Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak

Evaluating Infectious, Neoplastic, Immunological, and Degenerative Diseases of the Central Nervous System with Cerebrospinal Fluid-Based Next-Generation Sequencing

Cerebrospinal fluid (CSF) is a clear and paucicellular fluid that circulates within the ventricular system and the subarachnoid space of the central nervous system (CNS), and diverse CNS disorders can impact its composition, volume, and flow. As conventional CSF testing suffers from suboptimal sensitivity, this review aimed to evaluate the role of next-generation sequencing (NGS) in the work-up of infectious, neoplastic, neuroimmunological, and neurodegenerative CNS diseases. Metagenomic NGS showed improved sensitivity—compared to traditional methods—to detect bacterial, viral, parasitic, and fungal infections, while the overall performance was maximized in some studies when all diagnostic modalities were used. In patients with primary CNS cancer, NGS findings in the CSF were largely concordant with the molecular signatures derived from tissue-based molecular analysis; of interest, additional mutations were identified in the CSF in some glioma studies, reflecting intratumoral heterogeneity. In patients with metastasis to the CNS, NGS facilitated diagnosis, prognosis, therapeutic management, and monitoring, exhibiting higher sensitivity than neuroimaging, cytology, and plasma-based molecular analysis. Although evidence is still rudimentary, NGS could enhance the diagnosis and pathogenetic understanding of multiple sclerosis in addition to Alzheimer and Parkinson disease. To conclude, NGS has shown potential to aid the research, facilitate the diagnostic approach, and improve the management outcomes of all the aforementioned CNS diseases. However, to establish its role in clinical practice, the clinical validity and utility of each NGS protocol should be determined. Lastly, as most evidence has been derived from small and retrospective studies, results from randomized control trials could be of significant value.

Metagenomic analysis of the effects of toll-like receptors on bacterial infection in the peritoneal cavity following cecum ligation and puncture in mice

Objective

To establish the composition of bacteria in mice following cecum ligation and puncture (CLP) through metagenomic analysis and investigate the role of TLRs on the composition of bacteria.

Methods

Total DNA extraction was done from the ascites, blood, and fecal samples from C57BL/6 mice sacrificed at 0, 4, 8, and 16 h, as well as from Tlr2^–/–, Tlr4^–/–, Tlr5^–/–, and NF-κB^–/–mice sacrificed at 16 h following CLP. Amplification of the V3–V4 regions of the bacterial 16S rRNA genes by PCR and the Illumina MiSeq sequencer was used for deep sequencing. Hierarchical clustering of the isolates was performed with Ward’s method using Euclidean distances. The relative abundance according to operational taxonomic unit (OTU) number or taxa was used to compare the richness among subgroups in the experiments.

Results

There were 18 taxa that had significantly different abundances among the different samples of the C57BL/6 mice at 16 h following CLP. Various dynamic changes in the infectious bacteria inside the peritoneal cavity after CLP were found. While knockout of Tlr5 and NF-κB impaired the ability of bacterial clearance inside the peritoneal cavity for some kinds of bacteria found in the C57BL/6 mice, the knockout of Tlr4 enhanced clearance for other kinds of bacteria, and they presented excessive abundance in the peritoneal cavity despite their scarce abundance in the stool.

Conclusion

NF-κB and TLRs are involved in bacterial clearance and in the expression pattern of the bacterial abundance inside the peritoneal cavity during polymicrobial infection.

Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks

BACKGROUND

While overall rates of meningococcal disease have been declining in the United States for the past several decades, New York City (NYC) has experienced two serogroup C meningococcal disease outbreaks in 2005-2006 and in 2010-2013. The outbreaks were centered within drug use and sexual networks, were difficult to control, and required vaccine campaigns.

METHODS

Whole Genome Sequencing (WGS) was used to analyze preserved meningococcal isolates collected before and during the two outbreaks. We integrated and analyzed epidemiologic, geographic, and genomic data to better understand transmission networks among patients. Betweenness centrality was used as a metric to understand the most important geographic nodes in the transmission networks. Comparative genomics was used to identify genes associated with the outbreaks.

RESULTS

Neisseria meningitidis serogroup C (ST11/ET-37) was responsible for both outbreaks with each outbreak having distinct phylogenetic clusters. WGS did identify some misclassifications of isolates that were more distant from the outbreak strains, as well as those that should have been included based on high genomic similarity. Genomes for the second outbreak were more similar than the first and no polymorphism was found to either be unique or specific to either outbreak lineage. Betweenness centrality as applied to transmission networks based on phylogenetic analysis demonstrated that the outbreaks were transmitted within focal communities in NYC with few transmission events to other locations.

CONCLUSIONS

Neisseria meningitidis is an ever changing pathogen and comparative genomic analyses can help elucidate how it spreads geographically to facilitate targeted interventions to interrupt transmission.

Metagenome Analysis as a Tool to Study Bacterial Infection Associated with Acute Surgical Abdomen

Background: The purpose of this study was to profile the bacterium in the ascites and blood of patients with acute surgical abdomen by metagenome analysis. Methods: A total of 97 patients with acute surgical abdomen were included in this study. Accompanied with the standard culture procedures, ascites and blood samples were collected for metagenome analysis to measure the relative abundance of bacteria among groups of patients and between blood and ascites. Results: Metagenomic analysis identified 107 bacterial taxa from the ascites of patients. A principal component analysis (PCA) could separate the bacteria of ascites into roughly three groups: peptic ulcer, perforated or non-perforated appendicitis, and a group which included cholecystitis, small bowel lesion, and colon perforation. Significant correlation between the bacteria of blood and ascites was found in nine bacterial taxa both in blood and ascites with more than 500 sequence reads. However, the PCA failed to separate the variation in the bacteria of blood into different groups of patients, and the bacteria of metagenomic analysis is only partly in accordance with those isolated from a conventional culture method. Conclusion: This study indicated that the metagenome analysis can provide limited information regarding the bacteria in the ascites and blood of patients with acute surgical abdomen.

Distinct evolutionary patterns of Neisseria meningitidis serogroup B disease outbreaks at two universities in the USA

Neisseria meningitidis serogroup B (MnB) was responsible for two independent meningococcal disease outbreaks at universities in the USA during 2013. The first at University A in New Jersey included nine confirmed cases reported between March 2013 and March 2014. The second outbreak occurred at University B in California, with four confirmed cases during November 2013. The public health response to these outbreaks included the approval and deployment of a serogroup B meningococcal vaccine that was not yet licensed in the USA. This study investigated the use of whole-genome sequencing(WGS) to examine the genetic profile of the disease-causing outbreak isolates at each university. Comparative WGS revealed differences in evolutionary patterns between the two disease outbreaks. The University A outbreak isolates were very closely related, with differences primarily attributed to single nucleotide polymorphisms/insertion-deletion (SNP/indel) events. In contrast, the University B outbreak isolates segregated into two phylogenetic clades, differing in large part due to recombination events covering extensive regions (>30 kb) of the genome including virulence factors. This high-resolution comparison of two meningococcal disease outbreaks further demonstrates the genetic complexity of meningococcal bacteria as related to evolution and disease virulence.

Comprehensive Diagnosis of Bacterial Infection Associated with Acute Cholecystitis Using Metagenomic Approach

Acute cholecystitis (AC), which is strongly associated with retrograde bacterial infection, is an inflammatory disease that can be fatal if inappropriately treated. Currently, bacterial culture testing, which is basically recommended to detect the etiological agent, is a time-consuming (4–6 days), non-comprehensive approach. To rapidly detect a potential pathogen and predict its antimicrobial susceptibility, we undertook a metagenomic approach to characterize the bacterial infection associated with AC. Six patients (P1–P6) who underwent cholecystectomy for AC were enrolled in this study. Metagenome analysis demonstrated possible single or multiple bacterial infections in four patients (P1, P2, P3, and P4) with 24-h experimental procedures; in addition, the CTX-M extended-spectrum ß-lactamase (ESBL) gene was identified in two bile samples (P1 and P4). Further whole genome sequencing of Escherichia coli isolates suggested that CTX-M-27-producing ST131 and CTX-M-14-producing novel-ST were identified in P1 and P4, respectively. Metagenome analysis of feces and saliva also suggested some imbalance in the microbiota for more comprehensive assessment of patients with AC. In conclusion, metagenome analysis was useful for rapid bacterial diagnostics, including assessing potential antimicrobial susceptibility, in patients with AC.

Acute bacterial meningitis in adults

Over the past several decades, the incidence of bacterial meningitis in children has decreased but there remains a significant burden of disease in adults, with a mortality of up to 30%. Although the pathogenesis of bacterial meningitis is not completely understood, knowledge of bacterial invasion and entry into the CNS is improving. Clinical features alone cannot determine whether meningitis is present and analysis of cerebrospinal fluid is essential for diagnosis. Newer technologies, such as multiplex PCR, and novel diagnostic platforms that incorporate proteomics and genetic sequencing, might help provide a quicker and more accurate diagnosis. Even with appropriate antimicrobial therapy, mortality is high and so attention has focused on adjunctive therapies; adjunctive corticosteroids are beneficial in certain circumstances. Any further improvements in outcome are likely to come from either modulation of the host response or novel approaches to therapy, rather than new antibiotics. Ultimately, the best hope to reduce the disease burden is with broadly protective vaccines.

Genome Sequencing and Comparative Genomics Analysis Revealed Pathogenic Potential in Penicillium capsulatum as a Novel Fungal Pathogen Belonging to Eurotiales

Penicillium capsulatum is a rare Penicillium species used in paper manufacturing, but recently it has been reported to cause invasive infection. To research the pathogenicity of the clinical Penicillium strain, we sequenced the genomes and transcriptomes of the clinical and environmental strains of P. capsulatum. Comparative analyses of these two P. capsulatum strains and close related strains belonging to Eurotiales were performed. The assembled genome sizes of P. capsulatum are approximately 34.4 Mbp in length and encode 11,080 predicted genes. The different isolates of P. capsulatum are highly similar, with the exception of several unique genes, INDELs or SNPs in the genes coding for glycosyl hydrolases, amino acid transporters and circumsporozoite protein. A phylogenomic analysis was performed based on the whole genome data of 38 strains belonging to Eurotiales. By comparing the whole genome sequences and the virulence-related genes from 20 important related species, including fungal pathogens and non-human pathogens belonging to Eurotiales, we found meaningful pathogenicity characteristics between P. capsulatum and its closely related species. Our research indicated that P. capsulatum may be a neglected opportunistic pathogen. This study is beneficial for mycologists, geneticists and epidemiologists to achieve a deeper understanding of the genetic basis of the role of P. capsulatum as a newly reported fungal pathogen.

Whole genome sequencing of Salmonella Typhimurium illuminates distinct outbreaks caused by an endemic multi-locus variable number tandem repeat analysis type in Australia, 2014

Background

Salmonella Typhimurium (STM) is an important cause of foodborne outbreaks worldwide. Subtyping of STM remains critical to outbreak investigation, yet current techniques (e.g. multilocus variable number tandem repeat analysis, MLVA) may provide insufficient discrimination. Whole genome sequencing (WGS) offers potentially greater discriminatory power to support infectious disease surveillance.

Methods

We performed WGS on 62 STM isolates of a single, endemic MLVA type associated with two epidemiologically independent, food-borne outbreaks along with sporadic cases in New South Wales, Australia, during 2014. Genomes of case and environmental isolates were sequenced using HiSeq (Illumina) and the genetic distance between them was assessed by single nucleotide polymorphism (SNP) analysis. SNP analysis was compared to the epidemiological context.

Results

The WGS analysis supported epidemiological evidence and genomes of within-outbreak isolates were nearly identical. Sporadic cases differed from outbreak cases by a small number of SNPs, although their close relationship to outbreak cases may represent an unidentified common food source that may warrant further public health follow up. Previously unrecognised mini-clusters were detected.

Conclusions

WGS of STM can discriminate foodborne community outbreaks within a single endemic MLVA clone. Our findings support the translation of WGS into public health laboratory surveillance of salmonellosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-016-0831-3) contains supplementary material, which is available to authorized users.

Third generation sequencing technologies applied to diagnostic microbiology: benefits and challenges in applications and data analysis

INTRODUCTION

The diagnosis of infectious diseases is among the most successful areas of application of new generation sequencing technologies. The field has seen the development of numerous experimental and analytical approaches for the detection and the fine description of pathogenic and non-pathogenic microorganisms.

AREAS COVERED

Without claiming to be exhaustive with respect to all applications and methods developed over the years, this review focuses on the advantages and the issues brought by the new technologies, with an eye in particular to third generation sequencing methods. Both experimental procedures and algorithmic strategies are presented, following the most relevant publications which have led to progress in our ability of detecting infectious agents. Expert commentary: The technical advance brought by third generation sequencing platforms has the potential to significantly expand the range of diagnostic tools that will be available to clinicians. Nonetheless, the implementation of these technologies in clinical practice is still far from being actionable and will temporally follow the path undertaken by second generation methods, which still require the setup of standardized pipelines in both wet and dry laboratory procedures.

The use of current genotyping assay methods for Neisseria gonorrhoeae

The review deals with up-to-date genotyping assay methods of Neisseria gonorrhoeae. The review covers the characteristics and features of each method, application areas of genotyping assay of Neisseria gonorrhoeae. The methods described enable to upgrade the diagnostication of gonococcal infection, predict its antibiotic resistance, trace the contagion and channels of the infection as well as study the processes of molecular evolution of the microorganism. Information obtained based on up-to-date N. gonorrhoeae genotyping assay methods can be used in developing the reproductive health strategy of the population.

It Is Not All about Single Nucleotide Polymorphisms: Comparison of Mobile Genetic Elements and Deletions in Listeria monocytogenes Genomes Links Cases of Hospital-Acquired Listeriosis to the Environmental Source

The control of food-borne outbreaks caused by Listeria monocytogenes in humans relies on the timely identification of food or environmental sources and the differentiation of outbreak-related isolates from unrelated ones. This study illustrates the utility of whole-genome sequencing for examining the link between clinical and environmental isolates of L. monocytogenes associated with an outbreak of hospital-acquired listeriosis in Sydney, Australia. Comparative genomic analysis confirmed an epidemiological link between the three clinical and two environmental isolates. Single nucleotide polymorphism (SNP) analysis showed that only two SNPs separated the three human outbreak isolates, which differed by 19 to 20 SNPs from the environmental isolates and 71 to >10,000 SNPs from sporadic L. monocytogenes isolates. The chromosomes of all human outbreak isolates and the two suspected environmental isolates were syntenic. In contrast to the genomes of background sporadic isolates, all epidemiologically linked isolates contained two novel prophages and a previously unreported clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) locus subtype sequence. The mobile genetic element (MGE) profile of these isolates was distinct from that of the other serotype 1/2b reference strains and sporadic isolates. The identification of SNPs and clonally distinctive MGEs strengthened evidence to distinguish outbreak-related isolates of L. monocytogenes from cocirculating endemic strains.

Computational algorithms to predict Gene Ontology annotations

Background

Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful.

Methods

We used a set of computational algorithms and weighting schemes to infer novel gene annotations from a set of known ones. We used the latent semantic analysis approach, implementing two popular algorithms (Latent Semantic Indexing and Probabilistic Latent Semantic Analysis) and propose a novel method, the Semantic IMproved Latent Semantic Analysis, which adds a clustering step on the set of considered genes. Furthermore, we propose the improvement of these algorithms by weighting the annotations in the input set.

Results

We tested our methods and their weighted variants on the Gene Ontology annotation sets of three model organism genes (Bos taurus, Danio rerio and Drosophila melanogaster ). The methods showed their ability in predicting novel gene annotations and the weighting procedures demonstrated to lead to a valuable improvement, although the obtained results vary according to the dimension of the input annotation set and the considered algorithm.

Conclusions

Out of the three considered methods, the Semantic IMproved Latent Semantic Analysis is the one that provides better results. In particular, when coupled with a proper weighting policy, it is able to predict a significant number of novel annotations, demonstrating to actually be a helpful tool in supporting scientists in the curation process of gene functional annotations.

Current and emerging Legionella diagnostics for laboratory and outbreak investigations

Legionnaires' disease (LD) is an often severe and potentially fatal form of bacterial pneumonia caused by an extensive list of Legionella species. These ubiquitous freshwater and soil inhabitants cause human respiratory disease when amplified in man-made water or cooling systems and their aerosols expose a susceptible population. Treatment of sporadic cases and rapid control of LD outbreaks benefit from swift diagnosis in concert with discriminatory bacterial typing for immediate epidemiological responses. Traditional culture and serology were instrumental in describing disease incidence early in its history; currently, diagnosis of LD relies almost solely on the urinary antigen test, which captures only the dominant species and serogroup, Legionella pneumophila serogroup 1 (Lp1). This has created a diagnostic "blind spot" for LD caused by non-Lp1 strains. This review focuses on historic, current, and emerging technologies that hold promise for increasing LD diagnostic efficiency and detection rates as part of a coherent testing regimen. The importance of cooperation between epidemiologists and laboratorians for a rapid outbreak response is also illustrated in field investigations conducted by the CDC with state and local authorities. Finally, challenges facing health care professionals, building managers, and the public health community in combating LD are highlighted, and potential solutions are discussed.

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.

KvarQ: targeted and direct variant calling from fastq reads of bacterial genomes

BACKGROUND

High-throughput DNA sequencing produces vast amounts of data, with millions of short reads that usually have to be mapped to a reference genome or newly assembled. Both reference-based mapping and de novo assembly are computationally intensive, generating large intermediary data files, and thus require bioinformatics skills that are often lacking in the laboratories producing the data. Moreover, many research and practical applications in microbiology require only a small fraction of the whole genome data.

RESULTS

We developed KvarQ, a new tool that directly scans fastq files of bacterial genome sequences for known variants, such as single nucleotide polymorphisms (SNP), bypassing the need of mapping all sequencing reads to a reference genome and de novo assembly. Instead, KvarQ loads "testsuites" that define specific SNPs or short regions of interest in a reference genome, and directly synthesizes the relevant results based on the occurrence of these markers in the fastq files. KvarQ has a versatile command line interface and a graphical user interface. KvarQ currently ships with two "testsuites" for Mycobacterium tuberculosis, but new "testsuites" for other organisms can easily be created and distributed. In this article, we demonstrate how KvarQ can be used to successfully detect all main drug resistance mutations and phylogenetic markers in 880 bacterial whole genome sequences. The average scanning time per genome sequence was two minutes. The variant calls of a subset of these genomes were validated with a standard bioinformatics pipeline and revealed >99% congruency.

CONCLUSION

KvarQ is a user-friendly tool that directly extracts relevant information from fastq files. This enables researchers and laboratory technicians with limited bioinformatics expertise to scan and analyze raw sequencing data in a matter of minutes. KvarQ is open-source, and pre-compiled packages with a graphical user interface are available at http://www.swisstph.ch/kvarq.