Microarray detection of human parainfluenzavirus 4 infection associated with respiratory failure in an immunocompetent adult

A microarray-based pathogen chip for simultaneous molecular detection of transfusion-transmitted infectious agents

BACKGROUND

New and emerging transfusion-transmitted infections remain a threat to the blood supply. Blood donors are currently screened for less than half of known agents, primarily by individual tests. A screening platform that could simultaneously detect all known transfusion-transmitted pathogens and allow rapid addition of new targets would significantly increase blood safety and could improve the response to new agents. We describe the early stage development and validation of a microarray-based platform (pathogen chip) for simultaneous molecular detection of transfusion-transmitted RNA viruses.

METHODS

Sixteen RNA viruses that pose a significant risk for transfusion-transmission were selected for inclusion on the pathogen chip. Viruses were targeted for detection by 1769 oligonucleotide probes selected by Agilent eArray software. Differentially concentrated positive plasma samples were used to evaluate performance and limits of detection in the context of individual pathogens or combinations to simulate coinfection. RNA-viruses detection and concentration were validated by RT-qPCR.

RESULTS

Hepatitis A, B and C, Chikungunya, dengue 1-4, HIV 1-2, HTLV I-II, West Nile and Zika viruses were all correctly identified by the pathogen chip within the range of 10⁵ to 10² copies/mL; hepatitis E virus from 10⁵ to 10⁴. In mixtures of 3-8 different viruses, all were correctly identified between 10⁵ and 10³ copies/mL.

CONCLUSIONS

This microarray-based multi-pathogen screening platform accurately and reproducibly detected individual and mixed RNA viruses in one test from single samples with limits of detection as low as 10² copies mL.

Bioinformatics and Microarray-Based Technologies to Viral Genome Sequence Analysis

Identification of microbial pathogen is an important event which lead to diagnosis, treatment, and control of infections produce by them. The high-throughput technology like microarray and new-generation sequencing machine are able to generate huge amount of nucleotide sequences of viral and bacterial genome of both known and unknown pathogens. Few years ago it was the DNA microarrays which had great potential to screen all the known pathogens and yet to be identified pathogen simultaneously. But after the development of a new generation sequencing, technologies and advance computational approach researchers are looking forward for a complete understanding of microbes and host interactions. The powerful sequencing platform is rapidly transforming the landscape of microbial identification and characterization. As bioinformatics analysis tools and databases are easily available to researchers, the enormous amount of data generated can be meaningfully handled for better understanding of the microbial world. Here in this chapter, we present commentary on how the computational method incorporated with sequencing technique made easy for microbial detection and characterization.

Development and Assessment of a Diagnostic DNA Oligonucleotide Microarray for Detection and Typing of Meningitis-Associated Bacterial Species

Meningitis is commonly caused by infection with a variety of bacterial or viral pathogens. Acute bacterial meningitis (ABM) can cause severe disease, which can progress rapidly to a critical life-threatening condition. Rapid diagnosis of ABM is critical, as this is most commonly associated with severe sequelae with associated high mortality and morbidity rates compared to viral meningitis, which is less severe and self-limiting. We have designed a microarray for detection and diagnosis of ABM. This has been validated using randomly amplified DNA targets (RADT), comparing buffers with or without formamide, in glass slide format or on the Alere ArrayTube^TM (Alere Technologies GmbH) microarray platform. Pathogen-specific signals were observed using purified bacterial nucleic acids and to a lesser extent using patient cerebral spinal fluid (CSF) samples, with some technical issues observed using RADT and glass slides. Repurposing the array onto the Alere ArrayTube^TM platform and using a targeted amplification system increased specific and reduced nonspecific hybridization signals using both pathogen nucleic and patient CSF DNA targets, better revealing pathogen-specific signals although sensitivity was still reduced in the latter. This diagnostic microarray is useful as a laboratory diagnostic tool for species and strain designation for ABM, rather than for primary diagnosis.

Particle and bioaerosol characteristics in a paediatric intensive care unit

The paediatric intensive care unit (PICU) provides care to critically ill neonates, infants and children. These patients are vulnerable and susceptible to the environment surrounding them, yet there is little information available on indoor air quality and factors affecting it within a PICU. To address this gap in knowledge we conducted continuous indoor and outdoor airborne particle concentration measurements over a two-week period at the Royal Children's Hospital PICU in Brisbane, Australia, and we also collected 82 bioaerosol samples to test for the presence of bacterial and viral pathogens. Our results showed that both 24-hour average indoor particle mass (PM₁₀) (0.6-2.2μgm^-3, median: 0.9μgm^-3) and submicrometer particle number (PN) (0.1-2.8×10³pcm^-3, median: 0.67×10³pcm^-3) concentrations were significantly lower (p<0.01) than the outdoor concentrations (6.7-10.2μgm^-3, median: 8.0μgm^-3 for PM₁₀ and 12.1-22.2×10³pcm^-3, median: 16.4×10³pcm^-3 for PN). In general, we found that indoor particle concentrations in the PICU were mainly affected by indoor particle sources, with outdoor particles providing a negligible background. We identified strong indoor particle sources in the PICU, which occasionally increased indoor PN and PM₁₀ concentrations from 0.1×10³ to 100×10³pcm^-3, and from 2μgm^-3 to 70μgm^-3, respectively. The most substantial indoor particle sources were nebulization therapy, tracheal suction and cleaning activities. The average PM₁₀ and PN emission rates of nebulization therapy ranged from 1.29 to 7.41mgmin^-1 and from 1.20 to 3.96pmin^-1×10¹¹, respectively. Based on multipoint measurement data, it was found that particles generated at each location could be quickly transported to other locations, even when originating from isolated single-bed rooms. The most commonly isolated bacterial genera from both primary and broth cultures were skin commensals while viruses were rarely identified. Based on the findings from the study, we developed a set of practical recommendations for PICU design, as well as for medical and cleaning staff to mitigate aerosol generation and transmission to minimize infection risk to PICU patients.

Metagenomic Investigation of Plasma in Individuals with ME/CFS Highlights the Importance of Technical Controls to Elucidate Contamination and Batch Effects

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease causing indefinite fatigue. ME/CFS has long been hypothesised to have an infectious cause; however, no specific infectious agent has been identified. We used metagenomics to analyse the RNA from plasma samples from 25 individuals with ME/CFS and compare their microbial content to technical controls as well as three control groups: individuals with alternatively diagnosed chronic Lyme syndrome (N = 13), systemic lupus erythematosus (N = 11), and healthy controls (N = 25). We found that the majority of sequencing reads were removed during host subtraction, thus there was very low microbial RNA content in the plasma. The effects of sample batching and contamination during sample processing proved to outweigh the effects of study group on microbial RNA content, as the few differences in bacterial or viral RNA abundance we did observe between study groups were most likely caused by contamination and batch effects. Our results highlight the importance of including negative controls in all metagenomic analyses, since there was considerable overlap between bacterial content identified in study samples and control samples. For example, Proteobacteria, Firmicutes, Actinobacteria, and Bacteriodes were found in both study samples and plasma-free negative controls. Many of the taxonomic groups we saw in our plasma-free negative control samples have previously been associated with diseases, including ME/CFS, demonstrating how incorrect conclusions may arise if controls are not used and batch effects not accounted for.

Genomic Assays for Identification of Chikungunya Virus in Blood Donors, Puerto Rico, 2014

A newly developed transcription-mediated amplification assay was used to detect chikungunya virus infection in 3 of 557 asymptomatic donors (0.54%) from Puerto Rico during the 2014–2015 Caribbean epidemic. Viral detection was confirmed by using PCR, microarray, and next-generation sequencing. Molecular clock analysis dated the emergence of the Puerto Rico strains to early 2013.

Solid and Suspension Microarrays for Microbial Diagnostics

Advancements in molecular technologies have provided new platforms that are being increasingly adopted for use in the clinical microbiology laboratory. Among these, microarray methods are particularly well suited for diagnostics as they allow multiplexing, or the ability to test for multiple targets simultaneously from the same specimen. Microarray technologies commonly used for the detection and identification of microbial targets include solid-state microarrays, electronic microarrays and bead suspension microarrays. Microarray methods have been applied to microbial detection, genotyping and antimicrobial resistance gene detection. Microarrays can offer a panel approach to diagnose specific patient presentations, such as respiratory or gastrointestinal infections, and can discriminate isolates by genotype for tracking epidemiology and outbreak investigations. And, as more information has become available on specific genes and pathways involved in antimicrobial resistance, we are beginning to be able to predict susceptibility patterns based on sequence detection for particular organisms. With further advances in automated microarray processing methods and genotype-phenotype prediction algorithms, these tests will become even more useful as an adjunct or replacement for conventional antimicrobial susceptibility testing, allowing for more rapid selection of targeted therapy for infectious diseases.

Metagenomic assay for identification of microbial pathogens in tumor tissues

Screening for thousands of viruses and other pathogenic microorganisms, including bacteria, fungi, and parasites, in human tumor tissues will provide a better understanding of the contributory role of the microbiome in the predisposition for, causes of, and therapeutic responses to the associated cancer. Metagenomic assays designed to perform these tasks will have to include rapid and economical processing of large numbers of samples, supported by straightforward data analysis pipeline and flexible sample preparation options for multiple input tissue types from individual patients, mammals, or environmental samples. To meet these requirements, the PathoChip platform was developed by targeting viral, prokaryotic, and eukaryotic genomes with multiple DNA probes in a microarray format that can be combined with a variety of upstream sample preparation protocols and downstream data analysis. PathoChip screening of DNA plus RNA from formalin-fixed, paraffin-embedded tumor tissues demonstrated the utility of this platform, and the detection of oncogenic viruses was validated using independent PCR and deep sequencing methods. These studies demonstrate the use of the PathoChip technology combined with PCR and deep sequencing as a valuable strategy for detecting the presence of pathogens in human cancers and other diseases.

IMPORTANCE

This work describes the design and testing of a PathoChip array containing probes with the ability to detect all known publicly available virus sequences as well as hundreds of pathogenic bacteria, fungi, parasites, and helminths. PathoChip provides wide coverage of microbial pathogens in an economical format. PathoChip screening of DNA plus RNA from formalin-fixed, paraffin-embedded tumor tissues demonstrated the utility of this platform, and the detection of oncogenic viruses was validated using independent PCR and sequencing methods. These studies demonstrate that the PathoChip technology is a valuable strategy for detecting the presence of pathogens in human cancers and other diseases.

Detection of a divergent Parainfluenza 4 virus in an adult patient with influenza like illness using next-generation sequencing

BACKGROUND

Human Parainfluenza viruses are a common cause of both upper and lower respiratory tract infections, particularly in children. Of the four Parainfluenza virus serotypes, Parainfluenza 4 is least well characterised from both the clinical, epidemiological and genetic perspectives.

METHODS

Flocked nose or throat swabs from a previous study investigating viral prevalence in community-based adults suffering from influenza like illness were used as the basis for this study. Samples in which no virus was detected using a 16 viral respiratory pathogen real-time PCR panel were barcoded and pyrosequenced using the Roche 454 GS FLX Titanium chemistry. The sequences were analysed using the VirusHunter bioinformatic pipeline. Sanger sequencing was used to complete the detected Parainfluenza 4 coding region.

RESULTS

A variant Parainfluenza 4 subtype b strain (QLD-01) was discovered in an otherwise healthy adult who presented with influenza like illness. Strain QLD-01 shared genomic similarities with both a and b subtypes. The extent of divergence of this genome from the 5 available whole Parainfluenza 4 genomes impacted the predicted binding efficiencies of the majority of published Parainfluenza 4 PCR assays.

CONCLUSIONS

These findings further support a possible role for Parainfluenza 4 in the aetiology of adult respiratory disease within the community setting, and highlight the caution needed to be used in designing PCR assays from limited sequence information or in using proprietary commercial PCR assays.

Deep sequencing to identify the causes of viral encephalitis

Deep sequencing allows for a rapid, accurate characterization of microbial DNA and RNA sequences in many types of samples. Deep sequencing (also called next generation sequencing or NGS) is being developed to assist with the diagnosis of a wide variety of infectious diseases. In this study, seven frozen brain samples from deceased subjects with recent encephalitis were investigated. RNA from each sample was extracted, randomly reverse transcribed and sequenced. The sequence analysis was performed in a blinded fashion and confirmed with pathogen-specific PCR. This analysis successfully identified measles virus sequences in two brain samples and herpes simplex virus type-1 sequences in three brain samples. No pathogen was identified in the other two brain specimens. These results were concordant with pathogen-specific PCR and partially concordant with prior neuropathological examinations, demonstrating that deep sequencing can accurately identify viral infections in frozen brain tissue.

An easy operating pathogen microarray (EOPM) platform for rapid screening of vertebrate pathogens

Background

Infectious diseases emerge frequently in China, partly because of its large and highly mobile population. Therefore, a rapid and cost-effective pathogen screening method with broad coverage is required for prevention and control of infectious diseases. The availability of a large number of microbial genome sequences generated by conventional Sanger sequencing and next generation sequencing has enabled the development of a high-throughput high-density microarray platform for rapid large-scale screening of vertebrate pathogens.

Methods

An easy operating pathogen microarray (EOPM) was designed to detect almost all known pathogens and related species based on their genomic sequences. For effective identification of pathogens from EOPM data, a statistical enrichment algorithm has been proposed, and further implemented in a user-friendly web-based interface.

Results

Using multiple probes designed to specifically detect a microbial genus or species, EOPM can correctly identify known pathogens at the species or genus level in blinded testing. Despite a lower sensitivity than PCR, EOPM is sufficiently sensitive to detect the predominant pathogens causing clinical symptoms. During application in two recent clinical infectious disease outbreaks in China, EOPM successfully identified the responsible pathogens.

Conclusions

EOPM is an effective surveillance platform for infectious diseases, and can play an important role in infectious disease control.

Viral surveillance and discovery

The field of virus discovery has burgeoned with the advent of high throughput sequencing platforms and bioinformatics programs that enable rapid identification and molecular characterization of known and novel agents, investments in global microbial surveillance that include wildlife and domestic animals as well as humans, and recognition that viruses may be implicated in chronic as well as acute diseases. Here we review methods for viral surveillance and discovery, strategies and pitfalls in linking discoveries to disease, and identify opportunities for improvements in sequencing instrumentation and analysis, the use of social media and medical informatics that will further advance clinical medicine and public health.

Virus discovery: one step beyond

•

Efficient responses to viral threats require a integrated multidisciplinary approach.

•

Several relatively newly formed initiatives focus on effective response management.

Recent advances in the metagenomics field have had huge effects on the identification and characterization of newly emerging viral pathogens. To allow timely and efficient responses to future viral threats, an integrated multidisciplinary approach utilizing expertises in several areas, including clinical assessment, virus surveillance, virus discovery, pathogenesis, and the molecular basis of the host response to infection, is required. It requires the scientific community involved in virus discovery to go one step beyond.

Discovery of a divergent HPIV4 from respiratory secretions using second and third generation metagenomic sequencing

Molecular detection of viruses has been aided by high-throughput sequencing, permitting the genomic characterization of emerging strains. In this study, we comprehensively screened 500 respiratory secretions from children with upper and/or lower respiratory tract infections for viral pathogens. The viruses detected are described, including a divergent human parainfluenza virus type 4 from GS FLX pyrosequencing of 92 specimens. Complete full-genome characterization of the virus followed, using Single Molecule, Real-Time (SMRT) sequencing. Subsequent "primer walking" combined with Sanger sequencing validated the RS platform's utility in viral sequencing from complex clinical samples. Comparative genomics reveals the divergent strain clusters with the only completely sequenced HPIV4a subtype. However, it also exhibits various structural features present in one of the HPIV4b reference strains, opening questions regarding their lifecycle and evolutionary relationships among these viruses. Clinical data from patients infected with the strain, as well as viral prevalence estimates using real-time PCR, is also described.

Evaluation of a field-portable DNA microarray platform and nucleic acid amplification strategies for the detection of arboviruses, arthropods, and bloodmeals

Highly multiplexed assays, such as microarrays, can benefit arbovirus surveillance by allowing researchers to screen for hundreds of targets at once. We evaluated amplification strategies and the practicality of a portable DNA microarray platform to analyze virus-infected mosquitoes. The prototype microarray design used here targeted the non-structural protein 5, ribosomal RNA, and cytochrome b genes for the detection of flaviviruses, mosquitoes, and bloodmeals, respectively. We identified 13 of 14 flaviviruses from virus inoculated mosquitoes and cultured cells. Additionally, we differentiated between four mosquito genera and eight whole blood samples. The microarray platform was field evaluated in Thailand and successfully identified flaviviruses (Culex flavivirus, dengue-3, and Japanese encephalitis viruses), differentiated between mosquito genera (Aedes, Armigeres, Culex, and Mansonia), and detected mammalian bloodmeals (human and dog). We showed that the microarray platform and amplification strategies described here can be used to discern specific information on a wide variety of viruses and their vectors.

Discovery of a novel polyomavirus in acute diarrheal samples from children

Polyomaviruses are small circular DNA viruses associated with chronic infections and tumors in both human and animal hosts. Using an unbiased deep sequencing approach, we identified a novel, highly divergent polyomavirus, provisionally named MX polyomavirus (MXPyV), in stool samples from children. The ∼5.0 kB viral genome exhibits little overall homology (<46% amino acid identity) to known polyomaviruses, and, due to phylogenetic variation among its individual proteins, cannot be placed in any existing taxonomic group. PCR-based screening detected MXPyV in 28 of 834 (3.4%) fecal samples collected from California, Mexico, and Chile, and 1 of 136 (0.74%) of respiratory samples from Mexico, but not in blood or urine samples from immunocompromised patients. By quantitative PCR, the measured titers of MXPyV in human stool at 10% (weight/volume) were as high as 15,075 copies. No association was found between the presence of MXPyV and diarrhea, although girls were more likely to shed MXPyV in the stool than boys (p=0.012). In one child, viral shedding was observed in two stools obtained 91 days apart, raising the possibility of chronic infection by MXPyV. A multiple sequence alignment revealed that MXPyV is a closely related variant of the recently reported MWPyV and HPyV10 polyomaviruses. Further studies will be important to determine the association, if any, of MXPyV with disease in humans.

Nucleic acid-based diagnostics for infectious diseases in public health affairs

Infectious diseases, mostly caused by bacteria and viruses but also a result of fungal and parasitic infection, have been one of the most important public health concerns throughout human history. The first step in combating these pathogens is to get a timely and accurate diagnosis at an affordable cost. Many kinds of diagnostics have been developed, such as pathogen culture, biochemical tests and serological tests, to help detect and fight against the causative agents of diseases. However, these diagnostic tests are generally unsatisfactory because they are not particularly sensitive and specific and are unable to deliver speedy results. Nucleic acid-based diagnostics, detecting pathogens through the identification of their genomic sequences, have shown promise to overcome the above limitations and become more widely adopted in clinical tests. Here we review some of the most popular nucleic acid-based diagnostics and focus on their adaptability and applicability to routine clinical usage. We also compare and contrast the characteristics of different types of nucleic acid-based diagnostics.

A novel duplex real-time PCR for HPIV-4 detects co-circulation of both viral subtypes among ill children during 2008

The two subtypes of the human parainfluenzavirus type 4 (HPIV-4) are rarely sought in testing for acute respiratory illness (ARI) and this may be confounding our understanding of its role. This study presents a novel duplex real-time RT-PCR assay targeting the P gene that can detect and differentiate the two subtypes in a single reaction. Subtype-specific synthetic RNA positive controls were prepared and used to determine an analytical sensitivity of 10 copies per reaction with an 8log(10) dynamic range. The assays were validated using 1140 clinical specimens mostly nasopharyngeal aspirates collected from children during 2008. These included specimens previously determined to be positive for all commonly considered respiratory viruses. The novel assay did not cross-reaction with any other virus. Fourteen HPIV-4 positives, ten detected in the absence of any co-detections (four with rhinovirus), were identified in 2008 and their subtype confirmed by conventional RT-PCR and sequencing of P gene fragments. Most detections were in children two years of age or younger. Our assay proved suitably sensitive and specific for inclusion in future studies seeking to better understand the role HPIV-4 and other respiratory viruses in children with ARI.

Virus identification in unknown tropical febrile illness cases using deep sequencing

Dengue virus is an emerging infectious agent that infects an estimated 50–100 million people annually worldwide, yet current diagnostic practices cannot detect an etiologic pathogen in ∼40% of dengue-like illnesses. Metagenomic approaches to pathogen detection, such as viral microarrays and deep sequencing, are promising tools to address emerging and non-diagnosable disease challenges. In this study, we used the Virochip microarray and deep sequencing to characterize the spectrum of viruses present in human sera from 123 Nicaraguan patients presenting with dengue-like symptoms but testing negative for dengue virus. We utilized a barcoding strategy to simultaneously deep sequence multiple serum specimens, generating on average over 1 million reads per sample. We then implemented a stepwise bioinformatic filtering pipeline to remove the majority of human and low-quality sequences to improve the speed and accuracy of subsequent unbiased database searches. By deep sequencing, we were able to detect virus sequence in 37% (45/123) of previously negative cases. These included 13 cases with Human Herpesvirus 6 sequences. Other samples contained sequences with similarity to sequences from viruses in the Herpesviridae, Flaviviridae, Circoviridae, Anelloviridae, Asfarviridae, and Parvoviridae families. In some cases, the putative viral sequences were virtually identical to known viruses, and in others they diverged, suggesting that they may derive from novel viruses. These results demonstrate the utility of unbiased metagenomic approaches in the detection of known and divergent viruses in the study of tropical febrile illness.

Dengue virus infection is a global health concern, affecting as many as 100 million people annually worldwide. A critical first step to proper treatment and control of any virus infection is a correct diagnosis. Traditional diagnostic tests for viruses depend on amplification of conserved portions of the viral genome, detection of the binding of antibodies to viral proteins, or replication of the virus in cell cultures. These methods have a major shortcoming: they are unable to detect divergent or novel viruses for which a priori sequence, serological, or cellular tropism information is not known. In our study, we use two approaches, microarrays and deep sequencing, to virus identification that are less susceptible to such shortcomings. We used these unbiased tools to search for viruses in blood collected from Nicaraguan children with clinical symptoms indicating dengue virus infection, but for whom current dengue virus detection assays yielded negative results. We were able to identify both known and divergent viruses in about one third of previously negative samples, demonstrating the utility of these approaches to detect viruses in cases of unknown dengue-like illness.

Parainfluenza virus infections in children with hematologic malignancies

BACKGROUND

Parainfluenza virus (PIV) infections are an important cause of morbidity in children with upper or lower respiratory tract infection (URTI and LRTI, respectively). However, the epidemiology of PIV infections in children with cancer has not been well studied.

METHODS

This retrospective study sought to determine the epidemiology of PIV infections and risk factors for progression to an LRTI in 1381 children diagnosed with leukemia or lymphoma, between 2000 and 2009.

RESULTS

PIV infections were diagnosed in 83 (10%) of 820 children tested for respiratory infections. PIV type 3 accounted for 49 (61%) of the PIV infections. Of the 83 infections, 75 (90%) were community acquired. Children less than 2 years of age were more likely to have PIV infection (P = 0.002; odds ratio, 2.69; 95% confidence interval, 1.5-4.8). PIV infections were more common in children with acute lymphoblastic leukemia as compared with other malignancies (P < 0.0001; odds ratio, 4.13; 95% confidence interval, 2.37-7.21). The majority of patients, 66 (80%), had URTI. Children with LRTI were a median age of 27 months as compared with 56 months for children with URTI (P = 0.005). Fever with severe neutropenia was more common in patients with LRTI than with URTI (P = 0.02). LRTI was significantly associated with absolute neutrophil count <500 cells/μL (P = 0.002) and absolute lymphocyte count <100 cells/μL (P = 0.008) at onset of PIV infection. There was no mortality attributed to PIV infections, although 3 children required mechanical ventilation for respiratory failure due to PIV infection.

CONCLUSIONS

PIV was the second most common respiratory viral infection in this population after influenza (A and B). Young children were more likely to have PIV infection and LRTI. Severe neutropenia and lymphopenia were associated with LRTI.

Phylogeny-directed search for murine leukemia virus-like retroviruses in vertebrate genomes and in patients suffering from myalgic encephalomyelitis/chronic fatigue syndrome and prostate cancer

Gammaretrovirus-like sequences occur in most vertebrate genomes. Murine Leukemia Virus (MLV) like retroviruses (MLLVs) are a subset, which may be pathogenic and spread cross-species. Retroviruses highly similar to MLLVs (xenotropic murine retrovirus related virus (XMRV) and Human Mouse retrovirus-like RetroViruses (HMRVs)) reported from patients suffering from prostate cancer (PC) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) raise the possibility that also humans have been infected. Structurally intact, potentially infectious MLLVs occur in the genomes of some mammals, especially mouse. Mouse MLLVs contain three major groups. One, MERV G3, contained MLVs and XMRV/HMRV. Its presence in mouse DNA, and the abundance of xenotropic MLVs in biologicals, is a source of false positivity. Theoretically, XMRV/HMRV could be one of several MLLV transspecies infections. MLLV pathobiology and diversity indicate optimal strategies for investigating XMRV/HMRV in humans and raise ethical concerns. The alternatives that XMRV/HMRV may give a hard-to-detect “stealth” infection, or that XMRV/HMRV never reached humans, have to be considered.

Cross-species transmission of a novel adenovirus associated with a fulminant pneumonia outbreak in a new world monkey colony

Adenoviruses are DNA viruses that naturally infect many vertebrates, including humans and monkeys, and cause a wide range of clinical illnesses in humans. Infection from individual strains has conventionally been thought to be species-specific. Here we applied the Virochip, a pan-viral microarray, to identify a novel adenovirus (TMAdV, titi monkey adenovirus) as the cause of a deadly outbreak in a closed colony of New World monkeys (titi monkeys; Callicebus cupreus) at the California National Primate Research Center (CNPRC). Among 65 titi monkeys housed in a building, 23 (34%) developed upper respiratory symptoms that progressed to fulminant pneumonia and hepatitis, and 19 of 23 monkeys, or 83% of those infected, died or were humanely euthanized. Whole-genome sequencing of TMAdV revealed that this adenovirus is a new species and highly divergent, sharing <57% pairwise nucleotide identity with other adenoviruses. Cultivation of TMAdV was successful in a human A549 lung adenocarcinoma cell line, but not in primary or established monkey kidney cells. At the onset of the outbreak, the researcher in closest contact with the monkeys developed an acute respiratory illness, with symptoms persisting for 4 weeks, and had a convalescent serum sample seropositive for TMAdV. A clinically ill family member, despite having no contact with the CNPRC, also tested positive, and screening of a set of 81 random adult blood donors from the Western United States detected TMAdV-specific neutralizing antibodies in 2 individuals (2/81, or 2.5%). These findings raise the possibility of zoonotic infection by TMAdV and human-to-human transmission of the virus in the population. Given the unusually high case fatality rate from the outbreak (83%), it is unlikely that titi monkeys are the native host species for TMAdV, and the natural reservoir of the virus is still unknown. The discovery of TMAdV, a novel adenovirus with the capacity to infect both monkeys and humans, suggests that adenoviruses should be monitored closely as potential causes of cross-species outbreaks.

Infection from adenoviruses, viruses that cause a variety of illnesses in humans, monkeys, and other animals, has conventionally been thought to be species-specific. We used the Virochip, a microarray designed to detect all viruses, to identify a new species of adenovirus (TMAdV, or titi monkey adenovirus) that caused a deadly outbreak in a colony of New World titi monkeys at the California National Primate Research Center (CNPRC), and also infected a human researcher. One-third of the monkeys developed pneumonia and liver inflammation, and 19 of 23 monkeys died or were humanely euthanized. The unusually high death rate (83%) makes titi monkeys unlikely to be natural hosts for TMAdV, and the genomic sequence of TMAdV revealed that it is very different from any other known adenovirus. The researcher developed an acute respiratory illness at the onset of the outbreak, and was found to be infected by TMAdV by subsequent antibody testing. A clinically ill family member with no prior contact with the CNPRC also tested positive. Further investigation is needed to identify whether TMAdV originated from humans, monkeys, or another animal. The discovery of TMAdV suggests that adenoviruses should be monitored closely as potential causes of cross-species outbreaks.

Temporal analysis of the honey bee microbiome reveals four novel viruses and seasonal prevalence of known viruses, Nosema, and Crithidia

Honey bees (Apis mellifera) play a critical role in global food production as pollinators of numerous crops. Recently, honey bee populations in the United States, Canada, and Europe have suffered an unexplained increase in annual losses due to a phenomenon known as Colony Collapse Disorder (CCD). Epidemiological analysis of CCD is confounded by a relative dearth of bee pathogen field studies. To identify what constitutes an abnormal pathophysiological condition in a honey bee colony, it is critical to have characterized the spectrum of exogenous infectious agents in healthy hives over time. We conducted a prospective study of a large scale migratory bee keeping operation using high-frequency sampling paired with comprehensive molecular detection methods, including a custom microarray, qPCR, and ultra deep sequencing. We established seasonal incidence and abundance of known viruses, Nosema sp., Crithidia mellificae, and bacteria. Ultra deep sequence analysis further identified four novel RNA viruses, two of which were the most abundant observed components of the honey bee microbiome (∼10(11) viruses per honey bee). Our results demonstrate episodic viral incidence and distinct pathogen patterns between summer and winter time-points. Peak infection of common honey bee viruses and Nosema occurred in the summer, whereas levels of the trypanosomatid Crithidia mellificae and Lake Sinai virus 2, a novel virus, peaked in January.

Using a pan-viral microarray assay (Virochip) to screen clinical samples for viral pathogens

The diagnosis of viral causes of many infectious diseases is difficult due to the inherent sequence diversity of viruses as well as the ongoing emergence of novel viral pathogens, such as SARS coronavirus and 2009 pandemic H1N1 influenza virus, that are not detectable by traditional methods. To address these challenges, we have previously developed and validated a pan-viral microarray platform called the Virochip with the capacity to detect all known viruses as well as novel variants on the basis of conserved sequence homology¹. Using the Virochip, we have identified the full spectrum of viruses associated with respiratory infections, including cases of unexplained critical illness in hospitalized patients, with a sensitivity equivalent to or superior to conventional clinical testing^2-5. The Virochip has also been used to identify novel viruses, including the SARS coronavirus^6,7, a novel rhinovirus clade⁵, XMRV (a retrovirus linked to prostate cancer)⁸, avian bornavirus (the cause of a wasting disease in parrots)⁹, and a novel cardiovirus in children with respiratory and diarrheal illness¹⁰. The current version of the Virochip has been ported to an Agilent microarray platform and consists of ~36,000 probes derived from over ~1,500 viruses in GenBank as of December of 2009. Here we demonstrate the steps involved in processing a Virochip assay from start to finish (~24 hour turnaround time), including sample nucleic acid extraction, PCR amplification using random primers, fluorescent dye incorporation, and microarray hybridization, scanning, and analysis.

Microbe hunting

Platforms for pathogen discovery have improved since the days of Koch and Pasteur; nonetheless, the challenges of proving causation are at least as daunting as they were in the late 1800 s. Although we will almost certainly continue to accumulate low-hanging fruit, where simple relationships will be found between the presence of a cultivatable agent and a disease, these successes will be increasingly infrequent. The future of the field rests instead in our ability to follow footprints of infectious agents that cannot be characterized using classical microbiological techniques and to develop the laboratory and computational infrastructure required to dissect complex host-microbe interactions. I have tried to refine the criteria used by Koch and successors to prove linkage to disease. These refinements are working constructs that will continue to evolve in light of new technologies, new models, and new insights. What will endure is the excitement of the chase. Happy hunting!

Microbe hunting in laboratory animal research

Recent advances in nucleic acid diagnostic technologies have revolutionized microbiology by facilitating rapid, sensitive pathogen surveillance and differential diagnosis of infectious diseases. With the expansion and dissemination of genomic sequencing technology scientists are discovering new microbes at an accelerating pace. In this article we review recent progress in the field of pathogen surveillance and discovery with a specific focus on applications in the field of laboratory animal research. We discuss the challenges in proving a causal relationship between the presence of a candidate organism and disease. We also discuss the strengths and limitations of various assay platforms and describe a staged strategy for viral diagnostics. To illustrate the complexity of pursuing pathogen discovery research, we include examples from our own work that are intended to provide insights into the process that led to the selection of particular strategies.

A microbial detection array (MDA) for viral and bacterial detection

Background

Identifying the bacteria and viruses present in a complex sample is useful in disease diagnostics, product safety, environmental characterization, and research. Array-based methods have proven utility to detect in a single assay at a reasonable cost any microbe from the thousands that have been sequenced.

Methods

We designed a pan-Microbial Detection Array (MDA) to detect all known viruses (including phages), bacteria and plasmids and developed a novel statistical analysis method to identify mixtures of organisms from complex samples hybridized to the array. The array has broader coverage of bacterial and viral targets and is based on more recent sequence data and more probes per target than other microbial detection/discovery arrays in the literature. Family-specific probes were selected for all sequenced viral and bacterial complete genomes, segments, and plasmids. Probes were designed to tolerate some sequence variation to enable detection of divergent species with homology to sequenced organisms, and to have no significant matches to the human genome sequence.

Results

In blinded testing on spiked samples with single or multiple viruses, the MDA was able to correctly identify species or strains. In clinical fecal, serum, and respiratory samples, the MDA was able to detect and characterize multiple viruses, phage, and bacteria in a sample to the family and species level, as confirmed by PCR.

Conclusions

The MDA can be used to identify the suite of viruses and bacteria present in complex samples.

Intertwining threshold settings, biological data and database knowledge to optimize the selection of differentially expressed genes from microarray

Background

Many tools used to analyze microarrays in different conditions have been described. However, the integration of deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion based on biological functions exists to determine a threshold demonstrating that a gene is indeed differentially expressed.

Methodology/Principal Findings

To improve transcriptomic analysis of microarrays, we propose a new statistical approach that takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed genes in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us to select the optimal threshold required for the most pertinent selection of differentially expressed genes.

Conclusions/Significance

We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. We thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes that are truly differentially expressed.

A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America

Although metagenomics has been previously employed for pathogen discovery, its cost and complexity have prevented its use as a practical front-line diagnostic for unknown infectious diseases. Here we demonstrate the utility of two metagenomics-based strategies, a pan-viral microarray (Virochip) and deep sequencing, for the identification and characterization of 2009 pandemic H1N1 influenza A virus. Using nasopharyngeal swabs collected during the earliest stages of the pandemic in Mexico, Canada, and the United States (n = 17), the Virochip was able to detect a novel virus most closely related to swine influenza viruses without a priori information. Deep sequencing yielded reads corresponding to 2009 H1N1 influenza in each sample (percentage of aligned sequences corresponding to 2009 H1N1 ranging from 0.0011% to 10.9%), with up to 97% coverage of the influenza genome in one sample. Detection of 2009 H1N1 by deep sequencing was possible even at titers near the limits of detection for specific RT-PCR, and the percentage of sequence reads was linearly correlated with virus titer. Deep sequencing also provided insights into the upper respiratory microbiota and host gene expression in response to 2009 H1N1 infection. An unbiased analysis combining sequence data from all 17 outbreak samples revealed that 90% of the 2009 H1N1 genome could be assembled de novo without the use of any reference sequence, including assembly of several near full-length genomic segments. These results indicate that a streamlined metagenomics detection strategy can potentially replace the multiple conventional diagnostic tests required to investigate an outbreak of a novel pathogen, and provide a blueprint for comprehensive diagnosis of unexplained acute illnesses or outbreaks in clinical and public health settings.

Human rhinovirus C: a newly discovered human rhinovirus species

Although often ignored, human rhinoviruses (HRVs) are the most frequent causes of respiratory tract infections (RTIs). A group of closely related novel rhinoviruses have recently been discovered. Based on their unique phylogenetic position and distinct genomic features, they are classified as a separate species, HRV-C. After their discovery, HRV-C viruses have been detected in patients worldwide, with a reported prevalence of 1.4-30.9% among tested specimens. This suggests that the species contribute to a significant proportion of RTIs that were unrecognized in the past. HRV-C is also the predominant HRV species, often with a higher detection rate than that of the two previously known species, HRV-A and HRV-B. HRV-C infections appear to peak in fall or winter in most temperate or subtropical countries, but may predominate in the rainy season in the tropics. In children, HRV-C is often associated with upper RTIs, with asthma exacerbation and wheezing episodes being common complications. The virus has also been detected in children with bronchitis, bronchiolitis, pneumonia, otitis media, sinusitis and systemic infections complicated by pericarditis. As for adults, HRV-C has been associated with more severe disease such as pneumonia and exacerbation of chronic obstructive pulmonary disease. However, larger clinical studies with asymptomatic controls are required to better define the significance of HRV-C infection in the adult population. On the basis of VP4 sequence analysis, a potential distinct subgroup within HRV-C has also been identified, although more complete genome sequences are needed to better define the genetic diversity of HRV-C.

VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

BACKGROUND

All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance.

RESULTS

To specifically address this issue we have developed a novel interpretive algorithm, VIPR (Viral Identification using a PRobabilistic algorithm), which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF) using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation.

CONCLUSIONS

VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.

Metagenomics for the discovery of novel human viruses

Modern laboratory techniques for the detection of novel human viruses are greatly needed as physicians and epidemiologists increasingly deal with infectious diseases caused by new or previously unrecognized pathogens. There are many clinical syndromes in which viruses are suspected to play a role, but for which traditional microbiology techniques routinely fail in uncovering the etiologic agent. In addition, new viruses continue to challenge the human population owing to the encroachment of human settlements into animal and livestock habitats, globalization, climate change, growing numbers of immunocompromised people and bioterrorism. Metagenomics-based tools, such as microarrays and high-throughput sequencing are ideal for responding to these challenges. Pan-viral microarrays, containing representative sequences from all known viruses, have been used to detect novel and distantly-related variants of known viruses. Sequencing-based methods have also been successfully employed to detect novel viruses and have the potential to detect the full spectrum of viruses, including those present in low numbers.

Emerging molecular assays for detection and characterization of respiratory viruses

This article describes several emerging molecular assays that have potential applications in the diagnosis and monitoring of respiratory viral infections. These techniques include direct nucleic acid detection by quantum dots, loop-mediated isothermal amplification, multiplex ligation-dependent probe amplification, amplification using arbitrary primers, target-enriched multiplexing amplification, pyrosequencing, padlock probes, solid and suspension microarrays, and mass spectrometry. Several of these systems already are commercially available to provide multiplex amplification and high-throughput detection and identification of a panel of respiratory viral pathogens. Further validation and implementation of such emerging molecular assays in routine clinical virology services will enhance the rapid diagnosis of respiratory viral infections and improve patient care.

Target amplification for broad spectrum microbial diagnostics and detection

Microarrays are massively parallel detection platforms that were first used extensively for gene expression studies, but have also been successfully applied to microbial detection in a number of diverse fields requiring broad-range microbial identification. This technology has enabled researchers to gain an insight into the microbial diversity of environmental samples, facilitated discovery of a number of new pathogens and enabled studies of multipathogen infections. In contrast to gene expression studies, the concentrations of targets in analyzed samples for microbial detection are usually much lower, and require the use of nucleic acid amplification techniques. The rapid advancement of manufacturing technologies has increased the content of the microarrays; thus, the required amplification is a challenging problem. The constant parallel improvements in both microarray and sample amplification techniques in the near future may lead to a radical progression in medical diagnostics and systems for efficient detection of microorganisms in the environment.

Basic concepts of microarrays and potential applications in clinical microbiology

The introduction of in vitro nucleic acid amplification techniques, led by real-time PCR, into the clinical microbiology laboratory has transformed the laboratory detection of viruses and select bacterial pathogens. However, the progression of the molecular diagnostic revolution currently relies on the ability to efficiently and accurately offer multiplex detection and characterization for a variety of infectious disease pathogens. Microarray analysis has the capability to offer robust multiplex detection but has just started to enter the diagnostic microbiology laboratory. Multiple microarray platforms exist, including printed double-stranded DNA and oligonucleotide arrays, in situ-synthesized arrays, high-density bead arrays, electronic microarrays, and suspension bead arrays. One aim of this paper is to review microarray technology, highlighting technical differences between them and each platform's advantages and disadvantages. Although the use of microarrays to generate gene expression data has become routine, applications pertinent to clinical microbiology continue to rapidly expand. This review highlights uses of microarray technology that impact diagnostic microbiology, including the detection and identification of pathogens, determination of antimicrobial resistance, epidemiological strain typing, and analysis of microbial infections using host genomic expression and polymorphism profiles.

Diagnostics and discovery in viral hemorrhagic fevers

The rate of discovery of new microbes and of new associations of microbes with health and disease is accelerating. Many factors contribute to this phenomenon including those that favor the true emergence of new pathogens as well as new technologies and paradigms that enable their detection and characterization. This chapter reviews recent progress in the field of pathogen surveillance and discovery with a focus on viral hemorrhagic fevers.

Clinical and molecular epidemiology of human parainfluenza virus 4 infections in hong kong: subtype 4B as common as subtype 4A

In this 1-year study, 35 (1.2%) of 2,912 nasopharyngeal aspirates were positive for human parainfluenza virus 4 (HPIV4) by reverse transcription-PCR. Patients with HPIV4 infection were mainly young children and immunocompromised adults. In contrast to the reported predominance of HPIV4A infection, molecular subtyping revealed that 15 (44%) cases were caused by HPIV4B.

Viruses and kidney disease: beyond HIV

SUMMARY

Human immunodeficiency virus (HIV)-infected patients may acquire new viral co-infections; they also may experience the reactivation or worsening of existing viral infections, including active, smoldering, or latent infections. HIV-infected patients may be predisposed to these viral infections owing to immunodeficiency or risk factors common to HIV and other viruses. A number of these affect the kidney, either by direct infection or by deposition of immune complexes. In this review we discuss the renal manifestations and treatment of hepatitis C virus, BK virus, adenovirus, cytomegalovirus, and parvovirus B19 in patients with HIV disease. We also discuss an approach to the identification of new viral renal pathogens, using a viral gene chip to identify viral DNA or RNA.