Carlos Henrique Madeiros Castelletti

Electrochemical DNA biosensor for bovine papillomavirus detection using polymeric film on screen-printed electrode

A new electrochemical DNA biosensor for bovine papillomavirus (BPV) detection that was based on screen-printed electrodes was comprehensively studied by electrochemical methods of cyclic voltammetry (CV) and differential pulse voltammetry (DPV). A BPV probe was immobilised on a working electrode (gold) modified with a polymeric film of poly-L-lysine (PLL) and chitosan. The experimental design was carried out to evaluate the influence of polymers, probe concentration (BPV probe) and immobilisation time on the electrochemical reduction of methylene blue (MB). The polymer poly-L-lysine (PLL), a probe concentration of 1 μM and an immobilisation time of 60 min showed the best result for the BPV probe immobilisation. With the hybridisation of a complementary target sequence (BPV target), the electrochemical signal decreased compared to a BPV probe immobilised on the modified PLL-gold electrode. Viral DNA that was extracted from cattle with papillomatosis also showed a decrease in the MB electrochemical reduction, which suggested that the decreased electrochemical signal corresponded to a bovine papillomavirus infection. The hybridisation specificity experiments further indicated that the biosensor could discriminate the complementary sequence from the non-complementary sequence. Thus, the results showed that the development of analytical devices, such as a biosensor, could assist in the rapid and efficient detection of bovine papillomavirus DNA and help in the prevention and treatment of papillomatosis in cattle.

In Silico Identification of New Genetic Variations as Potential Risk Factors for Alzheimer’s Disease in a Microarray-oriented Simulation

Genomic and proteomic studies of neurodegenerative disorders require complementary approaches to integrate the massive amount of data generated in high throughput experimental procedures. We propose a Bioinformatics pipeline in which expression studies guide the selection of candidate genes that should be screened for potential new genetic variations from a public expressed site tags (ESTs) database. Motivated by the former interest of our group in genetic polymorphisms involved with the immune system, we selected five genes from a previous expression microarrays study of hippocampal cornu ammonis (CA1) area of Alzheimer’s Disease subjects (AD). The CLCbio Workbench Combined® version 3.6.2. was initially used to build ESTs and mRNA files retrieved respectively from the Goldenpath of University of California Santa Cruz (UCSC) and National Center for Biotechnology Information (NCBI) databases and latter to perform multiple batches of Smith–Waterman alignments. A total of 116 ESTs sequences were selected after proper stringent parameters were applied to the first set of mismatches. The annotation revealed various classes of variations, most of them deletions (176). Amongst this specific group, some were frameshift deletions (35) and the virtual translation of a few others (5) were predicted to induce no change other than a single aminoacid removal, with no subsequent repercussions at the protein sequence. In addition, the analysis identified transitions (three), transversions (52), synonymous (41), non-synonymous (12), and deletions in 36 ESTs located in Untranslated Regions -UTRs (Supplementary data). Deletions are often associated to major genetics syndromes with dysmorphic features. However, various recent studies show that common microdeletions might be highly associated with common neuropsychiatric disorders such as schizophrenia, autism, mental retardation, or even in various ethnicities, detected in whole genome sequencing experiments. A virtual validation confirmed that some of the variations identified were previously reported and confirmed in DNA samples, showing that this method is a feasible way to detect genetic variations that merit further exploration in AD genetic risk factor association studies.

Bioinformatics analysis of non-synonymous variants in the KLF genes related to cardiac diseases

Kruppel-like Factors (KLF) are responsible for regulating many genes involved in physiological and pathological processes. They are characterized by three conserved zinc-fingers in the DNA-binding domain, wherein mutations could affect the binding efficiency and transcription regulation. This study aimed to perform bioinformatics analysis to determine the most deleterious non-synonymous variants in KLFs involved in cardiac development and diseases, and their effects over the protein structure and stability. Eight hundred and fifty non-synonymous variants were found in seven KLFs related to cardiac diseases. Seventeen algorithms were used to predict the effect of selected variants over the structure and function of seven KLFs. The Top3 variants were selected in each category of conserved and non-conserved residues in the zinc-finger (ZF) domain. KLF5 p.Cys410Phe was the only variant predicted as deleterious in all algorithms, occurring in a conserved residue of zinc ion interaction. KLF15 p.Arg364Pro was the only variant predicted to affect the DNA-binding, and also occurs in a conserved ZF-domain. Our bioinformatics analysis determined potential variants that may lead to development of cardiac diseases, as well as reinforced the importance of KLF analysis in vitro and in vivo.

Point-of-care devices: the next frontier in personalized chemotherapy

The ‘standard-of-care’ is the commonest type of treatment, determined by averaging responses across large cohorts. However, every patient has their own genetic background and lifestyle, which indicates that each one should receive individualized care as based on clinical trials. The ‘Precise Medicine’ era has emerged to achieve successful treatment for each patient based on their personal characteristics and it is pushing forward ‘point-of-care’ (POC) devices [1]. The POC concept relies on portable, userfriendly and robust devices to perform sensitive and specific detection anywhere. This technology can also be linked to a cell phone coupled to a detection device [2]. One of the prime fields for application of this technology is cancer therapy, focusing on evaluating the treatment scheme for each patient.

Clinical and molecular aspects of breast cancer: Targets and therapies

Breast Cancer is a complex disease characterized by the occurrence of multiple molecular alterations. Currently, some molecular markers are in use for breast cancer diagnostic, prognostic, and predictive purposes. Thus, genetic signatures are available for improving the decision-making. The biomarkers are also essential as therapeutic approaches, but many questions remain due to the lack of efficacy on breast cancer treatment, mainly for triple-negative breast cancer subtype. Since the genetic profile of breast cancer can also be related to different ethnic groups and geographic areas, the reference populations of the genetic assays and clinical trials need to include a broader population beyond the European and North American patients. In this review, we analyzed the current and potential molecular markers that could help to improve the strategies for breast cancer therapy.

Putative biomarkers for cervical cancer: SNVs, methylation and expression profiles

Cervical cancer is primarily caused by Human papillomavirus (HPV) infection, but other factors such as smoking habits, co-infections and genetic background, can also contribute to its development. Although this cancer is avoidable, it is the fourth most frequent type of cancer in females worldwide and can only be treated with chemotherapy and radical surgery. There is a need for biomarkers that will enable early diagnosis and targeted therapy for this type of cancer. Therefore, a systems biology pipeline was applied in order to identify potential biomarkers for cervical cancer, which show significant reports in three molecular aspects: DNA sequence variants, DNA methylation pattern and alterations in mRNA/protein expression levels. CDH1, CDKN2A, RB1 and TP53 genes were selected as putative biomarkers, being involved in metastasis, cell cycle regulation and tumour suppression. Other ten genes (CDH13, FHIT, PTEN, MLH1, TP73, CDKN1A, CACNA2D2, TERT, WIF1, APC) seemed to play a role in cervical cancer, but the lack of studies prevented their inclusion as possible biomarkers. Our results highlight the importance of these genes. However, further studies should be performed to elucidate the impact of DNA sequence variants and/or epigenetic deregulation and altered expression of these genes in cervical carcinogenesis and their potential as biomarkers for cervical cancer diagnosis and prognosis.