The authors thank Salman Khetani, Jared Allen, Chris Flaim, and Austin Derfus for helpful discussions during the process of designing this device. This work was supported by the National Science Foundation Faculty Early Career Development Program, National Institutes of Health/National Institute of Diabetes and Digestive and Kidney Diseases, and the David and Lucile Packard Foundation. E.E.H. was supported by a Ruth L. Kirschstein National Research Service Award.

Preparation of cell cultures:
<ol>
<li>Start with silicon parts coated with plasma-treated polystyrene. </li>
<li>Coat parts with appropriate extracellular matrix proteins to support attachment of desired cell type. For hepatocytes, incubate in 50 g/ml Collagen-1 solution at 37&deg;C for 45 min. For 3T3 fibroblasts, no matrix is needed. </li>
<li>Lock parts with complementary parts in contact configuration. </li>
<li>Soak in 70% ethanol for a minimum of 10 min to sterilize. Rinse 2x in ddH2O, and 1x in cell culture media. </li>
<li>Seed cells at a concentration of 500,000 cells/ml in the appropriate culture medium. Use 1 ml in each well of a 12-well culture plate. </li>
<li>Incubate for 1 hr, shaking every 15 min to re-suspend cells evenly. </li>
<li>If a confluent monolayer has not been achieved after 1 hr, aspirate the cell suspension and repeat seeding with a fresh suspension. Repeat until the desired cell density has been achieved. </li>
<li>Remove the complementary parts. Transfer parts to fresh wells and incubate overnight to allow cells to adhere and spread fully. </li>
<li>Form co-cultures by locking appropriate parts into either the gap or contact configuration. The configuration may be changed at any desired point during culture. </li>
<li>When changing media, take care to leave cells dry for as little time as possible, preferably just a second or two. Draw out fluid with one hand and immediately replace media using the other hand. </li>
</ol>
Processing silicon parts for reuse:
<ol>
<li>Strip cells by soaking in bleach and rinsing with water. </li>
<li>Allow parts to dry completely. Soak in toluene for 2 h to strip polystyrene. </li>
<li>Clean in piranha solution (1:2 H2O2:H2SO4) heated to 120&deg;C. </li>
<li>Rinse for 15 min under a continuous flow of ddH2O. If you are not going to deposit polystyrene immediately, store the parts in water. </li>
<li>Dissolve polystyrene in toluene at 100 mg/ml. Vortex in polypropylene conical for about 1 hr, or until fully dissolved. A little more than 1 ml of solution is required for every 10 parts. </li>
<li>Spin coat polystyrene solution on individual silicon parts at 2,400 rpm for 30 sec. </li>
<li>Bake for at least 5 h at 120&deg;C. </li>
<li>Treat with oxygen plasma (200 mTorr, 200 W) for 1 min. </li>
</ol>

<ol>
	<li>Hui, E. E., Bhatia, S. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Micromechanical+control+of+cell-cell+interactions.">Micromechanical control of cell-cell interactions.</a> Proceedings of the National Academy of Sciences. 104, 5722-5726 (2007).</li><li>Bhatia, S. N., Balis, U. J., Yarmush, M. L., Toner, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effect+of+cell-cell+interactions+in+preservation+of+cellular+phenotype:+cocultivation+of+hepatocytes+and+nonparenchymal+cells.">Effect of cell-cell interactions in preservation of cellular phenotype: cocultivation of hepatocytes and nonparenchymal cells.</a> The FASEB Journal. 13, 1883-1900 (1999).</li><li>El-Ali, J., Sorger, P. K., Jensen, K. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cells+on+Chips.">Cells on Chips.</a> Nature. 442, 403-411 (2006).</li></ol>

The authors have nothing to disclose.

This system is unique in that it enables the spatial organization of tissue to be dynamically manipulated at the cellular level. Consequently, this device has enabled a number of novel biological experiments, spanning topics such as intercellular signaling dynamics, contact-mediated versus soluble signaling, cell fate decisions, toxicology, and cellular crosstalk. This device should be widely generalizable since the culture substrate is standard tissue culture plastic, and the system is compatible with standard culture m...

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">	
		
		<div>
		<table border="1">
		<thead>
		<tr>
		<th>Material Name</th>
		<th>Type</th>
		<th>Company</th>
		<th>Catalogue Number</th>
		<th>Comment</th>
		</tr>
		</thead>
		<tbody>
		
<tr>
<td>Silicon Comb Substrates</td>
<td>Tool</td>
<td>N/A</td>
<td>N/A</td>
<td>Parts are available for collaborative research projects. Please contact Elliot Hui (eehui @ alum . mit . edu) or Sangeeta Bhatia (sbhatia @ mit . edu).</td>
</tr>		</tbody>
		</table>
		</div>
			<div>
					</div>

silicon microchips for manipulating cell-cell interaction

The role of the cellular microenvironment is recognized as crucial in determining cell fate and function in virtually all mammalian tissues from development to malignant transformation.&nbsp; In particular, interaction with neighboring stroma has been implicated in a plethora of biological phenomena; however, conventional techniques limit the ability to interrogate the spatial and dynamic elements of such interactions.
In Micromechanical Reconfigurable Culture (RC), we employ a micromachined silicon substrate with moving parts to dynamically control cell-cell interactions through mechanical repositioning. Previously, this method has been applied to investigate intercellular communication in co-cultures of hepatocytes and non-parenchymal cells, demonstrating time-dependent interactions and a limited range for soluble signaling 1.
Here, we describe in detail the preparation and use of the RC system. We begin by demonstrating the handling of the device parts using tweezers, including actuating between the gap and contact configurations (cell populations separated by a narrow 80-&micro;m gap, or in direct intimate contact). Next, we detail the process of preparing the substrates for culture, and the multi-step cell seeding process required for obtaining confluent cell monolayers. Using live microscopy, we then illustrate real-time manipulation of cells between the different possible experimental configurations. Finally, we demonstrate the steps required in order to regenerate the device surface for reuse: toluene and piranha cleaning, polystyrene coating, and oxygen plasma treatment.

Watch this Scientific Journal Video about Silicon Microchips for Manipulating Cell-cell Interaction at JoVE.com

Silicon Microchips for Manipulating Cell-cell Interaction

This article describes an experimental approach for dynamic regulation of cell-cell interactions between adherent cells on a micrometer scale. Manipulation of intercellular communication between hepatocytes and stromal cell is demonstrated. The developed platform enables investigation of cell-cell interactions in a variety of biological processes, including development and pathogenesis.

The role of the cellular microenvironment is recognized as crucial in determining cell fate and function in virtually all mammalian tissues from ...

silicon-microchips-for-manipulating-cell-cell-interaction

Research

JoVE Journal

Biology

10.7K Views.  MIT - Massachusetts Institute of Technology. This article describes an experimental approach for dynamic regulation of cell-cell interactions between adherent cells on a micrometer scale. Manipulation of intercellular communication between hepatocytes and stromal cell is demonstrated. The developed platform enables investigation of cell-cell interactions in a variety of biological processes, including development and pathogenesis.

Video: Silicon Microchips for Manipulating Cell-cell Interaction

Using Laser Tweezers For Manipulating Isolated Neurons In Vitro

In this paper and video, we describe the protocols used in our laboratory to study the targeting preferences of regenerating cell processes of adult retinal neurons in vitro. Procedures for preparing retinal cell cultures start with the dissection, digestion and trituration of the retina, and end with the plating of isolated retinal cells on dishes made especially for use with laser tweezers. These dishes are divided into a cell adhesive half and a cell repellant half. The cell adhesive side is coated with a layer of Sal-1 antibodies, which provide a substrate upon which our cells grow. Other adhesive substrates could be used for other cell types. The cell repellant side is coated with a thin layer of poly-HEMA. The cells plated on the poly-HEMA side of the dish are trapped with the laser tweezers, transported and then placed adjacent to a cell on the Sal-1 side to create a pair. Formation of cell groups of any size should be possible with this technique. "Laser-tweezers-controlled micromanipulation" means that the investigator can choose which cells to move, and the desired distance between the cells can be standardized. Because the laser beam goes through transparent surfaces of the culture dish, cell selection and placement are done in an enclosed, sterile environment. Cells can be monitored by video time-lapse and used with any cell biological technique required. This technique may help investigations of cell-cell interactions.

This video describes the manipulation of cultured neurons using laser tweezers in vitro.

In this paper and video, we describe the protocols used in our laboratory to study the targeting preferences of regenerating cell processes of adult ...

Automated Hydrophobic Interaction Chromatography Column Selection for Use in Protein Purification

In contrast to other chromatographic methods for purifying proteins (e.g. gel filtration, affinity, and ion exchange), hydrophobic interaction chromatography (HIC) commonly requires experimental determination (referred to as screening or "scouting") in order to select the most suitable chromatographic medium for purifying a given protein 1. The method presented here describes an automated approach to scouting for an optimal HIC media to be used in protein purification.
HIC separates proteins and other biomolecules from a crude lysate based on differences in hydrophobicity. Similar to affinity chromatography (AC) and ion exchange chromatography (IEX), HIC is capable of concentrating the protein of interest as it progresses through the chromatographic process. Proteins best suited for purification by HIC include those with hydrophobic surface regions and able to withstand exposure to salt concentrations in excess of 2 M ammonium sulfate ((NH4)2SO4). HIC is often chosen as a purification method for proteins lacking an affinity tag, and thus unsuitable for AC, and when IEX fails to provide adequate purification. Hydrophobic moieties on the protein surface temporarily bind to a nonpolar ligand coupled to an inert, immobile matrix. The interaction between protein and ligand are highly dependent on the salt concentration of the buffer flowing through the chromatography column, with high ionic concentrations strengthening the protein-ligand interaction and making the protein immobile (i.e. bound inside the column) 2. As salt concentrations decrease, the protein-ligand interaction dissipates, the protein again becomes mobile and elutes from the column. Several HIC media are commercially available in pre-packed columns, each containing one of several hydrophobic ligands (e.g. S-butyl, butyl, octyl, and phenyl) cross-linked at varying densities to agarose beads of a specific diameter 3. Automated column scouting allows for an efficient approach for determining which HIC media should be employed for future, more exhaustive optimization experiments and protein purification runs 4.
The specific protein being purified here is recombinant green fluorescent protein (GFP); however, the approach may be adapted for purifying other proteins with one or more hydrophobic surface regions. GFP serves as a useful model protein, due to its stability, unique light absorbance peak at 397 nm, and fluorescence when exposed to UV light 5. Bacterial lysate containing wild type GFP was prepared in a high-salt buffer, loaded into a Bio-Rad DuoFlow medium pressure liquid chromatography system, and adsorbed to HiTrap HIC columns containing different HIC media. The protein was eluted from the columns and analyzed by in-line and post-run detection methods. Buffer blending, dynamic sample loop injection, sequential column selection, multi-wavelength analysis, and split fraction eluate collection increased the functionality of the system and reproducibility of the experimental approach.

An automated method for identifying suitable hydrophobic interaction chromatography (HIC) media to be used in the process of protein purification is presented. The method utilizes a medium-pressure liquid chromatography system including automated buffer blending, dynamic sample loop injection, sequential column selection, multi-wavelength analysis, and split fraction eluate collection.

In contrast to other chromatographic methods for purifying proteins (e.g. gel filtration, affinity, and ion exchange), hydrophobic interaction ...

A Liquid Phase Affinity Capture Assay Using Magnetic Beads to Study Protein-Protein Interaction: The Poliovirus-Nanobody Example

In this article, a simple, quantitative, liquid phase affinity capture assay is presented. Provided that one protein can be tagged and another protein labeled, this method can be implemented for the investigation of protein-protein interactions. It is based on one hand on the recognition of the tagged protein by cobalt coated magnetic beads and on the other hand on the interaction between the tagged protein and a second specific protein that is labeled. First, the labeled and tagged proteins are mixed and incubated at room temperature. The magnetic beads, that recognize the tag, are added and the bound fraction of labeled protein is separated from the unbound fraction using magnets. The amount of labeled protein that is captured can be determined in an indirect way by measuring the signal of the labeled protein remained in the unbound fraction. The described liquid phase affinity assay is extremely useful when conformational conversion sensitive proteins are assayed. The development and application of the assay is demonstrated for the interaction between poliovirus and poliovirus recognizing nanobodies1. Since poliovirus is sensitive to conformational conversion2 when attached to a solid surface (unpublished results), the use of ELISA is limited and a liquid phase based system should therefore be preferred. An example of a liquid phase based system often used in polioresearch3,4 is the micro protein A-immunoprecipitation test5. Even though this test has proven its applicability, it requires an Fc-structure, which is absent in the nanobodies6,7. However, as another opportunity, these interesting and stable single-domain antibodies8 can be easily engineered with different tags. The widely used (His)6-tag shows affinity for bivalent ions such as nickel or cobalt, which can on their turn be easily coated on magnetic beads. We therefore developed this simple quantitative affinity capture assay based on cobalt coated magnetic beads. Poliovirus was labeled with 35S to enable unhindered interaction with the nanobodies and to make a quantitative detection feasible. The method is easy to perform and can be established with a low cost, which is further supported by the possibility of effectively regenerating the magnetic beads.

In this article, a simple, quantitative, liquid phase affinity capture assay is presented. It is a reliable technique based on the interaction between magnetic beads and tagged proteins (e.g. nanobodies) on one hand and the affinity between the tagged protein and a second, labeled protein (e.g. poliovirus) on the other.

In this article, a simple, quantitative, liquid phase affinity capture assay is presented. Provided that one protein can be tagged and another protein ...

Manipulating the Murine Lacrimal Gland

The lacrimal gland (LG) secretes aqueous tears necessary for maintaining the structure and function of the cornea, a transparent tissue essential for vision. In the human a single LG resides in the orbit above the lateral end of each eye delivering tears to the ocular surface through 3 - 5 ducts. The mouse has three pairs of major ocular glands, the most studied of which is the exorbital lacrimal gland (LG) located anterior and ventral to the ear. Similar to other glandular organs, the LG develops through the process of epithelial branching morphogenesis in which a single epithelial bud within a condensed mesenchyme undergoes multiple rounds of bud and duct formation to form an intricate interconnected network of secretory acini and ducts. This elaborate process has been well documented in many other epithelial organs such as the pancreas and salivary gland. However, the LG has been much less explored and the mechanisms controlling morphogenesis are poorly understood. We suspect that this under-representation as a model system is a consequence of the difficulties associated with finding, dissecting and culturing the LG. Thus, here we describe dissection techniques for harvesting embryonic and post-natal LG and methods for ex vivo culture of the tissue.

The lacrimal gland (LG) is a branching organ that produces the aqueous components of tears necessary for maintaining vision and ocular health. Here we describe murine LG dissection and ex vivo culture techniques to decipher signaling pathways involved in LG development.

The lacrimal gland (LG) secretes aqueous tears necessary for maintaining the structure and function of the cornea, a transparent tissue essential for ...

Identifying Protein-protein Interaction Sites Using Peptide Arrays

Protein-protein interactions mediate most of the processes in the living cell and control homeostasis of the organism. Impaired protein interactions may result in disease, making protein interactions important drug targets. It is thus highly important to understand these interactions at the molecular level. Protein interactions are studied using a variety of techniques ranging from cellular and biochemical assays to quantitative biophysical assays, and these may be performed either with full-length proteins, with protein domains or with peptides. Peptides serve as excellent tools to study protein interactions since peptides can be easily synthesized and allow the focusing on specific interaction sites. Peptide arrays enable the identification of the interaction sites between two proteins as well as screening for peptides that bind the target protein for therapeutic purposes. They also allow high throughput SAR studies. For identification of binding sites, a typical peptide array usually contains partly overlapping 10-20 residues peptides derived from the full sequences of one or more partner proteins of the desired target protein. Screening the array for binding the target protein reveals the binding peptides, corresponding to the binding sites in the partner proteins, in an easy and fast method using only small amount of protein.
In this article we describe a protocol for screening peptide arrays for mapping the interaction sites between a target protein and its partners. The peptide array is designed based on the sequences of the partner proteins taking into account their secondary structures. The arrays used in this protocol were Celluspots arrays prepared by INTAVIS Bioanalytical Instruments. The array is blocked to prevent unspecific binding and then incubated with the studied protein. Detection using an antibody reveals the binding peptides corresponding to the specific interaction sites between the proteins.

Peptide array screening is a high throughput assay for identifying protein-protein interaction sites. This allows mapping multiple interactions of a target protein and can serve as a method for identifying sites for inhibitors that target a protein. Here we describe a protocol for screening and analyzing peptide arrays.

Protein-protein interactions mediate most of the processes in the living cell and control homeostasis of the organism. Impaired protein interactions may ...

Inducible LAP-tagged Stable Cell Lines for Investigating Protein Function, Spatiotemporal Localization and Protein Interaction Networks

Multi-protein complexes, rather than single proteins acting in isolation, often govern molecular pathways regulating cellular homeostasis. Based on this principle, the purification of critical proteins required for the functioning of these pathways along with their native interacting partners has not only allowed the mapping of the protein constituents of these pathways, but has also provided a deeper understanding of how these proteins coordinate to regulate these pathways. Within this context, understanding a protein's spatiotemporal localization and its protein-protein interaction network can aid in defining its role within a pathway, as well as how its misregulation may lead to disease pathogenesis. To address this need, several approaches for protein purification such as tandem affinity purification (TAP) and localization and affinity purification (LAP) have been designed and used successfully. Nevertheless, in order to apply these approaches to pathway-scale proteomic analyses, these strategies must be supplemented with modern technological developments in cloning and mammalian stable cell line generation. Here, we describe a method for generating LAP-tagged human inducible stable cell lines for investigating protein subcellular localization and protein-protein interaction networks. This approach has been successfully applied to the dissection of multiple cellular pathways including cell division and is compatible with high-throughput proteomic analyses.

We describe a method for generating localization and affinity purification (LAP)-tagged inducible stable cell lines for investigating protein function, spatiotemporal subcellular localization and protein-protein interaction networks.

Multi-protein complexes, rather than single proteins acting in isolation, often govern molecular pathways regulating cellular homeostasis. Based on this ...

Luciferase Complementation Imaging Assay in Nicotiana benthamiana Leaves for Transiently Determining Protein-protein Interaction Dynamics

Protein-protein interactions are fundamental mechanisms for relaying signal transduction in most cellular processes; therefore, identification of novel protein-protein interaction pairs and monitoring protein interaction dynamics are of particular interest for revealing how plants respond to environmental factors and/or developmental signals. A plethora of approaches have been developed to examine protein-protein interactions, either in vitro or in vivo. Among them, the recently established luciferase complementation imaging (LCI) assay is the simplest and fastest method for demonstrating in vivo protein-protein interactions. In this assay, protein A or protein B is fused with the amino-terminal or carboxyl-terminal half of luciferase, respectively. When protein A interacts with protein B, the two halves of luciferase will be reconstituted to form a functional and active luciferase enzyme. Luciferase activity can be recorded with a luminometer or CCD-camera. Compared with other approaches, the LCI assay shows protein-protein interactions both qualitatively and quantitatively. Agrobacterium infiltration in Nicotiana benthamiana leaves is a widely used system for transient protein expression. With the combination of LCI and transient expression, these approaches show that the physical interaction between COP1 and SPA1 was gradually reduced after jasmonate treatment.

Luciferase Complementation Imaging Assay in Nicotiana benthamiana Leaves for Transiently Determining Protein-protein Interaction Dynamics

This manuscript describes an easy and rapid experimental procedure for determining protein-protein interactions based on the measurement of luciferase activity.

Protein-protein interactions are fundamental mechanisms for relaying signal transduction in most cellular processes; therefore, identification of novel ...

Visualization of DNA Repair Proteins Interaction by Immunofluorescence

Mammalian cells are constantly exposed to chemicals, radiations, and naturally occurring metabolic by-products, which create specific types of DNA insults. Genotoxic agents can damage the DNA backbone, break it, or modify the chemical nature of individual bases. Following DNA insult, DNA damage response (DDR) pathways are activated and proteins involved in the repair are recruited. A plethora of factors are involved in sensing the type of damage and activating the appropriate repair response. Failure to correctly activate and recruit DDR factors can lead to genomic instability, which underlies many human pathologies including cancer. Studies of DDR proteins can provide insights into genotoxic drug response and cellular mechanisms of drug resistance.
There are two major ways of visualizing&#160;proteins in vivo: direct observation, by tagging the protein of interest with a fluorescent protein and following it by live imaging, or indirect immunofluorescence on fixed samples. While visualization of fluorescently tagged proteins allows precise monitoring over time, direct tagging in N- or C-terminus can interfere with the protein localization or function. Observation of proteins in their unmodified, endogenous version is preferred. When DNA repair proteins are recruited to the DNA insult, their concentration increases locally and they form groups, or &#8220;foci&#8221;, that can be visualized by indirect immunofluorescence using specific antibodies.
Although detection of protein foci does not provide a definitive proof of direct interaction, co-localization of proteins in cells indicates that they regroup to the site of damage and can inform of the sequence of events required for complex formation. Careful analysis of foci spatial overlap in cells expressing wild type or mutant versions of a protein can provide precious clues on functional domains important for DNA repair function. Last, co-localization of proteins indicates possible direct interactions that can be verified by co-immunoprecipitation in cells, or direct pulldown using purified proteins.

Following DNA damage, human cells activate essential repair pathways to restore the integrity of their genome. Here, we describe the method of indirect immunofluorescence as a means to detect DNA repair proteins, analyze their spatial and temporal recruitment, and help interrogate protein-protein interaction at the sites of DNA damage.

Mammalian cells are constantly exposed to chemicals, radiations, and naturally occurring metabolic by-products, which create specific types of DNA ...

AirID-Based Proximity Labeling for Protein-Protein Interaction in Plants

In mammalian cells and plants, proximity labeling (PL) approaches using modified ascorbate peroxidase (APEX) or the Escherichia coli biotin ligase BirA (known as BioID) have proven successful in identifying protein-protein interactions (PPIs). APEX, BioID, and TurboID, a revised version of BioID have some restrictions in addition to being valuable technologies. The recently developed AirID, a novel version of BioID for proximity identification in protein-protein interactions, overcame these restrictions. Previously, AirID has been used in animal models, while the current study demonstrates the use of AirID in plants, and the results confirmed that AirID performs better in plant systems as compared to other PL enzymes such as BioID and TurboID for protein labeling that are proximal to the target proteins. Here is a step-by-step protocol for identifying protein interaction partners using AT4G18020 (APRR2) protein as a model. The methods describe the construction of vector, the transformation of construct through agroinfiltration, biotin transformation, extraction of proteins, and enrichment of biotin-labeled proteins through affinity purification technique. The results conclude that AirID is a novel and ideal enzyme for analyzing PPIs in plants. The method can be applied to study other proteins in plants.

Here, we present a step-by-step protocol for performing the proximity labeling (PL) experiment in cucumber (Cucumis sativus L.) using AT4G18020 (APRR2)-AirID protein as a model. The method describes the construction of a vector, the transformation of a construct through agroinfiltration, biotin infiltration, protein extraction, and purification of biotin-labeled proteins through affinity purification technique.

In mammalian cells and plants, proximity labeling (PL) approaches using modified ascorbate peroxidase (APEX) or the Escherichia coli biotin ligase BirA ...

CorrelationCalculator: A Bioinformatics Tool for Building Single Interaction Metabolites Network Based on Expression Data

To begin, download a sample comma-delimited input file containing a list of metabolites with experimental measurements. Double click on the downloaded sample file to open it and verify that it contains labels for both the samples and the metabolites. Next, download the correlation calculator Java application, and double click on the downloaded JAR file to launch the application.On the input tab, click the browse button to upload the input file. Under specify file format, select samples in rows. Click on the next button from the bottom right of the window to move to the data normalization tab.Under select methods, check the box next to log to transform data and autoscale data. Under normalized data, click the run button. Once the normalization is complete, click the save button to save the new data file.Click on the next button to move to the data analysis tab and under Calculate Pearson's Correlation, click run to determine the best Pearson's correlation range for the data. Click on the view histogram button to review the frequency of the maximal Pearson's correlation scores per feature in the view heat map button to review the representation of Pearson's correlation matrix. Under Filter by Pearson's Correlations, leave the default numbers to filter by a range of 0.00 to 1.00.Then under Select Partial Correlation Method, select the desired method as DSPC method. And under Calculate Partial Correlations, click the run button. Click on the view CSV file to view the results, and click the save button to save the results.A representative network constructed from a subset of the KORA population study metabolomics data consisting of 151 metabolites across 240 subjects is shown. Consensus network clustering resulted in the identification of nine sub-networks or metabolic modules.