Consolidating and Upscaling Molecular Research Capacity in Nigeria: On Who's Account?

Molecular research and researchers engage in studies that seek to understand the structures, functions, and interactions of biomolecules as the basis for cellular and systemic effects in living organisms. This research approach was made possible by considerable technological advancements that equip researchers with tools to view biomolecules. Although molecular research holds great promises for improving lives and living, the technological requirements and equipment to undertake molecular research are quite expensive, often requiring a heavy start-up capital or investment. In developing countries such as Nigeria, where the majority of the population lives below the poverty line and research funding is abysmally low, such heavy investments into research that do not provide immediate solutions to societal problems are difficult. This is mostly due to limited resources available to tackle many urgent and pressing needs, and limited perspective and understanding of policymakers, leading to infrastructural and skilled personnel deficit to support molecular research. Despite all these, the field of molecular research continues to grow exponentially globally, hence, funding and investments into this critical life science research area have become imperative. With the rich biodiversity of humans, animals, and plants in Nigeria, and the huge burden of infectious diseases in the country or region, global advances in genomics and proteomics studies will be incomplete without adequate contribution from Nigeria and sub-Saharan Africa region. This paper examines the progression and challenges of undertaking molecular research in Nigeria, and how Nigerian molecular research scientists are tackling these issues, with recommendations for improved molecular research capacity and output in the country or region.

Recent Advances in Combretastatin A-4 Inspired Inhibitors of Tubulin Polymerization-An Update

Cancer is one of the leading causes of fatality and mortality worldwide. Investigations on developing therapeutic strategies for cancer are supported throughout the world. The massive achievements in molecular sciences involving biochemistry, molecular chemistry, medicine, and pharmacy, and high throughput techniques such as genomics and proteomics have helped to create new potential drug targets for cancer treatment. Microtubules are very attractive targets for cancer therapy because of the crucial roles they play in cell division. In recent years, lots of efforts have been put into the identification of new microtubule-targeting agents (MTAs) in anticancer therapy. Combretastatin A-4 (CA-4) is a natural compound that binds to microtubules’ colchicine binding site and inhibits microtubule polymerization. Due to CA-4’s structural simplicity, many analogs have been synthesized. This article summarizes the new molecule development efforts to reach CA-4 analogs by modifications on its pharmacophore groups, published since 2015.

Review of global use of licensed vaccines and development of new vaccines for the prevention of pneumococcal infection

Streptococcus pneumoniae infection is the most common cause of high morbidity and mortality among children under 5 years of age, immunocompromised people, and the elderly. Despite significant success, the approved pneumococcal conjugate and polysaccharide vaccines are of limited efficacy, providing protection against a small fraction of the known pneumococcal serotypes. The rapid spread of multidrug-resistant strains exacerbates the global challenge of treating infection caused by S. pneumoniae. At the same time, the emerging new strains dictate the need to include new serotypes into vaccines. In view of this, further improvement of vaccines for the prevention of pneumococcal infections is an urgent task. The aim of this study was to review advances in the development of polysaccharide, conjugate, whole-cell pneumococcal vaccines, as well as vaccines based on protein antigens and vaccines with an antigen delivery system. Genomics and proteomics data have helped to improve approaches to the creation of polysaccharide and protein-based vaccines, as well as whole-cell vaccines with the potential for population prophylactic coverage against various pneumococcal serotypes that are not included in the licensed pneumococcal vaccines. The method of antigen delivery to the cell is of great importance in the development of vaccines. The most promising strategy for improving pneumococcal vaccines is the creation of vaccines based on bacterium-like or synthetic particles carrying several antigens, including pneumococcal surface proteins. In conclusion, it should be noted that top-priority vaccines are those that provide a wide range of protection against circulating pneumococcal serotypes and, in addition to eliciting a systemic immune response, also induce local immunity.

Identification of Unique Peptides for SARS-CoV-2 Diagnostics and Vaccine Development by an In Silico Proteomics Approach

Ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus strains is posing new COVID-19 diagnosis and treatment challenges. To help efforts to meet these challenges we examined data acquired from proteomic analyses of human SARS-CoV-2-infected cell lines and samples from COVID-19 patients. Initially, 129 unique peptides were identified, which were rigorously evaluated for repeats, disorders, polymorphisms, antigenicity, immunogenicity, toxicity, allergens, sequence similarity to human proteins, and contributions from other potential cross-reacting pathogenic species or the human saliva microbiome. We also screened SARS-CoV-2-infected NBHE and A549 cell lines for presence of antigenic peptides, and identified paratope peptides from crystal structures of SARS-CoV-2 antigen-antibody complexes. We then selected four antigen peptides for docking with known viral unbound T-cell receptor (TCR), class I and II peptide major histocompatibility complex (pMHC), and identified paratope sequences. We also tested the paratope binding affinity of SARS-CoV T- and B-cell peptides that had been previously experimentally validated. The resultant antigenic peptides have high potential for generating SARS-CoV-2-specific antibodies, and the paratope peptides can be directly used to develop a COVID-19 diagnostics assay. The presented genomics and proteomics-based in-silico approaches have apparent utility for identifying new diagnostic peptides that could be used to fight SARS-CoV-2.

SMAP: A pipeline for sample matching in proteogenomics

Integration of genomics and proteomics (proteogenomics) offers unprecedented promise for in-depth understanding of human diseases. However, sample mix-up is a pervasive, recurring problem, due to complex sample processing in proteogenomics. Here we present a pipeline for Sample Matching in Proteogenomics (SMAP) for verifying sample identity to ensure data integrity. SMAP infers sample-dependent protein-coding variants from quantitative mass spectrometry (MS), and aligns the MS-based proteomic samples with genomic samples by two discriminant scores. Theoretical analysis with simulation data indicates that SMAP is capable of uniquely match proteomic and genomic samples, when ≥20% genotypes of individual samples are available. When SMAP was applied to a large-scale proteomics dataset from 288 biological samples generated by the PsychENCODE BrainGVEX project, we identified and corrected 18.8% (54/288) mismatched samples. The correction was further confirmed by ribosome profiling and assay for transposase-accessible chromatin sequencing data from the same set of samples. Thus our results demonstrate that SMAP is an effective tool for sample verification in a large-scale MS-based proteogenomics study. The source code, manual, and sample data of the SMAP are publicly available at https://github.com/UND-Wanglab/SMAP, and a web-based SMAP can be accessed at https://smap.shinyapps.io/smap/.

Abstract P506: Sirt6 Overexpression Inhibits Senescence And Inflammation In Human Mesenchymal Stem Cells

Background: Mesenchymal Stem Cells (MSCs) offer regenerative and therapeutic potential in an injured tissue in diabetic conditions. But the functional efficiency of MSCs has been shown to decrease with diabetes and aging. This reduces the potential of cell-based therapy in diabetic patients. Recent studies have established the role of sirtuin family proteins in metabolic disease, inflammation, longevity, and DNA repair. However, their potential to be used as a therapeutic target in cardiomyopathy and heart failure remain unexplored. Objective: To investigate the role of Sirtuin 6 (SIRT6) in mesenchymal stem cells senescence and cardiac regeneration. Methods and Results: We performed genomics and proteomics in the human control and diabetic heart tissues collected from the heart transplant. Human MSCs were treated with high glucose and mouse MSCs were derived from the bone marrow of diabetic db/db mice for this study. We found that SIRT6 expression is reduced in the myocardium of diabetic patients compared to non-diabetic controls. The SIRT6 expression decreased in high glucose-treated human MSCs compared to mannitol-treated control MSCs as well as in db/db mice MSCs compared to control mice MSCs. These high glucose-treated human MSCs and db/db mice MSCs showed increased expression of senescence and inflammation-related markers like that in diabetic human myocardium. Furthermore, we used small interfering RNA (SIRT6-siRNA) in human MSCs to knock down the SIRT6 gene and validated our findings. Indeed, the knockdown of SIRT6 promoted senescence and inflammation in those MSCs. Finally, we used adeno-associated viruses (AAV-SIRT6) to overexpress SIRT6 in MSCs treated with high glucose and performed proteomic analysis. SIRT6 overexpression in high glucose-treated MSCs reduced the expression of senescence and inflammation related genes and proteins. Conclusion: Our results highlight the importance of SIRT6 in diabetic myocardium and its role in balancing senescence and inflammation in MSCs. The validation of such in vitro studies in a diabetic mouse model ( db/db ) along with transplantation of SIRT6 overexpressed db/db MSCs into the myocardium of diabetic mice could open doors to successfully use MSC therapy in diabetic patients in the future.

Hierarchical Clustering on RNA Dependent RNA Polymerase using Machine Learning.

RNA Dependent RNA Polymerase (RdRP) catalyzes the replication of RNA from an RNA template and is mostly found in Viruses. We have collected over 161 viral RdRP FASTA Sequences from the NCBI protein database using python script. Each of these sequences was transformed with TfidfVectorizer using sklearn module, with the one Letter word, because each Letter belongs to one Amino acid. These transformed data were sent to Hierarchical clustering using scipy library and visualized data using Dendrogram. These Machine Learning technique is able to classify or segment similar RdRp into one cluster. Each of these clusters was tested for their multiple sequence alignment with COBALT of NCBI. We observed that these clusters predicted similar RdRP among various viruses. These techniques can be further improved to segment or classify various proteins. These Machine Learning or Artificial Intelligence techniques need more improvement in their algorithms to solve genomics and proteomics.