The diagnostic value of nasal microbiota and clinical parameters in a multi-parametric prediction model to differentiate bacterial versus viral infections in lower respiratory tract infections.

BACKGROUND: The ability to accurately distinguish bacterial from viral infection would help clinicians better target antimicrobial therapy during suspected lower respiratory tract infections (LRTI). Although technological developments make it feasible to rapidly generate patient-specific microbiota profiles, evidence is required to show the clinical value of using microbiota data for infection diagnosis. In this study, we investigated whether adding nasal cavity microbiota profiles to readily available clinical information could improve machine learning classifiers to distinguish bacterial from viral infection in patients with LRTI. RESULTS: Various multi-parametric Random Forests classifiers were evaluated on the clinical and microbiota data of 293 LRTI patients for their prediction accuracies to differentiate bacterial from viral infection. The most predictive variable was C-reactive protein (CRP). We observed a marginal prediction improvement when 7 most prevalent nasal microbiota genera were added to the CRP model. In contrast, adding three clinical variables, absolute neutrophil count, consolidation on X-ray, and age group to the CRP model significantly improved the prediction. The best model correctly predicted 85% of the 'bacterial' patients and 82% of the 'viral' patients using 13 clinical and 3 nasal cavity microbiota genera (Staphylococcus, Moraxella, and Streptococcus). CONCLUSIONS: We developed high-accuracy multi-parametric machine learning classifiers to differentiate bacterial from viral infections in LRTI patients of various ages. We demonstrated the predictive value of four easy-to-collect clinical variables which facilitate personalized and accurate clinical decision-making. We observed that nasal cavity microbiota correlate with the clinical variables and thus may not add significant value to diagnostic algorithms that aim to differentiate bacterial from viral infections.

SARS-CoV-2 viral-load distribution reveals that viral loads increase with age: a retrospective cross-sectional cohort study.

BACKGROUND: Describing the SARS-CoV-2 viral-load distribution in different patient groups and age categories. METHODS: All results from first nasopharyngeal (NP) and oropharyngeal (OP) swabs from unique patients tested via SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) collected between 1 January and 1 December 2020 predominantly in the Public Health Services regions Kennemerland and Hollands Noorden, province of North Holland, the Netherlands, were included in this study. SARS-CoV-2 PCR crossing-point (Cp)-values were used to estimate viral loads. RESULTS: In total, 278 455 unique patients were tested, of whom 9.1% (n = 25.374) were SARS-CoV-2-positive. PCRs performed by Public Health Services (n = 211 914), in which sampling and inclusion were uniform, revealed a clear relation between age and SARS-CoV-2 viral load, with especially children aged <12 years showing lower viral loads than adults (ß: -0.03, 95% confidence interval: -0.03 to -0.02, p < 0.001), independently of sex and/or symptom duration. Interestingly, the median Cp-values between the >79- and <12-year-old populations differed by more than four PCR cycles, suggesting an ∼16-fold difference in viral load. In addition, the proportion of children aged <12 years with a low load (Cp-value >30) was higher compared with other patients (31.1% vs 17.2%, p-value < 0.001). CONCLUSIONS: In patients tested by Public Health Services, SARS-CoV-2 viral load increases with age. Further studies should elucidate whether the lower viral load in children is indeed related to their suggested limited role in SARS-CoV-2 transmission. Moreover, as rapid antigen tests are less sensitive than PCR, these results suggest that SARS-CoV-2 antigen tests have lower sensitivity in children than in adults.

Validation of a multi-species-specific PCR panel to diagnose patients with suspected postoperative bacterial endophthalmitis.

INTRODUCTION: Currently, patients suspected of endophthalmitis are referred to a tertiary centre for a vitreous biopsy and bacterial culture, thereby causing a treatment delay for the intravitreal antibiotics injection. We developed a new diagnostic tool, multi-mono-PCR (mm-PCR), not requiring viable bacteria, allowing antibiotic injection without delay. Performance of mm-PCR was tested on biopsies from patients with suspected postoperative endophthalmitis with known bacterial culture results. METHODS: Most frequently occurring pathogens in endophthalmitis were determined using published data and treatment logs of endophthalmitis patient of the Rotterdam Eye Hospital. Vitreous biopsies from patients with suspected endophthalmitis were aliquoted in two parts. One part was sent out for bacterial culture and another was stored at -80°C for mm-PCR analysis and, as a backup, also by panbacterial PCR. Twelve vitreous samples from patients not suspected of having endophthalmitis were added as control samples. RESULTS: Concordancy between bacterial culture and mm-PCR was 89% (24 of 27). All twelve control samples were negative. In three nonconcordant samples, the PCR results were most likely the correct ones. CONCLUSION: mm-PCR results are highly concordant with bacterial culture. mm-PCR with panbacterial PCR as backup could be considered a diagnostic tool in patients with endophthalmitis, which would allow us to reverse the order of diagnosis and treatment while maintaining diagnostic surveillance, thereby preventing treatment delay.

Understanding and overcoming the pitfalls and biases of next-generation sequencing (NGS) methods for use in the routine clinical microbiological diagnostic laboratory.

Recent advancements in next-generation sequencing (NGS) have provided the foundation for modern studies into the composition of microbial communities. The use of these NGS methods allows for the detection and identification of ('difficult-to-culture') microorganisms using a culture-independent strategy. In the field of routine clinical diagnostics however, the application of NGS is currently limited to microbial strain typing for epidemiological purposes only, even though the implementation of NGS for microbial community analysis may yield clinically important information. This lack of NGS implementation is due to many different factors, including issues relating to NGS method standardization and result reproducibility. In this review article, the authors provide a general introduction to the most widely used NGS methods currently available (i.e., targeted amplicon sequencing and shotgun metagenomics) and the strengths and weaknesses of each method is discussed. The focus of the publication then shifts toward 16S rRNA gene NGS methods, which are currently the most cost-effective and widely used NGS methods for research purposes, and are therefore more likely to be successfully implemented into routine clinical diagnostics in the short term. In this respect, the experimental pitfalls and biases created at each step of the 16S rRNA gene NGS workflow are explained, as well as their potential solutions. Finally, a novel diagnostic microbiota profiling platform ('MYcrobiota') is introduced, which was developed by the authors by taking into consideration the pitfalls, biases, and solutions explained in this article. The development of the MYcrobiota, and future NGS methodologies, will help pave the way toward the successful implementation of NGS methodologies into routine clinical diagnostics.

Galaxy mothur Toolset (GmT): a user-friendly application for 16S rRNA gene sequencing analysis using mothur.

BACKGROUND: The determination of microbial communities using the mothur tool suite (https://www.mothur.org) is well established. However, mothur requires bioinformatics-based proficiency in order to perform calculations via the command-line. Galaxy is a project dedicated to providing a user-friendly web interface for such command-line tools (https://galaxyproject.org/). RESULTS: We have integrated the full set of 125+ mothur tools into Galaxy as the Galaxy mothur Toolset (GmT) and provided a set of workflows to perform end-to-end 16S rRNA gene analyses and integrate with third-party visualization and reporting tools. We demonstrate the utility of GmT by analyzing the mothur MiSeq standard operating procedure (SOP) dataset (https://www.mothur.org/wiki/MiSeq_SOP). CONCLUSIONS: GmT is available from the Galaxy Tool Shed, and a workflow definition file and full Galaxy training manual for the mothur SOP have been created. A Docker image with a fully configured GmT Galaxy is also available.

Monitoring of microbial dynamics in a drinking water distribution system using the culture-free, user-friendly, MYcrobiota platform.

Drinking water utilities currently rely on a range of microbiological detection techniques to evaluate the quality of their drinking water (DW). However, microbiota profiling using culture-free 16S rRNA gene next-generation sequencing (NGS) provides an opportunity for improved monitoring of the microbial ecology and quality of DW. Here, we evaluated the utility of a previously validated microbiota profiling platform (MYcrobiota) to investigate the microbial dynamics of a full-scale, non-chlorinated DW distribution system (DWDS). In contrast to conventional methods, we observed spatial and temporal bacterial genus changes (expressed as operational taxonomic units - OTUs) within the DWDS. Further, a small subset of bacterial OTUs dominated with abundances that shifted across the length of the DWDS, and were particularly affected by a post-disinfection step. We also found seasonal variation in OTUs within the DWDS and that many OTUs could not be identified, even though MYcrobiota is specifically designed to reduce potential PCR sequencing artefacts. This suggests that our current knowledge about the microbial ecology of DW communities is limited. Our findings demonstrate that the user-friendly MYcrobiota platform facilitates culture-free, standardized microbial dynamics monitoring and has the capacity to facilitate the introduction of microbiota profiling into the management of drinking water quality.

Development and evaluation of a culture-free microbiota profiling platform (MYcrobiota) for clinical diagnostics.

Microbiota profiling has the potential to greatly impact on routine clinical diagnostics by detecting DNA derived from live, fastidious, and dead bacterial cells present within clinical samples. Such results could potentially be used to benefit patients by influencing antibiotic prescribing practices or to generate new classical-based diagnostic methods, e.g., culture or PCR. However, technical flaws in 16S rRNA gene next-generation sequencing (NGS) protocols, together with the requirement for access to bioinformatics, currently hinder the introduction of microbiota analysis into clinical diagnostics. Here, we report on the development and evaluation of an "end-to-end" microbiota profiling platform (MYcrobiota), which combines our previously validated micelle PCR/NGS (micPCR/NGS) methodology with an easy-to-use, dedicated bioinformatics pipeline. The newly designed bioinformatics pipeline processes micPCR/NGS data automatically and summarizes the results in interactive, but simple web reports. In order to explore the utility of MYcrobiota in clinical diagnostics, 47 clinical samples (40 "damaged skin" samples and 7 synovial fluids) were investigated using routine bacterial culture as comparator. MYcrobiota confirmed the presence of bacterial DNA in 37/37 culture-positive samples and detected bacterial taxa in 2/10 culture-negative samples. Moreover, 36/38 potentially relevant aerobic bacterial taxa and 3/3 mixtures of anaerobic bacteria were identified using culture and MYcrobiota, with the sensitivity and specificity being 95%. Interestingly, the majority of the 448 bacterial taxa identified using MYcrobiota were not identified using culture, which could potentially have an impact on clinical decision-making. Taken together, the development of MYcrobiota is a promising step towards the introduction of microbiota analysis into clinical diagnostic laboratories.

Characterization of the nasopharyngeal and middle ear microbiota in gastroesophageal reflux-prone versus gastroesophageal reflux non-prone children.

Otitis media (OM) is one of the most common pediatric infections worldwide, but the complex microbiology associated with OM is poorly understood. Previous studies have shown an association between OM and gastroesophageal reflux (GER) in children. Therefore, in order to bridge the gap in our current understanding of the interaction between GER and OM, we investigated the nasopharyngeal and middle ear microbiota of children suffering from GER-associated OM and OM only, using culture-independent 16S rRNA gene sequencing. Middle ear fluid, nasopharyngeal swabs, and clinical data were collected as part of a prospective pilot study conducted at the Department of Otorhinolaryngology of the Erasmus MC-Sophia Children's Hospital, Rotterdam, the Netherlands. A total of 30 children up to 12 years of age who suffered from recurrent acute otitis media (AOM) (5), chronic otitis media with effusion (OME) (23), or both (2), and who were listed for tympanostomy tube placement, were included in the study. Nine children were included in the GER-associated OM cohort and 21 in the OM-only cohort. We found no obvious effect of GER on the nasopharyngeal and middle ear microbiota between the two groups of children. However, our results highlight the need to assess the true role of Alloiococcus spp. and Turicella spp. in children presenting with a high prevalence of recurrent AOM and chronic OME.

Novel micelle PCR-based method for accurate, sensitive and quantitative microbiota profiling.

In the last decade, many researchers have embraced 16S rRNA gene sequencing techniques, which has led to a wealth of publications and documented differences in the composition of microbial communities derived from many different ecosystems. However, comparison between different microbiota studies is currently very difficult due to the lack of a standardized 16S rRNA gene sequencing protocol. Here we report on a novel approach employing micelle PCR (micPCR) in combination with an internal calibrator that allows for standardization of microbiota profiles via their absolute abundances. The addition of an internal calibrator allows the researcher to express the resulting operational taxonomic units (OTUs) as a measure of 16S rRNA gene copies by correcting the number of sequences of each individual OTU in a sample for efficiency differences in the NGS process. Additionally, accurate quantification of OTUs obtained from negative extraction control samples allows for the subtraction of contaminating bacterial DNA derived from the laboratory environment or chemicals/reagents used. Using equimolar synthetic microbial community samples and low biomass clinical samples, we demonstrate that the calibrated micPCR/NGS methodology possess a much higher precision and a lower limit of detection compared with traditional PCR/NGS, resulting in more accurate microbiota profiles suitable for multi-study comparison.

Comparison of Mycoplasma pneumoniae Genome Sequences from Strains Isolated from Symptomatic and Asymptomatic Patients.

Mycoplasma pneumoniae is a common cause of respiratory tract infections (RTIs) in children. We recently demonstrated that this bacterium can be carried asymptomatically in the respiratory tract of children. To identify potential genetic differences between M. pneumoniae strains that are carried asymptomatically and those that cause symptomatic infections, we performed whole-genome sequence analysis of 20 M. pneumoniae strains. The analyzed strains included 3 reference strains, 3 strains isolated from asymptomatic children, 13 strains isolated from clinically well-defined patients suffering from an upper (n = 4) or lower (n = 9) RTI, and one strain isolated from a follow-up patient who recently recovered from an RTI. The obtained sequences were each compared to the sequences of the reference strains. To find differences between strains isolated from asymptomatic and symptomatic individuals, a variant comparison was performed between the different groups of strains. Irrespective of the group (asymptomatic vs. symptomatic) from which the strains originated, subtype 1 and subtype 2 strains formed separate clusters. We could not identify a specific genotype associated with M. pneumoniae virulence. However, we found marked genetic differences between clinical isolates and the reference strains, which indicated that the latter strains may not be regarded as appropriate representatives of circulating M. pneumoniae strains.

Detection of Healthcare-Related Extended-Spectrum Beta-Lactamase-Producing Escherichia coli Transmission Events Using Combined Genetic and Phenotypic Epidemiology.

BACKGROUND: Since the year 2000 there has been a sharp increase in the prevalence of healthcare-related infections caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli. However, the high community prevalence of ESBL-producing E. coli isolates means that many E. coli typing techniques may not be suitable for detecting E. coli transmission events. Therefore, we investigated if High-throughput MultiLocus Sequence Typing (HiMLST) and/or Raman spectroscopy were suitable techniques for detecting recent E. coli transmission events. METHODS: This study was conducted from January until December 2010 at Erasmus University Medical Center, Rotterdam, the Netherlands. Isolates were typed using HiMLST and Raman spectroscopy. A genetic cluster was defined as two or more patients carrying identical isolates. We used predefined definitions for epidemiological relatedness to assess healthcare-related transmission. RESULTS: We included 194 patients; strains of 112 patients were typed using HiMLST and strains of 194 patients were typed using Raman spectroscopy. Raman spectroscopy identified 16 clusters while HiMLST identified 10 clusters. However, no healthcare-related transmission events were detected. When combining data from both typing techniques, we identified eight clusters (n = 34 patients), as well as 78 patients with a non-cluster isolate. However, we could not detect any healthcare-related transmission in these 8 clusters. CONCLUSIONS: Although clusters were genetically detected using HiMLST and Raman spectroscopy, no definite epidemiological relationships could be demonstrated which makes the possibility of healthcare-related transmission events highly unlikely. Our results suggest that typing of ESBL-producing E. coli using HiMLST and/or Raman spectroscopy is not helpful in detecting E. coli healthcare-related transmission events.

Micelle PCR reduces chimera formation in 16S rRNA profiling of complex microbial DNA mixtures.

16S rRNA gene profiling has revolutionized the field of microbial ecology. Many researchers in various fields have embraced this technology to investigate bacterial compositions of samples derived from many different ecosystems. However, it is important to acknowledge the current limitations and drawbacks of 16S rRNA gene profiling. Although sample handling, DNA extraction methods and the choice of universal 16S rRNA gene PCR primers are well known factors that could seriously affect the final results of microbiota profiling studies, inevitable amplification artifacts, such as chimera formation and PCR competition, are seldom appreciated. Here we report on a novel micelle based amplification strategy, which overcomes these limitations via the clonal amplification of targeted DNA molecules. Our results show that micelle PCR drastically reduces chimera formation by a factor of 38 (1.5% vs. 56.9%) compared with traditional PCR, resulting in improved microbial diversity estimates. In addition, compartmentalization during micelle PCR prevents PCR competition due to unequal amplification rates of different 16S template molecules, generating robust and accurate 16S microbiota profiles required for comparative studies (e.g. longitudinal surveys).

Genome analysis of Legionella pneumophila strains using a mixed-genome microarray.

BACKGROUND: Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. METHODS: Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in The Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. RESULTS: Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. CONCLUSIONS: The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.

High-throughput multilocus sequence typing: bringing molecular typing to the next level.

Multilocus sequence typing (MLST) is a widely used system for typing microorganisms by sequence analysis of housekeeping genes. The main advantage of MLST in comparison to other typing techniques is the unambiguity and transferability of sequence data. However, a main disadvantage is the high cost of DNA sequencing. Here we introduce a high-throughput MLST (HiMLST) method that employs next-generation sequencing (NGS) technology (Roche 454), to generate large quantities of high-quality MLST data at low costs. The HiMLST protocol consists of two steps. In the first step MLST target genes are amplified by PCR in multi-well plates. During this PCR the amplicons of each bacterial isolate are provided with a unique DNA barcode, the multiplex identifier (MID). In the second step all amplicons are pooled and sequenced in a single NGS-run. The MLST profile of each individual isolate can be retrieved easily using its unique MID. With HiMLST we have profiled 575 isolates of Legionella pneumophila, Staphylococcus aureus, Pseudomonas aeruginosa and Streptococcus pneumoniae in mixed species HiMLST experiments. In conclusion, the introduction of HiMLST paves the way for a broad employment of the MLST as a high-quality and cost-effective method for typing microbial species.

Diagnostic value of zinc protoporphyrin in a screening strategy for alpha-thalassemia.

The definitive diagnosis of alpha-thalassemia involves detection of a deletion of one or more alpha-globin that encode the alpha-chains of Hb (hemoglobin). To determine whether DNA analysis is indicated, screening tests such as mean corpuscular volume (MCV) and Hb typing are employed. alpha-Thalassemia often correlates with normal or low HbA2 values. Zinc protoporphyrin (ZPP) is usually high in ferropenic anemia or lead-poisoning and is normal or slightly raised in beta-thalassemia. Therefore, ZPP is currently used as a marker to discriminate between ferropenic anemia and beta-thalassemia. We investigated the diagnostic potential of ZPP < 150 micromol/mol heme in a screening strategy for alpha-thalassemia. We measured ZPP and performed DNA analysis for detecting the seven most prevalent alpha-thalassemia deletions, namely, alpha3.7, SEA, alpha20.5, alpha4.2, MED, FIL, and THAI, in the blood samples of 200 patients with MCV < 70 fL and HbA2 < or = 3.5%. Deletions were detected in 9% subjects in the ZPP > or = 150 group (n = 175) and 56% subjects in the ZPP < 150 group (n = 29); this difference was statistically significant (chi-square test, P < 0.001). We conclude that ZPP < 150 micromol/mol heme can be used in a new screening strategy for alpha-thalassemia.

Characterization of plasmid pOR1 from Ornithobacterium rhinotracheale and construction of a shuttle plasmid.

The bacterium Ornithobacterium rhinotracheale has been recognized as an emerging pathogen in poultry since about 10 years ago. Knowledge of this bacterium and its mechanisms of virulence is still very limited. Here we report the development of a transformation system that enables genetic modification of O. rhinotracheale. The system is based on a cryptic plasmid, pOR1, that was derived from an O. rhinotracheale strain of serotype K. Sequencing indicated that the plasmid consisted of 14,787 nucleotides. Sequence analysis revealed one replication origin and several rep genes that control plasmid replication and copy number, respectively. In addition, pOR1 contains genes with similarity to a heavy-metal-transporting ATPase, a TonB-linked siderophore receptor, and a laccase. Reverse transcription-PCR demonstrated that these genes were transcribed. Other putative open reading frames exhibited similarities with a virulence-associated protein in Actinobacillus actinomycetemcomitans and a number of genes coding for proteins with unknown function. An Escherichia coli-O. rhinotracheale shuttle plasmid (pOREC1) was constructed by cloning the replication origin and rep genes from pOR1 and the cfxA gene from Bacteroides vulgatus, which codes for resistance to the antibiotic cefoxitin, into plasmid pGEM7 by using E. coli as a host. pOREC1 was electroporated into O. rhinotracheale and yielded cefoxitin-resistant transformants. The pOREC1 isolated from these transformants was reintroduced into E. coli, demonstrating that pOREC1 acts as an independent replicon in both E. coli and O. rhinotracheale, fulfilling the criteria for a shuttle plasmid that can be used for transformation, targeted mutagenesis, and the construction of defined attenuated vaccine strains.

Identification of genes affecting Salmonella enterica serovar enteritidis infection of chicken macrophages.

Screening of 7,680 Salmonella enterica serovar Enteritidis mutants for attenuation in a chicken macrophage infection model yielded a series of mutants including several with defects in previously unrecognized Salmonella virulence genes. One of the newly identified genes was the pbpA2 gene, belonging to the penicillin binding protein gene family.

Identification of genes that are associated with DNA repeats in prokaryotes.

Using in silico analysis we studied a novel family of repetitive DNA sequences that is present among both domains of the prokaryotes (Archaea and Bacteria), but absent from eukaryotes or viruses. This family is characterized by direct repeats, varying in size from 21 to 37 bp, interspaced by similarly sized non-repetitive sequences. To appreciate their characteri-stic structure, we will refer to this family as the clustered regularly interspaced short palindromic repeats (CRISPR). In most species with two or more CRISPR loci, these loci were flanked on one side by a common leader sequence of 300-500 b. The direct repeats and the leader sequences were conserved within a species, but dissimilar between species. The presence of multiple chromosomal CRISPR loci suggests that CRISPRs are mobile elements. Four CRISPR-associated (cas) genes were identified in CRISPR-containing prokaryotes that were absent from CRISPR-negative prokaryotes. The cas genes were invariably located adjacent to a CRISPR locus, indicating that the cas genes and CRISPR loci have a functional relationship. The cas3 gene showed motifs characteristic for helicases of the superfamily 2, and the cas4 gene showed motifs of the RecB family of exonucleases, suggesting that these genes are involved in DNA metabolism or gene expression. The spatial coherence of CRISPR and cas genes may stimulate new research on the genesis and biological role of these repeats and genes.