Development of an efficient antimicrobial susceptibility testing method with species identification by Nanopore sequencing of 16S rRNA amplicons

Time-course analysis of the effect of paraprobiotics ABG0050 on the intestinal immune system of broilers

With tightening regulations on antibiotic use in broiler production, paraprobiotics (inactivated probiotics) may be a promising alternative to antibiotics. The aim of this study was to analyze the effects of continuous intake of the paraprobiotic Lactiplantibacillus plantarum ABG0050 on growth-associated changes in the immune system of broilers at homeostasis and on the response to immune stimulation. Eighteen three-day-old broiler chicks were divided into two groups: 1: basal diet (Ctrl), 2: basal diet with 0.01 % paraprobiotic ABG0050 (LB). They were reared until 21 days of age, and feces, containing immune-related components secreted in the digestive tract, were collected over time to measure changes in immune markers. On the last day, five birds per group were immunologically stimulated using LPS. Five hours after LPS administration, the birds were dissected, and proventricular tissue was collected to evaluate the expression levels of immune factors at their primary production sites. Analysis of immune markers from fecal samples over time revealed that the expression of antimicrobial peptides AvBD (avian β-defensin) 7 and 12 significantly changed in the LB group, suggesting a modification of innate immunity. Correlation analysis between immune markers and body weight gain (BWG) showed both positive and negative correlations. The expression levels of AvBDs and cytokines in the proventricular tissue after LPS stimulation were measured, and a two-way ANOVA was conducted to analyze the effects of LPS and LB. The results showed no significant effects of either factor on AvBDs, but the expression of Th1-type cytokines, including IFN-γ, IL-6, and IL-12, was significantly increased by the LB factor without interaction with LPS, suggesting that the Th1/Th2 balance was shifted towards Th1 dominance regardless of LPS stimulation. In conclusion, the paraprobiotic ABG0050 modifies both the innate and acquired immune systems of broilers, and the changes in immune markers were also associated with BWG. Furthermore, the modulation of the adaptive immune system by ABG0050 was observed regardless of antigen stimulation.

16S rRNA Gene Sequence Analysis of V6-V8 Region Provides Limited Advantage in Diagnosis of Chronic Prostatitis

Background: 16S rRNA analysis has been used in various diseases to identify pathogenic bacteria. In particular, pathogens that are difficult to cultivate or previously unknown can be detected with great certainty. In chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS), a distinction between bacterial and non-bacterial genesis is essential with regard to categorization and therapy. The objective of this study is to investigate the value of 16S rRNA gene sequence analysis in the routine management of patients with CP/CPPS especially after failure to detect a pathogen in conventional culture and polymerase chain reaction for sexually transmitted diseases (STI-PCR). Methods: In total, 228 patients with CP/CPPS were prospectively enrolled and received a comprehensive andrological work-up. Microbial analysis consisted of standard bacterial cultures and the detection of sexually transmitted pathogens by PCR using urine specimens from a 2-glass test and semen analysis. 16S rRNA gene sequence analysis was performed in patients with urine and semen of patients without bacterial pathogens in microbiological culture and STI-PCR. Results: In 184 of 199 (92%) patients with negative ejaculate culture and negative STI-PCR, no pathogen could be detected by 16S rRNA analysis and in the case of a positive result, the analysis only showed non-pathogenic bacteria of the normal flora. There was no statistical association between the 16S rRNA analysis and the inflammatory markers or the National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) scores. Conclusions: At least in our study cohort, the 16S rRNA analysis provided no additional benefit following microbiological culture and STI-PCR in the categorization of patients with CP/CPPS.

Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin? A systematic review

Food authentication using molecular techniques is of great importance to fight food fraud. Metabarcoding, based on the next-generation sequencing (NGS) technologies, allowing large-scale taxonomic identification of complex samples via massive parallel sequencing of fragments (called DNA barcodes) simultaneously, has become increasingly popular in many scientific fields. A systematic review to answer the question "Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin?" is presented. The inclusion criteria were focused on the selection of scientific papers (SPs) only applying metabarcoding to foodstuff of animal origin collected on the market. The 23 included SPs were first analyzed with respect to the metabarcoding phases: library preparation (target genes, primer pairs, and fragment length), sequencing (NGS platforms), and final data analysis (bioinformatic pipelines). Given the importance of primer selection, the taxonomic coverage of the used primers was also evaluated. In addition, the SPs were scored based on the use of quality control measures (procedural blanks, positive controls, replicates, curated databases, and thresholds to filter the data). A lack of standardized protocols, especially with respect to the target barcode/s and the universal primer/s, and the infrequent application of the quality control measures, leads to answer that metabarcoding is not ripe enough for authenticating foodstuff of animal origin. However, the observed trend of the SP quality improvement over the years is encouraging. Concluding, a proper protocol standardization would allow a wider use of metabarcoding by both official and private laboratories, enabling this method to become the primary for the authentication of foodstuffs of animal origin.

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.