Microwell arrays were fabricated and characterized at the Center for Nanophase Materials Sciences User Facilities Division, Office of Basic Energy Sciences, U.S. Department of Energy. Financial support for this work was provided through the Oak Ridge National Laboratory Director&#39;s Research and Development Fund. The authors would also like to thank the J. Mougous Laboratory (University of Washington, Seattle, WA) for the supply of P. aeruginosa strains used in these studies.

<ol><li>Zhou, J., Deng, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stochasticity%2C+succession%2C+and+environmental+perturbations+in+a+fluidic+ecosystem%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci%22%5BJournal%5D)">Stochasticity, succession, and environmental perturbations in a fluidic ecosystem.</a> Proc Natl Acad Sci. 111, E836-E845 (2014).</li>
<li>Valm, A. M., Welch, J. L. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Systems-level+analysis+of+microbial+community+organization+through+combinatorial+labeling+and+spectral+imaging%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci+USA%22%5BJournal%5D)">Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging.</a> Proc Natl Acad Sci USA. 108 (10), 4152-4157 (2011).</li>
<li>Satoh, H., Miura, Y., Tsushima, I., Okabe, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Layered+structure+of+bacterial+and+archaeal+communities+and+their+in+situ+activities+in+anaerobic+granules%5BTitle%5D)+AND+%22Appl+Environ+Microbiol%22%5BJournal%5D)">Layered structure of bacterial and archaeal communities and their in situ activities in anaerobic granules.</a> Appl Environ Microbiol. 73 (22), 7300-7307 (2007).</li>
<li>Kim, H. J., Boedicker, J. Q., Choi, J. W., Ismagilov, R. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Defined+spatial+structure+stabilizes+a+synthetic+multispecies+bacterial+community%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci+USA%22%5BJournal%5D)">Defined spatial structure stabilizes a synthetic multispecies bacterial community.</a> Proc Natl Acad Sci USA. 105 (47), 18188-18193 (2008).</li>
<li>Nunan, N., Wu, K., Young, I. M., Crawford, J. W., Ritz, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Spatial+distribution+of+bacterial+communities+and+their+relationships+with+the+micro-architecture+of+soil%5BTitle%5D)+AND+%22FEMS+Microbiol+Ecol%22%5BJournal%5D)">Spatial distribution of bacterial communities and their relationships with the micro-architecture of soil.</a> FEMS Microbiol Ecol. 44, 203-215 (2003).</li>
<li>Grundmann, G. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Spatial+scales+of+soil+bacterial+diversity+-+The+size+of+a+clone%5BTitle%5D)+AND+%22FEMS+Microbiol+Ecol%22%5BJournal%5D)">Spatial scales of soil bacterial diversity - The size of a clone.</a> FEMS Microbiol Ecol. 48, 119-127 (2004).</li>
<li>Langenheder, S., Lindstrom, E. S., Tranvik, L. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Structure+and+Function+of+Bacterial+Communities+Emerging+from+Different+Sources+under+Identical+Conditions%5BTitle%5D)+AND+%22Appl+Environ+Microbiol%22%5BJournal%5D)">Structure and Function of Bacterial Communities Emerging from Different Sources under Identical Conditions.</a> Appl Environ Microbiol. 72 (1), 212-220 (2006).</li>
<li>Camp, J. G., Kanther, M., Semova, I., Rawls, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Patterns+and+Scales+in+Gastrointestinal+Microbial+Ecology%5BTitle%5D)+AND+%22Gastroenterology%22%5BJournal%5D)">Patterns and Scales in Gastrointestinal Microbial Ecology.</a> Gastroenterology. 136 (6), 1989-2002 (2009).</li>
<li>Renner, L. D., Weibel, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Physicochemical+regulation+of+biofilm+formation%5BTitle%5D)+AND+%22MRS+Bull%22%5BJournal%5D)">Physicochemical regulation of biofilm formation.</a> MRS Bull. 36 (5), 347-355 (2011).</li>
<li>Wessel, A. K., Hmelo, L., Parsek, M. R., Whiteley, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Going+local%3A+technologies+for+exploring+bacterial+microenvironments%5BTitle%5D)+AND+%22Nat+Rev+Microbiol%22%5BJournal%5D)">Going local: technologies for exploring bacterial microenvironments.</a> Nat Rev Microbiol. 11 (5), 337-348 (2013).</li>
<li>Stacy, A., McNally, L., Darch, S. E., Brown, S. P., Whiteley, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+biogeography+of+polymicrobial+infection%5BTitle%5D)+AND+%22Nat+Rev+Microbiol%22%5BJournal%5D)">The biogeography of polymicrobial infection.</a> Nat Rev Microbiol. 14 (2), 93-105 (2015).</li>
<li>Hansen, R. R., Shubert, K. R., Morrell-Falvey, J. L., Lokitz, B. S., Doktycz, M. J., Retterer, S. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Microstructured+block+copolymer+surfaces+for+control+of+microbe+adhesion+and+aggregation%5BTitle%5D)+AND+%22Biosensors%22%5BJournal%5D)">Microstructured block copolymer surfaces for control of microbe adhesion and aggregation.</a> Biosensors. 4 (1), 63-75 (2014).</li>
<li>Hansen, R. R., Hinestrosa, J. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Lectin-functionalized+poly%28glycidyl+methacrylate%29-+block+-poly%28vinyldimethyl+azlactone%29+surface+scaffolds+for+high+avidity+microbial+capture%5BTitle%5D)+AND+%22Biomacromolecules%22%5BJournal%5D)">Lectin-functionalized poly(glycidyl methacrylate)- block -poly(vinyldimethyl azlactone) surface scaffolds for high avidity microbial capture.</a> Biomacromolecules. 14 (10), 3742-3748 (2013).</li>
<li>Timm, C. M., Hansen, R. R., Doktycz, M. J., Retterer, S. T., Pelletier, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Microstencils+to+generate+defined%2C+multi-species+patterns+of+bacteria%5BTitle%5D)+AND+%22Biomicrofluidics%22%5BJournal%5D)">Microstencils to generate defined, multi-species patterns of bacteria.</a> Biomicrofluidics. 9 (6), (2015).</li>
<li>Keymer, J. E., Galajda, P., Muldoon, C., Park, S., Austin, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Bacterial+metapopulations+in+nanofabricated+landscapes%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci+USA%22%5BJournal%5D)">Bacterial metapopulations in nanofabricated landscapes.</a> Proc Natl Acad Sci USA. 103 (46), 17290-17295 (2006).</li>
<li>Zhang, Q., Lambert, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Acceleration+of+Emergence+of+Bacterial+Antibiotic+Resistance+in+Connected+Microenvironments%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Acceleration of Emergence of Bacterial Antibiotic Resistance in Connected Microenvironments.</a> Science. 333 (6050), 1764-1767 (2011).</li>
<li>Friedlander, R. S., Vlamakis, H., Kim, P., Khan, M., Kolter, R., Aizenberg, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Bacterial+flagella+explore+microscale+hummocks+and+hollows+to+increase+adhesion%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci+USA%22%5BJournal%5D)">Bacterial flagella explore microscale hummocks and hollows to increase adhesion.</a> Proc Natl Acad Sci USA. 110 (14), 5624-5629 (2013).</li>
<li>Zhou, J., Liu, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stochastic+Assembly+Leads+to+Alternative+Communities+with+Distinct+Functions+in+a+Bioreactor+Microbial+Community%5BTitle%5D)+AND+%22MBio%22%5BJournal%5D)">Stochastic Assembly Leads to Alternative Communities with Distinct Functions in a Bioreactor Microbial Community.</a> MBio. 4 (2), 1-8 (2013).</li>
<li>van Vliet, S., Hol, F. J., Weenink, T., Galajda, P., Keymer, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+effects+of+chemical+interactions+and+culture+history+on+the+colonization+of+structured+habitats+by+competing+bacterial+populations%5BTitle%5D)+AND+%22BMC+Microbiol%22%5BJournal%5D)">The effects of chemical interactions and culture history on the colonization of structured habitats by competing bacterial populations.</a> BMC Microbiol. 14 (1), 116(2014).</li>
<li>Niepa, T. H. R., Hou, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Microbial+Nanoculture+as+an+Artificial+Microniche%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Microbial Nanoculture as an Artificial Microniche.</a> Sci Rep. 6, 30578(2016).</li>
<li>Hansen, R. H., Timm, A. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stochastic+Assembly+of+Bacteria+in+Microwell+Arrays+Reveals+the+Importance+of+Confinement+in+Community+Development%5BTitle%5D)+AND+%22PLoS+ONE%22%5BJournal%5D)">Stochastic Assembly of Bacteria in Microwell Arrays Reveals the Importance of Confinement in Community Development.</a> PLoS ONE. 11 (5), e0155080(2016).</li>
<li>Hood, R. D., Singh, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+Type+VI+Secretion+System+of+Pseudomonas+aeruginosa+Targets+a+Toxin+to+Bacteria%5BTitle%5D)+AND+%22Cell+Host+Microbe%22%5BJournal%5D)">A Type VI Secretion System of Pseudomonas aeruginosa Targets a Toxin to Bacteria.</a> Cell Host Microbe. 7 (1), 25-37 (2010).</li>
<li>LeRoux, M., Ja De Leon,, et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quantitative+single-cell+characterization+of+bacterial+interactions+reveals+type+VI+secretion+is+a+double-edged+sword%5BTitle%5D)+AND+%22Proc+Natl+Acad+Sci%22%5BJournal%5D)">Quantitative single-cell characterization of bacterial interactions reveals type VI secretion is a double-edged sword.</a> Proc Natl Acad Sci. 109 (48), 19804-19809 (2012).</li>
<li>Whitney, J. C., Beck, C. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Genetically+distinct+pathways+guide+effector+export+through+the+type+VI+secretion+system%5BTitle%5D)+AND+%22Mol+Microbiol%22%5BJournal%5D)">Genetically distinct pathways guide effector export through the type VI secretion system.</a> Mol Microbiol. 92 (3), 529-542 (2014).</li>
<li>Warrick, J. W., Timm, A., Swick, A., Yin, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tools+for+Single-Cell+Kinetic+Analysis+of+Virus-Host+Interactions%5BTitle%5D)+AND+%22PLoS+ONE%22%5BJournal%5D)">Tools for Single-Cell Kinetic Analysis of Virus-Host Interactions.</a> PLoS ONE. 11 (1), e0145081(2016).</li>
<li>Zwietering, M. H., Jongenburger, I., Rombouts, F. M., Van't Riet, K. <a target="_blank" href="https://www.ncbi.nlm.nih.gov/pubmed/16348228">Modeling of the Bacterial Growth Curve.</a> Appl Environ Microbiol. 56 (6), 1875-1881 (1990).</li>
<li>Halsted, M., Wilmoth, J. L., et al. <a target="_blank" href="https://www.researchgate.net/publication/308753041_Development_of_transparent_microwell_arrays_for_optical_monitoring_and_dissection_of_microbial_communities">Development of transparent microwell arrays for optical monitoring and dissection of microbial communities.</a> J Vac Sci Technol B Nanotechnol Microelectron. 34 (6), 06KI03(2016).</li>
</ol>

The authors have nothing to disclose.

This article presented a microwell array device and experimental protocols designed to enable high-throughput and high-content live-cell imaging-based analysis of bacterial community development. While the focus of the demonstration here was to study the effects of contact-mediated Type VI secretion on community development, the arrays were designed to be flexible and accommodate the study of a broad range of microbial communities and microbe-microbe interactions. The work here focuses solely on the use of bacteria that constitutively express fluorescent markers to allow facile tracking of member abundance and location. However, opportunities to sample biological material from individual wells following growth or perturbation by changing the chemical environment could, in principal, be used to identify community composition and gene expression.
Each silicon device is composed of dozens of arrays containing microwells with various well diameters, organized at either a 2x, 3x, or 4x diameter pitch, and etched to a depth between 3 &#38; 3.5 &#181;m. Because nutrients and secondary metabolites can diffuse freely through and across the agarose lid, different pitch sub-arrays were included to allow for the examination of how signaling between microwells or local nutrient depletion impact community development. In this demonstration, growth and community development did not appear to be impacted by microwell spacing or location within the arrays. The shallow depth was chosen to simplify image analysis, limiting all microbial growth and development to a single image plane. However, deeper wells (20 &#181;m deep) have been used previously and can be easily modulated in depth by varying the duration of the silicon etching process. Increasing the aspect ratio of the wells essentially alters the degree of confinement experienced by the cells in the interior of the wells, effectively changing the ratio of the total well volume to the area through which nutrients diffuse into the top of the well. This variety of array configurations could be used to study the effects of well-to-well or intra-well signaling.
One limitation of using silicon to fabricate the microwells is that it is opaque to visible light. Consequently, routine analyses that rely on transmission of light (e.g., brightfield, phase, or differential interference contrast imaging) cannot be used to monitor growth. Ongoing research and development in our group has focused on adapting this silicon microwell configuration and experimental protocol for work with transparent arrays to allow for higher-resolution fluorescence and brightfield imaging for monitoring and quantification27. By using transparent materials for fabrication, such as SU-8 epoxy on a glass coverslip, it is possible to acquire both brightfield and fluorescence images with objectives operating at shorter working distances. This allows for more optimal resolution to be obtained with water immersion or oil objectives having &#8805;40X magnification, without the difficulty of imaging through an agar layer, as is the case for silicon arrays.
As described in our prior work, seeding conditions and well geometry impact the seeding of cells within the well arrays. At low seeding densities or in small wells, high levels of variation in the number and types of cells that load into individual wells allows for a broad and rapid exploration of experimental parameter space. Higher seeding densities and/or imaging larger wells yields more consistent ratios of cell types and total inoculum levels, allowing for the analysis of large numbers of experimental replicates. A quick look at images during the earliest stages of growth suggests that cells attach and grow primarily along the edges of the wells (Figure 5a). It is not clear if this is an artifact related to some evaporative drying during the seeding process or suggests a preference for cell attachment to multiple edges. Intentionally altering the topography or surface chemistry of the wells in a deterministic manner could reveal which factors have the greatest impact on cell attachment and biofilm formation.
Growth of the bacteria in these wells is supported by the use of an agarose gel-coated glass coverslip infused with R2A medium. The methods described to create this agarose-coated coverslip ensure an even thickness through which to image and a fairly constant z-position, allowing for the possibility to simultaneously image multiple silicon chips. The use of ultra-pure agarose as the gelling agent and a minimal medium rather than a complete medium results in a cleaner, less autofluorescent background, increasing the overall signal-to-noise ratio. When relying on fluorescence for the quantitative tracking of microbial communities, it is essential to keep imaging conditions consistent and to be acutely aware of contributions from autofluorescence, photobleaching, and non-uniform illumination. In addition, for experiments requiring long time-lapse image acquisition, a thick layer of agarose, such as used here, is desired. Thinner layers (~100 &#181;m thick) can be made to enable higher magnification imaging. However, it is difficult to keep the assembly humid enough to prevent that thin layer from drying out.
Though the initial analysis of growth parameters and initial inoculum levels has not yet revealed any significant correlations for the simple system described here, the protocols and data shown emphasize the depth of information that can be extracted from images of community development over time. Spatial organization within the wells evolves as single-species colonies expand from initial &#34;nucleation&#34; sites. Thus, factors associated with the initial attachment density (i.e.&#160;stemming perhaps from the greater preference of one species for the well surface compared to another) or growth rate of individual patches could dramatically influence community development. Subtler interactions, such as those mediated by contact between species (patches) established very late in the growth process may require more in-depth analysis of the image data.
The microwell array platform and protocol presented here facilitate the rapid assembly and high-content analysis of microbial community development and microbe-microbe interactions. Future work that allows for the control of the local chemical environment, by changing the composition of medium within the agar lid or by directly modulating and sampling via integrated microfluidics, should allow for experimental protocols that move beyond mimicking natural confinement and niche size and begin to explore the impact of dynamically changing environments, similar to those found in nature. Future work will augment the array design with integrated microfluidics that can be used to dynamically modulate the local chemical environment and to sample fluid from individual wells. Additional work on the development of optically clear microwell arrays that can be used for higher-resolution and brightfield tracking of community growth has been described elsewhere27.

Microbial communities are shaped by both deterministic factors, such as the structure of the environment, and stochastic processes, which are associated with cell death, division, protein concentration, number of organelles, and mutation1. Within the natural environment, it can be nearly impossible to parse the individual impact of these influences on community composition and activity. Obscured by natural structures and buried within a chemical and biological milieu, identifying community members and further resolving their spatiotemporal distribution within the natural environment is extremely challenging. Nonetheless, recent efforts have underscored the importance of spatial organization on community function and point towards the need to account for both member abundance and organization in ongoing studies2,3,4.
It is clear that the local chemical environment (i.e.&#160;the availability of nutrients and secondary metabolites), the physical structure (e.g., soil architecture, plant roots, ocean particles, or the intestinal microvilli), the presence or absence of oxygen, and the introduction of pathogenic species all affect the composition, architecture, and function of microbial communities5,6,7,8,9,10,11. Nonetheless, traditional techniques for cultures that neglect to capture these factors continue to prevail. Community composition (e.g., the presence of co-dependent species), physical attachment, signaling molecule concentration, and direct cell-cell contact are all important factors for shaping a microbial community and can be lost in conventional culture conditions. These properties are difficult to replicate in a bulk liquid culture or on an agar plate. The availability of microfluidic, micropatterning, and nanofabrication techniques that allow for the replication of key physical and chemical features of natural environments has, however, enabled many researchers to build bacterial communities to study their interactions12,13,14 and to develop synthetic environments that mimic natural conditions4,15,16,17,18,19,20.
This protocol describes a method to fabricate a microwell array device and provides detailed experimental procedures that can be used to functionalize the wells in the array and to grow bacteria, both as single-species colonies and in multi-member communities. This work also demonstrates how bacteria modified to produce fluorescent reporter proteins can be used to monitor bacterial growth within wells over time. A similar array was presented previously and showed that it is possible to track the growth of single-species colonies of Pseudomonas aeruginosa (P. aeruginosa)&#160;in microwells. By modulating well size and seeding density, the starting conditions of thousands of growth experiments can be varied in parallel to determine how the initial inoculation conditions affect the ability of the bacteria to grow21. The current work uses a slightly modified version of the microwell array that builds on the previous work by enabling the simultaneous comparison of multiple arrays and by using a more robust experimental protocol. The array used in this work contains multiple subarrays, or array ensembles, containing wells of different sizes, ranging from 15 - 100 &#181;m in diameter, that are arranged at three different pitches (i.e.&#160;2x, 3x, and 4x the well diameter). The arrays are etched into silicon, and the growth of the bacteria seeded in the silicon arrays is enabled by sealing the arrays with a coverslip that has been coated with a medium-infused agarose gel. P. aeruginosa mutants designed to study the Type VI secretion system are used in this demonstration.
The results presented here build toward the ultimate goal of analyzing multimember communities within microwell arrays, enabling researchers to monitor the abundance and organization of bacteria in situ while controlling and probing the chemical environment. This should ultimately provide insights into the &#34;rules&#34; that govern community development and succession.

<table><tbody><tr><td>Parylene N</td><td>Specialty Coating Systems</td><td>CAS NO.:1633-22-3</td><td></td></tr><tr><td>Parylene coater</td><td>Specialty Coating Systems</td><td>Labcoter 2 Parylene Deposition Unit PDS2010</td><td></td></tr><tr><td>Silicon Wafer</td><td>WRS Materials</td><td>100mm diameter, 500-550&amp;mu;m thickness, Prime, 10-20 resistivity, N/Phos&amp;lt;100&gt;,</td><td></td></tr><tr><td>adhesion promoter</td><td>Shin-Etsu Microsci</td><td>MicroPrime P20 adhesion promoter</td><td></td></tr><tr><td>postive tone photoresist</td><td>Rohm and Haas Electronics Materials LLC (Owned by Dow)</td><td>Microposit S1818 Positive Photoresist (code 10018357)</td><td></td></tr><tr><td>Quintel Contact Aligner</td><td>Neutronix Quintel Corp</td><td>NXQ 7500 Mask Aligner</td><td></td></tr><tr><td>Reactive Ion Etching Tool</td><td>Oxford Instruments</td><td>Plasmalab System 100 Reactive Ion Etcher</td><td></td></tr><tr><td>R2A Broth</td><td>TEKnova</td><td>R0005</td><td></td></tr><tr><td>Bovine Serum Albumin</td><td>Sigma</td><td>A9647</td><td></td></tr><tr><td>Multimode Plate Reader</td><td>Perkin Elmer</td><td>Enspire, 2300-0000</td><td></td></tr><tr><td>Fluorescent Microscope</td><td>Nikon</td><td>Eclipse Ti-U</td><td></td></tr><tr><td>Automated Stage</td><td>Prior</td><td>ProScan III</td><td></td></tr><tr><td>CCD camera</td><td>Nikon</td><td>DS-QiMc</td><td></td></tr><tr><td>Stage-top environmental control chamber</td><td>In Vivo Scientific</td><td>STEV ECU-HOC</td><td></td></tr><tr><td>Phosphate Buffered Saline</td><td>ThermoFisher Scientific</td><td>14190144</td><td></td></tr><tr><td>UltraPure Agarose</td><td>ThermoFisher Scientific</td><td>16500500</td><td></td></tr><tr><td>25 x 75 mm No. 1.5 coverslip</td><td>Nexterion</td><td>High performance #1.5H coverslips</td><td></td></tr><tr><td>Fluorescence Reference Slides</td><td>Ted Pella</td><td>2273</td><td></td></tr><tr><td>Physical Stylus Profilometer</td><td>KLA Tencor</td><td>P-6</td><td></td></tr><tr><td>lab wipes</td><td>Kimberly Clark</td><td>Kimipe KIMTECH SCIENCE Brand, 34155</td><td></td></tr><tr><td>commercial software</td><td>Nikon</td><td>NIS Elements</td><td></td></tr><tr><td>Zeiss 710 Confocal Microscope</td><td>Zeiss</td><td></td><td></td></tr><tr><td>filter cubes</td><td>Nikon</td><td>Nikon FITC (96311), Nikon Texas Red(96313)</td><td></td></tr></tbody></table>

assembly and tracking of microbial community development within a microwell array platform

The development of microbial communities depends on a combination of complex deterministic and stochastic factors that can dramatically alter the spatial distribution and activities of community members. We have developed a microwell array platform that can be used to rapidly assemble and track thousands of bacterial communities in parallel. This protocol highlights the utility of the platform and describes its use for optically monitoring the development of simple, two-member communities within an ensemble of arrays within the platform. This demonstration uses two mutants of Pseudomonas aeruginosa, part of a series of mutants developed to study Type VI secretion pathogenicity. Chromosomal inserts of either mCherry or GFP genes facilitate the constitutive expression of fluorescent proteins with distinct emission wavelengths that can be used to monitor community member abundance and location within each microwell. This protocol describes a detailed method for assembling mixtures of bacteria into the wells of the array and using time-lapse fluorescence imaging and quantitative image analysis to measure the relative growth of each member population over time. The seeding and assembly of the microwell platform, the imaging procedures necessary for the quantitative analysis of microbial communities within the array, and the methods that can be used to reveal interactions between microbial species area all discussed.

The experimental platform presented here is designed for high-throughput and high-content studies of bacterial communities. The design enables thousands of communities, growing in wells of various sizes, to be analyzed simultaneously. With this microwell array design, the dependence of the final community composition on initial seeding densities, well size, and chemical environment can be determined. This work demonstrates the growth of a two-member community in the microwell array and puts forth methods to analyze community composition and organization.
The model system used here was designed in the Mougous lab to study Type VI secretion in P. aeruginosa. The system is composed of several mutant strains, containing either GFP or mCherry fluorescent reporters. In this work used 2 different strains. The first is a GFP-labeled &#916;retS mutant that constitutively expresses the toxic effector proteins associated with Type VI secretion, resulting in higher levels of cell death in susceptible cells. The second is an RFP-labeled &#916;retS&#916;tse/i1-6 strain that is a deletion mutant missing all six known effector proteins and that has been shown to be more susceptible to Type VI pathogenesis22,23,24. The growth trajectories of each species were tracked individually and within two member communities (i.e.&#160;co-culture within the array platform).
The &#916;retS and &#916;retS&#916;tse/i1-6 mutants were seeded onto three arrays, each separately and also mixed together in a 1:2 ratio, and then imaged every 30 min for 20 h. Bacterial growth in the wells ceased between 6 &#38; 12 h postseeding. Examples of the fluorescent image data are shown in Figures 2 and 3. Figure 2 shows growth over time of the &#916;retS and &#916;retS&#916;tse/i1-6 strains in 45 &#181;m diameter wells, and Figure 3 shows the state of these same two-member communities about 6 h postseeding (hps) in wells of various sizes.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55701/55701fig2.jpg" /> 
Figure 2: Sample Images from a Time-course co-culture Growth Experiment. Two mutants of P. aeruginosa, expressing either mCherry (&#916;retS&#916;tse/i1-6) (red) or GFP (&#916;retS) (green), are seeded together in a 2:1 mCherry:GFP ratio in the microwell arrays. Pictured here are composite images taken at 3 different times postseeding in the 45 &#181;m diameter wells. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55701/55701fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55701/55701fig3.jpg" /> 
Figure 3: Range of Well Diameters Included in the Microwell Array Device. Representative images of two-member communities captured at 8 h of growth. Generally, mCherry (&#916;retS&#916;tse/i1-6) (red) or GFP (&#916;retS) (green) colonies show minimal colocalization, remaining within distinct areas in the microwells. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55701/55701fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Prior to the acquisition of the measurements, a sliding parabaloid background subtraction was performed. An illumination correction step was employed so that the signal from each microwell imaged in a given experiment could be compared quantitatively. These methods have been previously described25. Using the microarray plugin in ImageJ, the average intensity of the red and green bacteria was measured in the corrected images, along with a local background signal. The local background signal was subtracted from the well signal, and the GFP signal was adjusted to correct for the autofluorescence of P. aeruginosa co-cultures (autofluorescence determined from mCherry &#916;retS&#916;tse/i1-6-only arrays). Once all these corrections were performed, the quantitative growth trajectories of mCherry- and GFP-expressing bacteria could be plotted. Example growth trajectories from 20 and 50 &#181;m diameter wells are shown in Figure 4.
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/55701/55701fig4.jpg" /> 
Figure 4: Growth Curves of Mono- and Co-cultures of P. aeruginosa Type VI Secretion Mutants. (a and d) GFP-&#916;retS monoculture growth curves in 20-&#181;m and 50-&#181;m wells, respectively. (b and e) mCherry-&#916;retS&#916;tse/i1-6 monoculture growth curves in 20 and 50 &#181;m wells, respectively. (c and f) Co-culture of a 1:2 ratio mixture of GFP (green) and mCherry (red) P. aeruginosa strains. Growth curves are plotted from when image acquisition began, approximately 2 h postseeding (hps). <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55701/55701fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The growth trajectories from the mono- and co-culture of P. aeruginosa strains indicate that there is some variability in growth from well to well and that this variability is increased in wells of smaller dimensions. However, the mean intensity is not significantly affected by well size. There does not appear to be a dramatic or clear negative effect on the growth of the susceptible strain (&#916;retS&#916;tse/i1-6) when the &#916;retS strain is present. The overall intensity for each strain decreased, but this was due to a lower starting concentration of each strain in the wells, as the total OD was kept consistent across experiments, not the individual OD of each strain. However, it is difficult to determine what factors are most important to understanding the growth of bacteria in these wells simply by looking at growth trajectories alone. Therefore, each trajectory was fit with a modified logistic function26 (Figure 5a) so that relevant parameters could be extracted and used to analyze bacterial growth data. Each trajectory was transformed by taking the natural log of the signal divided by the initial signal. A modified logistic function, with three parameters corresponding to a maximum signal (A), a maximum rate (&#181;), and a lag time (&#964;), was used to fit each trajectory.
Given the known interaction between the GFP-&#916;retS and mCherry-&#916;retS&#916;tse/i1-6 strains, one might hypothesize that the growth of the mCherry strain would be inhibited in co-cultures with the GFP-&#916;retS strain22,24. Using the extracted parameters, it is possible to look for positive or negative correlations between the parameters extracted from GFP and mCherry trajectories. The initial parameter analysis suggested that the co-culture of these species had a negligible effect on their overall growth. The variability seen in the growth curves is likely due to environmental factors, such as initial seeding density, which becomes more variable at smaller well diameters (Figure 5b). Significant negative effects on the mCherry strain due to the presence of GFP-&#916;retS were not observed. For example, when plotting the maximum mCherry signal versus the ratio of the initial GFP-to-RFP signal, no decrease in mCherry expression was found when there was a higher ratio of GFP-&#916;retS in the wells.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/55701/55701fig5.jpg" /> 
Figure 5: Fluorescent Growth Trajectories Fit with a Modified Logistic Equation. (a) The example curve is normalized and then fit with a modified logistic equation by adjusting three parameters, a maximum intensity (A), a maximum rate (&#181;), and a lag time (&#964;). (b) Initial mCherry signal versus initial GFP signal in individual wells of various diameters. (c) The maximum mCherry reporter signal plotted versus the ratio of the initial intensity of the GFP-expressing bacteria to the RFP-expressing bacteria. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55701/55701fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Previous work in the Mougous lab indicated that the effects of Type VI secretion require direct cell-to-cell contact between secreting and susceptible cells and that a longer contact period results in more cell lysis23. Therefore, we believe that, in these arrays, the exponential growth of the two mutants is simply out-pacing the contact-mediated pathogenic effects in this model system. However, in wells of all sizes, the GFP- and mCherry-expressing bacteria grow in distinct patches (Figures 2 and 3). Therefore, rather than focusing on growth rates, bacterial communities containing contact-mediated pathogenic actors may be better studied using spatial analyses. For example, rather than focusing on the integrated intensity, which is representative of the total number of red or green cells in a well, this microwell format allows for the number and location of red and/or green pixels to be counted. It is possible to analyze the growth of individual colonies or patches within these wells, focusing on the borders where the red and green signals overlap (Figure 6a). Quantifying co-localization events and nearest-neighbor analyses can then be executed to look more closely at properties like patch size, patch growth rate, and patch overlap within individual wells. Spatial analyses would be aided by higher-magnification imaging and confocal microscopy (Figure 6b).
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/55701/55701fig6.jpg" /> 
Figure 6: The Spatial Organization of Different Species may be Analyzed using Epifluorescent and Confocal Microscopy. (a) Series of images from one 100 &#181;m well acquired using a confocal microscope with 20X magnification and NA of 0.8. The white arrows point toward yellow regions where red and green colonies overlap or are mixed. Analyzing how the colonies grow in these regions would be interesting for studying contact-based pathogenesis. (b and c) Confocal images (20X magnification, NA = 0.8) of 15 &#181;m diameter, ~7.5 &#181;m deep wells. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55701/55701fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Assembly and Tracking of Microbial Community Development within a Microwell Array Platform at JoVE.com

Montaż i śledzenie rozwoju społeczności drobnoustrojów w ramach platformy mikrodołkowej | Bioinżynieria | Wideo

Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

The development of microbial communities depends on a combination of factors, including environmental architecture, member abundance, traits, and interactions. This protocol describes a synthetic, microfabricated environment for the simultaneous tracking of thousands of communities contained in femtoliter wells, where key factors such as niche size and confinement can be approximated.

The development of microbial communities depends on a combination of complex deterministic and stochastic factors that can dramatically alter the spatial ...

assembly-tracking-microbial-community-development-within-microwell

Nanyang Technological University

Research

Education

JoVE Journal

JoVE Core

Biology

Bioengineering

Ecology

Population and Community Ecology

SCIENTISTS IN ACTION

8.9K Views.  Oak Ridge National Laboratory. The development of microbial communities depends on a combination of factors, including environmental architecture, member abundance, traits, and interactions. This protocol describes a synthetic, microfabricated environment for the simultaneous tracking of thousands of communities contained in femtoliter wells, where key factors such as niche size and confinement can be approximated.

Video: Assembly and Tracking of Microbial Community Development within a Microwell Array Platform

Polymer Microarrays for High Throughput Discovery of Biomaterials

The discovery of novel biomaterials that are optimized for a specific biological application is readily achieved using polymer microarrays, which allows a combinatorial library of materials to be screened in a parallel, high throughput format1. Herein is described the formation and characterization of a polymer microarray using an on-chip photopolymerization technique 2. This involves mixing monomers at varied ratios to produce a library of monomer solutions, transferring the solution to a glass slide format using a robotic printing device and curing with UV irradiation. This format is readily amenable to many biological assays, including stem cell attachment and proliferation, cell sorting and low bacterial adhesion, allowing the ready identification of 'hit' materials that fulfill a specific biological criterion3-5. Furthermore, the use of high throughput surface characterization (HTSC) allows the biological performance to be correlated with physio-chemical properties, hence elucidating the biological-material interaction6. HTSC makes use of water contact angle (WCA) measurements, atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). In particular, ToF-SIMS provides a chemically rich analysis of the sample that can be used to correlate the cell response with a molecular moiety. In some cases, the biological performance can be predicted from the ToF-SIMS spectra, demonstrating the chemical dependence of a biological-material interaction, and informing the development of hit materials5,3.

A description of the formation of a polymer microarray using an on-chip photopolymerization technique. The high throughput surface characterization using atomic force microscopy, water contact angle measurements, X-ray photoelectron spectroscopy and time of flight secondary ion mass spectrometry and a cell attachment assay is also described.

The discovery of novel biomaterials that are optimized for a specific biological application is readily achieved using polymer microarrays, which allows a ...

Microfluidic Picoliter Bioreactor for Microbial Single-cell Analysis: Fabrication, System Setup, and Operation

In this protocol the fabrication, experimental setup and basic operation of the recently introduced microfluidic picoliter bioreactor (PLBR) is described in detail. The PLBR can be utilized for the analysis of single bacteria and microcolonies to investigate biotechnological and microbiological related questions concerning, e.g.&#160;cell growth, morphology, stress response, and metabolite or protein production on single-cell level. The device features continuous media flow enabling constant environmental conditions for perturbation studies, but in addition allows fast medium changes as well as oscillating conditions to mimic any desired environmental situation. To fabricate the single use devices, a silicon wafer containing sub micrometer sized SU-8 structures served as the replication mold for rapid polydimethylsiloxane casting. Chips were cut, assembled, connected, and set up onto a high resolution and fully automated microscope suited for time-lapse imaging, a powerful tool for spatio-temporal cell analysis. Here, the biotechnological platform organism Corynebacterium glutamicum&#160;was seeded into the PLBR and cell growth and intracellular fluorescence were followed over several hours unraveling time dependent population heterogeneity on single-cell level, not possible with conventional analysis methods such as flow cytometry. Besides insights into device fabrication, furthermore, the preparation of the preculture, loading, trapping of bacteria, and the PLBR cultivation of single cells and colonies is demonstrated. These devices will add a new dimension in microbiological research to analyze time dependent phenomena of single bacteria under tight environmental control. Due to the simple and relatively short fabrication process the technology can be easily adapted at any microfluidics lab and simply tailored towards specific needs.

In this protocol the fabrication, setup and basic operation of a microfluidic picoliter bioreactor (PLBR) for single-cell analysis of prokaryotic microorganisms is introduced. Industrially relevant microorganisms were analyzed as proof of principle allowing insights into growth rate, morphology, and phenotypic heterogeneity over certain time periods, hardly possible with conventional methods.

In this protocol the fabrication, experimental setup and basic operation of the recently introduced microfluidic picoliter bioreactor (PLBR) is described ...

Easy and Accurate Mechano-profiling on Micropost Arrays

Cell culture substrates with integrated flexible microposts enable a user to study the mechanical interactions between cells and their immediate surroundings. Particularly, cell-substrate interactions are the main interest. Today micropost arrays are a well-characterized and established method with a broad range of applications that have been published over the last decade. However, there seems to be a reservation among biologists to adapt the technique due to the lengthy and challenging process of micropost manufacture along with the lack of easily approachable software for analyzing images of cells interacting with microposts. 
The force read-out from microposts is surprisingly easy. A micropost acts like a spring with the cell ideally attached at its tip. Depending on size a cell applies force from its cytoskeleton through one or multiple focal adhesion points to the micropost, thus deflecting the micropost. The amount of deflection correlates directly to the applied force in direction and in magnitude. The number of microposts covered by a cell and the post deflection patterns are characteristic and allow determination of values like force per post and many biologically relevant parameters that allow &#8220;mechano-profiling&#8221; of cell phenotypes.
A convenient method for mechano-profiling is described here combining the first generation of ready-to-use commercially available microposts with an in-house developed software package that is now accessible to all researchers. As a demonstration of typical application, single images of bone cancer cells were taken in bright-field microscopy for mechano-profiling of cell line models of metastasis. This combination of commercial traction force sensors and open source software for analysis allows for the first time a rapid implementation of the micropost array technique into routine lab work done by non-expert users. Furthermore, a robust and streamlined analysis process enables a user to analyze a large number of micropost images in a highly time-efficient manner.

Described are protocols for quantifying mechanical interactions between adherent cells and microstructured substrates. These interactions are closely linked to essential cell behaviors including migration, proliferation, differentiation, and apoptosis. The protocols present an open-source image analysis software called MechProfiler, which enables determination of involved forces for each micropost.

Cell culture substrates with integrated flexible microposts enable a user to study the mechanical interactions between cells and their immediate ...

Patterning of Microorganisms and Microparticles through Sequential Capillarity-assisted Assembly

Controlled patterning of microorganisms into defined spatial arrangements offers unique possibilities for a broad range of biological applications, including studies of microbial physiology and interactions. At the simplest level, accurate spatial patterning of microorganisms would enable reliable, long-term imaging of large numbers of individual cells and transform the ability to quantitatively study distance-dependent microbe-microbe interactions. More uniquely, coupling accurate spatial patterning and full control over environmental conditions, as offered by microfluidic technology, would provide a powerful and versatile platform for single-cell studies in microbial ecology. 
This paper presents a microfluidic platform to produce versatile and user-defined patterns of microorganisms within a microfluidic channel, allowing complete optical access for long-term, high-throughput monitoring. This new microfluidic technology is based on capillarity-assisted particle assembly and exploits the capillary forces arising from the controlled motion of an evaporating suspension inside a microfluidic channel to deposit individual microsized objects in an array of traps microfabricated onto a polydimethylsiloxane (PDMS) substrate. Sequential depositions generate the desired spatial layout of single or multiple types of micro-sized objects, dictated solely by the geometry of the traps and the filling sequence. 
The platform has been calibrated using colloidal particles of different dimensions and materials: it has proven to be a powerful tool to generate diverse colloidal patterns and perform surface functionalization of trapped particles. Furthermore, the platform was tested on microbial cells, using Escherichia coli cells as a model bacterium. Thousands of individual cells were patterned on the surface, and their growth was monitored over time. In this platform, the coupling of single-cell deposition and microfluidic technology allows both geometric patterning of microorganisms and precise control of environmental conditions. It thus opens a window into the physiology of single microbes and the ecology of microbe-microbe interactions, as shown by preliminary experiments.

We present a technology that uses capillarity-assisted assembly in a microfluidic platform to pattern micro-sized objects suspended in a liquid, such as bacteria and colloids, into prescribed arrays on a polydimethylsiloxane substrate.

Controlled patterning of microorganisms into defined spatial arrangements offers unique possibilities for a broad range of biological applications, ...

Engineering

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

Microfabricated cellular microarrays, which consist of contact-printed combinations of biomolecules on an elastic hydrogel surface, provide a tightly controlled, high-throughput engineered system for measuring the impact of arrayed biochemical signals on cell differentiation. Recent efforts using cell microarrays have demonstrated their utility for combinatorial studies in which many microenvironmental factors are presented in parallel. However, these efforts have focused primarily on investigating the effects of biochemical cues on cell responses. Here, we present a cell microarray platform with tunable material properties for evaluating both cell differentiation by immunofluorescence and biomechanical cell&#8211;substrate interactions by traction force microscopy. To do so, we have developed two different formats utilizing polyacrylamide hydrogels of varying Young&#39;s modulus fabricated on either microscope slides or glass-bottom Petri dishes. We provide best practices and troubleshooting for the fabrication of microarrays on these hydrogel substrates, the subsequent cell culture on microarrays, and the acquisition of data. This platform is well-suited for use in investigations of biological processes for which both biochemical (e.g., extracellular matrix composition) and biophysical (e.g., substrate stiffness) cues may play significant, intersecting roles.

Cell differentiation is regulated by a host of microenvironmental factors, including both matrix composition and substrate material properties. We describe here a technique utilizing cell microarrays in conjunction with traction force microscopy to evaluate both cell differentiation and biomechanical cell&#8211;substrate interactions as a function of microenvironmental context.

Microfabricated cellular microarrays, which consist of contact-printed combinations of biomolecules on an elastic hydrogel surface, provide a tightly ...

Fabrication of a Multiplexed Artificial Cellular MicroEnvironment Array

Cellular microenvironments consist of a variety of cues, such as growth factors, extracellular matrices, and intercellular interactions. These cues are well orchestrated and are crucial in regulating cell functions in a living system. Although a number of researchers have attempted to investigate the correlation between environmental factors and desired cellular functions, much remains unknown. This is largely due to the lack of a proper methodology to mimic such environmental cues in vitro, and simultaneously test different environmental cues on cells. Here, we report an integrated platform of microfluidic channels and a nanofiber array, followed by high-content single-cell analysis, to examine stem cell phenotypes altered by distinct environmental factors. To demonstrate the application of this platform, this study focuses on the phenotypes of self-renewing human pluripotent stem cells (hPSCs). Here, we present the preparation procedures for a nanofiber array and the microfluidic structure in the fabrication of a Multiplexed Artificial Cellular MicroEnvironment (MACME) array. Moreover, overall steps of the single-cell profiling, cell staining with multiple fluorescent markers, multiple fluorescence imaging, and statistical analyses, are described.

This article describes the detailed methodology to prepare a Multiplexed Artificial Cellular MicroEnvironment (MACME) array for high-throughput manipulation of physical and chemical cues mimicking in vivo cellular microenvironments and to identify the optimal cellular environment for human pluripotent stem cells (hPSCs) with single-cell profiling.

Cellular microenvironments consist of a variety of cues, such as growth factors, extracellular matrices, and intercellular interactions. These cues are ...

Competitive Genomic Screens of Barcoded Yeast Libraries

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily. The tempo of these advances is accelerating, promising greater depth and breadth. In light of these extraordinary advances, the need for fast, parallel methods to define gene function becomes ever more important. Collections of genome-wide deletion mutants in yeasts and E. coli have served as workhorses for functional characterization of gene function, but this approach is not scalable, current gene-deletion approaches require each of the thousands of genes that comprise a genome to be deleted and verified. Only after this work is complete can we pursue high-throughput phenotyping. Over the past decade, our laboratory has refined a portfolio of competitive, miniaturized, high-throughput genome-wide assays that can be performed in parallel. This parallelization is possible because of the inclusion of DNA 'tags', or 'barcodes,' into each mutant, with the barcode serving as a proxy for the mutation and one can measure the barcode abundance to assess mutant fitness. In this study, we seek to fill the gap between DNA sequence and barcoded mutant collections. To accomplish this we introduce a combined transposon disruption-barcoding approach that opens up parallel barcode assays to newly sequenced, but poorly characterized microbes. To illustrate this approach we present a new Candida albicans barcoded disruption collection and describe how both microarray-based and next generation sequencing-based platforms can be used to collect 10,000 - 1,000,000 gene-gene and drug-gene interactions in a single experiment.

We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily.  The tempo of these advances is ...

Fabrication and Use of MicroEnvironment microArrays (MEArrays)

The interactions between cells and their surrounding microenvironment have functional consequences for cellular behaviour. On the single cell level, distinct microenvironments can impose differentiation, migration, and proliferation phenotypes, and on the tissue level the microenvironment processes as complex as morphogenesis and tumorigenesis1. Not only do the cell and molecular contents of microenvironments impact the cells within, but so do the elasticity2 and geometry3 of the tissue. Defined as the sum total of cell-cell, -ECM, and -soluble factor interactions, in addition to physical characteristics, the microenvironment is complex. The phenotypes of cells within a tissue are partially due to their genomic content and partially due to the combinatorial interactions with the microenviroment. A major challenge is to link specific combinations of microenvironmental components with distinctive behaviours.
Here, we present the microenvironment microarray (MEArray) platform for cell-based functional screening of interactions with combinatorial microenvironments4. The method allows for simultaneous control of the molecular composition and the elastic modulus, and combines the use of widely available microarray and micropatterning technologies. MEArray screens require as few as 10,000 cells per array, which facilitates functional studies of rare cell types such as adult progenitor cells. A limitation of the technology is that entire tissue microenvironments cannot be completely recapitulated on MEArrays. However, comparison of responses in the same cell type to numerous related microenvironments, for instance pairwise combinations of ECM proteins that characterize a given tissue, will provide insights into how microenvironmental components elicit tissue-specific functional phenotypes.
MEArrays can be printed using a wide variety of recombinant growth factors, cytokines, and purified ECM proteins, and combinations thereof. The platform is limited only by the availability of specific reagents. MEArrays are amenable to time-lapsed analysis, but most often are used for end point analyses of cellular functions that are measureable with fluorescent probes. For instance, DNA synthesis, apoptosis, acquisition of differentiated states, or production of specific gene products are commonly measured. Briefly, the basic flow of an MEArray experiment is to prepare slides coated with printing substrata and to prepare the master plate of proteins that are to be printed. Then the arrays are printed with a microarray robot, cells are allowed to attach, grow in culture, and then are chemically fixed upon reaching the experimental endpoint. Fluorescent or colorimetric assays, imaged with traditional microscopes or microarray scanners, are used to reveal relevant molecular and cellular phenotypes (Figure 1).

Fabrication and Use of MicroEnvironment microArrays MEArrays

A combinatorial functional screening method for gaining insights into the impacts of the molecular composition of microenvironments on cellular functions is described. The method takes advantage of existing microarray-based technologies to generate arrays of defined combinatorial microenvironments that support cell adhesion and functional analysis.

The interactions between cells and their surrounding microenvironment have functional consequences for cellular behaviour. On the single cell level, ...

Photodegradable Hydrogel Interfaces for Bacteria Screening, Selection, and Isolation

Biologists have long attempted to understand the relationship between phenotype and genotype. To better understand this connection, it is crucial to develop practical technologies that couple microscopic cell screening with cell isolation at high purity for downstream genetic analysis. Here, the use of photodegradable poly(ethylene glycol) hydrogels for screening and isolation of bacteria with unique growth phenotypes from heterogeneous cell populations is described. The method relies on encapsulating or entrapping cells with the hydrogel, followed by culture, microscopic screening, then use of a high-resolution light patterning tool for spatiotemporal control of hydrogel degradation and release of selected cells into a solution for retrieval. Applying different light patterns allows for control over the morphology of the extracted cell, and patterns such as rings or crosses can be used to retrieve cells with minimal direct UV light exposure to mitigate DNA damage to the isolates. Moreover, the light patterning tool delivers an adjustable light dose to achieve various degradation and cell release rates. It allows for degradation at high resolution, enabling cell retrieval with micron-scale spatial precision. Here, the use of this material to screen and retrieve bacteria from both bulk hydrogels and microfabricated lab-on-a-chip devices is demonstrated. The method is inexpensive, simple, and can be used for common and emerging applications in microbiology, including isolation of bacterial strains with rare growth profiles from mutant libraries and isolation of bacterial consortia with emergent phenotypes for genomic characterizations.

The use of photodegradable hydrogels to isolate bacterial cells by utilizing a high-resolution light pattering tool is reported. Essential experimental procedures, results, and advantages of the process are reviewed. The method enables rapid and inexpensive isolation of targeted bacteria showing rare or unique functions from heterogeneous communities or populations.

Biologists have long attempted to understand the relationship between phenotype and genotype. To better understand this connection, it is crucial to ...

Bioreactor Assembly for Continuous Culture of Complex Fecal Communities

The microbiota, especially bacteria, respond to various environmental exposures such as micro and macronutrients, pharmacological compounds, and inflammatory mediators, which dynamically alter community composition and microbial metabolic output. Understanding how physiological culture conditions affect microbial communities and diversity and their metabolic capacity will contribute important knowledge of their impact on health and diseases. Here, we present a protocol adapted from the template published by Auchtung et al. to create mini-bioreactor arrays that can cultivate complex fecal communities, define bacterial consortiums or single strains under precise conditions, including nutrient availability, temperature, flow rate, pH, and oxygen content. We describe the process for building the mini-bioreactor system, including adaptations to improve limitations in the published protocol. We also discuss the setup of the mini-bioreactor system under anaerobic conditions with the use of MEGA media (adapted from Han et al.), which is a rich media supporting the growth of diverse bacteria. We describe the inoculation of gut humanized mouse fecal samples into the mini-bioreactor system, followed by the establishment of complex community cultures within the mini-bioreactor system, which can be grown under continuous flow with aseptic sampling to monitor community composition. This system is adaptable to dietary changes and other cultural modifications. The techniques described here allow for the characterization of diverse, fastidious fecal communities under dynamic conditions or in response to perturbation in isolation from host-derived factors.

This protocol details the assembly of mini-bioreactor arrays to be utilized for continuous flow culture of complex fecal communities under anaerobic conditions. We also discuss the methods for assembly, inoculation, and sampling of the reactors for further analysis.