Single-Cell Phenotyping of Extracellular Electron Transfer via Microdroplet Encapsulation

Single-Cell Phenotyping of Extracellular Electron Transfer via Microdroplet Encapsulation | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Single-Cell Phenotyping of Extracellular Electron Transfer via Microdroplet Encapsulation Gina Partipilo , Emily K. Bowman , Emma J. Palmer , Yang Gao , Rodney S. Ridley Jr. , Hal S. Alper , Benjamin K. Keitz doi: https://doi.org/10.1101/2024.06.13.598847 Gina Partipilo 1 McKetta Department of Chemical Engineering, University of Texas at Austin , Austin, TX, 78712 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emily K. Bowman 2 Interdisciplinary Life Sciences Graduate Program, University of Texas at Austin , Austin, TX, 78712 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Emma J. Palmer 3 Civil, Architectural, and Environmental Engineering, University of Texas at Austin , Austin, TX, 78712 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yang Gao 1 McKetta Department of Chemical Engineering, University of Texas at Austin , Austin, TX, 78712 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rodney S. Ridley Jr. 1 McKetta Department of Chemical Engineering, University of Texas at Austin , Austin, TX, 78712 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hal S. Alper 1 McKetta Department of Chemical Engineering, University of Texas at Austin , Austin, TX, 78712 Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: halper{at}che.utexas.edu keitz{at}utexas.edu Benjamin K. Keitz 1 McKetta Department of Chemical Engineering, University of Texas at Austin , Austin, TX, 78712 Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: halper{at}che.utexas.edu keitz{at}utexas.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Electroactive organisms contribute to metal cycling, pollutant removal, and other redox-driven environmental processes. Studying this phenomenon in high-throughput is challenging since extracellular reduction cannot easily be traced back to its cell of origin within a mixed population. Here, we describe the development of a microdroplet emulsion system to enrich EET-capable organisms. We validated our system using the model electroactive organism S. oneidensis and describe the tooling of a benchtop microfluidic system for oxygen-limited processes. We demonstrated enrichment of EET-capable phenotypes from a mixed wild-type and EET-knockout population. As a proof-of-concept application, bacteria were collected from iron sedimentation from Town Lake (Austin, TX) and subjected to microdroplet enrichment. We observed an increase in EET-capable organisms in the sorted population that was distinct when compared to a population enriched in a bulk culture more closely akin to traditional techniques for discovering EET-capable bacteria. Finally, two bacterial species, C. sakazakii and V. fessus not previously shown to be electroactive, were further cultured and characterized for their ability to reduce channel conductance in an organic electrochemical transistor (OECT) and to reduce soluble Fe(III). We characterized two bacterial species not previously shown to exhibit electrogenic behavior. Our results demonstrate the utility of a microdroplet emulsions for identifying putative EET-capable bacteria and how this technology can be leveraged in tandem with existing methods. Introduction In the absence of oxygen, electroactive microorganisms export electrons out of the cell to reduce extracellular soluble and insoluble metal species in a process known as extracellular electron transfer (EET) 1 . This process is coupled to microbial growth, respiration, communication and sensing 2 . EET has been implicated in metal transport 3 , environmental remediation 4 – 7 , human health 8 – 11 and more. Furthermore, EET has been co-opted for the treatment of wastewater 12 , 13 , power generation in microbial fuel cells 14 – 19 , and biocatalysis 20 – 24 . Electroactive bacteria have been isolated from a variety of locations including in aquatic and soil environments 12 , 25 – 27 , the human gut microbiome 8 – 10 , 28 , and oral biofilms 29 . Traditional methods for identifying EET-capable microbes involve competitive respiration on poised iron electrodes, or other metal-based electron acceptors 12 , 30 – 39 . Unfortunately, it is difficult to establish genotype-phenotype relationship, especially in complex consortia, because EET occurs in the extracellular space. Bulk enrichments using poised electrodes avoid this challenge by selecting for biofilms 16 comprised of single or a handful of different electroactive species, but these experiments may not capture the complexity of the initial isolate 31 , 39 – 42 . A single species that forms a stable biofilm in bioelectrochemical cells can occlude other species from being incorporated into the biofilm altogether 43 . Such low throughput, bulk enrichment strategies require successful candidates outcompete other microbes for nutrients, electron acceptors, carbon sources, and access to the electrode. It also requires that a microbe be culturable in a laboratory environment. Consequently, bulk enrichment does not typically allow for more nuanced analysis of individual bacteria or the identification of EET in less fit, lower relative abundance, and unculturable microorganisms. Therefore, there is a need for high-throughput identification of single-cell EET behavior to identify novel electrogens in complex environments 32 , 44 , 45 . Cytometric techniques, such as flow cytometry and flow-assisted cell sorting, are powerful techniques for characterizing complex populations but require intracellular reporters and cannot be easily translated to extracellular processes. Accordingly, microdroplet emulsions have recently emerged as a method for characterizing extracellular processes including cell surface display, secretion, and other processes 46 . Individual microbes can be statistically isolated in microdroplet systems by diluting them in an aqueous solution and forming microdroplet emulsions via an oil countercurrent flow. Once formed, aqueous droplets can be cultured, merged with fresh aqueous solutions, and analyzed via fluorescence where they can be sorted into populations of low and high performers. Essentially, single-cell aqueous microdroplets function as individual reaction wells, capturing extracellular products or fluorescence 47 and muting cell-to-cell competition. Microdroplet screening of microbial consortia has previously been used for bioprospecting phenotypes of interest from environmental populations 48 – 50 , but to the best of our knowledge has not been used to identify electroactive organisms. This is likely due to the additional challenge of maintaining anaerobic conditions within a microdroplet screen and the lack of fluorescent reporters for EET. However, recently we detailed the coupling of Cu(I)-catalyzed Alkyne-Azide Cycloaddition (CuAAC) to electron transfer from S. oneidensis 24 , and saw that fluorescence from the cycloaddition of a small molecule could be used to quantify electron transfer. Here, we describe the development of a high-throughput microdroplet assay for characterizing EET. We detail the adaptation of CuAAC as a mechanism for EET-detection and the tooling of microdroplet instrumentation for use with anaerobic cultures via an oxygen-limited protocol. Our system was developed utilizing a monoculture of model electroactive organism Shewanella oneidensis MR-1, which allowed us to assess assay performance. A mixed population of EET- deficient strains and EET-capable strains of S. oneidensis facilitated fluorescent activated droplet sorting (FADs) to enrich the EET-capable strain from the mixed population. Additionally, a defined population mixture of E. coli Nissle 1917, S. cerevisiae BY4741, and S. oneidensis MR-1 demonstrated that signal could be detected even from a complex sample. As a test application, we identified EET-capable microbes from an environmental sample. We saw a distinctly enriched EET-capable population, which had upregulation of iron reduction genes compared to the initial consortium. Two bacteria, Cronobacter sakazakii and Vagococcus fessus , identified by our microdroplet screened were assessed in monoculture, and displayed marked electrogenic behavior. Herein, we describe the development of a microfluidic method for identifying extracellular reduction by EET-capable bacteria that is does not rely on reduction coupled to competitive growth. Results Optimization of CuAAC fluorescent probe assay for applications in microdroplets We recently utilized fluorescence from the EET-driven synthesis of a cycloaddition probe, CalFluor488 51 , to assess EET activity from the bacteria S. oneidensis via Cu(I)-catalyzed alkyne- azide cycloaddition (CuAAC) 52 . We determined that the rate of copper reduction was directly correlated to EET flux via the well-defined EET-protein pathway in S. oneidensis (the Mtr- pathway), and that fluorescence was tied to electron transfer. As a result, we recognized that the system could be used as a fluorescent sensor for EET, and we hypothesized that the fluorescence readout could be adapted into a screen for identifying electroactive microbes in microfluidic droplets. The quenched to fluorescent transition upon cycloaddition of the CalFluor488 51 probe is ideal for microfluidic application as the unreacted emulsion has little background fluorescence ( Figure 1 , Figure S2). First, we confirmed that neither the reaction nor the fluorescence output was inhibited by the reagents required for a stable emulsion. Traditionally, both a rich media and low- to-no organic solvents are required for stabilizing emulsions as well as supporting microbial growth within droplet emulsions 46 . Our previous use of S. oneidensis to perform CuAAC was performed in minimal media with DMSO as a co-solvent 52 , and which in initial screens yielded droplet instability. Anaerobic reactions performed with S. oneidensis in a 96-well plate showed that nearly all DMSO could be omitted apart from the small volume of co-solvent in the CalFluor488 stock. Neither cell growth nor conversion was hindered under these conditions even with increased concentrations of reagents. (Figure S1). A similar control performed in Lysogeny broth (LB broth) in the presence of fluorinated oil with or without the biosurfactant present (Sphere fluidics), showed a slightly decreased, but still large fluorescence response. Download figure Open in new tab Figure 1. Microdroplet assay set up and schematic. The reaction scheme for performing oxygen-limited CuAAC via microbial respiration in a microfluidic system. Inset is an image of S. oneidensis -containing microdroplets image prior to sorting. Having confirmed that the reagents necessary for a stable emulsion did not interfere with cell growth or CuAAC activity, we moved forward to adapting the assay to the microdroplet system. Abiotic emulsions were created with starting material and chemically-synthesized product. The emulsions were mixed in known ratios and analyzed via fluorescent activated droplet sorting (FADS) to determine the ability to distinguish reacted product from background (Figure S2). We found that the system could detect differences in the population including the 10% reacted emulsion from the 90% unreacted emulsion which is the target level of cellular encapsulation during a screen (1 filled droplet in every 10). Together, these benchtop assays suggested the CuAAC chemical system could be utilized as a microbially-driven fluorescent readout for microdroplet emulsion sorting. Oxygen-limited benchtop microdroplet system enabled Cu(I)-catalyzed Alkyne-Azide Wild-type S. oneidensis can convert CalFluor488, to a fluorescent cycloaddition product in approximately 5 hours when combined and sealed with the appropriate Cu, ligand, and alkyne source 52 . We began by emulsifying an aqueous reaction containing aerobically grown S. oneidensis at an OD 600 of 6 x 10 - 5 , calculated such that one in every 10 droplets was filled 53 , using the fluorinated oil and biosurfactant as the oil phase. However, we measured no distinguishable fluorescent signal after 24 hours under these conditions. Hypothesizing that the dilute cells could not withstand the simultaneous stress of encapsulation in the presence of Cu(II/I) and small molecules, we adapted a previously developed method for utilizing biosensors in microdroplets 46 . Specifically, we utilized “pico-injection” which flows a previously formed emulsion through a microfluidic chip and introduces a fresh aqueous solution into each droplet by applying a low voltage to merge the emulsion with the aqueous pico-injection solution. Previously, microdroplet emulsions have been pico-injected to add cell-based biosensors 46 , cell lysis reagents 54 , 55 , or fluorogenic enzyme substrates 56 – 59 into existing emulsions. We hypothesized this mechanism would provide robustness for withstanding the stress of both the microdroplet system and the Cu(II/I) and small molecules (Figure S3). We moved to pico-inject the CalFluor488, Cu(II), ligand, and alkyne after the emulsion had been created and allowed to stabilize for a full day. The 5X concentrated pico-injection solution was flowed into the emulsion utilizing a Pico-Mix TM chip (Sphere Fluidics) and merged under a low voltage of 0.15V where it was diluted to the desired concentration. This facilitated growth within the droplets, where the cell concentration within the emulsion increased, but each droplet contained genetically identical cells 56 with no droplet-to- droplet competition for resources. However, we measured no detectable fluorescent signal even under pico-injection scheme ( Figure 2a ). We posited that the emulsion was too oxygen-permeable, and that oxygen was preventing a shift to anaerobic metabolism in S. oneidensis as well as inhibiting the CuAAC reaction. Download figure Open in new tab Figure 2. Oxygen-limited conditions allow for detection using of S. oneidensis in microdroplet system. a. Histogram of aerobic FADS of S. oneidensis b. Histogram of an oxygen-limited FADS of S. oneidensis . c. Histogram of an oxygen-limited FADS of ΔMtr-pathway S. oneidensis d. Histogram of an oxygen-limited FADS of Δ mtrC Δ omcA Δ mtrF S. oneidensis. e. Histogram of an oxygen-limited FADS of S. oneidensis wild-type and mtrC Δ omcA Δ mtrF S. oneidensis mixed in a 1:1 ratio prior to encapsulation. f. Histogram of an oxygen-limited FADS of S. oneidensis wild-type and S. oneidensis ΔMtr-pathway mixed in a 1:1 ratio prior to encapsulation. g. Histogram of an oxygen-limited FADS of S. oneidensis wild-type, S. cerevisiae BY4741, and E. coli Nissle 1917 mixed in a 30:35:35 ratio prior to encapsulation. h. Representative image of emulsion from ( g.) prior to sorting with merged bright-field and fluorescence. i. Representative image of emulsion from ( f.) prior to sorting with merged bright-field and fluorescence. To overcome this challenge, we performed subsequent experiments in an oxygen-limited environment. All oils and buffers were sparged and prepared anaerobically. Tubing was attached, and the syringes were sealed within an anaerobic chamber to create a closed environment. A 12- mL collection syringe was similarly prepared with a small, cushion of fluorinated oil (500 µL) and anaerobic atmosphere (6 mL of 97% N 2 , 3% H 2 ), then sealed with a needle and heat-sealed tubing. The solutions and oils were removed from the chamber and loaded onto the syringe pumps under a positive pressure (Figure S3). Once the system had equilibrated and the emulsion or pico- injection was stable in size, the collection syringe could be used to collect the emulsion. As predicted, this oxygen-limited set up allowed S. oneidensis MR-1 encapsulated within droplets to perform CuAAC, which could be detected using our system ( Figure 1 , Figure 2b ). The fluorescence in the emulsion was clearly visible under fluorescent microscopy (Figure, 1 inset) and the ratio of fluorescent to non-fluorescent droplets approximated the predicted encapsulation ratio, one out of every 10 droplets filled. The histogram demonstrated that a higher percentage of the droplet population (y-axis) exhibited fluorescence (x-axis) and indicated we were able to detect the fluorescence on the FADS system ( Figure 2a and 2b ). In total, these results indicate that the bacteria can performs sufficient EET within the microdroplet system to catalyze CuAAC and that we can detect the extracellular reduction via fluorescence. CuAAC for the detection of Extracellular Electron Transfer in microdroplets Next, to confirm that signal was tied to EET, an EET-deficient strain of S. oneidensis (ΔMtr- pathway) lacking all outer membrane cytochromes was subjected to droplet encapsulation and fluorescent screening. As expected, no significant fluorescence was detected ( Figure 2c ). To confirm the cells were still alive within the droplets, a voltage was applied, and the emulsion was broken to harvest the cells. After plating the cells onto agar plates, lawns were recovered for the sorted indicating the cells were alive within the droplets, despite their lack of signal (Figure S4). Furthermore, a knockout of only the terminal EET-proteins (MtrC, MtrF, and OmcA) resulted in a similar histogram without appreciable signal ( Figure 2d ). Having demonstrated that CuAAC within microdroplets could distinguish between homogeneous populations in individual emulsions, we next examined a mixed culture of wild-type and EET-deficient strains of S. oneidensis ( Figure 2e and 2f ). A 1:1 ratio of wild-type MR-1 to knockout was mixed immediately prior to encapsulation. Immediately prior to sorting, microscopy revealed that approximately one out of every two filled droplets fluoresced ( Figure 2i ), indicating that that ΔMtr-pathway strain could be differentiated from wild-type S. oneidensis by fluorescence. During FADS of the mixture of Δ mtrC Δ mtrF Δ omcA and wild-type S. oneidensis , a subsection of the high fluorescent population was collected, and the emulsion was broken and plated on agar plates. Sections of the sorted emulsion were subjected to a colorimetric Fe(III/II) reduction assay 20 , and after 24 hours 9 colonies from each section were analyzed to determine if they had reduced Fe(III) to Fe(II). The unsorted population yielded 4 out of 9 colonies within one standard deviation of wild-type MR-1, while the sorted population (1-2V) had 7 colonies of MR-1, an enrichment of 1.75-fold over the starting material (Figure S5). These results validated that the microdroplet system could enrich EET-active strains in a mixed population. Wild-type could be enriched via fluorescence despite the fact that the Δ mtrC Δ omcA Δ mtrF strain is known to have spurious background reduction, due to the presence of the MtrA and MtrD which can still interact with soluble metals 22 , 52 . Based on the success at differentiating between two strains of the same species, we investigated the ability to detect an EET-capable bacteria within a synthetic multi-species co-culture. In picking our proof-of-concept consortia, we chose Eschericia coli Nissle 1917, Saccharomyces cerevisiae BY4741, and S. oneidensis MR-1 for their availability and ability to be grown at 30 °C, anaerobically. Each microbe was grown separately overnight, and mixed in a known ratio (35%, 35%, 30% respectively) immediately prior to encapsulation. We detected fluorescence even from this mixed population ( Figure 2g ) suggesting that our system could be used to characterize more complex samples. Under microscopy, visible growth was detected in approximately 10% of the microdroplets, which was the target encapsulation percentage. Of those with visible growth, approximately one in every three fluoresced ( Figure 2h ), indicating that even in more complex consortia, there is detectable differences within a population. These data indicate that emulsions made from homogenous populations are distinctly different and simple model consortia of very similar cells can be fluorescently sorted to isolate EET-capable phenotypes. Single-cell analysis of environmental samples reveals EET-capable bacteria Next, to evaluate the microdroplet system for a more complex environmental sample and to compare to a more traditional screen for EET, bulk enrichment, we interrogated a sediment- associated mixed microbial community collected from Town Lake in Austin, TX. To compare the efficacy of our microdroplet method relative to alternative methods for screening for EET activity, part of the sample was anaerobically incubated with a solid-phase Fe(III) source to select for electroactive, EET-capable microbes. The bulk enrichment experiment included lactate as a carbon source and iron-rich sediment as the electron acceptor. Sterilized sediments were isolated within a 3.5 kDa MWCO dialysis membrane tube to limit the contact between bacteria and iron minerals and avoiding biofilm formation 58 , 60 – 62 . The bulk enrichment culture was monitored for both pH and soluble Fe(II) concentration overtime ( Figure 3b ) and displayed an increase in soluble Fe(II) from 0.069 mg/L to 0.8 mg/mL over the course of 5 days indicating that this biological sample contained EET-capable organisms. Samples from before and after enrichment were harvested and subjected to 16S sequencing ( Figure 3 , samples I and II). Download figure Open in new tab Figure 3. Iron sediment gathered from Town Lake yields Fe(III)-reducing bacteria. a. A schematic outlining the experimental procedure, and where samples were gathered for 16S sequencing. Briefly, bacteria were collected from iron sedimentation. This starting material was sequenced and split into a bulk enrichment and a microdroplet enrichment. The microdroplet samples was sequenced pre- and post-sorting. Two different gates of the sorted enrichment were collected and subjected to sequencing. Inset of droplets is a representative image of the lake water emulsion prior to sorting and scale bar represents 100 µm. b. Bulk enrichment data monitoring pH and Fe(II) concentration over time. c . Histogram of microdroplet emulsion and gating of samples IV. and V. Histogram represents relative proportion of population after system has stabilized and collected for 87k droplets. Sorted populations were collected for a minimum of 500 droplets collected. d. Relative genus distributions of samples with greater than 0.05% prevalence. e. Top 20 genus’s as describe in d. 16S sequencing allowed for identification of high-performing targets The other section of split sediment-derived sample was subjected to the microfluidic screen where a clear sub-population exhibited improved fluorescence ( Figure 3a ), as indicated by a tailing end of high performers ( Figure 3c ). To evaluate the effect of microdroplet formation, both the initial sediment-derived population (Sample I) and the population immediately prior to sorting (Sample III) were both collected for 16S sequencing. To evaluate the effect of sorting the population by fluorescence, two portions of the population were sorted out, wide (greater than 2.5 V) (Sample IV) and tight (greater than 3.1V) (Sample V), gated and were also collected for 16S sequencing. The 16S sequencing data was normalized by the number of reads per sample, and compared to the starting, untreated lake water. From the bulk enrichment (Sample II), 68 bacteria were identified and 20 (29.4%) of these had been previously thought to been capable of EET 26 , 31 , 37 , 44 , 63 – 66 . The remaining 48 could indicate “cheaters”, bacteria that survived in bulk but were not actively reducing iron upon harvest. The bulk enrichment favored the Rheinheimera and Dechloromonas and Arcobacter genera. In the microdroplet system, when compared to the initial lake water, 45 species were enriched by encapsulation alone. A significant portion of the population that was present in the unsorted microdroplets screen were members of the Psuedamonas genus. However, the sorted droplet populations were enriched and favored Exiguobacterium , Acinetobacter , and Aeromonas genera, indicating that the sorting selects for reduction as opposed to selecting exclusively for survival within droplets. We identified a total of 56 bacterial species that were identified in the fluorescently sorted droplets indicative of an ability to reduce Cu(II) to Cu(I). Of the 56 bacterial species identified in the droplet sorted population, 16 (28.6%) had been previously reported as potentially EET-capable 26 , 31 , 37 , 44 , 63 – 66 . However, of the 366 species bacteria detected in the starting material (or in a subsequent enrichment), only 49 (13.4% of the starting material) were putative EET-capable bacteria and, only 29 (57.1% of the previously reported) of those survived encapsulation prior to sorting. This indicated that some were either unable to withstand the sediment to microdroplet transition or did not survive the initial reconstitution from iron sedimentation. Given that only 29 putative EET-capable species survived encapsulation, 16 (55.2%) of the putative EET bacteria within the pre-sort droplets were identified by our screen indicating that the screen was effective for detecting EET activity ( Figure 4b ). Download figure Open in new tab Figure 4. Analysis of species similarity between enrichment mechanisms. a. Percent of species containing one or more genes related to iron-regulation pathways as determined via HMM with FeGenie 67 . b. Venn diagram describing the relative species distributions and overlap between samples. c . Principal component analysis of the genus data represented in Figure 3d with a k =2. Interestingly, when comparing between the microdroplet enrichment (Samples IV and V) and bulk enrichment (Sample II) only 13 bacteria were enriched under both conditions. Only 6 of these shared species had been previously referenced as EET-capable: Acinobacter johnsonii, Aeromonas salmonicida, Aeromonas veronii , Ralstonia solanacearum, an unidentified Aeromonas species and a Citrobacter species, and were identified by both droplet and bulk screens. 7 other species were identified by both methods but had never been characterized as having the ability to perform EET ( Figure 4b ). A principal component analysis ( k =2) revealed that the starting material, droplets, and the bulk enrichment were clustered separately ( Figure 4c ), indicating that the populations of these samples were distinctly different. Finally, Rarefaction curves (Figure S6) suggested a drop in diversity between the starting material and the encapsulation, as well as the encapsulation and the sorted samples indicating that there was a bottleneck that decreased sample diversity. Together, this 16S sequencing data indicates that we enriched for a distinct sub-section of the population in the microdroplet FADS that potentially represents a phenotype with the ability to perform EET. FeGenie analysis of sorted populations reveal differing enrichments To further probe the features of the populations identified by the bulk and the microdroplet enrichments, example genomes from each enriched bacteria (for which a fully sequenced genome was available) were analyzed using FeGenie to identify iron-trafficking genes. 67 This program looks for homology using a hidden Markov model (HMM) against known iron-related protein pathways. We used it to identify whether a given bacterium within a population has one or more genes related to a known iron-redox pathway. Looking at four of the gene clusters related to iron reduction, the microdroplet system enriched for bacteria containing known pathways involved in iron reduction (CymA, MtrCAB, OmcF, OmcS, OmcZ, FmnA-dmkA-fmnB-pplA-ndh2-eetAB-dmkB 44 , 68 – 71 ) , notably including those most similar to what is found in S. oneidensis 1 , 72 – 75 . Compared to the initial consortium, 3.23-times more bacteria had one or more genes related to this specific iron reduction pathway, nearly 10% of the genomes analyzed ( Figure 4a ). The program also screens for genes related to iron reduction pathways where the there is no homolog to the terminal mtrC . These are characterized as “related to iron reduction” because they represent a potential, but incomplete pathway 67 – 71 . None of the genomes analyzed from the droplet enrichment fell into this category; however, these bacteria containing “related to iron reduction” genes (MtrCB, MtrAB, MtoAB-MtrC) were enriched over 1.65-fold over the initial consortia in the bulk enrichment. These data probe into the possible molecular mechanism of enrichment, indicating that a terminal protein for metal-interaction may potentially be required in the microdroplet system. However, given that the mechanisms of EET are diverse, these data only capture genes prevalent in previously characterized electrogens. Interestingly, in the bulk enrichment, we measured an increase in presence of genomes containing one or more genes related to iron oxidation. We believe this was likely due to reduction of Fe(III) to Fe(II) in the bulk enrichment, which could be used for iron oxidation by other bacteria. Combined, these data suggest competing mechanisms of enrichment that likely may contribute to the low number of shared bacteria between the enrichment samples ( Figure 4a ). Additionally, this indicates that the microdroplet enrichment was uniquely distinct, and potentially represented a more specific population of electrogens compared to the bulk enrichment which may select for interspecies collaborations or sub-sets of EET-mechanisms that represent multiple simultaneous phenotypes. Monoculture characterization of high-performers from microdroplet enrichment reveal putative electrogens Finally, we determined whether select species isolated in the highest performing droplets sort were EET-capable or if we were enriching for alternative phenotypes. To examine this, two bacteria identified solely in the highest sort (tight sort, Sample IV) gating of the lake water microdroplet enrichment, Cronobacter sakazakii and Vagococcus fessus , were characterized for their ability to perform EET. Neither bacteria was enriched in the bulk enrichment nor had they previously been reported as EET-capable, although C. sakazakii has been known to have iron-transport and acquisition related machinery that is vital to its survival 76 , 77 . Each bacterium was grown in its’ preferred culture media. As a benchmark, E. coli MG1655 and S. oneidensis MR-1 were measured concurrently in each respective media and evaluated for their EET-activity. The bacteria were incubated in an organic electrochemical transistor (OECT) under continuous electrode bias conditions to examine their ability to reduce insoluble electron acceptors. OECTs can translate and amplify biological signals into electrical responses where direct or shuttling EET reduces the conductance of the p-type channel 78 . OECTs have a faster response and require smaller volume compared to traditional electrochemical cells 78 . Conductance was measured under constant bias voltages (V DS = -0.05V, V GS = 0.2V). Both C. sakazakii and V. fessus exhibited a marked drop in conductance over the course of a 24 h period; however, only V. fessus outperformed E. coli in these devices ( Figure 5a and 5b ). To obtain a precise measurement of the electroactive activities, the transfer curves were plotted against the Ag/AgCl reference electrode (RE) (Figure S8). A more positive effective gate voltage (V G EFF ) or a more negative measured source electrode potential (V S ) indicates a reduction after incubation with the bacteria 78 . Next, to determine their ability to reduce soluble Fe(III), a Fe(III/II) reduction assay and growth on Fe(III) was collected for each bacteria. Both bacteria reduced Fe(III) to Fe(II) over 20 hours as measured by the colorimetric ferrozine assay 79 ( Figure 5c and 5d ). Neither bacteria appeared to require Fe(III) strictly as an electron acceptor for anaerobic growth; however, we were unable to establish culturing conditions for V. fessus without the presence of at least 0.1% sheep’s blood ( Figure 5e and 5f , Figure S7). In tandem these results suggest that these bacteria are capable of reducing soluble Fe(III) to Fe(II) and that, under our conditions, V. fessus exhibits similar EET-levels to S. oneidensis in reducing insoluble electron acceptors at the gate and channel of the OECT devices. Download figure Open in new tab Figure 5. Examination of putative electrogens C. sakazakii and V. fessus . a.-b. Current over time from bacterially generated de-doping of a PEDOT:PSS-coated electrode. The I DS /I DS0 curve was prepared with an initial inoculum OD 600 =0.01. Curve for a. was collected in Media 3 for all species, and curve for b. was collected in a 1:50 mixture of Media 260:LB broth. c.-d. Fe(II) generation curves measured via ferrozine colorimetric assay over time. Initial inoculum of OD 600 =0.01 was from the same bacterial stock used to generate a. and b. respectively and run in the same respective media. Cells were supplemented with 5 mM Fe(III) at beginning of assay. e.-f. Growth curves for C. sakazakii and V. fessus with and without Fe(III) supplementation. Data represents n=3 ± standard deviation. Discussion Microdroplet emulsions address key challenges of single-cell sorting when studying an extracellular process such as EET. Common methods for characterizing phenotypic differences within a population, such as FACS 80 , cannot be used for studying extracellular processes as signal cannot be attributed back to a source cell. In a microdroplet system, each cell is spatially isolated within its own pico- to nano- liter aqueous reaction vessel, allowing for smaller reaction sizes and higher sample numbers compared to a flask or even 96-well 81 or 384-well plates traditionally used to study EET 79 , 82 . However, microdroplet systems require new, potentially unconventional assay development requirements 52 . A notable barrier was the requirement of a fluorescent signal that correlates to EET-activity. Our recent work linking Cu(I)-catalyzed cycloaddition to EET in S. oneidensis provided the opportunity to use a fluorescent probe for cycloaddition as an indirect measure for EET. Two further obstacles to success in developing a microdroplet screen for EET were cell survivability in droplet formation and oxygenation. The first was overcome by adapting a pico-injection protocol 46 , and visible growth within droplets was seen ( Figure 2h and 2i ). The second challenge, involving oxygenation, required a more unique solution. Many microdroplet system designed elements aim to introduce oxygen and oxygenation at multiple steps, including the oxygen-permeable fluorinated oil. To circumvent this problem, an oxygen-limited benchtop method was developed by degassing the starting solutions and plumbing the microfluidic system under a positive pressure ( Figure 1 , Figure S3, and Figure 2a-c ). This created a closed system that could be maintained through collection into a nitrogen-filled syringe, and anaerobic bacteria could be grown in the droplet system. The ability to retrofit a bench-top system for oxygen-limited screens is advantageous in the study of anaerobic bacteria. This could prove to be useful in the study of anaerobic gut bacteria, of which some have been seen to be EET-capable, but their role is still poorly understood. The amendments to the protocol allowed for a fluorescence output from CuAAC within S. oneidensis filled- droplets. CalFluor488 51 is uniquely suited to the microdroplet system, as it undergoes a quenched to fluorescent conversion, allowing for low background in unreacted droplets. Additionally, the reaction is catalyzed by Cu(I), which can amplify signal and improve sensitivity as even a small amount of reduction can produce enough catalyst to yield fluorescent signal. While the droplet histograms are not diagnostic, populations can be sorted based on fluorescent output and sorting parameters were selected and recorded based on fluorescently gating the output. Utilizing this method, wild-type S. oneidensis and an EET-deficient knockout (Δ mtrC Δ mtrF Δ omcA ) were mixed and screened for the ability to perform EET. We measured an approximately 2-fold enrichment of the wild-type in the sorted population, validating our ability to enrich for EET. The Δ mtrC Δ mtrF Δ omcA knockout is not a perfect negative control ( Figure 2d ), as it can still perform some reduction due to the remaining MtrA and MtrD proteins. Background reduction is something we and others have seen before 20 , 52 , 69 , 79 , 83 ; however, our enrichment for MR-1 indicates that despite this background reduction we can capture electrogens in a mixed environment. Stricter sorts involving multiple sequential FADS could be used to isolate a more selective subset of bacterial species, where the sorted population would be collected and subjected to additional rounds of sorting. Microscopy images ( Figure 2h and 2i ) confirm that bacteria are growing within the microdroplets, and that within a mixed population a high fluorescent signal is not tied to solely cell growth but corresponds to the relative population density of the EET-capable phenotype. Microfluidic systems are ideal for avoiding microbe-microbe competition for resources which can mute studies of their phenotypic behavior 47 , 49 , 80 . This is best illustrated by examining the prevenance of iron oxidation capable genomes in the lake water enrichment, which is increased in the bulk enrichment but decreased for the droplet system ( Figure 4a ). These data could be a result of the bulk enrichment where multiple species interact and affect the presence or absence of each other: as Fe(II) builds up due to the presence of iron reducers, there is an off-target advantage for iron-oxidizers which contain genes similar to MtoAB and Cyc2 (cluster 3) which have been implicated in iron oxidation 67 . If this is the case, it highlights a potential advantage of the microdroplet system as no genes from this cluster were identified from the example genomes in the droplet enriched population. When examining the genus distribution of the microdroplet screen of the lake water, encapsulation alone (prior to FADS) enriched notably for Psuedomonas (76.1% of the encapsulated population). These results are not surprising given that certain Psuedomonas species are known to secrete Cu-binding small molecules and the assay exposes the bacteria to a relatively high concentration of copper 84 – 86 . Consequently, there is likely a growth advantage in this particular genus due to co-encapsulation with Cu. Interestingly, despite the large percentage of Psuedomonas in the droplet population, no Pseudomonas was detected in any of the fluorescent sorted populations indicating that it was not actively catalyzing CuAAC despite its growth-based advantage. These results highlight the utility of the microfluidic system, despite the growth-based advantage observed with Pseudomonas , growth is separated from function in a way that cannot easily be done in traditional bulk EET-screens. Many traditional enrichments tie growth to function; however, our system allows the sorting to overcome the initial encapsulation bias. Consequently, the droplet system may be a powerful tool for identifying non-growth related EET, especially where mediated electron transfer may not necessarily be tied to the central carbon metabolism 25 . We identified a number of interesting bacteria from droplet sorting of an environmental sample. Despite not previously being reported as EET-capable, several bacteria were identified by both bulk and droplet enrichment, indicating that they may have electrogenic behavior. Acinetobacter lwoffii , was originally isolated from an arsenic-polluted environment. It has been reported to co- exist with many heavy metal compounds, and was enriched in both droplet and bulk enrichments 87 . Granulicatella adiacens , is notoriously difficult to culture under laboratory conditions 88 , but has been reported in several cases of infection surrounding metallic hip replacements 89 . Our microdroplet screen identified a large increase in G. adiacens ; however, it was present in a much- lower quantities in the bulk enrichment perhaps indicating its difficulty growing under typical laboratory conditions. Further, Exiguobacterium indicum , which has been shown to bio-reduce hexavalent chromium 90 , was similarly isolated by our screen and the bulk enrichment. E. indicum is also referenced as having the ability to reduce azo dyes 91 , an ability shared by Shewanella species and sometimes attributed to EET 92 , 93 . Additionally, known EET-capable organisms such as Ochrobactrum species, were enriched only in the microdroplet system where we had over 1000- fold enrichment 19 . To validate species identified solely the microdroplet screen, we selected two species that were not previously reported as EET-capable, C. sakazakii and V. fessus , and analyzed them in monoculture. They both identified solely in the top 1.8% of performers (Sample V, tight gate), and we examined their ability to reduce Fe(III) and current. C. sakazakii is known to infect infant formula and has previously been the focus of study regarding its iron acquisition systems and ability for ferric iron to disrupt biofilm formation 76 , 77 , but the ability to generate current or perform EET has not been reported. To the best of our knowledge, there has not been a report of V. fessus displaying any iron-specific, heavy metal tolerance, or current generation. In monoculture, V. fessus was able to reduce the current at a rate comparable to that of S. oneidensis . Both bacteria generated Fe(II) from soluble Fe(III), although C. sakazakii only marginally outperformed the negative control of E. coli . Interestingly, it appears that neither bacteria, under our culturing conditions, was able to utilize Fe(III) as its sole terminal electron acceptor. Notably, we were unable to culture V. fessus without the presence of at least 0.1% sheep’s blood. Even when attempting to substitute with soluble Fe(III) citrate, the bacteria would not grow (Figure S7). These data in tandem with their identification in our microdroplet screen reinforces that we are able to look for non-growth-related electron transfer via microdroplets. We believe this indicates electrogenic behavior of these bacteria, particularly strong electrogenic behavior from V. fessus and potentially weak electrogenic behavior from C. sakazakii . While there are some commonly accepted bacteria known to perform EET: S. oneidensis , L. monocytogenes, G. sulfurreducens ; to the best of our knowledge, there is not a master list or completely agreed upon set of conditions for what may be considered an “EET-capable” or Fe(III)- reducing bacteria. While there are sets of genes and behaviors that indicate ability to perform EET, very few bacteria have been expressly tested for this phenotype and few agree what constitutes as an appropriate test for EET 11 , 12 , 34 , 94 – 96 . When compiling a literature search, including review articles, of EET-capable organisms existing lists often had little to no overlap between others. Of the articles we examined, the average number of species shared between the lists was 3 with standard deviation of 6 species 26 , 31 , 37 , 44 , 63 – 66 , indicating that we needed to additional tools for examining our data. For this reason, we utilized the FeGenie program 67 , which looks at potential iron-related genes and their relative abundance within a set of genomes as an indirect method for looking for EET-ability. This program was designed to be used with full genome sequencing not with 16S data. As a result, example genomes were gathered from the NIH National Center for Biotechnology Information (NCBI), and we were limited to only to the representative genomes available. These example genomes most likely do not fully capture the information potential in the data set or the power of the FeGenie program. For that reason, we limited identification to the presence of one or more genes in each pathway as opposed to genomic frequency of homologous genes. Of the 366 starting bacteria, full genome sequencing was only available for 222 genomes through NCBI with many being members of a specific genus but not of a known species name. This highlights the power of partnering a phenotype screen with full genome sequencing that could fully utilize the capabilities of FeGenie. However, the diverse nature of electrogens and lack of consensus emphasizes that genotyping alone is incomplete as a mechanism of identifying EET- capable bacteria. This underscores the necessity of a phenotype screen to further inform the genotype-phenotype relationship. The potential difference selective pressures between the droplet and bulk enrichment indicates that while this microdroplet screen is useful particularly at identifying S. oneidensis -like EET, for which it was developed, it should serve to complement traditional EET screening such as growth on electrodes 31 , 45 , 97 , 98 , dialysis enrichments 60 , 99 , 100 , growth on iron 34 , 35 , 101 , and more. This is likely due to a few reasons: the requirement for survival in the emulsion, the relatively high concentration of Cu within the droplets, and the use of Cu(II) rather than Fe(III) for an extracellular electron acceptor. Notably, current methods for identifying EET activity tend to rely on growth-related behavior, such as the ability to use Fe(III) as a sole terminal electron acceptor, or the ability to outcompete other bacteria within a bulk enrichment or in biofilm 8 , 29 , 102 – 104 . There exists a need to study both weak electrogens, and non-growth associated EET for their complex role in the environment, mineral-microbe interactions, and microbe-microbe interactions 25 , 30 , 44 , 105 . Furthermore, some bacteria exhibit EET only under certain conditions which are not always captured in vitro , such as during pathogenesis 106 or under specific substrate and potential conditions 107 . Further work focused on increasing cell viability and detecting Fe(III) reduction as opposed to Cu(II) reduction would further aid in investigating electrogens in complex environments. In summary, this work represents a step towards high-throughput methods for identifying specific types of EET and for isolating bacteria based on phenotype in a microdroplet emulsion. Materials and Methods CalFluor 488 (Click Chemistry Tools), alkyne-PEG4-acid (Click Chemistry Tools), copper(II) bromide (CuBr 2 , Sigma-Aldrich, 99%), 2-(4-((bis((1-(tert-butyl)-1H-1,2,3-triazol-4- yl)methyl)amino)methyl)-1H-1,2,3-triazol-1-yl)acetic acid (BTTAA, Click Chemistry Tools >95%), sodium DL-lactate (NaC 3 H 5 O 3 , TCI, 60% in water), sodium fumarate (Na 2 C 4 H 2 O 4 ,VWR, 98%), EPES buffer solution (C 8 H 18 N 2 O 4 S, VWR, 1 M in water, pH = 7.3), potassium phosphate dibasic (K 2 HPO 4 , Sigma-Aldrich), potassium phosphate monobasic (KH 2 PO 4 , Sigma-Aldrich), sodium chloride (NaCl, VWR), dimethyl sulfoxide (cell culture grade, Sigma-Aldrich), ammonium sulfate ((NH 4 ) 2 SO 4 , Fisher Scientific), magnesium(II) sulfate heptahydrate (MgSO 4 ·7H 2 O, VWR), trace mineral supplement (ATCC), casamino acids (VWR), Lysogeny Broth (BD), OptiPrep (Sigma-Aldrich), Pico-Gen TM 60 x 60 single aqueous (Sphere Fluidics), Pico-Wave TM (Sphere Fluidics), Pico-Break TM 1 (Sphere Fluidics), Pico-Mix TM (Sphere Fluidics), Pico-Surf TM (Sphere Fluidics), Medical Grade Polyethylene Micro Tubing / 0.015" ID x 0.043" OD (+/- .003") = .38mm ID x 1.09mm OD (+/- .076mm) / (100’ Roll) (Scientific Commodities), Cronobacter sakazaki (Farmer et al.) Iverson et al. (ATCC 29544), Vagococcus fessus Hoyles et al. (ATCC BAA-289), defibrillated sheep’s blood (Lampire), Tryptic Soy Broth (BD 211825), Nutrient Broth (BD cat 234000), Agar (BD), disodium;4-[3-pyridin-2-yl-6-(4- sulfonatophenyl)-1,2,4-triazin-5-yl]benzenesulfonate hydrate (Ferrozine, VWR) All media components were autoclaved or sterilized using 0.2 μm PES filters. Oxygen-Limited Encapsulation of S. oneidensis Overnight cultures were grown in a Coy Anaerobic Glovebox containing a humidified atmosphere at 3% hydrogen content and the balance nitrogen. The cultures were started by picking a single colony into argon-sparged LB broth supplemented with 20 mM sodium lactate (2.85 µL of 60% w/w sodium lactate per 1 mL culture). After overnight growth anaerobically at 30°C, cell cultures were diluted to an OD 600 of 0.00006 into a solution of 40 mM lactate, 80 mM fumarate, 20 wt% OptiPrep in LB broth. Inside of the anaerobic chamber, 1 mL of the cell solution was loaded into the aqueous syringe (BD). The tubing was prepared by heat-sealing one end, and the other was loaded onto a needle, inside of the anaerobic glove box, the needle was attached to an empty syringe and pressure was pulled three times and held for 30 seconds each time and then vented after each round to remove any O 2 present in the tubing. Additionally, 10 mL of argon-sparged 2.5% 008-FluoroSurfactant in Pico-Wave TM was loaded into the oil syringe (SGE) and capped with a sealed, sparged needle and tubing. A collection syringe was prepared by pulling 6 mL of the Coy Anaerobic Glovebox atmosphere and capped with a sealed, sparged needle and tubing. A PicoDroplet Single Cell Encapsulation System (Sphere Fluidics) was used. All sealed syringes were removed from the anaerobic chamber. Each syringe was loaded under a 100 µL/h positive pressure before clipping the heat-sealed end and connecting to the 60 × 60 droplet maker (Pico- Gen) chip. To make the emulsion, the syringe pumps were increased to 1000 µL/h (aqueous) and 1200 µL/h (oil). The system was allowed to calibrate before cutting and plumbing the collection syringe (BD). After encapsulation, emulsions were incubated at 30 °C 24 h to allow for growth within the droplets. Encapsulation of Mixed population Overnight cultures were grown in a Coy Anaerobic Glovebox containing a humidified atmosphere at 3% hydrogen content and the balance nitrogen. The cultures were either started by picking a single colony into argon-sparged LB broth supplemented with 20 mM sodium lactate (2.85 µL of 60% w/w sodium lactate per 1 mL culture) or 20 mM dextrose (for E. coli Nissle 1917 and S. cerevisiae BY4741). After overnight growth anaerobically at 30°C, cell cultures were diluted to an OD 600 of 1.8 x 10 5 (MR-1), 7.8 x 10 5 (EcN), and 0.008 ( S. cer ) into a solution of 40 mM lactate, 40 mM glucose, 80 mM fumarate, 20 wt% OptiPrep in LB broth. These reflect a loading density overall of 1 in 10 droplets, and the loading ration of 30:35:35 (MR-1:EcN: S. cer ). The remaining encapsulation is the same as that of S. oneidensis outlined above. Oxygen-Limited Pico-Injection of CuAAC components A 5X Cu(I)-catalyzed Alkyne—Azide Cycloaddition solution (70 µM CalFluor 488, 2 mM Alkyne-Peg4-acid, 2 mM Cu:BTTAA (1:6)) was prepared from a 3.2 mM stock of CalFluor 488 in DMSO, 8 mM stock of CuBr 2 in water, 48 mM stock of BTTAA in water and a 4 mM stock of Alkyne-Peg4-Acid in water in a Coy Anaerobic Glovebox containing a humidified atmosphere at 3% hydrogen content and the balance nitrogen. Into a 1 mL syringe, 200 µL of the solution was loaded into the aqueous syringe (BD) and capped with a sealed, sparged needle and tubing. Additionally, 10 mL of argon-sparged Pico-Wave TM was loaded into the oil syringe (SGE) and capped with a sealed, sparged needle and tubing. A collection syringe (12 mL Manufacterer) was prepared by pulling 6 mL of the Coy Anaerobic Glovebox atmosphere, adding in 500 µL of 008- Fluorosurfactant (5%) in Pico-Wave TM , and capped with a sealed, sparged needle and tubing. The droplets were then transferred to a 1 mL syringe (BD) and capped with a sealed, sparged needle and tubing. All sealed syringes were removed from the anaerobic chamber, loaded onto the syringe pumps set at 15 µL/h (aqueous), 100 µL/h (droplets) and 1200 µL/h (oil) before cutting off the sealed end and plumbing into a Pico-Mix TM chip. The system was allowed to calibrate before cutting and plumbing the collection syringe (PGE). After picoinjection, emulsions were incubated at 30 °C 24 h to allow for growth within the droplets. Fluorescent Sorting for heterogeneity For droplet sorting, a Single Cell Assay and Isolation platform (Sphere Fluidics) with a 488 nm laser 244 and 525/50 emission filter (GFP) was used. PMT setup of the system was set to a gain of 0.8 or 1 such that an appropriate spread was seen without maxing out the detector for both PMT 1 (GFP channel/bandpass 525/50) and PMT 2 (large bandpass 650/150). Peak detection minimum was set at 0.07 and maximum at 100. The minimum width was set to 0.18 and maximum set to 100. Sorting gates were determined based on population distribution and manually drawn above 1 V(MR-1), 2.1V, 3.5V (Lake water), 4.25V (Lake water enrichment round 2). The top 3000 droplets were then collected using an applied voltage of 0.3V. After sorting, the emulsion was broken with 100 μL Pico-Break (Sphere Fluidics) and with extracted or cultured. Culturing occurred in LB broth supplemented with 20 mM lactate at 30 °C overnight. Each sample was split, freezing 500 µL as a cryogenic stock, and diluting 10 µL into the anaerobic chamber to start the creation of the next generation of sort. Lake water enrichment Environmental and post-droplet enriched samples were enriched in an anaerobic bulk system microcosom similar to those previously described 61 . Briefly, 10 mL of sediment containing lake water containing a sediment-associated mixed microbial community was inoculated into a 250- mL anaerobic bulk systems filled with filter-sterilized lake water. The cells were provided with lactate at 0.1mM as a carbon source, and iron-containing sediments were isolated in 3.5 kDa dialysis tubing. The cells were allowed to grow for 5 days and redox potential, pH, and aqueous Fe(II) concentrations were measured daily. 16S Sample Extraction and sequencing DNA samples from both pre- and post-enriched samples via the oxygen-limited droplet protocol and bulk sedimentation enrichments were purified via the AllPrep DNA/RNA kit from Qiagen per manufacturer’s instructions. Samples were sent to Mr. DNA for microbial taxonomic analysis. Mr. DNA utilizes 515F-806R (V4 region) primers, and classification is determined using QIIME 108 . Taxonomic classification from Mr. DNA was utilized at the genus and species level for all subsequent analysis. Species richness for each sample was estimated using a rarefaction curve based on species level counts. The rarefaction curve data was generated using the ‘rarecurve’ function in the vegan (v. 2.6.4) 109 library with default settings. Taxonomic proportions were calculated by dividing counts from each individual taxa by the total number of read counts for that sample. We estimated a species to show prospective ‘enrichment’ for downstream testing within a sample based on the following criteria: if a certain taxa was above 0.015% of the initial population, and also showed a higher proportion in the compared population of interest. We estimated this initial population detection cutoff based on the initial library size and the consistency of the number of enrichments for a specified sample. Taxa of interest were also selected if they showed notable non-zero detection within samples of interest, while showing no observance in reference samples. Species enrichments were used to obtain a list of genomes to later be used for FeGenie. Analyses were performed using custom scripts in python and R. Taxonomic barplots and rarefaction plot were generated using ggplot2 (v. 3.5.0) 110 . The EET species database was generated via Genomic sequences from these taxa were collected for any full genome or 16S (full or V4) sequences available on NCBI from the following citations 18 , 19 , 26 , 31 , 44 , 63 – 65 , 65 , 66 , 105 , 111 . Plots were generated in R. FeGenie Example genomes were obtained using NCBI and chosen based on the longest whole genome sequencing available for a given genome. If the species level was not specified, the most appropriate example genome was chosen from the genus. Each genome was exported and FeGenie was run on Python3 and the code was available for download on GitHub. Results were then processed to normalize the number of genes per genome analyzed and represented as percentages. These graphs were created using Python3 and the code is available in the SI. Relative fold- enrichment was calculated by normalizing the enriched population by the starting population. OECT device operation and electrochemistry Two different types of electrolytes were used according to the bacterial strains. Medium 3 was used with Cronobacter sakazakii , S. oneidensis MR-1, and E. coli . A mixture of medium 260 and Luria-Bertani (LB) broth at 1:50 was used with Vagococcus fessus , S. oneidensis , and E. coli . All electrolytes were purged with argon bubbling for at least 15 minutes before use. Before each experiment, the OECT slides and PDMS layer were autoclaved separately and subsequently assembled in the biosafety cabinet. The fabrication of devices is outlined further in the Supplementary Information. To ensure an oxygen-free environment, the OECT experiments were carried out inside the nitrogen-filled glovebox. Electrochemical measurements were conducted with the multichannel potentiostat (MultiPalmSens4, PalmSens BV). Prior to inoculation, OECTs were equilibrated in the glovebox with abiotic electrolytes for 3 days. For the inoculation process of the OECTs, all cells were grown anaerobically overnight in their respective media. Grown cell cultures cell density (OD 600 ) measured, the cells were concentrated and resuspended to the intended OD600 at 0.1 with the respective purged media, forming the inoculum culture. Subsequently, the inoculum cultures were used to inoculate OECTs at a 1:9 ratio of cell culture to the OECT electrolyte, achieving an intended inoculation OD 600 at 0.01. During the OECT experiment, the gate voltage VGS and drain voltage VDS were constantly biased at 0.2 V and -0.05 V, respectively. Transfer curve measurements, were conducted 24 hours after inoculation, with the V DS kept at-0.05 V while the V GS scanned from -0.1 V to 0.6 V with a scan rate of 20mV/s. The open circuit potentials (OCP) of the source and gate electrode potentials were measured against the Ag/AgCl pellet reference electrodes (RE) (550010, A-M Systems). The Ag/AgCl electrodes were directly inserted into the OECT chamber without using any salt bridges. Ferrozine Assay Aerobic cultures of S. oneidensis, E. coli , C. sakazakii , and V. fessus were created in each bacteria’s preferred rich media (LB, LB, Media 3 and Media 260 respectively). The next day, cultures were diluted 1/100 into anaerobic media and allowed to grow overnight. Each bacteria was washed via centrifugation at 6000 rcf and decanted before the supernatant was exchanged for the reaction media (Media 3 for C. sakazakii and Media 260:LB 1:50 for V. fessus ). Cultures of S. oneidensis and E. coli were also washed and reconstituted in each media to be run concurrently. Ferrozine was dissolved into degassed, anaerobic growth media such that the final concentration of the assay can be run at 1 mg/mL. 6.57 µL of 190 mM Fe(III)citrate was added in addition to 10 µL of cells directly from aerobic overnights into a 250 µL reaction in a clear-bottom U shaped Grenier 96- well plate (final Fe(III) concentration of 2 mM). A calibration curve of Fe(II) sulfate stocks in sterile water were inoculated into control wells for each media containing ferrozine from 12 µM- 0 µM. Each media had a cell-free control inoculated with Fe(III) but no cells. The reduction of Fe(II) was measured using the calibration curve minus the background reduction via the media blank. The complete 96-well plate was sealed anaerobically and placed into an incubated plate reader. Readings were taken every 3 minutes at 562 nm. The mixed cultures of Δ mtrC Δ mtrF Δ omcA and wild-type MR-1 were grown overnight in Shewanella Basal Media (SBM) supplemented with 0.05 % casamino acids and Wolfe’s Mineral Solution. The cells were used without washing and subjected to the same treatment in SBM with casamino acids and mineral solution. Growth on Fe(III) To a 96-well plate, 6.57 µL of 190 mM Fe(III)citrate was added in addition to 10 µL of cells directly from aerobic overnights into a 250 µL reaction in a clear-bottom U shaped Grenier 96- well plate in the anaerobic growth media (Media 3 for C. sakazakii, and 1:50 Media 260:LB for V. fessus ). Fe(III)-free wells were made with the addition of water in the place of Fe(III). Media controls were included for blanking the readings. The complete 96-well plate was sealed anaerobically and placed into an incubated plate reader. Readings were taken every 3 minutes at 600 nm. Author Contributions G.P., E.K.B., H.S.A., and B.K.K. conceived the project and research design. G.P. and E.B. designed and performed microdroplet emulsion experiments. G.P. ran CuAAC control experiments and analyzed putative electrogens. E.J.P. ran bulk enrichment and extracted DNA for sequencing. Y.G. ran OECT experiments and characterized responses. R.R. and G.P analyzed 16S sequencing results. H.S.A. and B.K.K. supervised research. G.P., H.S.A., and B.K.K wrote the manuscript with input from all authors. Competing Interests The authors declare no competing interests. Materials & Correspondence Request for materials and correspondence should be addressed to H.S.A. and B.K.K. Data Availability Experimental data supporting the findings of this study will be available through the Texas Data Repository. Acknowledgements Collections of genomes were downloaded from the NIH with assistance by Kenneth C. Sabjel and Pedro Sobral. S. oneidensis Δ mtrC Δ omcA Δ mtrF and ϕ,Mtr were generously provided by Prof. Jeffrey Gralnick (U. Minnesota). The photo of Town Lake in Figure 3 was taken by Emma J Palmer. This research was financially supported by the Welch Foundation (Grant F-1929, B.K.K.), the National Institutes of Health under award number R35GM133640 (B.K.K.), an NSF CAREER award (1944334, B.K.K.), and the Air Force Office of Scientific Research under award number FA9550-20-1-0088 (B.K.K.). G.P. and E.J.P were supported through National Science Foundation Graduate Research Fellowships (Program Award No. DGE-1610403). The Sphere Fluidics system was funded by a Cooperative Agreement (W911NF-17-2-0091) between Army Research Laboratory (ARL) and UT Austin. Opinions, conclusions, interpretations, and recommendations are those of the authors and are not necessarily endorsed by the US Army. The mention of trade names or commercial products does not constitute endorsement or recommendation for use by the Department of the Army or the Department of Defense. 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