Microbiome in the Framework of Predictive, Preventive and Personalised Medicine

The human body is inhabited by trillions of diverse microorganisms collectively called "microbiome" or "microbiota". Microbiota consists of bacteria, viruses, fungi, protozoa, and archaea. Microbiome demonstrates multi-faceted effects on human physical and mental health. Per evidence there is a multi-functional interplay between the whole-body microbiome composition on the epithelial surfaces including skin, nasal and oral cavities, airway, gastro-intestinal and urogenital tracts on one hand and on the other hand, the individual health status. Microbiota composition as well as an option to modulate it - together create a highly attractive operation area for the translational bio/medical research with multi-professional expertise and healthcare-relevant output in the framework of predictive, preventive and personalised medicine (PPPM/3 PM). Advanced PPPM strategies implemented in the microbiome area are expected to significantly improve individual outcomes and overall cost-efficacy of healthcare. According to the accumulated research data, corresponding diagnostic and treatment approaches are applicable to primary care (health risk assessment in individuals with sub-optimal health conditions and prevention of a disease development), secondary care (personalised treatment of clinically manifested disorders preventing a disease progression) and tertiary care (making palliation to an optimal management of non-curable diseases). In the current book, we do highlight the implementation potential of the microbiome-relevant research in the framework of predictive diagnostics, targeted prevention and treatments tailored to the individualised patient profile.Copyright © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Microbial Dysbiosis and Epithelial Dysfunction in Vitamin A-Deficient Lungs

Once believed to be sterile, recent studies now show microbes inhabiting healthy lungs that are dysregulated in patients with chronic obstructive pulmonary disease (COPD), asthma, tuberculosis (TB), and SARS-CoV-2 infection. Other studies have shown an increase in pulmonary disease and recurrent respiratory infections in malnourished patients. According to the World Health Organization, vitamin A deficiency (VAD) is now a major public health issue in low-income communities and many developing countries. While VAD has been shown to alter gene expression and tissue morphology in humans and mice, research suggests the lung microbiome plays an intimate role in the metabolic regulation, pathogen inhibition, and inflammatory responses in the lung. Whether dysbiosis is a cause or consequence of chronic respiratory conditions, or whether retinoic acid (RA) - the bioactive metabolite of Vitamin A - is essential for lung microbiome homeostasis, remains unknown. Therefore, we hypothesize that dietary VAD leads to epithelial remodeling which promotes microbial dysbiosis;the dysbiosis then perpetuates epithelial remodeling via host-microbe interactions. Our preliminary results show anatomical/pathological changes to the epithelium in VAD adult mouse lungs compared to controls (VAS). Using our Nkx2- 1creERT2/dnRAR Rosa26 tdTomato transgenic mouse model that selectively induces VAD in the adult lung epithelium following tamoxifen injections, our data supports the hypothesis that host epithelial aberration associated with dietary VAD is induced locally in the lung and not via distal or systemic mechanisms. Our data also indicates the onset of dysbiosis in adult mouse lungs as early as three weeks post-diet modulation as observed through changes in microbial composition in VAD mice compared to controls. Finally, our bulk RNAseq analysis of host and microbial gene signatures has uncovered mechanisms associated with microbial metabolic functions, ciliopathy, host cellular polarity, and immune response to infection, that are dysregulated in the absence of vitamin A. Further, we have also identified altered transcriptional activity of microbes that are traditionally symbiotic or pathobiotic under normal homeostasis. This work indicates the presence of specific host-microbe interactions that are essential for lung homeostasis and protection against lung infection and disease that are dysregulated or lost in the absence of dietary vitamin A.

My Journeys with Three Microbes in the Reproductive Tract

Problem: The placenta performs various functions of the lung/GI/GU tract for the developing fetus, while also moderating host defenses of the fetus against infections in utero, and likely educates the developing fetal immune system. It thus has long-term impacts on the health of both the woman and the child. Knowledge is limited about the underlying mechanisms that enable the placenta to serve as a protective barrier for the fetus against infection. The long-term goals of my research program are to, 1) elucidate the normal barriers to infection in the placenta and show how dysfunction in barrier function can lead to adverse maternal-fetal outcomes, 2) define how viral infections impact placental biology, and 3) characterize possible functional roles for the newly described microbiota at the maternal-fetal interface. Method of Study: To address the above questions, our research includes the use human placentas, primary human trophoblasts and immune cells derived from term placentas, cultured placental cells, trophoblast organoids, and mousemodels. Results: We found that placentas from women who gave birth prematurely exhibit reduced autophagy activity. Prematurity and reduced autophagy levels were also strongly associated with maternal infection. In a mouse model of pregnancy, we showed that placentas from mice deficient for Atg16L1 were significantly less able to withstand infection, and the deficient mice gave birth prematurely upon an inflammatory stimulus. We have also shown that the autophagy pathway plays a key role in ZIKV vertical transmission from mother to fetus. We demonstrated that hydroxychloroquine (HCQ), an autophagy inhibitor approved for use in pregnant women, can attenuate placental and fetal ZIKV infection and ameliorate adverse placental and fetal outcomes. More recently, we have identified a small molecule inhibitor that targets the NS2B-NS3 protease of ZIKV and inhibits viral replication. It has recently become evident that SARS-CoV-2 infection is also associated with adverse outcomes for pregnant women, including preterm birth, preeclampsia, and fetal growth restriction. We localized SARS-CoV-2 to the placenta and showed that infection alters the Renin Angiotensin System (RAS) that regulates blood pressure, thereby increasing risk for preeclampsia. In new work, we are showing that SARS-CoV-2 non-structural proteins affect autophagy in different ways than in Zika virus. Finally, we have discovered that the maternal fetal interface of the placenta harbors intracellular resident microbes, and functionally demonstrated that they do not induce any inflammatory response or cell death but may promote immune tolerance and support normal pregnancy outcomes. Conclusions: For the past 10 years of my career, I have been working on host microbial interactions at the maternal fetal interface. Our work has led to new insights into viral infections, showing how they co-opt host defenses, and that tolerance may have microbial drivers. We have shown how cellular pathways in the placenta such as autophagy and RAS mechanistically regulate host defenses against pathogens, including ZIKV and SARS-CoV-2. Additionally, our studies provide a foundation for understanding possible 'commensal' microbial- placental interactions and hint at the functional importance of microbes at the fetal maternal interface in maintaining placental health and supporting fetal development.

Machine learning based predictive model and systems-level network of host-microbe interactions in post-COVID-19 mucormycosis.

Mucormycosis, a rare infection is caused by fungi Mucorales. The affiliation of mucormycosis with Coronavirus disease (COVID-19) is a rising issue of concern in India. There have been numerous case reports of association of rhino-cerebral-orbital, angioinvasive, pulmonary, respiratory and gastrointestinal tract related mucormycosis in patients with history of COVID-19. The immune dysregulation, preposterous use of steroids, interleukin-6-directed therapies and mechanical ventilation in COVID-19 immunocompromised individuals hypothesizes and predisposes to advancement of mucormycosis. The gaps in mode of presentation, disease course, diagnosis and treatment of post-COVID-19 mucormycosis requires critical analysis in order to control its morbidity and incidence and for prevention and management of opportunistic infections in COVID-19 patients. Our study performs machine learning, systems biology and bioinformatics analysis of post-COVID-19 mucormycosis in India incorporating multitudinous techniques. Text mining identifies candidate characteristics of post-COVID-19 mucormycosis cases including city, gender, age, symptoms, clinical parameters, microorganisms and treatment. The characteristics are incorporated in a machine learning based disease model resulting in predictive potentiality of characteristics of post-COVID-19 mucormycosis. The characteristics are used to create a host-microbe interaction disease network comprising of interactions between microorganism, host-microbe proteins, non-specific markers, symptoms and drugs resulting in candidate molecules. R1A (Replicase polyprotein 1a) and RPS6 (Ribosomal Protein S6) are yielded as potential drug target and biomarker respectively via potentiality analysis and expression in patients. The potential risk factors, drug target and biomarker can serve as prognostic, early diagnostic and therapeutic molecules in post-COVID-19 mucormycosis requiring further experimental validation and analysis on post-COVID-19 mucormycosis cases.

The Role of the PFNA Operon of Bifidobacteria in the Recognition of Host's Immune Signals: Prospects for the Use of the FN3 Protein in the Treatment of COVID-19.

Bifidobacteria are some of the major agents that shaped the immune system of many members of the animal kingdom during their evolution. Over recent years, the question of concrete mechanisms underlying the immunomodulatory properties of bifidobacteria has been addressed in both animal and human studies. A possible candidate for this role has been discovered recently. The PFNA cluster, consisting of five core genes, pkb2, fn3, aaa-atp, duf58, tgm, has been found in all gut-dwelling autochthonous bifidobacterial species of humans. The sensory region of the species-specific serine-threonine protein kinase (PKB2), the transmembrane region of the microbial transglutaminase (TGM), and the type-III fibronectin domain-containing protein (FN3) encoded by the I gene imply that the PFNA cluster might be implicated in the interaction between bacteria and the host immune system. Moreover, the FN3 protein encoded by one of the genes making up the PFNA cluster, contains domains and motifs of cytokine receptors capable of selectively binding TNF-α. The PFNA cluster could play an important role for sensing signals of the immune system. Among the practical implications of this finding is the creation of anti-inflammatory drugs aimed at alleviating cytokine storms, one of the dire consequences resulting from SARS-CoV-2 infection.

Network biology to uncover functional and structural properties of the plant immune system.

In the last two decades, advances in network science have facilitated the discovery of important systems' entities in diverse biological networks. This graph-based technique has revealed numerous emergent properties of a system that enable us to understand several complex biological processes including plant immune systems. With the accumulation of multiomics data sets, the comprehensive understanding of plant-pathogen interactions can be achieved through the analyses and efficacious integration of multidimensional qualitative and quantitative relationships among the components of hosts and their microbes. This review highlights comparative network topology analyses in plant-pathogen co-expression networks and interactomes, outlines dynamic network modeling for cell-specific immune regulatory networks, and discusses the new frontiers of single-cell sequencing as well as multiomics data integration that are necessary for unraveling the intricacies of plant immune systems.