A systematic literature review of the human skin microbiome as biomarker for dermatological drug development

Aims: To explore the potential of the skin microbiome as biomarker in six dermatological conditions: atopic dermatitis (AD), acne vulgaris (AV), psoriasis vulgaris (PV), hidradenitis suppurativa (HS), seborrhoeic dermatitis/pityriasis capitis (SD/PC) and ulcus cruris (UC). Methods: A systematic literature review was conducted according to the PRISMA guidelines. Two investigators independently reviewed the included studies and ranked the suitability microbiome implementation for early phase clinical studies in an adapted GRADE method. Results: In total, 841 papers were identified and after screening of titles and abstracts for eligibility we identified 42 manuscripts that could be included in the review. Eleven studies were included for AD, five for AV, 10 for PV, two for HS, four for SD and 10 for UC. For AD and AV, multiple studies report the relationship between the skin microbiome, disease severity and clinical response to treatment. This is currently lacking for the remaining conditions. Conclusion: For two indications - AD and AV - there is preliminary evidence to support implementation of the skin microbiome as biomarkers in early phase clinical trials. For PV, UC, SD and HS there is insufficient evidence from the literature. More microbiome-directed prospective studies studying the effect of current treatments on the microbiome with special attention for patient meta-data, sampling methods and analysis methods are needed to draw more substantial conclusions

Human Occupancy as a Source of Indoor Airborne Bacteria

Exposure to specific airborne bacteria indoors is linked to infectious and noninfectious adverse health outcomes. However, the sources and origins of bacteria suspended in indoor air are not well understood. This study presents evidence for elevated concentrations of indoor airborne bacteria due to human occupancy, and investigates the sources of these bacteria. Samples were collected in a university classroom while occupied and when vacant. The total particle mass concentration, bacterial genome concentration, and bacterial phylogenetic populations were characterized in indoor, outdoor, and ventilation duct supply air, as well as in the dust of ventilation system filters and in floor dust. Occupancy increased the total aerosol mass and bacterial genome concentration in indoor air PM10 and PM2.5 size fractions, with an increase of nearly two orders of magnitude in airborne bacterial genome concentration in PM10. On a per mass basis, floor dust was enriched in bacterial genomes compared to airborne particles. Quantitative comparisons between bacterial populations in indoor air and potential sources suggest that resuspended floor dust is an important contributor to bacterial aerosol populations during occupancy. Experiments that controlled for resuspension from the floor implies that direct human shedding may also significantly impact the concentration of indoor airborne particles. The high content of bacteria specific to the skin, nostrils, and hair of humans found in indoor air and in floor dust indicates that floors are an important reservoir of human-associated bacteria, and that the direct particle shedding of desquamated skin cells and their subsequent resuspension strongly influenced the airborne bacteria population structure in this human-occupied environment. Inhalation exposure to microbes shed by other current or previous human occupants may occur in communal indoor environments

A meta-analysis of changes in bacterial and archaeal communities with time.

Ecologists have long studied the temporal dynamics of plant and animal communities with much less attention paid to the temporal dynamics exhibited by microbial communities. As a result, we do not know if overarching temporal trends exist for microbial communities or if changes in microbial communities are generally predictable with time. Using microbial time series assessed via high-throughput sequencing, we conducted a meta-analysis of temporal dynamics in microbial communities, including 76 sites representing air, aquatic, soil, brewery wastewater treatment, human- and plant-associated microbial biomes. We found that temporal variability in both within- and between-community diversity was consistent among microbial communities from similar environments. Community structure changed systematically with time in less than half of the cases, and the highest rates of change were observed within ranges of 1 day to 1 month for all communities examined. Microbial communities exhibited species-time relationships (STRs), which describe the accumulation of new taxa to a community, similar to those observed previously for plant and animal communities, suggesting that STRs are remarkably consistent across a broad range of taxa. These results highlight that a continued integration of microbial ecology into the broader field of ecology will provide new insight into the temporal patterns of microbial and 'macro'-bial communities alike

Peptide tag forming a rapid covalent bond to a protein, through engineering a bacterial adhesin.

Protein interactions with peptides generally have low thermodynamic and mechanical stability. Streptococcus pyogenes fibronectin-binding protein FbaB contains a domain with a spontaneous isopeptide bond between Lys and Asp. By splitting this domain and rational engineering of the fragments, we obtained a peptide (SpyTag) which formed an amide bond to its protein partner (SpyCatcher) in minutes. Reaction occurred in high yield simply upon mixing and amidst diverse conditions of pH, temperature, and buffer. SpyTag could be fused at either terminus or internally and reacted specifically at the mammalian cell surface. Peptide binding was not reversed by boiling or competing peptide. Single-molecule dynamic force spectroscopy showed that SpyTag did not separate from SpyCatcher until the force exceeded 1 nN, where covalent bonds snap. The robust reaction conditions and irreversible linkage of SpyTag shed light on spontaneous isopeptide bond formation and should provide a targetable lock in cells and a stable module for new protein architectures

DEVELOPING COMPUTATIONAL METHODS TOPREDICT THE FATE OF INHALED PARTICLES IN THELUNG

The respiratory system can be targeted by many different types of diseases, for example asthmaand cancer. The drug delivery method by inhaling substances for treating diseases only started in the 1950s with the treating of asthma, considered also for many other diseases. Mathematical dosimetry models are used in drug development to predict the deposition of particles in the lungs. This prediction is not easily achieved experimentally, and therefore these mathematically models are of high importance. Monkeys are often used in the late stages of drug development due to their resemblance in humans. A good model for predicting the deposition pattern in monkeys is therefore useful in the development of drugs. However, there is at the moment no developed deposition mode lfor monkeys. In this thesis both a static model and the first dynamic deposition model was developed sing the data on the breathing pattern from respiratory inductance plethysmography (RIP) bands. This dynamic model provides regional and time resolved information on the particle deposition in the lungs of monkeys and can be used to get a deeper understanding of the fate of inhaled particles. This model can also determine inter-animals differences which have not been achieved before. An extensive implementation of these time resolved deposition models could be used to increase understanding about deposition in a variety of species and help the field to move forward

The role of the microbiome in psoriasis: moving from disease description to treatment selection?

With several million microbes per cm2 of skin, the task of mapping the physiological cutaneous microbiome is enormous. Indeed, the reliance on bacterial culture to identify cutaneous bacterial communities has led to a systematic under-appreciation of cutaneous microbial diversity, potentially limiting our understanding of common inflammatory skin diseases including psoriasis. However, based heavily on developments in molecular biology and bioinformatics, including next generation sequencing, the last decade has witnessed a marked increase in our understanding of the extent and composition of the cutaneous microbiome. It is already clear that skin-specific (skin site and skin microenvironment), individual-specific (hygiene, sex, age, and hormonal status), disease-specific (atopic eczema, acne) and genetic factors can all influence the cutaneous microbiome, albeit to varying and, as yet ill-defined, extents. This review briefly describes the process of 16S ribosomal RNA sequencing, before charting our current understanding of the cutaneous microbiome in health and the alterations (dysbiosis) associated with chronic inflammatory diseases with particular reference to psoriasis. The possibility and clinical relevance of intra-individual cross-talk between the various microbiomes is discussed and potential mechanisms underpinning the interactions between resident skin flora and the immune system are highlighted. We outline how the power of microbiome studies can be harnessed to provide new insights into disease pathogenesis and treatment selection. Ultimately, in the age of personalized medicine, the integration of cutaneous microbiome signatures and comprehensive disease and drug response endotypes will herald a novel approach in the clinical management of chronic, multi-system inflammatory diseases. This article is protected by copyright. All rights reserved.</p

A meta-analysis of changes in bacterial and archaeal communities with time

Ecologists have long studied the temporal dynamics of plant and animal communities with much less attention paid to the temporal dynamics exhibited by microbial communities. As a result, we do not know if overarching temporal trends exist for microbial communities or if changes in microbial communities are generally predictable with time. Using microbial time series assessed via high-throughput sequencing, we conducted a meta-analysis of temporal dynamics in microbial communities, including 76 sites representing air, aquatic, soil, brewery wastewater treatment, human- and plant-associated microbial biomes. We found that temporal variability in both within- and between-community diversity was consistent among microbial communities from similar environments. Community structure changed systematically with time in less than half of the cases, and the highest rates of change were observed within ranges of 1 day to 1 month for all communities examined. Microbial communities exhibited species–time relationships (STRs), which describe the accumulation of new taxa to a community, similar to those observed previously for plant and animal communities, suggesting that STRs are remarkably consistent across a broad range of taxa. These results highlight that a continued integration of microbial ecology into the broader field of ecology will provide new insight into the temporal patterns of microbial and ‘macro'-bial communities alike