Study of apoptotic deletion mediated by Bifidobacterium longum with construction of recombinant strains for Serpin encoding gene and phenotypes comparison in a pig cell model

The first part of the research project of the Co-Advisorship Ph.D Thesis was aimed to select the best Bifidobacterium longum strains suitable to set the basis of our study. We were looking for strains with the abilities to colonize the intestinal mucosa and with good adhesion capacities, so that we can test these strains to investigate their ability to induce apoptosis in “damaged” intestinal cells. Adhesion and apoptosis are the two process that we want to study to better understand the role of an adhesion protein that we have previously identified and that have top scores homologies with the recent serpin encoding gene identified in B. longum by Nestlè researchers. Bifidobacterium longum is a probiotic, known for its beneficial effects to the human gut and even for its immunomodulatory and antitumor activities. Recently, many studies have stressed out the intimate relation between probiotic bacteria and the GIT mucosa and their influence on human cellular homeostasis. We focused on the apoptotic deletion of cancer cells induced by B. longum. This has been valued in vitro, performing the incubation of three B.longum strains with enterocyte-like Caco- 2 cells, to evidence DNA fragmentation, a cornerstone of apoptosis. The three strains tested were defined for their adhesion properties using adhesion and autoaggregation assays. These features are considered necessary to select a probiotic strain. The three strains named B12, B18 and B2990 resulted respectively: “strong adherent”, “adherent” and “non adherent”. Then, bacteria were incubated with Caco-2 cells to investigate apoptotic deletion. Cocultures of Caco-2 cells with B. longum resulted positive in DNA fragmentation test, only when adherent strains were used (B12 and B18). These results indicate that the interaction with adherent B. longum can induce apoptotic deletion of Caco-2 cells, suggesting a role in cellular homeostasis of the gastrointestinal tract and in restoring the ecology of damaged colon tissues. These results were used to keep on researching and the strains tested were used as recipient of recombinant techniques aimed to originate new B.longum strains with enhanced capacity of apoptotic induction in “damaged” intestinal cells. To achieve this new goal it was decided to clone the serpin encoding gene of B. longum, so that we can understand its role in adhesion and apoptosis induction. Bifidobacterium longum has immunostimulant activity that in vitro can lead to apoptotic response of Caco-2 cell line. It secretes a hypothetical eukaryotic type serpin protein, which could be involved in this kind of deletion of damaged cells. We had previously characterised a protein that has homologies with the hypothetical serpin of B. longum (DD087853). In order to create Bifidobacterium serpin transformants, a B. longum cosmid library was screened with a PCR protocol using specific primers for serpin gene. After fragment extraction, the insert named S1 was sub-cloned into pRM2, an Escherichia coli - Bifidobacterium shuttle vector, to construct pRM3. Several protocols for B. longum transformation were performed and the best efficiency was obtained using MRS medium and raffinose. Finally bacterial cell supernatants were tested in a dotblot assay to detect antigens presence against anti-antitrypsin polyclonal antibody. The best signal was produced by one starin that has been renamed B. longum BLKS 7. Our research study was aimed to generate transformants able to over express serpin encoding gene, so that we can have the tools for a further study on bacterial apoptotic induction of Caco-2 cell line. After that we have originated new trasformants the next step to do was to test transformants abilities when exposed to an intestinal cell model. In fact, this part of the project was achieved in the Department of Biochemistry of the Medical Faculty of the University of Maribor, guest of the abroad supervisor of the Co-Advisorship Doctoral Thesis: Prof. Avrelija Cencic. In this study we examined the probiotic ability of some bacterial strains using intestinal cells from a 6 years old pig. The use of intestinal mammalian cells is essential to study this symbiosis and a functional cell model mimics a polarised epithelium in which enterocytes are separated by tight junctions. In this list of strains we have included the Bifidobacterium longum BKS7 transformant strain that we have previously originated; in order to compare its abilities. B. longum B12 wild type and B. longum BKS7 transformant and eight Lactobacillus strains of different sources were co-cultured with porcine small intestine epithelial cells (PSI C1) and porcine blood monocytes (PoM2) in Transwell filter inserts. The strains, including Lb. gasseri, Lb. fermentum, Lb. reuterii, Lb. plantarum and unidentified Lactobacillus from kenyan maasai milk and tanzanian coffee, were assayed for activation of cell lines, measuring nitric oxide by Griess reaction, H202 by tetramethylbenzidine reaction and O2 - by cytochrome C reduction. Cytotoxic effect by crystal violet staining and induction on metabolic activity by MTT cell proliferation assay were tested too. Transepithelial electrical resistance (TER) of polarised PSI C1 was measured during 48 hours co-culture. TER, used to observe epithelium permeability, decrease during pathogenesis and tissue becomes permeable to ion passive flow lowering epithelial barrier function. Probiotics can prevent or restore increased permeability. Lastly, dot-blot was achieved against Interleukin-6 of treated cells supernatants. The metabolic activity of PoM2 and PSI C1 increased slightly after co-culture not affecting mitochondrial functions. No strain was cytotoxic over PSI C1 and PoM2 and no cell activation was observed, as measured by the release of NO2, H202 and O2 - by PoM2 and PSI C1. During coculture TER of polarised PSI C1 was two-fold higher comparing with constant TER (~3000 ) of untreated cells. TER raise generated by bacteria maintains a low permeability of the epithelium. During treatment Interleukin-6 was detected in cell supernatants at several time points, confirming immunostimulant activity. All results were obtained using Lactobacillus paracasei Shirota e Carnobacterium divergens as controls. In conclusion we can state that both the list of putative probiotic bacteria and our new transformant strain of B. longum are not harmful when exposed to intestinal cells and could be selected as probiotics, because can strengthen epithelial barrier function and stimulate nonspecific immunity of intestinal cells on a pig cell model. Indeed, we have found out that none of the strains tested that have good adhesion abilities presents citotoxicity to the intestinal cells and that non of the strains tested can induce cell lines to produce high level of ROS, neither NO2. Moreover we have assayed even the capacity of producing certain citokynes that are correlated with immune response. The detection of Interleukin-6 was assayed in all our samples, including B.longum transformant BKS 7 strain, this result indicates that these bacteria can induce a non specific immune response in the intestinal cells. In fact, when we assayed the presence of Interferon-gamma in cells supernatant after bacterial exposure, we have no positive signals, that means that there is no activation of a specific immune response, thus confirming that these bacteria are not recognize as pathogen by the intestinal cells and are certainly not harmful for intestinal cells. The most important result is the measure of Trans Epithelial Electric Resistance that have shown how the intestinal barrier function get strengthen when cells are exposed to bacteria, due to a reduction of the epithelium permeability. We have now a new strain of B. longum that will be used for further studies above the mechanism of apoptotic induction to “damaged cells” and above the process of “restoring ecology”. This strain will be the basis to originate new transformant strains for Serpin encoding gene that must have better performance and shall be used one day even in clinical cases as in “gene therapy” for cancer treatment and prevention.

Convergent bioenergetic defects in Coenzyme Q10 depleted cells by pharmacological inhibition of coq2 enzyme (p-hydroxybenzoate polyprenyl transferase) and by genome editing technology targeting the encoding gene (COQ2)

Primary CoQ10 deficiency diseases encompass a heterogeneous spectrum of clinical phenotypes. Among these, defect or mutation on COQ2 gene, encoding a para-hydroxybenzoate polyprenyl transferase, have been associated with different diseases. Understanding the functional and metabolic impact of COQ2 mutation and the consequent CoQ10 deficiency is still a matter of debate. To date the aetiology of the neurological phenotypes correlated to CoQ10 deficiency does not present a clear genotype-phenotype association. In addition to the metabolic alterations due to Coenzyme Q depletion, the impairment of mitochondrial function, associated with the reduced CoQ level, could play a significant role in the metabolic flexibility of cancer. This study aimed to characterize the effect of varying degrees of CoQ10 deficiency and investigate the multifaceted aspect of CoQ10 depletion and its impact on cell metabolism. To induced CoQ10 depletion, different cell models were used, employing a chemical and genome editing approach. In T67 and MCF-7 CoQ10 depletion was achieved by a competitive inhibitor of the enzyme, 4-nitrobenzoate (4-NB), whereas in SH-SY5Y the COQ2 gene was edited via CRISPR-Cas9 cutting edge technology.

Tensor-Train decomposition for image classification problems

In these last years a great effort has been put in the development of new techniques for automatic object classification, also due to the consequences in many applications such as medical imaging or driverless cars. To this end, several mathematical models have been developed from logistic regression to neural networks. A crucial aspect of these so called classification algorithms is the use of algebraic tools to represent and approximate the input data. In this thesis, we examine two different models for image classification based on a particular tensor decomposition named Tensor-Train (TT) decomposition. The use of tensor approaches preserves the multidimensional structure of the data and the neighboring relations among pixels. Furthermore the Tensor-Train, differently from other tensor decompositions, does not suffer from the curse of dimensionality making it an extremely powerful strategy when dealing with high-dimensional data. It also allows data compression when combined with truncation strategies that reduce memory requirements without spoiling classification performance. The first model we propose is based on a direct decomposition of the database by means of the TT decomposition to find basis vectors used to classify a new object. The second model is a tensor dictionary learning model, based on the TT decomposition where the terms of the decomposition are estimated using a proximal alternating linearized minimization algorithm with a spectral stepsize.

Uncovering the encoding and transmission of behaviourally relevant information in neural activity

Most cognitive functions require the encoding and routing of information across distributed networks of brain regions. Information propagation is typically attributed to physical connections existing between brain regions, and contributes to the formation of spatially correlated activity patterns, known as functional connectivity. While structural connectivity provides the anatomical foundation for neural interactions, the exact manner in which it shapes functional connectivity is complex and not yet fully understood. Additionally, traditional measures of directed functional connectivity only capture the overall correlation between neural activity, and provide no insight on the content of transmitted information, limiting their ability in understanding neural computations underlying the distributed processing of behaviorally-relevant variables. In this work, we first study the relationship between structural and functional connectivity in simulated recurrent spiking neural networks with spike timing dependent plasticity. We use established measures of time-lagged correlation and overall information propagation to infer the temporal evolution of synaptic weights, showing that measures of dynamic functional connectivity can be used to reliably reconstruct the evolution of structural properties of the network. Then, we extend current methods of directed causal communication between brain areas, by deriving an information-theoretic measure of Feature-specific Information Transfer (FIT) quantifying the amount, content and direction of information flow. We test FIT on simulated data, showing its key properties and advantages over traditional measures of overall propagated information. We show applications of FIT to several neural datasets obtained with different recording methods (magneto and electro-encephalography, spiking activity, local field potentials) during various cognitive functions, ranging from sensory perception to decision making and motor learning. Overall, these analyses demonstrate the ability of FIT to advance the investigation of communication between brain regions, uncovering the previously unaddressed content of directed information flow.