POSTER PRESENTATIONS



P01
Characterization of Salmonella Typhimurium, Salmonella Enteritidis and Salmonella Albany isolated from chickens and ducks using Random Amplified Polymorphic DNA (RAPD) – PCR

Author(s):
Frederick Adzitey, University for Development Studies, Ghana

Abstract:
The objective of this study was to characterize Salmonella Typhimurium, Salmonella Enteritidis and Salmonella Albany strains isolated from chicken and ducks to determine their relatedness using Random Amplified Polymorphic Deoxyribonucleic Acid (RAPD)-PCR. RAPD-PCR analysis of the Salmonella serovars produced DNA bands that ranged from 242 to 3189 bp for Salmonella Typhimurium, 252 to 2756 bp for Salmonella Enteritidis and 232 to 2612 bp for Salmonella Albany. Cluster analysis at a coefficient of 0.85 grouped the Salmonella serovars into various clusters and singletons. Salmonella Typhimurium were grouped into 4 clusters and 1 singleton at a discriminatory index of 0.84. Salmonella Enteritidis were grouped into 2 clusters and 2 singletons at a discriminatory index of 0.64. Salmonella Albany were grouped into 3 clusters and 1 singleton at a discriminatory index of 0.71. One Salmonella Typhimurium isolated from chicken carcass was not characterized as the RAPD-PCR employed failed to produce any DNA band from that isolate. Characterizing Salmonella serovars from different sources is important to determine their genetic relatedness, and source of contamination and spread.


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P02
Reduction in Prevalence of Plasmodium falciparum Chloroquine/Amodiaquine Resistance (Pfcrt) and Multidrug Resistance (Pfmdr I) genes in Southwestern Nigeria

Author(s):
Grace Olasehinde, Covenant University, Nigeria
Adeshola Ajayi, Covenant University, Nigeria
Louis Egwari, Covenant University, Nigeria
Marion Adebiyi, Covenant University, Nigeria

Abstract:
Background
Molecular methods that detect genetic markers of drug resistance are potentially powerful tools for tracking drug-resistant malaria and providing advance information on the emergence of drug resistance patterns in the field.Such can be used to design malarial control strategies in regions where malaria is highly endemic.In this study, the combination of Pfcrt and Pfmdr1 mutationsin isolates associated with chloroquine and amodiaquin resistance was observed in Southwestern Nigeria.
Methodology
DNA was extracted from 140 Plasmodium falciparum positive blood samples using the QiaAmp DNA Blood Minikit extraction method. Nested Polymerase Chain Reaction followed by Restriction Fragment Length Polymorphisms (PCR/RFLP) were used for the detection of P. falciparum chloroquine resistance transporter (Pfcrt) and P. falciparum multidrug resistance 1 (pfmdr1) genes.
Result
Out of the 140Plasmodium falciparum positive samples, 5.7% harbored the chloroquine/amodiaquine resistant gene (Pfcrt) while 7.1% harbored the multidrug resistant gene (Pfmdr 1).
Conclusion
A remarkable reduction in the prevalence of crt and mdr 1 genes was noticed when compared with earlier findings from southwestern Nigeria and other regions of the world.The observed reduction in chloroquine/amodiaquine resistant markers suggests that there is a decline in the prevalence of resistant parasites as well as drug pressure in this region. Bioinformatic tools would be employed to predict potential resistant genes to contain future development of resistance to newer drugs.


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P03
Genetic relatedness of infecting and re-infecting human coronavirus NL63 Strains identified in a household community study in coastal Kenya

Author(s):
Patience Kiyuka, KEMRI-Wellcome Trust Research Programme, Kenya

Abstract:
Introduction: Human coronaviruses (HCoV) species are recognised to cause both upper and lower acute respiratory tract infections in humans. From a longitudinal surveillance study of household occupants individuals were observed to be infected repeatedly within a period of 4 months with the same HCoV-NL63 strains. Important will be to define the mechanism underlying these reinfection events.
Objectives: To characterise the genetic diversity of repeat infections of HCoV-NL63 identified in a household study at Costal Kenya.
Methods: Specimens used in this study will arise from a prospective study in which 47 households were recruited from Kilifi Health Demographic Surveillance Site and actively followed up during the RSV season of 2009/2010. Nasopharyngeal swab samples were collected irrespective of the symptoms from household members and screened for a panel of respiratory viruses including HCoV-NL63 using multiplex RT-PCR.
Results: A total of 47 households (493 individual participants) participated in the study. All the households had at least one of the three HCoV (229E,OC43 and NL63) detected over the surveillance period. HCoV-NL63 was detected in 70.2% (33/47) of the households. A total of 537 HCoV infection episodes and 79 outbreaks were recorded within the households with HCoV-NL63 accounting for 40.2%( 216) episodes and 36.7%(29/79) outbreaks.
Conclusions: HCoV-NL63 infection although recently discovered, accounted for the second most cause of reinfection events observed within the households and among individuals. The genetic diversity analysis as proposed by this study will be important in further elucidating the transmission and evolution of HCoV-NL63.


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P04
Genetic variability and population structure of Kenyan Plasmodium falciparum parasites

Author(s):
LUICER OLUBAYO, USAMRU-K, LUICER OLUBAYO, USAMRU-K, Kenya
EDWIN KAMAU, USAMRU, Kenya
HOSEA AKALA, USAMRU, Kenya
JELAGAT CHERUIYOT, USAMRU, Kenya
LORNA CHEBON, USAMRU, Kenya
BEN ANDAGALU, USAMRU, Kenya
BENJAMIN OPOT, USAMRU, Kenya

Abstract:
Multilocus genotyping of microbial pathogens has revealed a range of population structures, with some bacteria showing extensive recombination and others showing almost complete clonality. The population structure of the protozoan parasite Plasmodium falciparum has been harder to evaluate, since most studies have used a limited number of antigen-encoding loci that are known to be under strong selection. We describe length variation at 12 microsatellite loci in 465 infections collected from 9 locations worldwide. These data reveal dramatic differences in parasite population structure in different locations. Strong linkage disequilibrium (LD) was observed in six of nine populations. Significant LD occurred in all locations with prevalence ,1% and in only two of five of the populations from regions with higher transmission intensities. Where present, LD results largely from the presence of identical multilocus genotypes within populations, suggesting high levels of self-fertilization in populations with low levels of transmission. We also observed dramatic variation in diversity and geographical differentiation in different regions. Mean heterozygosities in South American countries (0.3–0.4) were less than half those observed in African locations (0.76–0.8), with intermediate heterozygosities in the Southeast Asia/Pacific samples (0.51–0.65). Furthermore, variation was distributed among locations in South America (FST = 0.364) and within locations in Africa (FST = 5 0.007). The intraspecific patterns of diversity and genetic differentiation observed in P. falciparum are strikingly similar to those seen in interspecific comparisons of plants and animals with differing levels of outcrossing, suggesting that similar processes may be involved. The differences observed may also reflect the recent colonization of non-African populations from an African source, and the relative influences of epidemiology and population history are difficult to disentangle. These data reveal a range of population structures within a single pathogen species and suggest intimate links between patterns of epidemiology and genetic structure in this organism.

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P05
Computational Analysis of Molecular Signatures of Selection at Candidate Genes for Egg and Growth in Indigenous Poultry

Author(s):
Eunice Wainaina, Jomo Kenyatta University of Agriculture and Technology, Eunice Wainaina, Jomo Kenyatta University of Agriculture and Technology, Kenya
Sheila Ommeh, Jomo Kenyatta University of Agriculture and Technology, Kenya
Daniel Kariuki, Jomo Kenyatta University of Agriculture and Technology, Kenya
Jacqueline Kasiiti, Ministry of Agriculture Livestock and Fisheries, Kenya
Caroline Sigei, Jomo Kenyatta University of Agriculture and Technology, Kenya
Vincent Obanda, Kenya Wildlife Service, Kenya
Simon Maina, Jomo Kenyatta University of Agriculture and Technology, Kenya
Moni Makanda, Jomo Kenyatta University of Agriculture and Technology, Kenya
Philip Oyier, Jomo Kenyatta University of Agriculture and Technology, Kenya
Phillister Malaki, Jomo Kenyatta University of Agriculture and Technology, Kenya
Emmanuel Ndiema, National Museums of Kenya, Kenya

Abstract:
70% of Kenya’s population resides in the rural areas with up to 90% engaging in indigenous poultry farming. Indigenous chickens form majority of the poultry population. They are reared for eggs and meat which contribute to the protein nutrition of the family especially for the vulnerable members of the household for example people living with HIV/AIDS. Indigenous poultry rearing is mainly done by women and youth as it requires little initial investment and generates quick returns which suits well the day to day expenditure of women and it also does not conflict with women’s daily household chores. Indigenous poultry are mainly reared under extensive scavenging conditions which are characterized by low egg and meat production. Crossbreeding has been used to improve productivity but it has not been successful as the genes implicated for production have not been targeted. Detection of signatures of selection at candidate genes for egg and meat production will solve some of these limitations. This technique will detect variation among poultry and when applied in genetic improvement will be more superior as it does not rely exclusively on phenotypes and information on progeny. Agriculture accounts for 26% of GDP in Kenya with poultry farming contributing 30% of Agricultural contribution to the GDP. Indigenous poultry farming can thus alleviate poverty and provide food security on identification of high producing genotypes.

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P06
In Silico Detection of Signatures for Adaptive Evolution at Innate Immune Genes and Heat Shock Protein Genes in Indigenous Poultry

Author(s):
Caroline Sigei, Jomo Kenyatta University of Agriculture and Technology, Caroline Sigei, Jomo Kenyatta University of Agriculture and Technology, Kenya
Sheila Ommeh, Jomo Kenyatta University of Agriculture and Technology, Kenya
Daniel Kariuki, Jomo Kenyatta University of Agriculture and Technology, Kenya
Emmanuel Ndiema, National Museums of Kenya, Kenya
Jacqueline Lichoti, Ministry of Agriculture Livestock and Fisheries, Kenya
Eunice Wainaina, Jomo kenyatta University of Agriculture and Technology, Kenya
Philip Oyier, Jomo kenyatta University of Agriculture and Technology, Kenya
Simon Maina, Jomo kenyatta University of Agriculture and Technology, Kenya
Phillister Malaki, Jomo kenyatta University of Agriculture and Technology, Kenya
Moni Makanda, Jomo kenyatta University of Agriculture and Technology, Kenya
Vincent Obanda, Kenya Wildlife Service, Kenya

Abstract:
Currently, the world poultry production is threatened by climatic extremes due to the ongoing climate change. This is associated with outbreaks of contagious diseases such as the Newcastle disease, Infectious Bursal Disease and the looming Avian Influenza which can cause up to 100% mortality in flocks (Garcia et al., 2013; Gardner, 2014). Outbreaks of these diseases coupled to the absence of an effective cure have occasionally caused catastrophic losses to poultry farmers in developing countries thus threatening their livelihoods. The discovery of hereditary DNA and high throughput sequencing technologies has made it possible to perform molecular evolution studies through utilization of computational tools in identification of genes and genomic regions that have been subject to natural selective pressures over evolutionary time. Molecular signatures left behind by such pressures may alter a protein’s fitness, stability, structure, expression, abundance and function. Therefore, computational detection of signatures of selection for adaptive traits such as disease-resistance and drought-tolerance is a quick approach to identify candidate genes for genetic improvement of poultry after experimental validation through in vitro and in vivo studies. The ISCB Africa conference provides a great opportunity for sharing my research findings with the wider scientific community so as to exchange and gain new ideas on improvement and utilization of indigenous poultry. Also, the scheduled bioinformatics workshops will provide a chance for comprehensive, interactive discussions and training across a wide range of bioinformatics and biomedical research disciplines which are relevant to my area of research.

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P07
Molecular Epidemiology and Characterization of Staphylococcus aureus from Clinical and Asymptomatic Carriers

Author(s):
Olayemi Ayepola, Covenant University, Olayemi Ayepola, Covenant University, Nigeria
Nurudeen OIasupo, Lagos State University, Nigeria
Louis Egwari, Covenant University, Nigeria
Frieder Schaumburg, University Hospital Muenster, Germany

Abstract:
Many studies have characterized S. aureus and MRSA isolates from individual hospitals or countries and have identified strains that appear to be well adapted to the hospital environment, are established in several hospitals within a country, or have spread internationally (epidemic MRSA, EMRSA). This has allowed a better understanding of the evolution of both S. aureus and methicillin-resistant S. aureus over time and the ability to compare the genetic variation in different geographic locations. Such studies are important because the epidemiology and resistance patterns of S. aureus show large interregional variability. The emergence of MRSA strains resistant to glycopeptides, as well as the increasing prevalence in the community highlights the need for worldwide epidemiological studies of this pathogen. The mechanisms for the emergence and spread of S. aureus clones in Africa are poorly understood. Therefore the characterization of isolates may provide baseline information needed in establishing effective infection control measures. In Nigeria, information on the resistance trends of S. aureus and MRSA both in health-care settings and in the community is limited. The fact that certain virulence factors can be associated with distinct human diseases strengthens the importance of examination of genes encoding pathogenicity factors. This study therefore seeks to investigate the genetic and phenotypic features of S. aureus isolated from clinical and carriage sources. The results of this study will aid implementation of strategies for the prevention and effective management of S. aureus infections in Nigeria.The information provided could help in monitoring the evolution of S. aureus strains in Nigeria over time.

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P08
Regulation analysis of Mycobacterium Tuberculosis

Author(s):
Abayomi Mosaku, Covenant University Bioinformatics Research (CUBRe), Nigeria
João Saraiva, Jena University Hospital, Germany
Rainer Koenig, Jena University Hospital, Germany

Abstract:
Mycobacterium tuberculosis (TB) causes 8-9 million cases of infection, and 1.5 million deaths every year. These numbers are on the rise globally, especially in Africa, Eastern Europe and the former Soviet Union. Part of the problem in treating TB is the appearance of drug resistant TB strains, including strains with multiple drug resistance (MDR) and, more recently, strains with extensive drug resistance (XDR), which are much more difficult to treat. M. tuberculosis is a gram-positive bacterium which causes tuberculosis and there are about 8-9 million new cases of TB annually, with much of the burden falling on the young and middle aged between 15-49 years old. In this ongoing work, we are analyzing the gene expression data of M. Tuberculosis infected human host cell using the modules developed using the R statistical programming language and the Bioconductor open source tools.
To do this, a detailed and proven workflow was envisioned. Gene set enrichment analysis was carried out using DAVID (Database for Annotation, Visualization and Integrated Discovery). We used the R/Bioconductor's PIANO (Platform for integrative analysis of omics data ) for our functional annotation analysis. Currently, we have arrived at some pathways that look promising as drug targets. Ultimately, interesting genes will be mapped to their respective transcription factors, thereafter mixed integer linear program (MILP) will be employed to infer or deduce gene regulation of the discovered Interesting genes.


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P10
A comparative analysis of proteins in invasive and multidrug resistant S. Typhimurium variants in Malawi

Author(s):
Benjamin Kumwenda, University of Malawi/Malawi-Liverpool Wellcome Trust, Malawi
Ozlem Tastan Bishop, Rhodes University, South Africa
Chisomo Msefula, University of Malawi, College of Medicine, Malawi
Dean Everett, Malawi-Liverpool Wellcome Trust, Malawi
Robert Hyderman, Malawi-Liverpool Wellcome Trust, Malawi

Abstract:
Bacteraemia in young children and HIV-infected adults in sub-Saharan Africa particularly Malawi has been found to be largely caused by invasive multidrug (MDR) resistant nontyphoidal Salmonella (NTS) serovar Typhimurium. Phylogenetic analysis of invasive NTS strains isolated between 1997 and 2008 revealed three major clusters. These were a pre-2002 cluster resistant to ampicillin and cotrimoxazole, an epidemic post-2002 cluster resistant to ampicillin, cotrimoxazole and chloramphenicol, and a third cluster which included post-2002 epidemic strains with similar antibiotic resistance profile. Twenty-three single nucleotide polymorphisms (SNPs) located in open reading frames separate the epidemic strains from the variant strains. These proteins are involved in respiration, metabolism and in vivo persistence. Protein structure modelling was performed to compare pre-epidemic and epidemic variants. The modelled structures were analysed for structural and functional differences due to the identified SNPs.
This study assessed the contribution of the observed 23 SNPs on protein structure, their influence on protein function and effect on bacterial fitness. Deleterious mutations were observed in protein structures of the emerging and dominant strains resulting in reduction of the length of beta sheets and loops. Protein structures from the third emerging epidemic resistant cluster were found to be less stable as compared to those from pre-2002 cluster. These finding suggest a micro-evolutionary process in dominant post-2002 epidemic strains to compensate drug resistance.


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P11
LASSA VIRUS: CODON USAGE AND BIAS ALONG WITH THEIR HOST

Author(s):
Lawrence Okoror, Federal University Oye-Ekiti, Nigeria, Nigeria
Ayo Eludire, Joseph Ayo Babalola University, Nigeria

Abstract:
Lassa virus continues to be endemic with frequent outbreak in areas of endemicity which is of a public health concern due to its fast evolutionary rate. There has been a report of new strains in different epidemic outbreak. We used seven different codon usage bias tools and indexes targeting synonymous codon usage which included GC content, ENC, SCUO, Codon Volatility, RSCU, Odd ration and Graphical Codon Usage Analysis tool. This study observed evolutionary pattern in Lassa virus from human, rodents and bats. It also observed the evolutionary pattern and influence of different geographical location in its evolutionary pattern and periodic outbreak. There was variation in the GC content in the glycoprotein gene, nucleoprotein gene, Z-protein gene, S-protein gene and polymerase gene. RSCU value was positively correlated with the Odd Ratio of dinucleotide in the codons. RSCU values of humans, rodents and bats were slightly different, though this result was not completely true for odd ratio. The GC content, ENC, SCUO and Codon Volatilty were similar across all the hosts. However, there was slight variation of genes from different geographical locations, thereby supporting reports that Lassa virus varies by strains from different locations. Though there was slight variation from years of isolation, the difference in host explains why the virus causes fever in humans as against being normal in other hosts.


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P12
Which Anopheles Mosquito Genes Are Most Important In Promoting Malaria Transmission? A Bioinformatics Perspective.

Author(s):
Yosi Shibberu, Jimma University, Ethiopia
Geletaw Sahle, Jimma University, Ethiopia
Zelalem Hailu, Jimma University, Ethiopia
Abebe Asale, Jimma University, Ethiopia
Alemayehu Shiferaw, Jimma University, Ethiopia

Abstract:
Despite a tremendous expansion in the financing and coverage of malaria control programmes resulting in wide-spread reduction in malaria incident and mortality, the disease continues to be a global health threat. There were an estimated 207 million cases of malaria in 2012 alone resulting in 627,000 deaths. 80% of the reported cases come from Sub-Saharan Africa with high mortality and morbidity especially in children under the age of five. Drug and insecticide resistance that operate at the gene level continue to be a major problem in disease control.

16 Anopheles genomes have recently been sequenced. Our main objective is to identify genes in these genomes that play a key role in promoting parasite infectivity in vector populations. We used 3-fold, 5-fold and 10-fold cross validation to classify malaria transmission vectors into major, minor and non-human malaria vectors using 52 genomic attributes. The classification techniques used build classification models with accuracies of 42%, 36.8%, 52.6% and 36.8% for J48 pruned decision trees, J48 un-pruned decision trees, k-nearest neighbors and Naive Baye’s algorithms respectively. Our preliminary analysis found the CP F-actin capping gene (AGAP007864) to play a leading role in parasite infectivity. Since most experimental data on transmission efficiency is for Anopheles gambiae, this introduced a gambiae bias in our analysis. We are currently refining our classification methods and will increase the number of genomic attributes we include in our final analysis.


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P13
Metagenomic and Metatranscriptomic analyses of the hepatocellular carcinoma-associated microbial communities and the potential role of microbial communities in liver cancer

Author(s):
Mahmoud ElHefnawi, National research centre, Mahmoud ElHefnawi, National research centre, Egypt
asmaa Ezzat, MicrobiologyNational research ceentre, Egypt

Abstract:
Objective: Metagenomics is a new science that revolutionized microbiology for its ability to study the microbiota of a given environment without the need of culture. Human microbiota is the collection of microbes that inhabit different sites of the human body and recently its alterations were related to different human diseases especially cancers. Liver cancer incidence is continually increasing in Egypt with a high mortality rate. This study aimed to identify the abundant microbial communities that inhabit the liver of the hepatocellular carcinoma patient and may be associated with disease incidence or at least disease progression. Methods: Fresh liver biopsy samples of two hepatocellular carcinoma Egyptian patients were obtained. DNA from one sample and RNA from other sample were extracted followed by Illumina sequencing. Taxonomic and functional analyses were performed using the MG-RAST server. Results: Proteobacteria was the dominant phylum followed by Firmicutes and Actinobacteria in both DNA and RNA samples. Some other phyla as Chlorobi, Bacteria and Cyanobacteria had the same abundance in the two dataset. But it was noted that the bacterial diversity and presence of useful bacteria in sample 2 of grade 1 disease (RNA sample) were more than it in sample 1 of grade 2 disease (DNA sample). Also, some other phyla are found in the cDNA dataset annotations. On the other hand, infectious diseases pathways analysis showed the enrichment of infectious diseases pathways of Staphylococcus aureus infection, Vibrio cholera infection, pathogenic Escherichia coli infection, Hepatitis c, Tuberculosis, Epithelial cell signalling in Helicobacter pylori infection, Bacterial invasion of epithelial cells, and salmonella infection. Conclusions: There is a potential link between some definite microbial communities and liver cancer that need some attention for improving early diagnosis and preventing disease progression. Further studies are required to support this.

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P14
Molecular detection of tick-borne pathogens along the shores and selected islands Lakes Baringo and Victoria, Kenya

Author(s):
David Omondi, ICIPE/EGERTON, David Omondi, ICIPE/EGERTON, Kenya
Daniel Masiga, ICIPE, Kenya
Yvonne Ajamma, ICIPE, Kenya
jandouwe Villinger , ICIPE, Kenya
Burtram Fielding, University of The Western Cape, South Africa
Edward Kariuki, 3. Depart Kenya Wildlife Service, Kenya

Abstract:
Background: Ticks are obligate hematophagous ectoparasites that transmit a wide range of pathogens to humans and animals. Apart from incidences of mosquito borne arbovirus outbreaks along the shores and adjacent islands of Lakes Baringo (Baringo County) and Victoria (Homa Bay County) in Kenya, little is known about tick borne pathogens (TBP) in both biogeographies that support pastoralism and fishing respectively. Methods: Entomological survey of TBP was carried out along the shores and selected islands of Lakes Baringo and Victoria, Kenya. Ticks were collected from vegetations, domesticated animals, tortoise, and monitor during the wet seasons of 2012-2013. The samples were identified to species and pooled (>8 individuals) by species, collection date and site. Molecular detection of TBP was achieved by total nucleic acid extractions followed by (RT-) PCR, high resolution melting (HRM) analyses and sequencing of amplicons.

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P15
Homology-based prediction of protein-protein interactions between Theileria parva and bovine host Bos taurus

Author(s):
Everlyn Kamau, Jomo Kenyatta University of Agriculture and Technology, Everlyn Kamau, Jomo Kenyatta University of Agriculture and Technology, Kenya
Steven Nyanjom, Jomo Kenyatta University of Agriculture and Technology, Kenya

Abstract:
Theileria parva infection is characterized by reversible transformation of infected bovine leukocytes dependent on presence of viable parasite residing freely in the host cell cytoplasm. Parasite-mediated control of host cell pathways may involve combinatorial molecular interactions through formation of protein complexes and these may be attributed to parasite-derived virulence factors. A computational approach involving supervised machine learning and homolog-based methods was used to infer an interaction network between bovine proteins and Theileria parva secreted and surface bound proteins. Predicted interactions were assessed by generating support vector machine (SVM) binary classifiers trained on sequence and structure features and subsequently tested on independent data of known protein interactions. The classifiers achieved good precision and recall values, and discriminated interacting and non-interacting protein pairs at high sensitivity, specificity and prediction accuracy. Predicted interactions were filtered for biological relevance, analysed for enriched functions and GO terms and compared to expression data available in literature. Functions enriched in the predicted interactions were associated with known phenotypic characteristics of Theileriatransformed cells: regulation of apoptosis, proliferation, growth, metastasis, immune response and metabolic adaptation. Since secreted proteins have potential to access bovine MHC class I presentation pathways, parasite proteins were also predicted to contain 9-mer peptides with strong binding affinities to MHC class I molecules. We inferred putative but yet experimentally verified protein interactions between Theileria parva and the bovine host, using homology information. The predictions were supported in literature, depicting parasite manipulation of host cellular processes for successful pathogenesis. Some of these interactions may constitute strategies involved in establishing successful infection, and therefore provide a candidate set for subsequent experimental studies.

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P16
Amylase Production by Aspergillus niger from Soursop (Annona muricata Linn) Fruit

Author(s):
Adesola Ajayi, Covenant University, Adesola Ajayi, Covenant University, Nigeria
Oluwabunmi Adedeji, Covenant University, Nigeria
Chinenye Peter-Albert, Covenant University, Nigeria

Abstract:
Soursop fruit as it is commonly called is derived from the Annona muricata plant. It has different names depending on different countries such as Graviola, Guanabana, Sauersak and Guayabano. The tree is found in rain forests throughout Africa, South America and Southeast Asia. In Nigeria, it is commonly found in the Southern part of the country. The soursop fruit is a sweet fruit with lots of health benefits associated with its consumption. The fruit is rich in nutrients with high moisture content. The ability of the fruit to kill all forms of cancer cells had been reported. Despite all the known benefits, the fruit is highly perishable and it deteriorates easily due to pre and post-harvest microorganisms. Aspergillus niger has been identified as one of these organisms. Apparently fresh soursop fruits obtained from a Supermarket along Idiroko road, Sango Ota were inoculated with isolates of A. niger from a stock culture. It was incubated under appropriate conditions of temperature and moisture to initiate infection. Extracts from the infected soursop fruits exhibited appreciable Amylase activity. The enzyme was purified using activated charcoal. The primary sequence was determined in silico and it was used for obtaining the amino acids sequence that was used for a three-dimensional design in a comparative modeling methodology. The models obtained were validated. This will be used for proposing a model for the Amylase.

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P17
A network based approach to understanding altered virulence in closely related Mycobacterium tuberculosis isolates.

Author(s):
Jon Ambler, University of Cape Town, South Africa
Keith Siame, University of Stellenbosch, South Africa
Anzaan Dippenaar, University of Stellenbosch, South Africa
Arnab Pain, King Abdullah University of Science and Technology, Saudi Arabia
Abdullah Abdullah, King Abdullah University of Science and Technology, Saudi Arabia
Rob Warren, University of Stellenbosch, South Africa
Samantha Sampson, University of Stellenbosch, South Africa
Nicola Mulder, University of Cape Town, South Africa

Abstract:
The investigation of complex phenotypic traits such as virulence in Mycobacterium tuberculosis through the integration and interpretation of datasets from multiple sources.


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P18
A Machine Learning Approach to Evaluating the Functional Properties of a Gene Set

Author(s):
Olubukola SMILE, University of Ibadan, Nigeria
Segun Fatumo, H3Africa Bioinformatics Network (H3ABioNet) Node, National Biotechnology Development Agency (NABDA), Federal Ministry of Science and Technology (FMST), Abuja , Nigeria

Abstract:
Evaluating functional associations between an experimentally derived gene and a database of known gene is essential both to verify that the genes identified in a biological experiment are functionally relevant to the said biological process and to discover new and hidden shared functions between the genes. The traditional approach to solving this problem is to apply common statistics such as FET on gene annotated databases. These methods are based on the assumption that all genes have an equal probability of being selected. However, genes are not evenly annotated to functions. Most times little or nothing is known about the phenotype or biological process in question. In such cases, the significance of the genes in the gene set is underestimated.
We proposed here to convert the large and complex gene annotated data into a vector of 0’s and 1’s resulting in a pattern recognition problem to Machine learning algorithms can be applied to learn and then deduce functional associations among gene set accurately by method of pattern matching thus eliminating the bias of the traditional approach.


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P19
A comparative Analysis of the genetic relationships between the pathogens of Ebola hemorrhagic fever, Marburg virus, HIV, Hepatitis A, Hepatitis B, Hepatitis C, Hepatitis D, and Hepatitis E

Author(s):
Olaitan Awe, University of Ibadan, Nigeria
Segun Fatumo, University of Ibadan, Nigeria
Olugbenga Oluwagbemi, Covenant University, Nigeria

Abstract:
Ebola is a public health problem and a global monster currently ravaging many nations of the world especially West Africa. Ebola viruses are highly pathogenic, exotic agents that can cause severe hemorrhagic fever disease in human and/or nonhuman primates. Ebola is a member of the negative-stranded RNA virus family Filoviridae. Ebola is a very deadly virus.
A comparison of the gene content and genome architecture of Ebola Hemorrhagic Fever, Marburg virus, HIV, Hepatitis A, Hepatitis B, Hepatitis C, Hepatitis D, and Hepatitis E; major, eight related pathogens with different life cycles and disease pathology, revealed a conserved core protein sequence of genes in large syntenic polycistronic gene clusters.
In this paper, we highlight the genetics of the Ebola genome with the genome of seven other viruses to identify points of significant similarities and disparities.
The basic structure of Ebola is long and filamentious, essentially bacilliform, but the virus often takes on a "U" shape, and the particles can be up to 14,000 nm in length and average 80 nm in diameter. Genomics provides an unprecedented opportunity to probe in minute detail into the genomes of West Africa's most recent deadly disease - Ebola Hemorrhagic Fever. Here we report comparative genomics of Ebola strain, Zaire ebolavirus isolate Ebola virus/H.sapiens-wt/SLE/2014/Makona-EM095, complete genome. Knowledge gained from this comparative analysis can help provide innovative methods in solving the Ebola menace. An integrative knowledge of genetics and skills in bioinformatics can form a formidable tool in fighting the Ebola menace.


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P20
Genome-wide prediction for Mycobacterium tuberculosis small RNAs and their target mRNAs

Author(s):
Mmakamohelo Direko, University of the Western Cape, South Africa

Abstract:
Before their discovery in 2001, small non-coding RNAs (ncRNAs) were widely named 'junk DNA' because they do not code for proteins. Small non-coding RNAs are crucial regulators of gene expression and genome function.

Depending on the location of their target, the ncRNAs can be cis or trans-acting and they function by forming a chimera with Protein-coding Sequences.
In contrast to mammalian microRNAs, bacterial ncRNAs are heterogeneous in size (~50-550 nucleotides) and structure. The bacterial species’ most intensely studied with respect to ncRNA biology, Escherichia coli and Salmonella Typhimurium, each harbour at least 140 small ncRNA genes. Less attention has been given to the potential role of ncRNA regulatory processes in Mycobacterium tuberculosis. A recent study using six tuberculosis genomes in a comparative genomics approach identified the first collection of ncRNAs for Mycobacterium tuberculosis. Most of these small ncRNAs were predicted from sequence conservation data. In collaboration with the MRC TB centre of excellence at Stellenbosch University, we aim to analyze the high throughput sequencing data for over 400 Mycobacterium tuberculosis genomes. Access to this genomic data allows us to predict, characterize and annotate ncRNAs in the genomes of Mycobacterium tuberculosis species using 400 sequenced mycobacterial genomes. The large experimental dataset has informed the use of a machine learning strategy as a complement to the existing sequence conservation-based method. They identified ncRNAs will be mapped to the clinical phenotypes of these mycobacterial strains to predict the functions of these RNAs in the context of disease.


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P21
A combined genomic and transcriptomic approach to Leishmania major clinical isolates with contrasted clinical outcomes

Author(s):
Fatma Guerfali, Institut Pasteur de Tunis, Tunisia
Amel Ghouila, Institut Pasteur de Tunis, Tunisia
Dhafer Laouini, Institut Pasteur de Tunis, Tunisia

Abstract:
Leishmania (L.) major parasites are pathogens transmitted by the bite of a sand-fly vector, and are responsible in Tunisia for zoonotic cutaneous leishmaniasis in humans. The lack of efficient vaccine and drugs maintains the constant need for identifying parasite molecular targets to drugs. Whereas vector components and host genetic background can determine the outcome of the disease, parasite polymorphism between and within species is becoming one of the most studied factors. While classical approaches usually focus on one aspect of parasite biology, we conducted a systems-wide approach including genomic and transcriptomic analysis to point out potential virulence determinants of this disease. Moreover, in order to reveal intra-species differences that could discriminate between the different clinical outcomes of the disease, we included in this study parasites from Tunisian clinical isolates showing a completely different severity profiles in humans and pathogenicity in mice model of infection. The integration of this huge amount of data was a major challenge, and our findings importantly highlighted how the systems-wide approach can be integrated into one bioinformatic pipeline of analysis to reveal parasite genome characteristics such as plasticity. This work presents key findings regarding intra-species differences using human clinical isolates, emphasizing on chromosome-level variations and candidate gene selection. Our future prospects lies on functional studies of potential candidate parasite genes as drug targets.


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P22
Characterization and Structural Determination of Cellulase from Tomato (Lycopersicon lycopersicum L. Karst) fruits Deteriorated by Aspergillus flavus Linn

Author(s):
Adesola Ajayi, Covenant University, Adesola Ajayi, Covenant University, Nigeria
Chinenye Peter-Albert, Covenant University, Nigeria
Marion Adebiyi, Covenant University, Nigeria

Abstract:
Tomato fruits infected by Aspergillus flavus Linn produced proteins with cellulolytic activity. The enzyme was partially purified by Ammonium Sulphate Precipitation, Gel filtration and ion-exchange chromatography. Three peaks of absorption A, B and C were obtained. Peak B had Cellulase activity with molecular weight of approximately 30,200 Daltons while Peaks A and C lacked Cellulase activity. Elution of components of Peak B on CM Sephadex C-25 produced four peaks of absorption designated Ba, Bb, Bc and Bd. Only components of Peaks Bb and Bc possessed Cellulase activity. Purification folds of approximately 80 and 81 were obtained for components of Peaks Bb and Bc respectively for Cellulase of A. flavus. The apparent Km values for the hydrolysis of carboxymethylcellulose by A.flavus Cellulase fractions, Bb and Bc were approximately 16.7 and 15.4mg/ml respectively. The partially purified enzyme preparations obtained from A.flavus during the deterioration of tomato fruits caused tissue maceration and cellular death. This result can be very useful in splitting and solubilization of pectic substances and pathogenicity.

Abstract PDF, Click to download


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P23
Predicting 3d Structure of Anopheles gambiae Cytochrome P450 Protein

Author(s):
TRUST ODIA, COVENANT UNIVERSITY, TRUST ODIA, COVENANT UNIVERSITY, Nigeria
Marion Adebiyi, COVENANT UNIVERSITY, Nigeria

Abstract:
Malaria is a deadly disease that kills over a thousand children in Africa. intensive research is on-going to combat the infectious disease. The relevance and importance of protein function in the cell of an organism and it's structure can not be over emphasized in drug therapeutics/design and understanding infectious diseases like malaria. For those researchers working on malaria, other bacteria and proteomics in general, this work exposes them to tools, computational approaches and knowledge relevant for research in this field. The research work reveals the function in the host cell and structure of the "uncharacterized/ putative" cytchrome P450 protein in Anopheles gambiae (vector of plasmodium falciparum parasite).

Abstract PDF, Click to download


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P24
Bioinformatic pipeline for prokaryotic new genome assembly

Author(s):
Kais Ghedira, Institut Pasteur de Tunis, Kais Ghedira, Institut Pasteur de Tunis, Tunisia
Kais Ghedira, Institut Pasteur de Tunis, Tunisia
Raida Zghal Zribi, Centre of Biotechnology of Sfax, Tunisia

Abstract:
Bacillus thuringiensis (Bt) is a prokaryotic species able to produce insecticidal parasporal crystal proteins and has been extensively used for the biological control of insect pests. Thousands of Bt strains were isolated and sequenced to search for the most highly insecticidal toxic ones for Bt biopesticide commercialization, using various insect pest control fields. Several strains were used as successful Bt biopesticide in many countries for a long time, such as “Entobacterin” in China and Russia and “Spicturin” in India. Comparative genomics analysis showed that these parasporal crystal proteins are mainly located on the plasmids. In most bacterial genome sequencing experiments, whole genomic DNA is extracted from the isolate and thus the sequence data includes both chromosomal and plasmid DNA. Many researchers are interested in exploring which sequences are present in the plasmids, which plasmids are present in their bacterial genomes and which genes are present in their plasmids which is a crucial task. In this work, we report a bioinformatic pipeline for the genome sequencing of one Bacillus thuringiensis strain using miSeq Illumina next-generation sequencing (NGS) technology. This bioinformatic pipeline aims to: 1) determine which sequences belong to plasmids and which belong to chromosomes. 2) identify the complete genome sequence of the studied Bt strain using high performant assembler and scaffolder. 3) finally annotate the genome of the studied strain and identify insecticidal crystal (Cry) and vegetative (Vip) proteins.

Abstract PDF, Click to download


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P25
Human LACE1, a member of SEC18-NSF, PAS1, CDC48-VCP, TBP family of ATPases is required for mitochondrial protein homeostasis maintenance

Author(s):
Lukas Stiburek, First Faculty of Medicine, Charles University in Prague, Lukas Stiburek, First Faculty of Medicine, Charles University in Prague, Czech Republic
Jana Cesnekova, First Faculty of Medicine, Charles University in Prague, Czech Republic
Jiri Zeman, First Faculty of Medicine, Charles University in Prague, Czech Republic

Abstract PDF, Click to download


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P26
Genomic diversity of polydnaviruses in tsetse fly species from East Africa

Author(s):
Benard Kulohoma, International Centre for Insect Physiology and Ecology, Benard Kulohoma, International Centre for Insect Physiology and Ecology, Kenya

Abstract PDF, Click to download


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P27
Genomics of adaptation

Author(s):
Agostinho Antunes, CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Portugal, Agostinho Antunes, CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Portugal, Portugal

Abstract PDF, Click to download


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P28
New Mathematical Methods to Analyze DNA Gel images

Author(s):
Ahmed Alzohairy, Zagazig University, Egypt

Abstract:
The analysis of gel electrophoresis images is very crucial for molecular biologists to comprehend and interpret their experimental results. Thus, enhancing current mathematical methods and developing new accurate ones is very important and challenging task for bioinfomaticians. In current research work trials have been made tried to enhance the commonly used mathematical method in gel analysis known as "Fitting method estimation" and proposed new efficient method entitled "Ruler estimation" for preprocessing a given image and detecting lanes and bands automatically. Both mathematical methods were applied to detect unknown bands inside the lanes and implemented in our newly developed software. Three mathematical models namely, linear, quadratic and cubic fitting, were tested for the accuracy of detecting the bands and lanes in the gel image to determine the best fitting model. The software has the ability to manually add or delete any band(s) and estimate the size of any unknown band(s) on the gel. Moreover, the similarity and (dis) similarity between lanes "samples" were estimated based on comparing the number and sizes of bands to generate a phylogram tree. A friendly user interface was developed for this new program using MATLB GUI to extract useful bimolecular information accurately and automatically.


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P29
Wide-ranging snake venom database

Author(s):
Iftikhar Tayubi, King Abdul Azizuniversity, Saudi Arabia
Abdulaziz saleah, King Abdulaziz university, Saudi Arabia
fahad alzahrani, King Abdulaziz university, Saudi Arabia

Abstract:
Snakes belongs to reptilia phylum of animal kingdom. They produce a special kind of substance which is mostly poisonous but not all snakes are poisonous. This special kind of substance is called venom. Snake bite causes number deaths or in some came physical or physiological abnormalities. Venom is composition of many types of protein, which differs from species to species. Venoms contain more than 20 different compounds, mostly proteins and polypeptides. A complex mixture of proteins, enzymes, and various other substances with toxic and lethal properties serves to immobilize the prey animal, enzymes play an important role in the digestion of prey, and various other substances are responsible for important but non-lethal biological effects. Some of the proteins in snake venom have very specific effects on various biological functions including blood coagulation, blood pressure regulation, and transmission of the nervous or muscular impulse and have been developed for use as pharmacological or diagnostic tools or even useful drugs.Different snake species are found all over the world distributed according to their habitat. This databse is designed to gather various information about snakes, venom and drugs for curing snake bites. MySql and PHP [2]we are going to use for designing the database. The user can navaigate their search according their need. This databse can be useful for neurologists, pharmacologists, toxicologists by proving them a platform on which they can extract the information related to their field


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P30
Automatic correction of the nucleotide sequences

Author(s):
Fouzia RADOUANI, Institut Pasteur du Maroc, Morocco
Zakaria ELYAZGHI, LabTIC - ENSATg, Abdelmalek Essaadi University, Tangier - Morocco Chlamydia and Mycoplasma Laboratory - IPM – Casablanca- Morocco, Morocco
Ahmed MOUSSA, LabTIC - ENSATg, Abdelmalek Essaadi University, Tangier - Morocco, Morocco

Abstract:
The computer output for a sequencing run consists of chromatogram in ABI Format. When viewing chromatograms, there are some ambiguities at various sites along the DNA sequence, because the sequencing machine used to call the bases cannot always precisely determine what nucleotide is, when it is represented by either a broad peak or a set of overlaying peaks. In such cases, a letter other than A, C, G, or T is recorded, most commonly “N”. The purpose of this work is to develop an application allowing the automatic correction of these ambiguities. This program run under R platform and consists in the development of friendly user interface for an easy exploitation of results. For tests, we used sequences of bacterial strains detected in urogenital samples of patients with urogenital infections. As results, we note that our program, ABI Base Recaller, can give a good correction, very close to the manual one, it increases the rate of identity and coverage and minimizes the number of mis-matches and gaps. Thus, it provides solution to this problem and save biologist's time and labor.


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P31
Ensembl Variant Effect Predictor and the Ensembl Genome Browser

Author(s):
Anja Thormann, European Bioinformatics Institute (EMBL-EBI), United Kingdom
William McLaren, European Bioinformatics Institute (EMBL-EBI), United Kingdom
Laurent Gil, European Bioinformatics Institute (EMBL-EBI), United Kingdom
Sarah Hunt, European Bioinformatics Institute (EMBL-EBI), United Kingdom
Paul Flicek, European Bioinformatics Institute (EMBL-EBI), United Kingdom
Fiona Cunningham, European Bioinformatics Institute (EMBL-EBI), United Kingdom

Abstract:
Genome sequencing and variant calling have become major activities in many research projects. The Variant effect predictor (VEP) is a highly sophisticated and freely available tool for annotation and prioritization of large scale variation data including SNPs, indels and structural variations. The VEP is highly integrated in the infrastructure of the Ensembl genome browser and leverages the data that is provided by Ensembl for the variant annotation. The data provided by Ensembl, and most relevant for the annotation of variants, are the high quality gene models, regulatory regions, ancestral genome information and the Ensembl variation resources.
Starting from a VCF or simple tab delimited file, the VEP can process up to 1000 variants a second to annotate an entire exome in one hour. The default output includes Sequence Ontology consequence terms, and the genes, transcripts or regulatory regions that the variant falls in. There is an online version with a web interface, an off-line script that can be run locally using a cache file and a REST API interface. VEP works for any species that has an annotated gene set, defined in a GTF file or Ensembl database. Furthermore, the functionality of VEP can be extended by writing plugins and it is also possible to configure VEP to query additional custom datasets. The poster will give an overview of the functionality of the VEP and how the VEP leverages the data provided by the Ensembl project for the annotation of variation data.


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P32
Developing a Disease and Population Genetics Simulation Framework

Author(s):
Jacquiline Mugo, University of Cape Town, South Africa
Nicola Mulder, University of Cape Town, South Africa
Emilson Chimusa, University of Cape Town, South Africa

Abstract:
Though the cost of obtaining genetic data continues to decrease, easing acquisition of real data, simulation of data in population genetics remains imperative in statistical method evaluation and in the designing of new approaches. In addition, access to human genetics data is usually limited and requires requests to data access committees for every data set. Today, several simulation tools under different simulation frameworks exist, however, there is a still a need for a unified simulation tool that can simulate genetic data with a disease under a complex admixture scenario, while considering different evolutionary and demographic factors, like mutation, recombination, genetic drift, selection and migration. In this research, we utilize the currently available data and explore differences in the odds ratio between the case and control populations, as well as the hybrid isolation model for admixture simulation, to design a simulation tool under the resampling simulation approach. The tool, developed in Python language, allows the user to: simulate homogeneous case-control data under a null model, homogeneous case-control data under a causal model, an admixed population over a specified number of generations, an admixed case-control dataset under a null model, and an admixed case-control dataset under a causal model.


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P33
Web Based Ontology Visualizer

Author(s):
Kenneth Opap, University of Cape Town, South Africa

Abstract:
Web Based Ontology (WebO) Viewer
WebO is a web based ontology viewer that takes as input OBO formatted ontology file and organizes the contents as a network diagram with annotations.
An ontology is a computational representation of a domain of knowledge based upon a controlled, standardized vocabulary for describing entities and the semantic relationships between the entities. Graphically, ontology is represented as a directed acyclic graph (DAG) in which nodes represent the ontology terms and the edges connecting the nodes depict the relationships that exist between the two nodes.
Problems that WebO seeks to address
• The need to view the whole network of terms in the ontology in a concise network diagram.
• Current ontology viewers require extensive domain knowledge in order to use effectively. It is difficult to for instance find terms based on the features of the graphs such degree centrality. As a result it is difficult to perform exploratory research using current viewers.
• The need to eliminate the requirement to install ontology viewer software and related dependencies. The tool is web-based; one only needs a web browser to access its functionalities. This feature makes it easier for WebO to be integrated into analysis pipelines.
• The need to allow for dynamic manipulation of the ontology hierarchy i.e. nodes can be collapsed or expanded to hide or show descendant terms.
Suggested extensions
Query by graph features e.g. degree centrality.


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P34
LocNuclei: sorting the nuclear proteome using Machine Learning

Author(s):
Tatyana Goldberg, Technical University of Munich, Germany
Sebastian Seitz, Technical University of Munich, Germany
Mikael Boden, The University of Queensland, Australia
Burkhard Rost, Technical University of Munich, Germany

Abstract:
Sub-nuclear structures are associated with various nuclear processes. Hence proteins localized in these substructures are of great interest in understanding the interior mechanisms in the nuclei. Despite work on high-throughput methods, experimentally annotated proteins continue to be a minority. Even though predictions of sub-cellular localizations reach high levels of accuracy and coverage, the distinct substructures inside the nucleus are mostly not covered in these methods.

LocNuclei tackles this problem by using a profile-based String Kernel with Support Vector Machines. In a two step-approach it first distinguishes between proteins localized to the nucleus only those traveling between the nucleus and other compartments of a cell. In the second step, we zoom into the nucleus to predict protein’s localization in 13 distinct sub-nuclear structures, such as nuclear envelope and nucleolus. Evaluated on a non-redundant test set, LocNuclei achieved Q2=72% accuracy in distinguishing between nuclear travelers and not, and Q13=62% in classifying those in 13 sub-nuclear structures.

Our prediction method LocNuclei presents a convenient approach to assess intra-nuclear localization of newly discovered proteins and its results may be applied to other problems in biology as well.


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P35
Alignment-free methods for the detection and specificity prediction of Adenylation domains.

Author(s):
Miguel Santos, CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Portugal, Portugal
Guillermin Agüero-Chapin, CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Portugal, Portugal
Gisselle Pérez-Machado, Universidad Central ¨Marta Abreu¨ de Las Villas (UCLV), Santa Clara, 54830, Cuba, Cuba
Aminael Sánchez-Rodríguez, Universidad Técnica Particular de Loja, San Cayetano Alto, S/N, Loja, Ecuador, Ecuador
Agostinho Antunes, CIIMAR/CIMAR, Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Portugal, Portugal

Abstract:
Identifying Adenylation domains (A-domains) and their substrate specificity can aid the detection of Nonribosomal peptide synthetases (NRPS) at genome/proteome level and allow inferring the structure of oligopeptides with relevant biological activities. However, that is challenging task due to the high sequence diversity of A-domains (~10-40% of amino acid identity), and their selectivity for 50 different natural/unnatural amino acids. Altogether these characteristics make their detection and the prediction of their substrate specificity a real challenge when using traditional sequence alignment methods, e.g. BLAST searches. Here we describe two workflows based on alignment-free methods for the identification and substrate specificity prediction of A-domains. (1) We introduce a graphical-numerical method, implemented in TI2BioP v 2.0 (Topological Indices to BioPolymers), which in a first step uses protein four-color maps to represent A-domains. In a second step, simple topological indices (TIs) called spectral moments, are derived from the graphical representations of known A-domains (positive dataset) and of unrelated but well-characterized sequences (negative set). Spectral moments are then used as input predictors for statistical classification techniques to build alignment-free models that can be used to explore entire proteomes for unannotated A-domains. (2) The second workflow is based on alignment-free models constructed by Transductive Support Vector Machines (TSVMs) that incorporate information of uncharacterized A-domains. A-domains with known specificities were clustered by physicochemical properties of amino acids (AA). In a second step Support Vector Machines (SVMs) were optimized from vectors of characterized A-domains and later, SVMs integrated a fraction of uncharacterized A-domains during training to predict unknown specificities.


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P36
A new associative rule-based classifier for disease severity estimation

Author(s):
amel ghouila, Institut Pasteur de Tunis, amel ghouila, Institut Pasteur de Tunis, Tunisia
abir Kachouti, Faculty of Sciences of Tunis, Tunisia
Sadok Ben Yahia, Faculty of Sciences of Tunis, Tunisia

Abstract:
With the increasing amount of data collected, predictive data mining tools are becoming an essential instrument in clinical medicine. These tools can help clinicians to estimate the disease severity from patients’ profiles or/and to plan the most suitable treatment to a given patient. Supervised classification algorithms are commonly used for this task. Their objective is to learn disease parameters and classification rules from a training set of patient profiles with a well-known disease outcome. The classifier is used to guide the prediction of disease outcome and help decision-making for new cases. A wide variety of classification tools exist, however, the choice of the appropriate method depends on the disease parameters and on data types. Applied to patients datasets, classical methods may fail to extract relevant diseases parameters depending on data complexity and several aspects still need to be tackled. A new associative rule-based classifier has been developed recently. This new method involves a filtering process using correlation-based measures in order to improve the accuracy of the classifier. Classifier parameters and rules are learned from a training set integrating well known patients and control cases gathered in public databases. Inferred rules can help understanding the interdependency of clinical features and investigating the involvement of environmental variables. The first experiments performed on public breast cancer data sets showed an increase in the sensitivity and a better accuracy compared to the classical methods. This fully automatic approach could be applied to many other diseases.

Abstract PDF, Click to download


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P37
Data migration of consistent Sickle Cell Disease clinical-database at Muhimbili National Hospital in Tanzania

Author(s):
Raphael Sangeda, Muhimbili University of Health and Allied Sciences, Raphael Sangeda, Muhimbili University of Health and Allied Sciences, Tanzania
Hans Morsch, Muhimbili University of Health and Allied Sciences, Tanzania
Evarist Msaki, Muhimbili University of Health and Allied Sciences, Tanzania
Frederick Mbuya, Muhimbili University of Health and Allied Sciences, Tanzania
Sharon Cox, Muhimbili University of Health and Allied Sciences, Tanzania
Amel Ghouila, L'Institut Pasteur de Tunis , Tunisia
Bruno Mmbando, L'Institut Pasteur de Tunis , Tunisia
Bruno Mmbando, Muhimbili University of Health and Allied Science, , Tanzania
Alia Benkahla, L'Institut Pasteur de Tunis - IPT, Tunisia
Charles Newton, KEMRI-Wellcome Trust Research Programme , Kenya
Kais Ghedira, L'Institut Pasteur de Tunis, Tunisia
Julie Makani, Muhimbili University of Health and Allied Sciences, Tanzania

Abstract:
Proper usage of biomedical data can be useful in designing future research strategies and in patient management and care. Exploring the clinical data with text mining allow the prediction of healthcare costs, disease diagnosis and prognosis, and the discovery related healthcare patterns from other databases establishing, relationships among diseases, and relationships among drugs. Moreover; clinical research on the data can allow discovering disease intervention strategies. However, exploration of clinical data can be hindered if the database is not properly designed, un-normalized or contain redundant data. We hereby describe the automated migration of a clinical database containing cohort data of Sickle cell disease (SCD) patients attending clinic at Muhimbili National Hospital, in Dar es Salaam, Tanzania. The main objective was to migrate in the old SCD database into a new consistent database.

Abstract PDF, Click to download


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P38
Novel Computational-aided Designed Compounds as potential Antimalarial Drug candidates

Author(s):
Efejiro Ashano, Covenant University, Nigeria, Nigeria

Abstract:
Even though Nigeria and the Democratic Republic of Congo account for more than 40% of the estimated global cases of Malaria, most efforts in antimalarial drug research to combat this health problem have come from outside these regions. Recently, there is accumulating evidence that computational-aided approaches toward drug discovery vastly improve the efficiency of the drug discovery process. We present our progress and workflow in our antimalarial drug discovery and development research also adopting a computational-aided methodology. Using a structure-based drug design approach, we have completed virtual screening and rational antimalarial inhibitor design against one of our high priority P. falciparum enzymatic sites using structural and biochemical data obtained from PlasmoDB databases. Currently, seven (7) novel antimalarial drug candidates have been synthesized for the first set of preclinical efficacy and toxicity studies set to commence at the Covenant University, Nigeria. Based on the in-vitro activities best drug candidate performers will further be subjected to drug development using successive cycles of design, synthesis and in-vitro and subsequently in-vivo drug testing. This research potentially lends additional support to the effectiveness of in silico drug design as an alternative to more traditional drug discovery workflows and also highlights Africa’s (particularly Nigeria) emergence in her participation and contribution to the discovery and development of a product that addresses a regional and world health issue. This is largely attributed to institutional partnerships and sustained funding support (e.g. the H3AbioNet) towards capacity building and infrastructure in computational biology and genomics research in Africa.


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P39
In-silico investigation of the Anti-giardial activity of Ezetimibe using a comparative model of giardia homolog of human cholesterol uptake receptor NPC1L1 Protein

Author(s):
Rehab Ahmed, Faculty of pharmacy- University of Khartoum, Sudan
Malik Suliman, Faculty of Pharmacy- University of Khartoum, Sudan
Faisal M. Fadlelmola, Faculty of Science, University of Khartoum, Sudan

Abstract:
Giardia is a well-known worldwide major human parasitic disease. It is one of the remaining parasitic infections of the first world but it is more highly prevalent in the developing countries. The major problem of giardia in developing countries is its difficult diagnosis and moreover it is largely under-reported and thus it might be implicated in many chronic diseases.
There is an urgent need for new antigiardial agents. The issue of the side effects of the current medications used to treat giardia is one reason. Up to the moment there is no vaccine for giardia furthermore the problem of the emerging giardia resistance given the limited number of ani-giardia agents. Hence searching for potential therapeutic targets and agents is the objective of this research. An in-silico approach has been undertaken to decipher the possible antigiardial activity of Ezetimibe, hence the possibility of therapeutically switching the use of this drug.
Comparative modelling or homology modelling is a method that is used to predict the 3D structure of proteins. I-TASSER; an online webserver is used to predict the 3D structure of giardia homolog of human Niemann-Pick C1-Like 1 (NPC1L1) receptor. Ezetimibe is a cholesterol lowering agent, and it’s believed to inhibit cholesterol absorption through binding to human Niemann-Pick C1-Like 1 (NPC1L1) receptor. The hypothesis we proposed is that Ezetimibe or slightly modified derivative of it might have an inhibitory and/or killing effect on Giardia. Using AutoDock the possible binding of Ezetimibe to the giardia homolog is tested.


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P40
Large Scale Comparative Analysis of Host, Vector and Parasite Heat Shock Protein 90s

Author(s):
Ngonidzashe Faya, Rhodes University, South Africa

Abstract:
Worldwide, parasitic diseases are a huge health burden. The treatment of parasitic diseases is challenging, and identification of new drug targets is very important. Parasites survive within host organisms, and often alternate between different hosts during their life cycle. Changing host environment puts enormous stress on parasites and many of them express large amounts of heat shock proteins (Hsps) to adapt to these changes. Among Hsps, Hsp90s have an important role in stress environments. Yet, there has been little computational research done on Hsp90s to analyse them as potential parasitic drug targets. In this study, an attempt was made to gain detailed insights into the differences between human, vector and parasitic Hsp90s. A total of 104 sequences were retrieved and analysis was done in three groups based on the localization of the Hsp90; namely cytosolic, mitochondrial and endoplasmic reticulum (ER). Further, the parasitic proteins were divided according to the type of parasite (protozoa, helminth and ectoparasite). Within each group of proteins, distinct differences were observed in terms of physicochemical properties, amino acid compositions, and phosphorylation sites as well as motif analysis. Pairwise sequence identity calculations and phylogenetic tree analysis revealed that protozoan Hsp90s are distantly related to human Hsp90s. Statistical analysis predicted that the environment where Hsp90s are located influence the physicochemical properties of proteins. Overall, the results supported the view that Hsp90s are interesting potential drug targets especially for protozoan parasitic diseases.


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P41
Using phylogeny to infer bacterial species candidates for drug development

Author(s):
Ryan Awori, International Centre of Insect Physiology and Ecology, Ryan Awori, International Centre of Insect Physiology and Ecology, Kenya
Peter Njenga Nga’ng’a, International Centre of Insect Physiology and Ecology, Kenya
Lorine Nanjala Nyongesa, International Centre of Insect Physiology and Ecology, Kenya
Sara Murugi Kagotho, Trek Science, Kenya
Waruguru Wanjau, Trek Science, Kenya
Nyotu Gitau, Trek Science, Kenya
Rose Mbeya, Trek Science, Kenya
Fridah Wambui Kariuki, Trek Science, Kenya
Benard Wesonga Kulohoma, International Centre of Insect Physiology and Ecology, Kenya
Francis B. Mwaura, University of Nairobi, Kenya
Charles Waturu, Kenya Agricultural and Livestock Research Organisation, Kenya
Nelson O. Amugune, University of Nairobi, Kenya
Daniel Masiga, International Centre of Insect Physiology and Ecology, Kenya

Abstract:
Xenorhabdus is a bacteria genus of two significant characteristics to human health. The first is their antimicrobial production. Secondly, their natural habitat as the gut of soil dwelling Steinernema nematodes. The latter provides a novel source of antibiotics in the wake of global antimicrobial resistance. The objective of this study was to establish the evolutionary history of the Xenorhabdus genus to infer selection of the most suitable species for the development of novel antibiotics against resistant causative agents. The selected species would then be tested to ascertain for the production of antibiotics. The phylogeny of the genus was reconstructed using 1.2Kb SSU rRNA gene fragments. A dataset of 189 (n=183 from public databases, and n=6 generated in this study) Xenorhabdus SSU rRNA sequences was used that included all twenty-four type strains. Similar species clustered together validating the accuracy of the reconstruction. Xenorhabdus griffiniae was selected as the most suitable species for development of novel antibiotics against resistant pathogens. Inhibitory assays of its extracts were then carried out. Cell free extracts of the bacteria were inhibitory to gram-positive cocci. An organic solvent fraction of the extract, with a peak uv absorption of 218 nm, was inhibitory to Methicillin resistant Staphylococcus aureus. This indicated the presence of antimicrobial lipopeptides from Xenorhabdus griffiniae that were effective against Methicillin resistant Staphylococcus aureus.

Abstract PDF, Click to download


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P42
"Immuno­informatics and nanoantibody binders: review and structural analysis of VHH sequences

Author(s):
Ayoub ksouri, Institut Pasteur of Tunis, Ayoub Ksouri, Institut Pasteur of Tunis, Tunisia
Balkiss Bouhaouala , Institut Pasteur of Tunis, Tunisia
Ozlem Tastan Bishop, Rhodes University, South Africa

Abstract:
Toxicity of the scorpion venoms is essentially due to the presence of small toxins (7 kDa MW). Polymorphism of the secreted toxins at individual as well as species levels complicates the approach of treatment by antibody polyclonals. Treatment using Nanobodies (corresponding to recombinant single-domain antigen-binding fragments) , offer special advantages in therapy over classic antibody fragments due to their robustness and smaller size, matching the size of the scorpion toxins. Two sets of nanobody molecular sequences reported by 'LMVT' reaserch unity, were analysed and exploited to design more rational on the interface of toxin/Nanobody interactions. Novel strategies were used to identify the position variability of amino acid sequences of immunoglobulin VHH fragments and highlighted conserved positions and domains (motifs) in the two groups of sequences. We studied known sequences and structures (templates) to identify useful features and signatures, conserved positions and domains (motifs) in CDR hypervariable domains were highlited according to the hydrophobicity, volume, chemecal characterestics and visual inspection in the sequence alignments. Then, pharmacological data value were integrated to the Nanobody amino acid sequences, we notice that the neutralisation capacity of 'NbAahI_12' ( around '100 LD 50' ) show a significantly divergence compared to the rest of sequences, described in some amino acid residues and motif positions. The elaborated commun amino acid positions and motifs was investigated on the protein (Nanobody) structures. Our strategy is designed to use valuable information’s from nanobody sequences as well as pharmacological properties related to their bind to scorpion toxins to study crucial elements responsible of their demonstrated neutralizing and protecting capacities. The present approach may be adapted to design methodology for studying motifs generated by hypermutation or antigenic variations.

Abstract PDF, Click to download


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P43
Leveraging cross-population Gene/Sub-network Meta-Analysis to recover signals underlying ethnic difference in disease

Author(s):
Emile Rugamika CHIMUSA, University of Cape Town, South Africa
Abdoelnaser M. Degoot, African Institute for mathematical Sciences, Ghana
Mbiyavanga Mamana, University of Cape Town, South Africa
Gaston K. Mazandu, University of Cape Town, South Africa
Nicola J. Mulder, University of Cape Town, South Africa

Abstract:
Detecting human genetic variants that have low disease risk or strong epistatic effects still poses a challenge, suggesting the need for novel methods to combine effects of single-nucleotide polymorphism (SNPs) within a gene to increase the likelihood of fully characterizing the susceptible gene. Designing a post disease scoring analysis that combines the effects of different SNPs within genes or pathways from multiple independent studies in a single analysis may be helpful in identifying associations with small effect sizes in order to reveal larger effects. Here, we present a probabilistic and graph-based approach, ancMETA, to integrate the association signal from different independent genome wide association studies (GWAS) in order to de-convolute the interactions between genes underlying the pathogenesis of complex diseases. While handling heterogeneity between studies, ancMETA performs meta-analysis at gene and sub-network levels, and integrates the association signal from different independent GWAS studies using prior biological knowledge. ancMETA is an integrative analysis test since it uploads the outcome signal from meta-analysis into prior biological knowledge datasets. We validated ancMETA on null and causal simulated GWAS datasets using African, European and Mexican population ourresults from both simulations demonstrates the robustness of ancMETA against type I and II error. We also demonstrate that ancMETA can de-convolute the interactions between genes underlying the pathogenesis of complex diseases and provide valuable information that is useful to prioritize the most important results.


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P44
Coverage rate of ADME genes from commercial genotyping and sequencing assays

Author(s):
Nabil Zaid, Montreal Heart Institute - University of Montreal, Canada
Hassan Ghazal, Université Mohammed Premier, Morocco

Abstract:
Pharmacogenomics offers remarkable potential for the rapid translation of discoveries into changes in clinical practice. In the present work, we are interested in evaluating the ability of commercially available GWA genotyping chips to cover genes that have high pharmacogenomics potential.

We used a set of 2,794 variations within 369 ADME genes of interest. We have compared the Illumina’s ExomeChip, Omni, Infinium Human Core BeadChip and Affymetrix’ Axiom microarray genotyping technologies. We have developed Python scripts to evaluate the coverage for each of these products. In particular, we considered a specific list of 155 allelic variants in 34 genes which present high pharmacogenomics potential. Both the direct and indirect coverage by linkage disequilibrium was assessed.

The highest direct coverage was 65.16% for Axiom and the highest indirect coverage was 67.74% for Omni 5.0 with a linkage disequilibrium threshold of 0.8. Given the need to have a good coverage to establish confidently the functionality of an enzyme, the observed rates are unlikely to provide sufficient evidence for pharmacogenomics studies. We also assessed the theoretical/actual coverage using enrichment technology for exome sequencing using the Illumina’s Trueseq exome, Affymetrix SureSelect and Haloplex exome, which offer a coverage of 96.12%, 91.61% and 88.38%, respectively.

Although pharmacogenomics advances had been limited in the past due in part to the lack of coverage of genotyping chips, it is anticipated that future studies that make use of new sequencing technologies should offer a greater potential for discovery.


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P45
Computational Pharmacology Modelling: The RAFAGene Tuberculosis Pharmacokinetic as a case study

Author(s):
EZEKIEL ADEBIYI, COVENANT UNIVERSITY, Nigeria
JUMOKE SOYEMI, THE FEDERAL POLYTECHNIC, ILARO AND COVENANT UNIVERSITY, Nigeria
JELLILI OYELADE, COVENANT UNIVERSITY, Nigeria

Abstract:
Computational pharmacology is the application of bioinformatics and computational biology with relevance to pharmacology, including understanding of drug action, adverse drug reaction, identification of drug targets and drug design. Drug safety is crucial to public health and the adverse drug reactions (ADR) causes suffering and sometimes death in individual patients thereby evoking distrust of pharmacotherapy. Serious and unpredictable ADR continue to be a major public health concern. Our research interest is in OFLOTUB and RAFAGene drug trials for Tuberculosis, one of the NIH RAFAGene study aimed towards pharmacokinetic and pharmacogenetics. This research intend to computationally link the clinical results of phases I and II of Tuberculosis to their preclinical trials by comparing ADRs results from our computational method with their existing biological results and thus predict the ADR results of the currently ongoing clinical phase III of the OFLOTUB/RAFAgene study.
The research used other machine learning
algorithms to predict ADR by integrating phenotypic characteristics of drugs, drug chemical and biological properties with protein target and pathway information. Machine learning algorithms were also used. Drugs in SIDER database were mapped with PubChem, DrugBank and KEGG. The novelty and contribution to knowledge in this research is a model that can be used to make informed decisions so as to reduce the rate of attrition for drugs under development and increase the number of drugs with an acceptable benefit/risk ratio with TB as case study and also save enormous time in the future development of new drugs against the TB pathogen in the human


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P46
Genetic association analysis using an alternative regression approach involving random forest and shrinkage methods applied to the study of platelet activation pathways

Author(s):
Bajuna Salehe, University of Reading, United Kingdom
Liam McGuffin, University of Reading, United Kingdom
Giuseppe Di Fatta, University of Reading, United Kingdom
Chris Jones, University of Reading, United Kingdom

Abstract:
Genetic association studies (GAS) help us to identify key genetic variants or single nucleotide polymorphisms (SNPs) susceptible for complex diseases and traits. Platelet activation is among the complex traits which results to different signalling pathways in the underlying thrombus formation process, which plays key role in some cardiovascular diseases (CVDs) conditions. These pathways are the result of platelet responses to agonists’ activation. Previous candidate gene data analyses involving four pathways (P-selectin in response to adenosine diphosphate (ADP), P-selectin in response to collagen related peptide cross-linked (CRP-XL), fibrinogen binding stimulated with ADP and fibrinogen binding stimulated with CRP-XL) revealed some causal single nucleotide polymorphisms (SNPs) that strongly influence these pathways. The underlying characteristic of these genetic association (GA) data is that they are in high dimensional space with small number of observations (n) and large number of variables or SNPs (p). However, the previous approach used in analysing these data for platelet activation pathways involved stepwise linear regression. From the literature and our further analysis, we argue that the initial approach is deemed to be sub optimal in dealing with high dimensionality of genetic data complemented with high collinearity. Here, we propose a new combined approach involving shrinkage methods, ridge regression and LASSO, with the use of a random forest (RF) algorithm. Using this approach, we identified novel functional genetic variations related to platelet activation pathways that were not previously revealed.


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P47
Genome-wide association studies

Author(s):
Bridgious Walusimbi, Wellcome Trust Sanger Institute, United Kingdom

Abstract:
Genome-wide association studies (GWASs) are an effective approach for identifying the common genetic variation that underpins the different complex diseases in human populations. In a typical GWAS, DNA samples are obtained from participants, both with (cases) and without disease (controls). Individual genomes are then surveyed using genotyping chip arrays, for selected markers (tag SNPs) so as to investigate all possible genetic variation.Basing on the difference in frequency of a given SNP, between cases and controls, the gene involved in disease aetiology can be predicted statistically.I have done the quality control (QC) on Uganda vaccination GWAS data on UNIX platform, with a repertoire of commands in plink. I did both sample QC and marker QC. I started with 1416 samples and 2277237 autosomal markers. 17 samples were removed due to failure to pass the sample QC thresholds. 2 had gender non-concordance, 13 had failed heterozygosity check. 11 more samples were further removed because of high relatedness. 73540 autosomal SNPs were removed since they could not meet SNP call rate threshold of 97%. On carrying out the Hardy Weinburg equilibrium check 27002 autosomal SNPs were excluded. I therefore wish to share results and explain clearly the rationale for each step in the QC pipeline, after permission from people in-charge of the data, on platform like ISCB-Africa and to learn more as a young African scientist with a keen interest in genomics-based approaches.


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P48
Role of bioinformatics in health:genetics of HbF in sickle cell in Tanzania

Author(s):
Siana Mtatiro, Muhimbili University of Health and Allied Sciences, Tanzania
Stephan Menzel, King's College London, United Kingdom
Helen Rooks, King's College London, United Kingdom
Swee Lay Thein, King's College London, United Kingdom
Jeff Barret, Wellcome Trust Sanger Institute, United Kingdom
Tarjinder Singh, Wellcome Trust Sanger Institute, United Kingdom
Harvest Mariki, Muhimbili University of Health and Allied Sciences, Tanzania
Josephine Mgaya, Muhimbili University of Health and Allied Sciences, Tanzania
Bruno Mmbando, Muhimbili University of Health and Allied Sciences, Tanzania
Soka Deogratias, Muhimbili University of Health and Allied Sciences, Tanzania
Evarist Msaki, Muhimbili University of Health and Allied Sciences, Tanzania
Sharon E Cox, London School of Hygiene and tropical medicine, United Kingdom
Julie Makani, Muhimbili University of health and allied sciences, Tanzania

Abstract:
Role of bioinformatics in health: Understanding the role of genetic factors in influencing disease cannot be underestimated. Meaningful genetic association studies require both accurate genotype and phenotypes data. We have studied genetic factors associated with a major modulator of sickle cell disease (SCD). With this study we show how important bioinformatics is important in health in African settings. Sickle cell disease and fetal hemoglobin(HbF): In Tanzania, up to 11,000 children are born with SCD annually1. HbF is a known major modulator of SCD and individuals with high levels of HbF experience a milder form of the disease 2. However, HbF levels are highly genetically controlled3 and studies have been conducted to determine genetic factors that influence HbF with the aim of developing interventions. Until lately, most of HbF genetic studies have been conducted in non-African countries/populations although these populations experience the greatest burden of the disease. What we have done: We have studied a total of 1900 individuals with SCD with the aim of determining the prevalence of known loci and identifying novel ones. We performed targeted genotyping and genome wide association study. We have confirmed the prevalence of 3 known major loci associated with HbF and identified suggestive novel loci. We have also performed fine mapping study for one of the major HbF locus and identified a region suggestive of a causative variant. Conclusion: In this study, we have utilized the existing developments in genomics and bioinformatics through collaborations with scientists in Africa and in the UK.

Abstract PDF, Click to download


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P49
Bioinformatics Skills Assessment

Author(s):
Judit Kumuthini, CPGR, South Africa

Abstract:
Recent technological advances in high-throughput genotyping and in related information technologies have facilitated the growth of Bioinformatics field. The rapid growth of Bioinformatics necessitates ongoing refinement of Bioinformatics ontology-based skills in order to adequately build up, maintain and manage their relevance in both educational and professional Bioinformatics. As the discipline of Bioinformatics and computational biology expands and matures, it is important to characterize the skill components that contribute to the success of professionals and education in this field. Skills management has been recently acknowledged as one of the main factors to adequately confront the increasing competitiveness between knowledge intensive fields.


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P50
Operons used for plant colonization by a plant growth promoting rhizobacterium Bacillus atrophaeus UCMB-5137

Author(s):
Liberata Mwita, University of Pretoria, South Africa
Wai Yin Chan, University of Pretoria, South Africa
Oleg Reva, University of Pretoria, South Africa

Abstract:
Bacillus atrophaeus is a Gram positive plant growth promoting rhizobacterium (PGPR). It regulates its gene expression for successful plant colonization. Root exudate was collected from maize roots to stimulate chemical signals affecting Bacillus atrophaeus UCMB-5137 in rhizosphere. RNA-seq was used to reveal the bacteria transcript. RNA sequences obtained by MiSeq 500 Illumina sequencing in Inqaba after quality control and trimming were mapped against an available complete genome sequence of UCMB-5137 using CLC Genomics Workbench 7. Two independent experiment samples and three control samples were sequenced. EDGE statistics approach was used to identify significantly up- and down- regulated genes (at least 2 folds difference) with a p-value of ≤ 0.01. Operons coding for stress response, biofilm formation, transcription regulation, translation and many metabolic processes were important for plant colonization by this PGPR bacterium.


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P51
Globus Connect Deployment for the H3ABioNet Consortium

Author(s):
Mohamed Alibi, Institut Pasteur de Tunis, Mohamed Alibi, Institut Pasteur de Tunis, Tunisia

Abstract PDF, Click to download


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P52
Human genetic polymorphisms associated with uncomplicated malaria in an area under surveillance of febrile episodes in Korogwe, Tanzania

Author(s):
Bruno Mmbando, National Institute for Medical Research, Tanzania
Deus Ishengoma, National Institute for Medical Research, Tanzania
Method Segeja, National Institute for Medical Research, Tanzania
Mathias Kamugisha, National Institute for Medical Research, Tanzania
Daniel Minja, National Institute for Medical Research, Tanzania
Martha Lemnge, National Institute for Medical Research, Tanzania
MalariaGen Consortium, University of Oxford, United Kingdom

Abstract:
Abstract
Introduction
Both human host and parasite factors play an important role in determining the susceptibility to malaria infections. This study was conducted to explore genetic variants associated with uncomplicated Plasmodium falciparum malaria in a population under surveillance of febrile episodes in Tanzania.

Method
DNA samples were extracted from a cohort of 776 individuals aged 0–45 years recruited in May/June 2007. DNA samples were genotyped for 271 single nucleotide polymorphisms (SNPs) across a range of genes associated with malaria protection or susceptibility. After quality control, 176 (65%) SNPs in 714 individuals were available for analysis. Malaria episodes accrued by individuals over eight years of follow-up was modelled as a Poisson random variable.

Results
A total of 4848 person years was observed during the eight years of follow-up, with 852 malaria episodes recorded (184 episodes per 1000 person per year) out of 714 individuals included in the analysis. Ten SNPs (rs2069718 in IFNG gene, rs708567 -IL17RE, rs2522051 -LOC441108, rs3212227 -IL12B and rs1801033 –C6) were significantly associated with protection against uncomplicated P. falciparum infection, while individuals carrying rs1143634 - IL1B, rs6780995 –IL17RD, rs159903 -P4HA2, rs3181216 -IL12B, rs730691 -IL12B were associated with malaria susceptibility, p-value < 0.01.

Conclusion
This study has proved association of SNPs (rs2069718, rs708567, rs2522051, rs3212227 and rs1801033) known to be linked to malaria susceptibility to infections. Five SNPs (rs159903, rs2522051, rs3181216, rs730691 and rs1801033) were also associated with risk of malaria in this cohort study. Further confirmatory studies are required to prove their association with malaria infection.


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