This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - SFB1535 - Project ID 458090666 (project B03 to KS, AM&#160;and IA), and Major Research Instrumentation INST 208/808-1. DCD is currently visiting HHU D&#252;sseldorf as a Mercator Fellow of the SFB1535. Additional support for EJK was provided by National Science Foundation Awards #1845463 and #2334680.

Protocol for Co-Culturing Sucrose-Secreting Cyanobacteria with Fungal Partners

The authors have nothing to disclose.

Handling of microorganisms in single axenic cultures in a laboratory context has been established for decades for many microbial models. Yet, though the prevailing form of life in nature is microbial communities, the combination of two or more partners in a single cultivation vessel is less established, and challenges are presented by gaps in the existing knowledge and methodology. It is also more difficult to predict the behavior of cells in a community, as emergent interactions and metabolite exchange arise between the cells, strongly influencing the fate of the co-culture34,35. Hence, co-culture establishment is not trivial, including on the level of growth media definition, the identification of common growth conditions, interspecies exchange of trace metabolites/signals, and the resulting co-culture composition over time. Progress of the last years in the assembly of phototrophic, sugar-secreting cyanobacteria with heterotrophic partners now allows to deduce first rules and methodology that can provide a helpful guideline to the design of novel co-cultivation pairs. Based on that knowledge, in the first part of this protocol a step-by-step guideline to the assembly of co-cultures containing a sucrose-secretion cyanobacterium and one or more yeasts is provided.
One critical consideration when first attempting to establish a co-culture between unrelated microbes is the composition of a common growth medium that satisfies all nutrient requirements for the two or more species. Due to space limitations, it is not feasible to provide a fully detailed protocol for this process here, which may also require a high degree of customization in some instances, but instead the following outlines important considerations to bear in mind. One straightforward initial approach involves comparing the typical cyanobacterial growth medium (e.g., BG11; see Table 1) with any established minimal media composed for the heterotrophic species of interest. Supplementing the standard cyanobacterial medium with any missing components that are contained within the heterotrophic minimal medium is a good starting point for initial testing8,36. Bear in mind that because minimal media are often supplemented with a significant organic carbon source for heterotrophic growth (e.g., 1%-4% glucose), they are often designed to support higher heterotroph cell density than is likely to be achieved in initial co-culture experiments. Likewise, some common medium components can also act as an organic carbon source independently of the photosynthate provided by the cyanobacterial partner (e.g., citrate), which can complicate later analysis of cyanobacteria/heterotroph co-cultures. Therefore, it may not be necessary to complement the minimal cyanobacterial medium with the full concentration of missing elements when designing a co-culture medium. For example, many organisms vary in their efficiency of use of different forms of environmental nitrogen (e.g., N2, nitrate, nitrite, urea) and may be completely unable to utilize some of the more oxidized nitrogen sources. Similarly, many microbes may require supplementation of essential vitamins (e.g., vitamin B12), co-factors or essential amino acids because they lack complete biosynthetic pathways for direct synthesis of these compounds. For these reasons, it may be most practical to start by simply &#34;merging&#34; the established minimal medium of the cyanobacterial partner (e.g., BG11) together with a well-defined minimal medium of the heterotroph (e.g., synthetic defined [SD]). Later cycles of reiteratively removing/reducing superfluous components can be used to optimize the medium and reduce the abundance of any compounds that may be inhibitory to the growth of one of the partners. A useful starting point is to buffer the medium at a neutral or slightly basic pH, as these tend to be conditions favored by most cyanobacterial model species.
At this point, it is often helpful to conduct preliminary tests of the growth of the supported heterotroph in the new co-culture medium when an excess of sucrose is supplied. Of course, when selecting a potential heterotroph, it is important to pick one that is capable of catabolizing the primary source(s) of organic carbon that will be supplied by the cyanobacterial partner. It is useful to note here that sucrose, as the dominant carbohydrate supplied in many engineered cyanobacterial/heterotrophic cultures4, is not a carbohydrate that is as universally utilized by heterotrophic microbes as glucose: dedicated sucrose transporters must be encoded by the heterotrophic species or extracellular invertases may be necessary to convert sucrose to fructose and glucose that are often recognized by higher-affinity transporters8. An important observation commonly reported by multiple laboratories researching mixed microbial communities is that higher-order synergies and antagonisms emerge between the phototrophic and heterotrophic partners4,8,13. For example, other naturally secreted metabolites (e.g., organic acids, reduced forms of nitrogen) or co-factors (e.g., siderophores) may enable higher growth rates of one or both partners when cultivated in the same medium relative to axenic controls. Conversely, potentially harmful metabolic byproducts, such as hyperoxygenation of the medium by photosynthetic water splitting, have been reported to cause inter-species inhibition of growth for one or both partners8. Therefore, axenic controls can provide a useful benchmark, but the co-culture performance may vary from expectations due to these emergent properties.
Depending on the heterotrophic partner and the capabilities of S. elongatus to excrete sucrose (based on the level of induction, used IPTG concentration), different ratios of both organisms should be tested. The success of the cultures depends primarily on the ability of S. elongatus to maintain the growth of the heterotrophic partner (i.e., can it produce enough carbon source). While overgrowth of the heterotrophic strain is typically limited by the lack of organic carbon provided in the co-culture medium composition, cyanobacteria can outpace the heterotroph, which may lead to emergent inhibitory interactions (e.g., hyperoxic conditions8,13).&#160;When attempting to initially determine appropriate ratios of cell density for the cyanobacterium: yeast, a good approximate rule is that the cyanobacterial partner can support an equal cell volume of the accompanying heterotrophic cells. Since eukaryotic yeasts tend to have considerably larger cell volumes than model sucrose-secreting cyanobacteria, this may likely mean that the density of cyanobacterial cells will be considerably higher (e.g., 50-100 fold for S. cerevisiae) in a steady-state. Therefore, a good starting point when setting up a new co-culture with the researcher-specific laboratory and species conditions would be to calculate the average cell volume for both the cyanobacterium and yeast (based on published values; e.g., see B10NUMB3R537) to estimate the volumetric ratio. Initial flasks can be seeded with this ratio of cells. To explore the solution space, the researcher may wish to hold the concentration of cyanobacteria constant (e.g., OD750 = 0.3) while varying the concentration of yeast cells up or down by approximately an order of magnitude in increments based on the throughput allowed by the researcher&#39;s available phototrophic cultivation space. Of course, this volumetric &#39;rule of thumb&#39; is dependent upon the rate at which the phototrophic partner is capable of secreting organic photosynthates (e.g., sucrose) that can be utilized by the heterotrophic partner. Once co-cultivation conditions have been established, careful monitoring of the growth performance of both partners over time will provide valuable data regarding ideal species ratios, especially if early co-cultures can be maintained for days to weeks, thereby allowing the researcher to identify the steady-state ratio reached near the end of a co-culture. This information can be utilized when selecting the initial inoculation density for each partner species in subsequent experiments to help the culture more rapidly reach the self-determined ideal species ratio.
In the second part of the protocol, detailed instructions for co-culture analytics are provided. A reliable quantification of the co-cultures is key to their successful implementation: Growth (or at least metabolic activity) of the phototropic, carbon-secreting partner is essential to sustain the heterotrophs. While the ratio of cyanobacteria:heterotroph used to inoculate the culture may not always be critical to optimize, since longer-term co-cultures tend to converge towards stable proportions, it may be important to integrate methods to check unrestrained growth of either partner through culture dilution or encapsulation of one or more species36,38,39,40. As mentioned above, byproducts of the cyanobacterial partner may be inhibitory to the heterotroph at high concentrations (e.g., O2), and some products of heterotrophic metabolism may also be detrimental to cyanobacterial health. Most published co-cultures utilize heterotrophs that have a faster growth rate than most model cyanobacterial species; therefore, the heterotrophic growth rate tends to be constrained by the supply of organic carbon produced by the cyanobacterium. Nonetheless, determination of the species abundance dynamics over time is a critical value for elucidating failures in stability and optimizing for robust co-cultures in long-term cultivation.
Protocols for quantification using counting chambers, particle counters, and single-cell flow cytometry are provided. All techniques are valuable tools for the characterization of co-cultures, however, with different prerequisites, advantages, and limitations. Counting chambers are very broadly applicable for co-culture quantification, provided that all partners in the culture can be distinguished visually by their cell shapes or other properties. The great advantage is the low price of this device, such that it is basically achievable for every laboratory. Besides information on the co-culture composition and ratio of the different partners, an impression of the cell&#39;s morphology and fitness can be gained alongside, and potential contaminants can be detected. However, the application of the counting chamber is also very time-consuming, comes with a high workload, and can only support a low throughput.
Both particle counters and single-cell flow cytometry provide the huge benefits of a high throughput and convenient, time-saving handling. While the cell counter relies on clear differences in cell sizes of the partners in the co-culture, single-cell cytometry can also discriminate fluorescence labels, resulting in the ability to quantify co-cultures with more than two members of the same size or even two different mutants of the same organism based on different fluorescent markers. In the provided example of an artificial assembly of Synechocystis with S. cerevisiae and U.&#160;maydis, the intracellular fluorescence reporters mKate2 and eGFP were used to discriminate the two yeasts. The same fluorescent reporters could also be used to distinguish two genetically modified strains of the same organism (e.g. S. cerevisiae) which could not be separated based on their light scattering properties alone. Similar strategies have been implemented to track synthetic bacterial consortia41. Depending on the cell type, the number of partners in a consortium, and their potential range of autofluorescence(s), the selection of fluorescent markers needs extra attention to avoid overlap of spectral qualities, particularly given the autofluorescent properties of cyanobacteria.42
We advocate here how to adhere to FAIR&#160;guiding principles in terms of storage, management, and sharing of scientific data. FAIR is an acronym that stands for Findable, Accessible, Interoperable, and Reusable43. As these principles gain wider acceptance, they promise to transform the landscape of biological research, promoting a more open, collaborative, and efficient approach to data management and use. While critical components of accessibility can be ensured by depositing data on Annotated Research Context (ARC)44, it is important to enable the reproduction of the data processing steps with open-access software. Raw FCS files store both data and metadata (information about lasers and detectors, including wavelengths, filters, etc.) about flow cytometry experiments45. They can be loaded and read outside of proprietary software that allows for sophisticated data analysis, e.g., a number of packages are available to work with raw data inside the Python environment. The developed package demonstrates how to load, read, and visualize raw .fcs files containing cytometry data outside the proprietary software using one of many available packages in Python23. Using open software such as described above eliminates the need for costly licensing fees associated with proprietary software, provides full control over data processing (e.g., transformation, compensation, gating) and additionally allows integration of numerous tools in one place.
A valuable extra benefit of utilizing single-cell cytometry in conjunction with a cell sorter is the opportunity to also collect cells of a distinct type by FACS. This can be extremely valuable for applying any -omics technologies for detailed insights into the species interaction within the co-culture, like RNASeq or metabolomics. The clear downside of these devices is their high prices, so the affordability and availability of such machines might be an apparent limitation in some laboratories.
Interestingly, a direct comparison of the presented methods for quantification of the three partners in a consortium revealed a very good accordance between the different techniques, indicating that the mixture that has been assembled based on OD measurements is reliably quantified by all described methods. Interestingly, the total number of cyanobacteria was about 3-4 times higher than the number of the two yeast species, a phenomenon likely due to their smaller cell size. This observation is in good accordance with the common knowledge that ODs do not provide information on actual cell numbers without calibration46. The yeasts, however showed counts on a comparable level (Table 2 and Table 3). In addition, the comparison with the quantification of the single cultures demonstrates that all three methods are reliable tools to discriminate the cell types, with the exception of the particle counter that did not separate the two yeast species.
In essence, single-cell cytometry applications are clearly the most powerful tool to monitor the composition of co-cultures, allowing for the counting of 1,000-10,000 cells per second. This is especially true if the number of partners increases to more than two or if the partners are similar in shape and/or diameter. Notably, there are plenty of alternatives that allow the monitoring of co-cultures. Growth of fluorescently labeled microbes in co-cultures can, for example, be tracked continuously by fluorimetry or microbioreactors47. However, these are often limited to a co-culture of two partners and require careful experimental design, for instance, in the choice of fluorescence markers. Amplicon sequencing (16S rRNA sequencing) and other next-generation sequencing techniques in combination with sophisticated bioinformatics is another option for the characterization of synthetic communities48,49,50. These techniques are suitable for high throughput approaches and can address established interactions in long-term cultivations, evolutionary questions, or tracking of mutations with multiple microbial partners.
Taken together, simplistic microbial co-cultures that are rationally designed provide a powerful &#34;bottom-up&#34; approach for interrogating inter-species dynamics that can be more difficult to approach within multi-species communities that dominate the natural world51,52,53. Herein, a streamlined protocol that may be readily adapted by the scientific community for the establishment and analysis of novel pairs of cyanobacteria and heterotrophic partners is provided. It is evident that much research is needed to both capitalize upon the potential fundamental insights that may be gained from artificial microbial co-cultures as well as to determine if synthetically designed microbial consortia can match the potential often ascribed to them in the literature for biotechnological applications.

With the rapid expansion of genomic tools and DNA technologies in recent years, bioengineering efforts are increasingly able to consider mixed communities of microbes as viable for bioproduction strategies rather than solely focusing on axenic cultures. Microbial consortia hold multiple potential advantages relative to single-species cultures, including specialization and division of labor, adaptability and robustness, and efficiency of substrate utilization1. However, the predictable engineering of multi-species consortia is complicated by uncertainties caused by higher-order behaviors that emerge from inter-species interactions2. Cross-species signaling and metabolite exchange are at the heart of the principle of division of labor but also lead to unexpected synergies and antagonisms between participants of the consortia3. Considerable development in the field is necessary if the full potential of mixed microbial consortia can be realized, including the use of flexible 2- and 3-partner co-culture platforms, which can be used to better characterize and understand microbial interactivity from the &#34;bottom up.&#34;
A few dominant types of co-culture platforms are currently in use within the field, including complimentary auxotrophic partners and microbes that secrete metabolites that are generally beneficial to a broad range of microbial species. In the latter category, cyanobacteria have been engineered to become enhanced primary producers through the introduction of pathways that lead to the secretion of easily metabolized carbohydrates and have now been explored in a variety of rationally designed consortia. Briefly, in such engineered microbial communities, the cyanobacterial partner is capable of utilizing light and CO2 as the primary inputs, and through the process of oxygenic photosynthesis, these strains can secrete central carbon sugars as a public good. One class of such engineered cyanobacterial strains are those that have been engineered to secrete the disaccharide sucrose4. Such strains have likely enjoyed their success because sucrose is a metabolite that is close to central carbon metabolism for many species and is also frequently hyper-accumulated as a so-called &#34;compatible solute&#34; to adapt to a variety of environmental abiotic stresses5. A minimal number of genetic interventions can lead to efficient sucrose secretion in a range of cyanobacterial model organisms4.
Sucrose-secreting cyanobacteria are a useful platform for the investigation of rationally designed microbial consortia because a wide range of heterotrophic species can metabolize sucrose as their dominant source of carbon and energy. Indeed, utilizing a few model cyanobacteria with sucrose-secreting capabilities, many laboratories have rationally designed mixed species co-cultures and consortia that contain one or more heterotrophic microbes and which are ultimately supported by the primary inputs of light and CO2 without supplementation of organic carbon feedstocks4. The heterotrophic strains may simply subsist on the cyanobacterial-derived carbohydrates, or they may be utilized to convert the sucrose feedstock into higher-value bioproducts (e.g., fuels, polymers, pigments, etc.). In addition to being a potential strategy for sustainable bioproduction, such simplistic co-cultures may also be useful as a platform for the investigation of emergent interactions between unrelated microbial species.
This video article focuses on methodologies and prerequisites for utilizing sugar-producing cyanobacteria as a flexible platform for the design of simple microbial consortia that can be stable by supplementing only light and inorganic carbon inputs. While the setup and monitoring of cultures containing single established microorganisms are mostly straightforward and can easily be achieved using optical density (OD) or backscatter methodology, this is not feasible once two or more organisms are combined in one vessel. The major reason is that these methods do not distinguish between the different microorganisms, hence, they only provide an overall picture of the culture and do not resolve growth of the individual organisms. Moreover, cyanobacteria have a wide absorption spectrum in the 400-750 nm range, so to measure the OD600 of a heterotroph would lead to false results due to phycocyanin (that absorbs in 620 nm). Therefore, specific protocols for the setup of cyanobacteria-heterotroph mixed communities within the laboratory as well as useful generic protocols for the analysis of the performance of these consortia over time, are provided. While the protocols focus on a specific pairing of a model, sucrose-secreting cyanobacterial species with one or more model heterotrophic microbe, the intent of this work is to provide a resource for researchers who might wish to design new species pairings and to accelerate the optimization phase for the establishment of such cultures. Therefore, in addition to species-specific protocols, information and strategies that can be used to adapt and generalize these protocols for custom communities, as defined by the reader&#39;s needs, are included.
Because of the flexibility of the co-culture platform described herein, protocols for a number of different heterotrophic species that have been previously reported in co-cultivation with sugar-secreting cyanobacteria are described. For instance, the step-by-step protocol for a co-culture of Synechococcus elongatus PCC 7942 with the common laboratory yeast Saccharomyces cerevisiae is provided. Yet, the article also includes protocols that are appropriate for assaying the performance of co-cultures containing other model species, including the yeast form of Ustilago maydis.
The article focuses on a core set of protocols necessary to establish a cyanobacteria/heterotrophic co-culture and perform basic characterization of the performance of these mixed consortia over time. Specifically, single-cell flow cytometry and particle counting methods suitable to take an accurate census of different species, as well as microscopy approaches to evaluate cell morphology, are emphasized. These protocols are meant to serve as the basis for adaptation to the needs and equipment available. Importantly, technical notes and other considerations that are important for establishing and monitoring co-cultures within the laboratory are provided. Finally, examples of nonproprietary alternatives for data analyses of raw FCS6 files using Python packages are included. In summary, the goal is to make cyanobacteria-based co-culture techniques more accessible to a wider scientific audience.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr >
			<td >10x Ph1 objective</td>
			<td >Carl Zeiss AG</td>
			<td >46 04 01-9904</td>
			<td ></td>
		</tr>
		<tr >
			<td >525/40 nm Bandpass Filter</td>
			<td >Beckman Coulter, Inc.</td>
			<td >A01-1-0051</td>
			<td>FITC filter (in 488 nm laser)</td>
		</tr>
		<tr >
			<td >660/10 nm Bandpass Filter</td>
			<td >Beckman Coulter, Inc.</td>
			<td>A01-1-0055</td>
			<td>APC channel (in 638 nm laser)</td>
		</tr>
		<tr >
			<td >710/50 nm Bandpass Filter</td>
			<td >Beckman Coulter, Inc.</td>
			<td>B71092</td>
			<td>PC5.5 channel (in 561 nm laser)</td>
		</tr>
		<tr >
			<td >Accuvettes for Multisizer 4e</td>
			<td>Beckman Coulter, Inc.</td>
			<td>A35473</td>
			<td>Sample cups with lids</td>
		</tr>
		<tr >
			<td >Aperture tube 30 &#956;M for Multisizer 4e</td>
			<td>Beckman Coulter, Inc.</td>
			<td>C92760</td>
			<td>Capillary</td>
		</tr>
		<tr >
			<td >Autoclave</td>
			<td >Lab Associates</td>
			<td >EQM-ARBP</td>
			<td>for sterilisation of material</td>
		</tr>
		<tr >
			<td >Baffled flasks ROTILABO&#174;, Straight neck, 250 ml</td>
			<td >Carl Roth GmbH + Co. KG</td>
			<td >LY95.1</td>
			<td></td>
		</tr>
		<tr >
			<td >BG11 / CoYBG11 components</td>
			<td>different suppliers</td>
			<td ></td>
			<td >see Table 1&#160;</td>
		</tr>
		<tr >
			<td >Bottle top sterile filter</td>
			<td >Sigmaaldrich</td>
			<td >Z222593</td>
			<td>to sterile media if you dont want to use autoclave</td>
		</tr>
		<tr >
			<td >Capillary 45 &#181;m</td>
			<td >Omni Life Science</td>
			<td>OLS 5651738</td>
			<td></td>
		</tr>
		<tr >
			<td >CASY Cell Counter Model TTC</td>
			<td>Schaerfe Systems</td>
			<td ></td>
			<td></td>
		</tr>
		<tr >
			<td >CASY cups</td>
			<td >Omni Life Science</td>
			<td>OLS 5651794</td>
			<td></td>
		</tr>
		<tr >
			<td >CASYclean</td>
			<td >Omni Life Science</td>
			<td>OLS 5651786</td>
			<td>Cleaning solution</td>
		</tr>
		<tr >
			<td >CASYton solution</td>
			<td >Omni Life Science</td>
			<td>OLS 5651808</td>
			<td>Isotonic solution&#160;</td>
		</tr>
		<tr >
			<td >Centrifuge tubes (50 mL)</td>
			<td >Sigmaaldrich</td>
			<td >CLS430828</td>
			<td></td>
		</tr>
		<tr >
			<td >CO2</td>
			<td >BOC</td>
			<td >270182-L</td>
			<td>to supply cyanobacteria axenic cultures and co-cultures</td>
		</tr>
		<tr >
			<td >CONTRAD&#174; 70</td>
			<td >Beckman Coulter, Inc.</td>
			<td>81911</td>
			<td>Deep clean solution</td>
		</tr>
		<tr >
			<td >Cover glass 20 &#215; 26 x 0.4 mm</td>
			<td >VWR International GmbH</td>
			<td>631-1190</td>
			<td>Cover glass for counting chamber</td>
		</tr>
		<tr >
			<td >Cuvettes</td>
			<td>Sarstedt&#160;</td>
			<td>67.742</td>
			<td></td>
		</tr>
		<tr >
			<td >Cyanobacteria BG-11 Freshwater Solution</td>
			<td >Merck KGaA</td>
			<td>C3061</td>
			<td></td>
		</tr>
		<tr >
			<td >CytExpert Software v. 2.6</td>
			<td >Beckman Coulter, Inc.</td>
			<td ></td>
			<td>Cytometer application software</td>
		</tr>
		<tr >
			<td >CytoFLEX Sheath Fluid</td>
			<td >Beckman Coulter, Inc.</td>
			<td >B51503</td>
			<td>Sheat fluid</td>
		</tr>
		<tr >
			<td >Cytometer CytoFLEX S</td>
			<td >Beckman Coulter, Inc.</td>
			<td >BE51180</td>
			<td></td>
		</tr>
		<tr >
			<td >DxH Cleaner for Multisizer 4e</td>
			<td>Beckman Coulter, Inc.</td>
			<td>628022</td>
			<td>Cleaning solution</td>
		</tr>
		<tr >
			<td >Eppendorf tube centrifuge (small)</td>
			<td >Labstac</td>
			<td >CEN16-15</td>
			<td>to centrifuge less than 2mL of culture</td>
		</tr>
		<tr >
			<td >Ethanol</td>
			<td >Carl Roth GmbH + Co. KG</td>
			<td >K928.1</td>
			<td></td>
		</tr>
		<tr >
			<td >FACS tubes</td>
			<td >Beckman Coulter, Inc.</td>
			<td >2523749</td>
			<td>tubes for semi-automatic mode</td>
		</tr>
		<tr >
			<td >FlowClean Cleaning Agent, 500ml</td>
			<td >Beckman Coulter, Inc.</td>
			<td>C48093</td>
			<td>Daily clean solution</td>
		</tr>
		<tr >
			<td >Graduated cylinders</td>
			<td >Sigmaaldrich</td>
			<td >Z131121</td>
			<td>for preparation of media</td>
		</tr>
		<tr >
			<td >HEPPSO</td>
			<td >Merck KGaA</td>
			<td>R426725</td>
			<td></td>
		</tr>
		<tr >
			<td >Infors MultiTron photoincubator</td>
			<td >Infors AG</td>
			<td ></td>
			<td>white LED light</td>
		</tr>
		<tr >
			<td >IPTG</td>
			<td >Merck KGaA</td>
			<td >I6758</td>
			<td>Prepare aliquots, store at -20&#176;C, thaw and keep on ice&#160;</td>
		</tr>
		<tr >
			<td >Isoton II for Multisizer 4e</td>
			<td>Beckman Coulter, Inc.</td>
			<td>8448011</td>
			<td>Isotonic solution&#160;</td>
		</tr>
		<tr >
			<td >Kaluza v. 2.2</td>
			<td >Beckman Coulter, Inc.</td>
			<td >B16406</td>
			<td>Cytometry data analysis software</td>
		</tr>
		<tr >
			<td >KimWipes</td>
			<td >VWR International GmbH</td>
			<td >115-2221</td>
			<td>Lint-free tissues</td>
		</tr>
		<tr >
			<td >KOH</td>
			<td >Merck KGaA</td>
			<td >221473</td>
			<td></td>
		</tr>
		<tr >
			<td >KPO3</td>
			<td >Noah Chemicals</td>
			<td>7790-53-6</td>
			<td></td>
		</tr>
		<tr >
			<td >Measuring beakers</td>
			<td >VWR</td>
			<td >213-3747</td>
			<td></td>
		</tr>
		<tr >
			<td >Micro test plate, 96 well, slip-on lid, flat base, PS, transparent</td>
			<td >SARSTEDT AG &#38; Co. KG</td>
			<td >82.1581.001</td>
			<td></td>
		</tr>
		<tr >
			<td >Microscope base</td>
			<td >Carl Zeiss AG</td>
			<td >47 09 18-9902/16</td>
			<td></td>
		</tr>
		<tr >
			<td >Microsope head</td>
			<td >Carl Zeiss AG</td>
			<td>47 30 14</td>
			<td></td>
		</tr>
		<tr >
			<td >Milli-Q water purification system</td>
			<td >Merck Millipore</td>
			<td>C85358</td>
			<td></td>
		</tr>
		<tr >
			<td >Mulitisizer 4e particle counter</td>
			<td>Beckman Coulter, Inc.</td>
			<td>B23005</td>
			<td>Alternative to the CASY Cell Counter</td>
		</tr>
		<tr >
			<td >Neubauer improved, depth 0.02 mm</td>
			<td>Assistent Germany</td>
			<td></td>
			<td>Counting chamber</td>
		</tr>
		<tr >
			<td >Neubauer improved, depth 0.1 mm</td>
			<td >Paul Marienfeld GmbH &#38; Co. KG</td>
			<td >640010</td>
			<td>Counting chamber</td>
		</tr>
		<tr >
			<td >Ready to Use Daily QC Fluorospheres</td>
			<td >Beckman Coulter, Inc.</td>
			<td >C65719</td>
			<td>Reference for QC</td>
		</tr>
		<tr >
			<td >SCHOTT bottles</td>
			<td >Dutscher</td>
			<td >90347</td>
			<td>for storage</td>
		</tr>
		<tr >
			<td >Specord&#174;200 Plus Spectrophotometer</td>
			<td>Analytic Jena GmbH</td>
			<td ></td>
			<td>OD600/750</td>
		</tr>
		<tr >
			<td >Sucrose</td>
			<td >Merck KGaA</td>
			<td>84100</td>
			<td></td>
		</tr>
		<tr >
			<td >Table top centrifuge (big)</td>
			<td >Labstac</td>
			<td >CEN18-06R</td>
			<td>collect culture biomass</td>
		</tr>
		<tr >
			<td >Yeast Nitrogen Base, without amino acids, without ammonium sulfate</td>
			<td >Thermo Fisher Scientific Inc.</td>
			<td >11743014</td>
			<td></td>
		</tr>
	</tbody>
</table>

assembly and quantification of co-cultures combining heterotrophic yeast with phototrophic sugar-secreting cyanobacteria

With the increasing demand for sustainable biotechnologies, mixed consortia containing a phototrophic microbe and heterotrophic partner species are being explored as a method for solar-driven bioproduction. One approach involves the use of CO2-fixing cyanobacteria that secrete organic carbon to support the metabolism of a co-cultivated heterotroph, which in turn transforms the carbon into higher-value goods or services. In this protocol, a technical description to assist the experimentalist in the establishment of a co-culture combining a sucrose-secreting cyanobacterial strain with a fungal partner(s), as represented by model yeast species, is provided. The protocol describes the key prerequisites for co-culture establishment: Defining the media composition, monitoring the growth characteristics of individual partners, and the analysis of mixed cultures with multiple species combined in the same growth vessel. Basic laboratory techniques for co-culture monitoring, including microscopy, cell counter, and single-cell flow cytometry, are summarized, and examples of nonproprietary software to use for data analysis of raw flow cytometry standard (FCS) files in line with FAIR (Findable, Accessible, Interoperable, Reusable) principles are provided. Finally, commentary on the bottlenecks and pitfalls frequently encountered when attempting to establish a co-culture with sugar-secreting cyanobacteria and a novel heterotrophic partner is included. This protocol provides a resource for researchers attempting to establish a new pair of co-cultured microbes that includes a cyanobacterium and a heterotrophic microbe.

Establishment of co-cultures of phototrophic S.&#160;elongatus and heterotrophic yeasts 
We have previously reported detailed results from the co-cultivation of Synechococcus elongatus PCC 7942 with a variety of substrains of S. cerevisiae. For a comprehensive description of co-culture results with this cyanobacteria/yeast pair, see8. For the sake of brevity and accuracy, these results are not reproduced here. Briefly, prior results indicate a number of considerations that are important for the establishment of long-term cyanobacterial-yeast co-cultures. Of primary concern, the capacity of yeast to survive under conditions where cyanobacteria provide the sole forms of fixed carbon is strongly dependent upon the efficiency with which the yeast strain can utilize sucrose. S. cerevisiae strains that were evolved or engineered to more efficiently metabolize sucrose27,28 were more likely to survive the transition to the co-culture growth mode, achieved higher cell densities, and exhibited higher robustness in long-term (days to weeks) cyanobacterial co-culture experiments8. The initial phase of inoculating a co-culture was especially important for yeast viability, likely due to stresses of culture dilution, switching media composition, and/or withdrawal of a more concentrated carbon source. Therefore, efforts to ease the transition from a richer growth medium to minimal carbon availability at co-culture initiation can improve experimental performance and consistency (see step 1.2.1.1). Additionally, S. cerevisiae exhibited stress responses consistent with hyperoxia when inoculated into dense cultures of S.&#160;elongatus, consistent with the formation of O2 as a primary byproduct of oxygenic photosynthesis. Therefore, efforts to prevent the overgrowth of the cyanobacterial partner and/or alternating &#34;day/night&#34; light cycles could substantially extend the viability of S.&#160;cerevisiae in long-term co-cultures. See the Discussion section for an additional summary of phenomena common in co-cultures relative to axenic control samples.
Monitoring the growth of co-cultures using different methodologies 
In the following section, the exemplary quantification of an artificially mixed tripartite consortium of Synechocystis and the two yeasts S. cerevisiae and U. maydis using three different methods is described. For the mixture, OD750 (for cyanobacteria) and OD600 (for the heterotrophs) of single cultures were determined and adjusted to OD 0.1. Single cultures were mixed in a ratio of 1:1:1 using optical density (which is distinct from cell counts, see above). To facilitate the discrimination of the yeasts in the cytometer, reporter strains of genetically modified S. cerevisiae FY1679-O1B29 constitutively producing cytoplasmic mKate2 (genotype: URA3&#916;/pTDH3::mKate2; strain: S. cerevisiae mKate230) and U. maydis strain AB3331 constitutively producing eGFP (genotype: pep4&#916;/pRpl40::egfp; strain: U. maydis eGFP32) were used. Of note, the cyanobacterial strain was equipped with a replicative plasmid promoting the constitutive, strong expression of the yellow fluorescent protein version mVenus (Synechocystis sp. PCC 6803 pSHDY-Pcpc560-mVenus, strain Synechocystis mVenus, similar to33) and in addition, exhibits the typical strong autofluorescence due to the presence of the photosynthetic machinery.
Microscopic quantification using counting chambers: All cell types in the used artificial mixture of three microorganisms can easily be discriminated microscopically (Figure 2A): Synechocystis and S. cerevisiae are represented by spherical cells that however differ greatly in their diameter (Synechocystis: approx. diameter of 1.5-3 &#181;m, S. cerevisiae: approx. diameter of 3-6 &#181;m), whilst U. maydis cells have an elongated, cigar-shape morphology and a length of at least 10 &#181;m (Figure 2A). These clear morphological traits allow for the exact quantification of each partner in the mixture. As an illustrative example, 37, 18, 36, and 21 S. cerevisiae cells are counted in the four large squares, respectively (Figure 2B). The mean value is 28 cells. Since a large square of the used hemocytometer has an area of 1 mm2 and the chamber depth was 0.02 mm, this results in 28 cells per 0.02&#160;&#181;L. This corresponds to 1,400 cells/&#181;L, which is equivalent to 1.4 x 106 cells/mL. The other cell types were counted, and concentrations were determined accordingly (Figure 2C, Table 2).
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/67311/67311fig02.jpg" /> 
Figure&#160;2:&#160;Microscopic quantification of a tripartite consortium consisting of Synechocystis and the yeasts&#160;S.&#160;cerevisiae and U. maydis. (A) Microscopic differential contrast (DIC) image of an artificially combined mixture of the indicated microorganisms. All species can be easily distinguished by their morphology. Scale bar: 10 &#181;m. (B) Exemplary counting results for an artificially assembled mix of the indicated strains based on axenic cultures with an OD of 0.1. The four large squares at the grid edges were analyzed (red mark in Figure 1D). (C) The mean value of the different cells counted in the four squares were used to calculate the concentration of cells in the suspension using the following equation: Mean value/(chamber depth [0.02 mm] x size of counted square [1 mm2] x 1,000). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67311/67311fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Quantification using particle counters: Particle counters determine the number of particles in a suspension depending on their size. In the example dataset, a particle counter with a 45 &#181;m capillary was used. Since S. cerevisiae and U. maydis cells show similar dimensions, they cannot be distinguished in the particle counter, while the smaller Synechocystis cells can be clearly separated. The analysis of single cultures hence shows peaks at identical positions referring to 3 to 6 &#181;m for the two yeasts (Figure 3A). During the measurement, a negative pressure is applied, which causes the cells to enter the capillary. This briefly changes the electrical resistance so that the device can determine the particle size based on the alteration. In the mixed culture, two distinct peaks can be detected, one associated with the smaller cyanobacterial cells and the other representing a joint fraction of the two yeast species (Figure 3B). Importantly, in addition to the peaks reflecting the living cells, additional peaks were detected at about 1 &#181;m (Figure 3), corresponding to cell debris and smaller particles. Signals that would appear at larger diameters than expected can be caused by cell aggregations. Of note, the shape of peaks reflects the homogeneity of cells: A sharp peak shows very homogenous cells, which is unlikely for a co-culture. In a co-culture, it is expected to see a very broad peak or even two peaks if the partners of the co-culture are clearly different in size. For the axenic cultures of heterotrophic fungi, the peak might be a medium broad peak.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/67311/67311fig3v2.jpg" /> 
Figure 3: Quantification of a tripartite consortium consisting of Synechocystis mVenus&#160;and the yeasts S. cerevisiae mKate2 and U. maydis eGFP&#160;using a particle counter. (A) Visual output of analyses of axenic cultures of the three strains as indicated in the graphs (cell counter with 45 &#181;m capillary). (B) Exemplary visual output file for the analysis of the artificial tripartite consortium using identical conditions. The particle counter does not support the discrimination of the two yeast species which are both represented by the second peak. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67311/67311fig3v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Quantification using single-cell cytometry: Using the single-cell flow cytometer the different cell populations can easily be distinguished based on their (auto-) fluorescence and light scattering properties. Phototrophic cells (Synechocystis) can&#160;be differentiated&#160;from heterotrophic cells (U. maydis and S. cerevisiae) based on the red autofluorescence of the photosynthetic pigments which is measured in the APC-H channel (Figure 4A). Based on that initial separation of phototrophic and heterotrophic cells, the two heterotrophic populations can be distinguished based on their fluorescent markers eGFP in the FITC-H channel and mKate2 in the PC5.5 channel (Figure 4B,C). In a dot plot showing the scattering properties of all three populations (FSC-H and FSC-Width), the populations can also be distinguished with only some minor overlaps of the populations (Figure 4D).
With this method, 10 &#181;L of the diluted samples were analyzed with a flow rate of 10 &#181;L/min, allowing a quantification of approximately 70,000 cells in 1 min. Roughly 60% of those cells could be assigned to Synechocystis (4.23&#160;x&#160;106&#160;cells/mL), while the remaining 40% were equally distributed between U. maydis (1.35 x 106 cells/mL) and S. cerevisiae (1.36 x 106 cells/mL,&#160;Figure 4E, Table 2).
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/67311/67311fig04.jpg" /> 
Figure 4: Quantification of a tripartite consortium consisting of the cyanobacterium Synechocystis mVenus&#160;and the yeasts U. maydis eGFP and S. cerevisiae mKate2 using single-cell flow cytometry. Example&#160;plots obtained after measurement of a mixed culture of Synechocystis mVenus (dark green), U. maydis eGFP (light green) and S. cerevisiae mKate2 (red) in a ratio of &#8531; OD750 / &#8531; OD600 / &#8531; OD600 on a cytometer (A) showing a histogram of the event count and fluorescence in the APC-H channel (ex.: 638 nm, em.: 660/10 nm) of all cells used to differentiate phototrophic and heterotrophic cells based on their autofluorescence. (B) A histogram of the event count and fluorescence in the FITC-H channel (ex.: 488 nm, em.: 525/40 nm) of all heterotrophic cells used to differentiate U. maydis eGFP and S.&#160;cerevisiae mKate2 cells based on their green fluorescence properties. (C) A histogram of the event count and fluorescence in the PC5.5-H channel (ex.: 561 nm, em.: 710/50 nm) of all heterotrophic cells used to differentiate U. maydis eGFP and S.&#160;cerevisiae mKate2 cells based on their red fluorescence properties. (D) A dot plot of the scattering signals in the FSC-Width over the FSC-H channel used to identify the cell populations without fluorescence properties. (E) The population statistics including the event counts, percentages, and arithmetic means and standard deviations (SD) of the relevant fluorescence channels. The total amount of cells, along with their size and fluorescence, was determined in a volume of 10&#160;&#181;L with a flow rate of&#160;10&#160;&#181;L/min. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67311/67311fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
To comparatively visualize the output of the different quantification methods the determined cell numbers are presented in the following two tables (Table 2 and Table 3). The final concentrations of cells determined using the three previously described methods are in a similar range for all methods. The cytometer provides the highest sample size, followed by the particle counter and the microscopic quantification, with a decrease of approximately one order of magnitude between the methods.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">Co-culture 1:1:1</td>
			<td>Photometer</td>
			<td colspan="2">Cytometer</td>
			<td colspan="2">Particle Counter</td>
			<td colspan="2">Microscopy Counting Chamber</td>
		</tr>
		<tr>
			<td colspan="2">Organism</td>
			<td>OD750/600</td>
			<td>cell count</td>
			<td>cells/mL</td>
			<td>cell count</td>
			<td>cells/mL</td>
			<td>cell count</td>
			<td>cells/mL</td>
		</tr>
		<tr>
			<td colspan="2">Saccharomyces cerevisiae mKate2</td>
			<td>0.0333</td>
			<td>13,618</td>
			<td>1.36 x 106</td>
			<td rowspan="2">1,546*</td>
			<td rowspan="2">2.58 x 106*</td>
			<td>112</td>
			<td>1.40 x 106</td>
		</tr>
		<tr>
			<td colspan="2">Ustilago maydis eGFP</td>
			<td>0.0333</td>
			<td>13,541</td>
			<td>1.35 x 106</td>
			<td>89</td>
			<td>1.11 x 106</td>
		</tr>
		<tr>
			<td colspan="2">Synechocystis sp. PCC 6803 mVenus</td>
			<td>0.0333</td>
			<td>42,330</td>
			<td>4.23 x 106</td>
			<td>3,094</td>
			<td>5.16 x 106</td>
			<td>271</td>
			<td>3.39 x 106</td>
		</tr>
	</tbody>
</table>
Table 2: Comparison of the different quantification methods: Artificial mixed culture.&#160;Note that&#160;U. maydis and&#160;S.&#160;cerevisiae cannot be distinguished using a particle&#160;counter (*).
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="2">Single culture</td>
			<td>Photometer</td>
			<td colspan="2">Cytometer</td>
			<td colspan="2">Particle Counter</td>
			<td colspan="2">Microscopy Counting Chamber</td>
		</tr>
		<tr>
			<td colspan="2">Organism</td>
			<td>OD750/600</td>
			<td>cell count</td>
			<td>cells/mL</td>
			<td>cell count</td>
			<td>cells/mL</td>
			<td>cell count</td>
			<td>cells/mL</td>
		</tr>
		<tr>
			<td colspan="2">Saccharomyces cerevisiae mKate2</td>
			<td>0.1</td>
			<td>38,936</td>
			<td>3.89 x 106</td>
			<td>1,928</td>
			<td>3.21 x 106</td>
			<td>403</td>
			<td>4.03 x 106</td>
		</tr>
		<tr>
			<td colspan="2">Ustilago maydis eGFP</td>
			<td>0.1</td>
			<td>36,927</td>
			<td>3.69 x 106</td>
			<td>2,465</td>
			<td>4.11 x 106</td>
			<td>307</td>
			<td>3.07 x 106</td>
		</tr>
		<tr>
			<td colspan="2">Synechocystis sp. PCC 6803 mVenus</td>
			<td>0.1</td>
			<td>127,864</td>
			<td>1.28 x 107</td>
			<td>8,186</td>
			<td>1.36 x 107</td>
			<td>428</td>
			<td>1.07 x 107</td>
		</tr>
	</tbody>
</table>
Table 3: Comparison of the different quantification methods: Calibration with single/axenic cultures.

Assembly and Quantification of Co-Cultures Combining Heterotrophic Yeast with Phototrophic Sugar-Secreting Cyanobacteria

This protocol provides a comprehensive guideline for the setup and quantitative monitoring of co-cultures, including photoautotrophic sugar-secreting cyanobacteria and heterotrophic yeasts.

With the increasing demand for sustainable biotechnologies, mixed consortia containing a phototrophic microbe and heterotrophic partner species are being ...

assembly-quantification-co-cultures-combining-heterotrophic-yeast

Nanyang Technological University

Research

JoVE Journal

Bioengineering

539 Views.  Heinrich Heine University Düsseldorf. This protocol provides a comprehensive guideline for the setup and quantitative monitoring of co-cultures, including photoautotrophic sugar-secreting cyanobacteria and heterotrophic yeasts. 

Video: Assembly and Quantification of Co-Cultures Combining Heterotrophic Yeast with Phototrophic Sugar-Secreting Cyanobacteria

Localization and Relative Quantification of Carbon Nanotubes in Cells with Multispectral Imaging Flow Cytometry

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich cell structures and de facto there is still no quantitative method to assess their distribution at cell and tissue levels. What we propose here is an innovative method allowing the detection and quantification of CNTs in cells using a multispectral imaging flow cytometer (ImageStream, Amnis). This newly developed device integrates both a high-throughput of cells and high resolution imaging, providing thus images for each cell directly in flow and therefore statistically relevant image analysis. Each cell image is acquired on bright-field (BF), dark-field (DF), and fluorescent channels, giving access respectively to the level and the distribution of light absorption, light scattered and fluorescence for each cell. The analysis consists then in a pixel-by-pixel comparison of each image, of the 7,000-10,000 cells acquired for each condition of the experiment. Localization and quantification of CNTs is made possible thanks to some particular intrinsic properties of CNTs: strong light absorbance and scattering; indeed CNTs appear as strongly absorbed dark spots on BF and bright spots on DF with a precise colocalization.
This methodology could have a considerable impact on studies about interactions between nanomaterials and cells given that this protocol is applicable for a large range of nanomaterials, insofar as they are capable of absorbing (and/or scattering) strongly enough the light.

In this study, the main purpose was to monitor the cellular uptake and eventual exocytosis of carbon nanotubes (CNTs). From this perspective, we proposed here a unique method using multispectral imaging flow cytometry allowing a quantification and localization of CNTs in a statistically relevant number of cells.

Carbon-based nanomaterials, like carbon nanotubes (CNTs), belong to this type of nanoparticles which are very difficult to discriminate from carbon-rich ...

ECM Protein Nanofibers and Nanostructures Engineered Using Surface-initiated Assembly

The extracellular matrix (ECM) in tissues is synthesized and assembled by cells to form a 3D fibrillar, protein network with tightly regulated fiber diameter, composition and organization. In addition to providing structural support, the physical and chemical properties of the ECM play an important role in multiple cellular processes including adhesion, differentiation, and apoptosis. In vivo, the ECM is assembled by exposing cryptic self-assembly (fibrillogenesis) sites within proteins. This process varies for different proteins, but fibronectin (FN) fibrillogenesis is well-characterized and serves as a model system for cell-mediated ECM assembly. Specifically, cells use integrin receptors on the cell membrane to bind FN dimers and actomyosin-generated contractile forces to unfold and expose binding sites for assembly into insoluble fibers. This receptor-mediated process enables cells to assemble and organize the ECM from the cellular to tissue scales. Here, we present a method termed surface-initiated assembly (SIA), which recapitulates cell-mediated matrix assembly using protein-surface interactions to unfold ECM proteins and assemble them into insoluble fibers. First, ECM proteins are adsorbed onto a hydrophobic polydimethylsiloxane (PDMS) surface where they partially denature (unfold) and expose cryptic binding domains. The unfolded proteins are then transferred in well-defined micro- and nanopatterns through microcontact printing onto a thermally responsive poly(N-isopropylacrylamide) (PIPAAm) surface. Thermally-triggered dissolution of the PIPAAm leads to final assembly and release of insoluble ECM protein nanofibers and nanostructures with well-defined geometries. Complex architectures are possible by engineering defined patterns on the PDMS stamps used for microcontact printing. In addition to FN, the SIA process can be used with laminin, fibrinogen and collagens type I and IV to create multi-component ECM nanostructures. Thus, SIA can be used to engineer ECM protein-based materials with precise control over the protein composition, fiber geometry and scaffold architecture in order to recapitulate the structure and composition of the ECM in vivo.

A method to obtain nanofibers and complex nanostructures from single or multiple extracellular matrix proteins is described. This method uses protein-surface interactions to create free-standing protein-based materials with tunable composition and architecture for use in a variety of tissue engineering and biotechnology applications.

The extracellular matrix (ECM) in tissues is synthesized and assembled by cells to form a 3D fibrillar, protein network with tightly regulated fiber ...

Formation of Biomembrane Microarrays with a Squeegee-based Assembly Method

Lipid bilayer membranes form the plasma membranes of cells and define the boundaries of subcellular organelles. In nature, these membranes are heterogeneous mixtures of many types of lipids, contain membrane-bound proteins and are decorated with carbohydrates. In some experiments, it is desirable to decouple the biophysical or biochemical properties of the lipid bilayer from those of the natural membrane. Such cases call for the use of model systems such as giant vesicles, liposomes or supported lipid bilayers (SLBs). Arrays of SLBs are particularly attractive for sensing applications and mimicking cell-cell interactions. Here we describe a new method for forming SLB arrays. Submicron-diameter SiO2 beads are first coated with lipid bilayers to form spherical SLBs (SSLBs). The beads are then deposited into an array of micro-fabricated submicron-diameter microwells. The preparation technique uses a "squeegee" to clean the substrate surface, while leaving behind SSLBs that have settled into microwells. This method requires no chemical modification of the microwell substrate, nor any particular targeting ligands on the SSLB. Microwells are occupied by single beads because the well diameter is tuned to be just larger than the bead diameter. Typically, more 75% of the wells are occupied, while the rest remain empty. In buffer SSLB arrays display long-term stability of greater than one week. Multiple types of SSLBs can be placed in a single array by serial deposition, and the arrays can be used for sensing, which we demonstrate by characterizing the interaction of cholera toxin with ganglioside GM1. We also show that phospholipid vesicles without the bead supports and biomembranes from cellular sources can be arrayed with the same method and cell-specific membrane lipids can be identified.

Supported lipid bilayers and natural membrane particles are convenient systems that can approximate the properties of cell membranes and be incorporated in a variety of analytical strategies. Here we demonstrate a method for preparing microarrays composed of supported lipid bilayer-coated SiO2 beads, phospholipid vesicles or natural membrane particles.

Lipid bilayer membranes form the plasma membranes of cells and define the boundaries of subcellular organelles. In nature, these membranes are ...

Micropatterning and Assembly of 3D Microvessels

In vitro platforms to study endothelial cells and vascular biology are largely limited to 2D endothelial cell culture, flow chambers with polymer or glass based substrates, and hydrogel-based tube formation assays. These assays, while informative, do not recapitulate lumen geometry, proper extracellular matrix, and multi-cellular proximity, which play key roles in modulating vascular function. This manuscript describes an injection molding method to generate engineered vessels with diameters on the order of 100 &#181;m. Microvessels are fabricated by seeding endothelial cells in a microfluidic channel embedded within a native type I collagen hydrogel. By incorporating parenchymal cells within the collagen matrix prior to channel formation, specific tissue microenvironments can be modeled and studied. Additional modulations of hydrodynamic properties and media composition allow for control of complex vascular function within the desired microenvironment. This platform allows for the study of perivascular cell recruitment, blood-endothelium interactions, flow response, and tissue-microvascular interactions. Engineered microvessels offer the ability to isolate the influence from individual components of a vascular niche and precisely control its chemical, mechanical, and biological properties to study vascular biology in both health and disease.

This manuscript presents an injection molding method to engineer microvessels that recapitulate physiological properties of endothelium. The microfluidic-based process creates patent 3D vascular networks with tailorable conditions, such as flow, cellular composition, geometry, and biochemical gradients. The fabrication process and examples of potential applications are described.

In vitro platforms to study endothelial cells and vascular biology are largely limited to 2D endothelial cell culture, flow chambers with polymer or glass ...

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available &#34;design space&#34; represented by &#34;devices&#34; created as combinations of individual genetic components. However, manual assembly of such large numbers of devices is time-intensive, error-prone, and costly. The increasing sophistication and scale of synthetic biology research necessitates an efficient, reproducible way to accommodate large-scale, complex, and high throughput device construction.
Here, a DNA assembly protocol using the Type-IIS restriction endonuclease based Modular Cloning (MoClo) technique is automated on two liquid-handling robotic platforms. Automated liquid-handling robots require careful, often times tedious optimization of pipetting parameters for liquids of different viscosities (e.g. enzymes, DNA, water, buffers), as well as explicit programming to ensure correct aspiration and dispensing of DNA parts and reagents. This makes manual script writing for complex assemblies just as problematic as manual DNA assembly, and necessitates a software tool that can automate script generation. To this end, we have developed a web-based software tool, http://mocloassembly.com, for generating combinatorial DNA device libraries from basic DNA parts uploaded as Genbank files. We provide access to the tool, and an export file from our liquid handler software which includes optimized liquid classes, labware parameters, and deck layout. All DNA parts used are available through Addgene, and their digital maps can be accessed via the Boston University BDC ICE Registry. Together, these elements provide a foundation for other organizations to automate modular cloning experiments and similar protocols.
The automated DNA assembly workflow presented here enables the repeatable, automated, high-throughput production of DNA devices, and reduces the risk of human error arising from repetitive manual pipetting. Sequencing data show the automated DNA assembly reactions generated from this workflow are ~95% correct and require as little as 4% as much hands-on time, compared to manual reaction preparation.

Here, an automated workflow to perform modular DNA &#34;device&#34; assembly using a modular cloning DNA assembly method on liquid-handling robots is presented. The protocol uses an intuitive software tool for generating liquid handler picklists for combinatorial DNA device library generation, which we demonstrate using two liquid handling platforms.

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available &#34;design space&#34; ...

Synthesis of Cationized Magnetoferritin for Ultra-fast Magnetization of Cells

Many important biomedical applications, such as cell imaging and remote manipulation, can be achieved by labeling cells with superparamagnetic iron oxide nanoparticles (SPIONs). Achieving sufficient cellular uptake of SPIONs is a challenge that has traditionally been met by exposing cells to elevated concentrations of SPIONs or by prolonging exposure times (up to 72 hr). However, these strategies are likely to mediate toxicity. Here, we present the synthesis of the protein-based SPION magnetoferritin as well as a facile surface functionalization protocol that enables rapid cell magnetization using low exposure concentrations. The SPION core of magnetoferritin consists of cobalt-doped iron oxide with an average particle diameter of 8.2 nm mineralized inside the cavity of horse spleen apo-ferritin. Chemical cationization of magnetoferritin produced a novel, highly membrane-active SPION that magnetized human mesenchymal stem cells (hMSCs) using incubation times as short as one minute and iron concentrations as lows as 0.2 mM.

A protocol for the synthesis and cationization of cobalt-doped magnetoferritin is presented, as well as a method to rapidly magnetize stem cells with cationized magnetoferritin.

Many important biomedical applications, such as cell imaging and remote manipulation, can be achieved by labeling cells with superparamagnetic iron oxide ...

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 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 ...

Co-transplantation of Human Ovarian Tissue with Engineered Endothelial Cells: A Cell-based Strategy Combining Accelerated Perfusion with Direct Paracrine Delivery

Infertility is a frequent side effect of chemotherapy and/or radiotherapy and for some patients, cryopreservation of oocytes or embryos is not an option. As an alternative, an increasing number of these patients are choosing to cryopreserve ovarian tissue for autograft following recovery and remission. Despite improvements in outcomes among patients undergoing auto-transplantation of cryopreserved ovarian tissue, efficient revascularization of grafted tissue remains a major obstacle. To mitigate ischemia and thus improve outcomes in patients undergoing auto-transplantation, we developed a vascular cell-based strategy for accelerating perfusion of ovarian tissue. We describe a method for co-transplantation of exogenous endothelial cells (ExECs) with cryopreserved ovarian tissue in a mouse xenograft model. We extend this approach to employ ExECs that have been engineered to constitutively express Anti-Mullerian hormone (AMH), thus enabling sustained paracrine signaling input to ovarian grafts. Co-transplantation with ExECs increased follicular volume and improved antral follicle development, and AMH-expressing ExECs promoted retention of quiescent primordial follicles. This combined strategy may be a useful tool for mitigating ischemia and modulating follicular activation in the context of fertility preservation and/or infertility at large.

For some patients, the only option for fertility preservation is cryopreservation of ovarian tissue. Unfortunately, delayed revascularization undermines follicular viability. Here, we present a protocol to co-transplant human ovarian tissue with endothelial cells for utilization as a cell-based strategy combining accelerated perfusion with a direct paracrine delivery of bioactive molecules.

Infertility is a frequent side effect of chemotherapy and/or radiotherapy and for some patients, cryopreservation of oocytes or embryos is not an option. ...

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the cognitive powers of the brain with comparable efficiency and density. To date, silicon-based three-terminal transistors and two-terminal memristors have been widely used in neuromorphic circuits, in large part due to their ability to co-locate information processing and memory. Yet these devices cannot achieve the interconnectivity and complexity of the brain because they are power-hungry, fail to mimic key synaptic functionalities, and suffer from high noise and high switching voltages. To overcome these limitations, we have developed and characterized a biomolecular memristor that mimics the composition, structure, and switching characteristics of biological synapses. Here, we describe the process of assembling and characterizing biomolecular memristors consisting of a 5 nm-thick lipid bilayer formed between lipid-functionalized water droplets in oil and doped with voltage-activated alamethicin peptides. While similar assembly protocols have been used to investigate biophysical properties of droplet-supported lipid membranes and membrane-bound ion channels, this article focuses on key modifications of the droplet interface bilayer method essential for achieving consistent memristor performance. Specifically, we describe the liposome preparation process and the incorporation of alamethicin peptides in lipid bilayer membranes, and the appropriate concentrations of each constituent as well as their impact on the overall response of the memristors. We also detail the characterization process of biomolecular memristors, including measurement and analysis of memristive current-voltage relationships obtained via cyclic voltammetry, as well as short-term plasticity and learning in response to step-wise voltage pulse trains.

Soft, low-power, biomolecular memristors leverage similar composition, structure, and switching mechanisms of bio-synapses. Presented here is a protocol to assemble and characterize biomolecular memristors obtained from insulating lipid bilayers formed between water droplets in oil. The incorporation of voltage-activated alamethicin peptides results in memristive ionic conductance across the membrane.

The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the ...

Establishing Single-Cell Based Co-Cultures in a Deterministic Manner with a Microfluidic Chip

Cell co-culture assays have been widely used for studying cell-cell interactions between different cell types to better understand the biology of diseases including cancer. However, it is challenging to clarify the complex mechanism of intercellular interactions in highly heterogeneous cell populations using conventional co-culture systems because the heterogeneity of the cell subpopulation is obscured by the average values; the conventional co-culture systems can only be used to describe the population signal, but are incapable of tracking individual cells behavior. Furthermore, conventional single-cell experimental methods have low efficiency in cell manipulation because of the Poisson distribution. Microfabricated devices are an emerging technology for single-cell studies because they can accurately manipulate single cells at high-throughput and can reduce sample and reagent consumption. Here, we describe the concept and application of a microfluidic chip for multiple single-cell co-cultures. The chip can efficiently capture multiple types of single cells in a culture chamber (~46%) and has a sufficient culture space useful to study the cells&#39; behavior (e.g., migration, proliferation, etc.) under cell-cell interaction at the single-cell level. Lymphatic endothelial cells and oral squamous cell carcinoma were used to perform a single-cell co-culture experiment on the microfluidic platform for live multiple single-cell interaction studies.

This report describes a microfluidic chip-based method to set up a single cell culture experiment in which high-efficiency pairing and microscopic analysis of multiple single cells can be achieved.

Cell co-culture assays have been widely used for studying cell-cell interactions between different cell types to better understand the biology of diseases ...