Comparing Vaginal and Endometrial Microbiota Using Culturomics: Proof of Concept.

It is generally accepted that microorganisms can colonize a non-pathological endometrium. However, in a clinical setting, endometrial samples are always collected by passing through the vaginal-cervical route. As such, the vaginal and cervical microbiomes can easily cross-contaminate endometrial samples, resulting in a biased representation of the endometrial microbiome. This makes it difficult to demonstrate that the endometrial microbiome is not merely a reflection of contamination originating from sampling. Therefore, we investigated to what extent the endometrial microbiome corresponds to that of the vagina, applying culturomics on paired vaginal and endometrial samples. Culturomics could give novel insights into the microbiome of the female genital tract, as it overcomes sequencing-related bias. Ten subfertile women undergoing diagnostic hysteroscopy and endometrial biopsy were included. An additional vaginal swab was taken from each participant right before hysteroscopy. Both endometrial biopsies and vaginal swabs were analyzed using our previously described WASPLab-assisted culturomics protocol. In total, 101 bacterial and two fungal species were identified among these 10 patients. Fifty-six species were found in endometrial biopsies and 90 were found in vaginal swabs. On average, 28 % of species were found in both the endometrial biopsy and vaginal swab of a given patient. Of the 56 species found in the endometrial biopsies, 13 were not found in the vaginal swabs. Of the 90 species found in vaginal swabs, 47 were not found in the endometrium. Our culturomics-based approach sheds a different light on the current understanding of the endometrial microbiome. The data suggest the potential existence of a unique endometrial microbiome that is not merely a presentation of cross-contamination derived from sampling. However, we cannot exclude cross-contamination completely. In addition, we observe that the microbiome of the vagina is richer in species than that of the endometrium, which contradicts the current sequence-based literature.

Culturomics to Investigate the Endometrial Microbiome: Proof-of-Concept.

The microbiome of the reproductive tract has been associated with (sub)fertility and it has been suggested that dysbiosis reduces success rates and pregnancy outcomes. The endometrial microbiome is of particular interest given the potential impact on the embryo implantation. To date, all endometrial microbiome studies have applied a metagenomics approach. A sequencing-based technique, however, has its limitations, more specifically in adequately exploring low-biomass settings, such as intra-uterine/endometrial samples. In this proof-of-concept study, we demonstrate the applicability of culturomics, a high-throughput culturing approach, to investigate the endometrial microbiome. Ten subfertile women undergoing diagnostic hysteroscopy and endometrial biopsy, as part of their routine work-up at Brussels IVF, were included after their informed consent. Biopsies were used to culture microbiota for up to 30 days in multiple aerobic and anaerobic conditions. Subsequent WASPLab®-assisted culturomics enabled a standardized methodology. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) or 16S rRNA sequencing was applied to identify all of bacterial and fungal isolates. Eighty-three bacterial and two fungal species were identified. The detected species were in concordance with previously published metagenomics-based endometrial microbiota analyses as 77 (91%) of them belonged to previously described genera. Nevertheless, highlighting the added value of culturomics to identify most isolates at the species level, 53 (62.4%) of the identified species were described in the endometrial microbiota for the first time. This study shows the applicability and added value of WASPLab®-assisted culturomics to investigate the low biomass endometrial microbiome at a species level.

A comparison of E. coli susceptibility for amoxicillin/clavulanic acid according to EUCAST and CLSI guidelines.

In our tertiary care center, the reported susceptibility of E. coli blood isolates to amoxicillin/clavulanic acid exceeded 90% in 2005 and showed a progressive decrease to 50% by 2017. In this study, we investigate whether there is a real increase in resistant E. coli strains or if this apparent decline in reported susceptibility might be attributed to the substitution of CLSI by EUCAST guidelines in 2014. We randomly selected 237 E. coli blood isolates (stored at - 80 °C) from 1985 to 2018 and reassessed their MIC values, applying both the CLSI (fixed ratio of clavulanic acid) and EUCAST guidelines (fixed concentration of clavulanic acid). In parallel, the susceptibility of these isolates was retested by disk diffusion, according to the EUCAST guidelines. Whole genome sequencing was successfully performed on 233 of the 237 isolates. In only 130 of the 237 isolates (55.0%), testing according to the EUCAST and CLSI criteria delivered identical MIC values for amoxicillin/clavulanic acid. In 64 of the 237 isolates (27.0%), the MIC values diverged one dilution; in 38 (16.0%), two dilutions; and in five (2.1%), three dilutions. From these 107 discrepant results, testing according to EUCAST methodology revealed more resistant profiles in 93 E. coli strains (94.1%). Also, phenotypical susceptibility testing according to EUCAST guidelines tends to correlate better with the presence of beta-lactamase genes compared to CLSI testing procedure. This study highlights the low agreement between EUCAST and CLSI methodologies when performing MIC testing of amoxicillin/clavulanic acid. More strains are categorized as resistant when EUCAST guidelines are applied. The low agreement between EUCAST and CLSI was confirmed by WGS, since most of EUCAST resistant/CLSI sensitive isolates harbored beta-lactamase genes.

Culturomics in Unraveling the Upper Female Reproductive Tract Microbiota.

In recent years, the study of the human microbiome has surged, shedding light on potential connections between microbiome composition and various diseases. One specific area of intense interest within this research is the female reproductive tract, as it holds the potential to influence the process of embryo implantation. Advanced sequencing technologies have delivered unprecedented insights into the microbial communities, also known as microbiota, residing in the female reproductive tract. However, their efficacy encounters significant challenges when analyzing low-biomass microbiota, such as those present in the endometrium. These molecular techniques are susceptible to contamination from laboratory reagents and extraction kits, leading to sequencing bias that can significantly alter the perceived taxonomy of a sample. Consequently, investigating the microbiota of the upper female reproductive tract necessitates the exploration of alternative methods. In this context, the current review delves into the application of culturomics in unraveling the upper female reproductive tract microbiota. While culturomics holds value in research, its transition to routine clinical practice appears remote, at least in the foreseeable future.

Healthcare-Associated COVID-19 across Five Pandemic Waves: Prediction Models and Genomic Analyses.

BACKGROUND: Healthcare-associated SARS-CoV-2 infections need to be explored further. Our study is an analysis of hospital-acquired infections (HAIs) and ambulatory healthcare workers (aHCWs) with SARS-CoV-2 across the pandemic in a Belgian university hospital. METHODS: We compared HAIs with community-associated infections (CAIs) to identify the factors associated with having an HAI. We then performed a genomic cluster analysis of HAIs and aHCWs. We used this alongside the European Centre for Disease Control (ECDC) case source classifications of an HAI. RESULTS: Between March 2020 and March 2022, 269 patients had an HAI. A lower BMI, a worse frailty index, lower C-reactive protein (CRP), and a higher thrombocyte count as well as death and length of stay were significantly associated with having an HAI. Using those variables to predict HAIs versus CAIs, we obtained a positive predictive value (PPV) of 83.6% and a negative predictive value (NPV) of 82.2%; the area under the ROC was 0.89. Genomic cluster analyses and representations on epicurves and minimal spanning trees delivered further insights into HAI dynamics across different pandemic waves. The genomic data were also compared with the clinical ECDC definitions for HAIs; we found that 90.0% of the 'definite', 87.8% of the 'probable', and 70.3% of the 'indeterminate' HAIs belonged to one of the twenty-two COVID-19 genomic clusters we identified. CONCLUSIONS: We propose a novel prediction model for HAIs. In addition, we show that the management of nosocomial outbreaks will benefit from genome sequencing analyses.