Detection of Intestinal Dysbiosis in Post-COVID-19 Patients One to Eight Months after Acute Disease Resolution.

The intestinal microbiota plays an important role in the immune response against viral infections, modulating both innate and adaptive immune responses. The cytokine storm is associated with COVID-19 severity, and the patient's immune status is influenced by the intestinal microbiota in a gut-lung bidirectional interaction. In this study, we evaluate the intestinal microbiota of Brazilian patients in different post-COVID-19 periods, and correlate this with clinical data and the antibiotic therapy used during the acute phase. DNA extracted from stool samples was sequenced and total anti-SARS-CoV-2 antibodies and C-reactive protein were quantified. Compared with controls, there were significant differences in the microbiota diversity in post-COVID-19 patients, suggesting an intestinal dysbiosis even several months after acute disease resolution. Additionally, we detected some genera possibly associated with the post-COVID-19 dysbiosis, including Desulfovibrio, Haemophillus, Dialister, and Prevotella, in addition to decreased beneficial microbes, associated with antibiotic-induced dysbiosis, such as Bifidobacterium and Akkermansia. Therefore, our hypothesis is that dysbiosis and the indiscriminate use of antibiotics during the pandemic may be associated with post-COVID-19 clinical manifestations. In our study, 39% (n = 58) of patients reported symptoms, including fatigue, dyspnea, myalgia, alopecia, anxiety, memory loss, and depression. These data suggest that microbiota modulation may represent a target for recovery from acute COVID-19 and a therapeutic approach for post-COVID-19 sequelae.

Healthcare-Associated Infections-Related Bacteriome and Antimicrobial Resistance Profiling: Assessing Contamination Hotspots in a Developing Country Public Hospital.

Hospital-built environment colonization by healthcare-associated infections-related bacteria (HAIrB) and the interaction with their occupants have been studied to support more effective tools for HAI control. To investigate HAIrB dynamics and antimicrobial resistance (AMR) profile we carried out a 6-month surveillance program in a developing country public hospital, targeting patients, hospital environment, and healthcare workers, using culture-dependent and culture-independent 16S rRNA gene sequencing methods. The bacterial abundance in both approaches shows that the HAIrB group has important representativeness, with the taxa Enterobacteriaceae, Pseudomonas, Staphylococcus, E. coli, and A. baumannii widely dispersed and abundant over the time at the five different hospital units included in the survey. We observed a high abundance of HAIrB in the patient rectum, hands, and nasal sites. In the healthcare workers, the HAIrB distribution was similar for the hands, protective clothing, and mobile phones. In the hospital environment, the healthcare workers resting areas, bathrooms, and bed equipment presented a wide distribution of HAIrB and AMR, being classified as contamination hotspots. AMR is highest in patients, followed by the environment and healthcare workers. The most frequently detected beta-lactamases genes were, bla SHV-like, bla OXA- 23 -like, bla OXA- 51 -like, bla KPC-like, bla CTX-M- 1, bla CTX-M- 8, and bla CTX-M- 9 groups. Our results demonstrate that there is a wide spread of antimicrobial resistance due to HAIrB in the hospital environment, circulating among patients and healthcare workers. The contamination hotspots identified proved to be constant over time. In the fight for patient safety, these findings can reorient practices and help to set up new guidelines for HAI control.

Equivolumetric Protocol Generates Library Sizes Proportional to Total Microbial Load in 16S Amplicon Sequencing.

High-throughput sequencing of 16S rRNA amplicon has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample bacterial composition directly from samples. However, most studies are limited to information regarding relative bacterial abundances (sample proportions), ignoring scenarios in which sample microbe biomass can vary widely. Here, we use an equivolumetric protocol for 16S rRNA amplicon library preparation capable of generating Illumina sequencing data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances within each sample. Under specified conditions, we show that the estimation of colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues. Our results indicate that predictive errors vary consistently below one order of magnitude for total microbial load and abundance of observed bacteria. We also demonstrate our approach has the potential to generalize to previously unseen bacteria, but predictive performance is hampered by specific taxa of uncommon profile. Finally, it remains clear that high-throughput sequencing data are not inherently restricted to sample proportions only, and such technologies bear the potential to meet the working scales of traditional microbiology.

Swab pooling: A new method for large-scale RT-qPCR screening of SARS-CoV-2 avoiding sample dilution.

To minimize sample dilution effect on SARS-CoV-2 pool testing, we assessed analytical and diagnostic performance of a new methodology, namely swab pooling. In this method, swabs are pooled at the time of collection, as opposed to pooling of equal volumes from individually collected samples. Paired analysis of pooled and individual samples from 613 patients revealed 94 positive individuals. Having individual testing as reference, no false-positives or false-negatives were observed for swab pooling. In additional 18,922 patients screened with swab pooling (1,344 pools), mean Cq differences between individual and pool samples ranged from 0.1 (Cr.I. -0.98 to 1.17) to 2.09 (Cr.I. 1.24 to 2.94). Overall, 19,535 asymptomatic patients were screened using 4,400 RT-qPCR assays. This corresponds to an increase of 4.4 times in laboratory capacity and a reduction of 77% in required tests. Therefore, swab pooling represents a major alternative for reliable and large-scale screening of SARS-CoV-2 in low prevalence populations.

One year cross-sectional study in adult and neonatal intensive care units reveals the bacterial and antimicrobial resistance genes profiles in patients and hospital surfaces.

Several studies have shown the ubiquitous presence of bacteria in hospital surfaces, staff, and patients. Frequently, these bacteria are related to HAI (healthcare-associated infections) and carry antimicrobial resistance (AMR). These HAI-related bacteria contribute to a major public health issue by increasing patient morbidity and mortality during or after hospital stay. Bacterial high-throughput amplicon gene sequencing along with identification of AMR genes, as well as whole genome sequencing (WGS), are biotechnological tools that allow multiple-sample screening for a diversity of bacteria. In this paper, we used these methods to perform a one-year cross sectional profiling of bacteria and AMR genes in adult and neonatal intensive care units (ICU and NICU) in a Brazilian public, tertiary hospital. Our results showed high abundances of HAI-related bacteria such as S. epidermidis, S. aureus, K. pneumoniae, A. baumannii complex, E. coli, E. faecalis, and P. aeruginosa in patients and hospital surfaces. Most abundant AMR genes detected throughout ICU and NICU were mecA, blaCTX-M-1 group, blaSHV-like, and blaKPC-like. We found that NICU environment and patients were more widely contaminated with pathogenic bacteria than ICU. Patient samples, despite the higher bacterial load, have lower bacterial diversity than environmental samples in both units. Finally, we also identified contamination hotspots in the hospital environment showing constant frequencies of bacterial and AMR contamination throughout the year. Whole genome sequencing (WGS), 16S rRNA oligotypes, and AMR identification allowed a high-resolution characterization of the hospital microbiome profile.