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Caffeine is an important naturally occurring compound that can be degraded by bacteria. Excessive caffeine consumption is known to have some adverse problems. Previously, Leifsonia sp. strain SIU capable of degrading caffeine was isolated from agricultural soil. The bacterium was tested for its ability to degrade caffeine as the sole carbon and nitrogen source. The isolate was encapsulated in gellan gum and its ability to degrade caffeine in the presence of heavy metals was determined. Out of the nine heavy metals tested, Copper (Cu), Mercury (Hg), and Silver (Ag) had significant effects on caffeine degradation at 1mg/L. Therefore, the concentration of these heavy metals was varied from 0 -1 mg/L to see at what concentration each metal it has effect. Ag and Hg showed effect at 0.1 mg/L with caffeine degradation of 64.05 and 52.17% respectively, while Cu showed effect at 0.8 mg/L with caffeine degradation of 64.74%. These bacterium features make it an ultimate means for caffeine bioremediation. This is the first report of effect of heavy metals on caffeine degradation by immobilised Leifsonia sp. strain SIU.

The well function of aquatic and soil organisms including terrestrial, as well as those of all other living things, can be jeopardized if dyes aren't properly treated, as their degradation might lead to carcinogenic chemicals. Complete mineralization of dye is the only option, and this can be done using microorganisms. The azo blue dye inhibitory effect to its biodegradation by Streptomyces DJP15 was modelled using several inhibition kinetic models such as Haldane, Monod, Luong, Aiba, Teissier-Edwards, Han-Levenspiel and Yano. The result shows that only the Luong model failed to fit the data. The rest of the models visually ft the data although data fitting is problematic with datapoints of less than 10, which the result in this work demonstrates where it is not easy to choose the best model where nearly all of the models fit the data in a similar manner. Resorting to statistical discriminatory function, the best model was Monod with the smallest RMSE and AICc values and the highest adjR2 values and values for AF and BF close to unity. However, Monod has only two parameters and is the most robust. The Monod’s parameters were maximum specific degradation rate of 0.431 (1/h) (95% confidence interval from 0.391 to 0.456) and concentration of substrate giving half maximal rate or Ks value of 0.0001 (mg/L) (95% C.I. from -0.01 to 12.12). The confidence interval value for the Ks value was very large indicating poor data quality. This should be an important consideration in future works where the data point number can be increased to improve model fitting exercise.

Tributyltin (TBT) is one of the most toxic substances ever deliberately introduced into the marine environment. The high toxicity of TBT has resulted in a wide range of adverse effects on biological systems ranging from bacteria to mammals and from the molecular to the community level. One of the most deleterious effects of TBT is imposex. The growth kinetics of TBT-Resistant Bacterium containing lead was studied. In this study various lead concentrations ranging from 1 to 100 mg/dm 3 were used. Seven kinetic models (Teissier, Monod, Yano, Luong, Aiba, Webb, and Haldane,) were investigated and the accuracy of the fitted models were evaluated using statistical analysis such as coefficient of determination, adjusted coefficient of determination (R 2 ) and root mean square (RMSE). Aiba model was fitted to the experimental growth kinetics data and gave a very good fit with an R 2 of 0.98 and RMSE of 0.0042 respectively. The calculated value for the Aiba constants such as maximal growth rate, half saturation constant and half inhibition constant rate symbolized by µ max , k s , and k i , were 0.