Experiments in vitro vs those with dead organisms and fixated tissue

Experiments in vitro vs those with dead organisms and fixated tissue

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Does the term in vitro necessarily imply that the organism/organs/cells of study are dead?

If not, is there an alternative latin term to refer to studies of dead biological matter ? (e.g. in Connectomics where the tissue is biologically dead, and has been fixated and sectioned with a microtome)

Does the term in vitro necessarily imply that the organism/organs/cells of study are dead?

No, in vitro studies are often carried out with living cells - just think of in vitro fertilisation. The nearest I can come up with for what you want is histology, but I think even this encompasses studies of living cells and tissues.

Tissue macrophages: heterogeneity and functions

Macrophages are present in all vertebrate tissues, from mid-gestation throughout life, constituting a widely dispersed organ system. They promote homeostasis by responding to internal and external changes within the body, not only as phagocytes in defence against microbes and in clearance of dead and senescent cells, but also through trophic, regulatory and repair functions. In this review, we describe macrophage phenotypic heterogeneity in different tissue environments, drawing particular attention to organ-specific functions.

Biology Chapter 1

DNA migrates throughout the cell and interacts directly with other molecules in the cytoplasm.

DNA is translated into protein and then transcribed to RNA.

The information in DNA is transcribed to RNA and then usually translated into protein.

A-Individuals in a population of any species vary in many heritable traits.

B-Individuals with heritable traits best suited to the local environment will generally produce a disproportionate number of healthy, fertile offspring.

C-A population of any species has the potential to produce far more offspring than will survive to produce offspring of their own.

systems biology . reductionism

descent from a common ancestor . adaptation through natural selection

ensures that the variable being tested is measured without error

ensures that hypotheses can be confirmed with certainty

allows rejection of hypotheses

nonsystematic observation and analysis of data

If the animals observed require organic molecules as nutrients, then it can be concluded that all animals require organic molecules as nutrients.

Because worms lack bones, they are classified as invertebrates.

A paramecium moves by means of the rhythmic motion of its cilia.

some conceivable observation or experiment could reveal whether a given hypothesis is incorrect

the hypothesis has been proved wrong

only a controlled experiment can prove whether the hypothesis is correct or incorrect

in rephrasing an alternative hypothesis

during the formulation of a hypothesis

during initial observation(s)

explaining naturally occurring events

determining the physical causes for physical phenomena

formulating testable hypotheses in seeking natural causes for natural phenomena

that the drug seems to have little effect on viral transmission at the dosage given

nothing, because no control group was used in the test of the drug

that the drug is effective and testing on humans should begin

grow bean plants with and without sodium

look for sodium in leaf tissues using autoradiography

measure the amount of sodium in a few bean plants

is too difficult for researchers doing fieldwork

is not necessary if the scientist obtains enough background information

should always be done by changing a variable

No, it is not necessary to test only one variable per experiment, especially when time is of the essence.

As long as the experiment is repeated a sufficient number of times, it does not matter how many variables are used.

Yes, an experiment should test only one variable at a time. That way, the experiment will have to be performed only once.

a well-supported concept that has broad explanatory power

a poorly supported idea that has little backing but might be correct

not correct unless it is several years old

None of the listed responses is correct.

both negative feedback where the pathway shuts down and positive feedback where the pathway speeds up

negative feedback where the pathway does not change

negative feedback where the pathway speeds up

positive feedback where the pathway shuts down

Regardless of whether the models were placed in the beach or the inland habitat, the camouflaged model always acted as the __________ group.

Molecule, tissue, cell, organelle, organ

Community, population, ecosystem, habitat, biosphere

Organism, ecosystem, community, population, biosphere

Tissue, organ system, organ, cell, organism

transcription, translation, and protein folding

translation, transcription, and protein folding

protein folding, translation, and transcription

protein folding, transcription, and translation

are bacteria, archaea, and eukarya

are animalia, plantae, and fungi

are bacteria, archaea, and animalia

are bacteria, protists, and animalia

allows us to reduce complex systems to simpler components that are more manageable to study

starts at the global scale for studying biology

focuses on information that is seen from space

is never used in the study of biology

forming and testing hypotheses

community analysis and feedback

exploration and discovery

societal benefits and outcomes

involves chemical cycling from light energy from the sun for the production of chemical energy in food to the decomposition and the returning of chemicals to the cycle

involves chemical cycling from chemical energy in food to light energy from the sun to heat lost from the ecosystem


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1.4. Primary cell culture

As discussed above, the primary cell culture is the first culture of cells, tissues or organs derived directly from an organism in other words it is the culture before the first subculture, whereas the cell line is for maintenance or propagation of a culture after subculture. There are certain techniques available for the development of primary cell cultures, such as:

  • Mechanical disaggregation.
  • Enzymatic disaggregation.
  • Primary explant techniques.

1.4.1. Mechanical disaggregation

It is necessary to disaggregate soft tissues such as soft tumors. The mechanical approach involves slicing or harvesting tissue and subsequent harvesting of spill out cells. This can be achieved by sieving, syringing and pipetting. This procedure is inexpensive, rapid and simple, however, all these approaches involve the risk of cell damage, thus mechanical disaggregation is only used when the viability of the cells in the final yield is not very important.

1.4.2. Enzymatic disaggregation

This approach involves efficient disaggregation of cells with high yield by using enzymes such as trypsin, collagenase and others. Enzyme based disaggregation allows hydrolysis of fibrous connective tissue and the extracellular matrix. Currently, the enzymatic method is extensively used as it offers high recovery of cells without affecting the viability of cells. Trypsin based disaggregation or trypsinization

This allows disaggregation of tissue using trypsin, usually crude trypsin because this trypsin contains other proteases. In addition, cells can tolerate crude trypsin well and the ultimate effect of crude trypsin can easily be neutralized by serum or trypsin inhibitor (supplementation of trypsin inhibitor is required in the case of serum-free media). Pure trypsin can also be utilized for disaggregation of cells, provided that it is less toxic and very specific in its action. An overview of primary cell culture development is shown in figure 1.1. Two common approaches, namely warm and cold trypsinization, are described in the following.

Figure 1.1. Alternative approaches for the preparation of primary cell cultures.

Warm trypsinization

This approach is extensively utilized for the disaggregation of cells. During the initial step, sliced tissue is washed with dissection basal salt solution and is subsequently transferred to a container of warm trypsin (37 °C). At regular intervals of 30 min the contents are stirred properly. Then, the supernatant having dissociated, the cells are separated to disperse in a suitable medium. Efficient dispersion of cells can be achieved by placing the container over ice.

Cold trypsinization

This method is also called trypsinization with cold pre-exposure. In this process the chance of cellular damage due to constant exposure to trypsin is reduced, which results in a high yield of viable cells with an improved survival rate for the cells (after 24 h of incubation). Since this method does not involve frequent stirring or centrifugation, it can be conveniently adopted in the research laboratory. During this process, after washing and chopping, tissue pieces are kept over ice in a vial and then subjected to treatment with cold trypsin for 6–24 h. Then, after the cold trypsin treatment the trypsin is removed and discarded. However, the tissue fragments still contain residual trypsin. These fragments are incubated at 37 °C (for 20–30 min) followed by repeated pipetting. This will encourage the dispersion of cells. The fully dispersed cells can be counted using a cell counter and properly diluted, and then further utilized.

Drawbacks of trypsin disaggregation

Trypsinization of cells can damage some cells, such as epithelial cells, and sometimes it is not effective for certain tissues, such as fibrous connective tissue, thus other enzymes are also recommended for dissociation of cells. Collagenase based disaggregation

Collagenase is an enzyme which is responsible for the cleavage of peptide bonds in collagen. Collagen is a structural protein which is abundantly found in higher animals, mainly in the extracellular matrix of connective tissue and muscle. Collagenase, mainly crude collagenase, can be successfully used for the disaggregation of several tissues that may or may not be sensitive to trypsin. Purified collagenase has also been experimented with, but has shown poor results in comparison to crude collagenase. So far collagenase disaggregation has be carried out on several human tumors, epithelial tissues, the brain, lungs and other mammalian tissue. The combination of collagenase with hyaluronidase offers better results in disaggregating rat or rabbit liver, which can be achieved by perfusing the whole organ in situ. Several researchers have also utilized trypsin and collagenase in combination to dissociate cells to develop chick serum.

This process involves an initial transfer of the desired tissue into a basal salt solution which contains antibiotics. This is followed by washing with settling and then transfer into a medium containing collagenase. The solution is incubated for 1–5 days, followed by repeated pipetting for uniform dispersal of cells. Separation of these dispersed cells is encouraged by keeping the solution in a stationary phase to further encourage the settling of cells, as shown in figure 1.2.

Figure 1.2. Standard growth curve of cells in a culture. Other enzymes

In addition to the above mentioned enzymes, certain other enzymes such as bacterial proteases (e.g. dispase, pronase) have been tested, but unfortunately have not shown significant results. However, enzymes such as hyaluronidase and neuraminidase have received attention due to their significant results, and thus can potentially be utilized in conjugation with the enzymes discussed above.

1.4.3. Primary explant technique

In 1907 Harrison provided the first demonstration of the primary explant technique, which subsequently underwent many modifications. A simple protocol for the primary explant technique is represented in figure 1.1. As in the above procedures, in this process tissue is initially suspended in basal salt solution and then chopped properly and washed by settling. Tissue fragments are uniformly distributed over the growth surface. This is followed by the addition of a suitable medium and then incubation for 3–5 days. Old medium is replaced by fresh medium unless desired growth or considerable outgrowth of the cells is not achieved. Once optimum growth is achieved the explants are separated and transferred to new culture vessels which contain fresh medium.

This technique is mainly used for disaggregation of small quantities of tissue. Mechanical and enzymatic disaggregation are not suitable for small amounts of tissues, as there is a risk of cell damage which can ultimately affect cell viability. A major drawback of this technique is the poor adhesiveness of certain tissues on the growth surface (substrate material), which can create problems in the selection of cells for desirable outgrowth. However, this technique has been utilized frequently for culturing embryonic cells, in particular glial cells, fibroblasts, myoblasts and epithelial cells.

Stepwise Procedeures

1. Cell Culture [TIMING ~ 4 Days]

1.1) Seed cells into 100 mm culture dishes at 25�% confluence, and grow them for 3 days (at 37ଌ and 5% CO2) in appropriate culture medium (e.g., M3 cells, use DMEM with 10% (vol/vol) FBS [see Reagent Setup)].

1.2) Remove medium from culture dish by gentle aspiration, wash cells twice with sterile 1X PBS, add trypsin-EDTA enough to completely cover the cells and place them at 37ଌ for 2 min. After incubation, add an equal volume of complete medium to stop the trypsin-EDTA reaction and collect all the liquid in a sterile tube. Centrifuge the cell suspension for 5 min at 300 g at RT, then remove the trypsin-EDTA solution by aspiration and mix the cells with fresh medium containing serum. Determine cell concentration using a hemocytometer.

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1.3) (Optional step, depending on the cell type used) Coating dishes with extracellular matrix (ECM) substrates (e.g., gelatin, collagen, or fibronectin) in order to adhere the cells and incubate it at 4ଌ overnight.

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2. Wound Healing Assay Using Silicone Insert vs. Scratch Assay Using Pipette Tip

2.1) Seed the cell suspension into each well with the silicone culture insert on 35 mm culture insert μ-dish to perform wound healing assay (option A), or alternatively seed cells onto all surface of 35 mm culture μ-dish to perform scratch assay (option B) (see scheme on Figure 1A). Incubate the dishes for 6 h or overnight at 37ଌ and 5% CO2, allowing cells to adhere and spread on the substrate. The number of cells to create a confluent monolayer depends on your cell type and the size of dishes. You have to adjust the characteristics depending on these parameters [e.g., using M3 cells, seed 3뜐 4 cells/well when using the silicone culture insert (area for each well = 0.22 cm 2 ) and seed 4.5뜐 5 cells/dish (area for dish = 3.5 cm 2 )].

CRITICAL STEP. To ensure the reproducibility on the results, it is very important to create a confluent cell monolayer (90�% confluence) and maintain a constant seeding number specific to each cell line.

2.2) Follow option A to perform the wound healing assay with culture insert, and option B to perform scratch assay with pipette tip (Figure 1A).

(A) In vitro wound healing assay (with insert) and data analysis [TIMING ~ 2 days]

(i) Check the cells under the microscope to ensure that a confluent cell monolayer (95�%) is created.

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(ii) Remove the culture insert with sterile forceps.

CRITICAL STEP. Use sterile forceps to grab the insert slowly and gently from the dish. Avoid twisting the insert.

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(iii) Remove debris and non-attached cells by washing the cell layer twice with 1 ml of sterile 1X PBS and then replace it with 2 ml of appropriate medium for the assay, if it is necessary add a treatment to the medium (e.g., metastasis inhibitor Wang et al., 2015, antibiotics Zhu et al., 2016, depending on the aim of the experiment).

CRITICAL STEP. Pre-warm the 1X PBS and the medium at 37ଌ. Avoid detaching cells in the wash.

(iv) Place the dish under a phase-contrast scanning confocal microscope with a CO2 microscope cage incubator, image acquisition is performed at 37ଌ and 5% CO2. Define exact positions and focal planes, avoiding overlapping fields. Start image acquisition by taking images several times throughout 20� h (e.g., time-lapse measurements for cultured M3 melanoma cells were performed for 20 h with a time interval of 1 h and 10X objective). Select 3 or 4 fields from each wound and at least three wounds per sample.

CRITICAL STEP. Prior to the time-lapse microscopy setup, switch on the CO2 and temperature to equilibrate the system at least 30 min before starting acquisition. Ensure that the parameters are set at 5% CO2 and 37ଌ.

OPTIONAL STRATEGY. Fluorescent-tagged cells can be used in this assay, although the segmentation steps prior to wound area quantification should be modified, as right now they are optimized for transmission light images. You must also be careful with light intensity during time-lapse acquisition, as it may cause photo-toxicity.

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(v) After acquiring the time-lapse images, review the frames in a sequence format ( * .tif, * .oif, * .zvi or equivalent).

PAUSE POINT. Data processing can be conducted as per convenience of user.

(vi) Quantitative data analysis can be performed with Open-source software (ImageJ/Fiji). In ImageJ/Fiji, time-lapse sequences can be opened by clicking FileOpen.

(vii) Calibrate the image sequence by using AnalyzeSet scale and introduce the correct scale (pixels/μm) depending on the objective and microscope used (Supplementary Figure 1A), if this information is not stored automatically by your microscope's software in the data file.

CRITICAL STEP. It is important to set the correct scale for the cell migration analysis.

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(viii) Select the measurement parameters AnalyzeSet measurementsArea (Supplementary Figure 1A).

(ix) Click on duplicate the image sequence ImageDuplicate.

(x) Detect the change intensity on the edge on the duplicate sequence ProcessFind edges (Supplementary Figure 1B).

(xi) Apply a blurred edge filter ProcessFiltersGaussian Blur (e.g., Sigma (Radius) = 5) (Supplementary Figure 1C).

(xii) Adjust the intensity threshold to detect the wound area ImageAdjustThreshold (Supplementary Figure 1D).

CRITICAL STEP. Correctly define the threshold parameter to determine exactly the empty wound area. By default, the macro is running an AutoThreshold using the Minimum method (Supplementary Data 1), which acceptably operates in most of time-lapse data.

(xiii) Create a selection around the threshold area EditSelectionCreate selection.

(xiv) The area selection is first shrunk and then enlarged (e.g., 10 pixels) in order to eliminate small thresholded areas not related with the wound, and then is returned back to the original size in the wound EditSelectionEnlarge (e.g., first plug20, then 20).

(xv) Add all time-points into ROI manager AnalyzeToolROI manager.

Steps xiii – xv must be repeated for every time-point if done manually (without using the macro).

(xvi) Obtain the area value in the different time-points AnalyzeMeasure (Supplementary Figure 1E).

(xvii) We have written the steps between (ix) and (xvi) in a macro for ImageJ/Fiji to automatically analyze the wound healing area in each image sequence. The code “Wound_healing.ijm” is provided in Supplementary Data 1. Execute this code at ImageJ/Fiji and your time-lapse images will be automatically quantified.

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(xviii) Additionally, Click on “Straight” button (toolbar) and measure the length (μm) between one side of the scratch and the other in the images acquired at initial (0 h) and end time to determine the cell front velocity. Scratch length measurement should be done in three regions of each image between the closest points on both sides of the wound.

(xix) Import the data to spreadsheet software and determine the relative wound area closure, velocity, and other parameters (see ANTICIPATED RESULTS and Figure 2). Statistical significance of the differences between samples was estimated by unpaired two-tailed Student's t-test, which can be performed straight in the spreadsheet. If your experimental setup includes more than two conditions to compare, you may use more specific software like SPSS, where you could perform more complex analysis by one-way ANOVA followed by Tukey-Kramer post-hoc test.

(B) In vitro scratch assay (with pipette tip) and data analysis [TIMING ~ 2 days]

(i) Continuing from step 2.2 (option B), make a wound by scratching the cell monolayer in a straight line with a sterile P-200 pipette tip.

CRITICAL STEP. Scratching should be done gently with a P-200 pipette tip in a straight line in the center of the dish to only detach central cells. Try to move the tip in a continuous way and always with a similar size in each well to avoid variation between conditions.

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(ii) Wash twice with 1 ml of sterile 1X PBS to remove the floating cells and debris and add 2 ml of appropriate medium for the assay (if it is necessary add a treatment in the medium).

CRITICAL STEP. Pre-warm the 1X PBS and the medium at 37ଌ. Avoid detaching cells in the wash.

(iii) Repeat steps 2.2(A) (iv-v) for phase-contrast scanning setup and acquisition parameters.

(iv) Quantitative data analysis. Repeat steps 2.2(A) (vi)–(xvii). In ImageJ/Fiji, open the individual images and perform the same procedure.

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(v) Additionally, Click on “Straight” button (toolbar) and measure the length (μm) between one side of the scratch and the other in the images acquired at initial (0 h) and end time to determine the cell front velocity. Length scratch measurement should be done in three regions of each image between the closest points on both sides of the wound.

(vi) Import data to spreadsheet software and proceed as explained in the step 2.2(A) (xix).

3. Individual Cell-Tracking Assay and Data Analysis [TIMING ~ 2 Days]

3.1) Continuing from step 1.2 (or optionally step 1.3), seed 1.2뜐 4 cells in 500 μl of proper complete medium onto each well on 24-well plates and grow them overnight (at 37ଌ and 5% CO2) (e.g., for M3 melanoma cells, use DMEM with 10% (vol/vol) FBS (see Reagent Setup) and perform at least three biological replicates for each different experimental condition).

CRITICAL STEP. To analyze individual cell-tracking, cells are seeded at low density. The number of seeded cells depends on the characteristics of the cell type and the size of dishes.

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3.2) Carefully remove the debris and dead cells by washing the wells once with 500 μl of sterile 1X PBS and then replace it with 500 μl of proper medium for the assay. Add a specific treatment in the medium, if necessary.

3.3) Immediately place the 24-well plate under the phase-contrast or fluorescence microscope with a CO2 microscope cage incubator (at 37ଌ and 5% CO2). Perform time-lapse imaging (e.g., taking an image every 20 min for 20 h using 20X objective). You should acquire about 10� fields for each of the three biological replicates in order to obtain data from at least 300 cells.

CRITICAL STEP. Define the image acquisition setup depending on the previous knowledge about your cell line (e.g., higher temporal resolution if your cell line is known to have high motility). Avoid overlapping fields.

CRITICAL STEP. Prior to time-lapse microscopy setup, switch on the CO2 and temperature to equilibrate the system at least 30 min before starting acquisition. Ensure that the parameters are set at 5% CO2 and 37ଌ.

OPTIONAL STRATEGY. Fluorescent-tagged cells can be used in this assay. You must also be careful with light intensity during time-lapse acquisition, as it may cause photo-toxicity.

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3.4) Quantitative data analysis. Repeat steps 2.2(A) (v)-(vii).

3.5) Open PluginsTrackingManual Tracking.

3.6) Set the parameters “Time interval,” “x/y calibration,” and “z calibration” in the Manual Tracking (Supplementary Figure 2A).

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3.7) Start individual cell-tracking analysis, click on “Add track” and then select one cell in the first time-point and follow it through all time-points, finally click on “End track.” Repeat it for all the cells in the frame through all the time-points. A new window with the results (track, slice, distance and velocity) appears (Supplementary Figure 2B).

3.8) Save the values in (.txt) format and click on “Overlay dots and line” to save the sequence with the track.

3.9) Download Chemotaxis plugin and open it in ImageJ/Fiji PluginsChemotaxis tool. Alternatively, the “Chemotaxis and migration tool” software can be downloaded and used with the same function (see EQUIPMENT).

3.10) Set parameters. Click on “Settings” and apply the correct settings for “Time interval” and “x/y calibration” (Supplementary Figure 2C).

? Troubleshooting

3.11) Import dataset. Click on “Import data” and select the (.txt) file with the obtained values in Manual Tracking plugin. Select the file, set the number of slices to analyze and click on “Add dataset.” Select up to four datasets and work simultaneously on this plugin (Supplementary Figure 2D). Optionally add some restrictions in the parameters. Click on “Open restrictions” and “set split dataset,” “threshold distance,” and “threshold velocity.”

3.12) Click on “Apply settings.”

3.13) Click on “Plot feature” select no marks (or appropriate marks), adjust the axis scaling and click on “Plot graph” to obtain the trajectory plot. Optionally, an animated trajectory plot can be obtained.

3.14) (Optional step, depending on the analysis). Click on “Diagram feature” and select “Plot histogram,” “Plot rose diagram,” or “Circular plot” to obtain several plots that show an orientation/distribution of all cell migration directions.

3.15) Click on “Statistics feature” and select “velocity,” “distance” (euclidean and accumulated), “FMI” (Forward Migration Index) and “directionality.” Save or export these data to spreadsheet software.

3.16) In the spreadsheet software, determine the mean and standard deviation (SD) of velocity (μm/h), accumulated distance (μm), euclidean distance (μm) and others parameters (see ANTICIPATED RESULTS and Figure 3). Statistical significance of the differences between samples was estimated by unpaired two-tailed Student's t-test, which can be performed straight in the spreadsheet. If your experimental setup includes more than two conditions to compare, you may use more specific software like SPSS, where you could perform more complex analysis by one-way ANOVA followed by Tukey-Kramer post-hoc test.

4. Transwell Cell Migration/Invasion Assay and Data Analysis [TIMING ~ 2 Days]

4.1) This assay can be used to analyze cell migration and/or invasion. To analyze cell invasion, the transwell insert membrane is coated with Matrigel while in cell migration assays it is not. This procedure is identic for both possibilities the only difference is the presence or not of Matrigel. (If you want to do a migration assay omit the Matrigel steps).

4.2) Matrigel step: Thaw the Matrigel solution at 4 ଌ overnight. Coat the down side surface of the transwell membrane with 25 μl of Matrigel solution (see the preparation in Reagent Setup, Figure 4A).

CRITICAL STEP. Matrigel solution is liquid at 4ଌ, but it gels very quickly at RT. Remember to work in cold conditions and previously chill at �ଌ all the material (pipettes, tips, and forceps).

4.3) Incubate the transwell with Matrigel at 37ଌ for 30 min for gelling.

? Troubleshooting

4.4) (Optional step) Wash off the Matrigel of the down side of the membrane twice with pre-warmed serum-free culture medium (e.g., for M3 melanoma cells culture use DMEM medium without FBS).

CRITICAL STEP. Gentle washes. Avoid detaching Matrigel in the washes.

4.5) Add 500 μl of culture medium (with or without chemoattractant) into each well on 24-well plate (e.g., for melanoma cells transwell assay, 10% FBS was used as a chemoattractant. See scheme Figure 4B).

4.6) (Optional step) Add a treatment in the culture medium if necessary.

4.7) Use sterile forceps to transfer the transwell insert into each well of the 24-well plate already filled with culture medium (with or without chemoattractant).

4.8) Continue from step 1.2, add 400 μl of cell suspension (at final confluence 50�%) onto the transwell upper chamber (see scheme Figure 4A).

CRITICAL STEP. Depending on your cell type size, the required pore size of the transwell membrane insert may change (e.g., in this protocol 8 μm pore diameter membranes are used).

4.9) Incubate at 37ଌ and 5% CO2 for 20� h.

4.10) Fix cells by adding paraformaldehyde (PFA) at final concentration 4% in culture medium into both sides of each transwell insert for 15 min at RT. CAUTION. Perform cell fixation in a safety chemical fume hood, and wear appropriate personal protective equipment.

4.11) Remove culture medium with 4% PFA by gentle aspiration.

4.12) Wash transwell insert twice at both sides of the membrane with sterile 1X PBS to remove debris, non-attached cells, and fixation solution excess.

CRITICAL STEP. Be gentle with all washes to avoid detaching cells.

PAUSE POINT. Samples can be stored in 1X PBS at 4ଌ for up to 1 month.

4.13) Stain cells, by incubating the transwell insert (with or without Matrigel) with Hoechst (final concentration 10 μg ml 𢄡 in 400 μl of 1X PBS) for 15 min at RT protected from light. (Crystal violet or Hematoxylin can also be used).

CRITICAL STEP. From this step until step 4.18 work in dark conditions.

4.14) Wash the transwell insert twice with sterile 1X PBS to remove Hoechst solution excess.

4.15) Maintain inserts in the 24-well plate with sterile 1X PBS to avoid drying the membrane.

4.16) Capture several images in order to cover up all the surface of the transwell insert membrane, either with Matrigel coating or not, using 10X or 4X objectives on a fluorescence microscope. To avoid overlapping fields, an automatic tiling function when acquiring images may be used (if it is available in your equipment). The number of cells counted using these images will be the total number of cells in invasion assay (if Matrigel was used) or the total number of cells in migration assay (if Matrigel was not used).

4.17) Immediately remove non-invaded/migrated cells from the upper surface of the transwell membrane by gently scrapping with a cotton swab. If Crystal violet or Hematoxilin is used the membrane turns blue. Scrap the membrane surface until the last swab used remains white (or clean).

CRITICAL STEP. Be careful with scrapping. Scrapping must be gentle with little pressure to remove all the cells on the upper surface of the membrane but not affecting the migrated/invaded cells of the bottom. If it is necessary, repeat the scrapping with a second cotton swab.

? Troubleshooting

4.18) Repeat step 4.16, but in this case the acquired images represent the invaded or migrated cells (with or without Matrigel, respectively).

4.19) Quantitative data analysis can be performed with Open-source software (ImageJ/Fiji). In ImageJ/Fiji, acquired images can be opened by clicking FileOpen.

4.20) Select ProcessFind Maxima to measure automatically the total number of cells in each image.

? Troubleshooting

4.21) Adjust the parameter “Noise tolerance” to avoid background noise, detect, and count all cells (nuclei stained by Hoechst) (Supplementary Figure 3A).

? Troubleshooting

4.22) (Alternatively to step 4.20𠄴.21), a manual counting can be obtained by opening PluginsAnalyzeCell counter.

4.23) Select “Initialize” and “Type I” and click on the cells (nuclei stained by Hoechst) manually to obtain the total number of cells (Supplementary Figure 3B).

4.24) Import data to the spreadsheet software and determine the percentage of migrated and/or invaded cells (see ANTICIPATED RESULTS and Figure 4). Statistical significance of the differences between samples was estimated by unpaired two-tailed Student's t-test, which can be performed straight in the spreadsheet. If your experimental setup includes more than two conditions to compare, you may use more specific software like SPSS, where you could perform more complex analysis by one-way ANOVA followed by Tukey-Kramer post-hoc test.

5. Spreading Assay and Data Analysis [TIMING ~ 2 Days]

5.1) Continue from step 1.2, seed 5뜐 4 cells in 500 μl of proper medium for the cell line used onto each well on 24-well plates and grow them overnight or at least 6 h (at 37ଌ and 5% CO2), allowing cells to adhere (e.g., for M3 cells, use DMEM with 10% (vol/vol) FBS (see Reagent Setup). Perform at least three biological replicates for each different experimental condition).

CRITICAL STEP. Cells are seeded at 60�% confluence. The number of seeded cells depends on the cell type and the size of dishes.

5.2) Remove medium from each well by gentle aspiration, wash the cells once with sterile 1X PBS and add 500 μl of medium (with or without treatment).

5.3) Incubate at 37ଌ and 5% CO2 for 24 h.

CRITICAL STEP. The incubation period depends on the treatment and the experiment.

5.4) Coat the wells of a new 24-well plate with 250 μl of fibronectin (10 μg ml 𢄡 ) and incubate for 1 h at 37ଌ or overnight at 4ଌ (see the preparation in Reagent Setup). Other extracellular matrix (ECM) substrates can be used e.g., gelatin or collagen, depending on your cell line.

? Troubleshooting

5.5) Remove the unbound fibronectin by gentle aspiration and wash twice with sterile 1X PBS.

5.6) (Optional step to block chemoattractant proteins present in the extracellular matrix coating). Add 200 μl of heat-denatured BSA solution (10 mg ml 𢄡 ) into each well, incubate for 30 min at RT or overnight at 4ଌ and wash twice with sterile 1X PBS (see the preparation in Reagent Setup).

5.7) After step 5.3, remove medium (with or without treatment) from each well by gentle aspiration, wash cells once with sterile 1X PBS and add trypsin-EDTA to completely cover the cells. Place them at 37ଌ for 2 min. Add equal volume of complete medium to stop the trypsin-EDTA reaction. Centrifuge the cell suspension for 5 min at 300 g at RT, and then remove the trypsin-EDTA and complete media solution by aspiration. Mix cells with 500 μl of fresh medium containing serum.

5.8) Seed 2뜐 4 cells in 500 μl of proper medium (according to cell line used) onto the fibronectin coated 24-well plate (step 5.5).

? Troubleshooting

5.9) Incubate at 37ଌ and 5% CO2 for 1 h.

CRITICAL STEP. The incubation period depends on the cell type and the treatment used. This cell type-specific binding time must be determined previously by the researchers.

? Troubleshooting

5.10) Fix cells. Add PFA in the medium (final concentration 2%) of each well for 15 min at RT.

CAUTION. Perform the cell fixation in a safety chemical fume hood, and wear appropriate personal protective equipment.

5.11) Remove culture medium containing 2% PFA by gentle aspiration.

5.12) Wash the wells twice with sterile 1X PBS to remove debris, non-attached cells, and fixation solution excess.

CRITICAL STEP. Be gentle with all washes to avoid detaching the cells.

PAUSE POINT. Samples can be stored in 1X PBS at 4ଌ for up to 1 month.

5.13) Acquire several images of fixed cells in a phase-contrast microscope using 10X objective and avoid overlapping fields.

5.14) Quantitative data analysis can be performed with Open-source software (ImageJ/Fiji). In ImageJ/Fiji, acquired images can be opened by clicking FileOpen.

CRITICAL STEP. In order to be analyzed, images must be 8-bit. If they are in a different bit depth, modify them by clicking ImageType8-bit.

5.15) Image background was substracted using a rolling ball of 10px radius by clicking ProcessSubstract background. Afterwards, the image was duplicated by clicking ImageDuplicate. One image will be used to quantify the unspread cells, while in the other one we will quantify all the cells.

5.16) To quantify unspread cells (Supplementary Figure 4A), the image was thresholded by the Yen method, just leaving the brightest sections of the image (corresponding to unspread cells) by clicking ImageAdjustThreshold and selecting the Yen method. This creates a binary image. Afterwards, the image was inverted by clicking in EditInvert.

5.17) Some binary operations, like 𠇎rode,” 𠇍ilate,” and 𠇏ill Holes” were performed in order to polish the thresholding you can find them in ProcessBinary → … Later, the watershed algorithm was used to segment cells that were touching each other, by clicking ProcessBinaryWatershed.

5.18) Particle number was counted automatically by clicking AnalyzeAnalyze particles, setting a minimal size of 100px 2 (as smaller particles were just little remains of other features coming from the thresholding, not real unspread cells).

5.19) To quantify all cells (Supplementary Figure 4B), the duplicated image created in step 5.15 was used. First, to better detect the spread cells, we highlighted all the cell edges by clicking ProcessFind Edges. Afterwards, the image was inverted by clicking in EditInvert.

5.20) The image was thresholded using the Trinagle method, less restrictive than the Yen method but still selecting where the cells are, by clicking ImageAdjustThreshold and selecting the Triangle method, creating a binary image.

5.21) Some binary operations, like 𠇎rode,” 𠇍ilate,” and 𠇏ill Holes” were performed in order to polish the thresholding, you can find them in ProcessBinary → … Later, the watershed algorithm was used to segment cells that were touching each other, by clicking ProcessBinaryWatershed.

5.22) Particle number was counted automatically by clicking AnalyzeAnalyze particles, setting a minimal size of 100px 2 (as smaller particles were just little remains of other features coming from the thresholding, not real cells).

5.23) We have written the steps between 5.15 and 5.22 in a macro for ImageJ/Fiji to automatically analyze and determine the number of unspread and total cells in the image. The code “Unspreadɪll_.ijm” is provided in Supplementary Data 3. Execute this code at ImageJ/Fiji and your images will be automatically quantified.

CRITICAL STEP. The macro may have troubles in identifying the total number of cells if the cells are seeded too confluent it is better to seed at lower density and take images of a few more fields in order to ensure a reliable quantification. Otherwise, the analysis may be done manually (PluginsAnalyzeCell counter), but this will slow down the quantification a lot, and still it is hard to identify the boundary between cells if the culture is too confluent.

CRITICAL STEP. Round and refringent cells were considered unspread, while dark cells with cytoplasm surrounding the entire circumference of the nucleus were considered spread cells. The sum of spread and unspread cells is the total number of cells. We can infer the number of spread cells from the difference between total number of cells and unspread cells.

5.24) Import data to the spreadsheet software and determine the percentage of spread cells to total cells (see ANTICIPATED RESULTS and Figure 5). Statistical significance of the differences between samples was estimated by unpaired two-tailed Student's t-test, which can be performed straight in the spreadsheet. If your experimental setup includes more than two conditions to compare, you may use more specific software like SPSS, where you could perform more complex analysis by one-way ANOVA followed by Tukey-Kramer post-hoc test.

Figure 1. Overview of the wound healing assay preparation protocols. (A) Step-by-step scheme showing the differences between wound healing protocol using a culture insert (option A) and using pipette tip (option B). Phase-contrast microscopy shows gap appearance and both cell fronts just before to start the time-lapse experiment. (B) Measurements of wound width (μm) in culture insert (n = 50) or pipette tip (n = 50). Mean values (thick horizontal lines), confidence limits (α = 0.05, thin horizontal lines), and coefficients of variation (label) are shown.

Figure 2. Analysis of M3 melanoma cells migration by in vitro wound healing assay. (A) Time-lapse microscopy images of wound closure of untreated (left panels) and treated with Chloroquine (CQ 25 μM, right panels) melanoma cells at 0, 10, and 20 h after culture insert removal. The dotted lines define the area lacking cells. Scale bars, 100 μm. (B) Quantification of the wounded area invaded during 20 h by untreated (green) and treated with CQ 25 μM (red) melanoma cells presented in relative units (r.u.). Results represent the mean of four measurements of each wounded area, obtained in 3 independent experiments (n = 12). Mean values of relative wound closure and corresponding confidence limits (α = 0.05, shaded lines) are plotted. Dotted line marks the time in which significant differences start. (C) Analysis of cell front velocity in untreated and CQ 25 μM treated melanoma cells. Mean ± SD from 3 independent experiments (n = 12). (D) Quantification of healing speed area (μm 2 /h) during 20 h in untreated and treated cells (n = 12). Dotted lines mark the average of healing speed area in each treatment. (E) Graph showing the average healing speed area (μm 2 /h) quantitative analysis of untreated and treated (CQ 25 μM) melanoma cells mean ± SD, (n = 12), from 3 independent experiments. The corresponding p-values obtained by unpaired two-tailed Student's t-test are shown in (C,E) plots.

Figure 3. Analysis of individual melanoma cells migration. (A) Representative phase-contrast images of untreated and treated with Mibefradil (5 μM) melanoma cells (captured by time-lapse microscopy at 20 min intervals) at initial (0 h) and end (20 h) time. The Manual Tracking plugin of ImageJ/Fiji was used to manually trace 14 representative cell trajectory tracks, marked in colors. Scale bars, 100 μm. (B) Trajectory plots showing melanoma cells trajectory during 20 h in untreated (green) and treated (red) cells. All tracks were set to a common origin (intersection of x and y axes) using Chemotaxis plugin of ImageJ/Fiji. (C) Quantitative analysis of average accumulated distance (μm) and (D) velocity (μm/h) of untreated and Mibefradil (5 μM) treated melanoma cells. Values are means ± SD (n = 5 independent experiments 300 cells were analyzed for each group). The corresponding p-values obtained by unpaired two-tailed Student's t-test are shown in (C,D) plots.

Figure 4. Quantitative and qualitative analysis of melanoma cell migration assessed by in vitro transwell assay. (A) Schematic illustration of the different parts of transwell system. (B) Experimental design scheme of transwell migration assay. Cells were seeded on the upper side of the transwell membrane. In the upper and/or lower compartment, 10% FBS was added as a chemoattractant (red color). When stated, Mibefradil (5 μM) was added in lower compartment. (C) Representative fluorescent images of nuclear Hoechst staining (10 μg ml 𢄡 ) were captured at 20 h after treatment indicated total cells (left panel) and migrated cells (right panel). Scale bars, 100 μm. (D) Percentage of migrated cells after 20 h, with or without treatment and (–) or (+) chemoattractant (10% FBS). Cells were counted from 10 random microscope fields for each sample in 3 independent experiments. Values are means ± SD. The corresponding p-values (*** = p < 0.0001) were obtained by one-way ANOVA followed by Tukey-Kramer post-hoc test.

Figure 5. Cell spreading assay in M3 melanoma cells. (A) Experimental design scheme of spreading assay. Cells were treated for 24 h, trypsinized and seeded onto fibronectin (10 μg ml 𢄡 ) coated plate. After 1 h cells were fixed with 2% PFA and (B) phase-contrast images were captured. Scale bars, 50 μm. (C) Plot showing the percentage of spreading cells. Round bright cells were considered unspread. Values are percentage of spread cells ± SD (n = 3 independent experiments at least 600 cells for each experiment were counted). The corresponding p-value obtained by unpaired two-tailed Student's t-test is shown.


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  3. Winsor L. Tissue processing. In Woods A and Ellis R eds. Laboratory histopathology. New York: Churchill Livingstone, 19944.2-1 - 4.2-39.
  4. Williams JH, Mepham BL, Wright DH. Tissue preparation for immunocytochemistry. J Clin Pathol 199750422-428.
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2. Amine dyes.

Amine dyes are one of the greatest flow cytometry inventions since automatic compensation. First, they are fixable, so whether you’re traditionally staining your cells or fixing and permeabilizing your cells, the fluorescence is maintained. As a result, you can batch a large number of samples while still keeping your flow cytometry best practices intact.

Second, amine dyes are available in a wide range of excitation and emission profiles, making them extremely easy to work into today’s increasingly multi-parametric and multicolor assays. Amine dyes are also membrane impermeant, but rather than binding DNA, they work by binding the amine groups of cellular proteins. Live cells with intact membranes will allow the dye access only to the few amines on the cell surface, while dead cells will allow the dye access to the many more amines on proteins inside the cell, resulting in higher fluorescence.

Pros: There is a wide selection of amine dyes from multiple manufacturers so you can fit these into any flow cytometry antibody panel with ease. Amine dyes are also fixable so they can be easily integrated into batching protocols. Finally, amine-reactive beads are now readily available for use as your dead cell marker compensation control.

Cons: While amine dyes are ideal for your fixation and permeabilization experiments, their use will add time to your fixation protocol. In addition, amine dyes are more expensive than the other reagents listed here. Titration of your amine dyes can reduce costs, but titration must be done carefully to minimize the number freeze-thaw cycles you subject the reagents to. Most importantly, you must remember to label your cells with amine reactive dyes only in the absence of free protein, otherwise you’ll stain the protein in your solution, not the cells of interest.

2 Collagen Type I

2.1 General Introduction about Collagen

Collagen is a ubiquitous protein in animals. Only among the vertebrates, already 28 different types of collagen can be found. [ 7 ] All collagen-containing supramolecular structures in an organism are formed by different types of collagen and also noncollagenous components. The combination of collagen types, [ 8 ] postsynthesis modifications, [ 9 ] and the interaction with noncollagenous components is specific for each tissue and its function. [ 10 ]

Collagen type I is the most abundant fibrillar protein of the extracellular matrix (ECM), being present in bone, skin, tendons, and ligaments. [ 11 ] It is a heterotrimeric molecule composed of two α1-chains and one α2-chain. These left-handed chains adopt a right-handed triple helix as tertiary structure. Each α-chain has a characteristic [Gly-Xaa-Yaa] repeating unit, with Xaa and Yaa being majorly proline (Pro) and 4-hydroxyproline (4-Hyp), respectively. The Gly-Pro-Hyp sequence represents the 12% of the amino acids. [ 12 ] Glycine residues showed to be essential for the formation of the triple helix and mutations in its position are related to diseases, such as osteogenesis imperfecta (also known as the brittle bone disease). [ 13 ]

2.2 Structure of Collagen Microfibrils and Fibrils

The collagen molecules (Figure 1a) have a length of ≈300 nm and a width of ≈1.5 nm. They spontaneously assemble into fibrils and fibers that can be up to 1 cm in length and 1 µm in diameter, depending on the tissue.

Fibrils are composed of smaller rope-like building blocks called microfibrils. These are formed of five tropocollagen molecules arranged with an offset of 67 nm between neighboring molecules (Figure 1b). Their organization in a quasihexagonal unit cell with an axial length of 67 nm [ 14 ] was confirmed by high-resolution mapping combined with crystallographic information and modeling. [ 15 ] Orgel et al. were able to fit the amino sequence of collagen to the experimental electron density map of collagen molecules obtained in situ. [ 15 ] The quasihexagonal structure is maintained throughout the microfibril and each unit cell contains the molecular segments of four tropocollagen molecules and a gap region. Being able to visualize the full path covered by a single molecule through successive unit cells allowed to determine that neighboring microfibers are interdigitated by crosslinks, which explains why it is not possible to isolate microfibrils. [ 7 ] The interpretation of the electron density map also provides insight into the collagen regions that interact with other biomolecules. [ 16 ] Moreover, collagen fibrils can bundle into fibers. The orientation in which the fibrils align within the fibers largely contributes to the mechanical properties of different tissues.

The staggered arrangement of collagen molecules within the microfibrils into gap and overlap regions leads to a characteristic banding pattern that can be easily observed by electron microscopy as zones of low and high contrast, as shown in Figure 1d. This banding pattern is termed D-periodicity, D-spacing, or D-band pattern, with D-periodicity the most commonly used term.

With chemical staining, several sub-bands can be identified. Positive staining using phosphotungstate (PTA) reveals the position of positively charged amino acid residues in the collagen sequence. [ 17 ] PTA are large anions that react with the positively charged sidechains of Lys, Hyl, and Arg. These amino acids are nonuniformly distributed in groups along the axial direction of the microfibril. When collagen fibrils are positively stained with PTA and imaged with transmission electron microscopy (TEM), up to 12 peaks of different intensities are observed. These peaks, schematically shown in Figure 1c can be assigned to the positively charged groups in the gap (a3, a2, a1, e2, e1, d, c3), overlap (c2, c1, b2, b1) and both regions (a4). [ 17 ]

The precise location and orientation of charged amino acids along the collagen molecule can give insight on the potential sites for intrafibrillar infiltration of minerals as well as the interaction sites for non-collageneous proteins (NCPs). [ 18 ] Recently, Xu et al. [ 18, 19 ] performed molecular dynamics simulations on a collagen microfibril to understand how the relative position of the collagen molecules changes along the c-axis leading to the formation of possible infiltration paths within the fibrils (Figure 1e). They managed to describe with atomic level detail the shape and size of the void space between molecules in a microfibril and confirm the presence of channels across adjacent microfibrils. Their findings indicate that early mineralization would be favored in the channels formed in the a- and e-bands, which agrees with experimental results. [ 20 ] The calculated dimensions for the a-band are 1.5 nm in height (a-axis) × 5.8 nm in width (c-axis) and for the “e” band are 1.5 × 5.6 nm 2 . [ 19 ] The length of the channels (b-axis) would correspond to the diameter of a fibril, that is between 100 and 200 nm 2 . While there are also voids formed in the d-band, these channels appear tortuous for infiltration. Moreover, Xu et al. showed that the density of water within the gap region is 0.7 g cm −3 , less than in bulk (1 g cm −3 ). This reduction in water density promotes mineralization by reducing the enthalpic penalty for desolvation of mineralization precursors.

2.3 Sources, Extraction Methods, and Formulations

Collagen type I used for biomedical, commercial, and basic research applications is mainly extracted from animal tissues, mostly from skin and tendon of porcine, bovine, and ovine origin. [ 21 ] Less common are collagens from fish [ 22 ] and sponges. [ 23 ] Due to the relatively easy and mild extraction method, it is also common to use collagen extracted from rat tail tendon for research purposes.

The methods used to extract collagen from different sources depend on the source (animal and tissue) of the collagen. Tissues where collagen fibrils present a low degree of crosslinking, such as tendon, require mild methods like acidic solutions, while tissues with high degree of crosslinking require harsher methods, usually including proteolytic digestion. The source and extraction method will affect the purity and integrity of the collagen: cross-links and telopeptides regions might be lost during the process. [ 24 ] This can affect the kinetics of polymerization and final properties of the collagenous material. Moreover, it is important to note that the lack of standardization among collagen sources makes the comparison between studies difficult (see also Section 5).

The use of collagen from animal sources for biomedical applications has the disadvantage of being potentially immunogenic (i.e., provoke an immune response in the host) and of being susceptible to batch-to-batch variabilities. The use of recombinant collagen, produced by genetically modified organisms, could overcome both issues but has low yields and the resulting collagen lacks of some post-translational modifications. [ 25 ] Small synthetic peptides with collagen-like sequences have been used to gain insight on the molecular structure, biochemistry, stability, and self-assembly of collagen. [ 26 ] While their use for biomedical applications is still very limited, they have been used for studies of mineralization. [ 27 ]

Research on collagen mineralization, which will be discussed in Section 4, has been done in reconstituted collagen in different formulations, such as, soft hydrogels, assembled fibrils, freeze-dried sponges, and demineralized tissues. The election of the collagen formulation depends on the research goal and the desired application.

2.3.1 Collagen Hydrogels

Collagen hydrogels are water-swollen collagen networks typically formed by neutralization of an acidic collagen solution and incubation at 37 °C. The kinetics of self-assembly, the morphological and structural characteristics depend on various parameters, such as the source and extraction method of collagen, the collagen concentration, the pH, ionic strength, and temperature. [ 28 ] For a given application, it can be necessary to induce chemical, physical, or biological crosslinks [ 12 ] to strength the reconstituted hydrogels and avoid their disintegration during its handling and use.

2.3.2 Assembled Fibrils

Collagen fibrils can be assembled on 2D substrates such as glass cover slides [ 29 ] or TEM grids, [ 30 ] following neutralization methods similar to the preparation of 3D collagen hydrogels. This facilitates the use of characterization techniques that require thin specimens. Collagen mineralization has been studied in self-assembled grids in TEM grids, [ 20 ] allowing TEM imaging and electron tomography measurements without further treatments to the specimen.

2.3.3 Freeze-Dried Sponges

Typically, collagen suspensions are immersed and freeze in a cryogenic bath at temperatures between −20 and −45 °C. The composition of the suspension and the freezing parameters can be tuned to regulate the pore size of the sponge. [ 31 ]

2.3.4 Demineralized Tissues

The minerals present in mineralized tissues such as bovine bones or fish scales can be removed by chemical treatments leading to a collagenous structure. [ 32 ] Following this process, the hierarchical levels of the tissues are preserved and hence, the templates can be tougher and stronger than other forms of reconstituted collagen.

Humanised bone approaches for disease modelling

While TE techniques can be applied in vitro to study the interaction between bone cells and cancer cells, only in vivo models are capable of recapitulating metastatic spread through the host vasculature and subsequent homing to the bone (Dadwal et al., 2016 Hutmacher et al., 2010 Sitarski et al., 2018). Therefore, to understand the importance of the interaction between human bone and human cancer cells in modelling disease pathophysiology, several groups established rudimentary in vivo models of a humanised bone environment. In these in vivo murine systems, ex vivo human bone fragments were ectopically implanted into immunocompromised mice to study human bone physiology in normal and disease states. Fetal bone subcutaneously grafted into SCID mice maintained human haematopoiesis for up to 20 weeks after implantation (Kyoizumi et al., 1992), retained the bone marrow and resident stromal cells, and underwent bone remodelling processes (Nemeth et al., 1999). Conversely, Wagner et al. reported that maintenance of the marrow compartment in subcutaneously implanted adult cancellous bone depended on supplementation with rhBMP-7 at the time of implantation, as the marrow compartment was replaced with fibrous tissue without rhBMP-7 (Wagner et al., 2016). Perhaps this indicates that the fetal bone engrafts in murine models and maintains the marrow compartment and haematopoiesis better than the adult bone, but the availability of fetal bone for research is limited and has important ethical considerations. Human bone graft-bearing mice have also been used to study primary bone malignancies, such as osteosarcoma, and metastatic lesions from prostate and breast cancer, which we discuss in detail below.

Subcutaneous implantation of human bone fragments for studying normal human bone physiology and the role of human bone in disease processes has both benefits and drawbacks. These bone fragments are subject to higher patient-to-patient variability, caused by idiosyncrasies intrinsic to individual patients, and because the procedure itself employs minimal preprocessing steps of the ex vivo human tissue. However, this can also be advantageous, as the tissue is minimally handled and therefore representative of the patient's native bone organ. This is important, as the bone stromal and marrow niche is crucial for normal human haematopoiesis and plays a central role in haematopoietic diseases (Kaplan et al., 2005). There are also logistical implications in using bone fragments from surgical waste, as the amount of bone material available for implantation is often not known until after the surgery is performed and the tissue harvested. Furthermore, successful implantation into the mouse is confined to a brief time window following bone tissue collection. Therefore, using human bone fragments from surgical waste does not permit extensive experimental preplanning. Moreover, researchers have reported inconsistencies regarding the maintenance of the endogenous bone marrow, and haematopoiesis, necrosis and infiltration of murine fibrous tissue into the grafted human bone fragment (Holzapfel et al., 2013).

Tissue engineering techniques to generate the organ bone

In order to overcome the limitations of native human bone fragments for studying the human bone in normal physiological and disease processes, TE techniques have been employed to form de novo bone in in vivo models (Fig. 3, Table 5). The major advantage of TE bone is the ability to fully customise the physical properties of the osteoconductive scaffold and the inclusion of osteoinductive growth factors and cell sources. TE bone models can also be used to gain mechanistic insights into bone formation. For example, Eyckmans et al. used an ectopic TE bone model to study bone formation. They delineated the roles of BMP and WNT protein signalling (Box 1) during osteoinduction by knocking down or overexpressing the regulators of these signalling pathways in human periosteal cells and analysing the effects on bone formation (Eyckmans et al., 2010).


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