Microbiology

Permanent URI for this collectionhttps://dspace.summituniversity.edu.ng/handle/123456789/24

Final Year Project in Microbiology

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ANTIBIOGRAM OF ISOLATED BACTERIA FROM SELECTED SACHET WATER IN OFFA, KWARA STATE AND DATASET COLLECTION FOR PREDICTIVE MODEL
(2023) LAWAL, AISHAT BOLANLE
In Nigeria, sachet water is the only reliable source of drinking water. Aiming to evaluate the prevalence and antibiogram of bacteria isolated from specific brands of sachet water in Offa, Kwara State, this study attempts to evaluate the health concerns posed by diseases contracted from eating contaminated water internationally. Ten different brands of sachet water available in Offa, Kwara state, were examined using established techniques to ascertain the pH and bacteriological purity. Two bacterial isolates were characterized by sequencing the 16S rDNA using the universal primers 27F and 1492R to amplify the 16S target region. All the samples were clear and odourless with the exception of Sc4. Antibiotic susceptibility testing was performed using the disc diffusion method. Some bacterial isolates cannot be taxonomically identified from phenotypic characteristics. The water samples' pH values ranged from 1.7 to 7.0. Out of the ten water samples, bacterial growths were found in every single one. The range of the total heterotrophic count in cfu/ml was 2.0 to 5.8. Most of the water samples contained coliforms, with a value ranging from 1.1 to 7.0x103 cfu/ml. Staphylococcus aureus, Pseudomonas sp, Alcaligenes feacalis, Bacillus cereus, Proteus vulgaris, and Escherichia coli were among the isolates that were detected. Most isolates were shown to be extremely susceptible to ciprofloxacin, ofloxacin, and gentamycin while being resistant to ceftriazone sulbactam, cefotaxime, and amoxicillin clavulanate. Except for Escherichia coli, the majority of the isolates were susceptible to Gentamycin (GN), and all but one of them were resistant to Ceftriaxone sulbactam. Since none of the sachet water samples examined in this study met WHO standards for drinking water, routine monitoring of sachet water makers ought to be mandated.
ANTIBIOTICS PROFILING OF BACTERIA ISOLATED FROM CATFISH HARVESTED FROM AFELELE RIVER
(2022) ADERINKOLA, Adenike Tayibat
Fishes are cheap sources of protein and are commonly reared in aquaculture systems such as rivers in Nigeria. Bacterial infested fishes have been a serious public health concern. This study was aimed at isolating and identifying bacteria associated with the internal organs (gills, intestine, guts) of Clarias gariepinus (African Catfish) in Afelele river in Offa, kwara state, Nigeria. In addition, the bacterial load of the organs and antibiotic susceptibility profile of the isolates to conventional antibiotics were determined. An African catfish was sampled from the river. Bacteria isolated on Mac-Conkey agar and Nutrient agar plates were identified based on morphological and biochemical characteristics. Susceptibility of the isolates to antibiotics was carried out using the Kirby-Bauer disc diffusion method. Isolates from the fish organs include species of Vibrio, Aeromonas, Pseudomonas, Klebsiella, Staphylococcus, Serratia, Proteus, Bacillus, Streptococcus and Micrococcus. Results also revealed that there was significant difference in the bacterial load recovered from the fish organs (gut, gill and intestine). Serratia sp. was the most abundant gram positive bacterium in the organs of the fish sample, while Pseudomonas sp., a gram negative organism, appeared in the intestine and gut. Percentage susceptibility of the bacteria to antibiotics was highest with Ciprofloxacin and Gentamycin (85%) and least with Ampicillin and Vancomycin (75.0%). The most susceptible isolates were species of Bacillus and Klebsiella while Staphylococcus specie was the most resistant bacterium. This study has shown that high bacteria load are found in the internal organs of the fish and a good number of the bacteria are resistant to some of the antibiotics tested. Therefore, there is a need for adherence to proper sanitary measures to avoid bacterial contamination of fish.
ANTIMICROBIAL EFFECTS OF SOME SELECTED ESSENTIAL OILS AGAINST SKIN PATHOGENS WITH THE COLLATION OF DATASET AND PREDICTIVE MODELS
(2023) ADEKUNLE, HALIMA ITUNU
Essential Oils (EOs) are concentrated natural extracts derived from plants, which were proved to be good source of antimicrobial properties. The study followed the effect of some commonly used essential oils against some of the most common pathogenic bacteria. The various oils used were Castor oil. Almond oil, Olive oil and Carrot oil against selected skin pathogens namely; Staphylococcus aureus, Corynebacterium diphtheria, Bacillus subtilis, Aeromonas and Pseudomonas aeruginosa. The collected isolates were confirmed using biochemical and microbiological tests. Carrot oil had the highest inhibiting activity against Bacilli and Corynebacterium with the value of 20mm while Almond oil and olive oil had no inhibition zone (NZ) against Corynebacterium and Pseudomonas. Ciprofloxacin was the control used and it showed significant inhibition against the clinical isolates. Olive oil had the lowest inhibition ranging from 5mm to 10mm. Combinatorial effect of the essential oils showed no antimicrobial activity against the isolates depicting antagonistic effects of the essential oils. In conclusion, carrot oil and castor oil had higher activity while almond oil and olive oil had the lowest activity against the selected clinical isolates.
ARTIFICIAL INTELLIGENCE FOR POST-PANDEMIC ASSESSMENT OF COVID- 19 VACCINATION UPTAKES IN SELECTED UNIVERSITIES IN KWARA STATE
(2024) ABDULHAMID, Khadijah Aliyu
Vaccination is aimed at averting the spread of COVID-19, but complications like vaccine hesitancy and resistance continue to arise, particularly in low-middle-income countries (LMIC) like Nigeria. This study examines factors contributing to vaccine hesitancy and the effectiveness of various communication strategies intended to promote vaccination. Through questionnaires distributed across four institutions in Kwara state, 201 participants were recruited. Most of the responded were between age 26-40 years where 95% were students, thus emphasizing the focus of the study on the student population. A smaller proportion consists of lecturers (3%) and non-teaching staff (2%). Females accounted for 58.2% while males had 41.8% of the population, indicating a relatively balanced gender representation within the study. The survey showed that only 42.7% received the COVID-19 vaccine, of these vaccinated participants, 53.4% received up to the second dose. While only 10.5% of participants had been fully immunized (AstraZeneca, Moderna, Pfizer-BioNTech, Johnson and Johnson). The most recurrent factors affecting the uptake of the COVID-19 vaccine among vaccine recipients were Friends and families (58.1%), Social media (5.1%), Personal decision (34.9%), Work (5.8%), The study found that the p-value, for significance regarding the factors influencing vaccination uptake is below 0.05. This suggests that the connections between the variables examined (like awareness, perception, and readiness to get the COVID-19 vaccine) and vaccination uptake are statistically significant, at a 5% level of significance. In addition, a predictive model was created with the help of machine learning techniques to predict vaccination trends, with precision pinpointing specific areas that require focused interventions. The research highlights the importance of public education and the promising role that artificial intelligence can play in improving vaccination strategies and overall public health results.
ASSESSMENT OF FOODBORNE PATHOGEN IN READY-TO-EAT FOOD SOLD BY THE STREET FOOD VENDORS IN OFFA
(2024) ADEKUNLE, AANUOLUWAPO ADERONKE
Street food vendors offer a wide variety of ready-to-eat foods that are popular due to their convenience and flavor. However, these foods can pose significant health risks if not handled properly. This study aims to assess the prevalence and types of foodborne pathogens present in ready-to-eat food sold by street food vendors. Using a combination of microbiological techniques and observational assessments, we collected and analyzed samples from various street food vendors across different locations The study focused on identifying common foodborne pathogens, including Salmonella, Shigella, Escherichia coli, Bacillus cereus, and Staphylococcus aureus. Results indicate the presence of multiple pathogens in a significant proportion of samples, highlighting critical areas where food safety practices can be improved. The findings emphasize the need for enhanced hygiene standards and regular monitoring to reduce the risk of foodborne illnesses associated with street food. This study provides a foundation for developing targeted interventions and public health policies to ensure safer street food consumption
ASSESSMENT OF THE INTRINSIC BIOREMEDIATION POTENTIAL OF SURFACE WATER OF AFELELE RIVER, OFFA, KWARA STATE
(2021) ABDULRAHEEM, Khairat Abiola
Study of the intrinsic bioremediation potential of Afelele River, Offa, Kwara state. The Objectives of this study is to determine the physicochemical properties, heavy metal content and also to isolate and characterize bacteria from Afelele surface water. Physicochemical properties were determined according to APHA standard method for the examination of water and waste water and Heavy metals contents of surface water were determined using Atomic Absorption Spectrophotometer (Bulk scientific VGP 210 model). Bacteriological analysis and biochemical characterization was carried out according to Bergey’s manual of determinative bacteriology. In view off the various anthropological activities around the study area such as dumping of refuse and washing, which has resulted in heavy pollution of the water. Hence, the potential of the river to bioremediate itself naturally (self-purification) is jeopardized. Microbes are very helpful to remediate the contaminated environment. The Physicochemical analysis of the river water indicates alkaline pH of surface water 8.81 ± 0.05. Other physicochemical properties indicate significant variations in the values obtained for the surface water. The alkalinity of the right wing RW1 is 65.30, while the Left wing LW1 is 66.80 and the outflow OF1 is 66.85. The acidity of IF2 is relatively low at 12.52±0.10. The Total dissolved solid (TDS) of OF1 at 250.55±2.51 is low compared to 299.50 ± 2.90 mg/l found in LW1, while IF-2 has the highest amount of the Total Suspended Solids (TSS) with 1196.85±4.51 compared to 1115.50±4.10 found in RW1. The value of the BOD is high in RW-2 at 3.80±0.02 and it is lower in the IF2 at 3.50±0.05.COD values are also high in the surface water. The COD of RW-2 is 4.07±0.09 which is the lowest among the regions of the river. The pH of the surface water is 8.81 ± 0.05 at the outflow OF1. Heavy metals content analysis showed high concentrations in the river water. Isolates obtained from the river water were identified as Pseudomonas aeruginosa, Yersinia pestris, Micrococcus spp., Klebsiella pneumoniae, and Edwardsiella tarda. This study has shown that Afelele river is a polluted system that requires remediation and that neither the water nor the fishes in the water is safe for human consumption. It also revealed the diverse culturable members of the surface water are well-adapted to various pollutants in the water and might play important role in the intrinsic bioremediation of the polluted ecosystem.
BASE - DATA FOR PREDICTIVE MODELLING OF MOBILE PHONE RADIATION IMPACT ON EAR BACTERIA FLORA
(2024) MOMOH, Maimuna Amira
Mobile phones have become an important part of modern life, providing so many advantages and conveniences. However, the ubiquity of these devices has raised concerns about their potential impact on human health, particularly in relation to the delicate ecosystem of the human ear. This research investigates the effect of mobile phone radiation on the microbial flora isolated from ear wax. The human ear and its functions, the ear microbiome, the characteristics of mobile phone radiation, and its potential biological effects were reviewed. Three distinct bacterial species - Pseudomonas aeruginosa, Staphylococcus aureus, and Staphylococcus epidermidis - were isolated from ear wax samples and identified based on their morphological and biochemical characteristics. The isolated bacteria were then subjected to mobile phone radiation exposure in an experimental setup. The results revealed that radiation inhibited microbial growth and it also significantly reduced the number of colonies formed on exposed plates compared to control plates. This finding is supported by quantitative data on the comparison of colony forming units (CFU/mL) between control and exposed plates over multiple samples and time periods. These results underscore the need for continued research into the biological effects of mobile phone radiation on microbial ecosystems and emphasize potential implications for public health and hygiene practices. The integration of artificial intelligence in predictive modeling could provide valuable insights into the complex interactions between mobile phone radiation and the ear microbiome. This study lays the foundation for future work on developing predictive models to understand and mitigate the impact of mobile phone radiation on the delicate microbial balance in the human ear.
BIOFLOCCULANT PRODUCTION FROM MICROBIAL CONSORTIUM AND EVALUATION OF FLOCCULATING ACTIVITY USING ARTIFICIAL INTELLIGENCE
(2023) ALLI, WULAIMOT TEJUMOLA
Water pollution from industrial sources has increased, and it has become a serious environmental problem. Improperly treated wastewater, including chemical and microbial waste, pollutes water bodies and poses risks to ecosystems and human health. Inorganic flocculation has been used as a viable method of wastewater treatment but poses potential health risks. Therefore, we need to find safe alternatives to inorganic flocculant. This project aims to generate bioflocculants from a microbial consortium and evaluate their flocculating activity using artificial intelligence. This study focuses on isolating bacteria from the Henge River from and testing their ability to produce bioflocculants. Twelve bacterial were isolated and group into three i.e., GROUP A (1= Bacillus sp, 2= Pseudomonas sp, 3= Pseudomonas sp, 4= Bacillus cereus) GROUP B (1= Streptococcus sp, 2= Serratia sp, 3= Klebsiella 0sp, 4= Staphylococcus sp) and GROUP C (1= Staphylococcus sp, 2= Corynebacterium sp, 3= micrococcus sp, 4= Acetobacter sp) at double, triple, and quadruple combination. The statistical variance was also calculated using ANOVA and post HOC test. Group A showed a range of flocculating activity of 85%, to 34% which were produced by consortium A1, 3, 4 and A1, 2, 3 and 4. The range of flocculating activity for Group B was 93%, to 64% which were produced by consortium B2, 4 and B1, 3. For consortium C, the flocculating activity range was 88% to 52% which were produced by consortium C1, 3 and C3, 4. The consortium of the isolate showed significant flocculating activity suggesting that combination of organism could produce bioflocculant with better activity. The compilation of dataset for the artificial intelligence in evaluating activity will minimize human errors and enhance precision.
BIOPROCESS OPTIMIZATION OF MICROBIAL OIL YIELD FROM Aspergillus niger USING MACHINE LEARNING MODEL AND CO-CULTURE OF SWEET POTATO PEEL AND SHEA BUTTER KERNEL AS CARBON SOURCE
(2024) AKINLOLU, Rahmota Layemi
This study investigates the optimization of microbial oil production with the fungus Aspergillus niger utilizing bioprocess engineering methodologies supplemented by machine learning models. To increase lipid yield, co-culture system that includes sweet potato peel and shea butter kernel as carbon sources. The project’s goal is to establish optimal conditions for microbial growth and oil production by investigating the relationships between co-culture substrates and fungal metabolism. This project research investigates the isolation of fungal species, the screening of oleaginous microorganisms, and the processes of fermentation, extraction, optimization, and quantification of microbial oil from oleaginous fungal strains capable of lipid production, utilizing the Congo red agar screening techniques. Five distinct fungal isolates were obtained, with two of these identified as oleaginous fungi through Congo red screening. One of these two isolates was selected for further analysis regarding microbial oil production. This isolate was characterized by its morphological features, growth rate, microscopic structure, biomass yield, and microbial oil output. The likely identify of selected isolate is Aspergillus niger. Highest biomass weight was recorded at day 7 (13.74g) for co culture fermentation of shea butter kernel and sweet potatoe peel, while the lowest weight was recorded at day3 (8.89g). Highest biomass weight was recorded at day 11 (22.50g) for fermentation of glucose, while the lowest weight was recorded at day3 (13.80g). The research indicate that the extracted microorganisms have the potential as a suitable feedstock for producing microbial oil, Due to their ability to breakdown lipids and generate high oil yields. Also, this research attempts to establish an effective and sustainable approach for microbial oil production, contributing to the advancement of bio-based alternatives.
BIOPROCESS OPTIMIZATION OF MICROBIAL OIL YIELD FROM Aspergillus niger USING MACHINE LEARNING MODEL AND PALM FRUIT EMPTY FIBRE AS CARBON SOURCE.
(2024) BELLO, Roqeebat Opeyemi
Microbial oil is a valuable product that can be produced from Aspergillus niger through a process called fermentation and it is one of the filamentous oleaginous fungi, as several studies shows that the fungus can be cultured on various growth media showing important accumulation of single-cell oil. Palm fruit empty fiber (PFEF) is a type of agrowaste used as a bioprocess substrate in this research. The samples were collected from two dumpsites location (Afelele river and Summit university), isolation of fungi using PDA at 20-25 for 5 days incubation period, screening of oleaginous fungi isolates for lipid synthesis using Congo red Agar leaving a clear precipitation zone (hydrolysis activity) around the pure fungal colony in the plates, identification of fungi with the use of microscope, Yeast Extract Peptone Dextrose broth was used in the fermentation process using PFEF and Glucose as carbon source in extraction and optimization of lipid production was used in this research approach, so as, to utilize microbial lipids can simultaneously support the generation of clean energy, manage biomass waste and deliver clean energy. However, decision tree algorithm was used in predicting the result in this research study. Result of the fermentation, it is observed that Day 11 has the highest growth rate of 8.81g for the wet oleaginous fungi while 1.32g for the dried and for these results, it discussed the most recent developments in the bioprocessing of oleaginous fungus using palm fruit empty fiber as carbon source.
BIOPROCESS OPTIMIZATION OF MICROBIAL OIL YIELD FROM Aspergillus niger USING MACHINE LEARNING MODELS AND CORNCOB AS CARBON SOURCE
(2024) MUHEEB, Wasilat Opeyemi
Microbial oils present a sustainable alternative to traditional fats, and Aspergillus niger emerges as an ideal candidate due to its exceptional production capacity and genetic engineering. By utilizing corncob, a readily available agricultural residue, this research not only offers a cost-effective solution but also aligns with the principles of environmental sustainability. The optimization of bioprocess plays an essential involvement in maximizing oil yield, and genetic algorithms provide an efficient approach to identify the optimum conditions. This study, Consequently addresses global challenges such as the scarcity of fossil fuels and the necessity for environmental sustainability by Supporting the transition towards a bio-based economy and enhancing our understanding of bioprocess engineering. Samples were collected from two different dump sites, PDA was used to isolate fungal using serial dilution and pour plate method, screening for lipolytic activities using Congo red Agar media, Yeast Extract Peptone Dextrose broth was used for fermentation with Corncob and Glucose. Aspergillus niger was identified with the aid of microscope, the utilization of microbial lipid was obtained from the dried biomass based on Bligh and Dyer extraction methods and decision trees was used for prediction. Five pure isolates of different strains of fungal were obtained on PDA plates after incubation at 20-25°С. Two fungal isolates show a positive clear zone of precipitation around the pure fungal isolate, of which one organism was studied. Using the results for the fermentation, it was observed that Day 11 has the highest growth rate of 16.02g for the wet Oleaginous fungi while 2.88g for the dried and for these results. The study has shown that Oleaginous fungi can produce lipids that are beneficial for biodiesel production through the utilization of Corncob.
BIOPROCESS OPTIMIZATION OF MICROBIAL OIL YIELD FROM Aspergillus niger USING MACHINE LEARNING MODELS AND SHEA BUTTER KERNEL EXTRACT AS CARBON SOURCE
(2024) FATUNMBI, Kanyinsola Cynthia
The optimization of biological processes involving Aspergillus niger is necessary and vital for improving its industrial applications, especially in valuable metabolites production. This study burrow into the utilization of Machine Learning (ML) models to maximize the metabolite production and growth of Aspergillus niger using Shea Butter Kernel Extract (SBKE) as a carbon source. This research involves sample isolation, serial dilution, preparation of Potato Dextrose Agar (PDA), Fungi isolation, identification of fungi isolate macroscopically, preparation of stock culture, screening of oleaginous fungi using Congo red Agar, medium of fermentation for the preparation of microbial oil using SBKE as a carbon source and also using glucose as a carbon source, identification of fungi microscopically, lipid extraction from oleaginous isolate and optimization of microbial oil yield using ML models. The result shows that five (5) fungal isolates were obtained on PDA plates after being incubated, the morphological characteristics, the oleaginous activities and lipopolytic activities of fungi isolates, the result of the wet biomass with glucose compared to SBKE and the result of the dry biomass with glucose compared to SBKE. Incubation day 13 has the highest fungal biomass while incubation day 3 has the lowest fungal biomass while using SBKE. . Incubation day 9 has the highest fungal biomass while incubation day 13 has the lowest fungal biomass. From the result on the graph, glucose yielded better than SBKE except on day 13 (2.63g) and 15 (2.23). This research adds to sustainable biological processing by using a renewable carbon source and illustrates the importance of ML to transform the applications of biotechnology.
BIOPROCESS OPTIMIZATION OF MICROBIAL OIL YIELD USING RESPONSE SURFACE METHODOLOGY
(2023) ZUBAIR GANIYAT OLANSHILE
Microbial oil, which has found applications in the food and cosmetics industries, is considered a valuable substitute for traditional oil sources. The production of microbial oil by oleaginous microorganisms offers a potential solution for sustainable oil production. The biodiesel industry faces challenges related to the availability of low-cost feedstocks, which could be addressed by exploring microbial oils from filamentous fungi. The purpose of the study is to optimize filamentous fungi to produce microbial oil yield using response surface methodology (RSM). In this study the isolation of isolates was carried out using serial dilution techniques, screening for lipolytic activity using Congo red plate, and Sudan black B staining, identification was carried out using microscopic, and colonial morphology characteristics, fermentation was carried out using solid-state and extraction of lipid fungi in compliance with the Bligh and Dyer method. A total of 16 fungal isolates were obtained out of which 8 isolates were filamentous fungi. Three (3) out of the Eight (8) isolates show precipitation zones on the plates, the selected fungus indicates the presence of black colored globules within the cell for Sudan black staining. The 8 positive isolates belong to the following genera: Trichoderma sp, Aspergillus sp, Rhizopus sp, and Candida sp,. The amount of lipid yield against incubation days were: 1ml at day3, 2ml at day 5, 2.2ml at day 7 and 3ml at day9. The study revealed that oil-enriched soil harbors a significant abundance of oleaginous micro organisms, which can serve as a viable substitute for biodiesel production.
BIOSYNTHESIS OF ZINC OXIDE NANOPARTICLES USING SWEET POTATO PEEL EXTRACT (Ipomea batata) AND IT’S ANTIMICROBIAL EFFECTS
(2023) AFOLABI, BOLAJI ABUBAKAR
This study focuses on the biosynthesis of silver nitrate (AgNps) and zinc oxide nanoparticles (ZnO NPs) using sweet potato peel extract. The aim of the research is to develop a sustainable and environmentally friendly approach for the green synthesis of ZnO NPs, overcoming the limitations of conventional methods. The specific objectives include the extraction and characterization of bioactive components from sweet potato peels, characterization of the synthesized AgNps and Znps using UV- spectrophotometer and assessment of the antifungal activity of the nanoparticles. The sweet potato peel extract proved to be an effective reducing and stabilizing agent for the synthesis of ZnO NPs and Ag NPs. Proximate analysis was done and the values obtained ranges from 0.88% which was the lowest recorded value at lipid Concentra to about 90% which was the highest value recorded at dry Matter. Phytochemical analysis of the sweet potato peel extract revealed the presence of bioactive compounds such as phenols, tannins, flavonoids, saponins, alkaloids, terpenoids, and steroids. The values obtained from the result for the phytochemical analysis ranges from 0.120482 mg/l which was the lowest recorded for saponin to 10.19391mg/l which was the highest recorded value for flavonoid. These compounds are known to possess antioxidant, antimicrobial, and other beneficial properties, suggesting their involvement in the biosynthesis and stabilization of the nanoparticles. Antifungal activity assessment demonstrated the potential of the synthesized nanoparticles as effective antifungal agents as the nanoparticles were treated against Aspergillus sp isolated.. ZnO NPs exhibited potential higher inhibitory effects against isolated fungal pathogens compared to Ag NPs. These findings indicate that the biosynthesized nanoparticles could serve as eco-friendly alternatives for controlling fungal infections. This study recommend that further research should explore the utilization of other waste biomass sources for the synthesis of nanoparticles, contributing so as to contribute to waste management and sustainable nanomaterial production
DEVELOPMENT OF AN AI-POWERED SYSTEM FOR LABORATORY IDENTIFICATION OF SELECTED ENTERIC BACTERIA
(2024) MUHAMMAD Fatima Bashir
Microorganisms, commonly referred to as microbes, are living organisms too small to be seen by the naked eye but observable with a microscope. This study presents the development of an AI-powered system for the laboratory identification of selected enteric bacteria. Leveraging machine learning algorithms and comprehensive datasets containing morphological and biochemical features, the system aims to enhance the accuracy and efficiency of bacterial identification. The process includes gathering relevant data and literature on laboratory identification methods for selected bacteria, compiling a comprehensive database of identification features, developing machine learning algorithms capable of identifying bacteria based on key features, and laboratory confirmation of selected isolates with the developed model. The dataset encompasses selected enteric bacteria: Pseudomonas species, Vibrio species, Escherichia species, Citrobacter species, Staphylococcus species, Salmonella species, Shigella species, Campylobacter species, Clostridium species, and Enterococcus species. Results from the analysis showed that the Support Vector Machine (SVM) and Random Forest models achieved the highest accuracy at 83%, while the XGBoost model reached 50%. Conversely, the Decision Tree and ANN models performed poorly with 16% accuracy each. These findings underscore the potential of AI-driven approaches, particularly SVM and Random Forest, to revolutionize bacterial identification, with significant implications for public health, research, and clinical practice.
EVALUATION OF SILVER NANOPARTICLE AND BIOFLOCCULANT IN WASTEWATER TREATMENT USING SMART ANALYSIS
(2024) KOLAWOLE, Teslimah Oyindamola
Wastewater is just water that has been used and contaminated, usually in industrial, agricultural, or home settings. The research reports on the impacts of a combination of bioflocculants and silver nanoparticles made by two microorganisms taken from the microbiology lab at Summit University. The use of chemicals for wastewater treatment has been shown to have negative effects on humans and ecosystems. For this reason, the United Nations adopted the Sustainable Development Goals (SDG) in 2015, resulting in the creation of 17 global SDGs, of which Goal 6 is about clean water and sanitation to support the maintenance of global ecosystems, human prosperity, and peace. The organisms were identified as Klebsiella sp. and Staphylococcus sp. after they were earlier recovered from the Afelele River in Offa, Kwara State. Bioflocculant was made with formed bioflocculant culture broth, and neem (Azadirachta indica) was used to create silver nanoparticles (AgNo3). After shaking for seven days, the flocculating activities of AgNO3 were the lowest at 68.5%, while those of Klebsiella sp. and Staphylococcus sp. were 71.1% and 71.4%, respectively. With a flocculating activity of 81.9%, the combination of AgNo3 and Staphylococcus sp. bioflocculant demonstrated higher activity than a single usage. These findings point to a synergistic interaction between the bioflocculant and nanoparticles that improves wastewater treatment activity. The use of sophisticated analysis to the flocculating and nanoparticle activities decreased human error and improved the accuracy of the results.
ISOLATION, SCREENING AND PRODUCTION OF MICROBIAL OIL YIELD FROM OLEAGINOUS MICROORGANISMS
(2023) AWOSANYA, LAMIN MEDINAH
This study intends to isolate oleaginous microorganisms (fungi) from oil-rich soil and optimize bioprocesses to increase microbial oil yield. First, prospective oleaginous fungi in oil-rich soil must be isolated. The objective is to identify lipid-producing bacteria that can develop quickly in their natural environment. A screening procedure is used to determine which fungi produce the greatest lipids after they have been isolated. Usually, to achieve this, isolated fungi are cultured in environments that encourage lipid buildup. There are numerous screening methods that can be used. The ideal Oleaginous fungi (Aspergillus niger)growing conditions must be achieved in order to maximize lipid synthesis. These microbes grow and accumulate lipids in response to factors like temperature, pH, nutrient concentrations, and the availability of carbon sources. The process of removing the lipids from the cells comes next when the fungi have gathered enough lipids. It is possible to refine the recovered lipids further to produce pure oils suitable for use in biofuels or other high-value goods. The results made it clear that low-cost carbon sources must be used to grow these microorganisms and that the bioprocess's performance needs to be improved in terms of both yield and productivity. Oleaginous fungi can accumulate more lipids than 20% of their dry biomass. A variety of species of yeasts and filamentous fungi are categorized as oleaginous because they have the capacity to synthesize and store considerable amounts of TAG within their cells—up to 70% of the biomass weight. Single cell oil (SCO) production methods using heterotrophic oleaginous microorganisms have received a lot of attention recently. Due to their outstanding efficiency at accumulating intracellular TAG, oleaginous fungi, particularly yeasts, are projected to be utilized by the biofuel industry. The absence of readily available , reasonably priced feed stocks is the main issue facing the biodiesel industry. A successful method to boost microbial lipid productivity and lower the cost of microbial biofuel production is to regulate environmental conditions and optimize environmental parameters to improve the synthesis of microbial lipid.
MICROBIAL DIVERSITY OF RAW MILK COLLECTED FROM OFFA METROPOLIS
(2021) POPOOLA, OPEYEMI HELEN
Milk has an outstanding nutritional quality but it is also an excellent medium for bacterial growth and an important source of bacterial infection when consumed without pasteurization. Generally microbial contamination of milk can occur through the udder and its exterior, milk handlers and storage equipment. Furthermore, the collection and transportation of raw milk to the processing centers in most developing countries usually goes unchecked/ unsupervised. There is paucity of data on the routine hygienic quality control of raw milk and milk product in Offa and thus poses significant health risk to the consumers. The aim of this study is to isolate, identify, and characterized bacteria from fresh milk samples collected around Offa and its environment for evaluation of consumption safety. The samples was carried out by using serial dilution of 104,6&7 and was plated by using pour plate method, morphological characterization was carried out and lastly biochemical test. A total of ten isolates were recovered from three fresh milk samples across Federal Polytechnic Offa (animal husbandry), Ojuku area and Ilemona area in Offa. The pathogenic bacteria was identified by using the bergeys manual of determinative bacteriology from the sample includes Klebsiella oxytoca (20%), Enterobacter intermedius (40%), Klebsiella pneumonia (20%), Enterobacter aerogenes (10%), and Serratia fonticola (10%). Many bacteria could get access to milk and milk product such as E. coli (coliforms) which are often used as indicator organisms to confirm the bacteria contamination of milk.
PRELIMINARY PHYTOCHEMICAL INVESTIGATION AND ANTIBACTERIAL ACTIVITIES OF LEAF EXTRACT OF CHERRY MANGO AGAINST SELECTED CLINICAL ISOLATES
(2024) ABDULAZEEZ AISHAT OPEYEMI
The project "Preliminary Phytochemical Investigation and Antibacterial Activities of Leaf Extract of Cherry Mango against Selected Clinical Isolates" explores the medicinal potential of cherry mango leaves. It aims to identify bioactive compounds in the leaf extract and evaluate their antibacterial properties against clinical bacterial isolates. The study involves extracting leaves using various solvents, screening for phytochemicals, and testing antibacterial activity against Gram-positive and Gram-negative bacteria. Preliminary findings indicate the presence of several therapeutic phytochemicals and significant antibacterial effects, suggesting the extract's potential as a natural antibacterial agent. The research supports the traditional use of cherry mango leaves in herbal medicine and contributes to developing new plant-based antimicrobials. Further studies are recommended to isolate active compounds and assess their clinical efficacy and safety. The study investigates the phytochemical composition and antibacterial properties of cherry mango leaf extract against specific clinical bacteria strains. This research aims to identify potential bioactive compounds present in the leaf extract and evaluate their effectiveness in inhibiting bacterial growth, providing valuable insights into the medicinal properties of cherry mango leaves. Standard methods were employed to screen for the phytochemicals. Agar well diffusion method was used to determine the antimicrobial effects of methanolic extracts of Mangifera Indica leaves against four different clinical isolates namely: Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa and Salmonella typhi which S. aureus has the lowest zone of inhibition (22mm) while S. typhi has no zone of inhibition in leave while in bark, P. aeruginosa has the highest (22mm) and S. typhi has the highest zone of inhibition (25mm) and were compared with standard antibiotics which also high zones of inhibition. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extract was done using broth dilution and the activity of different extracts will be compared. Aqueous extract will be demonstrated at a higher activity than the ethanolic extracts Staphylococcus aureus will show highest sensitivity to the aqueous extract to the least sensitivity will be observed in the Klebsiella pneumoniae with each in the two extract Mangifera Indica will exhibit a significant antimicrobial activity compare to gentamicin will be used as control.
PRELIMINARY PHYTOCHEMICAL INVESTIGATIONS AND ANTIBACTERIAL ACTIVITIES ON LEAF EXTRACT OF JULIE MANGO CULTIVAR AGAINST SELECTED CLINICAL ISOLATES
(2023) MUSTAPHA, FAIZAH
The source of a large outbreak of food borne disease caused by contaminated food (dried fish) has been traced to Nigeria. Although the microbiological quality of dry fish sampled was similar to that found in markets from developed countries, the presence of pathogens causes a risk of infection for consumers. There are several ways in which dried fish processing and consumption can be affected by pollution as result of environmental consequences. Environmental Air pollution is detrimental effect of fish processing. Each of these will be considered in turn in this work. The objective of this work was to evaluate the effect of air pollution in food stuff such as dried fish.Fish processing environment is very favorable for the growth of microorganisms and highlights a potential risk associated with microbial hazards. The present study investigated the growth behavior of aerobic bacteria, yeasts and molds, and bacterial pathogens or surrogate (Listeria monocytogenes and Clostridium sporogeneses) on thawed and fresh catfish fillets during refrigerated storage (5°C - 7°C). Thawed and fresh fillets were respectively inoculated with L. monocytogenes and C. sporogeneses’, and packaged in LDPE bags. In uninoculated catfish, the populations of aerobic bacteria, and yeasts and molds increased significantly (P < 0.05) after 24 h of storage. The acceptable microbial limit was exceeded by aerobic bacteria (7.446 log CFU/g) after 4 days, and yeasts and molds (2.97 log CFU/g) after 3 days of refrigerated storage. Listeria population increased by 1.51 log CFU/g on thawed catfish after 6 days of storage. However, there was no significant increase in growth of C. sporogeneses’ vegetative cells on fresh catfish fillets. These results indicated that the microbiological quality of refrigerated thawed catfish would become unacceptable within 3 - 4 days. Our results also implied that environmental pathogens such as L. monocytogenes and Clostridium sp. can survive on catfish fillets for extended periods during refrigerated storage