Comparative analyses on medium optimization using one-factor-at-a-time, response surface methodology, and artificial neural network for lysine–methionine biosynthesis by Pediococcus pentosaceus RF-1

Optimization strategy that encompassed one-factor-at-a-time (OFAT), response surface methodology (RSM), and artificial neural network method was implemented during medium formulation with specific aim for lysine-methionine biosynthesis employing a newly isolated strain of Pediococcus pentosaceus RF-1. OFAT technique was used in the preliminary screening of factors (molasses, nitrogen sources, fish meal, glutamic acid and initial medium pH) before proceeded to optimization study. Implementation of central composite design of experiment subsequently generated 30 experimental runs based on four factors (molasses, fish meal, glutamic acid, and initial medium pH). From RSM analysis, a quadratic polynomial model can be devoted to describing the relationship between various medium components and responses. It also suggested that using molasses (9.86 g/L), fish meal (10.06 g/L), glutamic acid (0.91 g/L), and initial medium pH (5.30) would enhance the biosynthesis of lysine (15.77 g/L) and methionine (4.21 g/L). Alternatively, a three-layer neural network topography at 4-5-2 predicted a further improvement in the biosynthesis of lysine (16.52 g/L) and methionine (4.53 g/L) by using formulation composed of molasses (10.02 g/L), fish meal (18.00 g/L), and glutamic acid (1.17 g/L) with initial medium pH (4.26), respectively

Assessment of heavy metal tolerance and biosorptive potential of Klebsiella variicola isolated from industrial effluents

Abstract Heavy metal contamination now a day is one of the major global environmental concerns. Textile effluents of Faisalabad Pakistan are heavily contaminated with heavy metals and demands to explore native microorganisms as effective bioremediation tool. Study aimed to isolate heavy metal tolerant bacteria from textile effluents of Faisalabad Pakistan and to evaluate their biosorptive potential. Out of 30 collected samples 13 isolates having metal tolerance potential against Ni and Co were screened out. Maximum tolerable concentration and multi metal resistance was determined. A native bacterial strain showing maximum tolerance to Ni and Co and multi metal resistance against Ni, Co and Cr at different levels was selected and named as Abuzar Microbiology 1 (AMIC1). Molecular characterization confirmed it as Klebsiella variicola which was submitted in First fungal culture bank of Pakistan (FCBP-WB-0688). ICP-OES revealed that it reduced Ni (50, 49%) and Co (71, 68.6%) after 24 and 48 h, respectively. FT-IR was used to analyze functional groups and overall nature of chemical bonds. Changes in spectra of biomass were observed after absorption of Ni and Co by K. variicola. SEM revealed morphological changes in bacteria in response to metal stress. Both metals affected bacterial cell wall and created pores in it. However effect of Ni was more pronounced than Co. It was concluded that K. variicola, a native novel strain possessed significant heavy metal tolerance and bioremediation potential against Ni and Co. It may be used in future for development of bioremediation agents to detoxify textile effluents at industrial surroundings