During the poster sessions of the 1^st International Biotechnology Conference, we present the various research initiatives we have developed within the area of Microbial Ecology of the Universidad San Francisco de Quito (USFQ).

Microbial ecology is the branch of ecology that investigates microorganisms in their ecosystems or within natural tissues, which exhibit essential functions for all living beings on our planet. It includes the study of symbioses, biogeochemical cycles and the interaction of microbes with anthropogenic effects such as pollution and climate change.

Our research team focuses on the associations between plants or animals and their respective microorganisms, thereby integrating functional macroecology with molecular and applied microbiology.

Recent revolutions in genomics have delivered an interesting toolbox of promising techniques that can help us understand the enormous amount of data generated by translating all the genetic information.

Instead of focusing on single genes, we are now able to sequence whole genomes of millions of DNA molecules, and recently it is possible to analyse a mix of many different species altogether in one single sample.

These advances allow us to accurately study the identification of the microbial community that lives in or around multicellular organisms. In addition, in a country like Ecuador with an enormous visible MACRObiodiversity, we hypothesize that the invisible MICRObiodiversity has co-evolved to a similar magnitude or even higher.

Currently, we are developing multidisciplinary research lines that focus on functional microbiomes of emblematic species which inhabit diverse landscapes like the Andean highlands, the Amazon rainforest and soon at the Galápagos Islands. We aim to facilitate the knowledge of microbiomes in benefit of the challenges that confront our planet, for instance improving the disease resistance of crops and to identify the effects that climate change might have on the health of wild populations of migratory species like humpback whales.

Hemophilia can be defined as a genetic disorder in which the body loses its capability to clot blood, and hence can’t stop blood flow. It is an X- linked recessive disease, hence mostly seen in males, with its severity significantly reduced in females. In India, hemophilia has an occurrence of 1 per 10,000 births, which generally progresses to a chronic disability or premature death in subjects left untreated or provided with suboptimal treatment, a case prevalent in India [1]. The two major types of this condition are hemophilia A or factor VIII deficiency and hemophilia B or factor IX deficiency. In addition, hemophilia C is a rare category in which inhibitory antibodies develop which show high affinity to procoagulants, thus neutralizing the effect of a coagulation factor. Inhibitors are much less common in patients with hemophilia B than in those with hemophilia A. The F8 gene present on the X chromosome is responsible for guiding the production of coagulation factor VIII, essential for forming blood clots. In hemophilia A, mutation results from two gross (140 kbp or 600 kbp) chromosomal inversions that involve introns 1 and 22, respectively. Similarly, the F9 gene present on the X chromosome mutates through several different mechanisms to give rise to hemophilia B condition. The conditions associated with hemophilia Leyden, ribosome readthrough of nonsense mutation and apparently ‘silent’ changes that do not alter amino acids are the major mutations studied. It has been observed that reconstitution with 1–2% of the clotting factor helps uplift the quality of life, while 5–20% reconstitution is required to ameliorate the genetic disorder. Gene-specific genome editing is preferred over random integration of expression cassettes as this helps avoid genotoxicity and achieve the required physiological levels of expression. Advances in genome engineering based on CRISPR- associated RNA- guided endonuclease Cas9 are empowering the guidance of the said endonuclease to target locations by a short RNA search string [2]. It requires a programmable sequence-specific RNA to direct it and introduce cleavage and double-stranded breaks at the target site. In case of hemophilia A, induced pluripotent stem cells (iPSCs) can be derived from patients with inversion genotypes with an aim to revert these chromosomal conditions to the corrected state with the assistance of CRISPR- Cas9 nucleases [3]. The endothelial cells from the corrected iPSCs can be checked for expression of F8 gene and the production of factor VIII. Likewise, in case of hemophilia B, delivery of naked Cas9-sgRNA plasmid and donor DNA, aiming to recover the mutation has shown a detectable gene correction (>1%) in F9 alleles of hepatocytes [4]. To construct the related plasmids, an AAVS1-Cas9-sgRNA plasmid is designed to cut the AAVSI locus in human. Subsequently, two donor plasmids are designed to insert GFP and F9 cDNA into the designated AAVS1 locus. Whole genome sequencing (WGS) is used in combination with this editing method to identify off-target mutations, to ensure that editing takes place at the desired site. The technique offers several benefits over the popularly used Adeno- associated viral (AAV) vectors such as precision, decreased insertional oncogenesis and control through an endogenous promoter [5]. The CRISPR/Cas9- mediated genome editing with an AAV8 vector has been put to use to provide an adjustable path to induce double-strand breaks at the target genes in hepatocytes [6]. The foremost need for CRISPR-Cas9 is the identification of targets that have undergone a mutation, which has led to the development of the said condition. Although a few targets are known, none of the target mutation has been capable to render a 5-20 percent of reconstitution that is required for the elimination of the disorder. Hence, there is a need to find novel targets for the CRISPR-Cas9 system, which in turn requires the assistance of computational tools. The aim of this study is to identify positive CRISPR-Cas9 targets which would help in better and more accurate treatment of the disorder with computational biology facilitating the research. The study provide targets which possess minimum off-target mutations, providing maximum reconstitution for hemophilia.

References

[1] Kar, A., Phadnis, S., Dharmarajan, S., & Nakade, J. (2014). Epidemiology & social costs of haemophilia in India. The Indian journal of medical research, 140(1), 19.

[2] Hsu, P. D., Lander, E. S., & Zhang, F. (2014). Development and applications of CRISPR-Cas9 for genome engineering. Cell, 157(6), 1262-1278.

[3] Park, C. Y., Kim, D. H., Son, J. S., Sung, J. J., Lee, J., Bae, S., ... & Kim, J. S. (2015). Functional correction of large factor VIII gene chromosomal inversions in hemophilia A patient-derived iPSCs using CRISPR-Cas9. Cell stem cell, 17(2), 213-220.

[4] Huai, C., Jia, C., Sun, R., Xu, P., Min, T., Wang, Q., ... & Lu, D. (2017). CRISPR/Cas9-mediated somatic and germline gene correction to restore hemostasis in hemophilia B mice. Human genetics, 136(7), 875-883.

[5] Doshi, B. S., & Arruda, V. R. (2018). Gene therapy for hemophilia: what does the future hold?.Therapeutic advances in hematology, 9(9), 273-293.

[6] Ohmori, T., Nagao, Y., Mizukami, H., Sakata, A., Muramatsu, S. I., Ozawa, K., ... & Sakata, Y. (2017). CRISPR/Cas9-mediated genome editing via postnatal administration of AAV vector cures haemophilia B mice. Scientific reports, 7(1), 4159.

Cancer stands as major cause of mortality in the world, and it's the morbidity has significantly increased in both developing and developed nations. In spite of the recent advancement in cancer therapies, the clinical follow-up still lags far behind.Recent studies show that, stem cells are bestowed with distinctive functions, like tumor cells relocation, immunosuppression and production of bioactive elements, that helps in cancer targeting that bypassobstacles.Recent understanding show that Preclinical stem cell-based strategies has proved potential for targeted anti-tumor therapy applications. Stem cell applications in modulation and remodeling of immune system happens to be frequent procedure used past ten years in successfully treating tumor.Generation of human somatic cells into induced pluripotent stem cells (iPSCs) has often been a time consuming laborious intensive and expensive process. Additionally, the major problem with iPSCs is their tendency to revert to original somatic state. Hence, a robust computational model in discovering genes/molecules necessary for iPSC generation and maintenance can be a major leap towards in stem cell research.The synergistic combination of genetic relationship data, advanced computing hardware and nonlinear algorithms and could make artificially-induced pluripotent stem cells (aiPSC) a near future reality. Genes or proteins that are known to be essential in human pluripotent stem cells (hPSC) could possibly be used for system modelling. The present investigation is aimed to develop an unsupervised deep machine learning technology for the prediction of genes relevant in aiPSC production and its maintenance for both common and rare diseases making it a cost-effective approach.

The distribution coefficient (log P) is an important molecular characteristic that allows us to estimate the lipophilicity of chemical compounds and predict how a drug will behave, fundamentally against the processes of absorption and excretion. The experimental determination of this and other properties of interest has several limitations, such as the high time invested and the consumption of considerable amounts of sample. In recent years, the development of new drugs has been supported by computational tools that allow a theoretical prediction of their properties from the information collected by their molecular descriptors, their design being much faster and cheaper. This paper shows the results of a structure-property relationship (QSPR) study aimed at finding a predictive mathematical model of the distribution coefficient of organic compounds of pharmaceutical interest. Through the computer programs ACDLabs (simplified molecular representations and calculation of log P) and MODESLAB (calculation of molecular descriptors) a training series consisting of 200 compounds classified in ten pharmacological groups was formed. Using the BuildQSAR computer program, an optimal prediction model of log P was obtained, considering the five molecular descriptors that best correlated with this property as independent variables. The model obtained showed a percentage of adjustment to the experimental data of 85%, as well as a standard error of the estimate lower than the logarithmic unit. Its internal validation showed an adjustment percentage of 80%.

The Ebola viral disease with high fatality ratio is making a comeback in the Democratic Republic of Congo (DRC), after its rampage in West Africa in2014-16, that has spawned fears of leading to a pandemic. Vaccines such as the experimental rVSV-ZEBOV has provided protection in 70-80% of the cases, but such vaccines are in short supply and doubts exist of its availability and sustainability in pandemic cases.

Peptide vaccines promise to amend this lacunae as a chemical construct that can be scaled up to requirement in manufacturing set-up, are easy to produce in pure form and store as well as transport much more easily and economically than traditional vaccines. Although no peptide vaccines have been licensed yet for human use, the rapid growth of applications of in silica approaches to peptide vaccine design and application to a myriad of virus infections, and subsequent follow-up experimental work, have led to expectations to licensures in the near future. We have proposed a protocol to automate the search procedure for suitable vaccines using mathematical and computational modelling approaches that ensure long life of such vaccines even in the face of rapid mutational changes in viral sequences. In this paper we outline the mathematical model we have used and the recent improvements in the techniques to ensure the best recommendations for peptide vaccine libraries, especially against the Ebola virus that threatens to spill over the Congo border and cause epidemic and pandemics in a globalized world.