Journal: NPJ biofilms and microbiomes
Bath toys pose an interesting link between flexible plastic materials, potable water, external microbial and nutrient contamination, and potentially vulnerable end-users. Here, we characterized biofilm communities inside 19 bath toys used under real conditions. In addition, some determinants for biofilm formation were assessed, using six identical bath toys under controlled conditions with either clean water prior to bathing or dirty water after bathing. All examined bath toys revealed notable biofilms on their inner surface, with average total bacterial numbers of 5.5 × 106 cells/cm2(clean water controls), 9.5 × 106 cells/cm2(real bath toys), and 7.3 × 107 cells/cm2(dirty water controls). Bacterial community compositions were diverse, showing many rare taxa in real bath toys and rather distinct communities in control bath toys, with a noticeable difference between clean and dirty water control biofilms. Fungi were identified in 58% of all real bath toys and in all dirty water control toys. Based on the comparison of clean water and dirty water control bath toys, we argue that bath toy biofilms are influenced by (1) the organic carbon leaching from the flexible plastic material, (2) the chemical and biological tap water quality, (3) additional nutrients from care products and human body fluids in the bath water, as well as, (4) additional bacteria from dirt and/or the end-users' microbiome. The present study gives a detailed characterization of bath toy biofilms and a better understanding of determinants for biofilm formation and development in systems comprising plastic materials in contact with potable water.
It is well appreciated that microbial metabolism of drugs can influence treatment efficacy. Microbial β-glucuronidases in the gut can reactivate the excreted, inactive metabolite of irinotecan, a first-line chemotherapeutic for metastatic colorectal cancer. Reactivation causes adverse drug responses, including severe diarrhea. However, a direct connection between irinotecan metabolism and the composition of an individual’s gut microbiota has not previously been made. Here, we report quantitative evidence of inter-individual variability in microbiome metabolism of the inactive metabolite of irinotecan to its active form. We identify a high turnover microbiota metabotype with potentially elevated risk for irinotecan-dependent adverse drug responses. We link the high turnover metabotype to unreported microbial β-glucuronidases; inhibiting these enzymes may decrease irinotecan-dependent adverse drug responses in targeted subsets of patients. In total, this study reveals metagenomic mining of the microbiome, combined with metabolomics, as a non-invasive approach to develop biomarkers for colorectal cancer treatment outcomes.
Biofouling is a major problem caused by bacteria colonizing abiotic surfaces, such as medical devices. Biofilms are formed as the bacterial metabolism adapts to an attached growth state. We studied whether bacterial metabolism, hence biofilm formation, can be modulated in electrochemically active surfaces using the conducting conjugated polymer poly(3,4-ethylenedioxythiophene) (PEDOT). We fabricated composites of PEDOT doped with either heparin, dodecyl benzene sulfonate or chloride, and identified the fabrication parameters so that the electrochemical redox state is the main distinct factor influencing biofilm growth. PEDOT surfaces fitted into a custom-designed culturing device allowed for redox switching in Salmonella cultures, leading to oxidized or reduced electrodes. Similarly large biofilm growth was found on the oxidized anodes and on conventional polyester. In contrast, biofilm was significantly decreased (52-58%) on the reduced cathodes. Quantification of electrochromism in unswitched conducting polymer surfaces revealed a bacteria-driven electrochemical reduction of PEDOT. As a result, unswitched PEDOT acquired an analogous electrochemical state to the externally reduced cathode, explaining the similarly decreased biofilm growth on reduced cathodes and unswitched surfaces. Collectively, our findings reveal two opposing effects affecting biofilm formation. While the oxidized PEDOT anode constitutes a renewable electron sink that promotes biofilm growth, reduction of PEDOT by a power source or by bacteria largely suppresses biofilm formation. Modulating bacterial metabolism using the redox state of electroactive surfaces constitutes an unexplored method with applications spanning from antifouling coatings and microbial fuel cells to the study of the role of bacterial respiration during infection.
The ability of uropathogenic Escherichia coli (UPEC) to adopt a biofilm lifestyle in the urinary tract is suggested as one cause of recurrent urinary tract infections (UTIs). A clinical role of UPEC biofilm is further supported by the presence of bacterial aggregates in urine of UTI patients. Yet, no diagnostics exist to differentiate between the planktonic and biofilm lifestyle of bacteria. Here, we developed a rapid diagnostic assay for biofilm-related UTI, based on the detection of cellulose in urine. Cellulose, a component of biofilm extracellular matrix, is detected by a luminescent-conjugated oligothiophene, which emits a conformation-dependent fluorescence spectrum when bound to a target molecule. We first defined the cellulose-specific spectral signature in the extracellular matrix of UPEC biofilm colonies, and used these settings to detect cellulose in urine. To translate this optotracing assay for clinical use, we composed a workflow that enabled rapid isolation of urine sediment and screening for the presence of UPEC-derived cellulose in <45 min. Using multivariate analysis, we analyzed spectral information obtained between 464 and 508 nm by optotracing of urine from 182 UTI patients and 8 healthy volunteers. Cellulose was detected in 14.8% of UTI urine samples. Using cellulose as a biomarker for biofilm-related UTI, our data provide direct evidence that UPEC forms biofilm in the urinary tract. Clinical implementation of this rapid, non-invasive and user-friendly optotracing diagnostic assay will potentially aid clinicians in the design of effective antibiotic treatment.
The biofilm chemical and physical properties in engineered systems play an important role in governing pathogen transmission, fouling facilities, and corroding metal surfaces. Here, we investigated how simulated drinking water biofilm chemical composition, structure, and stiffness responded to the common scale control practice of adjusting divalent ions and adding polyphosphate. Magnetomotive optical coherence elastography (MM-OCE), a tool developed for diagnosing diseased tissues, was used to determine biofilm stiffness in this study. MM-OCE, together with atomic force microscopy (AFM), revealed that the biofilms developed from a drinking water source with high divalent ions were stiffer compared to biofilms developed either from the drinking water source with low divalent ions or the water containing a scale inhibitor (a polyphosphate). The higher stiffness of biofilms developed from the water containing high divalent ions was attributed to the high content of calcium carbonate, suggested by biofilm composition examination. In addition, by examining the biofilm structure using optical coherence tomography (OCT), the highest biofilm thickness was found for biofilms developed from the water containing the polyphosphate. Compared to the stiff biofilms developed from the water containing high divalent ions, the soft and thick biofilms developed from the water containing polyphosphate will be expected to have higher detachment under drinking water flow. This study suggested that water chemistry could be used to predict the biofilm properties and subsequently design the microbial safety control strategies.
Imbalances of the microbiome, also referred to as microbial dysbiosis, could lead to a series of different diseases. One factor that has been shown to lead to dysbiosis of the microbiome is exposure to psychological stressors. Throughout evolution microorganisms of the human microbiome have developed systems for sensing host-associated signals such as hormones associated with those stressors, enabling them to recognize essential changes in their environment, thus changing their expression gene profile to fit the needs of the new environment. The most widely accepted theory explaining the ability of hormones to affect the outcome of an infection involves the suppression of the immune system. Commensal microbiota is involved in stressor-induced immunomodulation, but other biological effects are not yet known. Here we present the impact that cortisol had on the community-wide transcriptome of the oral community. We used a metatranscriptomic approach to obtain first insights into the metabolic changes induced by this stress hormone as well as which members of the oral microbiome respond to the presence of cortisol in the environment. Our findings show that the stress hormone cortisol directly induces shifts in the gene expression profiles of the oral microbiome that reproduce results found in the profiles of expression of periodontal disease and its progression.
Mucus layers often provide a unique and multi-functional hydrogel interface between the epithelial cells of organisms and their external environment. Mucus has exceptional properties including elasticity, changeable rheology and an ability to self-repair by re-annealing, and is therefore an ideal medium for trapping and immobilising pathogens and serving as a barrier to microbial infection. The ability to produce a functional surface mucosa was an important evolutionary step, which evolved first in the Cnidaria, which includes corals, and the Ctenophora. This allowed the exclusion of non-commensal microbes and the subsequent development of the mucus-lined digestive cavity seen in higher metazoans. The fundamental architecture of the constituent glycoprotein mucins is also evolutionarily conserved. Although an understanding of the biochemical interactions between bacteria and the mucus layer are important to the goal of developing new antimicrobial strategies, they remain relatively poorly understood. This review summarises the physicochemical properties and evolutionary importance of mucus, which make it so successful in the prevention of bacterial infection. In addition, the strategies developed by bacteria to counteract the mucus layer are also explored.
Methods for the study of member species in complex microbial communities remain a high priority, particularly for rare and/or novel member species that might play an important ecological role. Specifically, methods that link genomic information of member species with its spatial structure are lacking. This study adopts an integrative workflow that permits the characterisation of previously unclassified bacterial taxa from microbiomes through: (1) imaging of the spatial structure; (2) taxonomic classification and (3) genome recovery. Our study attempts to bridge the gaps between metagenomics/metatranscriptomics and high-resolution biomass imaging methods by developing new fluorescence in situ hybridisation (FISH) probes-termed as R-Probes-from shotgun reads that harbour hypervariable regions of the 16S rRNA gene. The sample-centric design of R-Probes means that probes can directly hybridise to OTUs as detected in shotgun sequencing surveys. The primer-free probe design captures larger microbial diversity as compared to canonical probes. R-Probes were designed from deep-sequenced RNA-Seq datasets for both FISH imaging and FISH-Fluorescence activated cell sorting (FISH-FACS). FISH-FACS was used for target enrichment of previously unclassified bacterial taxa prior to downstream multiple displacement amplification (MDA), genomic sequencing and genome recovery. After validation of the workflow on an axenic isolate of Thauera species, the techniques were applied to investigate two previously uncharacterised taxa from a tropical full-scale activated sludge community. In some instances, probe design on the hypervariable region allowed differentiation to the species level. Collectively, the workflow can be readily applied to microbiomes for which shotgun nucleic acid survey data is available.
The gut microbiota has been linked to various neurological disorders via the gut-brain axis. Diet influences the composition of the gut microbiota. The ketogenic diet (KD) is a high-fat, adequate-protein, low-carbohydrate diet established for treatment of therapy-resistant epilepsy in children. Its efficacy in reducing seizures has been confirmed, but the mechanisms remain elusive. The diet has also shown positive effects in a wide range of other diseases, including Alzheimer’s, depression, autism, cancer, and type 2 diabetes. We collected fecal samples from 12 children with therapy-resistant epilepsy before starting KD and after 3 months on the diet. Parents did not start KD and served as diet controls. Applying shotgun metagenomic DNA sequencing, both taxonomic and functional profiles were established. Here we report that alpha diversity is not changed significantly during the diet, but differences in both taxonomic and functional composition are detected. Relative abundance of bifidobacteria as well as E. rectale and Dialister is significantly diminished during the intervention. An increase in relative abundance of E. coli is observed on KD. Functional analysis revealed changes in 29 SEED subsystems including the reduction of seven pathways involved in carbohydrate metabolism. Decomposition of these shifts indicates that bifidobacteria and Escherichia are important contributors to the observed functional shifts. As relative abundance of health-promoting, fiber-consuming bacteria becomes less abundant during KD, we raise concern about the effects of the diet on the gut microbiota and overall health. Further studies need to investigate whether these changes are necessary for the therapeutic effect of KD.
Over 90% of cystic fibrosis (CF) patients die due to chronic lung infections leading to respiratory failure. The decline in CF lung function is greatly accelerated by intermittent and progressively severe acute pulmonary exacerbations (PEs). Despite their clinical impact, surprisingly few microbiological signals associated with PEs have been identified. Here we introduce an unsupervised, systems-oriented approach to identify key members of the microbiota. We used two CF sputum microbiome data sets that were longitudinally collected through periods spanning baseline health and PEs. Key taxa were defined based on three strategies: overall relative abundance, prevalence, and co-occurrence network interconnectedness. We measured the association between changes in the abundance of the key taxa and changes in patient clinical status over time via change-point detection, and found that taxa with the highest level of network interconnectedness tracked changes in patient health significantly better than taxa with the highest abundance or prevalence. We also cross-sectionally stratified all samples into the clinical states and identified key taxa associated with each state. We found that network interconnectedness most strongly delineated the taxa among clinical states, and that anaerobic bacteria were over-represented during PEs. Many of these anaerobes are oropharyngeal bacteria that have been previously isolated from the respiratory tract, and/or have been studied for their role in CF. The observed shift in community structure, and the association of anaerobic taxa and PEs lends further support to the growing consensus that anoxic conditions and the subsequent growth of anaerobic microbes are important predictors of PEs.