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microbiome</title> <meta name="description" content="Search results for: microbiome"> <meta name="keywords" content="microbiome"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="microbiome"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 90</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: microbiome</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">90</span> Metagenomics, Urinary Microbiome, and Chronic Prostatitis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elmira%20Davasaz%20Tabrizi">Elmira Davasaz Tabrizi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mushteba%20Sevil"> Mushteba Sevil</a>, <a href="https://publications.waset.org/abstracts/search?q=Ercan%20Arican"> Ercan Arican</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Directly or indirectly, the human microbiome, or the population of bacteria and other microorganisms living in the human body, has been linked with human health. Various research has examined the connection with both illness status and the composition of the human microbiome, even though current studies indicate that the gut microbiome influences the mucosa and immune system. A significant amount of effort is being put into understanding the human microbiome's natural history in terms of health outcomes while also expanding our comprehension of the molecular connections between the microbiome and the host. To maintain health and avoid disease, these efforts ultimately seek to find efficient methods for recovering human microbial communities. This review article describes how the human microbiome leads to chronic diseases and discusses evidence for an important significant disorder that is related to the microbiome and linked to prostate cancer: chronic prostatitis (CP). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=urobiome" title="urobiome">urobiome</a>, <a href="https://publications.waset.org/abstracts/search?q=chronic%20prostatitis" title=" chronic prostatitis"> chronic prostatitis</a>, <a href="https://publications.waset.org/abstracts/search?q=metagenomic" title=" metagenomic"> metagenomic</a>, <a href="https://publications.waset.org/abstracts/search?q=urinary%20microbiome" title=" urinary microbiome"> urinary microbiome</a> </p> <a href="https://publications.waset.org/abstracts/159463/metagenomics-urinary-microbiome-and-chronic-prostatitis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159463.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">89</span> Liquid Biopsy Based Microbial Biomarker in Coronary Artery Disease Diagnosis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eyup%20Ozkan">Eyup Ozkan</a>, <a href="https://publications.waset.org/abstracts/search?q=Ozkan%20U.%20Nalbantoglu"> Ozkan U. Nalbantoglu</a>, <a href="https://publications.waset.org/abstracts/search?q=Aycan%20Gundogdu"> Aycan Gundogdu</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehmet%20Hora"> Mehmet Hora</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Emre%20Onuk"> A. Emre Onuk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The human microbiome has been associated with cardiological conditions and this relationship is becoming to be defined beyond the gastrointestinal track. In this study, we investigate the alteration in circulatory microbiota in the context of Coronary Artery Disease (CAD). We received circulatory blood samples from suspected CAD patients and maintain 16S ribosomal RNA sequencing to identify each patient’s microbiome. It was found that Corynebacterium and Methanobacteria genera show statistically significant differences between healthy and CAD patients. The overall biodiversities between the groups were observed to be different revealed by machine learning classification models. We also achieve and demonstrate the performance of a diagnostic method using circulatory blood microbiome-based estimation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=coronary%20artery%20disease" title="coronary artery disease">coronary artery disease</a>, <a href="https://publications.waset.org/abstracts/search?q=blood%20microbiome" title=" blood microbiome"> blood microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=angiography" title=" angiography"> angiography</a>, <a href="https://publications.waset.org/abstracts/search?q=next-generation%20sequencing" title=" next-generation sequencing"> next-generation sequencing</a> </p> <a href="https://publications.waset.org/abstracts/144219/liquid-biopsy-based-microbial-biomarker-in-coronary-artery-disease-diagnosis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144219.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">156</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">88</span> Microbiome Role in Tumor Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chro%20Kavian">Chro Kavian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The studies conducted show that cancer is a disease caused by populations of microbes, a notion gaining traction as the interaction between the human microbiome and the tumor microenvironment (TME) increasingly shows how environment and microbes dictate the progress and treatment of neoplastic diseases. A person’s human microbiome is defined as a collection of bacteria, fungi, viruses, and other microorganisms whose structure and composition influence biological processes like immune system modulation and nutrient metabolism, which, in turn, affect how susceptible a person is to neoplastic diseases, and response to different therapies. Recent reports demonstrated the influence specific microbiome bacterial populations have on the TME, thereby altering tumoral behaviors and the TME’s contributing factors that impact patients' lives. In addition, gut microbes and their SCFA products are important determinants of the inflammatory landscape of tumors and augment anti-tumor immunity, which can influence immunotherapy outcomes. Studies have also found that dysbiosis, or microbial imbalance, correlates with biological processes such as cancer progression, metastasis, and therapy resistance, leading scientists to explore the use of microbiome deficiencies as adjunctive approaches to chemotherapy and other, more traditional treatments. Nonetheless, mental health practitioners struggling to comprehend the existent gap between cancer patients with pronounced resolutive capabilities and the profound clinical impact Microbiome-targeted cancer therapy has been proven to possess. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microbiome" title="microbiome">microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=cancer" title=" cancer"> cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=tumor" title=" tumor"> tumor</a>, <a href="https://publications.waset.org/abstracts/search?q=immune%20system" title=" immune system"> immune system</a> </p> <a href="https://publications.waset.org/abstracts/193827/microbiome-role-in-tumor-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193827.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">18</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">87</span> The Metaproteomic Analysis of HIV Uninfected Exposed Infants’ Gut Microbiome to Help Understand Their Poor Health Statuses in An African Cohort</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tara%20Miller">Tara Miller</a>, <a href="https://publications.waset.org/abstracts/search?q=Tariq%20Ganief"> Tariq Ganief</a>, <a href="https://publications.waset.org/abstracts/search?q=Jonathan%20Blackburn"> Jonathan Blackburn</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Millions of babies are still born to HIV-infected mothers each year despite the ramped-up HAART use. However, these infants are HIV uninfected but exposed, which is now a growing population that has weakened immune systems and poorer outcomes. Due to HIV exposure and possible ARV exposure during pregnancy and breastfeeding, these infants are believed to have altered immune responses and microbiomes when compared to their healthy counterparts. The gut microbiome roles an important role in infant development, specifically in the immune system. Research has shown these HIV-exposed, uninfected infants have weaker immune responses to their neonate vaccines, and in developing countries, this leaves them vulnerable to opportunistic disease. By gaining a deeper understanding of the gut microbiome and the products of the microbes via metaproteomic analysis, we can hopefully understand and improve the immune system and health of these infants. To investigate the metaproteome of the infants’ guts, mass spectrometry will be used, followed by data analysis using DIA-NN. The hypothesized results are that the HIV-exposed, uninfected infants have an altered microbiome compared to their healthy counterparts. Additionally, the differences found are hypothesized to be involved with inflammation which would contribute to the poor health of the infants. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HIV" title="HIV">HIV</a>, <a href="https://publications.waset.org/abstracts/search?q=mass%20spectrometry" title=" mass spectrometry"> mass spectrometry</a>, <a href="https://publications.waset.org/abstracts/search?q=metaproteomics" title=" metaproteomics"> metaproteomics</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a> </p> <a href="https://publications.waset.org/abstracts/159308/the-metaproteomic-analysis-of-hiv-uninfected-exposed-infants-gut-microbiome-to-help-understand-their-poor-health-statuses-in-an-african-cohort" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159308.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">91</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">86</span> The Comparison Study of Human Microbiome in Chronic Rhinosinusitis between Adults and Children</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Il%20Ho%20Park">Il Ho Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Joong%20Seob%20Lee"> Joong Seob Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung%20Hun%20Kang"> Sung Hun Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jae-Min%20Shin"> Jae-Min Shin</a>, <a href="https://publications.waset.org/abstracts/search?q=Il%20Seok%20Park"> Il Seok Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Seok%20Min%20Hong"> Seok Min Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Seok%20Jin%20Hong"> Seok Jin Hong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: The human microbiota is the aggregate of microorganisms, and the bacterial microbiome of the human digestive tract contributes to both health and disease. In health, bacteria are key components in the development of mucosal barrier function and in innate and adaptive immune responses, and they also work to suppress the establishment of pathogens. In human upper airway, the sinonasal microbiota might play an important role in chronic rhinosinusitis (CRS). The purpose of this study is to investigate the human upper airway microbiome in CRS patients and to compare the sinonasal microbiome of adults with children. Materials and methods: A total of 19 samples from 19 patients (Group1; 9 CRS in children, aged 5 to 14 years versus Group 2; 10 CRS in adults aged 21 to 59 years) were examined. Swabs were collected from the middle meatus and/or anterior ethmoid region under general anesthesia during endoscopic sinus surgery or tonsillectomy. After DNA extraction from swab samples, we analysed bacterial microbiome consortia using 16s rRNA gene sequencing approach (the Illumina MiSeq platform). Results: In this study, relatively abundance of the six bacterial phyla and tremendous genus and species found in substantial amounts in the individual sinus swab samples, include Corynebacterium, Hemophilus, Moraxella, and Streptococcus species. Anaerobes like Fusobacterium and Bacteroides were abundantly present in the children group, Bacteroides and Propionibacterium were present in adults group. In genus, Haemophilus was the most common CRS microbiome in children and Corynebacterium was the most common CRS microbiome in adults. Conclusions: Our results show the diversity of human upper airway microbiome, and the findings will suggest that CRS is a polymicrobial infection. The Corynebacterium and Hemophilus may live as commensals on mucosal surfaces of sinus in the upper respiratory tract. The further study will be needed for analysis of microbiome-human interactions in upper airway and CRS. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microbiome" title="microbiome">microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=upper%20airway" title=" upper airway"> upper airway</a>, <a href="https://publications.waset.org/abstracts/search?q=chronic%20rhinosinusitis" title=" chronic rhinosinusitis"> chronic rhinosinusitis</a>, <a href="https://publications.waset.org/abstracts/search?q=adult%20and%20children" title=" adult and children"> adult and children</a> </p> <a href="https://publications.waset.org/abstracts/101447/the-comparison-study-of-human-microbiome-in-chronic-rhinosinusitis-between-adults-and-children" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101447.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">126</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">85</span> A Study of Fecal Sludge Management in Auroville and Its Surrounding Villages in Tamilnadu, India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Preethi%20Grace%20Theva%20Neethi%20Dhas">Preethi Grace Theva Neethi Dhas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A healthy human gut microbiome has commensal and symbiotic functions in digestion and is a decisive factor for human health. The soil microbiome is a crucial component in the ecosystem of soils and their health and resilience. Changes in soil microbiome are linked to human health. Ever since the industrial era, the human and the soil microbiome have been going through drastic changes. The soil microbiome has changed due to industrialization and extensive agricultural practices, whereas humans have less contact with soil and increased intake of highly processed foods, leading to changes in the human gut microbiome. Regenerating the soil becomes crucial in maintaining a healthy ecosystem. The nutrients, once obtained from the soil, need to be given back to the soil. Soil degradation needs to be addressed in effective ways, like adding organic nutrients back to the soil. Manure from animals and humans needs to be returned to the soil, which can complete the nutrient cycle in the soil. On the other hand, fecal sludge management (FSM) is a growing concern in many parts of the developing world. Hence, it becomes crucial to treat and reuse fecal sludge in a safe manner, i.e., low in risk to human health. Co-composting fecal sludge with organic wastes is a practice that allows the safe management of fecal sludge and the safe application of nutrients to the soil. This paper will discuss the possible impact of co-composting fecal sludge with coconut choir waste on the soil, water, and ecosystem at large. Impact parameters like nitrogen, phosphorus, and fecal coliforms will be analyzed. The overall impact of fecal sludge application on the soil will be researched and presented in this study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fecal%20sludge%20management" title="fecal sludge management">fecal sludge management</a>, <a href="https://publications.waset.org/abstracts/search?q=nutrient%20cycle" title=" nutrient cycle"> nutrient cycle</a>, <a href="https://publications.waset.org/abstracts/search?q=soil%20health" title=" soil health"> soil health</a>, <a href="https://publications.waset.org/abstracts/search?q=composting" title=" composting"> composting</a> </p> <a href="https://publications.waset.org/abstracts/175735/a-study-of-fecal-sludge-management-in-auroville-and-its-surrounding-villages-in-tamilnadu-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175735.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">74</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">84</span> Remodeling of Gut Microbiome of Pakistani Expats in China After Intermittent Fasting/Ramadan Fasting</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hafiz%20Arbab%20Sakandar">Hafiz Arbab Sakandar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Time-restricted intermittent fasting (TRIF) impacts host’s physiology and health. Plenty of health benefits have been reported for TRIF in animal models. However, limited studies have been conducted on humans especially in underdeveloped economies. Here, we designed a study to investigate the impact of TRIF/Ramadan fasting (16:8) on the modulation of gut-microbiome structure, metabolic pathways, and predicted metabolites and explored the correlation among them at different time points (during and after the month of Ramadan) in Pakistani Expats living in China. We observed different trends of Shannon-Wiener index in different subjects; however, all subjects showed substantial change in bacterial diversity with the progression of TRIF. Moreover, the changes in gut microbial structure by the end of TRIF were higher vis-a-vis in the beginning, significant difference was observed among individuals. Additionally, metabolic pathways analysis revealed that amino acid, carbohydrate and energy metabolism, glycan biosynthesis metabolism of cofactors and vitamins were significantly affected by TRIF. Pyridoxamine, glutamate, citrulline, arachidonic acid, and short chain fatty acid showed substantial difference at different time points based on the predicted metabolism. In conclusion, these results contribute to further our understanding about the key relationship among, dietary intervention (TRIF), gut microbiome structure and function. The preliminary results from study demonstrate significant potential for elucidating the mechanisms underlying gut microbiome stability and enhancing the effectiveness of microbiome-tailored interventions among the Pakistani populace. Nonetheless, extensive, and rigorous large-scale research on the Pakistani population is necessary to expound on the association between diet, gut microbiome, and overall health. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gut%20microbiome" title="gut microbiome">gut microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=health" title=" health"> health</a>, <a href="https://publications.waset.org/abstracts/search?q=fasting" title=" fasting"> fasting</a>, <a href="https://publications.waset.org/abstracts/search?q=functionality" title=" functionality"> functionality</a> </p> <a href="https://publications.waset.org/abstracts/169806/remodeling-of-gut-microbiome-of-pakistani-expats-in-china-after-intermittent-fastingramadan-fasting" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169806.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">75</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">83</span> Foodborne Pathogens in Different Types of Milk: From the Microbiome to Risk Assessment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pasquali%20Frederique">Pasquali Frederique</a>, <a href="https://publications.waset.org/abstracts/search?q=Manfreda%20Chiara"> Manfreda Chiara</a>, <a href="https://publications.waset.org/abstracts/search?q=Crippa%20Cecilia"> Crippa Cecilia</a>, <a href="https://publications.waset.org/abstracts/search?q=Indio%20Valentina"> Indio Valentina</a>, <a href="https://publications.waset.org/abstracts/search?q=Ianieri%20Adriana"> Ianieri Adriana</a>, <a href="https://publications.waset.org/abstracts/search?q=De%20Cesare%20Alessandra"> De Cesare Alessandra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Microbiological hazards can be transmitted to humans through milk. In this study, we compared the microbiome composition and presence of foodborne pathogens in organic milk (n=6), organic hay milk (n=6), standard milk (n=6) and high-quality milk (n=6). The milk samples were collected during six samplings between December 2022 to January 2023 and between April and May 2024 to take into account seasonal variations. The 24 milk samples were submitted to DNA extraction and library preparation before shotgun sequencing on the Illumina HiScan™ SQ System platform. The total sequencing output was 600 GB. In all the milk samples, the phyla with the highest relative abundances were Pseudomonadota, Bacillota, Ascomycota, Actinomycetota and Apicomplexa, while the most represented genera were Pseudomonas, Streptococcus, Geotrichum, Acinetobacter and Babesia. The alpha and beta diversity indexes showed a clear separation between the microbiome of high-quality milk and those of the other milk types. Moreover, in the high-quality milk, the relative abundance of Staphylococcus (4.4%), Campylobacter (4.5%), Bacillus (2.5%), Enterococcus (2.4%), Klebsiella (1.3%) and Escherichia (0 .7%) was significantly higher in comparison to other types of milk. On the contrary, the relative abundance of Geotrichum (0.5%) was significantly lower. The microbiome results collected in this study showed significant differences in terms of the relative abundance of bacteria genera, including foodborne pathogen species. These results should be incorporated into risk assessment models tailored to different types of milk. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=raw%20milk" title="raw milk">raw milk</a>, <a href="https://publications.waset.org/abstracts/search?q=foodborne%20pathogens" title=" foodborne pathogens"> foodborne pathogens</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20assessment" title=" risk assessment"> risk assessment</a> </p> <a href="https://publications.waset.org/abstracts/188934/foodborne-pathogens-in-different-types-of-milk-from-the-microbiome-to-risk-assessment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/188934.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">25</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">82</span> Blood Microbiome in Different Metabolic Types of Obesity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Irina%20M.%20Kolesnikova">Irina M. Kolesnikova</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrey%20M.%20Gaponov"> Andrey M. Gaponov</a>, <a href="https://publications.waset.org/abstracts/search?q=Sergey%20A.%20Roumiantsev"> Sergey A. Roumiantsev</a>, <a href="https://publications.waset.org/abstracts/search?q=Tatiana%20V.%20Grigoryeva"> Tatiana V. Grigoryeva</a>, <a href="https://publications.waset.org/abstracts/search?q=Dilyara%20R.%20Khusnutdinova"> Dilyara R. Khusnutdinova</a>, <a href="https://publications.waset.org/abstracts/search?q=Dilyara%20R.%20Kamaldinova"> Dilyara R. Kamaldinova</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20V.%20Shestopalov"> Alexander V. Shestopalov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background. Obese patients have unequal risks of metabolic disorders. It is accepted to distinguish between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUHO). MUHO patients have a high risk of metabolic disorders, insulin resistance, and diabetes mellitus. Among the other things, the gut microbiota also contributes to the development of metabolic disorders in obesity. Obesity is accompanied by significant changes in the gut microbial community. In turn, bacterial translocation from the intestine is the basis for the blood microbiome formation. The aim was to study the features of the blood microbiome in patients with various metabolic types of obesity. Patients, materials, methods. The study included 116 healthy donors and 101 obese patients. Depending on the metabolic type of obesity, the obese patients were divided into subgroups with MHO (n=36) and MUHO (n=53). Quantitative and qualitative assessment of the blood microbiome was based on metagenomic analysis. Blood samples were used to isolate DNA and perform sequencing of the variable v3-v4 region of the 16S rRNA gene. Alpha diversity indices (Simpson index, Shannon index, Chao1 index, phylogenetic diversity, the number of observed operational taxonomic units) were calculated. Moreover, we compared taxa (phyla, classes, orders, and families) in terms of isolation frequency and the taxon share in the total bacterial DNA pool between different patient groups. Results. In patients with MHO, the characteristics of the alpha-diversity of the blood microbiome were like those of healthy donors. However, MUHO was associated with an increase in all diversity indices. The main phyla of the blood microbiome were Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. Cyanobacteria, TM7, Thermi, Verrucomicrobia, Chloroflexi, Acidobacteria, Planctomycetes, Gemmatimonadetes, and Tenericutes were found to be less significant phyla of the blood microbiome. Phyla Acidobacteria, TM7, and Verrucomicrobia were more often isolated in blood samples of patients with MUHO compared with healthy donors. Obese patients had a decrease in some taxonomic ranks (Bacilli, Caulobacteraceae, Barnesiellaceae, Rikenellaceae, Williamsiaceae). These changes appear to be related to the increased diversity of the blood microbiome observed in obesity. An increase of Lachnospiraceae, Succinivibrionaceae, Prevotellaceae, and S24-7 was noted for MUHO patients, which, apparently, is explained by a magnification in intestinal permeability. Conclusion. Blood microbiome differs in obese patients and healthy donors at class, order, and family levels. Moreover, the nature of the changes is determined by the metabolic type of obesity. MUHO linked to increased diversity of the blood microbiome. This appears to be due to increased microbial translocation from the intestine and non-intestinal sources. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blood%20microbiome" title="blood microbiome">blood microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=blood%20bacterial%20DNA" title=" blood bacterial DNA"> blood bacterial DNA</a>, <a href="https://publications.waset.org/abstracts/search?q=obesity" title=" obesity"> obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolically%20healthy%20obesity" title=" metabolically healthy obesity"> metabolically healthy obesity</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolically%20unhealthy%20obesity" title=" metabolically unhealthy obesity"> metabolically unhealthy obesity</a> </p> <a href="https://publications.waset.org/abstracts/145332/blood-microbiome-in-different-metabolic-types-of-obesity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145332.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">163</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">81</span> Insights into Archaeological Human Sample Microbiome Using 16S rRNA Gene Sequencing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alisa%20Kazarina">Alisa Kazarina</a>, <a href="https://publications.waset.org/abstracts/search?q=Guntis%20Gerhards"> Guntis Gerhards</a>, <a href="https://publications.waset.org/abstracts/search?q=Elina%20Petersone-Gordina"> Elina Petersone-Gordina</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilva%20Pole"> Ilva Pole</a>, <a href="https://publications.waset.org/abstracts/search?q=Viktorija%20Igumnova"> Viktorija Igumnova</a>, <a href="https://publications.waset.org/abstracts/search?q=Janis%20Kimsis"> Janis Kimsis</a>, <a href="https://publications.waset.org/abstracts/search?q=Valentina%20Capligina"> Valentina Capligina</a>, <a href="https://publications.waset.org/abstracts/search?q=Renate%20Ranka"> Renate Ranka</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Human body is inhabited by a vast number of microorganisms, collectively known as the human microbiome, and there is a tremendous interest in evolutionary changes in human microbial ecology, diversity and function. The field of paleomicrobiology, study of ancient human microbiome, is powered by modern techniques of Next Generation Sequencing (NGS), which allows extracting microbial genomic data directly from archaeological sample of interest. One of the major techniques is 16S rRNA gene sequencing, by which certain 16S rRNA gene hypervariable regions are being amplified and sequenced. However, some limitations of this method exist including the taxonomic precision and efficacy of different regions used. The aim of this study was to evaluate the phylogenetic sensitivity of different 16S rRNA gene hypervariable regions for microbiome studies in the archaeological samples. Towards this aim, archaeological bone samples and corresponding soil samples from each burial environment were collected in Medieval cemeteries in Latvia. The Ion 16S™ Metagenomics Kit targeting different 16S rRNA gene hypervariable regions was used for library construction (Ion Torrent technologies). Sequenced data were analysed by using appropriate bioinformatic techniques; alignment and taxonomic representation was done using Mothur program. Sequences of most abundant genus were further aligned to E. coli 16S rRNA gene reference sequence using MEGA7 in order to identify the hypervariable region of the segment of interest. Our results showed that different hypervariable regions had different discriminatory power depending on the groups of microbes, as well as the nature of samples. On the basis of our results, we suggest that wider range of primers used can provide more accurate recapitulation of microbial communities in archaeological samples. Acknowledgements. This work was supported by the ERAF grant Nr. 1.1.1.1/16/A/101. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=16S%20rRNA%20gene" title="16S rRNA gene">16S rRNA gene</a>, <a href="https://publications.waset.org/abstracts/search?q=ancient%20human%20microbiome" title=" ancient human microbiome"> ancient human microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=archaeology" title=" archaeology"> archaeology</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a>, <a href="https://publications.waset.org/abstracts/search?q=genomics" title=" genomics"> genomics</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=molecular%20biology" title=" molecular biology"> molecular biology</a>, <a href="https://publications.waset.org/abstracts/search?q=next-generation%20sequencing" title=" next-generation sequencing"> next-generation sequencing</a> </p> <a href="https://publications.waset.org/abstracts/78646/insights-into-archaeological-human-sample-microbiome-using-16s-rrna-gene-sequencing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78646.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">189</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">80</span> Analysis of the Lung Microbiome in Cystic Fibrosis Patients Using 16S Sequencing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manasvi%20Pinnaka">Manasvi Pinnaka</a>, <a href="https://publications.waset.org/abstracts/search?q=Brianna%20Chrisman"> Brianna Chrisman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cystic fibrosis patients often develop lung infections that range anywhere in severity from mild to life-threatening due to the presence of thick and sticky mucus that fills their airways. Since many of these infections are chronic, they not only affect a patient’s ability to breathe but also increase the chances of mortality by respiratory failure. With a publicly available dataset of DNA sequences from bacterial species in the lung microbiome of cystic fibrosis patients, the correlations between different microbial species in the lung and the extent of deterioration of lung function were investigated. 16S sequencing technologies were used to determine the microbiome composition of the samples in the dataset. For the statistical analyses, referencing helped distinguish between taxonomies, and the proportions of certain taxa relative to another were determined. It was found that the Fusobacterium, Actinomyces, and Leptotrichia microbial types all had a positive correlation with the FEV1 score, indicating the potential displacement of these species by pathogens as the disease progresses. However, the dominant pathogens themselves, including Pseudomonas aeruginosa and Staphylococcus aureus, did not have statistically significant negative correlations with the FEV1 score as described by past literature. Examining the lung microbiology of cystic fibrosis patients can help with the prediction of the current condition of lung function, with the potential to guide doctors when designing personalized treatment plans for patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bacterial%20infections" title="bacterial infections">bacterial infections</a>, <a href="https://publications.waset.org/abstracts/search?q=cystic%20fibrosis" title=" cystic fibrosis"> cystic fibrosis</a>, <a href="https://publications.waset.org/abstracts/search?q=lung%20microbiome" title=" lung microbiome"> lung microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=16S%20sequencing" title=" 16S sequencing"> 16S sequencing</a> </p> <a href="https://publications.waset.org/abstracts/161103/analysis-of-the-lung-microbiome-in-cystic-fibrosis-patients-using-16s-sequencing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/161103.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">99</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">79</span> Changes in the fecal Microbiome of Periparturient Dairy Cattle and Associations with the Onset of Salmonella Shedding</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lohendy%20Munoz-Vargas">Lohendy Munoz-Vargas</a>, <a href="https://publications.waset.org/abstracts/search?q=Stephen%20O.%20Opiyo"> Stephen O. Opiyo</a>, <a href="https://publications.waset.org/abstracts/search?q=Rose%20Digianantonio"> Rose Digianantonio</a>, <a href="https://publications.waset.org/abstracts/search?q=Michele%20L.%20Williams"> Michele L. Williams</a>, <a href="https://publications.waset.org/abstracts/search?q=Asela%20Wijeratne"> Asela Wijeratne</a>, <a href="https://publications.waset.org/abstracts/search?q=Gregory%20Habing"> Gregory Habing</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Non-typhoidal Salmonella enterica is a zoonotic pathogen with critical importance in animal and public health. The persistence of Salmonella on farms affects animal productivity and health, and represents a risk for food safety. The intestinal microbiota plays a fundamental role in the colonization and invasion of this ubiquitous microorganism. To overcome the colonization resistance imparted by the gut microbiome, Salmonella uses invasion strategies and the host inflammatory response to survive, proliferate, and establish infections with diverse clinical manifestations. Cattle serve as reservoirs of Salmonella, and periparturient cows have high prevalence of Salmonella shedding; however, to author`s best knowledge, little is known about the association between the gut microbiome and the onset of Salmonella shedding during the periparturient period. Thus, the objective of this study was to assess the association between changes in bacterial communities and the onset of Salmonella shedding in cattle approaching parturition. In a prospective cohort study, fecal samples from 98 dairy cows originating from four different farms were collected at four time points relative to calving (-3 wks, -1 wk, +1 wk, +3 wks). All 392 samples were cultured for Salmonella. Sequencing of the V4 region of the 16S rRNA gene using the Illumina platform was completed to evaluate the fecal microbiome in a selected sample subset. Analyses of microbial composition, diversity, and structure were performed according to time points, farm, and Salmonella onset status. Individual cow fecal microbiomes, predominated by Bacteroidetes, Firmicutes, Spirochaetes, and Proteobacteria phyla, significantly changed before and after parturition. Microbial communities from different farms were distinguishable based on multivariate analysis. Although there were significant differences in some bacterial taxa between Salmonella positive and negative samples, our results did not identify differences in the fecal microbial diversity or structure for cows with and without the onset of Salmonella shedding. These data suggest that determinants other than the significant changes in the fecal microbiome influence the periparturient onset of Salmonella shedding in dairy cattle. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dairy%20cattle" title="dairy cattle">dairy cattle</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=periparturient" title=" periparturient"> periparturient</a>, <a href="https://publications.waset.org/abstracts/search?q=Salmonella" title=" Salmonella"> Salmonella</a> </p> <a href="https://publications.waset.org/abstracts/95942/changes-in-the-fecal-microbiome-of-periparturient-dairy-cattle-and-associations-with-the-onset-of-salmonella-shedding" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95942.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">78</span> Effect of Radiotherapy/Chemotherapy Protocol on the Gut Microbiome in Pediatric Cancer Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nourhan%20G.%20Sahly">Nourhan G. Sahly</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Moustafa"> Ahmed Moustafa</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20S.%20Zaghloul"> Mohamed S. Zaghloul</a>, <a href="https://publications.waset.org/abstracts/search?q=Tamer%20Z.%20Salem"> Tamer Z. Salem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The gut microbiome plays important roles in the human body that includes but not limited to digestion, immunity, homeostasis and response to some drugs such as chemotherapy and immunotherapy. Its role has also been linked to radiotherapy and associated gastrointestinal injuries, where the microbial dysbiosis could be the driving force for dose determination or the complete suspension of the treatment protocol. Linking the gut microbiota alterations to different cancer treatment protocols is not easy especially in humans. However, enormous effort was exerted to understand this complex relationship. In the current study, we described the gut microbiota dysbiosis in pediatric sarcoma patients, in the pelvic region, with regards to radiotherapy and antibiotics. Fecal samples were collected as a source of microbial DNA for which the gene encoding for V3-V5 regions of 16S rRNA was sequenced. Two of the three patients understudy had experienced an increase in alpha diversity post exposure to 50.4 Gy. Although phylum Firmicutes overall relative abundance has generally decreased, six of its taxa increased in all patients. Our results may indicate the possibility of radiosensitivity or enrichment of the antibiotic resistance of the elevated taxa. Further studies are needed to describe the extent of radiosensitivity with regards to antibiotic resistance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=combined%20radiotherapy%20and%20chemotherapy" title="combined radiotherapy and chemotherapy">combined radiotherapy and chemotherapy</a>, <a href="https://publications.waset.org/abstracts/search?q=gut%20microbiome" title=" gut microbiome"> gut microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=pediatric%20cancer" title=" pediatric cancer"> pediatric cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=radiosensitivity" title=" radiosensitivity"> radiosensitivity</a> </p> <a href="https://publications.waset.org/abstracts/99183/effect-of-radiotherapychemotherapy-protocol-on-the-gut-microbiome-in-pediatric-cancer-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99183.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">151</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">77</span> Analyzing Emerging Scientific Domains in Biomedical Discourse: Case Study Comparing Microbiome, Metabolome, and Metagenome Research in Scientific Articles</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kenneth%20D.%20Aiello">Kenneth D. Aiello</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Simeone"> M. Simeone</a>, <a href="https://publications.waset.org/abstracts/search?q=Manfred%20Laubichler"> Manfred Laubichler</a> </p> <p class="card-text"><strong>Abstract:</strong></p> It is increasingly difficult to analyze emerging scientific fields as contemporary scientific fields are more dynamic, their boundaries are more porous, and the relational possibilities have increased due to Big Data and new information sources. In biomedicine, where funding, medical categories, and medical jurisdiction are determined by distinct boundaries on biomedical research fields and definitions of concepts, ambiguity persists between the microbiome, metabolome, and metagenome research fields. This ambiguity continues despite efforts by institutions and organizations to establish parameters on the core concepts and research discourses. Further, the explosive growth of microbiome, metabolome, and metagenomic research has led to unknown variation and covariation making application of findings across subfields or coming to a consensus difficult. This study explores the evolution and variation of knowledge within the microbiome, metabolome, and metagenome research fields related to ambiguous scholarly language and commensurable theoretical frameworks via a semantic analysis of key concepts and narratives. A computational historical framework of cultural evolution and large-scale publication data highlight the boundaries and overlaps between the competing scientific discourses surrounding the three research areas. The results of this study highlight how discourse and language distribute power within scholarly and scientific networks, specifically the power to set and define norms, central questions, methods, and knowledge. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=biomedicine" title="biomedicine">biomedicine</a>, <a href="https://publications.waset.org/abstracts/search?q=conceptual%20change" title=" conceptual change"> conceptual change</a>, <a href="https://publications.waset.org/abstracts/search?q=history%20of%20science" title=" history of science"> history of science</a>, <a href="https://publications.waset.org/abstracts/search?q=philosophy%20of%20science" title=" philosophy of science"> philosophy of science</a>, <a href="https://publications.waset.org/abstracts/search?q=science%20of%20science" title=" science of science"> science of science</a>, <a href="https://publications.waset.org/abstracts/search?q=sociolinguistics" title=" sociolinguistics"> sociolinguistics</a>, <a href="https://publications.waset.org/abstracts/search?q=sociology%20of%20knowledge" title=" sociology of knowledge"> sociology of knowledge</a> </p> <a href="https://publications.waset.org/abstracts/119612/analyzing-emerging-scientific-domains-in-biomedical-discourse-case-study-comparing-microbiome-metabolome-and-metagenome-research-in-scientific-articles" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/119612.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">76</span> Predicting Potential Protein Therapeutic Candidates from the Gut Microbiome </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Prasanna%20Ramachandran">Prasanna Ramachandran</a>, <a href="https://publications.waset.org/abstracts/search?q=Kareem%20Graham"> Kareem Graham</a>, <a href="https://publications.waset.org/abstracts/search?q=Helena%20Kiefel"> Helena Kiefel</a>, <a href="https://publications.waset.org/abstracts/search?q=Sunit%20Jain"> Sunit Jain</a>, <a href="https://publications.waset.org/abstracts/search?q=Todd%20DeSantis"> Todd DeSantis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=protein-interactions" title="protein-interactions">protein-interactions</a>, <a href="https://publications.waset.org/abstracts/search?q=machine-learning" title=" machine-learning"> machine-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=metagenomics" title=" metagenomics"> metagenomics</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a> </p> <a href="https://publications.waset.org/abstracts/62501/predicting-potential-protein-therapeutic-candidates-from-the-gut-microbiome" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62501.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">376</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">75</span> Unraveling the Gut-Brain Connection in Alcohol Use Disorder: Microbiome Dysbiosis and Probiotic Therapy as Emerging Treatment Pathways</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Noah%20Emil%20Glisik">Noah Emil Glisik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Alcohol use disorder (AUD) presents significant health challenges worldwide and is particularly concerning in Slovenia, where high alcohol consumption contributes to elevated rates of comorbidities, including depression and suicide. This review examines emerging evidence linking gut microbiome dysbiosis to AUD, exploring whether gut microbiome alterations merely result from alcohol use or actively contribute to the persistence of addiction. Additionally, it discusses how microbial changes may influence psychological symptoms, including anxiety and depressive states, which are closely associated with suicidality in this population. To address gaps in existing research, a systematic literature search was conducted through PubMed, Web of Science, and ScienceDirect. Inclusion criteria focused on studies examining gut microbiome changes in AUD, particularly those assessing gut-brain axis interactions and microbial species impacting inflammation and neurotransmitter pathways. Studies were excluded if they lacked peer review or did not specifically assess microbiome effects on mental health outcomes. A qualitative literature review approach was applied, synthesizing findings into key themes on microbial changes, neuroinflammatory pathways, and treatment implications. Data were organized into tables to provide a clear comparison of microbiota alterations across studies, highlighting specific bacterial species and their potential effects on AUD. This review emphasizes patterns in AUD patients, where reductions in anti-inflammatory species, such as Faecalibacterium prausnitzii and Roseburia intestinalis, coincide with increases in pro-inflammatory bacteria like Enterococcus faecalisand Lactobacillus rhamnosus. These shifts contribute to increased gut permeability and systemic inflammation, potentially influencing the kynurenine pathway, which is linked to depressive symptoms and elevated alcohol cravings. Furthermore, the review explores the potential of probiotic therapies targeting these microbial imbalances as adjunctive treatments for AUD, particularly those focusing on strains that support anti-inflammatory pathways and gut barrier integrity. Restoring microbial homeostasis through probiotics or fecal microbiota transplantation may not only reduce inflammation but also alleviate mental health symptoms associated with addiction, including suicidality. The findings underscore the need for further clinical trials assessing microbiome-targeted therapies as innovative, multifaceted approaches to AUD treatment in Slovenia and beyond. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=alcohol%20use%20disorder" title="alcohol use disorder">alcohol use disorder</a>, <a href="https://publications.waset.org/abstracts/search?q=gut-brain%20axis" title=" gut-brain axis"> gut-brain axis</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome%20dysbiosis" title=" microbiome dysbiosis"> microbiome dysbiosis</a>, <a href="https://publications.waset.org/abstracts/search?q=probiotic%20therapy." title=" probiotic therapy."> probiotic therapy.</a> </p> <a href="https://publications.waset.org/abstracts/193579/unraveling-the-gut-brain-connection-in-alcohol-use-disorder-microbiome-dysbiosis-and-probiotic-therapy-as-emerging-treatment-pathways" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193579.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">9</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">74</span> Characterization of the Blood Microbiome in Rheumatoid Arthritis Patients Compared to Healthy Control Subjects Using V4 Region 16S rRNA Sequencing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20Hammad">D. Hammad</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20P.%20Tonge"> D. P. Tonge</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Rheumatoid arthritis (RA) is a disabling and common autoimmune disease during which the body's immune system attacks healthy tissues. This results in complicated and long-lasting actions being carried out by the immune system, which typically only occurs when the immune system encounters a foreign object. In the case of RA, the disease affects millions of people and causes joint inflammation, ultimately leading to the destruction of cartilage and bone. Interestingly, the disease mechanism still remains unclear. It is likely that RA occurs as a result of a complex interplay of genetic and environmental factors including an imbalance in the microorganism population inside our body. The human microbiome or microbiota is an extensive community of microorganisms in and on the bodies of animals, which comprises bacteria, fungi, viruses, and protozoa. Recently, the development of molecular techniques to characterize entire bacterial communities has renewed interest in the involvement of the microbiome in the development and progression of RA. We believe that an imbalance in some of the specific bacterial species in the gut, mouth and other sites may lead to atopobiosis; the translocation of these organisms into the blood, and that this may lead to changes in immune system status. The aim of this study was, therefore, to characterize the microbiome of RA serum samples in comparison to healthy control subjects using 16S rRNA gene amplification and sequencing. Serum samples were obtained from healthy control volunteers and from patients with RA both prior to, and following treatment. The bacterial community present in each sample was identified utilizing V4 region 16S rRNA amplification and sequencing. Bacterial identification, to the lowest taxonomic rank, was performed using a range of bioinformatics tools. Significantly, the proportions of the Lachnospiraceae, Ruminococcaceae, and Halmonadaceae families were significantly increased in the serum of RA patients compared with healthy control serum. Furthermore, the abundance of Bacteroides and Lachnospiraceae nk4a136_group, Lachnospiraceae_UGC-001, RuminococcaceaeUCG-014, Rumnococcus-1, and Shewanella was also raised in the serum of RA patients relative to healthy control serum. These data support the notion of a blood microbiome and reveal RA-associated changes that may have significant implications for biomarker development and may present much-needed opportunities for novel therapeutic development. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blood%20microbiome" title="blood microbiome">blood microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=gut%20and%20oral%20bacteria" title=" gut and oral bacteria"> gut and oral bacteria</a>, <a href="https://publications.waset.org/abstracts/search?q=Rheumatoid%20arthritis" title=" Rheumatoid arthritis"> Rheumatoid arthritis</a>, <a href="https://publications.waset.org/abstracts/search?q=16S%20rRNA%20gene%20sequencing" title=" 16S rRNA gene sequencing"> 16S rRNA gene sequencing</a> </p> <a href="https://publications.waset.org/abstracts/94190/characterization-of-the-blood-microbiome-in-rheumatoid-arthritis-patients-compared-to-healthy-control-subjects-using-v4-region-16s-rrna-sequencing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94190.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">132</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">73</span> Dysbiosis of the Intestinal Microbiome in Colorectal Cancer Patients at Hospital of Amizour, Bejaia, Algeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adjebli%20Ahmed">Adjebli Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Messis%20Abdelaziz"> Messis Abdelaziz</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayeche%20Riad"> Ayeche Riad</a>, <a href="https://publications.waset.org/abstracts/search?q=Tighilet%20Karim"> Tighilet Karim</a>, <a href="https://publications.waset.org/abstracts/search?q=Talbi%20Melissa"> Talbi Melissa</a>, <a href="https://publications.waset.org/abstracts/search?q=Smaili%20Yanis"> Smaili Yanis</a>, <a href="https://publications.waset.org/abstracts/search?q=Lehri%20Mokrane"> Lehri Mokrane</a>, <a href="https://publications.waset.org/abstracts/search?q=Louardiane%20Mustapha"> Louardiane Mustapha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Colorectal cancer is one of the most common types of cancer worldwide, and its incidence has been increasing in recent years. Data and fecal samples from colorectal cancer patients were collected at the Amizour Public Hospital's oncology department (Bejaia, Algeria). Microbiological and cohort study were conducted at the Biological Engineering of Cancers laboratory at the Faculty of Medicine of the University of Bejaia. All the data showed that patients aged between 50 and 70 years were the most affected by colorectal cancer, while the age categories of [30-40] and [40-50] were the least affected. Males were more likely to be at risk of contracting colorectal cancer than females. The most common types of colorectal cancer among the studied population were sigmoid cancer, rectal cancer, transverse colon cancer, and ascending colon cancer. The hereditary factor was found to be more dominant than other risk factors. Bacterial identification revealed the presence of certain pathogenic and opportunistic bacterial genera, such as E. coli, K. pneumoniae, Shigella sp, and Streptococcus group D. These results led us to conclude that dysbiosis of the intestinal microbiome is strongly present in colorectal cancer patients at the EPH of Amizour. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microbiome" title="microbiome">microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=colorectal%20cancer" title=" colorectal cancer"> colorectal cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=risk%20factors" title=" risk factors"> risk factors</a>, <a href="https://publications.waset.org/abstracts/search?q=bacterial%20identification" title=" bacterial identification"> bacterial identification</a> </p> <a href="https://publications.waset.org/abstracts/164659/dysbiosis-of-the-intestinal-microbiome-in-colorectal-cancer-patients-at-hospital-of-amizour-bejaia-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164659.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">85</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">72</span> Data Analysis for Taxonomy Prediction and Annotation of 16S rRNA Gene Sequences from Metagenome Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suchithra%20V.">Suchithra V.</a>, <a href="https://publications.waset.org/abstracts/search?q=Shreedhanya"> Shreedhanya</a>, <a href="https://publications.waset.org/abstracts/search?q=Kavya%20Menon"> Kavya Menon</a>, <a href="https://publications.waset.org/abstracts/search?q=Vidya%20Niranjan"> Vidya Niranjan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Skin metagenomics has a wide range of applications with direct relevance to the health of the organism. It gives us insight to the diverse community of microorganisms (the microbiome) harbored on the skin. In the recent years, it has become increasingly apparent that the interaction between skin microbiome and the human body plays a prominent role in immune system development, cancer development, disease pathology, and many other biological implications. Next Generation Sequencing has led to faster and better understanding of environmental organisms and their mutual interactions. This project is studying the human skin microbiome of different individuals having varied skin conditions. Bacterial 16S rRNA data of skin microbiome is downloaded from SRA toolkit provided by NCBI to perform metagenomics analysis. Twelve samples are selected with two controls, and 3 different categories, i.e., sex (male/female), skin type (moist/intermittently moist/sebaceous) and occlusion (occluded/intermittently occluded/exposed). Quality of the data is increased using Cutadapt, and its analysis is done using FastQC. USearch, a tool used to analyze an NGS data, provides a suitable platform to obtain taxonomy classification and abundance of bacteria from the metagenome data. The statistical tool used for analyzing the USearch result is METAGENassist. The results revealed that the top three abundant organisms found were: Prevotella, Corynebacterium, and Anaerococcus. Prevotella is known to be an infectious bacterium found on wound, tooth cavity, etc. Corynebacterium and Anaerococcus are opportunist bacteria responsible for skin odor. This result infers that Prevotella thrives easily in sebaceous skin conditions. Therefore it is better to undergo intermittently occluded treatment such as applying ointments, creams, etc. to treat wound for sebaceous skin type. Exposing the wound should be avoided as it leads to an increase in Prevotella abundance. Moist skin type individuals can opt for occluded or intermittently occluded treatment as they have shown to decrease the abundance of bacteria during treatment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bacterial%2016S%20rRNA" title="bacterial 16S rRNA ">bacterial 16S rRNA </a>, <a href="https://publications.waset.org/abstracts/search?q=next%20generation%20sequencing" title=" next generation sequencing"> next generation sequencing</a>, <a href="https://publications.waset.org/abstracts/search?q=skin%20metagenomics" title=" skin metagenomics"> skin metagenomics</a>, <a href="https://publications.waset.org/abstracts/search?q=skin%20microbiome" title=" skin microbiome"> skin microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=taxonomy" title=" taxonomy"> taxonomy</a> </p> <a href="https://publications.waset.org/abstracts/99878/data-analysis-for-taxonomy-prediction-and-annotation-of-16s-rrna-gene-sequences-from-metagenome-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99878.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">71</span> Incidence of Breast Cancer and Enterococcus Infection: A Retrospective Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Matthew%20Cardeiro">Matthew Cardeiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Amalia%20D.%20Ardeljan"> Amalia D. Ardeljan</a>, <a href="https://publications.waset.org/abstracts/search?q=Lexi%20Frankel"> Lexi Frankel</a>, <a href="https://publications.waset.org/abstracts/search?q=Dianela%20Prado%20Escobar"> Dianela Prado Escobar</a>, <a href="https://publications.waset.org/abstracts/search?q=Catalina%20Molnar"> Catalina Molnar</a>, <a href="https://publications.waset.org/abstracts/search?q=Omar%20M.%20Rashid"> Omar M. Rashid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Enterococci comprise the natural flora of nearly all animals and are ubiquitous in food manufacturing and probiotics. However, its role in the microbiome remains controversial. The gut microbiome has shown to play an important role in immunology and cancer. Further, recent data has suggested a relationship between gut microbiota and breast cancer. These studies have shown that the gut microbiome of patients with breast cancer differs from that of healthy patients. Research regarding enterococcus infection and its sequala is limited, and further research is needed in order to understand the relationship between infection and cancer. Enterococcus may prevent the development of breast cancer (BC) through complex immunologic and microbiotic adaptations following an enterococcus infection. This study investigated the effect of enterococcus infection and the incidence of BC. Methods: A retrospective study (January 2010- December 2019) was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using a Humans Health Insurance Database. International Classification of Disease (ICD) 9th and 10th codes, Current Procedural Terminology (CPT), and National Drug Codes were used to identify BC diagnosis and enterococcus infection. Patients were matched for age, sex, Charlson Comorbidity Index (CCI), antibiotic treatment, and region of residence. Chi-squared, logistic regression, and odds ratio were implemented to assess the significance and estimate relative risk. Results: 671 out of 28,518 (2.35%) patients with a prior enterococcus infection and 1,459 out of 28,518 (5.12%) patients without enterococcus infection subsequently developed BC, and the difference was statistically significant (p<2.2x10⁻¹⁶). Logistic regression also indicated enterococcus infection was associated with a decreased incidence of BC (RR=0.60, 95% CI [0.57, 0.63]). Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 398 out of 11,523 (3.34%) patients with a prior enterococcus infection and treated with antibiotics were compared to 624 out of 11,523 (5.41%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed BC. Results remained statistically significant (p<2.2x10-16) with a relative risk of 0.57 (95% CI [0.54, 0.60]). Conclusion & Discussion: This study shows a statistically significant correlation between enterococcus infection and a decrease incidence of breast cancer. Further exploration is needed to identify and understand not only the role of enterococcus in the microbiome but also the protective mechanism(s) and impact enterococcus infection may have on breast cancer development. Ultimately, further research is needed in order to understand the complex and intricate relationship between the microbiome, immunology, bacterial infections, and carcinogenesis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title="breast cancer">breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=enterococcus" title=" enterococcus"> enterococcus</a>, <a href="https://publications.waset.org/abstracts/search?q=immunology" title=" immunology"> immunology</a>, <a href="https://publications.waset.org/abstracts/search?q=infection" title=" infection"> infection</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a> </p> <a href="https://publications.waset.org/abstracts/140139/incidence-of-breast-cancer-and-enterococcus-infection-a-retrospective-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140139.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">173</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">70</span> Habitat-Specific Divergences in the Gene Repertoire among the Reference Prevotella Genomes of the Human Microbiome</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vinod%20Kumar%20Gupta">Vinod Kumar Gupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Narendrakumar%20M.%20Chaudhari"> Narendrakumar M. Chaudhari</a>, <a href="https://publications.waset.org/abstracts/search?q=Suchismitha%20Iskepalli"> Suchismitha Iskepalli</a>, <a href="https://publications.waset.org/abstracts/search?q=Chitra%20Dutta"> Chitra Dutta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background-The community composition of the human microbiome is known to vary at distinct anatomical niches. But little is known about the nature of variations if any, at the genome/sub-genome levels of a specific microbial community across different niches. The present report aims to explore, as a case study, the variations in gene repertoire of 28 Prevotella reference draft genomes derived from different body-sites of human, as reported earlier by the Human Microbiome Consortium. Results-The analysis reveals the exclusive presence of 11798, 3673, 3348 and 934 gene families and exclusive absence of 17, 221, 115 and 645 gene families in Prevotella genomes derived from the human oral cavity, gastro-intestinal tracts (GIT), urogenital tract (UGT) and skin, respectively. The pan-genome for Prevotella remains “open”. Distribution of various functional COG categories differs appreciably among the habitat-specific genes, within Prevotella pan-genome and between the GIT-derived Bacteroides and Prevotella. The skin and GIT isolates of Prevotella are enriched in singletons involved in Signal transduction mechanisms, while the UGT and oral isolates show higher representation of the Defense mechanisms category. No niche-specific variations could be observed in the distribution of KEGG pathways. Conclusion-Prevotella may have developed distinct genetic strategies for adaptation to different anatomical habitats through selective, niche-specific acquisition and elimination of suitable gene-families. In addition, individual microorganisms tend to develop their own distinctive adaptive stratagems through large repertoires of singletons. Such in situ, habitat-driven refurbishment of the genetic makeup can impart substantial intra-lineage genome diversity within the microbes without perturbing their general taxonomic heritage. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=body%20niche%20adaptation" title="body niche adaptation">body niche adaptation</a>, <a href="https://publications.waset.org/abstracts/search?q=human%20microbiome" title=" human microbiome"> human microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=pangenome" title=" pangenome"> pangenome</a>, <a href="https://publications.waset.org/abstracts/search?q=Prevotella" title=" Prevotella"> Prevotella</a> </p> <a href="https://publications.waset.org/abstracts/43428/habitat-specific-divergences-in-the-gene-repertoire-among-the-reference-prevotella-genomes-of-the-human-microbiome" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43428.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">247</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">69</span> Nutritional Genomics Profile Based Personalized Sport Nutrition</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eszter%20Repasi">Eszter Repasi</a>, <a href="https://publications.waset.org/abstracts/search?q=Akos%20Koller"> Akos Koller</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Our genetic information determines our look, physiology, sports performance and all our features. Maximizing the performances of athletes have adopted a science-based approach to the nutritional support. Nowadays genetics studies have blended with nutritional sciences, and a dynamically evolving, new research field have appeared. Nutritional genomics is needed to be used by nutritional experts. This is a recent field of nutritional science, which can provide a solution to reach the best sport performance using correlations between the athlete’s genome, nutritions, molecules, included human microbiome (links between food, microbiome and epigenetics), nutrigenomics and nutrigenetics. Nutritional genomics has a tremendous potential to change the future of dietary guidelines and personal recommendations. Experts need to use new technology to get information about the athletes, like nutritional genomics profile (included the determination of the oral and gut microbiome and DNA coded reaction for food components), which can modify the preparation term and sports performance. The influence of nutrients on the genes expression is called Nutrigenomics. The heterogeneous response of gene variants to nutrients, dietary components is called Nutrigenetics. The human microbiome plays a critical role in the state of health and well-being, and there are more links between food or nutrition and the human microbiome composition, which can develop diseases and epigenetic changes as well. A nutritional genomics-based profile of athletes can be the best technic for a dietitian to make a unique sports nutrition diet plan. Using functional food and the right food components can be effected on health state, thus sports performance. Scientists need to determine the best response, due to the effect of nutrients on health, through altering genome promote metabolites and result changes in physiology. Nutritional biochemistry explains why polymorphisms in genes for the absorption, circulation, or metabolism of essential nutrients (such as n-3 polyunsaturated fatty acids or epigallocatechin-3-gallate), would affect the efficacy of that nutrient. Controlled nutritional deficiencies and failures, prevented the change of health state or a newly discovered food intolerance are observed by a proper medical team, can support better sports performance. It is important that the dietetics profession informed on gene-diet interactions, that may be leading to optimal health, reduced risk of injury or disease. A special medical application for documentation and monitoring of data of health state and risk factors can uphold and warn the medical team for an early action and help to be able to do a proper health service in time. This model can set up a personalized nutrition advice from the status control, through the recovery, to the monitoring. But more studies are needed to understand the mechanisms and to be able to change the composition of the microbiome, environmental and genetic risk factors in cases of athletes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gene-diet%20interaction" title="gene-diet interaction">gene-diet interaction</a>, <a href="https://publications.waset.org/abstracts/search?q=multidisciplinary%20team" title=" multidisciplinary team"> multidisciplinary team</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=diet%20plan" title=" diet plan"> diet plan</a> </p> <a href="https://publications.waset.org/abstracts/72214/nutritional-genomics-profile-based-personalized-sport-nutrition" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72214.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">68</span> Exploring the Correlation between Body Constitution of an Individual as Per Ayurveda and Gut Microbiome in Healthy, Multi Ethnic Urban Population in Bangalore, India </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shalini%20TV">Shalini TV</a>, <a href="https://publications.waset.org/abstracts/search?q=Gangadharan%20GG"> Gangadharan GG</a>, <a href="https://publications.waset.org/abstracts/search?q=Sriranjini%20S%20Jaideep"> Sriranjini S Jaideep</a>, <a href="https://publications.waset.org/abstracts/search?q=ASN%20Seshasayee"> ASN Seshasayee</a>, <a href="https://publications.waset.org/abstracts/search?q=Awadhesh%20Pandit"> Awadhesh Pandit</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Prakriti (body-mind constitution of an individual) is a conventional, customized and unique understanding of which is essential for the personalized medicine described in Ayurveda, Indian System of Medicine. Based on the Doshas( functional, bio humoral unit in the body), individuals are categorized into three major Prakriti- Vata, Pitta, and Kapha. The human gut microbiome hosts plenty of highly diverse and metabolically active microorganisms, mainly dominated by the bacteria, which are known to influence the physiology of an individual. Few researches have shown the correlation between the Prakriti and the biochemical parameters. In this study, an attempt was made to explore any correlation between the Prakriti (phenotype of an individual) with the Genetic makeup of the gut microbiome in healthy individuals. Materials and methods: 270 multi-ethnic, healthy volunteers of both sex with the age group between 18 to 40 years, with no history of antibiotics in the last 6 months were recruited into three groups of Vata, Pitta, and Kapha. The Prakriti of the individual was determined using Ayusoft, a software designed by CDAC, Pune, India. The volunteers were subjected to initial screening for the assessment of their height, weight, Body Mass Index, Vital signs and Blood investigations to ensure they are healthy. The stool and saliva samples of the recruited volunteers were collected as per the standard operating procedure developed, and the bacterial DNA was isolated using Qiagen kits. The extracted DNA was subjected to 16s rRNA sequencing using the Illumina kits. The sequencing libraries are targeting the variable V3 and V4 regions of the 16s rRNA gene. Paired sequencing was done on the MiSeq system and data were analyzed using the CLC Genomics workbench 11. Results: The 16s rRNA sequencing of the V3 and V4 regions showed a diverse pattern in both the oral and stool microbial DNA. The study did not reveal any specific pattern of bacterial flora amongst the Prakriti. All the p-values were more than the effective alpha values for all OTUs in both the buccal cavity and stool samples. Therefore, there was no observed significant enrichment of an OTU in the patient samples from either the buccal cavity or stool samples. Conclusion: In healthy volunteers of multi-ethnicity, due to the influence of the various factors, the correlation between the Prakriti and the gut microbiome was not seen. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gut%20microbiome" title="gut microbiome">gut microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=ayurveda%20Prakriti" title=" ayurveda Prakriti"> ayurveda Prakriti</a>, <a href="https://publications.waset.org/abstracts/search?q=sequencing" title=" sequencing"> sequencing</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-ethnic%20urban%20population" title=" multi-ethnic urban population"> multi-ethnic urban population</a> </p> <a href="https://publications.waset.org/abstracts/116206/exploring-the-correlation-between-body-constitution-of-an-individual-as-per-ayurveda-and-gut-microbiome-in-healthy-multi-ethnic-urban-population-in-bangalore-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116206.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">135</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">67</span> Rheumatoid Arthritis, Periodontitis and the Subgingival Microbiome: A Circular Relationship</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Isabel%20Lopez-Oliva">Isabel Lopez-Oliva</a>, <a href="https://publications.waset.org/abstracts/search?q=Akshay%20Paropkari"> Akshay Paropkari</a>, <a href="https://publications.waset.org/abstracts/search?q=Shweta%20Saraswat"> Shweta Saraswat</a>, <a href="https://publications.waset.org/abstracts/search?q=Stefan%20Serban"> Stefan Serban</a>, <a href="https://publications.waset.org/abstracts/search?q=Paola%20de%20Pablo"> Paola de Pablo</a>, <a href="https://publications.waset.org/abstracts/search?q=Karim%20Raza"> Karim Raza</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Filer"> Andrew Filer</a>, <a href="https://publications.waset.org/abstracts/search?q=Iain%20Chapple"> Iain Chapple</a>, <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Dietrich"> Thomas Dietrich</a>, <a href="https://publications.waset.org/abstracts/search?q=Melissa%20Grant"> Melissa Grant</a>, <a href="https://publications.waset.org/abstracts/search?q=Purnima%20Kumar"> Purnima Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: We aimed to explicate the role of the subgingival microbiome in the causal link between rheumatoid arthritis (RA) and periodontitis (PD). Methods: Subjects with/without RA and with/without PD were randomized for treatment with scaling and root planing (SRP) or oral hygiene instructions. Subgingival biofilm, gingival crevicular fluid, and serum were collected at baseline and at 3- and 6-months post-operatively. Correlations were generated between 72 million 16S rDNA sequences, immuno-inflammatory mediators, circulating antibodies to oral microbial antigens, serum inflammatory molecules, and clinical metrics of RA. The dynamics of inter-microbial and host-microbial interactions were modeled using differential network analysis. Results: RA superseded periodontitis as a determinant of microbial composition, and DAS28 score superseded the severity of periodontitis as a driver of microbial assemblages (p=0.001, ANOSIM). RA subjects evidenced higher serum anti-PPAD (p=0.0013), anti-Pg-enolase (p=0.0031), anti-RPP3, anti- Pg-OMP and anti- Pi-OMP (p=0.001) antibodies than non-RA controls (with and without periodontitis). Following SRP, bacterial networks anchored by IL-1b, IL-4, IL-6, IL-10, IL-13, MIP-1b, and PDGF-b underwent ≥5-fold higher rewiring; and serum antibodies to microbial antigens decreased significantly. Conclusions: Our data suggest a circular relationship between RA and PD, beginning with an RA-influenced dysbiosis within the healthy subgingival microbiome that leads to exaggerated local inflammation in periodontitis and circulating antibodies to periodontal pathogens and positive correlation between severity of periodontitis and RA activity. Periodontal therapy restores host-microbial homeostasis, reduces local inflammation, and decreases circulating microbial antigens. Our data highlights the importance of integrating periodontal care into the management of RA patients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rheumatoid%20arthritis" title="rheumatoid arthritis">rheumatoid arthritis</a>, <a href="https://publications.waset.org/abstracts/search?q=periodontal" title=" periodontal"> periodontal</a>, <a href="https://publications.waset.org/abstracts/search?q=subgingival" title=" subgingival"> subgingival</a>, <a href="https://publications.waset.org/abstracts/search?q=DNA%20sequence%20analysis" title=" DNA sequence analysis"> DNA sequence analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=oral%20microbiome" title=" oral microbiome"> oral microbiome</a> </p> <a href="https://publications.waset.org/abstracts/158914/rheumatoid-arthritis-periodontitis-and-the-subgingival-microbiome-a-circular-relationship" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/158914.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">108</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">66</span> Characterizing and Developing the Clinical Grade Microbiome Assay with a Robust Bioinformatics Pipeline for Supporting Precision Medicine Driven Clinical Development</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Danyi%20Wang">Danyi Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Schriefer"> Andrew Schriefer</a>, <a href="https://publications.waset.org/abstracts/search?q=Dennis%20O%27Rourke"> Dennis O'Rourke</a>, <a href="https://publications.waset.org/abstracts/search?q=Brajendra%20Kumar"> Brajendra Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Yang%20Liu"> Yang Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Fei%20Zhong"> Fei Zhong</a>, <a href="https://publications.waset.org/abstracts/search?q=Juergen%20Scheuenpflug"> Juergen Scheuenpflug</a>, <a href="https://publications.waset.org/abstracts/search?q=Zheng%20Feng"> Zheng Feng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=16S%20rRNA%20sequencing" title="16S rRNA sequencing">16S rRNA sequencing</a>, <a href="https://publications.waset.org/abstracts/search?q=analytical%20validation" title=" analytical validation"> analytical validation</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics%20pipeline" title=" bioinformatics pipeline"> bioinformatics pipeline</a>, <a href="https://publications.waset.org/abstracts/search?q=metagenomics" title=" metagenomics"> metagenomics</a> </p> <a href="https://publications.waset.org/abstracts/127959/characterizing-and-developing-the-clinical-grade-microbiome-assay-with-a-robust-bioinformatics-pipeline-for-supporting-precision-medicine-driven-clinical-development" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127959.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">170</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">65</span> Rhizosphere Microbiome Involvement in the Natural Suppression of Soybean Cyst Nematode in Disease Suppressive Soil</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Imran%20Hamid">M. Imran Hamid</a>, <a href="https://publications.waset.org/abstracts/search?q=Muzammil%20Hussain"> Muzammil Hussain</a>, <a href="https://publications.waset.org/abstracts/search?q=Yunpeng%20Wu"> Yunpeng Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Meichun%20Xiang"> Meichun Xiang</a>, <a href="https://publications.waset.org/abstracts/search?q=Xingzhong%20Liu"> Xingzhong Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The rhizosphere microbiome elucidate multiple functioning in the soil suppressiveness against plant pathogens. Soybean rhizosphere microbial communities may involve in the natural suppression of soybean cyst nematode (SCN) populations in disease suppressive soils. To explore these ecological mechanisms of microbes, a long term monoculture suppressive soil were taken into account for further investigation to test the disease suppressive ability by using different treatments. The designed treatments are as, i) suppressive soil (S), ii) conducive soil (C), iii) conducive soil mixed with 10% (w/w) suppressive soil (CS), iv) suppressive soil treated at 80°C for 1 hr (S80), and v) suppressive soil treated with formalin (SF). By using an ultra-high-throughput sequencing approach, we identified the key bacterial and fungal taxa involved in SCN suppression. The Phylum-level investigation of bacteria revealed that Actinobacteria, Bacteroidetes, and Proteobacteria in the rhizosphere soil of soybean seedlings were more abundant in the suppressive soil than in the conducive soil. The phylum-level analysis of fungi in rhizosphere soil indicated that relative abundance of Ascomycota was higher in suppressive soil than in the conducive soil, where Basidiomycota was more abundant. Transferring suppressive soil to conducive soil increased the population of Ascomycota in the conducive soil by lowering the populations of Basidiomycota. The genera, such as, Pochonia, Purpureocillium, Fusarium, Stachybotrys that have been well documented as bio-control agents of plant nematodes were far more in the disease suppressive soils. Our results suggested that the plants engage a subset of functional microbial groups in the rhizosphere for initial defense upon nematode attack and protect the plant roots later on by nematodes to response for suppression of SCN in disease-suppressive soils. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=disease%20suppressive%20soil" title="disease suppressive soil">disease suppressive soil</a>, <a href="https://publications.waset.org/abstracts/search?q=high-throughput%20sequencing" title=" high-throughput sequencing"> high-throughput sequencing</a>, <a href="https://publications.waset.org/abstracts/search?q=rhizosphere%20microbiome" title=" rhizosphere microbiome"> rhizosphere microbiome</a>, <a href="https://publications.waset.org/abstracts/search?q=soybean%20cyst%20nematode" title=" soybean cyst nematode"> soybean cyst nematode</a> </p> <a href="https://publications.waset.org/abstracts/95784/rhizosphere-microbiome-involvement-in-the-natural-suppression-of-soybean-cyst-nematode-in-disease-suppressive-soil" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95784.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">153</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">64</span> TAXAPRO, A Streamlined Pipeline to Analyze Shotgun Metagenomes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sofia%20Sehli">Sofia Sehli</a>, <a href="https://publications.waset.org/abstracts/search?q=Zainab%20El%20Ouafi"> Zainab El Ouafi</a>, <a href="https://publications.waset.org/abstracts/search?q=Casey%20Eddington"> Casey Eddington</a>, <a href="https://publications.waset.org/abstracts/search?q=Soumaya%20Jbara"> Soumaya Jbara</a>, <a href="https://publications.waset.org/abstracts/search?q=Kasambula%20Arthur%20Shem"> Kasambula Arthur Shem</a>, <a href="https://publications.waset.org/abstracts/search?q=Islam%20El%20Jaddaoui"> Islam El Jaddaoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayorinde%20Afolayan"> Ayorinde Afolayan</a>, <a href="https://publications.waset.org/abstracts/search?q=Olaitan%20I.%20Awe"> Olaitan I. Awe</a>, <a href="https://publications.waset.org/abstracts/search?q=Allissa%20Dillman"> Allissa Dillman</a>, <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Ghazal"> Hassan Ghazal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ability to promptly sequence whole genomes at a relatively low cost has revolutionized the way we study the microbiome. Microbiologists are no longer limited to studying what can be grown in a laboratory and instead are given the opportunity to rapidly identify the makeup of microbial communities in a wide variety of environments. Analyzing whole genome sequencing (WGS) data is a complex process that involves multiple moving parts and might be rather unintuitive for scientists that don’t typically work with this type of data. Thus, to help lower the barrier for less-computationally inclined individuals, TAXAPRO was developed at the first Omics Codeathon held virtually by the African Society for Bioinformatics and Computational Biology (ASBCB) in June 2021. TAXAPRO is an advanced metagenomics pipeline that accurately assembles organelle genomes from whole-genome sequencing data. TAXAPRO seamlessly combines WGS analysis tools to create a pipeline that automatically processes raw WGS data and presents organism abundance information in both a tabular and graphical format. TAXAPRO was evaluated using COVID-19 patient gut microbiome data. Analysis performed by TAXAPRO demonstrated a high abundance of Clostridia and Bacteroidia genera and a low abundance of Proteobacteria genera relative to others in the gut microbiome of patients hospitalized with COVID-19, consistent with the original findings derived using a different analysis methodology. This provides crucial evidence that the TAXAPRO workflow dispenses reliable organism abundance information overnight without the hassle of performing the analysis manually. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metagenomics" title="metagenomics">metagenomics</a>, <a href="https://publications.waset.org/abstracts/search?q=shotgun%20metagenomic%20sequence%20analysis" title=" shotgun metagenomic sequence analysis"> shotgun metagenomic sequence analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=COVID-19" title=" COVID-19"> COVID-19</a>, <a href="https://publications.waset.org/abstracts/search?q=pipeline" title=" pipeline"> pipeline</a>, <a href="https://publications.waset.org/abstracts/search?q=bioinformatics" title=" bioinformatics"> bioinformatics</a> </p> <a href="https://publications.waset.org/abstracts/147152/taxapro-a-streamlined-pipeline-to-analyze-shotgun-metagenomes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147152.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">220</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">63</span> Analysis of Taxonomic Compositions, Metabolic Pathways and Antibiotic Resistance Genes in Fish Gut Microbiome by Shotgun Metagenomics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anuj%20Tyagi">Anuj Tyagi</a>, <a href="https://publications.waset.org/abstracts/search?q=Balwinder%20Singh"> Balwinder Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Naveen%20Kumar%20B.%20T."> Naveen Kumar B. T.</a>, <a href="https://publications.waset.org/abstracts/search?q=Niraj%20K.%20Singh"> Niraj K. Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Characterization of diverse microbial communities in specific environment plays a crucial role in the better understanding of their functional relationship with the ecosystem. It is now well established that gut microbiome of fish is not the simple replication of microbiota of surrounding local habitat, and extensive species, dietary, physiological and metabolic variations in fishes may have a significant impact on its composition. Moreover, overuse of antibiotics in human, veterinary and aquaculture medicine has led to rapid emergence and propagation of antibiotic resistance genes (ARGs) in the aquatic environment. Microbial communities harboring specific ARGs not only get a preferential edge during selective antibiotic exposure but also possess the significant risk of ARGs transfer to other non-resistance bacteria within the confined environments. This phenomenon may lead to the emergence of habitat-specific microbial resistomes and subsequent emergence of virulent antibiotic-resistant pathogens with severe fish and consumer health consequences. In this study, gut microbiota of freshwater carp (Labeo rohita) was investigated by shotgun metagenomics to understand its taxonomic composition and functional capabilities. Metagenomic DNA, extracted from the fish gut, was subjected to sequencing on Illumina NextSeq to generate paired-end (PE) 2 x 150 bp sequencing reads. After the QC of raw sequencing data by Trimmomatic, taxonomic analysis by Kraken2 taxonomic sequence classification system revealed the presence of 36 phyla, 326 families and 985 genera in the fish gut microbiome. At phylum level, Proteobacteria accounted for more than three-fourths of total bacterial populations followed by Actinobacteria (14%) and Cyanobacteria (3%). Commonly used probiotic bacteria (Bacillus, Lactobacillus, Streptococcus, and Lactococcus) were found to be very less prevalent in fish gut. After sequencing data assembly by MEGAHIT v1.1.2 assembler and PROKKA automated analysis pipeline, pathway analysis revealed the presence of 1,608 Metacyc pathways in the fish gut microbiome. Biosynthesis pathways were found to be the most dominant (51%) followed by degradation (39%), energy-metabolism (4%) and fermentation (2%). Almost one-third (33%) of biosynthesis pathways were involved in the synthesis of secondary metabolites. Metabolic pathways for the biosynthesis of 35 antibiotic types were also present, and these accounted for 5% of overall metabolic pathways in the fish gut microbiome. Fifty-one different types of antibiotic resistance genes (ARGs) belonging to 15 antimicrobial resistance (AMR) gene families and conferring resistance against 24 antibiotic types were detected in fish gut. More than 90% ARGs in fish gut microbiome were against beta-lactams (penicillins, cephalosporins, penems, and monobactams). Resistance against tetracycline, macrolides, fluoroquinolones, and phenicols ranged from 0.7% to 1.3%. Some of the ARGs for multi-drug resistance were also found to be located on sequences of plasmid origin. The presence of pathogenic bacteria and ARGs on plasmid sequences suggested the potential risk due to horizontal gene transfer in the confined gut environment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=antibiotic%20resistance" title="antibiotic resistance">antibiotic resistance</a>, <a href="https://publications.waset.org/abstracts/search?q=fish%20gut" title=" fish gut"> fish gut</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20pathways" title=" metabolic pathways"> metabolic pathways</a>, <a href="https://publications.waset.org/abstracts/search?q=microbial%20diversity" title=" microbial diversity"> microbial diversity</a> </p> <a href="https://publications.waset.org/abstracts/99462/analysis-of-taxonomic-compositions-metabolic-pathways-and-antibiotic-resistance-genes-in-fish-gut-microbiome-by-shotgun-metagenomics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99462.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">144</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">62</span> History of Recurrent Mucosal Infections and Immune System Disorders Is Related to Complications of Non-infectious Anterior Uveitis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Barbara%20Torres%20Rives">Barbara Torres Rives</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Uveitis. Non-infectious anterior uveitis is a polygenic inflammatory eye disease, and it is suggested that mediated processes by the immune system (autoimmune or not) are the main mechanisms proposed in the pathogenesis of this type of uveitis. A relationship between infectious processes, digestive disorders, and a dysbiosis of the microbiome was recently described. In addition, alterations in the immune response associated with the initiation and progression of the disease have been described. Objective: The aim of this study was to identify factors related to the immune system associated with complicated non-infectious anterior uveitis. Methods: A cross-sectional observational analytical study was carried out. The universe consisted of all patients attending the ocular inflammation service of the Cuban Institute of Ophthalmology Ramón Pando Ferrer. The sample consisted of 213 patients diagnosed with non-infectious anterior uveitis. Results: Of the 213 patients with non-infectious anterior uveitis, the development of ophthalmologic complications predominated 56.3% (p=0.0094). In patients with complications was more frequent the presence of human leukocyte antigen-B27 allele (49.2%) (p<0.0001), decreased immunoglobulin G (24.2%, p=0.0124), increased immunoglobulin A (14.2%, p=0.0024), history of recurrent sepsis (59.2%, p=0.0018), recurrent respiratory infections (44.2%, p=0.0003), digestive alterations (40%, p=0.0013) and spondyloarthropathies (30%, p=0.0314). By logistic regression, it was observed that, for each completed year, the elevated risk for developing complicated non-infectious anterior uveitis in human leukocyte antigen-B27 allele positive patients (OR: 4.22, p=0.000), Conclusions: The control of recurrent sepsis at mucosal level and immunomodulation could prevent complications in non-infectious anterior uveitis. Therefore, the microbiome becomes the target of treatment and prevention of complications in non-infectious anterior uveitis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-infectious%20anterior%20uveitis" title="non-infectious anterior uveitis">non-infectious anterior uveitis</a>, <a href="https://publications.waset.org/abstracts/search?q=immune%20system%20disorders" title=" immune system disorders"> immune system disorders</a>, <a href="https://publications.waset.org/abstracts/search?q=recurrent%20mucosal%20infections" title=" recurrent mucosal infections"> recurrent mucosal infections</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a> </p> <a href="https://publications.waset.org/abstracts/157786/history-of-recurrent-mucosal-infections-and-immune-system-disorders-is-related-to-complications-of-non-infectious-anterior-uveitis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157786.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">90</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">61</span> Human Microbiome Hidden Association with Chronic and Autoimmune Diseases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elmira%20Davasaz%20Tabrizi">Elmira Davasaz Tabrizi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mu%CC%88s%CC%A7teba%20Sevil"> Müşteba Sevil</a>, <a href="https://publications.waset.org/abstracts/search?q=Ercan%20Arican"> Ercan Arican</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent decades, there has been a sharp increase in the prevalence of several unrelated chronic diseases. The use of long-term antibiotics for chronic illnesses is increasing. The antibiotic resistance occurrence and its relationship with host microbiomes are still unclear. Properties of the identifying antibodies have been the focus of chronic disease research, such as prostatitis or autoimmune. The immune system is made up of a complicated but well-organized network of cell types that constantly monitor and maintain their surroundings. The regulated homeostatic interaction between immune system cells and their surrounding environment shapes the microbial flora. Researchers believe that the disappearance of special bacterial species from our ancestral microbiota might have altered the body flora that can cause a rise in disease during the human life span. This unpleasant pattern demonstrates the importance of focusing on discovering and revealing the root causes behind the disappearance or alteration of our microbiota. In this review, we gathered the results of some studies that reveal changes in the diversity and quantity of microorganisms that may affect chronic and autoimmune diseases. Additionally, a Ph.D. thesis that is still in process as Metagenomic studies in chronic prostatitis samples is mentioned. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metagenomic" title="metagenomic">metagenomic</a>, <a href="https://publications.waset.org/abstracts/search?q=autoimmune" title=" autoimmune"> autoimmune</a>, <a href="https://publications.waset.org/abstracts/search?q=prostatitis" title=" prostatitis"> prostatitis</a>, <a href="https://publications.waset.org/abstracts/search?q=microbiome" title=" microbiome"> microbiome</a> </p> <a href="https://publications.waset.org/abstracts/159476/human-microbiome-hidden-association-with-chronic-and-autoimmune-diseases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159476.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge 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