Forward and reverse primers for constructing each chimeric gene.
\r\n\t
",isbn:"978-1-83881-922-4",printIsbn:"978-1-83881-921-7",pdfIsbn:"978-1-83881-923-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"dcfc52d92f694b0848977a3c11c13d00",bookSignature:"Dr. Fiaz Ahmad and Prof. Muhammad Sultan",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10454.jpg",keywords:"Agricultural Engineering, Technologies, Application, Sustainable Agriculture, Information Technology in Agriculture, Food Security, Renewable Energies, Precision Farming, Smart Agriculture, Farm Mechanization, Robotics, Post Harvest Technologies",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 25th 2020",dateEndSecondStepPublish:"December 23rd 2020",dateEndThirdStepPublish:"February 21st 2021",dateEndFourthStepPublish:"May 12th 2021",dateEndFifthStepPublish:"July 11th 2021",remainingDaysToSecondStep:"2 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Ahmad is a researcher in the field of agricultural mechanization and agricultural equipment engineering, in-charge of Farm Machinery Design Laboratory at Bahauddin Zakariya University, with expertise in modeling and simulation. He applied for two patents at the national level.",coeditorOneBiosketch:"Renowned researcher with a focus on developing energy-efficient heat- and/or water-driven temperature and humidity control systems for agricultural storage, greenhouse, agricultural livestock and poultry applications including HVAC, desiccant air-conditioning, adsorption, Maisotsenko cycle (M-cycle), and adsorption desalination.",coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"338219",title:"Dr.",name:"Fiaz",middleName:null,surname:"Ahmad",slug:"fiaz-ahmad",fullName:"Fiaz Ahmad",profilePictureURL:"https://mts.intechopen.com/storage/users/338219/images/system/338219.jpg",biography:"Fiaz Ahmad obtained his Ph.D. (2015) from Nanjing Agriculture University China in the field of Agricultural Bioenvironmental and Energy Engineering and Postdoc (2020) from Jiangsu University China in the field of Plant protection Engineering. He got the Higher Education Commission, Pakistan Scholarship for Ph.D. studies, and Post-Doctoral Fellowship from Jiangsu Government, China. During postdoctoral studies, he worked on the application of unmanned aerial vehicle sprayers for agrochemical applications to control pests and weeds. He passed the B.S. and M.S. degrees in agricultural engineering from the University of Agriculture Faisalabad, Pakistan in 2007. From 2007 to 2008, he was a Lecturer in the Department of Agricultural Engineering, Bahauddin Zakariya University, Multan-Pakistan. Since 2009, he has been an Assistant Professor in the Department of Agricultural Engineering, BZ University Multan, Pakistan. He is the author of 33 journal articles. He also supervised 6 master students and is currently supervising 5 master and 2 Ph.D. students. In addition, Dr. Ahmad completed three university-funded projects. His research interests include the design of agricultural machinery, artificial intelligence, and plant protection environment.",institutionString:"Bahauddin Zakariya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Bahauddin Zakariya University",institutionURL:null,country:{name:"Pakistan"}}}],coeditorOne:{id:"199381",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sultan",slug:"muhammad-sultan",fullName:"Muhammad Sultan",profilePictureURL:"https://mts.intechopen.com/storage/users/199381/images/system/199381.jpeg",biography:"Muhammad Sultan completed his Ph.D. (2015) and Postdoc (2017) from Kyushu University (Japan) in the field of Energy and Environmental Engineering. He was an awardee of MEXT and JASSO fellowships (from the Japanese Government) during Ph.D. and Postdoc studies, respectively. In 2019, he did Postdoc as a Canadian Queen Elizabeth Advanced Scholar at Simon Fraser University (Canada) in the field of Mechatronic Systems Engineering. He received his Master\\'s in Environmental Engineering (2010) and Bachelor in Agricultural Engineering (2008) with distinctions, from the University of Agriculture, Faisalabad. He worked for Kyushu University International Institute for Carbon-Neutral Energy Research (WPI-I2CNER) for two years. Currently, he is working as an Assistant Professor at the Department of Agricultural Engineering, Bahauddin Zakariya University (Pakistan). He has supervised 10+ M.Eng./Ph.D. students so far and 10+ M.Eng./Ph.D. students are currently working under his supervision. He has published more than 70+ journal articles, 70+ conference articles, and a few magazine articles, with the addition of 2 book chapters and 2 edited/co-edited books. Dr. Sultan is serving as a Leading Guest Editor of a special issue in the Sustainability (MDPI) journal (IF 2.58). In addition, he is appointed as a Regional Editor for the Evergreen Journal of Kyushu University. His research is focused on developing energy-efficient heat- and/or water-driven temperature and humidity control systems for agricultural storage, greenhouse, livestock, and poultry applications. His research keywords include HVAC, desiccant air-conditioning, evaporative cooling, adsorption cooling, energy recovery ventilator, adsorption heat pump, Maisotsenko cycle (M-cycle), wastewater, energy recovery ventilators; adsorption desalination; and agricultural, poultry and livestock applications.",institutionString:"Bahauddin Zakariya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Bahauddin Zakariya University",institutionURL:null,country:{name:"Pakistan"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"8",title:"Chemistry",slug:"chemistry"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"252211",firstName:"Sara",lastName:"Debeuc",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/252211/images/7239_n.png",email:"sara.d@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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For most bioconversion processes with cellulose, endo(1-4)-β-D-glucan glucanhydrolases and exo(1-4)-β-D-glucan cellobiohydrolases are necessary for catalyzing the random hydrolysis of cellulose to produce cellobiose. On the basis of substrate specificity, β-glucosidases can be classified into aryl-β-glucosidases, cellobioses hydrolysing only oligosaccharides, and those hydrolysing both aryl-β-glucosides and oligosaccharides [1, 2]. β-glucosidases are important components of the cellulase enzyme complex required for the hydrolysis of cellulose into glucose by catalysing the final step, which is the conversion of cellobiose into glucose [3]. From the basis of sequence homology β-glucosidases have been divided into two sub-families, namely BGA (β-gucosidases and phospho-β-glucosidases from bacteria to mammals) and BGB (β-glucosidases from yeast, mold and rumen bacteria) [4]. The study of these enzymes has been facilitated by the use of recombinant DNA technology [5,6,7,8]. A number of cellulase genes including several forms of β-glucosidases, have been cloned and expressed in both E.coli and S.cereviciae [9,10]. In recent years, protein engineering has become an increasingly important tool in the development of novel hybrid enzymes with useful catalytic functions [11,12,13]. The catalytic activities and thermal stabilities of enzymes can be improved by the construction of chimeric enzymes with gene-shuffling from different species of genes [14]. For this purpose, chimeric genes are normally constructed by the application of one of two methods: using restriction enzymes or by overlapping polymerase chain reaction (PCR) [15]. Although the use of restriction enzymes is the easier method, a high level of identity is required between the parental DNA sequences to obtain common restriction enzyme sites in both genes. Often, the availability of common restriction enzyme sites limits the use of this strategy in the construction of chimeric genes. In contrast, there are no such limitations in defining shuffling sites for chimeric genes constructed via overlapping PCR technique.
\n\t\t\tIn order to construct new types of the chimeric β-glucosidases, Thermotoga maritima (TM) gene and Celvibrio gilvus (CG) gene were used for gene-shuffling. Celvibrio gilvus [16], a cellulose-metabolizing bacterium, has the unique property of producing cellobiose in high yields from acidic swollen cellulose. Thermotoga maritima is a fermentative, marine, hyperthermophilic eubacterium that can be grown in temperatures of up to 90ºC with an optimal temperature of around 80ºC [17,18]. Two novel active β -glucosidase were successfully constructed from the pool of chimeric genes and their properties were characterized. These results proved the chimeric gene construction is promising approach for searching for the better β-glucosidase
\n\t\tThe plasmids pET-CG and pET-TM were constructed by introducing the CG gene and the TM gene for β-glucosidase into the pET28a (+) vector (Novagen, Germany) carrying an N-terminal His tag and a thrombin cleavage site. Topo-XL TOP 10 (Invitrogen, USA) was used for cloning of chimeric genes, and the pET28 (a) vector was used for introducing the Topo-XL-chimeric gene. The BL21 (DE3) (NextGen Sciences, Inc., USA) strain was used for expression of the chimeric protein produced through the pET28a (+) vector.
\n\t\t\tFor the construction of 8 kinds of chimeric genes from CG and TM, three steps of PCR were applied. The first step was the amplification of gene fragments for domain-shuffling using the CG and TM gene as templates for overlapping PCR. The outside primer was prepared from the shuffling region of both templates and contained the restriction site, while the inside primer contained the opposite gene region. The second step involved targeting the chimeric gene with overlapped PCR from the templates prepared in the first step. At this stage the primers were not used as this step was exclusively focused on annealing of the two templates of CG and AT genes. PCR was initially performed at 98ºC for 3 min, in order to convert the single DNA into a template. Polymerase was not added in this step. PCR was repeated at 25ºC for 1 hr for purposes of overlapping both genes. DNA polymerase was then added and 15 PCR cycles were performed at 25ºC. This completed the construction of the chimeric gene. The third step involved the amplification of the newly constructed chimeric gene using the primers from the first step, allowing for an exponential increase in the amount of chimeric genes produced.
\n\t\t\tEach chimeric gene required 4 primers to be constructed, and thus, 20 kinds of primers (forward and reverse) were designed as Figure 1 and Table 1. Figure 1 showed the position of forward and reverse primers and Table 1 explained the structure of primers for each chimeric gene, respectively.
\n\t\t\tAll PCR products were purified after agarose gel electrophoresis, using the QIAquick PCR purification kit (QIAGEN, Germany). The amplified chimeric genes were cloned using the pCR-TOPO cloning kit (Invitrogen, USA). The resulting recombinant pCR-TOPO plasmid
\n\t\t\t\tDesign of 8 kinds of chimeric β-glucosidase gene from CG and TM with higher homology region. Numerics in bold gothic are designated as numbers of amino acids, and numerics in circle are designated as forward primers, in square are reverse primers for constructing chimeric enzymes. N: non-homology region, H: higher homology region.
containing chimeric β-glucosidase genes was confirmed by colony PCR, and then extracted using a QIAminiprep kit (QIAGEN, Germany), and sequenced with a DNA sequencer (Model 373A, Applied Biosystem, USA). The sequence data was analyzed using the GENETYX program (Software Development Co., Tokyo, Japan).
\n\t\t\tThe TOPO-cloned chimeric β-glucosidase genes were transferred into the pET28a (+) vector with hydrolysing NdeI and HindIII restriction enzymes. The host E.coli BL21 (DE3) competent cells were tranformed with pET28a (+) vector carrying the chimeric β-glucosidase genes to check its activity. Active colonies were selected with solid medium including pNP-glucopyranoside.
\n\t\t\tBL21 (DE3) cells carrying the chimeric gene were cultivated in Luria-Bertani broth (LB) medium (1000 ml) containing kanamycin (30 mg/ml) at 37ºC. On reaching an optimum density of 0.2 at 600 nm, protein production was induced by the addition of 1 mM isopropyl-β-D-thiogalactopyranoside (IPTG) into the culture media and incubating it overnight. When the absorbance of the broth at 660 nm reached values between 0.4-0.5, the cells were harvested by centrifugation (8,000 rpm, 10 min at 4ºC) and suspended in 50 mM MOPS buffer pH 6.5. The cells were then disrupted by sonication (Branson sonifier 250D). The intact cells and debris were removed by centrifugation (12,000 rpm, 10 min at 4ºC).
\n\t\t\t\tPurification was achieved by binding of the cleared lysate with Ni-NTA resin, which bound to the target protein. This resin was then packed into a column to facilitate the washing and
\n\t\t\t\tChimera No | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t1st PCR primer\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tOverlapping PCR primer\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t||
FWD | \n\t\t\t\t\t\t\tREV | \n\t\t\t\t\t\t\tFWD | \n\t\t\t\t\t\t\tREV | \n\t\t\t\t\t\t|
\n\t\t\t\t\t\t\t\t1)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t① ccatgggcagcagc catc | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t ttccttccgttgcgc ggctcg | \n\t\t\t\t\t\t\t② gccgcgcaacggaag gaatttcgagtacta | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t aagcttatggttt gaatctcttct | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t2)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t⑥ ccatatggaaaggat cgatg | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t agttgcggccacaa agagggtttctgtgaat | \n\t\t\t\t\t\t\t⑦ ccctctttgtggccgcaa cttcgaatac | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t caagctttcagcgtg cgc | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t3)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t① | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t ctcccgcgtaccagt cggacatgacataac | \n\t\t\t\t\t\t\t③ gtccgactggtacg cgggagacaac | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t4)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t⑥ | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t gggtggcgccccag tcgctcatcacgaaa | \n\t\t\t\t\t\t\t⑧ gagcgactggggcg ccaccca | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t5)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t① | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t acctgtatccgaccgc cgcacc | \n\t\t\t\t\t\t\t④ tgcggcggtcgcatacagg tactacgacacc | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t6)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t⑥ | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t acttgtagcccacgtagatgtcttcct | \n\t\t\t\t\t\t\t⑨ cattcacgtgggctacaa gtggttcgacct | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t7)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t① | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t gagctttgatgtacac ctgcggcacgtc | \n\t\t\t\t\t\t\t⑤ gcaggtgtacatcaa agctccaaaa | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t8)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t⑥ | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t tcggcgcggcgtaga cctgtgagacttcctt | \n\t\t\t\t\t\t\t⑩ acaggtctacgccgcg ccga | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
Forward and reverse primers for constructing each chimeric gene.
elution steps. Washing and elution were performed by the batch procedure described in TheQIA expressionist TM (QAIGEN, Germany) with a step gradient of 250 mM imidazol in 50 mM Na-phosphate buffer, pH 8.0. The fractions of 1 ml were collected and assayed for chimeric β-glucosidase activity. The active fractions were combined and dialyzed against 5 mM MOPS buffer, pH 6.5 overnight at 4ºC. The dialysed enzyme solution was futher purified on a Mono-S HR 5/5 column (Pharmacia, Sweden) equilibrated with 20 mM acetate buffer (pH 5.0). Chromatography was performed with a linear gradient of NaCl (20 ml, 0-0.5 M) at a flow rate of 1.0 ml/min using a Pharmacia FPLC system (Sweden). The removal of salt from the pooled active fraction was performed by dialyzing against 5 mM MPOS buffer, pH 6.5.
\n\t\t\tThe enzyme activity of chimeric β-glucosidase was determined by measuring the absorbance at 405 nm, which was related to the amount of pNP (p-nitrophenol) released from the pNP-β-D-glucopyranoside by the enzyme at 30ºC. The assay mixture, consisting of 5 mM substrate (pNP-β-D-glc) and 50 mM MOPS buffer (pH 6.5) was incubated with the enzyme, in a total volume of 0.5 ml. The reaction was stopped by the addition of 0.5 ml of 0.2 M glycine-NaOH (pH 10.5). One unit of β-glucosidase was defined as the amount of enzyme releasing 1 μmole of p-nitrophenol per minute under the above-mentioned conditions.
\n\t\t\tSodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was conducted on 1 mm thick, 12% acrylamide slab gels. The samples were dissolved in Tris/HCl loading buffer containing 1% (w/v) SDS, 20% (v/v) glycerol and 2% (v/v) 2-mercaptoethanol and then heated at 95ºC in heating block for 5 min. Proteins were stained with 1% (w/v) Coomassie Brilliant Blue R 250 in methanol/acetic acid/water (30:10:60), and then destained with the electric-range.
\n\t\t\tTo determine the effect of pH, 50 mM concentrations of various buffers namely sodium phosphate (pH 1.1-3.1), sodium formate (pH 2.8-4.45), sodium succinate (pH 3.23-6.4), 3-[N-morpholino]propanesulfonic acid (MOPS; pH 6.2-8.18), N-[2-hydroxyethyl] piperazine-N\'-[2-ethanesulfinic acid] (HEPES; pH 5.93-9.13), piperidine (pH 10.0-12.0), 2-[N-cyclohexylamino]ethanesulfonic acid (CHES; pH8.15-10.2), McIlvaine buffer (pH 2.6-7.6) were used at 30ºC. A test of the pH stability of the enzyme at 30ºC was performed by pre-incubating the enzyme with each of the above buffers for 30 min and determining the remaining activity using a standard procedure. For optimum pH, the enzyme was incubated with substrates in each of the above buffers at 30ºC for 10 min, then reaction was stopped with 0.5M glycine(pH 10.3) solution, and followed enzyme assay. The optimum temperature of the enzyme was determined by incubating with substrates in a temperature range from 20ºC to 100ºCfor 10 min, at three different pH levels, pH 3.0, 4.5 and 5.0, and analysed the enzyme activity. Similarly, the thermal stability of the enzyme was also determind by incubating the purified protein for 30 min at temperatures ranging from 20 to 100ºC. After cooling the sample on ice for 10 min, the remaining activity was determined using standard procedures.
\n\t\t\tMichaelis-Menten constants were determined from Line Weaver-Burk plots. The data used were obtained by measuring the initial rate of pNP-glucose hydrolysis by incubating the enzyme with appropriate concentrations of the substrate in 25 mM MOPS at 30ºC. The reaction was monitored at 405 nm on a Beckman spectrophotometer (model DU 640, USA) equipped with a temperature-controlled cell holder. The initial rate was determined at six different concentrations ranging from approximately 0.5 to 2.0 times the Km. The catalytic constant Kcat was deduced using the molecular mass of 80 kDa, while the kinetic parameters (KM and Vmax) with their standard error was determined using the linear regression analysis.
\n\t\t\tThe characterization of β-glucosidase from CG and TM, as well as the cloning and analysis of the gene coding for these enzymes have previously been investigated by the National Food Research Institute (NFRI). Based on the amino acid alignment between TM and CG enzymes, an N-terminal domain, a C-terminal region, and a non-homologus region were reported(5,16). The amino acid homology between TM and CG was 30.7%. The homology of N-terminal region and C-terminal region were found to be 32% and 36%, respectively, both of which fall within the highly homologus regions of the amino acid sequence. From these data, 8 kinds of chimeric β-glucosidases were designed from the TM gene and CG gene as shown in Fig. 1, and these chimeras were constructed by overlapping PCR.
\n\t\t\tAfter conducting overlapping PCR for construction of 8 chimeric genes, the PCR products were introduced into the pCR-TOPO plasmid. For confirmation of the inserted chimeric genes, colony PCR was performed using expressed colonies as a template. 8 kinds of chimeric β-glucosidase genes were introduced into the pCR-TOPO plasmid and these were confirmed with colony PCR. This confirmation was also shown positively in the other 7 chimeric genes (data not shown). From the colony PCR, some successfully inserted chimeric genes for 8 different chimeric β-glucosidase types were obtained. Colony PCR was found to be a fast and convenient method for confirmation of inserted target DNA fragments.
\n\t\t\tFor the selection of active chimeric β-glucosidase colonies, TOPO plasmids were transferred into the pET28a (+) vector, and colony PCR was performed to confirm the presence of the inserted chimeric gene. BL21 (DE3) cells were then transformed with the plasmid and spread on a solid plate containing pNP-β-D-glucopyranoside. We obtained some successfully inserted chimeric gene colonies for 8 designed chimeric types from colony PCR. However, only 2 kinds of active chimeric β-glucosidases were obtained from No.6 and No.8 chimeric types. Activities of other types of chimeric β-glucosidases were not expressed. Inclusion bodies were produced due to the over-production by the pET28a (+) vector [19,20,21]. In some instances, the chimeric proteins were unfolded in structure [22,23].
\n\t\t\tThe pET vector is known to be a powerful expression system [24,25], and over-produced chimeric β-glucosidases can accumulate in an insoluble form. Harvested cells were suspended in 25 mM MOPS buffer (pH 6.5) and then disrupted by sonication. The soluble fraction was obtained by centrifugation of the sonically treated cell suspension at 15,000 rpm for 15 min. The resultant pellet was solublized in 8 M urea solution in the above-mentioned buffer, and after centrifugation (15,000 rpm for 15 min), the supernatant was used as the insoluble fraction [15,26,27]. The proteins in both the soluble and insoluble fractions of No.6 and No.8 were analyzed by 7.5% SDS-PAGE followed by Coomassie Brilliant Blue staining and the molecular mass of both protein constructs were found to be around 80 kDa (Fig. 2). The activities of the chimeric β-glucosidases were monitored at each step of the purification process and these activities are summarized in Table 2. Enzyme activities of both chimeric β-glucosidases were not very different from each other based on the specific activity that was calculated.
\n\t\t\t\t\n\t\t\t\t\t\t\t\tPurification step\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tProtein (mg) | \n\t\t\t\t\t\t\tTotal activity (unit) | \n\t\t\t\t\t\t\tSpecific activity (unit/mg) | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tPurification factor(fold)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tRecovery (%) | \n\t\t\t\t\t\t|||||
No.6 | \n\t\t\t\t\t\t\tNo.8 | \n\t\t\t\t\t\t\tNo.6 | \n\t\t\t\t\t\t\tNo.8 | \n\t\t\t\t\t\t\tNo.6 | \n\t\t\t\t\t\t\tNo.8 | \n\t\t\t\t\t\t\tNo.6 | \n\t\t\t\t\t\t\tNo.8 | \n\t\t\t\t\t\t\tNo.6 | \n\t\t\t\t\t\t\tNo.8 | \n\t\t\t\t\t\t|
\n\t\t\t\t\t\t\t\tCrude extract\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t335 | \n\t\t\t\t\t\t\t350 | \n\t\t\t\t\t\t\t55.3 | \n\t\t\t\t\t\t\t49.5 | \n\t\t\t\t\t\t\t0.17 | \n\t\t\t\t\t\t\t0.14 | \n\t\t\t\t\t\t\t1.0 | \n\t\t\t\t\t\t\t1.0 | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t\t100 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\tNi-NTA\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t16.75 | \n\t\t\t\t\t\t\t15.05 | \n\t\t\t\t\t\t\t24.8 | \n\t\t\t\t\t\t\t18.8 | \n\t\t\t\t\t\t\t1.48 | \n\t\t\t\t\t\t\t1.25 | \n\t\t\t\t\t\t\t8.71 | \n\t\t\t\t\t\t\t8.93 | \n\t\t\t\t\t\t\t44.8 | \n\t\t\t\t\t\t\t38.0 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\tMono-S\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t2.43 | \n\t\t\t\t\t\t\t2.03 | \n\t\t\t\t\t\t\t13.5 | \n\t\t\t\t\t\t\t9.2 | \n\t\t\t\t\t\t\t5.55 | \n\t\t\t\t\t\t\t4.53 | \n\t\t\t\t\t\t\t32.65 | \n\t\t\t\t\t\t\t32.35 | \n\t\t\t\t\t\t\t24.4 | \n\t\t\t\t\t\t\t18.6 | \n\t\t\t\t\t\t
Purification step for chimeric β-glucosidases.
SDS-PAGE of soluble and insoluble fractions of chimeric β-glucosidase from No.6 and No. 8.Lane M, Marker; lane 1 and 2, insoluble fraction of pET-chimeric β-glucosidase after IPTG induction of No.6 and No.8, respectively; lane 3 and 5, soluble fraction of pET-chimeric β-glucosidase after IPTG induction of No.6 and No.8, respectively; lane 4 and 6, purification on Mono-S column after Ni-NTA-agarose slurry.
The influence of pH on the chimeric β-glucosidase activity was determined using a series of various buffers at 30ºC. The stability test [28] of the purified enzyme at different pH levels indicated that it was stable in the pH range of 3.0 to 5.0 for No.6 chimeric enzyme and 3.0 to 7.0 for No.8 chimeric enzyme at 30ºC. The pH stability for the parents of these chimeric enzymes was followed the pervious paper(5,15), CG and Tm were pH 4.0 to 8.0 and pH 4.0 to 12.0, respectively (Fig. 3). For pH stability, chimeric enzymes generally correlate with the parental enzymes. The shuffling regions in the C-terminal domain may have played a very important role in enzyme-folding and stability because both chimeric genes were replaced
\n\t\t\t\tpH stability range of No.6 (a) and No.8 (b) chimeric enzyme. CG and Tm as parents of these chimeric enzymes.
Optimum pH of No.6 (a) and No.8 (b) chimeric enzyme. CG and Tm as parents of these chimeric enzymes.
with CG terminal domain by 20% (No.6-chimeric enzyme) and 12% (No.8-chimeric enzyme) on the whole TM gene. For determining the optimum pH of the chimeric enzymes, the pH of the parent enzymes was investigated. The optimum pH of CG and Tm was reported to be 6.4 and 3.4, respectively (Fig. 4). The optimum pH of No.6 chimeric enzymes was found to be 3.0 and 5.0, which showed different maximum activity according to the buffer used. No.8 chimeric enzyme showed an optimum pH of 4.5. The optimum pH profile of both chimeric enzymes is closer to that of TM than that of CG. The optimum pH of No.6 and No.8 was shifted between both the optimum pH properties of CG and TM, which is an indication of inherited pH properties.
\n\t\t\tThe enzyme activity correlated with the pH unit. The optimum pH was reported at two different positions that varied according to the buffer used. The optimum temperature therefore, also varied between the two different pH points, pH 3.0 (formate buffer) and pH 5.0 (succinate buffer) for No.6 chimeric enzyme, and pH 4.5 (McIlvain buffer) for No.8 chimeric enzyme (Fig. 5). The optimum temperature of CG and TM was found to be 30ºC and 70ºC, respectively. The optimum temperature of the chimeric enzymes of No.6 (pH 5.0) and No.8 (pH 4.5) was reported to be at 60ºC, and No.6 (pH 3.0) at 50ºC, even though the activity was very low(Fig. 6). The optimum temperature of both chimeric β-glucosidases were found to lie between that of CG and TM. A temperature stability test was carried out for the parental and chimeric enzymes. For estimation of the heat stability of each β-glucosidase, residual activity was determined using a standard assay after a 30 min pre-incubation at various temperatures. The heat stability of CG and TM was at 41ºC and 87ºC
\n\t\t\t\tOptimum temperature of No. 6 and No. 8 chimeric β-glucosidase with the buffer used, CG and TM as parents β-glucosidase. S: Succinate buffer, M: McIlvain buffer, F: Formate buffer
respectively, while those of the chimeric enzymes of No.6 and No.8 were 70ºC and 74ºC respectively. The heat stability of the chimeric enzymes increased by 29-33ºC relative to CG. himeric β-glucosidases were more stable than CG, but less stable than TM. These results demonstrated that the temperature stability of the chimeric enzymes generally correlated well with the thermal stability of the parental enzymes. In addition, the optimal temperature for the enzymatic reaction correlated successfully with the heat stability of the enzyme.
\n\t\t\t\tEffect of temperature on the thermal stability of the chimeric β-glucosidase, CG and TM as parents of β-glucosidase. For estimation of the heat stability of the each β-glucosidase, residual activity was determined using a standard assay after a 30 min pre-incubation at various temperatures.
The kinetic parameters of the two parental and chimeric β-glucosidases were investigated using pNP-β-D-glucopyranoside as the substrate(Table 3). The observed Km values for the chimeric No.6 and No.8 enzymes toward pNP-β-D-glucopyranoside were calculated to be 0.012 and 0.0082 mM, respectively. These Km values were lower than that of CG (0.44 mM), but are more or less similar to that obtained for TM (0.0039 mM). However, the Kcat values observed for the chimeric No.6 and No.8 enzymes were 5.62/sec and 3.38/sec respectively, which is lower than that obtained for both prental enzymes, i.e. TM (6.4/sec) and CG (42.2/sec). This indicated that the substrate specificities of the chimeric enzymes No.6 and No.8 were similar to each other and were closer to that of TM than CG. Also, No.8 chimeric β-glucosidase showed greater affinity toward pNP-β-D-glucopyranoside than that of No.6 chimeric enzyme. Thus the shuffling regions in the C-terminal domain produced a slight effect on the enzyme\'s substrate specificity and catalytic efficiency.
\n\t\t\t\t\n\t\t\t\t\t\t\t\tEnzymes\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tKm (mM)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tKcat (/sec)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tKcat/Km (mM/sec)\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\tTM\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0.0039 | \n\t\t\t\t\t\t\t6.4 | \n\t\t\t\t\t\t\t1640 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\tNo.6\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0.012 | \n\t\t\t\t\t\t\t5.62 | \n\t\t\t\t\t\t\t468 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\tNo.8\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0.0082 | \n\t\t\t\t\t\t\t3.84 | \n\t\t\t\t\t\t\t468 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\tCG\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t0.44 | \n\t\t\t\t\t\t\t42.2 | \n\t\t\t\t\t\t\t95.9 | \n\t\t\t\t\t\t
Kinetic parameters of the parental and chimeric β-glucosidases toward pNP-β-D-glucopyranoside
Chimeric β-glucosidases with improved enzymatic properties can be prepared in a convenient and effective way manipulating homology region of parental enzymes with overlapping PCR. The characteristics of the daughter enzymes suach as stability and optimization of pH and temperature, kinetic parameters were inherited with inter-mediate properties of parents. Also, the shuffling regions in the C-terminal domain may have played a very important role in determining enzyme characteristics, and changes in enzymatic properties.
\n\t\tResearch methodology is the path through which researchers need to conduct their research. It shows the path through which these researchers formulate their problem and objective and present their result from the data obtained during the study period. This research design and methodology chapter also shows how the research outcome at the end will be obtained in line with meeting the objective of the study. This chapter hence discusses the research methods that were used during the research process. It includes the research methodology of the study from the research strategy to the result dissemination. For emphasis, in this chapter, the author outlines the research strategy, research design, research methodology, the study area, data sources such as primary data sources and secondary data, population consideration and sample size determination such as questionnaires sample size determination and workplace site exposure measurement sample determination, data collection methods like primary data collection methods including workplace site observation data collection and data collection through desk review, data collection through questionnaires, data obtained from experts opinion, workplace site exposure measurement, data collection tools pretest, secondary data collection methods, methods of data analysis used such as quantitative data analysis and qualitative data analysis, data analysis software, the reliability and validity analysis of the quantitative data, reliability of data, reliability analysis, validity, data quality management, inclusion criteria, ethical consideration and dissemination of result and its utilization approaches. In order to satisfy the objectives of the study, a qualitative and quantitative research method is apprehended in general. The study used these mixed strategies because the data were obtained from all aspects of the data source during the study time. Therefore, the purpose of this methodology is to satisfy the research plan and target devised by the researcher.
The research design is intended to provide an appropriate framework for a study. A very significant decision in research design process is the choice to be made regarding research approach since it determines how relevant information for a study will be obtained; however, the research design process involves many interrelated decisions [1].
This study employed a mixed type of methods. The first part of the study consisted of a series of well-structured questionnaires (for management, employee’s representatives, and technician of industries) and semi-structured interviews with key stakeholders (government bodies, ministries, and industries) in participating organizations. The other design used is an interview of employees to know how they feel about safety and health of their workplace, and field observation at the selected industrial sites was undertaken.
Hence, this study employs a descriptive research design to agree on the effects of occupational safety and health management system on employee health, safety, and property damage for selected manufacturing industries. Saunders et al. [2] and Miller [3] say that descriptive research portrays an accurate profile of persons, events, or situations. This design offers to the researchers a profile of described relevant aspects of the phenomena of interest from an individual, organizational, and industry-oriented perspective. Therefore, this research design enabled the researchers to gather data from a wide range of respondents on the impact of safety and health on manufacturing industries in Ethiopia. And this helped in analyzing the response obtained on how it affects the manufacturing industries’ workplace safety and health. The research overall design and flow process are depicted in Figure 1.
Research methods and processes (author design).
To address the key research objectives, this research used both qualitative and quantitative methods and combination of primary and secondary sources. The qualitative data supports the quantitative data analysis and results. The result obtained is triangulated since the researcher utilized the qualitative and quantitative data types in the data analysis. The study area, data sources, and sampling techniques were discussed under this section.
According to Fraenkel and Warren [4] studies, population refers to the complete set of individuals (subjects or events) having common characteristics in which the researcher is interested. The population of the study was determined based on random sampling system. This data collection was conducted from March 07, 2015 to December 10, 2016, from selected manufacturing industries found in Addis Ababa city and around. The manufacturing companies were selected based on their employee number, established year, and the potential accidents prevailing and the manufacturing industry type even though all criterions were difficult to satisfy.
It was obtained from the original source of information. The primary data were more reliable and have more confidence level of decision-making with the trusted analysis having direct intact with occurrence of the events. The primary data sources are industries’ working environment (through observation, pictures, and photograph) and industry employees (management and bottom workers) (interview, questionnaires and discussions).
Desk review has been conducted to collect data from various secondary sources. This includes reports and project documents at each manufacturing sectors (more on medium and large level). Secondary data sources have been obtained from literatures regarding OSH, and the remaining data were from the companies’ manuals, reports, and some management documents which were included under the desk review. Reputable journals, books, different articles, periodicals, proceedings, magazines, newsletters, newspapers, websites, and other sources were considered on the manufacturing industrial sectors. The data also obtained from the existing working documents, manuals, procedures, reports, statistical data, policies, regulations, and standards were taken into account for the review.
In general, for this research study, the desk review has been completed to this end, and it had been polished and modified upon manuals and documents obtained from the selected companies.
The study population consisted of manufacturing industries’ employees in Addis Ababa city and around as there are more representative manufacturing industrial clusters found. To select representative manufacturing industrial sector population, the types of the industries expected were more potential to accidents based on random and purposive sampling considered. The population of data was from textile, leather, metal, chemicals, and food manufacturing industries. A total of 189 sample sizes of industries responded to the questionnaire survey from the priority areas of the government. Random sample sizes and disproportionate methods were used, and 80 from wood, metal, and iron works; 30 from food, beverage, and tobacco products; 50 from leather, textile, and garments; 20 from chemical and chemical products; and 9 from other remaining 9 clusters of manufacturing industries responded.
A simple random sampling and purposive sampling methods were used to select the representative manufacturing industries and respondents for the study. The simple random sampling ensures that each member of the population has an equal chance for the selection or the chance of getting a response which can be more than equal to the chance depending on the data analysis justification. Sample size determination procedure was used to get optimum and reasonable information. In this study, both probability (simple random sampling) and nonprobability (convenience, quota, purposive, and judgmental) sampling methods were used as the nature of the industries are varied. This is because of the characteristics of data sources which permitted the researchers to follow the multi-methods. This helps the analysis to triangulate the data obtained and increase the reliability of the research outcome and its decision. The companies’ establishment time and its engagement in operation, the number of employees and the proportion it has, the owner types (government and private), type of manufacturing industry/production, types of resource used at work, and the location it is found in the city and around were some of the criteria for the selections.
The determination of the sample size was adopted from Daniel [5] and Cochran [6] formula. The formula used was for unknown population size Eq. (1) and is given as
where n = sample size, Z = statistic for a level of confidence, P = expected prevalence or proportion (in proportion of one; if 50%, P = 0.5), and d = precision (in proportion of one; if 6%, d = 0.06). Z statistic (Z): for the level of confidence of 95%, which is conventional, Z value is 1.96. In this study, investigators present their results with 95% confidence intervals (CI).
The expected sample number was 267 at the marginal error of 6% for 95% confidence interval of manufacturing industries. However, the collected data indicated that only 189 populations were used for the analysis after rejecting some data having more missing values in the responses from the industries. Hence, the actual data collection resulted in 71% response rate. The 267 population were assumed to be satisfactory and representative for the data analysis.
The sample size for the experimental exposure measurements of physical work environment has been considered based on the physical data prepared for questionnaires and respondents. The response of positive were considered for exposure measurement factors to be considered for the physical environment health and disease causing such as noise intensity, light intensity, pressure/stress, vibration, temperature/coldness, or hotness and dust particles on 20 workplace sites. The selection method was using random sampling in line with purposive method. The measurement of the exposure factors was done in collaboration with Addis Ababa city Administration and Oromia Bureau of Labour and Social Affair (AACBOLSA). Some measuring instruments were obtained from the Addis Ababa city and Oromia Bureau of Labour and Social Affair.
Data collection methods were focused on the followings basic techniques. These included secondary and primary data collections focusing on both qualitative and quantitative data as defined in the previous section. The data collection mechanisms are devised and prepared with their proper procedures.
Primary data sources are qualitative and quantitative. The qualitative sources are field observation, interview, and informal discussions, while that of quantitative data sources are survey questionnaires and interview questions. The next sections elaborate how the data were obtained from the primary sources.
Observation is an important aspect of science. Observation is tightly connected to data collection, and there are different sources for this: documentation, archival records, interviews, direct observations, and participant observations. Observational research findings are considered strong in validity because the researcher is able to collect a depth of information about a particular behavior. In this dissertation, the researchers used observation method as one tool for collecting information and data before questionnaire design and after the start of research too. The researcher made more than 20 specific observations of manufacturing industries in the study areas. During the observations, it found a deeper understanding of the working environment and the different sections in the production system and OSH practices.
Interview is a loosely structured qualitative in-depth interview with people who are considered to be particularly knowledgeable about the topic of interest. The semi-structured interview is usually conducted in a face-to-face setting which permits the researcher to seek new insights, ask questions, and assess phenomena in different perspectives. It let the researcher to know the in-depth of the present working environment influential factors and consequences. It has provided opportunities for refining data collection efforts and examining specialized systems or processes. It was used when the researcher faces written records or published document limitation or wanted to triangulate the data obtained from other primary and secondary data sources.
This dissertation is also conducted with a qualitative approach and conducting interviews. The advantage of using interviews as a method is that it allows respondents to raise issues that the interviewer may not have expected. All interviews with employees, management, and technicians were conducted by the corresponding researcher, on a face-to-face basis at workplace. All interviews were recorded and transcribed.
The main tool for gaining primary information in practical research is questionnaires, due to the fact that the researcher can decide on the sample and the types of questions to be asked [2].
In this dissertation, each respondent is requested to reply to an identical list of questions mixed so that biasness was prevented. Initially the questionnaire design was coded and mixed up from specific topic based on uniform structures. Consequently, the questionnaire produced valuable data which was required to achieve the dissertation objectives.
The questionnaires developed were based on a five-item Likert scale. Responses were given to each statement using a five-point Likert-type scale, for which 1 = “strongly disagree” to 5 = “strongly agree.” The responses were summed up to produce a score for the measures.
The data was also obtained from the expert’s opinion related to the comparison of the knowledge, management, collaboration, and technology utilization including their sub-factors. The data obtained in this way was used for prioritization and decision-making of OSH, improving factor priority. The prioritization of the factors was using Saaty scales (1–9) and then converting to Fuzzy set values obtained from previous researches using triangular fuzzy set [7].
The researcher has measured the workplace environment for dust, vibration, heat, pressure, light, and noise to know how much is the level of each variable. The primary data sources planned and an actual coverage has been compared as shown in Table 1.
Planned versus actual coverage of the survey.
The response rate for the proposed data source was good, and the pilot test also proved the reliability of questionnaires. Interview/discussion resulted in 87% of responses among the respondents; the survey questionnaire response rate obtained was 71%, and the field observation response rate was 90% for the whole data analysis process. Hence, the data organization quality level has not been compromised.
This response rate is considered to be representative of studies of organizations. As the study agrees on the response rate to be 30%, it is considered acceptable [8]. Saunders et al. [2] argued that the questionnaire with a scale response of 20% response rate is acceptable. Low response rate should not discourage the researchers, because a great deal of published research work also achieves low response rate. Hence, the response rate of this study is acceptable and very good for the purpose of meeting the study objectives.
The pretest for questionnaires, interviews, and tools were conducted to validate that the tool content is valid or not in the sense of the respondents’ understanding. Hence, content validity (in which the questions are answered to the target without excluding important points), internal validity (in which the questions raised answer the outcomes of researchers’ target), and external validity (in which the result can generalize to all the population from the survey sample population) were reflected. It has been proved with this pilot test prior to the start of the basic data collections. Following feedback process, a few minor changes were made to the originally designed data collect tools. The pilot test made for the questionnaire test was on 10 sample sizes selected randomly from the target sectors and experts.
The secondary data refers to data that was collected by someone other than the user. This data source gives insights of the research area of the current state-of-the-art method. It also makes some sort of research gap that needs to be filled by the researcher. This secondary data sources could be internal and external data sources of information that may cover a wide range of areas.
Literature/desk review and industry documents and reports: To achieve the dissertation’s objectives, the researcher has conducted excessive document review and reports of the companies in both online and offline modes. From a methodological point of view, literature reviews can be comprehended as content analysis, where quantitative and qualitative aspects are mixed to assess structural (descriptive) as well as content criteria.
A literature search was conducted using the database sources like MEDLINE; Emerald; Taylor and Francis publications; EMBASE (medical literature); PsycINFO (psychological literature); Sociological Abstracts (sociological literature); accident prevention journals; US Statistics of Labor, European Safety and Health database; ABI Inform; Business Source Premier (business/management literature); EconLit (economic literature); Social Service Abstracts (social work and social service literature); and other related materials. The search strategy was focused on articles or reports that measure one or more of the dimensions within the research OSH model framework. This search strategy was based on a framework and measurement filter strategy developed by the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) group. Based on screening, unrelated articles to the research model and objectives were excluded. Prior to screening, researcher (principal investigator) reviewed a sample of more than 2000 articles, websites, reports, and guidelines to determine whether they should be included for further review or reject. Discrepancies were thoroughly identified and resolved before the review of the main group of more than 300 articles commenced. After excluding the articles based on the title, keywords, and abstract, the remaining articles were reviewed in detail, and the information was extracted on the instrument that was used to assess the dimension of research interest. A complete list of items was then collated within each research targets or objectives and reviewed to identify any missing elements.
Data analysis method follows the procedures listed under the following sections. The data analysis part answered the basic questions raised in the problem statement. The detailed analysis of the developed and developing countries’ experiences on OSH regarding manufacturing industries was analyzed, discussed, compared and contrasted, and synthesized.
Quantitative data were obtained from primary and secondary data discussed above in this chapter. This data analysis was based on their data type using Excel, SPSS 20.0, Office Word format, and other tools. This data analysis focuses on numerical/quantitative data analysis.
Before analysis, data coding of responses and analysis were made. In order to analyze the data obtained easily, the data were coded to SPSS 20.0 software as the data obtained from questionnaires. This task involved identifying, classifying, and assigning a numeric or character symbol to data, which was done in only one way pre-coded [9, 10]. In this study, all of the responses were pre-coded. They were taken from the list of responses, a number of corresponding to a particular selection was given. This process was applied to every earlier question that needed this treatment. Upon completion, the data were then entered to a statistical analysis software package, SPSS version 20.0 on Windows 10 for the next steps.
Under the data analysis, exploration of data has been made with descriptive statistics and graphical analysis. The analysis included exploring the relationship between variables and comparing groups how they affect each other. This has been done using cross tabulation/chi square, correlation, and factor analysis and using nonparametric statistic.
Qualitative data analysis used for triangulation of the quantitative data analysis. The interview, observation, and report records were used to support the findings. The analysis has been incorporated with the quantitative discussion results in the data analysis parts.
The data were entered using SPSS 20.0 on Windows 10 and analyzed. The analysis supported with SPSS software much contributed to the finding. It had contributed to the data validation and correctness of the SPSS results. The software analyzed and compared the results of different variables used in the research questionnaires. Excel is also used to draw the pictures and calculate some analytical solutions.
The reliability of measurements specifies the amount to which it is without bias (error free) and hence ensures consistent measurement across time and across the various items in the instrument [8]. In reliability analysis, it has been checked for the stability and consistency of the data. In the case of reliability analysis, the researcher checked the accuracy and precision of the procedure of measurement. Reliability has numerous definitions and approaches, but in several environments, the concept comes to be consistent [8]. The measurement fulfills the requirements of reliability when it produces consistent results during data analysis procedure. The reliability is determined through Cranach’s alpha as shown in Table 2.
Internal consistency and reliability test of questionnaires items.
K stands for knowledge; M, management; T, technology; C, collaboration; P, policy, standards, and regulation; H, hazards and accident conditions; PPE, personal protective equipment.
Cronbach’s alpha is a measure of internal consistency, i.e., how closely related a set of items are as a group [11]. It is considered to be a measure of scale reliability. The reliability of internal consistency most of the time is measured based on the Cronbach’s alpha value. Reliability coefficient of 0.70 and above is considered “acceptable” in most research situations [12]. In this study, reliability analysis for internal consistency of Likert-scale measurement after deleting 13 items was found similar; the reliability coefficients were found for 76 items were 0.964 and for the individual groupings made shown in Table 2. It was also found internally consistent using the Cronbach’s alpha test. Table 2 shows the internal consistency of the seven major instruments in which their reliability falls in the acceptable range for this research.
Face validity used as defined by Babbie [13] is an indicator that makes it seem a reasonable measure of some variables, and it is the subjective judgment that the instrument measures what it intends to measure in terms of relevance [14]. Thus, the researcher ensured, in this study, when developing the instruments that uncertainties were eliminated by using appropriate words and concepts in order to enhance clarity and general suitability [14]. Furthermore, the researcher submitted the instruments to the research supervisor and the joint supervisor who are both occupational health experts, to ensure validity of the measuring instruments and determine whether the instruments could be considered valid on face value.
In this study, the researcher was guided by reviewed literature related to compliance with the occupational health and safety conditions and data collection methods before he could develop the measuring instruments. In addition, the pretest study that was conducted prior to the main study assisted the researcher to avoid uncertainties of the contents in the data collection measuring instruments. A thorough inspection of the measuring instruments by the statistician and the researcher’s supervisor and joint experts, to ensure that all concepts pertaining to the study were included, ensured that the instruments were enriched.
Insight has been given to the data collectors on how to approach companies, and many of the questionnaires were distributed through MSc students at Addis Ababa Institute of Technology (AAiT) and manufacturing industries’ experience experts. This made the data quality reliable as it has been continually discussed with them. Pretesting for questionnaire was done on 10 workers to assure the quality of the data and for improvement of data collection tools. Supervision during data collection was done to understand how the data collectors are handling the questionnaire, and each filled questionnaires was checked for its completeness, accuracy, clarity, and consistency on a daily basis either face-to-face or by phone/email. The data expected in poor quality were rejected out of the acting during the screening time. Among planned 267 questionnaires, 189 were responded back. Finally, it was analyzed by the principal investigator.
The data were collected from the company representative with the knowledge of OSH. Articles written in English and Amharic were included in this study. Database information obtained in relation to articles and those who have OSH area such as interventions method, method of accident identification, impact of occupational accidents, types of occupational injuries/disease, and impact of occupational accidents, and disease on productivity and costs of company and have used at least one form of feedback mechanism. No specific time period was chosen in order to access all available published papers. The questionnaire statements which are similar in the questionnaire have been rejected from the data analysis.
Ethical clearance was obtained from the School of Mechanical and Industrial Engineering, Institute of Technology, Addis Ababa University. Official letters were written from the School of Mechanical and Industrial Engineering to the respective manufacturing industries. The purpose of the study was explained to the study subjects. The study subjects were told that the information they provided was kept confidential and that their identities would not be revealed in association with the information they provided. Informed consent was secured from each participant. For bad working environment assessment findings, feedback will be given to all manufacturing industries involved in the study. There is a plan to give a copy of the result to the respective study manufacturing industries’ and ministries’ offices. The respondents’ privacy and their responses were not individually analyzed and included in the report.
The result of this study will be presented to the Addis Ababa University, AAiT, School of Mechanical and Industrial Engineering. It will also be communicated to the Ethiopian manufacturing industries, Ministry of Labor and Social Affair, Ministry of Industry, and Ministry of Health from where the data was collected. The result will also be availed by publication and online presentation in Google Scholars. To this end, about five articles were published and disseminated to the whole world.
The research methodology and design indicated overall process of the flow of the research for the given study. The data sources and data collection methods were used. The overall research strategies and framework are indicated in this research process from problem formulation to problem validation including all the parameters. It has laid some foundation and how research methodology is devised and framed for researchers. This means, it helps researchers to consider it as one of the samples and models for the research data collection and process from the beginning of the problem statement to the research finding. Especially, this research flow helps new researchers to the research environment and methodology in particular.
There is no “conflict of interest.”
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