Microbiology

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

Final Year Project in Microbiology

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Start date: 2021End date: 2024

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    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.
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    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.
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    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.
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    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
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    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.
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    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.
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    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.
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    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
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    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.
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    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.