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$( a ) Schematic of the model at the cellular level. In a confluent tissue, cells rearrange by trading places with their neighbors. To trade places with their neighbors, cells must let go of their adhesions with their initial neighbors, migrate, and then form new adhesions with their new neighbors. ( b ) Schematic of the model’s physical interpretation of tissue fluidity. Tissue fluidity is defined as the neighbor exchange rate in the tissue. The adhesions between cells resist cell movement and act to reduce tissue fluidity. The forces of random cell migration provide the energy for cells to move and therefore increase tissue fluidity. Overall, it is the competition between motility and adhesion which determines the tissue fluidity. ( c ) Schematic of the model’s mathematical interpretation of tissue fluidity. The tissue fluidity, or the rate at which any cell pair swap places in the tissue, is determined by an Arrhenius relationship. The adhesion energy is represented as the energy barrier needed to be overcome to swap places. The random motility is represented as an effective temperature (more specifically, an effective thermal energy), which provides the energy to overcome this energy barrier. The amplitude A is defined as the fluidity of the tissue in the absence of adhesion, which is modeled as the diffusion-limited rate of random motility A = kBTM / γD 2 . A increases with the motility energy, kBTM , and decreases with both the coefficient of viscosity experienced by cells migrating through the tissue, γ , and the distance between cell centers, D , which must be traversed in order for cells to exchange places. Tissue fluidity decreases with the adhesion strength and increases with the motility energy. ( d ) Time-lapse montage of an example simulation initialized with two cell types randomly mixed in equal proportion, under the case of equal homotypic adhesion between cells of the same cell type and no heterotypic adhesion. Top: Color represents a unique identifier for each cell, determined by that cell’s initial position. The mixing of cells in space is indicated by the increasing rearrangement of colors over time. Bottom: Color represents each cell’s cell type, where sorting can be visualized by the formation of spatial domains of the same cell type. ( e ) For the simulation shown in (d), the degree of sorting is plotted as a function of time, using two different metrics of sorting. The left-hand y-axis represents the fraction of each cell’s four nearest neighbors that are the same cell type as that cell, averaged across all cells in the tissue. The right-hand axis represents the average width of domains of the same cell type in the tissue (see Methods ). ( f ) The tissue fluidity (i.e., the rate of neighbor exchange averaged over the tissue) over time (see Methods ). ( g ) Time-lapse montage of the experimental cell-sorting assay ( top ) and its associated best-fit simulation ( bottom ). Top: L929 cells co-expressing either Cdh3 (P-cadherin) and <t>EGFP</t> (green) or Cdh1 (E-cadherin) and mRFP (magenta) were mixed in equal proportions and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( h-i ) Mean (h) and standard deviation (i) of the same-cell-type domain size over time for the experiments (red dots) and for 5 replicate best-fit simulations (grey lines).$
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1) Product Images from "Tissue Fluidity: A Double-Edged Sword for Multicellular Patterning"

Article Title: Tissue Fluidity: A Double-Edged Sword for Multicellular Patterning

Journal: bioRxiv

doi: 10.1101/2025.03.01.640992

$( a ) Schematic of the model at the cellular level. In a confluent tissue, cells rearrange by trading places with their neighbors. To trade places with their neighbors, cells must let go of their adhesions with their initial neighbors, migrate, and then form new adhesions with their new neighbors. ( b ) Schematic of the model’s physical interpretation of tissue fluidity. Tissue fluidity is defined as the neighbor exchange rate in the tissue. The adhesions between cells resist cell movement and act to reduce tissue fluidity. The forces of random cell migration provide the energy for cells to move and therefore increase tissue fluidity. Overall, it is the competition between motility and adhesion which determines the tissue fluidity. ( c ) Schematic of the model’s mathematical interpretation of tissue fluidity. The tissue fluidity, or the rate at which any cell pair swap places in the tissue, is determined by an Arrhenius relationship. The adhesion energy is represented as the energy barrier needed to be overcome to swap places. The random motility is represented as an effective temperature (more specifically, an effective thermal energy), which provides the energy to overcome this energy barrier. The amplitude A is defined as the fluidity of the tissue in the absence of adhesion, which is modeled as the diffusion-limited rate of random motility A = kBTM / γD 2 . A increases with the motility energy, kBTM , and decreases with both the coefficient of viscosity experienced by cells migrating through the tissue, γ , and the distance between cell centers, D , which must be traversed in order for cells to exchange places. Tissue fluidity decreases with the adhesion strength and increases with the motility energy. ( d ) Time-lapse montage of an example simulation initialized with two cell types randomly mixed in equal proportion, under the case of equal homotypic adhesion between cells of the same cell type and no heterotypic adhesion. Top: Color represents a unique identifier for each cell, determined by that cell’s initial position. The mixing of cells in space is indicated by the increasing rearrangement of colors over time. Bottom: Color represents each cell’s cell type, where sorting can be visualized by the formation of spatial domains of the same cell type. ( e ) For the simulation shown in (d), the degree of sorting is plotted as a function of time, using two different metrics of sorting. The left-hand y-axis represents the fraction of each cell’s four nearest neighbors that are the same cell type as that cell, averaged across all cells in the tissue. The right-hand axis represents the average width of domains of the same cell type in the tissue (see Methods ). ( f ) The tissue fluidity (i.e., the rate of neighbor exchange averaged over the tissue) over time (see Methods ). ( g ) Time-lapse montage of the experimental cell-sorting assay ( top ) and its associated best-fit simulation ( bottom ). Top: L929 cells co-expressing either Cdh3 (P-cadherin) and EGFP (green) or Cdh1 (E-cadherin) and mRFP (magenta) were mixed in equal proportions and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( h-i ) Mean (h) and standard deviation (i) of the same-cell-type domain size over time for the experiments (red dots) and for 5 replicate best-fit simulations (grey lines).$
Figure Legend Snippet: ( a ) Schematic of the model at the cellular level. In a confluent tissue, cells rearrange by trading places with their neighbors. To trade places with their neighbors, cells must let go of their adhesions with their initial neighbors, migrate, and then form new adhesions with their new neighbors. ( b ) Schematic of the model’s physical interpretation of tissue fluidity. Tissue fluidity is defined as the neighbor exchange rate in the tissue. The adhesions between cells resist cell movement and act to reduce tissue fluidity. The forces of random cell migration provide the energy for cells to move and therefore increase tissue fluidity. Overall, it is the competition between motility and adhesion which determines the tissue fluidity. ( c ) Schematic of the model’s mathematical interpretation of tissue fluidity. The tissue fluidity, or the rate at which any cell pair swap places in the tissue, is determined by an Arrhenius relationship. The adhesion energy is represented as the energy barrier needed to be overcome to swap places. The random motility is represented as an effective temperature (more specifically, an effective thermal energy), which provides the energy to overcome this energy barrier. The amplitude A is defined as the fluidity of the tissue in the absence of adhesion, which is modeled as the diffusion-limited rate of random motility A = kBTM / γD 2 . A increases with the motility energy, kBTM , and decreases with both the coefficient of viscosity experienced by cells migrating through the tissue, γ , and the distance between cell centers, D , which must be traversed in order for cells to exchange places. Tissue fluidity decreases with the adhesion strength and increases with the motility energy. ( d ) Time-lapse montage of an example simulation initialized with two cell types randomly mixed in equal proportion, under the case of equal homotypic adhesion between cells of the same cell type and no heterotypic adhesion. Top: Color represents a unique identifier for each cell, determined by that cell’s initial position. The mixing of cells in space is indicated by the increasing rearrangement of colors over time. Bottom: Color represents each cell’s cell type, where sorting can be visualized by the formation of spatial domains of the same cell type. ( e ) For the simulation shown in (d), the degree of sorting is plotted as a function of time, using two different metrics of sorting. The left-hand y-axis represents the fraction of each cell’s four nearest neighbors that are the same cell type as that cell, averaged across all cells in the tissue. The right-hand axis represents the average width of domains of the same cell type in the tissue (see Methods ). ( f ) The tissue fluidity (i.e., the rate of neighbor exchange averaged over the tissue) over time (see Methods ). ( g ) Time-lapse montage of the experimental cell-sorting assay ( top ) and its associated best-fit simulation ( bottom ). Top: L929 cells co-expressing either Cdh3 (P-cadherin) and EGFP (green) or Cdh1 (E-cadherin) and mRFP (magenta) were mixed in equal proportions and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( h-i ) Mean (h) and standard deviation (i) of the same-cell-type domain size over time for the experiments (red dots) and for 5 replicate best-fit simulations (grey lines).

Techniques Used: Migration, Diffusion-based Assay, Viscosity, FACS, Expressing, Time-lapse Microscopy, Standard Deviation

( a ) L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. From the maximum intensity projection of the first timepoint for each condition, the median fluorescence intensity across the entire image was calculated for both the EGFP (open circles) and mRFP (closed circles) channels. The color indicates the experimental condition, and the two cell populations mixed in a single condition are grouped together along the x-axis. The x-label indicates which cell population corresponds to each channel within a given condition. The markers indicate different experimental replicates of a given condition. There were four replicates in each condition.

Figure Legend Snippet: ( a ) L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. From the maximum intensity projection of the first timepoint for each condition, the median fluorescence intensity across the entire image was calculated for both the EGFP (open circles) and mRFP (closed circles) channels. The color indicates the experimental condition, and the two cell populations mixed in a single condition are grouped together along the x-axis. The x-label indicates which cell population corresponds to each channel within a given condition. The markers indicate different experimental replicates of a given condition. There were four replicates in each condition.

Techniques Used: Expressing, Time-lapse Microscopy, Fluorescence

( a-b ) The average (a) and coefficient of variation (b) of the domain size are plotted as a function of time for each of the 4 different experimental conditions. Light markers: Replicates. Dark Markers: Average across 4 replicates. Sorting can only occur in a very narrow window where the adhesion and motility energies are nearly equal. ( c ) Representative images of each experimental cell-sorting assay ( top ) and its associated representative best-fit simulation ( bottom ) after 18 hours. Top: L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations with displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( d ) The best fit simulation parameters for each experimental dataset are plotted on top of a heatmap of the average domain size for all simulation parameters tested. Markers with a white outline represent the mean across the 4 replicates for each condition. ( e ) The best fit adhesion energy is plotted as a function of the best fit motility energy for each experimental dataset. The narrow sorting window is plotted exactly as in .

Figure Legend Snippet: ( a-b ) The average (a) and coefficient of variation (b) of the domain size are plotted as a function of time for each of the 4 different experimental conditions. Light markers: Replicates. Dark Markers: Average across 4 replicates. Sorting can only occur in a very narrow window where the adhesion and motility energies are nearly equal. ( c ) Representative images of each experimental cell-sorting assay ( top ) and its associated representative best-fit simulation ( bottom ) after 18 hours. Top: L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations with displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( d ) The best fit simulation parameters for each experimental dataset are plotted on top of a heatmap of the average domain size for all simulation parameters tested. Markers with a white outline represent the mean across the 4 replicates for each condition. ( e ) The best fit adhesion energy is plotted as a function of the best fit motility energy for each experimental dataset. The narrow sorting window is plotted exactly as in .

Techniques Used: FACS, Expressing, Time-lapse Microscopy

( a,d,h,j ) Time-lapse montage of the experimental cell-sorting assay ( top ) and its associated best-fit simulation ( bottom ). Top: L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations with displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( b,c,e,f,h,i,k,l ) Mean ( b,e,h,k ) and standard deviation ( c,f,i,l ) of the same-cell-type domain size over time for the experiments (red dots) and for 5 replicate best-fit simulations (grey lines). ( a-c ) Cdh2–EGFP high cells mixed with Cdh1–mRFP high cells, ( d-f ) Cdh2–EGFP low cells mixed with Cdh1 – mRFP low cells, (g -i ) Cdh3–EGFP high cells mixed with Cdh1 - mRFP high cells, (j -l ) Cdh3 – EGFP low cells mixed with Cdh1 – mRFP low cells

Figure Legend Snippet: ( a,d,h,j ) Time-lapse montage of the experimental cell-sorting assay ( top ) and its associated best-fit simulation ( bottom ). Top: L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations with displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( b,c,e,f,h,i,k,l ) Mean ( b,e,h,k ) and standard deviation ( c,f,i,l ) of the same-cell-type domain size over time for the experiments (red dots) and for 5 replicate best-fit simulations (grey lines). ( a-c ) Cdh2–EGFP high cells mixed with Cdh1–mRFP high cells, ( d-f ) Cdh2–EGFP low cells mixed with Cdh1 – mRFP low cells, (g -i ) Cdh3–EGFP high cells mixed with Cdh1 - mRFP high cells, (j -l ) Cdh3 – EGFP low cells mixed with Cdh1 – mRFP low cells

Techniques Used: FACS, Expressing, Time-lapse Microscopy, Standard Deviation

Image Search Results

Journal: bioRxiv

Article Title: Tissue Fluidity: A Double-Edged Sword for Multicellular Patterning

doi: 10.1101/2025.03.01.640992

Figure Lengend Snippet: ( a ) Schematic of the model at the cellular level. In a confluent tissue, cells rearrange by trading places with their neighbors. To trade places with their neighbors, cells must let go of their adhesions with their initial neighbors, migrate, and then form new adhesions with their new neighbors. ( b ) Schematic of the model’s physical interpretation of tissue fluidity. Tissue fluidity is defined as the neighbor exchange rate in the tissue. The adhesions between cells resist cell movement and act to reduce tissue fluidity. The forces of random cell migration provide the energy for cells to move and therefore increase tissue fluidity. Overall, it is the competition between motility and adhesion which determines the tissue fluidity. ( c ) Schematic of the model’s mathematical interpretation of tissue fluidity. The tissue fluidity, or the rate at which any cell pair swap places in the tissue, is determined by an Arrhenius relationship. The adhesion energy is represented as the energy barrier needed to be overcome to swap places. The random motility is represented as an effective temperature (more specifically, an effective thermal energy), which provides the energy to overcome this energy barrier. The amplitude A is defined as the fluidity of the tissue in the absence of adhesion, which is modeled as the diffusion-limited rate of random motility A = kBTM / γD 2 . A increases with the motility energy, kBTM , and decreases with both the coefficient of viscosity experienced by cells migrating through the tissue, γ , and the distance between cell centers, D , which must be traversed in order for cells to exchange places. Tissue fluidity decreases with the adhesion strength and increases with the motility energy. ( d ) Time-lapse montage of an example simulation initialized with two cell types randomly mixed in equal proportion, under the case of equal homotypic adhesion between cells of the same cell type and no heterotypic adhesion. Top: Color represents a unique identifier for each cell, determined by that cell’s initial position. The mixing of cells in space is indicated by the increasing rearrangement of colors over time. Bottom: Color represents each cell’s cell type, where sorting can be visualized by the formation of spatial domains of the same cell type. ( e ) For the simulation shown in (d), the degree of sorting is plotted as a function of time, using two different metrics of sorting. The left-hand y-axis represents the fraction of each cell’s four nearest neighbors that are the same cell type as that cell, averaged across all cells in the tissue. The right-hand axis represents the average width of domains of the same cell type in the tissue (see Methods ). ( f ) The tissue fluidity (i.e., the rate of neighbor exchange averaged over the tissue) over time (see Methods ). ( g ) Time-lapse montage of the experimental cell-sorting assay ( top ) and its associated best-fit simulation ( bottom ). Top: L929 cells co-expressing either Cdh3 (P-cadherin) and EGFP (green) or Cdh1 (E-cadherin) and mRFP (magenta) were mixed in equal proportions and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( h-i ) Mean (h) and standard deviation (i) of the same-cell-type domain size over time for the experiments (red dots) and for 5 replicate best-fit simulations (grey lines).

Article Snippet: This resultant plasmid (pLJM-EGFP_v2) was then used to generate a pLJM1-mRFP plasmid by replacing the EGFP coding sequence (CDS) with the mRFP CDS, obtained by PCR-amplification from the pcDNA-mRFP plasmid (Addgene; plasmid #13032).

Techniques: Migration, Diffusion-based Assay, Viscosity, FACS, Expressing, Time-lapse Microscopy, Standard Deviation

Journal: bioRxiv

Article Title: Tissue Fluidity: A Double-Edged Sword for Multicellular Patterning

doi: 10.1101/2025.03.01.640992

Figure Lengend Snippet: ( a ) L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. From the maximum intensity projection of the first timepoint for each condition, the median fluorescence intensity across the entire image was calculated for both the EGFP (open circles) and mRFP (closed circles) channels. The color indicates the experimental condition, and the two cell populations mixed in a single condition are grouped together along the x-axis. The x-label indicates which cell population corresponds to each channel within a given condition. The markers indicate different experimental replicates of a given condition. There were four replicates in each condition.

Techniques: Expressing, Time-lapse Microscopy, Fluorescence

Journal: bioRxiv

Article Title: Tissue Fluidity: A Double-Edged Sword for Multicellular Patterning

doi: 10.1101/2025.03.01.640992

Figure Lengend Snippet: ( a-b ) The average (a) and coefficient of variation (b) of the domain size are plotted as a function of time for each of the 4 different experimental conditions. Light markers: Replicates. Dark Markers: Average across 4 replicates. Sorting can only occur in a very narrow window where the adhesion and motility energies are nearly equal. ( c ) Representative images of each experimental cell-sorting assay ( top ) and its associated representative best-fit simulation ( bottom ) after 18 hours. Top: L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations with displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( d ) The best fit simulation parameters for each experimental dataset are plotted on top of a heatmap of the average domain size for all simulation parameters tested. Markers with a white outline represent the mean across the 4 replicates for each condition. ( e ) The best fit adhesion energy is plotted as a function of the best fit motility energy for each experimental dataset. The narrow sorting window is plotted exactly as in .

Techniques: FACS, Expressing, Time-lapse Microscopy

Journal: bioRxiv

Article Title: Tissue Fluidity: A Double-Edged Sword for Multicellular Patterning

doi: 10.1101/2025.03.01.640992

Figure Lengend Snippet: ( a,d,h,j ) Time-lapse montage of the experimental cell-sorting assay ( top ) and its associated best-fit simulation ( bottom ). Top: L929 cells co-expressing either high or low levels of Cdh2 (N-cadherin) or Cdh3 (P-cadherin) and EGFP (green) were mixed in equal proportions with cells co-expressing either high or low levels of Cdh1 (E-cadherin) and mRFP (magenta) and imaged by confocal time-lapse microscopy. Images represent maximum intensity projections. Bottom: Best-fit simulations with displayed as a heat map of cell type. Best fit parameters are listed in the inset legend. ( b,c,e,f,h,i,k,l ) Mean ( b,e,h,k ) and standard deviation ( c,f,i,l ) of the same-cell-type domain size over time for the experiments (red dots) and for 5 replicate best-fit simulations (grey lines). ( a-c ) Cdh2–EGFP high cells mixed with Cdh1–mRFP high cells, ( d-f ) Cdh2–EGFP low cells mixed with Cdh1 – mRFP low cells, (g -i ) Cdh3–EGFP high cells mixed with Cdh1 - mRFP high cells, (j -l ) Cdh3 – EGFP low cells mixed with Cdh1 – mRFP low cells

Techniques: FACS, Expressing, Time-lapse Microscopy, Standard Deviation

(A) In vitro produced bovine oocytes underwent IVF and the resulting zygotes non-invasively monitored by time-lapse image analysis until collection for immunostaining of nuclear structure. Another subset of zygotes was microinjected with fluorescently labeled modified mRNAs and chromosome segregation visualized during the first three mitotic divisions in real-time by live-cell confocal microscopy. Cleavage-stage embryos were disassembled into single blastomeres at the 2- to 12-cell stage for scDNA-seq and CNV analysis to determine the precise frequency of aneuploidy at multiple cleavage stages. Other zygotes were microinjected with non-overlapping morpholinos targeting the mitotic checkpoint protein, BUB1B, and/or modified BUB1B mRNA to test the effect and specificity of MCC inhibition on chromosome segregation, division dynamics, and preimplantation development. Gene expression profiling was also conducted on a subset of MCC deficit zygotes versus controls by quantitative RT-PCR to identify changes in gene abundance and molecular pathways associated with BUB1B knockdown. (B) Immunostaining of zygotes and (C) cleavage-stage embryos with LMNB1 (green) using DAPI (blue) to visualize DNA revealed several micro- and multi-nuclei (white arrows). (D) Blastocysts also immunostained for the trophoblast marker, CDX2 (red), showed that micronuclei are often present in the TE, (E) but can also be retained within the ICM of the embryo. Scale bar = 10μm.

Journal: bioRxiv

Article Title: Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

doi: 10.1101/2020.07.24.220475

Figure Lengend Snippet: (A) In vitro produced bovine oocytes underwent IVF and the resulting zygotes non-invasively monitored by time-lapse image analysis until collection for immunostaining of nuclear structure. Another subset of zygotes was microinjected with fluorescently labeled modified mRNAs and chromosome segregation visualized during the first three mitotic divisions in real-time by live-cell confocal microscopy. Cleavage-stage embryos were disassembled into single blastomeres at the 2- to 12-cell stage for scDNA-seq and CNV analysis to determine the precise frequency of aneuploidy at multiple cleavage stages. Other zygotes were microinjected with non-overlapping morpholinos targeting the mitotic checkpoint protein, BUB1B, and/or modified BUB1B mRNA to test the effect and specificity of MCC inhibition on chromosome segregation, division dynamics, and preimplantation development. Gene expression profiling was also conducted on a subset of MCC deficit zygotes versus controls by quantitative RT-PCR to identify changes in gene abundance and molecular pathways associated with BUB1B knockdown. (B) Immunostaining of zygotes and (C) cleavage-stage embryos with LMNB1 (green) using DAPI (blue) to visualize DNA revealed several micro- and multi-nuclei (white arrows). (D) Blastocysts also immunostained for the trophoblast marker, CDX2 (red), showed that micronuclei are often present in the TE, (E) but can also be retained within the ICM of the embryo. Scale bar = 10μm.

Article Snippet: The BUB1B coding sequence (CDS) was amplified from the plasmid, pcDNA5-EGFP-AID-BubR1 (Addgene #47330), followed by mutation of the MAO binding site using the Q5 site directed mutagenesis kit (NEB) according to the manufacturer’s instructions.

Techniques: In Vitro, Produced, Immunostaining, Labeling, Modification, Confocal Microscopy, Inhibition, Gene Expression, Quantitative RT-PCR, Knockdown, Marker

(A) DNA sequences of two non-overlapping MAOs designed to target the ATG start site (shown in red, BUB1B MAO #1) and the 5’ UTR (depicted in blue, BUB1B MAO #2) of BUB1B. (B) BUB1B knockdown efficiency was assessed in synchronized MDBK cells following 48 hours of treatment with 3μl/ml of colcemid alone (non-transfected), the Std control MAO, or BUB1B MAO #1 via immunofluorescence. BUB1B protein expression was analyzed in DAPI stained (blue) MDBK cells. Note the lack of or reduced number of BUB1B positive foci (red) in the BUB1B MAO #1 treated cells compared to the controls; Scale bar = 20μm. (C) Bar graph showing the percentage of MDBK cells in metaphase with BUB1B expression after colcemid treatment (black) or transfection with different concentrations (2, 4, and 8 μM) of the Std control MAO (blue) or BUB1B MAO #1 (red). While the number of cells exhibiting BUB1B positive foci was similar between the non-transfected and Std MAO controls, a dose-dependent decrease in BUB1B expression was observed following BUB1B MAO #1 treatment.

Journal: bioRxiv

Article Title: Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

doi: 10.1101/2020.07.24.220475

Figure Lengend Snippet: (A) DNA sequences of two non-overlapping MAOs designed to target the ATG start site (shown in red, BUB1B MAO #1) and the 5’ UTR (depicted in blue, BUB1B MAO #2) of BUB1B. (B) BUB1B knockdown efficiency was assessed in synchronized MDBK cells following 48 hours of treatment with 3μl/ml of colcemid alone (non-transfected), the Std control MAO, or BUB1B MAO #1 via immunofluorescence. BUB1B protein expression was analyzed in DAPI stained (blue) MDBK cells. Note the lack of or reduced number of BUB1B positive foci (red) in the BUB1B MAO #1 treated cells compared to the controls; Scale bar = 20μm. (C) Bar graph showing the percentage of MDBK cells in metaphase with BUB1B expression after colcemid treatment (black) or transfection with different concentrations (2, 4, and 8 μM) of the Std control MAO (blue) or BUB1B MAO #1 (red). While the number of cells exhibiting BUB1B positive foci was similar between the non-transfected and Std MAO controls, a dose-dependent decrease in BUB1B expression was observed following BUB1B MAO #1 treatment.

Techniques: Knockdown, Transfection, Control, Immunofluorescence, Expressing, Staining

Journal: bioRxiv

Article Title: Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

doi: 10.1101/2020.07.24.220475

Figure Lengend Snippet:

Techniques: Microinjection, Control

(A) Darkfield time-lapse imaging frames depicting the various embryo phenotypes (red arrows), including attempted division, multipolar division, and blastomere asymmetry observed following BUB1B MAO #1 or (B) BUB1B MAO #2 microinjection in bovine zygotes. (C) Representative stereomicroscope images of embryos and blastocysts from the Std control MAO, BUB1B MAO #1, and BUB1B MAO #1 plus BUB1B modified mRNA treatment groups. (D) Bar graph of the percentage of embryos that reached the blastocyst stage in non-injected, Std control MAO, BUB1B MAO #1, BUB1B MAO #2, or BUB1B MAO #1 plus BUB1B modified mRNA injected zygotes. While no blastocysts were obtained following BUB1B MAO #1 or #2 treatment, the co-injection of BUB1 MAO #1 and BUB1B modified mRNA was able to almost fully rescue the phenotype and restore blastocyst formation rates to that observed in controls. (E) Confocal images of LMNB1 (green) immunostaining in BUB1B MAO #1 or #2 treated embryos stained with DAPI (blue). Severely abnormal nuclear morphology and the presence of both micro- and multi-nuclei were detected (denoted with white arrowheads) in embryos at the zygote stage (top row) and cleavage-stage that exhibited abnormal cell divisions (bottom row). Note the DNA without nuclear envelope (white arrows) and the blastomere that completely lacked nuclear material in the 2-cell embryo located in the lower left image; Scale bars = 10μm. (E) CNV plots of blastomeres from different cleavage-stage embryos disassembled into single cells following BUB1B #1 MAO injection. While some euploid blastomeres were detected in BUB1B-injected embryos (upper left plot), most exhibited chaotic aneuploidy with multiple whole and sub-chromosomal losses and gains.

Journal: bioRxiv

Article Title: Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

doi: 10.1101/2020.07.24.220475

Figure Lengend Snippet: (A) Darkfield time-lapse imaging frames depicting the various embryo phenotypes (red arrows), including attempted division, multipolar division, and blastomere asymmetry observed following BUB1B MAO #1 or (B) BUB1B MAO #2 microinjection in bovine zygotes. (C) Representative stereomicroscope images of embryos and blastocysts from the Std control MAO, BUB1B MAO #1, and BUB1B MAO #1 plus BUB1B modified mRNA treatment groups. (D) Bar graph of the percentage of embryos that reached the blastocyst stage in non-injected, Std control MAO, BUB1B MAO #1, BUB1B MAO #2, or BUB1B MAO #1 plus BUB1B modified mRNA injected zygotes. While no blastocysts were obtained following BUB1B MAO #1 or #2 treatment, the co-injection of BUB1 MAO #1 and BUB1B modified mRNA was able to almost fully rescue the phenotype and restore blastocyst formation rates to that observed in controls. (E) Confocal images of LMNB1 (green) immunostaining in BUB1B MAO #1 or #2 treated embryos stained with DAPI (blue). Severely abnormal nuclear morphology and the presence of both micro- and multi-nuclei were detected (denoted with white arrowheads) in embryos at the zygote stage (top row) and cleavage-stage that exhibited abnormal cell divisions (bottom row). Note the DNA without nuclear envelope (white arrows) and the blastomere that completely lacked nuclear material in the 2-cell embryo located in the lower left image; Scale bars = 10μm. (E) CNV plots of blastomeres from different cleavage-stage embryos disassembled into single cells following BUB1B #1 MAO injection. While some euploid blastomeres were detected in BUB1B-injected embryos (upper left plot), most exhibited chaotic aneuploidy with multiple whole and sub-chromosomal losses and gains.

Techniques: Imaging, Microinjection, Control, Modification, Injection, Immunostaining, Staining

Heat map of all mitotic, cell cycle, developmentally-regulated, and cell survival genes assessed in individual BUB1B MAO #1 versus non-injected and Std Control-injected MAO bovine zygotes via microfluidic qRT-PCR. Cycle threshold (Ct) values were normalized to the most stable reference genes (RPL15 and GUSB) across embryo groups and presented as the average. Gray squares indicated no expression, whereas yellow, white, and purple squares correspond to low, medium, and high expression, respectively.

Journal: bioRxiv

Article Title: Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

doi: 10.1101/2020.07.24.220475

Figure Lengend Snippet: Heat map of all mitotic, cell cycle, developmentally-regulated, and cell survival genes assessed in individual BUB1B MAO #1 versus non-injected and Std Control-injected MAO bovine zygotes via microfluidic qRT-PCR. Cycle threshold (Ct) values were normalized to the most stable reference genes (RPL15 and GUSB) across embryo groups and presented as the average. Gray squares indicated no expression, whereas yellow, white, and purple squares correspond to low, medium, and high expression, respectively.

Techniques: Injection, Control, Quantitative RT-PCR, Expressing

The relative abundance of several mitotic, cell cycle, developmentally-regulated, and cell survival genes was assessed via microfluidic quantitative RT-PCR (qRT-PCR) in non-injected (NI; N=5), Std Control MAO (N=5), and BUB1B MAO #1 (N=5) individual zygotes using gene-specific primers. (A) The genes that were significantly downregulated (p<0.05) in BUB1B MAO-injected embryos compared to the NI and Std Control MAO groups + standard error is shown in the bar graph. (B) A bar graph of the genes that were significantly upregulated in BUB1B MAO-injected embryos relative to the controls + standard error. CNRQ values of each gene was compared across embryo groups using the Mann-Whitney U-test. The full list of the 96 genes with primer sequences assessed by qRT-PCR is available in and Supplemental Table S2 , respectively.

Journal: bioRxiv

Article Title: Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

doi: 10.1101/2020.07.24.220475

Figure Lengend Snippet: The relative abundance of several mitotic, cell cycle, developmentally-regulated, and cell survival genes was assessed via microfluidic quantitative RT-PCR (qRT-PCR) in non-injected (NI; N=5), Std Control MAO (N=5), and BUB1B MAO #1 (N=5) individual zygotes using gene-specific primers. (A) The genes that were significantly downregulated (p<0.05) in BUB1B MAO-injected embryos compared to the NI and Std Control MAO groups + standard error is shown in the bar graph. (B) A bar graph of the genes that were significantly upregulated in BUB1B MAO-injected embryos relative to the controls + standard error. CNRQ values of each gene was compared across embryo groups using the Mann-Whitney U-test. The full list of the 96 genes with primer sequences assessed by qRT-PCR is available in and Supplemental Table S2 , respectively.

Techniques: Quantitative RT-PCR, Injection, Control, MANN-WHITNEY

(A) Simplified model of how the lack of maternal and paternal pronuclear fusion (syngamy) at the zygote stage, followed by genome duplication and multipolar divisions, contributes to blastomeres with uniparental origins, or those that only contain maternal or paternal DNA. (B) Live-cell imaging also revealed the formation of anaphase lagging chromosomes likely from merotelic attachments prior to or during the first mitotic division. The chromosome(s) become encapsulated in nuclear envelope to form a micronucleus and the embryo continues to divide normally. In these subsequent bipolar divisions, most micronuclei either fuse back with the primary nucleus upon nuclear envelope breakdown or persist and undergo unilateral inheritance, but some micronuclei form a chromatin bridge with the nucleus of another blastomere during anaphase. (C) The depletion of BUB1B in zygotes resulted in no division or attempted division and embryo arrest, while multipolar divisions, blastomere asymmetry, and micro-/multi-nuclei were observed in MCC-deficient embryos that completed the first cytokinesis. These abnormal divisions also produced daughter cells with chaotic aneuploidy and/or empty blastomeres with no nuclear structure that induced embryo arrest and suggested that the lack of MCC permits the genotypic complexity detected at the early cleavage-stages of preimplantation development.

Journal: bioRxiv

Article Title: Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

doi: 10.1101/2020.07.24.220475

Figure Lengend Snippet: (A) Simplified model of how the lack of maternal and paternal pronuclear fusion (syngamy) at the zygote stage, followed by genome duplication and multipolar divisions, contributes to blastomeres with uniparental origins, or those that only contain maternal or paternal DNA. (B) Live-cell imaging also revealed the formation of anaphase lagging chromosomes likely from merotelic attachments prior to or during the first mitotic division. The chromosome(s) become encapsulated in nuclear envelope to form a micronucleus and the embryo continues to divide normally. In these subsequent bipolar divisions, most micronuclei either fuse back with the primary nucleus upon nuclear envelope breakdown or persist and undergo unilateral inheritance, but some micronuclei form a chromatin bridge with the nucleus of another blastomere during anaphase. (C) The depletion of BUB1B in zygotes resulted in no division or attempted division and embryo arrest, while multipolar divisions, blastomere asymmetry, and micro-/multi-nuclei were observed in MCC-deficient embryos that completed the first cytokinesis. These abnormal divisions also produced daughter cells with chaotic aneuploidy and/or empty blastomeres with no nuclear structure that induced embryo arrest and suggested that the lack of MCC permits the genotypic complexity detected at the early cleavage-stages of preimplantation development.

Techniques: Live Cell Imaging, Produced

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1) Product Images from "Tissue Fluidity: A Double-Edged Sword for Multicellular Patterning"

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