPLS) as an alternative to the commonly used Interpolated Markov model (IMM). Comparisons between the methods were performed on DNA, codon and protein sequences with highly conserved genes taken from several species with different genomic properties.

RESULTS

The multivariate CPPLS approach classified coding sequence substantially better than the commonly used IMM on the same set of sequences. We also found that the use of CPPLS with codon representation gave significantly better classification results than both IMM with protein (p < 0.001) and with DNA (p < 0.001). Further, although the mean performance was similar, the variation of CPPLS performance on codon representation was significantly smaller than for IMM (p < 0.001).

CONCLUSIONS

The performance of coding sequence modeling can be substantially improved by using an algorithm based on the multivariate CPPLS method applied to codon or DNA frequencies.

Relative entropy differences in bacterial chromosomes, plasmids, phages and genomic islands

BACKGROUND

We sought to assess whether the concept of relative entropy (information capacity), could aid our understanding of the process of horizontal gene transfer in microbes. We analyzed the differences in information capacity between prokaryotic chromosomes, genomic islands (GI), phages, and plasmids. Relative entropy was estimated using the Kullback-Leibler measure.

RESULTS

Relative entropy was highest in bacterial chromosomes and had the sequence chromosomes > GI > phage > plasmid. There was an association between relative entropy and AT content in chromosomes, phages, plasmids and GIs with the strongest association being in phages. Relative entropy was also found to be lower in the obligate intracellular Mycobacterium leprae than in the related M. tuberculosis when measured on a shared set of highly conserved genes.

CONCLUSIONS

We argue that relative entropy differences reflect how plasmids, phages and GIs interact with microbial host chromosomes and that all these biological entities are, or have been, subjected to different selective pressures. The rate at which amelioration of horizontally acquired DNA occurs within the chromosome is likely to account for the small differences between chromosomes and stably incorporated GIs compared to the transient or independent replicons such as phages and plasmids.

Molecular methods for pathogen and microbial community detection and characterization: current and potential application in diagnostic microbiology

Clinical microbiology laboratories worldwide have historically relied on phenotypic methods (i.e., culture and biochemical tests) for detection, identification and characterization of virulence traits (e.g., antibiotic resistance genes, toxins) of human pathogens. However, limitations to implementation of molecular methods for human infectious diseases testing are being rapidly overcome allowing for the clinical evaluation and implementation of diverse technologies with expanding diagnostic capabilities. The advantages and limitation of molecular techniques including real-time polymerase chain reaction, partial or whole genome sequencing, molecular typing, microarrays, broad-range PCR and multiplexing will be discussed. Finally, terminal restriction fragment length polymorphism (T-RFLP) and deep sequencing are introduced as technologies at the clinical interface with the potential to dramatically enhance our ability to diagnose infectious diseases and better define the epidemiology and microbial ecology of a wide range of complex infections.

Prospects for the future using genomics and proteomics in clinical microbiology

The availability of genome sequences has revolutionized the fields of microbiology and infectious diseases. Indeed, more than 1,000 bacterial genomes and 3,000 viral genomes, including representatives of all significant human pathogens, have been sequenced to date. Owing to this tremendous amount of data, genomes are regarded as chimeras of sequence fragments from various origins. Coupled with novel proteomic analyses, genome sequencing has also resulted in unprecedented advances in pathogen diagnosis and genotyping and in the detection of virulence and antibiotic resistance. Herein, we review current achievements of genomics and proteomics and discuss potential developments for clinical microbiology laboratories.

Widespread use of real-time PCR for rickettsial diagnosis

We report 2 years of experience with rickettsial molecular diagnosis using real-time PCR at the French National Reference Center. All Rickettsia genomes available were compared to discover specific sequences to design new sets of primers and probes. The specificity was verified in silico and against a panel of 30 rickettsial species. Sensitivity was determined using 10-fold serial dilutions. Finally, primers and probes that were both specific and sensitive were routinely used for the diagnosis of rickettsial infections from clinical specimens. We retained sets of primers and probes to detect spotted fever group Rickettsia, typhus group Rickettsia,Rickettsia conorii,Rickettsia slovaca,Rickettsia africae and Rickettsia australis; 643 clinical samples were screened for the presence of Rickettsia DNA. Overall, 45 positive samples were detected, including 15 Rickettsia africae, nine R. conorii, five Rickettsia sibirica mongolitimonae, four R. slovaca, two R. australis, four Rickettsia massiliae, one Rickettsia honei, one Rickettsia typhi and eight Rickettsia sp. Positive samples were detected mainly from cutaneous biopsies and swabs (31/45). Widespread use of real-time PCR is inexpensive and reduces delay in the diagnosis of rickettsial infections. These real-time PCR assays could be implemented easily in laboratories that have molecular facilities and may be added to existing molecular tools as a point-of-care strategy.

SNP/RD typing of Mycobacterium tuberculosis Beijing strains reveals local and worldwide disseminated clonal complexes

The Beijing strain is one of the most successful genotypes of Mycobacterium tuberculosis worldwide and appears to be highly homogenous according to existing genotyping methods. To type Beijing strains reliably we developed a robust typing scheme using single nucleotide polymorphisms (SNPs) and regions of difference (RDs) derived from whole-genome sequencing data of eight Beijing strains. SNP/RD typing of 259 M. tuberculosis isolates originating from 45 countries worldwide discriminated 27 clonal complexes within the Beijing genotype family. A total of 16 Beijing clonal complexes contained more than one isolate of known origin, of which two clonal complexes were strongly associated with South African origin. The remaining 14 clonal complexes encompassed isolates from different countries. Even highly resolved clonal complexes comprised isolates from distinct geographical sites. Our results suggest that Beijing strains spread globally on multiple occasions and that the tuberculosis epidemic caused by the Beijing genotype is at least partially driven by modern migration patterns. The SNPs and RDs presented in this study will facilitate future molecular epidemiological and phylogenetic studies on Beijing strains.

Genome-wide association studies and susceptibility to infectious diseases

Progress in genomics and the associated technological, statistical and bioinformatics advances have facilitated the successful implementation of genome-wide association studies (GWAS) towards understanding the genetic basis of common diseases. Infectious diseases contribute significantly to the global burden of disease and there is robust epidemiological evidence that host genetic factors are important determinants of the outcome of interactions between host and pathogen. Indeed, infectious diseases have exerted profound selective pressure on human evolution. However, the application of GWAS to infectious diseases has been relatively limited compared with non-communicable diseases. Here we review GWAS findings for important infectious diseases, including malaria, tuberculosis and HIV. We highlight some of the pitfalls recognized more generally for GWAS, as well as issues specific to infection, including the role of the pathogen which also has a genome. We also discuss the challenges encountered when studying African populations which are genetically more ancient and more diverse that other populations and disproportionately bear the main global burden of serious infectious diseases.

Prediction of protein-protein interactions between human host and a pathogen and its application to three pathogenic bacteria

Molecular understanding of disease processes can be accelerated if all interactions between the host and pathogen are known. The unavailability of experimental methods for large-scale detection of interactions across host and pathogen organisms hinders this process. Here we apply a simple method to predict protein-protein interactions across a host and pathogen organisms. We use homology detection approaches against the protein-protein interaction databases, DIP and iPfam in order to predict interacting proteins in a host-pathogen pair. In the present work, we first applied this approach to the test cases involving the pairs phage T4 -Escherichia coli and phage lambda -E. coli and show that previously known interactions could be recognized using our approach. We further apply this approach to predict interactions between human and three pathogens E. coli, Salmonella enterica typhimurium and Yersinia pestis. We identified several novel interactions involving proteins of host or pathogen that could be thought of as highly relevant to the disease process. Serendipitously, many interactions involve hypothetical proteins of yet unknown function. Hypothetical proteins are predicted from computational analysis of genome sequences with no laboratory analysis on their functions yet available. The predicted interactions involving such proteins could provide hints to their functions.

New detection systems of bacteria using highly selective media designed by SMART: selective medium-design algorithm restricted by two constraints

Culturing is an indispensable technique in microbiological research, and culturing with selective media has played a crucial role in the detection of pathogenic microorganisms and the isolation of commercially useful microorganisms from environmental samples. Although numerous selective media have been developed in empirical studies, unintended microorganisms often grow on such media probably due to the enormous numbers of microorganisms in the environment. Here, we present a novel strategy for designing highly selective media based on two selective agents, a carbon source and antimicrobials. We named our strategy SMART for highly Selective Medium-design Algorithm Restricted by Two constraints. To test whether the SMART method is applicable to a wide range of microorganisms, we developed selective media for Burkholderia glumae, Acidovorax avenae, Pectobacterium carotovorum, Ralstonia solanacearum, and Xanthomonas campestris. The series of media developed by SMART specifically allowed growth of the targeted bacteria. Because these selective media exhibited high specificity for growth of the target bacteria compared to established selective media, we applied three notable detection technologies: paper-based, flow cytometry-based, and color change-based detection systems for target bacteria species. SMART facilitates not only the development of novel techniques for detecting specific bacteria, but also our understanding of the ecology and epidemiology of the targeted bacteria.

Analysis of intra-genomic GC content homogeneity within prokaryotes

BACKGROUND

Bacterial genomes possess varying GC content (total guanines (Gs) and cytosines (Cs) per total of the four bases within the genome) but within a given genome, GC content can vary locally along the chromosome, with some regions significantly more or less GC rich than on average. We have examined how the GC content varies within microbial genomes to assess whether this property can be associated with certain biological functions related to the organism's environment and phylogeny. We utilize a new quantity GCVAR, the intra-genomic GC content variability with respect to the average GC content of the total genome. A low GCVAR indicates intra-genomic GC homogeneity and high GCVAR heterogeneity.

RESULTS

The regression analyses indicated that GCVAR was significantly associated with domain (i.e. archaea or bacteria), phylum, and oxygen requirement. GCVAR was significantly higher among anaerobes than both aerobic and facultative microbes. Although an association has previously been found between mean genomic GC content and oxygen requirement, our analysis suggests that no such association exits when phylogenetic bias is accounted for. A significant association between GCVAR and mean GC content was also found but appears to be non-linear and varies greatly among phyla.

CONCLUSIONS

Our findings show that GCVAR is linked with oxygen requirement, while mean genomic GC content is not. We therefore suggest that GCVAR should be used as a complement to mean GC content.