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Alzheimer's disease (AD) is a progressive neurodegenerative condition characterised by memory loss, changes in personality and behaviour and affecting 32% of individuals aged 80 and older. Recent research has uncovered a characteristic "oral microbiome stamp" in AD patients, prompting inquiries into oral microbiota diversity and the consequences thereof. What We Know: Research has delved into the connection between gut microbiome dysbiosis and neurological disorders and this reciprocal relationship is believed to extend to the oral microbiota and various systemic diseases like AD (Maitre et al., 2021). Specifically, a potential link between changes in the oral microbiome, periodontal disease and the onset of cognitive decline and AD has been proposed (Issilbayeva et al., 2024). Epidemiological correlations between AD and periodontitis are of interest, as several researchers have proposed that the link between the two may stem from heightened systemic inflammation associated with the proliferation of periodontal pathogens. These pathogens may potentially contribute to AD development by playing a role in vascular disease progression (Maitre et al., 2021). Additional research has also demonstrated the potential of the oral microbiome to invoke neuroinflammation (Issilbayeva et al., 2024). Industry Impact and Potential: The oral microbiome of AD shows higher microbial diversity, with  increased levels of Firmicutes and decreased levels of Bacteroidetes, Proteobacteria and Actinobacteria compared to control samples (Issilbayeva et al., 2024). An additional study looking at salivary samples representative of the oral microbiome in AD patients found that these contained increased levels of Moraxella, Leptotrichia and Sphaerochaeta, as well as decreased Rothia (Liu et al., 2019). Another study demonstrated a specific imbalance in the oral microbiome of AD patients, characterised by the presence of certain periodontal bacteria, such as A. actinomycetemcomitans, P. gingivalis, T. denticola and F. nucleatum which researchers propose constitute a characteristic “stamp” of AD (Maitre et al., 2021). However, delving into the full spectrum of the oral microbiome's composition in individuals with AD necessitates further exploration (Issilbayeva et al., 2024). The current findings underscore the significance of maintaining a healthy oral microbiome. Therefore, it is crucial to use oral hygiene products and adopt practices that safeguard and enhance oral microbial balance, fostering advancements in such product developments. Our Solution: Sequential specialises in analysing the oral microbiome, along with skin, scalp, and vulvar microbiomes, and leads the industry in developing microbiome-friendly products. Our team of experts is poised to help your company formulate innovative substances that promote a healthy oral microbiome and enhance microbiota diversity among consumers. References: Issilbayeva, A., Kaiyrlykyzy, A., Vinogradova, E., Jarmukhanov, Z., Kozhakhmetov, S., Kassenova, A., Nurgaziyev, M., Mukhanbetzhanov, N., Alzhanova, D., Zholdasbekova, G., Askarova, S. & Kushugulova, A.R. (2024) Oral Microbiome Stamp in Alzheimer’s Disease. Pathogens (Basel, Switzerland). 13 (3), 195. doi:10.3390/pathogens13030195. Liu, X.-X., Jiao, B., Liao, X.-X., Guo, L.-N., Yuan, Z.-H., Wang, X., Xiao, X.-W., Zhang, X.-Y., Tang, B.-S. & Shen, L. (2019) Analysis of Salivary Microbiome in Patients with Alzheimer’s Disease. Journal of Alzheimer’s Disease. 72 (2), 633–640. doi:10.3233/JAD-190587. Maitre, Y., Mahalli, R., Micheneau, P., Delpierre, A., Amador, G. & Denis, F. (2021) Evidence and Therapeutic Perspectives in the Relationship between the Oral Microbiome and Alzheimer’s Disease: A Systematic Review. International Journal of Environmental Research and Public Health. 18 (21), 11157. doi:10.3390/ijerph182111157.

Both the gut and skin are colonised with distinct microbial communities and operate as crucial organs in the body. Several conditions that primarily affect the gut also manifest in the skin, and the primary cause of several skin conditions has been identified as an underlying gastrointestinal disorder. This demonstration of a bidirectional connection between the gut and skin is known as the gut-skin axis. A summary of what we know: The connection between the gut and the skin is thought to be mediated by the host immune system, however, the underlying mechanisms of how the gut microbiome alters the skin’s immune system, and vice versa, are currently being investigated (De Pessemier et al., 2021) Specific diets as well as the consumption of prebiotics or probiotics that are beneficial for the gastrointestinal system have shown the potential to prevent and manage various skin conditions such as acne, atopic dermatitis and psoriasis (De Pessemier et al., 2021) The gut-skin axis is not only governed by diet as research has found that skin exposure to UVB, and therefore indirectly to serum vitamin D levels, increased the alpha and beta diversity of the gut microbiome (Bosman et al., 2019) Several studies have shown the use of both topical and oral pre and probiotics to be beneficial to the skin’s microbiome and overall health (Gao et al., 2023) Our progress: Through work with Dr Whitney Bowe based in NYC, we found synergistic effects on the skin microbiome diversity, when combining topical and oral probiotics. Certain key microbes were found to be altered more significantly when topical and oral probiotics were consumed over a period of 30 days. References Bosman ES, Albert AY, Lui H, Dutz JP, Vallance BA. Skin Exposure to Narrow Band Ultraviolet (UVB) Light Modulates the Human Intestinal Microbiome. Front Microbiol. 2019 Oct 24;10:2410. doi: 10.3389/fmicb.2019.02410. PMID: 31708890; PMCID: PMC6821880. De Pessemier B, Grine L, Debaere M, Maes A, Paetzold B, Callewaert C. Gut-Skin Axis: Current Knowledge of the Interrelationship between Microbial Dysbiosis and Skin Conditions. Microorganisms. 2021 Feb 11;9(2):353. doi: 10.3390/microorganisms9020353. PMID: 33670115; PMCID: PMC7916842. Gao T, Wang X, Li Y, Ren F. The Role of Probiotics in Skin Health and Related Gut-Skin Axis: A Review. Nutrients. 2023 Jul 13;15(14):3123. doi: 10.3390/nu15143123. PMID: 37513540; PMCID: PMC10385652.

Skin ageing is a natural and inevitable process caused by structural and functional changes in skin cells due to intrinsic and extrinsic factors e.g. biological age and environmental exposures, respectively. Several studies have evaluated the changes in the skin microbiome with age and more recently researchers are exploring whether the skin microbiome might directly influence skin ageing. A summary of what we know: Immediately after birth, newborn skin is colonised by surrounding microorganisms, which have been shown to differ depending on the mode of delivery (Dominguez-Bello et al., 2010; Luna, 2020) By 4–6 weeks after birth, infant skin microbiome structure and function significantly expand and diversify, with prominent body site specificities similar to those of the maternal skin microbiome (Chu et al., 2017; Luna, 2020) An infants skin microbiome continues to diversify and mature throughout childhood, then during puberty, shifts to the more lipophilic Actinobacteria (Corynebacterium and Cutibacterium) due to sebum overproduction (Oh et al., 2012) During adulthood, the skin microbial composition in healthy individuals has been found to remain largely stable until age-related physiologic changes start to occur in older individuals such as a decrease in sebum and sweat production (Oh et al., 2016; Luna, 2020) Alongside age, gender and race/ethnicity have been found to influence the microbial community composition of skin (Li et al., 2019) Recently, researchers have found an association between strains of C.acnes and S.epidermis and a decline in collagen in Caucasian women aged 54-60. However further studies are required to determine whether collagen levels influence or are influenced by the skin microbiome (Zhou et al., 2023) Our progress: When it comes to formulating with the microbiome in mind it is important to consider the microbial composition of different age groups. We are currently working with a client to support the formulation and in vivo testing of skin care products that are tailored to restoring and maintaining the microbiomes of different age groups. References Chu DM, Ma J, Prince AL, Antony KM, Seferovic MD, Aagaard KM. Maturation of the infant microbiome community structure and function across multiple body sites and in relation to mode of delivery. Nat Med. 2017 Mar;23(3):314-326. doi: 10.1038/nm.4272. Epub 2017 Jan 23. PMID: 28112736; PMCID: PMC5345907. Dominguez-Bello MG, Costello EK, Contreras M, Magris M, Hidalgo G, Fierer N, Knight R. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns. Proc Natl Acad Sci U S A. 2010 Jun 29;107(26):11971-5. doi: 10.1073/pnas.1002601107. Epub 2010 Jun 21. PMID: 20566857; PMCID: PMC2900693. Li M, Budding AE, van der Lugt-Degen M, Du-Thumm L, Vandeven M, Fan A. The influence of age, gender and race/ethnicity on the composition of the human axillary microbiome. Int J Cosmet Sci. 2019 Aug;41(4):371-377. doi: 10.1111/ics.12549. PMID: 31190339. Luna PC. Skin Microbiome as Years Go By. Am J Clin Dermatol. 2020 Sep;21(Suppl 1):12-17. doi: 10.1007/s40257-020-00549-5. PMID: 32910437; PMCID: PMC7584528. Zhou W., Fleming E., Legendre G., Roux L., Latreille J., Gendronneau G., et al. (2023). Skin microbiome attributes associate with biophysical skin ageing. Exp. Dermatol. 32 (9), 1546–1556. 10.1111/exd.14863

Atopic dermatitis (AD), also known as atopic eczema, is a common chronic inflammatory skin condition that is characterised by inflamed, dry and itchy skin. Multiple factors contribute to AD such as genetics and environment, although the exact mechanism is not well understood. Treatment is often very difficult, involving the use of topical steroids or oral antibiotics which can cause adverse side effects. Studies have shown that individuals with AD have a disturbed skin microbiome and are more often colonised with Staphylococcus aureus compared to healthy individuals. A summary of what we know: S. aureus contributes to skin barrier defects and inflammation in AD (Totté et al., 2016) Recent research has reported that commensal bacteria residing on normal skin (S. hominis) produce antimicrobial peptides that exhibit activity against S. aureus (Nakatsuji et al., 2017) Topical application of S. hominis has been shown to improve skin condition and may improve various skin conditions such as AD (Ohshima, Kurosumi and Kanto, 2021) Current solutions: Clinical data suggests a probiotic product containing Lactobacillus reuteri DSM 17938 could be a promising topical product for the management of AD (Butler, Christoffer and Axelsson, 2020). References Butler É, Lundqvist C, Axelsson J. Lactobacillus reuteri DSM 17938 as a Novel Topical Cosmetic Ingredient: A Proof of Concept Clinical Study in Adults with Atopic Dermatitis. Microorganisms. 2020 Jul 11;8(7):1026. doi: 10.3390/microorganisms8071026. PMID: 32664536; PMCID: PMC7409218. Ohshima H, Kurosumi M, Kanto H. New solution of beauty problem by Staphylococcus hominis: Relevance between skin microbiome and skin condition in healthy subject. Skin Res Technol. 2021 Sep;27(5):692-700. doi: 10.1111/srt.13001. Epub 2021 Jan 28. PMID: 33511688. Nakatsuji T, Chen TH, Narala S, Chun KA, Two AM, Yun T, Shafiq F, Kotol PF, Bouslimani A, Melnik AV, Latif H, Kim JN, Lockhart A, Artis K, David G, Taylor P, Streib J, Dorrestein PC, Grier A, Gill SR, Zengler K, Hata TR, Leung DY, Gallo RL. Antimicrobials from human skin commensal bacteria protect against Staphylococcus aureus and are deficient in atopic dermatitis. Sci Transl Med. 2017 Feb 22;9(378):eaah4680. doi: 10.1126/scitranslmed.aah4680. PMID: 28228596; PMCID: PMC5600545. Totté JE, van der Feltz WT, Hennekam M, van Belkum A, van Zuuren EJ, Pasmans SG. Prevalence and odds of Staphylococcus aureus carriage in atopic dermatitis: a systematic review and meta-analysis. Br J Dermatol. 2016 Oct;175(4):687-95. doi: 10.1111/bjd.14566. Epub 2016 Jul 5. PMID: 26994362.

Acne is a well-known chronic inflammatory condition that impacts individuals of all age groups worldwide. Several factors have been found to influence the development of acne and its severity, such as increased sebum production and hyperkeratinization. More recent studies have revealed that dysbiosis - an imbalance of the skin’s microbiome - is implicated in the manifestation of inflammatory skin diseases, including acne. Specifically, an imbalance of the bacteria Cutibacterium acnes has been regarded as one of the major factors involved in acne pathogenesis. However, now it is known that there are significant differences between the many strains of C. acnes, some of which are being shown to benefit the skin. A summary of what we know: Metagenomic analyses have revealed that the strain structure of C. acnes in acne patients differs from that of healthy individuals (Huang et al., 2023) Type IV and V strains are particularly prevalent in acne-affected skin, suggesting a correlation between specific C. acnes strains and acne pathology (Fitz-Gibbon et al., 2013) The species is divided into three main phylotypes: phylotype I as C. acnes subsp. acnes, phylotype II as C. acnes subsp. defendens, and phylotype III as C. acnes subsp. elongatum (Rhee et al., 2023) Recent research has suggested that strains more associated with health come from the C. acnes subsp. defendens phylotype (Rhee et al., 2023) Clinical data suggests the skin health benefits of topical application of a modified C. acnes subsp. defendens strain, XYCM42, and its ferment (Rhee et al., 2023) Industry impact & potential: Crown Laboratories, Inc. launched the BIOJUVE skin care collection earlier this year, incorporating Xycrobe technology, whose efficacy is backed by the clinical study of C. acnes subsp. defendens strain XYCM42. Understanding the differences between the many strains of microbiome species could be key to developing prebiotic, probiotic and postbiotic solutions for acne as well as multiple other skin conditions. Our solution: Sequential uses shotgun metagenomic sequencing in our R&D to understand which critical species and strains are influenced by cosmetic products and influence skin health. We have developed highly specific probes to measure the absolute quantity of these species and strains, down to the copy number. Therefore, we can help to perform in vivo studies and validate the sequencing results at strain level. References: Fitz-Gibbon S, Tomida S, Chiu BH, Nguyen L, Du C, Liu M, Elashoff D, Erfe MC, Loncaric A, Kim J, Modlin RL, Miller JF, Sodergren E, Craft N, Weinstock GM, Li H. Propionibacterium acnes strain populations in the human skin microbiome associated with acne. J Invest Dermatol. 2013 Sep;133(9):2152-60. doi: 10.1038/jid.2013.21. Epub 2013 Jan 21. PMID: 23337890; PMCID: PMC3745799. Huang C, Zhuo F, Han B, Li W, Jiang B, Zhang K, Jian X, Chen Z, Li H, Huang H, Dou X, Yu B. The updates and implications of cutaneous microbiota in acne. Cell Biosci. 2023 Jun 21;13(1):113. doi: 10.1186/s13578-023-01072-w. PMID: 37344849; PMCID: PMC10283232. Rhee MS, Alqam ML, Jones BC, Phadungpojna S, Day D, Hitchcock TM. Characterization of a live Cutibacterium acnes subspecies defendens strain XYCM42 and clinical assessment as a topical regimen for general skin health and cosmesis. J Cosmet Dermatol. 2023 Mar;22(3):1031-1045. doi: 10.1111/jocd.15510. Epub 2022 Nov 14. PMID: 36374551.

In the world of skincare, light-emitting diode (LED) technology has emerged as a powerful tool, emitting specific wavelengths of light, such as red and blue, which penetrate the skin at different depths and trigger specific cellular responses. As interest in LED devices grows, so does the scrutiny of their impact on the skin microbiome, prompting a surge in research efforts. What We Know: Red light (620-750 nm) effectively accelerates wound healing by promoting collagen production, stimulating fibroblast proliferation, enhancing local microvasculature and boosting cellular metabolism to facilitate tissue regeneration. Red light LED masks are thus popularly used to prevent signs of ageing and to treat conditions like psoriasis and rosacea (Zhang et al., 2024). Blue light (380-500 nm) exhibits antimicrobial properties. Narrowband LED therapy utilising blue light has shown efficacy and safety as an adjunctive treatment for mild to moderate acne. This occurs through the inactivation of Cutibacterium acnes when blue light combines with oxygen, producing reactive oxygen species, damaging the bacteria (Dai, 2017). Industry Impact and Potential: The sequential use of blue light followed by red light treatment to address skin disorders associated with microbial agents is a promising approach. Although blue light effectively targets C. acnes, its depth of skin penetration is limited. Red light, on the other hand, penetrates deeper and complements blue light therapy with its anti-inflammatory effects, leading to greater clinical improvement, especially in inflammatory acne lesions (Nestor et al., 2016). The versatility of LED therapy, influenced by light parameters and clinical application, allows for tailored treatment of various skin disorders, each with unique biological effects to address (Sorbellini, Rucco & Rinaldi, 2018). Prevalent commensal bacteria, such as Staphylococcus spp., contain pigments and proteins responsive to blue light, potentially influencing inflammation. These photosensitive targets, like flavins and porphyrins, can significantly impact microbial behaviour when excited. For instance, Acinetobacter baumannii and certain skin commensals alter biofilm formation and virulence in response to blue light. However, understanding the distribution of these light-sensitive elements across the skin microbiome remains unclear (Serrage et al., 2024). Our Solution: At Sequential, our flagship service empowers you to conduct personalised, comprehensive Skin Microbiome Studies. Backed by a vast database of 20,000 microbiome samples and a worldwide network of 10,000 testing participants, our team of experts is dedicated to assisting you in crafting a tailored microbiome study. This enables in-depth exploration into the impact of advanced skincare technologies, such as LED masks, on the skin microbiome. References: Dai, T. (2017) The antimicrobial effect of blue light: What are behind? Virulence. 8 (6), 649–652. doi:10.1080/21505594.2016.1276691. Nestor, M.S., Swenson, N., Macri, A., Manway, M. & Paparone, P. (2016) Efficacy and Tolerability of a Combined 445nm and 630nm Over-the-counter Light Therapy Mask with and without Topical Salicylic Acid versus Topical Benzoyl Peroxide for the Treatment of Mild-to-moderate Acne Vulgaris. The Journal of Clinical and Aesthetic Dermatology. 9 (3), 25–35. Serrage, H.J., Eling, C.J., Alves, P.U., Xie, E., McBain, A.J., Dawson, M.D., O’Neill, C. & Laurand, N. (2024) Spectral characterization of a blue light-emitting micro-LED platform on skin-associated microbial chromophores. Biomedical Optics Express. 15 (5), 3200–3215. doi:10.1364/BOE.522867. Sorbellini, E., Rucco, M. & Rinaldi, F. (2018) Photodynamic and photobiological effects of light-emitting diode (LED) therapy in dermatological disease: an update. Lasers in Medical Science. 33 (7), 1431–1439. doi:10.1007/s10103-018-2584-8. Zhang, L., Jiang, X., Li, S., Lan, Y., Liu, H., et al. (2024) Stretchable electronic facial masks for photodynamic therapy. Nano Energy. 123, 109407. doi:10.1016/j.nanoen.2024.109407.

The scalp hair shaft microbiota is distinct from that of the scalp skin. The composition of scalp hair microbiota is greatly influenced by the scalp microbiome, but it is also shaped by various intrinsic factors, including gender, as well as extrinsic factors like hair washing and styling. What We Know: Differences in bacterial community structures between the microbiome of hair shafts and scalp include variances in cell density and relative abundances of Firmicutes and Proteobacteria. There is also correlation between Actinobacteria and Firmicutes abundances between an individual's hair and scalp (Watanabe et al., 2020). The primary bacteria found on human scalp hair shafts are native inhabitants originating from the hair roots. Phyla Actinobacteria, Proteobacteria and Firmicutes are the species present in the greatest abundance, with the former two competing for dominance (Watanabe et al., 2021). Scalp hair shafts are known to harbour the hair-specific genus, Pseudomonas, alongside the skin-derived genera Cutibacterium and Staphylococcus, which is distinct from other human skin microbiomes. Cutibacterium, Lawsonella, Moraxella and Staphylococcus were notably elevated in males compared to females. Conversely, the bacterial cell count of Pseudomonas was higher in females than in males (Watanabe et al., 2021). Females using hair wax had reduced cell counts of Cutibacterium, Lawsonella and Moraxella, while hair bleach showed lowered Pseudomonas counts. In males, hair colour application decreased Cutibacterium, Lawsonella and Staphylococcus counts, and using hair dryers reduced Staphylococcus. Additionally, males who washed their hair in the morning had lower Lawsonella counts than those who washed it the night prior (Watanabe et al., 2021). Industry Impact and Potential: Given the shared bacterial species between scalp skin and hair shafts, environmental distinctions on scalp skin could potentially contribute to microbial differences observed on hair shafts (Watanabe et al., 2021). This discovery opens up a promising and largely uncharted frontier of scalp and hair care products. By focusing on nurturing the scalp microbiome, new innovative products can offer targeted support to the hair and understanding the interplay between scalp and hair microbiomes not only sheds light on individualised hair care, but also presents promising opportunities for product development. Our Solution: With a database of 20,000 microbiome samples and 4,000 ingredients, alongside a global network of 10,000 testing participants, Sequential offers tailored solutions to build your custom microbiome studies and product formulation. Our focus and emphasis on creating microbiome safe and friendly products guarantees the preservation of biome integrity, making us the perfect partner for your scalp and hair care product development needs. References: Watanabe, K., Yamada, A., Nishi, Y., Tashiro, Y. & Sakai, K. (2021) Host factors that shape the bacterial community structure on scalp hair shaft. Scientific Reports. 11 (1), 17711. doi:10.1038/s41598-021-96767-w. Watanabe, K., Yamada, A., Nishi, Y., Tashiro, Y. & Sakai, K. (2020) Relationship between the bacterial community structures on human hair and scalp. Bioscience, Biotechnology, and Biochemistry. 84 (12), 2585–2596. doi:10.1080/09168451.2020.1809989.

The interplay between skin wounds and the skin microbiome presents a captivating area of study. While the precise mechanisms remain elusive, ongoing research is unravelling how the microbiome influences wound healing, shedding light on both facilitative and inhibitory roles. What We Know: When the skin barrier is compromised due to injury, it enables the colonisation of microbes not typically present on the skin or the transfer of microbiota components to areas where they aren't normally found. Research indicates that microbiota may play a beneficial role in wound healing by regulating the innate immune response and promoting tissue regeneration (Yang et al., 2024). Burn injuries are an example of acute wounds, which increase the permeability of the skin, thus allowing skin microbes to penetrate deeper tissues, leading to possible infections. Therefore, burns significantly change the skin's microbial balance, favouring heat-loving microbes like Aeribacillus, Caldalkalibacilus and Nesterenkonia, while reducing helpful bacteria like Cutibacteria, Staphylococci and Corynebacteria. These shifts are linked to specific wound healing outcomes; higher levels of Corynebacterium are associated with infections, while Staphylococci and Cutibacteria are linked to lower infection rates post-burn (Yang et al., 2024). Research found that invasive moulds, including those from the Mucorales, Aspergillus and Fusarium species, were found to considerably prolong wound closure compared to non-fungal infected wounds with similar injury patterns. Enterococci was often observed in conjunction with invasive fungal infections, heightening the complexity of traumatic wounds (Warkentien et al., 2015). Industry Impact and Potential: Understanding microbe-host interactions in wounds can inform future therapeutic interventions, paving the way for microbiota-based mechanisms in wound treatment (Yang et al., 2024). Research has demonstrated that commensals play a vital role in initiating innate immune responses. Resident commensals and even generally pathogenic Staphylococcus aureus promote skin regeneration and wound-induced hair follicle growth (Wang et al., 2021). Studies have shown that Lactobacillus spp. enhance keratinocyte proliferation and migration and prevent biofilm formation. Animal models also showed the beneficial effects of these probiotics, as well as Bifidobacteria and Saccharomyces cerevisiae, in reducing pathogen colonisation and biofilm formation, facilitating tissue repair and reducing excessive scarring (Yang et al., 2024). Our Solution: Unlock the potential of microbiome-based wound healing products with Sequential's comprehensive end-to-end Microbiome Product Testing Solution. Whether used independently or alongside our expert-guided product development and formulation services, this holistic approach empowers your business to pioneer innovative solutions for addressing skin conditions. References: Wang, G., Sweren, E., Liu, H., Wier, E., Alphonse, M.P., et al. (2021) Bacteria induce skin regeneration via IL-1β signaling. Cell Host & Microbe. 29 (5), 777-791.e6. doi:10.1016/j.chom.2021.03.003. Warkentien, T.E., Shaikh, F., Weintrob, A.C., Rodriguez, C.J., Murray, C.K., Lloyd, B.A., Ganesan, A., Aggarwal, D., Carson, M.L., Tribble, D.R., & on behalf of the Infectious Disease Clinical Research Program Trauma Infectious Disease Outcomes Study Group (2015) Impact of Mucorales and Other Invasive Molds on Clinical Outcomes of Polymicrobial Traumatic Wound Infections. Journal of Clinical Microbiology. 53 (7), 2262–2270. doi:10.1128/jcm.00835-15. Yang, Y., Huang, J., Zeng, A., Long, X., Yu, N. & Wang, X. (2024) The role of the skin microbiome in wound healing. Burns & Trauma. 12, tkad059. doi:10.1093/burnst/tkad059.

It is a known fact that each and every individual has a unique microbiome, comprising a community of bacteria, fungi, viruses and protozoa (commonly referred to as microbes). Interestingly, the origin of a person's microbiome stems from the moment they were born. Studies show that regardless of birthing route (vaginal or caesarean), 58.5% of a baby’s microbiome is acquired from their mother (Bogaert., et al 2023). In recent years, the mother-to-child microbiome transfer has become a topic of note within the microbiome space. Despite growing literature about the baby microbiome, it is still an area that needs further exploration. This article will aim to highlight current research on the topic, whilst focusing on Atopic Dermatitis as seen within newborns and infants. It is crucial to understand and expand upon this research as it might lead to uncovering new microbial candidates that could impact skin conditions, such as Atopic Dermatitis, in early life and unlock their treatments. A Background on Atopic Dermatitis There are numerous paediatric skin disorders that can affect an infant in early life. Typically, we find that Atopic Dermatitis (AD), is the most prevalent skin disorder amongst infants and is an important condition to consider (Gilaberte et al., 2020). It has been seen that infants that suffer from AD can go on to develop a highly contagious condition known as impetigo (a bacterial infection that typically affects infants and young children)( Mannschreck et al.,2020).  According to a study published in 2015 “the median impetigo prevalence in children was 12.3%, (IQR 4.2–19.3%)” (Bowen et al., 2015).  It is known that the skin microbiome of infants is completely different to that of adults, however we also know that the pathophysiology and the inflammatory cytokines that are triggered are alike. The pathogenesis of AD is incredibly complex, which is why pinpointing its treatment has been difficult. Most of the drugs that are currently under investigation or are showing some positive results in clinical trials targeting skin cells, but we now understand that there are more solutions that intend to target the microbiome component (Baldwin et al., 2020). At present, there are two ways of exploring AD. One way is to look directly at the source and extract samples of the skin microbiome to observe changes in its profile. The alternative is to look at the gut microbiome, pulling from previously published literature that suggests that there is a convincing link between the gut microbiome and skin health. The Role of Staphylococcus aureus in AD. AD sites on the body are known to be dominated by Staphylococcus aureus (S. aureus), which is the most studied and well-described bacteria linked to AD. It is known that S. aureus goes through a stage of growth which leads to AD flare-ups in individuals (Khadka et al., 2021). This means that by identifying the growth of S. aureus early a threshold can be determined that when surpassed could be used to predict when a flare-up could be triggered, which may give rise to the opportunity for prevention. Mother-to-child Microbiome Transfer When exploring early colonisation of the baby microbiome, the transfer from mother-to-child is more commonly talked about. Until recently, it has been agreed that the womb is sterile. However, new research has been carried out on amniotic fluid which suggests that certain microbes might be present there as well (Kaisanlahti et al., 2023). Although the evidence used to support this research in scientific literature is generally regarded as weak, more studies are crucial before this can be proven or disputed. Another theory surrounding the amniotic fluid explores the idea that a baby might in fact ingest the amniotic fluid, resulting in bacterial transfer from the mother. This is another area that is currently lacking in evidence and requires further research. There is a significant transfer of microbes from a mother to her child during vaginal delivery as well as through skin-to-skin contact in a baby’s early moments of life. During breastfeeding, the bacteria surrounding the nipple is also transferred orally. According to recent publications, 58.5% of a baby’s microbiome is a direct result of their mother. The rest is attributed to their environment and other external factors (Bogaert., et al 2023). Whether there is a link between birthing route (vaginal or caesarean) and AD is currently unclear, with mixed study results and a vast majority of scientists agreeing that a clear link cannot consistently be established. Infant Early Life and AD: Skin Microbiome There are several published papers which explore the association of the baby microbiome with AD. For the purposes of this article “The skin microbiome in the first year of life and its association with atopic dermatitis” will be evaluated more closely (Rapin., et al 2023). This study was conducted in Oslo, Norway, in which the skin of babies was sampled at four timepoints (At birth, 3 months, 6 months and 12 months). Various investigational factors, including the composition of the skin microbiome, birthing methods, environmental influences, parental factors, and breastfeeding, were analyzed to assess potential associations with skin immunities. Thee results of this study ultimately showed that these factors were all correlated and instrumental in the development of the baby’s microbiome. The study further showed that each variable held a different influence on the skin microbiome depending on the timepoint the sample was taken at. For example, at birth the mode of delivery was most instrumental. However, as time went on different factors became more influential, such as birth location, breastfeeding, maternal AD, maternal food allergies, and exposure to pets. It is known that the delivery of a baby shapes the microbiome in early life. However, can an association be found between the birthing route and the development of AD? This Oslo study concluded that ultimately there is not a strong association between delivery mode and AD pathogenesis. The reasoning behind this conclusion was that the few differences that were noted at birth levelled out by 12 months and no longer held differentiable significance (Rapin., et al 2023). Infant early life and AD: Gut Microbiome It is interesting to note that the conclusions drawn from the skin microbiome study in Oslo is mirrored by another study that was conducted on the gut microbiome in association with AD. The study in question “The associations of maternal and children’s gut microbiota with the development of atopic dermatitis for children ages 2 years” (Fan et al., 2022) compared the gut microbiome of mothers and babies, and found that mothers of infants and toddlers with AD had higher abundance of Candidatus_Stoquefichus and Pseudomonas in pregnancy. The study also found that infants and toddlers with AD had a higher abundance of Eubacterium_xylanophilum group at birth, Ruminococcus_gauvreauii group at 1 year of age, UCG-002 at 2 years, and lower abundance of Gemella and Veillonella at 2 years of age. It is particularly interesting that the study also demonstrated a lower abundance of Prevotella in mothers of infants and toddlers with AD compared to mothers of the control group. The Skin Microbiome: New Findings A subsequent study performed shotgun metagenomic sequencing on the skin microbiome, it found that a dysbiosis in the microbiome exists prior to the onset of AD (Chaudhary et al., 2023). Firstly, the study affirmed that birth mode and demographics in fact did not associate with subsequent AD development. However, what the study did find was that by measuring the skin of babies, reduced Prevotella abundance could be a predictor of subsequent AD development. The benefits of using shotgun metagenomics meant that more functional analysis could be conducted, ultimately showing that there was a significant reduction in Prevotella abundance in the AD group compared to the control group. Additionally, there are some differences in host and bacterial features in certain genes that are interesting to target based on what is seen in shotgun metagenomic sequencing. When looking at lipid profiling they showed a complete difference between the AD group and control group. Prevotella has been found to be a good candidate as a potential predictor of AD development, as demonstrated by this study. Conclusion There is considerable research being conducted on the baby microbiome as well as AD in adults, however more research needs to be carried out in order to make stronger links between what might be the root cause of AD in babies and infants. The publications highlighted within the article give some good insights into AD and some of the positive and negative correlations between different variables. Notable, the role of Prevotella in AD might be an interesting one to explore further as there is strong evidence to suggest that it could be a good diagnostic target to better understand how AD might develop. At present, the majority of treatments within the personal care and pharmaceutical industry continue to target Staphylococcus aureus, with proven improvements and more clinical data to show that this approach is effective in adults with AD. However, new candidates must be studied so that the industry can adapt the way it approaches AD treatment and intervention in the future, particularly regarding the development of AD in children. Reference Baldwin H, Aguh C, Andriessen A, Benjamin L, Ferberg AS, Hooper D, Jarizzo JL, Lio PA, Tlougan B, Woolery-Lloyd HC, Zeichner J. Atopic Dermatitis and the Role of the Skin Microbiome in Choosing Prevention, Treatment, and Maintenance Options. J Drugs Dermatol. 2020 Oct 1;19(10):935-940. doi: 10.36849/JDD.2020.10.36849/JDD.2020.5393. PMID: 33026777. Bogaert D, van Beveren GJ, de Koff EM, Lusarreta Parga P, Balcazar Lopez CE, Koppensteiner L, Clerc M, Hasrat R, Arp K, Chu MLJN, de Groot PCM, Sanders EAM, van Houten MA, de Steenhuijsen Piters WAA. Mother-to-infant microbiota transmission and infant microbiota development across multiple body sites. Cell Host Microbe. 2023 Mar 8;31(3):447-460.e6. doi: 10.1016/j.chom.2023.01.018. PMID: 36893737. Bowen AC, Mahé A, Hay RJ, Andrews RM, Steer AC, Tong SY, Carapetis JR. The Global Epidemiology of Impetigo: A Systematic Review of the Population Prevalence of Impetigo and Pyoderma. PLoS One. 2015 Aug 28;10(8):e0136789. doi: 10.1371/journal.pone.0136789. PMID: 26317533; PMCID: PMC4552802. Chaudhary PP, Myles IA, Zeldin J, Dabdoub S, Deopujari V, Baveja R, Baker R, Bengtson S, Sutton A, Levy S, Hourigan SK. Shotgun metagenomic sequencing on skin microbiome indicates dysbiosis exists prior to the onset of atopic dermatitis. Allergy. 2023 Oct;78(10):2724-2731. doi: 10.1111/all.15806. Epub 2023 Jul 8. PMID: 37422700; PMCID: PMC10543534. Fan X, Zang T, Dai J, Wu N, Hope C, Bai J, Liu Y. The associations of maternal and children's gut microbiota with the development of atopic dermatitis for children aged 2 years. Front Immunol. 2022 Nov 17;13:1038876. doi: 10.3389/fimmu.2022.1038876. PMID: 36466879; PMCID: PMC9714546. Gilaberte Y, Pérez-Gilaberte JB, Poblador-Plou B, Bliek-Bueno K, Gimeno-Miguel A, Prados-Torres A. Prevalence and Comorbidity of Atopic Dermatitis in Children: A Large-Scale Population Study Based on Real-World Data. J Clin Med. 2020 May 28;9(6):1632. doi: 10.3390/jcm9061632. PMID: 32481591; PMCID: PMC7356227. Kaisanlahti, A., Turunen, J., Byts, N. et al. Maternal microbiota communicates with the fetus through microbiota-derived extracellular vesicles. Microbiome 11, 249 (2023). https://doi.org/10.1186/s40168-023-01694-9 Khadka VD, Key FM, Romo-González C, Martínez-Gayosso A, Campos-Cabrera BL, Gerónimo-Gallegos A, Lynn TC, Durán-McKinster C, Coria-Jiménez R, Lieberman TD, García-Romero MT. The Skin Microbiome of Patients With Atopic Dermatitis Normalizes Gradually During Treatment. Front Cell Infect Microbiol. 2021 Sep 24;11:720674. doi: 10.3389/fcimb.2021.720674. PMID: 34631601; PMCID: PMC8498027. Mannschreck D, Feig J, Selph J, Cohen B. Disseminated bullous impetigo and atopic dermatitis: Case series and literature review. Pediatr Dermatol. 2020 Jan;37(1):103-108. doi: 10.1111/pde.14032. Epub 2019 Nov 22. PMID: 31755570. Rapin A, Rehbinder EM, Macowan M, Pattaroni C, Lødrup Carlsen KC, Harris NL, Jonassen CM, Landrø L, Lossius AH, Nordlund B, Rudi K, Skjerven HO, Cathrine Staff A, Söderhäll C, Ubags N, Vettukattil R, Marsland BJ. The skin microbiome in the first year of life and its association with atopic dermatitis. Allergy. 2023 Jul;78(7):1949-1963. doi: 10.1111/all.15671. Epub 2023 Feb 24. PMID: 36779606.

Introduction: What are biosensors? Biosensors are described as analytical devices used to detect biomarkers, or analytes, which can be anything from toxic chemicals, to small molecules, microbes or even peptides and nucleotides (Bhalla et al., 2014). These devices are made up of key parts. Firstly, biological components which uphold the biosensing capacity, for example antibodies detecting antigens or aptamers binding to their specific targets. Then, physical or chemical information transducers which signal the presence of a target. Finally, the signal is processed and we obtain an output (Figure 1). Traditionally these kinds of biosensors rely on electrochemistry, and we often think of them in the context of diabetes and Continuous Glucose Monitoring Devices, allowing patients with the condition to control their blood sugars. However, biosensors have very diverse applications which can range from disease monitoring to environmental monitoring, and there is a continuing need to make cheap and reliable, as well as simple biosensors that can be used across a wide range of applications. Figure 1: Schematic of biosensors. Image taken from Verma and Gahlaut (2019) Synthetic biology biosensors Synthetic biology mainly relies on exploiting the power of nature to create useful tools, thus this approach could provide a new generation of biosensing systems that present great advantages over traditional devices. The first of these advantages lies in the fact that they are custom-made biological tools which allow for highly specific target identification. Moreover, there are two approaches in designing biosensors. On the one hand, they can be created by genetically engineering live cells to create Whole-Cell Biosensors (WCB) that are able to respond in real-time to their environment and detect specific analytes (Chen et al., 2023). On the other hand, we can generate cell-free biosensors which are essentially solutions consisting of all the required machinery, proteins and genetic circuits that allow for the detection of our targets (Zhang et al., 2020). Ultimately, both approaches produce a distinguishable qualitative or quantitative signal. They allow for quick and accurate sensing of targets, which as discussed is crucial for fulfilling the demand across a range of applications. The rationale behind the workings of such biosensors is quite simple. They have an input, which can be anything from environmental signals to light or even small molecules, this input gets converted into a signal that gets processed by a genetic network which can be designed to perform diverse functions depending on our applications (Wang et al., 2023). In a similar way to electrical circuits, we can add in different ranges of signal processing steps. As a result, our biosensor is able to generate an output, for instance a change in colour by production of pigments visible to the naked eye, emission of fluorescence that we can see and quantify with the right equipment or even liberation of gases that can be monitored using ultrasound (Figure 2). There is a level of adaptability and it is ultimately up to us to decide on the purpose of these biosensors. Figure 2: Schematic of synthetic biology based biosensors. (diagram from Xinyi Wan, University of Edinburgh, PhD Thesis) Bacterial biosensing Biosensors uphold great promises for bacterial biosensing whether it is from water, soil, human or food samples. It all starts with sample collection, treatment of the samples, and then detection can either be done directly on the bacteria by detecting exposed biomarkers or unique DNA and RNA sequences, or by indirect detection of unique toxins, peptides, or volatile organic compounds (VOCs) produced by the bacteria (Mazur et al. 2023). Point-of-care (POC) devices POC devices are medical diagnostic tools designed to provide rapid and convenient testing and analysis of patient samples. These devices aim to bring testing closer to the patients and aim to reduce the need for the sample to be sent into a central laboratory, thus allowing quicker decision making by healthcare providers. POC devices play a crucial role in improving patient outcomes, especially in scenarios where time sensitive results are required. A great example of those would be lateral-flow tests which can give simple informative results in less than 30 minutes without requiring the assistance of trained experts. Key features of POCs include: quick turnaround times of test results, great accessibility and ease of use in various healthcare and nontraditional settings and research areas, and crucially they must be user friendly even to those who are not laboratory staff (Mazur et al., 2023). These devices allow for great diagnostic ranges, for example diagnostic of infections, monitoring chronic conditions, and screening for patients before sourcing a study. Paper-based biosensors The vast majority of us will have been exposed to and acquainted with the use of paper-based biosensors during the COVID-19 pandemic, in the form of lateral flow tests. In simple terms, it corresponds to a sheet of paper where we have an ensemble of biological elements that can react with each other and generate our desired output upon contact with the target. They are cost-effective, provide rapid responses (usually between 5-30 minutes), are a simple portable solution, and can be adapted for remote or resource limited settings. Indeed, many of these advantages have been seen through the use of paper-based biosensors during the COVID-19 pandemic. These paper-based cell-free biosensors, and can be used alongside genetic networks to generate a whole new range of specific functions. The workflow behind paper-based biosensors follows as described in figure 3; firstly we have our platform which is the microchannel paper, it has great microfluidic capacities and is designed to use a special paper which contains microchannels and spots. These channels are created using a technique such as printing or wax patterning, and within those channels we can embed our capture molecules as well as our synthetic gene network and cell-free extracts. The capture molecules are substances that can specifically bind to the bacteria of interest, and they are immobilised within the paper's channels. The liquid sample is inserted into the biosensor, and if the sample contains the bacteria, it will be able to be processed by our synthetic genetic circuit. The liquid flows along the paper channels carrying the bacteria with it, and as it comes into contact with the capture molecules our systems work and a signal is generated (Pardee et al., 2014). Figure 3: Assembling a paper-based synthetic biology biosensor. (diagram taken from Pardee et al., 2014) Why are they relevant to us? There already exists a few golden standard techniques such as ELISA, qPCR, FTIR, etc., however while these techniques are very robust, accurate and sensitive to strain level, they can often also be costly, time consuming, require centralised laboratories, trained personnel,  extensive sample pretreatment and multi-step processing. There is now a need to develop point-of-care devices that are fast, cheap, portable, and do not require any specialist training. This is especially important as low-income regions too often struggle to access adequate diagnostic tools for the detection of pathogens, ultimately leading to higher mortality rates (Pardee et al. 2014). We will focus our attention on the article ‘A low-cost paper-based synthetic biology platform for analysing gut microbiota and host biomarkers’ (Takahashi et al, 2018). This study is of great importance, especially considering that the microbiome make-up is key to understanding health and diseases. This study was focused towards trying to detect the hypervariable regions of the 16S rRNA genes in order to perform taxonomic profiling of the microbiome. The study aimed to develop an approach that is affordable, on demand and allows for simple analysis of the microbiome from stool samples. In addition they aimed to develop a platform that could accurately identify species-specific mRNA from 10 different bacteria as well as the mRNA of 3 key biomarkers involved in inflammation (calprotectin, CXCL5 and IL-8) and one cytokine (oncostatin M) which helps to predict the efficacy of TNF-α therapies in IBD patients. Furthermore, they pushed their research for rapid and inexpensive detection of toxin mRNA in the diagnosis of C. difficile infections. As a result of the study, a platform was successfully developed for analysis of the gut microbiota for clinical research and adaptability and low resource settings.Their device allowed for the orthogonal detection of species-specific mRNA from 10 different bacteria associated with gut health and disease with 3 fM limit of detection (LOD) achieved. In other words, this tool was able to discriminate between different bacteria and accurately report which ones were detected without having any cross-talk or reporting the wrong species. On top of a great accuracy, it is important to consider the LOD, which refers to the lowest amount of a substance (here mRNA) detected by the sensor. The lower the LOD, the more sensitive the biosensor is, making it efficient in detecting extremely small amounts of the bacteria's genetic material. A LOD as low as the one they achieved is reflective of great sensitivity. For comparison, traditional methods like qPCR often have LODs in the range of picomolars (pM) or femtomolars (fM). As a result, this biosensor is great for accurately detecting bacteria even if they are present in very low concentrations! The Takahashi group was able to develop a simple approach to study relative abundances of bacteria in the stool samples via a semi-quantitative determination of the concentrations of each target mRNA. Although this semi-quantitative approach initially only provided them with a rough idea of mRNA amounts rather than exact concentrations, the group compared the samples with known referencing standards and created a standard curve which allowed them to estimate mRNA concentrations in the samples. Results were even validated by a comparison with RT-qPCR which showed very similar performance. Finally, they were also able to identify different toxin mRNA expression levels from pathogenic C.difficile strains that were otherwise indistinguishable by using standard DNA-based qPCR diagnosis. The system they generated is a translation-based biosensor which relies on a technology called “Toehold-switch sensors” that control the translation of genes. In simple terms, toehold switches correspond to a strand of RNA that can form a hairpin structure based on complementary base pairing. This RNA strand has a region specifically complementary to our target sequences and a region that encodes for the protein we want to express for the detection - in this case a green fluorescent protein (GFP). Due to the secondary structure of the RNA, the GFP cannot be expressed as it is made inaccessible to the transcriptional machinery. The only way of expressing the GFP is by exposing the toehold switch to the target mRNA sequence from the bacteria we want to detect. The two strands will be able to bind to each other, causing a conformational change in the toehold switch which allows GFP to be transcribed and expressed (Figure 4). The advantage of this technique is that RNA folding is universal and many computer design softwares can predict the 3D structure which facilitates their design. However, on the other hand RNA folding is highly sensitive to physiological conditions, so unless the right conditions are met, the ability of the biosensor to function might be hindered. Figure 4: Toe-hold switch mechanism. (Diagram taken from Takahashi et al., 2018) Advantages of this approach Some of the main advantages of this approach are that it provides us with a great ease of use with simple results being observed. Moreover, the biosensors can be adapted for low resource settings, as the reactions that are happening do not require highly specialised equipment. For example, the GFP detection can be monitored on affordable and easy to build portable electronic readers that can quantify the changes in absorbance. The sample amplification of the mRNA is enabled through Nucleic acid sequence based amplification (NASBA) by using simple isothermic incubators, so there is no real need for thermocyclers with greater powers such as the ones which are required for qPCR (Kia et al. 2023). Additionally an important aspect of this is the cost, using this technique the mRNA can be quantified in around 3-4 hours for $16 per transcript using commercially available kits, with the potential to decrease this cost to $2 per transcript by using in-house cell-free extracts. Compared to qPCR which costs significantly more, it is clear that this is a more cost effective alternative (Takahashi et al., 2018). All of this could be applied to a broad range of studies, including skin samples. This technology is easily adaptable to target other microorganisms, such as fungi, bacteriophages and human viruses. It could also be adapted for point-of-care use and at home monitoring for patients to respond to one of the greater goals: being able to regularly monitor disease progression in patients. Limitations of the study The first limitation that they encountered upon initial design was the low limit of detection of the toehold switch: with the sensor alone, the limit of detection was in the 10-30 nM range. They therefore decided to pair their approach with NASBA which is a technique done during the sample processing step to amplify the bacterial RNA prior to detection. This technique is very robust, particularly well-suited for RNA, and presents less risk of DNA contamination, therefore minimising the risk of a false positive result. As a result, this step greatly improved the sensitivity of this device to 3 fM. Additionally, as the 16S sensors they first generated presented significant crosstalk in closely related bacteria and were therefore not suitable for discriminating amongst highly related bacterial species, they chose to target different mRNA sequences which are unique to the desired bacteria based on a bioinformatics pipeline they generated and obtained a perfectly orthogonal detection of the different bacterial species. Their sensors were however not yet optimised to identify down to strain level. Moreover, despite requiring easily accessible equipment, their approach still involves some sample processing steps and is still not yet fully adapted for at-home testing, and therefore is not yet at the point-of-care application levels. However, we can still get a lot of important and valuable information in a more accessible way than traditional techniques. Pioneering skin microbiome biosensors There is very little research around biosensors in the field of the skin microbiome. However, translating this methodology and finding a wide array of specific targets for skin microbiome studies is achievable. An interesting avenue in the future would be introducing ribocomputing circuits for bacterial interaction studies to allow us to track the social interactions of bacteria in different dysbiosis conditions. Nowadays, more advanced paper-based biosensors allow for detection of signals directly with smartphones which can save the data into a cloud to monitor changes over time (Kim et al., 2021). The rapid advances in synthetic biology and growing interest in the skin microbiome will certainly open doors to a future where these proof-of-concept studies will serve as a basis to create wearable devices capturing in real time  the changes of our beloved skin microbial communities. References Bhalla, N., Jolly, P., Formisano, N. & Estrela, P. (2016) Introduction to biosensors. Essays in Biochemistry. 60 (1), 1-8. 10.1042/EBC20150001. Chen S, Chen X, Su H, Guo M, Liu H. Advances in Synthetic-Biology-Based Whole-Cell Biosensors: Principles, Genetic Modules, and Applications in Food Safety. Int J Mol Sci. 2023 Apr 28;24(9):7989. doi: 10.3390/ijms24097989. PMID: 37175695; PMCID: PMC10178329. Damour, A., Robin, B., Deroche, L., Broutin, L., Bellin, N., Verdon, J., Lina, G., Leclère, F. M., Garcia, M., Cremniter, J., Lévêque, N. & Bodet, C. (2021) Phenol-soluble modulins α are major virulence factors of Staphylococcus aureus secretome promoting inflammatory response in human epidermis. Virulence. 12 (1), 2474-2492. 10.1080/21505594.2021.1975909. Kia, V., Tafti, A., Paryan, M. & Mohammadi-Yeganeh, S. (2023) Evaluation of real-time NASBA assay for the detection of SARS-CoV-2 compared with real- time PCR. Irish Journal of Medical Science. 192 (2), 723-729. 10.1007/s11845-022-03046-2. Kim, S., Lee, M. H., Wiwasuku, T., Day, A. S., Youngme, S., Hwang, D. S. & Yoon, J. (2021) Human sensor-inspired supervised machine learning of smartphone-based paper microfluidic analysis for bacterial species classification. Biosensors & Bioelectronics. 188 113335. 10.1016/j.bios.2021.113335. Mazur, F., Tjandra, A. D., Zhou, Y., Gao, Y. & Chandrawati, R. (2023) Paper-based sensors for bacteria detection. Nature Reviews Bioengineering. 1 (3), 180-192. 10.1038/s44222-023-00024-w. Nai, Y. H., Doeven, E. H. & Guijt, R. M. (2022) An improved nucleic acid sequence-based amplification method mediated by T4 gene 32 protein. PloS One. 17 (3), e0265391. 10.1371/journal.pone.0265391. Pardee, K., Green, A. A., Ferrante, T., Cameron, D. E., DaleyKeyser, A., Yin, P. & Collins, J. J. (2014) Paper-Based Synthetic Gene Networks. Cell. 159 (4), 940-954. 10.1016/j.cell.2014.10.004. Takahashi, M. K., Tan, X., Dy, A. J., Braff, D., Akana, R. T., Furuta, Y., Donghia, N., Ananthakrishnan, A. & Collins, J. J. (2018) A low-cost paper-based synthetic biology platform for analyzing gut microbiota and host biomarkers. Nature Communications. 9 (1), 3347-12. 10.1038/s41467-018-05864-4. Wan, X. (2019) Synthetic biology enabled cellular and cell-free biosensors for environmental contaminants. The University of Edinburgh. Wang, C., Zeng, H., Liu, K., Lin, Y., Yang, H., Xie, X., Wei, D. & Ye, J. (2023) Biosensor-based therapy powered by synthetic biology. Smart Materials in Medicine. 4 212-224. 10.1016/j.smaim.2022.10.003. Zhang L, Guo W, Lu Y. Advances in Cell-Free Biosensors: Principle, Mechanism, and Applications. Biotechnol J. 2020 Sep;15(9):e2000187. doi: 10.1002/biot.202000187. Epub 2020 Jul 23. PMID: 32667120.

Introduction In this post we will be summarising multiple different articles looking at the biology of bacteriophages and their potential applications, with a focus on exploring what we can do to harness their potential. We will start by introducing the most common bacteriophages of the microbiome, and moving onto how these interact and manifest within the microbial communities of the skin, and then concluding with a discussion about whether we can harness them to develop technologies that can engineer the skin microbiome as a way to treat dermatological conditions that affect millions of people annually. We will primarily focus on the sebaceous (oily) sites of the skin such as the face, even though there are indeed a variety of other sites which are also important to consider when looking at phageomes and disease. The Virome To understand the role of bacteriophages, it is necessary to first look at defining the virome in relation to host health and microbiome ecology. The virome can be defined as ‘a subset of the core human microbiome consisting only of the viral biomass in a given community’. This applies to the skin also, which is colonised by numerous groups of viruses with their own ecology and interactions. It includes many different classes of virus, the three most common being Eukaryotic DNA viruses, Viral Genetic Elements and Bacteriophages (Phages) (Virgin, 2014). Virome composition is shaped by a variety of forces, both ecological and evolutionary. Some studies have found that the skin microenvironment, including physical properties (e.g. whether the skin is dry, moist or sebaceous) which appear to be a key driving force behind viral community dynamics (Byrd et al., 2018), with viral blooms appearing in specific sites along the skin including sebaceous regions of the face such the cheeks and the forehead (Oh et al., 2016). Other factors which might impact a person’s microbial community include geography such as pollution levels and UV exposure, in addition to lifestyle factors such as diet, health and personal care. However, it is important to note here that no core DNA virome has yet been found to exist, with lots of individual variation in virome composition. This could be due to a number of different factors, including biogeography of the skin, ethnicity, genetics, parental imprinting and transmission between and across populations (Byrd et al., 2018). Individual variation of the types of virus found in humans presents a possible future avenue of study to further explore why and how this is the case, and furthermore whether it has any key implications for individual differences in skin conditions. The Phageome Despite this lack of a cohesive virome in the human population, there does appear to be a subset of this community which possesses a more concerted signature than its larger counterpart. This is where the phageome comes in. The phageome refers to the net biomass of bacteriophages found within the human microbiome (Townsend et al., 2021). It differs from the virome in that it has been found to possess a conserved signature across human populations, despite any interspecific differences which may exist within the microbiome as a whole, therefore indicating the possibility of a shared core phageome existing (Oh et al., 2016). Bacteriophages fall under the umbrella of the phageome, and are described as ‘viruses which are capable of infecting and/or killing bacteria’ (Castillo et al., 2018). In the case of most humans, the bacteria on the skin microbiome are primarily infected by two core groups of phages found across sebaceous sites of the skin; Cutibacterium phages and Staphylococcus phages. These phages can be found across sebaceous areas of the face, usually with a single strain of phages dominating these sites. Like other phages, their populations tend to remain largely stable within their microenvironments compared to the transient eukaryotic DNA viruses, which suggests a level of fixation within their bacterial-host population (Oh et al., 2016). In regards to the types of interactions which manifest between bacteriophages and their respective host, these can vary depending on the evolutionary adaptations to the host species they decide to colonise (Hannigan et al., 2015). Interactions usually range from lysogenic, to pseudolysogenic, or purely lytic. Lysogenic phages integrate into the host genome as a prophage and continue to propagate in this form as the host replicates and divides, meaning that their fitness is ultimately linked to the survival of their bacterial host. On the other hand, pseudolysogenic phages can alternate between the two extremes, existing as prophages until they are exposed to environmental stress at which point they are excised and circularised to enter the lytic stage. Finally, the lytic viruses are a group which infect and kill the host while using them as a medium of replication, these types may go onto wipe out large populations of bacteria within a community causing dysbiosis that affect the human host, or in some cases having the opposite effect of preventing pathogenic bacterial species from propagating in the microbiome. C. acnes and The Skin C. acnes phages is a subset of Cutibacteria-infecting phages which colonise sebaceous areas of the body, such as the face, with most individuals possessing a single strain of this phage within the skin microbiome (Castillo et al., 2018). C. acnes phages, like many other Cutibacteria-infecting species, tend to be lacking in genetic diversity, with between 85 - 100% sequence identity observed between strains (Liu et al., 2015). Its presence is usually found associated with that of its target bacterial species, C. acnes, with which they form antagonistic interactions, going on to have a reductive effect on bacterial abundance and population size (Oh et al., 2016). Such antagonistic dynamics have played a role in modulating the position of the microbiome through the selective removal of certain C. acnes populations. However, the population sizes of some C. acnes have been found to positively correlate with phage prevalence, this indicates a certain amount of variability of the type of interaction which manifests between the two partners (Oh et al., 2016). These phages tend to assume a mostly lytic state, going onto infect and lyse their target host cells and effectively reduce the population size of  C. acnes species within the microbial community. However, some have been observed to have the ability to adopt a pseudolysogenic state. This shows that the type of bacteriophage that manifests is largely constrained by C. acnes lineage (Liu et al., 2015). This level of flexibility in C. acnes phage lifestyle could have evolved in order to enhance phage survival, but no comprehensive explanation has yet been uncovered for this. The overpopulation of certain C. acnes strains is associated with skin conditions such as acne. C. acnes phages are capable of lysing and destroying C. acnes strains from most lineages including pathogenic strains which can have the effect of reducing the relative abundance of C. acnes in the host microbiome by shifting the skin microbiome away from acne-associated dysbiosis (Liu et al., 2015). Additionally, C. acnes phages are more abundant in the facial skin samples of the individuals with healthy, non-acne infected skin, indicating the regulatory function of these phages in preventing proliferation of pathogenic C. acnes strains associated with the onset of acne (Liu et al., 2015). These findings suggest a link between phage abundance and the development of acne, and the role of these bacteriophages in regulating microbiome balance. S. aureus Phages and The Skin Staphylococcus aureus phages form interaction with Staphylococcus aureus strains of bacteria that are also highly abundant within the microbiome of sebaceous skin sites. These bacteria have been associated with the onset of many skin diseases, such as atopic dermatitis and psoriasis (Natarelli et al., 2023). Infection of these S. aureus strains by phages has also recently been linked as another potential risk factor in increasing the virulence of these bacterial strains, with phages helping to facilitate transmission of antibiotic resistant genes and virulence factors to these bacteria from other host reservoirs that harbour these genetic elements such as S. epidermidis (Hannigan et al., 2017). This allows these bacteria to fortify their defences against the human immune system, and cause disorders associated with the skin or in some cases even increase severity of skin-disorders. Many of these lysogenic S. aureus phages carry virulence factors that upon integration into the host genome can confer fitness benefits such as host propagation and survival. They can also carry many genes that might add to this fitness or cause genomic rearrangements that enhance the pathogenicity and virulence of S. aureus strains, going onto improve host fitness and survival and worsening the severity of certain skin conditions as these bacteria grow (Hannigan et al., 2017). The effects of this lysogeny on human skin has to some extent been associated with atopic dermatitis, with greater abundances of S. aureus being detected in patients possessing these lesions (Bjerre et al., 2021). Potential Applications of Phages We will now go on to explore the potential applications of these phages, and discuss technologies that have been devised to harness the power of some bacteriophages in the treatment of skin conditions such as acne or atopic dermatitis. It is important to note that suitable candidates for phage therapy must be lytic, non-lysogenic, and free of virulence factors and antibiotic resistant genes in order to properly target these problem strains without transferring virulence factors or genetic elements that might cause the bacteria being targeted more infectious (Kim et al., 2022). Acne and C. acnes phage therapy In the case of acne it is increased sebum production that can induce the growth of pathogenic C. acnes strains and this overgrowth is what might exacerbate the conditions and drive inflammation across the skin and bring about global effects (Natarelli et al., 2023). The overpopulation of these strains can go on to trigger dysbiosis by further reducing the already low levels of microbiome diversity, including wiping out other C. acnes populations regardless of whether they are commensal or pathogenic. This phenomenon suggests that acne might have less to do with increasing pathogenic C. acnes strain abundance, but rather it is the loss of C. acnes phylotype diversity in the microbiome (Mias et al., 2023). Certain C. acnes strains have been found to be more strongly associated with acne pathogenesis, while others are associated with healthy skin microbiome composition, this indicates that certain C. acnes phages can be used to target C. acnes bacterial population types associated with acne allowing the selective suppression of bacterial growth while still maintaining commensal or beneficial strain population structure (Fitz-Gibbon et al., 2013; Liu et al., 2015). Personalised phage therapies might also be developed to target particular strains of C. acnes present in the skin microbiome depending on individual bacterial community structure, in order to restore dysbiotic skin. Resistant C. acnes strains might require some more engineering of phages to be able to overcome host immune mechanisms and anti-virulence factors. However, preliminary studies attempting to treat pathogenic C. acnes strains with specific bacteriophages have already shown some promising results (Xuan et al., 2023), with near total population reduction upon application of these phages (Kim et al., 2019). Therefore, showing the potential to treat, or at least minimise, the effects of acne. Atopic dermatitis and S. aureus phage therapy In the case of atopic dermatitis, disease can also be brought about by dysbiosis of the skin microbiome. An overabundance of S. aureus populations relative to other species can trigger atopic dermatitis, by causing immune dysregulation and impairing the skin barrier function which leads to inflammation and flaking of the skin which is characteristic of this condition (Tham et al., 2020). The symptoms of AD can be worsened through the acquisition of virulence genes from bacteria that increase S. aureus strains pathogenicity. While some strains of phage support and promote the survival of S. aureus, a variety of other groups have been proven to have powerful anti S. aureus agents with several cases reporting complete eradication of S. aureus and/or patient improvement upon administration of these phage strains (Hatoum-Aslan, 2021). Many of these phages have small genomes which are too compact to support the integration of virulence-associated genes that can be transferred between the microbiome during transduction, thus eliminating the risk of increasing pathogenicity or inducing mutations. These can be engineered to express antibacterial compounds in their genomes that have the effect of destroying the infected cell upon expression (Hatoum-Aslan, 2021). Other studies have also demonstrated the effect of phage derived compounds against AD, showing the potential of specific S. aureus phages in combating these AD associated bacterial strains (Tham et al., 2020). The Potential of Phage Therapy Acne and atopic dermatitis industries in the US alone are worth $2.5 billion (Castillo et al., 2018) and $5 billion (Adamson, 2017) respectively, with treatments often being costly and difficult to develop. These conditions present a fresh, untapped market in which phage therapies can enter. Phage therapies can offer an alternative to traditional methods of treatment of bacterial infections requiring the use of antibiotics. This is especially important when considering the global burden of antibiotic resistance and the rising numbers of resistance annually observed, and demonstrates how antibiotics are not a sustainable method of treating many bacterial infections. These phages can be made to target bacteria that have developed some level of multidrug resistance, which presents the potential of them also reducing antibiotic resistance in a population and making the administration of antibiotics all the more effective (McCutcheon et al., 2020). Unlike traditional medicines, bacteriophage therapy is able to treat diseases in a target specific manner, without harming other components of the microbiome or human host. They are also easier and less expensive to produce en masse (Jończyk-Matysiak et al., 2017), therefore they are practical, economically feasible and able to cover a large area of the skincare market. Most importantly, as a natural part of the human microflora, they are safe and well tolerated with no adverse effects of their administration being reported as of yet (Castillo et al., 2018). Future Perspectives Phage therapy, as with all budding technologies, still has a considerably long way to go before it can become a conventional treatment for dermatological conditions. More research on the interactions between bacteriophages and the skin microbiome must be conducted to investigate any global effects which might be observed upon removal of any particular bacteria subpopulation, particularly as this is something which might have adverse effects that we are currently unaware of (Castillo et al., 2018). It will also help us get a better understanding of the extent to which these phages produce such bactericidal in regulatory effects on the microbiome. This will also help to identify the right phages in targeted treatment. Despite impressive findings surrounding the effectiveness of phages in removing disease-associated micropopulations, none of these involve the use of human models as a basis of study. Indeed, the conduction of more human trials are necessary before this field can expand and move forward towards being released to the market (Jończyk-Matysiak et al., 2017; Castillo et al., 2018). Caution must also be exercised when taking phage species which express a certain level of lysogeny within their strains, such as those strains targeting S. aureus. These lysogenic phages can have the opposite effect of reinforcing pathogenic bacteria, rather than having the desired effect of destroying them (Jończyk-Matysiak et al., 2017). The long term impact of population wide eradication on the microbiome health and ecology is not yet fully understood or characterised. This ultimately means we must proceed with caution moving forward. However, many remain optimistic that this technology will move forward to have transformative effects on the skin and healthcare industry, presenting an exciting new avenue for disease to be targeted and treated more efficiently than ever before. Improvements in technology and recent advances in our understanding of phage biology have certainly made it more likely for these expectations to one day become a reality. References Adamson, A. S. Adv Exp Med Biol 1027, 79–92 (2017) Bjerre, R. D. et al. BMC Microbiology 21, 256 (2021) Byrd, A. L. et al. Nat Rev Microbiol 16, 143–155 (2018) Castillo, D. E. et al. Dermatol Ther (Heidelb) 9, 19–31 (2018) Cheng, L. et al. BMC Microbiology 18, 19 (2018) Fitz-Gibbon, S. et al. J Invest Dermatol 133, 2152–2160 (2013) Hannigan, G. D. et al. PeerJ 5, e2959 (2017) Hatoum-Aslan, A. Trends in Microbiology 29, 1117–1129 (2021) Jończyk-Matysiak, E. et al. Front Microbiol 8, 164 (2017) Kim, S. et al. Antibiotics (Basel) 11, 1041 (2022) Liu, J. et al. ISME J 9, 2078–2093 (2015) McCutcheon, J. G. et al. International Journal of Molecular Sciences 21, 6338 (2020) Mias, C. et al. Journal of the European Academy of Dermatology and Venereology 37, 3–11 (2023) 15 Natarelli, N. et al. International Journal of Molecular Sciences 24, 2695 (2023) Oh, J. et al. Cell 165, 854–866 (2016) Tham, E. H. et al. Biotechnology Journal 15, 1900322 (2020) Townsend, E. M. et al. Frontiers in Cellular and Infection Microbiology 11, (2021) Virgin, H. W. Cell 157, 142–150 (2014) Xuan, G. et al. Microbial Pathogenesis 180, 106111 (2023)

Introduction The microbiome is an organic ecosystem of trillions of bacteria that live and interact with one another on and within our bodies (Berg et al., 2020). In recent years, more research has been carried out suggesting that the microbiome plays a critical role in our overall well-being, including our gut and skin health (Human Microbiome Project Consortium, 2012). It is widely accepted that every individual’s microbiome is unique, influenced by factors such as sex, age, physical health, lifestyle and environmental factors. However, recent research has emerged which begs the question: is the microbiome influenced by one's genetic makeup or rather by environmental factors? To answer this question, we look at a study conducted on twins to explore how their overlapping and diverse microbial communities give clues about what influences shape our microbiome. Due to limited research on twin skin microbiomes, we will rely on studies conducted predominantly on the gut and some on the oral microbiome. Defining Twins To better unearth the relationship between twin microbiomes, it is crucial to understand that not all twins are made alike. Identical twins (monozygotic) share the same DNA sequences, allowing us to better differentiate what elements of the microbiome are linked to genetics and which are influenced by environmental factors. On the other hand, fraternal twins (dizygotic) share about 50% of their DNA. Analysing genetically identical and fraternal twins can allow us to identify the environmental and genetic effects on their microbiome (Martin et al.,1997). Genetic Influence on Microbial Composition in the Gut A study (Goodrich et al., 2016) conducted 16S rRNA analysis on the gut microbiomes of approximately 1,126 twins in the United Kingdom. The results showed that the presence of specific genetic variants in the LCT (Lactase) gene locus was associated with relative abundances of the heritable genus Bifidobacterium. It is understood that Bifidobacterium metabolises lactose resulting in individuals exhibiting higher levels of Bifidobacterium if they are unable to produce enough Lactase (Goodrich et al., 2016). Another study conducted in Missouri, focused on four pairs of female adolescent twins (1 monozygotic and 3 dizygotic pairs). Within each pair, there was significant variability in weights, with one having lower body fat percentages and the other having higher levels. For the purpose of the study, fecal samples were collected from each participant and transplanted into healthy mice. The results of this study showed that the microbiota from the twins with a lower body fat percentage was better at breaking down and fermenting polysaccharides (carbs formed of sugar molecules) than the microbiota of the twins with higher body fat percentages. It was also found that mice who were transplanted with the microbiota of the twins with lower body fat percentage demonstrated protection from obesity phenotype (Ridaura et al, 2013). Genetic Influence on Microbial Composition in the Oral Cavity A study published under the name “Longitudinal Study of Oral Microbiome Variation in Twins” in 2020 evaluated the genetic and environmental factors attributed to oral caries (cavities) in both monozygotic and dizygotic twins. Dental plaque samples were extracted and analysed through 16S rRNA. It was noticed that changes in the oral microbiome were strongly influenced by the environment when compared to participant’s genetics. Other elements driving changes in the oral microbiome of twins was their age, the age at which they started brushing their teeth and their actions after brushing. The study identified the relevance of heritability on the microbiome by way of Capnocytophaga and Actinomyces in monozygotic twins, and Kingella within dizygotic twins. Certain bacteria were more associated with ageing: Veillonella and Corynebacterium. On the other hand, younger subjects were associated with Aggregatibacter. Streptococcus was found to decrease over time and Selenomonas increased with more frequent brushing per day (Freire et al., 2020). It was reported that unearthing the true biological mechanisms behind caries could unlock the potential to understand biomarkers and pathways that could help with prevention in early ears. However, further research needed to be carried out to reduce this knowledge gap. Genetic Influence and the Skin Microbiome Finally, another study conducted in Korea in 2015 evaluated the relationship between genetic and environmental factors on the skin microbiome of twins (Si et al, 2015). Results from Genetic associations and shared environmental effects on the skin microbiome of Korean twins (Si et al, 2015) Participants: The study in question included 45 subjects with 16 monozygotic twins, 8 dizygotic twins between the ages of 26 to 55, as well as their mothers and an additional 5 unrelated subjects. In 32 subjects (mothers and twins), skin traits such as pigmentation and skin humidity were measured. Sample collection: skin swabs were taken from each subject from the upper right arm to reduce variations due to external factors such as different personal care routines and varying cosmetic usage. Extraction: The entirety of the microbial DNA was extracted from the samples and the V2 and V3 regions of 16S rRNA genes and pyro-sequenced. Analysis: The 16S rRNA sequencing results were then analysed through Bioinformatics. Results from Genetic associations and shared environmental effects on the skin microbiome of Korean twins (Si et al, 2015) The results of this study demonstrated that Propionibacterium (now referred to as Cutibacterium), Staphylococcus and Streptococcus were the richest skin microbiota on a genus level, however as expected there was some variability amongst individuals. It was found that skin pigmentation has a significant impact on the skin bacteria with medium-skinned individuals having an increased microbial diversity. The results also showed that the highest similarities in skin microbiota existed between monozygotic twins followed by dizygotic twins and finally between mothers and twins. Furthermore, a negative correlation was found with an abundance of C. jeikeium and the allele T, which is a single polymorphism nucleotide (SNP) localised to a gene that plays a significant role in skin barrier function (filaggrin). From past research, we know that defects in filaggrin can be known to result in allergic skin conditions such as ichthyosis vulgaris and atopic eczema, both linked to excessive dryness of the skin (McAleer et al, 2013). This leads us to the conclusion that there might be a link between filaggrin processing and bacteria leading to pathogenesis (when an infection turns into a disease). To conclude the findings of this study on twin pairs, it was proven that both genetics and environmental factors can shape the skin microbiome (we saw this with pigmentation). A strong correlation between C. jeikeium from the skin microbiota and human genetic factors allele T was also found in relation to skin barrier function (Si et al, 2015). Next Steps Further research is needed in order to build on this study conducted in 2015. The question of whether the microbiome is influenced predominantly by genetics or environmental factors plays a crucial role into how we address the skin microbiome and the diseases that have been found to be linked to its disbalance. A significant next step to the work published above would be to include higher resolution taxonomic profiling, quantifying differences at species and strain level between identical twins would be of much importance. If you are interested in carrying out any research with us in studying the differences between identical twins’ microbiome, or you have questions about our testing platform for your own clinical studies - you can reach us through www.sequential.bio Lexicon Dizygotic: fraternal twins who are simply as alike as any other siblings, occurring when two eggs are released at a single ovulation and are fertilised by two different sperm. Microbiome: The microbiome is a characteristic microbial community occupying a reasonably well-defined habitat which has distinct physio-chemical properties. The microbiome not only refers to the microorganisms involved but also encompasses their theatre of activity, which results in the formation of specific ecological niches. This includes their genetic material, and also structural molecules, like enzymes, membrane lipids or polysaccharides (Definition based on Berg et al., 2020). Monozygotic: identical twins who develop when one egg is fertilised by a single sperm and then during the first two weeks of conception the developing embryo splits into two, causing two genetically identical babies to develop. Polysaccharides: Carbs formed of sugar molecules. Pathogenesis: The process by which an infection deteriorates into a disease. References Freire, M., Moustafa, A., Harkins, D.M. et al. Longitudinal Study of Oral Microbiome Variation in Twins. Sci Rep 10, 7954 (2020). https://doi.org/10.1038/s41598-020-64747-1 Martin, N., Boomsma, D. & Machin, G. A twin-pronged attack on complex traits. Nat Genet 17, 387-392, doi:10.1038/ng1297-387 (1997). Human Microbiome Project Consortium. (2012). Structure, function, and diversity of the healthy human microbiome. Nature, 486(7402), 207-214. Goodrich, J. K. et al. Genetic Determinants of the Gut Microbiome in UK Twins. Cell Host Microbe 19, 731-743, doi:10.1016/j.chom.2016.04.017 (2016). Ridaura, V. K. et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science 341, 1241214, doi:10.1126/science.1241214 (2013). Si, J., Lee, S., Park, J. M., Sung, J. & Ko, G. Genetic associations and shared environmental effects on the skin microbiome of Korean twins. BMC Genomics 16, 992, doi:10.1186/s12864-015-2131-y (2015). McAleer, M. A. & Irvine, A. D. The multifunctional role of filaggrin in allergic skin disease. J Allergy Clin Immunol 131, 280-291, doi:10.1016/j.jaci.2012.12.668 (2013).