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{"project":"LitCovid-PD-HP","denotations":[{"id":"T3","span":{"begin":7945,"end":7953},"obj":"Phenotype"},{"id":"T4","span":{"begin":13923,"end":13933},"obj":"Phenotype"},{"id":"T5","span":{"begin":17369,"end":17381},"obj":"Phenotype"},{"id":"T6","span":{"begin":27269,"end":27279},"obj":"Phenotype"},{"id":"T7","span":{"begin":27312,"end":27322},"obj":"Phenotype"},{"id":"T8","span":{"begin":40685,"end":40697},"obj":"Phenotype"},{"id":"T9","span":{"begin":56173,"end":56186},"obj":"Phenotype"}],"attributes":[{"id":"A3","pred":"hp_id","subj":"T3","obj":"http://purl.obolibrary.org/obo/HP_0002014"},{"id":"A4","pred":"hp_id","subj":"T4","obj":"http://purl.obolibrary.org/obo/HP_0002090"},{"id":"A5","pred":"hp_id","subj":"T5","obj":"http://purl.obolibrary.org/obo/HP_0002383"},{"id":"A6","pred":"hp_id","subj":"T6","obj":"http://purl.obolibrary.org/obo/HP_0002090"},{"id":"A7","pred":"hp_id","subj":"T7","obj":"http://purl.obolibrary.org/obo/HP_0002090"},{"id":"A8","pred":"hp_id","subj":"T8","obj":"http://purl.obolibrary.org/obo/HP_0002383"},{"id":"A9","pred":"hp_id","subj":"T9","obj":"http://purl.obolibrary.org/obo/HP_0003002"}],"text":"2 Electrochemical biosensor designs for pathogen detection\nA chemical sensor is a device that transforms chemical information, such as the concentration of a specific sample component or total compositional analysis into an analytically useful signal (Thévenot et al. 2001). The electrochemical method utilized is a distinguishing aspect of an electrochemical biosensor. In addition to the electrochemical method, the sample handling approach and sensor signal readout format also provide distinguishing aspects of a biosensor-based approach for pathogen detection. Thus, we review electrochemical biosensors for pathogen detection using a framework built upon transducer elements, biorecognition elements, and measurement formats. An overview of electrochemical biosensors for pathogen detection is provided in Fig. 1 . As shown in Fig. 2 a, while the detection of bacterial pathogens remains an area of focus, the detection of viral pathogens and protozoa is an emerging area. As shown in Fig. 2b, studies have focused on pathogen detection in various matrices. We next discuss the transduction elements, biorecognition elements, and measurement formats associated with electrochemical biosensors for pathogen detection.\nFig. 1 Components and measurement formats associated with electrochemical biosensors for pathogen detection.\nFig. 2 a) Trend in pathogens detected by electrochemical biosensors since 2005 based on the data shown in Table 1, Table 2. b) Common matrices associated with the various pathogen detection applications.\n\n2.1 Transduction elements\nThe transduction element of an electrochemical biosensor is an electrochemical cell where the main component is commonly a working electrode. A three electrode format (working, auxiliary, and reference) is commonly employed in a potentiostatic system, while a two electrode format (working and auxiliary) is often used for conductometry and electrochemical impedance spectroscopy (EIS). Electrodes can be fabricated from multiple materials and using various manufacturing processes. An electrode is an electronic conductor through which charge is transported by the movement of electrons and holes (Bard and Faulkner, 2000). Electrodes are thus fabricated from conducting and semiconducting materials, including metals, such as gold (Au), and nonmetals, such as carbon. Manufacturing processes can be used to fabricate electrodes of various sizes, including bulk structures (greater than 1 mm) and micro- and nano-structures. As a result, electrodes can be classified by type and form of material, manufacturing process, and design. Electrode designs can be classified by form factor, which includes planar, wire, nanostructured, or array-based. The material, fabrication approach, and design affect the electrode's structure and properties, which ultimately determine the biosensor's performance, including sensitivity, selectivity, limit of detection (LOD), and dynamic range. They also influence the biosensor's cost, manufacturability, disposability, and measurement capabilities.\n\n2.1.1 Metal electrodes\nMetal electrodes, such as Au and platinum (Pt), have been commonly used for pathogen detection. Thick metal electrodes are commonly fabricated from bulk structures via cutting processes. Thin-film metal electrodes are often fabricated by deposition of metals on insulating substrates through traditional microfabrication approaches, including physical vapor deposition (Hierlemann et al. 2003) and screen printing (Taleat et al. 2014). Resultant conductive components are often embedded in insulating polymer or ceramic substrates, including Teflon, polyetherkeytone (PEK), and glass, to complete fabrication of the transducer element. While not yet applied to pathogen detection applications, three-dimensional (3D) printing processes, including inkjet printing (Bhat et al. 2018; Medina-Sánchez et al. 2014; Pavinatto et al. 2015), selective laser melting (Ambrosi et al. 2016; Loo et al. 2017), and microextrusion printing (Foo et al. 2018), have also been used for the fabrication of electrochemical sensors and electrodes using a variety of metals. As shown in Table 1 , unstructured metal electrodes exhibit a range of detection limits. For example, the detection limits of electrochemical biosensors for bacteria that employ unstructured metal electrodes range from 1 to 104 CFU/mL (see Table 1).\nTable 1 Classification of label-free electrochemical biosensors for detection of pathogens in terms of: target, working electrode, biorecognition element, electrochemical method, limit of detection, and electrochemical probe. Abbreviations: quartz crystal microbalance (QCM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), plaque-forming unit (PFU), colony-forming unit (CFU), indium tin oxide (ITO), carbon nanotube (CNT), magnetic bead (MB), nanoparticle (NP), differential pulse voltammetry (DPV), square wave voltammetry (SWV), anodic stripping voltammetry (ASV), hemagglutination units (HAU), and median tissue culture infectious dose (TCID50).\nTarget Pathogen Working Electrode Biorecognition Element Electrochemical Method \u0026 Probe Limit of Detection Reference\nE. coli Au interdigitated microelectrode array polyclonal anti-E.coli EIS 104 CFU/mL Radke and Alocilja (2005)\nE. coli ITO electrode monoclonal anti-E. coli CV, EIS; Fe(CN)63-/4- 4 × 103 CFU/mL Zhang et al. (2005)\nE. coli chromium interdigitated microelectrode array anti-E. coli EIS – Suehiro et al. (2006)\nS. typhimurium ITO interdigitated microelectrode array anti-S. typhimurium EIS 10 CFU/mL Yang and Li (2006)\nV. cholerae carbon electrode polyclonal anti-V. cholerae amperometry 8 CFU/mL Sharma et al. (2006)\nE. coli Pt wire electrode polyclonal anti-E. coli potentiometry 9 × 105 CFU/mL Boehm et al. (2007)\nE. coli Au microelectrode polyclonal anti-E.coli EIS 10 CFU/mL Maalouf et al. (2007)\nL. monocytogenes TiO2 nanowires on Au electrode monoclonal anti-L. monocytogenes EIS 470 CFU/mL Wang et al. (2008)\nE. coli Au electrode polyclonal anti-E. coli CV, EIS; Fe(CN)63-/4- 50 CFU/mL Geng et al. (2008)\nS. typhimurium Au electrode polyclonal anti-S. typhimurium EIS; Fe(CN)63-/4- 10 CFU/mL Pournaras et al. (2008)\nS. typhimurium Au microelectrode anti-S. typhimurium EIS; Fe(CN)63-/4- 500 CFU/mL Nandakumar et al. (2008)\nE. coli graphite interdigitated microelectrode array E. coli-specific bacteriophages EIS 104 CFU/mL Shabani et al. (2008)\nS. typhimurium Au electrode polyclonal anti-S. typhimurium EIS 100 CFU/mL Mantzila et al. (2008)\nS. typhimurium macroporous silicon electrode anti-S. typhimurium EIS 103 CFU/mL Das et al. (2009)\nWest Nile virus (WNV) nanostructured alumina on Pt wire electrode monoclonal anti-WNV AC voltammetry 0.02 viruses/mL Nguyen et al. (2009)\nS. typhimurium Au electrode monoclonal anti-S. typhimurium EIS; Fe(CN)63-/4- 100 CFU/mL La Belle et al. (2009)\nS. typhimurium CNTs on carbon rod electrode anti-S. typhimurium aptamer potentiometry 0.2 CFU/mL Zelada-Guillen et al. (2009)\nE. coli Au electrode anti-E. coli CV, EIS; Fe(CN)63-/4- 3.3 CFU/mL Escamilla-Gomez et al. (2009)\nB. anthracis Ag electrode monoclonal and polyclonal anti-B. anthracis conductometry 420 spores/mL Pal and Alocilja (2009)\nE. coli polysilicon interdigitated microelectrode array polyclonal anti-E. coli EIS 300 CFU/mL de la Rica et al. (2009)\nE. coli Au interdigitated microelectrode array E. coli-specific bacteriophages EIS 104 CFU/mL Mejri et al. (2010)\nE. coli CNTs on carbon rod electrode anti-E. coli aptamer potentiometry 6 CFU/mL Zelada-Guillen et al. (2010)\nCampylobacter jejuni Fe3O4 nanoparticles on carbon electrode monoclonal anti-Flagellin A EIS; Fe(CN)63-/4- 103 CFU/mL Huang et al. (2010)\nmarine pathogenic sulphate-reducing bacteria (SRB) AuNPs on nickel foam electrode anti-SRB EIS 21 CFU/mL Wan et al. (2010)\nE. coli Ag nanofiber array electrode monoclonal and polyclonal anti-E. coli conductometry 61 CFU/mL Luo et al. (2010)\nbovine viral diarrhea virus (BVDV) Ag nanofiber array electrode monoclonal and polyclonal anti-BVDV conductometry 103 CCID/mL Luo et al. (2010)\nE. coli Au interdigitated microelectrode array magainin I peptide EIS 103 CFU/mL Mannoor et al. (2010)\nE. coli Au rod electrode concanavalin A lectin capacitive 12 CFU/mL Jantra et al. (2011)\nrotavirus graphene microelectrode monoclonal anti-rotavirus CV 103 PFU/mL Liu et al. (2011)\nhuman influenza A virus H3N2 Au electrode polyclonal anti-H3N2 EIS 8 ng/mL Hassen et al. (2011)\nE. coli Au microelectrode polyclonal anti-E. coli capacitive, EIS, CV; Fe(CN)63-/4- 220 CFU/mL Li et al. (2011)\nEnterobacter cloacae Au electrode concanavalin A lectin, ricinus communis agglutinin lectin CV, EIS; Fe(CN)63-/4- 1 × 103 CFU/mL Xi et al. (2011)\nE. coli Au electrode concanavalin A lectin, ricinus communis agglutinin lectin CV, EIS; Fe(CN)63-/4- 100 CFU/mL Xi et al. (2011)\nB. subtilis Au electrode concanavalin A lectin CV, EIS; Fe(CN)63-/4- 1 × 104 CFU/mL Xi et al. (2011)\nE. coli Pt wire electrode anti-E. coli EIS 100 CFU/mL Tan et al. (2011)\nS. aureus Pt wire electrode anti-S. aureus EIS 100 CFU/mL Tan et al. (2011)\nmarine pathogenic sulphate-reducing bacteria (SRB) graphene/chitosan composite on carbon electrode anti-SRB CV, EIS; Fe(CN)63-/4- 18 CFU/mL Wan et al. (2011)\nswine influenza virus (SIV) H1N1 PDDA/CNT composite on Au microelectrode anti-SIV conductometry 180 TCID50/mL Lee et al. (2011)\nE. coli graphene microelectrode anti-E. coli amperometry 10 CFU/mL Huang et al. (2011)\nE. coli PEDOT:PSS electrode anti-E. coli amperometry 103 CFU/mL He et al. (2012)\ndengue type 2 virus (DENV-2) nanostructured alumina on Pt wire electrode monoclonal anti-DENV-2 DPV;Ferrocene methanol 1 PFU/mL Cheng et al. (2012)\nDENV-2 nanostructured alumina on Pt wire electrode monoclonal anti-DENV-2 CV, EIS; Ferrocene methanol 1 PFU/mL Nguyen et al. (2012)\nhuman influenza A viruses H1N1 and H3N2 silicon nanowire electrode array anti-H1N1, anti-H3N2 conductometry 2.9 × 104 viruses/mL Shen et al. (2012)\nE. coli AuNP/Chitosan/CNT and SiO2/thionine NP composite on Au electrode monoclonal anti-E. coli CV 250 CFU/mL Li et al. (2012)\nE. coli CNT/polyallylamine composite on graphite electrode monoclonal anti-E. coli ASV 800 cells/mL Viswanathan et al. (2012)\nCampylobacter CNT/polyallylamine composite on graphite electrode monoclonal anti-Campylobacter ASV 400 cells/mL Viswanathan et al. (2012)\nS. typhimurium CNT/polyallylamine composite on graphite electrode monoclonal anti-S. typhimurium ASV 400 cells/mL Viswanathan et al. (2012)\nS. aureus CNT electrode anti-S. aureus aptamer potentiometry 800 CFU/mL Zelada-Guillen et al. (2012)\nE. coli Au electrode mannose carbohydrate ligand EIS; Fe(CN)63-/4- 100 CFU/mL Guo et al. (2012)\nS. aureus graphene interdigitated microelectrode array odoranin-HP peptide conductometry 1 × 104 cells/mL Mannoor et al. (2012)\nHelicobacter pylori graphene interdigitated microelectrode array odoranin-HP peptide conductometry 100 cells Mannoor et al. (2012)\nL. innocua Au electrode L. innocua-specific bacteriophage EIS; Fe(CN)63-/4- 1.1 × 104 CFU/mL Tolba et al. (2012)\nE. coli polyaniline on Au electrode monoclonal anti-E. coli EIS 100 CFU/mL Chowdhury et al. (2012).\nE. coli Au interdigitated microelectrode array anti-E. coli EIS 2.5 × 104 CFU/mL Dweik et al. (2012).\nE. coli ultra-nanocrystalline diamond microelectrode array anti-E. coli EIS; Fe(CN)63-/4- 1 × 103 CFU/mL Siddiqui et al. (2012).\nhuman influenza A virus H1N1 Au microelectrode phenotype-specific sialic acid-galactose moieties EIS; Fe(CN)63-/4- – Wicklein et al. (2013)\nE. coli Au electrode E. coli-specific bacteriophages EIS; Fe(CN)63-/4- 800 CFU/mL Tlili et al. (2013)\nDENV-2, dengue virus 3 (DENV-3) Pt-coated nanostructured alumina membrane electrode monoclonal anti-dengue EIS; Fe(CN)63-/4- 0.23 PFU/mL, 0.71 PFU/mL Peh and Li (2013)\ncucumber mosaic virus (CMV) polypyrrole nanoribbons on Au microelectrode array polyclonal anti-CMV amperometry 10 ng/mL Chartuprayoon et al. (2013)\nE. coli Au electrode polyclonal anti-E. coli EIS; Fe(CN)63- 2 CFU/mL Barreiros dos Santos et al. (2013)\nE. coli AuNPs on reduced graphene oxide microelectrode anti-E. coli EIS; Fe(CN)63-/4- 150 CFU/mL Wang et al. (2013)\nE. coli Ag/AgCl wire electrode anti-E. coli EIS 10 CFU/mL Joung et al. (2013)\nmurine norovirus (MNV) AuNPs on carbon electrode anti-norovirus (MNV) aptamer SWV, fluorescence; Fe(CN)63-/Ru(NH3)63+ 180 viruses Giamberardino et al. (2013)\nrotavirus reduced graphene oxide microelectrode anti-rotavirus amperometry 100 PFU Liu et al. (2013)\nS. typhimurium AuNP-functionalized poly(amidoamine)-CNT-chitosan composite on carbon electrode anti- S. typhimurium CV, EIS; Fe(CN)63-/4- 500 CFU/mL Dong et al. (2013)\nE. coli Au-tungsten microwire electrode monoclonal anti-E. coli EIS; Fe(CN)63-/4- 5 CFU/mL Lu et al. (2013)\nE. coli Pt wire electrode anti-E. coli EIS 10 CFU/mL Chan et al. (2013)\nS. aureus reduced graphene oxide on carbon rod electrode anti-S. aureus aptamer potentiometry 1 CFU/mL Hernandez et al. (2014)\nE. coli PAA/PD/CNT composite on carbon electrode anti-E. coli ASV 13 CFU/mL Chen et al. (2014)\nS. typhimurium AuNPs on graphene oxide on carbon electrode anti-S. typhimurium aptamer EIS; Fe(CN)63-/4- 3 CFU/mL Ma et al. (2014)\nS. aureus AuNPs on reduced graphene oxide on carbon electrode anti-S. aureus synthetic aptamer EIS; Fe(CN)63-/4- 10 CFU/mL Jia et al. (2014)\nE. coli Au electrode mannose carbohydrate ligand CV, mass change 1 CFU/mL Yazgan et al. (2014)\nL. monocytogenes Au interdigitated microelectrode array leucocin A antimicrobial peptide EIS 103 CFU/mL Etayash et al. (2014)\nS. typhimurium Au interdigitated microelectrode array monoclonal anti-S. typhimurium EIS 3 × 103 CFU/mL Dastider et al. (2015)\nS. aureus Au electrode polyclonal anti-S. typhimurium EIS; Fe(CN)63-/4- 10 CFU/mL Bekir et al. (2015)\nE. coli CNTs on Au electrode clavanin A peptide EIS; Fe(CN)63-/4- 100 CFU/mL Andrade et al. (2015)\nKlebsiella pneumoniae CNTs on Au electrode clavanin A peptide EIS; Fe(CN)63-/4- 103 CFU/mL Andrade et al. (2015)\nEnterococcus faecalis CNTs on Au electrode clavanin A peptide EIS; Fe(CN)63-/4- 103 CFU/mL Andrade et al. (2015)\nB. subtilis CNTs on Au electrode clavanin A peptide EIS; Fe(CN)63-/4- 100 CFU/mL Andrade et al. (2015)\nE. coli PEI/CNT composite on carbon electrode E. coli-specific bacteriophages EIS; Fe(CN)63-/4- 50 CFU/mL Zhou and Ramasamy (2015)\ndengue virus 1–4 AuNPs on Au electrode anti-DENV-1, anti-DENV-2, anti-DENV-3, anti-DENV-4 CV, EIS; Fe(CN)63-/4- – Luna et al. (2015)\nE. coli ITO microelectrode monoclonal anti-E. coli EIS; Fe(CN)63-/4- 1 CFU/mL Barreiros dos Santos et al. (2015)\navian influenza virus (AIV) H5N1 Au interdigitated microelectrode array monoclonal anti-AIV-H5N1 EIS; Fe(CN)63-/4- 4 HAU/mL Lin et al. (2015)\nC. parvum AuNPs on carbon electrode anti-C. parvum aptamer SWV; Fe(CN)63-/4- 100 oocysts Iqbal et al. (2015)\nE. coli CNT-coated Au-tungsten microwire electrodes polyclonal anti-E. coli amperometry 100 CFU/mL Yamada et al. (2016)\nS. aureus CNT-coated Au-tungsten microwire electrodes polyclonal anti-S. aureus amperometry 100 CFU/mL Yamada et al. (2016)\nS. aureus Au interdigitated microelectrode array anti-S. aureus EIS; Fe(CN)63-/4- 1.3 CFU/mL Primiceri et al. (2016)\nL. monocytogenes Au interdigitated microelectrode array anti-L. monocytogenes EIS; Fe(CN)63-/4- 5 CFU/mL Primiceri et al. (2016)\nnorovirus Au microelectrode anti-norovirus aptamer SWV; Fe(CN)63-/Ru(NH3)63+ 10 PFU/mL Kitajima et al. (2016)\navian influenza virus (AIV) H5N1 Au interdigitated microelectrode array anti-AIV-H5N1 aptamer EIS; Fe(CN)63-/4- 4.2 HAU/mL Callaway et al. (2016)\nS. typhimurium poly[pyrrole-co-3-carboxyl-pyrrole] copolymer electrode anti-S. typhimurium aptamer EIS 3 CFU/mL Sheikhzadeh et al. (2016)\nE. coli polysilicon interdigitated microelectrodes polyclonal anti-E. coli EIS – Mallén-Alberdi et al. (2016)\nhuman influenza A virus H3N2 Au electrode phenotype-specific oligoethylene glycol moieties EIS 1.3 × 104 viruses/mL Hushegyi et al. (2016)\nE. coli PEI/CNT composite on Au microwire electrode polyclonal anti-E. coli amperometry 100 CFU/mL Lee and Jun (2016)\nV. cholerae CeO2 nanowires on Pt microelectrode anti-V. cholerae EIS; Fe(CN)63-/4- 100 CFU/mL Tam and Thang (2016)\nS. aureus PEI/CNT composite on Au microwire electrode polyclonal anti-S. aureus amperometry 100 CFU/mL Lee and Jun (2016)\nE. coli graphene microelectrode polyclonal anti-E. coli amperometry 5 × 103 CFU/mL Wu et al. (2016)\nE. coli Au electrode concanavalin A lectin EIS; Fe(CN)63-/4- 75 cells/mL Yang et al. (2016b)\nE. coli Pt wire electrodes anti-E. coli EIS 100 CFU/mL Tian et al. (2016)\nS. aureus Pt wire electrodes anti-S. aureus EIS 100 CFU/mL Tian et al. (2016)\nB. subtilis CNTs on Au interdigitated microelectrode array polyclonal anti-B. subtilis conductometry 100 CFU/mL Yoo et al. (2017)\nS. epidermidis Au microelectrode S. epidermidis-imprinted poly(3-aminophenylboronic acid) polymer film EIS; Fe(CN)63-/4- 103 CFU/mL Golabi et al. (2017)\nnorovirus graphene/AuNP composite on carbon electrode anti-norovirus aptamer DPV; Ferrocene 100 pM Chand and Neethirajan (2017)\nnorovirus Au electrode synthetic norovirus-specific peptide CV, EIS; Fe(CN)63-/4- 7.8 copies/mL Hwang et al. (2017)\nE. coli CuO/cysteine/reduced graphene/Au oxide electrode monoclonal anti-E. coli EIS; Fe(CN)63-/4- 3.8 CFU/mL Pandey et al. (2017)\nJapanese encephalitis virus (JEV) carbon NPs on carbon electrode monoclonal anti-JEV CV, EIS; Fe(CN)63-/4- 2 ng/mL Chin et al. (2017)\nS. aureus CNTs on carbon electrode polyclonal anti-S. aureus DPV; Fe(CN)63-/4- 13 CFU/mL Bhardwaj et al. (2017)\nhuman influenza A virus H1N1 PEDOT film electrode hemagglutinin-specific trisaccharide ligand EIS, potentiometry, mass change; Fe(CN)63-/4- 0.013 HAU Hai et al. (2017)\nhuman influenza A virus H1N1 reduced graphene oxide on Au microelectrode monoclonal anti-H1N1 chrono-amperometry; Fe(CN)63-/4- 0.5 PFU/mL Singh et al. (2017b)\nE. coli Au microelectrode E. coli-imprinted MAH/HEMA polymer film capacitive 70 CFU/mL Idil et al. (2017)\nE. coli chitosan/polypyrrole/CNT/AuNP composite on graphite electrode monoclonal coli CV; Fe(CN)63-/4- 30 CFU/mL Güner et al. (2017)\nS. dysenteriae AuNPs on carbon electrode anti-S. dysenteriae aptamer EIS; Fe(CN)63-/4- 1 CFU/mL Zarei et al. (2018)\nhuman influenza A virus H1N1 PEDOT:PSS film electrode hemagglutinin-specific trisaccharide ligand amperometry 0.015 HAU Hai et al. (2018)\nS. aureus fluoride-doped tin oxide electrode S. aureus-imprinted Ag–MnO2 film DPV; Fe(CN)63-/4- 103 CFU/mL Divagar et al. (2019)\nE. coli Au microelectrode E. coli-imprinted TEOS/MTMS sol-gel film EIS; Fe(CN)63-/4- 1 CFU/mL Jafari et al. (2019)\nnorovirus Au electrode norovirus-specific peptide EIS; Fe(CN)63-/4- 1.7 copies/mL Baek et al. (2019)\nC. parvum Au interdigitated microelectrode array monoclonal anti-C. parvum Capacitive; Fe(CN)63-/4- 40 cells/mm2 Luka et al. (2019)\nE. coli 4-(3-pyrrol) butryic acid electrode concanavalin A lectin, Arachis hypogaea lectin EIS 6 × 103 CFU/mL Saucedo et al. (2019)\nB. subtilis 4-(3-pyrrol) butryic acid electrode concanavalin A lectin, Arachis hypogaea lectin EIS 6 × 103 CFU/mL Saucedo et al. (2019)\nE. coli silica NPs on polyelectrolyte multilayer on Au electrode polyclonal anti-E. coli CV; Fe(CN)63-/4- 2 × 103 CFU/mL Mathelie-Guinlet et al. (2019)\nE. coli silica NPs on polyelectrolyte multilayer on Au electrode polyclonal anti-E. coli CV; Fe(CN)63-/4- 2 × 103 CFU/mL Mathelie-Guinlet et al. (2019)\n\n2.1.2 Ceramic electrodes\nConducting and semiconducting ceramics, including indium tin oxide (ITO), polysilicon, and titanium dioxide (TiO2) have also been examined for pathogen detection. For example, Das et al. used a silicon electrode for Salmonella typhimurium (S. typhimurium) detection (Das et al. 2009). Barreiros dos Santos et al. developed an antibody-functionalized ITO electrode for the detection of E. coliwith a dynamic range of 10–106 CFU/mL (Barreiros dos Santos et al. 2015). In addition to high conductivity, ITO is transparent, which presents various measurement advantages, including the ability to accurately correlate biosensor response with pathogen surface coverage (Aydın and Sezgintürk, 2017; Yang and Li, 2005). Transparent electrodes also enable in situ verification of target binding via microscopic techniques and offer compatibility with optical approaches, such as those based on optical stimulation (Wenzel et al. 2018). Carbon electrodes based on various allotropes of carbon, such as graphite and glass-like carbon, can also be classified as ceramic materials due to their mechanical properties (e.g., brittleness).\n\n2.1.3 Polymer electrodes\nPolymers have also been investigated as electrodes for pathogen detection. Polymers have various advantages, including tunable electrical conductivity, biocompatiblity, and environmentally stability. Polymer electrodes are also compatible with a range of biorecognition element immobilization techniques (Arshak et al. 2009; Guimard et al. 2007). Polymers also exhibit mechanical properties that enable electrode-tissue mechanical matching, an important consideration in the design of implantable and wearable biosensors. Polymer electrodes can be broadly classified as (1) conjugated polymer or (2) polymer composite.\nPolyaniline and polypyrrole have been the most commonly used conjugated polymers for pathogen detection due to their high conductivity in the doped state (Kaur et al. 2015). Moreover, polypyrrole has been shown to be biocompatible and exhibit affinity for methylated nucleic acids (Arshak et al. 2009). However, polyaniline films lose electrochemical activity in solutions of pH greater than 4, which presents a measurement challenge when considering samples of varying pH (Wan, 2008). Conjugated polymer electrodes commonly exhibit thin-film form factors and are deposited onto insulating substrates via layer-by-layer approaches, spin coating, or electrochemical polymerization (Xia et al. 2010). For example, Chowdhury et al. used a polyaniline electrode for detection of E. coli over a dynamic range of 102 to 107 CFU/mL (Chowdhury et al. 2012). Hai et al. and He et al. used organic transistors based on spin-coated poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) films for detection of human influenza A virus (H1N1) and E. coli, respectively (Hai et al. 2018; He et al. 2012).\nPolymer composite electrodes are often composed of a non-conducting polymer mixed with a conducting or semiconducting dispersed phase. Micro-particles and nanomaterials, such as graphite, Au nanoparticles (AuNPs), graphene, and carbon nanotubes (CNTs), have been commonly used as the dispersed phase (Dong et al. 2013; Lee et al. 2011; Lee and Jun 2016; Li et al. 2012; Viswanathan et al. 2012) in combination with various polymers, including chitosan (Güner et al. 2017), polyethylenimine (PEI) (Lee and Jun 2016), and polyallyamine (Viswanathan et al. 2012). For example, Viswanathan et al. developed a polyallylamine/CNT polymer composite electrode for the detection of E. coli, S. typhimurium, and Campylobacter via anodic stripping voltammetry over the dynamic range of 103 to 105 cells/mL (Viswanathan et al. 2012). A multicomponent polymer composite electrode of poly(amidoamine), CNTs, and chitosan layered with AuNPs enabled the detection of S. typhimurium (Dong et al. 2013). The detection limits associated with polymer composite electrodes are comparable to metallic and polymer electrodes and range from 1 to 103 CFU/mL (see Table 1). While polymer composite electrodes often contain nanomaterials, they are dispersed throughout the bulk of polymer, which is in contrast to the electrode nanostructuring techniques that occur at the electrode surface and are discussed in the following sections.\nPolymer electrode development has been, in part, driven by the need for flexible biosensors. For example, free-standing film electrodes and polymer electrodes on flexible substrates, such as paper, are now being examined for biosensing applications (Xu et al. 2019). Given conjugated polymers and polymer composites are compatible with 3D printing processes (Kong et al. 2014), polymer electrodes are also emerging as attractive candidates for wearable conformal (i.e., form-fitting) biosensors. While polymer electrodes typically exhibit planar form factors, such as thin films, they can also be constructed as nanowires and nanofibers, as discussed in the following section. A comprehensive discussion of biosensor LOD and dynamic range for all electrode materials is provided in Table 1, Table 2 .\nTable 2 Classification of electrochemical biosensors employing labels for pathogen detection in terms of: target, working electrode, biorecognition element, electrochemical method, limit of detection, electrochemical probe, and label or secondary processing step. Abbreviations: quartz crystal microbalance (QCM), electrochemical impedance spectroscopy (EIS), cyclic voltommetry (CV), plaque-forming unit (PFU), colony-forming unit (CFU), indium tin oxide (ITO), carbon nanotube (CNT), magnetic bead (MB), nanoparticle (NP), differential pulse voltammetry (DPV), square wave voltammetry (SWV), anodic stripping voltammetry (ASV), hemagglutination units (HAU), and median tissue culture infectious dose (TCID50).\nTarget Pathogen Working Electrode Biorecognition Element Electrochemical Method \u0026 Probe Limit of Detection Secondary Binding Step Reference\nE. coli ITO electrode anti-E. coli EIS; Fe(CN)63-/4- 6 × 105 cells/mL antibody/ALP conjugate label for amplification Yang and Li (2005)\nV. cholerae carbon/polystyrene electrode polyclonal anti-V.cholerae chrono-amperometry 105 cells/mL antibody-ALP conjugate label for amplification Rao et al. (2006)\nE. coli Au interdigitated microelectrode array polyclonal anti-E. coli EIS 2.67 × 106 cells/mL antibody-coated MBs for separation Varshney et al. (2007)\nV. parahaemolytic carbon electrode anti-V. parahaemolytic CV; thionine/hydrogen peroxide 7.37 × 104 CFU/mL antibody/HRP conjugate label for transduction Zhao et al. (2007)\nE. coli Au interdigitated microelectrode array polyclonal anti-E. coli EIS 7.4 × 104 CFU/mL antibody-coated MBs for separation and amplification Varshney and Li (2007)\nE. coli AuNPs on carbon electrode monoclonal and polyclonal anti-E. coli CV; ferrocenedicarboxylic acid/hydrogen peroxide 6 CFU/mL polyclonal antibody/HRP conjugate label for amplification Lin et al. (2008)\nS. aureus Au electrode anti-S. aureus amperometry; tetrathiafulvalene/hydrogen peroxide 370 cells/mL antibody/HRP conjugate label for amplification Escamilla-Gomez et al. (2008)\nS. typhimurium Au electrode monoclonal anti-S. typhimurium chrono-amperometry; tetramethylbenzidine dihydrochloride/hydrogen peroxide 21 CFU/mL anti-S. typhimurium polyclonal antibody/HRP conjugate label for amplification Salam and Tothill (2009)\nS. typhimurium graphite-epoxy composite electrode polyclonal anti-S. typhimurium amperometry 0.1 CFU/mL primary antibody-coated MBs for separation, secondary antibody/HRP conjugate label for amplification Liebana et al. (2009)\navian influenza virus (AIV) H5N1 Au interdigitated microelectrode array monoclonal anti-AIV-H5 EIS 0.26 HAU/mL antibody-coated MBs for separation Wang et al. (2010)\nStreptococcus pneumoniae Au electrode polyclonal anti-S. pneumoniae amperometry; tetrathiafulvalene/hydrogen peroxide 1.5 × 104 CFU/mL antibody-coated MBs for separation and bacteria immobilization, antibody/HRP conjugate label for amplification Campuzano et al. (2010)\nE. coli carbon-graphite electrode monoclonal anti-E. coli CV 7 CFU/mL antibody-coated MBs for separation, antibody/polyaniline label for amplification Setterington and Alocilja (2011)\nS. aureus MBs on Au electrode polyclonal anti-Protein A (S. aureus) amperometry; tetrathiafulvalene/hydrogen peroxide 1 CFU/mL antibody/Protein A/HRP conjugate for amplification Esteban-Fernandez de Avila et al. (2012)\navian influenza virus (AIV) H5N1 Au interdigitated microelectrode array monoclonal anti-AIV-H5, polyclonal anti-AIV-N1 EIS 103 EDI50/mL anti-AIV-H5 monoclonal antibody- coated MBs for separation, red blood cell label for amplification Lum et al. (2012)\nE. coli AuNPs/SiO2 nanocomposite on sulfhydryl chitosan/Fe(C2H5)2/C60 composite on carbon electrode monoclonal anti-E. coli CV; ferrocene 15 CFU/mL antibody/glucose oxidase/Pt nanochain conjugate label for amplification Li et al. (2013)\nC. parvum polypyrrole-coated carbon electrode polyclonal anti-C. parvum chrono-potentiometry; o-phenylenediamine/hydrogen peroxide 500 oocysts/mL antibody/HRP conjugate label for amplification Laczka et al. (2013)\nL. monocytogenes polymeric ion-selective membrane electrode anti-L. monocytogenes InlA aptamer potentiometry 10 CFU/mL aptamer/protamine label for transduction Ding et al. (2014)\navian influenza virus (AIV) H5N1 Au interdigitated electrode array anti-AIVH5N1 aptamer EIS 0.04 HAU/mL aptamer-coated MBs for separation, Concanavalin A/glucose oxide-coated AuNP labels for amplification Fu et al. (2014).\nL. monocytogenes interdigitated microelectrode array monoclonal and polyclonal anti-L. monocytogenes EIS 300 CFU/mL monoclonal antibody-coated MBs for separation, polyclonal antibody-coated AuNP label for secondary binding amplification Chen et al. (2015)\nE. coli carbon electrode polyclonal anti-E.coli chrono-amperometry 148 CFU/mL primary antibody-coated MBs for separation, secondary antibody-coated AuNPs for amplification Hassan et al. (2015)\navian influenza virus (AIV) H5N1 AuNPs on ITO microelectrode polyclonal anti-AIVH5N1 ASV 10 pg/mL antibody-coated MBs for separation and anodic stripping Zhou et al. (2015)\nE. coli Au interdigitated microelectrode array anti-E.coli EIS; Fe(CN)63-/4- 100 CFU/mL wheat germ agglutinin for amplification Li et al. (2015)\nE. coli carbon electrode monoclonal and polyclonal anti-E. coli DPV 10 CFU/mL monoclonal antibody-coated MBs for separation, polyclonal antibody-coated AuNP label for amplification Wang and Alocilja (2015)\nnorovirus nanostructured Au microelectrode concanavalin A lectin, polyclonal anti-norovirus CV, EIS; Fe(CN)63-/4- 35 copies/mL antibody-ALP conjugate label for amplification Hong et al. (2015)\nLegionella pneumophila carbon electrode polyclonal anti-L. pneumophila amperometry; hydroquinone/hydrogen peroxide 10 CFU/mL primary antibody- coated MBs for separation, secondary antibody/HRP conjugate label for amplification Martin et al. (2015)\nS. aureus carbon electrode anti-S.aureus aptamer ASV 1 CFU/mL primary aptamer-coated MBs for separation, secondary aptamer-coated AgNP label for anodic stripping Abbaspour et al. (2015)\nL. monocytogenes Au interdigitated microelectrode array monoclonal and polyclonal anti-L. monocytogenes EIS 160 CFU/mL monoclonal antibody-coated MBs for separation, polyclonal antibody-coated AuNP label for amplification Chen et al. (2016b)\nE. coli Au interdigitated microelectrode array polyclonal anti-E. coli CV, amperometry 52 CFU/mL antibody-coated, AuNP/glucose oxidase-modified MBs for separation and amplification Xu et al. (2016a)\nE. coli Au interdigitated microelectrode array anti- E. coli EIS 100 CFU/mL antibody-coated MBs for separation, antibody/glucose oxidase conjugate for amplification Xu et al. (2016b)\nS. typhimurium Au interdigitated microelectrode array monoclonal anti-S. typhimurium EIS 100 CFU/mL antibody-coated MBs for separation, antibody/glucose oxidase conjugate label for amplification Xu et al. (2016b)\nE. coli chitosan/CNT composite on carbon electrode polyclonal anti-E. coli CV; thionine/hydrogen peroxide 50 CFU/mL secondary antibody/HRP conjugate label enzyme-assisted reduction reaction Gayathri et al. (2016)\nS. typhimurium carbon electrode polyclonal and monoclonal anti-S. typhimurium DPV 100 cells/mL polyclonal antibody- coated MBs for separation, monoclonal antibody- coated AuNP label for amplification Afonso et al. (2016)\nE. coli Au electrode anti-E. coli EIS; Fe(CN)63-/4- 100 CFU/mL AuNP label for amplification Wan et al. (2016)\nL. monocytogenes Au interdigitated electrode array polyclonal anti-L. monocytogenes EIS 1.6 × 103 CFU/mL antibody-coated MBs for separation, antibody-coated AuNP label for amplification Wang et al. (2017)\nE. coli Au microelectrode monoclonal anti-E. coli LSV 39 CFU/mL antibody-coated MBs for separation, antibody/AuNP/nucleotide/CdSNP conjugate label for amplification Li et al. (2017)\nV. cholerae Au microelectrode polyclonal anti-V. cholerae LSV 32 CFU/mL antibody-coated MBs for separation, antibody/AuNP/nucleotide/PbSNP conjugate label for amplification Li et al. (2017)\navian influenza virus (AIV) H5N1 Au electrode anti-AIVH5N1, concanavalin A lectin CV 0.367 HAU/mL Concanavalin A- coated MB labels for amplification Zhang et al. (2017)\nhuman influenza A virus H9N2 carbon electrode polyclonal anti-influenza A virus M2 protein, fetuin A chrono-amperometry 16 HAU antibody-coated MBs for separation, fetuin A-coated AuNP label for amplification Sayhi et al. (2018)\nhuman enterovirus 71 (EV71) AuNPs on ITO electrode monoclonal anti-EV71 CV, EIS, colorimetry; Fe(CN)63-/4- 10 pg/mL antibody/HRP-coated MB labels for amplification Hou et al. (2018)\nE. coli Ag interdigitated microelectrode array melittin peptide EIS 1 CFU/mL MLT-coated MBs used for separation and bacteria immobilization Wilson et al. (2019)\nS. typhimurium Ag interdigitated electrode array melittin peptide EIS 10 CFU/mL MLT-coated MBs used for separation and bacteria immobilization Wilson et al. (2019)\nS. aureus Ag interdigitated electrode array melittin peptide EIS 110 CFU/mL MLT-coated MBs used for separation and bacteria immobilization Wilson et al. (2019)\nMiddle East respiratory syndrome corona virus (MERS-CoV) AuNPs on carbon electrode MERS-CoV antigen-antibody complex SWV; Fe(CN)63-/4- 400 fg/mL MERS CoV-antibody complex Layqah and Eissa (2019)\n\n2.1.4 Electrode form factor and patterning\nAs shown in Table 1, Au electrodes of various size and form factor have been used for pathogen detection. The use of complex masks and programmable tool paths with lithographic and 3D printing processes, respectively, also enable the fabrication of complex electrode geometries (Cesewski et al. 2018; Xu et al. 2017). In addition to complex form factor, lithographic processes, 3D printing processes, and assembly operations also enable the fabrication of electrode arrays through electrode patterning (Hintsche et al. 1994). Electrode arrays, including interdigitated microelectrodes and other patterned electrodes, have been developed in an attempt to enhance the sensitivity and multiplexing capability of biosensors. Interdigitated array microelectrodes (IDAMs) consist of alternating, parallel-electrode fingers organized in an interdigitated pattern. IDAMs have been shown to exhibit rapid response and high signal-to-noise ratio (Varshney and Li, 2009). As shown in Table 1, Au interdigitated microelectrode arrays are one of the most common electrode configurations for pathogen detection. For example, Dastider et al. usedinterdigitated Au microelectrode arrays for detection of S. typhimurium via EIS (see Fig. 4a) (Dastider et al. 2015). Ceramic electrodes, such as ITO, with interdigitated array designs have also been examined for the detection of S. typhimurium (Yang and Li, 2006). Mannoor et al. also examined interdigitated carbon-based electrodes for pathogen detection (Mannoor et al. 2012). The aforementioned emerging manufacturing processes are also used to construct electrode arrays that exhibit geometries other than interdigitated designs for electrochemical sensing applications. For example, Yang et al. used aerosol jet additive manufacturing to fabricate silver (Ag) microelectrode arrays (Yang et al. 2016a).\n\n2.1.5 Electrode nanostructuring\nTransducers with physical dimensions comparable to the target species have been widely investigated as a means of creating sensitive biosensors (Gupta et al. 2004; Pumera et al. 2007; Singh et al. 2010; Wei et al. 2009). Thus, electrodes ranging from micrometers to nanometers have been investigated for pathogen detection. While nanoscale planar electrodes are among the most commonly examined for pathogen detection (Hong et al. 2015; Peh and Li, 2013), the fabrication of nanoscale structures of conducting and semiconducting materials using a wide range of bottom-up and top-down nanomanufacturing processes, such as nanowires, has led to the investigation of nanostructured electrodes for pathogen detection (Patolsky and Lieber, 2005). Nanostructuring can be performed simultaneously with bottom-up electrode fabrication processes or as a post-processing step with top-down electrode fabrication processes.\nNanowire-based electrodes have been fabricated using a variety of engineering materials using both bottom-up and top-down nanomanufacturing processes (Hu et al. 1999; Yogeswaran and Chen, 2008). A detailed review of nanomanufacturing processes for nanowire fabrication can be found elsewhere (Hu et al. 1999). Nanowires can exhibit circular, hexagonal, and even triangular cross-sections. The nanowire aspect ratio, defined as the ratio of the length to width, often ranges from 1 to greater than 10 (Hu et al. 1999; Vaseashta and Dimova-Malinovska, 2005; Wanekaya et al. 2006).\nAs shown in Table 1, metallic and ceramic microwire- and nanowire-based electrodes have been examined for pathogen detection. For example, Wang et al. used nanowire-bundled TiO2 electrodes synthesized using a bottom-up wet chemistry process for the detection of Listeria monocytogenes (L. monocytogenes) (Wang et al. 2008). Shen et al. fabricated silicon nanowire-based electrodes using a chemical vapor deposition process for the rapid detection of human influenza A virus in an array-based format (Shen et al. 2012).\nAlthough polymer nanowires have been relatively more applied to the detection of non-pathogenic species (Travas-Sejdic et al. 2014), there appears to be potential for their application to pathogen detection. Polymer nanowires are also synthesized via bottom-up and top-down nanomanufacturing processes, including hard template methods, soft template methods, or physical approaches, but efficient, large-scale synthesis remains a challenge (Xia et al. 2010). A comprehensive summary of studies using micro- and nano-wire electrodes for pathogen detection is shown in Table 1. For example, Chartuprayoon et al. used Au microelectrode arrays modified with polypyrrole nanoribbons to detect cucumber mosaic virus (Chartuprayoon et al. 2013).\nThe topographical modification of electrode surfaces with micro- and nano-structured features beyond wire-like structures has also been investigated for pathogen detection. Electrode nanostructuring increases the electrode surface area without significantly increasing the electrode volume, thereby increasing the ratio of electrode surface area to fluid volume analyzed (Soleymani et al. 2009). Topographical modification of electrodes can also affect their mechanical and electrical properties. For example, electrochemical deposition of PEDOT on silicon electrodes reduces the electrode electrical impedance across a wide frequency range, which offers measurement advantages for neural monitoring and recording applications (Ludwig et al. 2006).\nElectrode nanostructuring for pathogen detection beyond the fabrication of nanowire-based electrodes has been accomplished primarily using bottom-up wet chemistry approaches and electrochemical methods. Among the wet chemistry approaches for electrode nanostructuring (Eftekhari et al. 2008), nanostructured electrodes are often fabricated by the deposition or coupling of nanoparticles to planar electrodes. For example, AuNPs are commonly deposited on planar electrodes to provide a nanostructured surface for biorecognition element immobilization. In such studies, the particles are bound to the planar electrode via physical adsorption processes (Attar et al. 2016) or chemical methods (Wang et al. 2013). In addition to AuNPs, CNTs have also been extensively investigated as potentially useful nanomaterials for electrode nanostructuring (see Table 1).\nDe Luna et al. found that high-curvature nanostructured Au microelectrodes exhibited a reduced extent of biorecognition element aggregation relative to that found on planar electrodes in DNA sensing studies using a combination of experimental studies and molecular dynamics simulations (see Fig. 3 a) (De Luna et al. 2017; Mahshid et al. 2016). A study by Chin et al. found that nanostructuring of carbon electrodes with carbon nanoparticles enhanced the electron transfer kinetics and current intensity of the electrode by 63% for the detection of Japanese encephalitis virus (Chin et al. 2017).\nFig. 3 Emerging transduction approaches associated with electrochemical biosensors for pathogen detection. a) A nanostructured Au microelectrode array with high curvature (De Luna et al. 2017). b) Cell-imprinted polymer (CIP) with ‘artificial’ biorecognition elements for detection of E. coli using electrochemical impedance spectroscopy (EIS) and the Fe(CN)63-/4- redox probe (Jafari et al. 2019).\nFig. 4 Measurement settings associated with electrochemical biosensor-based multiplexed pathogen detection. a) Microfluidic device with an interdigitated Au microelectrode array for continuous measurement of S. typhimurium (Dastider et al. 2015). b) Conjugated nanoparticles with two different biorecognition elements for E. coli and V. cholerae detection via voltammetry using Fe(CN)63-/4- (Li et al. 2017). c) Schematic of a microfluidic device with two separate spatial regions of biorecognition elements for E. coli and S. aureus (Tian et al. 2016).\nIn addition to fabricating nanostructured electrodes by coupling already processed nanomaterials to planar electrodes, electrochemical methods are also commonly used for bottom-up electrode nanostructuring processes and have been leveraged to fabricate nanostructured electrodes for pathogen detection. For example, Hong et al. fabricated a nanostructured Au electrode via electrochemical deposition of gold (III) chloride hydrates for the detection of norovirus in lettuce extracts (Hong et al. 2015). While the physical or chemical deposition of materials on planar electrodes provides a useful nanostructuring approach, introducing porosity to the electrode, such as nanoporosity, also enables electrode nanostructuring. For example, Nguyen et al. utilized nanoporous alumina-coated Pt microwires for the detection of West Nile virus (Nguyen et al. 2009).\nWhile studies have reported improved biosensor performance using electrode nanostructuring, such as improved sensitivity and LOD, it is prudent to consider the effect of nanostructuring on biorecognition element immobilization and target binding. For example, nanostructured electrodes that exhibit high-aspect-ratio structures and other three-dimensional structures have also been shown to enhance biomolecular steric hindrance effects, which may have implications for pathogen detection applications (Hong et al. 2015; Lam et al. 2012; Mahshid et al. 2017). There also remains a need to understand device-to-device and batch-to-batch variation in electrode nanostructuring quality. For example, it is presently unclear how the structure (e.g., topography, crystal structure) and material properties (e.g., electrical properties) of nanostructured surfaces vary among mass-produced electrodes. It is also unclear how such variance in nanostructuring quality affects the repeatability of biosensor performance.\n\n2.1.6 Integration of complementary transduction elements\nGiven the need for rapid and reliable measurements, biosensors that contain integrated electrodes and complementary transducers have also been examined for pathogen detection applications. For example, electrodes have been integrated with transducers that enable simultaneous fluid mixing and monitoring of molecular binding events (Choi et al. 2011). Biosensors composed of multiple transducers, referred to as hybrid biosensors, also offer unique opportunities for in situ verification of target binding as well as complementary analytical measurements (i.e., dual detection).\nHybrid electrochemical biosensors for pathogen detection have been developed by integrating electrodes with optical and mechanical transducers. Electrochemical-optical waveguide light mode spectroscopy (EC-OWLS) combines evanescent-field optical sensing with electrochemical sensing (Bearinger et al. 2003). EC-OWLS optically monitors changes and growth at the electrode surface to provide complementary information on surface reactions. EC-OWLS has been used to monitor the growth of bacteria (Nemeth et al. 2007) and could potentially be applied to selective detection of pathogens. Electrochemical-surface plasmon resonance (EC-SPR) combines SPR sensing capability based on binding-induced refractive index changes at the electrode-electrolyte interface with electrochemical sensing capability on the same electrode (Hu et al. 2008). This approach has been used for monitoring molecular binding events (Juan-Colas et al. 2017) and could potentially be applied to selective detection of pathogens.\nIn addition to their combination with optical transducers, hybrid electrochemical biosensors have also been combined with mechanical transducers. Mechanical transducers have included shear-mode resonators, such as the quartz crystal microbalance (QCM) and cantilever biosensors. Electrochemical-QCMs (E-QCMs) integrate mass-change and electrochemical sensing capabilities into a single platform. For example, Li et al. used an antibody-functionalized E-QCM for the detection of E. coli, which provided complementary cyclic voltammetry, EIS, and capacitive sensing measurements associated with the detection response (Li et al. 2011). Serra et al. used a lectin-modified E-QCM to detect E. coli using the biosensor's mass-change response (Serra et al. 2008).\nBesides providing complementary responses for verification of binding events (Johnson and Mutharasan, 2012, 2013a), hybrid biosensors for pathogen detection can also generate fluid and particle mixing at the electrode-electrolyte interface and in the bulk solution via acoustic streaming or primary radiation effects of mechanical transducers (Cesewski et al. 2018). Thus, secondary transducers can apply force to bound species, such as nonspecifically adsorbed background species or captured target species. For example, various studies have reported the removal of surface-bound biomolecules using mechanical transducers, such as shear-mode resonators or cantilever biosensors (Johnson and Mutharasan, 2014; Yeh et al. 2007). While the impediment or removal of nonspecifically adsorbed background species is a vital biosensor characteristic in pathogen detection applications that involve complex matrices, the regeneration of biosensor surfaces that contain specifically bound target species is essential for applications involving high-throughput characterization or process monitoring (e.g., bioprocesses or biomanufacturing processes) (Goode et al. 2015). Hybrid designs may also be useful for electrodes that exhibit a high extent of biofouling.\nIn addition to hybrid biosensor designs composed of combinations of electrodes with other transducers, hybrid biosensor-based assays for pathogen detection based on the combination of an electrochemical biosensor with a traditional bioanalytical technique have also been utilized. For example, electrochemical-colorimetric (EC-C) biosensing combines an electrochemical method and a colorimetric, fluorescent, or luminescent detection method. The electrode detects the presence of a target species, while the colorimetric transduction pathway enables quantification of the products associated with the reaction between the target and an active species (Hou et al. 2018). For example, Hou et al. used an EC-C approach based on a monoclonal antibody-functionalized AuNP-modified ITO electrode and dual-labeled magnetic beads for the detection of human enterovirus 71 (Hou et al. 2018). In that study, antibody- and horseradish peroxidase (HRP)-labeled magnetic nanobeads were introduced as a secondary binding step following exposure of the electrode to enterovirus-containing samples. Following the secondary binding step, the HRP-nanobead conjugates enabled colorimetric detection via monitoring of oxidative products produced by HRP-catalyzed redox reactions, while the functionalized electrode enabled electrochemical detection via chronoamperometry. Various techniques often rely on the use of optically-active labels for colorimetric, fluorescent, or luminescent sensing. The optical labels used in pathogen detection applications commonly include biological fluorophores, such as green fluorescent protein, non-protein organic fluorophores, such as fluorescein and rhodamine, and nanoparticles, such as quantum dots, including CdS, CdSe, and GaAs, among others (Mungroo and Neethirajan 2016; Pires et al. 2014). The use of such additional reagents to detect the target species is discussed further in the following sections.\n\n2.2 Biorecognition elements\nThe previous section discussed the transduction elements associated with pathogen detection using electrochemical biosensors. Given a biosensor is a device composed of integrated transducer and biorecognition elements, we next discuss the biorecognition elements used for selective detection of pathogens and corresponding immobilization techniques for their coupling to electrodes.\nBiorecognition elements for electrochemical biosensors can be defined as (1) biocatalytic or (2) biocomplexing. In the case of biocatalytic biorecognition elements, the biosensor response is based on a reaction catalyzed by macromolecules. Enzymes, whole cells, and tissues are the most commonly used biocatalytic biorecognition element. While enzyzmes provide biorecognition elements in various chemical sensing applications, they are often used as labels for pathogen detection applications and most commonly introduced via secondary binding steps. In the case of biocomplexing biorecognition elements, the biosensor response is based on the interaction of analytes with macromolecules or organized molecular assemblies. As shown in Table 1, Table 2, antibodies, peptides, and phages are the most commonly used biocomplexing biorecognition elements for pathogen detection. In addition to biomacromolecules, imprinted polymers have also been examined as biocomplexing biorecognition elements for pathogen detection using electrochemical biosensors.\n\n2.2.1 Antibodies and antibody fragments\nAntibodies and antibody fragments are among the most commonly utilized biorecognition elements for pathogen detection using electrochemical biosensors. Biosensors employing antibody-based biorecognition elements are commonly referred to as immunosensors. Given antibodies exhibit high selectivity and binding affinity for target species and can be generated for a wide range of infectious agents, antibodies are the gold-standard biorecognition element for pathogen detection. Antibodies contain recognition sites that selectively bind to antigens through a specific region of the antigen, referred to as an epitope (Patris et al. 2016). Antibodies can be labeled with fluorescent or enzymatic tags, which leads to the designation of the approach as label-based. While label-based approaches present measurement constraints associated with the use of additional reagents and processing steps (Cooper, 2009; Sang et al. 2016), antibody labeling may also alter the binding affinity to the antigen, which could affect the biosensor's selectivity. A detailed discussion of label-based biosensing approaches for pathogen detection has been reported elsewhere (Ahmed et al. 2014; Alahi and Mukhopadhyay, 2017; Bozal-Palabiyik et al. 2018; Leonard et al. 2003). A list of recent label-based approaches for pathogen detection using electrochemical biosensors, however, is provided in Table 2.\nWhile both monoclonal and polyclonal antibodies enable the selective detection of pathogens (Patris et al. 2016), they vary in terms of production method, selectivity, and binding affinity. Monoclonal antibodies are produced by hybridoma technology (Birch and Racher, 2006; James and Bell, 1987). Thus, monoclonal antibodies are highly selective and bind to a single epitope, making them less vulnerable to cross-reactivity. While monoclonal antibodies tend to have a higher degree of selectivity, they are more expensive and take longer to develop than polyclonal antibodies. Polyclonal antibodies are produced by separation of immunoglobulin proteins from the blood of an infected host (Birch and Racher, 2006). Polyclonal antibodies target different epitopes on a single antigen. While polyclonal antibodies exhibit increased variability between batches, they are relatively less expensive to produce than monoclonal antibodies and facilitate robust measurements in various settings (Byrne et al. 2009). Drawbacks to antibody use include high cost and stability challenges, such as the need for low-temperature storage. As shown in Table 1, Table 2, both monoclonal and polyclonal antibodies are used as biorecognition elements for pathogen detection. For assays involving secondary binding steps, monoclonal antibodies typically serve as the primary biorecognition element and are immobilized on the electrode, while polyclonal antibodies serve as the secondary biorecognition element and often facilitate target labeling. For assays that do not require secondary binding steps, polyclonal antibodies are also commonly used as immobilized biorecognition elements for pathogen detection. For example, Pandey et al. immobilized monoclonal anti-E. coli on a composite nanostructured electrode to detect E. coli across a wide dynamic range of 10 to 108 CFU/mL with a LOD of 3.8 CFU/mL (Pandey et al. 2017). Wu et al. used polyclonal anti-E. coli for detection of E. coli via amperometry that exhibited a LOD of 5 × 103 CFU/mL (Wu et al. 2016). Lin et al. used monoclonal antibodies for detection of avian influenza virus H5N1 in chicken swabs across a dynamic range of 2- 1 to 24 hemagglutination units (HAU)/50 μL using EIS and the ferri/ferrocyanide (Fe(CN)6 3 - /4-) couple as a redox probe (Lin et al. 2015). Luka et al. detected Cryptosporidium parvum (C. parvum) with a LOD of 40 cells/mm2 via capacitive sensing and Fe(CN)6 3 - /4- (Luka et al. 2019).\nAntibody fragments, such as single-chain variable fragments (scFvs), offer selectivity similar to antibodies, but they have the advantage of achieving relatively higher packing densities on electrode surfaces due to their relatively smaller size. For example, half-antibody fragments have been shown to improve biosensor sensitivity without the loss of selectivity, which warrants further investigation of reduced antibodies as biorecognition elements for pathogen detection applications (Sharma and Mutharasan, 2013). In addition to scFvs, Fabs, re-engineered IgGs, and dimers can also potentially be used as biorecognition elements for pathogen detection (Byrne et al. 2009).\n\n2.2.2 Carbohydrate-binding proteins\nCarbohydrate-binding proteins, such as lectins, also provide selective biorecognition elements for pathogen detection based on their ability to selectively bind ligands on target species. Peptide-based biorecognition elements are relatively low-cost, can be produced with high yield automated synthesis processes, and are modifiable (Pavan and Berti, 2012). For example, lectins have been investigated as biorecognition elements for pathogen detection through their ability to selectively bind glycosylated proteins on the surfaces of viruses and cells (Reina et al. 2008). Concanavalin A (ConA) lectin has been extensively investigated for E. coli detection (see Table 1) (Jantra et al. 2011; Saucedo et al. 2019; Xi et al. 2011; Yang et al. 2016b). While not yet widely investigated for pathogen detection using electrochemical biosensors, Etayash et al. recently showed that oligopeptides also provide attractive biorecognition elements for real-time biosensor-based detection of breast cancer cells (Etayash et al. 2015).\n\n2.2.3 Oligosaccharides\nTrisaccharides are carbohydrates that can selectively bind carbohydrate-specific receptors on pathogens. Thus, trisaccharide ligands have been used as biorecognition elements for pathogen detection using electrochemical biosensors. For example, Hai et al. used a hybrid E-QCM biosensor coated with hemagglutinin-specific trisaccharide ligands for the detection of human influenza A virus (H1N1) (Hai et al. 2017). The use of carbohydrates as biorecognition elements is limited in part due to the weak affinity of carbohydrate-protein interactions and low selectivity, which are currently mitigated through secondary interactions (Zeng et al. 2012).\n\n2.2.4 Oligonucleotides\nSingle-stranded DNA (ssDNA) is a useful biorecognition element for the detection of pathogens. While ssDNA is commonly used as a biorecognition element for DNA-based assays, ssDNA aptamers are commonly used for pathogen detection using electrochemical biosensors. Aptamers are single-stranded oligonucleotides capable of binding various molecules with high affinity and selectivity (Lakhin et al. 2013; Reverdatto et al. 2015). Aptamers are isolated from a large random sequence pool through a selection process that utilizes systematic evolution of ligands by exponential enrichment, also known as SELEX (Stoltenburg et al. 2007). Suitable binding sequences can be isolated from a large random oligonucleotide sequence pool and subsequently amplified for use. Thus, aptamers can exhibit high selectivity to target species (Stoltenburg et al. 2007). Aptamers can also be produced at a lower cost than alternative biorecognition elements, such as antibodies. Giamberardino et al. used SELEX to discover an aptamer for norovirus detection, which showed a million-fold higher binding affinity for the target than a random DNA strand that served as a negative control (Giamberardino et al. 2013). Iqbal et al. performed 10 rounds of SELEX to discover 14 aptamer clones with high affinities for C. parvum for detection in fruit samples (Iqbal et al. 2015). However, the use of aptamers as biorecognition elements has not yet replaced traditional biorecognition elements, such as antibodies, because of several challenges, such as aptamer stability, degradation, cross-reactivity, and reproducibility using alternative processing approaches (Lakhin et al. 2013).\n\n2.2.5 Phages\nPhages, also referred to as bacteriophages, are viruses that infect and replicate in bacteria through selective binding via tail-spike proteins (Haq et al. 2012). Thus, they have been examined as biorecognition elements for pathogen detection using electrochemical biosensors (Kutter and Sulakvelidze, 2004). Bacteriophages exhibit varying morphologies and are thus classified by selectivity and structure. A variety of bacteriophage-based electrochemical biosensors for pathogen detection can be found in Table 1. For example, Shabani et al. used E. coli-specific T4 bacteriophages for selective impedimetric detection studies (Shabani et al. 2008). Mejri et al. compared the use of bacteriophages to antibodies as biorecognition elements for E. coli detection (Mejri et al. 2010). In that study, they found that bacteriophages improved the water stability of the biosensor and increased the sensitivity by approximately a factor of four relative to the response obtained with antibodies based on EIS measurements (Mejri et al. 2010). In another study, Tolba et al. utilized immobilized bacteriophage-encoded peptidoglycan hydrolases on Au screen-printed electrodes for detection of L. innocua in pure milk with a LOD of 105 CFU/mL (Tolba et al. 2012). These results suggest that bacteriophages are potentially attractive biorecognition elements for water safety and environmental monitoring applications that require chronic monitoring of liquids.\n\n2.2.6 Cell- and molecularly-imprinted polymers\nGiven traditional biorecognition elements used in biosensing exhibit stability concerns, such as antibodies or aptamers, as discussed in Sections 2.2.1–2.2.4, there have been efforts to create engineered molecular biorecognition elements, such as scFvs. In contrast, materials-based biorecognition elements exploit the principle of target-specific morphology for selective capture (Pan et al. 2018; Zhou et al. 2019). The most common approach in materials-based biorecognition is based on cell- and molecularly-imprinted polymers (CIPs and MIPs, respectively) (Gui et al. 2018). CIPs and MIPs have been created using various processes, including bacteria-mediated lithography, micro-contact stamping, and colloid imprints (Chen et al. 2016a; Pan et al. 2018).\nAs shown in Fig. 3b, Jafari et al. used imprinted organosilica sol-gel films of tetraethoxysilane and (3-mercaptopropyl)trimethoxysilane (MPTS) for selective detection of E. coli using an impedimetric method (Jafari et al. 2019). Similarly, Golabi et al. used imprinted poly(3-aminophenylboronic acid) films for detection of Staphylococcus epidermidis (S. epidermidis) (Golabi et al. 2017). Despite the absence of a highly selective molecular biorecognition element, CIPs and MIPs exhibit selectivity when exposed to samples that contain multiple analytes (i.e., non-target species) (Golabi et al. 2017; Jafari et al. 2019; Qi et al. 2013). MIPs and CIPs are also of interest with regard to opportunities in biosensor regeneration. Common adverse effects of regeneration on biosensors that employ molecular biorecognition elements, such as irreversible changes in structure, are less likely to affect MIPs and CIPs. However, it is generally accepted that current CIPs and MIPs exhibit lower selectivity to target species than antibodies and aptamers due to reduction of available chemical selectivity (Cheong et al. 2013; Kryscio and Peppas, 2012; Yáñez-Sedeño et al. 2017).\n\n2.3 Immobilization and surface passivation\nGiven biosensors are self-contained devices composed of integrated transducer-biorecognition elements, the immobilization of biorecognition elements on electrodes is central to the design, fabrication, and performance of electrochemical biosensors for pathogen detection. The goal of immobilization is to achieve a stable, irreversible bond between the biorecognition element and the electrode with suitable packing density and orientation that maintains high accessibility and binding affinity to target species. Electrochemical biosensors for pathogen detection have typically used established techniques for preparation of the biorecognition layer. A detailed discussion of immobilization and surface passivation techniques is provided in Supporting Information.\n\n2.4 Thermodynamics of pathogen-biorecognition element binding reactions\nWhile the rate of biosensor response is typically governed by a mass transfer-limited heterogeneous reaction between the immobilized biorecognition element and target species, the net change in the biosensor response is dependent on the reaction thermodynamics. The binding affinity between a biorecognition element and target species, such as an antibody and antigen, is often reported in terms of a dissociation constant (K D), which has units of M. While the value of K D, solution = 1 nM provides a reasonable estimate for biosensor design considerations, such as understanding the mass transfer limitations associated with biosensor response (Squires et al. 2008), the binding affinity of antibodies can vary by orders of magnitude depending on the pathogen of interest and the clonality of the antibody. One important consideration when immobilizing biorecognition elements is potential effects of immobilization on binding affinity to the target. Traditionally, K D is obtained from a kinetic or thermodynamic analysis. Kinetic analyses measure association and dissociation rate constants (k a and k d, respectively) and enable calculation of K D as k d/k a. Thermodynamic analyses, such as calorimetric techniques, measure the binding enthalpy and entropy, which in turn provides the standard Gibbs free energy of the reaction (ΔG°), and thus, K A = K D −1 though the expression K A = exp(-ΔG°/RT), where R is the gas constant and T is the temperature. A detailed discussion of the kinetics and thermodynamics of biorecognition element-target binding reactions for solution- and surface-based biosensors is provided in Supporting Information."}

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