Microbial Community Profiling in Intensive Care Units Expose Limitations in Current Sanitary Standards

Trends in viable microbial bioburden on surfaces within a paediatric bone marrow transplant unit

BACKGROUND

Despite their role being historically overlooked, environmental surfaces have been shown to play a key role in the transmission of pathogens causative of healthcare-associated infection. To guide infection prevention and control (IPC) interventions and inform clinical risk assessments, more needs to be known about microbial surface bioburdens.

AIM

To identify the trends in culturable bacterial contamination across communal touch sites over time in a hospital setting.

METHODS

Swab samples were collected over nine weeks from 22 communal touch sites in a paediatric bone marrow transplant unit. Samples were cultured on Columbia blood agar and aerobic colony counts (ACC) per 100 cm2 were established for each site. Individual colony morphologies were grouped and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry or 16s rDNA sequencing.

FINDINGS

Highest mean counts were observed for sites associated with ward management activity and computer devices (3.29 and 2.97 ACC/100 cm2 respectively). A nurses' station keyboard had high mean ACC/100 cm2 counts (10.67) and diversity, while laundry controls had high mean ACC/100 cm2 counts (4.70) and low diversity. Micrococcus luteus was identified in all sampling groups. Clinical staff usage sites were contaminated with similar proportions of skin and environmental flora (52.19-46.59% respectively), but sites associated with parental activities were predominantly contaminated by environmental microflora (86.53%).

CONCLUSION

The trends observed suggest patterns in microbial loading based on site activities, surface types and user groups. Improved understanding of environmental surface contamination could help support results interpretation and IPC interventions, improving patient safety.

Bacterial Infections in Intensive Care Units: Epidemiological and Microbiological Aspects

Intensive care units constitute a critical setting for the management of infections. The patients' fragilities and spread of multidrug-resistant microorganisms lead to relevant difficulties in the patients' care. Recent epidemiological surveys documented the Gram-negative bacteria supremacy among intensive care unit (ICU) infection aetiologies, accounting for numerous multidrug-resistant isolates. Regarding this specific setting, clinical microbiology support holds a crucial role in the definition of diagnostic algorithms. Eventually, the complete patient evaluation requires integrating local epidemiological knowledge into the best practice and the standardization of antimicrobial stewardship programs. Clinical laboratories usually receive respiratory tract and blood samples from ICU patients, which express a significant predisposition to severe infections. Therefore, conventional or rapid diagnostic workflows should be modified depending on patients' urgency and preliminary colonization data. Additionally, it is essential to complete each microbiological report with rapid phenotypic minimum inhibitory concentration (MIC) values and information about resistance markers. Microbiologists also help in the eventual integration of ultimate genome analysis techniques into complicated diagnostic workflows. Herein, we want to emphasize the role of the microbiologist in the decisional process of critical patient management.

Disruptions of Gut Microbiota are Associated with Cognitive Deficit of Preclinical Alzheimer's Disease: A Cross-Sectional Study

BACKGROUND

Alzheimer's Disease (AD) is the most prevalent type of dementia. The early change of gut microbiota is a potential biomarker for preclinical AD patients.

OBJECTIVE

The study aimed to explore changes in gut microbiota characteristics in preclinical AD patients, including those with Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI), and detect the correlation between gut microbiota characteristics and cognitive performances.

METHODS

This study included 117 participants [33 MCI, 54 SCD, and 30 Healthy Controls (HC)]. We collected fresh fecal samples and blood samples from all participants and evaluated their cognitive performance. We analyzed the diversity and structure of gut microbiota in all participants through qPCR, screened characteristic microbial species through machine learning models, and explored the correlations between these species and cognitive performances and serum indicators.

RESULTS

Compared to the healthy controls, the structure of gut microbiota in MCI and SCD patients was significantly different. The three characteristic microorganisms, including Bacteroides ovatus, Bifidobacterium adolescentis, and Roseburia inulinivorans, were screened based on the best classification model (HC and MCI) having intergroup differences. Bifidobacterium adolescentis is associated with better performance in multiple cognitive scores and several serum indicators. Roseburia inulinivorans showed negative correlations with the scores of the Functional Activities Questionnaire (FAQ).

CONCLUSION

The gut microbiota in patients with preclinical AD has significantly changed in terms of composition and richness. Correlations have been discovered between changes in characteristic species and cognitive performances. Gut microbiota alterations have shown promise in affecting AD pathology and cognitive deficit.

Metagenomic insights into microbial contamination in critical healthcare environments and the efficacy of a novel "HLE" disinfectant

BACKGROUND

Bacterial contamination on inanimate clinical surfaces is directly linked to severe health problems, especially those caused by multidrug resistant (MDR) pathogens. Here, we evaluated the microbial burden in these environments and tested the efficacy of a novel HLE disinfectant solution.

METHODS

Microbial contamination of healthcare surfaces [Intensive Care Unit (ICU), Long Period Hospitalization Room (LPHR) and Otolaryngology Consultation (OC)] and the efficacy of HLE disinfectant solution were determined analyzing the viable counts on general and selective media, and also by molecular studies focused on metagenomic and specific qPCR.

RESULTS

Different contamination loads were detected with LPHR showing the highest contamination. Treatment with the HLE disinfectant solution curbed the spread of well-adapted pathogens on touched surfaces (ICU, LPHR and OC). Metagenomic analysis of microbial diversity of the Patient Table (most contaminated surface in LPHR) revealed the presence of mainly A. johnsonii and P. putida. Furthermore, functional annotation of toxin, virulence and antibiotic resistance sequences showed a high diversity of Acinetobacter spp. and Pseudomonas spp. In this context, specific qPCR analysis confirmed the efficacy of HLE disinfectant solution against the most prevalent and critical pathogens Pseudomonas sp. and Acinetobacter sp. achieving their complete eradication.

CONCLUSION

Given the persistence of detrimental resistant pathogens, the application of HLE disinfection solution could be a highly beneficial and effective option -used either alone or in combination-for infection prevention and control with the aim to eliminate microbial pathogens and their genes from contaminated contact-surfaces and thus limit the spread to humans and other ecological niches.

Human microbiome and microbiota identification for preventing and controlling healthcare-associated infections: A systematic review

Objective

This systematic review describes the role of the human microbiome and microbiota in healthcare-associated infections (HAIs). Studies on the microbiota of patients, healthcare environment (HE), medical equipment, or healthcare workers (HCW) and how it could be transmitted among the different subjects will be described in order to define alarming risk factors for HAIs spreading and to identify strategies for HAIs control or prevention.

Methods

This review was performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After retrieval in databases, identification, and screening of available records, 36 published studies were considered eligible and included in the review.

Results

A multifaceted approach is required and the analyses of the many factors related to human microbiota, which can influence HAIs onset, could be of paramount importance in their prevention and control. In this review, we will focus mainly on the localization, transmission, and prevention of ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) bacteria and Clostridium difficile which are the most common pathogens causing HAIs.

Conclusions

Healthcare workers' microbiota, patient's microbiota, environmental and medical equipment microbiota, ecosystem characteristics, ways of transmission, cleaning strategies, and the microbial resistome should be taken into account for future studies on more effective preventive and therapeutic strategies against HAIs.

Simultaneous monitoring of SARS-CoV-2 and bacterial profiles from the air of hospital environments with COVID-19-affected patients

The SARS-CoV-2 presence and the bacterial community profile in air samples collected at the Intensive Care Unit (ICU) of the Operational Unit of Infectious Diseases of Santa Caterina Novella Hospital in Galatina (Lecce, Italy) have been evaluated in this study. Air samplings were performed in different rooms of the ICU ward with and without COVID-19 patients. No sample was found positive to SARS-CoV-2, according to Allplex 2019-nCoV Assay. The airborne bacterial community profiles determined by the 16S rRNA gene metabarcoding approach up to the species level were characterized by richness and biodiversity indices, Spearman correlation coefficients, and Principal Coordinate Analysis. Pathogenic and non-pathogenic bacterial species, also detected in outdoor air samples, were found in all collected indoor samples. Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and others coagulase-negative staphylococci, detected at high relative abundances in all the patients' rooms, were the most abundant pathogenic species. The highest mean relative abundance of S. pettenkoferi and C. tuberculostearicum suggested that they were likely the main pathogens of COVID-19 patients at the ICU ward of this study. The identification of nosocomial pathogens representing potential patients' risks in ICU COVID-19 rooms and the still controversial airborne transmission of the SARS-CoV-2 are the main contributions of this study.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10453-022-09754-7.

Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples

The compositional analysis of 16S rRNA gene sequencing datasets is applied to characterize the bacterial structure of airborne samples collected in different locations of a hospital infection disease department hosting COVID-19 patients, as well as to investigate the relationships among bacterial taxa at the genus and species level. The exploration of the centered log-ratio transformed data by the principal component analysis via the singular value decomposition has shown that the collected samples segregated with an observable separation depending on the monitoring location. More specifically, two main sample clusters were identified with regards to bacterial genera (species), consisting of samples mostly collected in rooms with and without COVID-19 patients, respectively. Human pathogenic genera (species) associated with nosocomial infections were mostly found in samples from areas hosting patients, while non-pathogenic genera (species) mainly isolated from soil were detected in the other samples. Propionibacterium acnes, Staphylococcus pettenkoferi, Corynebacterium tuberculostearicum, and jeikeium were the main pathogenic species detected in COVID-19 patients' rooms. Samples from these locations were on average characterized by smaller richness/evenness and diversity than the other ones, both at the genus and species level. Finally, the ρ metrics revealed that pairwise positive associations occurred either between pathogenic or non-pathogenic taxa.

Gram-Negative Rods on Inanimate Surfaces of Selected Hospital Facilities and Their Nosocomial Significance

Inanimate surfaces are often referred to as nosocomial bacterial reservoirs and represent an important vector in the process of spreading pathogens to patients. Most gram-negative rods can survive on inanimate surfaces for several months. The aim of this study is to determine the prevalence and resistance of gram-negative bacteria isolated from the inanimate surfaces of two selected hospital departments. MALDI-TOF identified gram-negative rods isolated from inanimate surfaces. Antibiotic resistance was determined using a disk diffusion method, and the phenotype of resistance was determined using an inhibitory analyzer. From the inanimate surfaces, 98 strains of gram-negative nosocomial bacteria were identified by the MALDI-TOF MS. The most frequently isolated bacterium occurring in both departments was Pseudomonas aeruginosa (n = 33), followed by Acinetobacter baumannii (n = 20) and Enterobacter cloacae (n = 14). The most common phenotypic type of resistance in both departments was ampicillin resistance—AmpC (n = 38), then production of extended-spectrum β-lactamase (ESBL) (n = 33), followed by SHV-1 (n = 11), TEM-1 (n = 11), and fluoroquinolone resistance—Qnr (n = 22). The nosocomial important enzymes capable of hydrolyzing carbapenems, OXA-48 and metallo-β-lactamases, were confirmed in 12 and 2 cases, respectively. The results of our study prove that inanimate surfaces in hospitals are a reservoir of resistant gram-negative bacteria, which directly threaten hospitalized patients.

Monitoring microbial communities in intensive care units over one year in China

Healthcare-associated infections (HAIs) seriously threaten patient health in intensive care units (ICUs). Profiling the microbial composition and diversity in ICU is important to prevent HAI-related spreading. Given that microbial communities vary across different environments, the time-scale characteristics of pathogens in ICUs have not been explored in China. In our study, to study the bacterial communities of two different ICUs in China, we proceeded dynamic monitoring using 16S rRNA sequencing for a whole year among the bed sheets, bed rails, shared pulse oximeters, bedside lockers, nurses' hands, floor, and carts. Our results showed that the microbial composition significantly changed within months. Significant differences in alpha and beta diversities were also observed among the 12 sampling months in each ICU. Additionally, we found the persistence of several HAI-related bacteria, including Acinetobacter, Pseudomonas, Staphylococcus, Escherichia, and Enterococcus. Source tracking analysis showed that most bacteria in both ICUs came from buildings or human skin. With deep investigations of hospital microbial surveillance on a long-term time-scale, we hope that these results will provide constructive guidelines to prevent the spread of HAIs in ICUs.

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.

Nanopore Sequencing Provides Rapid and Reliable Insight Into Microbial Profiles of Intensive Care Units

Fast and accurate identification of pathogens is an essential task in healthcare settings. Second-generation sequencing platforms such as Illumina have greatly expanded the capacity with which different organisms can be detected in hospital samples, and third-generation nanopore-driven sequencing devices such as Oxford Nanopore's minION have recently emerged as ideal sequencing platforms for routine healthcare surveillance due to their long-read capacity and high portability. Despite its great potential, protocols and analysis pipelines for nanopore sequencing are still being extensively validated. In this work, we assess the ability of nanopore sequencing to provide reliable community profiles based on 16S rRNA sequencing in comparison to traditional Illumina platforms using samples collected from Intensive Care Units of a hospital in Brazil. While our results demonstrate that lower throughputs may be a shortcoming of the method in more complex samples, we show that the use of single-use Flongle flowcells in nanopore sequencing runs can provide insightful information on the community composition in healthcare settings.

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.

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.