Table Of Content

Biotechnology in Healthcare, Volume 1 Technologies and Innovations Thispageintentionallyleftblank Biotechnology in Healthcare, Volume 1 Technologies and Innovations Edited by Debmalya Barh Ph.D Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology, Nonakuri, Purba Medinipur, West Bengal, India Department of Genetics, Laboratory of Cellular & Molecular Genetics, Ecology & Evolution, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, CEP, 31270-901, Brazil AcademicPressisanimprintofElsevier 125LondonWall,LondonEC2Y5AS,UnitedKingdom 525BStreet,Suite1650,SanDiego,CA92101,UnitedStates 50HampshireStreet,5thFloor,Cambridge,MA02139,UnitedStates TheBoulevard,LangfordLane,Kidlington,OxfordOX51GB,UnitedKingdom Copyright©2022ElsevierInc.Allrightsreserved. Nopartofthispublicationmaybereproducedortransmittedinanyformorbyanymeans,electronicormechanical,including photocopying,recording,oranyinformationstorageandretrievalsystem,withoutpermissioninwritingfromthepublisher. Detailsonhowtoseekpermission,furtherinformationaboutthePublisher’spermissionspoliciesandourarrangementswith organizationssuchastheCopyrightClearanceCenterandtheCopyrightLicensingAgency,canbefoundatourwebsite:www. elsevier.com/permissions. ThisbookandtheindividualcontributionscontainedinitareprotectedundercopyrightbythePublisher(otherthanasmaybe notedherein). Notices Knowledgeandbestpracticeinthisfieldareconstantlychanging.Asnewresearchandexperiencebroadenourunderstanding, changesinresearchmethods,professionalpractices,ormedicaltreatmentmaybecomenecessary. Practitionersandresearchersmustalwaysrelyontheirownexperienceandknowledgeinevaluatingandusinganyinformation, methods,compounds,orexperimentsdescribedherein.Inusingsuchinformationormethodstheyshouldbemindfuloftheir ownsafetyandthesafetyofothers,includingpartiesforwhomtheyhaveaprofessionalresponsibility. Tothefullestextentofthelaw,neitherthePublishernortheauthors,contributors,oreditors,assumeanyliabilityforanyinjury and/ordamagetopersonsorpropertyasamatterofproductsliability,negligenceorotherwise,orfromanyuseoroperationof anymethods,products,instructions,orideascontainedinthematerialherein. ISBN:978-0-323-89837-9 ForInformationonallAcademicPresspublications visitourwebsiteathttps://www.elsevier.com/books-and-journals Publisher:StacyMasucci AcquisitionsEditor:RafaelE.Teixeira EditorialProjectManager:MariaElaineD.Desamero ProductionProjectManager:SwapnaSrinivasan CoverDesigner:MarkRogers TypesetbyMPSLimited,Chennai,India Dedication I dedicate this book to my little princess Vaibhavi. Thispageintentionallyleftblank Contents Listofcontributors xiii 2.3 Materialsofthree-dimensionalprinting 30 Abouttheeditor xvii 2.4 Three-dimensionalprintinginsurgical Preface xix planningandmedicaleducation 31 2.5 Three-dimensionalprintinginoraland 1. Overview of healthcare maxillofacialsurgery 32 biotechnology 1 2.6 Three-dimensionalprintingin orthopedics 33 AimanTanveer,KanchanYadav,ShrutiDwivedi, 2.7 Three-dimensionalprintingin SupriyaGupta,PramodK.YadavandDineshYadav neurosurgery 33 1.1 Introduction 1 2.8 Bioprintingtissueandorganfabrication 35 1.2 Genomics 1 2.9 Three-dimensionalprintingin 1.2.1 Geneticscreeningandtesting 3 pharmaceuticalindustry 36 1.2.2 Diagnosisofgeneticdisorders 3 2.10 Futureofthree-dimensionalprinting 36 1.2.3 Pharmacogenomicsand 2.10.1 Limitationsofthree-dimensional epigenomics 6 printings 37 1.2.4 Personalizedmedicine 6 2.11 Conclusion 37 1.3 Transcriptomics 7 References 37 1.3.1 Toolsoftranscriptomics 7 1.3.2 Transcriptomicsindiseasediagnosis 9 1.3.3 Transcriptomeprofilingindrug 3. Synthetic biology in healthcare: discovery 10 technologies and applications 41 1.4 Proteomics 10 1.4.1 Toolsandtechniquesinthe MubashirHassan,AnamNaz,AmmaraSiddique, proteomics-basedstudy 10 SabaShahzadi,SalahudDin,ZainabYaseen, 1.4.2 Biomarkerdiscovery 13 SawairaNaqvi,QinzaAli,FaryalMehwishAwan 1.4.3 Drugdevelopment 13 andAqsaIkram 1.5 Metabolomics 14 3.1 Introduction 41 1.5.1 Toolsandtechniquesin 3.1.1 Cell-freesystemsandapplications 41 metabolomicsstudy 16 3.2 TechnologiesforsyntheticDNA,proteins, 1.5.2 Metabolomicsintreatmentofcancer, andorganisms 41 neurological,andpsychiatric disorders 18 3.2.1 Syntheticbiology-basedDoggybone 1.5.3 Individualizedmetabolomics 20 DNAtechnologyanditsusesin 1.6 Conclusion 20 vaccinesandDNA-based Acknowledgments 20 genetherapyproducts 41 References 20 3.2.2 DevelopmentoflineardbDNA vaccineconstruct 42 2. Three-dimensional printing in 3.3 Gen9technology—microfluidicdevicesand healthcare 27 methodsforgenesynthesis 42 3.3.1 DNAsynthesisandscaleup YusufIzci (BioFabplatform) 42 2.1 Introduction 27 3.3.2 Technologiesforsyntheticgenomes 43 2.2 Three-dimensionalprintingtechnology 3.3.3 Syntheticbiologytocreatean (hardwareandsoftware) 27 artificialmembrane-bindingprotein 43 vii viii Contents 3.3.4 Pathwayrewiringwithadaptersand 4. Nanotechnology in healthcare: scaffolds 44 nanoparticles for diagnostic and 3.3.5 SyntheticDNAfordevelopingnew therapy 55 antibiotics 44 3.3.6 SyntheticDNAforamino-acid TugbaTezcanandChia-HsienHsu replacement 44 4.1 Introduction 55 3.3.7 Syntheticproteinstechnologies 45 4.2 Classificationandpropertiesof 3.3.8 Technologiestocreatesynthetic nanoparticles 56 organisms 45 4.2.1 Goldnanoparticles 56 3.3.9 Syntheticbiologyapplicationsin 4.2.2 Magneticnanoparticles 57 diagnostics 46 4.2.3 Quantumdots 57 3.4 Transcriptional,posttranslational,and 4.2.4 Carbonnanostructures 58 hybridbiosensingandapplications 46 4.2.5 Polymericnanoparticles 58 3.4.1 Transcriptionalbiosensing 46 4.3 Nanoparticle-basedbiosensorsfor 3.4.2 Posttranslationalbiosensing 46 medicaldiagnosis 59 3.4.3 Hybridbiosensing 46 4.3.1 Plasmonicbiosensors 59 3.5 Applications 46 4.3.2 QD-basedbiosensors 60 3.5.1 Paper-baseddiagnostic 47 4.3.3 Carbonnanostructure-based 3.5.2 Syntheticbiologyapplicationsfor biosensors 61 drugdiscoveryandtherapy 47 4.4 Nanoparticle-basedtherapyandimaging 61 3.5.3 Drug-targetidentification 4.4.1 Targeteddrugdelivery 62 (syntheticpathwaysandsystems) 48 4.4.2 Bioimagingandphotothermal 3.5.4 Drugdiscovery 48 therapy 63 3.5.5 Therapeutictreatment 4.4.3 Nanoparticlesintheclinic 64 (syntheticbiologydevices) 48 4.5 Conclusionandfutureperspective 65 3.5.6 Therapeuticdelivery 48 References 65 3.6 Syntheticbiologyforcreatinglivingsystems toproducesmallmolecules,forinstance, 5. Analysis and applications of aspirin,thatcharacteristicallycomefrom chemicalratherthanthebiological sequencing in healthcare 71 processes 49 MaloyjoJoyrajBhattacharjeeand 3.6.1 CodeEvolver-likeprotein-engineering BasantK.Tiwary synthetic-biologyplatformtocreate uniqueenzymesastherapeutics 49 5.1 Introduction 71 3.6.2 Chimericantigenreceptor 49 5.2 Methodofde-novoandreference-based 3.6.3 Syntheticgenomesandvaccinedesign DNAsequencing 71 (SARS-CoV-2andotherviruses) 49 5.3 GenerationofDNAreads 72 3.7 Livingtherapies—engineeringmicrobesand 5.4 Qualityassessmentofreads 73 bacteriophagetotreatdisease 50 5.5 TrimmingofDNAreads 74 3.7.1 Engineeredbacteria(suchas 5.6 MappingofDNAreads 74 Salmonella)todelivervaccines 50 5.7 Assembly 75 3.7.2 Understandingdiseasemechanism 50 5.8 AnalysisofDNAsequencesfor 3.7.3 Syntheticbiology-basedpathway marker-basedsurveillanceofdiseases 75 engineeringforpharmaceutical 5.9 Phylomedicineofgeneticdiseases 76 production 50 5.10 Methodofde-novoandreference-based 3.7.4 Constructingbiosyntheticpathways 50 RNAsequencing 76 3.7.5 Optimizingpathwayflux 51 5.11 GenerationofshortRNAreadsand 3.7.6 Programmingnovelfunctionalityand qualityassessment 77 materials 51 5.12 TrimmingofRNAreads 77 3.7.7 Chemicalretrosynthesisanditsfuture 5.13 MappingofRNAreads 77 applicationsinhealthcare 51 5.14 AssemblyofRNAreads 77 3.8 Futurechallengesandconclusions 51 5.15 Analysisofdifferentialexpressionof Acknowledgment 52 genesindiseasesstatesandinprognosis References 52 ofdisease 78 Contents ix 5.16 Analysisofalternativesplicingofgenes 6.4.3 Featureselectionwithdecisiontrees 92 andgenefusionindiseasestates 78 6.4.4 Featureselectionbyanalysis 94 5.17 AnalysisoflongnoncodingRNAandits 6.4.5 AnalysiswithedgeRorDESeq2 94 relevancetodisease 78 6.4.6 Pickupmachinelearningmodels 96 5.18 Genecoexpressionanalysisand 6.4.7 Evaluatemachinelearningmodel 96 annotationofTF-TFBSandgene 6.4.8 Workflowforprocessingreadingsin regulatorynetwork 79 RNA-seq 98 5.19 MethodofDAP-sequencingand 6.5 BIGDATA 100 genome-wideannotationofcistrome 79 Acknowledgments 101 5.20 AnalysisofDAPsequencesandits References 101 applicationinhealthcare 81 5.21 Genome-widemappingofTF-TFBSand visualizationofgene-regulatorynetwork 81 7. Omics applications in reproductive References 81 medicine 103 Rabajdova´ Miroslava,Sˇolty´sKatarı´na, Sˇpakova´ IvanaandUrdzı´kPeter 6. Innovative technologies in precision healthcare 83 7.1 Genetictestingandmolecularmethodsof femaleinfertility 103 Sˇolty´sKatarı´na,KlˇocMarek,Rabajdova´ Miroslava 7.1.1 Molecularmethodsoftranscriptome andMarekova´ Ma´ria analysisinfemaleinfertility 103 6.1 Definingprecisionandpersonalized 7.1.2 Methodsofmetabolomicsanalysis medicine 83 offemaleinfertility 104 6.1.1 Assessingemergingtechnologiesfor 7.1.3 Methodsofproteomicsanalysisof personalizedprecisionmedicines’ femaleinfertility 106 clinicaltrials 83 7.1.4 Molecularmethodsofmicrobial 6.1.2 Biosensorsinpersonalizedmedicine 84 analysisoffemaleinfertility 107 6.1.3 Omicsinprecisionhealthcare 84 7.1.5 Molecularmethodsofgenomic 6.1.4 Engineeringprecisionmedicine analysisoffemaleinfertility 108 technologyandplatforms 84 7.2 Genetictestingandmolecularmethods 6.2 Databasesapplicationsinprecision ofmaleinfertility 109 healthcare 85 7.2.1 Molecularmethodsoftranscriptome 6.2.1 Microbiomedatabases 85 analysisofmaleinfertility 110 6.2.2 Databasesforprotein-codinggenes 86 7.2.2 Methodsofmetabolomicsanalysisof 6.2.3 Databasesfornoncodinggenes 86 maleinfertility 111 6.2.4 Databasesusedforannotationof 7.2.3 Molecularmethodsofproteomic humangeneticvariantsand analysisofmaleinfertility 111 rearrangements 86 7.2.4 Molecularmethodsofmicrobial 6.2.5 Predictionofgenefunction 87 analysisofmaleinfertility 112 6.3 Bioengineering,machinelearningfor 7.2.5 Molecularmethodsofgenomic personalizedmedicine 87 analysisofmaleinfertility 113 6.3.1 Principleofmachinelearning 87 7.3 Genetictestingandmolecularmethods 6.3.2 Whymachinelearning? 88 ofembryonicanalysisandmonitoring 6.3.3 Supervisedmachinelearning 89 duringtheinvitrofertilizationprocess 115 6.3.4 Unsupervisedmachinelearning 89 7.3.1 Invasivepreimplantationgenetic 6.3.5 Reinforcementlearning 89 testingoftheembryointheinvitro 6.3.6 Onlinelearning 90 fertilizationprocess 115 6.3.7 Recommendationsinmachine 7.3.2 Noninvasivegenetictestingofembryo learning 90 qualityfortheinvitrofertilization 6.3.8 Testingandverification 90 processfromthespentblastocyst 6.4 Applicationofbioinformaticsmachine medium 115 learningandin-depthdataanalysis 90 7.3.3 Transcriptomicanalysesinspent 6.4.1 Getthedata 91 culturemedium 116 6.4.2 Exploreandpreparedata 91 7.4 Omicsmethodsofinfertility 118