What Does 16S rRNA Gene-Targeted Next Generation Sequencing Contribute to the Study of Infective Endocarditis in Heart-Valve Tissue?

Impact of lactic acid bacteria inoculation on fungal diversity during Spanish-style green table olive fermentations

This study delved into the evolution of fungal population during the fermentation of Spanish-style green table olives (Manzanilla cultivar), determining the influence of different factors such as fermentation matrix (brine or fruit) or the use of a lactic acid bacteria inoculum, on its distribution. The samples (n = 24) were directly obtained from industrial fermentation vessels with approximately 10.000 kg of fruits and 6.000 L of brines. Our findings showcased a synchronized uptick in lactic acid bacteria counts alongside fungi proliferation. Metataxonomic analysis of the Internal Transcribed Spacer (ITS) region unearthed noteworthy disparities across different fermentation time points (0, 24, and 83 days). Statistical analysis pinpointed two Amplicon Sequence Variants (ASV), Candida and Aureobasidium, as accountable for the observed variances among the different fermentation time samples. Notably, Candida exhibited a marked increase during 83 days of fermentation, opposite to Aureobasidium, which demonstrated a decline. Fungal biodiversity was slightly higher in brines than in fruits, whilst no effect of inoculation was noticed. At the onset of fermentation, prominently detected genera were also Mycosphaerella (19.82 %) and Apohysomyces (16.31 %), hitherto unreported in the context of table olive processing. However, their prevalence dwindled to nearly negligible levels from 24th day fermentation onwards (<2 %). On the contrary, they were replaced by the fermentative yeasts Saccharomyces and Isstachenkia. Results obtained in this work will be useful for designing new strategies for better control of table olive fermentations.

Evaluating the diagnostic accuracy and clinical utility of 16S and 18S rRNA gene targeted next-generation sequencing based on five years of clinical experience

BACKGROUND

The use of 16S/18S rRNA targeted next-generation sequencing (tNGS) has improved microbial diagnostics, however, the use of tNGS in a routine clinical setting requires further elucidation. We retrospectively evaluated the diagnostic accuracy and clinical utility of 16S/18S tNGS, routinely used in the North Denmark Region between 2017 and 2021.

METHODS

We retrieved 544 tNGS results from 491 patients hospitalised with suspected infection (e.g. meningitis, pneumonia, intraabdominal abscess, osteomyelitis and joint infection). The tNGS assays was performed using the Illumina MiSeq desktop sequencer, and BION software for annotation. The patients' diagnosis and clinical management was evaluated by medical chart review. We calculated sensitivity and specificity, and determined the diagnostic accuracy of tNGS by defining results as true positive, true negative, false positive, and false negative.

RESULTS

Overall, tNGS had a sensitivity of 56% and a specificity of 97%. tNGS was more frequently true positive compared to culture (32% vs 18%), and tNGS detected a greater variety of bacteria and fungi, and was more frequently polymicrobial. However, the total diagnostic turnaround time was 16 days, and although 73% of tNGS results were true positive or true negative, only 4.4% of results led to changes in clinical management.

CONCLUSIONS

As a supplement to culture, tNGS improves identification of pathogenic microorganisms in a broad range of clinical specimens. However, the long turnaround time of tNGS in our setting may have contributed to a limited clinical utility. An improved turnaround time can be the key to improved clinical utility in a future setting.

16S rRNA Gene PCR/Sequencing of Heart Valves for Diagnosis of Infective Endocarditis in Routine Clinical Practice

Sequencing is increasingly used for infective endocarditis (IE) diagnosis. Here, the performance of 16S rRNA gene PCR/sequencing of heart valves utilized in routine clinical practice was compared with conventional IE diagnostics. Subjects whose heart valves were sent to the clinical microbiology laboratory for 16S rRNA gene PCR/sequencing from August 2020 through February 2022 were studied. A PCR assay targeting V1 to V3 regions of the 16S rRNA gene was performed, followed by Sanger and/or next-generation sequencing (NGS) (using an Illumina MiSeq), or reported as negative, depending on an algorithm that included the PCR cycle threshold value. Fifty-four subjects, including 40 with IE, three with cured IE, and 11 with noninfective valvular disease, were studied. Thirty-one positive results, 11 from NGS and 20 from Sanger sequencing, were generated from analysis of 16S rRNA gene sequence(s). Positivity rates of blood cultures and 16S rRNA gene PCR/sequencing of valves were 55% and 75%, respectively (P = 0.06). In those with prior antibiotic exposure, positivity rates of blood cultures and 16S rRNA gene PCR/sequencing of valves were 11% and 76%, respectively (P < 0.001). Overall, 61% of blood culture-negative IE subjects had positive valve 16S rRNA gene PCR/sequencing results. 16S rRNA gene-based PCR/sequencing of heart valves is a useful diagnostic tool for pathogen identification in patients with blood culture-negative IE undergoing valve surgery in routine clinical practice.

Next-generation sequencing: what are the needs in routine clinical microbiology? A survey among clinicians involved in infectious diseases practice

Background

The translation of Next-Generation Sequencing (NGS) from research to clinical microbiology is increasing rapidly, but its integration into routine clinical care struggles to catch-up. A challenge for clinical laboratories is that the substantial investments made in the required technologies and resources must meet both current and forthcoming needs.

Methods

To get a clinical perspective of these needs, we have sent a survey to infectious diseases clinicians of five hospitals, covering the following topics: NGS knowledge, expected syndromes and patients foreseen to benefit from NGS, and expected impact on antimicrobial prescription.

Results

According to clinicians, benefits of NGS are mostly expected in neurological and respiratory infections diagnostics.

Conclusion

A better dialog between microbiologists and clinicians about hopes and limits of NGS in microbiology may help identifying key investments needed for clinical laboratories, today and tomorrow.

Diagnosis of pathogens causing bacterial meningitis using Nanopore sequencing in a resource-limited setting

Aim

The aim of the present study is to compare the performance of 16S rRNA Nanopore sequencing and conventional culture in detecting infectious pathogens in patients with suspected meningitis in a resource-limited setting without extensive bioinformatics expertise.

Methods

DNA was isolated from the cerebrospinal fluid (CSF) of 30 patients with suspected bacterial meningitis. The isolated DNA was subjected to 16S sequencing using MinION™. The data were analysed in real time via the EPI2ME cloud platform. The Nanopore sequencing was done in parallel to routine microbiological diagnostics.

Results

Nanopore sequencing detected bacterial pathogens to species level in 13 of 30 (43%) samples. CSF culture showed 40% (12/30) positivity. In 21 of 30 patients (70%) with suspected bacterial meningitis, both methods yielded concordant results. About nine of 30 samples showed discordant results, of these five were false positive and four were false negative. In five of the culture negative results, nanopore sequencing was able to detect pathogen genome, due to the higher sensitivity of the molecular diagnostics. In two other samples, the CSF culture revealed Cryptococcus neoformans and Streptococcus pneumoniae, which were not detected by Nanopore sequencing. Overall, using both the cultures and 16S Nanopore sequencing, positivity rate increased from 40% (12/30) to 57% (17/30).

Conclusion

Next-generation sequencing could detect pathogens within six hours and could become an important tool for both pathogen screening and surveillance in low- and middle-income countries (LMICs) that do not have direct access to extensive bioinformatics expertise.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12941-022-00530-6.