Towards light based dynamic control of synthetic biological systems

For the field of synthetic biology, the adaptation of principles, from the well established traditional engineering disciplines, like mechanical and electrical engineering, in order to realise complex synthetic biological circuits, is an intriguing prospect. These principles can enable a forward engineering, rational design and implementation approach, where a system's properties can be predicted or designed in silico followed by the manufacturing of the in vivo system, that can be tested, used or redesigned in the most efficient possible way. Achieving control over these circuits, is one of the important topics of the field, for these applications to become robust and render useful functions applicable to energy, medicine, pharmaceuticals and agriculture industries. In this work, I attempt to explore light, as a promising control 'dial' for synthetic circuitry. Light is fast, economic compared to chemicals, it can be interfaced with electronics, it is reversible in its effect and can be applied at a fine spatio-temporal resolution. These characteristics, are absent from the classically used chemical inducers, meaning that light, can open new possibilities for the user to control synthetic systems, or even facilitate the cell to cell communication, within population based networks. This work, is a contribution towards harnessing the advantages of light, for achieving control over synthetic circuits. More specifically, I start with the detailed theoretical and experimental study of the Cph8 two component system, a synthetic chimeric receptor which is responsive to red light. This is done, in order to develop a sufficient theoretical understanding of it, through detailed mechanistic modelling, in order to connect the specific system with the toggle switch and the dual feedback oscillator, in an optimal way and achieve control of these devices through light. The developed model, was able to highlight the main aspects and mechanisms inherent to its structure, describe most of the observations from the experimental system, to also make quantitative predictions. The second part of this work, was the development of novel promoters, that can be regulated by a commonly used transcription factor, such as LacI, but also, light responsive regulators like OmpR and CcaR. This yielded a direct way to integrate light and chemical inputs, into a single output, while the dual regulation, allowed to connect and modulate the toggle switch without the need of additional transcription factors. The latter, a light tuneable toggle switch, showed indications that it can function as a memory controller that can be reset by light. Finally, I show the design and modelling of a light tuneable dual feedback oscillator, where light of one wavelength can be used to tune the amplitude, while another wavelength can tune the period. The developed models and synthetic circuits are expected to contribute towards implementing finely tuned and controlled synthetic circuits through light.Open Acces

Putative antimicrobial peptides within bacterial proteomes affect bacterial predominance: a network analysis perspective

The predominance of bacterial taxa in the gut, was examined in view of the putative antimicrobial peptide sequences (AMPs) within their proteomes. The working assumption was that compatible bacteria would share homology and thus immunity to their putative AMPs, while competing taxa would have dissimilarities in their proteome-hidden AMPs. A network–based method (“Bacterial Wars”) was developed to handle sequence similarities of predicted AMPs among UniProt-derived protein sequences from different bacterial taxa, while a resulting parameter (“Die” score) suggested which taxa would prevail in a defined microbiome. T he working hypothesis was examined by correlating the calculated Die scores, to the abundance of bacterial taxa from gut microbiomes from different states of health and disease. Eleven publicly available 16S rRNA datasets and a dataset from a full shotgun metagenomics served for the analysis. The overall conclusion was that AMPs encrypted within bacterial proteomes affected the predominance of bacterial taxa in chemospheres

Assessing the dynamics and complexity of disease pathogenicity using 4-dimensional immunological data

Investigating disease pathogenesis and personalized prognostics are major biomedical needs. Because patients sharing the same diagnosis can experience different outcomes, such as survival or death, physicians need new personalized tools, including those that rapidly differentiate several inflammatory phases. To address these topics, a pattern recognition-based method (PRM) that follows an inverse problem approach was designed to assess, in <10min, eight concepts: synergy, pleiotropy, complexity, dynamics, ambiguity, circularity, personalized outcomes, and explanatory prognostics (pathogenesis). By creating thousands of secondary combinations derived from blood leukocyte data, the PRM measures synergic, pleiotropic, complex and dynamic data interactions, which provide personalized prognostics while some undesirable features—such as false results and the ambiguity associated with data circularity-are prevented. Here, this method is compared to Principal Component Analysis (PCA) and evaluated with data collected from hantavirus-infected humans and birds that appeared to be healthy. When human data were examined, the PRM predicted 96.9 % of all surviving patients while PCA did not distinguish outcomes. Demonstrating applications in personalized prognosis, eight PRM data structures sufficed to identify all but one of the survivors. Dynamic data patterns also distinguished survivors from non-survivors, as well as one subset of non-survivors, which exhibited chronic inflammation. When the PRM explored avian data, it differentiated immune profiles consistent with no, early, or late inflammation. Yet, PCA did not recognize patterns in avian data. Findings support the notion that immune responses, while variable, are rather deterministic: a low number of complex and dynamic data combinations may be enough to, rapidly, unmask conditions that are neither directly observable nor reliably forecasted.Conacyt of Mexico (Consejo Nacional de Ciencia y Tecnologíahttp://www.frontiersin.org/Immunologyam2020Veterinary Tropical Disease

High throughput sequencing technologies as a new toolbox for deep analysis, characterization and potentially authentication of protection designation of origin cheeses?

Protected Designation of Origin (PDO) labeling of cheeses has been established by the European Union (EU) as a quality policy that assures the authenticity of a cheese produced in a specific region by applying traditional production methods. However, currently used scientific methods for differentiating and establishing PDO are limited in terms of time, cost, accuracy and their ability to identify through quantifiable methods PDO fraud. Cheese microbiome is a dynamic community that progressively changes throughout ripening, contributing via its metabolism to unique qualitative and sensorial characteristics that differentiate each cheese. High Throughput Sequencing (HTS) methodologies have enabled the more precise identification of the microbial communities developed in fermented cheeses, characterization of their population dynamics during the cheese ripening process, as well as their contribution to the development of specific organoleptic and physio-chemical characteristics. Therefore, their application may provide an additional tool to identify the key microbial species that contribute to PDO cheeses unique sensorial characteristics and to assist to define their typicityin order to distinguish them from various fraudulent products. Additionally, they may assist the cheese-makers to better evaluate the quality, as well as the safety of their products. In this structured literature review indications are provided on the potential for defining PDO enabling differentiating factors based on distinguishable microbial communities shaped throughout the ripening procedures associated to cheese sensorial characteristics, as revealed through metagenomic and metatranscriptomic studies. Conclusively, HTS applications, even though still underexploited, have the potential to demonstrate how the cheese microbiome can affect the ripening process and sensorial characteristics formation via the catabolism of the available nutrients and interplay with other compounds of the matrix and/or production of microbial origin metabolites and thus their further quality enhancement

In Silico Identification of Antimicrobial Peptides in the Proteomes of Goat and Sheep Milk and Feta Cheese

Milk and dairy products are a major functional food group of growing scientific and commercial interest due to their nutritional value and bioactive &ldquo;load&rdquo;. A major fraction of the latter is attributed to milk&rsquo;s rich protein content and its biofunctional peptides that occur naturally during digestion. On the basis of the identified proteome datasets of milk whey from sheep and goat breeds in Greece and feta cheese obtained during previous work, we applied an in silico workflow to predict and characterise the antimicrobial peptide content of these proteomes. We utilised existing tools for predicting peptide sequences with antimicrobial traits complemented by in silico protein cleavage modelling to identify frequently occurring antimicrobial peptides (AMPs) in the gastrointestinal (GI) tract in humans. The peptides of interest were finally assessed for their stability with respect to their susceptibility to cleavage by endogenous proteases expressed along the intestinal part of the GI tract and ranked with respect to both their antimicrobial and stability scores

Investigating the Transition of Pre-Symptomatic to Symptomatic Huntington’s Disease Status Based on Omics Data

Huntington&rsquo;s disease is a rare neurodegenerative disease caused by a cytosine&ndash;adenine&ndash;guanine (CAG) trinucleotide expansion in the Huntingtin (HTT) gene. Although Huntington&rsquo;s disease (HD) is well studied, the pathophysiological mechanisms, genes and metabolites involved in HD remain poorly understood. Systems bioinformatics can reveal synergistic relationships among different omics levels and enables the integration of biological data. It allows for the overall understanding of biological mechanisms, pathways, genes and metabolites involved in HD. The purpose of this study was to identify the differentially expressed genes (DEGs), pathways and metabolites as well as observe how these biological terms differ between the pre-symptomatic and symptomatic HD stages. A publicly available dataset from the Gene Expression Omnibus (GEO) was analyzed to obtain the DEGs for each HD stage, and gene co-expression networks were obtained for each HD stage. Network rewiring, highlights the nodes that change most their connectivity with their neighbors and infers their possible implication in the transition between different states. The CACNA1I gene was the mostly highly rewired node among pre-symptomatic and symptomatic HD network. Furthermore, we identified AF198444 to be common between the rewired genes and DEGs of symptomatic HD. CNTN6, DEK, LTN1, MST4, ZFYVE16, CEP135, DCAKD, MAP4K3, NUPL1 and RBM15 between the DEGs of pre-symptomatic and DEGs of symptomatic HD and CACNA1I, DNAJB14, EPS8L3, HSDL2, SNRPD3, SOX12, ACLY, ATF2, BAG5, ERBB4, FOCAD, GRAMD1C, LIN7C, MIR22, MTHFR, NABP1, NRG2, OTC, PRAMEF12, SLC30A10, STAG2 and Y16709 between the rewired genes and DEGs of pre-symptomatic HD. The proteins encoded by these genes are involved in various biological pathways such as phosphatidylinositol-4,5-bisphosphate 3-kinase activity, cAMP response element-binding protein binding, protein tyrosine kinase activity, voltage-gated calcium channel activity, ubiquitin protein ligase activity, adenosine triphosphate (ATP) binding, and protein serine/threonine kinase. Additionally, prominent molecular pathways for each HD stage were then obtained, and metabolites related to each pathway for both disease stages were identified. The transforming growth factor beta (TGF-&beta;) signaling (pre-symptomatic and symptomatic stages of the disease), calcium (Ca2+) signaling (pre-symptomatic), dopaminergic synapse pathway (symptomatic HD patients) and Hippo signaling (pre-symptomatic) pathways were identified. The in silico metabolites we identified include Ca2+, inositol 1,4,5-trisphosphate, sphingosine 1-phosphate, dopamine, homovanillate and L-tyrosine. The genes, pathways and metabolites identified for each HD stage can provide a better understanding of the mechanisms that become altered in each disease stage. Our results can guide the development of therapies that may target the altered genes and metabolites of the perturbed pathways, leading to an improvement in clinical symptoms and hopefully a delay in the age of onset

Selective Delivery to Cardiac Muscle Cells Using Cell-Specific Aptamers

In vivo SELEX is an advanced adaptation of Systematic Evolution of Ligands by Exponential Enrichment (SELEX) that allows the development of aptamers capable of recognizing targets directly within their natural microenvironment. While this methodology ensures a higher translation potential for the selected aptamer, it does not select for aptamers that recognize specific cell types within a tissue. Such aptamers could potentially improve the development of drugs for several diseases, including neuromuscular disorders, by targeting solely the proteins involved in their pathogenesis. Here, we describe our attempt to utilize in vivo SELEX with a modification in the methodology that drives the selection of intravenously injected aptamers towards a specific cell type of interest. Our data suggest that the incorporation of a cell enrichment step can direct the in vivo localization of RNA aptamers into cardiomyocytes, the cardiac muscle cells, more readily over other cardiac cells. Given the crucial role of cardiomyocytes in the disease pathology in DMD cardiomyopathy and therapy, these aptamers hold great potential as drug delivery vehicles with cardiomyocyte selectivity

Dysbiosis and Enhanced Beta-Defensin Production in Hair Follicles of Patients with Lichen Planopilaris and Frontal Fibrosing Alopecia

Despite their distinct clinical manifestation, frontal fibrosing alopecia (FFA) and lichen planopilaris (LPP) display similar histopathologic features. Aberrant innate immune responses to endogenous or exogenous triggers have been discussed as factors that could drive inflammatory cascades and the collapse of the stem cell niche. In this exploratory study, we investigate the bacterial composition of scalp skin and plucked hair follicles (HF) of patients with FFA, LPP and alopecia areata circumscripta (AAc), as well as healthy individuals, in relation to cellular infiltrates and the expression of defense mediators. The most abundant genus in lesional and non-lesional HFs of LPP and FFA patients was Staphylococcus, while Lawsonella dominated in healthy individuals and in AAc patients. We observed statistically significant differences in the ratio of Firmicutes to Actinobacteria between healthy scalp, lesional, and non-lesional sites of FFA and LPP patients. This marked dysbiosis in FFA and LPP in compartments close to the bulge was associated with increased HβD1 and HβD2 expression along the HFs from lesional sites, while IL-17A was increased in lesional HF from AAc patients. The data encourage further studies on how exogenous factors and molecular interactions across the HF epithelium could contribute to disease onset and propagation

Dysbiosis and Enhanced Beta-Defensin Production in Hair Follicles of Patients with Lichen Planopilaris and Frontal Fibrosing Alopecia

Despite their distinct clinical manifestation, frontal fibrosing alopecia (FFA) and lichen planopilaris (LPP) display similar histopathologic features. Aberrant innate immune responses to endogenous or exogenous triggers have been discussed as factors that could drive inflammatory cascades and the collapse of the stem cell niche. In this exploratory study, we investigate the bacterial composition of scalp skin and plucked hair follicles (HF) of patients with FFA, LPP and alopecia areata circumscripta (AAc), as well as healthy individuals, in relation to cellular infiltrates and the expression of defense mediators. The most abundant genus in lesional and non-lesional HFs of LPP and FFA patients was Staphylococcus, while Lawsonella dominated in healthy individuals and in AAc patients. We observed statistically significant differences in the ratio of Firmicutes to Actinobacteria between healthy scalp, lesional, and non-lesional sites of FFA and LPP patients. This marked dysbiosis in FFA and LPP in compartments close to the bulge was associated with increased HβD1 and HβD2 expression along the HFs from lesional sites, while IL-17A was increased in lesional HF from AAc patients. The data encourage further studies on how exogenous factors and molecular interactions across the HF epithelium could contribute to disease onset and propagation

Serum miRNAs as biomarkers for the rare types of muscular dystrophy

Muscular dystrophies are a group of disorders that cause progressive muscle weakness. There is an increasing interest for the development of biomarkers for these disorders and specifically for Duchene Muscular Dystrophy. Limited research however, has been performed on the biomarkers' development for the most rare muscular dystrophies, like the Facioscapulohumeral Muscular Dystrophy, Limb-Girdle Muscular Dystrophy and Myotonic Dystrophy type 2. Here, we aimed to identify novel serum-based miRNA biomarkers for these rare muscular dystrophies, through high-throughput next-generation RNA sequencing. We identified many miRNAs that associate with muscular dystrophy patients compared to controls. Based on a series of selection criteria, the two best candidate miRNAs for each of these disorders were chosen and validated in a larger number of patients. Our results showed that miR-223-3p and miR-206 are promising serum-based biomarkers for Facioscapulohumeral Muscular Dystrophy type 1, miR-143-3p and miR-486-3p for Limb-Girdle Muscular Dystrophy type 2A whereas miR-363-3p and miR-25-3p associate with Myotonic Dystrophy type 2. Some of the identified miRNAs were significantly elevated in the serum of the patients compared to controls, whereas some others were lower. In conclusion, we provide new evidence that certain circulating miRNAs may be used as biomarkers for three types of rare muscular dystrophies.This Project (POST-DOC/0916/0235) was co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research and Innovation Foundation. A.C.K, A.O., M.T. and G.M.S. were funded by the European Commission Research Executive Agency Grant BIORISE [number 669026], under the Spreading Excellence, Widening Participation, Science with and for Society Framework. H.L. receives support from the Canadian Institutes of Health Research (Foundation Grant FDN-167281), the Canadian Institutes of Health Research and Muscular Dystrophy Canada (Network Catalyst Grant for NMD4C), the Canada Foundation for Innovation (CFI-JELF 38412), and the Canada Research Chairs program (Canada Research Chair in Neuromuscular Genomics and Health, 950-232279