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

Machine Learning Metabolomics Profiling of Dietary Interventions from a Six-Week Randomised Trial

Metabolomics can uncover physiological responses to prebiotic fibre and omega-3 fatty acid supplements with known health benefits and identify response-specific metabolites. We profiled 534 stool and 799 serum metabolites in 64 healthy adults following a 6-week randomised trial comparing daily omega-3 versus inulin supplementation. Elastic net regressions were used to separately identify the serum and stool metabolites whose change in concentration discriminated between the two types of supplementations. Random forest was used to explore the gut microbiome's contribution to the levels of the identified metabolites from matching stool samples. Changes in serum 3-carboxy-4-methyl-5-propyl-2-furanpropanoate and indoleproprionate levels accurately discriminated between fibre and omega-3 (area under the curve (AUC) = 0.87 [95% confidence interval (CI): 0.63-0.99]), while stool eicosapentaenoate indicated omega-3 supplementation (AUC = 0.86 [95% CI: 0.64-0.98]). Univariate analysis also showed significant increases in indoleproprionate with fibre, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, and eicosapentaenoate with omega-3. Out of these, only the change in indoleproprionate was partly explained by changes in the gut microbiome composition (AUC = 0.61 [95% CI: 0.58-0.64] and Rho = 0.21 [95% CI: 0.08-0.34]) and positively correlated with the increase in the abundance of the genus Coprococcus (p = 0.005). Changes in three metabolites discriminated between fibre and omega-3 supplementation. The increase in indoleproprionate with fibre was partly explained by shifts in the gut microbiome, particularly Coprococcus, previously linked to better health.

Improved Diagnostics in Bacterial Neonatal Meningitis Using a Next-Generation Sequencing Platform

INTRODUCTION

Bacterial meningitis in infants is an infrequent but life-threatening condition. Empiric therapy should begin as soon as meningitis is thought likely. Consequently, the causative microorganisms may not always be detected using culturing techniques, as cerebrospinal fluid (CSF) cultures are influenced by antibiotics. Nucleic acid amplification tests, such as polymerase chain reaction (PCR) (multiplex panels), may overcome this limitation but require a priori knowledge of the likely pathogen present within the sample. With this in mind, we investigated to what extent a culture-free, broad-range 16S rRNA gene next-generation sequencing (NGS) platform (MYcrobiota) could add to the microbiological diagnosis of meningitis.

METHODS

Retrospective cohort study at level III neonatal intensive care unit. Included were all infants with suspected meningitis admitted between 10 November 2017 and 31 December 2020. A comparison was made of the bacterial pathogen detection rate between MYcrobiota and conventional bacterial culture.

RESULTS

In a 3-year period, 37 CSF samples (diagnostic and follow-up) from 35 infants with proven or possible meningitis were available for MYcrobiota testing. MYcrobiota detected the presence of bacterial pathogens in 11 samples (30%), in contrast with the conventional CSF culture, which detected bacteria in 2 of 36 samples (5.6%).

CONCLUSION

Addition of 16S rRNA sequencing to conventional culturing greatly improved the identification of the aetiology of bacterial meningitis compared to culturing of CSF samples alone.

Comparison of 16S rDNA Amplicon Sequencing With the Culture Method for Diagnosing Causative Pathogens in Bacterial Corneal Infections

Purpose

The purpose of this study was to explore if 16S rDNA amplicon sequencing can improve the conventional diagnosis of causative pathogens for bacterial corneal infection.

Methods

Corneal scraping and conjunctiva and eyelid margin swab samples from infected eyes of patients diagnosed with "bacterial corneal infection" and conjunctiva and eyelid margin swab samples from a random eye of healthy participants were collected. Each swab was used for both aerobic and anaerobic cultures and 16S rDNA amplicon sequencing. The V3 to V4 region of the 16S rDNA was amplified using polymerase chain reaction (PCR) and sequenced on the Illumina HiSeq 2500 Sequencing Platform.

Results

The overall culture positivity rate for all 72 samples was 69% (72% in the bacterial keratitis group and 67% in the healthy control group), whereas 1719 operational taxonomic units in total were generated using 16S rDNA amplicon sequencing with each sample showing 123 to 337 different genera. Staphylococcus, Corynebacterium, Propionibacterium, and Micrococcus most frequently appeared in culture, whereas Streptococcus, Acinetobacter, and Lactobacillus were the most common genera, with large ratios in 16S rDNA amplicon sequencing. The causative pathogens detected by the two methods were inconsistent for most samples, except for several corneal samples.

Conclusions

We suggest that a combination of different techniques, such as clinical observation, microscopic analysis, culture, and next-generation sequencing techniques including 16S rDNA amplicon sequencing, should be used to comprehensively analyze pathogens in corneal and external ocular infections.

Translational Relevance

This paper uses a basic research methodology for studying the microbiome in ocular samples to help improve the diagnostic accuracy of corneal and external ocular infections.

A High Protein Diet Is More Effective in Improving Insulin Resistance and Glycemic Variability Compared to a Mediterranean Diet-A Cross-Over Controlled Inpatient Dietary Study

The optimal dietary pattern to improve metabolic function remains elusive. In a 21-day randomized controlled inpatient crossover feeding trial of 20 insulin-resistant obese women, we assessed the extent to which two isocaloric dietary interventions—Mediterranean (M) and high protein (HP)—improved metabolic parameters. Obese women were assigned to one of the following dietary sequences: M–HP or HP–M. Cardiometabolic parameters, body weight, glucose monitoring and gut microbiome composition were assessed. Sixteen women completed the study. Compared to the M diet, the HP diet was more effective in (i) reducing insulin resistance (insulin: Beta (95% CI) = −6.98 (−12.30, −1.65) µIU/mL, p = 0.01; HOMA-IR: −1.78 (95% CI: −3.03, −0.52), p = 9 × 10⁻³); and (ii) improving glycemic variability (−3.13 (−4.60, −1.67) mg/dL, p = 4 × 10⁻⁴), a risk factor for T2D development. We then identified a panel of 10 microbial genera predictive of the difference in glycemic variability between the two diets. These include the genera Coprococcus and Lachnoclostridium, previously associated with glucose homeostasis and insulin resistance. Our results suggest that morbidly obese women with insulin resistance can achieve better control of insulin resistance and glycemic variability on a high HP diet compared to an M diet.

Comparison Between Cultivation and Sequencing Based Approaches for Microbiota Analysis in Swabs and Biopsies of Chronic Wounds

Chronic wounds are a prominent health concern affecting 0.2% of individuals in the Western population. Microbial colonization and the consequent infection contribute significantly to the healing process. We have compared two methods, cultivation and 16S amplicon sequencing (16S-AS), for the characterization of bacterial populations in both swabs and biopsy tissues obtained from 45 chronic wounds. Using cultivation approach, we detected a total of 39 bacterial species, on average 2.89 per sample (SD = 1.93), compared to 5.9 (SD = 7.1) operational taxonomic units per sample obtained with 16S-AS. The concordance in detected bacteria between swab and biopsy specimens obtained from the same CWs was greater when using cultivation (58.4%) as compared to 16S-AS (25%). In the entire group of 45 biopsy samples concordance in detected bacterial genera between 16S-AS and cultivation-based approach was 36.4% and in swab samples 28.7%. Sequencing proved advantageous in comparison to the cultivation mainly in case of highly diverse microbial communities, where we could additionally detect numerous obligate and facultative anaerobic bacteria from genera Anaerococcus, Finegoldia, Porphyromonas, Morganella, and Providencia. Comparing swabs and biopsy tissues we concluded, that neither sampling method shows significant advantage over the other regardless of the method used (16S-AS or cultivation). In this study, chronic wound microbiota could be distributed into three groups based on the bacterial community diversity. The chronic wound surface area was positively correlated with bacterial diversity in swab specimens but not in biopsy tissues. Larger chronic wound surface area was also associated with the presence of Pseudomonas in both biopsy and swab specimens. The presence of Corynebacterium species at the initial visit was the microbial marker most predictive of the unfavorable clinical outcome after one-year follow-up visit.

The prebiotic effects of omega-3 fatty acid supplementation: A six-week randomised intervention trial

Prebiotics are compounds in food that benefit health via affecting the gut microbiome. Omega-3 fatty acids have been associated with differences in gut microbiome composition and are widely accepted to have health benefits, although recent large trials have been inconclusive. We carried out a 6-week dietary intervention comparing the effects of daily supplementation with 500 mg of omega-3 versus 20 g of a well-characterized prebiotic, inulin. Inulin supplementation resulted in large increases in Bifidobacterium and Lachnospiraceae. In contrast, omega-3 supplementation resulted in significant increases in Coprococcus spp. and Bacteroides spp, and significant decreases in the fatty-liver associated Collinsella spp. On the other hand, similar to the results with inulin supplementation which resulted in significant increases in butyrate, iso-valerate, and iso-butyrate (p < .004), omega-3 supplementation resulted in significant increases in iso-butyrate and isovalerate (p < .002) and nearly significant increases in butyrate (p < .053). Coprococcus, which was significantly increased post-supplementation with omega-3, was found to be positively associated with iso-butyric acid (Beta (SE) = 0.69 (0.02), P = 1.4 x 10-3) and negatively associated with triglyceride-rich lipoproteins such as VLDL (Beta (SE) = -0.381 (0.01), P = .001) and VLDL-TG (Beta (SE) = -0.372 (0.04), P = .001) after adjusting for confounders. Dietary omega-3 alters gut microbiome composition and some of its cardiovascular effects appear to be potentially mediated by its effect on gut microbial fermentation products indicating that it may be a prebiotic nutrient.

Advantages and Limitations of 16S rRNA Next-Generation Sequencing for Pathogen Identification in the Diagnostic Microbiology Laboratory: Perspectives from a Middle-Income Country

Bacterial culture and biochemical testing (CBtest) have been the cornerstone of pathogen identification in the diagnostic microbiology laboratory. With the advent of Sanger sequencing and later, next-generation sequencing, 16S rRNA next-generation sequencing (16SNGS) has been proposed to be a plausible platform for this purpose. Nevertheless, usage of the 16SNGS platform has both advantages and limitations. In addition, transition from the traditional methods of CBtest to 16SNGS requires procurement of costly equipment, timely and sustainable maintenance of these platforms, specific facility infrastructure and technical expertise. All these factors pose a challenge for middle-income countries, more so for countries in the lower middle-income range. In this review, we describe the basis for CBtest and 16SNGS, and discuss the limitations, challenges, advantages and future potential of using 16SNGS for bacterial pathogen identification in diagnostic microbiology laboratories of middle-income countries.

Lower gut microbiome diversity and higher abundance of proinflammatory genus Collinsella are associated with biopsy-proven nonalcoholic steatohepatitis

There is increasing evidence for the role of gut microbial composition in the pathogenesis of nonalcoholic fatty liver disease (NAFLD). Nonalcoholic steatohepatitis (NASH) is the most serious form of NAFLD where inflammation causes liver damage that can progress to cirrhosis. We have characterized the gut microbiome composition in UK patients with biopsy-proven NASH (n = 65) and compared it to that in healthy controls (n = 76). We report a 7% lower Shannon alpha diversity in NASH patients without cirrhosis (n = 40) compared to controls (p = 2.7x 10^-4) and a 14% drop in NASH patients with cirrhosis (n = 25, p = 5.0x 10^-4). Beta diversity (Unweighted UniFrac distance) was also significantly reduced in both NASH (p = 5.6x 10^-25) and NASH-cirrhosis (p = 8.1x 10^-7) groups. The genus most strongly associated with NASH in this study was Collinsella (0.29% abundance in controls, 3.45% in NASH without cirrhosis (False Discovery Rate (FDR) p = .008), and 4.38% in NASH with cirrhosis (FDR p = .02)). This genus, which has been linked previously to obesity and atherosclerosis, was also positively correlated with fasting levels of triglycerides (p = .01) and total cholesterol (p = 1.2x 10^-4) and negatively correlated with high-density lipoprotein cholesterol (p = 2.8x 10^-6) suggesting that some of the pathways present in this microbial genus may influence lipid metabolism in the host. In patients, we also found decreased abundance of some of the Ruminococcaceae which are known to produce high levels of short-chain fatty acids which can lower inflammation. This may thus contribute to pathology associated with NASH.

Issues and current standards of controls in microbiome research

Good scientific practice is important in all areas of science. In recent years this has gained more and more attention, especially considering the 'scientific reproducibility crisis'. While most researchers are aware of the issues with good scientific practice, not all of these issues are necessarily clear, and the details can be very complicated. For many years it has been accepted to perform and publish sequencing based microbiome studies without including proper controls. Although in recent years more scientists realize the necessity of implementing controls, this poses a problem due to the complexity of the field. Another concern is the inability to properly interpret the information gained from controls in microbiome studies. Here, we will discuss these issues and provide a comprehensive overview of problematic points regarding controls in microbiome research, and of the current standards in this area.

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.

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.