Research Outputs

Permanent URI for this collection

http://hdl.handle.net/20.500.11837/3255

Browse

Browsing Research Outputs by Title

Now showing 1 - 5 of 5
  • Thumbnail Image
    Item
    Chryseobacterium aquifrigidense keratinase liberated essential and nonessential amino acids from chicken feather degradation
    (Taylor and Francis, 2023) Bokveld, Amahle; Nnolim, Nonso E.; Digban, Tennison O.; Nwodo, Uchechukwu U.
    Keratinous biomass valorization for value-added products presents a high prospect in ecological management and the advancement of the bio-economy. Consequently, soil samples from the poultry dumpsite were collected. The bacteria isolated on the basal salt medium were screened for keratinolytic activity. The potent chicken feathers degrading bacteria were identified through 16S rRNA gene sequencing and phylogenetic analysis. Fermentation process conditions were optimized, and the amino acid compositions of the feather hydrolysate were likewise quantified. Ten (10) proteolytic bacteria evaluated on skimmed milk agar showed intact chicken feather degradation ranging from 33% (WDS-03) to 88% (FPS-09). The extracellular keratinase activity ranged from 224.52 ± 42.46 U/mL (WDS-03) to 834.55 ± 66.86 U/mL (FPS-07). Based on 16S rRNA gene sequencing and phylogenetic analysis, the most potent keratinolytic isolates coded as FPS-07, FPS-09, FPS-01, and WDS-06 were identified as Chryseobacterium aquifrigidense FANN1, Chryseobacterium aquifrigidense FANN2, Stenotrophomonas maltophilia ANNb, and Bacillus sp. ANNa, respectively. C aquifrigidense FANN2 maximally produced keratinase (1460.90 ± 26.99 U/mL) at 72 h of incubation under optimal process conditions of pH (6), inoculum side (5%; v/v), temperature (30°C), and chicken feather (25 g/L). The feather hydrolysate showed a protein value of 67.54%, with a relative abundance of arginine (2.84%), serine (3.14%), aspartic acid (3.33%), glutamic acid (3.73%), and glycine (2.81%). C. aquifrigidense FANN2 yielded high keratinase titre and dismembered chicken feathers into amino acids-rich hydrolysate, highlighting its significance in the beneficiation of recalcitrant keratinous wastes into dietary proteins as potential livestock feed supplements.
  • Thumbnail Image
    Item
    Draft genome sequence of multi-drug resistant Klebsiella quasipneumoniae subsp. similipneumoniae isolated from a teaching hospital wastewater in South West, Nigeria.
    (American Society for Microbiology, 2024-01-24) Akinola, Omowumi T.; Dahunsi, Samuel O.; Okoh, Anthony Ifeanyi
    This broadcast is about the whole genome sequence of Klebsiella quasipneumoniae subsp. similipneumoniae (ST 1422) isolated from a teaching hospital wastewater in South West, Nigeria, in May 2022. This data set compiles information on the DNA size (5,332,183 bp) and GC content (57.91%) in its genome.
  • Thumbnail Image
    Item
    Evidence of zoonotic rickettsiae in ixodid ticks of domestic animals in some communal farms in the Eastern Cape Province, South Africa
    (Network for the Veterinarians of Bangladesh, 2024-06-04) Adelabu, Olusesan Adeyemi; Iweriebor, Benson Chuks; Obi, Chikwelu Larry
    Objective: The abundance of tick populationsin South Africa represents a probable risk for both animal and human health. Rickettsia spp. and Borrelia spp. are well-known agents of emerging human tick-borne infectious diseases worldwide. Nevertheless, the epidemiology of their infections has been underreported in South Africa. Therefore, this study aimed to profile zoonotic Rickettsia and Borrelia species from ticks infesting domesticated animals in the Eastern Cape, South Africa. Materials and Methods: Morphological and molecular identification techniques were conducted on 1,200 tick samples collected from domestic animals before screening for the target bacterial pathogens. The molecular identification of the tick samples was based on the amplification of the 12S rRNA mitochondrial Deoxyribonucleic acid. At the same time, those of Rickettsia and Borrelia species were carried out by amplifying fragments of gltA and ompB genes for Rickettsia and flaB gene for Borrelia spp. Thereafter, the positive amplicons for Rickettsia ompB were sequenced and further analyzed. Borrelia PCRs were negative; therefore, sequencing could not be performed. Results: Eight species of ticks belonging to three genera; Rhipicephalus, Amblyomma, and Haemaphysalis, were identified. A total of 27% (320/1,200) samples were confirmed positive for Rickettsia, of which 23% (74/320) were positive for ompB genes. Phylogenetic analysis of ompB revealed a high homology to rickettsial reference strains from GenBank, with no positive result for Borrelia. The generated sequences showed homology with R. africae-KX227790 (100%), R. parkeri-KY113111 (99.8%), R. peacockii (99.3%), and R. slovaca-JX683122 (99.1%) representative sequences in GenBank. Conclusion: The findings from this study revealed that ticks harbored Rickettsia species with possible zoonotic potential.
  • Thumbnail Image
    Item
    Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density
    (Elsevier, 2022-10-28) Ekundayo, CT; Oluwatosin, AI.; Igbinosa, EO.; Okoh, AI.
    Seasonal variations (SVs) affect the population density (PD), fate, and fitness of pathogens in environmental water resources and the public health impacts. Therefore, this study is aimed at applying machine learning intelligence (MLI) to predict the impacts of SVs on P. shigelloides population density (PDP) in the aquatic milieu. Physicochemical events (PEs) and PDP from three rivers acquired via standard microbiological and instrumental techniques across seasons were fitted to MLI algorithms (linear regression (LR), multiple linear regression (MR), random forest (RF), gradient boosted machine (GBM), neural network (NN), K-nearest neighbour (KNN), boosted regression tree (BRT), extreme gradient boosting (XGB) regression, support vector regression (SVR), decision tree regression (DTR), M5 pruned regression (M5P), artificial neural network (ANN) regression (with one 10-node hidden layer (ANN10), two 6- and 4-node hidden layers (ANN64), and two 5- and 5-node hidden layers (ANN55)), and elastic net regression (ENR)) to assess the implications of the SVs of PEs on aquatic PDP. The results showed that SVs significantly influenced PDP and PEs in the water (p < 0.0001), exhibiting a site-specific pattern. While MLI algorithms predicted PDP with differing absolute flux magnitudes for the contributing variables, DTR predicted the highest PDP value of 1.707 log unit, followed by XGB (1.637 log unit), but XGB (meansquared-error (MSE) = 0.0025; root-mean-squared-error (RMSE) = 0.0501; R2 =0.998; medium absolute deviation (MAD) = 0.0275) outperformed other models in terms of regression metrics. Temperature and total suspended solids (TSS) ranked first and second as significant factors in predicting PDP in 53.3% (8/15) and 40% (6/15), respectively, of the models, based on the RMSE loss after permutations. Additionally, season ranked third among the 7 models, and turbidity (TBS) ranked fourth at 26.7% (4/15), as the primary significant factor for predicting PDP in the aquatic milieu. The results of this investigation demonstrated that MLI predictive modelling techniques can promisingly be exploited to complement the repetitive laboratory-based monitoring of PDP and other pathogens, especially in low-resource settings, in response to seasonal fluxes and can provide insights into the potential public health risks of emerging pathogens and TSS pollution (e.g., nanoparticles and micro- and nanoplastics) in the aquatic milieu. The model outputs provide low-cost and effective early warning information to assist watershed managers and fish farmers in making appropriate decisions about water resource protection, aquaculture management, and sustainable public health protection.
  • Thumbnail Image
    Item
    Virulence Signatures, Integrons, and Antibiotic Resistance Genes in Bacterial Strains Recovered from Selected Commercial Dairy Products and Fresh Raw Meat
    (Springer, 2023-06-24) Aiyegoro, Olayinka A.; Moyane, Jeremia N.; Adegoke, Anthony A.; Jideani, Afam I.O.; Reddy, Poovendhree; Okoh, Anthony Ifeanyi
    Bacterial species responsible for food infections and intoxication are sometimes carried through the food production and processing. Very few published literatures exist on integrons among antibiotic-resistant staphylococcal strains from foods of animal origin in Gauteng Province, South Africa, hence this study. A total of 720 samples (360 meat and 360 dairies) from a community abattoir of a research farm in South Africa, using conventional bacteriological and molecular methods. Nine (9) bacterial strains, including Bacillus subtilis AYO-123, Acinetobacter baumannii AYO-241, Staphylococcus lentus AYO-352, among others were identified and submitted to GenBank. More bacterial strains were recovered from raw meat (90.5%) than dairy products (9.5%). Resistance was shown (0–100%) to Imipenem, Meropenem, Norfloxacin, Clindamycin, and 22 other antibiotics, without any carbapenem-resistant Acinetobacter baumannii and methicillin/vancomycin-resistant Staphylococcus species (MRSS/VRSS). Virulence genes for fibronectin-binding protein A (FnbA) were predominant (56.24%) followed by the circulating nucleic acids (cna) gene (43.75%). Others were staphylococcal enterotoxin A (sea, 41%), staphylococcal enterotoxin B (seb, 23.5%). Co-presence of sea and seb genes occurred in 11.76% of the isolates, but no coa genes was amplified. Antibiotic resistance genes (ARGs), tetK (70.58%), linA (29.4%), and ermA (11.76%) were detected, but none of the mecA and vat genes was amplified. Class 2 integron (50%) was more predominantly detected than integron 1 (25%), but no Class 3 integron was detected. Bacteria with both the detected virulence and antibiotic resistance genes are of potentialrisks to human health.